Science Enabled by Specimen Data

Cosentino, F., E. C. J. Seamark, V. Van Cakenberghe, and L. Maiorano. 2023. Not only climate: The importance of biotic interactions in shaping species distributions at macro scales. Ecology and Evolution 13. https://doi.org/10.1002/ece3.9855

Abiotic factors are usually considered key drivers of species distribution at macro scales, while biotic interactions are mostly used at local scales. A few studies have explored the role of biotic interactions at macro scales, but all considered a limited number of species and obligate interactions. We examine the role of biotic interactions in large‐scale SDMs by testing two main hypotheses: (1) biotic factors in SDMs can have an important role at continental scale; (2) the inclusion of biotic factors in large‐scale SDMs is important also for generalist species. We used a maximum entropy algorithm to model the distribution of 177 bat species in Africa calibrating two SDMs for each species: one considering only abiotic variables (noBIO‐SDMs) and the other (BIO‐SDMs) including also biotic variables (trophic resource richness). We focused the interpretation of our results on variable importance and response curves. For each species, we also compared the potential distribution measuring the percentage of change between the two models in each pixel of the study area. All models gave AUC >0.7, with values on average higher in BIO‐SDMs compared to noBIO‐SDMs. Trophic resources showed an importance overall higher level than all abiotic predictors in most of the species (~68%), including generalist species. Response curves were highly interpretable in all models, confirming the ecological reliability of our models. Model comparison between the two models showed a change in potential distribution for more than 80% of the species, particularly in tropical forests and shrublands. Our results highlight the importance of considering biotic interactions in SDMs at macro scales. We demonstrated that a generic biotic proxy can be important for modeling species distribution when species‐specific data are not available, but we envision that a multi‐scale analysis combined with a better knowledge of the species might provide a better understanding of the role of biotic interactions.

Sánchez, C. A., H. Li, K. L. Phelps, C. Zambrana-Torrelio, L.-F. Wang, P. Zhou, Z.-L. Shi, et al. 2022. A strategy to assess spillover risk of bat SARS-related coronaviruses in Southeast Asia. Nature Communications 13. https://doi.org/10.1038/s41467-022-31860-w

Emerging diseases caused by coronaviruses of likely bat origin (e.g., SARS, MERS, SADS, COVID-19) have disrupted global health and economies for two decades. Evidence suggests that some bat SARS-related coronaviruses (SARSr-CoVs) could infect people directly, and that their spillover is more frequent than previously recognized. Each zoonotic spillover of a novel virus represents an opportunity for evolutionary adaptation and further spread; therefore, quantifying the extent of this spillover may help target prevention programs. We derive current range distributions for known bat SARSr-CoV hosts and quantify their overlap with human populations. We then use probabilistic risk assessment and data on human-bat contact, human viral seroprevalence, and antibody duration to estimate that a median of 66,280 people (95% CI: 65,351–67,131) are infected with SARSr-CoVs annually in Southeast Asia. These data on the geography and scale of spillover can be used to target surveillance and prevention programs for potential future bat-CoV emergence. Coronaviruses may spill over from bats to humans. This study uses epidemiological data, species distribution models, and probabilistic risk assessment to map overlap among people and SARSr-CoV bat hosts and estimate how many people are infected with bat-origin SARSr-CoVs in Southeast Asia annually.

McGowan, N. E., N. Roche, T. Aughney, J. Flanagan, P. Nolan, F. Marnell, and N. Reid. 2021. Testing consistency of modelled predictions of the impact of climate change on bats. Climate Change Ecology 2: 100011. https://doi.org/10.1016/j.ecochg.2021.100011

Species Distribution Models (SDMs) are a cornerstone of climate change conservation research but temporal extrapolations into future climate scenarios cannot be verified until later this century. One way of assessing the robustness of projections is to compare their consistency between different mod…

Cooper, N., A. L. Bond, J. L. Davis, R. Portela Miguez, L. Tomsett, and K. M. Helgen. 2019. Sex biases in bird and mammal natural history collections. Proceedings of the Royal Society B: Biological Sciences 286: 20192025. https://doi.org/10.1098/rspb.2019.2025

Natural history specimens are widely used across ecology, evolutionary biology and conservation. Although biological sex may influence all of these areas, it is often overlooked in large-scale studies using museum specimens. If collections are biased towards one sex, studies may not be representativ…

Park, D. S., and O. H. Razafindratsima. 2018. Anthropogenic threats can have cascading homogenizing effects on the phylogenetic and functional diversity of tropical ecosystems. Ecography 42: 148–161. https://doi.org/10.1111/ecog.03825

Determining the mechanisms that underlie species distributions and assemblages is necessary to effectively preserve biodiversity. This cannot be accomplished by examining a single taxonomic group, as communities comprise a plethora of interactions across species and trophic levels. Here, we examine …