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Accurate simulation of plant phenology is important in Earth system models as phenology modulates land-atmosphere coupling and the carbon cycle. Evaluations based on grid-cell average leaf area index (LAI) can be misleading because multiple plant functional types (PFT) may be present in one model grid cell and PFTs with different phenology schemes have different LAI seasonal cycles. Here we examined PFT-specific LAI amplitudes and seasonal cycles in the Community Land Model versions 5.0 and 4.5 (CLM5.0 and CLM4.5) and their relationship with the onset of growing season triggers in the Northern Hemisphere. LAI seasonal cycle and spring onset in CLM show the best agreement with MODIS for temperature-dominated deciduous PFTs. Although the agreement in LAI amplitude between CLM5.0 and MODIS is better than CLM4.5, the agreement in seasonal cycles is worse in CLM5.0. CLM5.0 also simulates higher soil moisture and shows lower influences of soil moisture on LAI amplitudes and seasonal cycles. While productivity depends on the environmental factors to which the plant is exposed during any given growing season, differences in phenology sensitivity to its environment necessitate a decoupling between the seasonality of LAI and GPP, which in turn could lead to biases in the carbon cycle as well as surface energy balance and hence land-atmosphere interactions. Because the discrepancy not only depends on parameterizing phenology but phenology-environment relationship, future improvements to other model components (e.g., soil moisture) could better align the seasonal cycle of LAI and GPP.

Peatland biogeochemical processes have not been adequately represented in existing earth system models, which might have biased the quantification of Arctic carbon-climate feedbacks. We revise the Peatland Terrestrial Ecosystem Model (PTEM) by incorporating additional peatland biogeochemical processes. The revised PTEM is evaluated by comparing with Holocene Peatland Model (HPM) in simulating peat physical and biogeochemical dynamics in three North American peatlands: a permafrost-free fen site, a permafrost-free bog site and a permafrost bog site. Peatland carbon dynamics are simulated from peat initiation to 1990 and then to year 2300. Model responses to the changes in temperature and precipitation are analyzed to identify key processes affecting peatland carbon accumulation rates. We find that the net C balance is sensitive to water table depth and nutrient availability. Future simulations to year 2300 are conducted with both models under RCP 2.6, RCP 4.5, and RCP 8.5. PTEM predicts these peatlands to be C sources or weaker C sinks when insufficient precipitation suppresses soil moisture and thereby net N mineralization and net primary production, while HPM predicts the same when drier climate leads to increasing water table depth. Our results highlight the importance of water balance and C-N feedback on peatland C dynamics. With a warmer climate, these peatlands could become a weaker C sink or a source under drier conditions, otherwise a larger C sink if wetter. Improved understanding to peatland processes can help future quantification of peatland C dynamics in the boreal and Arctic regions.

Coastal wetlands are important components in the global carbon cycle; however, little is known regarding the carbon sink and source capacity of coastal wetlands in the northern high latitudes, nor their importance in the global methane budget. In this study, we investigate methane and carbon dioxide fluxes from coastal wetlands located along the mouth of the Kenai River of Southcentral Alaska. We measured methane fluxes with a portable greenhouse gas analyzer and a custom-made gas flux chamber along four transects with varying moisture, salinity, and tidal conditions during August 2021. To better understand the drivers of these fluxes, we also collected soil samples, recorded the vegetation composition, and measured salinity at each site. Preliminary results indicate that methane fluxes are lower in areas frequently inundated by tides as compared to areas with minimal to no tidal influence. In addition, we use these data to investigate the effects of salinity and moisture on coastal wetland methane and carbon dioxide fluxes. The overarching goal of this study is to understand whether Northern coastal wetlands are likely to become carbon sinks or sources with ongoing climate change and how future sea level rise will affect the methane and carbon dioxide emissions from these ecosystems at the land-ocean interface.

Degradation, conversion and drainage of tropical peatlands generate sizeable emissions of greenhouse gases (GHG). Current IPCC default emission factors (EF) for drained tropical peatlands are based on a very limited number of observations, thereby resulting in large uncertainties in emissions estimates. Impacts of disturbance on peat GHG emissions in undrained tropical peatlands can also be substantial but are not well characterized and not considered by IPCC guidelines. Research is critically needed to support development of more accurate EF for national GHG accounting for both drained and undrained degraded tropical peatlands. To explore the potential of process-based modelling to refine tropical peat EF, we used the DeNitrification DeComposition (DNDC) model to simulate peat GHG emissions and biogeophysical variables in oil palm plantations and undrained primary and secondary peat swamp forests of Central Kalimantan, Indonesia.The simulated magnitude of C inputs (litterfall and root mortality) and dynamics of annual heterotrophic respiration and peat decomposition N2O fluxes in oil palm plantations were generally consistent with field observations. The modelled onsite oil palm peat CO2 EF was lower than the IPCC default (11 Mg CO2-C ha-1 yr-1) and decreased from 7.7 ± 0.4 Mg C ha-1 yr-1 in the first decade to 3.0 ± 0.2 and 1.8 ± 0.3 Mg C ha-1 yr-1 in the second and third decades of the rotation. The modelled N2O EF from peat decomposition was higher than the IPCC default (1.2 kg N ha-1 yr-1) and increased from 3.5 ± 0.3 kg N ha-1 yr-1 in the first decade to 4.6 ± 0.5 kg N ha-1 yr-1 in the following ones. Modelled fertilizer-induced N2O emissions were minimal and much less than 1.6% of N inputs indicated by the IPCC EF in wet climates regardless of soil type. Temporal variations in oil palm EF were strongly linked to soil C:N ratio and mineral N content for CO2 and fertilizer-induced N2O emissions, and to precipitation, water table level, and soil NH4+ content for peat decomposition N2O emissions. These results suggest that current IPCC EF for oil palm on organic soil could over-estimate onsite CO2 emissions and underestimate peat decomposition N2O emissions and that decadal-scale temporal variation in emissions should be considered for further improvement of EF. Simulations allowed the generation of oil palm EF disaggregated by plantation age and emission source (decomposition, fertilizer-induced), a practical and useful application for GHG inventories in tropical peatlands.In unconverted land uses, the GHG budget (Mg CO2-equivalent ha-1 yr-1) was ten times higher in the secondary forest (10.2 ± 4.5) than in the primary forests (0.9 ± 3.9) on the account of a larger peat C budget and N2O emission rate. Preliminary modelling results suggest increased peat C outputs from heterotrophic respiration and decreased C inputs from litterfall and root mortality in secondary forest compared to primary forest. Our study highlights the disastrous atmospheric impact associated with not only conversion to oil palm but also forest degradation in tropical peatlands and stresses the need to investigate GHG fluxes in disturbed undrained lands.

Summary Desertification in Northern China degrades air quality in China's eastern cities by causing frequent dust storms. To stop desert expansion, China's government initiated the Three-North Shelterbelt Program, a large-scale reforestation project. Many issues with the project have been raised, from the choice of ill-adapted species to planting methods. Recently, the government implemented “natural reforestation”—closing former pastures to let vegetation regrow naturally. Unfortunately, it has been difficult to estimate the large-scale success of natural reforestation because measuring arid ecosystem productivity is a challenge for optical remote sensing. Here, we use satellite data to monitor vegetation water content and photosynthetic activity, thereby quantifying changes in vegetation biomass and productivity in Northern China. These satellite data corroborate official reforestation data. Our results show that vegetation activity is strongly correlated with both natural and traditional active reforestation, indicating opportunities for new natural reforestation techniques combined with satellite monitoring in other semi-arid regions.

Oil palm plantations on peat and associated drainage generate sizeable GHG emissions. Current IPCC default emission factors (EF) for oil palm on organic soil are based on a very limited number of observations from young plantations, thereby resulting in large uncertainties in emissions estimates. To explore the potential of process-based modeling to refine oil palm peat CO

Permafrost thaw increases active layer thickness, changes landscape hydrology and influences vegetation species composition. These changes alter belowground microbial and geochemical processes, affecting production, consumption and net emission rates of climate forcing trace gases. Net carbon dioxide (CO2) and methane (CH4) fluxes determine the radiative forcing contribution from these climate-sensitive ecosystems. Permafrost peatlands may be a mosaic of dry frozen hummocks, semi-thawed or perched sphagnum dominated areas, wet permafrost-free sedge dominated sites and open water ponds. We revisited estimates of climate forcing made for 1970 and 2000 for Stordalen Mire in northern Sweden and found the trend of increasing forcing continued into 2014. The Mire continued to transition from dry permafrost to sedge and open water areas, increasing by 100% and 35%, respectively, over the 45-year period, causing the net radiative forcing of Stordalen Mire to shift from negative to positive. This trend is driven by transitioning vegetation community composition, improved estimates of annual CO2 and CH4 exchange and a 22% increase in the IPCC's 100-year global warming potential (GWP_100) value for CH4. These results indicate that discontinuous permafrost ecosystems, while still remaining a net overall sink of C, can become a positive feedback to climate change on decadal timescales. This article is part of a discussion meeting issue ‘Rising methane: is warming feeding warming? (part 2)’.

Mitigation of greenhouse gas emissions from agriculture requires an understanding of spatial-temporal dynamics of nitrous oxide (N

Peatlands are climate critical carbon (C) reservoirs that could become a C source under continued warming. A strong relationship between plant tissue chemistry and the soil organic matter (SOM) that fuels C gas emissions is inferred, but rarely examined at the molecular level. Here we compared Fourier transform infrared (FT-IR) spectroscopy measurements of solid phase functionalities in plants and SOM to ultra-high-resolution mass spectrometric analyses of plant and SOM water extracts across a palsa-bog-fen thaw and moisture gradient in an Arctic peatland. From these analyses we calculated the C oxidation state (NOSC), a measure which can be used to assess organic matter quality. Palsa plant extracts had the highest NOSC, indicating high quality, whereas extracts of Sphagnum, which dominated the bog, had the lowest NOSC. The percentage of plant compounds that are less bioavailable and accumulate in the peat, increases from palsa (25%) to fen (41%) to bog (47%), reflecting the pattern of percent Sphagnum cover. The pattern of NOSC in the plant extracts was consistent with the high number of consumed compounds in the palsa and low number of consumed compounds in the bog. However, in the FT-IR analysis of the solid phase bog peat, carbohydrate content was high implying high quality SOM. We explain this discrepancy as the result of low solubilization of bog SOM facilitated by the low pH in the bog which makes the solid phase carbohydrates less available to microbial decomposition. Plant-associated condensed aromatics, tannins, and lignin-like compounds declined in the unsaturated palsa peat indicating decomposition, but lignin-like compounds accumulated in the bog and fen peat where decomposition was presumably inhibited by the anaerobic conditions. A molecular-level comparison of the aboveground C sources and peat SOM demonstrates that climate-associated vegetation shifts in peatlands are important controls on the mechanisms underlying changing C gas emissions.

Soil microbes drive decomposition of soil organic matter (SOM) and regulate soil carbon (C) dynamics. Process‐based models have been developed to quantify changes in soil organic carbon (SOC) and carbon dioxide (CO2) fluxes in agricultural ecosystems. However, microbial processes related to SOM decomposition have not been, or are inadequately, represented in these models, limiting predictions of SOC responses to changes in microbial activities. In this study, we developed a microbial‐mediated decomposition model based on a widely used biogeochemical model, DeNitrification‐DeComposition (DNDC), to simulate C dynamics in agricultural ecosystems. The model simulates organic matter decomposition, soil respiration, and SOC formation by simulating microbial and enzyme dynamics and their controls on decomposition, and considering impacts of climate, soil, crop, and farming management practices (FMPs) on C dynamics. When evaluated against field observations of net ecosystem CO2 exchange (NEE) and SOC change in two winter wheat systems, the model successfully captured both NEE and SOC changes under different FMPs. Inclusion of microbial processes improved the model's performance in simulating peak CO2 fluxes induced by residue return, primarily by capturing priming effects of residue inputs. We also investigated impacts of microbial physiology, SOM, and FMPs on soil C dynamics. Our results demonstrated that residue or manure input drove microbial activity and predominantly regulated the CO2 fluxes, and manure amendment largely regulated long‐term SOC change. The microbial physiology had considerable impacts on the microbial activities and soil C dynamics, emphasizing the necessity of considering microbial physiology and activities when assessing soil C dynamics in agricultural ecosystems.

The sources of atmospheric methane (CH4) during the Holocene remain widely debated, including the role of high latitude wetland and peatland expansion and fen-to-bog transitions. We reconstructed CH4 emissions from northern peatlands from 13,000 before present (BP) to present using an empirical model based on observations of peat initiation (>3600 14C dates), peatland type (>250 peat cores), and contemporary CH4 emissions in order to explore the effects of changes in wetland type and peatland expansion on CH4 emissions over the end of the late glacial and the Holocene. We find that fen area increased steadily before 8000 BP as fens formed in major wetland complexes. After 8000 BP, new fen formation continued but widespread peatland succession (to bogs) and permafrost aggradation occurred. Reconstructed CH4 emissions from peatlands increased rapidly between 10,600 BP and 6900 BP due to fen formation and expansion. Emissions stabilized after 5000 BP at 42 ± 25 Tg CH4 y-1 as high-emitting fens transitioned to lower-emitting bogs and permafrost peatlands. Widespread permafrost formation in northern peatlands after 1000 BP led to drier and colder soils which decreased CH4 emissions by 20% to 34 ± 21 Tg y-1 by the present day.

Here we provide an update to global gridded annual and monthly crop datasets. This new dataset uses the crop categories established by the Global Agro-Ecological Zones (GAEZ) Version 3 model, which is based on the Food and Agricultural Organization of the United Nations (FAO) crop production data. We used publicly available data from the FAOSTAT database as well as GAEZ Version 4 global gridded dataset to generate circa 2015 annual crop harvested area, production, and yields by crop production system (irrigated and rainfed) for 26 crops and crop categories globally at 5-minute resolution. We additionally used available data on crop rotations, cropping intensity, and planting and harvest dates to generate monthly gridded cropland data for physical areas for the 26 crops by production system. These data are in standard georeferenced gridded format, and can be used by any global hydrology, land surface, or other earth system model that requires gridded annual or monthly crop data inputs., Measurement(s)crop yield • crop harvest area • crop production • area of croplandTechnology Type(s)national reportingSample Characteristic - EnvironmentagricultureSample Characteristic - Locationglobal Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.16924087

Peatlands are impacted by climate and land-use changes, with feedback to warming by acting as either sources or sinks of carbon. Expert elicitation combined with literature review reveals key drivers of change that alter peatland carbon dynamics, with implications for improving models. The carbon balance of peatlands is predicted to shift from a sink to a source this century. However, peatland ecosystems are still omitted from the main Earth system models that are used for future climate change projections, and they are not considered in integrated assessment models that are used in impact and mitigation studies. By using evidence synthesized from the literature and an expert elicitation, we define and quantify the leading drivers of change that have impacted peatland carbon stocks during the Holocene and predict their effect during this century and in the far future. We also identify uncertainties and knowledge gaps in the scientific community and provide insight towards better integration of peatlands into modelling frameworks. Given the importance of the contribution by peatlands to the global carbon cycle, this study shows that peatland science is a critical research area and that we still have a long way to go to fully understand the peatland-carbon-climate nexus.

The surface urban heat island (SUHI) is one of the most significant human-induced alterations to the Earth's surface climate and can aggravate health risks for city dwellers during heat waves. Although the SUHI effect has received growing attention, its diurnal cycles (i.e., the variations over the full 24 h within the diel cycle) are poorly understood because polar-orbiting satellites (e.g., Landsat Series, Sentinel, Terra, Aqua) only provide one or two observations over each repeat cycle (e.g., 16 days) with constant overpass time for the same area. Geostationary satellites provide high-frequency land surface temperature (LST) observations throughout the day and the night, and thereby offer unprecedented opportunities for exploring the diurnal cycles of SUHI. Here we examined how the SUHI intensity varied over the course of the diurnal cycle in the Boston Metropolitan Area using LST observations from the NOAA's latest generation of Geostationary Operational Environmental Satellites (GOES-R). GOES-R LST was strongly correlated with MODIS LST (R2 = 0.98, p

Permafrost carbon feedback (PCF) modeling has focused on gradual thaw of near-surface permafrost leading to enhanced carbon dioxide and methane emissions that accelerate global climate warming. These state-of-the-art land models have yet to incorporate deeper, abrupt thaw in the PCF. Here we use model data, supported by field observations, radiocarbon dating, and remote sensing, to show that methane and carbon dioxide emissions from abrupt thaw beneath thermokarst lakes will more than double radiative forcing from circumpolar permafrost-soil carbon fluxes this century. Abrupt thaw lake emissions are similar under moderate and high representative concentration pathways (RCP4.5 and RCP8.5), but their relative contribution to the PCF is much larger under the moderate warming scenario. Abrupt thaw accelerates mobilization of deeply frozen, ancient carbon, increasing 14C-depleted permafrost soil carbon emissions by ~125–190% compared to gradual thaw alone. These findings demonstrate the need to incorporate abrupt thaw processes in earth system models for more comprehensive projection of the PCF this century., Permafrost carbon feedback modeling has focused on gradual thaw of near-surface permafrost leading to greenhouse gas emissions that accelerate climate change. Here the authors show that deeper, abrupt thaw beneath lakes will more than double radiative forcing from permafrost-soil carbon fluxes this century.

Croplands, occupying approximately 13% of the Earth's land surface, can dramatically alter surface temperature via multiple biophysical processes. However, it remains unclear whether and to what extent croplands warm or cool the land surface globally. Here we present new evidence of the temperature effects of global croplands based on high-resolution satellite observations of land surface temperature (LST). We find general daytime warming and nighttime cooling of crop-dominated lands (cropland intensity ≥90%) relative to other vegetation cover, with net daily cooling in the arid zone and net daily warming in all other areas. On a per-pixel basis, however, nearly half of the crop-dominated lands cool daytime LST and/or warm nighttime LST. The temperature effects vary greatly by location and season. The per-pixel intensity can exceed 10 °C likely due to the changes in surface evapotranspiration, albedo, and background climate. By extending the LST changes of crop-dominated lands to the full land surface, we find that croplands make large contributions to regional and global land surface warming. Daytime warming can reach 0.56 °C in Europe during spring. Nationally, China, India, and Brazil lead the warming due to their large cropland areas and strong local climate effects. Our results highlight the importance of accounting for the biophysical effects of croplands for projecting climate change and formulating adaptation and mitigation strategies.

Arctic peatlands are an important part of the global carbon cycle, accumulating atmospheric carbon as organic matter since the Late glacial. Current methods for understanding the changing efficiency of the peatland carbon sink rely on peatlands with an undisturbed stratigraphy. Here we present a method of estimating primary carbon accumulation rate from a site where permafrost processes have either vertically or horizontally translocated nearby carbon-rich sediment out of stratigraphic order. Briefly, our new algorithm estimates the probability of the age of deposition of a random increment of sediment in the core. The method assumes that if sediment age is measured at even depth increments, dates are more likely to occur during intervals of higher accumulation rate and vice versa. Multiplying estimated sedimentation rate by measured carbon density yields carbon accumulation rate. We perform this analysis at the Imnavait Creek Peatland, near the Arctic Long Term Ecological Research network site at Toolik Lake, Alaska. Using classical radiocarbon age modeling, we find unreasonably high rates of carbon accumulation at various Holocene intervals. With our new method, we find accumulation rate changes that are in improved agreement within the context of other sites throughout Alaska and the rest of the Circum-Arctic region.

Current peatland models generally lack dynamic feedback between the plant community structure and the environment, although the vegetation dynamics and ecosystem functioning are tightly linked. Realistic projections of peatland response to climate change requires including vegetation dynamics in ecosystem models. In peatlands, Sphagnum mosses are key engineers. The species composition in a moss community varies primarily following habitat moisture conditions. Hence, modelling the mechanisms in controlling the habitat preference of Sphagna is a good first step for modelling the community dynamics in peatlands. In this study, we developed the Peatland Moss Simulator (PMS), a process-based model, for simulating community dynamics of the peatland moss layer that results in habitat preferences of Sphagnum species along moisture gradients. PMS employed an individual-based approach to describe the variation of functional traits among shoots and the stochastic base of competition. At the shoot-level, growth and competition were driven by net photosynthesis, which was regulated by hydrological processes via capitulum water retention. The model was tested by predicting the habitat preferences of S. magellanicum and S. fallax, two key species representing dry (hummock) and wet (lawn) habitats in a poor fen peatland (Lakkasuo, Finland). PMS successfully captured the habitat preferences of the two Sphagnum species, based on observed variations in trait properties. Our model simulation further showed that the validity of PMS depended on the interspecific differences in capitulum water retention being correctly specified. Neglecting the water-retention differences led to the failure of PMS to predict the habitat preferences of the species in stochastic simulations. Our work highlights the importance of capitulum water retention to the dynamics and carbon functioning of Sphagnum communities in peatland ecosystems. Studies of peatland responses to changing environmental conditions thus need to include capitulum water processes as a control on the vegetation dynamics. For that our PMS model could be used as an elemental design for the future development of dynamic vegetation models for peatland ecosystems.

Monitoring vegetation phenology is critical for quantifying climate change impacts on ecosystems. We present an extensive dataset of 1783 site-years of phenological data derived from PhenoCam network imagery from 393 digital cameras, situated from tropics to tundra across a wide range of plant functional types, biomes, and climates. Most cameras are located in North America. Every half hour, cameras upload images to the PhenoCam server. Images are displayed in near-real time and provisional data products, including timeseries of the Green Chromatic Coordinate (Gcc), are made publicly available through the project web page (https://phenocam.sr.unh.edu/webcam/gallery/). Processing is conducted separately for each plant functional type in the camera field of view. The PhenoCam Dataset v2.0, described here, has been fully processed and curated, including outlier detection and expert inspection, to ensure high quality data. This dataset can be used to validate satellite data products, to evaluate predictions of land surface models, to interpret the seasonality of ecosystem-scale CO2 and H2O flux data, and to study climate change impacts on the terrestrial biosphere., Measurement(s)plant phenological trait • plant greennessTechnology Type(s)digital cameraSample Characteristic - OrganismEmbryophytaSample Characteristic - Environmentterrestrial biomeSample Characteristic - LocationEarth (planet) Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.9913694