Effects of climate change and wildfire on stream temperatures and salmonid thermal habitat in a mountain river network

Watershed features shape spatial patterns of fish tissue mercury in a boreal river network

Freshwater mercury (Hg) contamination is a widespread environmental concern but how proximate sources and downstream transport shape Hg spatial patterns in riverine food webs is poorly understood. We measured total Hg (THg) in slimy sculpin (Cottus cognatus) across the Kuskokwim River, a large boreal river in western Alaska and home to subsistence fishing communities which rely on fish for primary nutrition. We used spatial stream network models (SSNMs) to quantify watershed and instream conditions influencing sculpin THg. Spatial covariates for local watershed geology and slope accounted for 55 % of observed variation in sculpin THg and evidence for downstream transport of Hg in sculpins was weak. Empirical semivariograms indicated these spatial covariates accounted for most spatial autocorrelation in observed THg. Watershed geology and slope explained up to 70 % of sculpin THg variation when SSNMs accounted for instream spatial dependence. Our results provide network-wide predictions for fish tissue THg based largely on publicly available geospatial data and open-source software for SSNMs, and demonstrate how these emerging models can be used to understand contaminant behavior in spatially complex aquatic ecosystems.

Evidence of deviations between experimental and empirical mixing lengths: Multi-discharge field tests in an arid river system

Despite advances in wastewater treatment plant (WWTP) efficiencies, multiple contaminants of concern, such as microplastics, pharmaceuticals, and per- and poly-fluoroalkyl substances (PFAS) remain largely untreated near discharge points and can be highly concentrated before they are fully mixed within the receiving river. Environmental agencies enforce mixing zone permits for the temporary exceedance of water quality parameters beyond targeted control levels under the assumption that contaminants are well-mixed and diluted downstream of mixing lengths, which are typically quantified using empirical equations derived from one-dimensional transport models. Most of these equations were developed in the 1970s and have been assumed to be standard practice since then. However, their development and validation lacked the technological advances required to test them in the field and under changing flow conditions. While new monitoring techniques such as remote sensing and infrared imaging have been employed to visualize mixing lengths and test the validity of empirical equations, those methods cannot be easily repeated due to high costs or flight restrictions. We investigated the application of Lagrangian and Eulerian monitoring approaches to experimentally quantify mixing lengths downstream of a WWTP discharging into the Rio Grande near Albuquerque, New Mexico (USA). Our data spans river to WWTP discharges ranging between 2-22x, thus providing a unique dataset to test long-standing empirical equations in the field. Our results consistently show empirical equations could not describe our experimental mixing lengths. Specifically, while our experimental data revealed "bell-shaped" mixing lengths as a function of increasing river discharges, all empirical equations predicted monotonically increasing mixing lengths. Those mismatches between experimental and empirical mixing lengths are likely due to the existence of threshold processes defining mixing at different flow regimes, i.e., jet diffusion at low flows, the Coanda effect at intermediate flows, and turbulent mixing at higher flows, which are unaccounted for by the one-dimensional empirical formulas. Our results call for a review of the use of empirical mixing lengths in streams and rivers to avoid widespread exposures to emerging contaminants.

Heterogeneity in post-fire thermal responses across Pacific Northwest streams: A multi-site study

Over the past century, water temperatures in many streams across the Pacific Northwest (PNW) have steadily risen, shrinking endangered salmonid habitats. The warming of PNW stream reaches can be further accelerated by wildfires burning forest stands that provide shade to streams. However, previous research on the effect of wildfires on stream water temperatures has focused on individual streams or burn events, limiting our understanding of the diversity in post-fire thermal responses across PNW streams. To bridge this knowledge gap, we assessed the impact of wildfires on daily summer water temperatures across 31 PNW stream sites, where 10-100% of their riparian area burned. To ensure robustness of our results, we employed multiple approaches to characterize and quantify fire effects on post-fire stream water temperature changes. Averaged across the 31 burned sites, wildfires corresponded to a 0.3 - 1°C increase in daily summer water temperatures over the subsequent three years. Nonetheless, post-fire summer thermal responses displayed extensive heterogeneity across burned sites where the likelihood and rate of a post-fire summer water temperature warming was higher for stream sites with greater proportion of their riparian area burned under high severity. Also, watershed features such as basin area, post-fire weather, bedrock permeability, pre-fire riparian forest cover, and winter snowpack depth were identified as strong predictors of the post-fire summer water temperature responses across burned sites. Our study offers a multi-site perspective on the effect of wildfires on summer stream temperatures in the PNW, providing insights that can inform freshwater management efforts beyond individual streams and basins.

Modeling instream temperature from solar insolation under varying timber harvesting intensities using RPAS laser scanning

Stream temperatures are influenced by the amount of solar insolation they receive. Increasing stream temperatures associated with climate warming pose detrimental health risks to freshwater ecosystems. In British Columbia (BC), Canada, timber harvesting along forested streams is managed using riparian buffer zones of varying widths and designations. Within buffer zones, depending on distance from the stream, selective thinning may be permitted or harvest may be forbidden. In this study, we used airborne laser scanning (ALS) point cloud data acquired via a remotely piloted aircraft system (RPAS) to derive forest canopy characteristics that were then used to estimate daily incoming summer and fall solar insolation for five stream reaches in coastal conifer-dominated temperate forests in Vancouver Island, BC, Canada. We then examined empirical relationships between estimated insolation and actual instream temperature measurements. Based on these empirical relationships, the potential effects of timber harvest on instream temperatures were simulated by comparing scenarios of different riparian forest harvest intensities. Our results indicated that modeled solar insolation explained 43-90 % of the variation in observed stream reach temperatures, and furthermore, when a single cold-water stream reach was excluded explained an overall 81 % of variation. Simulated harvesting scenarios generally projected increases in maximum stream reach temperatures 1-2 °C in summer and early fall months. However, in a full clearcut scenario (i.e. where all trees were removed), maximum stream reach temperatures increased as much as 5.8 °C. Our results emphasize the importance of retaining riparian vegetation for the maintenance of habitable temperatures for freshwater-reliant fish with thermal restrictions. In addition, we demonstrate the feasibility of RPAS-based monitoring of stream reach shading and canopy cover, enabling detailed assessment of environmental stressors faced by fish populations under climate warming.

Empirical evidence of climate change and urbanization impacts on warming stream temperatures

Climate change and urbanization threaten streams and the biodiversity that rely upon them worldwide. Emissions of greenhouse gases are causing air and sea surface temperatures to increase, and even small areas of urbanization are degrading stream biodiversity, water quality and hydrology. However, empirical evidence of how increasing air temperatures and urbanization together affect stream temperatures over time and their relative influence on stream temperatures is limited. This study quantifies changes in stream temperatures in a region in South-East Australia with an urban-agricultural-forest landcover gradient and where increasing air temperatures have been observed. Using Random Forest models we identify air temperature and urbanization drive increasing stream temperatures and that their combined effects are larger than their individual effects occurring alone. Furthermore, we identify potential mitigation measures useful for waterway managers and policy makers. The results show that both local and global solutions are needed to reduce future increases to stream temperature.

Physicochemical properties of mountain streams in the High and Western Tatras

The aim of this study was to measure the physicochemical properties of 28 mountain streams in Tatra National Park, Slovakia. Sampling sites (119) were selected based on a previous study conducted in 2010. Physical properties (e.g., temperature, conductivity, total dissolved solids, pH, and dissolved oxygen) and chemical components (e.g., nitrogen oxides, ammonia oxides, chloride compounds, and chemical oxygen demand) of the water were determined. Environmental parameters of streams (elevation, slope, aspect, width, depth, flow accumulation, watershed size, bedrock, and presence of mountain lakes) at sampling sites were examined. While comparing results from both periods (2010 and 2017), we found a correlation in data trends, concluding that elevation plays a significant role in almost all investigated parameters. Downstream, streams were more saturated by dissolved solids, CaCO3, and nitrates, increasing the pH level. Despite this well-known trend, we observed significant higher levels of ammonias and chlorides in the alpine zone, especially at sites where higher water temperature and lower values of dissolved oxygen were observed. This occurred in the Eastern Tatras, below mountain lakes, and where watersheds had granite origins. There are indications that denitrification processes were significantly stronger in 2017, but, on the other hand, increased chlorides resulted in stronger inhibition of nitrification processes in alpine zones at sites below mountain lakes.

Spatial analysis for interval-valued data

Symbolic data analysis deals with complex data with symbolic objects, such as lists, histograms, and intervals. Spatial analysis for symbolic data is relatively underexplored. To fill the gap, this paper proposes a statistical framework for spatial interval-valued data (SIVD) analysis. We provide geostatistical methods for spatial prediction, predictive performance measure for prediction assessment, and visualization for mapping SIVD. The proposed methods are illustrated with both simulated and real examples.

Elevation-dependent intensification of fire danger in the western United States

Studies have identified elevation-dependent warming trends, but investigations of such trends in fire danger are absent in the literature. Here, we demonstrate that while there have been widespread increases in fire danger across the mountainous western US from 1979 to 2020, trends were most acute at high-elevation regions above 3000 m. The greatest increase in the number of days conducive to large fires occurred at 2500-3000 m, adding 63 critical fire danger days between 1979 and 2020. This includes 22 critical fire danger days occurring outside the warm season (May-September). Furthermore, our findings indicate increased elevational synchronization of fire danger in western US mountains, which can facilitate increased geographic opportunities for ignitions and fire spread that further complicate fire management operations. We hypothesize that several physical mechanisms underpinned the observed trends, including elevationally disparate impacts of earlier snowmelt, intensified land-atmosphere feedbacks, irrigation, and aerosols, in addition to widespread warming/drying.

Multi-scale variability of hydrothermal regime based on wavelet analysis - The middle reaches of the Yangtze River, China

Water temperature is a major driver of riverine ecosystems and has an extremely significant impact on them. Understanding the multi-scale water temperature dynamics in a river basin is critical to analyze the water temperature status of rivers. In this study, the intra-annual and inter-annual time series of water temperature (WT) at Yichang station in the middle reaches of the Yangtze River over the past 62 years was analyzed using complex Morlet wavelet functions to reveal the complex structure of water temperature variation at multiple time scales. The ecological impact of water temperature changes on the reproduction of the "Four Major Chinese Carp" under the influence of the Three Gorges Dam (TGD). The results showed that the water temperature at Yichang Station has a multi-level time scale structure, with an increasing trend at the inter-annual scale from 1956 to 2017, but different variations at the seasonal scale, and the water temperature cycles at both the inter-annual and seasonal scales have time scale variations of about 8-14 years and 4-7 years, with obvious characteristics of WT variation stages. The inter-annual and summer scales will have low WT in 2017-2022 and high WT in 2023-2027, while the other seasonal scales will have high WT in the next few years, either in the short or medium term. The correlation between air temperature and WT is the most significant among the three drivers of air temperature, flow and rainfall, and the correlation between WT and the air temperature is the most significant in winter scale under the influence of the Three Gorges Dam construction. Since the completion of TGD in 2003, the summer drainage temperature has decreased and the breeding period of the "Four Major Chinese Carp" has been shortened by 30-40 days compared to that before the construction of TGD. The results of this study can be used as a basis for further exploration of the formation mechanism of river water temperature and provide a scientific basis for river ecological protection.

Riparian vegetation shade restoration and loss effects on recent and future stream temperatures

River temperatures are expected to increase this century harming species requiring cold-water habitat unless restoration activities protect or improve habitat availability. Local shading by riparian vegetation can cool water temperatures, but uncertainty exists over the scaling of this local effect to larger spatial extents. We evaluate this issue using a regional spatial stream network temperature model with covariates representing shade effects to predict mean August stream temperatures across 78,195 km of tributaries flowing into the Columbia River in the northwestern US. We evaluate nine scenarios predicting stream temperatures for three riparian shade conditions (current, restored, and no riparian vegetation) within three different climate periods (2000s, 2040s, and 2080s). Results suggest riparian shade restoration (2000s climate) could decrease mean August stream temperatures by 0.62°C across the study network. Under the same restored shade conditions, temperature predictions for tributaries at their confluence with the Columbia River range from 0.02-2.08°C cooler than under current shade conditions. The climate warming effect predicted for the 2040s and 2080s, however, is greater than the cooling effect from restoring riparian shade. Streams less than 10m bankfull width cooled more frequently with riparian shade restoration. In Oregon, the proportion of fish habitat for salmon and trout rearing and migration that meet temperature numeric water quality criteria could be increased by 20% under restored shade conditions although net habitat declines may still occur in the future. We conclude riparian vegetation restoration could partially mitigate future warming and help maintain cold-water habitats that function as thermal refuges if implemented strategically.

Variable wildfire impacts on the seasonal water temperatures of western US streams: A retrospective study

Recent increases in the burn area and severity of wildfires in the western US have raised concerns about the impact on stream water temperature–a key determinant of cold-water fish habitats. However, the effect on seasonal water temperatures of concern, including winter and summer, are not fully understood. In this study, we assessed the impact of wildfire burns at Boulder Creek (Oregon), Elk Creek (Oregon), and Gibbon River (Wyoming) watersheds on the downstream winter and summer water temperatures for the first three post-fire years. To obtain results independent of the choice of the analytical method, we evaluated the consequence of each burn using three different statistical approaches that utilize local water temperature data. Our results from the three approaches indicated that the response of water temperatures to wildfire burns varied across seasons and sites. Wildfire burns were associated with a median increase of up to 0.56°C (Standard Error; S.E. < 0.23°C) in the summer mean water temperatures (MWT) and 62 degree-day Celsius (DDC; S.E. < 20.7 DDC) in the summer accumulated degree days (ADD) for the three subsequent years across studied stream sites. Interestingly, these burns also corresponded to a median decrease of up to 0.49°C (S.E. < 0.45°C) in the winter MWT and 39 DDC (S.E. < 40.5 DDC) in the winter ADD for the same period across sites. Wildfire effects on the downstream water temperatures diminished with increasing site distance from the burn perimeter. Our analyses demonstrated that analytical methods that utilize local watershed data could be applied to evaluate fire effects on downstream water temperatures.

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.

Temperature Modeling, a Key to Assessing Impact on Rivers Due to Urbanization and Climate Change

With widespread ongoing urbanization and as climate change continues, the importance of protecting the water quality of streams and lakes is intensifying. However, while many water quality constituents in lakes and rivers are of overall interest, water temperature is a ‘key’ variable as temperature influences mixing within a waterbody, influences the acceptability of the habitat for flora and fauna, and serves as a guide to the general health of a stream. To enable the assessment, a physics-based, deterministic hydraulic and heat-balance modeling procedure using the combination of MIKE SHE, MIKE HYDRO and ECO Lab is described to assess heat transfer magnitudes in portions of the Credit River, Ontario. Changes in instream temperature regimes are examined, including both frequency and spatial extent, providing insights into the impacts of urbanization in terms of seasonal temperature shifts arising from land use changes. For flow and temperature regimes, Nash–Sutcliffe model efficiency coefficient (NSE) values of 0.49 and 0.955 were achieved, respectively, for current threshold conditions. Durations of temperature increases from threshold levels indicate that land use changes from current agriculture conditions to urbanization may change stream water temperatures for 9% of the time by 1 °C, and 2% of the time by 2 °C for distances of 1000 m downstream, because of land use change from agriculture to low-density urbanization, and for 20% of the time by 1 °C, and 4% of the time by 2 °C at distances of 1000 m downstream with land use change to high-density urbanization. With climate change RCP 4.5 Scenario in 2050 (Base, for a Wet Year—2017), the continuous amount of time the stream water temperature remains at elevated temperatures of more than 3 °C (from 5000 m to 25,607 m from the most upstream point of Fletchers Creek) for a distance of 20,000 m is more than 13 h. These elevations in temperature may have serious implications for flora and fauna in the creek, particularly impacting the cold-water and mixed-water fish species.

Hydroclimatic Conditions, Wildfire, and Species Assemblages Influence Co-Occurrence of Bull Trout and Tailed Frogs in Northern Rocky Mountain Streams

Although bull trout (Salvelinus confluentus) and tailed frogs (Ascaphus montanus) have co-existed in forested Pacific Northwest streams for millennia, these iconic cold-water specialists are experiencing rapid environmental change caused by a warming climate and enhanced wildfire activity. Our goal was to inform future conservation by examining the habitat associations of each species and conditions that facilitate co-occupancy. We repurposed data from previous studies in the northern Rocky Mountains to assess the efficacy of bull trout electrofishing surveys for determining the occurrence of tailed frogs and the predictive capacity of habitat covariates derived from in-stream measurements and geospatial sources to model distributions of both species. Electrofishing reliably detected frog presence (89.2% rate). Both species were strongly associated with stream temperature and flow regime characteristics, and less responsive to riparian canopy cover, slope, and other salmonids. Tailed frogs were also sensitive to wildfire, with occupancy probability peaking around 80 years after a fire. Co-occupancy was most probable in locations with low-to-moderate frequencies of high winter flow events, few other salmonids, a low base-flow index, and intermediate years since fire. The distributions of these species appear to be sensitive to environmental conditions that are changing this century in forests of the northern Rocky Mountains. The amplification of climate-driven effects after wildfire may prove to be particularly problematic in the future. Habitat differences between these two species, considered to be headwater specialists, suggest that conservation measures designed for one may not fully protect the other. Additional studies involving future climate and wildfire scenarios are needed to assess broader conservation strategies and the potential to identify refuge streams where both species are likely to persist, or complementary streams where each could exist separately into the future.

An Assessment of the Impacts of Snowmelt Rate and Continuity Shifts on Streamflow Dynamics in Three Alpine Watersheds in the Western U.S

In semiarid to arid regions of the western U.S., river flow availability and variability are highly subject to shifts in snow accumulation and ablation in alpine watersheds. This study aims to examine how shifts in snowmelt rate (SMR) and snow continuity, an indicator of the consistent existence of snow on the ground, affect snow-driven streamflow dynamics in three alpine watersheds in the U.S. Great Basin. To achieve this end, the coupled hydro-ecological simulation system (CHESS) is used to simulate river flow dynamics, and multiple snow metrics are calculated to quantify the variation of SMR and snow continuity, the latter of which is measured by snow persistence (SP), snow residence time (SRT), and snow season length (SSL). Then, a new approach is proposed to partition streamflow into snow-driven and rain-driven streamflow. The statistical analyses indicate that the three alpine watersheds experienced a downward trend in SP, SRT, SSL, and SMR during the study period of 1990–2016 due to regional warming. As a result, the decrease in SMR and the decline in snow continuity shifted the occurrence day of 25% and 50% of the snow-driven cumulative discharge, as well as peak discharge, toward an earlier occurrence. Moreover, the magnitudes of snow-driven annual streamflow, summer baseflow, and peak discharge also decreased due to the declined snow continuity and the reduced SMR. Overall, by using multiple snow and flow metrics, and by partitioning streamflow into snow-driven and rain-driven flow via the newly proposed approach, we found that SMR and snow continuity determine the streamflow hydrographs and magnitudes in the three alpine watersheds. Given that warming can significantly affect snow dynamics in alpine watersheds in semiarid to arid regions, this has important implications for water resource management in the snow-dominated region when facing future climate warming.

Stream Temperature Predictions for River Basin Management in the Pacific Northwest and Mid-Atlantic Regions Using Machine Learning

Stream temperature (Ts) is an important water quality parameter that affects ecosystem health and human water use for beneficial purposes. Accurate Ts predictions at different spatial and temporal scales can inform water management decisions that account for the effects of changing climate and extreme events. In particular, widespread predictions of Ts in unmonitored stream reaches can enable decision makers to be responsive to changes caused by unforeseen disturbances. In this study, we demonstrate the use of classical machine learning (ML) models, support vector regression and gradient boosted trees (XGBoost), for monthly Ts predictions in 78 pristine and human-impacted catchments of the Mid-Atlantic and Pacific Northwest hydrologic regions spanning different geologies, climate, and land use. The ML models were trained using long-term monitoring data from 1980–2020 for three scenarios: (1) temporal predictions at a single site, (2) temporal predictions for multiple sites within a region, and (3) spatiotemporal predictions in unmonitored basins (PUB). In the first two scenarios, the ML models predicted Ts with median root mean squared errors (RMSE) of 0.69–0.84 °C and 0.92–1.02 °C across different model types for the temporal predictions at single and multiple sites respectively. For the PUB scenario, we used a bootstrap aggregation approach using models trained with different subsets of data, for which an ensemble XGBoost implementation outperformed all other modeling configurations (median RMSE 0.62 °C).The ML models improved median monthly Ts estimates compared to baseline statistical multi-linear regression models by 15–48% depending on the site and scenario. Air temperature was found to be the primary driver of monthly Ts for all sites, with secondary influence of month of the year (seasonality) and solar radiation, while discharge was a significant predictor at only 10 sites. The predictive performance of the ML models was robust to configuration changes in model setup and inputs, but was influenced by the distance to the nearest dam with RMSE <1 °C at sites situated greater than 16 and 44 km from a dam for the temporal single site and regional scenarios, and over 1.4 km from a dam for the PUB scenario. Our results show that classical ML models with solely meteorological inputs can be used for spatial and temporal predictions of monthly Ts in pristine and managed basins with reasonable (<1 °C) accuracy for most locations.

Which environmental factors control extreme thermal events in rivers? A multi-scale approach (Wallonia, Belgium)

Managers need to know how to mitigate rising stream water temperature (WT) due to climate change. This requires identifying the environmental drivers that influence thermal regime and determining the spatial area where interventions are most effective. We hypothesized that (i) extreme thermal events can be influenced by a set of environmental factors that reduce thermal sensitivity and (ii) the role played by those factors varies spatially. To test these hypotheses, we (i) determined which of the environmental variables reported to be the most influential affected WT and (ii)identified the spatial scales over which those environmental variables influenced WT. To this end, the influence of multi-scale environmental variables, namely land cover, topography (channel slope, elevation), hydromorphology (channel sinuosity, water level, watershed area, baseflow index) and shade conditions, was analyzed on the three model variables (day thermal sensitivity, night thermal sensitivity, and non-convective thermal flux) in the model developed by Georges et al. (2021) of the temporal thermal dynamics of daily maximum WT during extreme events. Values were calculated on six spatial scales (the entire upstream catchment and the associated 1 km and 2 km circular buffer, and 50 m wide corridors on each side of the stream with the associated 1 km and 2 km circular buffer). The period considered was 17 extreme days during the summer identified by Georges et al. (2021) based on WT data measured every 10 min for 7 years (2012-2018) at 92 measurement sites. Sites were located evenly throughout the Wallonia (southern Belgium) hydrological network. Results showed that shade, baseflow index (a proxy of the influence of groundwater), water level and watershed area were the most significant variables influencing thermal sensitivity. Since managers with finite financial and human resources can act on only a few environmental variables, we advocate restoring and preserving the vegetation cover that limits solar radiation on the watercourse as a cost-effective solution to reduce thermal sensitivity. Moreover, management at small spatial scale (50 m riparian buffer) should be strategically promoted (for finance and staffing) as our results show that a larger management scale is not more effective in reducing thermal sensitivity to extreme events.

Wildfire and climate change adaptation of western North American forests: a case for intentional management

Forest landscapes across western North America (wNA) have experienced extensive changes over the last two centuries, while climatic warming has become a global reality over the last four decades. Resulting interactions between historical increases in forested area and density and recent rapid warming, increasing insect mortality, and wildfire burned areas, are now leading to substantial abrupt landscape alterations. These outcomes are forcing forest planners and managers to identify strategies that can modify future outcomes that are ecologically and/or socially undesirable. Past forest management, including widespread harvest of fire- and climate-tolerant large old trees and old forests, fire exclusion (both Indigenous and lightning ignitions), and highly effective wildfire suppression have contributed to the current state of wNA forests. These practices were successful at meeting short-term demands, but they match poorly to modern realities. Hagmann et al. review a century of observations and multi-scale, multi-proxy, research evidence that details widespread changes in forested landscapes and wildfire regimes since the influx of European colonists. Over the preceding 10 millennia, large areas of wNA were already settled and proactively managed with intentional burning by Indigenous tribes. Prichard et al. then review the research on management practices historically applied by Indigenous tribes and currently applied by some managers to intentionally manage forests for resilient conditions. They address 10 questions surrounding the application and relevance of these management practices. Here, we highlight the main findings of both papers and offer recommendations for management. We discuss progress paralysis that often occurs with strict adherence to the precautionary principle; offer insights for dealing with the common problem of irreducible uncertainty and suggestions for reframing management and policy direction; and identify key knowledge gaps and research needs.

Clair SI, Bratsman S, Merritt M, Norris AJ, Carling GT, Hansen N, St. Clair SB, Abbott BW. Megafire affects stream sediment flux and dissolved organic matter reactivity, but land use dominates nutrient dynamics in semiarid watersheds

Climate change is causing larger wildfires and more extreme precipitation events in many regions. As these ecological disturbances increasingly coincide, they alter lateral fluxes of sediment, organic matter, and nutrients. Here, we report the stream chemistry response of watersheds in a semiarid region of Utah (USA) that were affected by a megafire followed by an extreme precipitation event in October 2018. We analyzed daily to hourly water samples at 10 stream locations from before the storm event until three weeks after its conclusion for suspended sediment, solute and nutrient concentrations, water isotopes, and dissolved organic matter concentration, optical properties, and reactivity. The megafire caused a ~2,000-fold increase in sediment flux and a ~6,000-fold increase in particulate carbon and nitrogen flux over the course of the storm. Unexpectedly, dissolved organic carbon (DOC) concentration was 2.1-fold higher in burned watersheds, despite the decreased organic matter from the fire. DOC from burned watersheds was 1.3-fold more biodegradable and 2.0-fold more photodegradable than in unburned watersheds based on 28-day dark and light incubations. Regardless of burn status, nutrient concentrations were higher in watersheds with greater urban and agricultural land use. Likewise, human land use had a greater effect than megafire on apparent hydrological residence time, with rapid stormwater signals in urban and agricultural areas but a gradual stormwater pulse in areas without direct human influence. These findings highlight how megafires and intense rainfall increase short-term particulate flux and alter organic matter concentration and characteristics. However, in contrast with previous research, which has largely focused on burned-unburned comparisons in pristine watersheds, we found that direct human influence exerted a primary control on nutrient status. Reducing anthropogenic nutrient sources could therefore increase socioecological resilience of surface water networks to changing wildfire regimes.

Some (Fish Might) Like It Hot: Habitat Quality and Fish Growth from Past to Future Climates

Current expectation is that projected climate change may have adverse effects on fish habitats and survival. The analysis leading to these concerns is typically done at large scale with limited possibility to quantify the local biological response and compare with previous conditions. Our research investigated the effects of recorded climate conditions on Chinook salmon (Oncorhynchus tshawytscha) spawning and rearing habitats and growth responses to the local climate and compared those conditions to predicted responses to a climate change. The study site was a 7 km long reach of Bear Valley Creek, an important spawning stream for this US Endangered Species Act listed species, in the Pacific Northwest of United States. We used 2D numerical modeling supported by accurate, high-resolution survey data to calculate flow hydraulics at various discharges from base to bankfull flows. For past and future conditions, computed flow hydraulics were combined with habitat suitability indices (SI) to compute spawning and rearing habitat suitability. Information on habitat suitability along with fish density and stream water temperature informed a growth model to quantify the potential fish size, an index of survival rates and fitness. Our results indicate that yearly-averaged rearing habitat quality remains similar to historic, but the timing of high- and low-quality habitat periods shift within the calendar year. Future spawning habitat quality may be significantly reduced during the seasonal period to which Chinook have currently adapted their spawning behavior. The growth model indicates an increase in anticipated size of Chinook salmon for predicted future climate conditions due to water temperature increase. Consequently, future climate conditions may have a substantial negative impact on spawning and limited impact on rearing conditions due to flow reduction and thus quality and extent of available habitat. However, the expected warmer stream water temperatures may benefit rearing, because of increased fish size in these high elevation streams.

Can Landsat Thermal Imagery and Environmental Data Accurately Estimate Water Temperatures in Small Streams?

The ability to monitor water temperature is important for assessing changes in riverine ecosystems resulting from climate warming. Direct in situ water temperature collection efforts provide point samples but are cost-prohibitive for characterizing stream temperatures across large spatial scales, especially for small, remote streams. In contrast, satellite thermal infrared imagery may provide a spatially extensive means of monitoring riverine water temperatures; however, researchers do not have a good understanding of the accuracy of these remotely sensed temperatures for small streams. Here, we investigated the utility of Landsat 8 thermal infrared imagery and both local and regional environmental variables to estimate subsurface temperatures in high-latitude small streams (2–30 m wetted width) from a test watershed in southcentral Alaska. Our results suggested that Landsat-based surface temperatures were biased high, and the degree of bias varied with hydrological and meteorological factors. However, with limited in-stream validation work, results indicated it is possible to reconstruct average in situ water temperatures for small streams at regional scales using a regression modelling framework coupled with publicly available Landsat or air temperature information. Generalized additive models built from stream stage information from a single gage and air temperatures from a single weather station in the drainage fit to a limited set of in situ temperature recordings could estimate average stream temperatures at the watershed level with reasonable accuracy (root mean square error = 2.4°C). Landsat information did track closely with regional air temperatures and we could also incorporate it into a regression model as a substitute for air temperature to estimate in situ stream temperatures at watershed scales. Importantly, however, while average watershed-scale stream temperatures may be predictable, site-level estimates did not improve with the use of Landsat information or other local covariates, indicating that additional information may be necessary to generate accurate spatially explicit temperature predictions for small order streams.

Warming enabled upslope advance in western US forest fires

Forest fires of the western United States have advanced upslope over the past few decades, scorching territories previously too wet to burn. We document an upslope advancement of high-elevation fires of 7.6 m/y, a rate comparable to the elevational velocity of vapor pressure deficit of 8.9 m/y. Strong interannual links between aridity and high-elevation forest fires and reduced influence of fire exclusion policies in montane mesic forests imply such changes are a byproduct of climate warming. We estimate that increased aridity between 1984 and 2017 exposed an additional 81,500 km² of western US montane forests to fires. These changes have significant implications for terrestrial carbon storage, snowpack, and water quantity and quality.

Increases in burned area and large fire occurrence are widely documented over the western United States over the past half century. Here, we focus on the elevational distribution of forest fires in mountainous ecoregions of the western United States and show the largest increase rates in burned area above 2,500 m during 1984 to 2017. Furthermore, we show that high-elevation fires advanced upslope with a median cumulative change of 252 m (−107 to 656 m; 95% CI) in 34 y across studied ecoregions. We also document a strong interannual relationship between high-elevation fires and warm season vapor pressure deficit (VPD). The upslope advance of fires is consistent with observed warming reflected by a median upslope drift of VPD isolines of 295 m (59 to 704 m; 95% CI) during 1984 to 2017. These findings allow us to estimate that recent climate trends reduced the high-elevation flammability barrier and enabled fires in an additional 11% of western forests. Limited influences of fire management practices and longer fire-return intervals in these montane mesic systems suggest these changes are largely a byproduct of climate warming. Further weakening in the high-elevation flammability barrier with continued warming has the potential to transform montane fire regimes with numerous implications for ecosystems and watersheds.

Long-term nationwide spatiotemporal changes of freshwater temperature in Japan during 1982-2016

We analyzed freshwater temperature data from 1982 to 2016 throughout Japan to better understand how waters are warming in Japan. We used linear regression to determine the temperature change rate and Mann-Kendall tests to identify significant temporal trends in the annual maximum and mean temperatures. Among 11,240 monitoring sites screened, 159 with fewer missing values were selected for analysis. On the basis of this analysis, we identified and ranked the sites showing significant temporal increasing or decreasing trends for future management. At nearly half (42%) of the analyzed sites, the annual mean freshwater temperature was increasing; thus, in the future, adverse impacts from warm temperatures may increase in those aquatic ecosystems. The temperature change rate of fresh water was higher than that of air, indicating that the observed increases in freshwater temperature were not due to atmospheric warming only. Among individual sites, the annual maximum freshwater temperature change rate ranged from -1.27 to 1.91 °C/decade, and the annual mean rate ranged from -1.13 to 1.28 °C/decade. Few other studies have reported decreasing temperatures for fresh water. We expect our results will improve understanding of how freshwater temperatures are changing at a large scale, enhance understanding of human impacts on the aquatic environment, support effective management of ecosystems experiencing temperature changes, and help to minimize the loss of biodiversity over the next half century.

Towards more integration of physiology, dispersal and land-use change to understand the responses of species to climate change

The accelerating biodiversity crisis, for which climate change has become an important driver, urges the scientific community for answers to the question of whether and how species are capable of responding successfully to rapidly changing climatic conditions. For a better understanding and more realistic predictions of species' and biodiversity responses, the consideration of extrinsic (i.e. environment-related) and intrinsic (i.e. organism-related) factors is important, among which four appear to be particularly crucial: climate change and land-use change, as extrinsic factors, as well as physiology and dispersal capacity, as intrinsic factors. Here, I argue that these four factors should be considered in an integrative way, but that the scientific community has not yet been very successful in doing so. A quantitative literature review revealed a generally low level of integration within global change biology, with a pronounced gap especially between the field of physiology and other (sub)disciplines. After a discussion of potential reasons for this unfortunate lack of integration, some of which may relate to key deficits e.g. in the reward and incentive systems of academia, I suggest a few ideas that might help to overcome some of the barriers between separated research communities. Furthermore, I list several examples for promising research along the integration frontier, after which I outline some research questions that could become relevant if one is to push the boundary of integration among disciplines, of data and methods, and across scales even further - for a better understanding and more reliable predictions of species and biodiversity in a world of global change.

Thermal sensitivity and flow-mediated migratory delays drive climate risk for coastal sockeye salmon

Climate change is subjecting aquatic species to increasing temperatures and shifting hydrologic conditions. Understanding how these changes affect individual survival can help guide conservation and management actions. Anadromous Pacific salmon ( Oncorhynchus spp.) in some large river systems are acutely impacted by the river temperatures and flows encountered during their spawning migrations. However, comparatively little is known about drivers of en route mortality for salmon in smaller coastal watersheds, and climate impacts may differ across watersheds and locally adapted salmon populations. To understand the effects of climate on the survival of coastal sockeye salmon ( Oncorhynchus nerka; hísn in Haíɫzaqv), we tagged 1785 individual fish with passive integrated transponders across four migration seasons in the Koeye River—a low-elevation watershed in coastal British Columbia—and tracked them during their relatively short migration (∼13 km) from river entry to spawning grounds. Overall, 64.7% of sockeye survived to enter the spawning grounds, and survival decreased rapidly when water temperatures exceeded 15 °C. The best-fitting model included an interaction between river flow and temperature, such that temperature effects were worse when flows were low, and river entry ceased at the lowest flows. Results revealed temperature-mediated mortality and migration delays from low water that may synergistically reduce survival among sockeye salmon returning to coastal watersheds.

Landscape resistance mediates native fish species distribution shifts and vulnerability to climate change in riverscapes

A broader understanding of how landscape resistance influences climate change vulnerability for many species is needed, as is an understanding of how barriers to dispersal may impact vulnerability. Freshwater biodiversity is at particular risk, but previous studies have focused on popular cold-water fishes (e.g., salmon, trout, and char) with relatively large body sizes and mobility. Those fishes may be able to track habitat change more adeptly than less mobile species. Smaller, less mobile fishes are rarely represented in studies demonstrating effects of climate change, but depending on their thermal tolerance, they may be particularly vulnerable to environmental change. By revisiting 280 sites over a 20 year interval throughout a warming riverscape, we described changes in occupancy (i.e., site extirpation and colonization probabilities) and assessed the environmental conditions associated with those changes for four fishes spanning a range of body sizes, thermal and habitat preferences. Two larger-bodied trout species exhibited small changes in site occupancy, with bull trout experiencing a 9.2% (95% CI = 8.3%-10.1%) reduction, mostly in warmer stream reaches, and westslope cutthroat trout experiencing a nonsignificant 1% increase. The small-bodied cool water slimy sculpin was originally distributed broadly throughout the network and experienced a 48.0% (95% CI = 42.0%-54.0%) reduction in site occupancy with declines common in warmer stream reaches and areas subject to wildfire disturbances. The small-bodied comparatively warmer water longnose dace primarily occupied larger streams and increased its occurrence in the lower portions of connected tributaries during the study period. Distribution shifts for sculpin and dace were significantly constrained by barriers, which included anthropogenic water diversions, natural step-pools and cascades in steeper upstream reaches. Our results suggest that aquatic communities exhibit a range of responses to climate change, and that improving passage and fluvial connectivity will be important climate adaptation tactics for conserving aquatic biodiversity.

Concealment of juvenile bull trout in response to temperature, light, and substrate: Implications for detection

Bull trout (Salvelinus confluentus) are challenging to detect as a result of the species cryptic behavior and coloration, relatively low densities in complex habitats, and affinity for cold, high clarity, low conductivity waters. Bull trout are also closely associated with the stream bed, frequently conceal in substrate, and this concealment behavior is poorly understood. Consequently, population assessments are problematic and biologists and managers often lack quantitative information to accurately describe bull trout distributions, estimate abundance, and assess status and trends; particularly for stream-dwelling populations. During controlled laboratory trials, we recorded concealment, resting, and swimming behavior of juvenile wild bull trout in response to: (1) constant and fluctuating water temperature, (2) presence or absence of light, and (3) substrate size. Light level had the strongest influence on wild fish concealment and more fish concealed as light levels increased from darkness to daylight. Wild fish were 14.5 times less likely to conceal in constant darkness and 4.1 times more likely to conceal in 12 h light x 12 h darkness compared to constant light. Wild fish were 6.2 times less likely to conceal in small (26–51 mm) substrate compared to larger (52–102 mm) substrate. As water temperature increased, fewer wild fish concealed. Knowledge of wild bull trout concealment will improve field sampling protocols and increase detection efficiencies. These data also enhance knowledge of bull trout niche requirements which illuminates ecological differences among species and informs conservation and restoration efforts.

Thermal heterogeneity, migration, and consequences for spawning potential of female bull trout in a river-reservoir system

The likelihood that fish will initiate spawning, spawn successfully, or skip spawning in a given year is conditioned in part on availability of energy reserves. We evaluated the consequences of spatial heterogeneity in thermal conditions on the energy accumulation and spawning potential of migratory bull trout (Salvelinus confluentus) in a regulated river-reservoir system. Based on existing data, we identified a portfolio of thermal exposures and migratory patterns and then estimated their influence on energy reserves of female bull trout with a bioenergetics model. Spawning by females was assumed to be possible if postspawning energy reserves equaled or exceeded 4 kJ/g. Given this assumption, results suggested up to 70% of the simulated fish could spawn each year. Fish that moved seasonally between a cold river segment and a warmer reservoir downstream had a greater growth rate and higher propensity to spawn in a given year (range: 40%-70%) compared with fish that resided solely in the cold river segment (25%-40%). On average, fish that spawned lost 30% of their energy content relative to their prespawn energy. In contrast, fish that skipped spawning accumulated, on average, 16% energy gains that could be used toward future gamete production. Skipped spawning occurred when water temperatures were relatively low or high, and if upstream migration occurred relatively late (mid-July or later) or early (early-May or earlier). Overall, our modeling effort suggests the configuration of thermal exposures, and the ability of bull trout to exploit this spatially and temporally variable thermal conditions can strongly influence energy reserves and likelihood of successful spawning.

Use of Multiple Temperature Logger Models Can Alter Conclusions

Remote temperature loggers are often used to measure water temperatures for ecological studies and by regulatory agencies to determine whether water quality standards are being maintained. Equipment specifications are often given a cursory review in the methods; however, the effect of temperature logger model is rarely addressed in the discussion. In a laboratory environment, we compared measurements from three models of temperature loggers at 5 to 40 °C to better understand the utility of these devices. Mean water temperatures recorded by logger models differed statistically even for those with similar accuracy specifications, but were still within manufacturer accuracy specifications. Maximum mean temperature difference between models was 0.4 °C which could have regulatory and ecological implications, such as when a 0.3 °C temperature change triggers a water quality violation or increases species mortality rates. Additionally, precision should be reported as the overall precision (including a consideration of significant digits) for combined model types which in our experiment was 0.7 °C, not the ≤0.4 °C for individual models. Our results affirm that analyzing data collected by different logger models can result in potentially erroneous conclusions when <1 °C difference has regulatory compliance or ecological implications and that combining data from multiple logger models can reduce the overall precision of results.

Accurate spatiotemporal predictions of daily stream temperature from statistical models accounting for interactions between climate and landscape

Spatial and temporal patterns in stream temperature are primary factors determining species composition, diversity and productivity in stream ecosystems. The availability of spatially and temporally continuous estimates of stream temperature would improve the ability of biologists to fully explore the effects of stream temperature on biota. Most statistical stream temperature modeling techniques are limited in their ability to account for the influence of variables changing across spatial and temporal gradients. We identified and described important interactions between climate and spatial variables that approximate mechanistic controls on spatiotemporal patterns in stream temperature. With identified relationships we formed models to generate reach-scale basin-wide spatially and temporally continuous predictions of daily mean stream temperature in four Columbia River tributaries watersheds of the Pacific Northwest, USA. Models were validated with a testing dataset composed of completely distinct sites and measurements from different years. While some patterns in residuals remained, testing dataset predictions of selected models demonstrated high accuracy and precision (averaged RMSE for each watershed ranged from 0.85–1.54 °C) and was only 17% higher on average than training dataset prediction error. Aggregating daily predictions to monthly predictions of mean stream temperature reduced prediction error by an average of 23%. The accuracy of predictions was largely consistent across diverse climate years, demonstrating the ability of the models to capture the influences of interannual climatic variability and extend predictions to timeframes with limited temperature logger data. Results suggest that the inclusion of a range of interactions between spatial and climatic variables can approximate dynamic mechanistic controls on stream temperatures.

Acclimation temperature changes spermatozoa flagella length relative to head size in brown trout

Temperature is a ubiquitous environmental factor affecting physiological processes of ectotherms. Due to the effects of climate change on global air and water temperatures, predicting the impacts of changes in environmental thermal conditions on ecosystems is becoming increasingly important. This is especially crucial for migratory fish, such as the ecologically and economically vital salmonids, because their complex life histories make them particularly vulnerable. Here, we addressed the question whether temperature affects the morphology of brown trout, Salmo trutta L. spermatozoa. The fertilising ability of spermatozoa is commonly attributed to their morphological dimensions, thus implying direct impacts on the reproductive success of the male producing the cells. We show that absolute lengths of spermatozoa are not affected by temperature, but spermatozoa from warm acclimated S. trutta males have longer flagella relative to their head size compared to their cold acclimated counterparts. This did not directly affect sperm swimming speed, although spermatozoa from warm acclimated males may have experienced a hydrodynamic advantage at warmer temperatures, as suggested by our calculations of drag based on head size and sperm swimming speed. The results presented here highlight the importance of increasing our knowledge of the effects of temperature on all aspects of salmonid reproduction in order to secure their continued abundance.

Citizen science evidence from the past century shows that Scottish rivers are warming

Salmonid species are highly sensitive to river water temperature. Although long-term river temperature monitoring is essential for assessing drivers of change in ecological systems, these data are rarely available from statutory monitoring. We utilized a 105-year citizen science data set of river water temperature from the River Spey, North-East Scotland, gathered during the fishing season (April-October) between 1912 and 2016. As there were gaps in the records we applied generalised additive models to reconstruct long-term daily river temperature in the fishing season from air temperature, cumulative air temperature, day length and runoff. For that, continuous hydrometeorological data have been obtained from statutory monitoring and process-based models. Long-term warming trends of river temperature, namely an increase of 0.2 K per decade after 1961, have been mostly related to increasing air temperature of the same magnitude. Indirect impacts of rising air temperatures include less snow accumulation and snow melt as well as earlier snow melt. The snow free period starts around 2 days earlier per decade throughout the study period and 7 days earlier per decade after 1965. Consequently, the contribution of snow melt and its cooling properties to river temperature in spring are declining. Citizen science delivered a data set that filled a vital knowledge gap in the long-term historical assessment of river temperatures. Such information provides a robust basis for future assessments of global change and can help inform decision-makers about the potential importance of enhancing the resilience of rivers and aquatic ecology to climate change.

Structured Decision-Making Incorporates Stakeholder Values into Management Decisions Thereby Fulfilling Moral and Legal Obligations to Conserve Species

More than 1,500 species of plants and animals in the United States are listed as threatened or endangered under the Endangered Species Act and habitat destruction is the leading cause of population decline. However, developing conservation plans that are consistent with a diversity of stakeholder (e.g., states, tribes, private landowners) values is difficult. Adaptive management and structured decision-making are frameworks that resource managers can use to integrate diverse and conflicting stakeholder value systems into species recovery planning. Within this framework difficult decisions are deconstructed into the three basic components: explicit, quantifiable objectives that represent stakeholder values; mathematical models used to predict the effect of management decisions on the outcome of objectives; and management alternatives or actions. We use Bull Trout Salvelinus confluentus, a species listed in 1999 as threatened pursuant to the Endangered Species Act, as an example of how structured decision-making transparently incorporates stakeholder values and biological information into conservation planning and the decision process. Three moral philosophies—consequentialism, deontology, and virtue theory—suggest that structured decision-making is a justified method that can guide natural resource decisions in the future, consistent with United States Congress' mandate, and will honor society's obligation to recover Endangered Species Act listed species and their habitats. Natural sciences offer a biological basis for predicting the outcomes of decisions. Additionally, an understanding of how to integrate humanities into scientifically defensible conservation planning is helpful in providing the foundation for lasting and effective species conservation.

Modelling daily water temperature from air temperature for the Missouri River

The bio-chemical and physical characteristics of a river are directly affected by water temperature, which thereby affects the overall health of aquatic ecosystems. It is a complex problem to accurately estimate water temperature. Modelling of river water temperature is usually based on a suitable mathematical model and field measurements of various atmospheric factors. In this article, the air–water temperature relationship of the Missouri River is investigated by developing three different machine learning models (Artificial Neural Network (ANN), Gaussian Process Regression (GPR), and Bootstrap Aggregated Decision Trees (BA-DT)). Standard models (linear regression, non-linear regression, and stochastic models) are also developed and compared to machine learning models. Analyzing the three standard models, the stochastic model clearly outperforms the standard linear model and nonlinear model. All the three machine learning models have comparable results and outperform the stochastic model, with GPR having slightly better results for stations No. 2 and 3, while BA-DT has slightly better results for station No. 1. The machine learning models are very effective tools which can be used for the prediction of daily river temperature.

Dam operations may improve aquatic habitat and offset negative effects of climate change

Dam operation impacts on stream hydraulics and ecological processes are well documented, but their effect depends on geographical regions and varies spatially and temporally. Many studies have quantified their effects on aquatic ecosystem based mostly on flow hydraulics overlooking stream water temperature and climatic conditions. Here, we used an integrated modeling framework, an ecohydraulics virtual watershed, that links catchment hydrology, hydraulics, stream water temperature and aquatic habitat models to test the hypothesis that reservoir management may help to mitigate some impacts caused by climate change on downstream flows and temperature. To address this hypothesis we applied the model to analyze the impact of reservoir operation (regulated flows) on Bull Trout, a cold water obligate salmonid, habitat, against unregulated flows for dry, average, and wet climatic conditions in the South Fork Boise River (SFBR), Idaho, USA.

Monitoring spatial and temporal variation of dissolved oxygen and water temperature in the Savannah River using a sensor network

Dissolved oxygen is a critical component of river water quality. This study investigated average weekly dissolved oxygen (AWDO) and average weekly water temperature (AWT) in the Savannah River during 2015 and 2016 using data from the Intelligent River^® sensor network. Weekly data and seasonal summary statistics revealed distinct seasonal patterns that impact both AWDO and AWT regardless of location along the river. Within seasons, spatial patterns of AWDO and AWT along the river are also evident. Linear mixed effects models indicate that AWT and low and high river flow conditions had a significant impact on AWDO, but added little predictive information to the models. Low and high river flow conditions had a significant impact on AWT, but also added little predictive information to the models. Spatial linear mixed effects models yielded parameter estimates that were effectively the same as non-spatial linear mixed effects models. However, components of variance from spatial linear mixed effects models indicate that 23-32% of the total variance in AWDO and that 12-18% of total variance in AWT can be apportioned to the effect of spatial covariance. These results indicate that location, week, and flow-directional spatial relationships are critically important considerations for investigating relationships between space- and time-varying water quality metrics.

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.

The Potential Impacts of Climate Change on Biodiversity in Flowing Freshwater Systems

Ongoing increases in air temperature and changing precipitation patterns are altering water temperatures and flow regimes in lotic freshwater systems, and these changes are expected to continue in the coming century. Freshwater taxa are responding to these changes at all levels of biological organization. The generation of appropriate hydrologic and water temperature projections is critical to accurately predict the impacts of climate change on freshwater systems in the coming decade. The goal of this review is to provide an overview of how changes in climate affect hydrologic processes and how climate-induced changes in freshwater habitat can impact the life histories and traits of individuals, and the distributions of freshwater populations and biodiversity. Projections of biological responses during the coming century will depend on accurately representing the spatially varying sensitivity of physical systems to changes in climate, as well as acknowledging the spatially varying sensitivity of freshwater taxa to changes in environmental conditions.

Coupling LiDAR and thermal imagery to model the effects of riparian vegetation shade and groundwater inputs on summer river temperature

In the context of global warming, it is important to understand the drivers controlling river temperature in order to mitigate temperature increases. A modeling approach can be useful for quantifying the respective importance of the different drivers, notably groundwater inputs and riparian shading which are potentially critical for reducing summer temperature. In this study, we use a one-dimensional deterministic model to predict summer water temperature at an hourly time step over a 21km reach of the lower Ain River (France). This sinuous gravel-bed river undergoes summer temperature increase with potential impacts on salmonid populations. The model considers heat fluxes at the water-air interface, attenuation of solar radiation by riparian forest, groundwater inputs and hydraulic characteristics of the river. Modeling is performed over two periods of five days during the summers 2010 and 2011. River properties are obtained from hydraulic modeling based on cross-section profiles and water level surveys. We model shadows of the vegetation on the river surface using LiDAR data. Groundwater inputs are determined using airborne thermal infrared (TIR) images and hydrological data. Results indicate that vegetation and groundwater inputs can mitigate high water temperatures during summer. Riparian shading effect is fairly similar between the two periods (-0.26±0.12°C and -0.31±0.18°C). Groundwater input cooling is variable between the two studied periods: when groundwater discharge represents 16% of the river discharge, it cools the river down by 0.68±0.13°C while the effect is very low (0.11±0.01°C) when the groundwater discharge contributes only 2% to the discharge. The effect of shading varies through the day: low in the morning and high during the afternoon and the evening whereas those induced by groundwater inputs is more constant through the day. Overall, the effect of riparian vegetation and groundwater inputs represents about 10% in 2010 and 24% in 2011 of water temperature diurnal amplitudes.