Natural history studies documenting spatial and temporal variation of species assemblages and their interactions are critical for understanding biodiversity and community ecology. We characterized caterpillar–parasitoid assemblages on shrubs in the genus
Abstract in Spanish is available with online material.
Biotic specialization holds information about the assembly, evolution, and stability of biological communities. Partner availabilities can play an important role in enabling species interactions, where uneven partner availabilities can bias estimates of biotic specialization when using phylogenetic diversity indices. It is therefore important to account for partner availability when characterizing biotic specialization using phylogenies. We developed an index, phylogenetic structure of specialization (PSS), that avoids bias from uneven partner availabilities by uncoupling the null models for interaction frequency and phylogenetic distance. We incorporate the deviation between observed and random interaction frequencies as weights into the calculation of partner phylogenetic α‐diversity. To calculate the PSS index, we then compare observed partner phylogenetic α‐diversity to a null distribution generated by randomizing phylogenetic distances among the same number of partners. PSS quantifies the phylogenetic structure (i.e., clustered, overdispersed, or random) of the partners of a focal species. We show with simulations that the PSS index is not correlated with network properties, which allows comparisons across multiple systems. We also implemented PSS on empirical networks of host–parasite, avian seed‐dispersal, lichenized fungi–cyanobacteria, and hummingbird pollination interactions. Across these systems, a large proportion of taxa interact with phylogenetically random partners according to PSS, sometimes to a larger extent than detected with an existing method that does not account for partner availability. We also found that many taxa interact with phylogenetically clustered partners, while taxa with overdispersed partners were rare. We argue that species with phylogenetically overdispersed partners have often been misinterpreted as generalists when they should be considered specialists. Our results highlight the important role of randomness in shaping interaction networks, even in highly intimate symbioses, and provide a much‐needed quantitative framework to assess the role that evolutionary history and symbiotic specialization play in shaping patterns of biodiversity. PSS is available as an R package at
Understanding how growth and reproduction will adapt to changing environmental conditions is a fundamental question in evolutionary ecology, but predicting the responses of specific taxa is challenging. Analyses of the physiological effects of climate change upon life history evolution rarely consider alternative hypothesized mechanisms, such as size‐dependent foraging and the risk of predation, simultaneously shaping optimal growth patterns. To test for interactions between these mechanisms, we embedded a state‐dependent energetic model in an ecosystem size‐spectrum to ask whether prey availability (foraging) and risk of predation experienced by individual fish can explain observed diversity in life histories of fishes. We found that asymptotic growth emerged from size‐based foraging and reproductive and mortality patterns in the context of ecosystem food web interactions. While more productive ecosystems led to larger body sizes, the effects of temperature on metabolic costs had only small effects on size. To validate our model, we ran it for abiotic scenarios corresponding to the ecological lifestyles of three tuna species, considering environments that included seasonal variation in temperature. We successfully predicted realistic patterns of growth, reproduction, and mortality of all three tuna species. We found that individuals grew larger when environmental conditions varied seasonally, and spawning was restricted to part of the year (corresponding to their migration from temperate to tropical waters). Growing larger was advantageous because foraging and spawning opportunities were seasonally constrained. This mechanism could explain the evolution of gigantism in temperate tunas. Our approach addresses variation in food availability and individual risk as well as metabolic processes and offers a promising approach to understand fish life‐history responses to changing ocean conditions.
A pressing challenge in ecology is to understand the effects of changing global temperatures on food web structure and dynamics. The stability of these complex ecological networks largely depends on how predator–prey interactions may respond to temperature changes. Because predators and prey rely on their velocities to catch food or avoid being eaten, understanding how temperatures may affect animal movement is central to this quest. Despite our efforts, we still lack a mechanistic understanding of how the effect of temperature on metabolic processes scales up to animal movement and beyond. Here, we merge a biomechanical approach, the Metabolic Theory of Ecology and empirical data to show that animal movement displays multiple regimes of temperature dependence. We also show that crossing these regimes has important consequences for population dynamics and stability, which depend on the parameters controlling predator–prey interactions. We argue that this dependence upon interaction parameters may help explain why experimental work on the temperature dependence of interaction strengths has so far yielded conflicting results. More importantly, these changes in the temperature dependence of animal movement can have consequences that go well beyond ecological interactions and affect, for example, animal communication, mating, sensory detection, and any behavioral modality dependent on the movement of limbs. Finally, by not taking into account the changes in temperature dependence reported here we might not be able to properly forecast the impact of global warming on ecological processes and propose appropriate mitigation action when needed.
