DOI: 10.5061/dryad.n2z34tn3h
title: Data from: warming and top-down control of stage-structured prey: linking theory to patterns in natural systems

description: Warming has broad and often nonlinear impacts on organismal physiology and
 traits, allowing it to impact species interactions like predation through
 a variety of pathways that may be difficult to predict. Predictions are
 commonly based on short-term experiments and models, and these studies
 often yield conflicting results depending on the environmental context,
 spatiotemporal scale, and the predator and prey species considered. Thus,
 the accuracy of predicted changes in interaction strength, and their
 importance to the broader ecosystems they take place in, remain unclear.
 Here, we attempted to link one such set of predictions generated using
 theory, modeling, and controlled experiments to patterns in the natural
 abundance of prey across a broad thermal gradient. To do so, we first
 predicted how warming will impact a stage-structured predator-prey
 interaction in riverine rock pools between Pantala spp. dragonfly nymph
 predators and Aedes atropalpus mosquito larval prey. We then described
 temperature variation across a set of hundreds of riverine rock pools (n =
 775) and leveraged this natural gradient to look for evidence for or
 against our model’s predictions. Our model’s predictions suggested that
 warming should weaken predator control of mosquito larval prey by
 accelerating their development and shrinking the window of time that
 aquatic dragonfly nymphs could consume them in. This was consistent with
 data collected in rock pool ecosystems, where the negative effects of
 dragonfly nymph predators on mosquito larval abundance were weaker in
 warmer pools. Our findings provide additional evidence to substantiate our
 model-derived predictions, while emphasizing the importance of assessing
 similar predictions using natural gradients of temperature whenever
 possible.
description: # Warming and top-down control of stage-structured prey: linking theory to
 patterns in natural systems
 [https://doi.org/10.5061/dryad.n2z34tn3h](https://doi.org/10.5061/dryad.n2z34tn3h) Contains data and models describing rock pool temperature variation and its relationship with the abundance of mosquito larvae and their dragonfly nymph predators at Belle Isle, Richmond VA. ## Description of the data and file structure For variable descriptions, refer to the corresponding tabs in the file "metadata.xlsx". The files "abundance.rmd" and "abundance_data.csv" contain data and code used to model the distribution and abundance of *Ae. atropalpus* mosquito larvae as a function of predatory dragonfly nymphs (*Pantala* spp.) and predicted rock pool temperatures. The files "pantala_FR.rmd" and "TDFR_Pantala-Atro_data.csv" contain data and code used to fit temperature-dependent functional response models, describing *Pantala* spp. dragonfly nymphs feeding rates on *Ae. atropalpus* mosquito larval prey. The files "sizedep_supplement.rmd" and "sizedep-pred_data.csv" contain supplemental data and code describing the relationship between mosquito larval body size and predation rates by *Erythemis simplicicollis* and *Pachydiplax longipennis* dragonfly nymphs. The files "abiotic_data.csv", "CompiledTempData_Master.csv", "temperature_data.csv", and "temp_analysis.rmd" contain data and code used to model the thermal environment of riverine rock pools as a function of their abiotic characteristics, as well as predicted maximum temperatures for the full rock pool landscape at our field site. Fields with "-" indicate missing data for that pool, and pools with missing data or other peculiarities (e.g., "not a pool", "channel feature", or "filled in" in the Notes column) were excluded from the final analysis. Code has been annotated for legibility, but please direct any questions to Dr. Andy Davidson at davidsonat@vcu.edu ## Sharing/Access information A more organized and comprehensive version of this data set and codebase, including model outputs and figures, is also available on Github, at https://github.com/davidsonat/2022_tdep-landscape