Can mechanism inform species' distribution models?

被引:443
作者
Buckley, Lauren B. [1 ]
Urban, Mark C. [2 ]
Angilletta, Michael J. [3 ]
Crozier, Lisa G. [4 ]
Rissler, Leslie J. [5 ]
Sears, Michael W. [6 ]
机构
[1] Univ N Carolina, Dept Biol, Chapel Hill, NC 27599 USA
[2] Univ Connecticut, Storrs, CT 06269 USA
[3] Indiana State Univ, Dept Biol, Terre Haute, IN 47809 USA
[4] NOAA Fisheries, NW Fisheries Sci Ctr, Seattle, WA 98112 USA
[5] Univ Alabama, Dept Biol Sci, Tuscaloosa, AL 35487 USA
[6] Bryn Mawr Coll, Dept Biol, Bryn Mawr, PA 19010 USA
基金
美国国家科学基金会;
关键词
Biophysical model; climate change; climate envelope model; demography; fundamental niche; physiology; realized niche; species' range model; LIZARD SCELOPORUS-UNDULATUS; CLIMATE-CHANGE; BIOTIC INTERACTIONS; IMPROVE PREDICTION; LANDSCAPE SCALE; RANGE SHIFTS; NICHE; PHYLOGEOGRAPHY; TEMPERATURE; POPULATIONS;
D O I
10.1111/j.1461-0248.2010.01479.x
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
P>Two major approaches address the need to predict species distributions in response to environmental changes. Correlative models estimate parameters phenomenologically by relating current distributions to environmental conditions. By contrast, mechanistic models incorporate explicit relationships between environmental conditions and organismal performance, estimated independently of current distributions. Mechanistic approaches include models that translate environmental conditions into biologically relevant metrics (e.g. potential duration of activity), models that capture environmental sensitivities of survivorship and fecundity, and models that use energetics to link environmental conditions and demography. We compared how two correlative and three mechanistic models predicted the ranges of two species: a skipper butterfly (Atalopedes campestris) and a fence lizard (Sceloporus undulatus). Correlative and mechanistic models performed similarly in predicting current distributions, but mechanistic models predicted larger range shifts in response to climate change. Although mechanistic models theoretically should provide more accurate distribution predictions, there is much potential for improving their flexibility and performance.
引用
收藏
页码:1041 / 1054
页数:14
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