Species distribution models (SDMs) coupled with metapopulation dynamics models can integrate multiple threats and population-level processes that influence species distributions. However, multiple sources of uncertainties could lead to substantial differences in model outputs and jeopardize risk assessments. We evaluate uncertainties in coupled species distribution–metapopulation dynamics models and focus on two often underappreciated sources of uncertainty: the choice of general circulation model (GCM) and demographic parameter uncertainty of the metapopulation model. We rank the risks associated with potential climate changes and habitat loss on projected range margin dynamics of the Hooded Warbler (Setophaga citrina).
Breeding range of the Hooded Warbler, North America.
Using SDMs, we quantified variability in projected future distributions using four GCMs and a consensus model at the biogeographic scale and assessed the propagation of uncertainty through to metapopulation viability projections. We applied a global sensitivity analysis to the coupled species distribution–metapopulation models to rank the influence of choice of GCM, parameter uncertainty and simulated effects of habitat loss on metapopulation viability, thereby addressing error propagation through the whole modelling process.
The Hooded Warbler range was consistently projected to shift north: choice of GCMs influenced the magnitude of change, and variability was spatially structured. Variability in the choice of GCMs propagated through to metapopulation viability at the northern range boundary. Although viability measures were sensitive to the GCM used, measures of direct habitat loss were more influential. Despite the high ranking of vital rates in the global sensitivity analysis, direct habitat loss had a larger negative influence on extinction risk than potential future climate changes.
This work underscores the importance of a global sensitivity analysis framework applied to coupled models to disentangle the relative influence of uncertainties on projections. The use of multiple GCMs enabled the exploration of a range of possible outcomes relative to the consensus GCM, helping to inform risk estimates. Ranking uncertainties informs the prioritization of management actions for species affected by dynamic anthropogenic threats over multiple spatial scales.