Sensitivity analyses of spatial population viability analysis models for species at risk and habitat conservation planning.
Population viability analysis (PVA) is an effective framework for modeling species- and habitat-recovery efforts, but uncertainty in parameter estimates and model structure can lead to unreliable predictions. Integrating complex and often uncertain information into spatial PVA models requires that comprehensive sensitivity analyses be applied to explore the influence of spatial and nonspatial parameters on model predictions. We reviewed 87 analyses of spatial demographic PVA models of plants and animals to identify common approaches to sensitivity analysis in recent publications. In contrast to best practices recommended in the broader modeling community, sensitivity analyses of spatial PVAs were typically ad hoc, inconsistent, and difficult to compare. Most studies applied local approaches to sensitivity analyses, but few varied multiple parameters simultaneously. A lack of standards for sensitivity analysis and reporting in spatial PVAs has the potential to compromise the ability to learn collectively from PVA results, accurately interpret results in cases where model relationships include nonlinearities and interactions, prioritize monitoring and management actions, and ensure conservation-planning decisions are robust to uncertainties in spatial and nonspatial parameters. Our review underscores the need to develop tools for global sensitivity analysis and apply these to spatial PVA.
Naujokaitis-Lewis
Ilona R
IR
Centre for Applied Conservation Research, Faculty of Forestry, University of British Columbia, Forest Sciences Building, 2424 Main Mall, Vancouver, British Columbia V6T 1Z4, Canada. inlewis@alumni.sfu.ca
Curtis
Janelle M R
JM
Arcese
Peter
P
Rosenfeld
Jordan
J
D003247:Conservation of Natural Resources / Q000379:methods*; D003710:Demography; D017753:Ecosystem; D008962:Models, Theoretical; D011157:Population Dynamics; D012680:Sensitivity and Specificity