Spatiotemporal variations and correlation factors of species habitat appropriateness in China from a satellite-based perspective
•Both DHI Cum and DHI Min had strong explanatory power for estimating species richness.•The species habitat appropriateness in the areas with high species habitat appropriateness tended to decrease over time in China.•The species habitat appropriateness in the areas with low species habitat appropri...
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Published in | Ecological indicators Vol. 151; p. 110317 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
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Elsevier Ltd
01.07.2023
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Abstract | •Both DHI Cum and DHI Min had strong explanatory power for estimating species richness.•The species habitat appropriateness in the areas with high species habitat appropriateness tended to decrease over time in China.•The species habitat appropriateness in the areas with low species habitat appropriateness tended to increase over time in in China.•The correlation factors for the variation of biodiversity varied spatially in China.
For development planning and biodiversity management in China, it is crucial to understand the past and present patterns of biodiversity. Using satellite data has proven to be an effective means of characterizing the spatial distribution of species based on the species energy hypothesis, thereby supporting the conservation of biodiversity. This study’s specific purposes included assessing different surrogates for annual species richness in China using MODIS as input for the Dynamic Habitat Indices (DHIs) and analyzing the trend and triggers of variation in DHI from 2003 to 2018. We evaluated the linear relationships between the species richness and different DHIs (containing DHI Cum, cumulative productivity; DHI Min, minimum productivity; DHI Var, intra-annual variation of productivity) in China. Further, we conducted a least squares linear regression analysis to investigate the long-term trend of the best performed DHI, as well as an analysis of correlation factors. Our results demonstrated that both DHI Cum and DHI Min had strong explanatory power for estimating species richness, while DHI Var had a poor performance. Among all individual DHIs, GPP-DHI Cum performed the best. The trend analysis showed that the species habitat appropriateness in the areas with high species habitat appropriateness tended to decrease over time, while that in the areas with low species habitat appropriateness tended to increase over time. We also found that the correlation factors for the variation of biodiversity varied spatially. The decrease of biodiversity in the south and eastern coast of China was associated with the decrease of the solar radiation, the increases of the temperature and precipitation, and the expansion of human footprint. By comparison, the increase of biodiversity in the Tibetan Plateau was associated with the increases of the temperature while that in the Loess Plateau was associated with the increases of the precipitation. In addition to climatic factors, the implementations of ecological restoration projects have also driven increased diversity. Besides an improved understanding of biodiversity dynamics, these findings may help to promote biodiversity conservation and policy making. |
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AbstractList | For development planning and biodiversity management in China, it is crucial to understand the past and present patterns of biodiversity. Using satellite data has proven to be an effective means of characterizing the spatial distribution of species based on the species energy hypothesis, thereby supporting the conservation of biodiversity. This study’s specific purposes included assessing different surrogates for annual species richness in China using MODIS as input for the Dynamic Habitat Indices (DHIs) and analyzing the trend and triggers of variation in DHI from 2003 to 2018. We evaluated the linear relationships between the species richness and different DHIs (containing DHI Cum, cumulative productivity; DHI Min, minimum productivity; DHI Var, intra-annual variation of productivity) in China. Further, we conducted a least squares linear regression analysis to investigate the long-term trend of the best performed DHI, as well as an analysis of correlation factors. Our results demonstrated that both DHI Cum and DHI Min had strong explanatory power for estimating species richness, while DHI Var had a poor performance. Among all individual DHIs, GPP-DHI Cum performed the best. The trend analysis showed that the species habitat appropriateness in the areas with high species habitat appropriateness tended to decrease over time, while that in the areas with low species habitat appropriateness tended to increase over time. We also found that the correlation factors for the variation of biodiversity varied spatially. The decrease of biodiversity in the south and eastern coast of China was associated with the decrease of the solar radiation, the increases of the temperature and precipitation, and the expansion of human footprint. By comparison, the increase of biodiversity in the Tibetan Plateau was associated with the increases of the temperature while that in the Loess Plateau was associated with the increases of the precipitation. In addition to climatic factors, the implementations of ecological restoration projects have also driven increased diversity. Besides an improved understanding of biodiversity dynamics, these findings may help to promote biodiversity conservation and policy making. •Both DHI Cum and DHI Min had strong explanatory power for estimating species richness.•The species habitat appropriateness in the areas with high species habitat appropriateness tended to decrease over time in China.•The species habitat appropriateness in the areas with low species habitat appropriateness tended to increase over time in in China.•The correlation factors for the variation of biodiversity varied spatially in China. For development planning and biodiversity management in China, it is crucial to understand the past and present patterns of biodiversity. Using satellite data has proven to be an effective means of characterizing the spatial distribution of species based on the species energy hypothesis, thereby supporting the conservation of biodiversity. This study’s specific purposes included assessing different surrogates for annual species richness in China using MODIS as input for the Dynamic Habitat Indices (DHIs) and analyzing the trend and triggers of variation in DHI from 2003 to 2018. We evaluated the linear relationships between the species richness and different DHIs (containing DHI Cum, cumulative productivity; DHI Min, minimum productivity; DHI Var, intra-annual variation of productivity) in China. Further, we conducted a least squares linear regression analysis to investigate the long-term trend of the best performed DHI, as well as an analysis of correlation factors. Our results demonstrated that both DHI Cum and DHI Min had strong explanatory power for estimating species richness, while DHI Var had a poor performance. Among all individual DHIs, GPP-DHI Cum performed the best. The trend analysis showed that the species habitat appropriateness in the areas with high species habitat appropriateness tended to decrease over time, while that in the areas with low species habitat appropriateness tended to increase over time. We also found that the correlation factors for the variation of biodiversity varied spatially. The decrease of biodiversity in the south and eastern coast of China was associated with the decrease of the solar radiation, the increases of the temperature and precipitation, and the expansion of human footprint. By comparison, the increase of biodiversity in the Tibetan Plateau was associated with the increases of the temperature while that in the Loess Plateau was associated with the increases of the precipitation. In addition to climatic factors, the implementations of ecological restoration projects have also driven increased diversity. Besides an improved understanding of biodiversity dynamics, these findings may help to promote biodiversity conservation and policy making. |
ArticleNumber | 110317 |
Author | Xie, Tieli Guo, Hancheng Wang, Yanyu Xu, Hanyi Shi, Zhou Wu, Wenqiang Chen, Qianqian |
Author_xml | – sequence: 1 givenname: Yanyu orcidid: 0000-0002-5369-6860 surname: Wang fullname: Wang, Yanyu organization: Institute of Agricultural Remote Sensing and Information Technology Application, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China – sequence: 2 givenname: Wenqiang surname: Wu fullname: Wu, Wenqiang organization: Institute of Agricultural Remote Sensing and Information Technology Application, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China – sequence: 3 givenname: Hancheng surname: Guo fullname: Guo, Hancheng organization: Institute of Agricultural Remote Sensing and Information Technology Application, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China – sequence: 4 givenname: Qianqian surname: Chen fullname: Chen, Qianqian organization: Institute of Agricultural Remote Sensing and Information Technology Application, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China – sequence: 5 givenname: Hanyi surname: Xu fullname: Xu, Hanyi organization: Institute of Agricultural Remote Sensing and Information Technology Application, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China – sequence: 6 givenname: Tieli surname: Xie fullname: Xie, Tieli organization: Institute of Agricultural Remote Sensing and Information Technology Application, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China – sequence: 7 givenname: Zhou surname: Shi fullname: Shi, Zhou email: shizhou@zju.edu.cn organization: Institute of Agricultural Remote Sensing and Information Technology Application, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China |
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Keywords | Spatiotemporal variation Biodiversity China Species richness MODIS |
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Snippet | •Both DHI Cum and DHI Min had strong explanatory power for estimating species richness.•The species habitat appropriateness in the areas with high species... For development planning and biodiversity management in China, it is crucial to understand the past and present patterns of biodiversity. Using satellite data... |
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Title | Spatiotemporal variations and correlation factors of species habitat appropriateness in China from a satellite-based perspective |
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