Oikos

Progressive destruction and isolation of natural habitat is a major threat to biodiversity worldwide. In this study we use a trophic metacommunity model with complex, spatially explicit structure to address how the interaction of local and regional processes affects the functional diversity of autotroph (producer) communities within and between individual habitat patches. One important driver of biodiversity in metacommunities is spatial heterogeneity of the environment, as it enables source-sink dynamics between patches. Besides a-priori differences in the environmental conditions, heterogeneous distributions of resources and species biomasses can also emerge through self-organised pattern formation caused by scale-dependent feedback between local trophic and regional dispersal dynamics. We show that this emergent heterogeneity can enhance the functional diversity of local autotroph communities by jointly strengthening source-sink dynamics and reducing stabilising selection pressure. Our results indicate that this effect is particularly strong in highly connected metacommunities, while metacommunity size (number of patches) alone plays a lesser role. We demonstrate that the positive effect on local diversity is driven by an eco-evo-spatial feedback loop that is fueled by the asynchronous biomass- and trait dynamics between the patches created by self-organised pattern formation. In highly connected metacommunities, oscillatory biomass patterns with particularly large amplitude strengthen this feedback loop. Our findings are highly relevant in the light of anthropogenic habitat changes that often destroy dispersal pathways, thereby increasing habitat isolation, lowering overall connectance of metacommunities and ultimately threatening the biodiversity in local habitats. Only a joint investigation of the contributing ecological, evolutionary, and spatial mechanisms in complex model systems can yield comprehensive understanding of these processes, allowing for the development of strategies to mitigate adverse anthropogenic influence.

Biological invasions are globally affecting ecosystems, causing local species loss and altering ecosystem functioning. Understanding the success and unfolding of such biological invasions is thus of high priority. Both local properties and the spatial network structure have been shown to be determinants of invasion success, and the identification of spatial invasion hubs directly promoting invasion dynamics is gaining attention. Spatial dynamics, however, could also indirectly alter invasion success by shaping local community structure: in many ecosystems, such as riverine networks, regional properties such as patch size distribution are known drivers of local community structures, which themselves may affect the establishment success of invading species. Using microcosm experiments in dendritic networks, we disentangled how patch size distribution and dispersal along specific network topologies shaped local communities, and, subsequently, affected the establishment success of invading species. We find that inherent patch size distributions shaped composition and diversity of local communities, and, subsequently, modulated invasion success. Specifically, the relationship between local diversity and invasion success changed across an increasing patch size gradient from a negative to a positive correlation, while overall increasing patch size reduced invasion success. Connectivity did not have a direct effect on invasion success but indirectly affected invasions by shaping diversity patterns in the whole network. Our results emphasize the relevance of indirect, landscape-level effects on species invasions, which need to be considered in the management of spatial habitat networks.

In a rapidly changing world, the composition, diversity and structure of ecological communities face many threats. Biodiversity-Ecosystem Functioning (BEF) and community food-chain analyses have focused on investigating the consequences of these changes on ecosystem processes and the resulting functions. These different and diverging conceptual frameworks have each produced important results and identified a set of important mechanisms, that shape ecosystem functions. But the disconnection between these frameworks, and the various simplifications of the study systems are not representative of the complexity of real-world communities. Here we use food webs as a more realistic depiction of communities, and use a bioenergetic model to simulate their biomass dynamics and quantify the resulting flows and stocks of biomass. We use tools from food web analysis to investigate how the predictions from BEF and food-chain analyses fit together, how they correlate to food-web structure and how it might help us understand the interplay between various drivers of ecosystem functioning. We show that food web structure is correlated to the communitys efficiency in storing the captured biomass, which may explain the distribution of biomass (top heaviness) across the different trophic compartments (producers, primary and secondary consumers). While we know that ecological network structure is important in shaping ecosystem dynamics, identifying structural attributes important in shaping ecosystem processes and synthesizing how it affects various underpinning mechanisms may help prioritize key conservation targets to protect not only biodiversity but also its structure and the resulting services.

Dispersal is a key process mediating ecological and evolutionary dynamics. Its effects on metapopulations dynamics, population genetics or species range distribution can depend on phenotypic differences between dispersing and non-dispersing individuals (i.e., dispersal syndromes). However, scaling up to the importance of dispersal syndromes for meta-ecosystems have rarely been considered, despite intraspecific phenotypic variability is now recognised as an important factor mediating ecosystem functioning. In this study, we characterised the intraspecific variability of dispersal syndromes in twenty isolated genotypes of the ciliate Tetrahymena thermophila to test their consequences for biomass productivity in communities composed of five Tetrahymena species. To do so, dispersers and residents of each genotype were introduced, each separately, in ciliate communities composed of four other competing species of the genus Tetrahymena to investigate the effects of dispersal syndromes. We found that introducing dispersers led to a lower biomass compared to introducing residents. This effect was highly consistent across the twenty T. thermophila genotypes despite their marked differences of dispersal syndromes. Finally, we found a strong genotypic effect on biomass production, confirming that intraspecific variability in general affected ecosystem functions in our system. Our study shows that intraspecific variability and the existence of dispersal syndromes can impact the functioning of spatially structured ecosystems in a consistent and therefore predictable way.

Self-organized formation of spatial patterns is known from a variety of different ecosystems, yet little is known how these patterns affect functional diversity of local and regional communities. Here we use a food chain model in which autotroph diversity is described by a continuous distribution of a trait that affects both growth rate and defense against a heterotroph. On a single patch, stabilizing selection always promotes the dominance of a single autotroph species. Two alternative community states, with either defended or undefended species, are possible. In a metacommunity context, dispersal can destabilize these states, and complex spatio-temporal patterns emerge. This creates varying selection pressures on the local autotroph communities, which feed back on the trait dynamics. Local functional diversity increases ten-fold compared to a situation without self-organized pattern formation, thereby maintaining the adaptive potential of communities in an environment threatened by fragmentation and global change.

The functioning of plant-pollinator mutualistic networks is crucial for ecosystem service provisioning and biodiversity maintenance. However, multiple drivers of global change are causing an alarming decline of wild pollinators abundance and richness. We propose an ecological, process-based mathematical model describing the dynamics of pollinators and plants, properly mediated by reward resources. Our model explicitly accounts for the main interactions of both facilitative and competitive nature that occur both within and between the two guilds. We apply our model to a broad set of real communities in fragmented landscapes to investigate the mechanisms that link the architecture of the interaction networks, the pollinators temporal persistence and abundance at the community level, and their rarity at the landscape level. Our results suggest that few generalist pollinators form a core of abundant, persistent and widely distributed species, while a lower number of mutualistic partners is generally associated with low abundance, low persistence and high turnover between patches. Specialists, however, are crucial to maintaining high levels of biodiversity within the community. This finding highlights the importance of ecological connectivity, through which local extinctions can be counter-balanced by recolonizations. Our analysis shows how a mechanistic model accounting for the structure of plant-pollinator networks can serve as a tool to investigate important ecological mechanisms driving community composition, dynamics and the resulting species distribution patterns.

In recent years there has been a growing body of research on human resilience to extreme climatic shifts in the past. Most studies focus on comparing archaeological records prior to a perceived climatic shift with those after it, to investigate a causal relationship between the two. Although these comparisons are important, they are limited in their potential to facilitate causal understanding of the factors that determined the human response to climate change. We assert that for such understanding, it is necessary to explicitly consider prior processes that could have made certain populations more resilient to the extreme climatic shift. This assertion calls for a new focus on the cultural and demographic dynamics in prehistorical populations, over the generations that preceded the climatic shift. In this article, we lay out several mechanisms of cultural evolution that - together with the experienced climatic dynamics prior to extreme climatic shifts - may have determined populations abilities to cope with them. This endeavor allows us to outline alternative hypotheses regarding what determined the fate of different human groups. These, in turn, may help direct the collection and analysis of archaeological data and to highlight modalities within it that may be helpful for inference of the mechanisms that determined populations resilience to climatic shifts.

Even when environments deteriorate gradually, ecosystems may shift abruptly from one state to another. Such catastrophic shifts are difficult to predict and reverse (hysteresis). While well studied in simplified contexts, we lack a general understanding of how catastrophic shifts spread in realistic spatial contexts. For different types of landscape structure, including typical terrestrial modular and riverine dendritic networks, we here investigate landscape-scale stability in metapopulations made of bistable patches. We find that such metapopulations usually exhibit large scale catastrophic shifts and hysteresis, and that the properties of these shifts depend strongly on metapopulation spatial structure and dispersal rate: intermediate dispersal rates and a riverine spatial structure can largely reduce hysteresis size. Interestingly, our study suggests that large-scale restoration is easier with spatially clustered restoration efforts and in populations characterized by an intermediate dispersal rate.

The authors have withdrawn their manuscript whilst they conduct additional data analysis to confirm if some of their conclusions are affected by data analysis artefact or not. Therefore, the authors do not wish this work to be cited as a reference for the project. If you have any questions, please contact the corresponding author.

Overexploitation, the depletion of a resource by its consumer on a short timescale, is widespread in nature but its general implications for biomass control and community stability are not clear. Most approaches investigating the interactions between trophic levels and variations in biomass patterns or in population dynamics generally ignore overexploitation. Here we use a resource-plant-herbivore food chain model allowing for overexploitation (i.e. the plant can overexploit the resource and/or the herbivore can overexploit the plant). We uncover the conditions under which either type of overexploitation occurs and show that they qualitatively change ecological patterns, mainly by suppressing top-down control when interaction strength is high. When plant productivity increases, top-down control patterns are suppressed above the level when the plant starts to overexploit resources. Similarly, when herbivory intensity increases, top-down control patterns disappear when plants become overex-ploited. Overexploitation also prevents enrichment-driven destabilization by capping the energy fluxes in the community. These findings connect top-down and bottom-up controls in a single framework, and highlight the role overexploitation can play in structuring and stabilizing food chains via the modulation of interaction strengths.

Some plant species inhibit or stimulate soil nitrification, the transformation of ammonium into nitrate by microorganisms. The control of nitrification may in turn alter ecosystem productivity and functioning. Given the potential positive impacts of nitrification control on plant fitness, we aim to determine the conditions under which nitrification control is likely to have been selected, and the consequences of that selection on ecosystem functioning. We investigate both the role of the abiotic context (nutrient availability and diffusion) and the role of other plant traits (mortality and dispersal). A first mean-field model shows that when nitrogen pools are shared among individuals within the plant population, the control of nitrification is counter-selected. A tragedy of the commons occurs because the costs of controlling nitrification (ie. of producing root exudates) only affect the controlling individuals while benefits are shared among all individuals. We then assume that the effects of the control of nitrification are spatially restricted to the rhizosphere, and we build a spatially explicit, individual-based model in which mutation of control of nitrification is possible. Plant capacity to control nitrification evolves when the plant environment is sufficiently private and generation time sufficiently long, leading to higher fitness benefits of the construction process. In such cases, plants evolve to inhibit nitrification when losses of nitrate are greater than losses of ammonium and evolve to stimulate nitrification when losses of ammonium are greater than losses of nitrate. Finally, biomass production tends to be maximal at the selected strategy when the diffusion of ammonium and nitrate is low. Our results help predict which strategies should be selected and likely to be found in different plants in different parts of the world.

In metacommunities, habitat heterogeneity facilitates species coexistence if superior competitors disperse maladaptively towards unfavourable habitats or if they hedge insufficiently against fluctuating environmental conditions. We show that similar mechanisms also operate in metacommunities with homogeneous habitat quality when heterogeneous biomass distributions emerge from self-organised pattern formation. Depending on whether the induced biomass patterns are static or fluctuating, either lower or higher dispersal rates can allow inferior competitors to coexist with their superior counterparts. Coexistence is further promoted when the inferiors can plastically reduce emigration from resource-rich patches. Furthermore, if the competitors differ in their abilities to induce pattern formation, a novel coexistence mechanism akin to relative non-linearity emerges, where the temporarily dominant competitor modifies the spatio-temporal variation in the biomass distributions such that it favours the recovery of the currently rare competitor. Self-organised pattern formation thus generically provides mechanisms for maintaining diversity in metacommunities without requiring a priori habitat heterogeneity.

In the scenarios concerning the emergence and selection of spatiotemporal cognitive abilities in vagile plant-eating animals, there is always an implicit assumption: the distribution of plants does not change and ultimately shapes the cognitive abilities of the animals, hence their movement. Yet, if plant distribution patterns are likely to remain unchanged over short time periods, they may change over long time periods as a result of animal exploitation. In particular, animal movement can shape the environment by dispersing plant seeds. Using an agent-based model simulating the foraging behaviour of a seed disperser endowed with spatiotemporal knowledge of resource distribution, I investigated whether resource spatiotemporal patterns could be influenced by the level of cognition involved in foraging. This level of cognition represented how well resource location and phenology were predicted by the agent. I showed that seed dispersers could shape the long-term distribution of resources by materialising the routes repeatedly used by the agent with the newly recruited plants. This stemmed from the conjunction of two forces: competition for space between plants and a seed-dispersing agent moving from plant to plant based on spatiotemporal memory. In turn, resource landscape modifications affected the benefits of spatiotemporal memory. This could create eco-evolutionary feedback loops between animal spatiotemporal cognition and the distribution patterns of plant resources. Altogether, the results emphasise that foraging cognition is a cause and a consequence of resource heterogeneity.

Successful ecosystem restoration is intimately linked to the persistence of species in local communities and across landscapes. As such quantitative approaches to ecological restoration require the integration of community and metapopulation ecology. Together these disciplines demonstrate that local colonisation, via habitat connectivity and size, and species interactions, both modulate the process of community assembly. However, thus far restoration ecology still remains disconnected from network ecology this preventing a holistic, community-wide perspective to restoration. We aim to inform ecological restoration using a multi-layer modelling framework integrating ecological interactions and species dispersal dynamics. We explore the drivers that modulate recolonisation dynamics of species across restored landscapes. We further investigate how restoration improves the structural properties of food webs, the number of successful recolonisations and the role of configuration of restored patches in restoration outcomes. We find that recolonisation is the result of a trade-off between dispersal ability and energy requirements. 97% of plant recolonisation and 88% of herbivore recolonisations happened within close proximity to the source patches. Better dispersers - intermediate and top species in the food webs - were able to recolonise habitat by benefitting from the increased biomass influx from restoration. When only a small proportion of the landscape could be restored, the location and connectivity of restored areas strongly influenced the outcome of restoration: more connected patches enabled on average the recolonisation of about 1 additional intermediate species compared to that of isolated patches. However, this difference faded as soon as more patches were restored, and improving larger portions of the landscape always resulted in better outcomes. Restoring 1/3 of the landscape enabled on average the recolonisation of ~4 additional species. Our findings suggest that quantitative models can inform restoration efforts necessary to bring native species back to restored areas. They also suggest that attention should be given to the requirements of the recolonisers, the distance of their introduction from restored areas and their trophic and ecological niche. These aspects are crucial to assess their energy and habitat requirements for successful establishment.

Many metrics that describe the structure of mutualistic plant-pollinator networks have been found to be important for network stability and robustness. These metrics are impacted by a suite of variables, including species traits, species abundances, their spatial configuration, and their phylogenetic history. Here, we consider a specific trait, phenology, or the timing of life history events. We expect that timing and duration of activity of pollinators, or of flowering in plants, could greatly affect the structure of the networks in which they are embedded. Using plant-pollinator networks from 33 sites in southern British Columbia, Canada, we asked a) how phenological species traits, specifically timing of first appearance in the network and duration of activity in a network, were related to network structure, and b) how those traits affected network robustness to phenologically biased species loss. We found that long duration of activity increased connection within modules for both pollinators and plants and among modules for plants. We also found that date of first appearance was positively related to interaction strength asymmetry in plants but negatively related in pollinators. Networks were generally more robust to the loss of pollinators than plants, but robustness declined with loss of early-flying or long-duration pollinators. These pollinators tended to be among-module connectors. Our results show that changes in phenology have the potential to impact plant-pollinator networks, which may have conservation relevance in a time of changing climate.

The mid-domain effect (MDE) predicts that geometric constraints drive unimodal species richness patterns within bounded gradients. However, the role of this effect in ecological networks is currently unexplored. Here we evaluate the role of the MDE in structuring interaction networks. We combine null-model simulations and empirical analyses of plant-pollinator and ant-plant networks along elevational gradients to assess whether the MDE can drive systematic variation in network structure. Our simulations demonstrated that the MDE alone can generate unimodal/U-shaped patterns in network metrics such as connectance, generality, and vulnerability. However, empirical networks only partially conformed to MDE predictions, with deviations indicating the likely influence of other ecological processes. MDE-based models best explained patterns in network-level specialization and nestedness, while only partially explaining patterns in connectance and generality. Because MDEs can shape interaction networks, MDE null models should be used when quantifying the influence of other ecological processes on network structure.

Migration is a ubiquitous process that links ecosystems with distinct seasonal dynamics, transferring biomass and species interactions across space. Despite being widely altered by global change, studies commonly overlook the interaction of seasonal characteristics and bidirectional migration on species coexistence and biomass production across meta-ecosystems. We developed a mathematical model to study how migration interacts with key characteristics of seasonality--amplitude of variation and length of summer--to influence migrant persistence, consumer coexistence, and biomass production. Our findings demonstrate that seasonal characteristics mediate the effect of migration on coexistence and biomass production across meta-ecosystems. However, the effects strongly depend on migration timing: phenological mismatches can reduce biomass at local and meta-ecosystem scales and lead to the extinction of migratory and non-migratory consumers. Our study highlights how migration and seasonality interact to shape community structure and ecosystem function across scales, emphasizing the importance of system-level approaches for studying ecological outcomes of global change.

Habitat fragmentation, driven by human activities, disrupts habitat connectivity and alters ecological processes through geometric and demographic fragmentation effects. Dispersal plays a fundamental role in shaping the distribution, abundance, and persistence of species in modified landscapes. While previous research looked at the evolution of dispersal strategies at the species level, community-level dynamics remain underexplored. Species exhibit diverse dispersal strategies to persist in modified landscapes, yet predicting how these strategies interact at the community level requires a more integrated approach. This study employed an individual-based simulation model to explore how fragmentation and other landscape characteristics influence community-level dispersal strategies. We tested the effects of varying fragmentation levels, environmental autocorrelation, habitat amount, and disturbance levels on the emerging distribution of dispersal distances within a community in modified and continuous landscapes. We hypothesised that fragmentation and other spatial patterns would significantly shape community composition, favouring particular dispersal strategies under specific environmental conditions. The findings reveal that higher disturbance levels and greater habitat amount increased the community-weighted mean of dispersal distance, while fragmentation showed only minor variation. Additionally, low autocorrelation was associated with the highest community-weighted mean of dispersal distance. These results highlight the importance of considering community-level dynamics when predicting ecosystem responses to landscape modification. By clarifying how landscape structure and disturbance shape community-level dispersal strategies, this study advances our understanding of the mechanisms underlying species persistence and community structure in modified landscapes.

Should what is left of nature be contained in a Single Large or Several Small (SLoSS) areas? This question of what would minimize the impact severity of habitat destruction on biodiversity loss is much debated, mainly because studies generally focus on different spatial and temporal scales. Using a semi-spatially explicit, (near-)neutral, individual-based model, we investigate the effects of fragmentation on biodiversity loss at two spatial (landscape-versus subcommunity level) and two temporal scales (static versus dynamic effects). Our results show that the role of spatial configuration of habitat destruction depends on when and at what scale we measure biodiversity loss. When considering the more realistic assumption that species differ in dispersal capacity, differences between spatial configurations are likely to be amplified. Our results indicate that the spatial configuration of habitat loss needs to be considered when evaluating the risks of further habitat destruction.

Understanding how the structure of ecological communities varies across biotic and abiotic dimensions is a fundamental goal in ecology. This challenge is now approachable due to the increasing availability of data on community structure across the globe. Ecological communities are often defined with respect to the guilds considered and the interactions they engage in, but it is unclear whether interactions of different types respond similarly to large-scale environmental gradients. Therefore, we lack a deeper understanding of how the emergent structure of interaction networks varies across biogeographical gradients, and how this effect may change depending on their constituent interaction types. Here, using a unique dataset of 952 networks across the globe, we provide a first comparison of network structural metrics and their large-scale variability for five overarching interaction types (feeding, frugivory, herbivory, parasitism and pollination). We show that degree distribution, but not connectance alone, helps us understand the observed network structures, and this pattern is maintained across interaction types (with the partial exception of food webs). Moreover, degree distribution descriptors are generally explained by differences across studies, which represent a proxy for variability in sampling and network construction methods. Environ-mental factors show weaker but robust effects on network degree distribution, and food webs are generally more sensitive to changes in environmental factors than networks of other interaction types. By analysing common descriptors of the degree distributions of ecological networks, this study underscores for the first time generalities and differences across networks of different interaction types and their response to environmental and anthropogenic factors.