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DOI10.1111/ele.13348
Forecasting species range dynamics with process-explicit models: matching methods to applications
Briscoe, Natalie J.1; Elith, Jane1; Salguero-Gomez, Roberto2,3,4; Lahoz-Monfort, Jose J.1; Camac, James S.1; Giljohann, Katherine M.1; Holden, Matthew H.3; Hradsky, Bronwyn A.1; Kearney, Michael R.1; McMahon, Sean M.5; Phillips, Ben L.1; Regan, Tracey J.1,6; Rhodes, Jonathan R.7; Vesk, Peter A.1; Wintle, Brendan A.1; Yen, Jian D. L.1; Guillera-Arroita, Gurutzeta1
2019-07-29
发表期刊ECOLOGY LETTERS
ISSN1461-023X
EISSN1461-0248
出版年2019
卷号22期号:11页码:1940-1956
文章类型Review
语种英语
国家Australia; England; Germany; USA
英文摘要

Knowing where species occur is fundamental to many ecological and environmental applications. Species distribution models (SDMs) are typically based on correlations between species occurrence data and environmental predictors, with ecological processes captured only implicitly. However, there is a growing interest in approaches that explicitly model processes such as physiology, dispersal, demography and biotic interactions. These models are believed to offer more robust predictions, particularly when extrapolating to novel conditions. Many process-explicit approaches are now available, but it is not clear how we can best draw on this expanded modelling toolbox to address ecological problems and inform management decisions. Here, we review a range of process-explicit models to determine their strengths and limitations, as well as their current use. Focusing on four common applications of SDMs - regulatory planning, extinction risk, climate refugia and invasive species - we then explore which models best meet management needs. We identify barriers to more widespread and effective use of process-explicit models and outline how these might be overcome. As well as technical and data challenges, there is a pressing need for more thorough evaluation of model predictions to guide investment in method development and ensure the promise of these new approaches is fully realised.


英文关键词Demography mechanistic population dynamics process-based models species distribution model
领域资源环境
收录类别SCI-E
WOS记录号WOS:000478534900001
WOS关键词INTEGRAL PROJECTION MODELS ; CLIMATE-CHANGE ; POPULATION-DYNAMICS ; EXTINCTION RISK ; SPATIAL SPREAD ; R-PACKAGE ; METAPOPULATION VIABILITY ; ENVIRONMENTAL-CHANGE ; MECHANISTIC MODELS ; OCCUPANCY MODELS
WOS类目Ecology
WOS研究方向Environmental Sciences & Ecology
引用统计
文献类型期刊论文
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/185346
专题资源环境科学
作者单位1.Univ Melbourne, Sch Biosci, Melbourne, Vic, Australia;
2.Univ Oxford, Dept Zool, Oxford, England;
3.Univ Queensland, Sch Biol Sci, Brisbane, Qld, Australia;
4.Max Planck Inst Demog Res, Rostock, Germany;
5.Smithsonian Environm Res Ctr, Forest Global Earth Observ, POB 28, Edgewater, MD 21037 USA;
6.Arthur Rylah Inst Environm Res, Dept Environm Land Water & Planning, Heidelberg, Vic, Australia;
7.Univ Queensland, Sch Earth & Environm Sci, Brisbane, Qld, Australia
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GB/T 7714
Briscoe, Natalie J.,Elith, Jane,Salguero-Gomez, Roberto,et al. Forecasting species range dynamics with process-explicit models: matching methods to applications[J]. ECOLOGY LETTERS,2019,22(11):1940-1956.
APA Briscoe, Natalie J..,Elith, Jane.,Salguero-Gomez, Roberto.,Lahoz-Monfort, Jose J..,Camac, James S..,...&Guillera-Arroita, Gurutzeta.(2019).Forecasting species range dynamics with process-explicit models: matching methods to applications.ECOLOGY LETTERS,22(11),1940-1956.
MLA Briscoe, Natalie J.,et al."Forecasting species range dynamics with process-explicit models: matching methods to applications".ECOLOGY LETTERS 22.11(2019):1940-1956.
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