Ecological Applications

1. Natal dispersal is a key process in population ecology because it links local demographic processes to broader-scale population dynamics by redistributing individuals. When using capture-recapture data, multistate capture-recapture models using discrete spatial units as states are the gold standard for estimating natal dispersal among spatial units while accounting for spatial variation in survival, recruitment and imperfect detection. However, because their computational cost increases rapidly with the number of spatial units, applications have been limited to a small number of units. Therefore, in practice, these models cannot provide spatially detailed inference on natal dispersal across large landscapes. 2. We develop a computationally efficient Bayesian capture-recapture model, called the efficient natal dispersal (END) model, to estimate natal dispersal among discrete spatial units jointly with spatial variation in demographic parameters and detection probabilities. The END model relies on two key structural features: juveniles and breeders are separated into two arrays, and resightings outside the natal spatial unit are aggregated over time for individuals released as juveniles. 3. Using simulations, we show that the END model is considerably (up to 30 times) more computationally efficient than a conventional multistate model, while maintaining comparable parameter accuracy. We then apply the END model to white stork (Ciconia ciconia) capture-recapture data from Germany across 101 hexagonal spatial units, a spatial resolution at which a conventional multistate model is computationally infeasible. We estimate natal dispersal among units jointly with spatial variation in survival and recruitment. This allows us to identify areas of lower or higher survival, earlier or delayed recruitment, and dispersal probabilities among all units. By combining estimated dispersal probabilities with existing data on the number of juveniles born in each spatial unit, we estimate natal dispersal in terms of numbers of individuals and identify units with positive or negative net migration, sources and sinks. 4. Overall, our approach moves capture-recapture analyses from estimating natal dispersal among a few spatial units to inferring dispersal networks and assessing their demographic consequences across large domains. Our approach is applicable to many spatially structured capture-recapture datasets, opening new opportunities for studying spatial population dynamics.

The ecological and economic threat posed by invasive pests demands proactive mitigation. Species distribution models (SDMs) are widely used in efforts to predict where invasive species might spread after introduction, though such models face several limitations. Among these is the unrealistic assumption of niche uniformity throughout a species' range. This has led to interest in developing SDMs that explicitly account for local adaptation, though few methods have achieved this in a way that confidently separates local adaptation from population structure. Here we develop and implement a sequential SDM approach that incorporates experimentally verified associations between genotype, phenotype, and environment to forecast establishment risk in a major agricultural pest. We leverage genomic data from 738 individuals to characterize the geographic distribution of alleles at a major-effect locus for cold tolerance (tret1) in Helicoverpa armigera, an invasive crop pest of major economic concern in North America. We demonstrate that a recently detected North American population carries a cold-adapted tret1 allele, which has likely contributed to its persistence. We quantify the contribution of cold-adapted tret1 to the potential invasive range of H. armigera in North America under current and future climate scenarios. We find that cold-adapted tret1 may dramatically expand the potential range of H. armigera, and that potential future range expansion is likely to be driven primarily by cold-adapted individuals. Our results highlight the importance of accounting for intraspecific variation in invasive species risk assessments and management strategies.

Citizen science observations are abundant, but conservation requires turning uneven records into reliable predictions and directing new surveys to where information is missing. We developed a biodiversity platform for Japan that is updated monthly and integrates 2.32 million records to predict 8,297 species across seven taxonomic groups. Shared representation models outperformed species-specific models in four groups and extended predictions to species with few records. Five independent datasets, including structured monitoring, environmental DNA and complete forest inventories, confirmed that the models ranked observed species and occupied sites above alternatives, with median AUCs of 0.724 to 0.894 across sites and 0.650 to 0.841 across species. For any user-selected area, the platform returns candidate species, distribution predictions, a biodiversity map corrected for uneven observation effort, a conservation priority map for native species and a map recommending where to survey next. This map highlights places where species with few records are predicted to occur despite limited sampling. Independent observations showed that areas ranked highly by this predicted potential contained many such species, indicating that model predictions can help direct surveys toward knowledge gaps. New observations are incorporated into monthly updates, creating a national feedback system connecting citizen science, local conservation decisions and future surveys.

1- Biological control of mosquitoes using aquatic predators offers a sustainable alternative to chemical insecticides, yet the specific predator and prey functional traits that govern consumption efficacy remain poorly quantified at a global scale. 2- We conducted a global meta-analysis of 755 effect sizes across 59 studies to evaluate how predator identity (fish vs. odonate naiads), body size, dietary guilds, and prey characteristics influence consumption rates. Using multilevel models and robust publication-bias corrections, we quantified predation efficiency, expressed throughout as the consumption rate (CR, larvae predator -1 h -1 ), while accounting for methodological variations across experimental designs. The primary literature itself proved geographically skewed towards Asia (chiefly India), with Africa, the Americas, and Europe markedly under-represented. 3- Grouping predators solely by broad taxonomic identity concealed the central pattern in our data. Although naiads outperformed fish when compared directly within the same studies, this taxon-level difference was driven almost entirely by non-mosquitofish species, the least efficient predator group overall. Mosquitofish (\textit{Gambusia} spp.) and dragonfly naiads were statistically indistinguishable from one another, indicating that dietary specialisation, not taxonomic identity, is the stronger predictor of predation efficacy. Predator body size strongly and positively predicted consumption rates in naiads---driven primarily by dragonflies---but showed no significant or negative relationship in fish. 4- Methodological traits heavily structured the extreme heterogeneity observed across studies; notably, exposure time acted as a severe rate-suppressor, where prolonged assays drastically underestimated per-hour consumption rates due to satiety or handling constraints. Nevertheless, a combined model incorporating all significant ecological moderators simultaneously explained a substantial share of the between-study variance, confirming that predator-prey dynamics in these systems are highly predictable from functional traits. 5- Effective biological control cannot rely on broad taxonomic assumptions but requires evidence-based trait-matching. Management programs should prioritise body size when deploying insect predators, selecting the largest individuals within species known to consume mosquito larvae and favour insectivorous fish species over generalists. Crucially, because short-term laboratory assays artificially inflate efficacy, multi-duration assessments are essential to accurately scale up biocontrol predictions from experimental arenas to complex, real-world ecosystems.

Managers must make decisions in the face of uncertainty, especially when available resources are limiting. Identifying thresholds when certain conditions are met or exceeded enable the potential to mitigate risks. In 2005, sustainable harvest levels of willow ptarmigan were identified to avoid harvest efforts exceeding three hunter days km2. Here we evaluate these recommendations by analyzing line transect counts and harvest data from six areas forming three open/closed pairs in a region of state managed willow ptarmigan harvest. We developed three sets of Bayesian hierarchical models, one static distance model, and two dynamics models. One mechanistic hazard model and a Gompertz phenomenological model. Adult and juvenile density showed pronounced year-to-year variation that was largely synchronous across all six sites regardless of hunting status. The harvest effort parameter shows a striking difference between the two models. In the Hazard model, is positive, and excludes zero with near certainty, but in the Gompertz model, the parameter is highly uncertain. However, the two models do not contradict each other but answer complementary questions with different sensitivity to the harvest signal, harvest mortality is additive at the individual level, but this additive mortality is masked at the level of population abundance. The demographic cost of harvest is therefore real and quantifiable through the survival chain, but bounded in the long run by the stabilizing dynamics. A fixed limit anchored to monitored effort and bag is not a crude substitute for adaptive management but the appropriate design under the information commonly at hand. It will be a precautionary instrument grounded in the one relationship this study establishes firmly, the translation of hunter effort into harvest mortality.

Citizen science data are increasingly used to infer biodiversity change, but causal claims based on such data are credible only if sampling effort and its temporal shifts are explicitly modeled. Zhang et al. (1) used citizen science data to conclude that greater photovoltaic policy stringency, measured using the photovoltaic policy stringency index (PSI), reduced county-level bird diversity in China. We reproduced their fixed effects and instrumental variable estimates. However, the observed Shannon diversity derived from pooled citizen science records reflects both bird communities and sampling effort, which the authors' controls do not adequately capture. Accounting for observer count changed the reported statistically significant 2.10% decline in Shannon index to a nonsignificant 0.58% increase (P = 0.288) per one-standard-deviation increase in PSI, and rendered the instrumental variable estimate statistically indistinguishable from zero (P = 0.912). Yet observer count is only one of many sources of sampling bias. PSI was also associated with multiple dimensions of sampling effort, consistent with sampling effort acting as a potential mediator in the PSI-diversity chain. The sampling domain also shifted markedly from 2014 to 2023: recorded county-months increased almost 24-fold, median observer count rose from one to three, and zero-duration records declined from 57.2% to 0.17%. Without adequate adjustment, these shifts confound estimates of temporal change in observed bird diversity. Beyond its inadequate treatment of sampling effort, the original study also misinterpreted its statistical results. Although the reported R{superscript 2} values are high, they are dominated by county and year-month fixed effects, with PSI contributing a partial R{superscript 2} of only 0.048% on observed Shannon index. The PSI-photovoltaic-area correlation is also weak (r = 0.0414) and vanishes after accounting for fixed effects (P = 0.977). Furthermore, the released bird observation data contain many erroneous outliers, raising significant concerns about insufficiently rigorous data preprocessing and quality control. These results show that the released data cannot properly distinguish ecological change from sampling effort change. Robust inference from citizen science data requires checklist-level effort metadata, explicit correction for spatiotemporal sampling shifts, and close collaboration among researchers with complementary methodological and ecological expertise.

Protected areas are vital to the recovery of endangered species. Of the 24 remaining endemic passerines in Hawaii, 16 species are endangered or critically endangered. Yet protected areas in the archipelago are changing as a result of climate change and biological invasions. For example, the non-native southern house mosquito (Culex quinquefasciatus), the primary vector of avian malaria (Plasmodium relictum), has been encroaching upward as higher elevations warm. How the ranges of endemic birds have also shifted their range upward in the Ka[u] Rainforest, the largest native forest on the Island of Hawaii, is not well understood. We used hierarchical distance sampling to characterize how population density has changed from 2002 to 2024 for eight endemic bird species in the Ka[u] Rainforest. For five species, the most parsimonious model included an interaction between year and a quadratic elevation effect. Species that were most common at lower elevations in 2002, e.g., Apapane (Himatione sanguinea), tended to be most common at mid-elevations by 2024. Species that were already most common at higher elevations, such as Iiwi (Drepanis coccinea) and Hawaii [A]kepa (Loxops coccineus), tended to decline in density. For example, Iiwi density at 1,530 m declined from 3.31 birds per ha (95% confidence interval [CI]: 2.67-4.11) to 1.34 birds per ha (95% CI: 1.05-1.71), and Hawaii [A]kepa were completely extirpated from elevations below 1,530 m by 2024. Our results demonstrate how the elevational ranges of endemic species have shifted in response to climate change, biological invasions, and habitat degradation. Translating these results into conservation measures may require a more thorough investigation of the causal mechanisms of these range shifts with finer scale habitat data, under the same hierarchical modeling framework.

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.

Conserving migratory birds effectively requires full annual cycle strategies that identify where on-the-ground efforts can have the greatest impact. Here, we present a hemispheric spatial framework to identify priority areas for 112 migratory bird species across the Americas. Building on full annual cycle prioritizations, we defined finer-scale spatial planning units that reflect differences in migratory and congregational behaviors between shorebirds and landbirds. We compiled population data for each planning unit and focal species and applied conservation planning tools to design area-efficient portfolios of sites and landscapes that secure 10% of each species population within the Americas flyways. The resulting minimum area portfolios include 175 shorebird sites and 80 landbird landscapes optimized to meet the species-specific 10% representation targets across breeding, non-breeding, and passage seasons. We also identified a broader set of complementary solutions, ranked by an importance score, to provide decision-makers with flexible options for strategic resource allocation. This framework provides the scientific foundation for the Americas Flyways Initiative (AFI), which aims to catalyze investment in nature-based solutions and bird-friendly infrastructure to enhance the conservation of migratory birds and strengthen the resilience of the Americas flyways by 2050.

Urbanization is reshaping freshwater ecosystems, with well-documented effects across gradients of land-use change, hydrologic alteration, and habitat degradation. However, how biodiversity is organized among neighboring urban aquatic habitats that differ in hydrologic connectivity, disturbance transmission, residence time, management history, and opportunities for species movement is often less clear. This creates a challenge for interpreting urban fish communities at local scales as species occurrence may reflect both contemporary habitat filtering and historical contingencies including native persistence, interbasin transfer, stocking, and nonindigenous introductions. Here we use eDNA detections, historical records, phylogenetic information, and species trait data to investigate the fish assemblages of the Charlotte metropolitan region. We detect a highly mixed fauna that also depicts a strong signature of structured biodiversity profiles across taxonomic, phylogenetic, functional, and life-history dimensions between habitat types. In particular, bounded habitats contained assemblages with larger-bodied species that are fecund and faster to reproduce relative to free-flowing habitats. Species-level occurrence models did not support a simple trait-by-habitat rule. Instead our results demonstrate that urban aquatic habitats can sort historically mixed regional species pools into predictable assemblage-level life-history profiles while simultaneously retaining signatures of evolutionary and historical biogeographic contingency.

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.

Evidence is accumulating that global change is altering species distributions. Yet, detailed knowledge is missing about the relative and joint contribution of different drivers to observed species responses. Here, we implemented an impact attribution framework based on counterfactual simulations to assess the impact of climate and land use change on occupancy dynamics of North American breeding birds. We used a Bayesian framework to fit process-explicit dynamic occupancy models to long-term survey data for 159 species from 1995 to 2019, and quantified predictive performance using spatial and temporal cross-validation. We then assessed the relative importance and effect direction of climate and land use change while accounting for model predictive accuracy. Results indicate that climate change negatively affected 90 % of the species and land use change negatively impacted 96 %. Climate change emerged as more important than land use change for driving changes in occupancy across species. Remarkably, the effects of both drivers were mostly antagonistic rather than acting additively or synergistically. Climate was the most important driver for bird communities in the western USA, while land use change dominated in the southeast, and combined climate and land use change in the northeast. Our analysis demonstrates that recent changes in North American bird distributions are shaped by multiple global change drivers acting in concert. The effect of recent climate and land use change were mostly antagonistic, and thus trends in bird occupancy dynamics could not be understood by studying the impact of those drivers in isolation. By disentangling the effects of climate and land use change on biodiversity trends, impact attribution approaches can improve our understanding of global change impacts and can support conservation planning and more accurate and realistic projections of biodiversity response to global change.

Long-lived plants facing anthropogenic disturbance often exhibit recruitment failure despite persistent reproductive adults, generating extinction debt masked by longevity. However, whether adult presence reliably reflects environmental suitability for recruitment remains unclear. Here, we examine ontogenetic niche differentiation and its consequences for recruitment in Jubaea chilensis, an endangered long-lived Mediterranean palm with an aging population. We assigned individuals within the largest known population to four ontogenetic stages and characterized their environmental niches using climatic, edaphic, topographic, and vegetation variables. We then applied spatial and multivariate analyses, including Random Forest models to evaluate environmental segregation and identify predictors of seedling establishment. Age classes occupied significantly different environmental niches, with the greatest differentiation between seedlings and reproductive adults. Saplings and adult differentiation reflected mainly topographic variables at landscape scale, whereas seedling establishment was primarily predicted by microhabitat conditions (vegetation cover heterogeneity, east-facing slope orientation, and soil texture). This pattern is consistent with niche reconfiguring throughout the life cycle, suggesting that adult occurrence and recruitment suitability respond to distinct environmental conditions. Over one-fifth of sampled individuals occupied high-suitability sites without recruitment, suggesting that ontogenetic niche shifts are associated with a spatial decoupling between adult persistence and recruitment, consistent with demographic collapse independent of habitat degradation. This failure is likely mediated by insufficient effective seed dispersal, as the sole disperser (Octodon degus) preys on most seeds before dispersal. Conservation strategies based solely on adult distribution may therefore overestimate effective habitat and underestimate extinction risk in long-lived species.

Intensifying fire regimes threaten forests globally, but the risk of persistent post-fire forest loss and its potential mitigation remains poorly quantified. We analyzed millions of wildfires worldwide from 2001 to 2024 and tracked recovery in satellite-observed forest structure and ecosystem function. Post-fire persistent forest loss, indicated by modeled non-recovery to pre-fire conditions over decadal timescales, affected 57.1% of burned forest area globally since 2001, with hotspots in Pacific temperate and southern boreal forests. We then identified 'crucial fires' as events exceeding a stringent modeled-risk probability threshold for persistent structural or functional non-recovery, with fire severity strongly predicting this loss. This severity dependence revealed a management pathway, as locations with prior low-severity fire experienced lower severity in subsequent wildfires and had lower modeled probability of becoming crucial. Under a model-based counterfactual scenario, applying the estimated severity attenuation was associated with a 7.6% reduction; the top 1% of road-accessible areas accounted for 35% of this reduction. These results provide a global framework for identifying where wildfire threatens forest resistance and where targeted low-severity fire management like prescribed fire might be used to combat global forest loss.

Experimental hut trials (EHTs) are WHO-recommended for the entomological evaluation of insecticide-treated nets (ITNs), but several hut designs are in operational use, and structural differences between them may confound efficacy predictions and limit cross-site comparability. We developed a Bayesian hierarchical framework comprising a host-seeking model, which jointly estimates biting deterrence and preprandial mortality while accounting for night-to-night variation and overdispersion, and a postprandial mortality model, which expresses hut and net effects as hazard ratios through a complementary log-log link. We applied it to a comparative trial of four hut designs (East African, West African, Ifakara and Rapley) conducted at a single site in Tanzania, evaluating eight ITNs when new and after twenty washes. Posterior estimates parameterise a vectorial capacity framework to predict reductions in transmission potential. Hut design influenced baseline mosquito behaviour and all three modes of action. Relative to the Rapley reference, baseline feeding rates were substantially lower in the East African and West African huts and closer to Rapley in the Ifakara hut. Preprandial mortality was amplified in the Ifakara hut. Comparing to previous analysis provides evidence that combining mortality before and after feeding into a single endpoint does not reliably reflect impact, supporting the decomposition of entomological outcomes into separate modes of action. Expressing modes of action as mechanism-specific parameters allows the estimates to be carried directly into transmission models. For every net, the predicted reduction in vectorial capacity was greatest in the Ifakara hut and smallest in the West African and Rapley huts. The effect of hut design on predicted impact exceeded that of washing the nets twenty times. Results indicate that the hut design under which trial data were collected should be considered when forecasting population-level effect.

Many Sockeye salmon (Oncorhynchus nerka) populations have declined over recent decades, and climate change is likely to exacerbate these declines through direct and indirect ecological effects. The response to the associated environmental changes is likely to vary among life stages, populations, and regions. Quantitative estimates of climate change driven impacts that account for this variability could fill a critical gap and provide forward-looking insights into how sockeye are expected to respond to future climate-driven change across their lifecycle. To address this need we developed a hierarchical population dynamics model parameterized with juvenile, adult return and spawner abundance data from 13 sockeye salmon populations from Washington State to northern British Columbia. We used a formal causal inference framework that paired salmon abundance data with a suite of environmental covariates hypothesized to represent ecological conditions across the lifecycle. We used the model to estimate population-specific responses to each environmental driver, then combined parameter estimates with projections from down-scaled climate change models to estimate productivity responses to anticipated environmental change. We found that historical sockeye productivity was strongly associated with environmental covariates, which explained more interannual variability in return abundance than spawner abundance in most populations. However, the life stages and specific environmental covariates with the largest impacts differed among populations and regions, often displaying a latitudinal gradient. Increases in coastal ocean temperatures and mixed layer depth generally had negative effects though they varied among regions. Increased freshwater summer rearing and return migration temperatures had weaker but consistently negative effects. Under future climate conditions, projected changes in these environmental covariates are expected to result in substantial declines in productivity across most populations. Sockeye salmon display varying degrees of sensitivity to climate change across life stages, populations, and regions. Effective future management will require explicitly accounting for these life stage and population-specific responses.

1. Forest canopies harbour strong microclimatic gradients that shape plant performance, species interactions and ecosystem processes. Yet, despite renewed interest sparked by global change, forest canopies remain difficult-to-access experimental spaces. 2. With the goal to expand access to tree canopies as experimental arenas, we designed, built, and tested TreeTOP, a standardized experimental platform that opens canopy space for manipulative ecological experiments, specifically with potted plants. TreeTOP features lightweight aluminum frames placed in mature tree canopies non-invasively, allowing potted plants to be placed in three different heights, ground level, shade canopy, and sun canopy. 3. We implemented TreeTOP using two contrasting infrastructure concepts to demonstrate its applicability in both highly equipped canopy research facilities and forests without permanent canopy infrastructure. One installation relied on a canopy crane, grid power and fully automated irrigation, whereas the second was built by certified tree climbers and was equipped with an autonomous solar-powered, battery-operated irrigation system. At both sites, environmental sensor networks monitor the experiment. 4. TreeTOP successfully reproduced characteristic canopy microclimatic gradients, including increasing light availability, daytime air temperatures and thermal extremes with canopy height. Despite differing infrastructures, both implementations generated comparable microclimatic patterns, demonstrating that standardized canopy experiments are feasible in forests with or without permanent canopy access. By opening canopy space for manipulative experiments, TreeTOP provides a transferable framework for investigating plant performance, phenology, species interactions and microbiome assembly under realistic forest conditions.

Smoke from spring boreal wildfires increasingly impacts eastern North America, exposing breeding birds to hazardous air pollution that may impact reproductive outcomes. Using data collected in 2018-2025 from 70,979 monitored nests of four widespread cavity-nesting songbirds, we found strong evidence that smoke greatly delays egg laying and can extend incubation and nestling duration. We further found that while smoke is associated with increased clutch sizes, in some species smoke exposure strongly decreases hatching or fledging success. Our results demonstrate that extreme smoke can have wide-ranging impacts on breeding birds, from altering phenology to impacting fitness. While the exact mechanisms underlying these results remain elusive, the full suite of effects suggests that modifications to adult behavior under smoky conditions is the most likely cause. As fire regimes shift, birds and other wildlife are at greater risk of exposure to toxic smoke during the breeding season, which may further exacerbate the biodiversity crisis.

Biological invasions are a major driver of global change, reshaping ecosystems and threatening biodiversity worldwide. Anticipating where invaders will establish and where they will exert the strongest ecological impacts are key challenges for early detection and targeted management. Although Species Distribution Models (SDMs) are widely used to forecast biological invasions, they often provide uncertain estimates of establishment ranges and limited insight into invader performance, making it difficult to anticipate ecological impacts. Here, we address these limitations by integrating physiological information on invader performance with SDMs to identify regions of high invasion risk. Using the brown alga Rugulopteryx okamurae, one of the most prominent marine invaders in Europe, we first test alternative hypotheses of northern establishment limits: (i) a cold-survival constraint driven by winter temperatures and (ii) a growth constraint derived from the species' thermal performance. To identify the more likely scenario, we combine cold-tolerance experiments with seasonal growth comparisons between the invader and a native macroalga Dictyota dichotoma, whose established distribution allows physiological performance to be directly related to realised presence. Finally, we project seasonal growth of the invader across the predicted establishment range as a proxy for biomass accumulation and potential ecological impacts. Our results indicate that northern limit in Europe will be more likely constrained by winter survival rather than growth, extending the potential establishment range of Rugulopteryx to mid-Norway. In contrast, the highest impacts are likely to remain concentrated in southern Europe, where thermal conditions sustain high year-round growth. Overall, our approach illustrates how understanding the physiological response of invaders to their environment can improve the interpretation of SDM outputs and help identify areas at greatest risk of impact within their potential establishment range.

Polycultures have long been practiced in traditional agriculture, yet their ecology-based benefits have remained underexplored. Here, under realistic conditions, we experimentally evaluated the productivity and ecological interactions in cultivated milpa, a traditional Mesoamerican polyculture of maize, squash and beans, using a substitutive design in which total plant density was held constant while varying species composition. Specifically, we asked whether productivity gains arose through complementary or selection effects, and whether these gains were associated with changes in arthropod communities and herbivory. We additionally evaluated whether prior cultivation influenced maize performance in the following season. Milpa plots produced significantly higher total yields, more than 2.6 times those of monocultures, despite poor bean performance. In particular, squash and maize equivalent yields increased approximately threefold. We found that these improvements were mainly explained by complementary effects rather than selection effects. Arthropod communities responded in species-specific ways to crop diversity, with predator abundance tracking herbivore presence. However, no consistent patterns emerged between herbivore load, predator abundance and plant damage, suggesting that belowground plant interactions may play a more important role than top-down herbivore control in explaining complementarity effects. In the following season, maize yield increased by [~]30% in plots previously planted with squash or beans, with milpa plots showing intermediate responses. These findings demonstrate that milpa can substantially enhance productivity while generating benefits that extend into the advantages and soil into the following growing season. Overall, our results suggest that complementarity among crops is the primary driver of productivity in milpa under low-input conditions.