Structural divergence of terrestrial arthropod food webs in time and space

Climate change and landscape modification by agricultural intensification and rapid urbanization are two of the processes threatening biodiversity at a global scale. Our knowledge about the effects of this global changes on biodiversity are mostly based on findings at the species level. In this context, it is broadly accepted that agricultural intensification, climate change or pollution modify the number of species and individuals reducing or enhancing biodiversity. However, little attention has been paid to the effects on species interactions; on who interacts with whom and the strength or frequency of those interactions. Modifications at the food web structure can modify its stability and functionality even when species composition remains unaltered. Moreover, some of these interactions such as pollination or pest control sustain ecosystem services and contributes to the benefit of humans. In this essay, I examine how global change drivers impact interaction intensity, diversity and stability among food webs over time and space. In doing so, I explicitly target terrestrial food webs, with a focus on invertebrate networks. Mostly, I will target variation due to global changes such as land management, landscape complexity or climate change. Parasitism in invertebrates and mutualism between plants and pollinators are two networks that have been analyzed quantitatively for variation in their interaction structures in relation to global changes. Some of the variation in the food web complexity where shown to be driven by landscape complexity, geographical distance and time. Interactions, therefore, are dynamic processes and future research needs to take into account this aspect and include the food webs approach when investigating global change effects on natural communities. Thus, new data on how interactions vary the complexity of a network, is a current need to develop new knowledge about effects of global change on species interactions and to improve our predictions about the future of the ecosystems under the continuous changes induced by human activities