Vincent Devictor’s research while affiliated with Center for Natural Resource Studies and other places

As biodiversity is declining, the dynamics of species interactions is a growing conservation concern. However, estimating and monitoring species interactions across large spatial and temporal scales remain challenging, and thus changes in species interactions and the subsequent networks of interactions remain relatively unexplored. Here, we assess changes in the network structure of common bird communities from France. We estimate associated species pairs using spatial and temporal information for 109 species monitored across 1,969 sites during 17 years. We validate the ecological significance of associated species pairs by testing the relationship between the propensity to be associated and species functional proximity or shared habitat preference. We reconstruct association networks for these intra-guild bird communities and track temporal changes in network layout in terms of size, density of links, modularity and degree distribution. We show that, beyond species change, birds' local association networks become smaller with a similar relative number of associations that becomes unevenly distributed. These structural changes vary among types of bird communities and may impact community functioning and how communities can cope with global change.

Aim Population dynamics are usually assessed through linear trend analysis, quantifying their general direction. However, linear trends may hide substantial variations in population dynamics that could reconcile apparent discrepancies when quantifying the extent of the biodiversity crisis. We seek to determine whether the use of non‐linear methods and the quantification of temporal variability can offer a more complete representation of changes in global population dynamics than commonly‐used linear approaches. Methods We analysed 6437 population time series from 1257 vertebrate species from the Living Planet Database over the period 1950–2020. We modelled populations through the use of second‐order polynomials and classified trajectories according to their direction and acceleration. We modelled and classified these same populations using a more classical linear trend analysis. We quantified temporal variability using the mean squared error of the fitted polynomials. We then used generalised linear mixed models to test potential sources of heterogeneity in non‐linear trajectories and temporal variability. Results In all, 44.8% of the analysed population time series were non‐linear. Across all populations, 30% were declining, 30% were increasing, and 40% were with no linear trend. Among the population showing no linear trend, half were concave or convex. Non‐linearity was expressed differently between taxonomic groups, with mammals showing higher prevalence of non‐linearity. Marine and freshwater populations were more variable than terrestrial populations, and fish were more variable than other vertebrates. Differences between geographical regions were detected in both non‐linearity and temporal variability, but no straightforward pattern emerged. There were no differences in both components between IUCN categories. Main Conclusions Non‐linearity and temporal variability reveal usually overlooked dramatic declines or recovery signals in global population dynamics. Thus, moving beyond linearity can improve our understanding of complex population dynamics and better inform conservation decisions. In particular, populations usually classified as ‘stable’ can hide informative changes in non‐linear and variability patterns that need to be considered in global biodiversity assessments.

Populations and ecological communities are changing worldwide, and empirical studies exhibit a mixture of either declining or mixed trends. Confusion in global biodiversity trends thus remains, while assessing such changes is of major social, political, and scientific importance. Part of this variability may arise from the difficulty to reliably assess global biodiversity trends. Here, we conducted a literature review of studies documenting the temporal dynamics of global biodiversity. We classified the differences among approaches, data, and methodology used by the reviewed papers to reveal common findings and sources of discrepancies. We show that reviews and meta‐analyses, along with the use of global indicators, are more likely to conclude that trends are declining. On the other hand, the longer the data are available, the more nuanced are the trends they generate. Our results also highlight the lack of studies providing information on the impact of synergistic pressures on a global scale, making it even more difficult to understand the driving factors of the observed changes and how to decide conservation plan accordingly. Finally, we stress the importance of taking into account the sources of confusion identified, as well as the complexity of biodiversity changes, in order to implement effective conservation strategies. In particular, biodiversity dynamics are almost systematically assumed to be linear, while non‐linear trends are largely neglected. Clarifying the sources of confusion in global biodiversity trends should strengthen large‐scale biodiversity monitoring and conservation.

Conservation efforts and sustainable use of natural populations often seek to reach or maintain viable abundance levels for a target population. Yet, this goal can be undermined by a number of events resulting from out-of-equilibrium dynamics, including large and sudden changes in abundance. The dynamical properties of such temporal changes are valuable indications about population's capacity to cope with environmental changes. Correctly identifying past or anticipating impending occurrences of temporal abrupt shifts in ecological systems is thus of major importance to adjust conservation and management strategies. Despite many available abrupt shift detection methods, few offer the possibility to compare and agree on the best model among linear, nonlinear, or abrupt models. By combining several existing methods, we develop an approach that classifies any timeseries to a trajectory type – no change, linear, nonlinear (quadratic), abrupt – and confirms the occurrence of potential abrupt shifts. We assessed the classification performances using a set of simulated data for which we had deterministic predictions for each type of trajectories. We used various levels of noise and perturbation events to make the simulations more realistic. This classification can be of particular interest when comparing dynamics of many populations across space or time. We show this by applying this classification approach to three different temporal datasets commonly used in conservation: catch tonnage, bird index, and insect occupancy timeseries. With this tool, we hope to promote conservation and management practices that explicitly take into account the likelihood of out-of-equilibrium trajectories and especially abrupt shifts in ecological systems.

Aim. Population dynamics are usually assessed through linear trend analysis, quantifying their general direction. However, linear trends may hide substantial variations in population dynamics that could reconcile apparent discrepancies when quantifying the extent of the biodiversity crisis. We seek to determine whether the use of non-linear methods and the quantification of temporal variability can add value to the linear approach by offering a more complete representation of global population changes. In addition, we seek to determine how these components are distributed among biogeographical regions and taxonomic groups. Location.Global.Methods.We analysed 6,437 population time series from 1,257 species from the Living Planet Database over the period 1950-2020. We modeled populations through the use of second order polynomials and classified trajectories according to their direction and acceleration. We modeled and classified these same populations using a more common linear trend analysis. We quantified temporal variability using three metrics, the coefficient of variation, the mean squared error and the consecutive disparity index. We then used chi-squared tests and linear mixed-effects models to test potential sources of heterogeneity in non-linear trajectories and temporal variability.Results.Non-linear models were a better fit for 44.8 % of the analyzed time series, and temporal variability was higher among trajectories classified as linear. Linear models missed meaningful information by misclassifying recent declines or recovery signals. Marine populations were highly variable, and all taxonomic groups or IUCN categories exhibited variability in their degree of non-linearity and temporal variability.Main conclusions.Non-linearity and temporal variability reveal usually overlooked dramatic declines or recovery signals in global population dynamics. Thus, moving beyond linearity can help reduce the risk of misleading conclusions and better inform conservation decisions. In particular, population usually classified as « stable » can hide informative non-linear and variable changes to integrate in more advanced global biodiversity assessment.

Populations and ecological communities are changing worldwide, and empirical studies exhibit a mixture of either declining or mixed trends. Confusion in global biodiversity trends thus remains while being of major social, political, and scientific importance. Part of this variability may arise from the difficulty to reliably assess global biodiversity trends. Here, we conducted a literature review of studies documenting the temporal dynamics of global biodiversity. We classified the differences among approaches, data and methodology used by the reviewed papers to reveal common findings and sources of discrepancies. We show that reviews and meta-analyses, along with the use of global indicators, are more likely to conclude that trends are declining. On the other hand, the longer the data are available, the more nuanced are the trends they generate. Our results also highlight the lack of studies providing information on the impact of synergistic pressures on a global scale, making it even more difficult to understand the driving factors of the observed changes and how to decide conservation plan accordingly. Finally, we stress the importance of taking into account the sources of confusion identified, as well as the complexity of biodiversity changes, in order to implement effective conservation strategies. In particular, biodiversity dynamics are almost systematically assumed to be linear, while non-linear trends are largely neglected. Clarifying the sources of confusion in global biodiversity trends should strengthen large scale biodiversity monitoring and conservation.

Declines in European bird populations are reported for decades but the direct effect of major anthropogenic pressures on such declines remains unquantified. Causal relationships between pressures and bird population responses are difficult to identify as pressures interact at different spatial scales and responses vary among species. Here, we uncover direct relationships between population time-series of 170 common bird species, monitored at more than 20,000 sites in 28 European countries, over 37 y, and four widespread anthropogenic pressures: agricultural intensification, change in forest cover, urbanisation and temperature change over the last decades. We quantify the influence of each pressure on population time-series and its importance relative to other pressures, and we identify traits of most affected species. We find that agricultural intensification, in particular pesticides and fertiliser use, is the main pressure for most bird population declines, especially for invertebrate feeders. Responses to changes in forest cover, urbanisation and temperature are more species-specific. Specifically, forest cover is associated with a positive effect and growing urbanisation with a negative effect on population dynamics, while temperature change has an effect on the dynamics of a large number of bird populations, the magnitude and direction of which depend on species' thermal preferences. Our results not only confirm the pervasive and strong effects of anthropogenic pressures on common breeding birds, but quantify the relative strength of these effects stressing the urgent need for transformative changes in the way of inhabiting the world in European countries, if bird populations shall have a chance of recovering.

Aim There has been a wide interest in the effect of biotic interactions on species' occurrences and abundances at large spatial scales, coupled with a vast development of the statistical methods to study them. Still, evidence for whether the effects of within‐trophic‐level biotic interactions (e.g. competition and heterospecific attraction) are discernible beyond local scales remains inconsistent. Here, we present a novel hypothesis‐testing framework based on joint dynamic species distribution models and functional trait similarity to dissect between environmental filtering and biotic interactions. Location France and Finland. Taxon Birds. Methods We estimated species‐to‐species associations within a trophic level, independent of the main environmental variables (mean temperature and total precipitation) for common species at large spatial scale with joint dynamic species distribution (a multivariate spatiotemporal delta model) models. We created hypotheses based on species' functionality (morphological and/or diet dissimilarity) and habitat preferences about the sign and strength of the pairwise spatiotemporal associations to estimate the extent to which they result from biotic interactions (competition, heterospecific attraction) and/or environmental filtering. Results Spatiotemporal associations were mostly positive (80%), followed by random (15%), and only 5% were negative. Where detected, negative spatiotemporal associations in different communities were due to a few species. The relationship between spatiotemporal association and functional dissimilarity among species was negative, which fulfils the predictions of both environmental filtering and heterospecific attraction. Main conclusions We showed that processes leading to species aggregation (mixture between environmental filtering and heterospecific attraction) seem to dominate assembly rules, and we did not find evidence for competition. Altogether, our hypothesis‐testing framework based on joint dynamic species distribution models and functional trait similarity is beneficial in ecological interpretation of species‐to‐species associations from data covering several decades and biogeographical regions.

Population sizes of many birds are declining alarmingly and methods for estimating fluctuations in species' abundances at a large spatial scale are needed. The possibility to derive indicators from the tendency of specific species to co-occur with others has been overlooked. Here, we tested whether the abundance of resident titmice can act as a general ecological indicator of forest bird density in European forests. Titmice species are easily identifiable and have a wide distribution, which makes them potentially useful ecological indicators. Migratory birds often use information on the density of resident birds, such as titmice, as a cue for habitat selection. Thus, the density of residents may potentially affect community dynamics. We examined spatio-temporal variation in titmouse abundance and total bird abundance, each measured as biomass, by using long-term citizen science data on breeding forest birds in Finland and France. We analyzed the variation in observed forest bird density (excluding titmice) in relation to titmouse abundance. In Finland, forest bird density linearly increased with titmouse abundance. In France, forest bird density nonlinearly increased with titmouse abundance, the association weakening toward high titmouse abundance. We then analyzed whether the abundance (measured as biomass) of random species sets could predict forest bird density better than titmouse abundance. Random species sets outperformed titmice as an indicator of forest bird density only in 4.4% and 24.2% of the random draws, in Finland and France, respectively. Overall, the results suggest that titmice could act as an indicator of bird density in Northern European forest bird communities, encouraging the use of titmice observations by even less-experienced observers in citizen science monitoring of general forest bird density.