Characterizing biotic interactions within the Order Lagomorpha using Joint Species Distribution Models at 3 different spatial scales

Abstract

Species Distribution Models (SDMs) rarely incorporate biotic interactions, even though the latter may have great impacts on biogeographical patterns, because interactions can be difficult to model in time and space. In addition, the resolution of input data can have dramatic effects on results, with coarser resolutions unlikely to capture climatic variation at small scales, particularly in mountainous regions. Joint SDMs can be used to explore distributions of multiple, coexisting species and characterize modelled biotic interactions; however, the influence of scale on predictions is yet to be tested. We produced Joint SDMs for European lagomorph species at 3 hierarchical resolutions and calculated residual and environmental correlations that could explain why species may or may not co-occur, thereby suggesting biotic interactions. European lagomorph species exhibited similar environmental and biotic responses at all 3 resolutions (50 km, 25 km, and 10 km), with models at finer resolutions producing more precise estimates but requiring considerable computing time. The majority of pairwise residual responses were negative, indicating that European lagomorph species co-occur less than expected given their similarity in environmental responses, and suggesting modelled biotic interactions consistent with those reported in the literature. Finescale data and models offer greater precision but are not always necessary for multi-species models. However, caution is advised when inferring biotic interactions using data and models based on a coarser scale.

The Influence of the Interaction between Climate and Competition on the Distributional Limits of European Shrews

“…Actually, C. leucodon is known to vary habitat preferences along its distributional range [ 26 ], but always occurring in habitats that S. araneus usually avoids. These results, highlighting the direct impact of competition in limiting species’ distributions, regardless of climate, fall in line with several other previous studies, showing how biotic interactions directly impact species’ distributions [ 22 , 49 , 50 , 51 ].…”

“…Most of the large-scale studies focusing on the impact of biotic interactions involve plants [ 15 , 16 , 17 ], insects [ 18 , 19 ], or species associated with different trophic levels [ 20 , 21 ]. The work by Leach et al (2017) is one of the few studies that, following a modelling approach, analysed competition between closely related mammalian species (lagomorphs) at a continental scale, although models accounting for the interaction between environment and biotic interactions were not considered [ 22 ]. To fill this void, here we explore the relative impact of competition between closely related species and climate in defining species’ distributional limits at a continental geographical scale.…”

Spatial Pattern of Species Richness among Terrestrial Mammals in China

“…Typically, such works rely on field observation and are limited to smaller study areas [17][18][19]. Statistical models are also frequently used to analyze and predict distribution [20,21], focusing on the analysis of the single species distribution characteristics [22][23][24][25].…”

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“…There is a recognized need to consider biotic interactions (Guisan and Thuiller, 2005;Gelfand et al, 2006;McMahon et al, 2011;Elith and Leathwick, 2009) and macroevolutionary processes (Lawing and Matzke, 2014;Zamudio et al, 2016;Elliott and Davies, 2017) when modeling species and trait distributions. This is particularly true in species conservation and when forecasting changes to species distributions resulting from climate change (Leach et al, 2017;Lin et al, 2017), because, competition or mutualism between species may explain more of the observed geographic distribution than can be accounted for by abiotic factors alone. To help meet this need and to facilitate subsequent inference and interpretation, the PhyCoRT model leverages multiple species and multiple traits in a spatially explicit, integrative framework while accounting for shared evolutionary history, the co-occurrence of heterospecifics, and environmental conditions.…”

“…To better understand the mechanisms driving species coexistence or exclusion, joint species models have been applied to capture predator-prey dynamics (Sadykova et al, 2017), the spatial relationship among juvenile and adult cohorts (Ghosh et al, 2016), and a host of other biotic interactions (Pollock et al, 2014;Ovaskainen et al, 2016;Jones-Todd et al, 2017;Tikhonov et al, 2017). Joint species models have also found wide application in biological conservation (Thorson et al, 2015;Inoue et al, 2017) and may offer distinct advantages when extrapolating threatened species occurrence in a changing climate (Leach et al, 2017;Lin et al, 2017). Although the modern advent of sophisticated spatial statistical approaches to multi-species SDMs is a welcome development, a comparable level of progress has yet to be made embedding evolutionary information in SDMs.…”