Land use changes are a direct consequence of interactions between humans and nature.Analysing the spatial and temporal changes in habitat quality brought about by land use change can provide a scientific basis for eco...Land use changes are a direct consequence of interactions between humans and nature.Analysing the spatial and temporal changes in habitat quality brought about by land use change can provide a scientific basis for ecological protection and land planning.Based on the analysis of land use change from 1990 to 2010 in Northeast China,we used the InVEST(integrated valuation of ecosystem services and trade-offs)module to evaluate habitat quality based on watershed subdivision.The results show that:(1)the main land use changes from 1990 to 2010 were the transition from grasslands and forest lands to agricultural lands,which led to a decrease in connectivity of landscape and an increase in fragmentation;(2)areas of high habitat quality were distributed north of the Greater Khingan Mountains,the region of the Lesser Khingan Mountains and east of the Changbai Mountains,while the central plain had low habitat quality;(3)agricultural lands had the largest effect on habitat degradation among all habitat threats.During these 2 decades,the contribution of agricultural lands to habitat degradation were 43.4%in 1990,44.6%in 2000 and 43.9%in 2010;and,(4)at a landscape scale,patch density and splitting index present noticeable negative correlations with habitat quality index.Habitat quality was significantly affected by landscape fragmentation and decreased connectivity.展开更多
The Natural Forest Protection Program(NFPP)is one of the key ecological forestry programs in China.It not only facilitates the improvement of forest ecological quality in NFPP areas,but also plays a significant role i...The Natural Forest Protection Program(NFPP)is one of the key ecological forestry programs in China.It not only facilitates the improvement of forest ecological quality in NFPP areas,but also plays a significant role in increasing the carbon storage of forest ecosystems.The program covers 17 provinces,autonomous regions,and municipalities with correspondingly diverse forest resources and environments,ecological features,engineering measures and forest management regimes,all of which affect regional carbon storage.In this study,volume of timber harvest,tending area,pest-infested forest,firedamaged forest,reforestation,and average annual precipitation,and temperature were evaluated as factors that influence carbon storage.We developed a vector autoregression model for these seven indicators and we studied the dominant factors of carbon storage in the areas covered by NFPP.Timber harvest was the dominant factorinfluencing carbon storage in the Yellow and Yangtze River basins.Reforestation contributed most to carbon storage in the state-owned forest region in Xinjiang.In state-owned forest regions of Heilongjiang and Jilin Provinces,the dominant factors were forest fires and forest cultivation,respectively.For the enhancement of carbon sequestration capacity,a longer rotation period and a smaller timber harvest are recommended for the Yellow and Yangtze River basins.Trees should be planted in stateowned forests in Xinjiang.Forest fires should be prevented in state-owned forests in Heilongjiang,and greater forest tending efforts should be made in the state-owned forests in Jilin.展开更多
With the development of the Internet of Things(IoT),spatio-temporal crowdsourcing(mobile crowdsourcing)has become an emerging paradigm for addressing location-based sensing tasks.However,the delay caused by network tr...With the development of the Internet of Things(IoT),spatio-temporal crowdsourcing(mobile crowdsourcing)has become an emerging paradigm for addressing location-based sensing tasks.However,the delay caused by network transmission has led to low data processing efficiency.Fortunately,edge computing can solve this problem,effectively reduce the delay of data transmission,and improve data processing capacity,so that the crowdsourcing platform can make better decisions faster.Therefore,this paper combines spatio-temporal crowdsourcing and edge computing to study the Multi-Objective Optimization Task Assignment(MOO-TA)problem in the edge computing environment.The proposed online incentive mechanism considers the task difficulty attribute to motivate crowd workers to perform sensing tasks in the unpopular area.In this paper,the Weighted and Multi-Objective Particle Swarm Combination(WAMOPSC)algorithm is proposed to maximize both platform’s and crowd workers’utility,so as to maximize social welfare.The algorithm combines the traditional Linear Weighted Summation(LWS)algorithm and Multi-Objective Particle Swarm Optimization(MOPSO)algorithm to find pareto optimal solutions of multi-objective optimization task assignment problem as much as possible for crowdsourcing platform to choose.Through comparison experiments on real data sets,the effectiveness and feasibility of the proposed method are evaluated.展开更多
基金supported by the Key Research Program from Chinese Academy of Sciences(KFZD-SW-305-001)Special Research Institute Project(Y5YZX151YD)
文摘Land use changes are a direct consequence of interactions between humans and nature.Analysing the spatial and temporal changes in habitat quality brought about by land use change can provide a scientific basis for ecological protection and land planning.Based on the analysis of land use change from 1990 to 2010 in Northeast China,we used the InVEST(integrated valuation of ecosystem services and trade-offs)module to evaluate habitat quality based on watershed subdivision.The results show that:(1)the main land use changes from 1990 to 2010 were the transition from grasslands and forest lands to agricultural lands,which led to a decrease in connectivity of landscape and an increase in fragmentation;(2)areas of high habitat quality were distributed north of the Greater Khingan Mountains,the region of the Lesser Khingan Mountains and east of the Changbai Mountains,while the central plain had low habitat quality;(3)agricultural lands had the largest effect on habitat degradation among all habitat threats.During these 2 decades,the contribution of agricultural lands to habitat degradation were 43.4%in 1990,44.6%in 2000 and 43.9%in 2010;and,(4)at a landscape scale,patch density and splitting index present noticeable negative correlations with habitat quality index.Habitat quality was significantly affected by landscape fragmentation and decreased connectivity.
基金funded by Special Research Project of Institute of Applied Ecology,CAS(No.Y5YZX151YD)Key Laboratory of Forest Ecology and Management,Institute of Applied Ecology,CAS(No.LFEM2016-05)
文摘The Natural Forest Protection Program(NFPP)is one of the key ecological forestry programs in China.It not only facilitates the improvement of forest ecological quality in NFPP areas,but also plays a significant role in increasing the carbon storage of forest ecosystems.The program covers 17 provinces,autonomous regions,and municipalities with correspondingly diverse forest resources and environments,ecological features,engineering measures and forest management regimes,all of which affect regional carbon storage.In this study,volume of timber harvest,tending area,pest-infested forest,firedamaged forest,reforestation,and average annual precipitation,and temperature were evaluated as factors that influence carbon storage.We developed a vector autoregression model for these seven indicators and we studied the dominant factors of carbon storage in the areas covered by NFPP.Timber harvest was the dominant factorinfluencing carbon storage in the Yellow and Yangtze River basins.Reforestation contributed most to carbon storage in the state-owned forest region in Xinjiang.In state-owned forest regions of Heilongjiang and Jilin Provinces,the dominant factors were forest fires and forest cultivation,respectively.For the enhancement of carbon sequestration capacity,a longer rotation period and a smaller timber harvest are recommended for the Yellow and Yangtze River basins.Trees should be planted in stateowned forests in Xinjiang.Forest fires should be prevented in state-owned forests in Heilongjiang,and greater forest tending efforts should be made in the state-owned forests in Jilin.
基金supported in part by the National Natural Science Foundation of China under Grant 61822602,Grant 61772207,Grant 61802331,Grant 61572418,Grant 61602399,Grant 61702439 and Grant 61773331the China Postdoctoral Science Foundation under Grant 2019T120732 and Grant 2017M622691+1 种基金the National Science Foundation(NSF)under Grant 1704287,Grant 1252292 and Grant 1741277the Natural Science Foundation of Shandong Province under Grant ZR2016FM42.
文摘With the development of the Internet of Things(IoT),spatio-temporal crowdsourcing(mobile crowdsourcing)has become an emerging paradigm for addressing location-based sensing tasks.However,the delay caused by network transmission has led to low data processing efficiency.Fortunately,edge computing can solve this problem,effectively reduce the delay of data transmission,and improve data processing capacity,so that the crowdsourcing platform can make better decisions faster.Therefore,this paper combines spatio-temporal crowdsourcing and edge computing to study the Multi-Objective Optimization Task Assignment(MOO-TA)problem in the edge computing environment.The proposed online incentive mechanism considers the task difficulty attribute to motivate crowd workers to perform sensing tasks in the unpopular area.In this paper,the Weighted and Multi-Objective Particle Swarm Combination(WAMOPSC)algorithm is proposed to maximize both platform’s and crowd workers’utility,so as to maximize social welfare.The algorithm combines the traditional Linear Weighted Summation(LWS)algorithm and Multi-Objective Particle Swarm Optimization(MOPSO)algorithm to find pareto optimal solutions of multi-objective optimization task assignment problem as much as possible for crowdsourcing platform to choose.Through comparison experiments on real data sets,the effectiveness and feasibility of the proposed method are evaluated.
