Sarah C. Elmendorf’s research while affiliated with University of Colorado Boulder and other places

Motivation Here, we make available a second version of the BioTIME database, which compiles records of abundance estimates for species in sample events of ecological assemblages through time. The updated version expands version 1.0 of the database by doubling the number of studies and includes substantial additional curation to the taxonomic accuracy of the records, as well as the metadata. Moreover, we now provide an R package (BioTIMEr) to facilitate use of the database. Main Types of Variables Included The database is composed of one main data table containing the abundance records and 11 metadata tables. The data are organised in a hierarchy of scales where 11,989,233 records are nested in 1,603,067 sample events, from 553,253 sampling locations, which are nested in 708 studies. A study is defined as a sampling methodology applied to an assemblage for a minimum of 2 years. Spatial Location and Grain Sampling locations in BioTIME are distributed across the planet, including marine, terrestrial and freshwater realms. Spatial grain size and extent vary across studies depending on sampling methodology. We recommend gridding of sampling locations into areas of consistent size. Time Period and Grain The earliest time series in BioTIME start in 1874, and the most recent records are from 2023. Temporal grain and duration vary across studies. We recommend doing sample-level rarefaction to ensure consistent sampling effort through time before calculating any diversity metric. Major Taxa and Level of Measurement The database includes any eukaryotic taxa, with a combined total of 56,400 taxa. Software Format csv and. SQL.

The Arctic is warming four times faster than the global average¹ and plant communities are responding through shifts in species abundance, composition and distribution2, 3–4. However, the direction and magnitude of local changes in plant diversity in the Arctic have not been quantified. Using a compilation of 42,234 records of 490 vascular plant species from 2,174 plots across the Arctic, here we quantified temporal changes in species richness and composition through repeat surveys between 1981 and 2022. We also identified the geographical, climatic and biotic drivers behind these changes. We found greater species richness at lower latitudes and warmer sites, but no indication that, on average, species richness had changed directionally over time. However, species turnover was widespread, with 59% of plots gaining and/or losing species. Proportions of species gains and losses were greater where temperatures had increased the most. Shrub expansion, particularly of erect shrubs, was associated with greater species losses and decreasing species richness. Despite changes in plant composition, Arctic plant communities did not become more similar to each other, suggesting no biotic homogenization so far. Overall, Arctic plant communities changed in richness and composition in different directions, with temperature and plant–plant interactions emerging as the main drivers of change. Our findings demonstrate how climate and biotic drivers can act in concert to alter plant composition, which could precede future biodiversity changes that are likely to affect ecosystem function, wildlife habitats and the livelihoods of Arctic peoples5,6.

Global climate change phenomena are amplified in Arctic regions, driving rapid changes in the biota. Here, we examine changes in plant community structure over more than 30 years at two sites in arctic Alaska, USA, Imnavait Creek and Toolik Lake, to understand long‐term trends in tundra response to changing climate. Vegetation cover was sampled every 4–7 years on permanent 1 m² plots spanning a 1 km² grid using a point‐frame. The vascular plant canopies progressively closed at both locations. Canopy cover, defined here as an encounter of a vascular plant above the ground surface, increased from 63% to 91% at Imnavait Creek and from 63% to 89% at Toolik Lake. Both sites showed steady increases in maximum canopy height, increasing by approximately 50% (8 cm). While cover and height increased to some extent for all vascular plant growth forms, deciduous shrubs and graminoids changed the most. For example, at Imnavait Creek the cover of graminoids more than tripled (particularly in wet meadow plots), increasing by 237%. At Toolik Lake the cover of deciduous shrubs more than doubled (particularly in moist acidic plots), increasing by 145%. Despite the steady closing of the plant canopy, cryptogams (lichens and mosses) persisted; in fact, the cover of lichens increased. These results call into question the dominant dogma that cryptogams will decline with increases in vascular plant abundance and demonstrate the resilience of these understory plants. In addition to overall cover, the diversity of vascular plants increased at one site (Imnavait Creek). In contrast to much of the Arctic, summer air temperatures in the Toolik Lake region have not significantly increased over the 30+ year sampling period; however, winter temperatures increased substantially. Changes in vegetation community structure at Imnavait Creek and Toolik Lake are likely the result of winter warming.

The below‐ground growing season often extends beyond the above‐ground growing season in tundra ecosystems and as the climate warms, shifts in growing seasons are expected. However, we do not yet know to what extent, when and where asynchrony in above‐ and below‐ground phenology occurs and whether variation is driven by local vegetation communities or spatial variation in microclimate. Here, we combined above‐ and below‐ground plant phenology metrics to compare the relative timings and magnitudes of leaf and fine‐root growth and senescence across microclimates and plant communities at five sites across the Arctic and alpine tundra biome. We observed asynchronous growth between above‐ and below‐ground plant tissue, with the below‐ground season extending up to 74% (~56 days) beyond the onset of above‐ground leaf senescence. Plant community type, rather than microclimate, was a key factor controlling the timing, productivity, and growth rates of fine roots, with graminoid roots exhibiting a distinct ‘pulse’ of growth later into the growing season than shrub roots. Our findings indicate the potential of vegetation change to influence below‐ground carbon storage as the climate warms and roots remain active in unfrozen soils for longer. Taken together, our findings of increased root growth in soils that remain thawed later into the growing season, in combination with ongoing tundra vegetation change including increased shrub and graminoid abundance, indicate increased below‐ground productivity and altered carbon cycling in the tundra biome.

Following rapid climate change across the Arctic, tundra plant communities are experiencing extensive compositional shifts. One of the most prevalent changes is the encroachment of boreal species into the tundra (‘borealization’). Borealization has been reported at individual sites, but has not been systematically quantified across the tundra biome. Here, we use a dataset of 1,137 plots at 113 subsites across 32 study areas resurveyed at least once between 1981 and 2023 and encompassing 287 vascular plant species. We i) quantified the borealization of tundra ecosystems as the colonisation and the increase in abundance of boreal specialist and boreal-tundra boundary species, ii) assessed biogeographical, climatic and local drivers of borealization, and iii) identified species contributing most to borealization and their associated traits. Around half of the plots experienced borealization, especially at sites closer to the treeline, at higher elevations (mountains), in warmer and wetter regions, and at sites that had undergone the lowest magnitude of climate change. Boreal species were more likely to expand in Eurasia, and at sites with lower initial abundances of boreal species. Boreal species that colonised more plots were generally short, and more likely to be shrubs and graminoids than forbs. Boreal specialist species colonised three times less frequently than boreal-tundra boundary species, yet abundance changes were similar across groups. These findings indicate that borealization is mainly driven by the spread of already established species in the tundra, and suggest that future changes to Arctic ecosystems might not involve rapid, widespread replacement of Arctic species by boreal species. These observed and future plant community composition changes could affect land-atmosphere interactions, trophic dynamics and local and Indigenous livelihoods.

Plant functional traits are key drivers of ecosystem processes. However, plot-based monitoring of functional composition across both large spatial and temporal extents is a time-consuming and expensive undertaking. Airborne and satellite remote sensing platforms collect data across large spatial expanses, often repeatedly over time, raising the tantalising prospect of detection of biodiversity change over space and time through remotely sensed methods. Here, we test the degree to which in situ measurements of taxonomic and functional β-diversity, defined as pairwise dissimilarity either between sites, or between years within individual sites, is detectable in airborne hyperspectral imagery across both space and time in an alpine vascular plant community in the Front Range, Colorado, USA. Functional and taxonomic dissimilarity were signicantly related to spectral dissimilarity across space, but lacked robust relationships with spectral dissimilarity over time. Biomass showed stronger relationships with spectral dissimilarity than either taxonomic or functional dissimilarity over space, but exhibited no significant associations with spectral dissimilarity over time. Comparative analyses using NDVI revealed that NDVI alone explains much of the variation explained by the full-range spectra. Our results support the use of hyperspectral data to detect fine-scale changes in vascular plant β-diversity over space, but suggest that methodological limitations still preclude the use of this technology for long-term monitoring and change detection.