Ecosphere

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

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.

Diverse life history strategies allow species to spread risk across a mosaic of habitat conditions. In Chinook Salmon (Oncorhynchus tshawytscha), particularly in the Central Valley of California, this is expressed through varied adult run timings and juvenile outmigration strategies. Anthropogenic impacts, particularly dams, disrupt these fundamental life stage transitions, often forcing managed populations to adapt to homogenized, less stochastic hydrologic regimes. This is exemplified in the Sacramento River, where the conservation of endangered Sacramento River winter run Chinook salmon requires balancing complex water operations with the ecological needs of a population confined to a short stretch of suitable habitat downstream of Shasta Reservoir. Using a 23 year dataset (2002 to 2024), we evaluated the combined effects of flow, temperature, and spawner abundance on juvenile production and life history expression in this habitat. We found that flow and spawner abundance best predicted juvenile abundance at Red Bluff Diversion Dam while temperature had considerably less support. The proportion of juveniles migrating as smolts exhibited significant density dependence that was negatively correlated to both female spawner abundance and peak flows. These results suggest focusing on temperature management alone may be insufficient. Effective management strategies should consider flow variability and habitat restoration to facilitate varying migration strategies and expand upstream rearing capacity. By addressing these physical and hydrologic constraints, managers can better support the full suite of life history strategies necessary for the resilience of winter run Chinook salmon.

Once central challenge in adopting ecosystem-based fisheries management (EBFM) is understanding and predicting the interconnected processes, feedbacks, and temporal dependencies that characterize ecosystem dynamics. Structural equation models and structural causal models (SEM and SCM) quantify interconnected relationships and evaluate causality from observational data but cannot readily accommodate the incomplete and irregularly sampled data typical of complex systems. Dynamic structural equation models (DSEM) estimate SEMs but accommodate lagged effects, missing data, and non-linear and non-stationary effects. However, there is little guidance regarding how DSEM can be used to support EBFM, particularly within governance and decision-making contexts. Here, we present three case studies that highlight distinct inferential goals for understanding ecosystem processes in the context of EBFM. First, we quantify ecosystem-level indicators to support monitoring of climate-driven ecosystem changes. Second, we examine whether hypothesized direct and indirect ecosystem linkages improve predictions of recruitment. Finally, we compare support for hypotheses of causal drivers of fish productivity. To provide practical advice, we synthesize lessons learned into a workflow to for others navigating DSEM. We suggest that the first step is identifying the inferential objective, which establishes the foundation for the remainder of the workflow, guiding the development of graphical models, model specification, and the selection of statistical and scientific validation steps (e.g., testing conditional independencies) needed to evaluate hypothesized causal relationships. By integrating observational data, expert knowledge, and mechanistic hypotheses within a unified framework, DSEM is a powerful tool for advancing EBFM, and more broadly, understanding the processes that govern complex ecosystems.

Identifying the characteristics of climate refugia for multiple species is becoming increasingly urgent. We used repeated, fish community surveys in streams of the northern Great Plains, USA to characterize occupancy change between historical and contemporary surveys. We then identified variables correlated with community change. Across all sites, average community turnover was 56%, native species persistence was 60%, and contemporary surveys consisted of 37% colonizing species (native or introduced). Community turnover was driven about equally by species loss and colonization. Individual species showed highly variable trends in occupancy with native plains minnow (Hybognathus placitus), northern redbelly dace (Chrosomus eos), longnose sucker (Catostomus catostomus), and flathead chub (Platygobio gracilis), declining substantially, and introduced smallmouth bass (Micropterus dolomieu) and native channel catfish (Ictalurus punctatus) increased considerably. While factors associated with individual species persistence and colonization varied, warm temperatures and agriculture were most associated with community change. Importantly, cool water temperatures appear to buffer fish communities from turnover at sites moderately impacted by agriculture. Protection of cool-water refugia will thus be critical for persistence of fishes in agricultural regions.

Streambank erosion degrades both terrestrial and aquatic ecosystems, and riparian buffers are among the most widely used tools to control it. Yet most of what is known about how riparian vegetation controls erosion comes from one or two-species systems, which overlook the diversity of riparian communities and species interactions (competition and facilitation) that may shape the root systems that bind soil. We used a streambank mesocosm experiment to test whether plant species richness alters root traits, and whether root traits and species interactions reduce erosion. We established 85 mesocosms ranging from unvegetated controls to six-species polycultures, measured root biomass, length, volume, and diameter, quantified species interactions with relative yield totals (RYT), and measured erosion rate with a jet erosion test. Vegetated mesocosms eroded significantly less than unvegetated controls (t = 4.05, p = 0.023). Richness did not affect most root traits, although mean root diameter decreased as richness increased ({beta} = -0.0225, p = 0.047). RYT ranged from competition (RYT < 1) to facilitation (RYT >1), yet neither interactions nor any root trait was directly associated with erosion rate. However, RYT was negatively associated with soil moisture ({beta} = -0.196, p = 0.010). Piecewise structural equation models showed that erosion was best explained by a pathway linking species presence, root length, and soil moisture (AIC = 39.27; Fisher's C = 11.27, df = 12, p = 0.506). Panicum virgatum increased root length, whereas Lolium multiflorum and Echinochloa crus-galli reduced it; longer roots were associated with drier soil (standardized {beta} = -0.31, p = 0.005), and wetter soils eroded more slowly (standardized {beta} = -0.39, p < 0.001). Which species were present mattered more than how many, and plants were linked to erosion through soil moisture rather than root traits alone. Species selection for riparian buffers may need to consider effects on soil moisture as well as rooting extent, particularly as droughts followed by intense storms become more common under a changing climate.

Flood-control pumpstations compromise connectivity and survival for migratory fish globally, yet field evaluations of modern "fish-friendly" designs remain scarce. We evaluated out-migration survival and behavior of yearling coho salmon (Oncorhynchus kisutch) entrained through an open-Archimedes screw station (Hammersley) and a conventional radial station (Barrowtown) in the lower Fraser River floodplain, British Columbia. Using acoustic telemetry over two migration seasons (2024-2025), we tracked smolts across an 84-km corridor to New Westminster and modeled apparent survival using a Cormack-Jolly-Seber framework. Baseline natural mortality in downstream controls averaged 60% across years (cumulative survival: ~40%). Entrainment through the conventional radial station caused 87.5% mortality. The open-Archimedes station conferred an improvement over the conventional facility but still induced 11.5% mortality. Notably, pump-induced losses at the Archimedes pump were predominantly latent: while acute survival through immediate tailrace receivers was high (95-98%), survival deficits diverged downstream in the mainstem Fraser River. Entrainment also prolonged out-migration, causing up to a 10-day delay in 2024 driven by forebay holding and depressed downstream transit speeds. Our findings demonstrate that while open-Archimedes screws improve survival relative to legacy radial impellers, they still impose substantial latent mortality. In heavily altered basins where baseline smolt mortality is already high, additive losses from drainage infrastructure may exacerbate survival bottlenecks.

1. Atlantic salmon (Salmo salar) are an anadromous fish with a broad distribution from eastern North America to western Europe, with ecological, economic, and cultural significance. Despite their expansive range, wild populations across the North Atlantic have experienced decline. Survival to reproductive age is a management concern, with a focus on identifying factors affecting the juvenile freshwater life stage. Specifically, research is needed to identify potential bottlenecks limiting freshwater productivity. 2. We addressed this research gap with a case study on the Exploits River, Newfoundland - a watershed that receives one of the largest anadromous Atlantic salmon returns in North America. We aimed to identify biotic, chemical, and physical predictors of food resources for juvenile salmon (i.e., invertebrates) and food resources for invertebrates (i.e., periphyton). To test our hypotheses, we collected data on a suite of biotic (e.g., invertebrates and periphyton), chemical (e.g., total dissolved N), and physical (e.g., wetted width) variables at 42 sites within and around this watershed. 3. We observed evidence for relationships between invertebrate biomass and biotic and temporal variables. Specifically, invertebrate biomass was higher at sites with high periphyton biomass that were sampled later in the season. In addition, we observed that periphyton biomass was related to biotic, chemical, and physical variables. Here, we present evidence for bottom-up control, with increased periphyton biomass supporting increased invertebrate biomass. 4. We expect knock-on effects where increased invertebrate biomass results in increased juvenile Atlantic salmon biomass. Our large sample size revealed some predictors of invertebrate biomass and periphyton biomass. However, we found no evidence of correlation between invertebrate biomass and chemical or physical variables. The low productivity of our maritime boreal forest system could be an outlier in expected biotic, chemical, and physical relationships in streams. 5. Our findings provide an important step forward in furthering boreal stream ecology, producing novel invertebrate and periphyton knowledge for watershed managers.

While plant communities that exist at the edges of agricultural fields are typically composed of 'weedy' species, they provide essential resources for insect pollinators and other wildlife. However, little is known about how sublethal exposures to herbicides via drift (off-target chemical movement by air) affects the fitness of weedy plant species across varying agro-ecological environments. If weed species vary in sensitivity to herbicide drift, then this could result in plant community shifts in favor of more tolerant species. Consequently, these changes in species composition could alter resource availability in agroecosystems. Here, we replicated a common garden experiment in three US states where agriculture is a major form of land use (Michigan, Pennsylvania, and Tennessee). We exposed nine weed species to a sublethal, drift-level rate of the herbicide dicamba and examined plant fitness. We found that fitness in the presence of dicamba drift depended on both the weed species and the environmental context. For some species, dicamba drift significantly reduced fitness. For others, it had no effect, indicating greater tolerance to the herbicide. However, more variation in tolerance to dicamba drift among species was observed in Michigan compared to Pennsylvania or Tennessee, a result that was partially explained by the severity of damage from insect herbivory that occurred at each location. In a follow-up study, we explored the relationships between plant developmental traits and fitness to determine the functional pathways that underlie tolerance to dicamba drift using structural equation modeling. This approach revealed that weedy plants that are better able to buffer the effects of dicamba drift on short-term growth are then better equipped to minimize effects on flower production and ultimately fitness (seed set). Overall, our work advances knowledge about how wild plant populations in different contexts are responding to unintentional, yet increasingly common occurrences of anthropogenic stress in the form of off-target herbicide exposures.

Researcher disturbance can alter the behavior, survival, and breeding success of wildlife, with effects that are especially well-documented in waterbirds. Anecdotal reports suggest that disturbance can even cause cavity-nesting species to alter the structure of their nests. We used a long-term study of a burrowing seabird, the Leach's Storm-Petrel (Hydrobates leucorhous), to ask whether storm-petrels renovate existing burrows and whether such renovation is related to a history of researcher disturbance. Our study was conducted at the Bowdoin Scientific Station on Kent Island, New Brunswick, Canada, where in 2024 we measured the burrow architecture of 363 burrows, including length and structure for occupied and unoccupied burrows both inside and outside a long-term study site with consistent research activity. Of these, 150 burrows had been measured in 2006, allowing for direct longitudinal comparison of burrow architecture. Nearly all burrows changed in length over the 18-year study period (mean absolute change = 20.8 cm +- 18.2 SD). A linear model revealed two contrasting processes of burrow length change: more frequently occupied burrows grew longer, whereas initially longer burrows shortened towards mean burrow length (~50 cm) through collapse. Occupied burrows inside the long-term study site were on average 34% longer and significantly more complex than burrows adjacent to the site, suggesting that researcher disturbance directly or indirectly reshapes burrows. Overall, these results show that storm-petrel burrows are shaped by cycles of renovation and subsequent collapse that may be exacerbated by human disturbance. Given ongoing population declines in storm-petrels and other cavity-nesting seabirds, this study emphasizes the need to balance scientific research with minimizing disturbance, particularly in long-term studies.

Introduction: Despite decades of investment, stream restoration often fails to recover diverse benthic macroinvertebrate communities, as restored reaches tend to remain dominated by pollution-tolerant taxa. This shortfall in recovery is commonly attributed to either poor habitat quality or dispersal limitation of aquatic macroinvertebrate taxa, yet these hypotheses are rarely tested directly. Objectives: We conducted a manipulative field experiment in the eastern Piedmont region (Maryland, USA) within the Chesapeake Bay Watershed to evaluate whether restored streams can support pollution-sensitive taxa when dispersal barriers are removed. Methods: We translocated whole macroinvertebrate communities from three nearby reference streams into three restored streams using standardized habitat substrates and quantified macroinvertebrate survival after 28 days. We also assessed how effective leaf vs rock substrates were for accumulating diverse and abundant macroinvertebrate communities for translocation. Results: Across all sites, 77% of translocated individuals and 16 of 22 taxa sensitive and moderately sensitive to pollution persisted under restored stream conditions, demonstrating that restored reaches can support short-term survival of pollution-sensitive taxa that typically fail to recover. Substrate comparisons revealed that leaf packs accumulated higher macroinvertebrate abundances, whereas both substrates accumulated macroinvertebrate communities with similar taxa richness, EPT richness, and Shannon Diversity. Conclusions: This work suggests that dispersal limitation, rather than unsuitable habitat, may be an underappreciated constraint limiting macroinvertebrate recovery in restored streams. These findings challenge the assumption that habitat restoration alone is sufficient for biological recovery and highlight the potential for whole-community translocations to accelerate recovery and ecological uplift as part of stream restoration practices. Implication for Practice: Our study highlights the need to consider habitat connectivity and dispersal pathways during stream restoration designs. Restoring streams to meet habitat requirements of pollution-sensitive macroinvertebrate taxa may not be sufficient for their populations to recover if these taxa are unable to reach the restored stream. In scenarios where restoring connectivity to source populations is infeasible, whole community translocations may offer a novel restoration tool to overcome dispersal barriers and accelerate biological recovery in restored streams.

Data augmentation is now a standard device across capture--recapture and occupancy analysis: adding a fixed number M of all-zero encounter histories replaces a model of unknown dimension with one of fixed dimension. Although M is often treated as a computational tuning choice, it also specifies a finite superpopulation and hence a binomial support constraint on the number of undetected individuals. In a Bayesian implementation that constraint appears as an induced prior; in a likelihood implementation it is the same finite-support assumption reached by another route. That the Bernoulli specification for the inclusion indicators induces a binomial prior on abundance is established (Schofield & Barker 2014); our concern is what that choice costs in estimated uncertainty. We develop the argument using a simple closed-population abundance estimation problem. We show that augmented occupancy and Huggins conditional-likelihood analyses give numerically identical point estimates of N once M is sufficiently large. Their uncertainty estimates, however, need not agree. We distinguish two sources of discrepancy. First, when M is small relative to the number of undetected individuals, the finite binomial ceiling truncates the likelihood or posterior and suppresses uncertainty. Second, once that ceiling no longer binds, Taylor-series (Delta-method) approximations still understate variance, because the quantity of interest is a strongly non-linear function of the estimated parameters and local linearization does not reproduce its curvature. Gauss-Hermite quadrature on the unconstrained logit scale recovers much of the shortfall and approaches the MCMC posterior benchmark, though a small residual remains that does not close as M grows, reflecting the distinction between asymptotic likelihood theory and finite-sample Bayesian inference. Neither mechanism is peculiar to abundance estimation: the first follows from the augmented representation itself, the second from any derived quantity that is a non-linear function of estimated parameters. We close with framework-specific guidance for choosing M.

Okanagan sockeye salmon have shown a strong recovery over the past three decades, but the contribution of environmental conditions and management actions to this recovery has not been determined. We developed a hierarchical Bayesian model linking spawner abundances to fry emergence observations to evaluate how flow and water temperature during adult upstream migration and incubation periods influence spawner-to-fry production. Production declined by 62% in years with earlier onset and longer duration of periods when warm river temperatures created barriers to adult migration, indicating that migration conditions can have carry-over effects on reproductive success even when spawners successfully reach the spawning grounds. Additionally, production was 46% lower when flows fell above or below the management target range designed to minimize scour and desiccation during egg incubation. In contrast, we found little support for effects of pre-spawning flows or incubation temperature on production. These findings provide quantitative evidence that current flow management is increasing freshwater spawner-to-fry production and has likely contributed to the Okanagan sockeye recovery. Effective flow management may therefore help offset climate-driven impacts that increasingly threaten this population.

Riverine and riparian food webs are connected via 'allochthonous' resource flows from neighboring ecosystems. These resources, such as terrestrial leaf litter, contribute to benthic macroinvertebrate diets, supporting higher trophic levels. While allochthony occurs in streams globally, its sensitivity to broad environmental gradients remains poorly understood. We explored the drivers of allochthony across six river basins within the contiguous United States, including climate, stream size, and flow permanence. We used Bayesian mixing models to estimate macroinvertebrate dietary proportions in four functional feeding groups. Air temperature best predicted allochthony, with consumers relying less on allochthonous resources with increasing temperature. Our models indicate that macroinvertebrate diets become primarily autochthonous at approximately 15{degrees}C mean annual air temperature, with leaf litter-consuming shredders showing a slightly higher threshold for this shift. We also found increased allochthony in smaller, non-perennial streams. These findings highlight the complexity of stream allochthony and responses to multi-scale environmental factors.

Introduction and Aim: Future climate instability creates obstacles for organisms across taxa, especially in areas that experience higher stochasticity. Wetland wading bird populations are a prime example of this scenario, as the hydrologic cycles that drive population success in these habitats depend heavily on the predictability of wet and dry periods. When fluctuations in wet and dry periods shift excessively, populations may be forced to relocate or shift migration routes. Our goal is to predict if worsening environmental conditions could drive increases in facultative migration and subsequent residency shifts Location: State of Florida, USA. Methods: We developed an individual-based movement model motivated by wading birds in southern Florida to determine if this concept of climate-driven range or residency shift is likely to occur in the future. To further interpret the outputs of this individual-based model, we compared habitat suitability for the American wood stork across Southeast of the United States between 2010 and 2025, 2055 and 2085. Results: Our IBM model predicted that a northward residency shift is predicted to occur given the environmental scenario of harsher fluctuation via climate instability in the Everglades. Moreover, our findings suggest that wood storks with partial and/or facultative migration may be more likely to adapt to these fluctuations. Our suitability maps showed spatially heterogeneous responses, with notable increases in northern Georgia, and the Carolinas, and consistent declines in northern Florida, indicating a gradual northward shift in suitable breeding habitat. Main Conclusions: Conserving networks of suitable wetlands across broader spatial scales, may be critical for facilitating movement and persistence under hydrologic instability. Mechanistic models such as the one presented in this study can help anticipate these shifts and inform proactive conservation planning. This model can also be adapted to fit similar wetland systems, or other landscapes with various population and movement phenotypes present.

The density-yield relationship of wild plant populations, which in agricultural systems is typically consistent with the constant final yield hypothesis, has remained largely unexplored in a restoration context despite its potential importance. In degraded California shrublands, non-native annual grasses are associated with reduced native shrub recruitment. By studying their density-yield relationship, we can potentially optimize current restoration practices by identifying the level of grass control needed to reduce the competitive pressure they create for woody plants. This in turn could enhance woody plant establishment. Here, we conducted field experiments at a degraded chaparral site in Santa Barbara County, California. We manipulated the density of Bromus diandrus, a dominant invasive annual grass, through 0-100% removal treatments to test its density-yield relationship. Simultaneously, we outplanted Ceanothus megacarpus seedlings as phytometers while also monitoring soil moisture and light availability throughout the growing season. Our results demonstrate that the Bromus diandrus density-yield relationship follows the constant final yield hypothesis, with strong intraspecific competition observed from moderate to high grass density contributing to a constant population biomass and a density dependence allometric exponent comparable to previous agricultural studies. A reduction in grass biomass (yield) was observed at 75% grass removal, yet an increase in resource availability (i.e., light and soil moisture) was only observed at 100% grass removal, as indicated by both direct measurements and enhanced phytometer performance. Applied to restoration in California Chaparral and other Mediterranean ecosystems, where the reduction of "weed" biomass is a common management goal, our findings suggest full removal of non-native annual grasses is likely needed to aid in the restoration of native woody seedlings.

Fishery-dependent indices of abundance are often used to inform stock assessments, but fishing effort is generally not randomly distributed. Fishers concentrate sampling in locations expected to be profitable, leading to a form of preferential sampling that can bias model-based indices of abundance. We show that when the strength of preferential sampling is constant over time, it biases only the magnitude of an index, which is absorbed by estimated catchability parameters in most stock assessments. A more interesting case arises when the strength of preferential sampling changes over time; in these cases the index trend can be biased in a way that conventional catchability estimation cannot correct. Using simulations structured on long running trawl survey data from the west coast of the USA for shortspine thornyhead (Sebastolobus alascanus), we evaluate two structurally different methods for correcting time-varying trend bias: a joint spatiotemporal model of the density and sampling processes, and a discrete-choice model of fisher location choice. Our simulations include two mechanisms generating preferential biases: effort tracking local density, and effort responding to a spatially structured, but unobserved anomaly that also inflates catch. We show that the ability of the estimation methods to correct bias depends on the mechanism responsible for concentrating effort; while the joint model is robust to both data-generating mechanisms, the discrete choice model is only able to correct biases when the mechanism is anomaly-driven. As a real-world case study, we apply these corrections to simulated preferentially sampled data and include indices in the shortspine thornyhead stock assessment model. We found that uncorrected time-varying preferential sampling positively biased estimates of a major recruitment event and, to a lesser extent, unfished recruitment. This bias propagated through to bias in overfishing limits that grew as the population was projected forward. While bias-corrected indices still produced some positive biases in overfishing limits, these were substantially reduced compared to the naive approach. As the mechanism of preferential sampling is rarely known in advance, our results suggest that the joint model represents a robust default for correcting fishery-dependent indices of abundance.

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.

Animal movements can transport materials across ecosystem boundaries, while simultaneously modifying habitats through physical engineering. We integrated GPS telemetry, camera trapping, sediment measurements and physicochemical sampling of ponds on Santa Cruz Island, Galapagos, to evaluate how giant tortoises connect and shape terrestrial and freshwater ecosystems. Telemetry revealed 2,254 visits by 21 tortoises to 12 ponds, with visits lasting up to 21.38 h and showing strong seasonal and diel variation, while camera traps showed peak pond use in January and during early morning and late afternoon. Greater tortoise abundance was associated with higher ammonium, dissolved organic carbon and total phosphorus concentrations, while ponds with persistently greater tortoise abundance had higher total suspended solids. Departing tortoises carried a mean 505.9 g of sediment, yielding a conservative potential export of 8.20 kg per tortoise per year and tens of tonnes annually. These findings identify giant tortoises as mobile zoogeochemical engineers linking terrestrial and freshwater ecosystems through physical and biogeochemical pathways.

Space-for-time Cormack-Jolly-Seber (CJS) models have been developed to estimate survival of migrating animals that are imperfectly detected at spatially discrete sampling stations. However, space-for-time CJS models typically ignore survival over time and age-specific probability of movement, missing the diversity of life history strategies. To address these limitations, we extended space-for-time Cormack-Jolly-Seber models to explicitly incorporate time, age, and individual-level covariates to account for diverse life history strategies. We incorporate a sub-model that includes uncertainty in individuals age using a finite-mixture model. The detection and transition probabilities were parameterized using generalized linear models, facilitating flexible model specification and inclusion of spatiotemporal and individual covariates. We apply the model to detections of juvenile steelhead (Oncorhynchus mykiss) from two populations in the Snake River Basin in Idaho, USA, to estimate trends in survival with respect to population, age, time, and the length of individuals. Additionally, we generalized the model so that it can be applied to other systems and populations with different life history strategies and monitoring infrastructure.