case study of ecosystem service

Ecosystem Services – Concept, Methods and Case Studies

• © 2015
• Karsten Grunewald 0 ,
• Olaf Bastian 1

Leibniz Inst. of Ecological Urban and Regional Development, Dresden, Germany

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• Easily readable, understandable for a wide readership, but scientifically sophisticated representation of a future-oriented and highly relevant topic
• Explanation of terms, categories and assessment systems for ecosystem services
• Conceptual framework and methodological guidelines for the analysis and evaluation of ecosystem services
• Demonstration of extensive application possibilities of the ecosystem services approach in German cultural landscapes
• Includes supplementary material: sn.pub/extras

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Ecosystem Services

Ecosystem Services: Understanding Drivers, Opportunities, and Risks to Move Towards Sustainable Land Management and Governance

The Basic Ideas of the Ecosystem Service Concept

• Biodiversity
• cost-utility-analyses
• economic values
• ecosystem assessment
• ecosystem potentials
• environmental policy
• landscape functions
• nature capital
• nature conservation

Table of contents (7 chapters)

Front matter, ecosystem services (es): more than just a vogue term.

• K. Grunewald, O. Bastian

Development and Fundamentals of the ES Approach

• K. Grunewald, O. Bastian, K. Mannsfeld

Conceptual Framework

• O. Bastian, K. Grunewald

Ascertainment and Assessment of ES

• Benjamin Burkhard, Felix Müller, Burkhard Schweppe-Kraft, Karsten Grunewald, Ralf-Uwe Syrbe, Matthias Rosenberg et al.

Governing Biodiversity and Ecosystem Service Provision

• I. Ring, C. Schröter-Schlaack

Land Use, Maintenance and Protection to Ensure ES

Recommendations and outlook, back matter, editors and affiliations.

Karsten Grunewald, Olaf Bastian

About the editors

Bibliographic information.

Book Title : Ecosystem Services – Concept, Methods and Case Studies

Editors : Karsten Grunewald, Olaf Bastian

DOI : https://doi.org/10.1007/978-3-662-44143-5

Publisher : Springer Berlin, Heidelberg

eBook Packages : Earth and Environmental Science , Earth and Environmental Science (R0)

Copyright Information : Springer-Verlag Berlin Heidelberg 2015

Hardcover ISBN : 978-3-662-44142-8 Published: 02 June 2015

Softcover ISBN : 978-3-662-51577-8 Published: 18 October 2016

eBook ISBN : 978-3-662-44143-5 Published: 18 May 2015

Edition Number : 1

Number of Pages : XII, 312

Number of Illustrations : 53 b/w illustrations, 14 illustrations in colour

Topics : Environment, general , Environmental Management , Environmental Law/Policy/Ecojustice , Monitoring/Environmental Analysis

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Ecosystem service value evaluation method in a complex ecological environment: A case study of Gansu Province, China

Xiaojiong Zhao

1 Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, China

2 University of Chinese Academy of Sciences, Beijing, China

3 Gansu Academy of Eco-environmental Sciences, Lanzhou, China

4 Gansu Vocational & Technical College of Nonferrous Metallurgy, Jinchang, China

Associated Data

All relevant data are within the manuscript and its Supporting Information files.

The scientific assessment of regional ecosystem service value (ESV) is helpful in developing scientific ecological protection plans and compensation policies. However, an ESV evaluation method that can adapt to the complex and diverse characteristics of the ecological environment has not been established. This study takes Gansu Province in China as an example, fully considering the regional differences in ecosystem service function. Five correction indices for the value equivalent factor per unit area were constructed on a provincial scale, and a regional difference adjustment index for 11 categories of ecosystem services was constructed on a regional scale. In this way, a value evaluation model based on regional differences was established. The results show that in 2015, the total ESV reached 2,239.56 billion yuan in Gansu Province, with ESV gradually increasing from the northeast to the southwest, and the high-value areas of service function being located in Qilian and Longnan Mountains. The forest and grassland ecosystems contributed the most to the ESV. From the perspective of value composition, local climate regulation and biodiversity maintenance functions are the main service functions of Gansu Province. From 2000 to 2015, ESV increased by 3.43 billion yuan in the province. The value of forest and urban ecosystems continued to increase, whereas the value of cultivated land ecosystem continued to decrease. In terms of spatial characteristics of the service value change, the area that experienced value reduction gradually moved from the central part of Gansu Province to the surrounding areas. The evaluation method proposed in this paper provides a relatively comprehensive evaluation scheme for the spatiotemporal dynamic evaluation of ESV in complex ecological environments.

Introduction

Ecosystems not only provide various raw materials or products directly for human survival, but also have other functions such as regulating climate, reducing pollution, conserving water sources, maintaining soil quality, preventing wind and sand erosion, reducing disasters such as floods and fires, and protecting biodiversity. All ecosystem products and services are collectively referred to as ecosystem services (ES) [ 1 , 2 ]. The evaluation of ecosystem service value (ESV) forms the basis of regional ecological construction, ecological protection, ecological work division, and ecological decision-making regarding natural assets, and has become a popular research topic in ecology [ 3 – 5 ]. Since Costanza first quantified the value of global ES in 1997, ESV calculation has increasingly been used as the core basis of ecological asset accounting, thus helping the spatial cognition and sustainable management of national systems in a more intuitive way [ 5 , 6 ]. However, because of the different choices in parameters set by different scholars, the evaluation results of the same ES may vary greatly, and there is a lack of comparability between the ESV obtained through different pricing methods, while a mature pricing method for ESV has not yet been formed internationally [ 7 – 10 ].

At present, research on the evaluation method of ESV can be roughly divided into two categories. The fist is a method based on the service function price per unit area. This method evaluates some key service functions by means of a series of ecological equations, such as food production, soil and water conservation, carbon and oxygen production, and habitat quality [ 11 – 14 ]. The functional value method can accurately measure the extent of some service functions in a region. However, for different service functions, different ecological equations and parameter inputs are often required, and the calculation process is more complicated [ 3 ]. Therefore, this method is mostly applied on a small scale, and the implementation cost is high. In addition, when using this method for evaluation, scholars often lack consideration of the ecological background of the study area, and there is no standard in selecting which service functions to evaluate [ 15 ]. These shortcomings result in significant uncertainty of the evaluation results, and limitations in the comparison of results. The second is a method based on value equivalent factor per unit area. This method was first proposed by Costanza et al. [ 5 ], and divides different land ecosystems and service functions, obtaining the equivalent value based on meta-analysis and the area of each ecosystem, to obtain the regional ESV. Compared with the functional value method, this method evaluates ESV more effectively on a large scale [ 16 ] and is widely used in research [ 3 , 5 , 17 – 19 ].

However, scholars have found that the evaluation results of the equivalent factor method are valid and reliable only when the equivalent factor accurately reflects the ecological background in the study area [ 16 , 20 , 21 ]. The equivalent factor proposed by Costanza et al. [ 5 , 17 ] is aimed at global-scale value assessment, which is not consistent with the real ecological situation in China. Xie et al. [ 18 , 19 ] conducted a survey among Chinese ecologists, and put forward an equivalent factor table of ES for China in 2003 and 2008. In 2015, Xie et al. [ 3 ] updated and improved the equivalent factor table by adding information obtained from literature and including regional biomass. This table is currently the most scientific and systematic equivalent factor table in China. The equivalent factor table proposed by Xie et al. [ 3 ] essentially reflects the average level of the national ecosystem service function. Many more recent studies [ 14 ] have shown that the strength of the different service functions is affected by different ecological processes and conditions. For example, organic matter production, gas regulation, and nutrient cycling function [ 12 ] is closely related to net primary productivity (NPP); and water supply and regulation function is closely related to rainfall [ 22 ], soil erosion [ 23 ], habitat quality [ 13 ], and the accessibility of recreational sites [ 24 ]. Therefore, when the equivalent factor method is used to evaluate the ecological value of a region, the corresponding spatial correction of the equivalent factor is needed [ 8 , 25 ]. At present, scholars only use biomass or NPP to adapt all types of service functions [ 3 , 18 , 19 , 26 ], which does not match the real situation. Xie et al. [ 18 ] for the first time selected other ecological indicators (rainfall and soil retention) besides NPP to adapt the service function.

Based on the research framework of value equivalent factor per unit area, we adopted the method of meta-analysis and fully used the evaluation results based on the physical quantity method to determine the average unit area equivalent factor in different ecosystems in Gansu Province. This method avoids or reduces the subjective conjecture easily caused by relying on the experience of experts. Additionally, abundant ecological environment data are used to correct the equivalent factor, thus completing the evaluation of ESV in complex ecological environments. Compared with previous studies [ 3 , 18 , 19 , 27 , 28 ], the evaluation results are more scientific and reasonable. In the evaluation of ESV, the impact of human activities on the ESV, such as bearing capacity, air pollution, groundwater overdraft, and water pollution. is fully considered.

The types of ecosystems are complex and diverse in Gansu Province. The diversity of ecosystem types has caused significant regional differences. However, current research mostly focuses on single or several ecosystems, and only investigate certain ES functions in the ESV in Gansu Province, such as forests [ 29 – 31 ], grassland [ 32 , 33 ], and cultivated land [ 34 ]. Considering the complex ecological environment characteristics in Gansu Province, previous studies have not investigated the ESV considering the regional differences in space, and no value evaluation method has been established according to the specific ecological environment in the region.

This study considers the regional differences and the simplicity of the equivalent factor method. In view of the application of the equivalent factors of various ecosystems on a large scale, it is necessary to closely relate the equivalent factors to the national (large) scale and to the actual situation in Gansu Province. Based on a more refined classification of the ecosystem types in Gansu Province, the study added some ecosystem equivalent factors, constructed a revised index, and revised the equivalent factors studied by Xie et al. [ 3 ] to form an equivalent factor table that was suitable for the assessment of ESV in Gansu Province. We constructed 11 regional differential adjustment indexes and readjusted the values of different service functions. Finally, we constructed a regional differential value evaluation model to evaluate the change in ESV in Gansu Province from 2000 to 2015. Considering the increasingly severe shortage in and overuse of ecological services in the region, the results of this study can provide a scientific basis for decision support for local governments to formulate more complete ecological compensation policies.

Materials and methods

The case study region is located in northwest China ( Fig 1 ), at the intersection of three major plateaus—the Loess Plateau, the Qinghai Tibet Plateau, and the Inner Mongolia Plateau—and three natural regions—the northwest arid region, the Qinghai Tibet alpine region, and the eastern monsoon region. Gansu Province is a long and narrow region, covering a total land area of 425,800 km 2 , with complex and diverse geological landforms and climate types. In addition to the marine ecosystem, there are six main land use or cover types, including forests, grasslands, deserts, wetlands, farmland, and urban areas. The Gansu region forms part of China’s “two screens and three belts” strategic ecological security barrier policy, which aims to maintain and protect the survival and reproduction of organisms, maintain the natural ecological balance, and guarantee people’s livelihoods on the Qinghai Tibet Plateau, the Sichuan–Yunnan Loess Plateau and the north sand belt. It is an important water conservation and supply area in the upper reaches of the Yangtze River and the Yellow River.

Data sources

Ecosystem type data.

We used national ecosystem type datasets from the Satellite Application Center of the Ministry of Ecology and Environment and the Chinese Academy of Sciences, for the periods 2000, 2005, 2010, and 2015, for the classification of ecosystems. The resolution of Landsat TM/ETM images was 30 m, SPOT-5 images was 5 or 2.5 m, Envisat image was 30 m, and HJ-1 images was 30 m. From this data, and according to the study requirements, the ecosystem types were divided into 7 primary types and 21 secondary types in the research area, and a corresponding database was established.

We then used data from 2,508 ground verification points, including 38 different ecosystem types, and integrated these ecosystem types with the ecosystem types obtained through the satellite images, into a final database with 21 ecosystem types, as shown in Fig 2 , namely: 1) Deciduous broad-leaved forest; 2) Evergreen coniferous forest; 3) Coniferous broad-leaved mixed forest; 4) Deciduous broad-leaved shrub; 5) Meadow; 6) Grassland; 7) Other grassland; 8) Paddy field; 9) Non-irrigated farmland; 10) Garden land; 11) Herbaceous wetland; 12) Lake; 13) Reservoir; 14) River; 15) Urban green land; 16) Construction land; 17) Bare rock; 18) Bare land; 19) Desert; 20) Saline alkali land; and 21) Glacier. The overall accuracy of the classification was more than 85% [ 35 ].

Meteorological data

In this study, the monthly average temperature, precipitation, and sunshine hours from 1981 to 2012 in Gansu Province and its surrounding meteorological stations were used. The data was obtained from Gansu Meteorological Bureau and China Meteorological Science Data Sharing Service Network ( http://cdc.nmic.cn ).

Other geographic data

The annual average NPP data and the annual average water production data from 2000, 2005, 2010, and 2015 were used in this study, and were obtained from the Satellite Application Center of the Ministry of Ecology and Environment.

Socioeconomic data

Social and economic data from 2000 to 2015 were used in this study, and were obtained from the Gansu Province Statistical Yearbook, China Statistical Yearbook, and national agricultural product cost–benefit data. The cultivated land quality data are from the Annual Renewal Evaluation and Monitoring Results of Cultivated Land Quality in Gansu Province (2017), and the grain output of each county is from Gansu Province Rural Yearbook (2000–2014). The monitoring data of atmospheric environmental quality status comes from Gansu Environmental Monitoring Center Station for the period 2015–2018, and the monitoring data of surface water comes from the Bulletin of Environmental Conditions in Gansu Province and the Bulletin of Environmental Conditions in China, for the period 2000–2015.

Classification of ecosystem service functions

Based on the research results of Costanza et al. [ 5 ], de Groot et al. [ 36 ], MA [ 37 ], and Burkhard et al. [ 38 ] on the classification of ES and the characteristics of the ecosystems in Gansu Province, ES were divided into the following functions: ecological integrity, regulatory services, supply services, and cultural services. Because of the double-counting problem between ecological integrity and other ecosystem services, ecological integrity was, however, not included in the calculation of ESV. Supply services mainly considered crops, livestock, and fresh water; regulation services mainly considered local climate regulation, air quality regulation, groundwater supply, soil conservation, windbreak and sand fixation, and water purification; and cultural services mainly considered entertainment and aesthetic value. Because Gansu is rich in biodiversity, and this forms an important part of the value of ecological resources, the value of biodiversity protection was also included in the value calculation.

Improved method for value equivalent factor per unit area

Determination of standard equivalent factor.

The research period in this study is 2000–2015, and the net profit of agricultural products differed each year due to changes in social and economic conditions, and agricultural production technology. The ESV calculated only by the net profit of agricultural products during the study period is not representative. Therefore, in addition to the statistical information obtained (for example, from the Gansu Yearbook, the Second National Agricultural Census in Gansu Province, the Gansu Survey Yearbook, and the compilation of cost and income data of agricultural products in China), the sowing area and net profit of wheat, corn, potato, and oil crops per unit area were obtained, and the average sowing proportion and average net profit were calculated. Based on this, the value of a standard equivalent factor was calculated. The calculation method was as follows:

where D represents the ESV of a standard equivalent factor (yuan · hm -1 ); S W , S t , S V , and S X represe the sowing area proportion of wheat, corn, potato, and oil to the sowing area of the four crops; and F W , F T , F V , and F X represent the average net profit of wheat, corn, potato, and oil crops per unit area in Gansu Province (yuan · hm -1 ).

Value equivalent factor per unit area

The basic value equivalent of ecosystem service function per unit area (hereinafter referred to as basic equivalent) refers to the annual average value equivalent of various service functions of different ecosystem types per unit area. Previous studies on equivalence factors [ 3 , 18 , 19 ] are based on the annual average value on a national scale, and have a rough classification of ecosystem types, which cannot meet the need of the refinement of ecosystem classification, nor precisely reflect the difference in service function among ecosystem types. Therefore, in this study, the average value equivalent factor per unit area of different ecosystems was determined, by following the calculation process described below.

• For the types of ecosystems and the corresponding ecosystem service types in Gansu Province (in cases where there was an equivalent factor in the equivalence factor table of Xie et al. [ 3 ]), the national average value equivalence factor was used. On this basis, by constructing the correction coefficient, it was converted into the average value equivalence factor of ecosystem services functions, such as fresh water supply, local climate regulation, entertainment and aesthetic value, air quality regulation, and water purification.
• Relevant international literature, such as publications by Elsevier, Springer Nature, Wiley, and the Chinese How Net database, was searched. We inputted retrieval words such as Gansu Province, the names of each basin and city in Gansu Province, Qilian Mountain, and Gannan Plateau, to obtain research results on ecosystem service value calculated by ecosystem service function quantity in Gansu Province. If, in the future, there are many more papers on the evaluation of ESV, the journals with the highest influence should be selected for average calculation, and the proportion with standard equivalent should be calculated as the basic equivalent of ecosystem service functions, such as the local climate regulation and soil conservation functions of shrubs.
• We prioritized the collection and sorting of domestic published research results of ecosystem service value calculated by ecosystem service function quantity. The average of selected ESV, and thereafter the proportion with standard equivalents, should be calculated, so as to convert them into the average value equivalent factor of ecosystem service function, as the basic equivalent of the ecosystem service function, which is used to determine the value equivalent of ecosystem service functions, such as garden land, shrub land, forest land, and swamp wetland.
• If no relevant research results for Gansu Province can be found, relevant research results for other regions in China should be collected. ESV per unit area of ecosystem should be calculated, and then compared with the standard equivalent value. It can be converted into an average value equivalent factor of ecosystem service function by constructing a correction coefficient, as the basic equivalent of the ecosystem service function, which is used to determine the value equivalent of some ecosystem service functions, such as lakes, reservoirs, saline alkali land, and urban green space.
• There are great differences between the ecosystem service functions in Gansu Province and those of the entire country. Therefore, in this study, the value equivalence factor was localized and calibrated by calculating the ecosystem service function quantity per unit area, such as the biodiversity maintenance value of forest land, grassland, wetlands, and desert ecosystems, and the crop supply service of paddy fields and dry land.
• If there is no ecosystem service function value listed in directly corresponding documents in the secondary classification of ecosystem, and it is therefore difficult to calculate the ESV, refer to the equivalent factors listed by Xie et al. [ 3 ], as they were determined by experts’ experience. Transform them into the average value equivalent factors of the ecosystem service function in Gansu Province through use of the correction coefficient, as the basic equivalent of the ecosystem service function, such as local climate regulation and air quality regulation of the secondary types of desert and wetland ecosystems, and soil conservation services and water purification services of the second level of desert ecosystems.

Through the above six steps, the value of the main ecosystem types for a certain ecosystem service function per unit area in Gansu Province can be obtained, by referring to relevant literature or doing calculations, as shown in Table 1 .

Correction index of value equivalent factor per unit area

• 1 Crop supply correction index ( N)

The calculation method of crop supply correction index is as follows:

where y is the average output per unit area in Gansu Province, and Y is the national average output per unit area.

The calculation of y is based on the following formula: y = (average yield per unit area of wheat/average yield per unit area of wheat) × sowing proportion of wheat + (average yield per unit area of corn/average yield per unit area of corn) × sowing proportion of corn + (average yield per unit area of potato/average yield per unit area of potato) × sowing proportion of potato + (average yield per unit area of oil/average yield per unit area of oil) × sowing proportion of oil.

The calculation method of Y is the same as that of y .

• 2 Fresh water supply correction index ( D)

The fresh water supply correction index is calculated as follows:

where w is the average water supply per unit area in Gansu Province (10,000 m 3 ), and W is the average water supply per unit area in China (10,000 m 3 ). The water supply data comes from the Water Resources Bulletins (2000–2015) for Gansu Province and China.

• 3 Air quality regulation correction index (K)

The air quality regulation correction index is calculated as follows:

where a is the average proportion of air quality standards of prefecture level cities in Gansu Province, and A is the average proportion of air quality standards of prefecture level cities in China. The air quality standards data come from the Environmental Quality Bulletins (2000–2015) for Gansu Province and China.

• 4 Water purification correction index ( S )

The calculation method of water purification correction index is as follows:

where q is the average length proportion of class I–III water reach in Gansu Province, and Q is the average length proportion of class I–III water reach in China. The length data of water quality reach is from the Water Resources Bulletins (2000–2015) for Gansu Province and China.

• 5 Entertainment and aesthetic value correction index ( Y )

The calculation method of entertainment and aesthetics value is calculated as follows:

where r is the average tourism revenue per unit area in Gansu Province, and R is the average tourism revenue per unit area in China. The tourism revenue data comes from the Statistical Yearbooks (2000–2015) for Gansu Province and China.

Regional difference adjustment index

• 1 Crop supply regulation index ( A1 )

The crop supply regulation index is calculated as follows:

where ai is the average yield per unit area in Gansu Province, A is the average yield per unit area in Gansu Province, the calculation method of ai and A is the same as in Eq ( 1 ), a1 is the high-yield area, and a2 is the low-yield area.

According to Cheng [ 68 ], there are obvious spatial differences in grain production of cultivated land in Gansu Province. Previous studies [ 69 ] found that the correlation between cultivated land quality and land use is relatively high, with the correlation coefficient reaching 0.874. First, this was reflected in the cultivated land quality level (land use level) of each county as referred to in related studies [ 70 ] on the spatial distribution of land use level in 2015 in Gansu Province. Second, in terms of proportion of cultivated land use level to the total cultivated land area of each county in Gansu Province, 27% of the counties were classified as high-yield areas, and the rest were classified as low-yield areas. Finally, the average yield per unit area was calculated in high- and low-yield areas of each county, as well as in the province as a whole (refer to the calculation result of Eq ( 1 )). The average yield in the high- and low-yield areas was compared with the average yield per unit area in Gansu Province, and the regulation index of crop supply in high- and low-yield areas was obtained.

• 2 Livestock supply adjustment index ( A2)

The livestock supply adjustment index is calculated as follows:

where bi is the average livestock carrying capacity of each area; b1 is the average livestock carrying capacity in agricultural areas; b2 is the average livestock carrying capacity in semi-pastoral areas; and b3 is the average livestock carrying capacity in pastoral areas.

Gansu Province is divided into pastoral, semi-pastoral, and agricultural areas because of the great difference in livestock supply capacity between pastoral and agricultural areas. Previous studies [ 71 ] have calculated the livestock carrying capacity in agricultural and pastoral areas of Gansu Province, and found that the livestock carrying capacity of agricultural areas was 0.85 times that of pastoral areas. The average of livestock carrying capacity in agricultural and pastoral areas was considered the livestock carrying capacity in the semi-pastoral areas.

• 3 Fresh water supply regulation index ( A3 )

The fresh water supply regulation index was calculated as follows:

where ci is the average water yield per unit area of each area; c1 is the average water yield per unit area in the water rich areas; c2 is the average water yield per unit area in the water poor areas; and c3 is the average water yield per unit area in the dry areas.

The distance between the east and west, and the north and south is large in Gansu Province, and precipitation decreases from southeast to northwest due to the influence of water vapor and terrain. According to research [ 72 ], Gansu Province is divided into abundant water areas (Liupanshan–Longshan area, Longnan Mountain area, Gannan Plateau, and Qilian Mountain Area), water poor areas (Longdong, Longdong–Loess Plateau area, north of Lanzhou area), and dry areas (Hexi Corridor, Beishan Mountain area, and the desert area bounded by the Qilian Mountain foot). Using the water yield module in the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model, the average multi-year water yield of the water rich areas, water deficient areas, and dry areas was calculated for 2000–2015. The water yield per unit area in the water deficient areas was 0.68 times that in the water rich areas, and the water yield per unit area in the dry areas was 0.08 times that in the water rich areas.

• 4 Local climate regulation index (A4)

The local climate regulation index was calculated as follows:

where di is the average NPP of each partition; d1 is the NPP value of the high adjustment area; d2 is the mean value of NPP in the middle regulation area; and d3 is the NPP value of the low regulation area.

A large amount of observation data analysis shows that a change in surface vegetation may have a significant impact on local and regional climate by changing surface attributes such as surface albedo, roughness, and soil moisture [ 73 – 76 ]. The higher the area of vegetation NPP, the stronger the function of climate adjustment. Therefore, the value of NPP is used to measure regional differences in climate regulation. According to the spatial distribution characteristics of NPP and the boundaries of townships, Gansu Province is divided into high regulation area, middle regulation area, and low regulation area. The average value of NPP in the three regulation areas was calculated, and the ratio of NPP between the high regulation area and the middle adjustment area was taken as the adjustment index in the high adjustment area. The average value ratio of NPP between the low adjustment area and the median adjustment area was used as the adjustment index of the low value area.

• 5 Air quality regulation index ( A5 )

The air quality regulation index was calculated as follows:

where ei is the average vegetation coverage in each area; e1 is the average vegetation coverage in the area with good air quality; e2 is the average vegetation coverage in the area with average air quality; and e3 is the average vegetation coverage in the area with poor air quality.

Generally, the better the air quality in a region, the greater the air quality regulation service function. According to the 2015 Environmental Quality Bulletin in Gansu Province, PM 10 and PM 2.5 were the main air pollutants. Only one of the 14 cities and prefectures has reached the secondary standard of ambient air quality, so the concentration of pollutants was taken as the index to measure the level of air quality regulation function. In this study, PM 10 and PM 2.5 concentration monitoring data were selected at 111 provincial monitoring points in Gansu Province, and through Kriging interpolation, the spatial distribution of PM 10 and PM 2.5 concentration was obtained in the whole province, which was divided into three zones: the area meeting the secondary quality standard was classified as the area with the best air quality, indicating that the area had the highest air quality regulation function; the other two areas were demarcated according to pollutant concentration. Vegetation coverage is closely related to air purification function. In this study, the ratio of the average vegetation coverage in the three regions was used as the air quality regulation index.

• 6 Groundwater recharge regulation index ( A6 )

The groundwater recharge index was calculated as follows:

where fi is the ratio of actual exploitation amount and exploitable amount of groundwater in each zone; f1 is the ratio of actual exploitation amount and exploitable amount of groundwater in heavily mined areas; and f2 is the ratio of actual exploitation amount and exploitable amount of groundwater in areas that are not heavily mined, assuming that the actual exploitation amount and exploitable amount of groundwater in those areas are balanced, with the ratio set as 1.

The overexploitation of groundwater results in drainage of the aquifer, a decrease in groundwater level, the formation of a funnel, and land subsidence. Therefore, when rapid development exceeds the resource stock and environmental capacity, the value of the groundwater ecosystem will inevitably continue to appreciate. Different regions have different needs for groundwater recharge function, resulting in different values. To reflect the regional differences in groundwater recharge regulation function value, we used groundwater in heavily mined areas and areas that are not heavily mined to measure the regional differences in groundwater recharge function. Groundwater in heavily mined areas has a higher groundwater recharge value than in areas that are not heavily mined. According to the delimitation results of groundwater in heavily mined areas in Gansu Province [ 77 ], there are 46 heavily mined areas, involving 32 counties. The ratio of the actual and exploitable groundwater in the heavily mined area is used as the groundwater supply regulation index.

• 7 Soil conservation regulation index ( A7 )

The soil conservation regulation index was calculated as follows:

where gi is the average erosion modulus of each area; g1 is the average erosion modulus of the key prevention area; g2 is the average erosion modulus of the key control area; and g is the allowable amount of soil erosion.

Gansu Province is located at the junction of three plateaus, and its soil conservation functions vary substantially in different areas. In terms of soil and water loss in the key prevention and key governance areas, there is better vegetation, less soil and water loss, and stronger soil conservation functions in the key prevention areas, but low forest and grass coverage, a fragile ecological environment, and extensive soil and water loss in the key governance area. Therefore, the province is divided into two zones according to the range of the key prevention and governance areas. According to classification standards for soil erosion, the allowable amount of soil and water loss in the northwest Loess Plateau is 1,000 t/km 2 . Based on the ratio of the average erosion modulus and the allowable amount of soil and water loss in the two zones, the adjustment index of soil conservation was constructed.

• 8 Regulation index of windbreak and sand fixation ( A8 )

The windbreak and sand fixation regulation index was calculated as follows:

where hi is the amount of windbreak and sand fixation in each zone; h1 is the amount of windbreak and sand fixation in the service area of windbreak and sand fixation; and h2 is the amount of windbreak and sand fixation in other areas.

The Hexi Corridor in the north of Gansu Province, and the surrounding county of Qingyang City is located in the Gobi Desert area. Therefore, this area is classified as a service area for windbreak and sand fixation, whereas other areas are not considered to have that function.

• 9 Water purification regulation index ( A 9)

The water purification regulation index was calculated as follows:

where ji is the target proportion of water quality in each zone; j1 is the length proportion of class II and above water reaches in the high water purification area; and j2 is the length proportion of class III and below water reaches in the low water purification area.

Xie et al. [ 78 ] highlighted that, as the pollution of rivers and lakes is becoming more serious, the water quality regulation function of rivers is becoming lower, and rivers and lakes almost become an area of accumulation of waste. Therefore, the water quality of the reach is closely related to its water purification function. If the water quality of this area is significantly better than that of other areas, the water purification function of this area will be of considerable importance. In this study, the water quality objectives of 236 monitoring sections of the Rivers were used to measure the water purification function of the region, and the water quality objectives of each county were quantified. If the water quality objectives of class I, or class II, or class II water and class III water reaches can be achieved simultaneously, the water purification function of the county is considered to be high. Additionally, the length proportion of the class II and class III water reaches and below are calculated. The length proportion of the class II water reach to the class III water reach and below is taken as the water purification regulation index in the high water purification area.

• 10 Entertainment aesthetics value adjustment index ( A10 )

The value adjustment index of entertainment and aesthetics was calculated as follows:

where ki is the value adjustment index of entertainment aesthetics in each zone; k1 is the value adjustment index of entertainment and aesthetics in key tourist areas; k2 is the value adjustment index of entertainment and aesthetics in general tourist areas; and k3 is the value adjustment index of entertainment and aesthetics in other regions.

Entertainment value refers to the value obtained by tourists when they are engaged in tourism activities in an ecotourism scenic spot, which is the sum of the value used by direct recreation and the non-use value possessed by resources; aesthetic value refers to the pleasure value brought by natural ecosystems to people’s aesthetic perception of the natural and cultural landscape, and the value of its own objective aesthetic attributes is referred to as the non-use value. If people cannot reach an area that can bring recreational and pleasure value to people, it is considered that the area cannot provide the service function or temporarily does not have the function. Based on this, we first determined that the core area and buffer area of a nature reserve cannot provide this service temporarily. Other natural protected places such as forest parks, geoparks, scenic areas, and wetland areas are key tourism areas, which provide the highest entertainment and aesthetic value. Second, the whole tourism county (and not only the key tourism areas) is generally regarded as the tourism area, with the remaining areas having the lowest entertainment and aesthetic value. The adjustment indexes of the different regions are assigned by expert judgment.

• 11 Biodiversity maintenance value regulation index ( a11 )

The value adjustment index of biodiversity maintenance was calculated as follows:

where is the habitat quality index of each region; l 1 is the habitat quality index of the priority area for biodiversity conservation; and l 2 is the habitat quality index of other regions.

According to the conservation plan for biodiversity priority areas in Gansu Province, there are seven biodiversity priority areas in the province. This study considered that the areas located in the priority areas had the highest biodiversity maintenance value, followed by other areas, and the province was therefore divided into two areas. To determine the adjustment index of the different regions, we used the habitat quality module of the InVEST model to calculate the habitat quality index of the different regions [ 79 ], and determined the adjustment index by comparing the size of the habitat quality index of the two regions.

Through the above methods, the value equivalent factor table per unit area was established for Gansu Province ( Table 2 ).

1 Paddy field; 2 Non irrigated farmland; 3 Garden land; 4 Deciduous broad-leaved forest; 5 Evergreen coniferous forest; 6 Coniferous broad-leaved mixed forest; 7 Deciduous broad-leaved shrub; 8 Meadow; 9 Grassland; 10 Other grassland; 11 Lake; 12 Reservoir; 13 River; 14 Herbaceous wetland; 15 Construction land;16 Urban green land; 17 Desert; 18 Bare rock; 19 Saline alkali land;20 Bare land; 21 Glacier.

A: Crops supply; B: livestock supply; C: Fresh water supply; D: Local climate regulation; E: Air quality regulation; F: Groundwater supply; G: Soil conservation; H: Windbreak and sand fixation; I: Water purification; J: Entertainment aesthetic value; K: Biodiversity maintenance value.

Value evaluation model based on regional differences

Different geomorphic types will affect the distribution of light, heat, water, and soil types in the region [ 80 ]. Similarly, different regional ecological environments, degree of ecological protection, intensity of ecological demand for different land use types, and implementation of local policies will affect the benefits human beings derive from the ecosystem, thus affecting the regional differences and divisions of ESV. The ArcGIS spatial analysis tool was used to grid Gansu Province, and a complete grid of 1 km × 1 km was extracted. Based on the calculation of the ESV of the grid unit, the total ESV ( V ) was calculated using the following equation ( Fig 3 ):

where V c is the value of ecosystem service function c ; c is ecosystem service function, and the value is between 1 and 11.

where D is the standard equivalent factor; F m is the value equivalent factor per unit area of ecosystem type m; A c is the regional difference adjustment index of ecosystem service function c ; S m is the area of ecosystem type m (km 2 ); and n is the grid number.

Analysis of the change in ecosystem in Gansu Province

Desert is the largest ecosystem type in Gansu Province ( Table 3 ), followed by grassland, arable land, and forest. Both the glacier and wetland ecosystems account for a small part. Desert is mainly found in the north of Gansu; grasslands are mainly distributed in the Gannan Plateau in central and eastern Gansu; cultivated land is mainly distributed in the central area of Gansu and Hexi Corridor; and forests are mainly found in the Longnan, Ziwuling, and Qilian Mountains. In terms of changes in the ecosystem, the forest, grassland, and urban ecosystems have been increasing continuously in the past 15 y. The cultivated land ecosystem has been continuously decreasing. Although the wetland and glacier ecosystems have been increasing in the past 15 y, they have been decreasing over the longer term. The desert ecosystem has been increasing in general.

Overall evaluation of ESV in Gansu Province

In general, ESV decreases from south to north, and from east to west in Gansu Province ( Fig 4 ), which is consistent with the spatial distribution of forest, grassland, and desert ecosystems. There are adjoining desert areas north of Gansu Province, the area with the lowest ESV. However, the ecological environment is relatively healthy in the south of Gansu Province, with high vegetation coverage and ESV. In the center-east of Gansu Province, where human activities are most frequent, inducing relatively high disturbance on the natural ecological environment, the ESV is relatively low.

The value of local climate regulation and biodiversity maintenance ( Table 4 ) is much higher than that of other service functions, and constitutes the main contributor to ESV in Gansu Province. In terms of the change in each service function value, the value of soil conservation, windbreak and sand fixation, and biodiversity protection has been increasing continuously in the past 15 y, whereas the supply value of crops has been decreasing continuously. The supply value of fresh water, local climate regulation, air quality regulation, water purification function, groundwater supply, and entertainment and aesthetic value show a fluctuating change state and an overall decreasing trend.

The value of the grassland and forest ecosystems is the highest, accounting for more than 75% of the total value ( Table 5 ), whereas the value of urban and glacial ecosystems is the lowest. In terms of change in each ecosystem type value, the value of forest and urban ecosystems is increasing, whereas the value of cultivated land ecosystem is decreasing. The value of grassland, wetland, and glacier ecosystems fluctuates, and the overall trend is decreasing. In contrast, the value of the desert ecosystem fluctuates, and the overall trend is increasing. Over the past 15 y, the total value of the various ecosystem services has increased by 3.43 billion yuan, and the increase in forest ecosystem value has been the highest, whereas the decrease in grassland ecosystem value has been the highest.

Analysis of the spatiotemporal change in ESV in Gansu Province

Over the past 15 y, the townships with increased ESV are mainly distributed in the east and south of Gansu Province, and west of the Hexi Corridor. The townships which had a decrease in ESV are located in Qilian Mountain and Gannan Plateau ( Fig 5 ).

Over the past 15 y, the number of townships with increased ESV has decreased. There were 959 townships with an increased ESV in 2000–2005, 758 townships in 2005–2010, and only 391 townships increased in value in 2010–2015. From 2000 to 2015, there were 818 townships with increased ESV.

From 2000 to 2005, townships with increased ESV were mainly distributed in the Qilian Mountain, and the eastern and southern parts of Gansu (Tianshui, Pingliang, Qingyang, and Longnan). From 2005 to 2010, the ESV of most townships decreased in the Gannan Plateau and Qilian Mountain, whereas the increased townships were mainly located in Tianshui, Longnan, and the western section of the Hexi Corridor. From 2010 to 2015, the ESV of most townships declined in Lanzhou, Baiyin, Dingxi, Gannan Plateau, and Hexi Corridor, and the townships where the value increased were concentrated in the north and south.

Advanced value evaluation model

In this study, ESV was evaluated by improving the value equivalent factor per unit area and constructing a regional differential value assessment model in Gansu Province. Different ecosystem types provide different ES types to humans. In the current research on ESV, scholars mostly refer to the classification of ecosystem types by Costanza et al. [ 5 ], which is limited to forest, grassland, farmland, wetland, desert, and river. Xie et al. [ 3 ] improved this method by accounting for the value of 14 types of ecosystem services in China, and more precisely reflected the differences between ecosystem types. However, this method was based on national scale, and did not meet the needs of practical research, namely a reduction of the research scale and refinement of the classification of ecosystems. Based on the actual ecological situation in Gansu Province, this study identified 7 types of primary ecosystems and 21 types of secondary ecosystems to cover the main ecosystem types in Gansu Province more comprehensively. This reflected the differences between the types of ecosystems, and highlighted the importance of ESV.

In different regions, the same ecosystem type provides different ES and their value to humans are quite different. Therefore, the value equivalent factor of Costanza et al. [ 5 ] and Xie et al. [ 3 ] has been improved by scholars by introducing factors that reflect regional differences, such as NPP, biomass, vegetation coverage, and soil erosion. However, these factors can only reflect regional differences in the main types of ES functions, which are mainly driven by natural factors. It is even more difficult to truly reflect differences in ecological service functions in regions with complex ecological environment characteristics and socioeconomic conditions, such as Gansu Province. In this study, first, the correction index of the value equivalent factor per unit area was constructed. We converted the equivalent factors on the national average level provided by Xie et al. [ 3 ] to an average level in Gansu Province, calculated the average level of some of the equivalent factors in Gansu Province, and then converted the equivalent factors in the average level in Gansu Province to a level with significant regional differences by constructing the regional difference adjustment index of each ES function type. In the process of regional difference conversion, the differences in ecological environment quality, resource endowment, and economic and social development of the different regions were fully considered, thereby more accurately reflecting the ecological well-being of residents in different regions, and the degree of damage to the local ecological environment and resources.

Errors in the value evaluation model

The accurate construction of the equivalent factor table is the core of the equivalent factor method. In the process of improving the equivalent factor table of Xie et al. [ 3 ], this study integrated evaluation results from the literature based on the physical quantity method in Gansu Province or other regions in China. This can avoid or reduce subjective conjecture, which is easily caused by empiricism from the past. The accuracy of the research results in the literature on different ES types affects the size of the equivalent factor in this study. Considering the lack of complete research results on the different ecosystems or ecological service functions in Gansu Province, the ecological service functions of some ecosystem types are investigated based on available research results from other regions in China. This has led to a certain amount of uncertainty in this study. Future research needs to quantitatively calculate the physical quantity of ecosystem types or ecological service functions that are not currently available in the literature, and then determine the equivalent factor to improve the results of this study.

Reliability of value evaluation models

ESV assessment has been studied extensively in other regions of China, whereas there are few related studies on ESV in Gansu Province. The existing research focuses on the value of a single ecosystem service on a provincial scale [ 29 , 34 , 81 ], and the calculation method of unit area value is the main method. Research on provincial integrated ESV is almost non-existent at present [ 83 ]. The value of forest ecosystem services was 747.70 billion yuan in this study. However, this study does not consider the difference in people’s willingness to pay, and their ability to pay, for ESV caused by social development. By including the willingness and ability to pay, the value of forest ecosystem services was 1,971.23 billion yuan in 2010, which is closer to the official release of service value of the forest ecosystem (2,007.97 billion yuan in 2011), and the service value of the forest ecosystem assessed by Wang et al. [ 27 ] (2,163.86 billion yuan in 2009) and Wang et al. [ 82 ] (1,802.37 billion yuan in 2008). There was, however, a big difference between the ESV evaluated in Gansu Province by Qi [ 83 ] and the ESV in this study. The value per unit area was only 98.57 billion yuan in 2010 [ 83 ] by using the value calculation method per unit area, resulting in a significantly smaller value.

Conclusions

Based on the characteristics of ecosystems in Gansu Province, this study developed a revised index based on an increase in some ecosystem equivalent factors, and revised the equivalent factors studied by Xie et al. [ 3 ] to form an equivalent factor table in line with ecosystem service valuation in Gansu Province specifically. Eleven regional difference adjustment indices to readjust the value of different service functions were then constructed. The regional difference assessment model constructed in this study distinguished the regional differences in similar ecosystem services to evaluate the ESV in Gansu Province more objectively. The main conclusions are as follows:

• The desert ecosystem type covers the largest area in Gansu Province, followed by grassland, arable land, and forest ecosystems, and the remaining ecosystems account for only a small part. Desert is mostly located in northern Gansu. Grasslands are mainly located in the Gannan Plateau, Longzhong, and Longdong. Cultivated land is mainly located in Longzhong and Hexi Corridor, and forests are mainly located in Longnan, Ziwuling, and the Qilian Mountains.
• From 2000 to 2015, the grassland ecosystem area increased the most, whereas the cultivated land ecosystem area decreased the most. Forest, grassland, and urban ecosystems in Gansu Province continue to increase. Cultivated land ecosystems continue to decrease. Although wetlands and glacial ecosystems have increased over the past 15 y, they have decreased over the long term. The number of desert ecosystems has increased.
• In 2015, the total ESV for Gansu Province reached 2,239.56 billion yuan, to which the forest and grassland ecosystems contributed the most. In terms of the value of each service function of the ecosystem, the local climate regulation and biodiversity maintenance functions are the main service functions in the province. Regarding the spatial distribution of service values, ESV gradually increases from northeast to southwest, and the areas with high ESV concentrations are Qilian and Longnan Mountains.
• From 2000 to 2015, ESV increased by 3.43 billion yuan in Gansu Province. The value of forest ecosystems increased the most, whereas the value of grassland ecosystems decreased the most, showing a trend of increasing first, then decreasing, and then slowly increasing again. The value of forest and urban ecosystems continues to increase, and the value of cultivated land ecosystems continues to decrease. From the spatial characteristics of ESV changes, areas with reduced values gradually move from central Gansu to the surrounding areas.

Supporting information

Acknowledgments.

We are also grateful for the comments and criticisms of an early version of this manuscript by our colleagues and the journal’s reviewers. Acknowledgement for the data support from "National Earth System Science Data Center, National Science & Technology Infrastructure of China. ( http://www.geodata.cn )".We would like to thank Editage ( www.editage.cn ) for English language editing.

Funding Statement

The sources of funding for my study 1. This research was supported by Gansu Youth Science and Technology Fund Program(NO.18JR3RC420), Gansu Soft science project(NO.20CX3ZA002) and Gansu Social Science Planning Project(NO.19YB155). The funding institution of these projects is the Department of science and technology of Gansu Province. 2. The funding for the research was provided by the funders in the research, and the funding are used for data collection, writing and publishing manuscripts, but not for staff salaries.

Data Availability

• PLoS One. 2021; 16(2): e0240272.

Decision Letter 0

27 Oct 2020

PONE-D-20-28811

Evaluation method of ecosystem service value under complex ecological environment: A case study of Gansu Province, China

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Reviewer #1: In this paper, xiaojiong Zhao et al. has taken Gansu Province as an example, the regional division method of ecosystem service function is proposed based on the characteristics of differences among different regions, and the variation trend of ESV in Gansu province from 2000 to 2015 is analyzed, which expands the thinking of regional ecological evaluation. The subject matter of this paper is novel, the Angle is clear, the data analysis process is accurate and careful. However, the manuscript needs revision before it is acceptable for publication. The writing of the paper should be improved, I found some of the text is repetition and some parts are not very fluid. The specific sections are questions that should be answered before accepting and proceeding to publications.

1. In introduction, It is recommended that authors add comparisons with other ecosystem service value studies and introduce the advantages of the approach used in this article;

2. In the discussion section, I suggest comparing with other ecological service value assessment methods in Gansu Province;

3.There are still some problems in English grammar and sentences. Please check and correct them carefully.

Reviewer #2: comments to the Author:

The first time I looked at the title " Evaluation method of ecosystem service value under complex ecological environment: A case study of Gansu Province, China ", I was just wondering to know how would the authors deal with this topic. I was a little impressed and felt that this might be a very interesting manuscript. When I reviewed the manuscript, I didn't feel disappointed. In the manuscript, On the one hand, the average value equivalent factor per unit area of different ecosystems is determined in Gansu Province, with reference to the six calculation process. This method of meta-analysis will avoid or reduce the subjective conjecture which is easy to be caused by relying on experts' experience; On the other, through abundant eco-environmental data, this study established a value evaluation model and completed the evaluation of ecosystem service value under complex ecological environment. In particular, one thing is affirmed that the human activity factors that affect ecosystem service value are fully considered by Author to the evaluation of ecosystem service value, such as carrying capacity, air pollution, over exploitation of groundwater and water pollution etc. The methods and data used in the study are new. The manuscript meets the requirement for acceptation for publication.

My main concerns are as follows:

1. The description of Gansu Province may be suitable for the part of study area.

2. There lacks enough literature review on the topic in the study area. The authors may check some references on this topic in last decades.

Materials and Methods

1. What is the basis of the ecosystem type classification?

2. Please supplement the distribution map of ecosystem types

3. from 2000-2015, what does this mean? The authors have to state clearly which year was used.

4. Classification of ecosystem service functions. Please explain the specific problem of repeatability. The description is not fully understood due to the ecological integrity has been evaluated in previous research.

1. In the Table3, the unit of area is km2, while in formula 19, the unit of area is ha.

2. Biodiversity maintenance value regulation index (a11), How the habitat quality index is measured?

3. "invest" should be "InVEST"

Other detail question

English needs proofreading and editing, especially those sentences related to comparison. In addition, there exists many formatting problems in this manuscript, please verify the full text.

1.Please unify the number of decimal points in the whole text.

2. Table1. Please note that the black space.

Reviewer #3: (1)The paper takes Gansu Province as an example, on the basis of fully considering the 6 regional differences of ecosystem service function. But it don’t explain why Gansu was taken as an example? Does Gansu have a typical ecological service system?

(2)making dialogue with the ESV evaluation and calculation literatures by taking the role of your specific context.

(3)This paper did a poor job in readability, with many typo errors and unstructured sentences. The authors need a copy editor before next submission.

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Reviewer #1: No

Reviewer #2: No

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Submitted filename: reviewers comments.docx

Author response to Decision Letter 0

12 Dec 2020

Reply to Reviewer #1

“In introduction, It is recommended that authors add comparisons with other ecosystem service value studies and introduce the advantages of the approach used in this article.”

We added comparisons with other ecosystem service value studies and introduce the advantages of the approach used in this article, line108-118 in marked-up copy of my manuscript. The modified part is highlighted in yellow.

“In the discussion section, I suggest comparing with other ecological service value assessment methods in Gansu Province.”

There are few methods to evaluate the value of ecosystem services in Gansu Province, through literature retrieval, we compared with the study by Wang et al; line735-736 in marked-up copy of my manuscript. The modified part is highlighted in yellow.

“There are still some problems in English grammar and sentences. Please check and correct them carefully.”

We used Editage for English language editing that edited my manuscript, and we have carefully and thoroughly proofread the manuscript to correct all the grammar and typos. For details of manuscript editing, please refer to marked-up copy of my manuscript.

Reply to Reviewer #2

“In introduction, the description of Gansu Province may be suitable for the part of study area.”

In introduction,“Gansu Province is located in the northwestern inland in China. …..Its special geographical location and natural conditions form a more distinct ecological structure.”, this part is repeated with the content in the study area, so this description of Gansu Province has been deleted in introduction. line 119 in marked-up copy of my manuscript. The modified part is highlighted in yellow.

“There lacks enough literature review on the topic in the study area. The authors may check some references on this topic in last decades. ”

We checked some references about method of ecosystem services value, and added other ecosystem service value studies. line 108-118 in marked-up copy of my manuscript. The modified part is highlighted in yellow.

“What is the basis of the ecosystem type classification? ”

The basis of the ecosystem type classification was added in Ecosystem type data, line 160-184 in marked-up copy of my manuscript. The modified part is highlighted in yellow.

“Please supplement the distribution map of ecosystem types.”

The distribution map of ecosystem types was added in line 185(Figure 2) in marked-up copy of my manuscript. The modified part is highlighted in yellow.

“from 2000-2015, what does this mean? The authors have to state clearly which year was used. ”

The mean is “from 2000, 2005, 2010, and 2015”. line 194-195 in marked-up copy of my manuscript. The modified part is highlighted in yellow.

“Classification of ecosystem service functions. Please explain the specific problem of repeatability. The description is not fully understood due to the ecological integrity has been evaluated in previous research. ”

“The specific problem of repeatability” means is “the double- counting problem between ecological integrity and other ecosystem services”. line 217-219 in marked-up copy of my manuscript. The modified part is highlighted in yellow.

“In the Table3, the unit of area is km2, while in formula 19, the unit of area is ha. ”

The unit of area is unified as km2. line 593 in marked-up copy of my manuscript. The modified part is highlighted in yellow.

“Biodiversity maintenance value regulation index (a11), How the habitat quality index is measured? ”

The habitat quality index was measured in detail in another article of the author, so we added the reference. line 562-563 in marked-up copy of my manuscript. The modified part is highlighted in yellow.

“"invest" should be "InVEST"”

We modified the invest to InVEST. line 562 in marked-up copy of my manuscript. The modified part is highlighted in yellow.

“English needs proofreading and editing, especially those sentences related to comparison. In addition, there exists many formatting problems in this manuscript, please verify the full text. ”

Response10:

“Please unify the number of decimal points in the whole text. ”

Response11:

We unified the number of decimal points in the whole text.line 37, 42,567,612,632,646 in marked-up copy of my manuscript. The modified part is highlighted in yellow.

Comment 12:

“Table1. Please note that the black space. ”

Response12:

We revised the black space. line 314 in marked-up copy of my manuscript. The modified part is highlighted in yellow.

Reply to Reviewer #3

“The paper takes Gansu Province as an example, on the basis of fully considering the 6 regional differences of ecosystem service function. But it don’t explain why Gansu was taken as an example? Does Gansu have a typical ecological service system? ”

We stated the reasons that the types of ecosystems are complex and diverse in Gansu Province, line 119-127 in marked-up copy of my manuscript. The modified part is highlighted in yellow.

“making dialogue with the ESV evaluation and calculation literatures by taking the role of your specific context. ”

We have supplemented the relevant references on the other ecosystem service value studies, line108-118, 858-863 in marked-up copy of my manuscript. The modified part is highlighted in yellow.

“This paper did a poor job in readability, with many typo errors and unstructured sentences. The authors need a copy editor before next submission. ”

Submitted filename: Response to Reviewers.docx

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Peer-reviewed

Research Article

Ecosystem service value evaluation method in a complex ecological environment: A case study of Gansu Province, China

Contributed equally to this work with: Xiaojiong Zhao, Jian Wang, Junde Su, Wei Sun

Roles Methodology, Writing – original draft

Affiliations Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, China, University of Chinese Academy of Sciences, Beijing, China, Gansu Academy of Eco-environmental Sciences, Lanzhou, China

Roles Funding acquisition, Project administration

* E-mail: [email protected]

Affiliation Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, China

Roles Validation, Writing – original draft

Affiliation Gansu Vocational & Technical College of Nonferrous Metallurgy, Jinchang, China

Roles Writing – review & editing

Affiliation Gansu Academy of Eco-environmental Sciences, Lanzhou, China

• Xiaojiong Zhao, 
• Jian Wang, 
• Junde Su, 

• Published: February 5, 2021
• https://doi.org/10.1371/journal.pone.0240272
• Peer Review
• Reader Comments

The scientific assessment of regional ecosystem service value (ESV) is helpful in developing scientific ecological protection plans and compensation policies. However, an ESV evaluation method that can adapt to the complex and diverse characteristics of the ecological environment has not been established. This study takes Gansu Province in China as an example, fully considering the regional differences in ecosystem service function. Five correction indices for the value equivalent factor per unit area were constructed on a provincial scale, and a regional difference adjustment index for 11 categories of ecosystem services was constructed on a regional scale. In this way, a value evaluation model based on regional differences was established. The results show that in 2015, the total ESV reached 2,239.56 billion yuan in Gansu Province, with ESV gradually increasing from the northeast to the southwest, and the high-value areas of service function being located in Qilian and Longnan Mountains. The forest and grassland ecosystems contributed the most to the ESV. From the perspective of value composition, local climate regulation and biodiversity maintenance functions are the main service functions of Gansu Province. From 2000 to 2015, ESV increased by 3.43 billion yuan in the province. The value of forest and urban ecosystems continued to increase, whereas the value of cultivated land ecosystem continued to decrease. In terms of spatial characteristics of the service value change, the area that experienced value reduction gradually moved from the central part of Gansu Province to the surrounding areas. The evaluation method proposed in this paper provides a relatively comprehensive evaluation scheme for the spatiotemporal dynamic evaluation of ESV in complex ecological environments.

Citation: Zhao X, Wang J, Su J, Sun W (2021) Ecosystem service value evaluation method in a complex ecological environment: A case study of Gansu Province, China. PLoS ONE 16(2): e0240272. https://doi.org/10.1371/journal.pone.0240272

Editor: Bing Xue, Institute for Advanced Sustainability Studies, GERMANY

Received: September 19, 2020; Accepted: January 16, 2021; Published: February 5, 2021

Copyright: © 2021 Zhao et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the manuscript and its Supporting Information files.

Funding: The sources of funding for my study 1. This research was supported by Gansu Youth Science and Technology Fund Program(NO.18JR3RC420), Gansu Soft science project(NO.20CX3ZA002) and Gansu Social Science Planning Project(NO.19YB155). The funding institution of these projects is the Department of science and technology of Gansu Province. 2. The funding for the research was provided by the funders in the research, and the funding are used for data collection, writing and publishing manuscripts, but not for staff salaries.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Ecosystems not only provide various raw materials or products directly for human survival, but also have other functions such as regulating climate, reducing pollution, conserving water sources, maintaining soil quality, preventing wind and sand erosion, reducing disasters such as floods and fires, and protecting biodiversity. All ecosystem products and services are collectively referred to as ecosystem services (ES) [ 1 , 2 ]. The evaluation of ecosystem service value (ESV) forms the basis of regional ecological construction, ecological protection, ecological work division, and ecological decision-making regarding natural assets, and has become a popular research topic in ecology [ 3 – 5 ]. Since Costanza first quantified the value of global ES in 1997, ESV calculation has increasingly been used as the core basis of ecological asset accounting, thus helping the spatial cognition and sustainable management of national systems in a more intuitive way [ 5 , 6 ]. However, because of the different choices in parameters set by different scholars, the evaluation results of the same ES may vary greatly, and there is a lack of comparability between the ESV obtained through different pricing methods, while a mature pricing method for ESV has not yet been formed internationally [ 7 – 10 ].

At present, research on the evaluation method of ESV can be roughly divided into two categories. The fist is a method based on the service function price per unit area. This method evaluates some key service functions by means of a series of ecological equations, such as food production, soil and water conservation, carbon and oxygen production, and habitat quality [ 11 – 14 ]. The functional value method can accurately measure the extent of some service functions in a region. However, for different service functions, different ecological equations and parameter inputs are often required, and the calculation process is more complicated [ 3 ]. Therefore, this method is mostly applied on a small scale, and the implementation cost is high. In addition, when using this method for evaluation, scholars often lack consideration of the ecological background of the study area, and there is no standard in selecting which service functions to evaluate [ 15 ]. These shortcomings result in significant uncertainty of the evaluation results, and limitations in the comparison of results. The second is a method based on value equivalent factor per unit area. This method was first proposed by Costanza et al. [ 5 ], and divides different land ecosystems and service functions, obtaining the equivalent value based on meta-analysis and the area of each ecosystem, to obtain the regional ESV. Compared with the functional value method, this method evaluates ESV more effectively on a large scale [ 16 ] and is widely used in research [ 3 , 5 , 17 – 19 ].

However, scholars have found that the evaluation results of the equivalent factor method are valid and reliable only when the equivalent factor accurately reflects the ecological background in the study area [ 16 , 20 , 21 ]. The equivalent factor proposed by Costanza et al. [ 5 , 17 ] is aimed at global-scale value assessment, which is not consistent with the real ecological situation in China. Xie et al. [ 18 , 19 ] conducted a survey among Chinese ecologists, and put forward an equivalent factor table of ES for China in 2003 and 2008. In 2015, Xie et al. [ 3 ] updated and improved the equivalent factor table by adding information obtained from literature and including regional biomass. This table is currently the most scientific and systematic equivalent factor table in China. The equivalent factor table proposed by Xie et al. [ 3 ] essentially reflects the average level of the national ecosystem service function. Many more recent studies [ 14 ] have shown that the strength of the different service functions is affected by different ecological processes and conditions. For example, organic matter production, gas regulation, and nutrient cycling function [ 12 ] is closely related to net primary productivity (NPP); and water supply and regulation function is closely related to rainfall [ 22 ], soil erosion [ 23 ], habitat quality [ 13 ], and the accessibility of recreational sites [ 24 ]. Therefore, when the equivalent factor method is used to evaluate the ecological value of a region, the corresponding spatial correction of the equivalent factor is needed [ 8 , 25 ]. At present, scholars only use biomass or NPP to adapt all types of service functions [ 3 , 18 , 19 , 26 ], which does not match the real situation. Xie et al. [ 18 ] for the first time selected other ecological indicators (rainfall and soil retention) besides NPP to adapt the service function.

Based on the research framework of value equivalent factor per unit area, we adopted the method of meta-analysis and fully used the evaluation results based on the physical quantity method to determine the average unit area equivalent factor in different ecosystems in Gansu Province. This method avoids or reduces the subjective conjecture easily caused by relying on the experience of experts. Additionally, abundant ecological environment data are used to correct the equivalent factor, thus completing the evaluation of ESV in complex ecological environments. Compared with previous studies [ 3 , 18 , 19 , 27 , 28 ], the evaluation results are more scientific and reasonable. In the evaluation of ESV, the impact of human activities on the ESV, such as bearing capacity, air pollution, groundwater overdraft, and water pollution. is fully considered.

The types of ecosystems are complex and diverse in Gansu Province. The diversity of ecosystem types has caused significant regional differences. However, current research mostly focuses on single or several ecosystems, and only investigate certain ES functions in the ESV in Gansu Province, such as forests [ 29 – 31 ], grassland [ 32 , 33 ], and cultivated land [ 34 ]. Considering the complex ecological environment characteristics in Gansu Province, previous studies have not investigated the ESV considering the regional differences in space, and no value evaluation method has been established according to the specific ecological environment in the region.

This study considers the regional differences and the simplicity of the equivalent factor method. In view of the application of the equivalent factors of various ecosystems on a large scale, it is necessary to closely relate the equivalent factors to the national (large) scale and to the actual situation in Gansu Province. Based on a more refined classification of the ecosystem types in Gansu Province, the study added some ecosystem equivalent factors, constructed a revised index, and revised the equivalent factors studied by Xie et al. [ 3 ] to form an equivalent factor table that was suitable for the assessment of ESV in Gansu Province. We constructed 11 regional differential adjustment indexes and readjusted the values of different service functions. Finally, we constructed a regional differential value evaluation model to evaluate the change in ESV in Gansu Province from 2000 to 2015. Considering the increasingly severe shortage in and overuse of ecological services in the region, the results of this study can provide a scientific basis for decision support for local governments to formulate more complete ecological compensation policies.

Materials and methods

The case study region is located in northwest China ( Fig 1 ), at the intersection of three major plateaus—the Loess Plateau, the Qinghai Tibet Plateau, and the Inner Mongolia Plateau—and three natural regions—the northwest arid region, the Qinghai Tibet alpine region, and the eastern monsoon region. Gansu Province is a long and narrow region, covering a total land area of 425,800 km 2 , with complex and diverse geological landforms and climate types. In addition to the marine ecosystem, there are six main land use or cover types, including forests, grasslands, deserts, wetlands, farmland, and urban areas. The Gansu region forms part of China’s “two screens and three belts” strategic ecological security barrier policy, which aims to maintain and protect the survival and reproduction of organisms, maintain the natural ecological balance, and guarantee people’s livelihoods on the Qinghai Tibet Plateau, the Sichuan–Yunnan Loess Plateau and the north sand belt. It is an important water conservation and supply area in the upper reaches of the Yangtze River and the Yellow River.

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https://doi.org/10.1371/journal.pone.0240272.g001

Data sources

Ecosystem type data..

We used national ecosystem type datasets from the Satellite Application Center of the Ministry of Ecology and Environment and the Chinese Academy of Sciences, for the periods 2000, 2005, 2010, and 2015, for the classification of ecosystems. The resolution of Landsat TM/ETM images was 30 m, SPOT-5 images was 5 or 2.5 m, Envisat image was 30 m, and HJ-1 images was 30 m. From this data, and according to the study requirements, the ecosystem types were divided into 7 primary types and 21 secondary types in the research area, and a corresponding database was established.

We then used data from 2,508 ground verification points, including 38 different ecosystem types, and integrated these ecosystem types with the ecosystem types obtained through the satellite images, into a final database with 21 ecosystem types, as shown in Fig 2 , namely: 1) Deciduous broad-leaved forest; 2) Evergreen coniferous forest; 3) Coniferous broad-leaved mixed forest; 4) Deciduous broad-leaved shrub; 5) Meadow; 6) Grassland; 7) Other grassland; 8) Paddy field; 9) Non-irrigated farmland; 10) Garden land; 11) Herbaceous wetland; 12) Lake; 13) Reservoir; 14) River; 15) Urban green land; 16) Construction land; 17) Bare rock; 18) Bare land; 19) Desert; 20) Saline alkali land; and 21) Glacier. The overall accuracy of the classification was more than 85% [ 35 ].

https://doi.org/10.1371/journal.pone.0240272.g002

Meteorological data.

In this study, the monthly average temperature, precipitation, and sunshine hours from 1981 to 2012 in Gansu Province and its surrounding meteorological stations were used. The data was obtained from Gansu Meteorological Bureau and China Meteorological Science Data Sharing Service Network ( http://cdc.nmic.cn ).

Other geographic data.

The annual average NPP data and the annual average water production data from 2000, 2005, 2010, and 2015 were used in this study, and were obtained from the Satellite Application Center of the Ministry of Ecology and Environment.

Socioeconomic data.

Social and economic data from 2000 to 2015 were used in this study, and were obtained from the Gansu Province Statistical Yearbook, China Statistical Yearbook, and national agricultural product cost–benefit data. The cultivated land quality data are from the Annual Renewal Evaluation and Monitoring Results of Cultivated Land Quality in Gansu Province (2017), and the grain output of each county is from Gansu Province Rural Yearbook (2000–2014). The monitoring data of atmospheric environmental quality status comes from Gansu Environmental Monitoring Center Station for the period 2015–2018, and the monitoring data of surface water comes from the Bulletin of Environmental Conditions in Gansu Province and the Bulletin of Environmental Conditions in China, for the period 2000–2015.

Classification of ecosystem service functions

Based on the research results of Costanza et al. [ 5 ], de Groot et al. [ 36 ], MA [ 37 ], and Burkhard et al. [ 38 ] on the classification of ES and the characteristics of the ecosystems in Gansu Province, ES were divided into the following functions: ecological integrity, regulatory services, supply services, and cultural services. Because of the double-counting problem between ecological integrity and other ecosystem services, ecological integrity was, however, not included in the calculation of ESV. Supply services mainly considered crops, livestock, and fresh water; regulation services mainly considered local climate regulation, air quality regulation, groundwater supply, soil conservation, windbreak and sand fixation, and water purification; and cultural services mainly considered entertainment and aesthetic value. Because Gansu is rich in biodiversity, and this forms an important part of the value of ecological resources, the value of biodiversity protection was also included in the value calculation.

Improved method for value equivalent factor per unit area

Determination of standard equivalent factor..

Value equivalent factor per unit area.

The basic value equivalent of ecosystem service function per unit area (hereinafter referred to as basic equivalent) refers to the annual average value equivalent of various service functions of different ecosystem types per unit area. Previous studies on equivalence factors [ 3 , 18 , 19 ] are based on the annual average value on a national scale, and have a rough classification of ecosystem types, which cannot meet the need of the refinement of ecosystem classification, nor precisely reflect the difference in service function among ecosystem types. Therefore, in this study, the average value equivalent factor per unit area of different ecosystems was determined, by following the calculation process described below.

• For the types of ecosystems and the corresponding ecosystem service types in Gansu Province (in cases where there was an equivalent factor in the equivalence factor table of Xie et al. [ 3 ]), the national average value equivalence factor was used. On this basis, by constructing the correction coefficient, it was converted into the average value equivalence factor of ecosystem services functions, such as fresh water supply, local climate regulation, entertainment and aesthetic value, air quality regulation, and water purification.
• Relevant international literature, such as publications by Elsevier, Springer Nature, Wiley, and the Chinese How Net database, was searched. We inputted retrieval words such as Gansu Province, the names of each basin and city in Gansu Province, Qilian Mountain, and Gannan Plateau, to obtain research results on ecosystem service value calculated by ecosystem service function quantity in Gansu Province. If, in the future, there are many more papers on the evaluation of ESV, the journals with the highest influence should be selected for average calculation, and the proportion with standard equivalent should be calculated as the basic equivalent of ecosystem service functions, such as the local climate regulation and soil conservation functions of shrubs.
• We prioritized the collection and sorting of domestic published research results of ecosystem service value calculated by ecosystem service function quantity. The average of selected ESV, and thereafter the proportion with standard equivalents, should be calculated, so as to convert them into the average value equivalent factor of ecosystem service function, as the basic equivalent of the ecosystem service function, which is used to determine the value equivalent of ecosystem service functions, such as garden land, shrub land, forest land, and swamp wetland.
• If no relevant research results for Gansu Province can be found, relevant research results for other regions in China should be collected. ESV per unit area of ecosystem should be calculated, and then compared with the standard equivalent value. It can be converted into an average value equivalent factor of ecosystem service function by constructing a correction coefficient, as the basic equivalent of the ecosystem service function, which is used to determine the value equivalent of some ecosystem service functions, such as lakes, reservoirs, saline alkali land, and urban green space.
• There are great differences between the ecosystem service functions in Gansu Province and those of the entire country. Therefore, in this study, the value equivalence factor was localized and calibrated by calculating the ecosystem service function quantity per unit area, such as the biodiversity maintenance value of forest land, grassland, wetlands, and desert ecosystems, and the crop supply service of paddy fields and dry land.
• If there is no ecosystem service function value listed in directly corresponding documents in the secondary classification of ecosystem, and it is therefore difficult to calculate the ESV, refer to the equivalent factors listed by Xie et al. [ 3 ], as they were determined by experts’ experience. Transform them into the average value equivalent factors of the ecosystem service function in Gansu Province through use of the correction coefficient, as the basic equivalent of the ecosystem service function, such as local climate regulation and air quality regulation of the secondary types of desert and wetland ecosystems, and soil conservation services and water purification services of the second level of desert ecosystems.

Through the above six steps, the value of the main ecosystem types for a certain ecosystem service function per unit area in Gansu Province can be obtained, by referring to relevant literature or doing calculations, as shown in Table 1 .

https://doi.org/10.1371/journal.pone.0240272.t001

Correction index of value equivalent factor per unit area.

• 1. Crop supply correction index ( N)

The calculation of y is based on the following formula: y = (average yield per unit area of wheat/average yield per unit area of wheat) × sowing proportion of wheat + (average yield per unit area of corn/average yield per unit area of corn) × sowing proportion of corn + (average yield per unit area of potato/average yield per unit area of potato) × sowing proportion of potato + (average yield per unit area of oil/average yield per unit area of oil) × sowing proportion of oil.

The calculation method of Y is the same as that of y .

• 2. Fresh water supply correction index ( D)

• 3. Air quality regulation correction index (K)

• 4. Water purification correction index ( S )

• 5. Entertainment and aesthetic value correction index ( Y )

Regional difference adjustment index

• 1. Crop supply regulation index ( A1 )

According to Cheng [ 68 ], there are obvious spatial differences in grain production of cultivated land in Gansu Province. Previous studies [ 69 ] found that the correlation between cultivated land quality and land use is relatively high, with the correlation coefficient reaching 0.874. First, this was reflected in the cultivated land quality level (land use level) of each county as referred to in related studies [ 70 ] on the spatial distribution of land use level in 2015 in Gansu Province. Second, in terms of proportion of cultivated land use level to the total cultivated land area of each county in Gansu Province, 27% of the counties were classified as high-yield areas, and the rest were classified as low-yield areas. Finally, the average yield per unit area was calculated in high- and low-yield areas of each county, as well as in the province as a whole (refer to the calculation result of Eq ( 1 )). The average yield in the high- and low-yield areas was compared with the average yield per unit area in Gansu Province, and the regulation index of crop supply in high- and low-yield areas was obtained.

• 2. Livestock supply adjustment index ( A2)

Gansu Province is divided into pastoral, semi-pastoral, and agricultural areas because of the great difference in livestock supply capacity between pastoral and agricultural areas. Previous studies [ 71 ] have calculated the livestock carrying capacity in agricultural and pastoral areas of Gansu Province, and found that the livestock carrying capacity of agricultural areas was 0.85 times that of pastoral areas. The average of livestock carrying capacity in agricultural and pastoral areas was considered the livestock carrying capacity in the semi-pastoral areas.

• 3. Fresh water supply regulation index ( A3 )

The distance between the east and west, and the north and south is large in Gansu Province, and precipitation decreases from southeast to northwest due to the influence of water vapor and terrain. According to research [ 72 ], Gansu Province is divided into abundant water areas (Liupanshan–Longshan area, Longnan Mountain area, Gannan Plateau, and Qilian Mountain Area), water poor areas (Longdong, Longdong–Loess Plateau area, north of Lanzhou area), and dry areas (Hexi Corridor, Beishan Mountain area, and the desert area bounded by the Qilian Mountain foot). Using the water yield module in the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model, the average multi-year water yield of the water rich areas, water deficient areas, and dry areas was calculated for 2000–2015. The water yield per unit area in the water deficient areas was 0.68 times that in the water rich areas, and the water yield per unit area in the dry areas was 0.08 times that in the water rich areas.

• 4. Local climate regulation index (A4)

A large amount of observation data analysis shows that a change in surface vegetation may have a significant impact on local and regional climate by changing surface attributes such as surface albedo, roughness, and soil moisture [ 73 – 76 ]. The higher the area of vegetation NPP, the stronger the function of climate adjustment. Therefore, the value of NPP is used to measure regional differences in climate regulation. According to the spatial distribution characteristics of NPP and the boundaries of townships, Gansu Province is divided into high regulation area, middle regulation area, and low regulation area. The average value of NPP in the three regulation areas was calculated, and the ratio of NPP between the high regulation area and the middle adjustment area was taken as the adjustment index in the high adjustment area. The average value ratio of NPP between the low adjustment area and the median adjustment area was used as the adjustment index of the low value area.

• 5. Air quality regulation index ( A5 )

Generally, the better the air quality in a region, the greater the air quality regulation service function. According to the 2015 Environmental Quality Bulletin in Gansu Province, PM 10 and PM 2.5 were the main air pollutants. Only one of the 14 cities and prefectures has reached the secondary standard of ambient air quality, so the concentration of pollutants was taken as the index to measure the level of air quality regulation function. In this study, PM 10 and PM 2.5 concentration monitoring data were selected at 111 provincial monitoring points in Gansu Province, and through Kriging interpolation, the spatial distribution of PM 10 and PM 2.5 concentration was obtained in the whole province, which was divided into three zones: the area meeting the secondary quality standard was classified as the area with the best air quality, indicating that the area had the highest air quality regulation function; the other two areas were demarcated according to pollutant concentration. Vegetation coverage is closely related to air purification function. In this study, the ratio of the average vegetation coverage in the three regions was used as the air quality regulation index.

• 6. Groundwater recharge regulation index ( A6 )

The overexploitation of groundwater results in drainage of the aquifer, a decrease in groundwater level, the formation of a funnel, and land subsidence. Therefore, when rapid development exceeds the resource stock and environmental capacity, the value of the groundwater ecosystem will inevitably continue to appreciate. Different regions have different needs for groundwater recharge function, resulting in different values. To reflect the regional differences in groundwater recharge regulation function value, we used groundwater in heavily mined areas and areas that are not heavily mined to measure the regional differences in groundwater recharge function. Groundwater in heavily mined areas has a higher groundwater recharge value than in areas that are not heavily mined. According to the delimitation results of groundwater in heavily mined areas in Gansu Province [ 77 ], there are 46 heavily mined areas, involving 32 counties. The ratio of the actual and exploitable groundwater in the heavily mined area is used as the groundwater supply regulation index.

• 7. Soil conservation regulation index ( A7 )

Gansu Province is located at the junction of three plateaus, and its soil conservation functions vary substantially in different areas. In terms of soil and water loss in the key prevention and key governance areas, there is better vegetation, less soil and water loss, and stronger soil conservation functions in the key prevention areas, but low forest and grass coverage, a fragile ecological environment, and extensive soil and water loss in the key governance area. Therefore, the province is divided into two zones according to the range of the key prevention and governance areas. According to classification standards for soil erosion, the allowable amount of soil and water loss in the northwest Loess Plateau is 1,000 t/km 2 . Based on the ratio of the average erosion modulus and the allowable amount of soil and water loss in the two zones, the adjustment index of soil conservation was constructed.

• 8. Regulation index of windbreak and sand fixation ( A8 )

The Hexi Corridor in the north of Gansu Province, and the surrounding county of Qingyang City is located in the Gobi Desert area. Therefore, this area is classified as a service area for windbreak and sand fixation, whereas other areas are not considered to have that function.

• 9. Water purification regulation index ( A 9)

Xie et al. [ 78 ] highlighted that, as the pollution of rivers and lakes is becoming more serious, the water quality regulation function of rivers is becoming lower, and rivers and lakes almost become an area of accumulation of waste. Therefore, the water quality of the reach is closely related to its water purification function. If the water quality of this area is significantly better than that of other areas, the water purification function of this area will be of considerable importance. In this study, the water quality objectives of 236 monitoring sections of the Rivers were used to measure the water purification function of the region, and the water quality objectives of each county were quantified. If the water quality objectives of class I, or class II, or class II water and class III water reaches can be achieved simultaneously, the water purification function of the county is considered to be high. Additionally, the length proportion of the class II and class III water reaches and below are calculated. The length proportion of the class II water reach to the class III water reach and below is taken as the water purification regulation index in the high water purification area.

• 10. Entertainment aesthetics value adjustment index ( A10 )

Entertainment value refers to the value obtained by tourists when they are engaged in tourism activities in an ecotourism scenic spot, which is the sum of the value used by direct recreation and the non-use value possessed by resources; aesthetic value refers to the pleasure value brought by natural ecosystems to people’s aesthetic perception of the natural and cultural landscape, and the value of its own objective aesthetic attributes is referred to as the non-use value. If people cannot reach an area that can bring recreational and pleasure value to people, it is considered that the area cannot provide the service function or temporarily does not have the function. Based on this, we first determined that the core area and buffer area of a nature reserve cannot provide this service temporarily. Other natural protected places such as forest parks, geoparks, scenic areas, and wetland areas are key tourism areas, which provide the highest entertainment and aesthetic value. Second, the whole tourism county (and not only the key tourism areas) is generally regarded as the tourism area, with the remaining areas having the lowest entertainment and aesthetic value. The adjustment indexes of the different regions are assigned by expert judgment.

• 11. Biodiversity maintenance value regulation index ( a11 )

According to the conservation plan for biodiversity priority areas in Gansu Province, there are seven biodiversity priority areas in the province. This study considered that the areas located in the priority areas had the highest biodiversity maintenance value, followed by other areas, and the province was therefore divided into two areas. To determine the adjustment index of the different regions, we used the habitat quality module of the InVEST model to calculate the habitat quality index of the different regions [ 79 ], and determined the adjustment index by comparing the size of the habitat quality index of the two regions.

Through the above methods, the value equivalent factor table per unit area was established for Gansu Province ( Table 2 ).

https://doi.org/10.1371/journal.pone.0240272.t002

Value evaluation model based on regional differences

https://doi.org/10.1371/journal.pone.0240272.g003

Analysis of the change in ecosystem in Gansu Province

Desert is the largest ecosystem type in Gansu Province ( Table 3 ), followed by grassland, arable land, and forest. Both the glacier and wetland ecosystems account for a small part. Desert is mainly found in the north of Gansu; grasslands are mainly distributed in the Gannan Plateau in central and eastern Gansu; cultivated land is mainly distributed in the central area of Gansu and Hexi Corridor; and forests are mainly found in the Longnan, Ziwuling, and Qilian Mountains. In terms of changes in the ecosystem, the forest, grassland, and urban ecosystems have been increasing continuously in the past 15 y. The cultivated land ecosystem has been continuously decreasing. Although the wetland and glacier ecosystems have been increasing in the past 15 y, they have been decreasing over the longer term. The desert ecosystem has been increasing in general.

https://doi.org/10.1371/journal.pone.0240272.t003

Overall evaluation of ESV in Gansu Province

In general, ESV decreases from south to north, and from east to west in Gansu Province ( Fig 4 ), which is consistent with the spatial distribution of forest, grassland, and desert ecosystems. There are adjoining desert areas north of Gansu Province, the area with the lowest ESV. However, the ecological environment is relatively healthy in the south of Gansu Province, with high vegetation coverage and ESV. In the center-east of Gansu Province, where human activities are most frequent, inducing relatively high disturbance on the natural ecological environment, the ESV is relatively low.

https://doi.org/10.1371/journal.pone.0240272.g004

The value of local climate regulation and biodiversity maintenance ( Table 4 ) is much higher than that of other service functions, and constitutes the main contributor to ESV in Gansu Province. In terms of the change in each service function value, the value of soil conservation, windbreak and sand fixation, and biodiversity protection has been increasing continuously in the past 15 y, whereas the supply value of crops has been decreasing continuously. The supply value of fresh water, local climate regulation, air quality regulation, water purification function, groundwater supply, and entertainment and aesthetic value show a fluctuating change state and an overall decreasing trend.

https://doi.org/10.1371/journal.pone.0240272.t004

The value of the grassland and forest ecosystems is the highest, accounting for more than 75% of the total value ( Table 5 ), whereas the value of urban and glacial ecosystems is the lowest. In terms of change in each ecosystem type value, the value of forest and urban ecosystems is increasing, whereas the value of cultivated land ecosystem is decreasing. The value of grassland, wetland, and glacier ecosystems fluctuates, and the overall trend is decreasing. In contrast, the value of the desert ecosystem fluctuates, and the overall trend is increasing. Over the past 15 y, the total value of the various ecosystem services has increased by 3.43 billion yuan, and the increase in forest ecosystem value has been the highest, whereas the decrease in grassland ecosystem value has been the highest.

https://doi.org/10.1371/journal.pone.0240272.t005

Analysis of the spatiotemporal change in ESV in Gansu Province

Over the past 15 y, the townships with increased ESV are mainly distributed in the east and south of Gansu Province, and west of the Hexi Corridor. The townships which had a decrease in ESV are located in Qilian Mountain and Gannan Plateau ( Fig 5 ).

https://doi.org/10.1371/journal.pone.0240272.g005

Over the past 15 y, the number of townships with increased ESV has decreased. There were 959 townships with an increased ESV in 2000–2005, 758 townships in 2005–2010, and only 391 townships increased in value in 2010–2015. From 2000 to 2015, there were 818 townships with increased ESV.

From 2000 to 2005, townships with increased ESV were mainly distributed in the Qilian Mountain, and the eastern and southern parts of Gansu (Tianshui, Pingliang, Qingyang, and Longnan). From 2005 to 2010, the ESV of most townships decreased in the Gannan Plateau and Qilian Mountain, whereas the increased townships were mainly located in Tianshui, Longnan, and the western section of the Hexi Corridor. From 2010 to 2015, the ESV of most townships declined in Lanzhou, Baiyin, Dingxi, Gannan Plateau, and Hexi Corridor, and the townships where the value increased were concentrated in the north and south.

Advanced value evaluation model

In this study, ESV was evaluated by improving the value equivalent factor per unit area and constructing a regional differential value assessment model in Gansu Province. Different ecosystem types provide different ES types to humans. In the current research on ESV, scholars mostly refer to the classification of ecosystem types by Costanza et al. [ 5 ], which is limited to forest, grassland, farmland, wetland, desert, and river. Xie et al. [ 3 ] improved this method by accounting for the value of 14 types of ecosystem services in China, and more precisely reflected the differences between ecosystem types. However, this method was based on national scale, and did not meet the needs of practical research, namely a reduction of the research scale and refinement of the classification of ecosystems. Based on the actual ecological situation in Gansu Province, this study identified 7 types of primary ecosystems and 21 types of secondary ecosystems to cover the main ecosystem types in Gansu Province more comprehensively. This reflected the differences between the types of ecosystems, and highlighted the importance of ESV.

In different regions, the same ecosystem type provides different ES and their value to humans are quite different. Therefore, the value equivalent factor of Costanza et al. [ 5 ] and Xie et al. [ 3 ] has been improved by scholars by introducing factors that reflect regional differences, such as NPP, biomass, vegetation coverage, and soil erosion. However, these factors can only reflect regional differences in the main types of ES functions, which are mainly driven by natural factors. It is even more difficult to truly reflect differences in ecological service functions in regions with complex ecological environment characteristics and socioeconomic conditions, such as Gansu Province. In this study, first, the correction index of the value equivalent factor per unit area was constructed. We converted the equivalent factors on the national average level provided by Xie et al. [ 3 ] to an average level in Gansu Province, calculated the average level of some of the equivalent factors in Gansu Province, and then converted the equivalent factors in the average level in Gansu Province to a level with significant regional differences by constructing the regional difference adjustment index of each ES function type. In the process of regional difference conversion, the differences in ecological environment quality, resource endowment, and economic and social development of the different regions were fully considered, thereby more accurately reflecting the ecological well-being of residents in different regions, and the degree of damage to the local ecological environment and resources.

Errors in the value evaluation model

The accurate construction of the equivalent factor table is the core of the equivalent factor method. In the process of improving the equivalent factor table of Xie et al. [ 3 ], this study integrated evaluation results from the literature based on the physical quantity method in Gansu Province or other regions in China. This can avoid or reduce subjective conjecture, which is easily caused by empiricism from the past. The accuracy of the research results in the literature on different ES types affects the size of the equivalent factor in this study. Considering the lack of complete research results on the different ecosystems or ecological service functions in Gansu Province, the ecological service functions of some ecosystem types are investigated based on available research results from other regions in China. This has led to a certain amount of uncertainty in this study. Future research needs to quantitatively calculate the physical quantity of ecosystem types or ecological service functions that are not currently available in the literature, and then determine the equivalent factor to improve the results of this study.

Reliability of value evaluation models

ESV assessment has been studied extensively in other regions of China, whereas there are few related studies on ESV in Gansu Province. The existing research focuses on the value of a single ecosystem service on a provincial scale [ 29 , 34 , 81 ], and the calculation method of unit area value is the main method. Research on provincial integrated ESV is almost non-existent at present [ 83 ]. The value of forest ecosystem services was 747.70 billion yuan in this study. However, this study does not consider the difference in people’s willingness to pay, and their ability to pay, for ESV caused by social development. By including the willingness and ability to pay, the value of forest ecosystem services was 1,971.23 billion yuan in 2010, which is closer to the official release of service value of the forest ecosystem (2,007.97 billion yuan in 2011), and the service value of the forest ecosystem assessed by Wang et al. [ 27 ] (2,163.86 billion yuan in 2009) and Wang et al. [ 82 ] (1,802.37 billion yuan in 2008). There was, however, a big difference between the ESV evaluated in Gansu Province by Qi [ 83 ] and the ESV in this study. The value per unit area was only 98.57 billion yuan in 2010 [ 83 ] by using the value calculation method per unit area, resulting in a significantly smaller value.

Conclusions

Based on the characteristics of ecosystems in Gansu Province, this study developed a revised index based on an increase in some ecosystem equivalent factors, and revised the equivalent factors studied by Xie et al. [ 3 ] to form an equivalent factor table in line with ecosystem service valuation in Gansu Province specifically. Eleven regional difference adjustment indices to readjust the value of different service functions were then constructed. The regional difference assessment model constructed in this study distinguished the regional differences in similar ecosystem services to evaluate the ESV in Gansu Province more objectively. The main conclusions are as follows:

• The desert ecosystem type covers the largest area in Gansu Province, followed by grassland, arable land, and forest ecosystems, and the remaining ecosystems account for only a small part. Desert is mostly located in northern Gansu. Grasslands are mainly located in the Gannan Plateau, Longzhong, and Longdong. Cultivated land is mainly located in Longzhong and Hexi Corridor, and forests are mainly located in Longnan, Ziwuling, and the Qilian Mountains.
• From 2000 to 2015, the grassland ecosystem area increased the most, whereas the cultivated land ecosystem area decreased the most. Forest, grassland, and urban ecosystems in Gansu Province continue to increase. Cultivated land ecosystems continue to decrease. Although wetlands and glacial ecosystems have increased over the past 15 y, they have decreased over the long term. The number of desert ecosystems has increased.
• In 2015, the total ESV for Gansu Province reached 2,239.56 billion yuan, to which the forest and grassland ecosystems contributed the most. In terms of the value of each service function of the ecosystem, the local climate regulation and biodiversity maintenance functions are the main service functions in the province. Regarding the spatial distribution of service values, ESV gradually increases from northeast to southwest, and the areas with high ESV concentrations are Qilian and Longnan Mountains.
• From 2000 to 2015, ESV increased by 3.43 billion yuan in Gansu Province. The value of forest ecosystems increased the most, whereas the value of grassland ecosystems decreased the most, showing a trend of increasing first, then decreasing, and then slowly increasing again. The value of forest and urban ecosystems continues to increase, and the value of cultivated land ecosystems continues to decrease. From the spatial characteristics of ESV changes, areas with reduced values gradually move from central Gansu to the surrounding areas.

Supporting information

https://doi.org/10.1371/journal.pone.0240272.s001

Acknowledgments

We are also grateful for the comments and criticisms of an early version of this manuscript by our colleagues and the journal’s reviewers. Acknowledgement for the data support from "National Earth System Science Data Center, National Science & Technology Infrastructure of China. ( http://www.geodata.cn )".We would like to thank Editage ( www.editage.cn ) for English language editing.

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Ecosystem Services Assessment and Valuation

• Publications

Ecosystem services are the benefits that nature provides to human well-being: clean air and water, protection from natural disasters, fisheries, crop pollination and control of pests and disease, and outdoor places for recreation, solitude, and renewal. Ecosystem services underlie the functioning of our entire economy. They are neither worthless nor priceless, and by integrating the physical sciences, geography, and economics and other social sciences we can better understand how ecosystems provide value to people, and how to protect and enhance that value.

USGS scientists at GECSC use a variety of modeling and mapping approaches to improve our understanding of the value and distribution of ecosystem services. GECSC scientists pioneered the development of the Social Values for Ecosystem Services (SolVES) tool to map locations on the landscape that are valued by respondents to natural resource management surveys. Working with the USGS Powell Center for Synthesis and Analysis, we are estimating the values derived from migratory species to support new conservation funding mechanisms for valued species. We are also applying the Artificial Intelligence for Ecosystem Services (ARIES) tool to map and value ecosystem service flows at sites across the U.S. and globally. In collaboration with partners from a variety of Federal and State land management agencies, we are working to disseminate this information in support of more sustainable resource management and conservation planning.

Ecosystem Services-Related Research Underway at GECSC

• Social Values for Ecosystems Services (SolVES) :  SolVES is a tool developed by GECSC scientists to quantify and map perceived social values for ecosystem services (particularly cultural ecosystem services), calculated from a combination of spatial and non-spatial responses to public attitude and preferences surveys. We and our colleagues are applying SolVES in diverse locations to quantify and map cultural ecosystem services, develop guidelines for transferring mapped values, and pair cultural ecosystem services with biophysically modeled ecosystem services in support of natural resource management. The SolVES tool, user manual, sample data, tutorial, and publications are all available on the SolVES web site.
• Artificial Intelligence for Ecosystem Services (ARIES) :  The ARIES modeling framework seeks to advance ecosystem services science in two critical ways. First, ARIES fully accounts for the spatial dynamics of ecosystem services—the spatial mismatch between locations where ecosystem services are provided and where they are used, by quantifying spatial flows of ecosystem services. Second, ARIES is an Artificial Intelligence-equipped semantic modeling system that integrates data and models, enabling ecosystem service assessments to be conducted worldwide while accounting for locally important ecological and socioeconomic factors and using the most locally appropriate data in mapping. An overview of ARIES is available in the PLoS ONE article  A Methodology for Adaptable and Robust Ecosystem Services Assessment .
• Spatial Subsidies: Quantifying Linkages between Human and Natural Systems with Migratory Species :  Migratory species may provide more ecosystem goods and services to humans in certain parts of their range than others. These areas may or may not coincide with the locations on which the species is most dependent for its continued population viability. This situation can present significant policy challenges, as locations that most support a given species may be subsidizing the provision of services in other locations, often in different political jurisdictions. The ability to quantify these spatial subsidies could be used to develop economic incentives. Targeted payments for ecosystem services (PES) could provide economic incentives for conservation in areas where none presently exist, serving as a foundation for the cooperative, cross-jurisdictional management of migratory species.
• Technical Support to Other Department of the Interior Bureaus:  GECSC scientists provide technical support to other agencies looking to incorporate ecosystem services into natural resource planning and decision making. Working with the Bureau of Land Management (BLM),  we cataloged and tested ecosystem service tools to understand their readiness for bureau-wide use , and are continuing work to incorporate ecosystem services into a BLM master leasing plan. With the National Park Service (NPS),  we are similarly testing survey-based methods and biophysical models for ecosystem services for incorporation into the NPS planning process . Our work in mapping ecosystem services in the National Forests can support the ongoing effort by the USDA Forest Service to incorporate ecosystem services into planning,  per their 2012 planning rule . Finally GECSC scientists participate in  a multi-agency working group  to help build a consistent approach to using ecosystem services in federal resource management and planning.
• Linking ridge-to-reef ecosystem services in Hawaii:  GECSC scientists are working  to model and value the economic benefits provided by Hawaii's coral reefs, connecting changes in land management, rainfall, and ocean conditions under present-day and future scenarios . The work reflects how changes to the land surface impact runoff to coral reefs, affecting diverse values including recreation, coastal storm protection, and fisheries, which will eventually be expanded to provide decision support to diverse settings in the Pacific Islands.
• Integrated Resource Assessment:  GECSC scientists are developing and testing a framework to integrate USGS energy and mineral resource assessments with assessments of other biophysical resources to permit consideration of the interplay between management, landscape change, and environmental/economic costs and benefits. This framework endeavors to address the question of how landscape change is likely to impact a suite of resources and how those impacts can be limited via management activities and constraint designations. Many types of landscape change can be accommodated, such as development of an energy/mineral resource, fire, or urban growth.
• Economic accounting for ecosystem services:  Natural capital accounting— a tool being used in dozens of countries globally and by the private sector —tracks changes in ecosystem services and directly ties these changes to costs and benefits across different economic sectors. Yet, the compilation of a data, modeling, and valuation infrastructure to support natural capital accounting in the U.S. has not yet occurred. With funding from the USGS Powell Center and National Socio-Environmental Synthesis Center,  we are developing pilot natural capital accounts for the United States , increasing the delivery of clear and timely information about nature's value to society.

Below are publications associated with this project.

Tools for mapping ecosystem services

Defining ecosystem assets for natural capital accounting, toward an integrated understanding of perceived biodiversity values and environmental conditions in a national park, evaluating alternative methods for biophysical and cultural ecosystem services hotspot mapping in natural resource planning, a decision framework for identifying models to estimate forest ecosystem services gains from restoration, social-value maps for arapaho, roosevelt, medicine bow, routt, and white river national forests, colorado and wyoming, quasi-extinction risk and population targets for the eastern, migratory population of monarch butterflies ( danaus plexippus ), modeling the effects of urban expansion on natural capital stocks and ecosystem service flows: a case study in the puget sound, washington, usa, linking biophysical models and public preferences for ecosystem service assessments: a case study for the southern rocky mountains, replacement cost valuation of northern pintail ( anas acuta ) subsistence harvest in arctic and sub-arctic north america, validating a method for transferring social values of ecosystem services between public lands in the rocky mountain region, from theoretical to actual ecosystem services: mapping beneficiaries and spatial flows in ecosystem service assessments.

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• Published: 10 August 2024

Mapping biomimicry research to sustainable development goals

• Raghu Raman 1 ,
• Aswathy Sreenivasan 2 ,
• M. Suresh 2 &
• Prema Nedungadi 3  

Scientific Reports volume  14 , Article number:  18613 ( 2024 ) Cite this article

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• Environmental sciences
• Environmental social sciences

This study systematically evaluates biomimicry research within the context of sustainable development goals (SDGs) to discern the interdisciplinary interplay between biomimicry and SDGs. The alignment of biomimicry with key SDGs showcases its interdisciplinary nature and potential to offer solutions across the health, sustainability, and energy sectors. This study identified two primary thematic clusters. The first thematic cluster focused on health, partnership, and life on land (SDGs 3, 17, and 15), highlighting biomimicry's role in healthcare innovations, sustainable collaboration, and land management. This cluster demonstrates the potential of biomimicry to contribute to medical technologies, emphasizing the need for cross-sectoral partnerships and ecosystem preservation. The second thematic cluster revolves around clean water, energy, infrastructure, and marine life (SDGs 6, 7, 9, and 14), showcasing nature-inspired solutions for sustainable development challenges, including energy generation and water purification. The prominence of SDG 7 within this cluster indicates that biomimicry significantly contributes to sustainable energy practices. The analysis of thematic clusters further revealed the broad applicability of biomimicry and its role in enhancing sustainable energy access and promoting ecosystem conservation. Emerging research topics, such as metaheuristics, nanogenerators, exosomes, and bioprinting, indicate a dynamic field poised for significant advancements. By mapping the connections between biomimicry and SDGs, this study provides a comprehensive overview of the field's trajectory, emphasizing its importance in advancing global sustainability efforts.

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Introduction.

Biomimicry, which combines 'bio' (life) and 'mimicry' (imitation), uses nature's patterns to solve human problems, aligning with the SDGs by fostering innovations 1 . This discipline studies natural processes to inspire sustainable designs and promote responsible consumption and production 2 . Biomimicry emphasizes sustainability, ideation, and education in reconnecting with nature to achieve the SDGs 3 . Collaboration among designers, technologists, and business experts is vital for translating natural mechanisms into commercial solutions 4 . Biomimetics, which aims for radical innovations by replicating living systems, strives for breakthroughs in economic growth 5 . By promoting systemic change through the emulation of nature's regenerative processes, biomimicry's alignment with the SDGs could enhance sustainability efforts. Merging biomimicry insights with SDGs could exceed sustainability benchmarks.

Integrating biomimicry with sustainable development goals (SDGs) is crucial for addressing global challenges. The SDGs offer a blueprint for global well-being and environmental stewardship by 2030 6 . They aim to protect the environment and foster social and economic development. Biomimicry provides innovative approaches to these objectives, drawing from natural strategies. While SDGs offer clear targets, biomimicry complements these by providing a unique lens for solutions 7 . The investigation of biomimicry in conjunction with the SDGs is based on the understanding that the development of biologically inspired materials, structures, and systems offers a novel and sustainable solution to design problems, particularly in the built environment 8 . By mimicking nature's answers to complicated challenges, biomimicry produces creative, clever, long-lasting, and environmentally responsible ideas.

The SDGs outline a comprehensive sustainability agenda targeting social equity, environmental conservation, and poverty alleviation 9 . The use of biomimicry in research can lead to the development of solutions that mimic natural efficiency 10 , revolutionizing industries with resource-efficient technologies and enhancing sustainability. This synergy could lead to environmentally friendly products, improved energy solutions, and effective waste management systems. Integrating biomimicry into industry and education promotes environmental stewardship and ecological appreciation 11 . Marrying biomimicry research with SDGs has accelerated progress toward sustainable development.

Biomimicry can provide insightful and useful solutions consistent with sustainability ideals by imitating the adaptability and efficiency observed in biological systems 12 . The built environment's use of biomimicry has a greater sustainable impact when circular design features are included 13 . Reusing materials, cutting waste, and designing systems that work with natural cycles are all stressed in a circular design. Combining biomimicry and circular design promotes social inclusion, environmental resilience, resourcefulness, and compassionate governance, all of which lead to peaceful coexistence with the environment. This all-encompassing strategy demonstrates a dedication to tackling the larger social and environmental concerns that the SDGs represent and design challenges 14 . Complementing these studies, Wamane 7 examined the intersection of biomimicry, the environmental, social, and governance (ESG) framework, and circular economy principles, advocating for an economic paradigm shift toward sustainability.

A key aspect of realizing the impact of biomimicry on SDGs is the successful translation and commercialization of biomimicry discoveries. This involves overcoming barriers such as skill gaps, the engineering mindset, commercial acumen, and funding. Insights from the "The State of Nature-Inspired-Innovation in the UK" report provide a comprehensive analysis of these challenges and potential strategies to address them, underscoring the importance of integrating commercial perspectives into biomimicry research.

This research employs bibliometric techniques to assess the integration and coherence within circular economy policy-making, emphasizing the potential for a synergistic relationship between environmental stewardship, economic growth, and social equity to foster a sustainable future.

In addressing the notable gap in comprehensive research concerning the contribution of biomimicry solutions to specific SDGs, this study offers significant insights into the interdisciplinary applications of biomimicry and its potential to advance global sustainability efforts. Our investigation aims to bridge this research gap through a systematic analysis, resulting in the formulation of the following research questions:

RQ1: How does an interdisciplinary analysis of biomimicry research align with and contribute to advancing specific SDGs?

RQ2: What emerging topics within biomimicry research are gaining prominence, and how do they relate to the SDGs?

RQ3 : What are the barriers to the translation and commercialization of biomimicry innovations, and how can these barriers be overcome to enhance their impact on SDGs?

RQ4: Based on the identified gaps in research and the potential for interdisciplinary collaboration, what innovative areas within biomimicry can be further explored to address underrepresented SDGs?

The remainder of this paper is arranged as follows. Section " Literature review " focuses on the literature background of biomimicry, followed by methods (section " Methods ") and results and discussion, including emerging research topics (section " Results and discussion "). Section " Conclusion " concludes with recommendations and limitations.

Literature review

The potential of biomimicry solutions for sustainability has long been recognized, yet there is a notable lack of comprehensive studies that explore how biomimicry can address specific sustainable development goals (SDGs) (Table 1 ). This research aims to fill this gap by investigating relevant themes and building upon the literature in this field.

Biomimicry, with its roots tracing back to approximately 500 BC, began with Greek philosophers who developed classical concepts of beauty and drew inspiration from natural organisms for balanced design 15 . This foundational idea of looking to nature for design principles continued through history, as exemplified by Leonardo Da Vinci's creation of a flying machine inspired by birds in 1482. This early instance of biomimicry influenced subsequent advancements, including the Wright brothers' development of the airplane in 1948 12 , 15 . The term "bionics," coined in 1958 to describe "the science of natural systems or their analogs," evolved into "biomimicry" by 1982. Janine Benyus's 1997 book, “Biomimicry: Innovation Inspired by Nature,” and the founding of the Biomimicry Institute (Biomimicry 16 ) were pivotal, positioning nature as a guide and model for sustainable design. Benyus’s work underscores the potential of biomimicry in tackling contemporary environmental challenges such as climate change and ecosystem degradation 12 , 17 .

In recent years, the call for more targeted research in biomimicry has grown, particularly in terms of architecture and energy use. Meena et al. 18 and Varshabi et al. 19 highlighted the need for biomimicry to address energy efficiency in building design, stressing the potential of nature-inspired solutions to reduce energy consumption and enhance sustainability. This perspective aligns with that of Perricone et al. 20 , who explored the differences between artificial and natural systems, noting that biomimetic designs, which mimic the principles of organism construction, can significantly improve resource utilization and ecosystem restoration. Aggarwal and Verma 21 contributed to this discourse by mapping the evolution and applications of biomimicry through scientometric analysis, revealing the growing significance of nature-inspired optimization methodologies, especially in clustering techniques. Their work suggested that these methodologies not only provide innovative solutions but also reflect a deeper integration of biomimetic principles in technological advancements. Building on this, Pinzón and Austin 22 emphasized the infancy of biomimicry in the context of renewable energy, advocating for more research to explore how nature can inspire new energy solutions. Their work connects with that of Carniel et al. 23 , who introduced a natural language processing (NLP) technique to identify research themes in biomimicry across disciplines, facilitating a holistic understanding of current trends and future directions.

To further illustrate the practical applications of biomimicry, Nasser et al. 24 presented the Harmony Search Algorithm (HSA), a nature-inspired optimization technique. Their bibliometric analysis demonstrated the algorithm's effectiveness in reducing energy and resource consumption, highlighting the practical benefits of biomimicry in technological innovation. Rusu et al. 25 expanded on these themes by documenting significant advancements in soft robotics, showing how biomimicry influences design principles and applications in this rapidly evolving field. Their findings underscore the diverse applications of biomimetic principles, from robotics to building design. Shashwat et al. 26 emphasized the role of bioinspired solutions in enhancing energy efficiency within the built environment, promoting the use of high solar reflectance surfaces that mimic natural materials. This perspective is in line with that of Pires et al. 27 , who evaluated the application of biomimicry in dental restorative materials and identified a need for more clinical studies to realize the full potential of biomimetic innovations in healthcare. Liu et al. 28 explored the application of nature-inspired design principles in software-defined networks, demonstrating how biomimetic algorithms can optimize resource and energy utilization in complex systems. This study builds on the broader narrative of biomimicry's potential to transform various sectors by offering efficient, sustainable solutions. Finally, Hinkelman et al. 29 synthesized these insights by discussing the transdisciplinary applications of ecosystem biomimicry, which supports sustainable development goals by integrating biomimetic principles across engineering and environmental disciplines. This comprehensive approach underscores the transformative potential of biomimicry, suggesting that continued interdisciplinary research and innovation are crucial for addressing global sustainability challenges effectively.

PRISMA framework

This study utilizes the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework to structure its analysis, following the established five-step protocol: formulating research questions, defining a search strategy, executing a literature search, screening identified literature, and analyzing the findings (Page et al., 2021). The application of the PRISMA guidelines across various research domains, including the SDGs, is well documented 30 .

To ensure a comprehensive search, we searched the Scopus database, a widely utilized resource for bibliometric studies 31 (Donthu et al. 82 ), which led to the discovery of 46,141 publications from 2013 to 2023. This period marked significant research activity following the introduction of the SDGs at the Rio + 20 summit in 2012. Publications were identified using the following terms in the title and abstract: “ (biomimic* OR biomimetic* OR bioinspired OR bioinsp* OR bionic* OR nature-inspired OR "biologically inspired" OR bioinspiration OR biomimesis OR biognosis).”

During the screening phase, publications lacking complete author details were reviewed, narrowing the field to 46,083 publications for further analysis. The eligibility phase utilized proprietary algorithms to map publications to the 17 SDGs, informed by initiatives such as the University of Auckland (Auckland’s SDG mapping 32 ) and Elsevier's SDG Mapping Initiatives (Elsevier's SDG Mapping 33 ). The selection of the Elsevier SDG Mapping Initiative for this study was based on its seamless integration with Scopus, facilitating the use of predefined search queries for each SDG and employing a machine learning model that has been refined through expert review. This approach has been utilized in various studies to analyze research trends within emerging fields. For example, the exploration of green hydrogen was detailed by Raman et al. 34 , while investigations into Fake News and the Dark Web were conducted by Raman et al. 35 , 36 , 37 and Rama et al. 38 , respectively. These examples demonstrate the efficacy of SDG mapping in elucidating how research outputs align with and contribute to sustainable development goals in these emerging domains. This phase identified 13,287 publications as mapped to SDGs. In the inclusion phase, stringent criteria further filtered the publications to English-language journals and review articles, culminating in 13,271 publications deemed suitable for in-depth analysis. This process ensures a comprehensive and high-quality dataset for the study, reflecting the robust and systematic approach afforded by the PRISMA framework in evaluating literature relevant to SDGs.

Our keyword search strategy, while comprehensive, may capture papers that do not genuinely contribute to the field. To mitigate this, we employed manual verification. After the automated search, the authors conducted a manual review of a subset of the final set of identified papers to assess their relevance and authenticity in the context of biomimicry. The subset was based on 20 highly cited papers from each year. We believe that papers that are frequently cited within the community are more likely to be accurately classified. The authors mainly reviewed the introduction, methodology, and results sections to confirm the relevance and authenticity of the papers. However, we acknowledge that these steps may not fully eliminate the inclusion of irrelevant papers, which could skew the results of our meta-analysis.

SDG framework

The examination of sustainable development goals (SDGs) reveals their interconnected nature, where the achievement of one goal often supports progress in others. Studies by Le Blanc (2015) and Allison et al. (2016) have mapped out the complex web of relationships among the SDGs, identifying both strong and subtle linkages across different objectives. To visualize these connections, we employed a cocitation mapping approach using VOSviewer 39 , which allows us to depict the semantic relationships between SDGs through their cocitation rates in scholarly works. This approach generates a visual map where each SDG is represented as a node, with the node size reflecting the goal's research prominence and the thickness of the lines between nodes indicating the frequency of cocitations among the goals. This visual representation reveals the SDGs as an intricate but unified framework, emphasizing the collaborative nature of global sustainability initiatives.

Topic prominence percentile

The Scopus prominence percentile is a crucial metric indicating the visibility and impact of emerging research topics within the scientific community. High-ranking topics in this percentile are rapidly gaining attention, highlighting emerging trends and areas poised for significant advancements. This tool enables researchers and policymakers to identify and focus on innovative topics, ensuring that their efforts align with the forefront of scientific development 35 , 36 , 37 . Topics above the 99.9th percentile were used in this study.

Results and discussion

Rq1: sdg framework and interdisciplinary research (rq4).

This study evaluates biomimicry research through the framework of SDGs. A cocitation SDG map shows two clusters and provides insights into the interplay between biomimicry themes and SDGs, highlighting the cross-disciplinary nature of this research (Fig.  1 ). The blue box hidden behind the “3 – Good Health and Well-being” and “7 – Affordable and Clean Energy” is “11 – Sustainable cities and Communities”. The blue box hidden behind “15 – Life on Land” is “16 – Peace, Justice and Strong institutions”.

Interdisciplinary SDG network of biomimicry research.

Cluster 1 (Red): Biomimetic innovations for health, partnership, and life on land

This cluster comprises a diverse array of research articles that explore the application of biomimicry across various SDGs 3 (health), 17 (partnership), and 15 (land). The papers in this cluster delve into innovative biomimetic ideas, each contributing uniquely to the intersection of sustainable development and biological inspiration. SDG 3, emphasizing good health and well-being for all, is significantly represented, indicating a global effort to leverage biomimicry for advancements in healthcare, such as new medication delivery systems and medical technologies. Similarly, the frequent citations of SDG 17 underscore the vital role of partnerships in achieving sustainable growth, especially where bioinspired solutions require interdisciplinary collaboration to address complex challenges. Finally, the prominence of 15 SDG citations reflects a commitment to preserving terrestrial ecosystems, where biomimicry is increasingly applied in land management, demonstrating nature's adaptability and resilience as a model for sustainable practices. Table 2 lists the top 5 relevant papers from Cluster 1, further illustrating the multifaceted application of biomimicry in addressing these SDGs.

A unique binary variant of the gray wolf optimization (GWO) technique, designed especially for feature selection in classification tasks, was presented by Emary et al. 40 . GWO is a method inspired by the social hierarchy and hunting behavior of gray wolves to find the best solutions to complex problems. This bioinspired optimization technique was used to optimize SDG15, which also highlights its ecological benefits. The results of the study highlight the effectiveness of binary gray wolf optimization in identifying the feature space for ideal pairings and promoting environmental sustainability and biodiversity. Lin et al. 41 focused on SDG 3 by examining catalytically active nanomaterials as potential candidates for artificial enzymes. While acknowledging the limits of naturally occurring enzymes, this study explores how nanobiotechnology can address problems in the food, pharmaceutical, and agrochemical sectors.

The investigation of enzymatic nanomaterials aligns with health-related objectives, highlighting the potential for major improvements in human health. Parodi et al. 42 used biomimetic leukocyte membranes to functionalize synthetic nanoparticles, extending biomimicry into the biomedical domain. To meet SDG 3, this research presents "leukolike vectors," which are nanoporous silicon particles that can communicate with cells, evade the immune system, and deliver specific payloads. In line with the SDGs about health, this study emphasizes the possible uses of biomimetic structures in cancer detection and treatments. A novel strategy for biological photothermal nanodot-based anticancer therapy utilizing peptide‒porphyrin conjugate self-assembly was presented by Zou et al. 43 . For therapeutic reasons, efficient light-to-heat conversion can be achieved by imitating the structure of biological structures. By providing a unique biomimetic approach to cancer treatment and demonstrating the potential of self-assembling biomaterials in biomedical applications, this research advances SDG 3. Finally, Wang et al. 44 presented Monarch butterfly optimization (MBO), which is a bioinspired algorithm that mimics the migration patterns of monarch butterflies to solve optimization problems effectively. This method presents a novel approach to optimization, mimicking the migration of monarch butterflies, aligning with SDG 9. Comparative analyses highlight MBO's exceptional performance and demonstrate its capacity to address intricate issues about business and innovation, supporting objectives for long-term collaboration and sector expansion.

The publications in Cluster 1 show a wide range of biomimetic developments, from ecological optimization to new optimization techniques and biomedical applications. These varied contributions highlight how biomimicry can advance sustainable development in health, symbiosis, and terrestrial life.

Cluster 2 (green): Nature-inspired solutions for clean water, energy, and infrastructure

Cluster 2, which focuses on the innovative application of biomimicry in sustainable development, represents a range of research that aligns with SDGs 6 (sanitation), 7 (energy), 9 (infrastructure), and 14 (water). This cluster is characterized by studies that draw inspiration from natural processes and structures to offer creative solutions to sustainability-related challenges. The papers in this cluster, detailed in Table 3 , demonstrate how biomimicry can address key global concerns in a varied and compelling manner.

Within this cluster, the high citation counts for SDG 7 underscore the significance of accessible clean energy, a domain where biomimicry contributes innovative energy generation and storage solutions inspired by natural processes. This aligns with the growing emphasis on sustainable energy practices. The prominence of SDG 9 citations further highlights the global focus on innovation and sustainable industry, where biomimicry's role in developing nature-inspired designs is crucial for building robust systems and resilient infrastructure. Furthermore, the substantial citations for SDG 6 reflect a dedicated effort toward ensuring access to clean water and sanitation for all. In this regard, biomimicry principles are being applied in water purification technologies, illustrating how sustainable solutions modeled after natural processes can effectively meet clean water objectives.

The study by Sydney Gladman et al. (2016), which presented the idea of shape-morphing systems inspired by nastic plant motions, is one notable addition to this cluster. This discovery creates new opportunities for tissue engineering, autonomous robotics, and smart textile applications by encoding composite hydrogel designs that exhibit anisotropic swelling behavior. The emphasis of SDG 9 on promoting industry, innovation, and infrastructure aligns with this biomimetic strategy. SDGs 7 and 13 are addressed in the study of Li et al. 45 , which is about engineering heterogeneous semiconductors for solar water splitting. This work contributes to the goals of inexpensive, clean energy and climate action by investigating methods such as band structure engineering and bionic engineering to increase the efficiency of solar water splitting. Li et al. 46 conducted a thorough study highlighting the importance of catalysts for the selective photoreduction of CO2 into solar fuels. This review offers valuable insights into the use of semiconductor catalysts for selective photocatalytic CO2 reduction. Our work advances sustainable energy solutions by investigating biomimetic, metal-based, and metal-free cocatalysts and contributes to SDGs 7 and 13. Wang et al. 47 address the critical problem of water pollution. Creating materials with superlyophilic and superlyophobic qualities offers a creative method for effectively separating water and oil. This contributes to the goals of clean water, industry, innovation, and life below the water. It also correlates with SDGs 6, 9, and 14. Singh et al. 48 also explored the 'green' synthesis of metals and their oxide nanoparticles for environmental remediation, which furthers SDG 9. This review demonstrates the environmentally benign and sustainable features of green synthesis and its potential to lessen the environmental impact of conventional synthesis methods.

Cluster 2 provides nature-inspired solutions for clean water, renewable energy, and sustainable infrastructure, demonstrating the scope and importance of biomimicry. The varied applications discussed in these papers help overcome difficult problems and advance sustainable development in line with several SDGs.

RQ2: Emerging research topics

Temporal evolution of emerging topics.

Figure  2 displays the publication counts for various emerging topics from 2013 to 2022, indicating growth trends over the years. For 'Metaheuristics', there is a notable increase in publications peaking in approximately 2020, suggesting a surge in interest. 'Strain sensor' research steadily increased, reaching its highest publication frequency toward the end of the period, which is indicative of growing relevance in the field. 'Bioprinting' sharply increased over the next decade, subsequently maintaining high interest, which highlights its sustained innovation. In contrast, 'Actuators' showed fluctuating publication counts, with a recent upward trend. 'Cancer' research, while historically a major topic, displayed a spike in publications in approximately 2018, possibly reflecting a breakthrough or increased research funding. 'Myeloperoxidase' has a smaller presence in the literature, with a modest peak in 2019. The number of 'Water '-related publications remains relatively low but shows a slight increase, suggesting a gradual but increasing recognition of its importance. Research on exosomes has significantly advanced, particularly since 2018, signifying a greater area of focus. 'Mechanical' topic publications have moderate fluctuations without a clear trend, indicating steady research interest. 'Micromotors' experienced an initial publication surge, followed by a decline and then a recent resurgence, possibly due to new technological applications. 'Nanogenerators' have shown a dramatic increase in interest, particularly in recent years, while 'Hydrogel' publications have varied, with a recent decline, which may point toward a shift in research focus or maturity of the topic.

Evolution of emerging topics according to publications (y-axis denotes the number of publications; x-axis denotes the year of publication).

Figure  3 presents the distribution of various research topics based on their prominence percentile and total number of publications. Topics above the 99.9th percentile and to the right of the vertical threshold line represent the most emergent and prolific topics of study. Next, we examine the topics within each of the four quadrants, focusing on how each topic has developed over the years in relation to SDGs and the key phrases associated with each topic.

Distribution of research topics based on prominence percentile and total number of publications.

Next, we examine each research topic in four quadrants, assessing their evolution concerning SDGs. We also analyze the keyphrase cloud to identify which keyphrases are most relevant (indicated by their font size) and whether they are growing or not. In the key phrase cloud, green indicates an increasing relevance of the key phrase, grey signifies that its relevance remains constant, and blue represents a declining relevance of the key phrase.

Niche biomimetic applications

These are topics with a lower number of publications and prominence percentiles, indicating specialized or emerging areas of research that are not yet widely recognized or pursued (Quadrant 1—bottom left).

Myeloperoxidase; colorimetric; chromogenic compounds

The inclusion of myeloperoxidase indicates that inflammation and the immune system are the main research topics. The focus on chromogenic and colorimetric molecules suggests a relationship to analytical techniques for identifying biological materials. The evolution of the research is depicted in Fig.  4 a shows an evolving emphasis on various sustainable development goals (SDGs) over time. The research trajectory, initially rooted in SDG 3 (Good Health and Well-being), has progressively branched out to encompass SDG 7 (Affordable and Clean Energy) and SDG 6 (Clean Water and Sanitation), reflecting an expanding scope of inquiry within the forestry sciences. More recently, the focus has transitioned toward SDG 15 (Life on Land), indicating an increased recognition of the interconnectedness between forest ecosystems and broader environmental and sustainability goals. This trend underscores the growing complexity and multidisciplinary nature of forestry research, highlighting the need to address comprehensive ecological concerns along with human well-being and sustainable development.

Evolution of research ( a ) and key phrases ( b ).

The word cloud in Fig.  4 b highlights key phrases such as 'Biocompatible', 'Actuator', and 'Self-healing Hydrogel', reflecting a focus on advanced materials, while terms such as 'Elastic Modulus' and 'Polymeric Networks' suggest an emphasis on the structural properties essential for creating innovative diagnostic and environmental sensing tools. Such developments are pertinent to health monitoring and water purification, resonating with SDG 3 (Good Health and Well-being) and SDG 6 (Clean Water and Sanitation). The prominence of 'Self-healing' and 'Bioinspired' indicates a shift toward materials that emulate natural processes for durability and longevity, supporting sustainable industry practices aligned with SDG 9 (Industry, Innovation, and Infrastructure) and SDG 12 (Responsible Consumption and Production), contributing to the overarching aim of sustainable development.

Next, we analyzed the top 3 cited publications. Catalytically active nanomaterials, or nanozymes, are exciting candidates for artificial enzymes, according to Lin et al. 41 . The authors explore the structural features and biomimetics applications of these enzymes, classifying them as metal-, carbon-, and metal oxide-based nanomaterials. This study emphasizes the benefits of enzymes over natural enzymes, including their high stability, variable catalytic activity, and controlled production. Wang et al. 49 developed biomimetic nanoflowers made from nanozymes to cause intracellular oxidative damage in hypoxic malignancies. Under both normoxic and hypoxic conditions, the nanoflowers demonstrated catalytic efficiency. By overcoming the constraints of existing systems that depend on oxygen availability or external stimuli, this novel technique represents a viable treatment option for malignant neoplasms. Gao et al. 50 investigated the use of a dual inorganic nanozyme-catalyzed cascade reaction as a biomimetic approach for nanocatalytic tumor therapy. This approach produces a high level of therapeutic efficacy by cascading catalytic events inside the tumor microenvironment. This study highlights the potential of inorganic nanozymes for achieving high therapeutic efficacy and outstanding biosafety, which adds to the growing interest in nanocatalytic tumor therapy.

Water; hydrophobicity; aerogels

With an emphasis on hydrophobicity, aerogel use, and water-related features, this topic relates to materials science and indicates interest in cutting-edge materials with unique qualities. From Fig.  5 a, we can see that, initially, the focus was directed toward SDG 6 (Clean Water and Sanitation), which is intrinsically related to the research theme, as biomimetic approaches are leveraged to develop innovative water purification and management solutions. As the research progressed, the scope expanded to intersect with SDG 14 (Life Below Water) and SDG 7 (Affordable and Clean Energy), signifying a broadened impact of biomimetic innovations in marine ecosystem conservation and energy-efficient materials. The gradual involvement with SDG 9 (industry, innovation, and infrastructure) and SDG 13 (climate action) indicates the interdisciplinary reach of this research, which aims to influence industrial practices and climate change mitigation strategies.

The word cloud in Fig.  5 b reinforces this narrative by showcasing key phrases such as 'Hydrophobic', 'Bioinspired', 'Emulsion', and 'Oil Pollution', which reflect the emphasis on developing materials and technologies that mimic natural water repellency and separation processes. 'Aerogel' and 'polydopamine', along with 'Underwater' and 'Biomimetic Cleaning', suggest a strong focus on creating lightweight, efficient materials capable of self-cleaning and oil spill remediation. These keywords encapsulate the essence of the research theme, demonstrating a clear alignment with the targeted SDGs and the overall aim of sustainable development through biomimicry.

Three highly referenced works that have made substantial contributions to the field of biomimetic materials for oil/water separation are included in the table. The development of superlyophilic and superlyophobic materials for effective oil/water separation was examined by Wang et al. 47 . This review highlights the applications of these materials in separating different oil-and-water combinations by classifying them according to their surface wettability qualities. The excellent efficiency, selectivity, and recyclability of the materials—which present a viable treatment option for industrial oily wastewater and oil spills—are highlighted in the paper. Su et al. 51 explored the evolution of super wettability systems. The studies included superhydrophobicity, superoleophobicity, and undersea counterparts, among other extreme wettabilities. The kinetics, material structures, and wetting conditions related to obtaining superwettability are covered in the article. This demonstrates the wide range of uses for these materials in chemistry and materials science, including self-cleaning fabrics and systems for separating oil and water. Zhang et al. 52 presented a bioinspired multifunctional foam with self-cleaning and oil/water separation capabilities. To construct a polyurethane foam with superhydrophobicity and superoleophobicity, this study used porous biomaterials and superhydrophobic self-cleaning lotus leaves. Foam works well for separating oil from water because of its slight weight and ability to float on water. It also shows exceptional resistance to corrosive liquids. According to the article, multifunctional foams for large-scale oil spill cleaning might be designed using a low-cost fabrication technology that could be widely adopted.

Growing interest in bioinspired healthcare

These topics have a higher prominence percentile but a lower number of publications, suggesting growing interest and importance in the field despite a smaller body of research (Quadrant 2—top left).

Exosomes; extracellular vesicles; MicroRNAs

Exosomes and extracellular vesicles are essential for intercellular communication, and reference to microRNAs implies a focus on genetic regulation. The evolution of this topic reflects an increasing alignment with specific sustainable development goals (SDGs) over the years. The initial research focused on SDG 3 (good health and well-being) has expanded to encompass SDG 9 (industry, innovation, and infrastructure) and SDG 6 (clean water and sanitation), showcasing the multifaceted impact of biomimetic research in healthcare (Fig.  6 a). The research trajectory into SDG 9 and SDG 6 suggests broader application of bioinspired technologies beyond healthcare, potentially influencing sustainable industrial processes and water treatment technologies, respectively.

The word cloud (Fig.  6 b) underscores the central role of 'Extracellular Vesicles' and 'Exosomes' as platforms for 'Targeted Drug Delivery' and 'Nanocarrier' systems, which are key innovations in medical biotechnology. The prominence of terms such as 'Bioinspired', 'Biomimetic', 'Liposome', and 'Gold Nanoparticle' illustrates the inspiration drawn from biological systems for developing advanced materials and delivery mechanisms. These key phrases indicate significant advancements in 'Controlled Drug Delivery Systems', 'Cancer Chemotherapy', and 'Molecular Imaging', which have contributed to improved diagnostics and treatment options, consistent with the objectives of SDG 3.

The work by Jang et al. 53 , which introduced bioinspired exosome-mimetic nanovesicles for improved drug delivery to tumor tissues, is one of the most cited articles. These nanovesicles, which resemble exosomes but have higher creation yields, target cells and slow the growth of tumors in a promising way. Yong et al.'s 54 work presented an effective drug carrier for targeted cancer chemotherapy, focusing on biocompatible tumor cell-exocytosed exosome-biomimetic porous silicon nanoparticles. A paper by Cheng et al. 55 discussed the difficulties in delivering proteins intracellularly. This study suggested a biomimetic nanoparticle platform that uses extracellular vesicle membranes and metal–organic frameworks. These highly cited studies highlight the importance of biomimetic techniques in improving drug delivery systems for improved therapeutic interventions.

Nanogenerators; piezoelectric; energy harvesting

This topic advises concentrating on technology for energy harvesting, especially for those that use piezoelectric materials and nanogenerators. We see a rising focus on medical applications of biomimetics, from diagnostics to energy harvesting mimicking biological systems.

The evolution of this research topic reflects a broader contribution to the SDGs by not only addressing healthcare needs but also by promoting sustainable energy practices and supporting resilient infrastructure through biomimetic innovation (Fig.  7 a). Initially, the emphasis on SDG 3 (Good Health and Well-being) suggested the early application of biomimetic principles in healthcare, particularly in medical devices and diagnostics leveraging piezoelectric effects. Over time, the transition toward SDG 7 (Affordable and Clean Energy) and SDG 9 (Industry, Innovation, and Infrastructure) indicates an expansion of bioinspired technologies into sustainable energy solutions and industrial applications. Nanogenerators and energy harvesting techniques draw inspiration from biological processes and structures, aiming to optimize energy efficiency and contribute to clean energy initiatives.

The word cloud in Fig.  7 b emphasizes key phrases such as 'Piezoelectric', 'Energy Harvesting', 'Tactile Sensor', 'Triboelectricity', and 'Nanogenerators', highlighting the core technologies that are being developed. These terms, along with 'Bioinspired', 'Wearable Electronic Devices', and 'Energy Conversion Efficiency', illustrate the convergence of natural principles with advanced material science to create innovative solutions for energy generation and sensor technology.

Yang et al.'s 56 study in Advanced Materials presented the first triboelectrification-based bionic membrane sensor. Wearable medical monitoring and biometric authentication systems will find new uses for this sensor since it allows self-powered physiological and behavioral measurements, such as noninvasive human health evaluation, anti-interference throat voice recording, and multimodal biometric authentication. A thorough analysis of the state-of-the-art in piezoelectric energy harvesting was presented by Sezer and Koç 57 . This article addresses the fundamentals, components, and uses of piezoelectric generators, highlighting their development, drawbacks, and prospects. It also predicts a time when piezoelectric technology will power many electronics. The 2021 paper by Zhao et al. 58 examines the use of cellulose-based materials in flexible electronics. This section describes the benefits of these materials and the latest developments in intelligent electronic device creation, including biomimetic electronic skins, optoelectronics, sensors, and optoelectronic devices. This review sheds light on the possible drawbacks and opportunities for wearable technology and bioelectronic systems based on cellulose.

Leading edge of biomimetic sensing and electronics

This quadrant represents topics with both a high number of publications and a prominence percentile, indicating well-established and influential research areas (Quadrant 3—top right).

Strain sensor; flexible electronics; sensor

Figure  8 a highlights the progress of research on bioinspired innovations, particularly in the development of strain sensors and flexible electronics for adaptive sensing technologies. Initially, concentrated on health applications aligned with SDG 3 (Good Health and Well-being), the focus has expanded. The integration of SDG 9 (Industry, Innovation, and Infrastructure) indicates a shift toward industrial applications, while the incorporation of SDG 7 (Affordable and Clean Energy) suggests a commitment to energy-efficient solutions. Additionally, the mention of SDG 11 (Sustainable Cities and Communities) and SDG 12 (Responsible Consumption and Production) reflects the broadening scope to include urban sustainability and eco-friendly manufacturing practices.

Figure  8 b provides insight into the key phrases associated with this research topic, highlighting terms such as 'Bioinspired', 'Self-healing', 'Wearable Electronic Devices', 'Flexible Electronics', and 'Pressure Sensor'. These key phrases speak to the innovative approaches for creating sensors and electronics that are not only inspired by biological systems but also capable of seamlessly integrating human activity and environmental needs. The mention of 'Wearable Sensors' and 'Tactile Sensor' indicates a focus on user interaction and sensitivity, which is crucial for medical applications and smart infrastructure.

The top three articles with the most citations represent the cutting edge of this topic’s study. Chortos et al. 59 investigated how skin characteristics can be replicated for medicinal and prosthetic uses. Kim et al. 60 focused on creating ultrathin silicon nanoribbon sensors for smart prosthetic skin, opening up new possibilities for bionic systems with many sensors. A bioinspired microhairy sensor for ultraconformability on nonflat surfaces was introduced in Pang et al.'s 61 article, which significantly improved signal-to-noise ratios for accurate physiological measurements.

Cancer; photoacoustics; theranostic nanomedicine

Modern technologies such as photoacoustics, theranostic nanomedicine, and cancer research suggest that novel cancer diagnosis and therapy methods are highly needed. Figure  9 a traces the research focus that has evolved across various SDGs over time, commencing with SDG 3 (Good Health and Well-being), which is indicative of the central role of health in biomimetic research. It then extends into SDG 9 (Industry, Innovation, and Infrastructure) and SDG 7 (Affordable and Clean Energy), illustrating the cross-disciplinary applications of biomimetic technologies from healthcare to the energy and industrial sectors.

Figure  9 b provides a snapshot of the prominent keywords within this research theme, featuring terms such as “photodynamic therapy”, “photothermal chemotherapy”, “nanocarrier”, and “controlled drug delivery”. These terms underscore the innovative therapeutic strategies that mimic biological mechanisms for targeted cancer treatment. 'Bioinspired' and 'Biomimetic Synthesis' reflect the approach of deriving design principles from natural systems for the development of advanced materials and medical devices. 'Theranostic nanomedicine' integrates diagnosis and therapy, demonstrating a trend toward personalized and precision medicine.

A study conducted by Yu et al. 62 presented a novel approach for synergistic chemiexcited photodynamic-starvation therapy against metastatic tumors: a biomimetic nanoreactor, or bio-NR. Bio-NRs use hollow mesoporous silica nanoparticles to catalyze the conversion of glucose to hydrogen peroxide for starvation therapy while also producing singlet oxygen for photodynamic therapy. Bio-NR is promising for treating cancer metastasis because its coating on cancer cells improves its biological qualities. Yang et al.'s 63 study focused on a biocompatible Gd-integrated CuS nanotheranostic agent created via a biomimetic approach. This drug has low systemic side effects and good photothermal conversion efficiency, making it suitable for skin cancer therapy. It also performs well in imaging. The ultrasmall copper sulfide nanoparticles generated within ferritin nanocages are described in Wang et al.’s 64 publication. This work highlights the possibility of photoacoustic imaging-guided photothermal therapy with improved therapeutic efficiency and biocompatibility. These highly referenced articles highlight the significance of biomimetic techniques in furthering nanotheranostics and cancer therapy.

Established biomimetic foundations

Here, there are topics with a greater number of publications but a lower prominence percentile, which may imply areas where there has been significant research but that may be waning in influence or undergoing a shift in focus (Quadrant 4—bottom right).

Metaheuristics; Fireflies; Chiroptera

This topic is a fascinating mix of subjects. Using Firefly and Chiroptera in metaheuristic optimization algorithms provides a bioinspired method for resolving challenging issues. The thematic progression of research papers suggests the maturation of biomimetic disciplines that resonate with several SDGs (Fig.  10 a). The shift from initially aligning with SDG 3 (Good Health and Well-being) extends to intersecting with goals such as SDG 9 (Industry, Innovation, and Infrastructure), SDG 7 (Affordable and Clean Energy), SDG 11 (Sustainable Cities and Communities), SDG 13 (Climate Action), and SDG 15 (Life on Land). This diversification reflects the expansive utility of biomimetic approaches, from health applications to broader environmental and societal challenges.

The top keyphrases, such as 'Swarm Intelligence', 'Global Optimization', 'Cuckoo Search Algorithm', and 'Particle Swarm Optimization', are shown in Fig.  10 b highlights the utilization of nature-inspired algorithms for solving complex optimization problems. These terms, along with the 'Firefly Algorithm' and 'Bat Algorithm', underscore the transition of natural phenomena into computational algorithms that mimic the behavioral patterns of biological organisms, offering robust solutions in various fields, including resource management, logistics, and engineering design.

The three highly referenced metaheuristic publications centered around the “Moth Flame Optimization (MFO),” Salp Swarm Algorithm (SSA),” and Whale Optimization Algorithm (WOA).” The WOA, authored by Mirjalili and Lewis 65 , is a competitive solution for mathematical optimization and structural design issues because it emulates the social behavior of humpback whales. Inspired by the swarming behavior of salps, Mirjalili et al. 66 introduced the SSA and multiobjective SSA. This shows how well they function in optimizing a variety of engineering design difficulties. Finally, Mirjalili 67 suggested the MFO algorithm, which is modeled after the navigational strategy of moths and exhibits competitive performance in resolving benchmark and real-world engineering issues.

Bioprinting; three-dimensional printing; tissue engineering

The emphasis on sophisticated manufacturing methods for biological applications in this field suggests a keen interest in the nexus of biology and technology, especially in tissue engineering. As shown in Fig.  11 a, the topic's evolution encompasses Sustainable Development Goals (SDGs) that have transitioned over the years, including SDG 3 (Good Health and Well-being), which is inherently connected to the advancement of medical technologies and tissue engineering for health applications. This research also touches upon SDG 6 (Clean Water and Sanitation) and SDG 7 (Affordable and Clean Energy), suggesting applications of bioprinting technologies in the environmental sustainability and energy sectors. The progression toward SDG 9 (Industry, Innovation, and Infrastructure) and SDG 15 (Life on Land) reflects a broader impact, where biomimetic principles are applied to foster innovation in industrial processes and contribute to the preservation of terrestrial ecosystems.

Key phrases emerging from the word cloud in Fig.  11 b, such as “Hydrogel”, “Biofabrication”, “Tissue Scaffold”, and “Regenerative Medicine”, highlight the specialized methodologies and materials that are inspired by natural processes and structures. Terms such as 'Three-Dimensional Printing' and 'Bioprinting' underscore the technological advancements in creating complex biological structures, aiming to revolutionize the field of tissue engineering and regenerative medicine.

Three widely referenced papers about advances in 3D printing—particularly in bioprinting, soft matter, and the incorporation of biological tissue with functional electronics—are described next. Truby and Lewis’s 68 review of light- and ink-based 3D printing techniques is ground-breaking. This highlights the technology's capacity to create soft matter with tunable properties and its potential applications in robotics, shape-morphing systems, biologically inspired composites, and soft sensors. Ozbolat, and Hospodiuk 69 provide a thorough analysis of “extrusion-based bioprinting (EBB).” The adaptability of EBB in printing different biologics is discussed in the paper, with a focus on its uses in pharmaceutics, primary research, and clinical contexts. Future directions and challenges in EBB technology are also discussed. Using 3D printing, Mannoor et al. 70 presented a novel method for fusing organic tissue with functioning electronics. In the proof-of-concept, a hydrogel matrix seeded with cells and an interwoven conductive polymer containing silver nanoparticles are 3D printed to create a bionic ear. The improved auditory sensing capabilities of the printed ear show how this novel technology allows biological and nanoelectronic features to work together harmoniously.

RQ3: Translation and commercialization

Biomimicry offers promising solutions for sustainability in commercial industries with environmentally sustainable product innovation and energy savings with reduced resource commitment 71 . However, translating biomimicry innovations from research to commercialization presents challenges, including product validation, regulatory hurdles, and the need for strategic investment, innovative financial models, and interdisciplinary collaboration 71 , 72 , 73 , 74 . Ethical considerations highlight the need for universally applicable ethical guidelines regarding the moral debates surrounding biomimicry, such as motivations for pursuing such approaches and the valuation of nature 75 .

Addressing these barriers requires interdisciplinary collaboration, targeted education, and training programs. Strategic investment in biomimicry research and development is also crucial. Encouraging an engineering mindset that integrates biomimicry principles into conventional practices and developing commercial acumen among researchers is essential for navigating the market landscape 76 . Securing sufficient funding is essential for the development, testing, and scaling of these innovations 76 .

Successful case studies illustrate that the strategic integration of biomimicry enhances corporate sustainability and innovation (Larson & Meier 2017). In biomedical research, biomimetic approaches such as novel scaffolds and artificial skins have made significant strides (Zhang 2012). Architecture benefits through energy-efficient building facades modeled after natural cooling systems (Webb et al. 2017). The textile industry uses biomimicry to create sustainable, high-performance fabrics 77 .

RQ4: Interdisciplinary collaboration

Agricultural innovations (sdgs 1—no poverty and 2—zero hunger).

Environmental degradation, biodiversity loss, poverty, and hunger highlight the need for sustainable agricultural methods to mimic natural ecosystems. This includes computational models for ecological interactions, field experiments for biomimetic techniques, and novel materials inspired by natural soil processes. Research can develop solutions such as artificial photosynthesis for energy capture, polyculture systems mimicking ecosystem diversity, and bioinspired materials for soil regeneration and water retention 28 . These innovations can improve sustainability and energy efficiency in agriculture, addressing poverty and hunger through sustainable farming practices.

Educational models (SDG 4—Quality education)

Integrating sustainability principles and biomimicry into educational curricula at all levels presents opportunities for innovation. Collaborations between educators, environmental scientists, and designers can create immersive learning experiences that promote sustainability. This includes interdisciplinary curricula with biomimicry case studies, digital tools, and simulations for exploring biomimetic designs, and participatory learning approaches for engaging students with natural environments. Designing biomimicry-based educational tools and programs can help students engage in hands-on, project-based learning 10 , fostering a deeper understanding of sustainable living and problem-solving.

Gender-inclusive design (SDG 5—Gender inequality)

Gender biases in design and innovation call for research into biomimetic designs and technologies that facilitate gender equality. This includes participatory design processes involving women as cocreators, studying natural systems for inclusive strategies, and applying biomimetic principles to develop technologies supporting gender equality. Bioinspired technologies can address women's specific needs, enhancing access to education, healthcare, and economic opportunities. Interdisciplinary approaches involving gender studies, engineering, and environmental science can uncover new pathways for inclusive innovation.

Inclusive urban solutions (SDG 11—Sustainable cities and communities)

Rapid urbanization challenges such as housing shortages, environmental degradation, and unsustainable transportation systems require innovative solutions. Methodologies include systems thinking in urban planning, simulation tools for modeling biomimetic solutions, and pilot projects testing bioinspired urban innovations. Research on biomimetic architecture for affordable housing, green infrastructure for climate resilience, and bioinspired transportation systems can offer solutions. Collaborative efforts among architects, urban planners, ecologists, and sociologists are essential 78 .

Peace and justice (SDG 16—Peace, justice and institutions)

Social conflicts and weak institutions necessitate innovative approaches that integrate political science, sociology, and biology. Methods involve case studies, theoretical modeling, and participatory action research to develop strategies for peacebuilding and institutional development.

This research provides a comprehensive exploration of the multifaceted dimensions of biomimicry, SDG alignment, and interdisciplinary topics, demonstrating a clear trajectory of growth and relevance. Interdisciplinary collaboration has emerged as a pivotal strategy for unlocking the full potential of biomimicry in addressing underexplored SDGs.

While answering RQ1, the interdisciplinary analysis underscores the significant alignment of biomimicry research with several SDGs. This reflects the interdisciplinary nature of biomimicry and its ability to generate solutions for societal challenges. The analysis of two thematic clusters revealed the broad applicability of biomimicry across various sustainable development goals (SDGs). The first cluster includes health, partnership, and life on land (SDGs 3, 17, and 15), highlighting biomimicry's potential in medical technologies, sustainability collaborations, and land management. The second cluster encompasses clean water, energy, infrastructure, and marine life (SDGs 6, 7, 9, and 14), demonstrating innovative approaches to clean energy generation, sustainable infrastructure, and water purification.

In response to RQ2, this study highlights emerging topics within biomimicry research, such as metaheuristics and nanogenerators, which reflect a dynamic and evolving field that is swiftly gaining attention. These topics, alongside sensors, flexible electronics, and strain sensors, denote evolving research objectives and societal demands, pointing to new areas of study and innovation. This focus on interdisciplinary topics within biomimicry underscores the field’s adaptability and responsiveness to the shifting landscapes of technological and societal challenges.

In addressing RQ3, biomimicry holds potential for sustainable innovation but faces challenges in commercialization. Biomimicry inspires diverse technological and product innovations, driving sustainable advancements (Lurie-Luke 84 ). Overcoming these barriers through strategic investment, training, interdisciplinary collaboration, and ethical guidelines is essential for unlocking their full potential.

For RQ4 , the recommendations are formulated based on underexplored SDGs like 1, 4, 5, and 10 where biomimicry could play a pivotal role.

Future research could apply generative AI models to this dataset to validate the findings and explore additional insights. While our current study did not explore this topic, we see significant potential for this approach. Generative AI models can process extensive datasets and reveal patterns, potentially offering insights into biomimetic research correlations. The interpretation required for context-specific analysis remains challenging for generative AI 36 , 37

Our study provides valuable insights, but some limitations are worth considering. The chosen database might limit the comprehensiveness of the research captured, potentially excluding relevant work from other sources. Additionally, while the combination of cocitation mapping and BERTopic modeling provides a powerful analysis, both methods have inherent limitations. They may oversimplify the complexities of the field or introduce bias during theme interpretation, even with advanced techniques. Furthermore, our use of citations to thematically clustered publications as a proxy for impact inherits the limitations of citation analysis, such as biases toward established ideas and potential misinterpretations 79 , 80 . Another limitation of our study is the potential for missing accurate SDG mappings, as multiple SDG mapping initiatives are available, and our reliance on a single, Scopus-integrated method may not capture all relevant associations. Consequently, this could have resulted in the exclusion of papers that were appropriately aligned with certain SDGs but were not identified by our chosen mapping approach. Given these limitations, this study provides a valuable snapshot for understanding biomimicry research.

Data availability

All data generated or analyzed during this study are included in this published article and its supplementary information files.

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Google loses massive antitrust case over search, will appeal ruling

Google will appeal a U.S. District Court judge’s opinion Monday that found the technology giant acted illegally to maintain a monopoly in online search.

The decision from Judge Amit P. Mehta of the U.S. District Court for the District of Columbia is a major defeat for Google that could alter the way it does business and even change the structure of the internet as we know it, should the decision stand.

Mehta said that Google abused its monopoly power over the search business in part by paying companies like Apple to present its search engine as the default choice on their devices and web browsers. The Justice Department and states filed the antitrust suit against Google in 2020 , which kicked off in court in September 2023 .

Google pays companies, including Apple, Samsung and Mozilla, billions of dollars for prime placement in web browsers and on smartphones. In 2021 alone, Google spent $26 billion to be the default search engine across Apple and Android platforms. According to The New York Times, about $18 billion of that spend went to Apple alone. Google shares 36% of search ad revenue from Safari with Apple. The government has argued that paying for the dominant position effectively kneecapped competitors from being able to build up their own search engines to a scale that would give them the data and reach to stay competitive.

“After having carefully considered and weighed the witness testimony and evidence, the court reaches the following conclusion: Google is a monopolist, and it has acted as one to maintain its monopoly,” Mehta wrote in his opinion filed Monday. “It has violated Section 2 of the Sherman Act.”

Section 2 of the Sherman Act makes it illegal for any person or business to monopolize, attempt to monopolize or conspire to monopolize any part of trade or commerce.

Kent Walker, Google’s president of Global Affairs, told TechCrunch the company plans to appeal the decision. Walker doubled down on Google’s previous arguments that it has used its dominant position to make the best and most useful search engine, which has benefited consumers and advertisers alike.

“This decision recognizes that Google offers the best search engine, but concludes that we shouldn’t be allowed to make it easily available,” Walker told TechCrunch. “We appreciate the Court’s finding that Google is ‘the industry’s highest quality search engine, which has earned Google the trust of hundreds of millions of daily users’, that Google ‘has long been the best search engine, particularly on mobile devices’, ‘has continued to innovate in search’ and that ‘Apple and Mozilla occasionally assess Google’s search quality relative to its rivals and find Google’s to be superior.’”

The opinion caps off a years-long case — U.S. et al. v. Google — that resulted in a 10-week trial last year. The Department of Justice and a group of attorneys general from 38 states and territories, led by Colorado and Nebraska, filed similar but separate antitrust suits against Google in 2020, alleging that Google unfairly blocked out would-be search rivals like Bing and DuckDuckGo. The Department of Justice estimated that Google had a 90% share of the search market, a figure that Google disputed.

The outcome of the case is a significant win for the Justice Department in an election year when former president Donald Trump would, should he win a second term in office, almost certainly take a decidedly more hands-off, deregulatory approach to tech. President Joe Biden’s pick to lead the Federal Trade Commission, Lina Khan, has garnered a reputation for coming after big tech, particularly in regards to antitrust law, that many of those companies have not taken kindly to.

This case could set precedent for the raft of other antitrust lawsuits making their way through the courts today. The DOJ has sued Apple for making it difficult for consumers to switch away from the iPhone. The FTC has also recently sued Meta for stamping out early competitors and Amazon for squeezing sellers on its online marketplace.

Judge Mehta’s decision Monday may also impact the outcome of the Justice Department’s second antitrust suit against Google, which alleges that Google illegally monopolized the digital ads market. Arguments for that case are scheduled to begin September 9.

The judge has yet to decide remedies for Google’s behavior. He could force the company to change the way it runs its search business — or order it to sell off parts of that business. The opinion could be appealed, of course, and the final verdict may differ significantly, as happened with Microsoft’s famed antitrust case in the dot-com era.

In that case, Judge Thomas Penfield Jackson ruled that Microsoft violated antitrust laws and ordered the company to be split into two entities. Microsoft appealed the decision, and an appeals court overturned the breakup order, but Microsoft still had to take certain steps that experts today say might influence Mehta’s behavioral remedies for Google. As part of Microsoft’s settlement, the company had to share its APIs with third-party companies and appoint a panel to monitor its compliance.

Update: This article was originally published August 5 at 12:20 p.m. PT. It has been updated with more context and information from Google.

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A bi-objective model for the multi-period inventory-based reverse logistics network: a case study from an automobile component distribution network.

1. Introduction

• To optimize the transportation system in the ISACO company.
• To cut down transportation costs.
• To increase customer satisfaction by increasing the supply of customer demands.
• To allow the customers to return unused parts (which are not used by customers due to seasonal variations or environmental changes and market fluctuations.
• To collect and dispose or recycle the stock parts.

2. Literature Review

2.1. a review of the literature on distribution systems in supply chain management, 2.2. a review of the literature on green logistics in supply chain management, 3. materials and methods.

• Very high transportation costs induced by long round-trip distances.
• High costs imposed on the company as a result of vehicle breakdown.
• Frequent troubles related to timely goods delivery (e.g., the cities located far from Tehran, the chances are high that the goods do not reach on time).
• To benefit from the full capacity of cars, it is required that the amount of the ordered goods reach a certain quantity and then the goods be delivered to the representatives, which leads to dissatisfaction among the representatives and losing the competitive market.
• The lack of order and prioritization in the current system.
• Not considering different scenarios in decision making.
• Not being able to return unused or low-use parts by the representatives.
• The lack of an integrated system for receiving scrap parts.
• Not able to implement strategic planning.
• Some of the expected merits of the new system are the following:
• Reducing the costs resulting from redundant transportation.
• Increasing the representatives’ satisfaction level due to goods’ timely delivery and increasing the power to supply the demanded goods and the possibility of returning low-use parts to the representative.
• Systematizing transportation system which curbs other nuisances.
• Increasing the flexibility of the system.
• Decreasing the risks such as the sensitive parts becoming faulty during long transportation or the possibility of vehicle breakdowns that impose losses on the company.
• Building regional warehouses and reducing the heavy costs of the central warehouse.
• Controlling the system better and the potential to constantly improve.

5. Discussion and Conclusions

• Employing a multi-period model along with the power of inventory management so that it leads to reduced costs and increased revenue.
• With respect to the variety of available products, the number of product groups should be increased and included in the proposed model.
• Reducing the time of ordering periods to better use the multi-period model, supplying faster and more up-to-date customer demands in the year, and removing the barriers of the inventory cost increase through modeling and making decisions at the tactical and operational level.
• Raising the number of customers and applying the proposed model to the actual number of customers. It is worth mentioning that in this model, they were integrated into the provincial centers to facilitate the modeling of customer demand.
• Constructing regional warehouses in the locations suggested by the model outputs considering the construction cost and setting up and storing the goods in these warehouses.
• Launching the central warehouse number 2 when its effectiveness gets approved in all the models to properly benefit from it.
• Regularly controlling the proposed performance evaluation indices considering the possibility of changing the supply or demand pattern and making suitable decisions accordingly.
• Investigating the demand pattern in various time periods and the possibility of presenting a supplementary model for the probability mode of demand.
• Investigating the profit from waste recycling.
• Investigating the benefits of the brand’s mental image in terms of compliance with environmental issues.
• Considering production issues in the supply chain and distribution system.
• Including the demand of the different classes of customers in the distribution system and locating facilities; accordingly, in other words, assessing the effect of marketing decisions on the strategic macro-decisions of facility location.
• Considering other location benchmarks.
• Determining the order supply deadline for all sorts of goods orders and programming to supply them within the deadline and its effect on facility location problems.
• Considering other objective functions like social aspects, employment rates, and environmental impacts according to the priorities of managers and decision-makers.

Author Contributions

Data availability statement, conflicts of interest.

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Share and Cite

Khalilzadeh, M.; Antucheviciene, J.; Božanić, D. A Bi-Objective Model for the Multi-Period Inventory-Based Reverse Logistics Network: A Case Study from an Automobile Component Distribution Network. Systems 2024 , 12 , 299. https://doi.org/10.3390/systems12080299

Khalilzadeh M, Antucheviciene J, Božanić D. A Bi-Objective Model for the Multi-Period Inventory-Based Reverse Logistics Network: A Case Study from an Automobile Component Distribution Network. Systems . 2024; 12(8):299. https://doi.org/10.3390/systems12080299

Khalilzadeh, Mohammad, Jurgita Antucheviciene, and Darko Božanić. 2024. "A Bi-Objective Model for the Multi-Period Inventory-Based Reverse Logistics Network: A Case Study from an Automobile Component Distribution Network" Systems 12, no. 8: 299. https://doi.org/10.3390/systems12080299

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