The primary challenge of the contemporary world is to meet accelerating requirements for food.Limited land,competition between crop and livestock farming and climate change are major challenges.Agroforestry offer a fo...The primary challenge of the contemporary world is to meet accelerating requirements for food.Limited land,competition between crop and livestock farming and climate change are major challenges.Agroforestry offer a form of sustainable agriculture through the direct provision of food by raising farmers’incomes and through various ecosystem services.The first essential step in adopting agroforestry is the selection of appropriate tree species that fit local climates.In this paper,we mapped 20 fodder trees and important crops in China using the multi-model ensemble and Ecocrop modelling approach.Relying on the intersectional concept of set theory,the fuzzy logic technique was applied to identify regions where candidate trees could be grown with appropriate crops and livestock.The resulting models provide important insights into the climatic suitability of trees and crops and offer knowledge critical to the proper integration of trees with crops and livestock at specific locations.The results offer support for developing appropriate strategies regarding potential land-use within agroforestry systems in order to maximize ecosystem services and the benefits of sustainable agriculture.Model outputs could easily convert into conventional maps with clearly defined boundaries for site-specific planning for tree-crop-livestock integration.The next step for actualizing an integrated system is to investigate specifically what these different species may contribute to the existing farming systems,quantify the benefits and estimate any possible tradeoffs.展开更多
Large-scale gridded population datasets are usually produced for the year of input census data using a top-down approach and projected backward and forward in time using national growth rates.Such temporal projections...Large-scale gridded population datasets are usually produced for the year of input census data using a top-down approach and projected backward and forward in time using national growth rates.Such temporal projections do not include any subnational variation in population distribution trends and ignore changes in geographical covariates such as urban land cover changes.Improved predictions of population distribution changes over time require the use of a limited number of covariates that are time-invariant or temporally explicit.Here we make use of recently released multi-temporal high-resolution global settlement layers,historical census data and latest developments in population distribution modelling methods to reconstruct population distribution changes over 30 years across the Kenyan Coast.We explore the methodological challenges associated with the production of gridded population distribution time-series in data-scarce countries and show that trade-offs have to be found between spatial and temporal resolutions when selecting the best modelling approach.Strategies used to fill data gaps may vary according to the local context and the objective of the study.This work will hopefully serve as a benchmark for future developments of population distribution time-series that are increasingly required for population-at-risk estimations and spatial modelling in various fields.展开更多
基金“Agroforestry Systems for restoration and bio-industry technology development(grant no:2017YFC0505101)”the Agriculture Science and Technology Innovation Program(ASTIP-IAS07,CAAS-XTCX2016011-01)+2 种基金Research Program of the State Key Laboratory of Animal Nutrition(2004DA125184G1103)Bureau of International Cooperation Chinese Academy of Sciences(151853KYSB20160032)CGIAR Research Program on Climate Change(FTA-FP5).
文摘The primary challenge of the contemporary world is to meet accelerating requirements for food.Limited land,competition between crop and livestock farming and climate change are major challenges.Agroforestry offer a form of sustainable agriculture through the direct provision of food by raising farmers’incomes and through various ecosystem services.The first essential step in adopting agroforestry is the selection of appropriate tree species that fit local climates.In this paper,we mapped 20 fodder trees and important crops in China using the multi-model ensemble and Ecocrop modelling approach.Relying on the intersectional concept of set theory,the fuzzy logic technique was applied to identify regions where candidate trees could be grown with appropriate crops and livestock.The resulting models provide important insights into the climatic suitability of trees and crops and offer knowledge critical to the proper integration of trees with crops and livestock at specific locations.The results offer support for developing appropriate strategies regarding potential land-use within agroforestry systems in order to maximize ecosystem services and the benefits of sustainable agriculture.Model outputs could easily convert into conventional maps with clearly defined boundaries for site-specific planning for tree-crop-livestock integration.The next step for actualizing an integrated system is to investigate specifically what these different species may contribute to the existing farming systems,quantify the benefits and estimate any possible tradeoffs.
基金supported by the Belgian Science Policy(BELSPO)under the Research programme for Earth Obser-vation“STEREO III”[grant number SR/00/304]AJT is supported by a Wellcome Trust Sustaining Health Grant(106866/Z/15/Z)+4 种基金AJT,AS,AEG and FRS are supported by funding from the Bill and Melinda Gates Foundation[grant number OPP1106427],[grant number 1032350][grant number OPP1134076]supported by the Well-come Trust,UK as an intermediate fellow[grant number 095127]RWS is supported by the Wellcome Trust as Prin-cipal Research Fellow[grant number 103602]that also supported CWK.CWK is also grateful to the KEMRI Wellcome Trust Overseas Programme Strategic Award[grant number 084538]for additional support.
文摘Large-scale gridded population datasets are usually produced for the year of input census data using a top-down approach and projected backward and forward in time using national growth rates.Such temporal projections do not include any subnational variation in population distribution trends and ignore changes in geographical covariates such as urban land cover changes.Improved predictions of population distribution changes over time require the use of a limited number of covariates that are time-invariant or temporally explicit.Here we make use of recently released multi-temporal high-resolution global settlement layers,historical census data and latest developments in population distribution modelling methods to reconstruct population distribution changes over 30 years across the Kenyan Coast.We explore the methodological challenges associated with the production of gridded population distribution time-series in data-scarce countries and show that trade-offs have to be found between spatial and temporal resolutions when selecting the best modelling approach.Strategies used to fill data gaps may vary according to the local context and the objective of the study.This work will hopefully serve as a benchmark for future developments of population distribution time-series that are increasingly required for population-at-risk estimations and spatial modelling in various fields.
