ABSTRACT
Understanding the response of species to global change requires disentangling the drivers of their distributions across landscapes. Colonization and extinction processes, shaped by the interplay of landscape-level and local patch-level factors, are key determinants of these distributions. However, disentangling the influence of these factors, when larger-scale processes manifest at local scales, remains a challenge. We addressed this challenge by investigating the colonization and extinction dynamics of the aquatic plant, Hydrilla verticillata, in a complex riverine rock pool system. This system, with hundreds of rock pools experiencing varying flooding frequencies, provided a natural laboratory to examine how a single landscape-level disturbance can differentially impact colonization and extinction depending on local patch characteristics to shape species distributions. Using 5 years of data across over 500 sites and more than 5000 surveys, we employed dynamic occupancy models to model colonization, extinction, and changes in Hydrilla patch occupancy while accounting for imperfect detection. Our results revealed that larger, infrequently flooded pools closer to the river were more likely to be colonized. In contrast, local extinction of Hydrilla was more likely in smaller pools closer to the river that flooded frequently. These findings underscore the importance of considering context-dependence in species distribution models. The same landscape-level disturbance (flooding) had opposing effects on colonization and extinction, with the direction and magnitude of these effects varying with local patch characteristics. Our study highlights the need for integrating local and landscape-level factors, and considering how larger-scale processes play out at the patch level, to understand the complex dynamics that shape species distributions.
ABSTRACT
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 would 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 during which aquatic dragonfly nymphs could consume them. 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.
