TY  - JOUR
A1  - Pagel, Jörn
A1  - Schurr, Frank Martin
T1  - Forecasting species ranges by statistical estimation of ecological niches and spatial population dynamics
JF  - Global ecology and biogeography : a journal of macroecology
N2  - Aim The study and prediction of speciesenvironment relationships is currently mainly based on species distribution models. These purely correlative models neglect spatial population dynamics and assume that species distributions are in equilibrium with their environment. This causes biased estimates of species niches and handicaps forecasts of range dynamics under environmental change. Here we aim to develop an approach that statistically estimates process-based models of range dynamics from data on species distributions and permits a more comprehensive quantification of forecast uncertainties.
 Innovation We present an approach for the statistical estimation of process-based dynamic range models (DRMs) that integrate Hutchinson's niche concept with spatial population dynamics. In a hierarchical Bayesian framework the environmental response of demographic rates, local population dynamics and dispersal are estimated conditional upon each other while accounting for various sources of uncertainty. The method thus: (1) jointly infers species niches and spatiotemporal population dynamics from occurrence and abundance data, and (2) provides fully probabilistic forecasts of future range dynamics under environmental change. In a simulation study, we investigate the performance of DRMs for a variety of scenarios that differ in both ecological dynamics and the data used for model estimation.
 Main conclusions Our results demonstrate the importance of considering dynamic aspects in the collection and analysis of biodiversity data. In combination with informative data, the presented framework has the potential to markedly improve the quantification of ecological niches, the process-based understanding of range dynamics and the forecasting of species responses to environmental change. It thereby strengthens links between biogeography, population biology and theoretical and applied ecology.
KW  - Biogeography
KW  - ecological forecasts
KW  - global change
KW  - hierarchical Bayesian statistics
KW  - long-distance dispersal
KW  - niche theory
KW  - process-based model
KW  - range shifts
KW  - spatial demography
KW  - species distribution modelling
Y1  - 2012
U6  - https://doi.org/10.1111/j.1466-8238.2011.00663.x
SN  - 1466-822X
VL  - 21
IS  - 2
SP  - 293
EP  - 304
PB  - Wiley-Blackwell
CY  - Malden
ER  -