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Stordalen Mire is a peatland in the discontinuous permafrost zone in arctic Sweden that exhibits a habitat gradient from permafrost palsa, to Sphagnum bog underlain by permafrost, to Eriophorum‐dominated fully thawed fen. We used three independent approaches to evaluate the annual, multi‐decadal, and millennial apparent carbon accumulation rates (aCAR) across this gradient: seven years of direct semi‐continuous measurement of CO2 and CH4 exchange, and 21 core profiles for 210Pb and 14C peat dating. Year‐round chamber measurements indicated net carbon balance of −13 ± 8, −49 ± 15, and −91 ± 43 g C m−2 y−1 for the years 2012–2018 in palsa, bog, and fen, respectively. Methane emission offset 2%, 7%, and 17% of the CO2 uptake rate across this gradient. Recent aCAR indicates higher C accumulation rates in surface peats in the palsa and bog compared to current CO2 fluxes, but these assessments are more similar in the fen. aCAR increased from low millennial‐scale levels (17–29 g C m−2 y−1) to moderate aCAR of the past century (72–81 g C m−2 y−1) to higher recent aCAR of 90–147 g C m−2 y−1. Recent permafrost collapse, greater inundation and vegetation response has made the landscape a stronger CO2 sink, but this CO2 sink is increasingly offset by rising CH4 emissions, dominated by modern carbon as determined by 14C. The higher CH4 emissions result in higher net CO2‐equivalent emissions, indicating that radiative forcing of this mire and similar permafrost ecosystems will exert a warming influence on future climate. Key Points: Stordalen Mire, a permafrost peatland, has become a stronger carbon sink due to shifts in vegetation and inundation accompanying thawThis stronger carbon sink is offset by an increase in methane emission, resulting in higher net CO2‐equivalent emissionsAnalysis of respiration products indicates that methane emission from the fen and bog are dominated by modern carbon [ABSTRACT FROM AUTHOR]

Amazonia contains a vast expanse of contiguous tropical forest and is influential in global carbon and hydrological cycles. Whether ancient Amazonia was highly disturbed or modestly impacted, and how ancient disturbances have shaped current forest ecosystem processes, is still under debate. Amazonian Dark Earths (ADEs), which are anthropic soil types with enriched nutrient levels, are one of the primary lines of evidence for ancient human presence and landscape modifications in settings that mostly lack stone structures and which are today covered by vegetation. We assessed the potential of using moderate spatial resolution optical satellite imagery to predict ADEs across the Amazon Basin. Maximum entropy modeling was used to develop a predictive model using locations of ADEs across the basin and satellite-derived remotely sensed indices. Amazonian Dark Earth sites were predicted to be primarily along the main rivers and in eastern Amazonia. Amazonian Dark Earth sites, when compared with randomly selected forested sites located within 50 km of ADE sites, were less green canopies (lower normalized difference vegetation index) and had lower canopy water content. This difference was accentuated in two drought years, 2005 and 2010. This is contrary to our expectation that ADE sites would have nutrient-rich soils that support trees with greener canopies and forests on ADE soils being more resilient to drought. Biomass and tree height were lower on ADE sites in comparison with randomly selected adjacent sites. Our results suggested that ADE-related ancient human impact on the forest is measurable across the entirety of the 6 million km2 of Amazon Basin using remotely sensed data. [ABSTRACT FROM AUTHOR]

Northern peatlands in permafrost regions contain a large amount of organic carbon (C) in the soil. Climate warming and associated permafrost degradation are expected to have significant impacts on the C balance of these ecosystems, but the magnitude is uncertain. We incorporated a permafrost model, Northern Ecosystem Soil Temperature (NEST), into abiogeochemical model, DeNitrification-DeComposition (DNDC), to model C dynamics in high-latitude peatland ecosystems. The enhanced model was applied to assess effects of permafrost thaw on C fluxes of a subarctic peatland at Stordalen, Sweden. DNDC simulated soil freeze-thaw dynamics, net ecosystem exchange of CO2 (NEE), and CH4 fluxes across three typical land cover types, which represent a gradient in the process of ongoing permafrost thaw at Stordalen. Model results were compared with multiyear field measurements, and the validation indicates that DNDC was able to simulate observed differences in seasonal soil thaw, NEE, and CH4 fluxes across the three land cover types. Consistent with the results from field studies, the modeled C fluxes across the permafrost thaw gradient demonstrate that permafrost thaw and the associated changes in soil hydrology and vegetation not only increase net uptake of C from the atmosphere but also increase the annual to decadal radiative forcing impacts on climate due to increased CH4 emissions. This study indicates the potential of utilizing biogeochemical models, such as DNDC, to predict the soil thermal regime in permafrost areas and to investigate impacts of permafrost thaw on ecosystem C fluxes after incorporating a permafrost component into the model framework. [ABSTRACT FROM AUTHOR]

Controls on the fate of ~277 Pg of soil organic carbon (C) stored in permafrost peatland soils remain poorly understood despite the potential for a significant positive feedback to climate change. Our objective was to quantify the temperature, moisture, organic matter, and microbial controls on soil organic carbon (SOC) losses following permafrost thaw in peat soils across Alaska. We compared the carbon dioxide (CO2) and methane (CH4) emissions from peat samples collected at active layer and permafrost depths when incubated aerobically and anaerobically at −5, −0.5, +4, and +20 °C. Temperature had a strong, positive effect on C emissions; global warming potential (GWP) was >3× larger at 20 °C than at 4 °C. Anaerobic conditions significantly reduced CO2 emissions and GWP by 47% at 20 °C but did not have a significant effect at −0.5 °C. Net anaerobic CH4 production over 30 days was 7.1 ± 2.8 μg CH4-C gC−1 at 20 °C. Cumulative CO2 emissions were related to organic matter chemistry and best predicted by the relative abundance of polysaccharides and proteins ( R2 = 0.81) in SOC. Carbon emissions (CO2-C + CH4-C) from the active layer depth peat ranged from 77% larger to not significantly different than permafrost depths and varied depending on the peat type and peat decomposition stage rather than thermal state. Potential SOC losses with warming depend not only on the magnitude of temperature increase and hydrology but also organic matter quality, permafrost history, and vegetation dynamics, which will ultimately determine net radiative forcing due to permafrost thaw. [ABSTRACT FROM AUTHOR]

Boreal and arctic regions are predicted to warm faster and more strongly than temperate latitudes. Peatlands in these regions contain large stocks of soil carbon in frozen soil and these may effect a strong positive feedback on climate change. We modelled the predicted effects of climate change and wildfire on permafrost in organic soils using a peatland-specific soil thermal model to simulate soil temperatures. We evaluated the model at a lowland black spruce site in Alaska and a sedge-dominated Canadian arctic fen. We estimated the response of soil temperatures and the active layer thickness (AcLTh) under several climate change scenarios. With surface soil temperatures increased by 4.4 °C-5.4 °C, soil temperatures at 100 cm depth increased by 3.6 °C-4.3 °C, the AcLTh increased by 12-30 cm, the zone of partially thawed soil increased, and the number of thaw days increased by 17-26 %. Wildfire caused AcLTh to increase by 26-48 % in the year following fire; AcLTh differences in 2091-2100 were significant (8 cm) at one site. By 2100, climate change effects on AcLTh were larger than wildfire effects suggesting that persistent temperature increases will have a more substantial effect on permafrost than the transient effects of disturbance. [ABSTRACT FROM AUTHOR]

Contents [ABSTRACT FROM AUTHOR]

We analyzed the 10-year record (1999-2009) of SeaWinds Ku-band microwave backscatter from humid tropical forest regions in South America, Africa, and Indonesia/Malaysia. While backscatter was relatively stable across much of the region, it declined by 1-2 dB in areas of known large-scale deforestation, and increased by up to 1-2 dB in areas of secondary forest or plantation forest growth and in major metropolitan areas. The reduction in backscatter over 142 18.5 km × 18.5 km blocks of tropical forest was correlated with gross forest cover loss (as determined from Landsat data analysis) (R = -0.78); this correlation improved when restricted to humid tropical forest blocks in South America with high initial forest cover (R = -0.93, n = 22). This study shows that scatterometer-based analyses can provide an important geophysical data record leading to robust identification of the spatial patterns and timing of large-scale change in tropical forests. The coarse spatial resolution of SeaWinds ( ~ 10 km) makes it unsuitable for mapping deforestation at the scale of land-use activity. However, due to a combination of instrument stability, sensitivity to canopy change and insensitivity to atmospheric effects, and straight-forward data processing, Ku-band scatterometery can provide a fully independent assessment of large-scale tropical forest canopy dynamics which may complement the interpretation of higher resolution optical remote sensing. [ABSTRACT FROM AUTHOR]

The article explores climate sensitivity in the Anthropocene to avoid dangerous anthropogenic interference with the climate system. It discusses climate sensitivity which depends on climate feedbacks' sign and strength. It defines climate feedback which is induced by a climate forcing. It also discusses related topics including Earth's energy balance, feedback sensitivity, and carbon cycle feedbacks.

The article discusses a study on the role and implications of peat carbon in thawing permafrost soils in North America in response to global warming. It mentions that Northern peatlands comprise a large terrestrial carbon pool which plays a significant role in the carbon cycle. It also notes that most of it is in permafrost and is biogeochemically inert that will change with increased temperatures of soils caused by climate warming in the 21st century.

The article presents a study on the Holocene Peat Model (HPM), a simulation model designed to determine peat accumulation tested at a temperate bog in Ontario. It states that the HPM was made and evaluated considering factors such as hydrology, peat properties and the nature of plant communities. It adds that peat decomposition and dynamic peat accumulation models were combined in HPM. Moreover, it asserts that the HPM is capable of demonstrating balances in peatland carbon and watecycles.

We applied an inverse model to simulate global carbon (C) cycle dynamics during the Holocene period using atmospheric carbon dioxide (CO2) concentrations reconstructed from Antarctic ice cores and prescribed C accumulation rates of Northern Peatlands (NP) as inputs. Previous studies indicated that different sources could contribute to the 20 parts per million by volume (ppmv) atmospheric CO2 increase over the past 8000 years. These sources of C include terrestrial release of 40-200 petagram C (PgC, 1 petagram=1015 gram), deep oceanic adjustment to a 500 PgC terrestrial biomass buildup early in this interglacial period, and anthropogenic land-use and land-cover changes of unknown magnitudes. Our study shows that the prescribed peatland C accumulation significantly modifies our previous understanding of Holocene C cycle dynamics. If the buildup of the NP is considered, the terrestrial pool becomes the C sink of about 160-280 PgC over the past 8000 years, and the only C source for the terrestrial and atmospheric C increases is presumably from the deep ocean due to calcium carbonate compensation. Future studies need to be conducted to constrain the basal times and growth rates of the NP C accumulation in the Holocene. These research endeavors are challenging because they need a dynamically-coupled peatland simulator to be constrained with the initiation time and reconstructed C reservoir of the NP. Our results also suggest that the huge reservoir of deep ocean C explains the major variability of the glacial-interglacial C cycle dynamics without considering the anthropogenic C perturbation. [ABSTRACT FROM AUTHOR]

The availability of nitrogen represents a key constraint on carbon cycling in terrestrial ecosystems, and it is largely in this capacity that the role of N in the Earth's climate system has been considered. Despite this, few studies have included continuous variation in plant N status as a driver of broad-scale carbon cycle analyses. This is partly because of uncertainties in how leaf-level physiological relationships scale to whole ecosystems and because methods for regional to continental detection of plant N concentrations have yet to be developed. Here, we show that ecosystem CO[sub2] uptake capacity in temperate and boreal forests scales directly with whole-canopy N concentrations, mirroring a leaf-level trend that has been observed for woody plants worldwide. We further show that both CO[sub2] uptake capacity and canopy N concentration are strongly and positively correlated with shortwave surface albedo. These results suggest that N plays an additional, and overlooked, role in the climate system via its influence on vegetation reflectivity and shortwave surface energy exchange. We also demonstrate that much of the spatial variation in canopy N can be detected by using broad-band satellite sensors, offering a means through which these findings can be applied toward improved application of coupled carbon cycle-climate models. [ABSTRACT FROM AUTHOR]

We developed the McGill Wetland Model (MWM) based on the general structure of the Peatland Carbon Simulator (PCARS) and the Canadian Terrestrial Ecosystem Model. Three major changes were made to PCARS: the light use efficiency model of photosynthesis was replaced with a biogeochemical description of photosynthesis; 2. the description of autotrophic respiration was changed to be consistent with the formulation of photosynthesis; and 3. the cohort, multilayer soil respiration model was changed to a simple one box peat decomposition model divided into an oxic and anoxic zones by an effective water table, and a one-year residence time litter pool. MWM was then evaluated by comparing its output to the estimates of net ecosystem production (NEP), gross primary production (GPP) and ecosystem respiration (ER) from years of continuous measurements at the Mer Bleue peatland, a raised ombrotrophic bog located in southern Ontario, Canada (index of agreement [dimensionless]: NEP=0.80, GPP=0.97, ER=0.97; systematic RMSE [g C m-2 d-1]: NEP=0.12, GPP=0.07, ER=0.14; unsystematic RMSE [g C m-2 d-1]: NEP=0.15, GPP=0.27, ER=0.23). Simulated moss NPP approximates what would be expected for a bog peatland, but shrub NPP appears to be underestimated. Sensitivity analysis revealed that the model output did not change greatly due to variations in water table because of offsetting responses in production and respiration, but that even modest temperature increases could lead to converting the bog from a sink to a source of CO2. General weaknesses and further developments of MWM are discussed. [ABSTRACT FROM AUTHOR]

To accurately assess the impacts of human land use on the Earth system, information is needed on the current and historical patterns of land-use activities. Previous global studies have focused on developing reconstructions of the spatial patterns of agriculture. Here, we provide the first global gridded estimates of the underlying land conversions (land-use transitions), wood harvesting, and resulting secondary lands annually, for the period 1700–2000. Using data-based historical cases, our results suggest that 42–68% of the land surface was impacted by land-use activities (crop, pasture, wood harvest) during this period, some multiple times. Secondary land area increased 10–44 × 106 km2; about half of this was forested. Wood harvest and shifting cultivation generated 70–90% of the secondary land by 2000; permanent abandonment and relocation of agricultural land accounted for the rest. This study provides important new estimates of globally gridded land-use activities for studies attempting to assess the consequences of anthropogenic changes to the Earth's surface over time. [ABSTRACT FROM AUTHOR]

Two Thematic Mapper (TM) scenes were used to analyse the amount and pattern of land cover change in China's Pearl River delta. From 1988 to 1996 net cropland area decreased by 13.5%, net vegetated land cover decreased by 11.5%, and built-up land increased by over 272%. A perimeter/area (P/A) ratio analysis was performed on the size and shape of the cropland parcels that were lost between 1988-1996. Cropland was lost primarily due to conversion to vegetated (forest, orchard, etc.) or built-up land. The changes from cropland to vegetated land had a large percentage of area changed in smaller clumps with high P/A ratios, indicating potential linear changes that could be attributed to misregistration. The changes to built-up land cover had a large percentage of area changed in larger clumps with smaller P/A ratios. The P/A ratio appears to be an easily derived method for determining potential areas of linear 'false change' caused by misregistration in change detection analyses. [ABSTRACT FROM AUTHOR]

In this landscape-scale study we explored the potential for multitemporal 10-day composite data from the Vegetation sensor to characterize land cover types, in combination with Landsat TM image and agricultural census data. The study area (175 km by 165 km) is located in eastern Jiangsu Province, China. The Normalized Difference Vegetation Index (NDVI ) and the Normalized Difference Water Index (NDWI ) were calculated for seven 10-day composite (VGT-S10) data from 11 March to 20 May 1999. Multi-temporal NDVI and NDWI were visually examined and used for unsupervised classification. The resultant VGT classification map at 1 km resolution was compared to the TM classification map derived from unsupervised classification of a Landsat 5 TM image acquired on 26 April 1996 at 30 m resolution to quantify percent fraction of cropland within a 1 km VGT pixel; resulting in a mean of 60% for pixels classified as cropland, and 47% for pixels classified as cropland/natural vegetation mosaic. The estimates of cropland area from VGT data and TM image were also aggregated to county-level, using an administrative county map, and then compared to the 1995 county-level agricultural census data. This landscape-scale analysis incorporated image classification (e.g. coarse-resolution VGT data, fineresolution TM data), statistical census data (e.g. county-level agricultural census data) and a geographical information system (e.g. an administrative county map), and demonstrated the potential of multi-temporal VGT data for mapping of croplands across various spatial scales from landscape to region. This analysis also illustrated some of the limitations of per-pixel classification at the 1 km resolution for a heterogeneous landscape. [ABSTRACT FROM AUTHOR]

In an effort to develop the quantitative relationships between fieldmeasured leaf area index (LAI ) and VEGETATION-derived vegetation indices for paddy rice fields, we have measured LAI of paddy rice fields at 10-day intervals at five sampling sites in Jiangning County, Jiangsu Province of China during the rice growing season (July to October) of 1999, using a LI-COR LAI-2000 plant canopy analyser. Twenty-seven 10-day VEGETATION (VGT) synthesis products (VGT-S10) from 1-10 March to 21-30 November 1999 were acquired. Normalized difference vegetation index (NDVI) values were calculated for the VGT-S10 products, using ground surface reflectance values of VGT spectral bands (B3-near-infrared; B2-red). After rice transplanting in mid to late June, LAI increased rapidly and reached its plateau by early to mid August. There were similar temporal dynamics of NDVI and LAI among the five sampling sites over the growing season of paddy rice in 1999. Simple linear regression analyses indicate that there are statistically significant linear relationships between NDVI and LAI data over the growing season of paddy rice in 1999. [ABSTRACT FROM AUTHOR]

A unique physical feature of paddy rice fields is that rice is grown on flooded soil. During the period of flooding and rice transplanting, there is a large proportion of surface water in a land surface consisting of water, vegetation and soils. The VEGETATION (VGT) sensor has four spectral bands that are equivalent to spectral bands of Landsat TM, and its mid-infrared spectral band is very sensitive to soil moisture and plant canopy water content. In this study we evaluated a VGT-derived normalized difference water index (NDWI[sub VGT]=(B3-MIR)/ (B3+MIR)) for describing temporal and spatial dynamics of surface moisture. Twenty-seven 10-day composites (VGT- S10) from 1 March to 30 November 1999 were acquired and analysed for a study area (175 km by 165 km) in eastern Jiangsu Province, China, where a winter wheat and paddy rice double cropping system dominates the landscape. We compared the temporal dynamics and spatial patterns of normalized difference vegetation index (NDVI[sub VGT]) and NDWI[sub VGT]. The NDWI[sub VGT] temporal dynamics were sensitive enough to capture the substantial increases of surface water due to flooding and rice transplanting at paddy rice fields. A land use thematic map for the timing and location of flooding and rice transplanting was generated for the study area. Our results indicate that NDWI and NDVI temporal anomalies may provide a simple and effective tool for detection of flooding and rice transplanting across the landscape. [ABSTRACT FROM AUTHOR]

Organismic and Evolutionary Biology

Climate sensitivity in its most basic form is defined as the equilibrium change in global surface temperature that occurs in response to a climate forcing, or externally imposed perturbation of the planetary energy balance. Within this general definition, several specific forms of climate sensitivity exist that differ in terms of the types of climate feedbacks they include. Based on evidence from Earth's history, we suggest here that the relevant form of climate sensitivity in the Anthropocene (e.g. from which to base future greenhouse gas (GHG) stabilization targets) is the Earth system sensitivity including fast feedbacks from changes in water vapour, natural aerosols, clouds and sea ice, slower surface albedo feedbacks from changes in continental ice sheets and vegetation, and climate-GHG feedbacks from changes in natural (land and ocean) carbon sinks. Traditionally, only fast feedbacks have been considered (with the other feedbacks either ignored or treated as forcing), which has led to estimates of the climate sensitivity for doubled CO 2 concentrations of about 3 °C. The 2×CO2 Earth system sensitivity is higher than this, being ∼4-6°C if the ice sheet/vegetation albedo feedback is included in addition to the fast feedbacks, and higher still if climate-GHG feedbacks are also included. The inclusion of climate-GHG feedbacks due to changes in the natural carbon sinks has the advantage of more directly linking anthropogenic GHG emissions with the ensuing global temperature increase, thus providing a truer indication of the climate sensitivity to human perturbations. The Earth system climate sensitivity is difficult to quantify due to the lack of palaeo-analogues for the present-day anthropogenic forcing, and the fact that ice sheet and climate-GHG feedbacks have yet to become globally significant in the Anthropocene. Furthermore, current models are unable to adequately simulate the physics of ice sheet decay and certain aspects of the natural carbon and nitrogen cycles. Obtaining quantitative estimates of the Earth system sensitivity is therefore a high priority for future work. [ABSTRACT FROM AUTHOR]