Leafy spurge （Euphorbia esula L.） has substantial negative effects on grassland biodiversity, productivity, and economic benefit in North America. To predict these negative impacts, we need an appropriate plant-spre...Leafy spurge （Euphorbia esula L.） has substantial negative effects on grassland biodiversity, productivity, and economic benefit in North America. To predict these negative impacts, we need an appropriate plant-spread model which can simulate the response of an invading population to different control strategies. In this study, using a stochastic map lattice approach we generated a spatially explicitly stochastic process-based model to simulate dispersal trajectories of leafy spurge under various control scenarios. The model integrated dispersal curve, propagule pressure, and population growth of leafy spurge at local and short-temporal scales to capture spread features of leafy spurge at large spatial and long-temporal scales. Our results suggested that narrow-, medium-, and fat-tailed kernels did not differ in their ability to predict spread, in contrast to previous works. For all kernels, Allee effects were significantly present and could explain the lag phase （three decades） before leafy spurge spread accelerated. When simulating from the initial stage of introduction, Allee effects were critical in predicting spread rate of leafy spurge, because the prediction could be seriously affected by the low density period of leafy spurge community. No Allee effects models were not able to simulate spread rate well in this circumstance. When applying control strategies to the current distribution, Allee effects could stop the spread of leafy spurge; no Allee effects models, however, were able to slow but not stop the spread. The presence of Allee effects had significant ramifications on the efficiencies of control strategies. For both Allee and no Allee effects models, the later that control strategies were implemented, the more effort had to be input to achieve similar control results.展开更多
Deciphering biogeographic patterns of microorganisms is important for evaluating the maintenance of microbial diversity with respect to the ecosystem functions they drives.However,ecological processes shaping distribu...Deciphering biogeographic patterns of microorganisms is important for evaluating the maintenance of microbial diversity with respect to the ecosystem functions they drives.However,ecological processes shaping distribution patterns of microorganisms across large spatial‐scale watersheds remain largely unknown.Using Illumina sequencing and multiple statistical methods,we characterized distribution patterns and maintenance diversity of microorganisms(i.e.,archaea,bacteria,and fungi)in soils and sediments along the Yangtze River.Distinct microbial distribution patterns were found between soils and sediments,and microbial community similarity significantly decreased with increasing geographical distance.Physicochemical properties showed a larger effect on microbial community composition than geospatial and climatic factors.Archaea and fungi displayed stronger species replacements and weaker environmental constraints in soils than that in sediments,but opposite for bacteria.Archaea,bacteria,and fungi in soils showed broader environmental breadths and stronger phylogenetic signals compared to those in sediments,suggesting stronger environmental adaptation.Stochasticity dominated community assemblies of archaea and fungi in soils and sediments,whereas determinism dominated bacterial community assembly.Our results have therefore highlighted distinct microbial distribution patterns and diversity maintenance mechanisms between soils and sediments,and emphasized important roles of species replacement,environmental adaptability,and ecological assembly processes on microbial landscape.Our findings are helpful in predicting loss of microbial diversity in the Yangtze River Basin,and might assist the establishment of environmental policies for protecting fragile watersheds.展开更多
基金funded by the Integrating Economics and Biology for Bioeconomic Risk Assessment/Management of Invasive Species in Agriculture (Economic Research Service/USDA)
文摘Leafy spurge （Euphorbia esula L.） has substantial negative effects on grassland biodiversity, productivity, and economic benefit in North America. To predict these negative impacts, we need an appropriate plant-spread model which can simulate the response of an invading population to different control strategies. In this study, using a stochastic map lattice approach we generated a spatially explicitly stochastic process-based model to simulate dispersal trajectories of leafy spurge under various control scenarios. The model integrated dispersal curve, propagule pressure, and population growth of leafy spurge at local and short-temporal scales to capture spread features of leafy spurge at large spatial and long-temporal scales. Our results suggested that narrow-, medium-, and fat-tailed kernels did not differ in their ability to predict spread, in contrast to previous works. For all kernels, Allee effects were significantly present and could explain the lag phase （three decades） before leafy spurge spread accelerated. When simulating from the initial stage of introduction, Allee effects were critical in predicting spread rate of leafy spurge, because the prediction could be seriously affected by the low density period of leafy spurge community. No Allee effects models were not able to simulate spread rate well in this circumstance. When applying control strategies to the current distribution, Allee effects could stop the spread of leafy spurge; no Allee effects models, however, were able to slow but not stop the spread. The presence of Allee effects had significant ramifications on the efficiencies of control strategies. For both Allee and no Allee effects models, the later that control strategies were implemented, the more effort had to be input to achieve similar control results.
基金supported by the National Natural Science Foundation of China(42107147)Youth Innovation Promotion Association of the Chinese Academy of Sciences(2017388)+1 种基金National Science and Technology Fundamental Resources Investigation Program of China(2019FY100603)the Open Foundation of the State Key Laboratory of Urban and Regional Ecology of China(SKLURE2021-2-5).
文摘Deciphering biogeographic patterns of microorganisms is important for evaluating the maintenance of microbial diversity with respect to the ecosystem functions they drives.However,ecological processes shaping distribution patterns of microorganisms across large spatial‐scale watersheds remain largely unknown.Using Illumina sequencing and multiple statistical methods,we characterized distribution patterns and maintenance diversity of microorganisms(i.e.,archaea,bacteria,and fungi)in soils and sediments along the Yangtze River.Distinct microbial distribution patterns were found between soils and sediments,and microbial community similarity significantly decreased with increasing geographical distance.Physicochemical properties showed a larger effect on microbial community composition than geospatial and climatic factors.Archaea and fungi displayed stronger species replacements and weaker environmental constraints in soils than that in sediments,but opposite for bacteria.Archaea,bacteria,and fungi in soils showed broader environmental breadths and stronger phylogenetic signals compared to those in sediments,suggesting stronger environmental adaptation.Stochasticity dominated community assemblies of archaea and fungi in soils and sediments,whereas determinism dominated bacterial community assembly.Our results have therefore highlighted distinct microbial distribution patterns and diversity maintenance mechanisms between soils and sediments,and emphasized important roles of species replacement,environmental adaptability,and ecological assembly processes on microbial landscape.Our findings are helpful in predicting loss of microbial diversity in the Yangtze River Basin,and might assist the establishment of environmental policies for protecting fragile watersheds.
