FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2912487284> ?p ?o ?g. }

• W2912487284 endingPage "183" @default.
• W2912487284 startingPage "162" @default.
• W2912487284 abstract "The ecosystem services provision is constantly under threat by anthropogenic pressures, especially which is mainly related to land use changes. A solution proposed to address these issues is the implementation of spatial characteristics of land uses and ecological compensation (based on Payment for Ecosystem Services) programs. In this study, we developed a framework for analyzing the spatial characteristics of land uses and calculating ecological compensation from 2000 to 2015 in Sichuan Province, China. We firstly examined the utility of lacunarity analysis for detecting spatial characteristic scales of pattern of land uses. Due to large-scale and regular distribution, the spatial heterogeneity of cropland, woodland and grassland were higher than that of water body, construction land and unused land. We then investigated changes in ecosystem services in response to land use change through assignment of per unit area ecosystem service value method. The total ecosystem service value is about 10,780 billion yuan·year−1, and the woodland and grassland ecosystems contributed more to the total ecosystem service value. The critical areas (with higher ecosystem service value) for management purpose were identified depending on the heterogeneity of use services learned from spatially explicit measures. Considering the changed relationship between social and economic indicators and ecosystem service value based on spatial visualization and analysis, we finally constructed a quantitative estimate model for ecological compensation taking city (state) as study unit, and determined standard value so as to evaluate ecological compensation from 2000 to 2015. Spatial differences of the ecological compensation were significant among all the cities (states). The average payment standards of ecological compensation based on the population, ecological compensation based on city (state) area, and corrected ecological compensation were − 117.10 billion yuan, 4.41E-13 billion yuan, and − 58.55 billion yuan, respectively. The negative values suggested that the stakeholders of Sichuan Province should pay for ecological compensation, and the positive value meant the residents in the Sichuan Province can obtain the amount of ecological compensation. This proposed innovative framework provides a better understanding of spatial characteristic scales of land uses and enables evaluation of the ecological integrity of landscapes. It also fills up the gap in the field of quantitative evaluation of regional ecological compensation and provides a feasible way to reconcile the conflicts among benefits in the economic, social and ecological sectors." @default.
• W2912487284 created "2019-02-21" @default.
• W2912487284 creator A5018381716 @default.
• W2912487284 creator A5037989560 @default.
• W2912487284 date "2019-03-01" @default.
• W2912487284 modified "2023-10-12" @default.
• W2912487284 title "Spatial characteristics of land uses and ecological compensations based on payment for ecosystem services model from 2000 to 2015 in Sichuan Province, China" @default.
• W2912487284 cites W1582174288 @default.
• W2912487284 cites W1781571684 @default.
• W2912487284 cites W1788532006 @default.
• W2912487284 cites W1911824780 @default.
• W2912487284 cites W1923089275 @default.
• W2912487284 cites W1950004460 @default.
• W2912487284 cites W1963746476 @default.
• W2912487284 cites W1964798793 @default.
• W2912487284 cites W1971985217 @default.
• W2912487284 cites W1973814609 @default.
• W2912487284 cites W1975051557 @default.
• W2912487284 cites W1979793764 @default.
• W2912487284 cites W1979995047 @default.
• W2912487284 cites W1981223952 @default.
• W2912487284 cites W1981294824 @default.
• W2912487284 cites W1986652995 @default.
• W2912487284 cites W1988835035 @default.
• W2912487284 cites W2003015672 @default.
• W2912487284 cites W2004515015 @default.
• W2912487284 cites W2007298029 @default.
• W2912487284 cites W2014122417 @default.
• W2912487284 cites W2017142214 @default.
• W2912487284 cites W2020775234 @default.
• W2912487284 cites W2021512029 @default.
• W2912487284 cites W2027016436 @default.
• W2912487284 cites W2033045233 @default.
• W2912487284 cites W2034596884 @default.
• W2912487284 cites W2036370542 @default.
• W2912487284 cites W2038918352 @default.
• W2912487284 cites W2042358007 @default.
• W2912487284 cites W2045614401 @default.
• W2912487284 cites W2053997119 @default.
• W2912487284 cites W2054484622 @default.
• W2912487284 cites W2064359938 @default.
• W2912487284 cites W2069647463 @default.
• W2912487284 cites W2076898266 @default.
• W2912487284 cites W2078842478 @default.
• W2912487284 cites W2083840127 @default.
• W2912487284 cites W2085407238 @default.
• W2912487284 cites W2096136125 @default.
• W2912487284 cites W2112551164 @default.
• W2912487284 cites W2112955002 @default.
• W2912487284 cites W2117362873 @default.
• W2912487284 cites W2126778274 @default.
• W2912487284 cites W2130692480 @default.
• W2912487284 cites W2130910871 @default.
• W2912487284 cites W2135117561 @default.
• W2912487284 cites W2136579750 @default.
• W2912487284 cites W2142684499 @default.
• W2912487284 cites W2142865131 @default.
• W2912487284 cites W2152369329 @default.
• W2912487284 cites W2160370275 @default.
• W2912487284 cites W2171458065 @default.
• W2912487284 cites W2176637474 @default.
• W2912487284 cites W2181833317 @default.
• W2912487284 cites W2323248505 @default.
• W2912487284 cites W2514427236 @default.
• W2912487284 cites W2560499498 @default.
• W2912487284 cites W2632887393 @default.
• W2912487284 cites W2745184671 @default.
• W2912487284 cites W2746485780 @default.
• W2912487284 cites W2754451323 @default.
• W2912487284 cites W415441523 @default.
• W2912487284 doi "https://doi.org/10.1016/j.ecoinf.2019.01.001" @default.
• W2912487284 hasPublicationYear "2019" @default.
• W2912487284 type Work @default.
• W2912487284 sameAs 2912487284 @default.
• W2912487284 citedByCount "41" @default.
• W2912487284 countsByYear W29124872842019 @default.
• W2912487284 countsByYear W29124872842020 @default.
• W2912487284 countsByYear W29124872842021 @default.
• W2912487284 countsByYear W29124872842022 @default.
• W2912487284 countsByYear W29124872842023 @default.
• W2912487284 crossrefType "journal-article" @default.
• W2912487284 hasAuthorship W2912487284A5018381716 @default.
• W2912487284 hasAuthorship W2912487284A5037989560 @default.
• W2912487284 hasConcept C10138342 @default.
• W2912487284 hasConcept C107826830 @default.
• W2912487284 hasConcept C110872660 @default.
• W2912487284 hasConcept C122637931 @default.
• W2912487284 hasConcept C144133560 @default.
• W2912487284 hasConcept C145097563 @default.
• W2912487284 hasConcept C145420912 @default.
• W2912487284 hasConcept C158709400 @default.
• W2912487284 hasConcept C162853370 @default.
• W2912487284 hasConcept C180478619 @default.
• W2912487284 hasConcept C18903297 @default.
• W2912487284 hasConcept C203174812 @default.
• W2912487284 hasConcept C205649164 @default.
• W2912487284 hasConcept C2777483010 @default.
• W2912487284 hasConcept C2780378061 @default.

• next