Natural selection on floral volatiles and other traits can change with snowmelt timing and summer precipitation.

Climate change is disrupting floral traits that mediate mutualistic and antagonistic species interactions. Plastic responses of these traits to multiple shifting conditions may be adaptive, depending on natural selection in new environments. We manipulated snowmelt date over three seasons (3-11 d earlier) in factorial combination with growing-season precipitation (normal, halved, or doubled) to measure plastic responses of volatile emissions and other floral traits in Ipomopsis aggregata. We quantified how precipitation and early snowmelt affected selection on traits by seed predators and pollinators. Within years, floral emissions did not respond to precipitation treatments but shifted with snowmelt treatment depending on the year. Across 3 yr, emissions correlated with both precipitation and snowmelt date. These effects were driven by changes in soil moisture. Selection on several traits changed with earlier snowmelt or reduced precipitation, in some cases driven by predispersal seed predation. Floral trait plasticity was not generally adaptive. Floral volatile emissions shifted in the face of two effects of climate change, and the new environments modulated selection imposed by interacting species. The complexity of the responses underscores the need for more studies of how climate change will affect floral volatiles and other floral traits.

Global temperature homogenization can obliterate temporal isolation in migratory animals with potential loss of population structure.

Climate change is expected to increase the spatial autocorrelation of temperature, resulting in greater synchronization of climate variables worldwide. Possibly such 'homogenization of the world' leads to elevated risks of extinction and loss of biodiversity. In this study, we develop an empirical example on how increasing synchrony of global temperatures can affect population structure in migratory animals. We studied two subspecies of bar-tailed godwits Limosa lapponica breeding in tundra regions in Siberia: yamalensis in the west and taymyrensis further east and north. These subspecies share pre- and post-breeding stopover areas, thus being partially sympatric, but exhibiting temporal segregation. The latter is believed to facilitate reproductive isolation. Using satellite tracking data, we show that migration timing of both subspecies is correlated with the date of snowmelt in their respective breeding sites (later at the taymyrensis breeding range). Snow-cover satellite images demonstrate that the breeding ranges are on different climate trajectories and become more synchronized over time: between 1997 and 2020, the date of snowmelt advanced on average by 0.5 days/year in the taymyrensis breeding range, while it remained stable in the yamalensis breeding range. Previous findings showed how taymyrensis responded to earlier snowmelt by advancing arrival and clutch initiation. In the predicted absence of such advancements in yamalensis, we expect that the two populations will be synchronized by 2036-2040. Since bar-tailed godwits are social migrants, this raises the possibility of population exchange and prompts the question whether the two subspecies can maintain their geographic and morphological differences and population-specific migratory routines. The proposed scenario may apply to a wide range of (social) migrants as temporal segregation is crucial for promoting and maintaining reproductive isolation in many (partially sympatric) migratory populations. Homogenization of previously isolated populations could be an important consequence of increasing synchronized environments and hence climate change.

Altitude characteristics in the response of rain-on-snow flood risk to future climate change in a high-latitude water tower.

Global warming is profoundly impacting snowmelt runoff processes in seasonal freeze-thaw zones, thereby altering the risk of rain-on-snow (ROS) floods. These changes not only affect the frequency of floods but also alter the allocation of water resources, which has implications for agriculture and other key economic sectors. While these risks present a significant threat to our lives and economies, the risk of ROS floods triggered by climate change has not received the attention it deserves. Therefore, we chose Changbai Mountain, a water tower in a high-latitude cold zone, as a typical study area. The semi-distributed hydrological model SWAT is coupled with CMIP6 meteorological data, and four shared socioeconomic pathways (SSP126, SSP245, SSP370, and SSP585) are selected after bias correction, thus quantifying the impacts of climate change on hydrological processes in the Changbai Mountain region as well as future evolution of the ROS flood risk. The results indicate that: (1) Under future climate change scenarios, snowmelt in most areas of the Changbai Mountains decreases. The annual average snowmelt under SSP126, SSP245, SSP370, and SSP585 is projected to be 148.65 mm, 135.63 mm, 123.44 mm, and 116.5 mm, respectively. The onset of snowmelt is projected to advance in the future. Specifically, in the Songhua River (SR) and Yalu River (YR) regions, the start of snowmelt is expected to advance by 1-11 days. Spatially, significant reductions in snowmelt were observed in both the central part of the watershed and the lower reaches of the river under SSP585 scenario. (2) In 2021-2060, the frequency of ROS floods decreases sequentially for different scenarios, with SSP 126 > SSP 245 > SSP 370 > SSP 585. The frequency increments of ROS floods in the source area for the four scenarios were 0.12 days/year, 0.1 d/yr, 0.13 days/year, and 0.15 days/year, respectively. The frequency of high-elevation ROS events increases in the YR in the low emission scenario. Conversely, in high emission scenarios, YR high-elevation ROS events will only increase in 2061-2100. This phenomenon is more pronounced in the Tumen River (TR), where floods become more frequent with increasing elevation.

Differences in individual flowering time change pollen limitation and seed set in three montane wildflowers.

PREMISE: Changes to flowering time caused by climate change could affects plant fecundity, but studies that compare the individual-level responses of phenologically distinct, co-occurring species are lacking. We assessed how variation in floral phenology affects the fecundity of individuals from three montane species with different seasonal flowering times, including in snowmelt acceleration treatments to increase variability in phenology. METHODS: We collected floral phenology and seed set data for individuals of three montane plant species (Mertensia fusiformis, Delphinium nuttallianum, Potentilla pulcherrima). To examine the drivers of seed set, we measured conspecific floral density and conducted pollen limitation experiments to isolate pollination function. We advanced the phenology of plant communities in a controlled large-scale snowmelt acceleration experiment. RESULTS: Differences in individual phenology relative to the rest of the population affected fecundity in our focal species, but effects were species-specific. For our early-season species, individuals that bloomed later than the population peak bloom had increased fecundity, while for our midseason species, simply blooming before or after the population peak increased individual fecundity. For our late-season species, blooming earlier than the population peak increased fecundity. The early and midseason species were pollen-limited, and conspecific density affected seed set only for our early-season species. CONCLUSIONS: Our study shows that variation in individual phenology affects fecundity in three phenologically distinct montane species, and that pollen limitation may be more influential than conspecific density. Our results suggest that individual-level changes in phenology are important to consider for understanding plant reproductive success.

Variability of green infrastructure performance due to climatic regimes across Sweden.

In the context of increasing urbanization and global warming, there is a growing interest in the implementation of green infrastructure (GI) across different climates and regions. Identifying an appropriate GI design criteria is essential to ensure that the design is tailored to satisfy local environmental requirements. This article aims to compare the hydrological performance of GI facilities in eleven Swedish cities by isolating the effect of climatic conditions using an identical GI design configuration. Long-term simulations based on 23-years of meteorological time-series were used as inputs for the Storm Water Management Model (SWMM) with Low Impact Development (LID) controls representing two types of facilities: a biofilter cell (BC) and a green roof. (GR). Large differences in potential annual and seasonal runoff retention were found between locations, driven mainly by the extent of winter/spring season, and the distribution of precipitation patterns (for BCs) and the sequence of rainy days-dry periods and evapotranspiration rates (for GRs). Winter/spring and summer demonstrated the highest/lowest differences between the seasons, results that suggest that implications for design might be aligned to the spatio-temporal distribution of precipitation patterns, and runoff regimes generated by snowmelt and rain-on-snow events, in locations where snowmelt represent high portion of runoff generation.

Estimation of monthly snowmelt contribution to runoff using gridded meteorological data in SWAT model for Upper Alaknanda River Basin, India.

The purpose of hydrologic modeling of a watershed is to gain valuable information about the processes occurring within watershed. With increasing temperature of the earth atmosphere, the snow fed mountainous river basins are going to get impacted severely. Lack of adequate weather station limits the scope of researches in these mountainous basins which are critical source of water resource for the country. However, improvement of satellite-based weather products has been able to nullify this barrier to great extent. In this study, a semi distributed hydrologic model of Upper Alaknanda river basin has been developed using gridded meteorological input data sourced from India Meteorological Department (IMD), National Aeronautics and Space Administration (NASA) Power, and The SWAT (Soil and water Assessment Tool) model. The calibration and validation of the model reflected satisfactory performance with the validation period (2013-2017) showing better match between simulated and observed flow than calibration period (2005-2012). The values of Nash-Sutcliffe efficiency, coefficient of determination, and Percent of bias for calibration period are 0.65, 0.67, and 14% respectively. Adoption of semi distributed approach for modeling enables to analyze the basin while preserving the heterogeneous nature of the basin. The spatiotemporal evaluation of snowmelt reveals that highest snowmelt was generated during month of April which also causes highest snowmelt contribution to runoff for April (59.76 %). The outcomes of this study reveals that satellite-based meteorological product can be adopted satisfactorily with SWAT model for estimation of snowmelt in upper Himalayan regions which gives a new direction of research in SWAT diaspora.

Phenotypic plasticity and selection on leaf traits in response to snowmelt timing and summer precipitation.

Vegetative traits of plants can respond directly to changes in the environment, such as those occurring under climate change. That phenotypic plasticity could be adaptive, maladaptive, or neutral. We manipulated the timing of spring snowmelt and amount of summer precipitation in factorial combination and examined responses of specific leaf area (SLA), trichome density, leaf water content (LWC), photosynthetic rate, stomatal conductance and intrinsic water-use efficiency (iWUE) in the subalpine herb Ipomopsis aggregata. The experiment was repeated in three years differing in natural timing of snowmelt. To examine natural selection, we used survival, relative growth rate, and flowering as fitness indices. A 50% reduction in summer precipitation reduced stomatal conductance and increased iWUE, and doubled precipitation increased LWC. Combining natural and experimental variation, earlier snowmelt reduced soil moisture, photosynthetic rate and stomatal conductance, and increased trichome density and iWUE. Precipitation reduction reversed the mortality selection favoring high stomatal conductance under normal and doubled precipitation, and higher LWC improved growth. Earlier snowmelt is a strong signal of climate change and can change expression of leaf morphology and gas exchange traits, just as reduced precipitation can. Stomatal conductance and SLA showed adaptive plasticity under some conditions.

Flowering time advances since the 1970s in a sagebrush steppe community: Implications for management and restoration.

Climate change is widely known to affect plant phenology, but little is known about how these impacts manifest in the widespread sagebrush ecosystem of the Western United States, which supports a number of wildlife species of concern. Shifts in plant phenology can trigger consequences for the plants themselves as well as the communities of consumers that depend upon them. We assembled historical observations of first-flowering dates for 51 species collected in the 1970s and 1980s in a montane sagebrush community in the Greater Yellowstone Ecosystem and compared these to contemporary phenological observations targeting the same species and locations (2016-2019). We also assembled regional climate data (average spring temperature, day of spring snowmelt, and growing degree days) and tested the relationship between first-flowering time and these variables for each species. We observed the largest change in phenology in early-spring flowers, which, as a group, bloomed on average 17 days earlier, and as much as 36 days earlier, in the contemporary data set. Mid-summer flowers bloomed on average 10 days earlier, nonnative species 15 days earlier, and berry-producing shrubs 5 days earlier, while late summer flowering plants did not shift. The greatest correlates of early-spring and mid-summer flowering were average spring temperature and day of snowmelt, which was 21 days earlier, on average, in 2016-2019 relative to the 1973-1978 observations. The shifts in flowering phenology that we observed could indicate developing asynchronies or novel synchronies of these plant resources and wildlife species of conservation concern, including Greater Sage-grouse, whose nesting success is tied to availability of spring forbs; grizzly bears, which rely heavily on berries for their fall diet; and pollinators. This underscores the importance of maintaining a diverse portfolio of native plants in terms of species composition, genetics, phenological responsiveness to climatic cues, and ecological importance to key wildlife and pollinator species. Redundancy within ecological niches may also be important considering that species roles in the community may shift as climate change affects them differently. These considerations are particularly relevant to restoration and habitat-enhancement projects in sagebrush communities across western North America.

Early snowmelt projected to cause population decline in a subalpine plant.

How climate change influences the dynamics of plant populations is not well understood, as few plant studies have measured responses of vital rates to climatic variables and modeled the impact on population growth. The present study used 25 y of demographic data to analyze how survival, growth, and fecundity respond to date of spring snowmelt for a subalpine plant. Fecundity was estimated by seed production (over 15 y) and also divided into flower number, fruit set, seeds per fruit, and escape from seed predation. Despite no apparent effects on flower number, plants produced more seeds in years with later snowmelt. Survival and probability of flowering were reduced by early snowmelt in the previous year. Based on demographic models, earlier snowmelt with warming is expected to lead to negative population growth, driven especially by changes in seedling establishment and seed production. These results provide a rare example of how climate change is expected to influence the dynamics of a plant population. They furthermore illustrate the potential for strong population impacts even in the absence of more commonly reported visual signs, such as earlier blooming or reduced floral display in early melting years.

Earlier winter/spring runoff and snowmelt during warmer winters lead to lower summer chlorophyll-a in north temperate lakes.

Winter conditions, such as ice cover and snow accumulation, are changing rapidly at northern latitudes and can have important implications for lake processes. For example, snowmelt in the watershed-a defining feature of lake hydrology because it delivers a large portion of annual nutrient inputs-is becoming earlier. Consequently, earlier and a shorter duration of snowmelt are expected to affect annual phytoplankton biomass. To test this hypothesis, we developed an index of runoff timing based on the date when 50% of cumulative runoff between January 1 and May 31 had occurred. The runoff index was computed using stream discharge for inflows, outflows, or for flows from nearby streams for 41 lakes in Europe and North America. The runoff index was then compared with summer chlorophyll-a (Chl-a) concentration (a proxy for phytoplankton biomass) across 5-53 years for each lake. Earlier runoff generally corresponded to lower summer Chl-a. Furthermore, years with earlier runoff also had lower winter/spring runoff magnitude, more protracted runoff, and earlier ice-out. We examined several lake characteristics that may regulate the strength of the relationship between runoff timing and summer Chl-a concentrations; however, our tested covariates had little effect on the relationship. Date of ice-out was not clearly related to summer Chl-a concentrations. Our results indicate that ongoing changes in winter conditions may have important consequences for summer phytoplankton biomass and production.

Winter snow and spring temperature have differential effects on vegetation phenology and productivity across Arctic plant communities.

Tundra dominates two-thirds of the unglaciated, terrestrial Arctic. Although this region has experienced rapid and widespread changes in vegetation phenology and productivity over the last several decades, the specific climatic drivers responsible for this change remain poorly understood. Here we quantified the effect of winter snowpack and early spring temperature conditions on growing season vegetation phenology (timing of the start, peak, and end of the growing season) and productivity of the dominant tundra vegetation communities of Arctic Alaska. We used daily remotely sensed normalized difference vegetation index (NDVI), and daily snowpack and temperature variables produced by SnowModel and MicroMet, coupled physically based snow and meteorological modeling tools, to (1) determine the most important snowpack and thermal controls on tundra vegetation phenology and productivity and (2) describe the direction of these relationships within each vegetation community. Our results show that soil temperature under the snowpack, snowmelt timing, and air temperature following snowmelt are the most important drivers of growing season timing and productivity among Arctic vegetation communities. Air temperature after snowmelt was the most important control on timing of season start and end, with warmer conditions contributing to earlier phenology in all vegetation communities. In contrast, the controls on the timing of peak season and productivity also included snowmelt timing and soil temperature under the snowpack, dictated in part by the snow insulating capacity. The results of this novel analysis suggest that while future warming effects on phenology may be consistent across communities of the tundra biome, warming may result in divergent, community-specific productivity responses if coupled with reduced snow insulating capacity lowers winter soil temperature and potential nutrient cycling in the soil.

Evaluation of measured dissolved and bio-met predicted bioavailable Cu, Ni and Zn concentrations in runoff from three urban catchments.

Urban runoff is a diffuse source of pollution contributing to the poor ecological and chemical status of surface waters. Whilst the EU Priority Hazardous Substances Directive now identifies environmental quality standards for selected metals in relation to the bioavailable metal fraction the relationship between analytically determined metal size fractions transported by urban runoff and the often variably defined concept of bioavailability has not been thoroughly evaluated. This paper provides a review of the terminology used within urban runoff studies to characterise metal fractions and behaviour. Measured dissolved and truly dissolved (determined by ultrafiltration; <3000 molecular weight cutoff) Cu, Ni, and Zn concentrations are also compared to the bioavailable metal fraction (as predicted using Bio-met, a simplified biotic ligand model) in snowmelt and rainfall derived runoff samples from three urban catchments. The study shows that predicted bioavailable concentrations were significantly lower than truly dissolved concentrations for all metals and discusses current bioavailability modelling parameters in relation to rainfall and snowmelt runoff data sets. Statistical analysis of relationships between field and predicted bioavailable data sets indicate that the bioavailable fractions originate from both colloidal and truly dissolved fractions.

Impact of climate change on snowmelt runoff in a Himalayan basin, Nepal.

The Hindu Kush Himalaya (HKH) is one of the major sources of fresh water on Earth and is currently under serious threat of climate change. This study investigates the future water availability in the Langtang basin, Central Himalayas, Nepal under climate change scenarios using state-of-the-art machine learning (ML) techniques. The daily snow area for the region was derived from MODIS images. The outputs of climate models were used to project the temperature and precipitation until 2100. Three ML models, including Gated recurrent unit (GRU), Long short-term memory (LSTM), and Recurrent neural network (RNN), were developed for snowmelt runoff prediction, and their performance was compared based on statistical indicators. The result suggests that the mean temperature of the basin could rise by 4.98 °C by the end of the century. The annual average precipitation in the basin is likely to increase in the future, especially due to high monsoon rainfall, but winter precipitation could decline. The annual river discharge is projected to upsurge significantly due to increased precipitation and snowmelt, and no shift in hydrograph is expected in the future. Among three ML models, the LSTM model performed better than GRU and RNN models. In summary, this study depicts severe future climate change in the region and quantifies its effect on river discharge. Furthermore, the study demonstrates the suitability of the LSTM model in streamflow prediction in the data-scarce HKH region. The outcomes of this study will be useful for water resource managers and planners in developing strategies to harness the positive impacts and offset the negative effects of climate change in the basin.

Regulation of Cu and Zn migration in soil by biochar during snowmelt.

To study the migration characteristics of the heavy metals Cu and Zn carried by snowmelt water infiltrating soil during snowmelt periods and the regulation of this process by biochar, field experiments were carried out in which the variation in the Cu and Zn contents in soils on bare land (S1) and in soils with biochar coverage (S2) were analysed before snowfall and during snowmelt periods, and the degree of Cu and Zn pollution was determined on the basis of the enrichment factor (EF) and index of geoaccumulation (Igeo). The migration characteristics of Cu and Zn in soil were studied by combining the migration coefficient and leaching ratio. During the snowmelt period, the use of biochar reduced the migration coefficients of Cu and Zn carried by snowmelt water in shallow soil. The transport coefficients (Tj) of Cu and Zn in shallow soil (0-30 cm) in the S2 treatment were 0.89 and 0.81, respectively, lower than those in the S1 treatment. In addition, during the snowmelt period, the leaching ratios (Cij) of Cu and Zn in the 0-10 cm soil layer of the S2 treatment were 0.22 and 0.24 less than those of the S1 treatment, the index of geoaccumulation (Igeo) was 0.52 and 0.23 less, and the enrichment factor (EF) was 1.20 and 0.09 less, respectively. This study provides practical and theoretical guidance for future research on soil heavy metal pollution mitigation.

Early snowmelt significantly enhances boreal springtime carbon uptake.

We determine the annual timing of spring recovery from space-borne microwave radiometer observations across northern hemisphere boreal evergreen forests for 1979-2014. We find a trend of advanced spring recovery of carbon uptake for this period, with a total average shift of 8.1 d (2.3 d/decade). We use this trend to estimate the corresponding changes in gross primary production (GPP) by applying in situ carbon flux observations. Micrometeorological CO2 measurements at four sites in northern Europe and North America indicate that such an advance in spring recovery would have increased the January-June GPP sum by 29 g⋅C⋅m-2 [8.4 g⋅C⋅m-2 (3.7%)/decade]. We find this sensitivity of the measured springtime GPP to the spring recovery to be in accordance with the corresponding sensitivity derived from simulations with a land ecosystem model coupled to a global circulation model. The model-predicted increase in springtime cumulative GPP was 0.035 Pg/decade [15.5 g⋅C⋅m-2 (6.8%)/decade] for Eurasian forests and 0.017 Pg/decade for forests in North America [9.8 g⋅C⋅m-2 (4.4%)/decade]. This change in the springtime sum of GPP related to the timing of spring snowmelt is quantified here for boreal evergreen forests.

Soil erosion and radiocesium migration during the snowmelt period in grasslands and forested areas of Miyagi prefecture, Japan.

This study aimed to examine the influence of snowmelt on soil erosion processes in mountainous landscapes in the Miyagi prefecture of Japan. The investigated slopes had different expositions and were covered with grasslands and forests. The snowpack thickness, soil frost depth, volume of surface runoff, physicochemical properties of the soil and sediments, cesium composition of the snow and meltwater, and air dose rate were determined. In mid-February, snow cover reached its maximum thickness (100-179 cm). In the forest, the snow depth was always lower by 15-20 cm. The soil did not freeze in winter in any of the plots. Surface runoff was observed only in the grassland plots and depended on the slope aspect. The total volume of surface runoff ranged from 31 to 52 mm and snowmelt soil losses ranged from 2 to 9 kg ha-1 DM. Radiocesium concentrations in runoff samples ranged from 0.1 to 8.4 Bq L-1, below the standard limit for drinking water in Japan (10 Bq L-1). The average organic matter content of the sampled sediments was 0.4%, higher than that in the surface soil. The silt fraction in sediments became dominant for particle size distribution, and the activity concentration of total radiocesium was, on average, 250 Bq kg-1. The air dose rate was always lower than the maximum permissible level (0.2 µSv h-1) and varied from 0.02 to 0.09 µSv h-1 in winter, and from 0.08 to 0.13 µSv h-1 at times of the year without snow.

Snowmelt periods as hot moments for soil N dynamics: a case study in Maine, USA.

The vernal transition represents the seasonal transition to spring, occurring as temperatures rise at the end of winter. With rapid snowmelt, microbial community turnover, and accelerated nutrient cycling, this is a critical but relatively under-studied period of ecosystem function. We conducted a study over two consecutive winters (2015-2016) at the Bear Brook Watershed in Maine to examine how changing winter conditions (warming winters, reduced snow accumulation) altered soil nitrogen availability and stream N export during winter and the vernal transition, and how these patterns were influenced by ecosystem N status (N-enriched vs. N-limited). Of the two study years, 2016 had a warmer winter with substantially less snow accumulation and a discontinuous snowpack-and as a result, had a longer vernal transition and a snowpack that thawed before the vernal transition began. Across both years, snowmelt triggered a transition, signaled by increased ammonium concentrations in soil, decreased soil nitrate concentrations due to flushing by meltwater, and increased stream nitrate exports. Despite the contrasting winter conditions, both years showed similar patterns in N availability and export, differing only in the timing of these transitions. The vernal transition has conventionally been considered a critical period for biogeochemical cycling, because the associated snowmelt event triggers physicochemical and biochemical changes in soil systems. This was consistent with our results in 2015, but our data for 2016 show that this may not always hold true, and instead, that warmer, low-snow winters may demonstrate a temporal asynchrony between snowmelt and the vernal transition. We also show that ecosystem N status is a strong driver of the seasonal N pattern, and the interaction of N status and changing climate must be further investigated to understand ecosystem function under our current predicted trajectory of warming winters, declining snowfall, and winter thaw events.

When spring ephemerals fail to meet pollinators: mechanism of phenological mismatch and its impact on plant reproduction.

The flowering phenology of early-blooming plants is largely determined by snowmelt timing in high-latitude and high-altitude ecosystems. When the synchrony of flowering and pollinator emergence is disturbed by climate change, seed production may be restricted due to insufficient pollination success. We revealed the mechanism of phenological mismatch between a spring ephemeral ( Corydalis ambigua) and its pollinator (overwintered bumblebees), and its impact on plant reproduction, based on 19 years of monitoring and a snow removal experiment in a cool-temperate forest in northern Japan. Early snowmelt increased the risk of phenological mismatch under natural conditions. Seed production was limited by pollination success over the 3 years of the pollination experiment and decreased when flowering occurred prior to bee emergence. Similar trends were detected on modification of flowering phenology through snow removal. Following snowmelt, the length of the pre-flowering period strongly depended on the ambient surface temperature, ranging from 4 days (at greater than 7°C) to 26 days (at 2.5°C). Flowering onset was explained with an accumulated surface degree-day model. Bumblebees emerged when soil temperature reached 6°C, which was predictable by an accumulated soil degree-day model, although foraging activity after emergence might depend on air temperature. These results indicate that phenological mismatch tends to occur when snow melts early but subsequent soil warming progresses slowly. Thus, modification of the snowmelt regime could be a major driver disturbing spring phenology in northern ecosystems.

Snowmelt and early to mid-growing season water availability augment tree growth during rapid warming in southern Asian boreal forests.

Boreal forests are facing profound changes in their growth environment, including warming-induced water deficits, extended growing seasons, accelerated snowmelt, and permafrost thaw. The influence of warming on trees varies regionally, but in most boreal forests studied to date, tree growth has been found to be negatively affected by increasing temperatures. Here, we used a network of Pinus sylvestris tree-ring collections spanning a wide climate gradient the southern end of the boreal forest in Asia to assess their response to climate change for the period 1958-2014. Contrary to findings in other boreal regions, we found that previously negative effects of temperature on tree growth turned positive in the northern portion of the study network after the onset of rapid warming. Trees in the drier portion did not show this reversal in their climatic response during the period of rapid warming. Abundant water availability during the growing season, particularly in the early to mid-growing season (May-July), is key to the reversal of tree sensitivity to climate. Advancement in the onset of growth appears to allow trees to take advantage of snowmelt water, such that tree growth increases with increasing temperatures during the rapidly warming period. The region's monsoonal climate delivers limited precipitation during the early growing season, and thus snowmelt likely covers the water deficit so trees are less stressed from the onset of earlier growth. Our results indicate that the growth response of P. sylvestris to increasing temperatures strongly related to increased early season water availability. Hence, boreal forests with sufficient water available during crucial parts of the growing season might be more able to withstand or even increase growth during periods of rising temperatures. We suspect that other regions of the boreal forest may be affected by similar dynamics.

The impact of contemporary changes in climate and land use/cover on tendencies in water flow, suspended sediment yield and erosion intensity in the northeastern part of the Don River basin, SW European Russia.

The basin of the Don River (the fifth longest river in Europe), located mainly in the forest-steppe and steppe landscape zones, is one of the most populated and agriculturally developed regions of the East European (Russian) Plain. Sheet, rill and gully erosion occurring chiefly in snowmelt period (March-April) and also in moderate-to-heavy-rainfalls season (chiefly May-to-September) is the main factor of present-day soil degradation within cultivated lands of this basin. Using monitoring hydrological data, it is shown, by the examples of the Khopyor River and the Medveditsa River flowing in the northeastern part of the Don River basin (SW European Russia), that suspended sediment yield of the rivers, as an objective and sufficiently accurate indicator of total erosion intensity in river basins, was reduced by 3.6-3.8 times between the 1960s-1970s and 2008-2015. This conclusion is consistent with change in sedimentation rates (using 137Cs as a chronomarker) within one of the small catchments located in the basin of the upper reaches of the Medveditsa River. The noted dynamics in erosion intensity and suspended sediment yields took place against the background of a well-marked tendency (since the 1940s-1960s) of reduction in intra-annual unevenness of river water flow caused by a decrease in spring (snowmelt-induced, March-April) flood water flow, and by a more significant increase in water discharges during low-water-flow periods of year (winter (December-to-February) and river-ice-free period (mid-April-to-November)). These changes were accompanied by an increase in duration of spring (snowmelt-induced) flood flow with a reduction in its intensity, year-to-year anomalousness and contribution to total annual water flow of the rivers. The main reasons for all the changes noted over the last decades were climate change (a decrease in depth of soil freezing during snowmelt period caused by an increase in air temperature mainly in winter and spring months; an increase in winter thaws frequency) and human activity changes (mainly a reduction in cultivated land area, especially in the 1990s and early 2000s). The similar tendencies were identified over the last decades in other regions of the forest (south part), forest-steppe and steppe landscape zones of the East European Plain.