Trait-based sensitivity of large mammals to a catastrophic tropical cyclone: DNA metabarcoding data

AbstractExtreme weather events perturb ecosystems and increasingly threaten biodiversity1. Ecologists emphasize the need to forecast and mitigate the impacts of these incidents, which requires knowledge of how risk is distributed among species and environments, but the scale and unpredictability of extreme events complicates assessment1–4. These challenges are compounded for large animals (‘megafauna’), which play crucial ecological roles but are hard to study5. Traits such as body size, dispersal ability, and habitat affiliation are among the hypothesized determinants of animals’ vulnerability to natural hazards1,6,7. However, it has rarely been possible to test these propositions or, more generally, to link short- and longer-term effects of weather-related disturbance8,9. Here, we show how large herbivores and carnivores in Mozambique responded to Intense Tropical Cyclone Idai, the deadliest storm on record in Africa, across scales ranging from individual decisions in the hours after landfall to community-level responses nearly 20 months later. Animals occupying low-elevation habitats exhibited strong spatial responses to rising floodwaters. Body size predicted species’ subsequent numerical responses: small-bodied species exhibited the greatest population declines. We trace this sensitivity to limited mobility, which increased likelihood of death during the flood and constrained animals’ capacity to withstand food shortages afterward. Our results identify potentially general trait-based mechanisms underlying animal responses to severe weather and may help to inform strategies for wildlife conservation in a volatile climate. Climate Change 2022: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [H.-O. Pörtner, D.C. Roberts, M. Tignor, E.S. Poloczanska, K. Mintenbeck, A. Alegría, M. Craig, S. Langsdorf, S. Löschke, V. Möller, A. Okem, B. Rama (eds.)]. Cambridge University Press. Cambridge University Press, Cambridge, UK and New York, NY, USA, (2022). Smith, M. An ecological perspective on extreme climatic events: A synthetic definition and framework to guide future research. J. Ecol. 99, 656-663 (2011). Ummenhofer, C. C., & Meehl, G. A. Extreme weather and climate events with ecological relevance: a review, Phil. Trans. R. Soc. B. 372, 20160135 (2017). Jentsch, A., Kreyling, J., & Beierkuhnlein, C. A new generation of climate-change experiments: events, not trends. Front. Ecol. Environ. 5, 365-374 (2007). Pringle, R. M., et. al. Impacts of large herbivores on terrestrial ecosystems. Current Biology 33, R584-R610 (2023). Spiller, D. A., Losos, J. B., & Schoener, T. W. Impact of a catastrophic hurricane on island populations. Science 281, 695-697 (1998). Schoener, T. W., & Spiller, D. A. Nonsynchronous recovery of community characteristics in island spiders after a catastrophic hurricane. PNAS 103, 2220-2225 (2006). Pruitt, N., Little, A. G., Majumdar, S. J., Schoener, T. W., & Fisher, D. N. Call-to-Action: A global consortium for tropical cyclone ecology. TREE 34, 588-590 (2019). Lin, T. C., Hogan, J. A., & Chang, C. T. Tropical cyclone ecology: a scale-link perspective. TREE 35, 594-604 (2020).
MethodsThis archive presents raw and filtered data on the diets of 13 species of large mammalian herbivores and African wild dogs (Lycaon pictus) in Gorongosa National Park. Data were generated via DNA metabarcoding of fecal samples in three distinct seasons for large herbivores (late-wet, early-dry, and late-dry) and opportunistically for wild dogs. The methods summary below is from Walker et al. (2023); please see that paper for additional details, references, and context. All filtered datasets used in Walker et al. 2023 are deposited here alongside raw DNA metabarcoding data for African wild dog diets and large-herbivore diets in late-wet season 2018 and all seasons in 2019. Raw data for large-herbivore diet datasets also used in Walker et al. (2023) can be found in the following repositories: https://doi.org/10.5061/dryad.sxksn02zc (2018, early- and late-dry season); https://doi.org/10.5061/dryad.brv15dvcj (2016, early-dry season). DNA metabarcoding analysis of wild dog diets. Samples were collected on an opportunistic basis with unused nitrile gloves and placed in an unused plastic bag. Sampling date and location were recorded on the bag, which was placed on ice for transport to the field laboratory. There, samples were frozen at -20° C until processing. Every three months, all samples collected from the intervening period were thawed and preprocessed for DNA extraction. Sample preprocessing involved homogenizing each thawed sample by massaging the bag between thumb and forefinger. A pea-sized subsample was then transferred into a plastic tube containing silica bashing beads and 750uL of buffer (Xpedition Lysis/Stabilization Solution; Zymo Research, CA, USA). We then capped the tube and vortexed it for 30 s...