A framework integrating physiology, dispersal and land‐use to project species ranges under climate change

Abstract

To study the potential effects of climate change on species, one of the most popular approaches are species distribution models (SDMs). However, they usually fail to consider important species‐specific biological traits, such as species’ physiological capacities or dispersal ability. Furthermore, there is consensus that climate change does not influence species distributions in isolation, but together with other anthropogenic impacts such as land‐use change, even though studies investigating the relative impacts of different threats on species and their geographic ranges are still rare. Here we propose a novel integrative approach which produces refined future range projections by combining SDMs based on distribution, climate, and physiological tolerance data with empirical data on dispersal ability as well as current and future land‐use. Range projections based on different combinations of these factors show strong variation in projected range size for our study species Emberiza hortulana. Using climate and physiological data alone, strong range gains are projected. However, when we account for land‐use change and dispersal ability, future range‐gain may even turn into a future range loss. Our study highlights the importance of accounting for biological traits and processes in species distribution models and of considering the additive effects of climate and land‐use change to achieve more reliable range projections. Furthermore, with our approach we present a new tool to assess species’ vulnerability to climate change which can be easily applied to multiple species.

Avian SDMs: current state, challenges, and opportunities

“…Moreover, recent SDM applications assessed possible threats to biodiversity posed by mitigation actions against climate change (Wetzel et al 2012 for mammals;Brambilla et al 2016 for birds), an essential, yet often neglected topic (Turner et al 2010). Such studies have already contributed to the identification of the main sites for species conservation in a changing world, but should be further refined, for example by integrating species-specific physiological constraints (Methorst et al 2017) to make SDMs even more valuable tools for conservation planning.…”

“…Two factors make birds especially interesting to test hypotheses related to some of the key issues in contemporary distribution modeling, the first that birds are endotherms, and the second that they (often) show seasonal mobility (Fig. 1, Eyres et al 2017, Methorst et al 2017.…”

Time of emergence of novel climates for North American migratory bird populations

“…The ToE estimates in this study indicate the phases of the annual cycle when climate change are most likely to result in ecological surprises, novel ecosystems and altered ecosystem structure and function. We do not provide a physiological connection between climate and birds, a relationship that has been explored within the context of climate change primarily at a theoretical level; for example, in regard to the physiological requirements of migration (Klaassen et al 2012) or the physiological limitations of species' distributions (Methorst et al 2017). Rather, we identify when changes in climate are most likely to exceed a historically defined climatic threshold, generating novel climates, ecological disruptions and novel ecological domains.…”

Macroecology in the age of Big Data – Where to go from here?

“…The call for process-based models in macroecology is not new (e.g. The current trend in mechanistic macroecology is to include the manifold processes into an integrative modelling framework (Cabral, Valente, & Hartig, 2017;Leidinger & Cabral, 2017;Methorst, Böhning-Gaese, Khaliq, & Hof, 2017;Pontarp et al, 2018;Thuiller et al, 2013;Urban et al, 2016). These processes include, for example, physiology-related mechanisms (Kearney & Porter, 2004), microevolutionary dynamics of populations via explicit simulation of the genetic architecture of phenotypes (Schiffers et al, 2014), metapopulation dynamics via explicit simulation of dispersal and local demography across changing environment in distribution models (Juliano S Cabral & Schurr, 2010;Zurell et al, 2016), metacommunity dynamics via inclusion of resource competition and other biotic interactions (Juliano Sarmento Cabral & Kreft, 2012;Münkemüller et al, 2012), macroevolutionary processes (Aguilée, Gascuel, Lambert, & Ferriere, 2018;Cabral, Wiegand, & Kreft, 2019;Jõks & Pärtel, 2018;Rangel et al, 2018) and plate tectonics (Descombes et al, 2018;Leprieur et al, 2016).…”