Climate change, species distribution models, and physiological performance metrics: predicting when biogeographic models are likely to fail

Abstract

Modeling the biogeographic consequences of climate change requires confidence in model predictions under novel conditions. However, models often fail when extended to new locales, and such instances have been used as evidence of a change in physiological tolerance, that is, a fundamental niche shift. We explore an alternative explanation and propose a method for predicting the likelihood of failure based on physiological performance curves and environmental variance in the original and new environments. We define the transient event margin (TEM) as the gap between energetic performance failure, defined as CTmax, and the upper lethal limit, defined as LTmax. If TEM is large relative to environmental fluctuations, models will likely fail in new locales. If TEM is small relative to environmental fluctuations, models are likely to be robust for new locales, even when mechanism is unknown. Using temperature, we predict when biogeographic models are likely to fail and illustrate this with a case study. We suggest that failure is predictable from an understanding of how climate drives nonlethal physiological responses, but for many species such data have not been collected. Successful biogeographic forecasting thus depends on understanding when the mechanisms limiting distribution of a species will differ among geographic regions, or at different times, resulting in realized niche shifts. TEM allows prediction of the likelihood of such model failure.

Physiology and Biogeography: The Response of European Mussels (Mytilusspp.) to Climate Change*

“…Species distribution models are useful in understanding current and potential distributions of species; however, oftentimes one type of SDM is incapable of accurately predicting all of a species' range limits (e.g., north and south, east and west) (Woodin et al 2013). This is because a given SDM applies a single mechanism or environmental profi le across an entire species' range, when, it is often the case that different mechanisms or stressors control different portions of a species' geographic range or its distribution in different geographic regions (Sokolova et al 2012, Woodin et al 2013).…”

“…This is because a given SDM applies a single mechanism or environmental profi le across an entire species' range, when, it is often the case that different mechanisms or stressors control different portions of a species' geographic range or its distribution in different geographic regions (Sokolova et al 2012, Woodin et al 2013). This appears to be the case with Mytilus edulis and M. galloprovincialis.…”

“…We have taken the approach of focusing on the response of key ecosystem engineers that both control the composition and diversity of ecological communities and are primary determinants of the "function" of ecosystems with respect to the goods and services provided to human societies, using both correlative and mechanistic methods. Mechanistic SDMs have been suggested as a more responsive model to climate change and invasive species scenarios (Kearney and Porter 2009) as they are better able to extrapolate to novel environmental conditions due to an understanding of the causative mechanisms behind species distributions (Helmuth et al 2005, Kearney and Porter 2009, Woodin et al 2013. However, these two types of approaches are not mutually exclusive and we show that incorporating both may provide a more robust model of a species' complete biogeographic range (Lawler et al 2006, Elith and Leathwick 2009, Sará et al 2011.…”

“…We used their estimate of the critical SST at which SFG = 0 to determine the geographic regions in Europe in which each species can potentially maintain a permanent population. In regions that exceed the critical SST at which SFG = 0, populations of each species are expected to be absent or ephemeral (Sokolova et al 2012, Woodin et al 2013. We compared the distribution of M. edulis and M. galloprovincialis to the monthly SST along the European coastline and to the critical temperature at which SFG = 0 (Fly and Hilbish 2013).…”

“…These types of models can be generated fairly quickly and can often, particularly for a species for which little is known, provide more information on what specifi c environmental variables may be important for the distribution of that species (Robertson et al 2003, Elith andLeathwick 2009). Mechanistic SDMs create predictions based on knowledge of underlying physiological and/or life history responses to environmental variables (Robertson et al 2003, Kearney and Porter 2009, Buckley et al 2010, Woodin et al 2013. Mechanistic SDMs are more timeconsuming to develop, since the important physiological mechanisms that potentially regulate the species distribution must fi rst be determined (Kearney and Porter 2009), but may provide greater insight into the factors limiting a species' distribution than a purely correlative model.…”