• Energy Research

The Arctic is warming faster than anywhere else on Earth, placing tundra ecosystems at the forefront of global climate change. Plant biomass is a fundamental ecosystem attribute that is sensitive to changes in climate, closely tied to ecological function, and crucial for constraining ecosystem carbon dynamics. However, the amount, functional composition, and distribution of plant biomass are only coarsely quantified across the Arctic. Therefore, we developed the first moderate resolution (30 m) maps of live aboveground plant biomass (g m(-2)) and woody plant dominance (%) for the Arctic tundra biome, including the mountainous Oro Arctic. We modeled biomass for the year 2020 using a new synthesis dataset of field biomass harvest measurements, Landsat satellite seasonal synthetic composites, ancillary geospatial data, and machine learning models. Additionally, we quantified pixel-wise uncertainty in biomass predictions using Monte Carlo simulations and validated the models using a robust, spatially blocked and nested cross-validation procedure. Observed plant and woody plant biomass values ranged from 0 to similar to 6000 g m(-2) (mean approximate to 350 g m(-2)), while predicted values ranged from 0 to similar to 4000 g m(-2) (mean approximate to 275 g m(-2)), resulting in model validation root-mean-squared-error (RMSE) approximate to 400 g m(-2) and R-2 approximate to 0.6. Our maps not only capture large-scale patterns of plant biomass and woody plant dominance across the Arctic that are linked to climatic variation (e.g., thawing degree days), but also illustrate how fine-scale patterns are shaped by local surface hydrology, topography, and past disturbance. By providing data on plant biomass across Arctic tundra ecosystems at the highest resolution to date, our maps can significantly advance research and inform decision-making on topics ranging from Arctic vegetation monitoring and wildlife conservation to carbon accounting and land surface modeling. Peer reviewed

Macroclimate warming is often assumed to occur within forests despite the potential for tree cover to modify microclimates. Here, using paired measurements, we compared the temperatures under the canopy versus in the open at 98 sites across 5 continents. We show that forests function as a thermal insulator, cooling the understory when ambient temperatures are hot and warming the understory when ambient temperatures are cold. The understory versus open temperature offset is magnified as temperatures become more extreme and is of greater magnitude than the warming of land temperatures over the past century. Tree canopies may thus reduce the severity of warming impacts on forest biodiversity and functioning.

Litter decomposition is a key process for carbon and nutrient cycling in terrestrial ecosystems and is mainly controlled by environmental conditions, substrate quantity and quality as well as microbial community abundance and composition. In particular, the effects of climate and atmospheric nitrogen (N) deposition on litter decomposition and its temporal dynamics are of significant importance, since their effects might change over the course of the decomposition process. Within the TeaComposition initiative, we incubated Green and Rooibos teas at 524 sites across nine biomes. We assessed how macroclimate and atmospheric inorganic N deposition under current and predicted scenarios (RCP 2.6, RCP 8.5) might affect litter mass loss measured after 3 and 12 months. Our study shows that the early to mid-term mass loss at the global scale was affected predominantly by litter quality (explaining 73% and 62% of the total variance after 3 and 12 months, respectively) followed by climate and N deposition. The effects of climate were not litter-specific and became increasingly significant as decomposition progressed, with MAP explaining 2% and MAT 4% of the variation after 12 months of incubation. The effect of N deposition was litter-specific, and significant only for 12-month decomposition of Rooibos tea at the global scale. However, in the temperate biome where atmospheric N deposition rates are relatively high, the 12-month mass loss of Green and Rooibos teas decreased significantly with increasing N deposition, explaining 9.5% and 1.1% of the variance, respectively. The expected changes in macroclimate and N deposition at the global scale by the end of this century are estimated to increase the 12-month mass loss of easily decomposable litter by 1.1–3.5% and of the more stable substrates by 3.8–10.6%, relative to current mass loss. In contrast, expected changes in atmospheric N deposition will decrease the mid-term mass loss of high-quality litter by 1.4–2.2% and that of low-quality litter by 0.9–1.5% in the temperate biome. Our results suggest that projected increases in N deposition may have the capacity to dampen the climate-driven increases in litter decomposition depending on the biome and decomposition stage of substrate.

Abstract Biological communities are reshuffling owing to species range shifts in response to climate change. This process inherently leads to novel assemblages of interacting species. Yet, how climatic change and local dynamics in biotic interactions jointly affect range shifts is still poorly understood. We combine a unique long‐term transplant competition‐exclusion experiment with species distribution models (SDMs) to test the effects of biotic interactions on understorey species range shifts under climate change in European temperate forests. Using a time series of 18 years of individual‐level demographic data of four common understorey plant species transplanted beyond their cold range edge to plots with and without interspecific competition, we built integral projection models (IPMs) and analysed the effects of competition on five key vital rates and population growth (λ). We assessed the results of the transplant experiment in the context of the modelled species' current and future potential distributions. We find that species' population performances in the transplant experiment decreased with lower predicted habitat suitability from the SDMs. The population performance at the transplant sites was mediated by biotic interactions with the local plant community: for two species with intermediate levels of predicted habitat suitability at the transplant sites, competition effects could explicitly differentiate between net population growth (λ > 1) or shrinkage (λ < 1). Synthesis. Our findings contest the long‐standing idea that at cold range edges, mainly abiotic factors structure species' distributions. We conclude that biotic interactions, through acting on local population dynamics, may impact species distributions at the continental scale. Hence, predicting climate‐change impacts on biodiversity redistributions ultimately requires us to also integrate dynamics in biotic interactions.