Extreme event impacts on terrestrial and freshwater biota in the arctic: A synthesis of knowledge and opportunities

• Published in: Frontiers in Environmental Science
• Main Authors: van Beest, Floris M., Barry, Tom, Christensen, Tom, Heiðmarsson, Starri, McLennan, Donald, Schmidt, Niels M.
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: Frontiers Media SA 2022
• Subjects: Svalbard
• Online Access: http://dx.doi.org/10.3389/fenvs.2022.983637; https://www.frontiersin.org/articles/10.3389/fenvs.2022.983637/full

Extreme weather events are increasing in frequency and intensity across the Arctic, one of the planet’s most rapidly warming regions. Studies from southern latitudes have revealed that the ecological impacts of extreme events on living organisms can be severe and long-lasting, yet data and evidence from within the terrestrial Arctic biome appear underrepresented. By synthesizing a total of 48 research articles, published over the past 25 years, we highlight the occurrence of a wide variety of extreme events throughout the Arctic, with multiple and divergent impacts on local biota. Extreme event impacts were quantified using a myriad of approaches ranging from circumpolar modelling to fine-scale experimental studies. We also identified a research bias towards the quantification of impacts related to a few extreme event types in the same geographic location (e.g. rain-on-snow events in Svalbard). Moreover, research investigating extreme event impacts on the ecology of arthropods and especially freshwater biota were scant, highlighting important knowledge gaps. While current data allow for hypotheses development, many uncertainties about the long-term consequences of extreme events to Arctic ecosystems remain. To advance extreme event research in the terrestrial Arctic biome, we suggest that future studies i) objectively define what is extreme in terms of events and ecological impacts using long-term monitoring data, ii) move beyond single-impact studies and single spatial scales of observation by taking advantage of pan-Arctic science-based monitoring networks and iii) consider predictive and mechanistic modelling to estimate ecosystem-level impacts and recovery.