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The winter hydrological period is in transition across the Canadian subarctic, as climate warming is shifting precipitation regimes, thawing permafrost, and altering active layer dynamics, and thus increasing the overall amount, and variability, of winter streamflow. Effects of these changes are poorly understood on the Taiga Shield, which comprises ~20% of North America's permafrost‐covered area, and is characterized by a unique 'fill‐and‐spill' hydrology whereby runoff generation requires the exceedance of lake basin storage thresholds. Here, we assessed lake hydrostatic levels and used trail camera images of icings, which are sheet‐like masses of layered ice that are common manifestations of wintertime flow on the Taiga Shield, to understand landscape controls on winter water movement in this region. We further used paired geochemical measurements to explore how source water characteristics affect icing chemistry, and the degree to which icings may modify the chemical composition of active winter flow. We undertake this work over 2 years, and across watersheds of different sizes and lake basin characteristics. We show that icing growth is driven by hydroclimatic controls that include fill‐and‐spill hydrologic constraints and winter air temperatures, and that pre‐freshet pulses of water flow are common within this landscape. Across winters with variable antecedent precipitation levels, a larger catchment was able to support icing growth via continued runoff generation, while small catchments were not. Icings were often chemically dilute compared with source waters, indicating that solute exclusion may actively enrich geochemical concentrations in flowing water. Across icings, chemical variation appeared related to source water type (groundwater versus lake; lake size) and apparent redox conditions. These results highlight that streamwater hydrology and biogeochemistry can be dynamic during the understudied winter period, and illustrate that icings may alter the composition of wintertime flow as it moves through fluvial networks. [ABSTRACT FROM AUTHOR]

We consider the logistic metapopulation model over a stream network and use the metapopulation growth rate and the total biomass (of the positive equilibrium) as metrics for different aspects of population persistence. Our objective is to find distributions of resources that maximize these persistence measures. We begin our study by considering stream networks consisting of three nodes and prove that the strategy to maximize the total biomass is to concentrate all the resources in the most upstream locations. In contrast, when the diffusion rates are sufficiently small, the metapopulation growth rate is maximized when all resources are concentrated in one of the most downstream locations. These two main results are generalized to stream networks with any number of patches. [ABSTRACT FROM AUTHOR]

Low-order streams contribute to the abiotic and biotic character of large rivers and are renowned for harboring unique forms of aquatic flora and fauna. However, most studies on headwater streams mainly focus on the mainstems and overlook the contribution of the tributary systems. Moreover, low-order streams are generally overlooked in legislation and bioassessment programs, and consequently not protected in many countries. To contribute to the recognition of the ecological importance of low-orders streams, this study focused on determining whether river network characteristics and associated physico-chemical parameters can be used to effectively predict the variabilities in macroinvertebrate assemblage characteristics between first-order and second-order streams in the headwaters of the Nzoia River Basin, Kenya. The study quantified the structural and functional community composition, diversity, similarity, and richness of macroinvertebrate communities between the two river systems. Dissolved oxygen, coarse particulate organic matter, conductivity, stream width, depth, discharge and flow velocity were the main predictors of the diversity and distribution of macroinvertebrates in the first order and second-order streams. The first order streams recorded higher abundance of macroinvertebrates than the second-order streams. Taxa from families Ephydridae, Elmidae, Gomphidae, and genera Euthraulus, Neoperla, Orthothrichia and Prosopistoma were limited to the second-order stream sites while families Ceratopogonidae, Pisuliidae, Dytiscidae and genus Trichosetodes occurred exclusively in the first-order stream sites. Collector-filterers and collector-gatherers were the most abundant functional feeding groups (FFGs) in the two river systems. Scrapers were abundant in the second-order stream while shredders were abundant in the first order streams. The distinctness in the structural and functional composition of macroinvertebrates between the two river systems suggests that linkages among streams in a network as exemplified in the Nzoia River Basin, support and foster biodiversity.

Physics-based models are widely used to study dynamical systems in a variety of scientific and engineering problems. However, these models are necessarily approximations of reality due to incomplete knowledge or excessive complexity in modeling underlying processes. As a result, they often produce biased simulations due to inaccurate parameterizations or approximations used to represent the true physics. In this paper, we aim to build a new physics-guided machine learning framework to monitor dynamical systems. The idea is to use advanced machine learning model to extract complex spatio-temporal data patterns while also incorporating general scientific knowledge embodied in simulated data generated by the physics-based model. To handle the bias in simulated data caused by imperfect parameterization, we propose to extract general physical relations jointly from multiple sets of simulations generated by a physics-based model under different physical parameters. In particular, we develop a spatio-temporal network architecture that uses its gating variables to capture the variation of physical parameters. We initialize this model using a pre-training strategy that helps discover common physical patterns shared by different sets of simulated data. Then, we fine-tune it combining limited observations and adequate simulations. By leveraging the complementary strength of machine learning and domain knowledge, our method has been shown to produce accurate predictions, use less training samples and generalize to out-of-sample scenarios. We further show that the method can provide insights about the variation of physical parameters over space and time in two domain applications: predicting temperature in streams and predicting temperature in lakes. [ABSTRACT FROM AUTHOR]

The modeling of spatio-temporal processes is crucial in many fields such as environmental science, hydrology, and water storage engineering. A basic concept of the spatio-temporal model is an auto-covariance function. The stream network model based on the Euclidean distance as the auto-covariance function for investigating river pollution will potentially face a serious accuracy problem, due to the material or water pollutant movement on the water only occurring within the river network and the distance travelled not following the path of the river network. The use of the hydrologic distance may overcome the problem because, statistically, the Euclidean distance-based auto-covariance function is not valid if it is a negative-definite. Therefore, this study develops a spatio-temporal model of the generalized product–sum based on the hydrologic distance with a positive-definite property. The proposed model is built and, subsequently, it is then verified mathematically to be positive-definite. Furthermore, the relationships between the hydrologic distance, the Euclidean distance, and spatial configurations are also investigated. The simulation study result shows the proposed spatio-temporal model is positive-definite for some semivariogram models. The relationships between spatial configurations in the stream network follow an exponential model. [ABSTRACT FROM AUTHOR]

Longitudinal depictions of watershed structure and characteristics, including topography, stream networks, wetlands, ground water levels, and land use, can provide watershed knowledge and understanding unavailable from standard plan view maps. Three case studies provide examples of knowledge gained by applying longitudinal views of stream networks, watershed hydrologic behavior, and land use distributions. Longitudinal views of mountain stream networks show extreme variability in the slope‐area relationships of low Strahler order streams, large discontinuities in drainage area (large parts of drainage area space are absent in networks), and large variations in network curvature. Longitudinal views of a groundwater‐dominated headwater watershed increase the inference available from limited groundwater observations and clearly reveal how groundwater connections affect the permanence of surface water features and the distribution of vadose zone storage in the landscape. Plotting land uses longitudinally illuminates and allows a quantitative analysis of how land uses are distributed relative to topographic position. Viewing watersheds and stream networks longitudinally can provide new insights into watershed forms and processes and motivate new questions and research. [ABSTRACT FROM AUTHOR]

Abstract Streams in cultivated lowlands are commonly supersaturated with CO2 and are a source of CO2 to the atmosphere. Great uncertainties exist regarding the spatiotemporal variations of CO2 concentrations and emission rates in stream‐lake fluvial networks and small streams with variable plant cover. We studied this variability and the underlying mechanisms in 40 small, high‐alkalinity Danish streams, including 5 catchments with lakes. Generally CO2 concentrations were, on average, 9.2 times those of the atmosphere, declining downstream with rising water temperature, chlorophyll a concentration, and decreasing groundwater inputs. We furthermore observed that the concentrations of CO2 in stream waters declined at the outlet of lakes to values close to or below air saturation due to phytoplankton uptake and atmospheric loss during the long water retention time in the lakes. Downstream, CO2 concentrations were observed to decrease in summer and in the afternoons, which indicate plant uptake of CO2. Sites with deeper water and few plants and low gas transfer velocity retained high CO2 concentrations. Among 38 fluvial networks where emission could be calculated, it varied 10‐fold (0.41–4.06 g C m−2 d−1), but the overall mean was constrained to a narrow confidence interval (1.75–2.50 g C m−2 d−1). Our results highlight that a complex of physical, chemical and biological processes cause highly variable carbon dynamics and CO2 emissions in fluvial networks at local and catchment scales making upscaling challenging.

The modeling of spatio-temporal processes is crucial in many fields such as environmental science, hydrology, and water storage engineering. A basic concept of the spatio-temporal model is an auto-covariance function. The stream network model based on the Euclidean distance as the auto-covariance function for investigating river pollution will potentially face a serious accuracy problem, due to the material or water pollutant movement on the water only occurring within the river network and the distance travelled not following the path of the river network. The use of the hydrologic distance may overcome the problem because, statistically, the Euclidean distance-based auto-covariance function is not valid if it is a negative-definite. Therefore, this study develops a spatio-temporal model of the generalized product–sum based on the hydrologic distance with a positive-definite property. The proposed model is built and, subsequently, it is then verified mathematically to be positive-definite. Furthermore, the relationships between the hydrologic distance, the Euclidean distance, and spatial configurations are also investigated. The simulation study result shows the proposed spatio-temporal model is positive-definite for some semivariogram models. The relationships between spatial configurations in the stream network follow an exponential model.

The ever‐changing hydroclimatic conditions of the landscape induce ceaseless variations in the wet channel length (L) and the streamflow (Q) of a catchment. Here we use a perceptual model to analyze the links among (and the drivers of) four descriptors commonly used to characterize discharge and active length dynamics in streams, namely the L(Q) relationship and the cumulative distributions of local persistency, flowrate and active length. The model demonstrates that the shape of the L(Q) law is defined by the cumulative distribution of the specific subsurface discharge capacity along the network, a finding which provides a clue for the parametrization of L(Q) relations in dynamic streams. Furthermore, we show that L(Q) laws can be constructed combining the streamflow distribution with disjoint active length data. Our framework links previously unconnected formulations for characterizing stream network dynamics, and offers a novel perspective to describe the scaling between wet length and discharge in rivers. Plain Language Summary: Stream networks react to changing climatic conditions (wetting or drying) in the surrounding landscape. Consequently, the length of flowing channels and the corresponding streamflow vary through time owing to precipitation events and seasonal climatic patterns. Here we present a conceptual model that analyzes the controlling factors of four standard descriptors of streamflow and active length dynamics in streams, and identifies their mutual connections. The model provides insight on the physical processes that determine the joint changes of active length and discharge, investigating the impact of climate and landscape morphology on these standard descriptors. The approach formally describes how the relation between flowrate and active length originates from the spatial aggregation of local properties of the stream network (water supply and transport capacity). A set of mathematical relations is also derived, which can be used in practical applications to interpret and predict the relationship between wet length and catchment discharge ‐ even in cases in which synchronous measurements of these two variables are not available. Key Points: The shape of the active length (L) versus discharge (Q) relation mirrors the distribution of specific subsurface capacity along the networkThe L(Q) law can be reconstructed combining observations of active length and discharge collected during different time periodsWe derive exact analytical expressions that connect the L(Q) law to the distributions of local persistency, flowrate and active length [ABSTRACT FROM AUTHOR]

There are concerns that environmental changes, such as climate variability and forest harvesting, are altering stream thermal regimes and impacting aquatic ecosystems. Previous studies have suggested that the abundant headwater lakes found in northern landscapes may moderate downstream temperature response to forest harvesting. We investigated this hypothesis using a virtual experimental approach based on detailed field measurements made at boreal catchments in northern Sweden coupled with a process‐based stream temperature model. We simulated streamside harvesting for stream reaches with and without a headwater lake. Mean daily summer stream temperature response to harvesting was generally between 0.5 and 1.5°C higher for the stream without a lake than for the stream with a lake. However, during rain events the stream with the lake showed a greater stream temperature response than the stream without a lake. Headwater lakes typically store and delay runoff from rain events, augment baseflow, and have elevated outflow temperatures. These differences in upstream boundary conditions, in terms of flow and water temperature, were the key drivers for the contrasting harvest responses between streams with and without headwater lakes. These findings were generally consistent across different harvesting scenarios; however, uncertainty in the hyporheic term and post‐harvest microclimate conditions influenced the simulated magnitude of post‐harvest stream temperature response. Our study highlights the utility of virtual experiments for gaining insight on systems understanding but caution is needed when using models for predictions outside the conditions for which models are calibrated. [ABSTRACT FROM AUTHOR]

Hatch timing in autumn- spawning stream salmonids is poorly understood in the subarctic region because snow cover prevents direct sampling of cryptic early life stages. Otolith micro- increment analysis was used to infer hatch dates of white- spotted charr Salvelinus leucomaenis (Pallas) and masu salmon Oncorhynchus masou (Brevoort) in a mainstem- tributary network in northern Japan. Accuracy and precision were validated by ageing hatchery individuals with known hatch date ranges. In July 2018, 93 wild young- of- the- year white- spotted charr and 81 masu salmon were collected and aged. Masu salmon hatched, on average, 24 days earlier (mean = February 8) than white- spotted charr (March 4), and hatch dates spanned a minimum of 2 months for each species. In masu salmon, hatch dates of individuals collected in the mainstem were nearly 3 weeks earlier than those in a tributary. This study provided knowledge on intra- and inter- specific variation in hatch timing of native salmonids in a subarctic stream network. [ABSTRACT FROM AUTHOR]

Abstract Flowing stream networks extend and retract as their surrounding landscapes wet up and dry out, both seasonally and during rainstorms, with implications for aquatic ecosystems and greenhouse gas exchange. Some networks are much more dynamic than others, however, and the reasons for this difference are unknown. Here we show that the tendency of stream networks to extend and retract can be predicted from down‐valley changes in topographic attributes (slope, curvature, and contributing drainage area), without measuring subsurface hydrologic properties. Topography determines where water accumulates within valley networks, and we propose that it also modulates flow partitioning between the surface and subsurface. Measurements from 17 mountain stream networks support this hypothesis, showing that undissected valley heads have greater subsurface transport capacities than sharply incised valleys downstream. In catchments where broad valley heads rapidly transition to sharply incised valleys, subsurface transport capacity decreases abruptly, stabilizing stream length through wet and dry periods.

Stream confluences are important components of fluvial networks. Hydraulic forces meeting at stream confluences often produce changes in streambed morphology and sediment distribution. These changes often increase habitat heterogeneity relative to upstream and downstream locations, which have led some to identify them as biological hotspots. Despite their potential ecological importance, there are relatively few empirical studies documenting ecological patterns upstream and downstream of confluences. We have produced a publicly available dataset of stream confluences and associated watershed attributes for the conterminous United States. The dataset includes 1,085,629 stream confluences and 383 attributes for each confluence organized into 15 dataset tables for both tributary and mainstem upstream catchments and watersheds. Themes in the dataset include hydrology (e.g., stream order), land cover, land cover change, geology (e.g., calcium content of underlying lithosphere), physical condition (e.g., precipitation), measures of ecological integrity, and stressors (e.g., impaired streams). Additionally, we used measures of ecological integrity to assess the condition of the stream confluences. Aside from a generally positive east‐to‐west gradient in ecological condition, we found that approximately one‐third of the confluences had markedly contrasting ecological conditions between mainstem and tributary, catchment and watershed, or both. The dataset should support many, multifaceted studies of stream confluence ecology. Research Impact Statement: Stream confluences may be biological hotspots. We present a USA stream confluence dataset to stimulate further ecological research. The dataset contains 1,085,629 confluences and 383 attributes. [ABSTRACT FROM AUTHOR]

Agricultural headwaters are positioned at the interface between terrestrial and aquatic ecosystems and, therefore, at the margins of scientific disciplines. They are deemed devoid of biodiversity and too polluted by ecologists, overlooked by hydrologists, and are perceived as a nuisance by landowners and water authorities. While agricultural streams are widespread and represent a major habitat in terms of stream length, they remain understudied and thereby undervalued. Agricultural headwater streams are significantly modified and polluted but at the same time are the critical linkages among land, air, and water ecosystems. They exhibit the largest variation in streamflow, water quality, and greenhouse gas emission with cascading effects on the entire stream networks, yet they are underrepresented in monitoring, remediation, and restoration. Therefore, we call for more intense efforts to characterize and understand the inherent variability and sensitivity of these ecosystems to global change drivers through scientific and regulatory monitoring and to improve their ecosystem conditions and functions through purposeful and evidence-based remediation.

Riverine chemistry reflects both watershed conditions and instream processing, both of which vary across river networks, yet little is known about the scales at which watershed attributes regulate biogeochemical constituents. We used spatial stream network (SSN) models to quantify both watershed and instream effects on streamwater constituents in the Kuskokwim River (western Alaska), the largest free‐flowing river in the United States. We assessed chemical constituents spanning from labile nutrients (nitrate [NO3−] and orthophosphate [PO43−]) to biologically and chemically conservative tracers (calcium [Ca2+], strontium [Sr2+], and Sr isotopes [87Sr/86Sr]). We also examined the behavior of dissolved organic carbon (DOC) relative to these constituents to understand whether bulk DOC behaved conservatively in a large boreal river network, where future changes in DOC and nutrient loading are expected under a shifting climate. We derived watershed spatial covariates comprising land cover, geology, and geomorphic characteristics at 14 different spatial extents based on stream order and relative to position in the river network to understand the effect of distant and proximal watershed attributes on streamwater constituents. For all constituents but 87Sr/86Sr, watershed attributes in low‐order headwater catchments yielded the best predictive ability for streamwater constituent concentrations across the entire network. Spatial patterning for conservative tracers and bulk DOC showed strong spatial autocorrelation, whereas PO43− and NO3− exhibited spatial patchiness indicative of instream processing. Our work shows that headwater streams are disproportionately important contributors to network‐wide biogeochemical constituents supporting aquatic food webs and that conservation and management of aquatic systems should include these small and often remote watershed areas. Plain Language Summary: Streamwater chemistry is influenced by watershed attributes like geology, gradient, and land cover and biochemical changes occurring within the stream channel, but how the relative importance of these factors changes as water moves through a river network is not known. We used a statistical model that accounts for water flows and the spatial layout of the river to study how stream chemistry is influenced by both watershed attributes and instream conditions at local to watershed‐wide scales. We studied the Kuskokwim River in Alaska, America's largest free‐flowing river, and found that conditions in small, headwater streams play a disproportionately important role in shaping streamwater chemistry throughout the river network. We also found that chemicals that are rapidly used by algae and microbes are spatially more variable in the river network when compared to passively transported chemicals that have lower biological demand. This work is important because streamwater chemical patterns can influence how different organisms are distributed in rivers, and certain watershed attributes will influence how changing climate and land use affect river chemistry. Studying how different parts of the watershed influence streamwater chemistry will help scientists and resource managers understand how riverine chemistry and food webs may change in the future. Key Points: Little is known about the scales at which both watershed and instream factors shape streamwater biogeochemistryHeadwater catchment conditions such as relief and geology are important drivers of streamwater constituents across a river networkConservative tracers such as calcium had stronger spatial autocorrelation than dissolved organic carbon and labile nutrients like nitrate [ABSTRACT FROM AUTHOR]

Abstract Emergent aquatic insects transport aquatic‐derived resources into terrestrial ecosystems but are rarely studied at landscape or regional scales. Here, we investigate how stream network geometry constrains the spatial influence of aquatic insect subsidies in terrestrial ecosystems. We also explore potential factors (i.e., climate, topography, soils, and vegetation) that could produce variation in stream network geometry and thus change the extent of aquatic insect subsidies from one region to another. The stream signature is the percentage of aquatic insect subsidies traveling a given distance into the terrestrial ecosystem, relative to what comes out of the stream. We use this concept to model the spatial extent (area) and distribution (spatial patterning) of aquatic subsidies in terrestrial ecosystems across the contiguous United States. Our findings suggest that at least 8% of the subsidies measured at the aquatic–terrestrial boundary (i.e., the 8% stream signature) are typically transferred throughout the entire watershed and that variation in this spatial extent is largely influenced by the drainage density of the stream network. Moreover, we found stream signatures from individual stream reaches overlap such that the spatial extent of the 8% stream signature often includes inputs from multiple stream reaches. Landscape‐scale stream network characteristics increased the area of overlapping stream signatures more than reach‐scale channel properties. Finally, we found runoff was an important factor influencing stream network geometry suggesting a potential effect of climate on aquatic‐to‐terrestrial linkages that have been understudied.

Emergent aquatic insects transport aquatic-derived resources into terrestrial ecosystems but are rarely studied at landscape or regional scales. Here, we investigate how stream network geometry constrains the spatial influence of aquatic insect subsidies in terrestrial ecosystems. We also explore potential factors (i.e., climate, topography, soils, and vegetation) that could produce variation in stream network geometry and thus change the extent of aquatic insect subsidies from one region to another. The stream signature is the percentage of aquatic insect subsidies traveling a given distance into the terrestrial ecosystem, relative to what comes out of the stream. We use this concept to model the spatial extent (area) and distribution (spatial patterning) of aquatic subsidies in terrestrial ecosystems across the contiguous United States. Our findings suggest that at least 8% of the subsidies measured at the aquatic-terrestrial boundary (i.e., the 8% stream signature) are typically transferred throughout the entire watershed and that variation in this spatial extent is largely influenced by the drainage density of the stream network. Moreover, we found stream signatures from individual stream reaches overlap such that the spatial extent of the 8% stream signature often includes inputs from multiple stream reaches. Landscapescale stream network characteristics increased the area of overlapping stream signatures more than reach-scale channel properties. Finally, we found runoff was an important factor influencing stream network geometry suggesting a potential effect of climate on aquatic-to-terrestrial linkages that have been understudied. [ABSTRACT FROM AUTHOR]

We studied how multiple-stresssors in tributaries affect function, diversity, and physical habitat of recipient downstream ecosystems. Using a mesocosm model of a stream network, we manipulated sediment and nutrients individually and in combination in tributaries of second-order channels, to test the effect of complex stressor interactions within tributaries on recipient channels. Sedimentation in second-order channels increased with the level of disturbance of the tributaries. Moreover, Ephemeroptera, Plecoptera, and Trichoptera (EPT) density and EPT richness were higher in second-order channels fed by tributaries where the stressors were applied separately, compared to those fed by tributaries where the stressors were applied simultaneously. Our observations suggest this result was due to the combination of the two stressors within the same tributary reducing EPT drift from the tributaries further than the addition of the stressors in separate tributaries. These results support the hypothesis that cumulative upstream disturbance can influence downstream recipient ecosystems in stream networks. However, contrary to our expectations, most observed effects were due to impacts on dispersal patterns of EPT taxa, rather than downstream accumulation of disturbances throughout the network. Our results underscore the importance of metacommunity frameworks to understand how tributary disturbance may influence population dynamics in downstream ecosystems.

In view of the rapid proliferation of water infrastructures worldwide, balancing human and ecosystem needs for water resources is a critical environmental challenge of global significance. While there is abundant literature on the environmental impacts of individual water infrastructures, little attention has been paid to their cumulative effects in river networks, which may have basin‐to‐global impacts on freshwater ecology. Here we developed a methodological framework based on Pareto frontier analysis for optimizing trade‐offs between water withdrawal and ecological indicators. We applied this framework to a mountainous Ecuadorian headwater river network that is part of a continental water transfer for supply and demand management to optimize ecological conditions and the operation of 11 water intake structures used to provide potable water to the city of Quito. We found that the current water intake configuration has an important effect on the total length of fifth‐order stream sections (65% reduction compared to premanaged condition) and isolates 70.9% of the headwater stream length. The Pareto frontier analysis identified water intake portfolios (i.e., different combinations of intake sites) that decreased ecological impacts by 7.8% points (pp) and 13.0 pp for connectivity and stream order change, respectively, while meeting Quito's water demands. Additional portfolios accounting for monthly variability in water demand and resources further decrease the ecological impact up to 9.6 pp in connectivity and 13.4 pp in stream order. These eco‐friendly portfolios suggest that adaptive management at basin level may help optimize water withdrawal to fulfill urban demands while preserving ecological integrity. Key Points: We develop a methodological framework to perform trade‐off analyses between water withdrawal and ecological impacts at the basin scaleThrough a Pareto frontier analysis, the operation of 11 water intake structures used to provide potable water to Quito City is optimizedApplication of new water management practices are necessary to reach a more dynamic operation strategy to balance human and ecological needs [ABSTRACT FROM AUTHOR]

Flowing stream networks extend and retract as their surrounding landscapes wet up and dry out, both seasonally and during rainstorms, with implications for aquatic ecosystems and greenhouse gas exchange. Some networks are much more dynamic than others, however, and the reasons for this difference are unknown. Here we show that the tendency of stream networks to extend and retract can be predicted from down‐valley changes in topographic attributes (slope, curvature, and contributing drainage area), without measuring subsurface hydrologic properties. Topography determines where water accumulates within valley networks, and we propose that it also modulates flow partitioning between the surface and subsurface. Measurements from 17 mountain stream networks support this hypothesis, showing that undissected valley heads have greater subsurface transport capacities than sharply incised valleys downstream. In catchments where broad valley heads rapidly transition to sharply incised valleys, subsurface transport capacity decreases abruptly, stabilizing stream length through wet and dry periods. Plain Language Summary: Although stream networks are represented as fixed blue lines on maps, the actual extent of flowing water dynamically adjusts as landscapes become wetter and drier. This is an old observation, but one without a satisfying physical explanation. Intuitively, flowing streams extend during wetter periods, as smaller parts of the landscape are able to supply enough water to support streamflow. But the supply of water is only part of the story, because some parts of the landscape may have greater capacity to move supplied water through the subsurface without streamflow, affecting where water ultimately emerges. In this study, we use observations from 17 mountainous landscapes to show that topography can be used to predict both the supply of water and the capacity to move that water through the subsurface. Consequently, topographic maps can tell us how much a stream network will extend as its surrounding landscape becomes wetter. This helps us predict how dynamic (or, conversely, stable) stream networks will be during rainstorms, droughts, and longer‐term climatic shifts. Key Points: Some flowing stream networks lengthen dramatically as their catchments become wetter, whereas others change much lessThis tendency for networks to extend and retract can be predicted from down‐valley changes in slope, drainage area, and curvatureAs valleys become more sharply incised downstream, subsurface transmissivity decreases, which helps stabilize flowing stream length [ABSTRACT FROM AUTHOR]

Water quality data at gaging stations are typically compared with established federal, state, or local water quality standards to determine if violations (concentrations of specific constituents falling outside acceptable limits) have occurred. Based on the frequency and severity of water quality violations, risk metrics such as reliability, resilience, and vulnerability (R-R-V) are computed for assessing water quality-based watershed health. In this study, a modified methodology for computing R-R-V measures is presented, and a new composite watershed health index is proposed. Risk-based assessments for different water quality parameters are carried out using identified national sampling stations within the Upper Mississippi River Basin, the Maumee River Basin, and the Ohio River Basin. The distributional properties of risk measures with respect to water quality parameters are reported. Scaling behaviors of risk measures using stream order, specifically for the watershed health (WH) index, suggest that WH values increased with stream order for suspended sediment concentration, nitrogen, and orthophosphate in the Upper Mississippi River Basin. Spatial distribution of risk measures enable identification of locations exhibiting poor watershed health with respect to the chosen numerical standard, and the role of land use characteristics within the watershed. [ABSTRACT FROM AUTHOR]

The multiple scale of stream networks spatial organization reflects the hierarchical arrangement of streams habitats with increasingly levels of complexity from sub-catchments until entire hydrographic basins. Through these multiple spatial scales, local stream habitats form nested subsets of increasingly landscape scale and habitat size with varying contributions of both alpha and beta diversity for the regional diversity. Here, we aimed to test the relative importance of multiple nested hierarchical levels of spatial scales while determining alpha and beta diversity of caddisflies in regions with different levels of landscape degradation in a core Cerrado area in Brazil. We used quantitative environmental variables to test the hypothesis that landscape homogenization affects the contribution of alpha and beta diversity of caddisflies to regional diversity. We found that the contribution of alpha and beta diversity for gamma diversity varied according to landscape degradation. Sub-catchments with more intense agriculture had lower diversity at multiple levels, markedly alpha and beta diversities. We have also found that environmental predictors mainly associated with water quality, channel size, and habitat integrity (lower scores indicate stream degradation) were related to community dissimilarity at the catchment scale. For an effective management of the headwater biodiversity of caddisfly, towards the conservation of these catchments, heterogeneous streams with more pristine riparian vegetation found within the river basin need to be preserved in protected areas. Additionally, in the most degraded areas the restoration of riparian vegetation and size increase of protected areas will be needed to accomplish such effort. [ABSTRACT FROM AUTHOR]

In recent decades, the Rocky Mountains (RM) have undergone significant changes associated with anthropogenic activities and natural disturbances. These changes have the potential to alter primary productivity and biomass carbon storage. In particular, dissolved organic carbon (DOC) in RM streams can affect heterotrophic processes, act as a source for the nutrient cycle, absorb sunlight radiation, alter metal transport, and can promote the production of carcinogenic byproducts during water treatment. Recent studies have focused on the relationship between bark beetle infestations and stream organic matter but have reached conflicting conclusions. Consequently, here we compile and process multiple datasets representing features of the RM for the period 1983–2012 with the purpose of assessing their relative influence on stream DOC concentrations using spatial statistical modeling. Features representing climate, land cover, forest disturbances, topography, soil types, and anthropogenic activities are included. We focus on DOC during base-flow conditions in RM streams because base-flow concentrations are more representative of the longer-term (annual to decadal) impacts and are less dependent on episodic, short-term storm and runoff/erosion events. To predict DOC throughout the network, we use a stream network model in a 56,550 km2 area to address the intrinsic connectivity and hydrologic directionality of the stream network. Natural forest disturbances are positively correlated with increased DOC concentrations; however, the effect of urbanization is far greater. Similarly, higher maximum temperatures, which can be exacerbated by climate change, are also associated with elevated DOC concentrations. Overall, DOC concentrations present an increasing trend over time in the RM region. [ABSTRACT FROM AUTHOR]

1. Rivers are spatially organised into hierarchic dendritic networks. This unique physical structure and the associated directionality of physical flows set them apart from most other environments by regulating the dispersal of resident biota and therefore the distribution of biodiversity. 2. The aim of this special issue is to highlight the importance of the river network on structuring biodiversity, particularly through metacommunity dynamics and associated dispersal processes. 3. The issue covers a wide range of topics, including disease spread, nutrient uptake, trophic dynamics, effects of anthropogenic stressors and the joint roles of dispersal and environmental filtering. Contributions employ a broad range of approaches, including field and laboratory experiments, modelling, population genetics and conceptual synthesis. 4. Although these studies represent just a sample of the research that is being performed on biodiversity and metacommunity dynamics in river networks, several important findings have emerged; a common theme being that the structure of the network and spatial dynamics clearly influence the dynamics of populations and communities, and their functions. By taking a broad taxonomic focus (from diatoms and protists to fish), and spanning a large geographic gradient (from the tropics to the subarctic), this special issue provides a broad look at the dynamics that occur in river networks relating to their unique makeup. We hope that this selection of studies spurs additional research on these interesting, globally important, yet severely threatened ecological systems. [ABSTRACT FROM AUTHOR]

We provide an assessment of thermal characteristics and climate change vulnerability for brook trout ( Salvelinus fontinalis ) habitats in the upper Shavers Fork sub-watershed, West Virginia. Spatial and temporal (2001–2015) variability in observed summer (6/1–8/31) stream temperatures was quantified in 23 (9 tributary, 14 main-stem) reaches. We developed a mixed effects model to predict site-specific mean daily stream temperature from air temperature and discharge and coupled this model with a hydrologic model to predict future (2016–2100) changes in stream temperature under low (RCP 4.5) and high (RCP 8.5) emissions scenarios. Observed mean daily stream temperature exceeded the 21 °C brook trout physiological threshold in all but one main-stem site, and 3 sites exceeded proposed thermal limits for either 63- and 7-day mean stream temperature. We modeled mean daily stream temperature with a high degree of certainty ( R 2 = 0.93; RMSE = 0.76 °C). Predicted increases in mean daily stream temperature in main-stem and tributary reaches ranged from 0.2 °C (RCP 4.5) to 1.2 °C (RCP 8.5). Between 2091 and 2100, the average number of days with mean daily stream temperature > 21 °C increased within main-stem sites under the RCP 4.5 (0–1.2 days) and 8.5 (0 − 13) scenarios; however, no site is expected to exceed 63- or 7-day thermal limits. During the warmest 10 years, ≥ 5 main-stem sites exceeded the 63- or 7-day thermal tolerance limits under both climate emissions scenarios. Years with the greatest increases in stream temperature were characterized by low mean daily discharge. Main-stem reaches below major tributaries never exceed thermal limits, despite neighboring reaches having among the highest observed and predicted stream temperatures. Persistence of thermal refugia within upper Shavers Fork would enable persistence of metapopulation structure and life history processes. However, this will only be possible if projected increases in discharge are realized and offset expected increases in air temperature. [ABSTRACT FROM AUTHOR]

Intermittent and ephemeral streams represent more than half of the length of the global river network. Dryland freshwater ecosystems are especially vulnerable to changes in human-related water uses as well as shifts in terrestrial climates. Yet, the description and quantification of patterns of flow permanence in these systems is challenging mostly due to difficulties in instrumentation. Here, we took advantage of existing stream temperature datasets in dryland streams in the northwest Great Basin desert, USA, to extract critical information on climate-sensitive patterns of flow permanence. We used a signal detection technique, Hidden Markov Models (HMMs), to extract information from daily time series of stream temperature to diagnose patterns of stream drying. Specifically, we applied HMMs to time series of daily standard deviation (SD) of stream temperature (i.e., dry stream channels typically display highly variable daily temperature records compared to wet stream channels) between April and August (2015-2016). We used information from paired stream and air temperature data loggers as well as co-located stream temperature data loggers with electrical resistors as confirmatory sources of the timing of stream drying. We expanded our approach to an entire stream network to illustrate the utility of the method to detect patterns of flow permanence over a broader spatial extent. We successfully identified and separated signals characteristic of wet and dry stream conditions and their shifts over time. Most of our study sites within the entire stream network exhibited a single state over the entire season (80%), but a portion of them showed one or more shifts among states (17%). We provide recommendations to use this approach based on a series of simple steps. Our findings illustrate a successful method that can be used to rigorously quantify flow permanence regimes in streams using existing records of stream temperature. [ABSTRACT FROM AUTHOR]

Fragmented landscapes reduce gene flow and impair long term population viability. Stream networks are particularly susceptible to fragmentation because dispersal is constrained to linear upstream and downstream movements. Despite these potential effects, infrequent migrations can maintain genetic diversity and as few as one migrant per generation (OMPG) is commonly suggested as sufficient gene flow to minimize losses in genetic diversity. However, demography varies by taxa, space and time, making such a generalized rule of thumb unlikely to be applicable across a diverse array of fragmentation scenarios and species. We utilized a demogenetic model to evaluate the OMPG rule and simulate the influence of population demographics on the rate of genetic changes following fragmentation in a headwater meta-population of brook trout ( Salvelinus fontinalis) . A single migrant per generation increased allelic diversity by an average of 15% and decreased genetic differentiation by 31% following 40 years of simulations compared to complete isolation, however OMPG was not sufficient to prevent significant changes in within- or between-population genetic metrics in all but the largest population scenario ( N = 500). Less than 10 individuals were typically required to achieve no changes in both genetic metrics, yet this pattern was dependent on the source populations and will be context-specific given the population sub-structuring in a given stream network. Sensitivity analyses indicated the parameter controlling the proportion of mature females spawning annually was the most influential on population genetic responses in isolated populations, suggesting that when fewer females contribute to each generation the population is more likely to experience rapid changes in allelic frequency through genetic drift. This finding supports the use of metrics such as effective population size and the number of effective breeders in predicting population stability and viability following fragmentation. Variability in population dynamic processes and associated responses to fragmentation suggest that generalized rule of thumbs for management should be used with caution. Particularly when violations of the underlying theoretical assumptions exist, consideration of demographic processes (i.e. vital rates, species specific life history strategies and dispersal) and genetic structuring will allow for more appropriate conservation recommendations. [ABSTRACT FROM AUTHOR]

Thermal regimes of forested headwater streams control the growth and distribution of various aquatic organisms. In a western Oregon, USA, case study we examined: (1) forested headwater stream temperature variability in space and time; (2) relationships between stream temperature patterns and weather, above-stream canopy cover, and geomorphic attributes; and (3) the predictive ability of a regional stream temperature model to account for headwater stream temperature heterogeneity. Stream temperature observations were collected at 48 sites within a 128-ha managed forest in western Oregon during 2012 and 2013. Headwater stream temperatures showed the greatest spatial variability during summer (range up to 10 $$^\circ$$ C) and during cold and dry winter periods (range up to 7.5 $$^\circ$$ C), but showed less spatial variability during spring, fall and wet winter periods (range between 2 and 5 $$^\circ$$ C). Distinct thermal regimes among sites were identified; however, geomorphic attributes typically used in regional stream temperature models were not good predictors of thermal variability at headwater scales. A regional stream temperature model captured the mode of mean August temperatures observed across the study area, but overpredicted temperatures for a quarter of the sites by up to 2.8 $$^\circ$$ C. This study indicates considerable spatial thermal variability may occur at scales not resolved by regional stream temperature models. Recognizing this sub-landscape variability may be important when predicting distributions of aquatic organisms and their habitat under climate and environment change scenarios. [ABSTRACT FROM AUTHOR]

Combining landscape demographic and genetics models offers powerful methods for addressing questions for eco-evolutionary applications., Using two illustrative examples, we present Cost-Distance Meta-POPulation, a program to simulate changes in neutral and/or selection-driven genotypes through time as a function of individual-based movement, complex spatial population dynamics, and multiple and changing landscape drivers., Cost-Distance Meta-POPulation provides a novel tool for questions in landscape genetics by incorporating population viability analysis, while linking directly to conservation applications. [ABSTRACT FROM AUTHOR]

Tributary confluences play an important role in the dispersal of organisms, and consequently, in shaping regional scale diversity in stream networks. Despite their importance in dispersal processes, little is known about how ecological assemblages are organized in these habitats. We studied the scales of variability of stream fish assemblages over three seasons using a hierarchical sampling design, which incorporated three tributaries, three sites at the mouth of each tributary and using four sampling units at each site. We found strong scale dependent variability in species richness, composition and relative abundance. Most of the variation was accounted for by the interactive effect of season, between stream and between site effects, while habitat structure of the sampling units had a relatively minor role. Species richness showed a continuous decrease from the mainstem river in most cases, while species composition and relative abundance changed less consistently along the longitudinal profile. Consequently, we found that not only the junctions presented a strong filter on the species pool, but some species were filtered out if they passed this critical habitat bottleneck. Spatial position of the tributaries along the river also contributed to assemblage variability in the confluences. Overall, our results suggest high variability in fish assemblages across multiple scales at tributary confluences. Environmental management should take a more critical care on the filtering role of tributary confluences in species dispersal, for better understanding patterns and processes in the branches of dendritic stream networks.

Successfully addressing the multitude of stresses influencing forest catchments, their native biota, and the vital ecological services they provide humanity will require adapting an integrated view that incorporates the full range of natural and anthropogenic disturbances acting on these landscapes and their embedded fluvial networks. The concepts of dendritic networks, disturbance domains, the stream continuum, and hydrologic connectivity can facilitate this integration. Managing catchments based on these combined concepts would better maintain all the components of watersheds and the interacting processes that comprise their ecological integrity. To examine these ideas, I review riparian protection regulations in the Pacific Northwest of the United States, regulations considered by many to be among the best available, and evaluate their ability to protect headwater amphibians. I present evidence for the inadequacy of these rules to maintain robust populations of these amphibians, and discuss the implications of these shortcomings for downstream-dwelling coho salmon. Emphasizing headwaters (1st to 3rd-order channels), I discuss disturbance regimes and how differences in their fluvial and geomorphic processes determine the structuring of channels, their internal environments, and the composition of the resident biota. I examine amphibian dependence on specific channel attributes, and discuss links between their abundances, altered attribute states, and natural and anthropogenic disturbances. Using these examples, I discuss the limitations of current protections to maintain key attributes necessary to support robust populations of headwater amphibians, and via hydrologic connectivity, many downstream organisms. I propose that the goal of maintaining whole catchment biodiversity and ecological services could be improved by managing watersheds based on integrating science-based network organizing concepts and evaluating and adjusting outcomes with a suite of responsive bio-indicators.

In recent decades, the Rocky Mountains (RM) have undergone significant changes associated with anthropogenic activities and natural disturbances. These changes have the potential to alter primary productivity and biomass carbon storage. In particular, dissolved organic carbon (DOC) in RM streams can affect heterotrophic processes, act as a source for the nutrient cycle, absorb sunlight radiation, alter metal transport, and can promote the production of carcinogenic byproducts during water treatment. Recent studies have focused on the relationship between bark beetle infestations and stream organic matter but have reached conflicting conclusions. Consequently, here we compile and process multiple datasets representing features of the RM for the period 1983–2012 with the purpose of assessing their relative influence on stream DOC concentrations using spatial statistical modeling. Features representing climate, land cover, forest disturbances, topography, soil types, and anthropogenic activities are included. We focus on DOC during base-flow conditions in RM streams because base-flow concentrations are more representative of the longer-term (annual to decadal) impacts and are less dependent on episodic, short-term storm and runoff/erosion events. To predict DOC throughout the network, we use a stream network model in a 56,550 km2 area to address the intrinsic connectivity and hydrologic directionality of the stream network. Natural forest disturbances are positively correlated with increased DOC concentrations; however, the effect of urbanization is far greater. Similarly, higher maximum temperatures, which can be exacerbated by climate change, are also associated with elevated DOC concentrations. Overall, DOC concentrations present an increasing trend over time in the RM region.

Intermittent and ephemeral streams represent more than half of the length of the global river network. Dryland freshwater ecosystems are especially vulnerable to changes in human-related water uses as well as shifts in terrestrial climates. Yet, the description and quantification of patterns of flow permanence in these systems is challenging mostly due to difficulties in instrumentation. Here, we took advantage of existing stream temperature datasets in dryland streams in the northwest Great Basin desert, USA, to extract critical information on climate-sensitive patterns of flow permanence. We used a signal detection technique, Hidden Markov Models (HMMs), to extract information from daily time series of stream temperature to diagnose patterns of stream drying. Specifically, we applied HMMs to time series of daily standard deviation (SD) of stream temperature (i.e., dry stream channels typically display highly variable daily temperature records compared to wet stream channels) between April and August (2015–2016). We used information from paired stream and air temperature data loggers as well as co-located stream temperature data loggers with electrical resistors as confirmatory sources of the timing of stream drying. We expanded our approach to an entire stream network to illustrate the utility of the method to detect patterns of flow permanence over a broader spatial extent. We successfully identified and separated signals characteristic of wet and dry stream conditions and their shifts over time. Most of our study sites within the entire stream network exhibited a single state over the entire season (80%), but a portion of them showed one or more shifts among states (17%). We provide recommendations to use this approach based on a series of simple steps. Our findings illustrate a successful method that can be used to rigorously quantify flow permanence regimes in streams using existing records of stream temperature.

The GIS structural components, which are known as ArcObjects, are structures composed of functions, methods and different properties which are used in software environments in form of encapsulated entities and nowadays have important role in creating GIS softwares. Despite the important role of these objects in implementation of required concepts and algorithms in GIS softwares, unfortunately the usage of them have been less noticed while the facilities built in GIS software are limited too. On the other hand, the extent of using this technology, in natural resources sciences, agriculture and etc, increases day to day. In this research, using mentioned objects, a software including 12293 lines of code in form of 275 procedures has been designed and created. The software is capable of managing spatial, non-spatial and time series data (in scale of 1:250000) of gauging station and stream networks. The software provides possibilities to store, edit, query, and display data and also prepares output data. One of the software individual characteristics, which is not available in other current GIS softwares, is the execution of multiple spatial searches and quary on Geodatabase without any need to load and to display data layers into map display. The other software benefits are the production of figurative data layers resulted from spatial queries that can be displayed and used without any physical origins on hard disk.

Tributary confluences play an important role in the dispersal of organisms, and consequently, in shaping regional scale diversity in stream networks. Despite their importance in dispersal processes, little is known about how ecological assemblages are organized in these habitats. We studied the scales of variability of stream fish assemblages over three seasons using a hierarchical sampling design, which incorporated three tributaries, three sites at the mouth of each tributary and using four sampling units at each site. We found strong scale dependent variability in species richness, composition and relative abundance. Most of the variation was accounted for by the interactive effect of season, between stream and between site effects, while habitat structure of the sampling units had a relatively minor role. Species richness showed a continuous decrease from the mainstem river in most cases, while species composition and relative abundance changed less consistently along the longitudinal profile. Consequently, we found that not only the junctions presented a strong filter on the species pool, but some species were filtered out if they passed this critical habitat bottleneck. In addition, spatial position of the tributaries along the river also contributed to assemblage variability in the confluences. Overall, our results suggest high variability in fish assemblages across multiple scales at tributary confluences. Environmental management should take a more critical care on the filtering role of tributary confluences in species dispersal, for better understanding patterns and processes in the branches of dendritic stream networks. [ABSTRACT FROM AUTHOR]

Streams networks are part of transport networks and more generally of “spatial networks” that gave rise to fundamental researches (Barthelemy, 2011) and applied geography (Strano et al., 2012). Numerous studies have focused on fractal analysis of stream networks. However, only few papers compare or discuss the estimation methods and the uncertainty of the main fractal indicator, the fractal dimension. This work focuses on the fractal properties of vector networks both virtual and actual. We first mention the essential distinction between infinite mathematical fractal and nature fractal. Then, we present different theoretical and empirical dimensions that we use. In particular, we compare three fractal dimension estimators: the most classical estimator for stream networks, based on a topological approach with the Horton-Strahler ratios, and two other estimators based on a geometric approach, the box-counting dimension and the correlation dimension. Three main methodological results can be highlighted: 1- the study of virtual network contributes to the assessment of the various estimators’ relevance, according to the characteristics of networks; 2- an empirical fractal domain must be determined with an objective method to estimate fractal dimensions that can be compared; 3- the observation of uncertainty and stability of the fractal dimension is necessary for any valid comparison.

Context: Metacommunities are sets of local communities linked by dispersal. Their characteristics are defined by both large-scale spatial processes such as dispersal, and local environmental processes, although which factors are likely to predominate in a given situation is poorly understood. Objectives: We investigated whether flow regime at the network-scale helped explain the relative importance of spatial and local-environmental processes in structuring stream metacommunities. Methods: Spatial sampling of stream macroinvertebrates was carried out in stream networks in New Zealand. Local environmental variables were also measured throughout the stream networks, while hydrographs were modelled and calibrated with field measurements. Results: Significant associations with both spatial and local-environmental predictor variables were found, consistent with several metacommunity types. In particular, two measures of flow regime were associated with different metacommunity types. Thus, stream networks characterised by a period of stability just before sampling, and networks sampled after a long period of instability, had more significant spatial structuring of metacommunities than those of intermediate flow stability. The importance of spatial processes in structuring the network metacommunities also increased with time since the last community-resetting flow. Our results therefore suggested that metacommunity type depended on the flow regime. Dispersal traits and network topology also helped explain some of the variation among the metacommunities. Conclusions: Overall, our findings conform to theoretical predictions related to dispersal limitation and topology, and indicate that metacommunity models need to be dynamic to capture processes in both space and time. [ABSTRACT FROM AUTHOR]

Recent studies highlight linkages among the architecture of ecological networks, their persistence facing environmental disturbance, and the related patterns of biodiversity. A hitherto unresolved question is whether the structure of the landscape inhabited by organisms leaves an imprint on their ecological networks. We analyzed, based on pyrosequencing profiling of the biofilm communities in 114 streams, how features inherent tofluvial networks affect the co-occurrence networks that the microorganisms form in these biofilms. Our findings suggest that hydrology and metacommunity dynamics, both changing predictably across fluvial networks, affect the fragmentation of the microbial co-occurrence networks throughout the fluvial network. The loss of taxa from co-occurrence networks demonstrates that the removal of gatekeepers disproportionately contributed to network fragmentation, which has potential implications for the functions biofilms fulfill in stream ecosystems. Our findings are critical because of increased anthropogenic pressures deteriorating stream ecosystem integrity and biodiversity. [ABSTRACT FROM AUTHOR]

Accelerating climate change and other cumulative stressors create an urgent need to understand the influence of environmental variation and landscape features on the connectivity and vulnerability of freshwater species. Here, we introduce a novel modeling framework for aquatic systems that integrates spatially explicit, individual-based, demographic and genetic (demogenetic) assessments with environmental variables. To show its potential utility, we simulated a hypothetical network of 19 migratory riverine populations (e.g., salmonids) using a riverscape connectivity and demogenetic model (CDFISH). We assessed how stream resistance to movement (a function of water temperature, fluvial distance, and physical barriers) might influence demogenetic connectivity, and hence, population vulnerability. We present demographic metrics (abundance, immigration, and change in abundance) and genetic metrics (diversity, differentiation, and change in differentiation), and combine them into a single vulnerability index for identifying populations at risk of extirpation. We considered four realistic scenarios that illustrate the relative sensitivity of these metrics for early detection of reduced connectivity: (1) maximum resistance due to high water temperatures throughout the network, (2) minimum resistance due to low water temperatures throughout the network, (3) increased resistance at a tributary junction caused by a partial barrier, and (4) complete isolation of a tributary, leaving resident individuals only. We then applied this demogenetic framework using empirical data for a bull trout (Salvelinus confluentus) metapopulation in the upper Flathead River system, Canada and USA, to assess how current and predicted future stream warming may influence population vulnerability. Results suggest that warmer water temperatures and associated barriers to movement (e.g., low flows, dewatering) are predicted to fragment suitable habitat for migratory salmonids, resulting in the loss of genetic diversity and reduced numbers in certain vulnerable populations. This demogenetic simulation framework, which is illustrated in a web-based interactive mapping prototype, should be useful for evaluating population vulnerability in a wide variety of dendritic and fragmented riverscapes, helping to guide conservation and management efforts for freshwater species. [ABSTRACT FROM AUTHOR]

Abstract: This paper examines the effect of raster cell size on hydrographic feature extraction and hydrological modeling using LiDAR derived DEMs. LiDAR datasets for three experimental watersheds were converted to DEMs at various cell sizes. Watershed boundaries and stream networks were delineated from each DEM and were compared to reference data. Hydrological simulations were conducted and the outputs were compared. Smaller cell size DEMs consistently resulted in less difference between DEM-delineated features and reference data. However, minor differences been found between streamflow simulations resulted for a lumped watershed model run at daily simulations aggregated at an annual average. These findings indicate that while higher resolution DEM grids may result in more accurate representation of terrain characteristics, such variations do not necessarily improve watershed scale simulation modeling. Hence the additional expense of generating high resolution DEM's for the purpose of watershed modeling at daily or longer time steps may not be warranted. [Copyright &y& Elsevier]

For ecological and environmental data, prior inquiries into spatial sampling designs have considered two-dimensional domains and have shown that design optimality depends on the characteristics of the target spatial domain and intended inference. The structure and water-driven continuity of streams prompted the development of spatial autocovariance models for stream networks. The unique properties of stream networks, and their spatial processes, warrant evaluation of sampling design characteristics in comparison with their two-dimensional counterparts. Common inference scenarios in stream networks include spatial prediction, estimation of fixed effects parameters, and estimation of autocovariance parameters, with prediction and fixed effects estimation most commonly coupled with autocovariance parameter estimation. We consider these inference scenarios under a suite of network characteristics and stream-network spatial processes. Our results demonstrate, for parameter estimation and prediction, the importance of collecting samples from specific network locations. Additionally, our results mirror aspects from the prior two-dimensional sampling design inquiries, namely, the importance of collecting some samples within clusters when autocovariance parameter estimation is required. These results can be applied to help refine sample site selection for future studies and further showcase that understanding the characteristics of the targeted spatial domain is essential for sampling design planning. Published 2014. This article has been contributed to by US Government employees and their work is in the public domain in the USA. [ABSTRACT FROM AUTHOR]