Explore the vast range of titles available.

We hypothesized that the outcome of competition between ericaceous plants and grasses is strongly affected by the concentrations of phenolics in the litter that they produce. To test the effect of phenolic-rich litter on soluble soil nitrogen concentrations, plant nitrogen uptake and inter-specific competition, we conducted a greenhouse experiment with the shrub Calluna vulgaris and the grass Deschampsia flexuosa and their leaf litters. Two litters of C. vulgaris were used, with equal nitrogen concentration but different (high and low) concentrations of total phenolics. The D. flexuosa leaf litter contained lower concentrations of phenolics, but higher concentrations of nitrogen than the C. vulgaris litters. The plants were grown in monocultures and in mixed cultures. Inorganic and dissolved organic nitrogen were measured monthly during the experiment. After four months, we measured above- and belowground biomass and the nutrient concentrations in above- and belowground plant parts. In monocultures, C. vulgaris produced more shoot and root biomass on its own litter than with no litter. Growth of Calluna was reduced on grass litter. D. flexuosa plants produced most biomass on their own litter type, whether in monocultures or in mixed cultures. Addition of Calluna litter stimulated the growth of D. flexuosa both in monoculture and in mixtures. The grass plants outcompeted Calluna both on shrub litter and on grass litter but not when grown without litter. The two C. vulgaris litter types that differed in their concentration of phenolics did not differ in their effects on the competition between the two species or on the production of inorganic and dissolved organic nitrogen. We conclude that the nitrogen content of the litter is more important as a plant feature driving competition between shrubs and grasses than the concentrations of phenolics

(1) Increased atmospheric nitrogen deposition has shifted plant dominance from ericaceous plants to grass species. To elucidate the reduced competitiveness of heather, we tested the hypothesis that additions of nitrogen reduce the concentrations of phenolics and condensed tannins in ericaceous leaves and retard mycorrhizal colonisation in ericaceous plants. We also tested the negative effects of reduced light intensity on carbon-based secondary compounds and mycorrhizal colonisation in ericaceous plants. (2) We performed a field inventory at three heathland sites in the Netherlands varying in nutrient supply and light intensity. Leaves of ericaceous plants and grasses were collected and analysed for concentrations of tannins, phenolics and nutrients. Similarly, we took root samples to record mycorrhizal colonisation and soil samples to measure the soil mineralisation. In addition, we conducted two-factorial experiments with Calluna vulgaris plants, in which we varied fertiliser and shade levels under greenhouse and field conditions. (3) The field inventory revealed that nitrogen addition and shading both negatively affected the concentration of total phenolics. The total phenolics and condensed tannin concentrations were positively correlated (P < 0.001), but in the field experiment, the condensed tannins were not significantly affected by the treatments. Our results provide the first evidence that the carbon nutrient balance can be used to predict the amount of total phenolics in the dwarf shrub C. vulgaris. (4) In the field experiments, shading of plants resulted in significantly less mycorrhizal colonisation. Only in the greenhouse experiment did addition of nitrogen negatively affect mycorrhizal colonisation. (5) Our results imply that increased atmospheric nitrogen deposition can depress the tannin concentrations in ericaceous plants and the mycorrhizal colonisation in roots, thereby reducing the plants' competitiveness with respect to grasses. Additionally, if ericaceous plants are shaded by grasses that have become dominant due to increased nitrogen supply, these effects will be intensified and competitive replacement will be accelerated.

Open top chambers (OTCs) were adopted as the recommended warming mechanism by the International Tundra Experiment (ITEX) network in the early 1990’s. Since then, OTCs have been deployed across the globe. Hundreds of papers have reported the impacts of OTCs on the abiotic environment and the biota. Here we review the impacts of the OTC on the physical environment, with comments on the appropriateness of using OTCs to characterize the response of biota to warming. The purpose of this review is to guide readers to previously published work and to provide recommendations for continued use of OTCs to understand the implications of warming on low stature ecosystems. In short, the OTC is a useful tool to experimentally manipulate temperature, however the characteristics and magnitude of warming varies greatly in different environments, therefore it is important to document chamber performance to maximize the interpretation of biotic response. When coupled with long-term monitoring, warming experiments are a valuable means to understand the impacts of climate change on natural ecosystems.

Spring snowmelt occurs for a short duration on an annual time scale, but their timings considerably affect the carbon and hydrological cycle in high‐latitude ecosystems. Here, we developed a simple snowmelt model, treating the ecosystem surface as a bulk‐surface layer. Energy fluxes across this bulk surface and the snow‐soil boundary determine snow temperature and the energy utilized for snowmelt. Parameterizing the bulk surface using decade‐long eddy covariance site data from two Alaskan open black spruce forests offered an opportunity to quantitatively evaluate meteorological drivers affecting snowmelt timings without the needs for detailed canopy information. The sensitivity analysis suggested that the total snowfall on the forest floor, ranging from 0.35 m in 2016 to about 1 m in 2018 and 2020, was the most crucial driver for snowmelt timing. This factor accounted for a 10‐day difference in the interannual variations in snow disappearance dates. The importance of the snowfall varied from year to year, and in 2013, the late snowmelt was characterized by low air temperatures, which increased sensible heat loss from the snowpack. The importance of atmospheric radiation was revealed in relatively warm years, such as 2016 and 2019. Our modeling approach necessitates adjusting one empirical parameter that reflects the heat conductivity from the bulk surface to the snow, based on observations. Nevertheless, despite this need for adjustment, the bulk‐surface approach helps identify important meteorological drivers underlying observed snowmelt within a simple theoretical framework. Plain Language Summary It is essential to understand why and how spring snowmelt occurs in boreal forests because of its impact on both the biological and hydrological processes in the ecosystem. However, meteorological drivers related to snowmelt often change simultaneously, which makes it challenging to determine which single driver is vital for snowmelt. To address this challenge, we constructed a simple snowmelt model that treats the ecosystem surface as a single bulk layer. The simple model bypasses the needs for detailed canopy information and is easily constrained by observed data. Applying the model to decadal observation data from Alaskan boreal forests, we found that snowfall, air temperature, and atmospheric radiation were important meteorological drivers for explaining interannual variations in snowmelt timing. Each of them explained about 1–2 weeks of snowmelt disappearance dates. We also demonstrated that the model helped explain why the snowmelt was late in 2013 and early in 2016 and 2019 and why snow disappearance dates differed between study sites. While a simple model has its limitations, it can be beneficial for understanding snowmelt characteristics within a simple theoretical framework. Key Points A model‐based approach was introduced to delineate the roles of meteorological drivers on interannual variations in snowmelt timing Snowfall was the most important driver of the interannual variation in snowmelt timing followed by air temperature and atmospheric radiation Late snowmelt in 2013 was attributed to low air temperature, increasing sensible heat loss from the snowpack

Recent observations of changes in some tundra ecosystems appear to be responses to a warming climate. Several experimental studies have shown that tundra plants and ecosystems can respond strongly to environmental change, including warming; however, most studies were limited to a single location and were of short duration and based on a variety of experimental designs. In addition, comparisons among studies are difficult because a variety of techniques have been used to achieve experimental warming and different measurements have been used to assess responses. We used metaanalysis on plant community measurements from standardized warming experiments at 11 locations across the tundra biome involved in the International Tundra Experiment. The passive warming treatment increased plant-level air temperature by 1-3°C, which is in the range of predicted and observed warming for tundra regions. Responses were rapid and detected in whole plant communities after only two growing seasons. Overall, warming increased height and cover of deciduous shrubs and graminoids, decreased cover of mosses and lichens, and decreased species diversity and evenness. These results predict that warming will cause a decline in biodiversity across a wide variety of tundra, at least in the short term. They also provide rigorous experimental evidence that recently observed increases in shrub cover in many tundra regions are in response to climate warming. These changes have important implications for processes and interactions within tundra ecosystems and between tundra and the atmosphere.

Climate change has resulted in warmer soil temperatures, earlier spring thaw and later fall freeze-up, resulting in warmer soil temperatures and thawing of permafrost in tundra regions. While these changes in temperature metrics tend to lengthen the growing season for plants, light levels, especially in the fall, will continue to limit plant growth and nutrient uptake. We conducted a laboratory experiment using intact soil cores with and without vegetation from a tundra peatland to measure the effects of late freeze and early spring thaw on carbon dioxide (CO2) exchange, methane (CH4) emissions, dissolved organic carbon (DOC) and nitrogen (N) leaching from soils. We compared soil C exchange and N production with a 30 day longer seasonal thaw during a simulated annual cycle from spring thaw through freeze-up and thaw. Across all cores, fall N leaching accounted for ∼33% of total annual N loss despite significant increases in microbial biomass during this period. Nitrate ( NO 3 − ) leaching was highest during the fall (5.33 1.45 mg N m−2 d−1) following plant senescence and lowest during the summer (0.43 0.22 mg N m−2 d−1). In the late freeze and early thaw treatment, we found 25% higher total annual ecosystem respiration but no significant change in CH4 emissions or DOC loss due to high variability among samples. The late freeze period magnified N leaching and likely was derived from root turnover and microbial mineralization of soil organic matter coupled with little demand from plants or microbes. Large N leaching during the fall will affect N cycling in low-lying areas and streams and may alter terrestrial and aquatic ecosystem nitrogen budgets in the arctic.

Wildland fires exert substantial impacts on tundra ecosystems of the high northern latitudes (HNL), ranging from biogeochemical impact on climate system to habitat suitability for various species. Cloud-to-ground (CG) lightning is the primary ignition source of wildfires. It is critical to understand mechanisms and factors driving lightning strikes in this cold, treeless environment to support operational modeling and forecasting of fire activity. Existing studies on lightning strikes primarily focus on Alaskan and Canadian boreal forests where land-atmospheric interactions are different and, thus, not likely to represent tundra conditions. In this study, we designed an empirical-dynamical method integrating Weather Research and Forecast (WRF) simulation and machine learning algorithm to model the probability of lightning strikes across Alaskan tundra between 2001 and 2017. We recommended using Thompson 2-moment and Mellor-Yamada-Janjic schemes as microphysics and planetary boundary layer parameterizations for WRF simulations in the tundra. Our modeling and forecasting test results have shown a strong capability to predict CG lightning probability in Alaskan tundra, with the values of area under the receiver operator characteristics curves above 0.9. We found that parcel lifted index and vertical profiles of atmospheric variables, including geopotential height, dew point temperature, relative humidity, and velocity speed, important in predicting lightning occurrence, suggesting the key role of convection in lightning formation in the tundra. Our method can be applied to data-scarce regions and support future studies of fire potential in the HNL.

Arctic warming has increased vegetation growth and soil respiration during recent decades. The rate of Arctic warming will likely amplify over the 21st century. Previous studies have revealed that the most severe Arctic warming occurred during the cold season (September to May). The cold-season warming has posited significant CO2 emissions to the atmosphere via respiration, possibly offsetting warm-season (June to August) net CO2 uptake. However, prevailing Earth system land models poorly represent cold-season CO2 emissions, making estimates of Arctic tundra annual CO2 budgets highly uncertain. Here, we demonstrate that an improved version of the energy exascale Earth system model (E3SM) land model (ELMv1-ECA) captures the large amount of cold-season CO2 emissions over Alaskan Arctic tundra as reported by two independent, observationally-constrained datasets. We found that the recent seven-decades warming trend of cold-season soil temperature is three times that of the warm-season. The climate sensitivity of warm-season net CO2 uptake, however, is threefold higher than for the cold-season net CO2 loss, mainly due to stronger plant resilience than microbial resilience to hydroclimatic extremes. Consequently, the modeled warm-season net CO2 uptake has a larger positive trend (0.74 ± 0.14 gC m−2 yr−1) than that of cold-season CO2 emissions (0.64 ± 0.11 gC m−2 yr−1) from 1950 to 2017, supported by enhanced plant nutrient uptake and increased light- and water-use efficiency. With continued warming and elevated CO2 concentrations under the representative concentration pathway (RCP) 8.5 scenario, the increasing rate of warm-season net CO2 uptake is more than twice the rate of cold-season emissions (1.33 ± 0.32 gC m−2 yr−1 vs 0.50 ± 0.12 gC m−2 yr−1), making the modeled Alaskan Arctic tundra ecosystem a net CO2 sink by 2100. However, other geomorphological and ecological disturbances (e.g. abrupt permafrost thaw, thermokarst development, landscape-scale hydrological changes, wildfire, and insects) that are not considered here might alter our conclusion.

Reaching from interior Alaska across Canada to Labrador and Newfoundland, North America's boreal forest is the largest wilderness area left on the planet. It is critical habitat for billions of birds; more than 300 species regularly breed there. After the breeding season, many boreal birds migrate to seasonal habitats across the United States, Mexico, the Caribbean, and Central and South America. This volume brings together new research on boreal bird biology and conservation. It highlights the importance of the region to the global avifauna and to the connectivity between the boreal forest and ecoregions throughout the Americas. The contributions showcase a unique set of perspectives on the migration, wintering ecology, and conservation of bird communities that are tied to the boreal forest in ways that may not have been previously considered.