The structure of tropical bat-plant interaction networks during an extreme El Niño-Southern Oscillation event

Seed dispersal syndrome predicts ethanol concentration of fruits in a tropical dry forest

Studying fruit traits and their interactions with seed dispersers can improve how we interpret patterns of biodiversity, ecosystem function and evolution. Mounting evidence suggests that fruit ethanol is common and variable, and may exert selective pressures on seed dispersers. To test this, we comprehensively assess fruit ethanol content in a wild ecosystem and explore sources of variation. We hypothesize that both phylogeny and seed dispersal syndrome explain variation in ethanol levels, and we predict that fruits with mammalian dispersal traits will contain higher levels of ethanol than those with bird dispersal traits. We measured ripe fruit ethanol content in species with mammal- (n = 16), bird- (n = 14) or mixed-dispersal (n = 7) syndromes in a Costa Rican tropical dry forest. Seventy-eight per cent of fruit species yielded measurable ethanol concentrations. We detected a phylogenetic signal in maximum ethanol levels (Pagel's λ = 0.82). Controlling for phylogeny, we observed greater ethanol concentrations in mammal-dispersed fruits, indicating that dispersal syndrome helps explain variation in ethanol content, and that mammals may be more exposed to ethanol in their diets than birds. Our findings further our understanding of wild fruit ethanol and its potential role as a selective pressure on frugivore sensory systems and metabolism.

Changing with the times: Seasonal environmental gradients unveil dynamic bat assemblages and vulnerability

Uncovering the temporal and spatial dynamics of biological communities in response to biotic and abiotic drivers is essential to predict the effects of environmental change on biodiversity. Similarly, estimating species vulnerability in the face of such dynamics is crucial for implementing effective conservation actions. We explored how bat diversity changes over the year across an altitudinal gradient and identified the environmental drivers that shape bat communities. By analysing species' marginality within the biophysical niche space, we evaluated bats' vulnerability to foreseeable environmental changes. Our results suggest that altitude, the proportion of forest cover and shrub cover are the main drivers shaping bat communities year-round. Additionally, while some bat species are restricted to a single ecological assemblage (or ecological preferences group), others show greater plasticity throughout the year. Importantly, we found that although bats associated with highland habitats and forests could be particularly vulnerable to environmental changes (in particular Myotis mystacinus), this vulnerability correlates poorly with their national conservation status. We suggest that species' ecological plasticity is critical for the resilience of biological communities exposed to environmental changes and should be considered when planning tailored conservation strategies.

Examining paleobotanical databases: Revisiting trends in angiosperm folivory and unlocking the paleoecological promise of propensity score matching and specification curve analysis

Paleobotany is at a crossroads. Long-term trends in the fossil record of plants, encompassing their interactions with herbivores and with the environment, are of the utmost relevance for predicting global change as pCO2 continues to rise. Large data compilations with the potential to elucidate those trends are increasingly easy to assemble and access. However, in contrast to modern ecology and unlike various other paleontological disciplines, paleobotany has a limited history of “big data” meta-analyses. Debates about how much data are needed to address particular questions, and about how to control for potential confounding variables, have not examined paleobotanical data. Here I demonstrate the importance of analytical best practices by applying them to a recent meta-analysis of fossil angiosperms. Two notable analytical methods discussed here are propensity score matching and specification curve analysis. The former has been used in the biomedical and behavioral sciences for decades; the latter is a more recent method of examining relationships between, and inherent biases among, models. Propensity score matching allows one to account for potential confounding variables in observational studies, and more fundamentally, provides a way to quantify whether it is possible to account for them. Specification curve analysis provides the opportunity to examine patterns across a variety of schemes for partitioning data—for example, whether fossil assemblages are binned temporally by stage, epoch, or period. To my knowledge, neither of these methods has been used previously in paleontology, however, their use permits more robust analysis of paleoecological datasets. In the example provided here, propensity score matching is used to separate latitudinal trends from differences in age, climate, and plant community composition. Specification curve analysis is used to examine the robustness of apparent latitudinal trends to the schema used for assigning fossil assemblages to latitudinal bins. These analytical methods have the potential to further unlock the promise of the plant fossil record for elucidating long-term ecological and evolutionary change.