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.

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.

Shrub expansion in tundra ecosystems may act as a positive feedback to climate warming, the strength of which depends on its spatial extent. Recent studies have shown that shrub expansion is more likely to occur in areas with high soil moisture and nutrient availability, conditions typically found in subsurface water channels known as water tracks. Water tracks are 5-15 m wide channels of subsurface water drainage in permafrost landscapes and are characterized by deeper seasonal thaw depth, warmer soil temperatures, and higher soil moisture and nutrient content relative to adjacent tundra. Consequently, enhanced vegetation productivity, and dominance by tall deciduous shrubs, are typical in water tracks. Quantifying the distribution of water tracks may inform investigations of the extent of shrub expansion and associated impacts on tundra ecosystem carbon cycling. Here, we quantify the distribution of water tracks and their contribution to growing season CO 2 dynamics for a Siberian tundra landscape using satellite observations, meteorological data, and field measurements. We find that water tracks occupy 7.4% of the 448 km 2 study area, and account for a slightly larger proportion of growing season carbon uptake relative to surrounding tundra. For areas inside water tracks dominated by shrubs, field observations revealed higher shrub biomass and higher ecosystem respiration and gross primary productivity relative to adjacent upland tundra. Conversely, a comparison of graminoid-dominated areas in water tracks and inter-track tundra revealed that water track locations dominated by graminoids had lower shrub biomass yet increased net uptake of CO 2 . Our results show water tracks are an important component of this landscape. Their distribution will influence ecosystem structural and functional responses to climate, and is therefore of importance for modeling.

Foundation species have disproportionately large impacts on ecosystem structure and function. As a result, future changes to their distribution may be important determinants of ecosystem carbon (C) cycling in a warmer world. We assessed the role of a foundation tussock sedge (Eriophorum vaginatum) as a climatically vulnerable C stock using field data, a machine learning ecological niche model, and an ensemble of terrestrial biosphere models (TBMs). Field data indicated that tussock density has decreased by ~0.97 tussocks per m2 over the past ~38 years on Alaska’s North Slope from ~1981 to 2019. This declining trend is concerning because tussocks are a large Arctic C stock, which enhances soil organic layer C stocks by 6.9% on average and represents 745 Tg C across our study area. By 2100, we project that changes in tussock density may decrease the tussock C stock by 41% in regions where tussocks are currently abundant (e.g. -0.8 tussocks per m2 and -85 Tg C on the North Slope) and may increase the tussock C stock by 46% in regions where tussocks are currently scarce (e.g. +0.9 tussocks per m2 and +81 Tg C on Victoria Island). These climate-induced changes to the tussock C stock were comparable to, but sometimes opposite in sign, to vegetation C stock changes predicted by an ensemble of TBMs. Our results illustrate the important role of tussocks as a foundation species in determining future Arctic C stocks and highlights the need for better representation of this species in TBMs.

Abstract. Plant functional types (PFTs) are used to represent vegetation distribution in land surface models (LSMs). Large differences are found in the geographical distribution of PFTs currently used in various LSMs. These differences arise from the differences in the underlying land cover products but also the methods used to map or reclassify land cover data to the PFTs that a given LSM represents. There are large uncertainties associated with existing PFT mapping methods since they are largely based on expert judgment and therefore are subjective. In this study, we propose a new approach to inform the mapping or the cross-walking process using analyses from sub-pixel fractional error matrices, which allows for a quantitative assessment of the fractional composition of the land cover categories in a dataset. We use the Climate Change Initiative (CCI) land cover product produced by the European Space Agency (ESA). A previous study has shown that compared to fine-resolution maps over Canada, the ESA-CCI product provides an improved land cover distribution compared to that from the GLC2000 dataset currently used in the CLASSIC (Canadian Land Surface Scheme Including Biogeochemical Cycles) model. A tree cover fraction dataset and a fine-resolution land cover map over Canada are used to compute the sub-pixel fractional composition of the land cover classes in ESA-CCI, which is then used to create a cross-walking table for mapping the ESA-CCI land cover categories to nine PFTs represented in the CLASSIC model. There are large differences between the new PFTs and those currently used in the model. Offline simulations performed with the CLASSIC model using the ESA-CCI based PFTs show improved winter albedo compared to that based on the GLC2000 dataset. This emphasizes the importance of accurate representation of vegetation distribution for realistic simulation of surface albedo in LSMs. Results in this study suggest that the sub-pixel fractional composition analyses are an effective way to reduce uncertainties in the PFT mapping process and therefore, to some extent, objectify the otherwise subjective process.

Summary The response of vegetation to climate change has implications for the carbon cycle and global climate. It is frequently assumed that a species responds uniformly across its range to climate change. However, ecotypes − locally adapted populations within a species − display differences in traits that may affect their gross primary productivity (GPP) and response to climate change. To determine if ecotypes are important for understanding the response of ecosystem productivity to climate we measured and modeled growing season GPP in reciprocally transplanted and experimentally warmed ecotypes of the abundant Arctic sedge Eriophorum vaginatum. Transplanted northern ecotypes displayed home‐site advantage in GPP that was associated with differences in leaf area index. Southern ecotypes exhibited a greater response in GPP when transplanted. The results demonstrate that ecotypic differentiation can impact the morphology and function of vegetation with implications for carbon cycling. Moreover they suggest that ecotypic control of GPP may limit the response of ecosystem productivity to climate change. This investigation shows that ecotypes play a substantial role in determining GPP and its response to climate. These results have implications for understanding annual to decadal carbon cycling where ecotypes could influence ecosystem function and vegetation feedbacks to climate change.

This work evaluates efficacies of plausible ballast water management strategies and standards by integrating a global species spread risk assessment with a policy cost-effectiveness analysis. Specifically, we consider species spread risks and costs of port-and vessel-based strategies under both current organism concentration standards and stricter standards proposed by California. For each scenario, we estimate species spread risks and patterns using a higher-order analysis of a global ship-borne species spread model and estimate fleet costs for vessel-and barge-based ballast water treatment systems for each standard. We find that stricter standards may reduce species spread risk by a factor of 17 globally and would greatly simplify the complex network of shipborne species spread. The current policy of IMO standards is most cost-effectively achieved through ship-based treatment, and that any additional risk reduction will be most cost-effectively achieved by port-based (or barge-based) technologies, particularly if these are strategically implemented at the top ports within the largest clusters. Bargebased ballast water management would require a shift in governance, and we suggest that this next level of policymaking could be feasible for special areas designated by the IMO, by State or multistate authorities, or by voluntary port applications.