Pub Date : 2024-11-28DOI: 10.1016/j.ecolind.2024.112868
Zhixiang Zhou, Mengya Li, Xianzhe Xu, Huaqing Wu
This study introduces an innovative Data Envelopment Analysis (DEA) model that integrates spatial relationships among decision-making units (DMUs) to determine relative prices of all variables for evaluating ecological efficiency more accurately, particularly in the context of water resource management. To better capture ecological performance, we propose a model that includes spatial correlation, addressing interdependencies that traditional DEA models often overlook. By incorporating a spatial weight matrix, the model delineates interactions between DMUs, offering a comprehensive evaluation that considers both technical efficiency and the spatial efficiency impact. We demonstrate the utility of our model through an empirical analysis of 17 national monitoring cross-sections within the Chaohu Watershed, a critical ecological and economic zone within China’s Yangtze River Delta. This research contributes to the fields of environmental economics, resource management, and spatial analysis by providing a robust methodological framework and actionable insights for sustainable environmental stewardship.
本研究介绍了一种创新的数据包络分析（DEA）模型，该模型整合了决策单元（DMU）之间的空间关系，以确定所有变量的相对价格，从而更准确地评估生态效率，尤其是在水资源管理方面。为了更好地反映生态绩效，我们提出了一个包含空间相关性的模型，以解决传统 DEA 模型经常忽略的相互依存问题。通过纳入空间权重矩阵，该模型划定了 DMU 之间的相互作用，提供了一种既考虑技术效率又考虑空间效率影响的综合评价。我们通过对中国长江三角洲重要生态经济区巢湖流域内 17 个国家监测断面的实证分析，证明了我们模型的实用性。这项研究为环境经济学、资源管理和空间分析领域做出了贡献，为可持续环境管理提供了强大的方法框架和可行的见解。
{"title":"Integrating spatial relationships in the DEA approach for ecological efficiency evaluation: A case study of the Chaohu watershed","authors":"Zhixiang Zhou, Mengya Li, Xianzhe Xu, Huaqing Wu","doi":"10.1016/j.ecolind.2024.112868","DOIUrl":"10.1016/j.ecolind.2024.112868","url":null,"abstract":"<div><div>This study introduces an innovative Data Envelopment Analysis (DEA) model that integrates spatial relationships among decision-making units (DMUs) to determine relative prices of all variables for evaluating ecological efficiency more accurately, particularly in the context of water resource management. To better capture ecological performance, we propose a model that includes spatial correlation, addressing interdependencies that traditional DEA models often overlook. By incorporating a spatial weight matrix, the model delineates interactions between DMUs, offering a comprehensive evaluation that considers both technical efficiency and the spatial efficiency impact. We demonstrate the utility of our model through an empirical analysis of 17 national monitoring cross-sections within the Chaohu Watershed, a critical ecological and economic zone within China’s Yangtze River Delta. This research contributes to the fields of environmental economics, resource management, and spatial analysis by providing a robust methodological framework and actionable insights for sustainable environmental stewardship.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"169 ","pages":"Article 112868"},"PeriodicalIF":7.0,"publicationDate":"2024-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142724063","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-28DOI: 10.1016/j.ecolind.2024.112870
Ziyuan Gong , Fei Gao , Xinyu Chang , Tianqi Hu , Yaping Li
Facing the severe situation of global warming and water shortage, the research of hydrological cycle and regional scale climate has been paid more and more attention. Irrigation and evapotranspiration (ET) affect the hydrological cycle and regional climate. This paper selects articles based on the two title words “irrigation” and “ evapotranspiration”, conducts CNKI (Chinese National Knowledge Infrastructure) cluster analysis on all the search results, discusses the occurrence frequency of keywords in Chinese literature in recent 20 years, and analyzes the research status and development trend of irrigation and evaporation fields. Furthermore, WOS (web of science) is used to analyze the literature on international distribution based on the “irrigation”, “ET” and “irrigation” “transpiration” headings VOSviewer and Scimago graphic analyzed the basic information of the relevant literature. The study found that the hot spots mainly concentrated on ET, irrigation, remote sensing (RS) technology, crop yield, and water utilization rate. With the development of information technology, various RS techniques, learning algorithms, and models have been used to estimate ET and irrigation quantity. Improving the high resolution of the model, the uncertainty of the parameters, and the RS data in the lack of data are the development trend of estimating ET and irrigation quantity in the future. At the same time, irrigation will affect ET, resulting in a decrease in potential evapotranspiration (PET) (measured as reference evapotranspiration (ET0)) and an increase in actual evapotranspiration (ETa), but the mechanism of this effect is not very clear. This paper provides a brief review to illustrate the interactions between irrigation and ET, which can provide a good reference for future research on irrigation and ET, as well as a guide for identifying effective measures for adapting water resources to global change.
{"title":"A review of interactions between irrigation and evapotranspiration","authors":"Ziyuan Gong , Fei Gao , Xinyu Chang , Tianqi Hu , Yaping Li","doi":"10.1016/j.ecolind.2024.112870","DOIUrl":"10.1016/j.ecolind.2024.112870","url":null,"abstract":"<div><div>Facing the severe situation of global warming and water shortage, the research of hydrological cycle and regional scale climate has been paid more and more attention. Irrigation and evapotranspiration (ET) affect the hydrological cycle and regional climate. This paper selects articles based on the two title words “irrigation” and “ evapotranspiration”, conducts CNKI (Chinese National Knowledge Infrastructure) cluster analysis on all the search results, discusses the occurrence frequency of keywords in Chinese literature in recent 20 years, and analyzes the research status and development trend of irrigation and evaporation fields. Furthermore, WOS (web of science) is used to analyze the literature on international distribution based on the “irrigation”, “ET” and “irrigation” “transpiration” headings VOSviewer and Scimago graphic analyzed the basic information of the relevant literature. The study found that the hot spots mainly concentrated on ET, irrigation, remote sensing (RS) technology, crop yield, and water utilization rate. With the development of information technology, various RS techniques, learning algorithms, and models have been used to estimate ET and irrigation quantity. Improving the high resolution of the model, the uncertainty of the parameters, and the RS data in the lack of data are the development trend of estimating ET and irrigation quantity in the future. At the same time, irrigation will affect ET, resulting in a decrease in potential evapotranspiration (PET) (measured as reference evapotranspiration (ET<sub>0</sub>)) and an increase in actual evapotranspiration (ET<sub>a</sub>), but the mechanism of this effect is not very clear. This paper provides a brief review to illustrate the interactions between irrigation and ET, which can provide a good reference for future research on irrigation and ET, as well as a guide for identifying effective measures for adapting water resources to global change.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"169 ","pages":"Article 112870"},"PeriodicalIF":7.0,"publicationDate":"2024-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142723974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-27DOI: 10.1016/j.ecolind.2024.112867
Shiling Xu , Jiaxin Wang , Yan Zuo , Longfei Ma , Jun Chen , Zichao Zhang , Ping Xie , Jia Yu , Jie Liu
Trophic relationships between species in ecosystems are characterized by food webs. However, there is less research on the differences in food web characteristics at larger spatial scales. This study discusses the spatial variations in food web structures across 13 freshwater ecosystems located east of the Hu Line, based on stable isotope techniques. The results show that there are significant spatial differences in the structure of the food web of the studied ecosystem, which is associated with human activities, seasonal variation, environmental factors, etc. Additionally, this study describes how fish exhibit different dietary strategies in response to the fluctuations of food resources, such as the temporal lag of stable isotopic values and changes in trophic ecological niche width (overlap or differentiation). Finally, we summarize the potential uncertainties in the application of stable isotope techniques, emphasizing the necessity to carefully consider these uncertainties when utilizing stable isotope data for ecological research to ensure the accuracy and reliability of the results. The study provides theoretical support for the regional-scale management of freshwater ecosystems.
{"title":"Implications from the application of stable isotopes in freshwater food webs east of the Hu Line, China","authors":"Shiling Xu , Jiaxin Wang , Yan Zuo , Longfei Ma , Jun Chen , Zichao Zhang , Ping Xie , Jia Yu , Jie Liu","doi":"10.1016/j.ecolind.2024.112867","DOIUrl":"10.1016/j.ecolind.2024.112867","url":null,"abstract":"<div><div>Trophic relationships between species in ecosystems are characterized by food webs. However, there is less research on the differences in food web characteristics at larger spatial scales. This study discusses the spatial variations in food web structures across 13 freshwater ecosystems located east of the Hu Line, based on stable isotope techniques. The results show that there are significant spatial differences in the structure of the food web of the studied ecosystem, which is associated with human activities, seasonal variation, environmental factors, etc. Additionally, this study describes how fish exhibit different dietary strategies in response to the fluctuations of food resources, such as the temporal lag of stable isotopic values and changes in trophic ecological niche width (overlap or differentiation). Finally, we summarize the potential uncertainties in the application of stable isotope techniques, emphasizing the necessity to carefully consider these uncertainties when utilizing stable isotope data for ecological research to ensure the accuracy and reliability of the results. The study provides theoretical support for the regional-scale management of freshwater ecosystems.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"169 ","pages":"Article 112867"},"PeriodicalIF":7.0,"publicationDate":"2024-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142724062","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-27DOI: 10.1016/j.ecolind.2024.112863
Jordan L. Heiman , Jody M. Tucker , Sarah N. Sells , Joshua J. Millspaugh , Michael K. Schwartz
Natural resource agencies are frequently tasked with monitoring populations of at-risk species to ensure management activities do not negatively affect the viability of wildlife populations. Typically, these monitoring efforts evaluate trends in a population’s abundance, occupancy, or geographic distribution. Often, surveys provide local information, but results are generally not incorporated into broad-scale monitoring efforts that focus on range-wide population changes due to their variable nature in both spatial extent and effort. We investigated whether aggregating these local (hereafter “variable”) surveys can generate enough statistical power to estimate broad-scale population trends using simulations of declining populations of fishers (Pekaniapennati) over a 10-year time horizon. Our simulations included three population sizes which we refer to as abundant, common, and rare ( = 700, 350, and 100 individuals, respectively) with each declining at a rapid and moderate pace ( = 0.933, and 0.977, respectively). For each population, we simulated variable surveys using an occupancy framework to subsample the population with parameters that mimic combining multiple independent monitoring efforts which vary annually in location, and effort. Regardless of spatial consistency of annual sampling, there was minimal variation in statistical power under both high and low detection probability simulations. However, when sampling effort varied each year, statistical power was lower for most populations and sampling scenarios when compared to consistent sampling effort unless some baseline level of sampling effort was reliably achieved in all years. In many cases, adding low-level consistent baseline sampling to variable surveys resulted in statistical power close to that of consistent sampling efforts. Our results suggest statistical power is driven by annual consistency in the proportion of landscape sampled rather than spatial consistency in sampling locations. This result indicates that current variable surveys could be leveraged and combined to detect population declines for at-risk species at broad-scales if a baseline proportion of landscape is robustly sampled. The level of baseline sampling is highly dependent on population size and magnitudes of population change. In simulations with a common or abundant population experiencing a rapid decline, a baseline survey effort of at least 5% of the landscape in combination with variable surveys resulted in statistical power consistently above the standard threshold of 0.80 for occupancy monitoring. Leveraging existing local efforts to achieve high detection probability and baseline sampling would reduce financial and logistical burdens of broad-scale wildlife monitoring efforts.
{"title":"Leveraging local wildlife surveys for robust occupancy trend estimation","authors":"Jordan L. Heiman , Jody M. Tucker , Sarah N. Sells , Joshua J. Millspaugh , Michael K. Schwartz","doi":"10.1016/j.ecolind.2024.112863","DOIUrl":"10.1016/j.ecolind.2024.112863","url":null,"abstract":"<div><div>Natural resource agencies are frequently tasked with monitoring populations of at-risk species to ensure management activities do not negatively affect the viability of wildlife populations. Typically, these monitoring efforts evaluate trends in a population’s abundance, occupancy, or geographic distribution. Often, surveys provide local information, but results are generally not incorporated into broad-scale monitoring efforts that focus on range-wide population changes due to their variable nature in both spatial extent and effort. We investigated whether aggregating these local (hereafter “variable”) surveys can generate enough statistical power to estimate broad-scale population trends using simulations of declining populations of fishers (<em>Pekania</em> <em>pennati</em>) over a 10-year time horizon. Our simulations included three population sizes which we refer to as abundant, common, and rare (<span><math><msub><mi>N</mi><mn>0</mn></msub></math></span> = 700, 350, and 100 individuals, respectively) with each declining at a rapid and moderate pace (<span><math><mi>λ</mi></math></span> = 0.933, and 0.977, respectively). For each population, we simulated variable surveys using an occupancy framework to subsample the population with parameters that mimic combining multiple independent monitoring efforts which vary annually in location, and effort. Regardless of spatial consistency of annual sampling, there was minimal variation in statistical power under both high and low detection probability simulations. However, when sampling effort varied each year, statistical power was lower for most populations and sampling scenarios when compared to consistent sampling effort unless some baseline level of sampling effort was reliably achieved in all years. In many cases, adding low-level consistent baseline sampling to variable surveys resulted in statistical power close to that of consistent sampling efforts. Our results suggest statistical power is driven by annual consistency in the proportion of landscape sampled rather than spatial consistency in sampling locations. This result indicates that current variable surveys could be leveraged and combined to detect population declines for at-risk species at broad-scales if a baseline proportion of landscape is robustly sampled. The level of baseline sampling is highly dependent on population size and magnitudes of population change. In simulations with a common or abundant population experiencing a rapid decline, a baseline survey effort of at least 5% of the landscape in combination with variable surveys resulted in statistical power consistently above the standard threshold of 0.80 for occupancy monitoring. Leveraging existing local efforts to achieve high detection probability and baseline sampling would reduce financial and logistical burdens of broad-scale wildlife monitoring efforts.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"169 ","pages":"Article 112863"},"PeriodicalIF":7.0,"publicationDate":"2024-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142724064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-27DOI: 10.1016/j.ecolind.2024.112879
Simon Belle, Brian Huser, Richard K. Johnson
In this study, we used subfossil chironomids to assess temporal changes in lake ecological status over the last ca. 100 years in 30 lakes spread across different ecoregions in Sweden. By comparing Benthic Quality Index values and their temporal trends, we aimed to quantify the cumulative effects of climate change and land use on lakes and unravel how their effects may vary regionally. Results indicate that land use is the overarching driver of ecological changes in impacted lakes, in line with earlier studies showing that local pressures often suppress climate change effects on freshwaters. Furthermore, the known positive co-tolerance of chironomid species to temperature and eutrophication (e.g., cold stenotherm species also being indicators of oligotrophic condition, and conversely) was anticipated to induce antagonistic effects. However, the cumulative effects of climate change and land use differ across the landscape, being synergistic in the boreal forest ecoregion and antagonistic in the mixed forest ecoregion. We suggest that the pre-disturbance conditions (i.e., species composition and pressure sensitivities) play a key role in regulating the interactions between multiple pressures in freshwaters. Overall, this finding is encouraging as it implies that restoration of lakes that focuses on the most impactful pressure (e.g., nutrient loadings from agricultural fields and urban areas) remains a plausible restoration measure despite lake warming. Results also show that the net effect of climate change on the ecological status of the reference lakes varied regionally, being more pronounced in northern lakes due to the predominance of many cold water species which are more prone to disappear in response to small variations in temperature. As reference conditions are seldom revised, it is of fundamental importance to question whether the existing reference conditions are still applicable or need to be revised due to ongoing and future climate change.
{"title":"Cumulative effects of climate change and land use on the ecological status of Scandinavian lakes show contrasted interactions in different ecoregions: the role of pre-disturbance conditions in assessing ecological status","authors":"Simon Belle, Brian Huser, Richard K. Johnson","doi":"10.1016/j.ecolind.2024.112879","DOIUrl":"10.1016/j.ecolind.2024.112879","url":null,"abstract":"<div><div>In this study, we used subfossil chironomids to assess temporal changes in lake ecological status over the last <em>ca</em>. 100 years in 30 lakes spread across different ecoregions in Sweden. By comparing Benthic Quality Index values and their temporal trends, we aimed to quantify the cumulative effects of climate change and land use on lakes and unravel how their effects may vary regionally. Results indicate that land use is the overarching driver of ecological changes in impacted lakes, in line with earlier studies showing that local pressures often suppress climate change effects on freshwaters. Furthermore, the known positive co-tolerance of chironomid species to temperature and eutrophication (e.g., cold stenotherm species also being indicators of oligotrophic condition, and conversely) was anticipated to induce antagonistic effects. However, the cumulative effects of climate change and land use differ across the landscape, being synergistic in the boreal forest ecoregion and antagonistic in the mixed forest ecoregion. We suggest that the pre-disturbance conditions (i.e., species composition and pressure sensitivities) play a key role in regulating the interactions between multiple pressures in freshwaters. Overall, this finding is encouraging as it implies that restoration of lakes that focuses on the most impactful pressure (e.g., nutrient loadings from agricultural fields and urban areas) remains a plausible restoration measure despite lake warming. Results also show that the net effect of climate change on the ecological status of the reference lakes varied regionally, being more pronounced in northern lakes due to the predominance of many cold water species which are more prone to disappear in response to small variations in temperature. As reference conditions are seldom revised, it is of fundamental importance to question whether the existing reference conditions are still applicable or need to be revised due to ongoing and future climate change.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"169 ","pages":"Article 112879"},"PeriodicalIF":7.0,"publicationDate":"2024-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142723972","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-27DOI: 10.1016/j.ecolind.2024.112889
Teng Niu , Zhongze Hou , Jiaxin Yu , Jie Lu , Qiang Yu , Linzhe Yang , Jun Ma , Yafei Liu , Hui Shi , Xuyang Jin
<div><div>The water retention service of the forest ecosystem has ecological functions such as adjusting the climate and maintaining the ecological water balance. The Qinghai-Tibet Plateau is an alpine region. Due to its high altitude and harsh environment, it is difficult to manually observe the water retention in the field, and it is impossible to better evaluate the water retention function. In order to better obtain the water retention in the alpine region, hyperspectral technology is introduced and applied to the acquisition of surface vegetation information, and the water retention in a specific area is obtained by constructing a model. In this study, the Bayi District of Nyingchi Prefecture was used as the research area. The main tree species in the study area are <em>Picea likiangensis</em> var. <em>linzhiensis(PLVL)</em>, <em>Quercus aquifolioides(QA)</em>, <em>Pinus densata(PD)</em> and <em>Rhododendron nivale(RN)</em>. In actual situations, it is not easy to directly obtain water retention information, so a model can be found to quantitatively express the relationship between leaf spectrum and water retention. Then based on the leaf spectrum to invert the water retention. In order to study the quantitative relationship between different vegetation and water retention, each type of vegetation collects leaf samples and water retention data at 30 sampling points. Use ASD Fildsoec Handheld spectrometer to obtain hyperspectral data. Seven band indexes of red edge, green peak, NDVI, NDWI, EVI, WBI and NDPI were selected, and the relationship between vegetation band index and water conservation was fitted through many kinds of regression models. Comparing the fitting results, construct water retention prediction model. The interception of vegetation canopy, litter water holding capacity and soil water content are obtained through experiments. The sum of the three represents the water retention capacity of vegetation. The reflectance spectra of the four types of vegetation leaves all show similar regularities, and the difference in the visible light band is not obvious. The near-infrared to mid-infrared bands show four distinct water absorption bands, with the highest reflectivity in the red to near-infrared bands (700 nm-1400 nm). The reflectance of the four types of vegetation varies across different spectral bands, with the reflectance levels exhibiting the characteristic order of QA > PD > PLVL ≈ RN. Comparing the fitting results of different regression models with seven waveband parameters, the R<sup>2</sup> of the four types of vegetation are higher in the regression models of EVI and NDPI, and reach a significant level. According to the regression model corresponding to each kind of vegetation, the water retention prediction model is composed, and the simulation accuracy is tested by R<sup>2</sup> and RMSE. The overall simulation accuracy R<sup>2</sup> is greater than 0.7 and the RMSE is basically less than 10 t·hm<sup>−2</sup>, i
{"title":"Construction of prediction model for water retention of forest ecosystem in alpine region based on vegetation spectral features","authors":"Teng Niu , Zhongze Hou , Jiaxin Yu , Jie Lu , Qiang Yu , Linzhe Yang , Jun Ma , Yafei Liu , Hui Shi , Xuyang Jin","doi":"10.1016/j.ecolind.2024.112889","DOIUrl":"10.1016/j.ecolind.2024.112889","url":null,"abstract":"<div><div>The water retention service of the forest ecosystem has ecological functions such as adjusting the climate and maintaining the ecological water balance. The Qinghai-Tibet Plateau is an alpine region. Due to its high altitude and harsh environment, it is difficult to manually observe the water retention in the field, and it is impossible to better evaluate the water retention function. In order to better obtain the water retention in the alpine region, hyperspectral technology is introduced and applied to the acquisition of surface vegetation information, and the water retention in a specific area is obtained by constructing a model. In this study, the Bayi District of Nyingchi Prefecture was used as the research area. The main tree species in the study area are <em>Picea likiangensis</em> var. <em>linzhiensis(PLVL)</em>, <em>Quercus aquifolioides(QA)</em>, <em>Pinus densata(PD)</em> and <em>Rhododendron nivale(RN)</em>. In actual situations, it is not easy to directly obtain water retention information, so a model can be found to quantitatively express the relationship between leaf spectrum and water retention. Then based on the leaf spectrum to invert the water retention. In order to study the quantitative relationship between different vegetation and water retention, each type of vegetation collects leaf samples and water retention data at 30 sampling points. Use ASD Fildsoec Handheld spectrometer to obtain hyperspectral data. Seven band indexes of red edge, green peak, NDVI, NDWI, EVI, WBI and NDPI were selected, and the relationship between vegetation band index and water conservation was fitted through many kinds of regression models. Comparing the fitting results, construct water retention prediction model. The interception of vegetation canopy, litter water holding capacity and soil water content are obtained through experiments. The sum of the three represents the water retention capacity of vegetation. The reflectance spectra of the four types of vegetation leaves all show similar regularities, and the difference in the visible light band is not obvious. The near-infrared to mid-infrared bands show four distinct water absorption bands, with the highest reflectivity in the red to near-infrared bands (700 nm-1400 nm). The reflectance of the four types of vegetation varies across different spectral bands, with the reflectance levels exhibiting the characteristic order of QA > PD > PLVL ≈ RN. Comparing the fitting results of different regression models with seven waveband parameters, the R<sup>2</sup> of the four types of vegetation are higher in the regression models of EVI and NDPI, and reach a significant level. According to the regression model corresponding to each kind of vegetation, the water retention prediction model is composed, and the simulation accuracy is tested by R<sup>2</sup> and RMSE. The overall simulation accuracy R<sup>2</sup> is greater than 0.7 and the RMSE is basically less than 10 t·hm<sup>−2</sup>, i","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"169 ","pages":"Article 112889"},"PeriodicalIF":7.0,"publicationDate":"2024-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142723973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-26DOI: 10.1016/j.ecolind.2024.112887
Hong Du , Sidong Zeng , Xin Liu , Jun Xia
Water-carbon relationships have been widely recognized in previous studies but rarely included in the Budyko framework. This study improves the Budyko-Fu model by considering the relationship of the underlying surface parameter with vegetation dynamics. Then the evapotranspiration (ET) was estimated using the improved Budyko model and the main driving factors of ET change were identified. The results show that the improved Budyko model considering the gross primary production in the equation could capture the annual ET changes quite well. ET tends to increase with an increase rate of 6.89 mm/a in the study area. Vegetation changes is the most important factor influencing the ET changes contributing 69.87 %, while climate changes in precipitation and potential evapotranspiration contribute 31.23 % and −1.10 % respectively. The main contributors to the estimated ET change differed in the subregion. With vegetation changes being the dominant factor for ET change in the southwestern part, while ET increase was mainly due to the increase in precipitation in the northeastern part of the study area. The contribution of vegetation to the estimated ET change shows a spatially increasing trend from northeast to southwest, while the contribution of precipitation shows a decreasing trend from northeast to southwest. This study proposed a new method for the estimation of ET changes based on the water-carbon coupling relationships and highlight the different contributions of vegetation dynamics to ET changes.
{"title":"An improved Budyko framework model incorporating water-carbon relationship for estimating evapotranspiration under climate and vegetation changes","authors":"Hong Du , Sidong Zeng , Xin Liu , Jun Xia","doi":"10.1016/j.ecolind.2024.112887","DOIUrl":"10.1016/j.ecolind.2024.112887","url":null,"abstract":"<div><div>Water-carbon relationships have been widely recognized in previous studies but rarely included in the Budyko framework. This study improves the Budyko-Fu model by considering the relationship of the underlying surface parameter with vegetation dynamics. Then the evapotranspiration (ET) was estimated using the improved Budyko model and the main driving factors of ET change were identified. The results show that the improved Budyko model considering the gross primary production in the equation could capture the annual ET changes quite well. ET tends to increase with an increase rate of 6.89 mm/a in the study area. Vegetation changes is the most important factor influencing the ET changes contributing 69.87 %, while climate changes in precipitation and potential evapotranspiration contribute 31.23 % and −1.10 % respectively. The main contributors to the estimated ET change differed in the subregion. With vegetation changes being the dominant factor for ET change in the southwestern part, while ET increase was mainly due to the increase in precipitation in the northeastern part of the study area. The contribution of vegetation to the estimated ET change shows a spatially increasing trend from northeast to southwest, while the contribution of precipitation shows a decreasing trend from northeast to southwest. This study proposed a new method for the<!--> <!-->estimation of ET changes based on the water-carbon coupling relationships and highlight the different contributions of vegetation dynamics to ET changes.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"169 ","pages":"Article 112887"},"PeriodicalIF":7.0,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142706420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-25DOI: 10.1016/j.ecolind.2024.112888
Piotr Krajewski, Monika Lebiedzińska
Over past 20 years analysis of driving forces of landscape change have become a popular research topic, but there is still insufficient amount of research on this issue in the countries of Eastern Europe. This is all the more important as a number of factors have accelerated changes in the landscape in the countries that have joined the European Union in recent years. The results of the research presented in the article concern the identification of those forces that significantly influenced the shape of changes from the perspective of residents living in different types of municipalities from the Lower Silesia region. The research approach used was to identify the landscape transformations that took place in the 3 time intervals 2005–2010, 2010–2015, 2015–2020, and then to present them in the form of a questionnaire to the inhabitants of the 6 municipalities that lived in the study area during the study period, asking them to identify which of the indicated phenomena or processes contributed to the indicated landscape transformations. The driving forces most often indicated by residents of the analyzed municipalities can be categorised as political forces (40.66 %), socio-economic forces (20.74 %) and cultural forces (16.61 %). However, the results showed differences in the reported drivers of landscape change depending on the type of landscape in which the changes occurred. In urban landscapes, the proportion of cultural drivers increased significantly, in contrast to agricultural or forest landscapes where natural and political forces were more important.
{"title":"Assessing the driving forces of landscape change in the perspective of Polish residents","authors":"Piotr Krajewski, Monika Lebiedzińska","doi":"10.1016/j.ecolind.2024.112888","DOIUrl":"10.1016/j.ecolind.2024.112888","url":null,"abstract":"<div><div>Over past 20 years analysis of driving forces of landscape change have become a popular research topic, but there is still insufficient amount of research on this issue in the countries of Eastern Europe. This is all the more important as a number of factors have accelerated changes in the landscape in the countries that have joined the European Union in recent years. The results of the research presented in the article concern the identification of those forces that significantly influenced the shape of changes from the perspective of residents living in different types of municipalities from the Lower Silesia region. The research approach used was to identify the landscape transformations that took place in the 3 time intervals 2005–2010, 2010–2015, 2015–2020, and then to present them in the form of a questionnaire to the inhabitants of the 6 municipalities that lived in the study area during the study period, asking them to identify which of the indicated phenomena or processes contributed to the indicated landscape transformations. The driving forces most often indicated by residents of the analyzed municipalities can be categorised as political forces (40.66 %), socio-economic forces (20.74 %) and cultural forces (16.61 %). However, the results showed differences in the reported drivers of landscape change depending on the type of landscape in which the changes occurred. In urban landscapes, the proportion of cultural drivers increased significantly, in contrast to agricultural or forest landscapes where natural and political forces were more important.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"169 ","pages":"Article 112888"},"PeriodicalIF":7.0,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142706418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-25DOI: 10.1016/j.ecolind.2024.112847
Zheran Zhai , Siyao Liu , Zimeng Li , Ruijie Ma , Xiaoyu Ge , Haidong Feng , Yang Shi , Chen Gu
This study aims to investigate the distribution patterns of bird species in urban built-up areas and their impact factors from multiple dimensions, including spatiotemporal distribution, environmental changes, and anthropogenic disturbances, as well as overall distribution and local hotspots. Leveraging geographic distribution data of 383 bird species from 70 families and 21 orders, the study recorded dynamic changes in bird distribution within urban built-up areas characterized by highly heterogeneous core areas and suburban areas. It examined species distribution across different seasons and land cover types, evaluated population fluctuations based on migratory behaviors, and assessed the relative abundance of bird families and species in hotspot areas. Additionally, this study employed three tree-based machine learning algorithms—Decision Tree (DT), Random Forest (RF), and Extreme Gradient Boosting (XGBoost)—to investigate the influence of environmental factors on bird species distribution within urban built-up areas. The findings showed that, temporally, the number of observed bird species in the study area peaked in May and September, while the lowest numbers of species (54.83 %) and individuals (5.45 %) were recorded during the high-temperature period from June to August. Spatially, (1) woodlands, including stable mature forests, unstable juvenile forests, and sparse vegetation, recorded the highest frequencies of bird observations (2,053 times), bird species (369 species), and bird individuals (38,623 individuals); (2) comprehensive parks, where bird species demonstrated higher adaptability to anthropogenic disturbances, experienced a more significant decline in species richness compared to country parks; and (3) the number of bird species in hotspot areas located in the core areas, which developed earlier, has decreased annually, while the number of species in suburban areas, which developed later, has increased annually. In terms of impact factors, water area (WA), point of interest kernel density (DPOI), relative humidity (RH), green space area (GSA), and nighttime light pollution (NL) were identified as the five most important environmental factors affecting bird species richness. These results suggest that although birds exhibit some adaptability to environmental changes and anthropogenic disturbances, species distribution remains significantly impacted. This research aims to provide a planning framework for future urban development that promotes biodiversity and adaptability, thereby bolstering the resilience of urban ecosystems.
{"title":"The spatiotemporal distribution patterns and impact factors of bird species richness: A case study of urban built-up areas in Beijing, China","authors":"Zheran Zhai , Siyao Liu , Zimeng Li , Ruijie Ma , Xiaoyu Ge , Haidong Feng , Yang Shi , Chen Gu","doi":"10.1016/j.ecolind.2024.112847","DOIUrl":"10.1016/j.ecolind.2024.112847","url":null,"abstract":"<div><div>This study aims to investigate the distribution patterns of bird species in urban built-up areas and their impact factors from multiple dimensions, including spatiotemporal distribution, environmental changes, and anthropogenic disturbances, as well as overall distribution and local hotspots. Leveraging geographic distribution data of 383 bird species from 70 families and 21 orders, the study recorded dynamic changes in bird distribution within urban built-up areas characterized by highly heterogeneous core areas and suburban areas. It examined species distribution across different seasons and land cover types, evaluated population fluctuations based on migratory behaviors, and assessed the relative abundance of bird families and species in hotspot areas. Additionally, this study employed three tree-based machine learning algorithms—Decision Tree (DT), Random Forest (RF), and Extreme Gradient Boosting (XGBoost)—to investigate the influence of environmental factors on bird species distribution within urban built-up areas. The findings showed that, temporally, the number of observed bird species in the study area peaked in May and September, while the lowest numbers of species (54.83 %) and individuals (5.45 %) were recorded during the high-temperature period from June to August. Spatially, (1) woodlands, including stable mature forests, unstable juvenile forests, and sparse vegetation, recorded the highest frequencies of bird observations (2,053 times), bird species (369 species), and bird individuals (38,623 individuals); (2) comprehensive parks, where bird species demonstrated higher adaptability to anthropogenic disturbances, experienced a more significant decline in species richness compared to country parks; and (3) the number of bird species in hotspot areas located in the core areas, which developed earlier, has decreased annually, while the number of species in suburban areas, which developed later, has increased annually. In terms of impact factors, water area (WA), point of interest kernel density (DPOI), relative humidity (RH), green space area (GSA), and nighttime light pollution (NL) were identified as the five most important environmental factors affecting bird species richness. These results suggest that although birds exhibit some adaptability to environmental changes and anthropogenic disturbances, species distribution remains significantly impacted. This research aims to provide a planning framework for future urban development that promotes biodiversity and adaptability, thereby bolstering the resilience of urban ecosystems.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"169 ","pages":"Article 112847"},"PeriodicalIF":7.0,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142706417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-25DOI: 10.1016/j.ecolind.2024.112856
Weijing Ma , Shujuan Hou , Wufan Su , Ting Mao , Xiaoya Wang , Tingting Liang
Sanjiangyuan National Park (SNP) is one of China’s national parks with high ecological significance and ecological vulnerability. In order to promote the healthy development of national park ecosystems, it is extremely important to investigate the carbon sequestration potential and the economic value of carbon sequestration in the SNP. Here, we comprehensively analyzed the characteristics of land use change from 1985 to 2022 based on the land use transfer matrix and land use dynamic degree, calculated the ecosystem carbon storage based on the InVEST model, and estimated the economic value of carbon storage in each period combined with compound interest present value method. The results show that: (1) From 1985 to 2022, carbon stocks generally went through three phases: increasing, stabilizing, and decreasing. (2) Low carbon density areas were concentrated in the Kekexili Natural Reserve in the Yangtze River Source Park and a small part of the Yellow River Source Park and Lancang River Source Park; The high carbon density area was concentrated in the water area and the forest land in the southeast of the Lancang River Source Park. (3) Land use change in SNP had a decisive impact on carbon storage change, and the economic value of carbon storage in SNP continued to increase from 1985 to 2022. In order to provide a scientific basis for the sustainable management of carbon sinks and the reduction of carbon emissions in the SNP area, it is necessary to further study the carbon cycle process, carbon storage and carbon emissions in the region in the future.
{"title":"Estimation of carbon stock and economic value of Sanjiangyuan National Park, China","authors":"Weijing Ma , Shujuan Hou , Wufan Su , Ting Mao , Xiaoya Wang , Tingting Liang","doi":"10.1016/j.ecolind.2024.112856","DOIUrl":"10.1016/j.ecolind.2024.112856","url":null,"abstract":"<div><div>Sanjiangyuan National Park (SNP) is one of China’s national parks with high ecological significance and ecological vulnerability. In order to promote the healthy development of national park ecosystems, it is extremely important to investigate the carbon sequestration potential and the economic value of carbon sequestration in the SNP. Here, we comprehensively analyzed the characteristics of land use change from 1985 to 2022 based on the land use transfer matrix and land use dynamic degree, calculated the ecosystem carbon storage based on the InVEST model, and estimated the economic value of carbon storage in each period combined with compound interest present value method. The results show that: (1) From 1985 to 2022, carbon stocks generally went through three phases: increasing, stabilizing, and decreasing. (2) Low carbon density areas were concentrated in the Kekexili Natural Reserve in the Yangtze River Source Park and a small part of the Yellow River Source Park and Lancang River Source Park; The high carbon density area was concentrated in the water area and the forest land in the southeast of the Lancang River Source Park. (3) Land use change in SNP had a decisive impact on carbon storage change, and the economic value of carbon storage in SNP continued to increase from 1985 to 2022. In order to provide a scientific basis for the sustainable management of carbon sinks and the reduction of carbon emissions in the SNP area, it is necessary to further study the carbon cycle process, carbon storage and carbon emissions in the region in the future.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"169 ","pages":"Article 112856"},"PeriodicalIF":7.0,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142706419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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