Multi-decadal changes in tundra environments and ecosystems: synthesis of the International Polar Year-Back to the Future project (IPY-BTF)

Understanding the responses of tundra systems to global change has global implications. Most tundra regions lack sustained environmental monitoring and one of the only ways to document multi-decadal change is to resample historic research sites. The International Polar Year (IPY) provided a unique opportunity for such research through the Back to the Future (BTF) project (IPY project #512). This article synthesizes the results from 13 papers within this Ambio Special Issue. Abiotic changes include glacial recession in the Altai Mountains, Russia; increased snow depth and hardness, permafrost warming, and increased growing season length in sub-arctic Sweden; drying of ponds in Greenland; increased nutrient availability in Alaskan tundra ponds, and warming at most locations studied. Biotic changes ranged from relatively minor plant community change at two sites in Greenland to moderate change in the Yukon, and to dramatic increases in shrub and tree density on Herschel Island, and in subarctic Sweden. The population of geese tripled at one site in northeast Greenland where biomass in non-grazed plots doubled. A model parameterized using results from a BTF study forecasts substantial declines in all snowbeds and increases in shrub tundra on Niwot Ridge, Colorado over the next century. In general, results support and provide improved capacities for validating experimental manipulation, remote sensing, and modeling studies.     

Multi-decadal Changes in Tundra Environments and Ecosystems: The International Polar Year-Back to the Future Project (IPY-BTF)

Polar and alpine environments are changing rapidly due to increases in temperature, which are amplified in the Arctic, as well as changes in many local factors. The impacts on ecosystems and their function have potential consequences for local residents and the global community. Tundra areas are vast and diverse, and the knowledge of geographical variation in environmental and ecosystem change is limited to relatively few locations, or to remote sensing approaches that are limited mostly to the past few decades. The International Polar Year, IPY, provided a context, stimulus and timely opportunities for re-visiting old research sites and data sets to collate data on past changes, to pass knowledge from old to new generations of researchers and to document environmental characteristics of sites to facilitate detection and attribution of future changes. Consequently, the project “Retrospective and Prospective Vegetation Change in the Polar Regions: Back to the Future,” BTF, was proposed and endorsed as an IPY activity (project #512). With national funding support, teams of researchers re-visited former sites and data sets throughout the Arctic and some alpine regions. These efforts have amounted to a gamut of “BTF” studies that are collectively geographically expansive and disciplinary diverse. A selection of these studies are introduced and presented in the current issue together with a brief synthesis of their findings.     

Forecasting Alpine Vegetation Change Using Repeat Sampling and a Novel Modeling Approach

Global change affects alpine ecosystems by, among many effects, by altering plant distributions and community composition. However, forecasting alpine vegetation change is challenged by a scarcity of studies observing change in fixed plots spanning decadal-time scales. We present in this article a probabilistic modeling approach that forecasts vegetation change on Niwot Ridge, CO using plant abundance data collected from marked plots established in 1971 and resampled in 1991 and 2001. Assuming future change can be inferred from past change, we extrapolate change for 100 years from 1971 and correlate trends for each plant community with time series environmental data (1971–2001). Models predict a decreased extent of Snowbed vegetation and an increased extent of Shrub Tundra by 2071. Mean annual maximum temperature and nitrogen deposition were the primary a posteriori correlates of plant community change. This modeling effort is useful for generating hypotheses of future vegetation change that can be tested with future sampling efforts.