• Energy Research

Peatlands and forests cover large areas of the boreal biome and are critical for global climate regulation. They also regulate regional climate through heat and water vapour exchange with the atmosphere. Understanding how land-atmosphere interactions in peatlands differ from forests may therefore be crucial for modelling boreal climate system dynamics and for assessing climate benefits of peatland conservation and restoration. To assess the biophysical impacts of peatlands and forests on peak growing season air temperature and humidity, we analysed surface energy fluxes and albedo from 35 peatlands and 37 evergreen needleleaf forests—the dominant boreal forest type—and simulated air temperature and vapour pressure deficit (VPD) over hypothetical homogeneous peatland and forest landscapes. We ran an evapotranspiration model using land surface parameters derived from energy flux observations and coupled an analytical solution for the surface energy balance to an atmospheric boundary layer (ABL) model. We found that peatlands, compared to forests, are characterized by higher growing season albedo, lower aerodynamic conductance, and higher surface conductance for an equivalent VPD. This combination of peatland surface properties results in a ∼20% decrease in afternoon ABL height, a cooling (from 1.7 to 2.5 °C) in afternoon air temperatures, and a decrease in afternoon VPD (from 0.4 to 0.7 kPa) for peatland landscapes compared to forest landscapes. These biophysical climate impacts of peatlands are most pronounced at lower latitudes (∼45°N) and decrease toward the northern limit of the boreal biome (∼70°N). Thus, boreal peatlands have the potential to mitigate the effect of regional climate warming during the growing season. The biophysical climate mitigation potential of peatlands needs to be accounted for when projecting the future climate of the boreal biome, when assessing the climate benefits of conserving pristine boreal peatlands, and when restoring peatlands that have experienced peatland drainage and mining.

AbstractCurrent 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 across all key biomes. The database will pave the way toward an improved global understanding of microclimate and bridge the gap between the available climate data and the climate at fine spatiotemporal resolutions relevant to most organisms and ecosystem processes.

AbstractIntensifying permafrost thaw alters carbon cycling by mobilizing large amounts of terrestrial substrate into aquatic ecosystems. Yet, few studies have measured aquatic carbon fluxes and constrained drivers of ecosystem carbon balance across heterogeneous Arctic landscapes. Here, we characterized hydrochemical and landscape controls on fluvial carbon cycling, quantified fluvial carbon fluxes, and estimated fluvial contributions to ecosystem carbon balance across 33 watersheds in four ecoregions in the continuous permafrost zone of the western Canadian Arctic: unglaciated uplands, ice‐rich moraine, and organic‐rich lowlands and till plains. Major ions, stable isotopes, and carbon speciation and fluxes revealed patterns in carbon cycling across ecoregions defined by terrain relief and accumulation of organics. In previously unglaciated mountainous watersheds, bicarbonate dominated carbon export (70% of total) due to chemical weathering of bedrock. In lowland watersheds, where soil organic carbon stores were largest, lateral transport of dissolved organic carbon (50%) and efflux of biotic CO2 (25%) dominated. In watersheds affected by thaw‐induced mass wasting, erosion of ice‐rich tills enhanced chemical weathering and increased particulate carbon fluxes by two orders of magnitude. From an ecosystem carbon balance perspective, fluvial carbon export in watersheds not affected by thaw‐induced wasting was, on average, equivalent to 6%–16% of estimated net ecosystem exchange (NEE). In watersheds affected by thaw‐induced wasting, fluvial carbon export approached 60% of NEE. Because future intensification of thermokarst activity will amplify fluvial carbon export, determining the fate of carbon across diverse northern landscapes is a priority for constraining trajectories of permafrost region ecosystem carbon balance.

AbstractThe regional variability in tundra and boreal carbon dioxide (CO2) fluxes can be high, complicating efforts to quantify sink‐source patterns across the entire region. Statistical models are increasingly used to predict (i.e., upscale) CO2 fluxes across large spatial domains, but the reliability of different modeling techniques, each with different specifications and assumptions, has not been assessed in detail. Here, we compile eddy covariance and chamber measurements of annual and growing season CO2 fluxes of gross primary productivity (GPP), ecosystem respiration (ER), and net ecosystem exchange (NEE) during 1990–2015 from 148 terrestrial high‐latitude (i.e., tundra and boreal) sites to analyze the spatial patterns and drivers of CO2 fluxes and test the accuracy and uncertainty of different statistical models. CO2 fluxes were upscaled at relatively high spatial resolution (1 km2) across the high‐latitude region using five commonly used statistical models and their ensemble, that is, the median of all five models, using climatic, vegetation, and soil predictors. We found the performance of machine learning and ensemble predictions to outperform traditional regression methods. We also found the predictive performance of NEE‐focused models to be low, relative to models predicting GPP and ER. Our data compilation and ensemble predictions showed that CO2 sink strength was larger in the boreal biome (observed and predicted average annual NEE −46 and −29 g C m−2 yr−1, respectively) compared to tundra (average annual NEE +10 and −2 g C m−2 yr−1). This pattern was associated with large spatial variability, reflecting local heterogeneity in soil organic carbon stocks, climate, and vegetation productivity. The terrestrial ecosystem CO2 budget, estimated using the annual NEE ensemble prediction, suggests the high‐latitude region was on average an annual CO2 sink during 1990–2015, although uncertainty remains high.