1. Aggregated species occurrence and abundance data from disparate sources are increasingly accessible to ecologists for the analysis of temporal trends in biodiversity. However, sampling biases relevant to any given research question are often poorly explored and infrequently reported; this can undermine statistical inference. In other disciplines, it is common for researchers to complete 'risk-ofbias' assessments to expose and document the potential for biases to undermine conclusions. The huge growth in available data, and recent controversies surrounding their use to infer temporal trends, indicate that similar assessments are urgently needed in ecology.2. We introduce ROBITT, a structured tool for assessing the 'Risk-Of-Bias In studies of Temporal Trends in ecology'. ROBITT has a similar format to its counterparts in other disciplines: it comprises signalling questions designed to elicit information on the potential for bias in key study domains. In answering these, users will define study inferential goal(s) and relevant statistical target populations. This information is used to assess potential sampling biases across domains relevant to the research question (e.g. geography, taxonomy, environment), and how these vary through time. If assessments indicate biases, then users must clearly describe them and/or explain what mitigating action will be taken.3. Everything that users need to complete a ROBITT assessment is provided: the tool, a guidance document and a worked example. Following other disciplines, the tool and guidance document were developed through a consensus-forming process across experts working in relevant areas of ecology and evidence synthesis.

Biodiversity-ecosystem functioning and food-web complexity-stability relationships are central to ecology. However, they remain largely untested in natural contexts. Here, we estimated the links among environmental conditions, richness, food-web structure, annual biomass and its temporal stability using a standardised monitoring dataset of 99 stream fish communities spanning from 1995 to 2018. We first revealed that both richness and average trophic level are positively related to annual biomass, with effects of similar strength. Second, we found that community stability is fostered by mean trophic level, while contrary to expectation, it is decreased by species richness. Finally, we found that environmental conditions affect both biomass and its stability mainly via effects on richness and network structure. Strikingly, the effect of species richness on community stability was mediated by population stability rather than synchrony, which contrasts with results from single trophic communities. We discuss the hypothesis that it could be a characteristic of multi-trophic communities.

Some ecosystems show nonlinear responses to gradual changes in environmental conditions, once a threshold in conditions—or critical point—is passed. This can lead to wide shifts in ecosystem states, possibly with dramatic ecological and economic consequences. Such behaviours have been reported in drylands, savannas, coral reefs or shallow lakes for example. Important research effort of the last decade has been devoted to identifying indicators that would help anticipate such ecosystem shifts and avoid their negative consequences. Theoretical and empirical research has shown that, as an ecosystem approaches a critical point, specific signatures arise in its temporal and spatial dynamics; these changes can be quantified using relatively simple statistical metrics that have been referred to as “early warning signals” (EWS) in the literature. Although tests of those EWS on experiments are promising, empirical evidence from out‐of‐laboratory datasets is still scarce, in particular for spatial EWS. The recent proliferation of remote‐sensing data provides an opportunity to improve this situation and evaluate the reliability of spatial EWS in many ecological systems. Here, we present a step‐by‐step workflow along with code to compute spatial EWS from raster data such as aerial images, test their significance compared to permutation‐based null models, and display their trends, either at different time steps or along environmental gradients. We created the R‐package spatialwarnings (MIT license) to help achieve all these steps in a reliable and reproducible way, and thereby promote the application of spatial EWS to empirical data. This software package and associated documentation provides an easy entry point for researchers and managers into spatial EWS‐based analyses. By facilitating a broader application, it will leverage the evaluation of spatial EWS on real data, and eventually contribute to providing tools to map ecosystems’ fragility to perturbations and inform management decisions.

Facilitation among plants mediated by grazers occurs when an unpalatable plant extends its protection against grazing to another plant. This type of indirect facilitation impacts species coexistence and ecosystem functioning in a large array of ecosystems worldwide. It has nonetheless generally been understudied so far in comparison with the role played by direct facilitation among plants. We aimed at providing original data on indirect facilitation at the community scale to determine the extent to which indirect facilitation mediated by grazers can shape plant communities. Such experimental data are expected to contribute to refining the conceptual framework on plant–plant–herbivore interactions in stressful environments. We set up a 2‐year grazing exclusion experiment in tropical alpine peatlands in Bolivia. Those ecosystems depend entirely on a few, structuring cushion‐forming plants (hereafter referred to as “nurse” species), in which associated plant communities develop. Fences have been set over two nurse species with different strategies to cope with grazing (direct vs. indirect defenses), which are expected to lead to different intensities of indirect facilitation for the associated communities. We collected functional traits which are known to vary according to grazing pressure (LDMC, leaf thickness, and maximum height), on both the nurse and their associated plant communities in grazed (and therefore indirect facilitation as well) and ungrazed conditions. We found that the effect of indirectly facilitated on the associated plant communities depended on the functional trait considered. Indirect facilitation decreased the effects of grazing on species relative abundance, mean LDMC, and the convergence of the maximum height distribution of the associated communities, but did not affect mean height or cover. The identity of the nurse species and grazing jointly affected the structure of the associated plant community through indirect facilitation. Our results together with the existing literature suggest that the “grazer–nurse–beneficiary” interaction module can be more complex than expected when evaluated in the field.