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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’. 

Human activities are fundamentally altering biodiversity. Projections of declines at the global scale are contrasted by highly variable trends at local scales, suggesting that biodiversity change may be spatially structured. Here, we examined spatial variation in species richness and composition change using more than 50,000 biodiversity time series from 239 studies and found clear geographic variation in biodiversity change. Rapid compositional change is prevalent, with marine biomes exceeding and terrestrial biomes trailing the overall trend. Assemblage richness is not changing on average, although locations exhibiting increasing and decreasing trends of up to about 20% per year were found in some marine studies. At local scales, widespread compositional reorganization is most often decoupled from richness change, and biodiversity change is strongest and most variable in the oceans. 

Feedbacks are an essential feature of resilient socio-economic systems, yet the feedbacks between biodiversity, ecosystem services and human wellbeing are not fully accounted for in global policy efforts that consider future scenarios for human activities and their consequences for nature. Failure to integrate feedbacks in our knowledge frameworks exacerbates uncertainty in future projections and potentially prevents us from realizing the full benefits of actions we can take to enhance sustainability. We identify six scientific research challenges that, if addressed, could allow future policy, conservation and monitoring efforts to quantitatively account for ecosystem and societal consequences of biodiversity change. Placing feedbacks prominently in our frameworks would lead to (i) coordinated observation of biodiversity change, ecosystem functions and human actions, (ii) joint experiment and observation programmes, (iii) more effective use of emerging technologies in biodiversity science and policy, and (iv) a more inclusive and integrated global community of biodiversity observers. To meet these challenges, we outline a five-point action plan for collaboration and connection among scientists and policymakers that emphasizes diversity, inclusion and open access. Efforts to protect biodiversity require the best possible scientific understanding of human activities, biodiversity trends, ecosystem functions and—critically—the feedbacks among them. 

For a half century, habitat configuration – the arrangement of habitat patches within a landscape – has been central to theories of landscape ecology, population dynamics, and community assembly, in addition to conservation strategies. A recent hypothesis advanced by Fahrig (2013) would, if supported, greatly diminish the relevance of habitat configuration as a predictor of diversity. The Habitat Amount Hypothesis posits that the sample area effect overrides patch size and patch isolation effects of habitat fragmentation on species richness. It predicts that the amount of habitat in a local landscape, regardless of configuration, is the main landscape‐level determinant of species richness. If habitat amount is indeed the major, landscape‐level driver of species richness, the slopes of the species–area relationship (SAR) for otherwise similar fragmented and unfragmented landscapes should be indistinguishable. We tested the Habitat Amount Hypothesis with data from two replicated and controlled habitat fragmentation experiments that disentangle the effects of habitat amount and configuration. One experiment provided time‐series data on plant species richness and the other on micro‐arthropod species richness. We found that, relative to less fragmented habitats, the SARs for fragmented habitats have significantly higher slopes and that the magnitude of the difference in slopes increased over time. Relatively more species were lost in smaller areas when fragments were more isolated. In both experiments, the proportion of species lost due to increased habitat fragmentation was nearly identical to the proportion lost due to reduced habitat amount. Our results provide a direct and experimentally derived refutation of the Habitat Amount Hypothesis, supporting the long‐held view that in addition to area, patch isolation and configuration are important determinants of species richness. Differences in species richness between fragmented and non‐fragmented habitats increase over time, demonstrating that long‐term studies are needed to understand the effects of fragmentation, above and beyond the amount of habitat lost.