Ecology

O_LIForests are vertically structured ecosystems where light attenuation, microclimatic buffering and resource availability occur along continuous gradients from the canopy to the understorey layers. Despite this complexity, studies rarely integrate trophic interactions across vertical layers, overlooking how vertical forest structure shapes consumer communities through abiotic and biotic pathways. C_LIO_LIIn this study, we combined layer-specific measurements of plant diversity, structure and microclimate with arthropod sampling in the canopy and understorey, as well as bird survey data, in a temperate forest. Applying Bayesian structural equation models with explicitly defined directional pathways, we modelled both consumer biomass and abundance across trophic levels and vertical layers. C_LIO_LIAbundance measures were predominantly filtered by local layer conditions, while biomass responded to conditions across layers, reflecting stand-level energy flow. This suggests that these two metrics capture fundamentally different ecological processes. Canopy conditions consistently predicted understorey arthropod abundance across trophic levels, while the reverse was not observed, suggesting a strong asymmetric downward propagation of canopy-driven effects. Furthermore, trophic interactions between arthropod primary and secondary consumers remained largely stratified within vertical layers, suggesting a vertical food web compartmentalisation rarely shown in structurally complex aboveground systems. C_LIO_LIPlant diversity, structure and microclimate shaped consumer communities mainly through the modulation of resource availability and plant apparency, with effects varying across vertical layers, trophic levels and taxonomic groups. Through complementary mechanisms, plant diversity likely determined the variability of resources available to consumers at different trophic levels. Structural properties, in contrast, potentially drove the spatial redistribution of these resources through light attenuation and microclimatic buffering, which in turn influenced the physiological capacity of consumers to access and exploit available resources. C_LIO_LIThese findings demonstrate that vertical stratification mediates trophic pathways in a highly directional manner, with canopy characteristics playing a disproportionate role in structuring the forest community across layers. Integrating layer-specific structural and trophic indicators into forest biodiversity assessments and management strategies is therefore essential to fully evaluate biodiversity dynamics and multifunctionality in structurally complex forest ecosystems. C_LI

Litter invertebrates mediate a substantial proportion of decomposition and nutrient cycling in terrestrial ecosystems, yet how moisture availability structures their communities remains poorly understood. We propose that moisture availability could shape litter faunal communities through two alternate pathways: (1) a productivity effect: greater productivity and detrital inputs in wetter forests should increase litter-faunal abundance, (2) a trait effect: phylogenetic differences in water balance should filter communities according to taxon-specific moisture tolerances. We tested these expectations across 100 forest sites spanning a moisture gradient in south-eastern Australia, from dry sclerophyll forest to cool temperate rainforest. Measuring 11 focal invertebrate taxa, total litter-faunal abundance increased threefold across the moisture gradient, from 400,000 individuals per hectare of dry forest to 1.2 million individuals per hectare of rainforest - consistent with greater resource availability in wetter and more productive habitats. However, this overall abundance trend masked pronounced variation in community composition across habitat types. While moisture-sensitive crustaceans and myriapods (particularly Isopoda and Chilopoda) were concentrated in rainforest litter, two groups of hexapods (Blattodea and Embioptera) were most abundant in dry forest litter and declined sharply toward rainforest habitat. These contrasting responses indicate that dry forests do not simply represent depauperate versions of wet-forest communities but harbour their own distinct and abundant litter invertebrate assemblages. Thus, moisture structures litter faunal communities via both proposed mechanisms: (1) a productivity effect and (2) a trait filtering effect. Given that moisture fundamentally structures litter faunal communities, shifts in forest moisture regimes under climate change may substantially alter detritivore communities, with consequences for decomposition processes and nutrient cycling globally.

Investigating the factors that stabilize biological communities is a central topic in ecology. Response diversity, defined as variation in species responses to environmental change, has been proposed as a key mechanism underlying the biodiversity-ecosystem functional stability (BEFS) relationship, whereby greater species diversity enhances ecological stability. Previous studies have shown that response diversity promotes ecological stability by generating asynchronous population fluctuations and the resulting compensatory dynamics. Although several metrics have been proposed to quantify response diversity, they do not explicitly consider the presence of insensitive species whose performance is unaffected by current environmental conditions. To examine how insensitive species influence response diversity, species persistence, and ecological stability, we conducted numerical simulations of a generalized Lotka-Volterra model under environmental forcing. We first confirmed that increasing variation among sensitive species increased the response diversity index and stabilized community dynamics. We then examined a scenario in which response diversity depended solely on the proportion of sensitive and insensitive species, assuming that all sensitive species responded identically to environmental change. Under this assumption, the response diversity index was maximized when sensitive and insensitive species occurred in equal proportions, whereas increasing the number of sensitive species monotonically destabilized community dynamics. Consequently, the relationship between response diversity and community stability depended on how response diversity was generated, such that higher response diversity could even be associated with lower community stability. These findings demonstrate that overlooking environmentally insensitive species can obscure the mechanisms linking response diversity and ecological stability. More broadly, our results reveal that response diversity comprises at least two distinct biological components--species sensitivity and response variation among sensitive species--that can have contrasting consequences for community stability. We therefore highlight the need to quantify sensitive species empirically and to develop response diversity metrics that distinguish these components. Author SummaryUnderstanding why some communities remain stable despite environmental change is a longstanding goal in ecology. Response diversity, which refers to differences in how species respond to environmental change, has been proposed as a key mechanism explaining why greater biodiversity (species richness) can promote ecological stability. Because species respond differently to changing environments, declines in some species can be compensated by increases in others, helping to stabilize community dynamics. However, previous studies have rarely considered species that are insensitive to current environmental changes. Using a mathematical model, we show that response diversity can arise from two distinct biological components--the number of sensitive species and variation in their responses--and that these components can have contrasting effects on ecological stability. When response diversity reflects variation among sensitive species, greater response diversity stabilizes community dynamics, as expected. In contrast, when response diversity changes only because of the proportions of sensitive and insensitive species, higher response diversity can be associated with lower community stability. Our findings highlight the importance of quantifying the number of sensitive species and developing response diversity metrics that distinguish species sensitivity from variation in responses among sensitive species.

1. Gall-inducing insects create structurally distinct microhabitats that mediate their interactions with associated parasitoid communities, and variation in gall architecture is recognized as an important driver of the composition and organization of these communities. 2. In cynipid gall wasps of the genus Diplolepis, galls range from single-chambered to multichambered structures, and this variation has previously been linked to differences in parasitoid attack rates and community composition, yet its consequences for the topology and stability of the resulting ecological networks remain unexplored. 3. We compiled 17 empirical Diplolepis-parasitoid interaction networks spanning seven host taxa and used dynamical (non-normalized return time) and structural (robustness) measures of stability, together with network topology and diversity metrics, to test whether gall architecture shapes the organization of the resulting parasitoid networks. We hypothesized that networks associated with multichambered galls would be more stable, more connected and more unevenly structured than those associated with single-chambered galls. 4. Multichambered-gall networks showed significantly higher robustness at the species level and lower species-level non-normalized return times under intermediate and weak self-regulation, together with higher species-level connectance and clustering coefficients. In contrast, gall architecture reduced rather than increased Shannon diversity after accounting for network size, and had no detectable effect on the Gini index. Most effects weakened after aggregation to the genus level, highlighting the sensitivity of gall-associated network descriptors to taxonomic resolution. 5. These results indicate that gall architecture leaves a measurable signature on the organization and stability of associated parasitoid networks that extends beyond simple differences in community composition, adding a network-level perspective to the study of gall morphology as an ecological filter of natural-enemy communities.

Beta diversity is a fundamental component of regional biodiversity that accumulates from compositional differences between local species assemblages. Although beta diversity is increasingly applied across spatial scales, its scale dependence remains incompletely synthesized, particularly concerning variation in spatial scale used to define alpha diversity (grain size). Using tree community data from Barro Colorado Island, we find that both additive and multiplicative beta diversity are consistently higher for unequal than equal grain divisions across different spatial extents and numbers of grains. These results can be explained by Jensen's inequality based on the concave-down relationship of alpha diversity with area that in turn increases beta diversity through the scaling relationship between alpha and gamma diversity. Combined with our additional analysis showing that this prediction is robust to more general models of species richness, including species--area and species--sampling-effort curves, these results reveal a previously unrecognized, predictable range of beta diversity variation.

Identifying how species interact in ecological networks is key to understanding species' contributions to ecosystem functioning, but can be difficult to establish in species-rich communities. Functional niches, which capture broader ecological strategies, are often easier to assess and could help approximate species' interaction roles. We tested this by integrating species interaction and leaf functional trait data of tree species and leaf-associated interaction types from a large-scale forest biodiversity experiment. We found that identity, variability, and similarities of functional niches shaped corresponding aspects of interaction roles. Interestingly, however, this association inversed in the case of functional niche variability, which decreased instead of increased the variability of species interactions. This suggests a potential trade-off between processes that determine variability in functional and interaction space. Furthermore, effects were not constrained within aspects, with similarities of interactions being particularly responsive to most tested niche aspects, indicating that interaction-based competition among plants is particularly sensitive to functional niche differences. Moreover, many effects of functional niches depended on tree species biomass and tree species richness, highlighting the importance of the larger ecological context for determining species interaction roles. Together, our findings show that species' interaction roles, while clearly altered by, are not simply a consequence of functional niches. Instead, interaction roles integrate multiple aspects of functional niches depending on species performances and community composition and can therefore be crucial for anticipating ecosystem change.

Extreme climate events are becoming more frequent, yet their consequences for the recovery of plant-invertebrate relationships under warming remain poorly understood. We investigated over two years of how ground-dwelling invertebrate communities recovered from a 40-days drought in outdoor grassland mesocosms exposed to ambient conditions, constant warming or periodic heatwaves, and both combined. We then examined how post-drought community shifts were associated with above-ground plant biomass, measured concurrently with invertebrate sampling. Drought had no detectable effect on total invertebrate abundance at either recovery time (one or four months after drought). By contrast, diversity showed warming-dependent responses one month after drought and a delayed drought legacy four months later, when diversity declined only under constant warming, with or without periodic heatwaves. At the four-month post-drought sampling, plant biomass-invertebrate diversity coupling was evident only in non-drought plots, with negative relationships under ambient and heatwave regimes but a positive relationship under constant warming alone. This pattern was largely associated with responses of herbivores, particularly Stylommatophora. Our results highlight lagged drought effects in invertebrate diversity that emerged months later and, under warming, extended to weakened plant biomass-invertebrate diversity coupling, pointing to disrupted bottom-up control with potential consequences for food-web functioning.

Disentangling causation from correlation is the foundation of the scientific method. Yet, growing evidence suggests that much observational ecology research has not correctly made this distinction due to inappropriate statistical modelling and unappreciated time-delays. Here, we apply time-lagged causal inference techniques to assess the drivers of seabird declines, using multi-decadal North Atlantic seabird data across the behaviour, mass, survival, reproduction and population size of two species ecology (Atlantic puffin, Fratercula arctica, and black-legged kittiwake, Rissa tridactyla). We demonstrate that both climate and anthropogenic activity can suppress breeding success and cause population declines. Moreover, population size is specifically impacted by delayed recruitment effects where both species decline after a lag corresponding to their estimated age of first reproduction. These North Atlantic seabirds are therefore at risk from future environmental and anthropogenic changes, as time-delays may result in populations already on an extinction trajectory prior to changes being detectable in their abundance.

As ecosystems face a growing number of threats, coextinctions (resultant extinctions following a primary extinction) are expected to proliferate. However, less is known about the conditions under which coextinctions could outpace primary extinctions. Because coextinctions often occur through lost species interactions, we posit that aspects of food web structure and complexity can help predict differences in vulnerability to coextinction across ecosystems. To test this, we leverage Bayesian network models to assess the extent to which variation in ecosystem vulnerability to coextinction varies with food web structure. We find that food webs with high maximum trophic level are most vulnerable to coextinction, and that maximum trophic level is a better predictor than other aspects of food web structure, such as species richness or trophic connectance. Extending this approach, we also find that maximum trophic level uncovers the relative vulnerability of ecosystem services to species coextinction across 12 empirical food webs.

Defended prey are often thought to rely on conspicuous warning signals to distinguish themselves from undefended prey, facilitating predator learning and avoidance. Yet many chemically defended organisms are inconspicuous and difficult to distinguish from palatable prey, raising a fundamental question: how do predators avoid defended prey when prey themselves provide little or no reliable signals of defense? We tested whether host plants can function as indirect indicators of prey defense using Carolina wrens (Thryothorus ludovicianus), chemically defended Eumaeus atala larvae, undefended Galleria mellonella larvae, and two distinct plant species. Defended and undefended prey were experimentally made to appear visually identical, forcing predators to rely on host-plant associations as the only available source of information. Wrens rapidly altered both search behavior and attack decisions according to plant identity. Mechanistic attack models incorporating predator discrimination between defended and undefended prey were strongly favored when plants were present, with defended prey experiencing substantially lower attack risk than undefended prey. When plants were removed, support for discrimination weakened and attacks on both prey types increased. Spatial autocorrelation of host plants further shaped predator behavior, with strongly clustered plants hosting defended prey receiving disproportionately fewer visits. Together, these results suggest host plants can function as ecologically meaningful cues of prey defense, influencing both predator search patterns and attack decisions. More broadly, our findings suggest warning systems may extend beyond prey phenotype alone, and that ecological context (including host-plant identity and spatial structure) may contribute to the evolution and maintenance of aposematism.

Diverse ecological communities can reduce pathogen transmission; a phenomenon known as the dilution effect of biodiversity. This effect, in turn, depends on variation in host species' ability to spread disease (i.e., host competence) and which host species persist under biodiversity loss. Mutualistic symbionts can influence host competence and are sensitive to variation in host biodiversity; yet whether mutualists can modify dilution effects is unknown, partially because quantifying host competence during epidemics remains challenging. We experimentally tested whether mutualists could modify dilution effects by establishing gradients of host species richness, community competence, and access to the below-ground arbuscular mycorrhizal fungus (AMF), Rhizoglomus irregulare. Plant hosts were then exposed to the fungal root pathogen, Rhizoctonia solani, and disease spread was monitored over the course of an epidemic. Overall, host richness did not affect epidemic outcomes. Instead, AMF inoculation increased disease risk via species-specific increases in host competence. Moreover, communities containing highly competent host species experienced more disease, but only in the presence of mutualistic AMF. These results underscore the importance of plant community composition in mycorrhiza-mediated disease dynamics and suggest that predicting disease in our changing world might require a deeper understanding of host-symbiont and pathogen-symbiont interactions under global change.

1. Detecting causal relationships from ecological time series remains challenging because community dynamics are often nonlinear, high-dimensional, noisy, and strongly synchronized. These characteristics can reduce the reliability of existing causal inference methods and complicate the identification of ecological interactions in complex natural systems. 2. I introduce Forest-weighted Causal Correlation (FORCC), a machine-learning-based framework that infers directional causality from adaptive neighborhood structures learned by random forests. Rather than evaluating causal direction through cross-map reconstruction, FORCC quantifies directional dependence from the preservation of neighborhood structure using rank-based associations among forest-weight matrices. 3. Simulations of coupled nonlinear systems showed that FORCC accurately recovered causal direction while substantially reducing synchronization-induced false-positive detections relative to conventional convergent cross mapping. Chatterjee's {xi} exhibited the strongest resistance to synchronization-induced errors among the evaluated rank-based statistics. 4. Application to a 12-year marine community time series from Maizuru Bay, Japan, identified asymmetric relationships between individual taxa and community dynamics, revealing candidate driver-like and passenger-like roles that were not readily explained by seasonal synchrony alone. 5. By combining adaptive neighborhood learning with rank-based causal inference, FORCC provides a scalable framework for causal discovery in ecological time series. The method offers a practical tool for screening causal relationships, generating ecological hypotheses, and investigating complex interactions in multivariate natural systems.

Abundance correlations cannot reveal ecological interactions without an assumption about the covariance of environmental noise. A natural biological expectation is that similar species respond similarly to environmental fluctuations, generating positive correlations. Yet the same species also tend to overlap more strongly in resource use and therefore compete more intensely, generating negative correlations. The simplest plausible benchmark is thus to take environmental-response correlations proportional to niche overlap. We show that, under this assumption and across a broad class of stochastic community models, the two effects cancel exactly: equal-time abundance correlations vanish, independently of interaction strength, heterogeneity, and system size. Away from this matched point, the observed correlations measure primarily the mismatch between shared environmental response and competition, rather than the interaction matrix itself. Correlations can recover information about niche overlap when competitive feedback is delayed relative to environmental forcing, but the inference then depends on a resource-response timescale that is generally not determined by the abundance time series alone. When stochasticity enters through the mechanism that generates similarity itself--for example, through fluctuating shared resources--nonzero correlations may persist, but they reflect yield-depletion mismatch rather than niche overlap. Abundance correlations therefore report how environmental variability reaches the community at least as much as they report who competes with whom.

Field ecologists often rely on observational data to understand the impact of environmental stressors and management interventions on natural systems. Natural and anthropogenic events (e.g. wildfires, protected areas, nutrient deposition) do not occur randomly in space, however, which can introduce bias into observational studies--which we refer to as causal selection bias. Field study designs that ignore the non-random occurrence of stressors may yield biased estimates of stressor effects on ecosystems. Matching methods commonly used in economics, political science and epidemiology offer a powerful framework for controlling for causal selection bias by identifying more comparable treatment and control sites. Although these methods are increasingly used in conservation, they are rarely used in ecological field-based studies. Here we review how Propensity Score Matching (PSM) can improve field sampling designs in ecology and strengthen causal identification of stressor effects. Then we apply this approach to a case study examining wildfire effects on forest recovery in California. We conclude with practical recommendations for implementing PSM to improve causal identification of ecological change, which is particularly important for developing effective management interventions.

Ecological coarse-graining of individuals or species into aggregate variables, such as total biomass or regional abundance, is common practice, yet differences among species can still influence aggregate dynamics. We propose a metric for quantifying this irreducible dynamical heterogeneity. For small fluctuations near a stable equilibrium, we compare the aggregate fluctuation spectrum of the full dynamical system with that of the best Ornstein-Uhlenbeck model having the same dimension as the aggregate. The remaining spectral mismatch quantifies the dynamical effects of hidden differences that the fitted aggregate model cannot capture. For weakly interacting random community models at fixed collective interaction strength, we show that increasing species richness can either reduce or increase this heterogeneity, depending on how species interact. Our framework helps understand when ecological and evolutionary differences average out versus when their dynamical effects persist.

In natural ecosystems, community dynamics are driven by diverse interactions operating through both ecological and reproductive processes. Although theory predicts that these processes jointly generate complex and contingent dynamics through the interplay of stabilizing (negative frequency dependence arising from niche differences) and destabilizing effects (positive frequency dependence caused by reproductive interference), empirical tests of this prediction remain scarce. Here, we combined experimental and theoretical approaches to investigate the dynamics of two congeneric annual plant species (Commelina) experiencing both ecological competition and reproductive interference. Our empirically parameterized model revealed a large niche difference and mutual reproductive interference. However, the reproductive interference was not strong enough to generate pronounced contingency of community dynamics on initial conditions. Instead, coexistence was the most likely outcome regardless of initial species composition. Parameter exploration indicated that the weak contingency arose because reproductive assurance strategies of Commelina species buffered the minority disadvantage caused by reproductive interference. These findings provide empirical evidence that reproductive interference does not necessarily destabilize coexistence and that it may be outweighed by ecological niche and fitness differences. Our study highlights the importance of integrating ecological and reproductive processes towards better prediction of community dynamics.

Understanding spatial and temporal variation in community composition is central to protecting and monitoring biodiversity. Similarity in the composition of two communities decreases along spatial and temporal gradients, a relationship known as distance decay. Comparing distance-decay relationships across taxonomic, functional, and bioclimatic facets of diversity provides a means of interrogating niche-based versus neutral influences on community assembly. Furthermore, the context in which these facets yield overlapping or complementary information about global change impacts remains poorly understood. In this study, we examined spatiotemporal distance-decay relationships for taxonomic, functional, and bioclimatic facets of alpine plant diversity leveraging elevation gradients on five peaks in the White Mountains, California, USA, sampled at 3-4 time points between 2007 and 2024. Using multivariate Bayesian beta regression models, we estimated the slopes of elevation distance decay over multiple surveys and across taxonomic, functional and bioclimatic diversity to understand how spatial distance-decay relationships are changing through time and across different facets of diversity. We found strong spatial distance decay of taxonomic similarity across all peaks, with the highest elevation peak showing the strongest decay. Functional and bioclimatic similarities decayed more weakly than taxonomic similarity, suggesting environmental filtering shapes trait and niche distributions. Critically, spatial decay patterns showed no temporal signal across facets of diversity, indicating community stasis rather than biotic homogenization or differentiation. This study adds further evidence that xeric alpine plant communities are resisting climate change impacts through time.

1. Temperature shapes life histories through its effects on energy allocation among growth, reproduction and maintenance. The resulting temperature dependence of performance is commonly characterised using thermal performance curves (TPCs), which are often treated as static descriptions that apply uniformly throughout life. Yet the response to thermal variability may change across ontogeny. 2. We recorded growth, reproduction and survival throughout the lifetimes of individual Daphnia magna under four thermal regimes: Constant Low (15C), Constant Rearing (20C), Constant High (25C) and Variable (15C to 25C). The mean temperature under Variable closely matched that under Constant Rearing. Using an allometric energy-allocation model, we derived age specific and lifetime performance measures and quantified their uncertainty with a stratified individual-level bootstrap. Our principal quantity was the Jensen contrast, defined as performance under Variable minus that under Constant Rearing. 3. Age specific point estimates of the Jensen contrast changed sign across ontogeny. A positive aggregate contrast in full trajectory growth concealed a negative mid-life contrast; reproductive point estimates were positive during early and mid life but negative later. Bootstrap support was strong for the positive early life and negative mid-life growth contrasts, and for the positive early life reproductive contrast. Under a second-order approximation, this pattern of estimated signs is consistent with ontogenetic changes in effective thermal curvature. 4. The positive early life reproductive response did not carry through to the lifetime outcome: expected lifetime reproduction was lower under Variable than under Constant Rearing, with strong bootstrap support for the negative lifetime contrast. Because lifetime reproduction is survival weighted, lower survival under Variable reduced later reproductive contributions; across the estimated trajectories, the accumulated negative late life contribution out-weighed the earlier positive contributions. 5. These results show why forecasts based on mean temperature, a single life stage or an aggregate TPC may misrepresent lifetime performance under variable thermal regimes. Accounting for both ontogeny and temperature variability may therefore improve forecasts of life-history performance in increasingly variable thermal environments.

Ecologists remotely track movement steps of animals (e.g., via global positioning systems) and use step selection functions to study the effect of environmental factors upon their movement decisions. Constructing such functions requires pairing each observed step with some number of unobserved but feasible comparison steps. Larger numbers of comparison steps generally yield better estimates but also incur potentially challenging computational demands. Thus, it is important to determine an appropriate number of comparison steps. No established guidance exists for this decision. Here, we use simulated tracks to assess how many comparison steps are needed, fitting each set of steps to a conditional logistic regression model. We monitor errors in estimated effects for several classes of tracks, identifying the number of comparison steps for which mean relative absolute error in estimated effects is consistently low. By this criterion, 32 comparison steps per observed step are needed for our primary class of simulated tracks. Tracks in more homogeneous landscapes, tracks with shorter mean step lengths, or shorter tracks generally require more comparison steps (ranging from 64 to 128 per observed step) to achieve the same level of accuracy. Longer tracks generally require fewer comparison steps (16 per observed step). These results clearly demonstrate that the number of comparison steps influences how well step selection functions estimate covariate effects and provides initial direction in a research area that currently lacks quantitative guidance. Movement ecologists should take care when selecting the number of comparison steps paired with each observed step because those decisions matter.

Successional communities often recover slowly because progression stalls at persistent stages that resist replacement. Here, we show that resilience in such systems is frequently governed by a single bottleneck stage with the lowest effective exit rate. Using empirical transition ma-trices from intertidal and plant communities, we demonstrate that altering the bottleneck has a much larger effect on resilience than modifying any other stage. We then show that this bottle-neck principle emerges naturally from both Markov and continuous-time models of succession. Specifically that the slowest return to equilibrium is controlled primarily by the stage with the smallest effective exit rate, which also dominates the mean first-passage time to late succession. These results provide a simple biological interpretation of resilience in successional communities and suggest that management efforts are most effective when they target the stage that limits the pace of succession.