Seasonal weather patterns drive population vital rates and persistence in a stream fish

Microgeographic variation in demography and thermal regimes stabilize regional abundance of a widespread freshwater fish

Predicting the persistence of species under climate change is an increasingly important objective in ecological research and management. However, biotic and abiotic heterogeneity can drive asynchrony in population responses at small spatial scales, complicating species-level assessments. For widely distributed species consisting of many fragmented populations, such as brook trout (Salvelinus fontinalis), understanding the drivers of asynchrony in population dynamics can improve the predictions of range-wide climate impacts. We analyzed the demographic time series from mark-recapture surveys of 11 natural brook trout populations in eastern Canada over 13 years to examine the extent, drivers, and consequences of fine-scale population variation. The focal populations were genetically differentiated, occupied a small area (~25 km2 ) with few human impacts, and experienced similar climate conditions. Recruitment was highly asynchronous, weakly related to climate variables and showed population-specific relationships with other demographic processes, generating diverse population dynamics. In contrast, individual growth was mostly synchronized among populations and driven by a shared positive relationship with stream temperature. Outputs from population-specific models were unrelated to four of the five hypothesized drivers (recruitment, growth, reproductive success, phylogenetic distance), but variation in groundwater inputs strongly influenced stream temperature regimes and stock-recruitment relationships. Finally, population asynchrony generated a portfolio effect that stabilized regional species abundance. Our results demonstrated that population demographics and habitat diversity at microgeographic scales can play a significant role in moderating species responses to climate change. Moreover, we suggest that the absence of human activities within study streams preserved natural habitat variation and contributed to asynchrony in brook trout abundance, while the small study area eased monitoring and increased the likelihood of detecting asynchrony. Therefore, anthropogenic habitat degradation, landscape context, and spatial scale must be considered when developing management strategies to monitor and maintain populations that are diverse, stable, and resilient to climate change.

Spatial asynchrony and cross-scale climate interactions in populations of a coldwater stream fish

Climate change affects populations over broad geographic ranges due to spatially autocorrelated abiotic conditions known as the Moran effect. However, populations do not always respond to broad-scale environmental changes synchronously across a landscape. We combined multiple datasets for a retrospective analysis of time-series count data (5-28 annual samples per segment) at 144 stream segments dispersed over nearly 1,000 linear kilometers of range to characterize the population structure and scale of spatial synchrony across the southern native range of a coldwater stream fish (brook trout, Salvelinus fontinalis), which is sensitive to stream temperature and flow variations. Spatial synchrony differed by life stage and geographic region: it was stronger in the juvenile life stage than in the adult life stage and in the northern sub-region than in the southern sub-region. Spatial synchrony of trout populations extended to 100-200 km but was much weaker than that of climate variables such as temperature, precipitation, and stream flow. Early life stage abundance changed over time due to annual variation in summer temperature and winter and spring stream flow conditions. Climate effects on abundance differed between sub-regions and among local populations within sub-regions, indicating multiple cross-scale interactions where climate interacted with local habitat to generate only a modest pattern of population synchrony over space. Overall, our analysis showed higher degrees of response heterogeneity of local populations to climate variation and consequently population asynchrony than previously shown based on analysis of individual, geographically restricted datasets. This response heterogeneity indicates that certain local segments characterized by population asynchrony and resistance to climate variation could represent unique populations of this iconic native coldwater fish that warrant targeted conservation. Advancing the conservation of this species can include actions that identify such priority populations and incorporate them into landscape-level conservation planning. Our approach is applicable to other widespread aquatic species sensitive to climate change.

Is now the time? Review of genetic rescue as a conservation tool for brook trout

Brook trout populations have been declining throughout their native range in the east coast of the United States. Many populations are now distributed in small, isolated habitat patches where low genetic diversity and high rates of inbreeding reduce contemporary viability and long-term adaptive potential. Although human-assisted gene flow could theoretically improve conservation outcomes through genetic rescue, there is widespread hesitancy to use this tool to support brook trout conservation. Here, we review the major uncertainties that have limited genetic rescue from being considered as a viable conservation tool for isolated brook trout populations and compare the risks of genetic rescue with other management alternatives. Drawing on theoretical and empirical studies, we discuss methods for implementing genetic rescue in brook trout that could yield long-term evolutionary benefits while avoiding negative fitness effects associated with outbreeding depression and the spread of maladapted alleles. We also highlight the potential for future collaborative efforts to accelerate our understanding of genetic rescue as a viable tool for conservation. Ultimately, while we acknowledge that genetic rescue is not without risk, we emphasize the merits that this tool offers for protecting and propagating adaptive potential and improving species' resilience to rapid environmental change.

Demographic consequences of changes in environmental periodicity

The fate of natural populations is mediated by complex interactions among vital rates, which can vary within and among years. Although the effects of random, among-year variation in vital rates have been studied extensively, relatively little is known about how periodic, nonrandom variation in vital rates affects populations. This knowledge gap is potentially alarming as global environmental change is projected to alter common periodic variations, such as seasonality. We investigated the effects of changes in vital-rate periodicity on populations of three species representing different forms of adaptation to periodic environments: the yellow-bellied marmot (Marmota flaviventer), adapted to strong seasonality in snowfall; the meerkat (Suricata suricatta), adapted to inter-annual stochasticity as well as seasonal patterns in rainfall; and the dewy pine (Drosophyllum lusitanicum), adapted to fire regimes and periodic post-fire habitat succession. To assess how changes in periodicity affect population growth, we parameterized periodic matrix population models and projected population dynamics under different scenarios of perturbations in the strength of vital-rate periodicity. We assessed the effects of such perturbations on various metrics describing population dynamics, including the stochastic growth rate, log λ_S . Overall, perturbing the strength of periodicity had strong effects on population dynamics in all three study species. For the marmots, log λ_S decreased with increased seasonal differences in adult survival. For the meerkats, density dependence buffered the effects of perturbations of periodicity on log λ_S . Finally, dewy pines were negatively affected by changes in natural post-fire succession under stochastic or periodic fire regimes with fires occurring every 30 years, but were buffered by density dependence from such changes under presumed more frequent fires or large-scale disturbances. We show that changes in the strength of vital-rate periodicity can have diverse but strong effects on population dynamics across different life histories. Populations buffered from inter-annual vital-rate variation can be affected substantially by changes in environmentally driven vital-rate periodic patterns; however, the effects of such changes can be masked in analyses focusing on inter-annual variation. As most ecosystems are affected by periodic variations in the environment such as seasonality, assessing their contributions to population viability for future global-change research is crucial.

Identifying mechanisms underlying individual body size increases in a changing, highly seasonal environment: The growing trout of West brook

As air temperature increases, it has been suggested that smaller individual body size may be a general response to climate warming. However, for ectotherms inhabiting cold, highly seasonal environments, warming temperatures may increase the scope for growth and result in larger body size. In a long-term study of individual brook trout Salvelinus fontinalis and brown trout Salmo trutta inhabiting a small stream network, individual lengths increased over the course of 15 years. As size-selective gains and losses to the population acted to reduce body sizes and mean body size at first tagging in the autumn (<60 mm) were not observed to change substantially over time, the increase in body size was best explained by higher individual growth rates. For brook trout, increasing water temperatures during the spring (when both trout species accomplish most of their total annual growth) was the primary driver of growth rate for juvenile fish and the environmental factor which best explained increases in individual body size over time. For brown trout, by contrast, reduction in and subsequent elimination of juvenile Atlantic salmon Salmo salar midway through the study period explained most of the increases in juvenile growth and body size. In addition to these major trends, a considerable amount of interannual variation in trout growth and body size was explained by other abiotic (stream flow) and biotic (population density) factors with the direction and magnitude of these effects differing by season, age-class and species. For example, stream flow was the dominant growth rate driver for adult fish with strong positive effects in the summer and autumn, but flow variation could not explain increases in body size as we observed no trend in flow. Overall, our work supports the general contention that for high-latitude ectotherms, increasing spring temperatures associated with a warming climate can result in increased growth and individual body size (up to a point), but context-dependent change in other factors can substantially contribute to both interannual variation and longer-term effects.

Effects of climate on salmonid productivity: A global meta-analysis across freshwater ecosystems

Salmonids are of immense socio-economic importance in much of the world, but are threatened by climate change. This has generated a substantial literature documenting the effects of climate variation on salmonid productivity in freshwater ecosystems, but there has been no global quantitative synthesis across studies. We conducted a systematic review and meta-analysis to gain quantitative insight into key factors shaping the effects of climate on salmonid productivity, ultimately collecting 1321 correlations from 156 studies, representing 23 species across 24 countries. Fisher's Z was used as the standardized effect size, and a series of weighted mixed-effects models were compared to identify covariates that best explained variation in effects. Patterns in climate effects were complex and were driven by spatial (latitude, elevation), temporal (time-period, age-class), and biological (range, habitat type, anadromy) variation within and among study populations. These trends were often consistent with predictions based on salmonid thermal tolerances. Namely, warming and decreased precipitation tended to reduce productivity when high temperatures challenged upper thermal limits, while opposite patterns were common when cold temperatures limited productivity. Overall, variable climate impacts on salmonids suggest that future declines in some locations may be counterbalanced by gains in others. In particular, we suggest that future warming should (1) increase salmonid productivity at high latitudes and elevations (especially >60° and >1500 m), (2) reduce productivity in populations experiencing hotter and dryer growing season conditions, (3) favor non-native over native salmonids, and (4) impact lentic populations less negatively than lotic ones. These patterns should help conservation and management organizations identify populations most vulnerable to climate change, which can then be prioritized for protective measures. Our framework enables broad inferences about future productivity that can inform decision-making under climate change for salmonids and other taxa, but more widespread, standardized, and hypothesis-driven research is needed to expand current knowledge.

Simple statistical models can be sufficient for testing hypotheses with population time-series data

Time-series data offer wide-ranging opportunities to test hypotheses about the physical and biological factors that influence species abundances. Although sophisticated models have been developed and applied to analyze abundance time series, they require information about species detectability that is often unavailable. We propose that in many cases, simpler models are adequate for testing hypotheses. We consider three relatively simple regression models for time series, using simulated and empirical (fish and mammal) datasets. Model A is a conventional generalized linear model of abundance, model B adds a temporal autoregressive term, and model C uses an estimate of population growth rate as a response variable, with the option of including a term for density dependence. All models can be fit using Bayesian and non-Bayesian methods. Simulation results demonstrated that model C tended to have greater support for long-lived, lower-fecundity organisms (K life-history strategists), while model A, the simplest, tended to be supported for shorter-lived, high-fecundity organisms (r life-history strategists). Analysis of real-world fish and mammal datasets found that models A, B, and C each enjoyed support for at least some species, but sometimes yielded different insights. In particular, model C indicated effects of predictor variables that were not evident in analyses with models A and B. Bayesian and frequentist models yielded similar parameter estimates and performance. We conclude that relatively simple models are useful for testing hypotheses about the factors that influence abundance in time-series data, and can be appropriate choices for datasets that lack the information needed to fit more complicated models. When feasible, we advise fitting datasets with multiple models because they can provide complementary information.

Do metapopulations and management matter for relict headwater bull trout populations in a warming climate?

Mountain headwater streams have emerged as important climate refuges for native cold-water species due to their slow climate velocities and extreme physical conditions that inhibit non-native invasions. Species persisting in refuges often do so as fragmented, relict populations from broader historical distributions that are subject to ongoing habitat reductions and increasing isolation as climate change progresses. Key for conservation planning is determining where remaining populations will persist and how habitat restoration strategies can improve biological resilience to enhance the long-term prospects for species of concern. Studying bull trout, a headwater species in the northwestern USA, we developed habitat occupancy models using a data set of population occurrence in 991 natal habitat patches with a suite of novel geospatial covariates derived from high-resolution hydroclimatic scenarios and other sources representing watershed and instream habitat conditions, patch geometry, disturbance, and biological interactions. The best model correctly predicted bull trout occupancy status in 82.6% of the patches and included effects for: patch size estimated as habitat volume, extent of within-patch reaches <9°C mean August temperature, distance to nearest occupied patch, road density, invasive brook trout prevalence, patch slope, and frequency of high winter flows. The model was used to assess 16 scenarios of bull trout occurrence within the study streams that represented a range of restoration strategies under three climatic conditions (baseline, moderate change, and extreme change). Results suggested that regional improvements in bull trout status were difficult to achieve in realistic restoration strategies due to the pervasive nature of climate change and the limited extent of restoration actions given their high costs. However, occurrence probabilities in a subset of patches were highly responsive to restoration actions, suggesting that targeted investments to improve the resilience of some populations may be contextually beneficial. A possible strategy, therefore, is focusing effort on responsive populations near more robust population strongholds, thereby contributing to local enclaves where dispersal among populations further enhances resilience. Equally important, strongholds constituted a small numerical percentage of patches (5%-21%), yet encompassed the large majority of occupied habitat by volume (72%-89%) and their protection could have significant conservation benefits for bull trout.

Thermal regime during parental sexual maturation, but not during offspring rearing, modulates DNA methylation in brook charr (Salvelinus fontinalis)

Epigenetic inheritance can result in plastic responses to changing environments being faithfully transmitted to offspring. However, it remains unclear how epigenetic mechanisms such as DNA methylation can contribute to multigenerational acclimation and adaptation to environmental stressors. Brook charr (Salvelinus fontinalis), an economically important salmonid, is highly sensitive to thermal stress and is of conservation concern in the context of climate change. We studied the effects of temperature during parental sexual maturation and offspring rearing on whole-genome DNA methylation in brook charr juveniles (fry). Parents were split between warm and cold temperatures during sexual maturation, mated in controlled breeding designs, then offspring from each family were split between warm (8°C) and cold (5°C) rearing environments. Using whole-genome bisulfite sequencing, we found 188 differentially methylated regions (DMRs) due to parental maturation temperature after controlling for family structure. By contrast, offspring rearing temperature had a negligible effect on offspring methylation. Stable intergenerational inheritance of DNA methylation and minimal plasticity in progeny could result in the transmission of acclimatory epigenetic states to offspring, priming them for a warming environment. Our findings have implications pertaining to the role of intergenerational epigenetic inheritance in response to ongoing climate change.

Life history strategies of stream fishes linked to predictors of hydrologic stability

Life history theory provides a framework to understand environmental change based on species strategies for survival and reproduction under stable, cyclical, or stochastic environmental conditions. We evaluated environmental predictors of fish life history strategies in 20 streams intersecting a national park within the Potomac River basin in eastern North America. We sampled stream sites during 2018-2019 and collected 3801 individuals representing 51 species within 10 taxonomic families. We quantified life history strategies for species from their coordinates in an ordination space defined by trade-offs in spawning season duration, fecundity, and parental care characteristic of opportunistic, periodic, and equilibrium strategies. Our analysis revealed important environmental predictors: Abundance of opportunistic strategists increased with low-permeability soils that produce flashy runoff dynamics and decreased with karst terrain (carbonate bedrock) where groundwater inputs stabilize stream flow and temperature. Conversely, abundance of equilibrium strategists increased in karst terrain indicating a response to more stable environmental conditions. Our study indicated that fish community responses to groundwater and runoff processes may be explained by species traits for survival and reproduction. Our findings also suggest the utility of life history theory for understanding ecological responses to destabilized environmental conditions under global climate change.

Snowpacks decrease and streamflows shift across the eastern US as winters warm

Climate change is increasing winter temperatures across the planet, altering snowmelt hydrology. This study addresses a gap in snow research in non-alpine areas by examining changes to snow and winter and spring streamflow across most of the eastern US using daily observations from weather stations and stream gages from water years 1960-2019. These daily data were aggregated across drainage basins and classified winters with similar temperatures; differences between winters and both seasonal and annual trends were statistically quantified. Winters were classified as "warm" or "cool" in each drainage basin relative to the 60-year mean; analysis of the data indicates that warm winters occur more frequently in recent decades from an average of 0.39 to 3.96 warm winters/decade from the 1960's to the 2010's respectively. Those classifications were then used to examine changes in snowpack over the same period, which shows that warmer winters have on average 50.1 cm less annual snowfall, a reduced maximum snowpack depth by 14.4 cm, and 34 more bare ground days. These changes correlate with shifts to higher winter streamflows as well as peak basin yields that are 0.02 cm lower and occur three days earlier in warm winters. In addition to altered soil moisture and stream ecosystem dynamics, these snow and streamflow changes may have negative infrastructure and economic implications including impacts to winter tourism and agriculture.

Modeling effects of disturbance across life history strategies of stream fishes

A central goal of population ecology is to establish linkages between life history strategy, disturbance, and population dynamics. Globally, disturbance events such as drought and invasive species have dramatically impacted stream fish populations and contributed to sharp declines in freshwater biodiversity. Here, we used RAMAS Metapop to construct stage-based demographic metapopulation models for stream fishes with periodic, opportunistic, and equilibrium life history strategies and assessed their responses to the effects of invasion (reduced carrying capacity), extended drought (reduced survival and fecundity), and the combined effects of both disturbances. Our models indicated that populations respond differentially to disturbance based on life history strategy. Equilibrium strategists were best able to deal with simulated invasion. Periodic strategists did well under lower levels of drought, whereas opportunistic strategists outperformed other life histories under extreme seasonal drought. When we modeled additive effects scenarios, these disturbances interacted synergistically, dramatically increasing terminal extinction risk for all three life history strategies. Modeling exercises that examine broad life history categories can help to answer fundamental ecological questions about the relationship between disturbance resilience and life history, as well as help managers to develop generalized conservation strategies when species-specific data are lacking. Our results indicate that life history strategy is a fundamental determinant of population trajectories, and that disturbances can interact synergistically to dramatically impact extinction outcomes.

Hybridization alters growth and migratory life-history expression of native trout

Human-mediated hybridization threatens many native species, but the effects of introgressive hybridization on life-history expression are rarely quantified, especially in vertebrates. We quantified the effects of non-native rainbow trout admixture on important life-history traits including growth and partial migration behavior in three populations of westslope cutthroat trout over five years. Rainbow trout admixture was associated with increased summer growth rates in all populations and decreased spring growth rates in two populations with cooler spring temperatures. These results indicate that non-native admixture may increase growth under warmer conditions, but cutthroat trout have higher growth rates during cooler periods. Non-native admixture consistently increased expression of migratory behavior, suggesting that there is a genomic basis for life-history differences between these species. Our results show that effects of interspecific hybridization on fitness traits can be the product of genotype-by-environment interactions even when there are minor differences in environmental optima between hybridizing species. These results also indicate that while environmentally mediated traits like growth may play a role in population-level consequences of admixture, strong genetic influences on migratory life-history differences between these species likely explains the continued spread of non-native hybridization at the landscape-level, despite selection against hybrids at the population-level.

Guiding riparian management in a transboundary watershed through high resolution spatial statistical network models

The United States Environmental Protection Agency and the Houlton Band of Maliseet Indians (HBMI) built a stream temperature spatial statistical network (SSN) model for the Meduxnekeag Watershed. The headwaters of the Meduxnekeag Watershed are in Maine, United States of America and the outlet is in New Brunswick, Canada, creating an additional challenge because many datasets are constrained to political boundaries. The release of the High-Resolution National Hydrology Dataset Plus included transboundary watersheds and enabled creation of fine resolution (1:24,000) SSN temperature models consistent with management scales for riparian buffers. SSN models were developed for July, August, and September median stream temperatures and the growing season maximum (GSM). Fitted SSN models had relatively high R² values (0.88-0.96) and all final models included significant parameters for shade-attenuated solar radiation, reference flow, air temperature, and bankfull depth or width. Fitted models predicted stream temperatures during a dry (2010) and wet (2011) year. Monthly models predicted the fewest cold water (<19.0 °C) reaches in July with 28% in the dry and 68% in the wet year. September had >99% cold water reaches, and August results were intermediate between July and September. GSM predictions found 81% of stream reaches could not support salmonid survival (>27.0 °C) in the dry year and 59% of the reaches were warmwater (22.5-27.0 °C) in the wet year. The model was used to predict stream temperatures following restoration scenarios of a forested 30-m or 90-m buffer of stream segments bordered by agricultural or developed land. The restoration scenarios expanded cold water habitat based on monthly median temperatures and decreased the habitat area with GSM above survival thresholds, with little difference in effectiveness of the two buffer widths. These results will guide riparian restoration projects by the HBMI to expand habitat for cold water fishes.

A geostatistical state-space model of animal densities for stream networks

Population dynamics are often correlated in space and time due to correlations in environmental drivers as well as synchrony induced by individual dispersal. Many statistical analyses of populations ignore potential autocorrelations and assume that survey methods (distance and time between samples) eliminate these correlations, allowing samples to be treated independently. If these assumptions are incorrect, results and therefore inference may be biased and uncertainty underestimated. We developed a novel statistical method to account for spatiotemporal correlations within dendritic stream networks, while accounting for imperfect detection in the surveys. Through simulations, we found this model decreased predictive error relative to standard statistical methods when data were spatially correlated based on stream distance and performed similarly when data were not correlated. We found that increasing the number of years surveyed substantially improved the model accuracy when estimating spatial and temporal correlation coefficients, especially from 10 to 15 yr. Increasing the number of survey sites within the network improved the performance of the nonspatial model but only marginally improved the density estimates in the spatiotemporal model. We applied this model to brook trout data from the West Susquehanna Watershed in Pennsylvania collected over 34 yr from 1981 to 2014. We found the model including temporal and spatiotemporal autocorrelation best described young of the year (YOY) and adult density patterns. YOY densities were positively related to forest cover and negatively related to spring temperatures with low temporal autocorrelation and moderately high spatiotemporal correlation. Adult densities were less strongly affected by climatic conditions and less temporally variable than YOY but with similar spatiotemporal correlation and higher temporal autocorrelation.

Brook trout distributional response to unconventional oil and gas development: Landscape context matters

We conducted a large-scale assessment of unconventional oil and gas (UOG) development effects on brook trout (Salvelinus fontinalis) distribution. We compiled 2231 brook trout collection records from the Upper Susquehanna River Watershed, USA. We used boosted regression tree (BRT) analysis to predict occurrence probability at the 1:24,000 stream-segment scale as a function of natural and anthropogenic landscape and climatic attributes. We then evaluated the importance of landscape context (i.e., pre-existing natural habitat quality and anthropogenic degradation) in modulating the effects of UOG on brook trout distribution under UOG development scenarios. BRT made use of 5 anthropogenic (28% relative influence) and 7 natural (72% relative influence) variables to model occurrence with a high degree of accuracy [Area Under the Receiver Operating Curve (AUC)=0.85 and cross-validated AUC=0.81]. UOG development impacted 11% (n=2784) of streams and resulted in a loss of predicted occurrence in 126 (4%). Most streams impacted by UOG had unsuitable underlying natural habitat quality (n=1220; 44%). Brook trout were predicted to be absent from an additional 26% (n=733) of streams due to pre-existing non-UOG land uses (i.e., agriculture, residential and commercial development, or historic mining). Streams with a predicted and observed (via existing pre- and post-disturbance fish sampling records) loss of occurrence due to UOG tended to have intermediate natural habitat quality and/or intermediate levels of non-UOG stress. Simulated development of permitted but undeveloped UOG wells (n=943) resulted in a loss of predicted occurrence in 27 additional streams. Loss of occurrence was strongly dependent upon landscape context, suggesting effects of current and future UOG development are likely most relevant in streams near the probability threshold due to pre-existing habitat degradation.

Statistical Models to Predict and Assess Spatial and Temporal Low-Flow Variability in New England Rivers and Streams

In the northern hemisphere, summer low flows are a key attribute defining both quantity and quality of aquatic habitat. I developed one set of models for New England streams/rivers predicting July/August median flows averaged across 1985 to 2015 as a function of weather, slope, % imperviousness, watershed storage, glacial geology and soils. These models performed better than most USGS models for summer flows developed at a statewide scale. I developed a second set of models predicting interannual differences in summer flows as a function of differences in air temperature, precipitation, the North Atlantic Oscillation Index (NAO), and lagged NAO. Use of difference equations eliminated the need for transformations and accounted for serial autocorrelations at lag 1. The models were used in sequence to estimate time series for monthly low flows and for two derived flow metrics (tenth percentile (Q10) and minimum 3-in-5 year average flows). The first metric is commonly used in assessing risk to low flow conditions over time while the second has been correlated with increased probability of localized extinctions for brook trout. The flow metrics showed increasing trends across most of New England for 1985-2015. However, application of summer flow models with average and extreme climate projections to the Taunton River, MA, a sensitive watershed undergoing rapid development, projected that low flow metrics will decrease over the next 50 years.