Fragmentation and thermal risks from climate change interact to affect persistence of native trout in the Colorado River basin

Conserving stream fishes with changing climate: Assessing fish responses to changes in habitat over a large region

Changes in climate are known to alter air temperature and precipitation and their associated thermal and hydrological regimes of freshwater systems, and such alterations in habitat are anticipated to modify fish composition in fluvial systems. Despite these expected changes, assessing climate change effects on habitat and fish over large regions has proven challenging. The goal of this study is to describe an approach to assess and identify stream reaches within a large region that are susceptible to climate changes based on responses of multiple fish species to changes in thermal and hydrological habitats occurring with changes in climate. We present a six-step approach to connect climate, habitat, and fish responses, demonstrated through an example to assess effects of climate change on fishes for all stream reaches in a large U.S. ecoregion (955,029 km²). Step 1 identified measures of air temperature and precipitation expected to change substantially in the future. Step 2 identified the climatic measures strongly associated with stream thermal and hydrologic metrics calculated from measured data from a subset of streams. Step 3 linked thermal and hydrologic metrics identified in Step 2 with abundances of fish species from the same stream reaches, and these fishes were combined into groups based on similar associations with specific thermal or hydrologic metrics. Step 4 used the linkages between fish groups and climatic measures and their associated thermal and hydrologic metrics to classify stream reaches. Step 5 assigned all stream reaches into classes based on the established classification under current climate measures and then re-assigned all stream reaches using projected climatic measures for three future time windows. Step 6 assessed changes in classes of stream reaches between current and future climate conditions. Stream reaches projected to change in stream classes were considered "vulnerable" to future climate change, as they would no longer support the same fish composition. The projected vulnerable streams for the years 2040, 2060, and 2090 were mapped and summarized to identify temporal patterns and identify their spatial distribution, along with underlying mechanisms leading to changes. Our results showed that 45.7% of the 320,000 reaches and 49.3% of the overall 650,000 km stream length in the study region were expected to change stream class by the year 2090, with spatially-explicit changes including streams' responding to changing air temperature or precipitation. This study provides critical guidance for integrating climate projections, landscape factors, stream habitat data, and fish data into a meaningful approach for understanding linkage. Outcomes greatly improve our ability to describe habitat changes at a stream reach scale throughout large regions, and they can aid in prioritizing management strategies to adapt to climate change at local and regional scales.

Bayesian Networks in Environmental Risk Assessment: A Review

Human activities both depend upon and have consequences on the environment. Environmental risk assessment (ERA) is a process of estimating the probability and consequences of the adverse effects of human activities and other stressors on the environment. Bayesian networks (BNs) can synthesize different types of knowledge and explicitly account for the probabilities of different scenarios, therefore offering a useful tool for ERA. Their use in formal ERA practice has not been evaluated, however, despite their increasing popularity in environmental modeling. This paper reviews the use of BNs in ERA based on peer-reviewed publications. Following a systematic mapping protocol, we identified studies in which BNs have been used in an environmental risk context and evaluated the scope, technical aspects, and use of the models and their results. The review shows that BNs have been applied in ERA, particularly in recent years, and that there is room to develop both the model implementation and participatory modeling practices. Based on this review and the authors' experience, we outline general guidelines and development ideas for using BNs in ERA. Integr Environ Assess Manag 2021;17:62-78. © 2020 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

The interaction of exposure and warming tolerance determines fish species vulnerability to warming stream temperatures

Species vulnerability to climate change involves an interaction between the magnitude of change (exposure) and a species's tolerance to change. We evaluated fish species vulnerability to predicted stream temperature increases by examining warming tolerances across the Wyoming fish assemblage. Warming tolerance combines stream temperature with a thermal tolerance metric to estimate how much warming beyond current conditions a species can withstand. Brown trout, rainbow trout and burbot had the lowest warming tolerances and the highest proportion of currently occupied sites that will become unsuitable under predicted temperature increases. These most vulnerable species were coldwater species, but had neither the lowest thermal tolerances nor would they experience the greatest temperature increases. Our results highlight the importance of considering the interaction of exposure and warming tolerance when predicting climate change vulnerability and demonstrate an approach that can be applied broadly.

Probabilistic measures of climate change vulnerability, adaptation action benefits, and related uncertainty from maximum temperature metric selection

Predictions of the projected changes in species distributions and potential adaptation action benefits can help guide conservation actions. There is substantial uncertainty in projecting species distributions into an unknown future, however, which can undermine confidence in predictions or misdirect conservation actions if not properly considered. Recent studies have shown that the selection of alternative climate metrics describing very different climatic aspects (e.g., mean air temperature vs. mean precipitation) can be a substantial source of projection uncertainty. It is unclear, however, how much projection uncertainty might stem from selecting among highly correlated, ecologically similar climate metrics (e.g., maximum temperature in July, maximum 30-day temperature) describing the same climatic aspect (e.g., maximum temperatures) known to limit a species' distribution. It is also unclear how projection uncertainty might propagate into predictions of the potential benefits of adaptation actions that might lessen climate change effects. We provide probabilistic measures of climate change vulnerability, adaptation action benefits, and related uncertainty stemming from the selection of four maximum temperature metrics for brook trout (Salvelinus fontinalis), a cold-water salmonid of conservation concern in the eastern United States. Projected losses in suitable stream length varied by as much as 20% among alternative maximum temperature metrics for mid-century climate projections, which was similar to variation among three climate models. Similarly, the regional average predicted increase in brook trout occurrence probability under an adaptation action scenario of full riparian forest restoration varied by as much as .2 among metrics. Our use of Bayesian inference provides probabilistic measures of vulnerability and adaptation action benefits for individual stream reaches that properly address statistical uncertainty and can help guide conservation actions. Our study demonstrates that even relatively small differences in the definitions of climate metrics can result in very different projections and reveal high uncertainty in predicted climate change effects.

A spatio-temporal statistical model of maximum daily river temperatures to inform the management of Scotland's Atlantic salmon rivers under climate change

The thermal suitability of riverine habitats for cold water adapted species may be reduced under climate change. Riparian tree planting is a practical climate change mitigation measure, but it is often unclear where to focus effort for maximum benefit. Recent developments in data collection, monitoring and statistical methods have facilitated the development of increasingly sophisticated river temperature models capable of predicting spatial variability at large scales appropriate to management. In parallel, improvements in temporal river temperature models have increased the accuracy of temperature predictions at individual sites. This study developed a novel large scale spatio-temporal model of maximum daily river temperature (Tw_max) for Scotland that predicts variability in both river temperature and climate sensitivity. Tw_max was modelled as a linear function of maximum daily air temperature (Ta_max), with the slope and intercept allowed to vary as a smooth function of day of the year (DoY) and further modified by landscape covariates including elevation, channel orientation and riparian woodland. Spatial correlation in Tw_max was modelled at two scales; (1) river network (2) regional. Temporal correlation was addressed through an autoregressive (AR1) error structure for observations within sites. Additional site level variability was modelled with random effects. The resulting model was used to map (1) spatial variability in predicted Tw_max under current (but extreme) climate conditions (2) the sensitivity of rivers to climate variability and (3) the effects of riparian tree planting. These visualisations provide innovative tools for informing fisheries and land-use management under current and future climate.

Thermal regimes of Rocky Mountain lakes warm with climate change

Anthropogenic climate change is causing a wide range of stresses in aquatic ecosystems, primarily through warming thermal conditions. Lakes, in response to these changes, are experiencing increases in both summer temperatures and ice-free days. We used continuous records of lake surface temperature and air temperature to create statistical models of daily mean lake surface temperature to assess thermal changes in mountain lakes. These models were combined with downscaled climate projections to predict future thermal conditions for 27 high-elevation lakes in the southern Rocky Mountains. The models predict a 0.25°C·decade^-1 increase in mean annual lake surface temperature through the 2080s, which is greater than warming rates of streams in this region. Most striking is that on average, ice-free days are predicted to increase by 5.9 days ·decade^-1, and summer mean lake surface temperature is predicted to increase by 0.47°C·decade^-1. Both could profoundly alter the length of the growing season and potentially change the structure and function of mountain lake ecosystems. These results highlight the changes expected of mountain lakes and stress the importance of incorporating climate-related adaptive strategies in the development of resource management plans.

Assessment of dam effects on streams and fish assemblages of the conterminous USA

Despite the prevalence of damming as a global disturbance to river habitats, detailed reach-based assessments of the ecological effects of dams are lacking, particularly across large spatial extents. Using data from nearly 50,000 large dams, we assessed stream network fragmentation and flow alteration by large dams for streams of the conterminous USA. We developed 21 dam metrics characterizing a diversity of dam influences operating at both localized (e.g., distances-to-dams) and landscape scales (e.g., cumulative reservoir storage throughout stream networks) for every stream reach in the study region. We further evaluated how dams have affected stream fish assemblages within large ecoregions using more than 37,000 stream fish samples. Streams have been severely fragmented by large dams, with the number of stream segments increasing by 801% compared to free-flowing streams in the absence of dams and a staggering 79% of stream length is disconnected from their outlet (i.e., oceans and Great Lakes). Flow alteration metrics demonstrate a landscape-scale disturbance of dams, resulting in total upstream reservoir storage volumes exceeding estimated annual discharge volumes of many of the nation's largest rivers. Further, we show large-scale changes in fish assemblages with dams. Species adapted to lentic habitats increase with dams across the conterminous USA, while rheophils, lithophils, and intolerant fishes decrease with dams. Overall, fragmentation and flow alteration by dams have affected fish assemblages as much or more than other anthropogenic stressors, with dam effects generally increasing with stream size. Dam-induced stream fragmentation and flow alteration are critical natural resource issues. This study emphasizes the importance of considering dams as a landscape-scale disturbance to river habitats along with the need to assess differential effects that dams may have on river habitats and the fishes they support. Together, these insights are essential for more effective conservation of stream resources and biotic communities globally.

Seasonal and temperature-related movement of Colorado River cutthroat trout in a low-elevation, Rocky Mountain stream

Mobile species will migrate considerable distances to find habitats suitable for meeting life history requirements, and stream‐dwelling salmonids are no exception. In April–October 2014, we used radio‐telemetry to examine habitat use and movement of 36 Colorado River cutthroat trout Oncorhynchus clarkii pleuriticus (CRCT) in a 14.9‐km fragment of Milk Creek, a relatively low‐elevation stream in the Rocky Mountains (Colorado). We also used a network of data loggers to track stream temperature across time and space. Our objectives were to (1) characterize distribution and movement of CRCT, (2) evaluate seasonal differences in distribution and movement of CRCT, and (3) explore the relationship between stream temperature and distribution and movement of CRCT. During the course of our study, median range of CRCT was 4.81 km (range = 0.14–10.94) and median total movement was 5.94 km (range = 0.14–26.02). Median location of CRCT was significantly further upstream in summer than in spring, whereas range and movement of CRCT were greater in spring than in summer. Twenty‐six of the 27 CRCT tracked through mid‐June displayed a potamodromous (freshwater migratory) life history, migrating 1.8–8.0 km upstream during the spring spawning season. Four of the seven CRCT tracked through July migrated >1.4 km in summer. CRCT selected relatively cool reaches during summer months, and early‐summer movement was positively correlated with mean stream temperature. Study fish occupied stream segments in spring and fall that were thermally unsuitable, if not lethal, to the species in summer. Although transmitter loss limited the scope of inference, our findings suggest that preferred habitat is a moving target in Milk Creek, and that CRCT move to occupy that target. Because mobile organisms move among complementary habitats and exploit seasonally‐unsuitable reaches, we recommend that spatial and temporal variability be accounted for in delineations of distributional boundaries.

Untangling the effects of multiple human stressors and their impacts on fish assemblages in European running waters

This work addresses human stressors and their impacts on fish assemblages at pan-European scale by analysing single and multiple stressors and their interactions. Based on an extensive dataset with 3105 fish sampling sites, patterns of stressors, their combination and nature of interactions, i.e. synergistic, antagonistic and additive were investigated. Geographical distribution and patterns of seven human stressor variables, belonging to four stressor groups (hydrological-, morphological-, water quality- and connectivity stressors), were examined, considering both single and multiple stressor combinations. To quantify the stressors' ecological impact, a set of 22 fish metrics for various fish assemblage types (headwaters, medium gradient rivers, lowland rivers and Mediterranean streams) was analysed by comparing their observed and expected response to different stressors, both acting individually and in combination. Overall, investigated fish sampling sites are affected by 15 different stressor combinations, including 4 stressors acting individually and 11 combinations of two or more stressors; up to 4 stressor groups per fish sampling site occur. Stressor-response analysis shows divergent results among different stressor categories, even though a general trend of decreasing ecological integrity with increasing stressor quantity can be observed. Fish metrics based on density of species 'intolerant to water quality degradation' and 'intolerant to oxygen depletion" responded best to single and multiple stressors and their interactions. Interactions of stressors were additive (40%), synergistic (30%) or antagonistic (30%), emphasizing the importance to consider interactions in multi-stressor analyses. While antagonistic effects are only observed in headwaters and medium-gradient rivers, synergistic effects increase from headwaters over medium gradient rivers and Mediterranean streams to large lowland rivers. The knowledge gained in this work provides a basis for advanced investigations in European river basins and helps prioritizing further restoration and management actions.

Temperature effects on hatching and viability of Juvenile Gill Lice, Salmincola californiensis

Salmonids of the genus Oncorhynchus, distributed throughout the Pacific Rim, can be infected by the gill lice species Salmincola californiensis (Dana, 1852), which makes them one of the most broadly distributed gill lice species. Despite their broad distribution and valuable obligate salmonid hosts, relatively little is known about S. californiensis. We evaluated effects of temperature on timing of S. californiensis hatching and survival of copepodids, and provide information on brood size and variability. Our results suggest that temperature was a primary driver of timing of S. californiensis hatching and post-hatching survival. Prior to this study, the free-swimming stage of S. californiensis was reported to survive approximately 2 days without a suitable host. We observed active copepodids 13 days after hatch with some individuals from most (>90%) viable egg sacs at all temperature treatments surviving ≥5 days. Our findings indicate that warmer temperatures could increase development rates of gill lice at certain life stages, potentially increasing fecundity. This information coupled with predictions that warmer water temperatures could intensify crowding of coldwater fishes, stress, and parasite transmission suggests that climate change could exacerbate negative effects of S. californiensis on ecologically and economically important salmonids.

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

Climate change affects seasonal weather patterns, but little is known about the relative importance of seasonal weather patterns on animal population vital rates. Even when such information exists, data are typically only available from intensive fieldwork (e.g., mark-recapture studies) at a limited spatial extent. Here, we investigated effects of seasonal air temperature and precipitation (fall, winter, and spring) on survival and recruitment of brook trout (Salvelinus fontinalis) at a broad spatial scale using a novel stage-structured population model. The data were a 15-year record of brook trout abundance from 72 sites distributed across a 170-km-long mountain range in Shenandoah National Park, Virginia, USA. Population vital rates responded differently to weather and site-specific conditions. Specifically, young-of-year survival was most strongly affected by spring temperature, adult survival by elevation and per-capita recruitment by winter precipitation. Low fall precipitation and high winter precipitation, the latter of which is predicted to increase under climate change for the study region, had the strongest negative effects on trout populations. Simulations show that trout abundance could be greatly reduced under constant high winter precipitation, consistent with the expected effects of gravel-scouring flows on eggs and newly hatched individuals. However, high-elevation sites would be less vulnerable to local extinction because they supported higher adult survival. Furthermore, the majority of brook trout populations are projected to persist if high winter precipitation occurs only intermittently (≤3 of 5 years) due to density-dependent recruitment. Variable drivers of vital rates should be commonly found in animal populations characterized by ontogenetic changes in habitat, and such stage-structured effects may increase population persistence to changing climate by not affecting all life stages simultaneously. Yet, our results also demonstrate that weather patterns during seemingly less consequential seasons (e.g., winter precipitation) can have major impacts on animal population dynamics.

Probabilistic accounting of uncertainty in forecasts of species distributions under climate change

Forecasts of species distributions under future climates are inherently uncertain, but there have been few attempts to describe this uncertainty comprehensively in a probabilistic manner. We developed a Monte Carlo approach that accounts for uncertainty within generalized linear regression models (parameter uncertainty and residual error), uncertainty among competing models (model uncertainty), and uncertainty in future climate conditions (climate uncertainty) to produce site-specific frequency distributions of occurrence probabilities across a species' range. We illustrated the method by forecasting suitable habitat for bull trout (Salvelinus confluentus) in the Interior Columbia River Basin, USA, under recent and projected 2040s and 2080s climate conditions. The 95% interval of total suitable habitat under recent conditions was estimated at 30.1-42.5 thousand km; this was predicted to decline to 0.5-7.9 thousand km by the 2080s. Projections for the 2080s showed that the great majority of stream segments would be unsuitable with high certainty, regardless of the climate data set or bull trout model employed. The largest contributor to uncertainty in total suitable habitat was climate uncertainty, followed by parameter uncertainty and model uncertainty. Our approach makes it possible to calculate a full distribution of possible outcomes for a species, and permits ready graphical display of uncertainty for individual locations and of total habitat.

Soil moisture's underestimated role in climate change impact modelling in low-energy systems

Shifts in precipitation regimes are an inherent component of climate change, but in low-energy systems are often assumed to be less important than changes in temperature. Because soil moisture is the hydrological variable most proximally linked to plant performance during the growing season in arctic-alpine habitats, it may offer the most useful perspective on the influence of changes in precipitation on vegetation. Here we quantify the influence of soil moisture for multiple vegetation properties at fine spatial scales, to determine the potential importance of soil moisture under changing climatic conditions. A fine-scale data set, comprising vascular species cover and field-quantified ecologically relevant environmental parameters, was analysed to determine the influence of soil moisture relative to other key abiotic predictors. Soil moisture was strongly related to community composition, species richness and the occurrence patterns of individual species, having a similar or greater influence than soil temperature, pH and solar radiation. Soil moisture varied considerably over short distances, and this fine-scale heterogeneity may contribute to offsetting the ecological impacts of changes in precipitation for species not limited to extreme soil moisture conditions. In conclusion, soil moisture is a key driver of vegetation properties, both at the species and community level, even in this low-energy system. Soil moisture conditions represent an important mechanism through which changing climatic conditions impact vegetation, and advancing our predictive capability will therefore require a better understanding of how soil moisture mediates the effects of climate change on biota.