Intransitive Stability Collapses Under the Influence of Dominant Competitors.

AbstractIntransitive competition has received much attention over the past decade. Indeed, these cyclic arrangements of species interactions have the potential to promote and stabilize species coexistence. However, the importance of intransitive interactions in real-world species-rich communities containing a mixture of hierarchic and intransitive interactions remains unknown. Here, using simulations, we explore the behavior of intransitive loops when they interact with outer competitors, as would be expected in real-world communities. Our results show that dominant competitors often cancel the beneficial effects of intransitive loops of inferior competitors. These results call for caution when inferring beneficial effects of intransitivity on species coexistence. Although intransitive loops are a frequent motif in competition networks, their positive effects on species coexistence may be less important than previously thought. The specific properties of a subnetwork-such as stabilization by intransitive loops-should thus not be interpreted independently of the global network.

A spatially explicit trait-based approach uncovers changes in assembly processes under warming.

The re-assembly of plant communities during climate warming depends on several concurrent processes. Here, we present a novel framework that integrates spatially explicit sampling, plant trait information and a warming experiment to quantify shifts in these assembly processes. By accounting for spatial distance between individuals, our framework allows separation of potential signals of environmental filtering from those of different types of competition. When applied to an elevational transplant experiment in the French Alps, we found common signals of environmental filtering and competition in all communities. Signals of environmental filtering were generally stronger in alpine than in subalpine control communities, and warming reduced this filter. Competition signals depended on treatments and traits: Symmetrical competition was dominant in control and warmed alpine communities, while hierarchical competition was present in subalpine communities. Our study highlights how distance-dependent frameworks can contribute to a better understanding of transient re-assembly dynamics during environmental change.

Lowland plant arrival in alpine ecosystems facilitates a decrease in soil carbon content under experimental climate warming.

Climate warming is releasing carbon from soils around the world, constituting a positive climate feedback. Warming is also causing species to expand their ranges into new ecosystems. Yet, in most ecosystems, whether range expanding species will amplify or buffer expected soil carbon loss is unknown. Here, we used two whole-community transplant experiments and a follow-up glasshouse experiment to determine whether the establishment of herbaceous lowland plants in alpine ecosystems influences soil carbon content under warming. We found that warming (transplantation to low elevation) led to a negligible decrease in alpine soil carbon content, but its effects became significant and 52% ± 31% (mean ± 95% confidence intervals) larger after lowland plants were introduced at low density into the ecosystem. We present evidence that decreases in soil carbon content likely occurred via lowland plants increasing rates of root exudation, soil microbial respiration, and CO2 release under warming. Our findings suggest that warming-induced range expansions of herbaceous plants have the potential to alter climate feedbacks from this system, and that plant range expansions among herbaceous communities may be an overlooked mediator of warming effects on carbon dynamics.

In a terrestrial ecosystem, the carbon cycle primarily represents the balance between plants consuming carbon dioxide from the atmosphere and soil microbes releasing carbon stored in the soil into the atmosphere (mostly as carbon dioxide). Given that carbon dioxide traps heat in the atmosphere, the balance of carbon inputs and outputs from an ecosystem can have important consequences for climate change. Rising temperatures caused by climate warming have led plants from lowland ecosystems to migrate uphill and start growing in alpine ecosystems, where temperatures are lower and most carbon is stored in the soil. Soil microbes use carbon stored in the soil and exuded from plants to grow, and they release this carbon ­ in the form of carbon dioxide ­ into the atmosphere through respiration. Walker et al. wanted to know how the arrival of lowland plants in alpine ecosystems under climate warming would affect carbon stores in the soil. To answer this question, Walker et al. simulated warmer temperatures by moving turfs (plants and soil) from alpine ecosystems to a warmer downhill site and planting lowland plants into the turfs. They compared the concentration of soil carbon in these turfs to that of soil in alpine turfs that had not been moved downhill and had no lowland plants. Their results showed that the warmed turfs containing lowland plants had a lower concentration of soil carbon. This suggests that climate warming will lead to more soil carbon being released into the atmosphere if lowland plants also migrate into alpine ecosystems. Walker et al. also wanted to know the mechanism through which lowland plants were decreasing soil carbon concentration under warming. They find that lowland plants probably release more small molecules into the soil than alpine plants. Soil microbes use the carbon and nutrients in these molecules to break down more complex molecules in the soil, thereby releasing nutrients and carbon that can then be used in respiration. This finding suggests that soil microbes breakdown and respire native soil carbon faster in the presence of lowland plants, releasing more carbon dioxide into the atmosphere and reducing carbon stores in the soil. Walker et al.'s results reveal a new mechanism through which uphill migration of lowland plants could increase the effects of climate change, in a feedback loop. Further research as to whether this mechanism occurs in different regions and ecosystems could help to quantify the magnitude of this feedback and allow scientists to make more accurate predictions about climate change.

The diversity of biotic interactions complements functional and phylogenetic facets of biodiversity.

Taxonomic, functional, and phylogenetic diversities are important facets of biodiversity. Studying them together has improved our understanding of community dynamics, ecosystem functioning, and conservation values.1-3 In contrast to species, traits, and phylogenies, the diversity of biotic interactions has so far been largely ignored as a biodiversity facet in large-scale studies. This neglect represents a crucial shortfall because biotic interactions shape community dynamics, drive important aspects of ecosystem functioning,4-7 provide services to humans, and have intrinsic conservation value.8,9 Hence, the diversity of interactions can provide crucial and unique information with respect to other diversity facets. Here, we leveraged large datasets of trophic interactions, functional traits, phylogenies, and spatial distributions of >1,000 terrestrial vertebrate species across Europe at a 10-km resolution. We computed the diversity of interactions (interaction diversity [ID]) in addition to functional diversity (FD) and phylogenetic diversity (PD). After controlling for species richness, surplus and deficits of ID were neither correlated with FD nor with PD, thus representing unique and complementary information to the commonly studied facets of diversity. A three-dimensional mapping allowed for visualizing different combinations of ID-FD-PD simultaneously. Interestingly, the spatial distribution of these diversity combinations closely matched the boundaries between 10 European biogeographic regions and revealed new interaction-rich areas in the European Boreal region and interaction-poor areas in Central Europe. Our study demonstrates that the diversity of interactions adds new and ecologically relevant information to multifacetted, large-scale diversity studies with implications for understanding eco-evolutionary processes and informing conservation planning.

Plant community impact on productivity: Trait diversity or key(stone) species effects?

Outside controlled experimental plots, the impact of community attributes on primary productivity has rarely been compared to that of individual species. Here, we identified plant species of high importance for productivity (key species) in >29,000 diverse grassland communities in the European Alps, and compared their effects with those of community-level measures of functional composition (weighted means, variances, skewness and kurtosis). After accounting for the environment, the five most important key species jointly explained more deviance of productivity than any measure of functional composition alone. Key species were generally tall with high specific leaf areas. By dividing the observations according to distinct habitats, the explanatory power of key species and functional composition increased and key-species plant types and functional composition-productivity relationships varied systematically, presumably because of changing interactions and trade-offs between traits. Our results advocate for a careful consideration of species' individual effects on ecosystem functioning in complement to community-level measures.

Cascading effects of moth outbreaks on subarctic soil food webs.

The increasing severity and frequency of natural disturbances requires a better understanding of their effects on all compartments of biodiversity. In Northern Fennoscandia, recent large-scale moth outbreaks have led to an abrupt change in plant communities from birch forests dominated by dwarf shrubs to grass-dominated systems. However, the indirect effects on the belowground compartment remained unclear. Here, we combined eDNA surveys of multiple trophic groups with network analyses to demonstrate that moth defoliation has far-reaching consequences on soil food webs. Following this disturbance, diversity and relative abundance of certain trophic groups declined (e.g., ectomycorrhizal fungi), while many others expanded (e.g., bacterivores and omnivores) making soil food webs more diverse and structurally different. Overall, the direct and indirect consequences of moth outbreaks increased belowground diversity at different trophic levels. Our results highlight that a holistic view of ecosystems improves our understanding of cascading effects of major disturbances on soil food webs.

On the Interpretations of Joint Modeling in Community Ecology.

Explaining and modeling species communities is more than ever a central goal of ecology. Recently, joint species distribution models (JSDMs), which extend species distribution models (SDMs) by considering correlations among species, have been proposed to improve species community analyses and rare species predictions while potentially inferring species interactions. Here, we illustrate the mathematical links between SDMs and JSDMs and their ecological implications and demonstrate that JSDMs, just like SDMs, cannot separate environmental effects from biotic interactions. We provide a guide to the conditions under which JSDMs are (or are not) preferable to SDMs for species community modeling. More generally, we call for a better uptake and clarification of novel statistical developments in the field of biodiversity modeling.

Effects of soil preservation for biodiversity monitoring using environmental DNA.

Environmental DNA (eDNA) metabarcoding is becoming a key tool for biodiversity monitoring over large geographical or taxonomic scales and for elusive taxa such as soil organisms. Increasing sample sizes and interest in remote or extreme areas often require the preservation of soil samples and thus deviations from optimal standardized protocols. However, we still ignore the impact of different methods of soil sample preservation on the results of metabarcoding studies and there is no guideline for best practices so far. Here, we assessed the impact of four methods of soil sample preservation that can be conveniently used also in metabarcoding studies targeting remote or difficult to access areas. Tested methods include: preservation at room temperature for 6 hr, preservation at 4°C for 3 days, desiccation immediately after sampling and preservation for 21 days, and desiccation after 6 hr at room temperature and preservation for 21 days. For each preservation method, we benchmarked resulting estimates of taxon diversity and community composition of three different taxonomic groups (bacteria, fungi and eukaryotes) in three different habitats (forest, river bank and grassland) against results obtained under ideal conditions (i.e., extraction of eDNA immediately after sampling). Overall, the different preservation methods only marginally impaired results and only under certain conditions. When rare taxa were considered, we detected small but significant changes in molecular operational taxonomic units (MOTU) richness of bacteria, fungi and eukaryotes across treatments, but MOTU richness was similar across preservation methods if rare taxa were not considered. All the approaches were able to identify differences in community structure among habitats, and the communities retrieved using the different preservation conditions were extremely similar. We propose guidelines on the selection of the optimal soil sample preservation conditions for metabarcoding studies, depending on the practical constraints, costs and ultimate research goals.

The productivity-biodiversity relationship varies across diversity dimensions.

Understanding the processes that drive the dramatic changes in biodiversity along the productivity gradient remains a major challenge. Insight from simple, bivariate relationships so far has been limited. We combined >11,000 community plots in the French Alps with a molecular phylogeny and trait information for >1200 plant species to simultaneously investigate the relationships between all major biodiversity dimensions and satellite-sensed productivity. Using an approach that tests for differential effects of species dominance, species similarity and the interplay between phylogeny and traits, we demonstrate that unimodal productivity-biodiversity relationships only dominate for taxonomic diversity. In forests, trait and phylogenetic diversity typically increase with productivity, while in grasslands, relationships shift from unimodal to declining with greater land-use intensity. High productivity may increase trait/phylogenetic diversity in ecosystems with few external constraints (forests) by promoting complementary strategies, but under external constraints (managed grasslands) successful strategies are similar and thus the best competitors may be selected.

The Latitudinal Diversity Gradient: Novel Understanding through Mechanistic Eco-evolutionary Models.

The latitudinal diversity gradient (LDG) is one of the most widely studied patterns in ecology, yet no consensus has been reached about its underlying causes. We argue that the reasons for this are the verbal nature of existing hypotheses, the failure to mechanistically link interacting ecological and evolutionary processes to the LDG, and the fact that empirical patterns are often consistent with multiple explanations. To address this issue, we synthesize current LDG hypotheses, uncovering their eco-evolutionary mechanisms, hidden assumptions, and commonalities. Furthermore, we propose mechanistic eco-evolutionary modeling and an inferential approach that makes use of geographic, phylogenetic, and trait-based patterns to assess the relative importance of different processes for generating the LDG.

Drought effects on the stability of forest-grassland ecotones under gradual climate change.

Plant communities in forest-grassland ecotones of the European Alps are already suffering from gradual climate change and will likely be exposed to more frequent and intense drought periods in the future. Yet, how gradual climate change and extreme drought will affect the stability of these plant communities is largely unknown. Here, we investigated how drought modulates the effects of gradual climate change on the long-term structural stability of these ecotone communities using a multidimensional approach. Using a spatially explicit landscape vegetation model, we simulated three drought scenarios, on top of gradual changes of climate variables, and their impacts on the dynamics of 24 plant functional groups, distinguishing between forests and grasslands, as well as different land uses. We then used n-dimensional hypervolumes to define community states under the different drought scenarios, and compared them to initial conditions to assess changes in community structural stability. In general, added drought effects did not counteract the long-term consequences of gradual climate changes, although they resulted in quantitatively different effects. Importantly, drought and climate change had non-negligible consequences for taxonomic and functional structure that differed between communities and land-use regimes. For instance, forest taxonomic structure was more overall more stable than grassland's, despite the observed functional shifts towards more warm-adapted species compositions. Conversely, unmanaged grasslands were the least stable, suffering the loss of characteristic alpine species. Also, while frequent and severe drought regimes caused forests to become more variable in time, they had the opposite effect on grasslands. Our results agree with observations of drought- and climate-driven changes in mountain communities of the Alps, and we discuss their relevance for ecosystem management. Importantly, we demonstrate the utility of this multidimensional approach to study community stability for analysing cross-community and cross-disturbance responses to global change.

Simulating plant invasion dynamics in mountain ecosystems under global change scenarios.

Across the globe, invasive alien species cause severe environmental changes, altering species composition and ecosystem functions. So far, mountain areas have mostly been spared from large-scale invasions. However, climate change, land-use abandonment, the development of tourism and the increasing ornamental trade will weaken the barriers to invasions in these systems. Understanding how alien species will react and how native communities will influence their success is thus of prime importance in a management perspective. Here, we used a spatially and temporally explicit simulation model to forecast invasion risks in a protected mountain area in the French Alps under future conditions. We combined scenarios of climate change, land-use abandonment and tourism-linked increases in propagule pressure to test if the spread of alien species in the region will increase in the future. We modelled already naturalized alien species and new ornamental plants, accounting for interactions among global change components, and also competition with the native vegetation. Our results show that propagule pressure and climate change will interact to increase overall species richness of both naturalized aliens and new ornamentals, as well as their upper elevational limits and regional range-sizes. Under climate change, woody aliens are predicted to more than double in range-size and herbaceous species to occupy up to 20% of the park area. In contrast, land-use abandonment will open new invasion opportunities for woody aliens, but decrease invasion probability for naturalized and ornamental alien herbs as a consequence of colonization by native trees. This emphasizes the importance of interactions with the native vegetation either for facilitating or potentially for curbing invasions. Overall, our work highlights an additional and previously underestimated threat for the fragile mountain flora of the Alps already facing climate changes, land-use transformations and overexploitation by tourism.

Extreme climate events counteract the effects of climate and land-use changes in Alpine treelines.

1. Climate change and extreme events, such as drought, threaten ecosystems worldwide and in particular mountain ecosystems, where species often live at their environmental tolerance limits. In the European Alps, plant communities are also influenced by land-use abandonment leading to woody encroachment of subalpine and alpine grasslands. 2. In this study, we explored how the forest-grassland ecotone of Alpine treelines will respond to gradual climate warming, drought events and land-use change in terms of forest expansion rates, taxonomic diversity and functional composition. We used a previously validated dynamic vegetation model, FATE-HD, parameterised for plant communities in the Ecrins National Park in the French Alps. 3. Our results showed that intense drought counteracted the forest expansion at higher elevations driven by land-use abandonment and climate change, especially when combined with high drought frequency (occurring every 2 or less than 2 years). 4. Furthermore, intense and frequent drought accelerated the rates of taxonomic change and resulted in overall higher taxonomic spatial heterogeneity of the ecotone than would be expected under gradual climate and land-use changes only. 5. Synthesis and applications. The results from our model show that intense and frequent drought counteracts forest expansion driven by climate and land-use changes in the forest-grassland ecotone of Alpine treelines. We argue that land-use planning must consider the effects of extreme events, such as drought, as well as climate and land-use changes, since extreme events might interfere with trends predicted under gradual climate warming and agricultural abandonment.

N-dimensional hypervolumes to study stability of complex ecosystems.

Although our knowledge on the stabilising role of biodiversity and on how it is affected by perturbations has greatly improved, we still lack a comprehensive view on ecosystem stability that is transversal to different habitats and perturbations. Hence, we propose a framework that takes advantage of the multiplicity of components of an ecosystem and their contribution to stability. Ecosystem components can range from species or functional groups, to different functional traits, or even the cover of different habitats in a landscape mosaic. We make use of n-dimensional hypervolumes to define ecosystem states and assess how much they shift after environmental changes have occurred. We demonstrate the value of this framework with a study case on the effects of environmental change on Alpine ecosystems. Our results highlight the importance of a multidimensional approach when studying ecosystem stability and show that our framework is flexible enough to be applied to different types of ecosystem components, which can have important implications for the study of ecosystem stability and transient dynamics.

Benchmarking novel approaches for modelling species range dynamics.

Increasing biodiversity loss due to climate change is one of the most vital challenges of the 21st century. To anticipate and mitigate biodiversity loss, models are needed that reliably project species' range dynamics and extinction risks. Recently, several new approaches to model range dynamics have been developed to supplement correlative species distribution models (SDMs), but applications clearly lag behind model development. Indeed, no comparative analysis has been performed to evaluate their performance. Here, we build on process-based, simulated data for benchmarking five range (dynamic) models of varying complexity including classical SDMs, SDMs coupled with simple dispersal or more complex population dynamic models (SDM hybrids), and a hierarchical Bayesian process-based dynamic range model (DRM). We specifically test the effects of demographic and community processes on model predictive performance. Under current climate, DRMs performed best, although only marginally. Under climate change, predictive performance varied considerably, with no clear winners. Yet, all range dynamic models improved predictions under climate change substantially compared to purely correlative SDMs, and the population dynamic models also predicted reasonable extinction risks for most scenarios. When benchmarking data were simulated with more complex demographic and community processes, simple SDM hybrids including only dispersal often proved most reliable. Finally, we found that structural decisions during model building can have great impact on model accuracy, but prior system knowledge on important processes can reduce these uncertainties considerably. Our results reassure the clear merit in using dynamic approaches for modelling species' response to climate change but also emphasize several needs for further model and data improvement. We propose and discuss perspectives for improving range projections through combination of multiple models and for making these approaches operational for large numbers of species.

What it takes to invade grassland ecosystems: traits, introduction history and filtering processes.

Whether the success of alien species can be explained by their functional or phylogenetic characteristics remains unresolved because of data limitations, scale issues and weak quantifications of success. Using permanent grasslands across France (50 000 vegetation plots, 2000 species, 130 aliens) and building on the Rabinowitz's classification to quantify spread, we showed that phylogenetic and functional similarities to natives were the most important correlates of invasion success compared to intrinsic functional characteristics and introduction history. Results contrasted between spatial scales and components of invasion success. Widespread and common aliens were similar to co-occurring natives at coarse scales (indicating environmental filtering), but dissimilar at finer scales (indicating local competition). In contrast, regionally widespread but locally rare aliens showed patterns of competitive exclusion already at coarse scale. Quantifying trait differences between aliens and natives and distinguishing the components of invasion success improved our ability to understand and potentially predict alien spread at multiple scales.

From species distributions to meta-communities.

The extent that biotic interactions and dispersal influence species ranges and diversity patterns across scales remains an open question. Answering this question requires framing an analysis on the frontier between species distribution modelling (SDM), which ignores biotic interactions and dispersal limitation, and community ecology, which provides specific predictions on community and meta-community structure and resulting diversity patterns such as species richness and functional diversity. Using both empirical and simulated datasets, we tested whether predicted occurrences from fine-resolution SDMs provide good estimates of community structure and diversity patterns at resolutions ranging from a resolution typical of studies within reserves (250 m) to that typical of a regional biodiversity study (5 km). For both datasets, we show that the imprint of biotic interactions and dispersal limitation quickly vanishes when spatial resolution is reduced, which demonstrates the value of SDMs for tracking the imprint of community assembly processes across scales.

Phylogenetic niche conservatism - common pitfalls and ways forward.

1. The prevalence of phylogenetic niche conservatism (PNC) in nature is still a conflicting issue. Disagreement arises from confusion over its precise definition and the variety of approaches to measure its prevalence. Recent work highlighted that common measures of PNC strongly depend on the assumptions of the underlying model of niche evolution. However, this warning has not been well recognized in the applied literature and questionable approaches are still frequently applied. 2. The aim of this paper is to draw attention to the assumptions underlying commonly applied simple measures of PNC. We used a series of simulations to illustrate how misleading results can be if assumptions of niche evolution are violated, that the violation of assumptions is a common phenomenon and that testing assumptions requires in-depth pre-test. 3. We conclude that the seemingly simple measures of PNC, such as phylogenetic sign6al and evolutionary rate, are not so easy to apply if one accounts for the necessity to test model assumptions. In addition, these measures can be difficult to interpret. The common assumption that strong phylogenetic signal indicates PNC will be often invalid. In addition, the interpretation of some measures, e.g. the conclusion that evolutionary rate is slow enough to indicate PNC, requires a comparison with another clade, another trait or well-developed null model assumptions and thus additional data. 4. We suggest that studies investigating PNC should always compare alternative evolutionary models, and that model comparisons should in particular include flexible niche evolution models such as multiple-optima OU models, although these are computational intensive. These models are directly inherited from the concept of macro-evolutionary adaptive landscape, and can indicate PNC either by relative few peak shifts or by narrow peaks in the adaptive landscape. A test of PNC thus requires comparing these parameters of the macroevolutionary landscape between clades or time periods. 5. The general prevalence of PNC in nature should be evaluated only based on studies keeping up to the high standards of communicating the used definition of PNC, testing the assumptions made in the modelling approaches and including newly developed models in a model comparison approach.

Decomposing changes in phylogenetic and functional diversity over space and time.

The α, ß, γ diversity decomposition methodology is commonly used to investigate changes in diversity over space or time but rarely conjointly. However, with the ever-increasing availability of large-scale biodiversity monitoring data, there is a need for a sound methodology capable of simultaneously accounting for spatial and temporal changes in diversity.Using the properties of Chao's index, we adapted Rao's framework of diversity decomposition between orthogonal dimensions to a multiplicative α, ß, γ decomposition of functional or phylogenetic diversity over space and time, thereby combining their respective properties. We also developed guidelines for interpreting both temporal and spatial ß-diversities and their interaction.We characterised the range of ß-diversity estimates and their relationship to the nested decomposition of diversity. Using simulations, we empirically demonstrated that temporal and spatial ß-diversities are independent from each other and from α and γ-diversities when the study design is balanced, but not otherwise. Furthermore, we showed that the interaction term between the temporal and the spatial ß-diversities lacked such properties.We illustrated our methodology with a case study of the spatio-temporal dynamics of functional diversity in bird assemblages in four regions of France. Based on these data, our method makes it possible to discriminate between regions experiencing different diversity changes in time. Our methodology may therefore be valuable for comparing diversity changes over space and time using large-scale datasets of repeated surveys.

On the sympatric evolution and evolutionary stability of coexistence by relative nonlinearity of competition.

If two species exhibit different nonlinear responses to a single shared resource, and if each species modifies the resource dynamics such that this favors its competitor, they may stably coexist. This coexistence mechanism, known as relative nonlinearity of competition, is well understood theoretically, but less is known about its evolutionary properties and its prevalence in real communities. We address this challenge by using adaptive dynamics theory and individual-based simulations to compare community stabilization and evolutionary stability of species that coexist by relative nonlinearity. In our analysis, evolution operates on the species' density-compensation strategies, and we consider a trade-off between population growth rates at high and low resource availability. We confirm previous findings that, irrespective of the particular model of density dependence, there are many combinations of overcompensating and undercompensating density-compensation strategies that allow stable coexistence by relative nonlinearity. However, our analysis also shows that most of these strategy combinations are not evolutionarily stable and will be outcompeted by an intermediate density-compensation strategy. Only very specific trade-offs lead to evolutionarily stable coexistence by relative nonlinearity. As we find no reason why these particular trade-offs should be common in nature, we conclude that the sympatric evolution and evolutionary stability of relative nonlinearity, while possible in principle, seems rather unlikely. We speculate that this may, at least in part, explain why empirical demonstrations of this coexistence mechanism are rare, noting, however, that the difficulty to detect relative nonlinearity in the field is an equally likely explanation for the current lack of empirical observations, and that our results are limited to communities with non-overlapping generations and constant resource supply. Our study highlights the need for combining ecological and evolutionary perspectives for gaining a better understanding of community assembly and biogeographic patterns.