RESUMEN
Spatial and trophic processes profoundly influence biodiversity, yet ecological theories often treat them independently. The theory of island biogeography and related theories on metacommunities predict higher species richness with increasing area across islands or habitat patches. In contrast, food-web theory explores the effects of traits and network structure on coexistence within local communities. Exploring the mechanisms by which landscape configurations interact with food-web dynamics in shaping metacommunities is important for our understanding of biodiversity. Here, we use a meta-food-web model to explore the role of landscape configuration in determining species richness and show that when habitat patches are interconnected by dispersal, more species can persist on smaller islands than predicted by classical theory. When patch sizes are spatially aggregated, this effect flattens the slope of the species-area relationship. Surprisingly, when landscapes have random patch-size distributions, the slope of the species-area relationships can even flip and become negative. This could be explained by higher biomass densities of lower trophic levels that then support species occupying higher trophic levels, which only persist on small and well-connected patches. This highlights the importance of simultaneously considering landscape configuration and local food-web dynamics to understand drivers of species-area relationships in metacommunities.This article is part of the theme issue 'Diversity-dependence of dispersal: interspecific interactions determine spatial dynamics'.
Asunto(s)
Biodiversidad , Cadena Alimentaria , Modelos Biológicos , Ecosistema , AnimalesRESUMEN
The dataset presents a compilation of stomach contents from six demersal fish species from two functional groups inhabiting the Baltic Sea. It includes detailed information on prey identities, body masses, and biomasses recovered from both the fish's digestive systems and their surrounding environment. Environmental parameters, such as salinity and temperature levels, have been integrated to enrich this dataset. The juxtaposition of information on prey found in stomachs and in the environment provides an opportunity to quantify trophic interactions across different environmental contexts and investigate how fish foraging behaviour adapts to changes in their environment, such as an increase in temperature. The compilation of body mass and taxonomic information for all species allows approaching these new questions using either a taxonomic (based on species identity) or functional trait (based on body mass) approach.
Asunto(s)
Peces , Contenido Digestivo , Animales , Países Bálticos , Océanos y MaresRESUMEN
At macroecological scales, the provision of Nature's contributions to people (NCP) is mostly estimated with biophysical information, ignoring the ecological processes underlying them. This hinders our ability to properly quantify the impact of declining biodiversity and the provision of NCP. Here, we propose a framework that combines local-scale food web energy flux approaches and large-scale biodiversity models to evaluate ecosystem functions and flux-related NCP at extensive spatiotemporal scales. Importantly, this approach has the potential to upscale ecosystem functions, assess the vulnerability of flux-related NCP to the climate crisis, and support the development of multiscale mitigation policies.
Asunto(s)
Biodiversidad , Ecosistema , Humanos , Cambio Climático , Conservación de los Recursos Naturales , Cadena Alimentaria , Modelos BiológicosRESUMEN
Higher temperatures are expected to reduce species coexistence by increasing energetic demands. However, flexible foraging behaviour could balance this effect by allowing predators to target specific prey species to maximize their energy intake, according to principles of optimal foraging theory. Here we test these assumptions using a large dataset comprising 2,487 stomach contents from six fish species with different feeding strategies, sampled across environments with varying prey availability over 12 years in Kiel Bay (Baltic Sea). Our results show that foraging shifts from trait- to density-dependent prey selectivity in warmer and more productive environments. This behavioural change leads to lower consumption efficiency at higher temperature as fish select more abundant but less energetically rewarding prey, thereby undermining species persistence and biodiversity. By integrating this behaviour into dynamic food web models, our study reveals that flexible foraging leads to lower species coexistence and biodiversity in communities under global warming.
RESUMEN
Understanding the factors that determine the occurrence and strength of ecological interactions under specific abiotic and biotic conditions is fundamental since many aspects of ecological community stability and ecosystem functioning depend on patterns of interactions among species. Current approaches to mapping food webs are mostly based on traits, expert knowledge, experiments, and/or statistical inference. However, they do not offer clear mechanisms explaining how trophic interactions are affected by the interplay between organism characteristics and aspects of the physical environment, such as temperature, light intensity or viscosity. Hence, they cannot yet predict accurately how local food webs will respond to anthropogenic pressures, notably to climate change and species invasions. Herein, we propose a framework that synthesises recent developments in food-web theory, integrating body size and metabolism with the physical properties of ecosystems. We advocate for combination of the movement paradigm with a modular definition of the predation sequence, because movement is central to predator-prey interactions, and a generic, modular model is needed to describe all the possible variation in predator-prey interactions. Pending sufficient empirical and theoretical knowledge, our framework will help predict the food-web impacts of well-studied physical factors, such as temperature and oxygen availability, as well as less commonly considered variables such as wind, turbidity or electrical conductivity. An improved predictive capability will facilitate a better understanding of ecosystem responses to a changing world.