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

Environmental drivers of increased ecosystem respiration in a warming tundra

Arctic and alpine tundra ecosystems are large reservoirs of organic carbon1,2. Climate warming may stimulate ecosystem respiration and release carbon into the atmosphere3,4. The magnitude and persistency of this stimulation and the environmental mechanisms that drive its variation remain uncertain5-7. This hampers the accuracy of global land carbon-climate feedback projections7,8. Here we synthesize 136 datasets from 56 open-top chamber in situ warming experiments located at 28 arctic and alpine tundra sites which have been running for less than 1 year up to 25 years. We show that a mean rise of 1.4 °C [confidence interval (CI) 0.9-2.0 °C] in air and 0.4 °C [CI 0.2-0.7 °C] in soil temperature results in an increase in growing season ecosystem respiration by 30% [CI 22-38%] (n = 136). Our findings indicate that the stimulation of ecosystem respiration was due to increases in both plant-related and microbial respiration (n = 9) and continued for at least 25 years (n = 136). The magnitude of the warming effects on respiration was driven by variation in warming-induced changes in local soil conditions, that is, changes in total nitrogen concentration and pH and by context-dependent spatial variation in these conditions, in particular total nitrogen concentration and the carbon:nitrogen ratio. Tundra sites with stronger nitrogen limitations and sites in which warming had stimulated plant and microbial nutrient turnover seemed particularly sensitive in their respiration response to warming. The results highlight the importance of local soil conditions and warming-induced changes therein for future climatic impacts on respiration.

Impacts of reduced synthetic fertiliser use under current and future climates: Exploration using integrated agroecosystem modelling in the upper River Taw observatory, UK

The intensification of farming and increased nitrogen fertiliser use, to satisfy the growing population demand, contributed to the extant climate change crisis. Use of synthetic fertilisers in agriculture is a significant source of anthropogenic Greenhouse Gas (GHG) emissions, especially potent nitrous oxide (N2O). To achieve the ambitious policy target for net zero by 2050 in the UK, it is crucial to understand the impacts of potential reductions in fertiliser use on multiple ecosystem services, including crop production, GHG emissions and soil organic carbon (SOC) storge. A novel integrated modelling approach using three established agroecosystem models (SPACSYS, CSM and RothC) was implemented to evaluate the associated impacts of fertiliser reduction (10%, 30% and 50%) under current and projected climate scenarios (RCP2.6, RCP4.5 and RCP8.5) in a study catchment in Southwest England. 48 unique combinations of soil types, climate conditions and fertiliser inputs were evaluated for five major arable crops plus improved grassland. With a 30% reduction in fertiliser inputs, the estimated yield loss under current climate ranged between 11% and 30% for arable crops compared with a 20-24% and 6-22% reduction in N2O and methane emissions, respectively. Biomass was reduced by 10-25% aboveground and by <12% for the root system. Relative to the baseline scenario, soil type dependent reductions in SOC sequestration rates are predicted under future climate with reductions in fertiliser inputs. Losses in SOC were more than doubled under the RCP4.5 scenario. The emissions from energy use, including embedded emissions from fertiliser manufacture, was a significant source (14-48%) for all arable crops and the associated GWP20.

Comparative responses of carbon flux components in recovering bare patches of degraded alpine meadow in the Source Zone of the Yellow River

The patchy degradation of alpine grasslands is a common phenomenon on the Qinghai-Tibetan Plateau, and the presence of bare patches (BP) in degraded grasslands significantly affects the functioning of the alpine meadow ecosystem. The succession of vegetation-recovered BP may lead to significant changes in ecosystem carbon (C) cycling. To date, it is unclear whether different components of net ecosystem carbon exchange (NEE) respond similarly or differently to the succession of recovering BP. Here, we conducted a field monitoring experiment in a degraded alpine meadow, and selected three successional stages for recovering BP to study the response of NEE and its components. We found that the succession of recoevering BP increased ecosystem respiration (ER) during the growing season and decreased ER during the off-growing season, with the differences in annual carbon output between different successional stages being insignificant. However, gross primary productivity increased with the successional gradient, and carbon input at the later stage of succession was significantly greater than that at the middle stage of succession. The succession of recovering BP promoted the carbon sequestration function of the alpine grassland, with the grassland acting as a carbon sink when it reached the state of healthy alpine meadow, while it acted as a carbon source during the middle stage of succession. Compared with BP, the amount of carbon sequested by healthy alpine meadows increased significantly by 219 g·C·m-2·yr-1. We also found that the responses of other components to the succession of recovering BP were inconsistent. In addition, the effects of succession of recovering BP on carbon flux were related to field-monitored variables (soil temperature and water content) and other considered variables (biomass, organic carbon, and microbial biomass carbon). These research findings highlight the importance of restoring vegetation in BPs, and are crucial for predicting the carbon balance in the future and formulating sustainable grassland management strategies.

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.

Persistent and enhanced carbon sequestration capacity of alpine grasslands on Earth's Third Pole

The carbon sequestration capacity of alpine grasslands, composed of alpine meadows and steppes, in the Tibetan Plateau has an essential role in regulating the regional carbon cycle. However, inadequate understanding of its spatiotemporal dynamics and regulatory mechanisms restricts our ability to determine potential climate change impacts. We assessed the spatial and temporal patterns and mechanisms of the net ecosystem exchange (NEE) of carbon dioxide in the Tibetan Plateau. The carbon sequestration of the alpine grasslands ranged from 26.39 to 79.19 Tg C year^-1 and had an increasing rate of 1.14 Tg C year^-1 between 1982 and 2018. While alpine meadows were relatively strong carbon sinks, the semiarid and arid alpine steppes were nearly carbon neutral. Alpine meadow areas experienced strong increases in carbon sequestration mainly because of increasing temperatures, while alpine steppe areas had weak increases mainly due to increasing precipitation. Carbon sequestration capacity of alpine grasslands on the plateau has undergone persistent enhancement under a warmer and wetter climate.

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 (R_eco ), net ecosystem CO₂ exchange (NEE; R_eco  - 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.

Soil moisture impacts the tundra carbon balance in a changing climate

There is growing recognition that soil moisture plays a crucial role in regulating the response of tundra carbon cycling to climate warming.

A widely-used eddy covariance gap-filling method creates systematic bias in carbon balance estimates

Climate change mitigation requires, besides reductions in greenhouse gas emissions, actions to increase carbon sinks in terrestrial ecosystems. A key measurement method for quantifying such sinks and calibrating models is the eddy covariance technique, but it requires imputation, or gap-filling, of missing data for determination of annual carbon balances of ecosystems. Previous comparisons of gap-filling methods have concluded that commonly used methods, such as marginal distribution sampling (MDS), do not have a significant impact on the carbon balance estimate. By analyzing an extensive, global data set, we show that MDS causes significant carbon balance errors for northern (latitude [Formula: see text]) sites. MDS systematically overestimates the carbon dioxide (CO[Formula: see text]) emissions of carbon sources and underestimates the CO[Formula: see text] sequestration of carbon sinks. We also reveal reasons for these biases and show how a machine learning method called extreme gradient boosting or a modified implementation of MDS can be used to substantially reduce the northern site bias.

Bioclimatic atlas of the terrestrial Arctic

The Arctic is the region on Earth that is warming at the fastest rate. In addition to rising means of temperature-related variables, Arctic ecosystems are affected by increasingly frequent extreme weather events causing disturbance to Arctic ecosystems. Here, we introduce a new dataset of bioclimatic indices relevant for investigating the changes of Arctic terrestrial ecosystems. The dataset, called ARCLIM, consists of several climate and event-type indices for the northern high-latitude land areas > 45°N. The indices are calculated from the hourly ERA5-Land reanalysis data for 1950-2021 in a spatial grid of 0.1 degree (~9 km) resolution. The indices are provided in three subsets: (1) the annual values during 1950-2021; (2) the average conditions for the 1991-2020 climatology; and (3) temporal trends over 1951-2021. The 72-year time series of various climate and event-type indices draws a comprehensive picture of the occurrence and recurrence of extreme weather events and climate variability of the changing Arctic bioclimate.

Asynchronous responses of microbial CAZymes genes and the net CO2 exchange in alpine peatland following 5 years of continuous extreme drought events

Peatlands act as an important sink of carbon dioxide (CO2). Yet, they are highly sensitive to climate change, especially to extreme drought. The changes in the net ecosystem CO2 exchange (NEE) under extreme drought events, and the driving function of microbial enzymatic genes involved in soil organic matter (SOM) decomposition, are still unclear. Herein we investigated the effects of extreme drought events in different periods of plant growth season at Zoige peatland on NEE and microbial enzymatic genes of SOM decomposition after 5 years. The results showed that the NEE of peatland decreased significantly by 48% and 26% on average (n = 12, P < 0.05) under the early and midterm extreme drought, respectively. The microbial enzymatic genes abundance of SOM decomposition showed the same decreasing trend under early and midterm extreme drought, but an increasing trend under late extreme drought. The microbial community that contributes to these degradation genes mainly derives from Proteobacteria and Actinobacteria. NEE was mainly affected by soil hydrothermal factors and gross primary productivity but weakly correlated with SOM enzymatic decomposition genes. Soil microbial respiration showed a positive correlation with microbial enzymatic genes involved in the decomposition of labile carbon (n = 18, P < 0.05). This study provided new insights into the responses of the microbial decomposition potential of SOM and ecosystem CO2 sink function to extreme drought events in the alpine peatland.

The future of tundra carbon storage in Greenland - Sensitivity to climate and plant trait changes

The continuous change in observed key indicators such as increasing nitrogen deposition, temperatures and precipitation will have marked but uncertain consequences for the ecosystem carbon (C) sink-source functioning of the Arctic. Here, we use multiple in-situ data streams measured by the Greenland Ecosystem Monitoring programme in tight connection with the Soil-Plant-Atmosphere model and climate projections from the high-resolution HIRHAM5 regional model. We apply this modelling framework with focus on two climatically different tundra sites in Greenland (Zackenberg and Kobbefjord) to assess how sensitive the net C uptake will expectedly be under warmer and wetter conditions across the 21st century and pin down the relative contribution to the overall C sink strength from climate versus plant trait variability. Our results suggest that temperatures (5-7.7 °C), total precipitation (19-110 %) and vapour pressure deficit will increase (32-36 %), while shortwave radiation will decline (6-9 %) at both sites by 2100 under the RCP8.5 scenario. Such a combined effect will, on average, intensify the net C uptake by 9-10 g C m^-2 year^-1 at both sites towards the end of 2100, but Zackenberg is expected to have more than twice the C sink strength capacity of Kobbefjord. Our sensitivity analysis not only reveals that plant traits are the most sensitive parameters controlling the net C exchange in both sites at the beginning and end of the century, but also that the projected increase in the net C uptake will likely be similarly influenced by future changes in climate and existing local nutrient conditions. A series of experiments forcing realistic changes in plant nitrogen status at both sites corroborates this hypothesis. This work proves the unique synergy between monitoring data and numerical models to assist robust model calibration/validation and narrow uncertainty ranges and ultimately produce more reliable C cycle projections in understudied regions such as Greenland.

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 CO_2-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.

Respiratory loss during late-growing season determines the net carbon dioxide sink in northern permafrost regions

Warming of northern high latitude regions (NHL, > 50 °N) has increased both photosynthesis and respiration which results in considerable uncertainty regarding the net carbon dioxide (CO₂) balance of NHL ecosystems. Using estimates constrained from atmospheric observations from 1980 to 2017, we find that the increasing trends of net CO₂ uptake in the early-growing season are of similar magnitude across the tree cover gradient in the NHL. However, the trend of respiratory CO₂ loss during late-growing season increases significantly with increasing tree cover, offsetting a larger fraction of photosynthetic CO₂ uptake, and thus resulting in a slower rate of increasing annual net CO₂ uptake in areas with higher tree cover, especially in central and southern boreal forest regions. The magnitude of this seasonal compensation effect explains the difference in net CO₂ uptake trends along the NHL vegetation- permafrost gradient. Such seasonal compensation dynamics are not captured by dynamic global vegetation models, which simulate weaker respiration control on carbon exchange during the late-growing season, and thus calls into question projections of increasing net CO₂ uptake as high latitude ecosystems respond to warming climate conditions.

The northern high latitude permafrost region has been an important contributor to the carbon sink since the 1980s. A new study finds that as tree cover increases, respiratory CO2 loss during late-growing season offsets photosynthetic CO2 uptake and leads to a slower rate of increasing annual net CO2 uptake.

Arctic soil respiration and microbial community structure driven by silicon and calcium

Global warming is most pronounced in the Arctic region. Greenhouse gas (GHG) release from Arctic soils increase due to global warming. By this, the Arctic may change from currently being a carbon sink to a future source. To improve accurate predictions of future GHG release from Arctic soils, it is important to unravel factors controlling both the microbial community structure and activity. Soil microbial activity is important for Arctic greenhouse gas production, but depends on soil conditions such as salinity being increased by calcium (Ca) and decreased by amorphous silica (Si) potentially enhancing water availability. In the Arctic, climate changes may alter salinity by changing Si and Ca concentrations upon permafrost thaw as a result of global warming with Si potentially decreasing and Ca potentially increasing salinity. Here, we show that higher Si concentration increased and higher Ca concentrations decreased the microbial CO₂ production for both a salt-poor and a salt-rich soil from Greenland. In the salt-rich soil, Si amendment increased CO₂ production and the abundance of gram-negative bacteria. However, the bacterial community became dominated by spore-forming gram-positive Firmicutes and Actinobacteria. The CO₂ release from soils was directly affected by the abundance of bacteria and fungi, and their community structure. Our results highlight the importance of the soil Si and Ca concentration on organic carbon turnover by strongly changing microbial abundance and community structure, with consequences for CO₂ release in the Arctic. Consequently, Ca and Si and their relation to Arctic soil microbial community structure has to be considered when estimating pan-Arctic carbon budgets.

Fencing farm dams to exclude livestock halves methane emissions and improves water quality

Agricultural practices have created tens of millions of small artificial water bodies ("farm dams" or "agricultural ponds") to provide water for domestic livestock worldwide. Among freshwater ecosystems, farm dams have some of the highest greenhouse gas (GHG) emissions per m² due to fertilizer and manure run-off boosting methane production-an extremely potent GHG. However, management strategies to mitigate the substantial emissions from millions of farm dams remain unexplored. We tested the hypothesis that installing fences to exclude livestock could reduce nutrients, improve water quality, and lower aquatic GHG emissions. We established a large-scale experiment spanning 400 km across south-eastern Australia where we compared unfenced (N = 33) and fenced farm dams (N = 31) within 17 livestock farms. Fenced farm dams recorded 32% less dissolved nitrogen, 39% less dissolved phosphorus, 22% more dissolved oxygen, and produced 56% less diffusive methane emissions than unfenced dams. We found no effect of farm dam management on diffusive carbon dioxide emissions and on the organic carbon in the soil. Dissolved oxygen was the most important variable explaining changes in carbon fluxes across dams, whereby doubling dissolved oxygen from 5 to 10 mg L^-1 led to a 74% decrease in methane fluxes, a 124% decrease in carbon dioxide fluxes, and a 96% decrease in CO₂ -eq (CH₄  + CO₂ ) fluxes. Dams with very high dissolved oxygen (>10 mg L^-1 ) showed a switch from positive to negative CO₂ -eq. (CO₂  + CH₄ ) fluxes (i.e., negative radiative balance), indicating a positive contribution to reduce atmospheric warming. Our results demonstrate that simple management actions can dramatically improve water quality and decrease methane emissions while contributing to more productive and sustainable farming.

Australian farm dams are becoming less reliable water sources under climate change

Worldwide food production is under ever-increasing demand. Meanwhile, climate change is disrupting rainfall and evaporation patterns, making agriculture freshwater supplies more uncertain. IPCC models predict an increased variability in rainfall and temperature over most of the globe under climate change. Yet, the effects of climate variability on water security remain poorly resolved. Here we used satellite images and deep-learning convolutional neural networks to analyse the impacts of annual averages, seasonality, climate anomaly, and temporal autocorrelation (or climate reddening) for rain and temperature on the water levels of >100,000 Australian farm dams across 55 years. We found that the risk of empty farm dams increased with warmer annual temperatures, lower yearly rainfall, stronger seasonality, reduced climate anomalies, and higher temporal autocorrelation. We used this information to develop a predictive model and estimate the likelihood of water limitations in farm dams between 1965 and 2050 using historical data and Coupled Model Intercomparison Project Phase 5 (CMIP5) at two climate change scenarios. Results showed that the frequency of empty water reserves has increased 2.5-fold since 1965 and will continue to increase across most (91%) of Australia. We estimated a 37% decline in rural areas with year-round water supplies between 1965 (457,076 km²) and 2050 (285,998 km²). Our continental-scale assessment documents complex temporal and spatial impacts of climate change on agricultural water security, with ramifications for society, economy, and the environment.

Regional and seasonal partitioning of water and temperature controls on global land carbon uptake variability

Global fluctuations in annual land carbon uptake (NEE_IAV) depend on water and temperature variability, yet debate remains about local and seasonal controls of the global dependences. Here, we quantify regional and seasonal contributions to the correlations of globally-averaged NEE_IAV against terrestrial water storage (TWS) and temperature, and respective uncertainties, using three approaches: atmospheric inversions, process-based vegetation models, and data-driven models. The three approaches agree that the tropics contribute over 63% of the global correlations, but differ on the dominant driver of the global NEE_IAV, because they disagree on seasonal temperature effects in the Northern Hemisphere (NH, >25°N). In the NH, inversions and process-based models show inter-seasonal compensation of temperature effects, inducing a global TWS dominance supported by observations. Data-driven models show weaker seasonal compensation, thereby estimating a global temperature dominance. We provide a roadmap to fully understand drivers of global NEE_IAV and discuss their implications for future carbon–climate feedbacks.

The dominant driver of variations in global land carbon sink remains unclear. Here the authors show that the seasonal compensation of temperature effects on land carbon sink in the Northern Hemisphere could induce a global water dominance.

Exploring the effects of land management change on productivity, carbon and nutrient balance: Application of an Ensemble Modelling Approach to the upper River Taw observatory, UK

Agriculture is challenged to produce healthy food and to contribute to cleaner energy whilst mitigating climate change and protecting ecosystems. To achieve this, policy-driven scenarios need to be evaluated with available data and models to explore trade-offs with robust accounting for the uncertainty in predictions. We developed a novel model ensemble using four complementary state-of-the-art agroecosystems models to explore the impacts of land management change. The ensemble was used to simulate key agricultural and environmental outputs under various scenarios for the upper River Taw observatory, UK. Scenarios assumed (i) reducing livestock production whilst simultaneously increasing the area of arable where it is feasible to cultivate (PG2A), (ii) reducing livestock production whilst simultaneously increasing bioenergy production in areas of the catchment that are amenable to growing bioenergy crops (PG2BE) and (iii) increasing both arable and bioenergy production (PG2A + BE). Our ensemble approach combined model uncertainty using the tower property of expectation and the law of total variance. Results show considerable uncertainty for predicted nutrient losses with different models partitioning the uncertainty into different pathways. Bioenergy crops were predicted to produce greatest yields from Miscanthus in lowland and from SRC-willow (cv. Endurance) in uplands. Each choice of management is associated with trade-offs; e.g. PG2A results in a significant increase of edible calories (6736 Mcal ha^-1) but reduced soil C (-4.32 t C ha^-1). Model ensembles in the agroecosystem context are difficult to implement due to challenges of model availability and input and output alignment. Despite these challenges, we show that ensemble modelling is a powerful approach for applications such as ours, offering benefits such as capturing structural as well as data uncertainty and allowing greater combinations of variables to be explored. Furthermore, the ensemble provides a robust means for combining uncertainty at different scales and enables us to identify weaknesses in system understanding.

Impacts of Permafrost Degradation on Carbon Stocks and Emissions under a Warming Climate: A Review

A huge amount of carbon (C) is stored in permafrost regions. Climate warming and permafrost degradation induce gradual and abrupt carbon emissions into both the atmosphere and hydrosphere. In this paper, we review and synthesize recent advances in studies on carbon stocks in permafrost regions, biodegradability of permafrost organic carbon (POC), carbon emissions, and modeling/projecting permafrost carbon feedback to climate warming. The results showed that: (1) A large amount of organic carbon (1460–1600 PgC) is stored in permafrost regions, while there are large uncertainties in the estimation of carbon pools in subsea permafrost and in clathrates in terrestrial permafrost regions and offshore clathrate reservoirs; (2) many studies indicate that carbon pools in Circum-Arctic regions are on the rise despite the increasing release of POC under a warming climate, because of enhancing carbon uptake of boreal and arctic ecosystems; however, some ecosystem model studies indicate otherwise, that the permafrost carbon pool tends to decline as a result of conversion of permafrost regions from atmospheric sink to source under a warming climate; (3) multiple environmental factors affect the decomposability of POC, including ground hydrothermal regimes, carbon/nitrogen (C/N) ratio, organic carbon contents, and microbial communities, among others; and (4) however, results from modeling and projecting studies on the feedbacks of POC to climate warming indicate no conclusive or substantial acceleration of climate warming from POC emission and permafrost degradation over the 21st century. These projections may potentially underestimate the POC feedbacks to climate warming if abrupt POC emissions are not taken into account. We advise that studies on permafrost carbon feedbacks to climate warming should also focus more on the carbon feedbacks from the rapid permafrost degradation, such as thermokarst processes, gas hydrate destabilization, and wildfire-induced permafrost degradation. More attention should be paid to carbon emissions from aquatic systems because of their roles in channeling POC release and their significant methane release potentials.

Plant uptake of CO2 outpaces losses from permafrost and plant respiration on the Tibetan Plateau

High-latitude and high-altitude regions contain vast stores of permafrost carbon. Climate warming may result in the release of CO2 from both the thawing of permafrost and accelerated autotrophic respiration, but it may also increase the fixation of CO2 by plants, which could relieve or even offset the CO2 losses. The Tibetan Plateau contains the largest area of alpine permafrost on Earth. However, the current status of the net CO2 balance and feedbacks to warming remain unclear, given that the region has recently experienced an atmospheric warming rate of over 0.3 °C decade-1 We examined 32 eddy covariance sites and found an unexpected net CO2 sink during 2002 to 2020 (26 of the sites yielded a net CO2 sink) that was four times the amount previously estimated. The CO2 sink peaked at an altitude of roughly 4,000 m, with the sink at lower and higher altitudes limited by a low carbon use efficiency and a cold, dry climate, respectively. The fixation of CO2 in summer is more dependent on temperature than the loss of CO2 than it is in the winter months, especially at higher altitudes. Consistently, 16 manipulative experiments and 18 model simulations showed that the fixation of CO2 by plants will outpace the loss of CO2 under a wetting-warming climate until the 2090s (178 to 318 Tg C y-1). We therefore suggest that there is a plant-dominated negative feedback to climate warming on the Tibetan Plateau.

Comparison of Machine Learning Methods to Up-Scale Gross Primary Production

Eddy covariance observation is an applicable way to obtain accurate and continuous carbon flux at flux tower sites, while remote sensing technology could estimate carbon exchange and carbon storage at regional and global scales effectively. However, it is still challenging to up-scale the field-observed carbon flux to a regional scale, due to the heterogeneity and the unstable air conditions at the land surface. In this paper, gross primary production (GPP) from ground eddy covariance systems were up-scaled to a regional scale by using five machine learning methods (Cubist regression tree, random forest, support vector machine, artificial neural network, and deep belief network). Then, the up-scaled GPP were validated using GPP at flux tower sites, weighted GPP in the footprint, and MODIS GPP products. At last, the sensitivity of the input data (normalized difference vegetation index, fractional vegetation cover, shortwave radiation, relative humidity and air temperature) to the precision of up-scaled GPP was analyzed, and the uncertainty of the machine learning methods was discussed. The results of this paper indicated that machine learning methods had a great potential in up-scaling GPP at flux tower sites. The validation of up-scaled GPP, using five machine learning methods, demonstrated that up-scaled GPP using random forest obtained the highest accuracy.