The role of biotic interactions in shaping distributions and realised assemblages of species: implications for species distribution modelling

Abstract

Predicting which species will occur together in the future, and where, remains one of the greatest challenges in ecology, and requires a sound understanding of how the abiotic and biotic environments interact with dispersal processes and history across scales. Biotic interactions and their dynamics influence species' relationships to climate, and this also has important implications for predicting future distributions of species. It is already well accepted that biotic interactions shape species' spatial distributions at local spatial extents, but the role of these interactions beyond local extents (e.g. 10 km2 to global extents) are usually dismissed as unimportant. In this review we consolidate evidence for how biotic interactions shape species distributions beyond local extents and review methods for integrating biotic interactions into species distribution modelling tools. Drawing upon evidence from contemporary and palaeoecological studies of individual species ranges, functional groups, and species richness patterns, we show that biotic interactions have clearly left their mark on species distributions and realised assemblages of species across all spatial extents. We demonstrate this with examples from within and across trophic groups. A range of species distribution modelling tools is available to quantify species environmental relationships and predict species occurrence, such as: (i) integrating pairwise dependencies, (ii) using integrative predictors, and (iii) hybridising species distribution models (SDMs) with dynamic models. These methods have typically only been applied to interacting pairs of species at a single time, require a priori ecological knowledge about which species interact, and due to data paucity must assume that biotic interactions are constant in space and time. To better inform the future development of these models across spatial scales, we call for accelerated collection of spatially and temporally explicit species data. Ideally, these data should be sampled to reflect variation in the underlying environment across large spatial extents, and at fine spatial resolution. Simplified ecosystems where there are relatively few interacting species and sometimes a wealth of existing ecosystem monitoring data (e.g. arctic, alpine or island habitats) offer settings where the development of modelling tools that account for biotic interactions may be less difficult than elsewhere.

Shading and litter mediate the effects of soil fertility on the performance of an understorey herb

“…For example, overstorey density directly affects both litter depth and shading, and we cannot readily separate their effects on plant performance. Despite these limitations, the multiple analysis approaches we employed suggested that several biotic variables have significant direct and indirect effects, which supports the growing evidence that biotic interactions can strongly affect plant distributions across abiotic gradients (Wisz et al, 2013). Overall, our results highlight how biotic conditions and soil fertility are strongly associated with regional distribution patterns and may interact with climate-related variables (e.g.…”

“…Models with biotic conditions alone were able to significantly distinguish presence from absence points, while models with topographic microclimate and/or soil fertility alone only weakly differentiated them (P-values close to 0Á05, Table 3). These results suggest that inclusion of biotic conditions may significantly improve distribution model predictions in space and time (Wisz et al, 2013), although the relative contribution of biotic conditions to distribution is likely to vary with species tolerance to disturbance and environmental stress (Meier et al, 2010). The strength of biotic conditions compared to abiotic factors in our models suggests that changes in biotic factors could significantly alter distribution patterns with respect to abiotic factors.…”

“…However, biotic conditions are often omitted in species distribution models (Elith and Leathwick, 2009) due to scarcity of relevant data, close correlations between biotic and abiotic variables, and uncertainty regarding the relative importance of biotic conditions at the larger spatial scales typically considered in distribution models (Wisz et al, 2013). To assess whether this absence of biotic variables is a significant problem, the relative importance of, and correlations between, abiotic and biotic variables need to be better understood.…”

Fine-scale spatial patterns of the Tertiary relict Zelkova abelicea (Ulmaceae) indicate possible processes contributing to its persistence to climate changes

“…Even though biotic interactions have generally been considered to be unimportant in determining large-scale distributions (for a review see Wisz et al 2013), they have recently been suggested to affect species distributions and plant assemblages at regional, continental and global scales (Hampe and Jump 2011;Wisz et al 2013). Thus, biotic interactions ought to be considered in management practices of Z. abelicea.…”

Phylogenetic structure and host abundance drive disease pressure in communities

“…Similarly, we can quantify the relative vulnerability of local species of concern to pathogen spillover from these same introduced species. Models to predict the future distribution of plant invasions have been constrained by the difficulty of incorporating biotic drivers, including pathogens and parasites 30 . We show how fairly simple information on the species composition of resident plant communities could help predict both variation in the spread of an invasive species across a landscape and variation in the impact of that species.…”