The inherent multidimensionality of temporal variability: how common and rare species shape stability patterns

Rare and common species contribute disproportionately to alpine meadow community construction and functional variation

It is widely accepted that rare species are the first species to become extinct after human-induced disturbances. However, the functional importance of rare species still needs to be better understood, especially in alpine meadow communities with harsher habitats, where the extinction rate of rare species may be higher. This study established a 1.85 × 105 m2 permanent research sample plot on the eastern Tibetan Plateau. We investigated data from 162 plots at 6 different sampling scales in alpine meadows to determine the contribution of rare and common species to alpine meadow communities' structural and functional variability. The results showed that (1) Asteraceae (Compositae) was the dominant family in the surveyed localities. The trends of species diversity indices were the same, and all of them increased with the increase of sampling scale, and the plant community showed apparent scale effects. (2) The community construction of rare species at small scales with high occupancy transitioned from neutral processes to ecological niche processes, while the community construction of common species at different sampling scales was all dominated by ecological niche processes. (3) The trait values of rare species at different sampling scales were different from those of common species, and their distribution in FEs (functional entities) was also different, indicating that they contributed differently to the ecological functions of the communities. Rare species with lower abundance in the surveyed communities had a higher proportion of FEs, indicating that rare species had a more significant proportion of contribution to FEs. The functional redundancy (FR) of rare species was lower than that of common species, and the functional vulnerability (FV) was higher than that of common species. Therefore, the loss of rare species is more likely to cause the loss of community ecological functions, affecting the function and resilience of alpine meadow ecosystems.

Multiple habitats drive the functional diversity of fish assemblages in a tropical estuary

Understanding estuarine diversity patterns is crucial to highlight the ecological value of coastal ecosystems for fish assemblages. To increase our knowledge, we investigated the functional diversity of fish assemblages in five estuarine habitats (sandy beaches, mudflats, seagrass meadows, mangrove fringes, and estuarine riparian vegetation) in a tropical estuary of Brazil. Functional diversity metrics were assessed considering seven fish functional traits and calculated using functional indices, PCoA (functional spaces), and community-weighted mean (CWM). Then, a unified RLQ and fourth-corner analysis were used to evaluate environment-trait relationships. A total of 27,036 individuals of 119 species were recorded in all habitats. Functional diversity showed similar trends to estuarine habitats, which were more driven by the spatial configuration rather than by their structure, emphasizing the importance of environmental heterogeneity. There was a greater occupation of functional space to habitats located in the lower estuary compared to the upper estuary. Furthermore, body shapes and trophic guilds were the most common traits related to changes in functional diversity between habitats. The RLQ analysis revealed differences in trait composition between habitats influenced by salinity and transparency, although the fourth corner method did not show a significant relationship between fish functional traits and environmental variables. Our results suggest that the mosaic of habitats support the high functional diversity of fishes in tropical estuaries.

Assessing the sensitivity and resistance of communities in a changing environment

We propose that the ecological resilience of communities to permanent changes of the environment can be based on how variation in the overall abundance of individuals affects the number of species. Community sensitivity is defined as the ratio between the rate of change in the log expected number of species and the rate of change in the log expected number of individuals in the community. High community sensitivity means that small changes in the total abundance strongly impact the number of species. Community resistance is the proportional reduction in expected number of individuals that the community can sustain before expecting to lose one species. A small value of community resistance means that the community can only endure a small reduction in abundance before it is expected to lose one species. Based on long-term studies of four bird communities in European deciduous forests at different latitudes large differences were found in the resilience to environmental perturbations. Estimating the variance components of the species abundance distribution revealed how different processes contributed to the community sensitivity and resistance. Species heterogeneity in the population dynamics was the largest component, but its proportion varied among communities. Species-specific response to environmental fluctuations was the second major component of the variation in abundance. Estimates of community sensitivity and resistance based on data only from a single year were in general larger than those based on estimates from longer time series. Thus, our approach can provide rapid and conservative assessment of the resilience of communities to environmental changes also including only short-term data. This study shows that a general ecological mechanism, caused by increased strength of density dependence due to reduction in resource availability, can provide an intuitive measure of community resilience to environmental variation. Our analyses also illustrate the importance of including specific assumptions about how different processes affect community dynamics. For example, if stochastic fluctuations in the environment affect all species in a similar way, the sensitivity and resistance of the community to environmental changes will be different from communities in which all species show independent responses.

Reactivity of complex communities can be more important than stability

Understanding stability-whether a community will eventually return to its original state after a perturbation-is a major focus in the study of various complex systems, particularly complex ecosystems. Here, we challenge this focus, showing that short-term dynamics can be a better predictor of outcomes for complex ecosystems. Using random matrix theory, we study how complex ecosystems behave immediately after small perturbations. Our analyses show that many communities are expected to be 'reactive', whereby some perturbations will be amplified initially and generate a response that is directly opposite to that predicted by typical stability measures. In particular, we find reactivity is prevalent for complex communities of mixed interactions and for structured communities, which are both expected to be common in nature. Finally, we show that reactivity can be a better predictor of extinction risk than stability, particularly when communities face frequent perturbations, as is increasingly common. Our results suggest that, alongside stability, reactivity is a fundamental measure for assessing ecosystem health.

Spatial heterogeneity of biomass turnover has contrasting effects on synchrony and stability in trophic metacommunities

Spatial heterogeneity is a fundamental feature of ecosystems, and ecologists have identified it as a factor promoting the stability of population dynamics. In particular, differences in interaction strengths and resource supply between patches generate an asymmetry of biomass turnover with a fast and a slow patch coupled by a mobile predator. Here, we demonstrate that asymmetry leads to opposite stability patterns in metacommunities receiving localized perturbations depending on the characteristics of the perturbed patch. Perturbing prey in the fast patch synchronizes the dynamics of prey biomass between the two patches and destabilizes predator dynamics by increasing the predator's temporal variability. Conversely, perturbing prey in the slow patch decreases the synchrony of the prey's dynamics and stabilizes predator dynamics. Our results have implications for conservation ecology and suggest reinforcing protection policies in fast patches to dampen the effects of perturbations and promote the stability of population dynamics at the regional scale.

No sensitivity to functional forms in the Rosenzweig-MacArthur model with strong environmental stochasticity

The classic Rosenzweig-MacArthur predator-prey model has been shown to exhibit, like other coupled nonlinear ordinary differential equations (ODEs) from ecology, worrying sensitivity to model structure. This sensitivity manifests as markedly different community dynamics arising from saturating functional responses with nearly identical shapes but different mathematical expressions. Using a stochastic differential equation (SDE) version of the Rosenzweig-MacArthur model with the three functional responses considered by Fussmann & Blasius (2005), I show that such sensitivity seems to be solely a property of ODEs or stochastic systems with weak noise. SDEs with strong environmental noise have by contrast very similar fluctuations patterns, irrespective of the mathematical formula used. Although eigenvalues of linearized predator-prey models have been used as an argument for structural sensitivity, they can also be an argument against structural sensitivity. While the sign of the eigenvalues' real part is sensitive to model structure, its magnitude and the presence of imaginary parts are not, which suggests noise-driven oscillations for a broad range of carrying capacities. I then discuss multiple other ways to evaluate structural sensitivity in a stochastic setting, for predator-prey or other ecological systems.

Relationships of temperature and biodiversity with stability of natural aquatic food webs

Temperature and biodiversity changes occur in concert, but their joint effects on ecological stability of natural food webs are unknown. Here, we assess these relationships in 19 planktonic food webs. We estimate stability as structural stability (using the volume contraction rate) and temporal stability (using the temporal variation of species abundances). Warmer temperatures were associated with lower structural and temporal stability, while biodiversity had no consistent effects on either stability property. While species richness was associated with lower structural stability and higher temporal stability, Simpson diversity was associated with higher temporal stability. The responses of structural stability were linked to disproportionate contributions from two trophic groups (predators and consumers), while the responses of temporal stability were linked both to synchrony of all species within the food web and distinctive contributions from three trophic groups (predators, consumers, and producers). Our results suggest that, in natural ecosystems, warmer temperatures can erode ecosystem stability, while biodiversity changes may not have consistent effects.

Individual species and site dynamics are the main drivers of spatial scaling of stability in aquatic communities

Introduction

Any measure of ecological stability scales with the spatial and temporal extent of the data on which it is based. The magnitude of stabilization effects at increasing spatial scale is determined by the degree of synchrony between local and regional species populations.

Methods

We applied two recently developed approaches to quantify these stabilizing effects to time series records from three aquatic monitoring data sets differing in environmental context and organism type.

Results and Discussion

We found that the amount and general patterns of stabilization with increasing spatial scale only varied slightly across the investigated species groups and systems. In all three data sets, the relative contribution of stabilizing effects via asynchronous dynamics across space was higher than compensatory dynamics due to differences in biomass fluctuations across species and populations. When relating the stabilizing effects of individual species and sites to species and site-specific characteristics as well as community composition and aspects of spatial biomass distribution patterns, however, we found that the effects of single species and sites showed large differences and were highly context dependent, i.e., dominant species can but did not necessarily have highly stabilizing or destabilizing effects on overall community biomass. The sign and magnitude of individual contributions depended on community structure and the spatial distribution of biomass and species in space. Our study therefore provides new insights into the mechanistic understanding of ecological stability patterns across scales in natural species communities.

Synchrony and Stability in Trophic Metacommunities: When Top Predators Navigate in a Heterogeneous World

Ecosystem stability strongly depends on spatial aspects since localized perturbations spread across an entire region through species dispersal. Assessing the synchrony of the response of connected populations is fundamental to understand stability at different scales because if populations fluctuate asynchronously, the risk of their simultaneous extinction is low, thus reducing the species' regional extinction risk. Here, we consider a metacommunity model consisting of two food chains connected by dispersal and we review the various mechanisms governing the transmission of small perturbations affecting populations in the vicinity of equilibrium. First, we describe how perturbations propagate vertically (i.e., within food chains through trophic interactions) and horizontally (i.e., between food chains through dispersal) in metacommunities. Then, we discuss the mechanisms susceptible to alter synchrony patterns such as density-depend dispersal or spatial heterogeneity. Density-dependent dispersal, which is the influence of prey or predator abundance on dispersal, has a major impact because the species with the highest coefficient of variation of biomass governs the dispersal rate of the dispersing species and determines the synchrony of its populations, thus bypassing the classic vertical transmission of perturbations. Spatial heterogeneity, which is a disparity between patches of the attack rate of predators on prey in our model, alters the vertical transmission of perturbations in each patch, thus making synchrony dependent on which patch is perturbed. Finally, by combining our understanding of the impact of each of these mechanisms on synchrony, we are able to full explain the response of realistic metacommunities such as the model developed by Rooney et al. (2006). By disentangling the main mechanisms governing synchrony, our metacommunity model provides a broad insight into the consequences of spacial aspects on food web stability.

Spatial and Ecological Scaling of Stability in Spatial Community Networks

There are many scales at which to quantify stability in spatial and ecological networks. Local-scale analyses focus on specific nodes of the spatial network, while regional-scale analyses consider the whole network. Similarly, species- and community-level analyses either account for single species or for the whole community. Furthermore, stability itself can be defined in multiple ways, including resistance (the inverse of the relative displacement caused by a perturbation), initial resilience (the rate of return after a perturbation), and invariability (the inverse of the relative amplitude of the population fluctuations). Here, we analyze the scale-dependence of these stability properties. More specifically, we ask how spatial scale (local vs. regional) and ecological scale (species vs. community) influence these stability properties. We find that regional initial resilience is the weighted arithmetic mean of the local initial resiliences. The regional resistance is the harmonic mean of local resistances, which makes regional resistance particularly vulnerable to nodes with low stability, unlike regional initial resilience. Analogous results hold for the relationship between community- and species-level initial resilience and resistance. Both resistance and initial resilience are “scale-free” properties: regional and community values are simply the biomass-weighted means of the local and species values, respectively. Thus, one can easily estimate both stability metrics of whole networks from partial sampling. In contrast, invariability generally is greater at the regional and community-level than at the local and species-level, respectively. Hence, estimating the invariability of spatial or ecological networks from measurements at the local or species level is more complicated, requiring an unbiased estimate of the network (i.e., region or community) size. In conclusion, we find that scaling of stability depends on the metric considered, and we present a reliable framework to estimate these metrics.

Independent Effects of Species Removal and Asynchrony on Invariability of an Intertidal Rocky Shore Community

Ecological stability depends on interactions between different levels of biological organization. The insurance effects occur when increasing species diversity leads to more temporally invariable (i.e., more stable) community-level properties, due in part to asynchronous population-level fluctuations. While the study of insurance effects has received considerable attention, the role of dominant species that contribute with particular functional traits across different level of organizations is less understood. Using a field-based manipulative experiment, we investigated how species richness and different types of parameters at the population level, such as the invariability of dominants, population invariability, and population asynchrony, influence the community invariability. The experiment involved the repetitive removal of the canopy forming alga Mazzaella laminarioides (hereafter “Mazzaella”) during 32 months in two rocky intertidal sites of northern-central Chile. We predicted that the invariability of dominants enhances community invariability, that the effect of multispecies population-level parameters on community invariability are dependent on species richness, and that subdominant algae are unable to fully compensate the loss of canopies of the dominant species. Biomass of algae and mobile invertebrates was quantified over time. We observed independent effects of Mazzaella removal and community-wide asynchrony on community invariability. While canopy removal reduced community invariability, population asynchrony boosted community invariability regardless of the presence of canopies. In addition, filamentous and foliose algae were unable to compensate the loss of biomass triggered by the experimental removal of Mazzaella. Canopy removal led to a severe decrement in the biomass of macrograzers, while, at the same time, increased the biomass of mesograzers. Asynchrony stemmed from compensatory trophic responses of mesograzers to increased abundances of opportunistic algae. Thus, further work on consumer-resource interactions will improve our understanding of the links between population- and community-level aspects of stability.

Stressor richness intensifies productivity loss but mitigates biodiversity loss

Ecosystems are subject to a multitude of anthropogenic environmental changes. Experimental research in the field of multiple stressors has typically involved varying the number of stressors, here termed stressor richness, but without controlling for total stressor intensity. Mistaking stressor intensity effects for stressor richness effects can misinform management decisions when there is a trade-off between mitigating these two factors. We incorporate multiple stressors into three community models and show that, at a fixed total stressor intensity, increasing stressor richness aggravates joint stressor effects on ecosystem functioning, but reduces effects on species persistence and composition. In addition, stressor richness weakens the positive selection and negative complementarity effects on ecosystem function. We identify the among-species variation of stressor effects on traits as a key determinant of the resulting community-level stressor effects. Taken together, our results unravel the mechanisms linking multiple environmental changes to biodiversity and ecosystem function.

Widespread agrochemicals differentially affect zooplankton biomass and community structure

Anthropogenic environmental change is causing habitat deterioration at unprecedented rates in freshwater ecosystems. Despite increasing more rapidly than many other agents of global change, synthetic chemical pollution-including agrochemicals such as pesticides-has received relatively little attention in freshwater community and ecosystem ecology. Determining the combined effects of multiple agrochemicals on complex biological systems remains a major challenge, requiring a cross-field integration of ecology and ecotoxicology. Using a large-scale array of experimental ponds, we investigated the response of zooplankton community properties (biomass, composition, and diversity metrics) to the individual and joint presence of three globally widespread agrochemicals: the herbicide glyphosate, the neonicotinoid insecticide imidacloprid, and nutrient fertilizers. We tracked temporal variation in zooplankton biomass and community structure along single and combined pesticide gradients (each spanning eight levels), under low (mesotrophic) and high (eutrophic) nutrient-enriched conditions, and quantified (1) response threshold concentrations, (2) agrochemical interactions, and (3) community resistance and recovery. We found that the biomass of major zooplankton groups differed in their sensitivity to pesticides: ≥0.3 mg/L glyphosate elicited long-lasting declines in rotifer communities, both pesticides impaired copepods (≥3 µg/L imidacloprid and ≥5.5 mg/L glyphosate), whereas some cladocerans were highly tolerant to pesticide contamination. Strong interactive effects of pesticides were only recorded in ponds treated with the combination of the highest doses. Overall, glyphosate was the most influential driver of aggregate community properties of zooplankton, with biomass and community structure responding rapidly but recovering unequally over time. Total community biomass showed little resistance when first exposed to glyphosate, but rapidly recovered and even increased with glyphosate concentration over time; in contrast, taxon richness decreased in more contaminated ponds but failed to recover. Our results indicate that the biomass of tolerant taxa compensated for the loss of sensitive species after the first exposure, conferring greater community resistance upon a subsequent contamination event; a case of pollution-induced community tolerance in freshwater animals. These findings suggest that zooplankton biomass may be more resilient to agrochemical pollution than community structure; yet all community properties measured in this study were affected at glyphosate concentrations below common water quality guidelines in North America.

Biodiversity as insurance: from concept to measurement and application

Biological insurance theory predicts that, in a variable environment, aggregate ecosystem properties will vary less in more diverse communities because declines in the performance or abundance of some species or phenotypes will be offset, at least partly, by smoother declines or increases in others. During the past two decades, ecology has accumulated strong evidence for the stabilising effect of biodiversity on ecosystem functioning. As biological insurance is reaching the stage of a mature theory, it is critical to revisit and clarify its conceptual foundations to guide future developments, applications and measurements. In this review, we first clarify the connections between the insurance and portfolio concepts that have been used in ecology and the economic concepts that inspired them. Doing so points to gaps and mismatches between ecology and economics that could be filled profitably by new theoretical developments and new management applications. Second, we discuss some fundamental issues in biological insurance theory that have remained unnoticed so far and that emerge from some of its recent applications. In particular, we draw a clear distinction between the two effects embedded in biological insurance theory, i.e. the effects of biodiversity on the mean and variability of ecosystem properties. This distinction allows explicit consideration of trade-offs between the mean and stability of ecosystem processes and services. We also review applications of biological insurance theory in ecosystem management. Finally, we provide a synthetic conceptual framework that unifies the various approaches across disciplines, and we suggest new ways in which biological insurance theory could be extended to address new issues in ecology and ecosystem management. Exciting future challenges include linking the effects of biodiversity on ecosystem functioning and stability, incorporating multiple functions and feedbacks, developing new approaches to partition biodiversity effects across scales, extending biological insurance theory to complex interaction networks, and developing new applications to biodiversity and ecosystem management.

Distinctive patterns and signals at major environmental events and collapse zone boundaries

We studied the patterns of pre-collapse communities, the small-scale and the large-scale signals of collapses, and the environmental events before the collapses using four paleoecological and one modern data series. We applied and evaluated eight indicators in our analysis: the relative abundance of species, hierarchical cluster analysis, principal component analysis, total abundance, species richness, standard deviation (without a rolling window), first-order autoregression, and the relative abundance of the dominant species. We investigated the signals at the probable collapse triggering unusual environmental events and at the collapse zone boundaries, respectively. We also distinguished between pulse and step environmental events to see what signals the indicators give at these two different types of events. Our results show that first-order autoregression is not a good environmental event indicator, but it can forecast or indicate the collapse zones in climate change. The rest of the indicators are more sensitive to the pulse events than to the step events. Step events during climate change might have an essential role in initiating collapses. These events probably push the communities with low resilience beyond a critical threshold, so it is crucial to detect them. Before collapses, the total abundance and the species richness increase, the relative abundance of the species decreases. The hierarchical cluster analysis and the relative abundance of species together designate the collapse zone boundaries. We suggest that small-scale signals should be involved in analyses because they are often earlier than large-scale signals.

Drought effects on invertebrate metapopulation dynamics and quasi-extinction risk in an intermittent river network

Ecological communities can remain stable in the face of disturbance if their constituent species have different resistance and resilience strategies. In turn, local stability scales up regionally if heterogeneous landscapes maintain spatial asynchrony across discrete populations-but not if large-scale stressors synchronize environmental conditions and biological responses. Here, we hypothesized that droughts could drastically decrease the stability of invertebrate metapopulations both by filtering out poorly adapted species locally, and by synchronizing their dynamics across a river network. We tested this hypothesis via multivariate autoregressive state-space (MARSS) models on spatially replicated, long-term data describing aquatic invertebrate communities and hydrological conditions in a set of temperate, lowland streams subject to seasonal and supraseasonal drying events. This quantitative approach allowed us to assess the influence of local (flow magnitude) and network-scale (hydrological connectivity) drivers on invertebrate long-term trajectories, and to simulate near-future responses to a range of drought scenarios. We found that fluctuations in species abundances were heterogeneous across communities and driven by a combination of hydrological and stochastic drivers. Among metapopulations, increasing extent of dry reaches reduced the abundance of functional groups with low resistance or resilience capacities (i.e. low ability to persist in situ or recolonize from elsewhere, respectively). Our simulations revealed that metapopulation quasi-extinction risk for taxa vulnerable to drought increased exponentially as flowing habitats contracted within the river network, whereas the risk for taxa with resistance and resilience traits remained stable. Our results suggest that drought can be a synchronizing agent in riverscapes, potentially leading to regional quasi-extinction of species with lower resistance and resilience abilities. Better recognition of drought-driven synchronization may increase realism in species extinction forecasts as hydroclimatic extremes continue to intensify worldwide.

Predator avoidance and foraging for food shape synchrony and response to perturbations in trophic metacommunities

The response of species to perturbations strongly depends on spatial aspects in populations connected by dispersal. Asynchronous fluctuations in biomass among populations lower the risk of simultaneous local extinctions and thus reduce the regional extinction risk. However, dispersal is often seen as passive diffusion that balances species abundance between distant patches, whereas ecological constraints, such as predator avoidance or foraging for food, trigger the movement of individuals. Here, we propose a model in which dispersal rates depend on the abundance of the species interacting with the dispersing species (e.g., prey or predators) to determine how density-dependent dispersal shapes spatial synchrony in trophic metacommunities in response to stochastic perturbations. Thus, unlike those with passive dispersal, this model with density-dependent dispersal bypasses the classic vertical transmission of perturbations due to trophic interactions and deeply alters synchrony patterns. We show that the species with the highest coefficient of variation of biomass governs the dispersal rate of the dispersing species and determines the synchrony of its populations. In addition, we show that this mechanism can be modulated by the relative impact of each species on the growth rate of the dispersing species. Species affected by several constraints disperse to mitigate the strongest constraints (e.g., predation), which does not necessarily experience the highest variations due to perturbations. Our approach can disentangle the joint effects of several factors implied in dispersal and provides a more accurate description of dispersal and its consequences on metacommunity dynamics.

Linking functional traits and demography to model species-rich communities

It has long been anticipated that relating functional traits to species demography would be a cornerstone for achieving large-scale predictability of ecological systems. If such a relationship existed, species demography could be modeled only by measuring functional traits, transforming our ability to predict states and dynamics of species-rich communities with process-based community models. Here, we introduce a new method that links empirical functional traits with the demographic parameters of a process-based model by calibrating a transfer function through inverse modeling. As a case study, we parameterize a modified Lotka–Volterra model of a high-diversity mountain grassland with static plant community and functional trait data only. The calibrated trait–demography relationships are amenable to ecological interpretation, and lead to species abundances that fit well to the observed community structure. We conclude that our new method offers a general solution to bridge the divide between trait data and process-based models in species-rich ecosystems.

Advances in process-based community ecology models are hindered by the challenge of linking functional traits to demography in species-rich systems, where a high number of parameters need to be estimated from limited data. Here the authors propose a new Bayesian framework to calibrate community models via functional traits, and validate it in a species-rich plant community.

General statistical scaling laws for stability in ecological systems

Ecological stability refers to a family of concepts used to describe how systems of interacting species vary through time and respond to disturbances. Because observed ecological stability depends on sampling scales and environmental context, it is notoriously difficult to compare measurements across sites and systems. Here, we apply stochastic dynamical systems theory to derive general statistical scaling relationships across time, space, and ecological level of organisation for three fundamental stability aspects: resilience, resistance, and invariance. These relationships can be calibrated using random or representative samples measured at individual scales, and projected to predict average stability at other scales across a wide range of contexts. Moreover deviations between observed vs. extrapolated scaling relationships can reveal information about unobserved heterogeneity across time, space, or species. We anticipate that these methods will be useful for cross-study synthesis of stability data, extrapolating measurements to unobserved scales, and identifying underlying causes and consequences of heterogeneity.

Synchrony and Perturbation Transmission in Trophic Metacommunities

AbstractIn a world where natural habitats are ever more fragmented, the dynamics of metacommunities are essential to properly understand species responses to perturbations. If species' populations fluctuate asynchronously, the risk of their simultaneous extinction is low, thus reducing the species' regional extinction risk. However, identifying synchronizing or desynchronizing mechanisms in systems containing several species and when perturbations affect multiple species is challenging. We propose a metacommunity model consisting of two food chains connected by dispersal to study the transmission of small perturbations affecting populations in the vicinity of an equilibrium. In spite of the complex responses produced by such a system, two elements enable us to understand the key processes that rule the synchrony between populations: (1) knowing which species have the strongest response to perturbations and (2) the relative importance of dispersal processes compared with local dynamics for each species. We show that perturbing a species in one patch can lead to asynchrony between patches if the perturbed species is not the most affected by dispersal. The synchrony patterns of rare species are the most sensitive to the relative strength of dispersal to demographic processes, thus making biomass distribution critical to understanding the response of trophic metacommunities to perturbations. We further partition the effect of each perturbation on species synchrony when perturbations affect multiple trophic levels. Our approach allows disentangling and predicting the responses of simple trophic metacommunities to perturbations, thus providing a theoretical foundation for future studies considering more complex spatial ecological systems.

Energetic constraints imposed on trophic interaction strengths enhance resilience in empirical and model food webs

Food web stability and resilience are at the heart of understanding the structure and functioning of ecosystems. Previous studies show that models of empirical food webs are substantially more stable than random ones, due to a few strong interactions embedded in a majority of weak interactions. Analyses of trophic interaction loops show that in empirical food webs the patterns of the interaction strengths prevent the occurrence of destabilizing heavy loops and thereby enhances resilience. Yet, it is still unexplored which biological mechanisms cause these patterns that enhance food web resilience. We quantified food web resilience using the real part of the maximum eigenvalue of the Jacobian matrix of the food web from a seagrass bed in the Yellow River Delta (YRD) wetland, that could be parametrized by the empirical data of the food web. We found that the empirically based Jacobian matrix of the YRD food web indicated a much higher resilience than random matrices with the same element values but arranged in random ways. Investigating the trophic interaction loops revealed that the high resilience was due to a negative correlation between the negative and positive interaction strengths (per capita top-down and bottom-up effects, respectively) within positive feedback loops with three species. The negative correlation showed that when the negative interaction strengths were strong the positive was weak, and vice versa. Our invented reformulation of loop weight in terms of biomasses and specific production rates showed that energetic properties of the trophic groups in the loop and mass-balance constraints, for example, the food uptake has to balance all losses, created the negative correlation between the interaction strengths. This result could be generalized using a dynamic intraguild predation model, which delivered the same pattern for a wide range of model parameters. Our results shed light on how energetic constraints at the trophic group and food web level create a pattern of interaction strengths within trophic interaction loops that enhances food web resilience.

Quantifying large-scale ecosystem stability with remote sensing data

To fully understand ecosystem functioning under global change, we need to be able to measure the stability of ecosystem functioning at multiple spatial scales. Although a number of stability components have been established at small spatial scales, there has been little progress in scaling these measures up to the landscape. Remote sensing data holds huge potential for studying processes at landscape scales but requires quantitative measures that are comparable from experimental field data to satellite remote sensing. Here we present a methodology to extract four components of ecosystem functioning stability from satellite-derived time series of Enhanced Vegetation Index (EVI) data. The four stability components are as follows: variability, resistance, recovery time and recovery rate in ecosystem functioning. We apply our method to the island of Ireland to demonstrate the use of remotely sensed data to identify large disturbance events in productivity. Our method uses stability measures that have been established at the field-plot scale to quantify the stability of ecosystem functioning. This makes our method consistent with previous small-scale stability research, whilst dealing with the unique challenges of using remotely sensed data including noise. We encourage the use of remotely-sensed data in assessing the stability of ecosystems at a scale that is relevant to conservation and management practices.

The ghost of disturbance past: long-term effects of pulse disturbances on community biomass and composition

Current global change is associated with an increase in disturbance frequency and intensity, with the potential to trigger population collapses and to cause permanent transitions to new ecosystem states. However, our understanding of ecosystem responses to disturbances is still incomplete. Specifically, there is a mismatch between the diversity of disturbance regimes experienced by ecosystems and the one-dimensional description of disturbances used in most studies on ecological stability. To fill this gap, we conducted a full factorial experiment on microbial communities, where we varied the frequency and intensity of disturbances affecting species mortality, resulting in 20 different disturbance regimes. We explored the direct and long-term effects of these disturbance regimes on community biomass. While most communities were able to recover biomass and composition states similar to undisturbed controls after a halt of the disturbances, we identified some disturbance thresholds that had long-lasting legacies on communities. Using a model based on logistic growth, we identified qualitatively the sets of disturbance frequency and intensity that had equivalent long-term negative impacts on experimental communities. Our results show that an increase in disturbance intensity is a bigger threat for biodiversity and biomass recovery than the occurrence of more frequent but less intense disturbances.

Biotic stability mechanisms in Inner Mongolian grassland

Biotic mechanisms associated with species diversity are expected to stabilize communities in theoretical and experimental studies but may be difficult to detect in natural communities exposed to large environmental variation. We investigated biotic stability mechanisms in a multi-site study across Inner Mongolian grassland characterized by large spatial variations in species richness and composition and temporal fluctuations in precipitation. We used a new additive-partitioning method to separate species synchrony and population dynamics within communities into different species-abundance groups. Community stability was independent of species richness but was regulated by species synchrony and population dynamics, especially of abundant species. Precipitation fluctuations synchronized population dynamics within communities, reducing their stability. Our results indicate generality of biotic stability mechanisms in natural ecosystems and suggest that for accurate predictions of community stability in changing environments uneven species composition should be considered by partitioning stabilizing mechanisms into different species-abundance groups.

Meta-analysis on pulse disturbances reveals differences in functional and compositional recovery across ecosystems

Most ecosystems are affected by anthropogenic or natural pulse disturbances, which alter the community composition and functioning for a limited period of time. Whether and how quickly communities recover from such pulses is central to our understanding of biodiversity dynamics and ecosystem organisation, but also to nature conservation and management. Here, we present a meta-analysis of 508 (semi-)natural field experiments globally distributed across marine, terrestrial and freshwater ecosystems. We found recovery to be significant yet incomplete. At the end of the experiments, disturbed treatments resembled controls again when considering abundance (94%), biomass (82%), and univariate diversity measures (88%). Most disturbed treatments did not further depart from control after the pulse, indicating that few studies showed novel trajectories induced by the pulse. Only multivariate community composition on average showed little recovery: disturbed species composition remained dissimilar to the control throughout most experiments. Still, when experiments revealed a higher compositional stability, they tended to also show higher functional stability. Recovery was more complete when systems had high resistance, whereas resilience and resistance were negatively correlated. The overall results were highly consistent across studies, but significant differences between ecosystems and organism groups appeared. Future research on disturbances should aim to understand these differences, but also fill obvious gaps in the empirical assessments for regions (especially the tropics), ecosystems and organisms. In summary, we provide general evidence that (semi-)natural communities can recover from pulse disturbances, but compositional aspects are more vulnerable to long-lasting effects of pulse disturbance than the emergent functions associated to them.