Environmental change is becoming synchronous across sites with frequent emergence of extremes in recent years, with potential impacts on species’ synchronous abundance over large scales. Analyzing 41 years of breeding bird survey data across North America, we observed that some birds showed mostly lower tail-dependent spatial synchrony (i.e., synchrony across sites at low abundances), while others showed mostly upper tail-dependent spatial synchrony (i.e., synchrony across sites at high abundances). We found that spatial synchrony in climate extremes (i.e., tail-dependence in climate), not the dispersal trait (hand-wing index), drove the spatial synchrony in abundance extremes (i.e., tail-dependence in abundance) up to 250 Km. Tail-dependence in high (or low, respectively) temperature across sites caused lower (or upper, respectively) tail-dependent spatial synchrony in abundance. In a rapidly changing environment, these findings highlight the importance of considering synchronized climatic extremes to assess species’ tail-dependent spatial synchrony across large scales.

Biodiversity may increase ecosystem resilience. However, we have limited understanding if this holds true for ecosystems that respond to gradual environmental change with abrupt shifts to an alternative state. We used a mathematical model of anoxic-oxic regime shifts and explored how trait diversity in three groups of bacteria influences resilience. We found that trait diversity did not always increase resilience: greater diversity in two of the groups increased but in one group decreased resilience of their preferred ecosystem state. We also found that simultaneous trait diversity in multiple groups often led to reduced or erased diversity effects. Overall, our results suggest that higher diversity can increase resilience but can also promote collapse when diversity occurs in a functional group that negatively influences the state it occurs in. We propose this mechanism as a potential management approach to facilitate the recovery of a desired ecosystem state.

The potential for forecasting the dynamics of ecological systems is currently unclear, with contrasting opinions regarding its feasibility due to ecological complexity. To investigate forecast skill within and across system complexity, we monitored a microbial system exposed to either constant or fluctuating temperatures in a five months long laboratory experiment. We tested how forecasting of species abundances depends on number and strength of interactions and on model size (number of predictors). We also tested how greater system complexity (i.e. the fluctuating temperatures) impacted these relations. We found that the more a species interacted, the weaker these interactions were and the better its abundance was predicted. Forecast skill increased with model size. Greater system complexity decreased forecast skill for three out of eight species. These insights into how abundance prediction depends on the embedding of the species within the system and on overall system complexity could improve species forecasting and monitoring.

1) Food web models explain and predict the trophic interactions in a food web, and they can infer missing interactions among the organisms. The allometric diet breadth model (ADBM) is a food web model based on the foraging theory. In the ADBM the foraging parameters are allometrically scaled to body sizes of predators and prey. In Petchey et al. (2008), the parameterisation of the ADBM had two limitations: (a) the model parameters were point estimates, and (b) food web connectance was not estimated. 2) The novelty of our current approach is: (a) we consider multiple predictions from the ADBM by parameterising it with approximate Bayesian computation, to estimate parameter distributions and not point estimates. (b) Connectance emerges from the parameterisation, by measuring model fit using the true skill statistic, which takes into account prediction of both the presences and absences of links. 3) We fit the ADBM using approximate Bayesian computation to 16 observed food webs from a wide variety of ecosystems. Connectance was consistently overestimated in the new parameterisation method. In some of the food webs, considerable variation in estimated parameter distributions occurred, and resulted in considerable variation (i.e. uncertainty) in predicted food web structure. 4) We conclude that the observed food web data is likely missing some trophic links that do actually occur, and that the ADBM likely predicts some links that do not exist. The latter could be addressed by accounting in the ADBM for additional traits other than body size. Further work could also address the significance of uncertainty in parameter estimates for predicted food web responses to environmental change.

While environmental science, and ecology in particular, is working to provide better understanding to base sustainable decisions on, the way scientific understanding is developed can at times be detrimental to this cause. Locked-in debates are often unnecessarily polarized and can compromise any common goals of the opposing camps. The present paper is inspired by a resolved debate from an unrelated field of psychology where Nobel laureate David Kahneman and Garry Klein turned what seemed to be a locked-in debate into a constructive process for their fields. The present paper is also motivated by previous discourses regarding the role of thresholds in natural systems for management and governance, but its scope of analysis targets the scientific process within complex social-ecological systems in general. We identified five features of environmental science that appear to predispose for locked-in debates: 1) The strongly context dependent behaviour of ecological systems. 2) The dominant role of single hypothesis testing. 3) The high prominence given to theory demonstration compared investigation. 4) The effect of urgent demands to inform and steer policy. This fertile ground is further cultivated by human psychological aspects as well as the structure of funding and publication systems.

1. Metadata plays an essential role in the long term preservation, reuse, and interoperability of data. Nevertheless, creating useful metadata can be sufficiently difficult and weakly-enough incentivised that many datasets may be accompanied by little or no metadata. One key challenge is, therefore, how to make metadata creation easier and more valuable. We present a solution that involves creating domain specific metadata schemes that are as complex as necessary and as simple as possible. These goals are achieved by co-development between a metadata expert and the researchers (i.e. the data creators). The final product is a bespoke metadata scheme into which researchers can enter information (and validate it) via the simplest of interfaces: a web browser application and a spreadsheet. 2.We provide the R package [‘dmdScheme‘](https://CRAN.R-project.org/package=dmdScheme) [@Krug2019] for creating a template domain specific scheme. We describe how to create a domain specific scheme from this template, including the iterative co-development process, and the simple methods for using the scheme, and simple methods for quality assessment, improvement, and validation. 3.The process of developing a metadata scheme following the outlined approach was successful, resulting in a metadata scheme which is used for the data generated in our research group. The validation quickly identifies forgotten metadata, as well as inconsistent metadata, therefore improving the quality of the metadata. Multiple output formats are available, including XML. 4. Making the provision of metadata easier while also ensuring high quality must be a priority for data curation initiatives. We show how both objectives are achieved by very close collaboration between metadata experts and researchers to create domain specific schemes. A near-future priority is to provide methods to interface domain specific schemes with general metadata schemes, such as the Ecological Metadata Language, to increase interoperability.

Theory and some evidence suggest that biodiversity promotes stability. However, evidence of how trophic interactions and environmental changes modulate this relationship in multitrophic communities is lacking. Given the current scenario of biodiversity loss and climate changes, where top predators are disproportionately more affected, filling these knowledge gaps is crucial. We simulated climate warming and top predator loss in natural microcosms to investigate their direct and indirect effects on temporal stability of microbial communites. We also investigated the role of underlying stabilizing mechanisms on community stability. Community stability was insensitive to warming, but indirectly decreased due to top predator loss via increased mesopredator abundance and consequent reduction of species asynchrony and stability. The magnitude of destabilizing effects differed among trophic levels, being disproportionally higher at lower trophic levels (e.g. producers). Our study unravels major patterns and causal mechanisms by which trophic downgrading destabilizes large food webs, regardless of climate warming scenarios.