Mapping Arctic tundra plant species and communities

The Arctic tundra's unique biodiversity holds profound intrinsic and cultural value for Indigenous peoples, and supports ecosystem stability under rapid climate change. The thin layer of Arctic vegetation is crucial, buffering immense permafrost carbon storage from the atmosphere—a key component of climate feedback mechanism. Yet, the precise composition and distribution of this diversity remain poorly resolved.

Current assessments of Arctic plant diversity are often conducted locally or rely on broad plant functional types, offering only a coarse approximation of actual species composition and relative abundance on regional scales. To address this gap, we utilize the Arctic Vegetation Archive (AVA), an unprecedented international effort to compile thousands of standardized Braun-Blanquet vegetation surveys and local floras collected over decades. This unique, high-resolution dataset, currently released for the Russian and Alaska Arctic, and forthcoming for Canada and Greenland, provides precise species-level and community-level data. It includes moss and lichen species, significantly underrepresented in current biodiversity assessments.

In this study, we leverage the AVA to develop high-resolution predictive models of Arctic plant diversity. We employ two modelling approaches: standard Species Distribution Models (SDMs) for individual taxa and a recently introduced multi-species deep-SDM approach to predict entire plant communities. The latter approach was previously shown to account for inter-species correlations and predict community composition more accurately on a national scale. Our models integrate critical environmental factors, such as temperature, precipitation and site water balance (CHELSA) with high-resolution remote sensing data (Sentinel-2) to capture the specific environmental niche and spectral signatures of both single species and plant communities.

We will present the first results of this modelling effort, offering a refined, species-level understanding of Arctic biodiversity distribution. We invite the broader community to discuss the potential for integrating these results into various applications, including conservation and future scenarios.

We hope that our results contribute to understanding of Arctic biodiversity and support maintaining it.