Self-organization as a mechanism of resilience in dryland ecosystems.

Self-organized spatial patterns are a common feature of complex systems, ranging from microbial communities to mussel beds and drylands. While the theoretical implications of these patterns for ecosystem-level processes, such as functioning and resilience, have been extensively studied, empirical evidence remains scarce. To address this gap, we analyzed global drylands along an aridity gradient using remote sensing, field data, and modeling. We found that the spatial structure of the vegetation strengthens as aridity increases, which is associated with the maintenance of a high level of soil multifunctionality, even as aridity levels rise up to a certain threshold. The combination of these results with those of two individual-based models indicate that self-organized vegetation patterns not only form in response to stressful environmental conditions but also provide drylands with the ability to adapt to changing conditions while maintaining their functioning, an adaptive capacity which is lost in degraded ecosystems. Self-organization thereby plays a vital role in enhancing the resilience of drylands. Overall, our findings contribute to a deeper understanding of the relationship between spatial vegetation patterns and dryland resilience. They also represent a significant step forward in the development of indicators for ecosystem resilience, which are critical tools for managing and preserving these valuable ecosystems in a warmer and more arid world.

The structure and robustness of ecological networks with two interaction types.

Until recently, most ecological network analyses investigating the effects of species' declines and extinctions have focused on a single type of interaction (e.g. feeding). In nature, however, diverse interactions co-occur, each of them forming a layer of a 'multilayer' network. Data including information on multiple interaction types has recently started to emerge, giving us the opportunity to have a first glance at possible commonalities in the structure of these networks. We studied the structural features of 44 tripartite ecological networks from the literature, each composed of two layers of interactions (e.g. herbivory and pollination), and investigated their robustness to species losses. Considering two interactions simultaneously, we found that the robustness of the whole community is a combination of the robustness of the two ecological networks composing it. The way in which the layers of interactions are connected to each other affects the interdependence of their robustness. In many networks, this interdependence is low, suggesting that restoration efforts would not automatically propagate through the whole community. Our results highlight the importance of considering multiple interactions simultaneously to better gauge the robustness of ecological communities to species loss and to more reliably identify key species that are important for the persistence of ecological communities.

A taxonomy of multiple stable states in complex ecological communities.

Natural systems are built from multiple interconnected units, making their dynamics, functioning and fragility notoriously hard to predict. A fragility scenario of particular relevance concerns so-called regime shifts: abrupt transitions from healthy to degraded ecosystem states. An explanation for these shifts is that they arise as transitions between alternative stable states, a process that is well-understood in few-species models. However, how multistability upscales with system complexity remains a debated question. Here, we identify that four different multistability regimes generically emerge in models of species-rich communities and other archetypical complex biological systems assuming random interactions. Across the studied models, each regime consistently emerges under a specific interaction scheme and leaves a distinct set of fingerprints in terms of the number of observed states, their species richness and their response to perturbations. Our results help clarify the conditions and types of multistability that can be expected to occur in complex ecological communities.

Landscape Structure Affects Metapopulation-Scale Tipping Points.

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

Spatial autocorrelation of local patch extinctions drives recovery dynamics in metacommunities.

Human activities put ecosystems under increasing pressure, often resulting in local extinctions. However, it is unclear how local extinctions affect regional processes, such as the distribution of diversity in space, especially if extinctions show spatial patterns, such as being clustered. Therefore, it is crucial to investigate extinctions and their consequences in a spatially explicit framework. Using highly controlled microcosm experiments and theoretical models, we ask here how the number and spatial autocorrelation of extinctions interactively affect metacommunity dynamics. We found that local patch extinctions increased local diversity (α-diversity) and inter-patch diversity (ß-diversity) by delaying the exclusion of inferior competitors. Importantly, recolonization dynamics depended more strongly on the spatial distribution than on the number of patch extinctions: clustered local patch extinctions resulted in slower recovery, lower α-diversity and higher ß-diversity. Our results highlight that the spatial distribution of perturbations should be taken into account when studying and managing spatially structured communities.

Unveiling dimensions of stability in complex ecological networks.

Understanding the stability of ecological communities is a matter of increasing importance in the context of global environmental change. Yet it has proved to be a challenging task. Different metrics are used to assess the stability of ecological systems, and the choice of one metric over another may result in conflicting conclusions. Although each of the multitude of metrics is useful for answering a specific question about stability, the relationship among metrics is poorly understood. Such lack of understanding prevents scientists from developing a unified concept of stability. Instead, by investigating these relationships we can unveil how many dimensions of stability there are (i.e., in how many independent components stability metrics can be grouped), which should help build a more comprehensive concept of stability. Here we simultaneously measured 27 stability metrics frequently used in ecological studies. Our approach is based on dynamical simulations of multispecies trophic communities under different perturbation scenarios. Mapping the relationships between the metrics revealed that they can be lumped into 3 main groups of relatively independent stability components: early response to pulse, sensitivities to press, and distance to threshold. Selecting metrics from each of these groups allows a more accurate and comprehensive quantification of the overall stability of ecological communities. These results contribute to improving our understanding and assessment of stability in ecological communities.

Scaling up biodiversity-ecosystem functioning relationships: the role of environmental heterogeneity in space and time.

The biodiversity and ecosystem functioning (BEF) relationship is expected to be scale-dependent. The autocorrelation of environmental heterogeneity is hypothesized to explain this scale dependence because it influences how quickly biodiversity accumulates over space or time. However, this link has yet to be demonstrated in a formal model. Here, we use a Lotka-Volterra competition model to simulate community dynamics when environmental conditions vary across either space or time. Species differ in their optimal environmental conditions, which results in turnover in community composition. We vary biodiversity by modelling communities with different sized regional species pools and ask how the amount of biomass per unit area depends on the number of species present, and the spatial or temporal scale at which it is measured. We find that more biodiversity is required to maintain functioning at larger temporal and spatial scales. The number of species required increases quickly when environmental autocorrelation is low, and slowly when autocorrelation is high. Both spatial and temporal environmental heterogeneity lead to scale dependence in BEF, but autocorrelation has larger impacts when environmental change is temporal. These findings show how the biodiversity required to maintain functioning is expected to increase over space and time.

Biogeography of global drylands.

Despite their extent and socio-ecological importance, a comprehensive biogeographical synthesis of drylands is lacking. Here we synthesize the biogeography of key organisms (vascular and nonvascular vegetation and soil microorganisms), attributes (functional traits, spatial patterns, plant-plant and plant-soil interactions) and processes (productivity and land cover) across global drylands. These areas have a long evolutionary history, are centers of diversification for many plant lineages and include important plant diversity hotspots. This diversity captures a strikingly high portion of the variation in leaf functional diversity observed globally. Part of this functional diversity is associated with the large variation in response and effect traits in the shrubs encroaching dryland grasslands. Aridity and its interplay with the traits of interacting plant species largely shape biogeographical patterns in plant-plant and plant-soil interactions, and in plant spatial patterns. Aridity also drives the composition of biocrust communities and vegetation productivity, which shows large geographical variation. We finish our review by discussing major research gaps, which include: studying regular vegetation spatial patterns; establishing large-scale plant and biocrust field surveys assessing individual-level trait measurements; knowing whether the impacts of plant-plant and plant-soil interactions on biodiversity are predictable; and assessing how elevated CO2 modulates future aridity conditions and plant productivity.

Scaling-up biodiversity-ecosystem functioning research.

A rich body of knowledge links biodiversity to ecosystem functioning (BEF), but it is primarily focused on small scales. We review the current theory and identify six expectations for scale dependence in the BEF relationship: (1) a nonlinear change in the slope of the BEF relationship with spatial scale; (2) a scale-dependent relationship between ecosystem stability and spatial extent; (3) coexistence within and among sites will result in a positive BEF relationship at larger scales; (4) temporal autocorrelation in environmental variability affects species turnover and thus the change in BEF slope with scale; (5) connectivity in metacommunities generates nonlinear BEF and stability relationships by affecting population  synchrony at local and regional scales; (6) spatial scaling in food web structure and diversity will generate scale dependence in ecosystem functioning. We suggest directions for synthesis that combine approaches in metaecosystem and metacommunity ecology and integrate cross-scale feedbacks. Tests of this theory may combine remote sensing with a generation of networked experiments that assess effects at multiple scales. We also show how anthropogenic land cover change may alter the scaling of the BEF relationship. New research on the role of scale in BEF will guide policy linking the goals of managing biodiversity and ecosystems.

Non-trophic interactions strengthen the diversity-functioning relationship in an ecological bioenergetic network model.

Ecological communities are undeniably diverse, both in terms of the species that compose them as well as the type of interactions that link species to each other. Despite this long recognition of the coexistence of multiple interaction types in nature, little is known about the consequences of this diversity for community functioning. In the ongoing context of global change and increasing species extinction rates, it seems crucial to improve our understanding of the drivers of the relationship between species diversity and ecosystem functioning. Here, using a multispecies dynamical model of ecological communities including various interaction types (e.g. competition for space, predator interference, recruitment facilitation in addition to feeding), we studied the role of the presence and the intensity of these interactions for species diversity, community functioning (biomass and production) and the relationship between diversity and functioning.Taken jointly, the diverse interactions have significant effects on species diversity, whose amplitude and sign depend on the type of interactions involved and their relative abundance. They however consistently increase the slope of the relationship between diversity and functioning, suggesting that species losses might have stronger effects on community functioning than expected when ignoring the diversity of interaction types and focusing on feeding interactions only.

Advancing our understanding of ecological stability.

The concept of ecological stability occupies a prominent place in both fundamental and applied ecological research. We review decades of work on the topic and examine how our understanding has progressed. We show that our understanding of stability has remained fragmented and is limited largely to simple or simplified systems. There has been a profusion of metrics proposed to quantify stability, of which only a handful are used commonly. Furthermore, studies typically quantify one to two metrics of stability at a time and in response to a single perturbation, with some of the main environmental pressures of today being the least studied. We argue that we need to build on the existing consensus and strong theoretical foundation of the stability concept to better understand its multidimensionality and the interdependencies between metrics, levels of organisation and types of perturbations. Only by doing so can we make progress in the quantification of stability in theory and in practice, and eventually build a more comprehensive understanding of how ecosystems will respond to ongoing environmental change.

How Structured Is the Entangled Bank? The Surprisingly Simple Organization of Multiplex Ecological Networks Leads to Increased Persistence and Resilience.

Species are linked to each other by a myriad of positive and negative interactions. This complex spectrum of interactions constitutes a network of links that mediates ecological communities' response to perturbations, such as exploitation and climate change. In the last decades, there have been great advances in the study of intricate ecological networks. We have, nonetheless, lacked both the data and the tools to more rigorously understand the patterning of multiple interaction types between species (i.e., "multiplex networks"), as well as their consequences for community dynamics. Using network statistical modeling applied to a comprehensive ecological network, which includes trophic and diverse non-trophic links, we provide a first glimpse at what the full "entangled bank" of species looks like. The community exhibits clear multidimensional structure, which is taxonomically coherent and broadly predictable from species traits. Moreover, dynamic simulations suggest that this non-random patterning of how diverse non-trophic interactions map onto the food web could allow for higher species persistence and higher total biomass than expected by chance and tends to promote a higher robustness to extinctions.

Structure and functioning of dryland ecosystems in a changing world.

Understanding how drylands respond to ongoing environmental change is extremely important for global sustainability. Here we review how biotic attributes, climate, grazing pressure, land cover change and nitrogen deposition affect the functioning of drylands at multiple spatial scales. Our synthesis highlights the importance of biotic attributes (e.g. species richness) in maintaining fundamental ecosystem processes such as primary productivity, illustrate how N deposition and grazing pressure are impacting ecosystem functioning in drylands worldwide, and highlight the importance of the traits of woody species as drivers of their expansion in former grasslands. We also emphasize the role of attributes such as species richness and abundance in controlling the responses of ecosystem functioning to climate change. This knowledge is essential to guide conservation and restoration efforts in drylands, as biotic attributes can be actively managed at the local scale to increase ecosystem resilience to global change.

Loss of predator species, not intermediate consumers, triggers rapid and dramatic extinction cascades.

Ecological networks are tightly interconnected, such that loss of a single species can trigger additional species extinctions. Theory predicts that such secondary extinctions are driven primarily by loss of species from intermediate or basal trophic levels. In contrast, most cases of secondary extinctions from natural systems have been attributed to loss of entire top trophic levels. Here, we show that loss of single predator species in isolation can, irrespective of their identity or the presence of other predators, trigger rapid secondary extinction cascades in natural communities far exceeding those generally predicted by theory. In contrast, we did not find any secondary extinctions caused by intermediate consumer loss. A food web model of our experimental system-a marine rocky shore community-could reproduce these results only when biologically likely and plausible nontrophic interactions, based on competition for space and predator-avoidance behaviour, were included. These findings call for a reassessment of the scale and nature of extinction cascades, particularly the inclusion of nontrophic interactions, in forecasts of the future of biodiversity.

The ecological forecast horizon, and examples of its uses and determinants.

Forecasts of ecological dynamics in changing environments are increasingly important, and are available for a plethora of variables, such as species abundance and distribution, community structure and ecosystem processes. There is, however, a general absence of knowledge about how far into the future, or other dimensions (space, temperature, phylogenetic distance), useful ecological forecasts can be made, and about how features of ecological systems relate to these distances. The ecological forecast horizon is the dimensional distance for which useful forecasts can be made. Five case studies illustrate the influence of various sources of uncertainty (e.g. parameter uncertainty, environmental variation, demographic stochasticity and evolution), level of ecological organisation (e.g. population or community), and organismal properties (e.g. body size or number of trophic links) on temporal, spatial and phylogenetic forecast horizons. Insights from these case studies demonstrate that the ecological forecast horizon is a flexible and powerful tool for researching and communicating ecological predictability. It also has potential for motivating and guiding agenda setting for ecological forecasting research and development.

Local Facilitation May Cause Tipping Points on a Landscape Level Preceded by Early-Warning Indicators.

Positive biotic interactions play a significant role in shaping ecological communities. We used an individual-based model to demonstrate that plant facilitation on a microscale may cause ecosystem shifts on a landscape scale that can be announced by generic early-warning indicators. Recruitment of woody plants in harsh environments such as drylands often depends on nurse plants that ameliorate stressful conditions and facilitate the establishment of seedlings under their canopy. We found that these facilitative interactions may cause a treeless and a woodland state to be alternative stable states on a landscape scale if nurse plant effects are strong and if the environment is harsh enough to make facilitation necessary for seedling survival. A corollary is that under such conditions environmental change can bring drylands to tipping points for woody plant encroachment or woodland collapse. We show that the proximity of tipping points may be indicated by slowness of recovery of woody vegetation cover from small perturbations as well as by elevated temporal and spatial autocorrelation and variance. These signs are known to be indicators of critical slowing down. This is the first demonstration that the systemic phenomena of tipping points, announced by critical slowing down as a warning signal, may plausibly arise from microscale individual interactions, such as plant facilitation.

Can we infer plant facilitation from remote sensing? a test across global drylands.

Facilitation is a major force shaping the structure and diversity of plant communities in terrestrial ecosystems. Detecting positive plant-plant interactions relies on the combination of field experimentation and the demonstration of spatial association between neighboring plants. This has often restricted the study of facilitation to particular sites, limiting the development of systematic assessments of facilitation over regional and global scales. Here we explore whether the frequency of plant spatial associations detected from high-resolution remotely sensed images can be used to infer plant facilitation at the community level in drylands around the globe. We correlated the information from remotely sensed images freely available through Google Earth with detailed field assessments, and used a simple individual-based model to generate patch-size distributions using different assumptions about the type and strength of plant-plant interactions. Most of the patterns found from the remotely sensed images were more right skewed than the patterns from the null model simulating a random distribution. This suggests that the plants in the studied drylands show stronger spatial clustering than expected by chance. We found that positive plant co-occurrence, as measured in the field, was significantly related to the skewness of vegetation patch-size distribution measured using Google Earth images. Our findings suggest that the relative frequency of facilitation may be inferred from spatial pattern signals measured from remotely sensed images, since facilitation often determines positive co-occurrence among neighboring plants. They pave the road for a systematic global assessment of the role of facilitation in terrestrial ecosystems.

Effects of trophic similarity on community composition.

Understanding how ecological processes determine patterns among species coexisting within ecosystems is central to ecology. Here, we explore relationships between species' local coexistence and their trophic niches in terms of their feeding relationships both as consumers and as resources. We build on recent concepts and methods from community phylogenetics to develop a framework for analysing mechanisms responsible for community composition using trophic similarity among species and null models of community assembly. We apply this framework to 50 food webs found in 50 Adirondack lakes and find that species composition in these communities appears to be driven by both bottom-up effects by which the presence of prey species selects for predators of those prey, and top-down effects by which prey more tolerant of predation out-compete less tolerant prey of the same predators. This approach to community food webs is broadly applicable and shows how species interaction networks can inform an increasingly large array of theory central to community ecology.

The interplay of facilitation and competition drives the emergence of multistability in dryland plant communities.

Within communities, species are wrapped in a set of feedbacks with each other and with their environment. When such feedbacks are strong enough they can generate alternative stable states. So far, research on alternative stable states has mostly focused on systems with a small number of species and a limited diversity of interaction types. Here, we analyze a spatial model of plant community dynamics in stressed ecosystems such as drylands, where each species is characterized by a strategy, and the different species interact through facilitation and competition for space and resources, such as water. We identify three different types of multistability emerging from the interplay of competition and facilitation. Under low-stress levels, plant communities organize in small groups of coexisting species, maintained by space, competition and facilitation ("cliques"). Under higher stress levels, positive feedback from facilitation lead to the dominance of a single facilitating species ("mutual exclusion states"). At the highest stress levels, the single facilitating species left in the system coexists with the desert state. By linking community ecology and alternative stable states theory using a spatial plant community model for stressed ecosystems, our study contributes to highlight the importance of positive feedback loops for the stability of ecological communities.

Spatial vegetation patterns and imminent desertification in Mediterranean arid ecosystems.

Humans and climate affect ecosystems and their services, which may involve continuous and discontinuous transitions from one stable state to another. Discontinuous transitions are abrupt, irreversible and among the most catastrophic changes of ecosystems identified. For terrestrial ecosystems, it has been hypothesized that vegetation patchiness could be used as a signature of imminent transitions. Here, we analyse how vegetation patchiness changes in arid ecosystems with different grazing pressures, using both field data and a modelling approach. In the modelling approach, we extrapolated our analysis to even higher grazing pressures to investigate the vegetation patchiness when desertification is imminent. In three arid Mediterranean ecosystems in Spain, Greece and Morocco, we found that the patch-size distribution of the vegetation follows a power law. Using a stochastic cellular automaton model, we show that local positive interactions among plants can explain such power-law distributions. Furthermore, with increasing grazing pressure, the field data revealed consistent deviations from power laws. Increased grazing pressure leads to similar deviations in the model. When grazing was further increased in the model, we found that these deviations always and only occurred close to transition to desert, independent of the type of transition, and regardless of the vegetation cover. Therefore, we propose that patch-size distributions may be a warning signal for the onset of desertification.