Mechanistic niche modelling: combining physiological and spatial data to predict species' ranges

被引:1601
作者
Kearney, Michael [1 ]
Porter, Warren [2 ]
机构
[1] Univ Melbourne, Dept Zool, Melbourne, Vic 3010, Australia
[2] Univ Wisconsin, Dept Zool, Madison, WI 53706 USA
基金
澳大利亚研究理事会;
关键词
Biophysical ecology; climate; fundamental niche; geographical information systems; microclimate; physiological ecology; realized niche; species distribution modelling; REBUILDING COMMUNITY ECOLOGY; BODY-TEMPERATURE; CLIMATE-CHANGE; CANE TOAD; ENERGETICS; DISTRIBUTIONS; POPULATION; HABITAT; THERMOREGULATION; CONSERVATION;
D O I
10.1111/j.1461-0248.2008.01277.x
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
Species distribution models (SDMs) use spatial environmental data to make inferences on species' range limits and habitat suitability. Conceptually, these models aim to determine and map components of a species' ecological niche through space and time, and they have become important tools in pure and applied ecology and evolutionary biology. Most approaches are correlative in that they statistically link spatial data to species distribution records. An alternative strategy is to explicitly incorporate the mechanistic links between the functional traits of organisms and their environments into SDMs. Here, we review how the principles of biophysical ecology can be used to link spatial data to the physiological responses and constraints of organisms. This provides a mechanistic view of the fundamental niche which can then be mapped to the landscape to infer range constraints. We show how physiologically based SDMs can be developed for different organisms in different environmental contexts. Mechanistic SDMs have different strengths and weaknesses to correlative approaches, and there are many exciting and unexplored prospects for integrating the two approaches. As physiological knowledge becomes better integrated into SDMs, we will make more robust predictions of range shifts in novel or non-equilibrium contexts such as invasions, translocations, climate change and evolutionary shifts.
引用
收藏
页码:334 / 350
页数:17
相关论文
共 91 条
[1]   Growth, seasonality, and lizard life histories: Age and size at maturity [J].
Adolph, SC ;
Porter, WP .
OIKOS, 1996, 77 (02) :267-278
[2]   TEMPERATURE, ACTIVITY, AND LIZARD LIFE-HISTORIES [J].
ADOLPH, SC ;
PORTER, WP .
AMERICAN NATURALIST, 1993, 142 (02) :273-295
[3]  
[Anonymous], 1986, The Ecological Web: More on the Distribution and Abundance of Animals
[4]   The importance of biotic interactions for modelling species distributions under climate change [J].
Araujo, Miguel B. ;
Luoto, Miska .
GLOBAL ECOLOGY AND BIOGEOGRAPHY, 2007, 16 (06) :743-753
[5]   Species distribution models and ecological theory: A critical assessment and some possible new approaches [J].
Austin, Mike .
ECOLOGICAL MODELLING, 2007, 200 (1-2) :1-19
[6]   Spatial prediction of species distribution: an interface between ecological theory and statistical modelling [J].
Austin, MP .
ECOLOGICAL MODELLING, 2002, 157 (2-3) :101-118
[7]  
Bird R B., 2002, Transportphenomena
[8]   Numerical investigation of the hydrodynamics of carangiform swimming in the transitional and inertial flow regimes [J].
Borazjani, Iman ;
Sotiropoulos, Fotis .
JOURNAL OF EXPERIMENTAL BIOLOGY, 2008, 211 (10) :1541-1558
[9]   Linking traits to energetics and population dynamics to predict lizard ranges in changing environments [J].
Buckley, Lauren B. .
AMERICAN NATURALIST, 2008, 171 (01) :E1-E19
[10]  
Campbell G.S., 1998, Environmental Biophysics, V2nd