Tropical land-use change alters trait-based community assembly rules for dung beetles and birds

Giant root-rat engineering and livestock grazing activities regulate plant functional trait diversity of an Afroalpine vegetation community in the Bale Mountains, Ethiopia

Disturbances from rodent engineering and human activities profoundly impact ecosystem structure and functioning. Whilst we know that disturbances modulate plant communities, comprehending the mechanisms through which rodent and human disturbances influence the functional trait diversity and trait composition of plant communities is important to allow projecting future changes and to enable informed decisions in response to changing intensity of the disturbances. Here, we evaluated the changes in functional trait diversity and composition of Afroalpine plant communities in the Bale Mountains of Ethiopia along gradients of engineering disturbances of a subterranean endemic rodent, the giant root-rat (Tachyoryctes macrocephalus Rüppell 1842) and human activities (settlement establishment and livestock grazing). We conducted RLQ (co-inertia analysis) and fourth-corner analyses to test for trait-disturbance (rodent engineering/human activities) covariation. Overall, our results show an increase in plant functional trait diversity with increasing root-rat engineering and increasing human activities. We found disturbance specific association with traits. Specifically, we found strong positive association of larger seed mass with increasing root-rat fresh burrow density, rhizomatous vegetative propagation negatively associated with increasing root-rat old burrow, and stolonifereous vegetative propagation positively associated with presence of root-rat mima mound. Moreover, both leaf size and leaf nitrogen content were positively associated with livestock dung abundance but negatively with distance from settlement. Overall, our results suggest that disturbances by rodents filter plant traits related to survival and reproduction strategies, whereas human activities such as livestock grazing act as filters for traits related to leaf economics spectrum along acquisitive resource-use strategy.

A roadmap towards predicting species interaction networks (across space and time)

Networks of species interactions underpin numerous ecosystem processes, but comprehensively sampling these interactions is difficult. Interactions intrinsically vary across space and time, and given the number of species that compose ecological communities, it can be tough to distinguish between a true negative (where two species never interact) from a false negative (where two species have not been observed interacting even though they actually do). Assessing the likelihood of interactions between species is an imperative for several fields of ecology. This means that to predict interactions between species-and to describe the structure, variation, and change of the ecological networks they form-we need to rely on modelling tools. Here, we provide a proof-of-concept, where we show how a simple neural network model makes accurate predictions about species interactions given limited data. We then assess the challenges and opportunities associated with improving interaction predictions, and provide a conceptual roadmap forward towards predictive models of ecological networks that is explicitly spatial and temporal. We conclude with a brief primer on the relevant methods and tools needed to start building these models, which we hope will guide this research programme forward. This article is part of the theme issue 'Infectious disease macroecology: parasite diversity and dynamics across the globe'.