Oikos

Successful ecosystem restoration is intimately linked to the persistence of species in local communities and across landscapes. As such quantitative approaches to ecological restoration require the integration of community and metapopulation ecology. Together these disciplines demonstrate that local colonisation, via habitat connectivity and size, and species interactions, both modulate the process of community assembly. However, thus far restoration ecology still remains disconnected from network ecology this preventing a holistic, community-wide perspective to restoration. We aim to inform ecological restoration using a multi-layer modelling framework integrating ecological interactions and species dispersal dynamics. We explore the drivers that modulate recolonisation dynamics of species across restored landscapes. We further investigate how restoration improves the structural properties of food webs, the number of successful recolonisations and the role of configuration of restored patches in restoration outcomes. We find that recolonisation is the result of a trade-off between dispersal ability and energy requirements. 97% of plant recolonisation and 88% of herbivore recolonisations happened within close proximity to the source patches. Better dispersers - intermediate and top species in the food webs - were able to recolonise habitat by benefitting from the increased biomass influx from restoration. When only a small proportion of the landscape could be restored, the location and connectivity of restored areas strongly influenced the outcome of restoration: more connected patches enabled on average the recolonisation of about 1 additional intermediate species compared to that of isolated patches. However, this difference faded as soon as more patches were restored, and improving larger portions of the landscape always resulted in better outcomes. Restoring 1/3 of the landscape enabled on average the recolonisation of ~4 additional species. Our findings suggest that quantitative models can inform restoration efforts necessary to bring native species back to restored areas. They also suggest that attention should be given to the requirements of the recolonisers, the distance of their introduction from restored areas and their trophic and ecological niche. These aspects are crucial to assess their energy and habitat requirements for successful establishment.

Existing literature on ecological networks provides valuable insights into the structure-stability relation of antagonistic, mutualistic or competitive systems, but it remains unclear whether these insights also apply to networks that contain a mix of different interaction types. Here, we study the effect of modularity on stability in systems that contain not only antagonistic interactions between two guilds, but also competition, facilitation or even antagonism within each guild, inspired by Ghanaian tree-liana interaction networks. We represent these systems as structured community matrices with random interaction strengths, in which we vary both the modularity within the antagonistic subnetwork and the type of intraguild interactions. Using the eigenvalues of the community matrix to assess stability, we find that modularity in antagonistic interactions generally has a stabilising effect, in line with results on single-interaction type networks. We furthermore find that the magnitude of this effect is modulated by the type of intra-guild interaction under consideration and is largest when these interactions describe facilitation. We explain these findings via a shift in the balance between self-reinforcing and self-damping feedback loops. Our results highlight the need to study how patterns in inter- and intraguild interactions jointly affect ecosystem stability.

In order to feed a growing global population without silencing nature, conceiving agricultural management strategies reconciling yield and conservation goals is key. Using numerical simulations of a metacommunity model, we explore the possibilities for compromise offered by spatial management strategies of farmed areas. Each strategy is characterized by its farming intensity, the proportion of farmed lands and their spatial aggregation. We show that achieving equitable yield-biodiversity compromise is difficult. While conciliatory strategies offering top yield and biodiversity are typically not possible, accepting slightly lower yields (ie, "Pretty Good Yield strategies") allows to recover substantial biodiversity. Such reconciliation possibilities are limited for species with small dispersal. Yield increases mainly through farmland expansion, whereas farming intensity strongly influences biodiversity, increasing it at low intensity before decreasing with further intensification. Finally, we demonstrate that reconciliation is easier if agricultural production relies on biodiversity through ecosystem services.

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.

Agroecosystems are dynamic ecosystems, constituted by patches of vegetation and agricultural use, where biodiversity is shaped by spatial and temporal variability. While most studies have focused on spatial composition and configuration, the role of temporal variability remains poorly understood. Yet, temporal dynamics can strongly modify species composition, abundance, and persistence in ecological communities. Temporal variability is particularly relevant in agroecosystems with rainfed agriculture where environmental conditions shift dramatically between rainy and dry seasons. In this paper, we assess the role of temporal variability on biodiversity maintenance in an agricultural matrix using a metacommunity model that simulates an agricultural landscape under rainfed conditions, that is, with abrupt seasonal changes in the agricultural patches. This model couples a local community network dynamic with a migration dynamic and is based on empirically documented features of rainfed agricultural matrices. Our results show that temporal variability provides new opportunities for species to recover from low densities. However, the effect of temporal variability is not straightforward. It depends on the initial and final conditions, the migration and mortality rates and the intensity of temporal variability. Overall, our findings highlight the need to further investigate temporal variability to better understand its role in shaping biodiversity in agricultural landscapes.

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.

O_LISpecies interactions are increasingly recognised as temporally dynamic. For plant-pollinator networks, evidence shows that interactions vary not only seasonally but also over the diel cycle. However, we still know little about what determines their diel structure, whether this structure is important for robustness to species loss, and which plant traits are associated with the roles plants play in this structure. These gaps are fundamental, because knowing what shapes networks over the diel cycle is required to predict the effects of global change drivers, such as light pollution, that may shift the timing of interactions. C_LIO_LIUsing 22 plant-pollinator networks sampled over morning, afternoon, and night, we addressed these gaps by applying a multilayer framework to characterise their diel structure, link it to robustness, and test which plant traits are associated with plant roles across diel periods (participation, versatility) and within them (centrality). C_LIO_LIDiel structure was non-random: interactions were segregated among diel periods yet integrated through plants visited across the diel cycle. Networks were more robust to simulated species loss when interactions were on average more evenly distributed across periods and when plants were more strongly interconnected among periods, although this benefit diminished when both properties were high simultaneously. The association between plant traits and their roles shifted with the temporal scale. Across diel periods, structural traits were the stronger predictors: taller plants were visited more evenly across the diel cycle (higher participation), whereas shorter plants shared pollinators with plants from multiple periods (higher versatility), potentially mediating indirect effects among them. Within diel periods, floral visual cues became more influential, with achromatic contrast the most consistent predictor: at night, plants with brighter flowers were well visited within the period, sharing pollinators with other plants of that period (higher centrality). C_LIO_LIThese findings identify diel structure as a functional axis of network organisation and indicate that plant-pollinator networks are assembled hierarchically: structural traits set a baseline across the diel cycle, whereas light conditions determine which traits matter within periods, ultimately defining distinct temporal pathways vulnerable to global change. C_LI

Warming affects food webs globally. In the iconic intraguild predation food web module consisting of a basal resource, a specialist consumer, and an omnivorous predator, resource enrichment can favor the predator by increasing the relative importance of intraguild predation compared to resource competition. Here, we integrate empirically established thermal scaling relationships into a model of intraguild predation. We show that warming can shift the power balance between consumer and predator and affect invasion and equilibrium outcomes by inducing changes to resource enrichment - without any differences in thermal optima between species. The nature of these shifts depends on the thermal scaling of resource self-regulation and the strength of resource top-down regulation. We also test the capacity of several generic early warning signals to predict these shifts and find variance-based indicators to be more reliable than autocorrelation-based ones. Our results have implications for predictive food web ecology and biocontrol applications under global change.

Mortality-inducing disturbances are important, ubiquitous drivers of community composition and function. Importantly, human activities and climate change are increasingly altering disturbance regimes. Most disturbance studies focus on the effects of current disturbance regimes, rarely considering those of historical regimes. However, recent theoretical work predicts that historical regimes can leave persistent legacies, modulating the communitys response to novel disturbances and invasive species. Here, we complement this theoretical approach using a model bacterial system that experienced disturbance regimes for [~]120 generations, followed by novel regimes and invasions for another [~]120 generations. Our results show persistent effects of historical legacies on disturbance-diversity relationships. Furthermore, some combinations of past and novel regimes promote invasion with increasing resident diversity, while others prevent it; legacies may explain conflicting diversity-invasibility relationships. These findings demonstrate the importance of historical legacies in disturbance-prone ecosystems, and underscore the challenges in predicting future community responses to disturbance regime changes.

Nutrient availability in many temperate ecosystems is shaped by soil properties and historical land use. Especially in otherwise nutrient-poor landscapes human-induced, local fertilisation can generate fine-scale mosaics of nutrient hotspots. Whether and how large herbivores respond to such heterogeneity remains poorly understood. We tested whether spatial variation in soil-derived nutrient availability structures habitat selection by large herbivores, using full-year GPS tracking data from 7 red deer (Cervus elaphus) in the Veluwe, the Netherlands. We used soil types as a proxy for nutrient availability and assigned nutrient scores based on soil pH, cation exchange capacity and soil structure. We then evaluated habitat selection across multiple components of space use: (i) home range size; (ii) use of relatively nutrient-rich parts within home ranges; (iii) selection among soil types; and (iv) selection of locally enriched former agricultural patches. Red deer used relatively nutrient-rich within their home range more than expected based on availability, including local patches enriched by former agricultural use. However, site selection did not consistently follow nutrient scores among soil types. These results show that nutrient availability does shape habitat selection, but primarily through fine-scale, localised nutrient enrichment rather than broad-scale variation in soil properties. Our findings demonstrate that nutrient-related foraging contributes to habitat selection in a large wild herbivore, while also revealing that this process is scale- and context-dependent. By repeatedly concentrating their foraging in nutrient-rich patches, large herbivores may contribute to nutrient redistribution across the landscape, with the potential to reinforce or modify existing spatial heterogeneity in resource availability and ecosystem functioning.

1. Species loss can erode food-web functioning not only through secondary extinctions, but also through biomass redistribution, weakened energy pathways, and threshold-like functional collapse. Common topology-, connectivity-, and extinction-based robustness metrics provide valuable summaries of structural disassembly and cascade risk, but they are not designed to quantify continuous biomass retention, collapse-associated species sets, and non-additive group-level effects within a single dynamic framework. 2. We develop a dynamic biomass-based framework for assessing food-web robustness under progressive species removal. The framework introduces Dynamic Area-based Robustness (DAR), which quantifies the weighted area between slow- and fast-collapse reference trajectories of total ecosystem biomass retention. Building on these trajectories, we operationally define the Minimal Vital Species Set (MVSS) as the smallest fast-collapse-prefix species set whose removal first drives biomass below a predefined functional-collapse threshold. We further propose Cluster Influence (CI), which compares the biomass effect of simultaneous group removal with the mean effect of removing the same species individually. 3. We evaluated the framework using 120 niche-model virtual food webs spanning controlled gradients of species richness and connectance, and further demonstrated its applicability on 16 empirical stream food webs. We compared DAR with AUC- and secondary-extinction-based robustness metrics and assessed the sensitivity of DAR, MVSS, and CI to key bioenergetic parameters and parameter uncertainty. 4. DAR captured biomass-based robustness patterns that were only partly aligned with structural and extinction-based metrics, indicating that dynamic functional degradation provides complementary information. In virtual food webs, MVSS subsets were strongly enriched in basal species or basal resource nodes, and smaller MVSS proportions were associated with stronger positive CI under fast-collapse trajectories. Together, DAR, MVSS, and CI provide a reproducible framework for linking food-web structure, biomass dynamics, collapse thresholds, and non-additive species-set effects, offering a practical tool for dynamic robustness assessment in theoretical and empirical food webs.

Ecologists have long investigated how community complexity affects ecological stability, yet how community complexity influences multistability, defined as the presence of alternative stable states, remains poorly understood. We developed a novel framework integrating stochastic community assembly with stability landscape analysis to quantify multistability from species interaction matrices. Using this framework, we systematically explored how species interaction properties shape the relationship between species diversity (species pool size) and the number of alternative stable states. Mean interaction strength was the primary determinant: competitive interactions amplified the positive relationship between species diversity and the number of alternative stable states. In competitive communities, a greater number of alternative stable states was associated with lower community uncertainty, a measure of the long-term unpredictability of community assembly dynamics. These results highlight the importance of characterizing the entire stability landscape. Our framework provides a general approach for understanding and quantifying multistability in complex ecological communities.

Under complex perturbation regimes, biodiversity dynamics show temporal variability in species and community abundance around long-term population trends. Many species indeed show long-term declines while other species increase, putting natural communities far from stationary regimes, while variability is often studied near equilibrium. We contribute to bridging this gap by investigating population and community variability during long-term trends caused by press perturbations in stochastic models of population dynamics. By estimating the deterministic changes in mean and variance during the transient regime, we show that population variability deviates from stationary expectations. Moreover, the deviation strongly depends on the sign of the population trends: increases generate excesses of variability while declines generate deficits. Scaling up to community variability, we propose a decomposition of community variability deviation, allowing to highlight that community variability in the transient regime depends on how the press perturbation is distributed within species relative abundances and growth rates. These results challenge the equilibrium assumption and open new perspectives for the study of the variability of ecological systems under multiple perturbation types.

Seasonal changes in climate, resources, and trophic interactions jointly shape prey population dynamics in ecological systems. In monsoon-driven tropical and subtropical landscapes, prey populations cycle between cool, wet, favourable periods during the rainy seasons and hot/cold, dry and sub-optimal conditions outside the rainy seasons, with resource availability and predation risk changing across seasons of the year. Defensive strategies and species interactions such as aposematism and Batesian mimicry are expected to interact with seasonal changes in resource availability and predation risk in determining population dynamics of prey species. Here we study population dynamics of mimetic butterfly community members using a 12-year long-term dataset from a subtropical urban forest in peninsular India. Our results show that climate and species interactions differentially influence population dynamics of different functional categories in mimetic butterfly communities, i.e., of aposematic species, mimetic and non-mimetic forms of mimetic species, and close relatives treated as ecological and phylogenetic contrasts. Population dynamics of non-mimetic species and forms were predominantly influenced by climate parameters such as temperature and precipitation, whereas population dynamics of mimics were more deeply impacted by mimetic interactions. Population dynamics of non-mimetic and mimetic forms of the same species showed distinct decoupling, with population dynamics of non-mimetic forms being similar to their non-mimetic relatives (phylogenetic contrasts). On the other hand, population dynamics of aposematic species and mimetic forms/species followed the predictions of negative frequency dependence and phase-shifting in mimicry theory: (a) mimetic forms/species were less abundant than their Batesian models, (b) the harmonic mean of populations of Batesian models influenced the upper limit of relative frequency of mimetic forms/species to a greater degree in these continuously breeding, seasonally fluctuating populations, and (c) populations of Batesian mimics peaked after population peaks of their Batesian models. These results reveal that climate and species interactions differentially determine population dynamics of prey species by functional categories at the community level, rather than by species identity and individual species attributes and resource demands.

AO_SCPLOWBSTRACTC_SCPLOWO_LICommunity assembly graphs (CAGs) summarize which species combinations can coexist and how single-species invasions drive transitions between them, encoding the pathways, alternative endpoints, and cycles that make up a communitys assembly history. Constructing CAGs from dynamical models requires methods that are both computationally tractable and faithful to the underlying ecological dynamics. However, existing methods rely on restrictive assumptions, such as global stability, that exclude alternative stable states and non-equilibrium dynamics known to occur in empirical systems. C_LIO_LIWe develop a computational pipeline that constructs CAGs from any generalized Lotka-Volterra model. Building on the invasion graph framework and its connection to permanence, the pipeline verifies that community dynamics are bounded, identifies which subsets of species coexist in the sense of permanence, determines which single-species invasions are dynamically realized, and assigns each community a topographic height equal to the length of the longest assembly path leading to it. We also provide a numerical algorithm to simulate the dynamics of community assembly. C_LIO_LIWe prove several general properties of the resulting graphs, including that a successful invader is never subsequently excluded and that, in the absence of assembly cycles, permanent communities can be reassembled by introducing their species one at a time in the right order. We prove that the CAG faithfully reproduces the compositional shifts seen in the numerically simulated dynamics of assembly. Applying the pipeline to three empirically based models (a New Zealand grassland, a European pasture, and a Puerto Rican ant community), we show how competition strength and mutualistic feedbacks reshape the assembly landscape and how intransitive competition generates assembly cycles. C_LIO_LIOur approach accommodates alternative stable states and non-equilibrium dynamics without requiring global stability, and it turns the long-standing landscape metaphor into a quantitative, mechanistically grounded object by resolving what "height" means. More broadly, it makes the topography of the assembly pathways measurable, providing a way to compare the historical contingency and predictability of the assembly in ecological systems. C_LI

The effect that environmental conditions have on community and network assembly processes remains unclear, in part because these processes operate at multiple scales. Because marine primary producers and microinvertebrates have limited mobility, are susceptible to multiple stressors, and can be observed interacting in situ, their habitat-based interactions provide an informative system for disentangling network organising processes. We sampled 646 habitat-use networks, quantifying interactions involving habitat-users and biogenic habitat-formers over 12 months at 9 sites within Te Ihutai/Avon-Heathcote estuary in Christchurch, Aotearoa New Zealand. Using generalised dissimilarity mixed-effect models, we examined whether changes to species interactions - deconstructed into species turnover and interaction rewiring - were modulated by environmental covariates, including freshwater discharge, elevation, temperature, spatial location and season. We found that with increasing dissimilarity in sites proximity to freshwater, interaction change was more driven by rewiring, whereas differences in elevation (i.e., between channels and non-channel habitats) were driven by species turnover, with more sessile species inhabiting tidal channels. The proximity of habitats also played a strong role, with nearby networks comprising more similar interactions, and species turnover becoming more prevalent with increasing distance. Our results highlight that the relative influence and magnitude of rewiring and species turnover in controlling estuarine interaction networks was affected by the individual species distributions across the estuary and their responses to separate, but co-occurring, environmental factors. Quantification of habitat-former/user interaction networks offers robust, albeit understudied, measures of processes that can underpin community assembly, highlighting their potential importance in research, management and conservation.

Ecological theory states that the geographic ranges and coexistence of species are determined by fundamental and realized niches - the sets of environments where a species intrinsic population growth rate is positive in the absence and presence of competitors, respectively. Yet large-scale tests of niche theory have been hampered by the challenge to obtain sufficient data on demography and competition. Here, we quantify fundamental and realized niches by combining data on variation in fundamental demographic rates, community composition and the abiotic environment across the global geographic ranges of 29 shrub species from the South African Fynbos biome (a global biodiversity hotspot). Estimated pairwise competition coefficients and fundamental-realized niche contrasts reveal multi-scale mechanisms of species coexistence. At small scales, species generally exert stronger competition on themselves than on other species. At biogeographical scales, more competitive species have narrower fundamental niches but are not significantly better dispersed, which provides evidence for a generalist-specialist trade-off rather than a competition-colonization trade-off. Under both present and future climates, interspecific competition more strongly limits the realized niches and geographic ranges of generalist species. The large-scale application of niche theory thus identifies key forces shaping biodiversity and indicates that generalist species may be more strongly impacted by climate change than previously thought.

Although cities are increasingly recognized as ecological islands, a unified framework explaining their susceptibility to alien plant invasion remains lacking. Using the most recent and comprehensive global dataset of urban alien plants, we modelled alien richness, mimicking island biogeography theory (IBT). Across all models, neither city size nor geographic isolation independently explained alien richness. Instead, richness was consistently associated with their interaction, supporting the central IBT prediction. However, the strength of this interaction depends on how city size was quantified, with socio-economic dimensions exhibiting stronger positive interactions with geographic isolation than physical measures of city size. Introduction-hub identity further modified these relationships. North America was the only hub for which the interaction between city size and isolation was consistently weakened, indicating that donor regions of alien plants are not ecologically equivalent. Simulations of simultaneous increases in city size and isolation showed that larger, more connected cities generally accumulated more alien plants despite increasing geographic distance, but the magnitude and direction of these responses are hub dependent. Our findings inspire an extension of classical IBT to a mechanistic explanation for global variation in urban alien plant richness in this increasingly urbanized and globally connected world.

Climate change is disrupting life's seasonal rhythms, altering the timing of key phenophases and reshaping how communities assemble. Beyond shifting flowering times, climate change can modify the extent of floral overlap and the sequence in which species bloom, generating novel assemblages with uncertain consequences for plant-pollinator interactions. Here, we ask whether flowering order generates priority effects in plant-pollinator communities, much like germination order does in plant communities. We tested how flowering order influences bee foraging behaviour and plant reproductive success in two co-flowering species, Hypochaeris radicata and Campanula rotundifolia, using a greenhouse experiment in which we manipulated the sequence of floral availability while allowing bees to forage repeatedly. We quantified changes in visit frequency, interspecific switches, handling time, and seed production. Our findings reveal priority effects in bee foraging that were strong enough to affect plant fitness: both species received more visits when flowering earlier than their co-occurring counterpart, and seed production declined when species flowered later. Overall, our results show that flowering order is an underappreciated driver of plant-pollinator interactions, suggesting that climate-driven phenological shifts could alter priority-effect dynamics with broader implications for community assembly. Key questions remain: How will climate-driven phenological shifts rearrange flowering sequences, and how will these priority effects emerge in more diverse communities in the wild? Our controlled experiment reveals strong flowering-order effects, underscoring the need to evaluate how widespread and impactful such dynamics are under accelerating climate change.

Land-use change, such as the transformation of woody ecosystems into open pastures, acts as a strong ecological filter, favouring some species while excluding others according to differences in ecological niche breadth. Understanding how differences in niche breadth influence species responses under anthropogenic filters is crucial to anticipate their persistence or displacement. In this study, we quantified realized niche breadth in two sympatric ecosystem engineers, the Neotropical leaf-cutter ants Atta cephalotes and Atta laevigata, to test whether breadth differences are consistent with specialist and generalist ecological strategies. We characterized realized niche breadth across fine-scale environmental gradients by integrating hemispherical photography, microclimatic data, mound architecture, and edaphic profiles from 114 colonies across a regional transect in the Colombian Andes, alongside macroclimatic data from Copernicus. Principal Component Analysis (PCA) and PERMANOVA identified canopy openness and bushes- and tree-type vegetation density as the principal axes of interspecific niche partitioning. The observed differences in realized niche breadth were consistent with specialist and generalist ecological strategies. A. laevigata was predominantly associated with open-canopy areas, warmer micro- and macroclimatic conditions, and narrower edaphic dispersion. In contrast, A. cephalotes occupied a wider range of microhabitat conditions. This broader realized niche breadth is compatible with previous reports of A. cephalotes occurring in urban areas. Together, these findings suggest that niche breadth may influence how Neotropical leaf-cutter ants respond to habitat transformation, helping to understand the ecological consequences of land-use change.