Spatial-explicitly mapping of the hotspots and coldspots is a vital link in the priority setting for ecosystem services （ES） conservation. However, little research has identified and tested the compactness and effic...Spatial-explicitly mapping of the hotspots and coldspots is a vital link in the priority setting for ecosystem services （ES） conservation. However, little research has identified and tested the compactness and efficiency of their ES hotspots and coldspots, which may weaken the effectiveness of ecological conservation. In this study, based on the RUSLE model and Getis-Ord Gi＊ statistics, we quantified the variation of annual soil conservation services （SC） and identified the statistically significant hotspots and coldspots in Shaanxi Province of China from 2000 to 2013. The results indicate that, 1） areas with high SC presented a significantly increasing trend as well, while areas with low SC only changed slightly; 2） SC hotspots and coldspots showed an obvious spatial differentiation--the hotspots were mainly spatially ag- gregated in southern Shaanxi, while the coldspots were mainly distributed in the Guanzhong Basin and Sand-windy Plateau; and 3） the identified hotspots had the highest capacity of providing SC, with 29.6% of the total area providing 59.7% of the total service. In contrast, the coldspots occupied 46.3% of the total area, but only provided 17.2% of the total SC. In addition to conserving single ES, the Getis-Ord Gi＊ statistics method can also help identify multi-functional priority areas for conserving multiple ES and biodiversity.展开更多
Context:Without clear understanding of the units used for ecosystem service(ES)mapping,ES assessment accuracy and the practical application of ES knowledge will be hampered.Method:We systematically reviewed 106 studie...Context:Without clear understanding of the units used for ecosystem service(ES)mapping,ES assessment accuracy and the practical application of ES knowledge will be hampered.Method:We systematically reviewed 106 studies over the past 11 years to explore the type,characteristic pattern and deficiencies of mapping units.Result:We proposed that ES mapping units can be categorized into minimal unit for assessing ESs using corresponding indicators and methods,and aggregated unit for analysis and application based on research objectives,and classified the mapping units into five common types.Of the 12 characterizing variables of ES mapping studies,some have been shown to introduce a difference in the selection of mapping units and to exhibit characteristic patterns.We also found that the accuracy of ES assessments based on minimal units was lacking,and aggregated units were insufficient to establish a link between ES knowledge and practice.Conclusion:Herein,we propose possible solutions such as the use of fine spatial resolution grids and the introduction of additional data beyond land cover as supplements to improve the assessment accuracy.To enhance the availability of the results for practice,aggregated units connected with urban planning units should be established at a spatial level suitable for urban management.展开更多
基金National Natural Science Foundation of China, No.41601182 National Social Science Foundation of China, No.14AZD094+3 种基金 National Key Research and Development Plan of China, No.2016YFC0501601 China Postdoctoral Science Foundation, No.2016M592743 Fundamental Research Funds for the Central Universities, No.GK201603078 Key Project of the Ministry of Education of China, No. 15JJD790022Acknowledgments We are grateful to the anonymous reviewers for their constructive advice about the paper, and we also thank Chen Guoyong from the Hunan University, who provided important aid in calculating the annual soil conservation of Shaanxi by MATLAB programming.
文摘Spatial-explicitly mapping of the hotspots and coldspots is a vital link in the priority setting for ecosystem services （ES） conservation. However, little research has identified and tested the compactness and efficiency of their ES hotspots and coldspots, which may weaken the effectiveness of ecological conservation. In this study, based on the RUSLE model and Getis-Ord Gi＊ statistics, we quantified the variation of annual soil conservation services （SC） and identified the statistically significant hotspots and coldspots in Shaanxi Province of China from 2000 to 2013. The results indicate that, 1） areas with high SC presented a significantly increasing trend as well, while areas with low SC only changed slightly; 2） SC hotspots and coldspots showed an obvious spatial differentiation--the hotspots were mainly spatially ag- gregated in southern Shaanxi, while the coldspots were mainly distributed in the Guanzhong Basin and Sand-windy Plateau; and 3） the identified hotspots had the highest capacity of providing SC, with 29.6% of the total area providing 59.7% of the total service. In contrast, the coldspots occupied 46.3% of the total area, but only provided 17.2% of the total SC. In addition to conserving single ES, the Getis-Ord Gi＊ statistics method can also help identify multi-functional priority areas for conserving multiple ES and biodiversity.
基金This work was supported by the China National R&D Program under grant number 2017YFC0505705.
文摘Context:Without clear understanding of the units used for ecosystem service(ES)mapping,ES assessment accuracy and the practical application of ES knowledge will be hampered.Method:We systematically reviewed 106 studies over the past 11 years to explore the type,characteristic pattern and deficiencies of mapping units.Result:We proposed that ES mapping units can be categorized into minimal unit for assessing ESs using corresponding indicators and methods,and aggregated unit for analysis and application based on research objectives,and classified the mapping units into five common types.Of the 12 characterizing variables of ES mapping studies,some have been shown to introduce a difference in the selection of mapping units and to exhibit characteristic patterns.We also found that the accuracy of ES assessments based on minimal units was lacking,and aggregated units were insufficient to establish a link between ES knowledge and practice.Conclusion:Herein,we propose possible solutions such as the use of fine spatial resolution grids and the introduction of additional data beyond land cover as supplements to improve the assessment accuracy.To enhance the availability of the results for practice,aggregated units connected with urban planning units should be established at a spatial level suitable for urban management.
