Closing the gap between science and management of cold-water refuges in rivers and streams.

Human activities and climate change threaten coldwater organisms in freshwater ecosystems by causing rivers and streams to warm, increasing the intensity and frequency of warm temperature events, and reducing thermal heterogeneity. Cold-water refuges are discrete patches of relatively cool water that are used by coldwater organisms for thermal relief and short-term survival. Globally, cohesive management approaches are needed that consider interlinked physical, biological, and social factors of cold-water refuges. We review current understanding of cold-water refuges, identify gaps between science and management, and evaluate policies aimed at protecting thermally sensitive species. Existing policies include designating cold-water habitats, restricting fishing during warm periods, and implementing threshold temperature standards or guidelines. However, these policies are rare and uncoordinated across spatial scales and often do not consider input from Indigenous peoples. We propose that cold-water refuges be managed as distinct operational landscape units, which provide a social and ecological context that is relevant at the watershed scale. These operational landscape units provide the foundation for an integrated framework that links science and management by (1) mapping and characterizing cold-water refuges to prioritize management and conservation actions, (2) leveraging existing and new policies, (3) improving coordination across jurisdictions, and (4) implementing adaptive management practices across scales. Our findings show that while there are many opportunities for scientific advancement, the current state of the sciences is sufficient to inform policy and management. Our proposed framework provides a path forward for managing and protecting cold-water refuges using existing and new policies to protect coldwater organisms in the face of global change.

Riverscape approaches in practice: perspectives and applications.

Landscape perspectives in riverine ecology have been undertaken increasingly in the last 30 years, leading aquatic ecologists to develop a diverse set of approaches for conceptualizing, mapping and understanding 'riverscapes'. Spatiotemporally explicit perspectives of rivers and their biota nested within the socio-ecological landscape now provide guiding principles and approaches in inland fisheries and watershed management. During the last two decades, scientific literature on riverscapes has increased rapidly, indicating that the term and associated approaches are serving an important purpose in freshwater science and management. We trace the origins and theoretical foundations of riverscape perspectives and approaches and examine trends in the published literature to assess the state of the science and demonstrate how they are being applied to address recent challenges in the management of riverine ecosystems. We focus on approaches for studying and visualizing rivers and streams with remote sensing, modelling and sampling designs that enable pattern detection as seen from above (e.g. river channel, floodplain, and riparian areas) but also into the water itself (e.g. aquatic organisms and the aqueous environment). Key concepts from landscape ecology that are central to riverscape approaches are heterogeneity, scale (resolution, extent and scope) and connectivity (structural and functional), which underpin spatial and temporal aspects of study design, data collection and analysis. Mapping of physical and biological characteristics of rivers and floodplains with high-resolution, spatially intensive techniques improves understanding of the causes and ecological consequences of spatial patterns at multiple scales. This information is crucial for managing river ecosystems, especially for the successful implementation of conservation, restoration and monitoring programs. Recent advances in remote sensing, field-sampling approaches and geospatial technology are making it increasingly feasible to collect high-resolution data over larger scales in space and time. We highlight challenges and opportunities and discuss future avenues of research with emerging tools that can potentially help to overcome obstacles to collecting, analysing and displaying these data. This synthesis is intended to help researchers and resource managers understand and apply these concepts and approaches to address real-world problems in freshwater management.

River temperature research and practice: Recent challenges and emerging opportunities for managing thermal habitat conditions in stream ecosystems.

There is growing evidence that river temperatures are increasing under climate change, which is expected to be exacerbated by increased abstractions to satisfy human water demands. Water temperature research has experienced crucial advances, both in terms of developing new monitoring and modelling tools, as well as understanding the mechanisms of temperature feedbacks with biogeochemical and ecological processes. However, water practitioners and regulators are challenged with translating the widespread and complex technological, modelling and conceptual advances made in river temperature research into improvements in management practice. This critical review provides a comprehensive overview of recent advances in the state-of-the-art monitoring and modelling tools available to inform ecological research and practice. In so doing, we identify pressing research gaps and suggest paths forward to address practical research and management challenges. The proposed research directions aim to provide new insights into spatio-temporal stream temperature dynamics and unravel drivers and controls of thermal river regimes, including the impacts of changing temperature on metabolism and aquatic biogeochemistry, as well as aquatic organisms. The findings of this review inform future research into ecosystem resilience in the face of thermal degradation and support the development of new management strategies cutting across spatial and temporal scales.

Temporal hydrochemical dynamics of the River Wensum, UK: Observations from long-term high-resolution monitoring (2011-2018).

In 2010, the UK government established the Demonstration Test Catchment (DTC) initiative to evaluate the extent to which on-farm mitigation measures can cost-effectively reduce the impacts of agricultural water pollution on river ecology whilst maintaining food production capacity. A central component of the DTC platform was the establishment of a comprehensive network of automated, web-based sensor technologies to generate high-temporal resolution (30 min) empirical datasets of surface water, groundwater and meteorological parameters over a long period (2011-2018). Utilising 8.9 million water quality measurements generated for the River Wensum, this paper demonstrates how long-term, high-resolution monitoring of hydrochemistry can improve our understanding of the complex temporal dynamics of riverine processes from 30 min to annual timescales. This paper explores the impact of groundwater-surface water interactions on instream pollutant concentrations (principally nitrogen, phosphorus and turbidity) and reveals how varying hydrochemical associations under contrasting flow regimes can elicit important information on the dominant pollution pathways. Furthermore, this paper examines the relationships between agricultural pollutants and precipitation events of varying magnitude, whilst demonstrating how high-resolution data can be utilised to develop conceptual models of hydrochemical processes for contrasting winter and summer seasons. Finally, this paper considers how high-resolution hydrochemical data can be used to increase land manager awareness of environmentally damaging farming operations and encourage the adoption of more water sensitive land management practices.

Drone-based Structure-from-Motion provides accurate forest canopy data to assess shading effects in river temperature models.

Climatic warming will increase river temperature globally, with consequences for cold water-adapted organisms. In regions with low forest cover, elevated river temperature is often associated with a lack of bankside shading. Consequently, river managers have advocated riparian tree planting as a strategy to reduce temperature extremes. However, the effect of riparian shading on river temperature varies substantially between locations. Process-based models can elucidate the relative importance of woodland and other factors driving river temperature and thus improve understanding of spatial variability of the effect of shading, but characterising the spatial distribution and height of riparian tree cover necessary to parameterise these models remains a significant challenge. Here, we document a novel approach that combines Structure-from-Motion (SfM) photogrammetry acquired from a drone to characterise the riparian canopy with a process based temperature model (Heat Source) to simulate the effects of tree shading on river temperature. Our approach was applied in the Girnock Burn, a tributary of the Aberdeenshire Dee, Scotland. Results show that SfM approximates true canopy elevation with a good degree of accuracy (R2 = 0.96) and reveals notable spatial heterogeneity in shading. When these data were incorporated into a process-based temperature model, it was possible to simulate river temperatures with a similarly-high level of accuracy (RMSE <0.7 °C) to a model parameterised using 'conventional' LiDAR tree height data. We subsequently demonstrate the utility of our approach for quantifying the magnitude of shading effects on stream temperature by comparing simulated temperatures against another model from which all riparian woodland has been removed. Our findings highlight drone-based SfM as an effective tool for characterising riparian shading and improving river temperature models. This research provides valuable insights into the effects of riparian woodland on river temperature and the potential of bankside tree planting for climate change adaptation.

Stream temperature under contrasting riparian forest cover: Understanding thermal dynamics and heat exchange processes.

Climate change is likely to increase summer temperatures in many river environments, raising concerns that this will reduce their thermal suitability for a range of freshwater fish species. As a result, river managers have pursued riparian tree planting due to its ability to moderate stream temperatures by providing shading. However, little is known about the relative ability of different riparian forest types to moderate stream temperatures. Further research is therefore necessary to inform best-practise riparian tree planting strategies. This article contrasts stream temperature and energy fluxes under three riparian vegetation types common to Europe: open grassland terrain (OS), semi-natural deciduous woodland (SNS), and commercial conifer plantation (CS). Data was recorded over the course of a year by weather stations installed in each of the vegetation types. Mean daily stream temperature was generally warmest at OS and coolest at CS. Energy gains at all sites were dominated by shortwave radiation, whereas losses where principally due to longwave and latent heat flux. The magnitude of shortwave radiation received at the water surface was strongly dependent upon vegetation type, with OS and SNS woodland sites receiving approximately 6× and 4× (respectively) the incoming solar radiation of CS. Although CS lost less energy through longwave or latent fluxes than the other sites, net surface heat flux was ordered OS>SNS>CS, mirroring the stream temperature results. These findings demonstrate that energy fluxes at the air-water interface vary substantially between different riparian forest types and that stream temperature response to bankside vegetation depends upon the type of vegetation present. These results present new insights into the conditions under which riparian vegetation shading is optimal for the reduction of surface heat fluxes and have important implications for the development of 'best-practice' tree planting strategies to moderate summer temperature extremes in rivers.

Improving representation of riparian vegetation shading in a regional stream temperature model using LiDAR data.

Modelling river temperature at the catchment scale is needed to understand how aquatic communities may adapt to current and projected climate change. In small and medium rivers, riparian vegetation can greatly reduce maximum water temperature by providing shade. It is thus important that river temperature models are able to correctly characterise the impact of this riparian shading. In this study, we describe the use of a spatially-explicit method using LiDAR-derived data for computing the riparian shading on direct and diffuse solar radiation. The resulting data are used in the T-NET one-dimensional stream temperature model to simulate water temperature from August 2007 to July 2014 for 270km of the Loir River, an indirect tributary of the Loire River (France). Validation is achieved with 4 temperature monitoring stations spread along the Loir River. The vegetation characterised with the LiDAR approach provides a cooling effect on maximum daily temperature (Tmax) ranging from 3.0°C (upstream) to 1.3°C (downstream) in late August 2009. Compared to two other riparian shading routines that are less computationally-intensive, the use of our LiDAR-based methodology improves the bias of Tmax simulated by the T-NET model by 0.62°C on average between April and September. However, difference between the shading routines reaches up to 2°C (monthly average) at the upstream-most station. Standard deviation of errors on Tmax is not improved. Computing the impact of riparian vegetation at the hourly timescale using reach-averaged parameters provides results close to the LiDAR-based approach, as long as it is supplied with accurate vegetation cover data. Improving the quality of riparian vegetation data should therefore be a priority to increase the accuracy of stream temperature modelling at the regional scale.