Advancing our understanding of ecological stability

Stability in plant-pollinator communities across organizational levels: present, gaps, and future

Abstract. The study of ecological stability continues to fill the pages of scientific journals almost seven decades after the first ecologists initiated this line of research. The many advances in this field have focused on understanding the stability of populations, communities or functions within single guilds or trophic levels, with less research conducted across multiple trophic levels and considering the different interactions that relate species to each other. Here, we review the recent literature on the multiple dimensions of ecological stability specifically within plant-pollinator communities. We then focus on one of stability´s dimensions, temporal invariability, and adapt an existing partitioning framework that bridges invariability and synchrony measures across spatial scales and organizational levels to accommodate interactions between plants and their pollinators. Finally, we use this framework to analyse temporal invariability in plant reproductive success, partitioning it on invariability and synchrony components across plant and pollinator populations and communities, as well as their interactions, using a well-resolved dataset that encompasses data for two years. Our review of the literature points to several significant gaps in our current knowledge, with simulation studies clearly overrepresented in the literature as opposed to experimental or empirical approaches. Our quantitative approach to partitioning invariability shows similar patterns of decreasing temporal invariability across increasing organizational levels driven by asynchronous dynamics amongst populations and communities, which overall stabilize ecosystem functioning (plant reproductive success). This study represents a first step towards a better comprehension of temporal invariability in ecosystem functions defined by interactions between species and provides a blueprint for the type of spatially replicated multi-year data that needs to be collected in the future to further our understanding of ecological stability within multi-trophic communities.

Structural dynamics of plant-pollinator mutualistic networks

The discourse surrounding the structural organization of mutualistic interactions mostly revolves around modularity and nestedness. The former is known to enhance the stability of communities, while the latter is related to their feasibility, albeit compromising the stability. However, it has recently been shown that the joint emergence of these structures poses challenges that can eventually lead to limitations in the dynamic properties of mutualistic communities. We hypothesize that considering compound arrangements-modules with internal nested organization-can offer valuable insights in this debate. We analyze the temporal structural dynamics of 20 plant-pollinator interaction networks and observe large structural variability throughout the year. Compound structures are particularly prevalent during the peak of the pollination season, often coexisting with nested and modular arrangements in varying degrees. Motivated by these empirical findings, we synthetically investigate the dynamics of the structural patterns across two control parameters-community size and connectance levels-mimicking the progression of the pollination season. Our analysis reveals contrasting impacts on the stability and feasibility of these mutualistic communities. We characterize the consistent relationship between network structure and stability, which follows a monotonic pattern. But, in terms of feasibility, we observe nonlinear relationships. Compound structures exhibit a favorable balance between stability and feasibility, particularly in mid-sized ecological communities, suggesting they may effectively navigate the simultaneous requirements of stability and feasibility. These findings may indicate that the assembly process of mutualistic communities is driven by a delicate balance among multiple properties, rather than the dominance of a single one.

The impact of grazing activities and environmental conditions on the stability of alpine grassland ecosystems

Globally, grazing activities have profound impacts on the structure and function of ecosystems. This study, based on a 20-year MODIS time series dataset, employs remote sensing techniques and the Seasonal-Trend decomposition using Loess (STL) algorithm to quantitatively assess the stability of alpine grassland ecosystems from multiple dimensions, and to reveal the characteristics of grazing activities and environmental conditions on ecosystem stability. The results indicate that only 5.77% of the area remains undisturbed, with most areas experiencing varying degrees of disturbance. Further analysis shows that grazing activities in high vegetation coverage areas are the main source of interference. In areas with concentrated interference, elevation and slope have a positive correlation with resistance stability, but a negative correlation with recovery stability. Precipitation and landscape diversity have positive effects on both resistance stability and recovery stability. Vegetation coverage and grazing intensity have a negative correlation with resistance stability, but a positive correlation with recovery stability. This highlights the complex interactions between human activities, environmental factors, and ecosystem stability. The findings emphasize the need for targeted conservation and management strategies to mitigate disturbances to ecosystems affected by human activities and enhance their stability.

The Stability of Competitive Metacommunities Is Insensitive to Dispersal Connectivity in a Fluctuating Environment

AbstractMaintaining the stability of ecological communities is critical for conservation, yet we lack a clear understanding of what attributes of metacommunity structure control stability. Some theories suggest that greater dispersal promotes metacommunity stability by stabilizing local populations, while others suggest that dispersal synchronizes fluctuations across patches and leads to global instability. These effects of dispersal on stability may be mediated by metacommunity structure: the number of patches, the pattern of connections across patches, and levels of spatiotemporal correlation in the environment. Thus, we need theory to investigate metacommunity dynamics under different spatial structures and ecological scenarios. Here, we use simulations to investigate whether stability is primarily affected by connectivity, including dispersal rate and topology of connectivity network, or by mechanisms related to the number of patches. We find that in competitive metacommunities with environmental stochasticity, network topology has little effect on stability on the metacommunity scale even while it could change spatial diversity patterns. In contrast, the number of connected patches is the dominant factor promoting stability through averaging stochastic fluctuations across more patches, rather than due to more habitat heterogeneity per se. These results broaden our understanding of how metacommunity structure changes metacommunity stability, which is relevant for designing effective conservation strategies.

Both local stability and dispersal contribute to metacommunity sensitivity to asynchronous habitat availability

The stability of isolated communities depends on the complexity of their foodwebs. However, it remains unclear how local stability interacts with dispersal in multitrophic metacommunities to shape biodiversity patterns. This lack of understanding is deeper in the more realistic frame of landscapes that exhibit non-trivial and time-varying structures. Therefore, in this study, we aim to evaluate the influence of local stabilizing factors versus dispersal in determining the sensitivity of metacommunity biodiversity to increasing asynchrony of site availability. Additionally, we assess the role of foodweb complexity and landscape structure as modulating factors. To accomplish our goals we developed a model based on random matrices for local communities, which are linked by stochastic dispersal over explicit dynamic landscapes. We ran numerical simulations and computed the effect sizes of foodweb temperature, self-limitation, dispersal ability, and all pairwise combinations, on the sensitivity of biodiversity to landscape asynchrony. In our experiments we explored gradients of species richness, foodweb connectance, number of sites, and landscape modularity. Our results showed that asynchrony among site availability periods reduced α -diversity and increased β -diversity. Asynchrony increased γ -diversity at high dispersal rates. Both local and regional stabilizing factors determined the sensitivity of metacommunities to landscape asynchrony. Local factors were more influential in landscapes with fewer sites and lower modularity, as well as in metacommunities composed of complex foodwebs. This research offers insights into the dynamics of metacommunities in dynamic landscapes, providing valuable knowledge about the interplay between local and regional factors in shaping ecological stability and species persistence.

A test of the loose-equilibrium concept with long-lived organisms: Evaluating temporal change in freshwater mussel assemblages

The loose-equilibrium concept (LEC) predicts that ecological assemblages change transiently but return towards an earlier or average structure. The LEC framework can help determine whether assemblages vary within expected ranges or are permanently altered following environmental change. Long-lived, slow-growing animals typically respond slowly to environmental change, and their assemblage dynamics may respond over decades, which transcends most ecological studies. Unionid mussels are valuable for studying dynamics of long-lived animals because they can live >50 years and occur in dense, species-rich assemblages (mussel beds). Mussel beds can persist for decades, but disturbance can affect species differently, resulting in variable trajectories according to differences in species composition within and among rivers. We used long-term data sets (10-40 years) from seven rivers in the eastern United States to evaluate the magnitude, pace and directionality of mussel assemblage change within the context of the LEC. Site trajectories varied within and among streams and showed patterns consistent with either the LEC or directional change. In streams that conformed to the LEC, rank abundance of dominant species remained stable over time, but directional change in other streams was driven by changes in the rank abundance and composition of dominant species. Characteristics of mussel assemblage change varied widely, ranging from those conforming to the LEC to those showing strong directional change. Conservation approaches that attempt to maintain or create a desired assemblage condition should acknowledge this wide range of possible assemblage trajectories and that the environmental factors that influence those changes remain poorly understood.

Interaction network structure explains species' temporal persistence in empirical plant-pollinator communities

Despite clear evidence that some pollinator populations are declining, our ability to predict pollinator communities prone to collapse or species at risk of local extinction is remarkably poor. Here, we develop a model grounded in the structuralist approach that allows us to draw sound predictions regarding the temporal persistence of species in mutualistic networks. Using high-resolution data from a six-year study following 12 independent plant-pollinator communities, we confirm that pollinator species with more persistent populations in the field are theoretically predicted to tolerate a larger range of environmental changes. Persistent communities are not necessarily more diverse, but are generally located in larger habitat patches, and present a distinctive combination of generalist and specialist species resulting in a more nested structure, as predicted by previous theoretical work. Hence, pollinator interactions directly inform about their ability to persist, opening the door to use theoretically informed models to predict species' fate within the ongoing global change.

Understanding temporal variability across trophic levels and spatial scales in freshwater ecosystems

A tenet of ecology is that temporal variability in ecological structure and processes tends to decrease with increasing spatial scales (from locales to regions) and levels of biological organization (from populations to communities). However, patterns in temporal variability across trophic levels and the mechanisms that produce them remain poorly understood. Here we analyzed the abundance time series of spatially structured communities (i.e., metacommunities) spanning basal resources to top predators from 355 freshwater sites across three continents. Specifically, we used a hierarchical partitioning method to disentangle the propagation of temporal variability in abundance across spatial scales and trophic levels. We then used structural equation modeling to determine if the strength and direction of relationships between temporal variability, synchrony, biodiversity, and environmental and spatial settings depended on trophic level and spatial scale. We found that temporal variability in abundance decreased from producers to tertiary consumers but did so mainly at the local scale. Species population synchrony within sites increased with trophic level, whereas synchrony among communities decreased. At the local scale, temporal variability in precipitation and species diversity were associated with population variability (linear partial coefficient, β = 0.23) and population synchrony (β = -0.39) similarly across trophic levels, respectively. At the regional scale, community synchrony was not related to climatic or spatial predictors, but the strength of relationships between metacommunity variability and community synchrony decreased systematically from top predators (β = 0.73) to secondary consumers (β = 0.54), to primary consumers (β = 0.30) to producers (β = 0). Our results suggest that mobile predators may often stabilize metacommunities by buffering variability that originates at the base of food webs. This finding illustrates that the trophic structure of metacommunities, which integrates variation in organismal body size and its correlates, should be considered when investigating ecological stability in natural systems. More broadly, our work advances the notion that temporal stability is an emergent property of ecosystems that may be threatened in complex ways by biodiversity loss and habitat fragmentation.

Divergent ecological responses to typhoon disturbance revealed via landscape-scale acoustic monitoring

Climate change is increasing the frequency, intensity, and duration of extreme weather events across the globe. Understanding the capacity for ecological communities to withstand and recover from such events is critical. Typhoons are extreme weather events that are expected to broadly homogenize ecological dynamics through structural damage to vegetation and longer-term effects of salinization. Given their unpredictable nature, monitoring ecological responses to typhoons is challenging, particularly for mobile animals such as birds. Here, we report spatially variable ecological responses to typhoons across terrestrial landscapes. Using a high temporal resolution passive acoustic monitoring network across 24 sites on the subtropical island of Okinawa, Japan, we found that typhoons elicit divergent ecological responses among Okinawa's diverse terrestrial habitats, as indicated by increased spatial variability of biological sound production (biophony) and individual species detections. This suggests that soniferous communities are capable of a diversity of different responses to typhoons. That is, spatial insurance effects among local ecological communities provide resilience to typhoons at the landscape scale. Even though site-level typhoon impacts on soundscapes and bird detections were not particularly strong, monitoring at scale with high temporal resolution across a broad spatial extent nevertheless enabled detection of spatial heterogeneity in typhoon responses. Further, species-level responses mirrored those of acoustic indices, underscoring the utility of such indices for revealing insight into fundamental questions concerning disturbance and stability. Our findings demonstrate the significant potential of landscape-scale acoustic sensor networks to capture the understudied ecological impacts of unpredictable extreme weather events.

Response trait diversity and species asynchrony underlie the diversity-stability relationship in Romanian bird communities

Biodiversity-stability relationships have frequently been studied in ecology, with the recent integration of traits to explain community stability over time. Classical theory underlying the biodiversity-stability relationship posits that different species' responses to the environment should stabilise community-level properties (e.g. biomass or abundance) through compensatory dynamics. However, functional response traits, which aim to predict how species respond to environmental change, are still rarely integrated into studies of ecological stability. Such traits should mechanistically drive community stability, both in terms of community abundance (functional variability) and composition (compositional variability). In turn, whether and how functional or compositional stability scales to affect temporal variation in functional effect traits (a proxy for ecosystem functioning) remains largely unknown, but is key to consistent ecosystem functioning under environmental change. Here, we explore the diversity-stability relationship in bird communities using annual survey data across 98 sites in central Romania, in combination with global trait databases and structural equation models. We show that higher response trait diversity promotes compositional variability directly, and functional variability indirectly via species asynchrony. In turn, functional variability impacts the temporal stability of effect trait diversity. Multiple facets of diversity and community stability differ between natural forests and agricultural or human-dominated survey sites, and the relationship between response diversity and functional variability is mediated by land cover. Further integration of response-and-effect trait frameworks into studies of community stability will enhance understanding of the drivers of biodiversity change, allowing targeted conservation decision-making with a focus on stable ecosystem functioning in the face of global environmental change.

Multidimensional responses of grassland stability to eutrophication

Eutrophication usually impacts grassland biodiversity, community composition, and biomass production, but its impact on the stability of these community aspects is unclear. One challenge is that stability has many facets that can be tightly correlated (low dimensionality) or highly disparate (high dimensionality). Using standardized experiments in 55 grassland sites from a globally distributed experiment (NutNet), we quantify the effects of nutrient addition on five facets of stability (temporal invariability, resistance during dry and wet growing seasons, recovery after dry and wet growing seasons), measured on three community aspects (aboveground biomass, community composition, and species richness). Nutrient addition reduces the temporal invariability and resistance of species richness and community composition during dry and wet growing seasons, but does not affect those of biomass. Different stability measures are largely uncorrelated under both ambient and eutrophic conditions, indicating consistently high dimensionality. Harnessing the dimensionality of ecological stability provides insights for predicting grassland responses to global environmental change.

Ecological network analysis reveals cancer-dependent chaperone-client interaction structure and robustness

Cancer cells alter the expression levels of metabolic enzymes to fuel proliferation. The mitochondrion is a central hub of metabolic reprogramming, where chaperones service hundreds of clients, forming chaperone-client interaction networks. How network structure affects its robustness to chaperone targeting is key to developing cancer-specific drug therapy. However, few studies have assessed how structure and robustness vary across different cancer tissues. Here, using ecological network analysis, we reveal a non-random, hierarchical pattern whereby the cancer type modulates the chaperones' ability to realize their potential client interactions. Despite the low similarity between the chaperone-client interaction networks, we highly accurately predict links in one cancer type based on another. Moreover, we identify groups of chaperones that interact with similar clients. Simulations of network robustness show that this group structure affects cancer-specific response to chaperone removal. Our results open the door for new hypotheses regarding the ecology and evolution of chaperone-client interaction networks and can inform cancer-specific drug development strategies.

Perspective: sustainability challenges, opportunities and solutions for long-term ecosystem observations

As interest in natural capital grows and society increasingly recognizes the value of biodiversity, we must discuss how ecosystem observations to detect changes in biodiversity can be sustained through collaboration across regions and sectors. However, there are many barriers to establishing and sustaining large-scale, fine-resolution ecosystem observations. First, comprehensive monitoring data on both biodiversity and possible anthropogenic factors are lacking. Second, some in situ ecosystem observations cannot be systematically established and maintained across locations. Third, equitable solutions across sectors and countries are needed to build a global network. Here, by examining individual cases and emerging frameworks, mainly from (but not limited to) Japan, we illustrate how ecological science relies on long-term data and how neglecting basic monitoring of our home planet further reduces our chances of overcoming the environmental crisis. We also discuss emerging techniques and opportunities, such as environmental DNA and citizen science as well as using the existing and forgotten sites of monitoring, that can help overcome some of the difficulties in establishing and sustaining ecosystem observations at a large scale with fine resolution. Overall, this paper presents a call to action for joint monitoring of biodiversity and anthropogenic factors, the systematic establishment and maintenance of in situ observations, and equitable solutions across sectors and countries to build a global network, beyond cultures, languages, and economic status. We hope that our proposed framework and the examples from Japan can serve as a starting point for further discussions and collaborations among stakeholders across multiple sectors of society. It is time to take the next step in detecting changes in socio-ecological systems, and if monitoring and observation can be made more equitable and feasible, they will play an even more important role in ensuring global sustainability for future generations. This article is part of the theme issue 'Detecting and attributing the causes of biodiversity change: needs, gaps and solutions'.

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.

Toward spatially polarized human pressure? A dynamic factor analysis of ecological stability and the role of territorial gradients in Czech Republic

In light of global change, research on ecosystem dynamics and the related environmental policies are increasingly required to face with the inherent polarization in areas with low and high human pressure. Differential levels of human pressure are hypothesized to reflect development paths toward ecological stability of local systems vis à vis socioeconomic resilience. To delineate the latent nexus between socioeconomic development paths and ecological stability of local systems, we proposed a multidimensional, diachronic analysis of 28 indicators of territorial disparities, and ecological stability in 206 homogeneous administrative units of Czech Republic over almost 30 years (1990-2018). Mixing time-invariant factors with time-varying socio-environmental attributes, a dynamic factor analysis investigated the latent relationship between ecosystem functions, environmental pressures, and the background socioeconomic characteristics of the selected spatial units. We identified four geographical gradients in Czech Republic (namely elevation, economic agglomeration, demographic structure, and soil imperviousness) at the base of territorial divides associated with the increased polarization in areas with low and high human pressure. The role of urbanization, agriculture, and loss of natural habitats reflective of rising human pressure was illustrated along the selected gradients. Finally, policy implications of the (changing) geography of ecological disturbances and local development paths in Czech Republic were briefly discussed.

Recent exposure to environmental stochasticity does not determine the demographic resilience of natural populations

Escalating climatic and anthropogenic pressures expose ecosystems worldwide to increasingly stochastic environments. Yet, our ability to forecast the responses of natural populations to this increased environmental stochasticity is impeded by a limited understanding of how exposure to stochastic environments shapes demographic resilience. Here, we test the association between local environmental stochasticity and the resilience attributes (e.g. resistance, recovery) of 2242 natural populations across 369 animal and plant species. Contrary to the assumption that past exposure to frequent environmental shifts confers a greater ability to cope with current and future global change, we illustrate how recent environmental stochasticity regimes from the past 50 years do not predict the inherent resistance or recovery potential of natural populations. Instead, demographic resilience is strongly predicted by the phylogenetic relatedness among species, with survival and developmental investments shaping their responses to environmental stochasticity. Accordingly, our findings suggest that demographic resilience is a consequence of evolutionary processes and/or deep-time environmental regimes, rather than recent-past experiences.

A density functional theory for ecology across scales

Ecology lacks a holistic approach that can model phenomena across temporal and spatial scales, largely because of the challenges in modelling systems with a large number of interacting constituents. This hampers our understanding of complex ecosystems and the impact that human interventions (e.g., deforestation, wildlife harvesting and climate change) have on them. Here we use density functional theory, a computational method for many-body problems in physics, to develop a computational framework for ecosystem modelling. Our methods accurately fit experimental and synthetic data of interacting multi-species communities across spatial scales and can project to unseen data. As the key concept we establish and validate a cost function that encodes the trade-offs between the various ecosystem components. We show how this single general modelling framework delivers predictions on par with established, but specialised, approaches for systems from predatory microbes to territorial flies to tropical tree communities. Our density functional framework thus provides a promising avenue for advancing our understanding of ecological systems.

Disentangling the effects of phosphorus loading on food web stability in a large shallow lake

Excessive nutrient loads reduce ecosystem resilience, resulting in fundamental changes in ecosystem structure and function when exceeding a certain threshold. However, quantitative analysis of the processes by which nutrient loading affects ecosystem resilience requires further exploration. Food web stability is at the heart of ecosystem resilience. In this study, we simulated the dynamics of the food web under different phosphorus loads for Lake Baiyangdian using the PCLake model and calculated the food web stability. Our results showed that there was a good correspondence between the food web stability and ecosystem state response to phosphorus loads. This relationship confirmed that food web stability could be regarded as a signal for the state transition in a real lake ecosystem. Moreover, our estimates suggested that food web stability was influenced only by several functional groups and their interaction strength. Diatoms and zooplankton were the key functional groups that affected food web stability. Phosphorus loads alter the distribution of functional group biomass, which in turn affects energy delivery and, ultimately, the stability of the food web. Corresponding to functional groups, the interactions among zooplankton, diatoms and detritus had the greatest impact, and the interaction strength of the three was positively correlated with food web stability. Overall, our study explained that food-web stability was critical to characterize ecosystem resilience response to external disturbances and can be turned into a scientific tool for lake ecosystem management.

Impacts of extreme climatic events on trophic network complexity and multidimensional stability

Untangling the relationship between network complexity and ecological stability under climate change is an arduous challenge for theoretical and empirical ecology. Even more so, when considering extreme climatic events. Here, we studied the effects of extreme climatic events (heatwaves) on the complexity of realistic freshwater ecosystems using topological and quantitative trophic network metrics. Next, we linked changes in network complexity with the investigation of four stability components (temporal stability, resistance, resilience, and recovery) of community's functional, compositional, and energy flux stability. We found reduction in topological network complexity to be correlated with reduction of functional and compositional resistance. However, temperature-driven increase in link-weighted network complexity increased functional and energy flux recovery and resilience, but at the cost of increased compositional instability. Overall, we propose an overarching approach to elucidate the effects of climate change on multidimensional stability through the lens of network complexity, providing helpful insights for preserving ecosystems stability under climate change.

Spatiotemporal variation of cultivated land ecosystem stability in typical regions of Lower Liaohe Plain China based on stress - buffer - response

The stability of cultivated land ecosystem is crucial to the green and high-quality development of agriculture. Revealing its spatio-temporal differentiation is an important scientific issue to improve the resilience of cultivated land and ensure food security. In this paper, Shenyang, a typical region of Lower Liaohe Plain, is the study area. Starting from the stress buffer response process of cultivated land ecosystem stability, USLE, RWEQ, SDI, RSEI and grey relational model are used to clarify the relationship between the three, and depict the temporal and spatial differentiation pattern of cultivated land ecosystem stability. The results showed that the external stress intensity of cultivated land in Shenyang decreased as a whole, but the stress intensity of cultivated land distributed in the northern and southeast hilly areas increased. Most of the endogenous buffer strength has been improved, and the buffer capacity of cultivated land in the northern hilly region has declined on a large scale. More than half of the response intensity to the effect has been improved, while the response intensity of cultivated land in the west and north has generally declined. The stability of cultivated land ecosystem in Shenyang has been improved for the most part, but in the hilly areas in the north and southeast, the stability in the lower reaches of Liaohe River plain in the south has declined. Terrain conditions and high-intensity cultivation patterns are the important reasons for the temporal and spatial differentiation of cultivated land ecosystem stability in the study area. The study clarified the dynamic process of cultivated land ecosystem stability and provided an important way to grasp the scientific law of stability change.

Ranking species based on sensitivity to perturbations under non-equilibrium community dynamics

Managing ecological communities requires fast detection of species that are sensitive to perturbations. Yet, the focus on recovery to equilibrium has prevented us from assessing species responses to perturbations when abundances fluctuate over time. Here, we introduce two data-driven approaches (expected sensitivity and eigenvector rankings) based on the time-varying Jacobian matrix to rank species over time according to their sensitivity to perturbations on abundances. Using several population dynamics models, we demonstrate that we can infer these rankings from time-series data to predict the order of species sensitivities. We find that the most sensitive species are not always the ones with the most rapidly changing or lowest abundance, which are typical criteria used to monitor populations. Finally, using two empirical time series, we show that sensitive species tend to be harder to forecast. Our results suggest that incorporating information on species interactions can improve how we manage communities out of equilibrium.

Increasing connections among temporal invariability, resistance and resilience of alpine grasslands on the Tibetan Plateau

Ecological stability contains multiple components, such as temporal invariability, resistance and resilience. Understanding the response of stability components to perturbations is beneficial for optimizing the management of biodiversity and ecosystem functioning. Although previous studies have investigated the effects of multiple perturbations on each stability component, few studies simultaneously measure the multiple stability components and their relationships. Alpine grasslands on the Tibetan Plateau are exposed to co-occurring perturbations, including climate change and human activities. Here, we quantified three stability components (temporal invariability, resistance, and resilience) of alpine grasslands on the Tibetan Plateau during periods of high (2000-2008) and low (2009-2017) human activity intensity, respectively. We focused on the effects of climate variables (temperature, precipitation, radiation) and human activities (grazing intensity) on covariation among stability components. The results show that (1) for periods of high and low human activity, temporal invariability was positively correlated with resistance and resilience, while resistance was independent of resilience; (2) the dimensionality of alpine grasslands decreased by almost 10%, from 0.61 in the first period to 0.55 in the second period, suggesting the increasing connections among temporal invariability, resistance and resilience of alpine grasslands; and (3) temperature but not grazing intensity dominated the changes in the dimensionality of stability. These findings improve our understanding of multi-dimensional stability and highlight the importance of climate variability on alpine grassland stability on the Tibetan Plateau.

Environmental factors indirectly reduce phytoplankton community stability via functional diversity

The biodiversity-stability relationship is a fundamental subject of ecological research. Considerable evidence demonstrates that biodiversity can either increase or decrease stability. Most relevant research mainly focuses on grassland and forest ecosystems. The biodiversity-stability relationship in aquatic ecosystems and the underlying mechanisms remain poorly understood. To fill the gap, we conducted a year-long study on the phytoplankton of reservoir ecosystems in the Xiangxi Bay of Three Gorges Reservoir (TGR) to test the following hypotheses: (H1) phytoplankton species richness and functional diversity directly reduce phytoplankton community stability in reservoir ecosystems; (H2) nutrient enrichment and water temperature increasing directly reduce phytoplankton community stability; and (H3) nutrients and water temperature indirectly reduce phytoplankton community stability via biodiversity. The structural equation model (SEM) found that functional diversity (community-weighted means of traits and functional divergence) had significant negative correlations with phytoplankton community stability (p < 0.05), while the species diversity had no significant correlation with phytoplankton community stability (p > 0.05). This finding partially supported the hypothesis H1, which suggested that the functional diversity had a closer tie with stability than the species diversity. SEM did not find any direct effect of environmental factors on phytoplankton community stability, which rejected our hypothesis H2. Instead, SEM found that water temperature and phosphate decreased phytoplankton community stability by increasing the first principal component of the community-weighted means of traits (CWM_PC1), which supported hypothesis H3. Further analysis showed that the increased water temperature and phosphate concentration can promote “r-strategists” species (larger CWM_PC1), which are less resistant to environmental disturbances, therefore decreasing the phytoplankton community stability. Our study highlights the importance of functional diversity in maintaining the relationship between biodiversity and stability in the phytoplankton community, which may provide a mechanistic understanding of the biodiversity-stability relationships in aquatic ecosystems.

Beyond Basic Diversity Estimates-Analytical Tools for Mechanistic Interpretations of Amplicon Sequencing Data

Understanding microbial ecology through amplifying short read regions, typically 16S rRNA for prokaryotic species or 18S rRNA for eukaryotic species, remains a popular, economical choice. These methods provide relative abundances of key microbial taxa, which, depending on the experimental design, can be used to infer mechanistic ecological underpinnings. In this review, we discuss recent advancements in in situ analytical tools that have the power to elucidate ecological phenomena, unveil the metabolic potential of microbial communities, identify complex multidimensional interactions between species, and compare stability and complexity under different conditions. Additionally, we highlight methods that incorporate various modalities and additional information, which in combination with abundance data, can help us understand how microbial communities respond to change in a typical ecosystem. Whilst the field of microbial informatics continues to progress substantially, our emphasis is on popular methods that are applicable to a broad range of study designs. The application of these methods can increase our mechanistic understanding of the ongoing dynamics of complex microbial communities.

Solar park promoted microbial nitrogen and phosphorus cycle potentials but reduced soil prokaryotic diversity and network stability in alpine desert ecosystem

Solar park (SP) is rapidly growing throughout the planet due to the increasing demand for low-carbon energy, which represents a remarkable global land-use change with implications for the hosting ecosystems. Despite dozens of studies estimating the environmental impacts of SP based on local microclimate and vegetation, responses of soil microbial interactions and nutrient cycle potentials remain poorly understood. To bridge this gap, we investigated the diversity, community structure, complexity, and stability of co-occurrence network and soil enzyme activities of soil prokaryotes and fungi in habitats of ambient, the first, and sixth year since solar park establishment. Results revealed different response patterns of prokaryotes and fungi. SP led to significant differences in both prokaryotic and fungal community structures but only reduced prokaryotic alpha diversity significantly. Co-occurrence network analysis revealed a unimodal pattern of prokaryotic network features and more resistance of fungal networks to environmental variations. Microbial nitrogen and phosphorus cycle potentials were higher in SP and their variances were more explained by network features than by diversity and environmental characteristics. Our findings revealed for the first time the significant impacts of SP on soil prokaryotic and fungal stability and functional potentials, which provides a microbial insight for impact evaluation and evidence for the optimization of solar park management to maximize the delivery of ecosystem services from this growing land use.

Scaling up our understanding of tipping points

Anthropogenic activities are increasingly affecting ecosystems across the globe. Meanwhile, empirical and theoretical evidence suggest that natural systems can exhibit abrupt collapses in response to incremental increases in the stressors, sometimes with dramatic ecological and economic consequences. These catastrophic shifts are faster and larger than expected from the changes in the stressors and happen once a tipping point is crossed. The primary mechanisms that drive ecosystem responses to perturbations lie in their architecture of relationships, i.e. how species interact with each other and with the physical environment and the spatial structure of the environment. Nonetheless, existing theoretical work on catastrophic shifts has so far largely focused on relatively simple systems that have either few species and/or no spatial structure. This work has laid a critical foundation for understanding how abrupt responses to incremental stressors are possible, but it remains difficult to predict (let alone manage) where or when they are most likely to occur in more complex real-world settings. Here, we discuss how scaling up our investigations of catastrophic shifts from simple to more complex-species rich and spatially structured-systems could contribute to expanding our understanding of how nature works and improve our ability to anticipate the effects of global change on ecological systems. This article is part of the theme issue 'Ecological complexity and the biosphere: the next 30 years'.

A resilience sensing system for the biosphere

We are in a climate and ecological emergency, where climate change and direct anthropogenic interference with the biosphere are risking abrupt and/or irreversible changes that threaten our life-support systems. Efforts are underway to increase the resilience of some ecosystems that are under threat, yet collective awareness and action are modest at best. Here, we highlight the potential for a biosphere resilience sensing system to make it easier to see where things are going wrong, and to see whether deliberate efforts to make things better are working. We focus on global resilience sensing of the terrestrial biosphere at high spatial and temporal resolution through satellite remote sensing, utilizing the generic mathematical behaviour of complex systems-loss of resilience corresponds to slower recovery from perturbations, gain of resilience equates to faster recovery. We consider what subset of biosphere resilience remote sensing can monitor, critically reviewing existing studies. Then we present illustrative, global results for vegetation resilience and trends in resilience over the last 20 years, from both satellite data and model simulations. We close by discussing how resilience sensing nested across global, biome-ecoregion, and local ecosystem scales could aid management and governance at these different scales, and identify priorities for further work. This article is part of the theme issue 'Ecological complexity and the biosphere: the next 30 years'.

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.

Whole community invasions and the integration of novel ecosystems

The impact of invasion by a single non-native species on the function and structure of ecological communities can be significant, and the effects can become more drastic–and harder to predict–when multiple species invade as a group. Here we modify a dynamic Boolean model of plant-pollinator community assembly to consider the invasion of native communities by multiple invasive species that are selected either randomly or such that the invaders constitute a stable community. We show that, compared to random invasion, whole community invasion leads to final stable communities (where the initial process of species turnover has given way to a static or near-static set of species in the community) including both native and non-native species that are larger, more likely to retain native species, and which experience smaller changes to the topological measures of nestedness and connectance. We consider the relationship between the prevalence of mutualistic interactions among native and invasive species in the final stable communities and demonstrate that mutualistic interactions may act as a buffer against significant disruptions to the native community.

Evaluation of ecosystem stability against climate changes via satellite data in the eastern sandy area of northern China

Intensive and frequent climate change events (e.g., droughts or extreme weather) significantly affect vulnerable water-limited ecosystems. Until now, the ecosystem stability against climate changes in regional scale sandy lands remain unclear. In this study, the AutoRegression (ARx) model was combined with time-series Net Primary Productivity (NPP) data to extract stability metrics (e.g., temporal stability, resilience, drought-resistance, and temperature-resistance) to evaluate the stability of the main sandy land regions of Northern China. Strong correlations among ecosystem stability metrics were found in the study area, such as the significant negative correlation between resilience and resistance (r = -0.49, p < 0.01), the strong positive correlation between drought-resistance and temperature-resistance, (r = 0.81, p < 0.01), except for the uncorrelation between resilience and temporal stability. Meanwhile, more unstable regions were found in the western low- or moderate-cover sandy grassland. Due to the differences of factors (e.g. hydrothermal conditions, vegetation species composition, and other disturbances or anthropogenic impacts), the unstable grasslands and barren regions, Otindag and Hulun Buir sandy lands, and slightly desertified area (SL) presented more resilience but less resistance and variance than the forest and cropland, Horqin Sandy Land, and Moderate (M) or Severe desertified areas (S), respectively. Thus, the unstable low-or moderate-cover grassland and SL area should be paid much more attention to meet the challenges of more intense climate extremes in the future.

Life history mediates the trade-offs among different components of demographic resilience

Accelerating rates of biodiversity loss underscore the need to understand how species achieve resilience—the ability to resist and recover from a/biotic disturbances. Yet, the factors determining the resilience of species remain poorly understood, due to disagreements on its definition and the lack of large‐scale analyses. Here, we investigate how the life history of 910 natural populations of animals and plants predicts their intrinsic ability to be resilient. We show that demographic resilience can be achieved through different combinations of compensation, resistance and recovery after a disturbance. We demonstrate that these resilience components are highly correlated with life history traits related to the species’ pace of life and reproductive strategy. Species with longer generation times require longer recovery times post‐disturbance, whilst those with greater reproductive capacity have greater resistance and compensation. Our findings highlight the key role of life history traits to understand species resilience, improving our ability to predict how natural populations cope with disturbance regimes.

The Effects of Tidal Flat Reclamation on the Stability of the Coastal Area in the Jiangsu Province, China, from the Perspective of Landscape Structure

As one of the most important wetland systems, coastal wetlands play an important role in conserving water, regulating the climate and protecting biodiversity. However, due to large-scale and long-term tidal flat reclamations, the landscape structure and function of the coastal wetlands have been greatly affected. Therefore, it is necessary to understand the spatio-temporal characteristics of the impact of tidal flat reclamation on regional ecology and to quantitatively assess the relationships between them. In this study based on long-term, multiperiod remote sensing data, the main spatio-temporal variation characteristics of stability, and the relationship between stability and tidal flat reclamation were analyzed with regard to the influence scope of tidal flat reclamation. The results showed that a substantial decrease in natural wetlands in 1980, mainly caused by tidal flat reclamation, was discovered in the Jiangsu coastal area, and the influence scope of tidal flat reclamation on regional landscape ecology was roughly 30 km. In the affected area, the overall stability had a tendency to improve, but the stability change characteristics between reclamation area and non-reclamation area varied greatly. Especially in the reclamation area, the stability of construction wetlands and non-wetlands deteriorated. Spatially, the stability outside the reclamation area had the characteristics of first deteriorating and then improving as the distance from the reclamation area increased. Under the influence of tidal flat reclamation, the influence of different use types of TFR on stability was not completely consistent, and the influence of the same uses type of tidal flat reclamation on different landscapes was also different.

Failures to disagree are essential for environmental science to effectively influence policy development

While environmental science, and ecology in particular, is working to provide better understanding to base sustainable decisions on, the way scientific understanding is developed can at times be detrimental to this cause. Locked‐in debates are often unnecessarily polarised and can compromise any common goals of the opposing camps. The present paper is inspired by a resolved debate from an unrelated field of psychology where Nobel laureate David Kahneman and Garry Klein turned what seemed to be a locked‐in debate into a constructive process for their fields. The present paper is also motivated by previous discourses regarding the role of thresholds in natural systems for management and governance, but its scope of analysis targets the scientific process within complex social‐ecological systems in general. We identified four features of environmental science that appear to predispose for locked‐in debates: (1) The strongly context‐dependent behaviour of ecological systems. (2) The dominant role of single hypothesis testing. (3) The high prominence given to theory demonstration compared investigation. (4) The effect of urgent demands to inform and steer policy. This fertile ground is further cultivated by human psychological aspects as well as the structure of funding and publication systems.

Increasing instability of a rocky intertidal meta-ecosystem

Climate change threatens to destabilize ecological communities, potentially moving them from persistently occupied "basins of attraction" to different states. Increasing variation in key ecological processes can signal impending state shifts in ecosystems. In a rocky intertidal meta-ecosystem consisting of three distinct regions spread across 260 km of the Oregon coast, we show that annually cleared sites are characterized by communities that exhibit signs of increasing destabilization (loss of resilience) over the past decade despite persistent community states. In all cases, recovery rates slowed and became more variable over time. The conditions underlying these shifts appear to be external to the system, with thermal disruptions (e.g., marine heat waves, El Niño-Southern Oscillation) and shifts in ocean currents (e.g., upwelling) being the likely proximate drivers. Although this iconic ecosystem has long appeared resistant to stress, the evidence suggests that subtle destabilization has occurred over at least the last decade.

Predators mitigate the destabilising effects of heatwaves on multitrophic stream communities

Amidst the global extinction crisis, climate change will expose ecosystems to more frequent and intense extreme climatic events, such as heatwaves. Yet, whether predator species loss-a prevailing characteristic of the extinction crisis-will exacerbate the ecological consequences of extreme climatic events remains largely unknown. Here, we show that the loss of predator species can interact with heatwaves to moderate the compositional stability of ecosystems. We exposed multitrophic stream communities, with and without a dominant predator species, to realistic current and future heatwaves and found that heatwaves destabilised algal communities by homogenising them in space. However, this happened only when the predator was absent. Additional heatwave impacts on multiple aspects of stream communities, including changes to the structure of algal and macroinvertebrate communities, as well as total algal biomass and its temporal variability, were not apparent during heatwaves and emerged only after the heatwaves had passed. Taken together, our results suggest that the ecological consequences of heatwaves can amplify over time as their impacts propagate through biological interaction networks, but the presence of predators can help to buffer such impacts. These findings underscore the importance of conserving trophic structure, and highlight the potential for species extinctions to amplify the effects of climate change and extreme events.

Global patterns of resilience decline in vertebrate populations

Maintaining the resilience of natural populations, their ability to resist and recover from disturbance, is crucial to prevent biodiversity loss. However, the lack of appropriate data and quantitative tools has hampered our understanding of the factors determining resilience on a global scale. Here, we quantified the temporal trends of two key components of resilience-resistance and recovery-in >2000 population time-series of >1000 vertebrate species globally. We show that the number of threats to which a population is exposed is the main driver of resilience decline in vertebrate populations. Such declines are driven by a non-uniform loss of different components of resilience (i.e. resistance and recovery). Increased anthropogenic threats accelerating resilience loss through a decline in the recovery ability-but not resistance-of vertebrate populations. These findings suggest we may be underestimating the impacts of global change, highlighting the need to account for the multiple components of resilience in global biodiversity assessments.

A roadmap towards predicting species interaction networks (across space and time)

Networks of species interactions underpin numerous ecosystem processes, but comprehensively sampling these interactions is difficult. Interactions intrinsically vary across space and time, and given the number of species that compose ecological communities, it can be tough to distinguish between a true negative (where two species never interact) from a false negative (where two species have not been observed interacting even though they actually do). Assessing the likelihood of interactions between species is an imperative for several fields of ecology. This means that to predict interactions between species-and to describe the structure, variation, and change of the ecological networks they form-we need to rely on modelling tools. Here, we provide a proof-of-concept, where we show how a simple neural network model makes accurate predictions about species interactions given limited data. We then assess the challenges and opportunities associated with improving interaction predictions, and provide a conceptual roadmap forward towards predictive models of ecological networks that is explicitly spatial and temporal. We conclude with a brief primer on the relevant methods and tools needed to start building these models, which we hope will guide this research programme forward. This article is part of the theme issue 'Infectious disease macroecology: parasite diversity and dynamics across the globe'.

Refocusing multiple stressor research around the targets and scales of ecological impacts

Ecological communities face a variety of environmental and anthropogenic stressors acting simultaneously. Stressor impacts can combine additively or can interact, causing synergistic or antagonistic effects. Our knowledge of when and how interactions arise is limited, as most models and experiments only consider the effect of a small number of non-interacting stressors at one or few scales of ecological organization. This is concerning because it could lead to significant underestimations or overestimations of threats to biodiversity. Furthermore, stressors have been largely classified by their source rather than by the mechanisms and ecological scales at which they act (the target). Here, we argue, first, that a more nuanced classification of stressors by target and ecological scale can generate valuable new insights and hypotheses about stressor interactions. Second, that the predictability of multiple stressor effects, and consistent patterns in their impacts, can be evaluated by examining the distribution of stressor effects across targets and ecological scales. Third, that a variety of existing mechanistic and statistical modelling tools can play an important role in our framework and advance multiple stressor research.

Environmental risk in an age of biotic impoverishment

The science underpinning biodiversity's importance to human well-being seems to be taken up little by environmental decision makers. Since the 1950s, ecological, evolutionary and environmental research has pointed to the importance of biodiversity as a significant factor influencing the stability and functioning of population, community, eco- and Earth-systems and the environmental services they provide. Despite its prominence and the tremendous contributions to our understanding of the natural world, this field of research, which we term 'bio-functional ecology', seems not to have had the impact it should. Biotic impoverishment, the loss of biodiversity across all scales and across all taxa, continues to worsen. We suggest that redirecting ecology's emphasis on ecological stability to a focus on environmental risk could help bring bio-functional ecology research more into the environmental arena. Rather than managing biodiversity as an agent of ecological stability, biodiversity could be managed as a natural capital asset in a portfolio of social, human, produced and financial capital assets. This would allow using portfolio theory to identify options for minimizing environmental risk while ensuring human well-being. In this essay, we argue that environmental risk more accurately captures people's motivation to preserve and manage biodiversity than does ecological stability. This redirection from stability to risk may provide greater clarity for decision makers and people in general as to why biodiversity is fundamentally linked to human well-being. In doing so, we can help curb the currently unabated spread of biotic impoverishment across the biosphere.

Habitat size influences community stability

Mechanisms linked to demographic, biogeographic, and food-web processes thought to underpin community stability could be affected by habitat size, but the effects of habitat size on community stability remain relatively unknown. We investigated whether those habitat-size-dependent properties influenced community instability and vulnerability to perturbations caused by disturbance. This is particularly important given that human exploitation is contracting ecosystems, and abiotic perturbations are becoming more severe and frequent. We used a perturbation experiment in which 10 streams, spanning three orders of magnitude in habitat size, were subjected to simulated bed movement akin to a major flood disturbance event. We measured the resistance, resilience, and variability of basal resources, and population and community-level responses across the stream habitat-size gradient immediately before, and at 0.5, 5, 10, 20, and 40 d post-disturbance. Resistance to disturbance consistently increased with stream size in all response variables. In contrast, resilience was significantly higher in smaller streams for some response variables. However, this higher resilience of small ecosystems was insufficient to compensate for their lower resistance, and communities of smaller streams were thus more variable over time than those of larger streams. Compensatory dynamics of populations, especially for predators, stabilized some aspects of communities, but these mechanisms were unrelated to habitat size. Together, our results provide compelling evidence for the links between habitat size and community stability, and should motivate ecologists and managers to consider how changes in the size of habitats will alter the vulnerability of ecosystems to perturbations caused by environmental disturbance.