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Evaluating the effectiveness of conservation actions is challenging for migratory species because a population can be impacted anywhere along its route. Conservation actions for the critically endangered Fennoscandian lesser white-fronted goose population include culling of red foxes in the breeding area and habitat improvements and reduction of illegal hunting in the non-breeding areas. One goal of the predator control strategy is to prevent adult birds from using an autumn migration route through western Asia, where mortality is believed to be higher than on the migration route through eastern Europe. We used 23 years of count data obtained at different staging areas to parameterize a seasonal state-space model describing the full-annual cycle dynamics of this population and evaluate whether the recent population recovery was linked to these conservation efforts. The results did not provide evidence that predator control influenced population recovery, as survival on the European route did not appear higher than on the allegedly riskier Asian route. However, adult survival at staging areas on both routes and at wintering sites may have improved in the last decade, suggesting a positive effect of the other conser- vation initiatives. These results emphasize the importance of including the non-breeding dynamics in population assessments of migratory species and highlight the challenge of evaluating the efficacy of separate conservation actions when a proper experimental design is unfeasible. Our study, which is a unique case of cross-national, coordinated conservation efforts, exemplifies how to model complex population dynamics to assess the influ- ence of costly conservation initiatives. Goose management State-space model Management evaluation Lesser whitefronted goose Unmarked individuals Non-breeding dynamics

Assessing the effectiveness of conservation actions to halt population declines is challenging when confounded by other factors. We assessed whether culling of red fox, a predator currently increasing in number in the sub‐Arctic, contributed to recent recovery of the critically endangered Fennoscandian population of Lesser White‐fronted Goose Anser erythropus, while controlling for potentially confounding food web dynamics. Using 19 years of data, 10 before and 9 after the implementation of annual red fox culling, we estimated the effect of this action on annual performance of the goose population. We corrected for the potentially confounding effects of cyclic rodent dynamics and semi‐domestic reindeer carrion abundance, both of which are expected to trigger predator functional and numerical responses, as well as for annual variation in spring phenology. Goose reproductive success fluctuated in synchrony with the rodent cycle and was negatively related to abundant carrion. When accounting for these aspects of food web dynamics, there was no evidence for an effect of red fox culling on reproductive success. There was, however, a tendency for fox culling to increase adult survival. Our analysis suggests that goose performance in their breeding area is influenced by fluctuating offspring predation, mediated by mainly natural (rodents) and partly anthropogenic (semi‐domestic reindeer) dynamic components of the food web. Synthesis and applications. The effect of a decade‐long red fox culling on goose reproductive success and survival is currently uncertain, despite predation driving reproductive success through changes in rodent and reindeer carrion abundance. New management actions may consist of regulation of reindeer herd sizes and/or removal of carcasses to reduce the subsidizing effect of reindeer carrion on mesopredators. Getting robust evidence regarding the impact of red fox culling on population recovery depends on continuing research to disentangle food web dynamics and efficiency of management actions.

Scientists and wildlife managers implementing adaptive monitoring and management schemes, are tasked with providing predictions of population responses to harvest and environmental changes. Such predictions are useful not only to forecast direct effects of climate, productivity, land use, or habitat degradation, but also changes in the food web, such as expanding/�increasing species that are predators, prey, and competitors of populations of concern. Explicit consideration of food webs and their dynamics in more complex models could provide better predictions of future changes, and allow us to better assess the influence of management actions. Here, we present our perspective on what we have learned from conducting a number of case studies using such a food web approach with a focus on climate and harvest impacts and their implications for management. We found empirical support for many of our hypothesized food web effects, and were able in some cases to obtain short-term forecasts with slightly lower prediction error using models that account for food web dynamics compared with simpler models. Predictions are the foundation of adaptive management because they allow quantitative assessment of the effects of management actions; however, evaluating predictions requires adequate and high-quality monitoring data. Results from our case studies show that a combination of long-term monitoring and different types of study designs coupled with models of adequate complexity are likely required to better understand populations’ responses to environmental changes and harvest, as well as the consequences for food webs.

The impact of climate change on the dynamics of populations has been well documented and is widespread. However, weather variability influences populations both directly and indirectly, and is mediated by species interactions. This complexity may impede proper climate impact assessments. Hence, predicting the consequences of climate change may require including processes that occur both with time lags and across trophic levels. Based on our current understanding of the mechanisms linking local climate and trophic interactions in tundra ecosystems, we used a state-space formulation of a mediation model that allowed for assessing the relative contribution of direct and indirect environmental (weather and trophic) effects on reindeer Rangifer tarandus reproductive success. Our study showed that the mediator effect of body condition caused delayed but predictable effects of weather, plant productivity, and reindeer densities on reproductive success. Furthermore, these predictors also affected reproductive success directly and with the same sign, suggesting that direct and indirect effects pulled in the same direction with respect to their combined total effect on reproductive success. Hence, poor weather conditions not only affect calf production negatively the same year, but also increase the likelihood of poor reproductive success the subsequent year. The results support the expectation that calf slaughter mass (as a proxy for herd body condition) is an important indicator of the state of reindeer herds with respect to their production potential and resilience to weather events and climate change. Finally, the model framework employed in the present study can be further developed as a potential vehicle for near-term forecasting, and thereby constitutes a useful tool for adaptive management.

Sustainable management of wildlife populations can be aided by building models that both identify current drivers of natural dynamics and provide near-term predictions of future states. We employed a Strategic Foresight Protocol (SFP) involving stakeholders to decide the purpose and structure of a dynamic state-space model for the population dynamics of the Willow Ptarmigan, a popular game species in Norway. Based on local knowledge of stakeholders, it was decided that the model should include food web interactions and climatic drivers to provide explanatory predictions. Modeling confirmed observations from stakeholders that climate change impacts Ptarmigan populations negatively through intensified outbreaks of insect defoliators and later onset of winter. Stakeholders also decided that the model should provide anticipatory predictions. The ability to forecast population density ahead of the harvest season was valued by the stakeholders as it provides the management extra time to consider appropriate harvest regulations and communicate with hunters prior to the hunting season. Overall, exploring potential drivers and predicting short-term future states, facilitate collaborative learning and refined data collection, monitoring designs, and management priorities. Our experience from adapting a SFP to a management target with inherently complex dynamics and drivers of environmental change, is that an open, flexible, and iterative process, rather than a rigid step-wise protocol, facilitates rapid learning, trust, and legitimacy. climate change; decision-making; food web; harvesting; near-term forecasting; population cycles; stakeholders; strategic foresight.

International audience; A conspicuous season-diversity relationship (SDR) can be seen in seasonal environments , often with a defined peak in active species diversity in the growing season. We ask is this a general pattern and are other patterns possible? In addition, we ask what is the ultimate cause of this pattern and can we understand it using existing ecological theory? To accomplish this task, we assembled a global database on changes in species diversity through time in seasonal environments for different taxa and habitats and also conducted a modeling study in an attempt to replicate observed patterns. Our global database includes terrestrial and aquatic habitats, temperate, tropical, and polar environments, and taxa from disparate groups including vertebrates, insects, and plankton. We constructed nine alternative models that vary in assumptions on type of seasonal forcing, responses to that forcing, species niches, and types of species interactions. We found that most guilds of species exhibit a repeatable SDR across years. For north temperate ecosystems, active species diversity generally peaks midyear. The peak for a guild is generally more pronounced in terrestrial habitats than aquatic habitats and more pronounced in temperate and polar regions than the tropics. We now have evidence that at least several different habitat and taxa types are likely to have multiple peaks in diversity in a year, for example, guilds of both aquatic microbes and desert vertebrates can show a bimodal or multimodal SDR. We compared all nine candidate models in their ability to explain the patterns and match their assumptions to the data. Some performed considerably better than others in being able to match the different patterns. We conclude that a model that includes both temperature niches and environmental feedbacks is necessary to explain the different SDRs. We use such a model to make predictions about how the SDR could be impacted by climate change. More effort should be put into documenting and understanding baseline seasonal patterns in diversity in order to predict future responses to global change.

Manuscript. Published version available in Oecologia, Dec. 2016, vol. 182, issue 4, pp 1175–1185 Biodiversity can be measured by taxonomic, phylogenetic, and functional diversity. How ecosystem functioning depends on these measures of diversity can vary from site to site and depends on successional stage. Here, we measured taxonomic, phylogenetic, and functional diversity, and examined their relationship with biomass in two successional stages of the broad-leaved Korean pine forest in northeastern China. Functional diversity was calculated from six plant traits, and aboveground biomass (AGB) and coarse woody productivity (CWP) were estimated using data from three forest censuses (10 years) in two large fully mapped forest plots (25 and 5 ha). 11 of the 12 regressions between biomass variables (AGB and CWP) and indices of diversity showed significant positive relationships, especially those with phylogenetic diversity. The mean tree diversity-biomass regressions increased from 0.11 in secondary forest to 0.31 in old-growth forest, implying a stronger biodiversity effect in more mature forest. Multi-model selection results showed that models including species richness, phylogenetic diversity, and single functional traits explained more variation in forest biomass than other candidate models. The models with a single functional trait, i.e., leaf area in secondary forest and wood density in mature forest, provided better explanations for forest biomass than models that combined all six functional traits. This finding may reflect different strategies in growth and resource acquisition in secondary and old-growth forests.

International audience; In forested ecosystems, it remains unclear whether environmental conditions, resource competition or their joint effects explain non-randomly distributed species pattern. Recently, trait-based approaches have been recognized as an important tool to infer processes governing community assembly patterns. In this study, we quantify patterns of functional composition and diversity to study how tree species coexistence is influenced by abiotic factors and biotic interactions in a species-rich temperate old-growth forest. In a 25 ha (500 × 500 m) fully mapped forest plot, we calculated functional composition (community weighted mean) and diversity of five key traits considering two spatial scales (20 × 20 and 50 × 50 m quadrats). We compared the observed patterns in functional diversity with randomly generated null communities to test for the presence of non-random patterns in community assembly, and studied the variation of functional composition and diversity along gradients of soil conditions to test for the shift in assembly processes along resource gradients. Functional diversity differed from null expectations depending on the spatial scale considered. In broad-scale quadrats (50 × 50 m), functional diversity in wood specific gravity (WSG) and leaf area (LA) was lower than expected by chance, whereas functional diversity in specific root length (SRL) was greater than expected. In small quadrats (20 × 20 m), functional diversity was lower than expected by chance in specific leaf area (SLA) and when considering all traits in combination. Functional composition and diversity varied along the soil resource gradient but the results were dependent on the scale considered. We found an increase in functional composition in maximum height (H) and WSG and a reduction in the functional diversity in most of traits suggesting an increase in competition with the increase in soil water content at small scale. The trait dispersion pattern for all traits in combination had no directional changes with some of individual traits generating more clear dispersion trend when the dominant competitor Pinus koraiensis was removed from the community dataset. The results presented here suggest that community assembly is governed by non-random processes in the studied forests. Interestingly, the choice of quadrat size seems to be crucial to describe community patterns and infer the forces governing community assembly. The consideration of different traits and environmental gradients allowed us to discover that different assembly mechanisms operate simultaneously in the studied forest.

A recent theory of the vertical distribution of phytoplankton considers how interacting niche construction processes such as resource depletion, behavior, and population dynamics contribute to spatial heterogeneity in the aquatic environment. In poorly mixed water columns with opposing resource gradients of nutrients and light, theory predicts that a species should aggregate at a single depth. This depth of aggregation, or biomass maximum, should change through time due to depletion of available resources. In addition, the depth of the aggregation should be deeper under low amounts of nutrient loading and shallower under higher amounts of nutrient loading. Theory predicts total biomass to exhibit a saturating relationship with nutrient supply. A surface biomass maximum limited by light and a deep biomass maximum limited by nutrients or co-limited by nutrients and light is also predicted by theory. To test this theory, we used a motile phytoplankton species (Chlamydomonas reinhardtii) growing in cylindrical plankton towers. In our experiment, the resource environment was strongly modified by the movement, self-shading, nutrient uptake, and growth of the phytoplankton. Supporting predictions, we routinely observed a single biomass maximum at the surface throughout the course of the experiment and at equilibrium under higher nutrient loading. However, at equilibrium, low nutrient loading led to a non-distinct biomass maximum with the population distributed over most of the water column instead of the distinct subsurface peak predicted by theory. Also supporting predictions, total biomass across water columns was positively related to nutrient supply but saturating at high nutrient supply conditions. Further supporting predictions, we also found evidence of light limitation for a surface biomass maximum and nutrient limitation for the deep biomass when no surface maximum was present. In addition, the light level leaving the bottom of the water column declined through time as the phytoplankton grew and was negatively related to nutrient loading. Nutrients were strongly depleted where biomass was present by the end of the experiment. This experimental study shows that the vertical distribution of phytoplankton may be driven by intraspecific resource competition in space.

According to recent reviews, the question of how trophic interactions may affect evolutionary responses to climate change remains unanswered. In this modelling study, we explore the evolutionary dynamics of thermal and plant–herbivore interaction traits in a warming environment. We find the herbivore usually reduces adaptation speed and persistence time of the plant by reducing biomass. However, if the plant interaction trait and thermal trait are correlated, herbivores can create different coevolutionary attractors. One attractor has a warmer plant thermal optimum, and the other a colder one compared with the environment. A warmer plant thermal strategy is given a head start under warming, the only case where herbivores can increase plant persistence under warming. Persistence time of the plant under warming is maximal at small or large thermal niche width. This study shows that considering trophic interactions is necessary and feasible for understanding how ecosystems respond to climate change.

International audience; Here, we address the essential question of whether, in the context of evolving populations, ecosystems attain properties that enable persistence of the ecosystem itself. We use a simple ecosystem model describing resource, producer, and consumer dynamics to analyze how evolution affects dynamical stability properties of the ecosystem. In particular, we compare resilience of the entire system after allowing the producer and consumer populations to evolve to their evolutionarily stable strategy (ESS) to the maximum attainable resilience. We find a substantial reduction in ecosystem resilience when producers and consumers are allowed to evolve compared to the maximal attainable resilience. This study illustrates the inherent difference and possible conflict between maximizing individual-level fitness and maximizing resilience of entire ecosystems.

What determines the vertical distribution of phytoplankton in different aquatic environments remains an open question. To address this question, we develop a model to explore how phytoplankton respond through growth and movement to opposing resource gradients and different mixing conditions. We assume stratification creates a well-mixed surface layer on top of a poorly mixed deep layer and nutrients are supplied from multiple depth-dependent sources. Intraspecific competition leads to a unique strategic equilibrium for phytoplankton, which allows us to classify the distinct vertical distributions that can exist. Biomass can occur as a benthic layer (BL), a deep chlorophyll maximum (DCM), or in the mixed layer (ML), or as a combination of BL+ML or DCM+ML. The ML biomass can be limited by nutrients, light, or both. We predict how the vertical distribution, relative resource limitation, and biomass of phytoplankton will change across environmental gradients. We parameterized our model to represent potentially light and phosphorus limited freshwater lakes, but the model is applicable to a broad range of vertically stratified systems. Increasing nutrient input from the sediments or to the mixed layer increases light limitation, shifts phytoplankton towards the surface, and increases total biomass. Increasing background light attenuation increases light limitation, shifts the phytoplankton towards the surface, and generally decreases total biomass. Increasing mixed layer depth increases, decreases, or has no effect on light limitation and total biomass. Our model is able to replicate the diverse vertical distributions observed in nature and explain what underlying mechanisms drive these distributions.

Phytoplankton compete for nutrients and light in a vertically heterogeneous environment determined by turbulent mixing. We analyzed a model of competition between two phytoplankton species in a stratified water column. We assume that the surface layer is uniformly mixed and that the deep layer is poorly mixed, as is commonly observed in lakes and oceans. We employed two analytical techniques, I(out) - (R)theory in the mixed surface layer and a game theoretical approach in the deep layer. Under our assumptions, at equilibrium, each species is either absent or resides in the benthic layer, the deep layer, or the surface layer. Assuming a trade-off between nutrient- and light-competitive abilities, we obtained five spatial configurations of coexistence and the corresponding parameter regions where they occur. Good light competitors show two distinct ecological niches: in mesotrophic conditions, they live as understory species below a layer of good nutrient competitors; in eutrophic conditions, they live as competitive dominants in the surface layer. Multiple regions of alternative stable states are possible in parameter space. This work extends previous phytoplankton competition theory to stratified water columns, as commonly found in lakes and oceans.