General statistical scaling laws for stability in ecological systems

Accounting for effects of growth rate when measuring ecological stability in response to pulse perturbations

Ecological stability is a vital component of natural ecosystems that can inform effective conservation and ecosystem management. Furthermore, there is increasing interest in making comparisons of stability values across sites, systems and taxonomic groups, often using comparative synthetic approaches, such as meta-analysis. However, these synthetic approaches often compare/contrast systems where measures of stability mean very different things to the taxa involved. Here, we present results from theoretical models and empirical data to illustrate how differences in growth rates among taxa influence four widely used metrics of ecological stability of species abundances responding to pulse perturbations: resilience, recovery, resistance and temporal stability. We refer to these classic growth-rate-dependent metrics as 'realised' stability. We show that realised resilience and realised temporal stability vary as a function of organisms' growth rates; realised recovery depends on the relation between growth rate and sampling duration; and realised resistance depends on the relation between growth rate and sampling interval. To account for these influences, we introduce metrics intended to be more independent of growth rates, which we refer to as 'intrinsic' stability. Intrinsic stability can be used to summarise the overall effects of a disturbance, separately from internal recovery processes - thereby allowing more general comparisons of disturbances across organisms and contexts. We argue that joint consideration of both realised and intrinsic stability is important for future comparative studies.

Examining the association of family environment and children emotional/behavioral difficulties in the relationship between parental anxiety and internet addiction in youth

Introduction

Associations between parental anxiety and adolescent internet addiction have been documented in the literature; however, few studies have analyzed the role of the family environment in this relationship. This study aims to explore the relationship between parental anxiety and adolescent internet addiction while also investigating the indirect relationships involving multiple dimensions of the family environment and child emotional behavior issues.

Methods

Surveys were conducted among 6,296 parent-child pairs. We administered SDQ, CIAS-R, and FES-CV to assess adolescents' issues and internet addiction, and evaluate family environment. Additionally, parents completed GAD-7 to assess parental anxiety levels.Results: Correlation analysis revealed that the family environment and adolescent emotional behavior issues played an indirect relationship in the link between parental anxiety and internet addiction.

Discussion

The findings emphasize the importance of addressing parental anxiety and fostering a positive family environment as effective measures to alleviate adolescent emotional behavior problems and reduce the risk of internet addiction.

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.

A landscape persistence-based methodological framework for assessing ecological stability

Ecological stability is a critical factor in global sustainable development, yet its significance has been overlooked. Here we introduce a landscape-oriented framework to evaluate ecological stability in the Qingzang Plateau (QP). Our findings reveal a medium-high stability level in the QP, with minimal changes over recent years. The driving factors vary across landscape types, with climate and anthropogenic factors emerging as crucial determinants. While anthropogenic factors are strong but unstable due to policy changes and economic development, climatic factors exert a consistent influence. Based on our results, we propose site-specific ecological conservation and restoration measures. The ecological stability assessment framework provides a practical tool to understand the link between environmental conditions and ecosystems.

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.

Understanding and applying biological resilience, from genes to ecosystems

The natural world is under unprecedented and accelerating pressure. Much work on understanding resilience to local and global environmental change has, so far, focussed on ecosystems. However, understanding a system's behaviour requires knowledge of its component parts and their interactions. Here we call for increased efforts to understand 'biological resilience', or the processes that enable components across biological levels, from genes to communities, to resist or recover from perturbations. Although ecologists and evolutionary biologists have the tool-boxes to examine form and function, efforts to integrate this knowledge across biological levels and take advantage of big data (e.g. ecological and genomic) are only just beginning. We argue that combining eco-evolutionary knowledge with ecosystem-level concepts of resilience will provide the mechanistic basis necessary to improve management of human, natural and agricultural ecosystems, and outline some of the challenges in achieving an understanding of biological resilience.

Book Review: On ecological networks and biological invasions

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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.

Metapopulation persistence can be inferred from incomplete surveys

Habitat destruction and fragmentation are principal causes of species loss. While a local population might go extinct, a metapopulation-populations inhabiting habitat patches connected by dispersal-can persist regionally by recolonizing empty patches. To assess metapopulation persistence, two widely adopted indicators in conservation management are metapopulation capacity and patch importance. However, we face a fundamental limitation in that assessing metapopulation persistence requires that we survey or sample all the patches in a landscape: often these surveys are logistically challenging to conduct and repeat, which raises the question whether we can learn enough about the metapopulation persistence from an incomplete survey. Here, we provide a robust statistical approach to infer metapopulation capacity and patch importance by sampling a portion of all patches. We provided analytic arguments on why the metapopulation capacity and patch importance can be well predicted from sub-samples of habitat patches. Full-factorial simulations with more complex models corroborate our analytic predictions. We applied our model to an empirical metapopulation of mangrove hummingbirds (Amazilia boucardi). On the basis of our statistical framework, we provide some sampling suggestion for monitoring metapopulation persistence. Our approach allows for rapid and effective inference of metapopulation persistence from incomplete patch surveys.

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.

Herbivory and Drought Reduce the Temporal Stability of Herbaceous Cover by Increasing Synchrony in a Semi-arid Savanna

Ecological stability in plant communities is shaped by bottom-up processes like environmental resource fluctuations and top-down controls such as herbivory, each of which have demonstrated direct effects but may also act indirectly by altering plant community dynamics. These indirect effects, called biotic stability mechanisms, have been studied across environmental gradients, but few studies have assessed the importance of top-down controls on biotic stability mechanisms in conjunction with bottom-up processes. Here we use a long-term herbivore exclusion experiment in central Kenya to explore the joint effects of drought and herbivory (bottom-up and top-down limitation, respectively) on three biotic stability mechanisms: (1) species asynchrony, in which a decline in one species is compensated for by a rise in another, (2) stable dominant species driving overall stability, and (3) the portfolio effect, in which a community property is distributed among multiple species. We calculated the temporal stability of herbaceous cover and biotic stability mechanisms over a 22-year time series and with a moving window to examine changes through time. Both drought and herbivory additively reduced asynchronous dynamics, leading to lower stability during droughts and under high herbivore pressure. This effect is likely attributed to a reduction in palatable dominant species under higher herbivory, which creates space for subordinate species to fluctuate synchronously in response to rainfall variability. Dominant species population stability promoted community stability, an effect that did not vary with precipitation but depended on herbivory. The portfolio effect was not important for stability in this system. Our results demonstrate that this system is naturally dynamic, and a future of increasing drought may reduce its stability. However, these effects will in turn be amplified or buffered depending on changes in herbivore communities and their direct and indirect impacts on plant community dynamics.

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.

Extreme flood disturbance effects on multiple dimensions of river invertebrate community stability

Multidimensional analysis of community stability has recently emerged as an overarching approach to evaluating ecosystem response to disturbance. However, the approach has previously been applied only in experimental and modelling studies. We applied this concept to an 18-year time series (2000-2017) of macroinvertebrate community dynamics from a southeast Alaskan river to further develop and test the approach in relation to the effects of two extreme flood events occurring in 2005 (event 1) and 2014 (event 2). Five components of stability were calculated for pairs of pre- or post-event years. Individual components were tested for differences between pre- and post-event time periods. Stability components' pairwise correlations were assessed and ellipsoids of stability were developed for each time period and compared to a null model derived from the permuted dataset. Only one stability component demonstrated a significant difference between time periods. In contrast, 80% of moderate and significant correlations between stability components were degraded post-disturbance and significant changes to the form of stability ellipsoids were observed. Ellipsoids of stability for all periods after the initial disturbance (2005) were not different to the null model. Our results illustrate that the dimensionality of stability approach can be applied to natural ecosystem time-series data. The major increase in dimensionality of stability observed following disturbance potentially indicates significant shifts in the processes which drive stability following disturbance. This evidence improves our understanding of community response beyond what is possible through analysis of individual stability components.