Dataset Information

Decreasing snow cover alters functional composition and diversity of Arctic tundra.

ABSTRACT: The Arctic is one of the least human-impacted parts of the world, but, in turn, tundra biome is facing the most rapid climate change on Earth. These perturbations may cause major reshuffling of Arctic species compositions and functional trait profiles and diversity, thereby affecting ecosystem processes of the whole tundra region. Earlier research has detected important drivers of the change in plant functional traits under warming climate, but studies on one key factor, snow cover, are almost totally lacking. Here we integrate plot-scale vegetation data with detailed climate and snow information using machine learning methods to model the responsiveness of tundra communities to different scenarios of warming and snow cover duration. Our results show that decreasing snow cover, together with warming temperatures, can substantially modify biotic communities and their trait compositions, with future plant communities projected to be occupied by taller plants with larger leaves and faster resource acquisition strategies. As another finding, we show that, while the local functional diversity may increase, simultaneous biotic homogenization across tundra communities is likely to occur. The manifestation of climate warming on tundra vegetation is highly dependent on the evolution of snow conditions. Given this, realistic assessments of future ecosystem functioning require acknowledging the role of snow in tundra vegetation models.

SUBMITTER: Niittynen P

PROVIDER: S-EPMC7474597 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Decreasing snow cover alters functional composition and diversity of Arctic tundra.

Niittynen Pekka P Heikkinen Risto K RK Luoto Miska M

Proceedings of the National Academy of Sciences of the United States of America 20200810 35

The Arctic is one of the least human-impacted parts of the world, but, in turn, tundra biome is facing the most rapid climate change on Earth. These perturbations may cause major reshuffling of Arctic species compositions and functional trait profiles and diversity, thereby affecting ecosystem processes of the whole tundra region. Earlier research has detected important drivers of the change in plant functional traits under warming climate, but studies on one key factor, snow cover, are almost t ...[more]

PMID: 32778575

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Project description:Climate warming is inducing widespread vegetation changes in Arctic tundra ecosystems, with the potential to alter carbon and nutrient dynamics between vegetation and soils. Yet, we lack a detailed understanding of how variation in vegetation and topography influences fine-scale temperatures ("microclimate") that mediate these dynamics, and at what resolution vegetation needs to be sampled to capture these effects. We monitored microclimate at 90 plots across a tundra landscape in western Greenland. Our stratified random study design covered gradients of topography and vegetation, while nested plots (0.8-100 m2 ) enabled comparison across different sampling resolutions. We used Bayesian mixed-effect models to quantify the direct influence of plot-level topography, moisture and vegetation on soil, near-surface and canopy-level temperatures (-6, 2, and 15 cm). During the growing season, colder soils were predicted by shrub cover (-0.24°C per 10% increase), bryophyte cover (-0.35°C per 10% increase), and vegetation height (-0.17°C per 1 cm increase). The same three factors also predicted the magnitude of differences between soil and above-ground temperatures, indicating warmer soils at low cover/height, but colder soils under closed/taller canopies. These findings were consistent across plot sizes, suggesting that spatial predictions of microclimate may be possible at the operational scales of satellite products. During winter, snow cover (+0.75°C per 10 snow-covered days) was the key predictor of soil microclimate. Topography and moisture explained little variation in the measured temperatures. Our results not only underline the close connection of vegetation and snow with microclimate in the Arctic tundra but also point to the need for more studies disentangling their complex interplay across tundra environments and seasons. Future shifts in vegetation cover and height will likely mediate the impact of atmospheric warming on the tundra soil environment, with potential implications for below-ground organisms and ecosystem functioning.

Project description:Background and aimsQuantifying relationships between snow cover duration and plant community properties remains an important challenge in alpine ecology. This study develops a method to estimate spatial variation in energy availability in the context of a topographically complex, high-elevation watershed, which was used to test the explanatory power of environmental gradients both with and without snow cover in relation to taxonomic and functional plant diversity.MethodsSnow cover in the French Alps was mapped at 15-m resolution using Landsat imagery for five recent years, and a generalized additive model (GAM) was fitted for each year linking snow to time and topography. Predicted snow cover maps were combined with air temperature and solar radiation data at daily resolution, summed for each year and averaged across years. Equivalent growing season energy gradients were also estimated without accounting for snow cover duration. Relationships were tested between environmental gradients and diversity metrics measured for 100 plots, including species richness, community-weighted mean traits, functional diversity and hyperspectral estimates of canopy chlorophyll content.Key resultsAccounting for snow cover in environmental variables consistently led to improved predictive power as well as more ecologically meaningful characterizations of plant diversity. Model parameters differed significantly when fitted with and without snow cover. Filtering solar radiation with snow as compared without led to an average gain in R(2) of 0·26 and reversed slope direction to more intuitive relationships for several diversity metrics.ConclusionsThe results show that in alpine environments high-resolution data on snow cover duration are pivotal for capturing the spatial heterogeneity of both taxonomic and functional diversity. The use of climate variables without consideration of snow cover can lead to erroneous predictions of plant diversity. The results further indicate that studies seeking to predict the response of alpine plant communities to climate change need to consider shifts in both temperature and nival regimes.

Project description:The arctic tundra is undergoing climate-driven changes and there are serious concerns related to the future of arctic biodiversity and altered ecological processes under possible climate change scenarios. Arctic land surface temperatures and precipitation are predicted to increase further, likely causing major transformation in terrestrial ecosystems. As a response to increasing temperatures, shifts in vegetation and soil fungal communities have already been observed. Little is known, however, how long-term experimental warming coupled with increased snow depth influence the trajectories of soil fungal communities in different tundra types. We compared edaphic variables and fungal community composition in experimental plots simulating the expected increase in summer warming and winter snow depth, based on DNA metabarcoding data. Fungal communities in the sampled dry and moist acidic tundra communities differed greatly, with tundra type explaining ca. one-third of compositional variation. Furthermore, dry and moist tundra appear to have different trajectories in response to climate change. Specifically, while both warming and increased snow depth had significant effects on fungal community composition and edaphic variables in dry tundra, the effect of increased snow was greater. However, in moist tundra, fungal communities mainly were affected by summer warming, while increased snow depth had a smaller effect and only on some functional groups. In dry tundra, microorganisms generally are limited by moisture in the summer and extremely low temperatures in winter, which is in agreement with the stronger effect of increased snow depth relative to warming. On the contrary, moist tundra soils generally are saturated with water, remain cold year-round and show relatively small seasonal fluctuations in temperature. The greater observed effect of warming on fungi in moist tundra may be explained by the narrower temperature optimum compared to those in dry tundra.

Dataset Information

Decreasing snow cover alters functional composition and diversity of Arctic tundra.

Publications

Decreasing snow cover alters functional composition and diversity of Arctic tundra.

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