Tue, Aug 03, 2021:On Demand
Background/Question/Methods
Ecologists have been relatively successful in describing species distributions, but less successful in identifying mechanisms and quantifying their importance for community assembly. Theory suggests that these mechanisms consist both of species’ responses to the environment and their interactions with other species, and species traits can provide important clues about these processes. If species’ morphological and ecological characteristics can help predict their responses to environmental gradients and interactions with each other, this can provide insights into the community assembly process. But are the influences of traits consistent across space and time? If so, predictions under various climate change scenarios can be informed by traits. If not, these processes may be more stochastic, but this may also imply additional potential for adaptation. Here we test for consistency in the relationships between traits, environmental gradients, and species associations in diverse dead wood dependent forest beetle communities from three distinct ecosystems: Norwegian boreonemoral forests, Finnish boreal forests, and German mixed temperate forests. Using Bayesian joint species distribution models, we ask whether traits and phylogeny predict beetle species distributions and interactions across environmental gradients, and whether these relationships are similar among bioclimatic regions. For species occurring in multiple regions, we test for consistency in their responses to climatic and habitat gradients.
Results/Conclusions Models that included beetles’ morphological and ecological traits allowed improved predictions of species’ responses to environmental gradients. The presence of substantial phylogenetic signal in species responses, beyond what is explained by current trait information, implies that additional unmeasured traits have an even stronger effect on species distributions. Although traits do have some explanatory power in each bioclimatic region we studied, these trait - environment relationships are not consistent among regions. Species associations, however, do not appear to be driven by degree of trait similarity among species in any of the three regions. Most of the (largely positive) associations we detected are likely due to unmeasured environmental covariates rather than direct interactions. For beetle species occurring in two or more of our bioclimatic study regions, responses to various environmental gradients – temperature, precipitation, forest age and volume, and habitat connectivity – were broadly similar. This implies that these species may be likely to respond to direct and indirect effects of climate change in ways that are consistent with their current distributions across these gradients, increasing confidence in future projections but perhaps limiting scope for adaptation.
Results/Conclusions Models that included beetles’ morphological and ecological traits allowed improved predictions of species’ responses to environmental gradients. The presence of substantial phylogenetic signal in species responses, beyond what is explained by current trait information, implies that additional unmeasured traits have an even stronger effect on species distributions. Although traits do have some explanatory power in each bioclimatic region we studied, these trait - environment relationships are not consistent among regions. Species associations, however, do not appear to be driven by degree of trait similarity among species in any of the three regions. Most of the (largely positive) associations we detected are likely due to unmeasured environmental covariates rather than direct interactions. For beetle species occurring in two or more of our bioclimatic study regions, responses to various environmental gradients – temperature, precipitation, forest age and volume, and habitat connectivity – were broadly similar. This implies that these species may be likely to respond to direct and indirect effects of climate change in ways that are consistent with their current distributions across these gradients, increasing confidence in future projections but perhaps limiting scope for adaptation.