Used-habitat calibration plots: a new procedure for validating species distribution, resource selection, and step-selection models

被引:40
|
作者
Fieberg, John R. [1 ]
Forester, James D. [1 ]
Street, Garrett M. [2 ]
Johnson, Douglas H. [3 ]
ArchMiller, Althea A. [1 ]
Matthiopoulos, Jason [4 ]
机构
[1] Univ Minnesota Twin Cities, Dept Fisheries Wildlife & Conservat Biol, St Paul, MN 55108 USA
[2] Mississippi State Univ, Dept Wildlife Fisheries & Aquaculture, Mississippi State, MS 39762 USA
[3] US Geol Survey, Northern Prairie Wildlife Res Ctr, 959 Natl Ctr, Reston, VA 22092 USA
[4] Univ Glasgow, Inst Biodivers Anim Hlth & Comparat Med, Glasgow, Lanark, Scotland
关键词
POINT PROCESS MODELS; WEIGHTED DISTRIBUTIONS; LOGISTIC-REGRESSION; TRANSFERABILITY; ACCURACY; MAXENT; EQUIVALENCE; POPULATIONS; PERFORMANCE; COMPLEXITY;
D O I
10.1111/ecog.03123
中图分类号
X176 [生物多样性保护];
学科分类号
090705 ;
摘要
Species distribution modeling' was recently ranked as one of the top five research fronts' in ecology and the environmental sciences by ISI's Essential Science Indicators, reflecting the importance of predicting how species distributions will respond to anthropogenic change. Unfortunately, species distribution models (SDMs) often perform poorly when applied to novel environments. Compounding on this problem is the shortage of methods for evaluating SDMs (hence, we may be getting our predictions wrong and not even know it). Traditional methods for validating SDMs quantify a model's ability to classify locations as used or unused. Instead, we propose to focus on how well SDMs can predict the characteristics of used locations. This subtle shift in viewpoint leads to a more natural and informative evaluation and validation of models across the entire spectrum of SDMs. Through a series of examples, we show how simple graphical methods can help with three fundamental challenges of habitat modeling: identifying missing covariates, non-linearity, and multicollinearity. Identifying habitat characteristics that are not well-predicted by the model can provide insights into variables affecting the distribution of species, suggest appropriate model modifications, and ultimately improve the reliability and generality of conservation and management recommendations.
引用
收藏
页码:737 / 752
页数:16
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