Regional atmospheric cooling and wetting effect of permafrost thaw-induced boreal forest loss

Warming-induced vapor pressure deficit suppression of vegetation growth diminished in northern peatlands

Recent studies have reported worldwide vegetation suppression in response to increasing atmospheric vapor pressure deficit (VPD). Here, we integrate multisource datasets to show that increasing VPD caused by warming alone does not suppress vegetation growth in northern peatlands. A site-level manipulation experiment and a multiple-site synthesis find a neutral impact of rising VPD on vegetation growth; regional analysis manifests a strong declining gradient of VPD suppression impacts from sparsely distributed peatland to densely distributed peatland. The major mechanism adopted by plants in response to rising VPD is the "open" water-use strategy, where stomatal regulation is relaxed to maximize carbon uptake. These unique surface characteristics evolve in the wet soil‒air environment in the northern peatlands. The neutral VPD impacts observed in northern peatlands contrast with the vegetation suppression reported in global nonpeatland areas under rising VPD caused by concurrent warming and decreasing relative humidity, suggesting model improvement for representing VPD impacts in northern peatlands remains necessary.

Vertical distribution of bacterial community diversity in the Greater Khingan Mountain permafrost region

Soil microorganisms are crucial contributors to the function of permafrost ecosystems, as well as the regulation of biogeochemical cycles. However, little is known about the distribution patterns and drivers of high‐latitude permafrost microbial communities subject to climate change and human activities. In this study, the vertical distribution patterns of soil bacterial communities in the Greater Khingan Mountain permafrost region were systematically analyzed via Illumina Miseq high‐throughput sequencing. Bacterial diversity in the active layer was significantly higher than in the permafrost layer. Principal coordinate analysis (PCoA) indicated that the bacterial community structure in the active layer and the permafrost layer was completely separated. Permutational multivariate analysis of variance (PERMANOVA) detected statistically significant differentiation across the different depths. The relative abundance of the dominant phyla Chloroflexi (17.92%–52.79%) and Actinobacteria (6.34%–34.52%) was significantly higher in the permafrost layer than in the active layer, whereas that of Acidobacteria (4.98%–38.82%) exhibited the opposite trend, and the abundance of Proteobacteria (2.49%–22.51%) generally decreased with depth. More importantly, the abundance of bacteria linked to human infectious diseases was significantly higher in the permafrost layer according to Tax4Fun prediction analysis. Redundancy analysis (RDA) showed that ammonium nitrogen (NH₄⁺‐N), total organic carbon (TOC), and total phosphorus (TP) were major factors affecting the bacterial community composition. Collectively, our findings provide insights into the soil bacterial vertical distribution patterns and major environmental drivers in high‐latitude permafrost regions, which is key to grasping the response of cold region ecosystem processes to global climate changes.

Trends in Satellite Earth Observation for Permafrost Related Analyses—A Review

Climate change and associated Arctic amplification cause a degradation of permafrost which in turn has major implications for the environment. The potential turnover of frozen ground from a carbon sink to a carbon source, eroding coastlines, landslides, amplified surface deformation and endangerment of human infrastructure are some of the consequences connected with thawing permafrost. Satellite remote sensing is hereby a powerful tool to identify and monitor these features and processes on a spatially explicit, cheap, operational, long-term basis and up to circum-Arctic scale. By filtering after a selection of relevant keywords, a total of 325 articles from 30 international journals published during the last two decades were analyzed based on study location, spatio-temporal resolution of applied remote sensing data, platform, sensor combination and studied environmental focus for a comprehensive overview of past achievements, current efforts, together with future challenges and opportunities. The temporal development of publication frequency, utilized platforms/sensors and the addressed environmental topic is thereby highlighted. The total number of publications more than doubled since 2015. Distinct geographical study hot spots were revealed, while at the same time large portions of the continuous permafrost zone are still only sparsely covered by satellite remote sensing investigations. Moreover, studies related to Arctic greenhouse gas emissions in the context of permafrost degradation appear heavily underrepresented. New tools (e.g., Google Earth Engine (GEE)), methodologies (e.g., deep learning or data fusion etc.) and satellite data (e.g., the Methane Remote Sensing LiDAR Mission (Merlin) and the Sentinel-fleet) will thereby enable future studies to further investigate the distribution of permafrost, its thermal state and its implications on the environment such as thermokarst features and greenhouse gas emission rates on increasingly larger spatial and temporal scales.

Large stocks of peatland carbon and nitrogen are vulnerable to permafrost thaw

Over many millennia, northern peatlands have accumulated large amounts of carbon and nitrogen, thus cooling the global climate. Over shorter timescales, peatland disturbances can trigger losses of peat and release of greenhouses gases. Despite their importance to the global climate, peatlands remain poorly mapped, and the vulnerability of permafrost peatlands to warming is uncertain. This study compiles over 7,000 field observations to present a data-driven map of northern peatlands and their carbon and nitrogen stocks. We use these maps to model the impact of permafrost thaw on peatlands and find that warming will likely shift the greenhouse gas balance of northern peatlands. At present, peatlands cool the climate, but anthropogenic warming can shift them into a net source of warming.

Northern peatlands have accumulated large stocks of organic carbon (C) and nitrogen (N), but their spatial distribution and vulnerability to climate warming remain uncertain. Here, we used machine-learning techniques with extensive peat core data (n > 7,000) to create observation-based maps of northern peatland C and N stocks, and to assess their response to warming and permafrost thaw. We estimate that northern peatlands cover 3.7 ± 0.5 million km² and store 415 ± 150 Pg C and 10 ± 7 Pg N. Nearly half of the peatland area and peat C stocks are permafrost affected. Using modeled global warming stabilization scenarios (from 1.5 to 6 °C warming), we project that the current sink of atmospheric C (0.10 ± 0.02 Pg C⋅y⁻¹) in northern peatlands will shift to a C source as 0.8 to 1.9 million km² of permafrost-affected peatlands thaw. The projected thaw would cause peatland greenhouse gas emissions equal to ∼1% of anthropogenic radiative forcing in this century. The main forcing is from methane emissions (0.7 to 3 Pg cumulative CH₄-C) with smaller carbon dioxide forcing (1 to 2 Pg CO₂-C) and minor nitrous oxide losses. We project that initial CO₂-C losses reverse after ∼200 y, as warming strengthens peatland C-sinks. We project substantial, but highly uncertain, additional losses of peat into fluvial systems of 10 to 30 Pg C and 0.4 to 0.9 Pg N. The combined gaseous and fluvial peatland C loss estimated here adds 30 to 50% onto previous estimates of permafrost-thaw C losses, with southern permafrost regions being the most vulnerable.

Remote Sensing of Boreal Wetlands 2: Methods for Evaluating Boreal Wetland Ecosystem State and Drivers of Change

The following review is the second part of a two part series on the use of remotely sensed data for quantifying wetland extent and inferring or measuring condition for monitoring drivers of change on wetland environments. In the first part, we introduce policy makers and non-users of remotely sensed data with an effective feasibility guide on how data can be used. In the current review, we explore the more technical aspects of remotely sensed data processing and analysis using case studies within the literature. Here we describe: (a) current technologies used for wetland assessment and monitoring; (b) the latest algorithmic developments for wetland assessment; (c) new technologies; and (d) a framework for wetland sampling in support of remotely sensed data collection. Results illustrate that high or fine spatial resolution pixels (≤10 m) are critical for identifying wetland boundaries and extent, and wetland class, form and type, but are not required for all wetland sizes. Average accuracies can be up to 11% better (on average) than medium resolution (11–30 m) data pixels when compared with field validation. Wetland size is also a critical factor such that large wetlands may be almost as accurately classified using medium-resolution data (average = 76% accuracy, stdev = 21%). Decision-tree and machine learning algorithms provide the most accurate wetland classification methods currently available, however, these also require sampling of all permutations of variability. Hydroperiod accuracy, which is dependent on instantaneous water extent for single time period datasets does not vary greatly with pixel resolution when compared with field data (average = 87%, 86%) for high and medium resolution pixels, respectively. The results of this review provide users with a guideline for optimal use of remotely sensed data and suggested field methods for boreal and global wetland studies.

Remote Sensing of Boreal Wetlands 1: Data Use for Policy and Management

Wetlands have and continue to undergo rapid environmental and anthropogenic modification and change to their extent, condition, and therefore, ecosystem services. In this first part of a two-part review, we provide decision-makers with an overview on the use of remote sensing technologies for the ‘wise use of wetlands’, following Ramsar Convention protocols. The objectives of this review are to provide: (1) a synthesis of the history of remote sensing of wetlands, (2) a feasibility study to quantify the accuracy of remotely sensed data products when compared with field data based on 286 comparisons found in the literature from 209 articles, (3) recommendations for best approaches based on case studies, and (4) a decision tree to assist users and policymakers at numerous governmental levels and industrial agencies to identify optimal remote sensing approaches based on needs, feasibility, and cost. We argue that in order for remote sensing approaches to be adopted by wetland scientists, land-use managers, and policymakers, there is a need for greater understanding of the use of remote sensing for wetland inventory, condition, and underlying processes at scales relevant for management and policy decisions. The literature review focuses on boreal wetlands primarily from a Canadian perspective, but the results are broadly applicable to policymakers and wetland scientists globally, providing knowledge on how to best incorporate remotely sensed data into their monitoring and measurement procedures. This is the first review quantifying the accuracy and feasibility of remotely sensed data and data combinations needed for monitoring and assessment. These include, baseline classification for wetland inventory, monitoring through time, and prediction of ecosystem processes from individual wetlands to a national scale.

Altitudinal disparity in growth of Dahurian larch (Larix gmelinii Rupr.) in response to recent climate change in northeast China

Forests are sensitive to climate change at high altitude and high latitude. Dahurian larch (Larix gmelinii Rupr.) has experienced an unprecedented forest retreat northward during the last century. Whether the response of growth to climate has dissimilar patterns at different altitudes, and what the "altitudinal trends" of forest development will be in the future, remains unclear. We dendroclimatically investigated the impacts of climate change on the growth of larch forests along an altitudinal gradient. In total, 721 trees from 25 forest stands, representing an altitudinal range from 400 to 950 m a.s.l. in the Great Xing'an Mountains, northeast China, were sampled and used to develop tree-ring width chronologies. The results suggest that warming caused a decline in larch growth at low altitude, while tree growth increased at high altitude. The growth-climate relationships indicate that October-February temperatures were positively correlated with larch growth at low- and high-altitude sites, but negatively correlated at medium-altitude sites (ca. 600-700 m a.s.l.). April-May (early spring) temperatures and October-January precipitation had positive effects on growth in general (ca. 75% of all sites). The effects of summer temperature/precipitation on larch growth at high-altitude sites were opposite to that at low-altitude sites. This change of response from significantly positive/negative correlation to significantly negative/positive correlation occurred gradually along the altitudinal gradient. The relationships varied significantly with altitude both in the case of temperature (R² = 0.425, P < 0.001) and precipitation (R² = 0.613, P < 0.001). The shift in response of larch forest to changes in summer temperature and precipitation occurred in the areas with a mean annual temperature of ca. -4 °C and ca. -5 °C, respectively; larch growth at temperatures lower or higher than these thresholds was limited by temperature and precipitation, respectively.

Detection of Fir Trees (Abies sibirica) Damaged by the Bark Beetle in Unmanned Aerial Vehicle Images with Deep Learning

Invasion of the Polygraphus proximus Blandford bark beetle causes catastrophic damage to forests with firs (Abies sibirica Ledeb) in Russia, especially in Central Siberia. Determining tree damage stage based on the shape, texture and colour of tree crown in unmanned aerial vehicle (UAV) images could help to assess forest health in a faster and cheaper way. However, this task is challenging since (i) fir trees at different damage stages coexist and overlap in the canopy, (ii) the distribution of fir trees in nature is irregular and hence distinguishing between different crowns is hard, even for the human eye. Motivated by the latest advances in computer vision and machine learning, this work proposes a two-stage solution: In a first stage, we built a detection strategy that finds the regions of the input UAV image that are more likely to contain a crown, in the second stage, we developed a new convolutional neural network (CNN) architecture that predicts the fir tree damage stage in each candidate region. Our experiments show that the proposed approach shows satisfactory results on UAV Red, Green, Blue (RGB) images of forest areas in the state nature reserve “Stolby” (Krasnoyarsk, Russia).

Ecological Response to Permafrost Thaw and Consequences for Local and Global Ecosystem Services

The Arctic may seem remote, but the unprecedented environmental changes occurring there have important consequences for global society. Of all Arctic system components, changes in permafrost (perennially frozen ground) are one of the least documented. Permafrost is degrading as a result of climate warming, and evidence is mounting that changing permafrost will have significant impacts within and outside the region. This review asks: What are key structural and functional properties of ecosystems that interact with changing permafrost, and how do these ecosystem changes affect local and global society? Here, we look beyond the classic definition of permafrost to include a broadened focus on the composition of frozen ground, including the ice and the soil organic carbon content, and how it is changing. This ecological perspective of permafrost serves to identify areas of both vulnerability and resilience as climate, ecological disturbance regimes, and the human footprint all continue to change in this sensitive and critical region of Earth.

Vegetation Indices Do Not Capture Forest Cover Variation in Upland Siberian Larch Forests

Boreal forests are changing in response to climate, with potentially important feedbacks to regional and global climate through altered carbon cycle and albedo dynamics. These feedback processes will be affected by vegetation changes, and feedback strengths will largely rely on the spatial extent and timing of vegetation change. Satellite remote sensing is widely used to monitor vegetation dynamics, and vegetation indices (VIs) are frequently used to characterize spatial and temporal trends in vegetation productivity. In this study we combine field observations of larch forest cover across a 25 km2 upland landscape in northeastern Siberia with high-resolution satellite observations to determine how the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI) are related to forest cover. Across 46 forest stands ranging from 0% to 90% larch canopy cover, we find either no change, or declines in NDVI and EVI derived from PlanetScope CubeSat and Landsat data with increasing forest cover. In conjunction with field observations of NDVI, these results indicate that understory vegetation likely exerts a strong influence on vegetation indices in these ecosystems. This suggests that positive decadal trends in NDVI in Siberian larch forests may correspond primarily to increases in understory productivity, or even to declines in forest cover. Consequently, positive NDVI trends may be associated with declines in terrestrial carbon storage and increases in albedo, rather than increases in carbon storage and decreases in albedo that are commonly assumed. Moreover, it is also likely that important ecological changes such as large changes in forest density or variable forest regrowth after fire are not captured by long-term NDVI trends.

A National Assessment of Wetland Status and Trends for Canada’s Forested Ecosystems Using 33 Years of Earth Observation Satellite Data

Wetlands are important globally for supplying clean water and unique habitat, and for storing vast amounts of carbon and nutrients. The geographic extent and state of wetlands vary over time and represent a dynamic land condition rather than a permanent land cover state. Herein, we combined a time series of land cover maps derived from Landsat data at 30-m resolution to inform on spatial and temporal changes to non-treed and treed wetland extents over Canada’s forested ecosystems (>650 million ha) from 1984 to 2016. Overall, for the period, 1984 to 2016, we found the extent of wetlands (non-treed and treed combined) in Canada’s forested ecosystems to be stable, with some regional variability, often resulting from offsetting decreases and increases within a given ecozone. Notwithstanding difficulties in using optical satellite data for mapping a land condition, by accumulating wetland evidence via earth observations consistently through multiple decades, our results capture the trends in wetland cover over a previously unmapped, national extent at a level of spatial detail and temporal reach suitable for further focused interpretations of wetlands and drivers and projections of wetland dynamics.

The Role of Climate and Land Use in the Changes in Surface Albedo Prior to Snow Melt and the Timing of Melt Season of Seasonal Snow in Northern Land Areas of 40°N–80°N during 1982–2015

The rapid warming of the Northern Hemisphere high latitudes and the observed changes in boreal forest areas affect the global surface albedo and climate. This study looks at the trends in the timing of the snow melt season as well as the albedo levels before and after the melt season in Northern Hemisphere land areas between 40°N and 80°N over the years 1982 to 2015. The analysis is based on optical satellite data from the Advanced Very High Resolution Radiometer (AVHRR). The results show that the changes in surface albedo already begin before the start of the melt season. These albedo changes are significant (the mean of absolute change is 4.4 albedo percentage units per 34 years). The largest absolute changes in pre-melt-season albedo are concentrated in areas of the boreal forest, while the pre-melt albedo of tundra remains unchanged. Trends in melt season timing are consistent over large areas. The mean of absolute change of start date of melt season is 11.2 days per 34 years, 10.6 days for end date of melt season and 14.8 days for length of melt season. The changes result in longer and shorter melt seasons, as well as changed timing of the melt, depending on the area. The albedo levels preceding the onset of melt and start of the melt season correlate with climatic parameters (air temperature, precipitation, wind speed). The changes in albedo are more closely linked to changes in vegetation, whereas the changes in melt season timing are linked to changes in climate.

Increasing canopy photosynthesis in rice can be achieved without a large increase in water use-A model based on free-air CO2 enrichment

Achieving higher canopy photosynthesis rates is one of the keys to increasing future crop production; however, this typically requires additional water inputs because of increased water loss through the stomata. Lowland rice canopies presently consume a large amount of water, and any further increase in water usage may significantly impact local water resources. This situation is further complicated by changing the environmental conditions such as rising atmospheric CO₂ concentration ([CO₂ ]). Here, we modeled and compared evapotranspiration of fully developed rice canopies of a high-yielding rice cultivar (Oryza sativa L. cv. Takanari) with a common cultivar (cv. Koshihikari) under ambient and elevated [CO₂ ] (A-CO₂ and E-CO₂ , respectively) via leaf ecophysiological parameters derived from a free-air CO₂ enrichment (FACE) experiment. Takanari had 4%-5% higher evapotranspiration than Koshihikari under both A-CO₂ and E-CO₂ , and E-CO₂ decreased evapotranspiration of both varieties by 4%-6%. Therefore, if Takanari was cultivated under future [CO₂ ] conditions, the cost for water could be maintained at the same level as for cultivating Koshihikari at current [CO₂ ] with an increase in canopy photosynthesis by 36%. Sensitivity analyses determined that stomatal conductance was a significant physiological factor responsible for the greater canopy photosynthesis in Takanari over Koshihikari. Takanari had 30%-40% higher stomatal conductance than Koshihikari; however, the presence of high aerodynamic resistance in the natural field and lower canopy temperature of Takanari than Koshihikari resulted in the small difference in evapotranspiration. Despite the small difference in evapotranspiration between varieties, the model simulations showed that Takanari clearly decreased canopy and air temperatures within the planetary boundary layer compared to Koshihikari. Our results indicate that lowland rice varieties characterized by high-stomatal conductance can play a key role in enhancing productivity and moderating heat-induced damage to grain quality in the coming decades, without significantly increasing crop water use.

Higher climate warming sensitivity of Siberian larch in small than large forest islands in the fragmented Mongolian forest steppe

Forest fragmentation has been found to affect biodiversity and ecosystem functioning in multiple ways. We asked whether forest size and isolation in fragmented woodlands influences the climate warming sensitivity of tree growth in the southern boreal forest of the Mongolian Larix sibirica forest steppe, a naturally fragmented woodland embedded in grassland, which is highly affected by warming, drought, and increasing anthropogenic forest destruction in recent time. We examined the influence of stand size and stand isolation on the growth performance of larch in forests of four different size classes located in a woodland-dominated forest-steppe area and small forest patches in a grassland-dominated area. We found increasing climate sensitivity and decreasing first-order autocorrelation of annual stemwood increment with decreasing stand size. Stemwood increment increased with previous year's June and August precipitation in the three smallest forest size classes, but not in the largest forests. In the grassland-dominated area, the tree growth dependence on summer rainfall was highest. Missing ring frequency has strongly increased since the 1970s in small, but not in large forests. In the grassland-dominated area, the increase was much greater than in the forest-dominated landscape. Forest regeneration decreased with decreasing stand size and was scarce or absent in the smallest forests. Our results suggest that the larch trees in small and isolated forest patches are far more susceptible to climate warming than in large continuous forests pointing to a grim future for the forests in this strongly warming region of the boreal forest that is also under high land use pressure.

Direct and indirect climate change effects on carbon dioxide fluxes in a thawing boreal forest-wetland landscape

In the sporadic permafrost zone of northwestern Canada, boreal forest carbon dioxide (CO₂ ) fluxes will be altered directly by climate change through changing meteorological forcing and indirectly through changes in landscape functioning associated with thaw-induced collapse-scar bog ('wetland') expansion. However, their combined effect on landscape-scale net ecosystem CO₂ exchange (NEE_LAND ), resulting from changing gross primary productivity (GPP) and ecosystem respiration (ER), remains unknown. Here, we quantify indirect land cover change impacts on NEE_LAND and direct climate change impacts on modeled temperature- and light-limited NEE_LAND of a boreal forest-wetland landscape. Using nested eddy covariance flux towers, we find both GPP and ER to be larger at the landscape compared to the wetland level. However, annual NEE_LAND (-20 g C m^-2 ) and wetland NEE (-24 g C m^-2 ) were similar, suggesting negligible wetland expansion effects on NEE_LAND . In contrast, we find non-negligible direct climate change impacts when modeling NEE_LAND using projected air temperature and incoming shortwave radiation. At the end of the 21st century, modeled GPP mainly increases in spring and fall due to reduced temperature limitation, but becomes more frequently light-limited in fall. In a warmer climate, ER increases year-round in the absence of moisture stress resulting in net CO₂ uptake increases in the shoulder seasons and decreases during the summer. Annually, landscape net CO₂ uptake is projected to decline by 25 ± 14 g C m^-2 for a moderate and 103 ± 38 g C m^-2 for a high warming scenario, potentially reversing recently observed positive net CO₂ uptake trends across the boreal biome. Thus, even without moisture stress, net CO₂ uptake of boreal forest-wetland landscapes may decline, and ultimately, these landscapes may turn into net CO₂ sources under continued anthropogenic CO₂ emissions. We conclude that NEE_LAND changes are more likely to be driven by direct climate change rather than by indirect land cover change impacts.

Threshold loss of discontinuous permafrost and landscape evolution

This study demonstrates linkages between the 1997/1998 El Niño/Southern Oscillation index and a threshold shift to increased permafrost loss within a southern Taiga Plains watershed, Northwest Territories, Canada. Three-dimensional contraction of permafrost plateaus and changes in vegetation structural characteristics are determined from multitemporal airborne Light Detection And Ranging (LiDAR) surveys in 2008, 2011 and 2015. Morphological changes in permafrost cover are compared with optical image analogues from 1970, 1977, 2000 and 2008 and time-series hydro-climate data. Results demonstrate that significant changes in air temperature, precipitation, runoff and a shortening of the snow-covered season by 35 days (1998-2014) and 50 days (1998 only) occurred after 1997. The albedo reduction associated with 35 and 50 days less snow cover leads to increases in shortwave energy receipt during the active thaw period of ~12% (3% annually) and ~16% (5% annually), respectively. From 2000 to 2015, sporadic permafrost loss accelerated from 0.19% (of total basin area) per year between 1970 and 2000 to 0.58% per year from 2000 to 2015, with a projected total loss of permafrost by ~2044. From ~1997 to 2011, we observe a corresponding shift to increased runoff ratio. However, observed increases in the proportion of snow precipitation and the volumetric contribution of permafrost loss to runoff post-1997 (0.6-6.4% per year) cannot fully explain this shift. This suggests increases in drainage efficiency and possible losses from long-term groundwater storage as a result of subtle terrain morphological and soil zone hydraulic conductivity changes. These hydrological changes appear coincident with high vegetation mortality at plateau margins combined with succession-related canopy growth in some bog and fen areas, which are presumed to be drying. Similar changes in runoff response were observed at adjacent Birch, Trout and Jean Marie River watersheds indicating that observations are representative of northern Boreal sporadic permafrost/wetland watersheds in the Taiga Plains.

The positive net radiative greenhouse gas forcing of increasing methane emissions from a thawing boreal forest-wetland landscape

At the southern margin of permafrost in North America, climate change causes widespread permafrost thaw. In boreal lowlands, thawing forested permafrost peat plateaus ('forest') lead to expansion of permafrost-free wetlands ('wetland'). Expanding wetland area with saturated and warmer organic soils is expected to increase landscape methane (CH₄ ) emissions. Here, we quantify the thaw-induced increase in CH₄ emissions for a boreal forest-wetland landscape in the southern Taiga Plains, Canada, and evaluate its impact on net radiative forcing relative to potential long-term net carbon dioxide (CO₂ ) exchange. Using nested wetland and landscape eddy covariance net CH₄ flux measurements in combination with flux footprint modeling, we find that landscape CH₄ emissions increase with increasing wetland-to-forest ratio. Landscape CH₄ emissions are most sensitive to this ratio during peak emission periods, when wetland soils are up to 10 °C warmer than forest soils. The cumulative growing season (May-October) wetland CH₄ emission of ~13 g CH₄  m^-2 is the dominating contribution to the landscape CH₄ emission of ~7 g CH₄  m^-2 . In contrast, forest contributions to landscape CH₄ emissions appear to be negligible. The rapid wetland expansion of 0.26 ± 0.05% yr^-1 in this region causes an estimated growing season increase of 0.034 ± 0.007 g CH₄  m^-2  yr^-1 in landscape CH₄ emissions. A long-term net CO₂ uptake of >200 g CO₂  m^-2  yr^-1 is required to offset the positive radiative forcing of increasing CH₄ emissions until the end of the 21st century as indicated by an atmospheric CH₄ and CO₂ concentration model. However, long-term apparent carbon accumulation rates in similar boreal forest-wetland landscapes and eddy covariance landscape net CO₂ flux measurements suggest a long-term net CO₂ uptake between 49 and 157 g CO₂  m^-2  yr^-1 . Thus, thaw-induced CH₄ emission increases likely exert a positive net radiative greenhouse gas forcing through the 21st century.