Population Ecology

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.

As anthropogenic threats have intensified over the past 500 years, we find ourselves in the midst of a sixth mass extinction, with continued losses of biodiversity threatening ecosystem stability. This biodiversity loss has caused species extinctions across taxa, and placed several others at high risk of functional extinction. These disturbance-driven impacts represent one of the most acute biodiversity crises facing global marine systems. Species exhibiting slow life histories characteristically have low resilience to disturbance. Here, we assess the risk of functional extinction and identify policy pathways for population recovery of the slow-living, Critically Endangered elasmobranch, the spinetail devil ray (Mobula mobular). We develop a stochastic, state-structured Integral Projection Model (IPM) parameterised with demographic data collected from fishery landings data in India, the world's largest mobulid fishery, and supplemented with data on vital rates from published literature. Using the IPM, we estimate that the population is declining at approximately 12% annually, experiencing substantial limiting pressure from fisheries overexploitation and failing to approach its biological maximum growth potential. Our results indicate that populations of M. mobular will be at high risk of functional extinction if 'business as usual' harvest scenario persists for another decade. We further show that long-term population recovery is only possible if survival increases significantly across all size classes, especially among large reproductive females, alongside a concurrent increase in fecundity. We conclude that no single policy measure is sufficient to recover population of M. mobular along the southeastern coast of India. Instead, combined protection through maximum bycatch mitigation and protection of nursery areas in no-take zones will be required for population recovery. This research demonstrates that recovery of overexploited populations often requires integrated resource management across life stages, and that the Critically Endangered M. mobular warrants urgent conservation action to avoid functional extinction.

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.

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.

AimSpecies in mountain ecosystems often experience upslope distribution shifts in response to climate change. However, elevational range dynamics exhibit substantial complexity around this general trend, with varying magnitude and direction of shifts observed among studies. We tested whether factors other than temperature, such as habitat size and land use, are also responsible for observed elevational shifts in a cold adapted species. LocationHokkaido, Japan MethodsWe resurveyed 61 historical (1963-2007) occurrence sites covering a wide elevational range (60-2,210 m) within the distribution range of the northern pika (Ochotona hyperborea). We assessed the existence of elevational shifts using quantile regression and the relative importance of temperature, habitat size, and land use on the shift using occupancy analysis. ResultsWe detected presence of the northern pika at 41 sites, suggesting extirpations at 20 sites (32.8%) across a wide elevational range of 60-1,550 m. The concentration of extirpation sites at low to mid elevations resulted in a significant upslope shift of the distribution centroid, although the shift was nonsignificant at lower and upper portions of the range. The occupancy analysis revealed a negative effect of long-term mean of summer maximum temperature and a stronger positive effect of habitat size. ConclusionsThis highlights the susceptibility of the northern pika to heat stress and the importance of larger habitats and thus habitat heterogeneity for persistence of local populations. Given the possibility that the observed shift represents a precursor of elevational contraction, continuous monitoring of the local populations is highly needed to evaluate their long-term viability.

After introduction, many non-native marine species are dispersed planktonically. Secondary spread within the non-native range has been shown to prevent the establishment of the introduced species if the advection of larvae prevents sufficient return of larvae to maintain the population in the face of competition with native species. However, those studies have largely neglected the effects of spatial variation in alongshore larval transport. We examine the introduction of a novel species with planktonic dispersal into a more realistic coastal environment which includes spatial variation in larval transport estimated from the Mercator Ocean 1/12th degree global circulation model. The introduction may either be from a distant habitat, or through range expansion. We find that there are locations in the global coastal ocean where introduced species are more likely to persist because of spatial variation of coastal currents. These include regions where alongshore larval transport diverges, such as estuaries. The location where a non-native species is introduced may not be where it flourishes - it cannot be assumed that the region where invading species are first noticed to be abundant is the region where it was introduced. We extend closed-population theory to open coastal systems to estimate persistence as a function of local circulation, habitat extent, and the competitive advantage of the introduced species. Software is provided which allows the estimations of regions where introduced species are more likely to persist and flourish as a function of larval depth behavior, planktonic duration and release timing.

The ability to model the complex and uncertain population dynamics of endangered species has improved dramatically in recent decades. However, approaches to identify optimal decisions often require a simplified representation of population dynamics. This leads to a conundrum where managers may be unsure about the output of dynamic decision models because they rely on simplified assumptions of the underlying population dynamics. Here, by pairing integrated population models (IPM) that synthesize diverse ecological data with deep reinforcement learning (DRL) capable of optimizing decisions with high-dimensional uncertainty, we introduce a framework that delivers data-driven and ecologically detailed adaptive management strategies. We demonstrate its utility through application to the supplementation program for the endangered Rio Grande silvery minnow. Using our IPM-DRL framework, we developed an adaptive decision model that selects production and distribution decisions of the supplementation program in response to the observed demographic, hydrological, and genetic environment. The decision model outperformed all heuristic approaches in the simulation across management objectives that weighed persistence and effective population size-related genetic impact differently. For example, the currently deployed supplementation strategy performed 5.3% worse than the decision model under the persistence-focused objective scoring and 185% worse under the genetics-focused one. Analysis of the models decisions in relation to demographic and environmental covariates revealed that minimum sub-population size and total population size were primary drivers of the models decisions. The results demonstrate that the IPM-DRL framework offers a high-performing and interpretable decision-support tool for managing endangered species. SignificanceConservation problems, like imperiled species management, are often challenging because the system dynamics are complex and uncertain. We demonstrate how combining an integrated population model that infers key demographic processes from noisy ecological data with a deep reinforcement learning framework that optimizes management actions addresses these challenges by generating high-performing supplementation strategies for a conservation-dependent species. Our approach embeds two decades of monitoring data within a multi-objective decision-making environment that accounts for ecological uncertainty. The result is a generalizable framework that links ecological inference directly to actionable policy outcomes, enabling scientists and managers to move beyond describing system states and processes toward identifying optimal management actions.

Reliable population estimates are essential for wildlife management, yet monitoring schemes often do not match the administrative scale at which decisions are made. We illustrate this challenge using the Eurasian lynx in the canton of Valais, Switzerland, where official state monitoring is fragmented across three reference areas surveyed in different years. We analyzed three winters (2023-2026) of independent, canton-wide camera trap data, recording 899 independent lynx captures (27, 31 and 34 adults per winter). Lynx distribution and reproduction concentrated in the Northwest and connected to the thriving Pre-alpine populations. Density modelling for 2025/2026 estimated 37 independent lynx (95% CI: 26-52) on the whole cantonal territory, corresponding to a density of 1.09 (0.77-1.56) individuals per 100 km2. These estimates are substantially below the figures improperly extrapolated from a cross-cantonal reference area and conveyed by political authorities. Future lynx management decisions should be rooted in scientifically sound, scale-relevant information.

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.

Khaya senegalensis (Desr.) A. Juss., the West African savanna mahogany, is listed as Vulnerable on the IUCN Red List due to prolonged commercial and medicinal overexploitation, compounded by failing natural regeneration amid growing deforestation and climate change. Restoration strategies generally rest on the implicit assumption that rigorous selection of seed trees based on their size improves offspring quality. Yet this assumption has never been confronted with the competing hypothesis of a determinism dominated by the planting site, using statistical approaches of adequate power. This study tests the relative contribution of seed-tree dendrometric characteristics (diameter, height) and planting site to germination and juvenile growth (6-24 months) of K. senegalensis, using six complementary analytical approaches: continuous regression, linear mixed models with site x seed-tree interaction, seed-mass mediation analysis, non-linear growth-trajectory modelling, between-site phenotypic plasticity indices, and multi-predictor allometric equations, across two contrasting bioclimatic sites in Cote dIvoire (Korhogo: Sudanian savanna, and Daloa: humid forest) and six seed-tree categories. Converging across all these approaches, the results show that the planting site exerts a decisive influence on germination (71.1% at Korhogo versus 63.9% at Daloa; {chi}{superscript 2} = 6.09; p = 0.014) and on the entire growth trajectory (p < 0.001), whereas no seed-tree characteristic affects offspring performance, whether in continuous regression (p > 0.37), mixed models with interaction (p > 0.29), or through a seed-mass mediation pathway (Sobel test, p = 0.46). An exponential growth model fits better than linear or power-law models ({Delta}AIC = 13.6-14.7 depending on site), and multi-predictor allometric equations (diameter and height) explain 97.4% of the variance in total biomass, versus 94.8% for the single-predictor model. These convergent results indicate that, contrary to the widespread practice of selecting seed trees on size criteria, it is the choice of planting site that truly determines the success of restoring this vulnerable species. A conclusion calling for a reorientation of priorities in reforestation and agroforestry programmes across West Africa.

Gray fox (Urocyon cinereoargenteus) populations in the Midwestern USA have suffered precipitous declines in recent decades, yet they are relatively understudied. However, understanding survival and cause-specific mortality is vital for declining populations and the limited existing survival studies have been performed outside of the Midwest. We equipped 13 gray foxes in southern Illinois with GPS radio collars to investigate their survival and cause-specific mortality. We calculated the Kaplan-Meier 6- and 12-month survival rates to be 0.79 (95% CI: 0.57-1.0) and 0.53 (95% CI: 0.27-1.0), respectively. We recorded 4 mortalities: 1 disease, 1 gunshot, and 2 unknown causes. While our study has a small sample size, it contributes key information on a data-deficient mesocarnivore suffering from a population decline driven by undefined causes. We recommend further research into the survival and mortality of this elusive mesocarnivore.

Across High Asia, snow leopards Panthera uncia share habitats with pastoralists and consume both wild and domestic herbivores. Increasing wild prey is vital for predator conservation, but its effect on livestock depredation is unclear: it could decrease depredation through apparent facilitation or increase it through apparent competition. We investigated this association using a 13-year time series dataset from Upper Spiti Landscape in the Indian Trans-Himalaya. Long-term data on elusive carnivores are rare, making this time series especially valuable for testing predator-mediated interactions. We found higher wild ungulate density was accompanied by significantly greater depredation of free-ranging livestock, and this association remained positive after bootstrapping to account for uncertainty in density estimates. These results suggest snow leopard-mediated apparent competition between wild and domestic herbivores. We recommend conservation efforts that increase wild prey must also integrate effective livestock protection and support strategies to enhance coexistence between predators, prey and pastoralists.

Social wasps (family: Vespidae) are increasingly concerning invaders and have been subject to increased detections and a growing number of invasive populations in the last few decades. As established invasive populations are challenging to eradicate, preventing introductions and prioritizing early interventions are the most cost-effective management solutions to mitigate these effects. A current challenge to this approach is that species distribution data is limited for many social wasp species, hindering our ability to accurately predict novel habitats with high suitability. To address this gap, we used MAXENT to create species distribution models (SDM) for 299 species of social vespid. We identified existing invasive populations of social wasps and incorporated their current invasive ranges to improve the transferability of our models in predicting habitat suitability in new environments. Current range sizes and habitat suitability varied widely among species and genera. We identified new species of high invasive concern, particularly in the genus Vespa. We also identified previously unrecognized regions that may be at high risk of future invasion primarily in Central Africa and the Indo-Australian Archipelago. Combining current and suitable ranges, we calculated an "Invasion Risk Score" to compare the relative likelihood of each species establishing a new invasive population based upon habitat suitability. To assess invasion risk in the future, we projected habitat suitability under four Shared Socioeconomic Pathway (SSP) climate change scenarios. Under all scenarios, species faced significant changes in habitat suitability for current native ranges. Habitat suitability generally shrank and shifted towards the poles, leaving equatorial species at highest risk of habitat loss. Notably, Vespa was the only genus whose suitable habitat expanded under these climate scenarios. Our framework demonstrates how multi-species SDMs can be applied to risk management of invasive populations.

Hibernation is a critical phase in the annual cycle of boreal bats, especially near the northern limit of their range where winter conditions are severe and suitable hibernacula are limited. In Finland, anthropogenic structures, such as abandoned bunkers, commonly serve as hibernacula for bats. In this research, we investigate how the size characteristics of bunkers affect species composition and abundance of hibernating bats. The length of the bunker was the best predictor of the presence and abundance of bats. The longest sites ([~]25-26 m) had the highest probability to host all studied species, or group of species of bats, specifically Eptesicus nilssonii, Plecotus auritus, and Myotis bats. Eptesicus nilssonii appeared to be a generalist species, utilizing a variety of bunkers regardless of their length or temperature regime. Still, its number per bunker was relatively low. The highest numbers of Myotis bats were observed in the longest bunkers with stable temperature. The number of P. auritus was positively related to the bunker length; however, it was rare in the studied hibernacula. Different species showed different patterns in hibernacula space usage. Eptesicus nilssonii hibernated in any part of the bunker, while Myotis bats used the most remote from the entrances areas in small sites, and occupied the whole area of the longest bunkers.

Population dynamics and their component vital rates may be driven by weather, climate teleconnections between sea and air (e.g. ENSO), or biotic interactions. These drivers operate directly or indirectly and on different temporal scales. We used a Bayesian structural equation model to characterize effects among weather, climate, and incidental intraguild predation (IGP) on the butterfly Euphydryas gillettii's vital rate of pre-diapause survival, using an 18 year dataset. IGP was a major determinant of pre-diapause survival, along with direct and indirect effects of weather and spring climate teleconnections. The direction of climate effects was reversed when mediated through IGP. Our analysis illustrates the need for sequential hypotheses to capture the cascading effects of abiotic factors via biotic interactions. Using sequential hypotheses addresses the debate on weather -- climate teleconnection roles by disentangling their contributions from one another. Finally, vital rates must be decomposed to component rates in order to detect their drivers.

Despite the impacts of within-host disease dynamics on disease outcomes in individual hosts and disease spread among-hosts, generic models of within-host population dynamics have received far less attention than their among-host counterparts. While a number of models have been proposed to explore theoretical eco-evolutionary dynamics, they have yet to be evaluated for estimability, raising questions about their ability to provide reliable inference when confronted with data. We evaluated the estimability of two generic within-host population dynamics models by assessing: (1) parameter estimation, our ability to recover correct values of model parameters from data, (2) the consequences of mis-assigning the underlying mechanistic model on parameter estimation, and (3) the reproduction of qualitative dynamics, or, our ability to use parameter estimates to reproduce observed dynamical behaviours. In some cases, fitting a mis-matched mechanistic model to time series data produced reasonable parameter estimates that were able to reproduce system dynamics, and that when provided the data-generating model, parameter uncertainty can produce substantial behavioural uncertainty. Our findings highlight the impacts of structural, parametric, and behavioural uncertainty on inference, and demonstrate the value of improving system-specific knowledge to prevent the use of incorrect functional forms and of measuring consequential parameters to improve estimability.

The performance of any natural population in variable environments depends on contemporaneous changes in its vital rates (e.g., survival, reproduction) as well as legacies carried by its population structure. Yet whether the relative contribution of these two pathways can be predicted from life history remains unknown. Here, we use stochastic simulations of 1,986 matrix population models from 137 species to quantify the contribution of transient dynamics to variation in population growth rate, and test its associations with key life history traits. Longer generation times were associated with reductions in transient contributions, contrary to theoretical expectations. Greater stage-specific survival heterogeneities were associated with increases in transient contributions, whereas greater iteroparity was associated with decreases in plants but increases in animals. These associations were robust to body size, phylogenetic relationships, and vital-rate variability. Life history traits therefore provide a strong predictor for when population structure shapes population responses to environmental variability.

For organisms with biparental care, successful reproduction hinges on coordination between partners. Seabirds face an extreme coordination challenge because parents must schedule nest attendance on land with long-distance foraging trips at sea. We present a computational model of incubation schedules for a vulnerable seabird, the Leachs Storm-Petrel (Hydrobates leucorhous). Using only simple energetic rules and parameters, the model recapitulates natural incubation rhythms, exposes a tradeoff between parent energy and egg attendance, and predicts severe reproductive failure in harsh environments. Incubation primarily fails through "schedule breakdown" -- a single point in the season when both parents spend too long foraging and the egg dies from cold. The resilience of the developing offspring to neglect is thus a fundamental adaptation to the uncertainties of biparental care. These results raise new alarms about the indirect causes of reproductive failure in sensitive marine species and provide theoretical foundations for the evolutionary ecology of scheduling behaviors.

Understanding the spatial patterns of biodiversity and their environmental determinants is fundamental to ecology and conservation, particularly in mountainous transitional zones where species assemblages can shift rapidly. Amphibians, as highly sensitive organisms, are excellent indicators of environmental change, yet quantitative assessments of their diversity in the Huangshan Mountains-a biodiversity hotspot at the junction of the Palaearctic and Oriental realms in southern Anhui, China-remain limited. We conducted systematic line-transect surveys across 200 grids (5 km x 5 km) during the spring and autumn of 2023 and 2024, recording a total of 10,342 individuals belonging to 23 species, 20 genera, 9 families, and 2 orders. Three species (Fejervarya multistriata, Microhyla fissipes, and Bufo gargarizans) were identified as dominant, and two nationally protected species (Hoplobatrachus chinensis and Andrias davidianus) were detected. Inter-annual alpha diversity did not differ significantly, but pronounced seasonal variation was observed, with spring supporting higher Shannon-Wiener and Pielou evenness than autumn in both years. Using generalized additive models and model averaging, we found that annual precipitation and the normalized difference vegetation index (NDVI) were consistently the strongest positive predictors of Shannon-Wiener diversity, Simpson dominance, and species richness, while species richness also declined significantly with increasing human footprint. Total beta diversity (Soerensen dissimilarity) was very high (0.981) and overwhelmingly driven by species turnover (97.86%) rather than nestedness. Partial Mantel tests and distance-based redundancy analysis further revealed that environmental distances-particularly annual precipitation-significantly shaped overall beta diversity and its turnover component after accounting for geographic distance. These results highlight the predominant role of climatic and vegetation gradients in structuring amphibian assemblages in this subtropical mountainous region, providing baseline data to inform local conservation strategies.

Flow regulation for hydropower production affects stream ecosystems through decreased connectivity and changed timing and magnitude of flows. Hydropeaking, a form of regulation in which infrequent large peak flows are replaced with frequent small peaks, increases riparian erosion and causes water and drought stress for riparian vegetation. Hydropeaking is likely to affect soil seed bank (SSB) formation and composition, while SSBs are important sources of self-restoration should a systems flow regulation be relaxed. We tested how hydropeaking intensity affects the size and composition of SSBs, including the functionally important group of large graminoids, and by calculating Ellenberg values for Moisture, Light and Soil disturbance. SSB samples were taken at 15 riparian zones across central and northern Sweden. Each site was regulated, but sites differed in their hydropeaking intensities. SSBs were subjected to a seedling emergence experiment, from which over 700 seedlings from 53 taxa emerged. We found that hydropeaking intensity affects the composition of soil seed banks on multiple levels. Seedling density was negatively correlated with hydropeaking intensity at the sites where samples were taken. SSB richness varied (two to eighteen species per site) and was not affected by hydropeaking intensity. The proportion of large graminoids in the seed bank showed a near-significant decrease with increasing hydropeaking intensity, and community-weighted means for Moisture, Light and Soil disturbance increased (non-significantly) with increasing intensity. Our results suggest that riparian SSBs, should flow regulation be relaxed or ceased, are not sufficient for self-restoration of functional riparian vegetation. Seeds of large graminoids and species that are tolerant to drought in the germination stage are less present in riparian SSBs of heavily-regulated streams. Supply of seeds of these groups, or even planting, may need to be considered when changes in flow management are implemented. HighlightsO_LIHydropeaking negatively affects riparian soil seed banks (SSBs) in Sweden C_LIO_LISSB size slightly decreases with hydropeaking intensity, but richness does not change C_LIO_LIThe proportion of large graminoid seeds in SSBs decreases with hydropeaking intensity C_LIO_LIRiparian SSBs from less-impacted sites have most potential for self-restoration C_LI