Soil moisture is an important driver of growth in boreal Alaska, but estimating soil hydraulic parameters can be challenging in this data-sparse region. Parameter estimation is further complicated in regions with rapidly warming climate, where there is a need to minimize model error dependence on interannual climate variations. To better identify soil hydraulic parameters and quantify energy and water balance and soil moisture dynamics, we applied the physically based, one-dimensional ecohydrological Simultaneous Heat and Water (SHAW) model, loosely coupled with the Geophysical Institute of Permafrost Laboratory (GIPL) model, to an upland deciduous forest stand in interior Alaska over a 13-year period. Using a Generalized Likelihood Uncertainty Estimation parameterisation, SHAW reproduced interannual and vertical spatial variability of soil moisture during a five-year validation period quite well, with root mean squared error (RMSE) of volumetric water content at 0.5 m as low as 0.020 cm(3)/cm(3). Many parameter sets reproduced reasonable soil moisture dynamics, suggesting considerable equifinality. Model performance generally declined in the eight-year validation period, indicating some overfitting and demonstrating the importance of interannual variability in model evaluation. We compared the performance of parameter sets selected based on traditional performance measures such as the RMSE that minimize error in soil moisture simulation, with one that is designed to minimize the dependence of model error on interannual climate variability using a new diagnostic approach we call CSMP, which stands for Climate Sensitivity of Model Performance. Use of the CSMP approach moderately decreases traditional model performance but may be more suitable for climate change applications, for which it is important that model error is independent from climate variability. These findings illustrate (1) that the SHAW model, coupled with GIPL, can adequately simulate soil moisture dynamics in this boreal deciduous region, (2) the importance of interannual variability in model parameterisation, and (3) a novel objective function for parameter selection to improve applicability in non-stationary climates.

Climate change in the European Alps during recent years has led to decreased snow cover duration as well as increases in the frequency and intensity of summer heat waves. The risk of drought for alpine wetlands and temporary pools, which rely on water from snowmelt and provide habitat for specialist plant and amphibian biodiversity, is largely unknown and understudied in this context. Here, we test and validate a novel application of Sentinel-2 imagery aimed at quantifying seasonal variation in water surface area in the context of 95 small (median surface area <100 m(2)) and shallow (median depth of 20 cm) alpine wetlands in the French Alps, using a linear spectral unmixing approach. For three study years (2016-2018), we used path-analysis to correlate mid-summer water surface area to annual metrics of snowpack (depth and duration) and spring and summer climate (temperature and precipitation). We further sought to evaluate potential biotic responses to drought for study years by monitoring the survival of common frog (Rana temporaria) tadpoles and wetland plant biomass production quantified using peak Normalized Difference Vegetation Index (NDVI). We found strong agreement between citizen science-based observations of water surface area and Sentinel-2 based estimates (R-2= 0.8-0.9). Mid-summer watershed snow cover duration and summer temperatures emerged as the most important factors regulating alpine wetland hydrology, while the effects of summer precipitation, and local and watershed snow melt-out timing were not significant. We found that a lack of summer snowfields in 2017 combined with a summer heat wave resulted in a significant decrease in mid-summer water surface area, and led to the drying up of certain wetlands as well as the observed mortality of tadpoles. We did not observe a negative effect of the 2017 summer on the biomass production of wetland vegetation, suggesting that wetlands that maintain soil moisture may act as favorable microhabitats for above treeline vegetation during dry years. Our work introduces a remote sensing-based protocol for monitoring the surface hydrology of alpine wetland habitats at the regional scale. Given that climate models predict continued reduction of snow cover in the Alps during the coming years, as well as particularly intense warming during the summer months, our conclusions underscore the vulnerability of alpine wetlands in the face of ongoing climate change.

Shifts from longer seasonal snowpacks to shorter, ephemeral snowpacks (snowpacks that persist for <60days) due to climate change will alter the timing and rates of water availability. Ephemeral snowmelt has less predictable timing and lowers soil water availability during the growing season. The Great Basin, United States is an ideal system to study snow ephemerality across a broad climate gradient. To identify the climatic controls on snow ephemerality, we analysed moderate resolution imaging spectroradiometer (MODIS) snow-covered products from water years 2001-2015 using an object-based mapping approach and a random forest model. Winter temperature and precipitation were the most influential variables on the maximum snow duration. We predict that warming the average winter air temperature by 2 and 4 degrees C would reduce the areal extent of seasonal snow by 14.7 and 47.8%, respectively (8.8% of the Great Basin's areal extent is seasonal in the historical record), with shifts to ephemeral snowpack concentrated in lower elevations and warmer regions. The combination of warming and interannual precipitation variability (i.e., reductions of 25%) had different effects on vegetation types. Vegetation types that have had consistent seasonal snow cover in their historical record are likely to have lower resilience to a new hydrologic regime, with earlier and more intermittent snowmelt causing a longer but drier growing season. Implications of increased snow ephemerality on vegetation productivity and susceptibility to disturbance will depend on local topography, subsurface water storage, and physiological adaptations. Nevertheless, patterns found in this study can help target management intervention to species that are most at risk.

Mountain ecosystems are experiencing rapid warming resulting in ecological changes worldwide. Projecting the response of these ecosystems to climate change is thus crucial, but also uncertain due to complex interactions between topography, climate, and vegetation. Here, we performed numerical simulations in a real and a synthetic spatial domain covering a range of contrasting climatic conditions and vegetation characteristics representative of the European Alps. Simulations were run with the mechanistic ecohydrological model Tethys-Chloris to quantify the drivers of ecosystem functioning and to explore the vulnerability of Alpine ecosystems to climate change. We correlated the spatial distribution of ecohydrological responses with that of meteorological and topographic attributes and computed spatially explicit sensitivities of net primary productivity, transpiration, and snow cover to air temperature, radiation, and water availability. We also quantified how the variance in several ecohydrological processes, such as transpiration, quickly diminishes with increasing spatial aggregation, which highlights the importance of fine spatial resolution for resolving patterns in complex topographies. We conducted controlled numerical experiments in the synthetic domain to disentangle the effect of catchment orientation on ecohydrological variables, such as streamflow. Our results support previous studies reporting an altitude threshold below which Alpine ecosystems are water-limited in the drier inner-Alpine valleys and confirm that the wetter areas are temperature-limited. High-resolution simulations of mountainous areas can improve our understanding of ecosystem functioning across spatial scales. They can also locate the areas that are the most vulnerable to climate change and guide future measurement campaigns.

The effect of thawing permafrost on boreal ecosystem water cycling represents a significant knowledge gap of how climate change will affect northern landscapes. Evapotranspiration, particularly transpiration, may be changing in response to changes in permafrost conditions, vegetation, and climate. This study focuses on the effect of permafrost thaw on boreal plant transpiration over two summers with contrasting weather conditions. We quantified the response of stomatal conductance (gs), from which transpiration was calculated, of deciduous and evergreen plants to soil environmental factors that permafrost thaw affects: soil water content (S), depth of seasonal thaw (D), and soil temperature (T). We found that gs was least sensitive to T compared with S and D at both sites and across both years. At the thawing site, gs was more sensitive to S in a dry year (2009) and to D in a wet year (2010). In the wet year, S of similar to 50cm represented a threshold wherein the sensitivity of gs to T and D switched between positive (S50cm). However, the sensitivities to T and D were negative when S was consistently less than 50cm in the dry year. This is one of the first studies to explore the effect of permafrost thaw on boreal plant gs and transpiration, and our model predicted higher transpiration rates from deciduous plants located on thawing permafrost. Copyright (c) 2013 John Wiley & Sons, Ltd.

Subalpine mixed-conifer ecosystems are dependent on snowfall, which is expected to decrease under projected climate change. Changes in snowpack are likely to have important consequences for water and carbon cycling in these and downstream ecosystems. Particularly within semi-arid environments, snowpack changes will directly influence localized water and carbon dynamics and indirectly influence regional-scale levels of water availability and carbon sequestration. In this study, we monitor soil evaporation (E) and soil respiration (R) and evaluate how snow cover affects these effluxes within a mixed-conifer ecosystem within the Santa Catalina Mountains about 10km north of Tucson, Arizona. Using time-lapse digital photos, we identified areas of consistent short and long snow duration, and we monitored E and R in these areas every 2weeks for 15months. Our primary findings include the following: (1) Dynamics of E are not different between long and short snow season sites, (2) E for both short and long snow seasons has a strong relationship with soil moisture and a poor relationship with soil temperature, (3) dynamics of R vary between long and short snow season sites throughout the year, with short snow season fluxes typically higher than those of long snow season sites, and (4) R for short and long snow seasons has a strong relationship with soil temperature and a poor relationship with soil moisture. Because climate change will only exacerbate both drying-wetting and cooling-warming cycles, detangling these complex relationships becomes increasingly important for understanding shifts in carbon dynamics in these subalpine mixed-conifer ecosystems. Copyright (c) 2013 John Wiley & Sons, Ltd.