A pragmatic approach for comparing species distribution models to increasing confidence in managing piping plover habitat

Abstract

Abstract Conservation management often requires decision‐making without perfect knowledge of the at‐risk species or ecosystem. Species distribution models (SDMs) are useful but largely under‐utilized due to model uncertainty. We used an ensemble modeling approach of two independently derived SDMs to explicitly address common modeling impediments and directly inform conservation decision‐making for piping plovers in a heavily populated mid‐Atlantic (USA) coastal zone. We summarized previously published Bayesian network and maximum entropy models to highlight similarities and differences in structure, and we compared the relative importance of predictors used. Despite differences in analytical approach, relative importance of factors driving nest‐site selection was consistent. Models demonstrated considerable agreement when comparing a binary (suitable/unsuitable) measure of suitability. Instances of model consensus (i.e., overlapping areas of predicted piping plover nesting habitat between models) provide a stronger “signal” in model results, reducing uncertainty related to biases or errors associated with either model. We tested model accuracy using a common dataset of plover nests initiated within the focal areas between 2013 and 2015, and we examined congruency in model outputs. Nearly, 90% of all nests occurred in areas predicted suitable by at least one model, and at least 33% of the total nests were predicted in areas suitable by both. Because models predominantly agreed on what drives piping plover nest‐site selection, areas predicted suitable by a single model should not be discounted. This case study demonstrates how models can effectively inform conservation planning by explicitly identifying the management objective, presenting robust evidence to allow managers to evaluate outcomes of alternative management decisions, and clearly communicating results that address real‐world conservation problems. Our results can greatly increase the piping plover management community's ability to prioritize candidate sites for future protection, manage existing nesting habitat appropriately, and make a compelling case for conservation actions against competing land use objectives.

Keywords

• conservation planning
• environmental suitability
• research‐implementation gap
• model uncertainty
• piping plover
• science communication