Persistent net release of carbon dioxide and methane from an Alaskan lowland boreal peatland complex.

Permafrost degradation in peatlands is altering vegetation and soil properties and impacting net carbon storage. We studied four adjacent sites in Alaska with varied permafrost regimes, including a black spruce forest on a peat plateau with permafrost, two collapse scar bogs of different ages formed following thermokarst, and a rich fen without permafrost. Measurements included year-round eddy covariance estimates of net carbon dioxide (CO2 ), mid-April to October methane (CH4 ) emissions, and environmental variables. From 2011 to 2022, annual rainfall was above the historical average, snow water equivalent increased, and snow-season duration shortened due to later snow return. Seasonally thawed active layer depths also increased. During this period, all ecosystems acted as slight annual sources of CO2 (13-59 g C m-2 year-1 ) and stronger sources of CH4 (11-14 g CH4 m-2 from ~April to October). The interannual variability of net ecosystem exchange was high, approximately ±100 g C m-2 year-1 , or twice what has been previously reported across other boreal sites. Net CO2 release was positively related to increased summer rainfall and winter snow water equivalent and later snow return. Controls over CH4 emissions were related to increased soil moisture and inundation status. The dominant emitter of carbon was the rich fen, which, in addition to being a source of CO2 , was also the largest CH4 emitter. These results suggest that the future carbon-source strength of boreal lowlands in Interior Alaska may be determined by the area occupied by minerotrophic fens, which are expected to become more abundant as permafrost thaw increases hydrologic connectivity. Since our measurements occur within close proximity of each other (≤1 km2 ), this study also has implications for the spatial scale and data used in benchmarking carbon cycle models and emphasizes the necessity of long-term measurements to identify carbon cycle process changes in a warming climate.

Modeled production, oxidation, and transport processes of wetland methane emissions in temperate, boreal, and Arctic regions.

Wetlands are the largest natural source of methane (CH4 ) to the atmosphere. The eddy covariance method provides robust measurements of net ecosystem exchange of CH4 , but interpreting its spatiotemporal variations is challenging due to the co-occurrence of CH4 production, oxidation, and transport dynamics. Here, we estimate these three processes using a data-model fusion approach across 25 wetlands in temperate, boreal, and Arctic regions. Our data-constrained model-iPEACE-reasonably reproduced CH4 emissions at 19 of the 25 sites with normalized root mean square error of 0.59, correlation coefficient of 0.82, and normalized standard deviation of 0.87. Among the three processes, CH4 production appeared to be the most important process, followed by oxidation in explaining inter-site variations in CH4 emissions. Based on a sensitivity analysis, CH4 emissions were generally more sensitive to decreased water table than to increased gross primary productivity or soil temperature. For periods with leaf area index (LAI) of ≥20% of its annual peak, plant-mediated transport appeared to be the major pathway for CH4 transport. Contributions from ebullition and diffusion were relatively high during low LAI (<20%) periods. The lag time between CH4 production and CH4 emissions tended to be short in fen sites (3 ± 2 days) and long in bog sites (13 ± 10 days). Based on a principal component analysis, we found that parameters for CH4 production, plant-mediated transport, and diffusion through water explained 77% of the variance in the parameters across the 19 sites, highlighting the importance of these parameters for predicting wetland CH4 emissions across biomes. These processes and associated parameters for CH4 emissions among and within the wetlands provide useful insights for interpreting observed net CH4 fluxes, estimating sensitivities to biophysical variables, and modeling global CH4 fluxes.

Carbon uptake in Eurasian boreal forests dominates the high-latitude net ecosystem carbon budget.

Arctic-boreal landscapes are experiencing profound warming, along with changes in ecosystem moisture status and disturbance from fire. This region is of global importance in terms of carbon feedbacks to climate, yet the sign (sink or source) and magnitude of the Arctic-boreal carbon budget within recent years remains highly uncertain. Here, we provide new estimates of recent (2003-2015) vegetation gross primary productivity (GPP), ecosystem respiration (Reco ), net ecosystem CO2 exchange (NEE; Reco - GPP), and terrestrial methane (CH4 ) emissions for the Arctic-boreal zone using a satellite data-driven process-model for northern ecosystems (TCFM-Arctic), calibrated and evaluated using measurements from >60 tower eddy covariance (EC) sites. We used TCFM-Arctic to obtain daily 1-km2 flux estimates and annual carbon budgets for the pan-Arctic-boreal region. Across the domain, the model indicated an overall average NEE sink of -850 Tg CO2 -C year-1 . Eurasian boreal zones, especially those in Siberia, contributed to a majority of the net sink. In contrast, the tundra biome was relatively carbon neutral (ranging from small sink to source). Regional CH4 emissions from tundra and boreal wetlands (not accounting for aquatic CH4 ) were estimated at 35 Tg CH4 -C year-1 . Accounting for additional emissions from open water aquatic bodies and from fire, using available estimates from the literature, reduced the total regional NEE sink by 21% and shifted many far northern tundra landscapes, and some boreal forests, to a net carbon source. This assessment, based on in situ observations and models, improves our understanding of the high-latitude carbon status and also indicates a continued need for integrated site-to-regional assessments to monitor the vulnerability of these ecosystems to climate change.

Pan-Arctic soil moisture control on tundra carbon sequestration and plant productivity.

Long-term atmospheric CO2 concentration records have suggested a reduction in the positive effect of warming on high-latitude carbon uptake since the 1990s. A variety of mechanisms have been proposed to explain the reduced net carbon sink of northern ecosystems with increased air temperature, including water stress on vegetation and increased respiration over recent decades. However, the lack of consistent long-term carbon flux and in situ soil moisture data has severely limited our ability to identify the mechanisms responsible for the recent reduced carbon sink strength. In this study, we used a record of nearly 100 site-years of eddy covariance data from 11 continuous permafrost tundra sites distributed across the circumpolar Arctic to test the temperature (expressed as growing degree days, GDD) responses of gross primary production (GPP), net ecosystem exchange (NEE), and ecosystem respiration (ER) at different periods of the summer (early, peak, and late summer) including dominant tundra vegetation classes (graminoids and mosses, and shrubs). We further tested GPP, NEE, and ER relationships with soil moisture and vapor pressure deficit to identify potential moisture limitations on plant productivity and net carbon exchange. Our results show a decrease in GPP with rising GDD during the peak summer (July) for both vegetation classes, and a significant relationship between the peak summer GPP and soil moisture after statistically controlling for GDD in a partial correlation analysis. These results suggest that tundra ecosystems might not benefit from increased temperature as much as suggested by several terrestrial biosphere models, if decreased soil moisture limits the peak summer plant productivity, reducing the ability of these ecosystems to sequester carbon during the summer.

Lowering water table reduces carbon sink strength and carbon stocks in northern peatlands.

Peatlands at high latitudes have accumulated >400 Pg carbon (C) because saturated soil and cold temperatures suppress C decomposition. This substantial amount of C in Arctic and Boreal peatlands is potentially subject to increased decomposition if the water table (WT) decreases due to climate change, including permafrost thaw-related drying. Here, we optimize a version of the Organizing Carbon and Hydrology In Dynamic Ecosystems model (ORCHIDEE-PCH4) using site-specific observations to investigate changes in CO2 and CH4 fluxes as well as C stock responses to an experimentally manipulated decrease of WT at six northern peatlands. The unmanipulated control peatlands, with the WT <20 cm on average (seasonal max up to 45 cm) below the surface, currently act as C sinks in most years (58 ± 34 g C m-2  year-1 ; including 6 ± 7 g C-CH4 m-2  year-1 emission). We found, however, that lowering the WT by 10 cm reduced the CO2 sink by 13 ± 15 g C m-2  year-1 and decreased CH4 emission by 4 ± 4 g CH4 m-2  year-1 , thus accumulating less C over 100 years (0.2 ± 0.2 kg C m-2 ). Yet, the reduced emission of CH4 , which has a larger greenhouse warming potential, resulted in a net decrease in greenhouse gas balance by 310 ± 360 g CO2-eq  m-2  year-1 . Peatlands with the initial WT close to the soil surface were more vulnerable to C loss: Non-permafrost peatlands lost >2 kg C m-2 over 100 years when WT is lowered by 50 cm, while permafrost peatlands temporally switched from C sinks to sources. These results highlight that reductions in C storage capacity in response to drying of northern peatlands are offset in part by reduced CH4 emissions, thus slightly reducing the positive carbon climate feedbacks of peatlands under a warmer and drier future climate scenario.

Assessing dynamic vegetation model parameter uncertainty across Alaskan arctic tundra plant communities.

As the Arctic region moves into uncharted territory under a warming climate, it is important to refine the terrestrial biosphere models (TBMs) that help us understand and predict change. One fundamental uncertainty in TBMs relates to model parameters, configuration variables internal to the model whose value can be estimated from data. We incorporate a version of the Terrestrial Ecosystem Model (TEM) developed for arctic ecosystems into the Predictive Ecosystem Analyzer (PEcAn) framework. PEcAn treats model parameters as probability distributions, estimates parameters based on a synthesis of available field data, and then quantifies both model sensitivity and uncertainty to a given parameter or suite of parameters. We examined how variation in 21 parameters in the equation for gross primary production influenced model sensitivity and uncertainty in terms of two carbon fluxes (net primary productivity and heterotrophic respiration) and two carbon (C) pools (vegetation C and soil C). We set up different parameterizations of TEM across a range of tundra types (tussock tundra, heath tundra, wet sedge tundra, and shrub tundra) in northern Alaska, along a latitudinal transect extending from the coastal plain near Utqiagvik to the southern foothills of the Brooks Range, to the Seward Peninsula. TEM was most sensitive to parameters related to the temperature regulation of photosynthesis. Model uncertainty was mostly due to parameters related to leaf area, temperature regulation of photosynthesis, and the stomatal responses to ambient light conditions. Our analysis also showed that sensitivity and uncertainty to a given parameter varied spatially. At some sites, model sensitivity and uncertainty tended to be connected to a wider range of parameters, underlining the importance of assessing tundra community processes across environmental gradients or geographic locations. Generally, across sites, the flux of net primary productivity (NPP) and pool of vegetation C had about equal uncertainty, while heterotrophic respiration had higher uncertainty than the pool of soil C. Our study illustrates the complexity inherent in evaluating parameter uncertainty across highly heterogeneous arctic tundra plant communities. It also provides a framework for iteratively testing how newly collected field data related to key parameters may result in more effective forecasting of Arctic change.

Statistical upscaling of ecosystem CO2 fluxes across the terrestrial tundra and boreal domain: Regional patterns and uncertainties.

The 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.

Identifying dominant environmental predictors of freshwater wetland methane fluxes across diurnal to seasonal time scales.

While wetlands are the largest natural source of methane (CH4 ) to the atmosphere, they represent a large source of uncertainty in the global CH4 budget due to the complex biogeochemical controls on CH4 dynamics. Here we present, to our knowledge, the first multi-site synthesis of how predictors of CH4 fluxes (FCH4) in freshwater wetlands vary across wetland types at diel, multiday (synoptic), and seasonal time scales. We used several statistical approaches (correlation analysis, generalized additive modeling, mutual information, and random forests) in a wavelet-based multi-resolution framework to assess the importance of environmental predictors, nonlinearities and lags on FCH4 across 23 eddy covariance sites. Seasonally, soil and air temperature were dominant predictors of FCH4 at sites with smaller seasonal variation in water table depth (WTD). In contrast, WTD was the dominant predictor for wetlands with smaller variations in temperature (e.g., seasonal tropical/subtropical wetlands). Changes in seasonal FCH4 lagged fluctuations in WTD by ~17 ± 11 days, and lagged air and soil temperature by median values of 8 ± 16 and 5 ± 15 days, respectively. Temperature and WTD were also dominant predictors at the multiday scale. Atmospheric pressure (PA) was another important multiday scale predictor for peat-dominated sites, with drops in PA coinciding with synchronous releases of CH4 . At the diel scale, synchronous relationships with latent heat flux and vapor pressure deficit suggest that physical processes controlling evaporation and boundary layer mixing exert similar controls on CH4 volatilization, and suggest the influence of pressurized ventilation in aerenchymatous vegetation. In addition, 1- to 4-h lagged relationships with ecosystem photosynthesis indicate recent carbon substrates, such as root exudates, may also control FCH4. By addressing issues of scale, asynchrony, and nonlinearity, this work improves understanding of the predictors and timing of wetland FCH4 that can inform future studies and models, and help constrain wetland CH4 emissions.

Increased high-latitude photosynthetic carbon gain offset by respiration carbon loss during an anomalous warm winter to spring transition.

Arctic and boreal ecosystems play an important role in the global carbon (C) budget, and whether they act as a future net C sink or source depends on climate and environmental change. Here, we used complementary in situ measurements, model simulations, and satellite observations to investigate the net carbon dioxide (CO2 ) seasonal cycle and its climatic and environmental controls across Alaska and northwestern Canada during the anomalously warm winter to spring conditions of 2015 and 2016 (relative to 2010-2014). In the warm spring, we found that photosynthesis was enhanced more than respiration, leading to greater CO2 uptake. However, photosynthetic enhancement from spring warming was partially offset by greater ecosystem respiration during the preceding anomalously warm winter, resulting in nearly neutral effects on the annual net CO2 balance. Eddy covariance CO2 flux measurements showed that air temperature has a primary influence on net CO2 exchange in winter and spring, while soil moisture has a primary control on net CO2 exchange in the fall. The net CO2 exchange was generally more moisture limited in the boreal region than in the Arctic tundra. Our analysis indicates complex seasonal interactions of underlying C cycle processes in response to changing climate and hydrology that may not manifest in changes in net annual CO2 exchange. Therefore, a better understanding of the seasonal response of C cycle processes may provide important insights for predicting future carbon-climate feedbacks and their consequences on atmospheric CO2 dynamics in the northern high latitudes.

Carbon dioxide sources from Alaska driven by increasing early winter respiration from Arctic tundra.

High-latitude ecosystems have the capacity to release large amounts of carbon dioxide (CO2) to the atmosphere in response to increasing temperatures, representing a potentially significant positive feedback within the climate system. Here, we combine aircraft and tower observations of atmospheric CO2 with remote sensing data and meteorological products to derive temporally and spatially resolved year-round CO2 fluxes across Alaska during 2012-2014. We find that tundra ecosystems were a net source of CO2 to the atmosphere annually, with especially high rates of respiration during early winter (October through December). Long-term records at Barrow, AK, suggest that CO2 emission rates from North Slope tundra have increased during the October through December period by 73% ± 11% since 1975, and are correlated with rising summer temperatures. Together, these results imply increasing early winter respiration and net annual emission of CO2 in Alaska, in response to climate warming. Our results provide evidence that the decadal-scale increase in the amplitude of the CO2 seasonal cycle may be linked with increasing biogenic emissions in the Arctic, following the growing season. Early winter respiration was not well simulated by the Earth System Models used to forecast future carbon fluxes in recent climate assessments. Therefore, these assessments may underestimate the carbon release from Arctic soils in response to a warming climate.

The Sphagnome Project: enabling ecological and evolutionary insights through a genus-level sequencing project.

Considerable progress has been made in ecological and evolutionary genetics with studies demonstrating how genes underlying plant and microbial traits can influence adaptation and even 'extend' to influence community structure and ecosystem level processes. Progress in this area is limited to model systems with deep genetic and genomic resources that often have negligible ecological impact or interest. Thus, important linkages between genetic adaptations and their consequences at organismal and ecological scales are often lacking. Here we introduce the Sphagnome Project, which incorporates genomics into a long-running history of Sphagnum research that has documented unparalleled contributions to peatland ecology, carbon sequestration, biogeochemistry, microbiome research, niche construction, and ecosystem engineering. The Sphagnome Project encompasses a genus-level sequencing effort that represents a new type of model system driven not only by genetic tractability, but by ecologically relevant questions and hypotheses.

Spring photosynthetic onset and net CO2 uptake in Alaska triggered by landscape thawing.

The springtime transition to regional-scale onset of photosynthesis and net ecosystem carbon uptake in boreal and tundra ecosystems are linked to the soil freeze-thaw state. We present evidence from diagnostic and inversion models constrained by satellite fluorescence and airborne CO2 from 2012 to 2014 indicating the timing and magnitude of spring carbon uptake in Alaska correlates with landscape thaw and ecoregion. Landscape thaw in boreal forests typically occurs in late April (DOY 111 ± 7) with a 29 ± 6 day lag until photosynthetic onset. North Slope tundra thaws 3 weeks later (DOY 133 ± 5) but experiences only a 20 ± 5 day lag until photosynthetic onset. These time lag differences reflect efficient cold season adaptation in tundra shrub and the longer dehardening period for boreal evergreens. Despite the short transition from thaw to photosynthetic onset in tundra, synchrony of tundra respiration with snow melt and landscape thaw delays the transition from net carbon loss (at photosynthetic onset) to net uptake by 13 ± 7 days, thus reducing the tundra net carbon uptake period. Two global CO2 inversions using a CASA-GFED model prior estimate earlier northern high latitude net carbon uptake compared to our regional inversion, which we attribute to (i) early photosynthetic-onset model prior bias, (ii) inverse method (scaling factor + optimization window), and (iii) sparsity of available Alaskan CO2 observations. Another global inversion with zero prior estimates the same timing for net carbon uptake as the regional model but smaller seasonal amplitude. The analysis of Alaskan eddy covariance observations confirms regional scale findings for tundra, but indicates that photosynthesis and net carbon uptake occur up to 1 month earlier in evergreens than captured by models or CO2 inversions, with better correlation to above-freezing air temperature than date of primary thaw. Further collection and analysis of boreal evergreen species over multiple years and at additional subarctic flux towers are critically needed.

The role of driving factors in historical and projected carbon dynamics of upland ecosystems in Alaska.

It is important to understand how upland ecosystems of Alaska, which are estimated to occupy 84% of the state (i.e., 1,237,774 km2 ), are influencing and will influence state-wide carbon (C) dynamics in the face of ongoing climate change. We coupled fire disturbance and biogeochemical models to assess the relative effects of changing atmospheric carbon dioxide (CO2 ), climate, logging and fire regimes on the historical and future C balance of upland ecosystems for the four main Landscape Conservation Cooperatives (LCCs) of Alaska. At the end of the historical period (1950-2009) of our analysis, we estimate that upland ecosystems of Alaska store ~50 Pg C (with ~90% of the C in soils), and gained 3.26 Tg C/yr. Three of the LCCs had gains in total ecosystem C storage, while the Northwest Boreal LCC lost C (-6.01 Tg C/yr) because of increases in fire activity. Carbon exports from logging affected only the North Pacific LCC and represented less than 1% of the state's net primary production (NPP). The analysis for the future time period (2010-2099) consisted of six simulations driven by climate outputs from two climate models for three emission scenarios. Across the climate scenarios, total ecosystem C storage increased between 19.5 and 66.3 Tg C/yr, which represents 3.4% to 11.7% increase in Alaska upland's storage. We conducted additional simulations to attribute these responses to environmental changes. This analysis showed that atmospheric CO2 fertilization was the main driver of ecosystem C balance. By comparing future simulations with constant and with increasing atmospheric CO2 , we estimated that the sensitivity of NPP was 4.8% per 100 ppmv, but NPP becomes less sensitive to CO2 increase throughout the 21st century. Overall, our analyses suggest that the decreasing CO2 sensitivity of NPP and the increasing sensitivity of heterotrophic respiration to air temperature, in addition to the increase in C loss from wildfires weakens the C sink from upland ecosystems of Alaska and will ultimately lead to a source of CO2 to the atmosphere beyond 2100. Therefore, we conclude that the increasing regional C sink we estimate for the 21st century will most likely be transitional.

The role of environmental driving factors in historical and projected carbon dynamics of wetland ecosystems in Alaska.

Wetlands are critical terrestrial ecosystems in Alaska, covering ~177,000 km2 , an area greater than all the wetlands in the remainder of the United States. To assess the relative influence of changing climate, atmospheric carbon dioxide (CO2 ) concentration, and fire regime on carbon balance in wetland ecosystems of Alaska, a modeling framework that incorporates a fire disturbance model and two biogeochemical models was used. Spatially explicit simulations were conducted at 1-km resolution for the historical period (1950-2009) and future projection period (2010-2099). Simulations estimated that wetland ecosystems of Alaska lost 175 Tg carbon (C) in the historical period. Ecosystem C storage in 2009 was 5,556 Tg, with 89% of the C stored in soils. The estimated loss of C as CO2 and biogenic methane (CH4 ) emissions resulted in wetlands of Alaska increasing the greenhouse gas forcing of climate warming. Simulations for the projection period were conducted for six climate change scenarios constructed from two climate models forced under three CO2 emission scenarios. Ecosystem C storage averaged among climate scenarios increased 3.94 Tg C/yr by 2099, with variability among the simulations ranging from 2.02 to 4.42 Tg C/yr. These increases were driven primarily by increases in net primary production (NPP) that were greater than losses from increased decomposition and fire. The NPP increase was driven by CO2 fertilization (~5% per 100 parts per million by volume increase) and by increases in air temperature (~1% per °C increase). Increases in air temperature were estimated to be the primary cause for a projected 47.7% mean increase in biogenic CH4 emissions among the simulations (~15% per °C increase). Ecosystem CO2 sequestration offset the increase in CH4 emissions during the 21st century to decrease the greenhouse gas forcing of climate warming. However, beyond 2100, we expect that this forcing will ultimately increase as wetland ecosystems transition from being a sink to a source of atmospheric CO2 because of (1) decreasing sensitivity of NPP to increasing atmospheric CO2 , (2) increasing availability of soil C for decomposition as permafrost thaws, and (3) continued positive sensitivity of biogenic CH4 emissions to increases in soil temperature.

A decade of boreal rich fen greenhouse gas fluxes in response to natural and experimental water table variability.

Rich fens are common boreal ecosystems with distinct hydrology, biogeochemistry and ecology that influence their carbon (C) balance. We present growing season soil chamber methane emission (FCH4 ), ecosystem respiration (ER), net ecosystem exchange (NEE) and gross primary production (GPP) fluxes from a 9-years water table manipulation experiment in an Alaskan rich fen. The study included major flood and drought years, where wetting and drying treatments further modified the severity of droughts. Results support previous findings from peatlands that drought causes reduced magnitude of growing season FCH4 , GPP and NEE, thus reducing or reversing their C sink function. Experimentally exacerbated droughts further reduced the capacity for the fen to act as a C sink by causing shifts in vegetation and thus reducing magnitude of maximum growing season GPP in subsequent flood years by ~15% compared to control plots. Conversely, water table position had only a weak influence on ER, but dominant contribution to ER switched from autotrophic respiration in wet years to heterotrophic in dry years. Droughts did not cause inter-annual lag effects on ER in this rich fen, as has been observed in several nutrient-poor peatlands. While ER was dependent on soil temperatures at 2 cm depth, FCH4 was linked to soil temperatures at 25 cm. Inter-annual variability of deep soil temperatures was in turn dependent on wetness rather than air temperature, and higher FCH4 in flooded years was thus equally due to increased methane production at depth and decreased methane oxidation near the surface. Short-term fluctuations in wetness caused significant lag effects on FCH4 , but droughts caused no inter-annual lag effects on FCH4 . Our results show that frequency and severity of droughts and floods can have characteristic effects on the exchange of greenhouse gases, and emphasize the need to project future hydrological regimes in rich fens.

Thermokarst rates intensify due to climate change and forest fragmentation in an Alaskan boreal forest lowland.

Lowland boreal forest ecosystems in Alaska are dominated by wetlands comprised of a complex mosaic of fens, collapse-scar bogs, low shrub/scrub, and forests growing on elevated ice-rich permafrost soils. Thermokarst has affected the lowlands of the Tanana Flats in central Alaska for centuries, as thawing permafrost collapses forests that transition to wetlands. Located within the discontinuous permafrost zone, this region has significantly warmed over the past half-century, and much of these carbon-rich permafrost soils are now within ~0.5 °C of thawing. Increased permafrost thaw in lowland boreal forests in response to warming may have consequences for the climate system. This study evaluates the trajectories and potential drivers of 60 years of forest change in a landscape subjected to permafrost thaw in unburned dominant forest types (paper birch and black spruce) associated with location on elevated permafrost plateau and across multiple time periods (1949, 1978, 1986, 1998, and 2009) using historical and contemporary aerial and satellite images for change detection. We developed (i) a deterministic statistical model to evaluate the potential climatic controls on forest change using gradient boosting and regression tree analysis, and (ii) a 30 × 30 m land cover map of the Tanana Flats to estimate the potential landscape-level losses of forest area due to thermokarst from 1949 to 2009. Over the 60-year period, we observed a nonlinear loss of birch forests and a relatively continuous gain of spruce forest associated with thermokarst and forest succession, while gradient boosting/regression tree models identify precipitation and forest fragmentation as the primary factors controlling birch and spruce forest change, respectively. Between 1950 and 2009, landscape-level analysis estimates a transition of ~15 km² or ~7% of birch forests to wetlands, where the greatest change followed warm periods. This work highlights that the vulnerability and resilience of lowland ice-rich permafrost ecosystems to climate changes depend on forest type.

The unseen iceberg: plant roots in arctic tundra.

Plant roots play a critical role in ecosystem function in arctic tundra, but root dynamics in these ecosystems are poorly understood. To address this knowledge gap, we synthesized available literature on tundra roots, including their distribution, dynamics and contribution to ecosystem carbon and nutrient fluxes, and highlighted key aspects of their representation in terrestrial biosphere models. Across all tundra ecosystems, belowground plant biomass exceeded aboveground biomass, with the exception of polar desert tundra. Roots were shallowly distributed in the thin layer of soil that thaws annually, and were often found in surface organic soil horizons. Root traits - including distribution, chemistry, anatomy and resource partitioning - play an important role in controlling plant species competition, and therefore ecosystem carbon and nutrient fluxes, under changing climatic conditions, but have only been quantified for a small fraction of tundra plants. Further, the annual production and mortality of fine roots are key components of ecosystem processes in tundra, but extant data are sparse. Tundra root traits and dynamics should be the focus of future research efforts. Better representation of the dynamics and characteristics of tundra roots will improve the utility of models for the evaluation of the responses of tundra ecosystems to changing environmental conditions.

Polygonal tundra geomorphological change in response to warming alters future CO2 and CH4 flux on the Barrow Peninsula.

The landscape of the Barrow Peninsula in northern Alaska is thought to have formed over centuries to millennia, and is now dominated by ice-wedge polygonal tundra that spans drained thaw-lake basins and interstitial tundra. In nearby tundra regions, studies have identified a rapid increase in thermokarst formation (i.e., pits) over recent decades in response to climate warming, facilitating changes in polygonal tundra geomorphology. We assessed the future impact of 100 years of tundra geomorphic change on peak growing season carbon exchange in response to: (i) landscape succession associated with the thaw-lake cycle; and (ii) low, moderate, and extreme scenarios of thermokarst pit formation (10%, 30%, and 50%) reported for Alaskan arctic tundra sites. We developed a 30 × 30 m resolution tundra geomorphology map (overall accuracy:75%; Kappa:0.69) for our ~1800 km² study area composed of ten classes; drained slope, high center polygon, flat-center polygon, low center polygon, coalescent low center polygon, polygon trough, meadow, ponds, rivers, and lakes, to determine their spatial distribution across the Barrow Peninsula. Land-atmosphere CO2 and CH4 flux data were collected for the summers of 2006-2010 at eighty-two sites near Barrow, across the mapped classes. The developed geomorphic map was used for the regional assessment of carbon flux. Results indicate (i) at present during peak growing season on the Barrow Peninsula, CO2 uptake occurs at -902.3 10(6) gC-CO2 day(-1) (uncertainty using 95% CI is between -438.3 and -1366 10(6) gC-CO2 day(-1)) and CH4 flux at 28.9 10(6) gC-CH4 day(-1) (uncertainty using 95% CI is between 12.9 and 44.9 10(6) gC-CH4 day(-1)), (ii) one century of future landscape change associated with the thaw-lake cycle only slightly alter CO2 and CH4 exchange, while (iii) moderate increases in thermokarst pits would strengthen both CO2 uptake (-166.9 10(6) gC-CO2 day(-1)) and CH4 flux (2.8 10(6) gC-CH4 day(-1)) with geomorphic change from low to high center polygons, cumulatively resulting in an estimated negative feedback to warming during peak growing season.

Changes in the structure and function of northern Alaskan ecosystems when considering variable leaf-out times across groupings of species in a dynamic vegetation model.

The phenology of arctic ecosystems is driven primarily by abiotic forces, with temperature acting as the main determinant of growing season onset and leaf budburst in the spring. However, while the plant species in arctic ecosystems require differing amounts of accumulated heat for leaf-out, dynamic vegetation models simulated over regional to global scales typically assume some average leaf-out for all of the species within an ecosystem. Here, we make use of air temperature records and observations of spring leaf phenology collected across dominant groupings of species (dwarf birch shrubs, willow shrubs, other deciduous shrubs, grasses, sedges, and forbs) in arctic and boreal ecosystems in Alaska. We then parameterize a dynamic vegetation model based on these data for four types of tundra ecosystems (heath tundra, shrub tundra, wet sedge tundra, and tussock tundra), as well as ecotonal boreal white spruce forest, and perform model simulations for the years 1970-2100. Over the course of the model simulations, we found changes in ecosystem composition under this new phenology algorithm compared with simulations with the previous phenology algorithm. These changes were the result of the differential timing of leaf-out, as well as the ability for the groupings of species to compete for nitrogen and light availability. Regionally, there were differences in the trends of the carbon pools and fluxes between the new phenology algorithm and the previous phenology algorithm, although these differences depended on the future climate scenario. These findings indicate the importance of leaf phenology data collection by species and across the various ecosystem types within the highly heterogeneous Arctic landscape, and that dynamic vegetation models should consider variation in leaf-out by groupings of species within these ecosystems to make more accurate projections of future plant distributions and carbon cycling in Arctic regions.

Plant functional types in Earth system models: past experiences and future directions for application of dynamic vegetation models in high-latitude ecosystems.

BACKGROUND: Earth system models describe the physical, chemical and biological processes that govern our global climate. While it is difficult to single out one component as being more important than another in these sophisticated models, terrestrial vegetation is a critical player in the biogeochemical and biophysical dynamics of the Earth system. There is much debate, however, as to how plant diversity and function should be represented in these models. SCOPE: Plant functional types (PFTs) have been adopted by modellers to represent broad groupings of plant species that share similar characteristics (e.g. growth form) and roles (e.g. photosynthetic pathway) in ecosystem function. In this review, the PFT concept is traced from its origin in the early 1800s to its current use in regional and global dynamic vegetation models (DVMs). Special attention is given to the representation and parameterization of PFTs and to validation and benchmarking of predicted patterns of vegetation distribution in high-latitude ecosystems. These ecosystems are sensitive to changing climate and thus provide a useful test case for model-based simulations of past, current and future distribution of vegetation. CONCLUSIONS: Models that incorporate the PFT concept predict many of the emerging patterns of vegetation change in tundra and boreal forests, given known processes of tree mortality, treeline migration and shrub expansion. However, representation of above- and especially below-ground traits for specific PFTs continues to be problematic. Potential solutions include developing trait databases and replacing fixed parameters for PFTs with formulations based on trait co-variance and empirical trait-environment relationships. Surprisingly, despite being important to land-atmosphere interactions of carbon, water and energy, PFTs such as moss and lichen are largely absent from DVMs. Close collaboration among those involved in modelling with the disciplines of taxonomy, biogeography, ecology and remote sensing will be required if we are to overcome these and other shortcomings.