The Arctic tundra is warming rapidly, yet the exact mechanisms linking warming and observed ecological changes are often unclear. Understanding mechanisms of change requires long‐term monitoring of multiple ecological parameters. Here, we present the findings of a collaboration between government scientists, local people, park rangers, and academic researchers that provide insights into changes in plant composition, phenology, and growth over 18 yr on Qikiqtaruk‐Herschel Island, Canada. Qikiqtaruk is an important focal research site located at the latitudinal tall shrub line in the western Arctic. This unique ecological monitoring program indicates the following findings: (1) nine days per decade advance of spring phenology, (2) a doubling of average plant canopy height per decade, but no directional change in shrub radial growth, and (3) a doubling of shrub and graminoid abundance and a decrease by one‐half in bare ground cover per decade. Ecological changes are concurrent with satellite‐observed greening and, when integrated, suggest that indirect warming from increased growing season length and active layer depths, rather than warming summer air temperatures alone, could be important drivers of the observed tundra vegetation change. Our results highlight the vital role that long‐term and multi‐parameter ecological monitoring plays in both the detection and attribution of global change.

Current analyses and predictions of spatially explicit patterns and processes in ecology most often rely on climate data interpolated from standardized weather stations. This interpolated climate data represents long-term average thermal conditions at coarse spatial resolutions only. Hence, many climate-forcing factors that operate at fine spatiotemporal resolutions are overlooked. This is particularly important in relation to effects of observation height (e.g. vegetation, snow and soil characteristics) and in habitats varying in their exposure to radiation, moisture and wind (e.g. topography, radiative forcing or cold-air pooling). Since organisms living close to the ground relate more strongly to these microclimatic conditions than to free-air temperatures, microclimatic ground and near-surface data are needed to provide realistic forecasts of the fate of such organisms under anthropogenic climate change, as well as of the functioning of the ecosystems they live in. To fill this critical gap, we highlight a call for temperature time series submissions to SoilTemp, a geospatial database initiative compiling soil and near-surface temperature data from all over the world. Currently, this database contains time series from 7,538 temperature sensors from 51 countries

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids thus fail to reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions are controlled and most terrestrial species reside. Here we provide global maps of soil temperature and bioclimatic variables at a 1-km² resolution for 0-5 and 5-15 cm depth. These maps were created by calculating the difference (i.e., offset) between in-situ soil temperature measurements, based on time series from over 1200 1-km² pixels (summarized from 8500 unique temperature sensors) across all of the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding 2 m gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (3.6 ± 2.3°C warmer than gridded air temperature), whereas soils in warm and humid environments are on average slightly cooler (0.7 ± 2.3°C cooler). The observed substantial and biome-specific offsets underpin that the projected impacts of climate and climate change on biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining global gaps by collecting more in-situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications.

Global biodiversity assessments have highlighted land-use change as a key driver of biodiversity change. However, there is little empirical evidence of how habitat transformations such as forest loss and gain are reshaping biodiversity over time. We quantified how change in forest cover has influenced temporal shifts in populations and ecological assemblages from 6090 globally distributed time series across six taxonomic groups. We found that local-scale increases and decreases in abundance, species richness, and temporal species replacement (turnover) were intensified by as much as 48% after forest loss. Temporal lags in population- and assemblage-level shifts after forest loss extended up to 50 years and increased with species’ generation time. Our findings that forest loss catalyzes population and biodiversity change emphasize the complex biotic consequences of land-use change.

Global assessments have highlighted land-use change as a key driver of biodiversity change. However, we lack real-world global-scale estimates of how habitat transformations such as forest loss and gain are reshaping biodiversity over time. Here, we quantify the influence of 150 years of forest cover change on populations and ecological assemblages worldwide and across taxa by analyzing change in 6,667 time series. We found that forest loss simultaneously intensified ongoing increases and decreases in abundance, species richness and temporal species replacement (turnover) by up to 48%. Temporal lags in these responses extended up to 50 years and increased with species’ generation time. Our findings demonstrate that land-use change precipitates divergent population and biodiversity change, highlighting the complex biotic consequences of deforestation and afforestation.One Sentence SummaryDeclines in forest cover amplify both gains and losses in population abundance and biodiversity over time.

Research in environmental science relies heavily on global climatic grids derived from estimates of air temperature at around 2 meter above ground1-3. These climatic grids however fail to reflect conditions near and below the soil surface, where critical ecosystem functions such as soil carbon storage are controlled and most biodiversity resides4-8. By using soil temperature time series from over 8500 locations across all of the world’s terrestrial biomes4, we derived global maps of soil temperature-related variables at 1 km resolution for the 0–5 and 5–15 cm depth horizons. Based on these maps, we show that mean annual soil temperature differs markedly from the corresponding 2 m gridded air temperature, by up to 10°C, with substantial variation across biomes and seasons. Soils in cold and/or dry biomes are annually substantially warmer (3.6°C ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are slightly cooler (0.7 ± 2.3°C). As a result, annual soil temperature varies less (by 17%) across the globe than air temperature. The effect of macroclimatic conditions on the difference between soil and air temperature highlights the importance of considering that macroclimate warming may not result in the same level of soil temperature warming. Similarly, changes in precipitation could alter the relationship between soil and air temperature, with implications for soil-atmosphere feedbacks9. Our results underpin that the impacts of climate and climate change on biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments.

Arctic landscapes are changing rapidly in response to warming, but future predictions are hindered by difficulties in scaling ecological relationships from plots to biomes. Unmanned aerial systems (hereafter ‘drones’) are increasingly used to observe Arctic ecosystems over broader extents than can be measured using ground-based approaches and are facilitating the interpretation of coarse-grained remotely sensed data. However, more information is needed about how drone-acquired remote sensing observations correspond with ecosystem attributes such as aboveground biomass. Working across a willow shrub-dominated alluvial fan at a focal study site in the Canadian Arctic, we conducted peak growing season drone surveys with an RGB camera and a multispectral multi-camera array. We derived photogrammetric reconstructions of canopy height and normalised difference vegetation index (NDVI) maps along with in situ point-intercept measurements and aboveground vascular biomass harvests from 36, 0.25 m2 plots. We found high correspondence between canopy height measured using in situ point-intercept methods compared to drone-photogrammetry (concordance correlation coefficient = 0.808), although the photogrammetry heights were positively biased by 0.14 m relative to point-intercept heights. Canopy height was strongly and linearly related to aboveground biomass, with similar coefficients of determination for point-intercept (R 2 = 0.92) and drone-based methods (R 2 = 0.90). NDVI was positively related to aboveground biomass, phytomass and leaf biomass. However, NDVI only explained a small proportion of the variance in biomass (R 2 between 0.14 and 0.23 for logged total biomass) and we found moss cover influenced the NDVI-phytomass relationship. Vascular plant biomass is challenging to infer from drone-derived NDVI, particularly in ecosystems where bryophytes cover a large proportion of the land surface. Our findings suggest caution with broadly attributing change in fine-grained NDVI to biomass differences across biologically and topographically complex tundra landscapes. By comparing structural, spectral and on-the-ground ecological measurements, we can improve understanding of tundra vegetation change as inferred from remote sensing.

1. An accumulating number of studies are reporting severe insect declines. These studies aim to quantify temporal changes in invertebrate populations and community composition and attribute them to anthropogenic drivers. 2. Seibold et al. 2019 (Nature, 574, 671-674) analysed arthropod biomass, abundance and species richness from forest and grassland plots in a region of Germany and reported declines of up to 78% between 2008 and 2018. However, their analysis did not account for the confounding effects of temporal pseudoreplication. 3. We show that simply by including a year random effect in the statistical models and thereby accounting for the common conditions experienced by proximal sites in the same years, four of the five reported declines become non-significant out of six tests overall. 4. To place recent estimates of insect trends in a broader context, we analysed invertebrate biomass, abundance and richness from 640 time series from 1167 sites around the world. We found that the average trends across the terrestrial and freshwater realms were not significantly distinguishable from no net change. Shorter time series that are likely most affected by sampling error variancesuch as those in Seibold et al. 2019 (Nature, 574, 671-674)yielded the most extreme decline and increase estimates. 5. We suggest that the media uptake of negative trends from short time series may be serving to exaggerate the 'insect Armageddon' and could undermine public confidence in research. We advocate that future research uses appropriate model structures to build a more robust understanding of biodiversity change.