Search for: All records

In situ observed data are commonly used as species occurrence response variables in species distribution models. However, the use of remotely observed data from high‐resolution multispectral remote‐sensing images as a source of presence/absence data for species distribution models remains under‐developed. Here, we describe an ensemble species distribution model of black microbial mats "Nostoc" using presence/absence points derived from the unmixing of 4‐m resolution WorldView‐2 and WorldView‐3 images in the Lake Fryxell basin region of Taylor Valley, Antarctica. Environmental and topographical characteristics such as soil moisture, snow, elevation, slope, and aspect were used as predictor variables in our models. We demonstrate that we can build and run ensemble species distribution models using both dependent and independent variables derived from remote‐sensing data to generate spatially explicit habitat suitability maps. Snow and soil moisture were found to be the most important variables accounting for about 80% of the variation in the distribution of black mats throughout the Fryxell basin. This study highlights the potential contribution of high‐resolution remote‐sensing to species distribution modeling and informs new studies incorporating remotely derived species occurrences in species distribution models, especially in remote areas where access to in situ data is often limited. 

Land cover changes alter hydrologic (e.g., infiltration-runoff), biochemical (e.g., nutrient loads), and ecological processes (e.g., stream metabolism). We quantified differences in aquatic ecosystem respiration in two contrasting stream reaches from a forested watershed in Colorado (1st-order reach) and an agricultural watershed in Iowa (3rd-order reach). We conducted two rounds of experiments in each of these reaches, featuring four sets of continuous injections of Cl as a conservative tracer, resazurin as a proxy for aerobic respiration, and one of the following nutrient treatments: (a) N, (b) N + C, (c) N + P, and (d) C + N + P. With those methods providing consistent information about solute transport, stream respiration, and nutrient processing at the same spatiotemporal scales, we sought to address: (1) Are respiration rates correlated with conservative transport metrics in forested or agricultural streams? and (2) Can short-term modifications of stoichiometric conditions (C:N:P ratios) override respiration patterns, or do long-term physicochemical conditions control those patterns? We found greater respiration in the reach located in the forested watershed but no correlations between respiration, discharge, and advective or transient storage timescales. All the experiments conducted in the agricultural stream featured a reaction-limited transformation of resazurin, suggesting the existence of nutrient or carbon limitations on respiration that our short-term nutrient treatments did not remove. In contrast, the forested stream was characterized by nearly balanced transformation and transient storage timescales. We also found that our short-lived nutrient treatments had minimal influence on the significantly different respiration patterns observed between reaches, which are most likely driven by the longer-term and highly contrasting ambient nutrient concentrations at each site. Our experimental results agree with large-scale analyses suggesting greater microbial respiration in headwater streams in the U.S. Western Mountains region than in second-to-third-order streams in the U.S. Temperate Plains region. 

Water quality and freshwater ecosystems are affected by river discharge and temperature. Models are frequently used to estimate river temperature on large spatial and temporal scales due to limited observations of discharge and temperature. In this study, we use physically based river routing and temperature models to simulate daily discharge and river temperature for rivers in 138 basins in Alaska, including the entire Yukon River basin, from 1990–2021. The river temperature model was optimized for ice free months using a surrogate‐based model optimization method, improving model performance at uncalibrated river gages. A common statistical model relating local air and water temperature was used as a benchmark. The physically based river temperature model exhibited superior performance compared to the benchmark statistical model after optimization, suggesting river temperature model optimization could become more routine. The river temperature model demonstrated high sensitivity to air temperature and model parameterization, and lower sensitivity to discharge. Validation of the models showed a Kling‐Gupta Efficiency of 0.46 for daily river discharge and a root mean square error of 2.04°C for daily river temperature, improving on the non‐optimized physical model and the benchmark statistical model, which had root mean square errors of 3.24 and 2.97°C, respectively. The simulation shows that rivers in northern Alaska have higher maximum summer temperatures and more variability than rivers in the Central and Southern regions. Furthermore, this framework can be readily adapted for use across models and regions. 

Abstract Record high temperatures were documented in the McMurdo Dry Valleys, Antarctica, on 18 March 2022, exceeding average temperatures for that day by nearly 30°C. Satellite imagery and stream gage measurements indicate that surface wetting coincided with this warming more than 2 months after peak summer thaw and likely exceeded thresholds for rehydration and activation of resident organisms that typically survive the cold and dry conditions of the polar fall in a freeze‐dried state. This weather event is notable in both the timing and magnitude of the warming and wetting when temperatures exceeded 0°C at a time when biological communities and streams have typically entered a persistent frozen state. Such events may be a harbinger of future climate conditions characterized by warmer temperatures and greater thaw in this region of Antarctica, which could influence the distribution, activity, and abundance of sentinel taxa. Here we describe the ecosystem responses to this weather anomaly reporting on meteorological and hydrological measurements across the region and on later biological observations from Canada Stream, one of the most diverse and productive ecosystems within the McMurdo Dry Valleys. 

High spatial and temporal resolution models are essential for understanding future climate impacts and developing effective climate resilience plans. However, existing regional and global river models often lack the resolution needed to accurately capture local conditions. This study uses a series of high-resolution models, including the Regional Arctic System Model, mizuRoute, and the river basin model, to analyze Arctic and sub-Arctic Alaskan hydrology. We compare a historical baseline (1991–2020) with six midcentury (2035–64) futures: two pseudo–global warming scenarios based on historical meteorology and four direct dynamically downscaled global climate models. The six futures reveal significant uncertainty in future annual discharge and peak flows, although a widespread increase in discharge during April (+63%) and October (+31%) is consistently shown across models. Projected increases in rain and shifting weather patterns lead to a transition from snow to rain in spring and autumn, reducing the fraction of snowmelt contributing to river discharge. Rising evapotranspiration moderates discharge changes, particularly in autumn, by offsetting precipitation increases. Average summer river temperatures are projected to increase by approximately 1.5°C, doubling the number of river segments that experience 18°C days, a critical threshold for salmon survival, and intensifying the heat flux to the ocean adding an average of 3.3 × 10¹²MJ yr⁻¹. These changes in the hydrologic cycle could profoundly impact riverine and oceanic ecosystems, posing substantial challenges to communities reliant on these environments. Significance StatementThe purpose of this study is to enhance our understanding of the midcentury climate change impacts on the Alaskan hydrologic cycle. In all six of the potential future scenarios, river flows in spring and autumn are predicted to increase and river temperatures are projected to be warmer throughout the year. These changes are significant as higher river temperatures could jeopardize fish survival. Additionally, the combined effect of increased river water and higher temperatures during spring and autumn will contribute more heat to the ocean, possibly reducing nearshore sea ice. This is crucial because many communities depend on rivers and sea ice for transportation and subsistence activities. 

Abstract Aquatic ecosystems - lakes, ponds and streams - are hotspots of biodiversity in the cold and arid environment of Continental Antarctica. Environmental change is expected to increasingly alter Antarctic aquatic ecosystems and modify the physical characteristics and interactions within the habitats that they support. Here, we describe physical and biological features of the peripheral ‘moat’ of a closed-basin Antarctic lake. These moats mediate connectivity amongst streams, lake and soils. We highlight the cyclical moat transition from a frozen winter state to an active open-water summer system, through refreeze as winter returns. Summer melting begins at the lakebed, initially creating an ice-constrained lens of liquid water in November, which swiftly progresses upwards, creating open water in December. Conversely, freezing progresses slowly from the water surface downwards, with water at 1 m bottom depth remaining liquid until May. Moats support productive, diverse benthic communities that are taxonomically distinct from those under the adjacent permanent lake ice. We show how ion ratios suggest that summer exchange occurs amongst moats, streams, soils and sub-ice lake water, perhaps facilitated by within-moat density-driven convection. Moats occupy a small but dynamic area of lake habitat, are disproportionately affected by recent lake-level rises and may thus be particularly vulnerable to hydrological change. 

Abstract Stream solute tracers are commonly injected to assess transport and transformation in study reaches, but results are biased toward the shortest and fastest storage locations. While this bias has been understood for decades, the impact of an experimental constraint on our understanding has yet to be considered. Here, we ask how different our understanding of reach‐ and segment‐scale transport would be if our empirical limits were extended. We demonstrate a novel approach to manipulate experimental conditions and observe mass that is stored at timescales beyond the traditional reach‐scale window of detection. We are able to explain the fate of an average of 26% of solute tracer mass that would have been considered as “lost” in a traditional study design across our 14 replicates, extending our detection limits to characterize flowpaths that would have been previously unmeasured. We demonstrate how this formerly lost mass leads to predicting lower magnitudes of gross gains and losses in individual reaches, and ultimately show that the network turnover we infer from solute tracers represents an upper limit on actual, expected behavior. Finally, we review the evolution of tracer studies and their interpretation including this approach and provide a proposed future direction to extend empirical studies to not‐before‐seen timescales. 

Abstract Arctic hydrology is experiencing rapid changes including earlier snow melt, permafrost degradation, increasing active layer depth, and reduced river ice, all of which are expected to lead to changes in stream flow regimes. Recently, long-term (>60 years) climate reanalysis and river discharge observation data have become available. We utilized these data to assess long-term changes in discharge and their hydroclimatic drivers. River discharge during the cold season (October–April) increased by 10% per decade. The most widespread discharge increase occurred in April (15% per decade), the month of ice break-up for the majority of basins. In October, when river ice formation generally begins, average monthly discharge increased by 7% per decade. Long-term air temperature increases in October and April increased the number of days above freezing (+1.1 d per decade) resulting in increased snow ablation (20% per decade) and decreased snow water equivalent (−12% per decade). Compared to the historical period (1960–1989), mean April and October air temperature in the recent period (1990–2019) have greater correlation with monthly discharge from 0.33 to 0.68 and 0.0–0.48, respectively. This indicates that the recent increases in air temperature are directly related to these discharge changes. Ubiquitous increases in cold and shoulder-season discharge demonstrate the scale at which hydrologic and biogeochemical fluxes are being altered in the Arctic.