Grassland gross carbon dioxide uptake based on an improved model tree ensemble approach considering human interventions: global estimation and covariation with climate

Grassland ecosystems act as a crucial role in the global carbon cycle and provide vital ecosystem services for many species. However, these low‐productivity and water‐limited ecosystems are sensitive and vulnerable to climate perturbations and human intervention, the latter of which is often not considered due to lack of spatial information regarding the grassland management. Here by the application of a model tree ensemble (MTE‐GRASS) trained on local eddy covariance data and using as predictors gridded climate and management intensity field (grazing and cutting), we first provide an estimate of global grassland gross primary production (GPP). GPP from our study compares well (modeling efficiency NSE = 0.85 spatial; NSE between 0.69 and 0.94 interannual) with that from flux measurement. Global grassland GPP was on average 11 ± 0.31 Pg C yr^?1 and exhibited significantly increasing trend at both annual and seasonal scales, with an annual increase of 0.023 Pg C (0.2%) from 1982 to 2011. Meanwhile, we found that at both annual and seasonal scale, the trend (except for northern summer) and interannual variability of the GPP are primarily driven by arid/semiarid ecosystems, the latter of which is due to the larger variation in precipitation. Grasslands in arid/semiarid regions have a stronger (33 g C m^?2 yr^?1/100 mm) and faster (0‐ to 1‐month time lag) response to precipitation than those in other regions. Although globally spatial gradients (71%) and interannual changes (51%) in GPP were mainly driven by precipitation, where most regions with arid/semiarid climate zone, temperature and radiation together shared half of GPP variability, which is mainly distributed in the high‐latitude or cold regions. Our findings and the results of other studies suggest the overwhelming importance of arid/semiarid regions as a control on grassland ecosystems carbon cycle. Similarly, under the projected future climate change, grassland ecosystems in these regions will be potentially greatly influenced.     

Evaluation of terrestrial carbon cycle models for their response to climate variability and to CO2 trends

The purpose of this study was to evaluate 10 process‐based terrestrial biosphere models that were used for the IPCC fifth Assessment Report. The simulated gross primary productivity (GPP) is compared with flux‐tower‐based estimates by Jung et al. [Journal of Geophysical Research 116 (2011) G00J07] (JU11). The net primary productivity (NPP) apparent sensitivity to climate variability and atmospheric CO₂ trends is diagnosed from each model output, using statistical functions. The temperature sensitivity is compared against ecosystem field warming experiments results. The CO₂ sensitivity of NPP is compared to the results from four Free‐Air CO₂ Enrichment (FACE) experiments. The simulated global net biome productivity (NBP) is compared with the residual land sink (RLS) of the global carbon budget from Friedlingstein et al. [Nature Geoscience 3 (2010) 811] (FR10). We found that models produce a higher GPP (133 ± 15 Pg C yr^?1) than JU11 (118 ± 6 Pg C yr^?1). In response to rising atmospheric CO₂ concentration, modeled NPP increases on average by 16% (5–20%) per 100 ppm, a slightly larger apparent sensitivity of NPP to CO₂ than that measured at the FACE experiment locations (13% per 100 ppm). Global NBP differs markedly among individual models, although the mean value of 2.0 ± 0.8 Pg C yr^?1 is remarkably close to the mean value of RLS (2.1 ± 1.2 Pg C yr^?1). The interannual variability in modeled NBP is significantly correlated with that of RLS for the period 1980–2009. Both model‐to‐model and interannual variation in model GPP is larger than that in model NBP due to the strong coupling causing a positive correlation between ecosystem respiration and GPP in the model. The average linear regression slope of global NBP vs. temperature across the 10 models is ?3.0 ± 1.5 Pg C yr^?1 °C^?1, within the uncertainty of what derived from RLS (?3.9 ± 1.1 Pg C yr^?1 °C^?1). However, 9 of 10 models overestimate the regression slope of NBP vs. precipitation, compared with the slope of the observed RLS vs. precipitation. With most models lacking processes that control GPP and NBP in addition to CO₂ and climate, the agreement between modeled and observation‐based GPP and NBP can be fortuitous. Carbon–nitrogen interactions (only separable in one model) significantly influence the simulated response of carbon cycle to temperature and atmospheric CO₂ concentration, suggesting that nutrients limitations should be included in the next generation of terrestrial biosphere models.     

Modeling the spatial and temporal heterogeneity of deforestation‐driven carbon emissions: the INPE‐EM framework applied to the Brazilian Amazon

We present a generic spatially explicit modeling framework to estimate carbon emissions from deforestation (INPE‐EM). The framework incorporates the temporal dynamics related to the deforestation process and accounts for the biophysical and socioeconomic heterogeneity of the region under study. We build an emission model for the Brazilian Amazon combining annual maps of new clearings, four maps of biomass, and a set of alternative parameters based on the recent literature. The most important results are as follows: (a) Using different biomass maps leads to large differences in estimates of emission; for the entire region of the Brazilian Amazon in the last decade, emission estimates of primary forest deforestation range from 0.21 to 0.26 Pg C yr^?1. (b) Secondary vegetation growth presents a small impact on emission balance because of the short duration of secondary vegetation. In average, the balance is only 5% smaller than the primary forest deforestation emissions. (c) Deforestation rates decreased significantly in the Brazilian Amazon in recent years, from 27 Mkm² in 2004 to 7 Mkm² in 2010. INPE‐EM process‐based estimates reflect this decrease even though the agricultural frontier is moving to areas of higher biomass. The decrease is slower than a non‐process instantaneous model would estimate as it considers residual emissions (slash, wood products, and secondary vegetation). The average balance, considering all biomass, decreases from 0.28 in 2004 to 0.15 Pg C yr^?1 in 2009; the non‐process model estimates a decrease from 0.33 to 0.10 Pg C yr^?1. We conclude that the INPE‐EM is a powerful tool for representing deforestation‐driven carbon emissions. Biomass estimates are still the largest source of uncertainty in the effective use of this type of model for informing mechanisms such as REDD+. The results also indicate that efforts to reduce emissions should focus not only on controlling primary forest deforestation but also on creating incentives for the restoration of secondary forests.     

Change in terrestrial ecosystem water‐use efficiency over the last three decades

Defined as the ratio between gross primary productivity (GPP) and evapotranspiration (ET), ecosystem‐scale water‐use efficiency (EWUE) is an indicator of the adjustment of vegetation photosynthesis to water loss. The processes controlling EWUE are complex and reflect both a slow evolution of plants and plant communities as well as fast adjustments of ecosystem functioning to changes of limiting resources. In this study, we investigated EWUE trends from 1982 to 2008 using data‐driven models derived from satellite observations and process‐oriented carbon cycle models. Our findings suggest positive EWUE trends of 0.0056, 0.0007 and 0.0001 g C m^?2 mm^?1 yr^?1 under the single effect of rising CO₂ (‘CO₂’), climate change (‘CLIM’) and nitrogen deposition (‘NDEP’), respectively. Global patterns of EWUE trends under different scenarios suggest that (i) EWUE‐CO₂ shows global increases, (ii) EWUE‐CLIM increases in mainly high latitudes and decreases at middle and low latitudes, (iii) EWUE‐NDEP displays slight increasing trends except in west Siberia, eastern Europe, parts of North America and central Amazonia. The data‐driven MTE model, however, shows a slight decline of EWUE during the same period (?0.0005 g C m^?2 mm^?1 yr^?1), which differs from process‐model (0.0064 g C m^?2 mm^?1 yr^?1) simulations with all drivers taken into account. We attribute this discrepancy to the fact that the nonmodeled physiological effects of elevated CO₂ reducing stomatal conductance and transpiration (TR) in the MTE model. Partial correlation analysis between EWUE and climate drivers shows similar responses to climatic variables with the data‐driven model and the process‐oriented models across different ecosystems. Change in water‐use efficiency defined from transpiration‐based WUE_t (GPP/TR) and inherent water‐use efficiency (IWUE_t, GPP×VPD/TR) in response to rising CO₂, climate change, and nitrogen deposition are also discussed. Our analyses will facilitate mechanistic understanding of the carbon–water interactions over terrestrial ecosystems under global change.     

Carbon accumulation of tropical peatlands over millennia: a modeling approach

Tropical peatlands cover an estimated 440 000 km² (~10% of global peatland area) and are significant in the global carbon cycle by storing about 40–90 Gt C in peat. Over the past several decades, tropical peatlands have experienced high rates of deforestation and conversion, which is often associated with lowering the water table and peat burning, releasing large amounts of carbon stored in peat to the atmosphere. We present the first model of long‐term carbon accumulation in tropical peatlands by modifying the Holocene Peat Model (HPM), which has been successfully applied to northern temperate peatlands. Tropical HPM (HPMTrop) is a one‐dimensional, nonlinear, dynamic model with a monthly time step that simulates peat mass remaining in annual peat cohorts over millennia as a balance between monthly vegetation inputs (litter) and monthly decomposition. Key model parameters were based on published data on vegetation characteristics, including net primary production partitioned into leaves, wood, and roots; and initial litter decomposition rates. HPMTrop outputs are generally consistent with field observations from Indonesia. Simulated long‐term carbon accumulation rates for 11 000‐year‐old inland, and 5 000‐year‐old coastal peatlands were about 0.3 and 0.59 Mg C ha^?1 yr^?1, and the resulting peat carbon stocks at the end of the 11 000‐year and 5 000‐year simulations were 3300 and 2900 Mg C ha^?1, respectively. The simulated carbon loss caused by coastal peat swamp forest conversion into oil palm plantation with periodic burning was 1400 Mg C ha^?1 over 100 years, which is equivalent to ~2900 years of C accumulation in a hectare of coastal peatlands.     

Terrestrial biosphere models need better representation of vegetation phenology: results from the North American Carbon Program Site Synthesis

Phenology, by controlling the seasonal activity of vegetation on the land surface, plays a fundamental role in regulating photosynthesis and other ecosystem processes, as well as competitive interactions and feedbacks to the climate system. We conducted an analysis to evaluate the representation of phenology, and the associated seasonality of ecosystem‐scale CO₂ exchange, in 14 models participating in the North American Carbon Program Site Synthesis. Model predictions were evaluated using long‐term measurements (emphasizing the period 2000–2006) from 10 forested sites within the AmeriFlux and Fluxnet‐Canada networks. In deciduous forests, almost all models consistently predicted that the growing season started earlier, and ended later, than was actually observed; biases of 2 weeks or more were typical. For these sites, most models were also unable to explain more than a small fraction of the observed interannual variability in phenological transition dates. Finally, for deciduous forests, misrepresentation of the seasonal cycle resulted in over‐prediction of gross ecosystem photosynthesis by +160 ± 145 g C m^?2 yr^?1 during the spring transition period and +75 ± 130 g C m^?2 yr^?1 during the autumn transition period (13% and 8% annual productivity, respectively) compensating for the tendency of most models to under‐predict the magnitude of peak summertime photosynthetic rates. Models did a better job of predicting the seasonality of CO₂ exchange for evergreen forests. These results highlight the need for improved understanding of the environmental controls on vegetation phenology and incorporation of this knowledge into better phenological models. Existing models are unlikely to predict future responses of phenology to climate change accurately and therefore will misrepresent the seasonality and interannual variability of key biosphere–atmosphere feedbacks and interactions in coupled global climate models.     

Climate‐driven uncertainties in modeling terrestrial gross primary production: a site level to global‐scale analysis

We used a land surface model to quantify the causes and extents of biases in terrestrial gross primary production (GPP) due to the use of meteorological reanalysis datasets. We first calibrated the model using meteorology and eddy covariance data from 25 flux tower sites ranging from the tropics to the northern high latitudes and subsequently repeated the site simulations using two reanalysis datasets: NCEP/NCAR and CRUNCEP. The results show that at most sites, the reanalysis‐driven GPP bias was significantly positive with respect to the observed meteorology‐driven simulations. Notably, the absolute GPP bias was highest at the tropical evergreen tree sites, averaging up to ca. 0.45 kg C m^?2 yr^?1 across sites (ca. 15% of site level GPP). At the northern mid‐/high‐latitude broadleaf deciduous and the needleleaf evergreen tree sites, the corresponding annual GPP biases were up to 20%. For the nontree sites, average annual biases of up to ca. 20–30% were simulated within savanna, grassland, and shrubland vegetation types. At the tree sites, the biases in short‐wave radiation and humidity strongly influenced the GPP biases, while the nontree sites were more affected by biases in factors controlling water stress (precipitation, humidity, and air temperature). In this study, we also discuss the influence of seasonal patterns of meteorological biases on GPP. Finally, using model simulations for the global land surface, we discuss the potential impacts of site‐level reanalysis‐driven biases on the global estimates of GPP. In a broader context, our results can have important consequences on other terrestrial ecosystem fluxes (e.g., net primary production, net ecosystem production, energy/water fluxes) and reservoirs (e.g., soil carbon stocks). In a complementary study (Barman et al., 2013 ), we extend the present analysis for latent and sensible heat fluxes, thus consistently integrating the analysis of climate‐driven uncertainties in carbon, energy, and water fluxes using a single modeling framework.     

Global forest carbon uptake due to nitrogen and phosphorus deposition from 1850 to 2100

Spatial patterns and temporal trends of nitrogen (N) and phosphorus (P) deposition are important for quantifying their impact on forest carbon (C) uptake. In a first step, we modeled historical and future change in the global distributions of the atmospheric deposition of N and P from the dry and wet deposition of aerosols and gases containing N and P. Future projections were compared between two scenarios with contrasting aerosol emissions. Modeled fields of N and P deposition and P concentration were evaluated using globally distributed in situ measurements. N deposition peaked around 1990 in European forests and around 2010 in East Asian forests, and both increased sevenfold relative to 1850. P deposition peaked around 2010 in South Asian forests and increased 3.5‐fold relative to 1850. In a second step, we estimated the change in C storage in forests due to the fertilization by deposited N and P (?C_{ν dep}), based on the retention of deposited nutrients, their allocation within plants, and C:N and C:P stoichiometry. ?C_{ν dep} for 1997–2013 was estimated to be 0.27 ± 0.13 Pg C year^?1 from N and 0.054 ± 0.10 Pg C year^?1 from P, contributing 9% and 2% of the terrestrial C sink, respectively. Sensitivity tests show that uncertainty of ?C_{ν dep} was larger from P than from N, mainly due to uncertainty in the fraction of deposited P that is fixed by soil. ?C_{P dep} was exceeded by ?C_{N dep} over 1960–2007 in a large area of East Asian and West European forests due to a faster growth in N deposition than P. Our results suggest a significant contribution of anthropogenic P deposition to C storage, and additional sources of N are needed to support C storage by P in some Asian tropical forests where the deposition rate increased even faster for P than for N.     

Importance of disturbance history on net primary productivity in the world's most productive forests and implications for the global carbon cycle

Analysis of growth and biomass turnover in natural forests of Eucalyptus regnans, the world's tallest angiosperm, reveals it is also the world's most productive forest type, with fire disturbance an important mediator of net primary productivity (NPP). A comprehensive empirical database was used to calculate the averaged temporal pattern of NPP from regeneration to 250 years age. NPP peaks at 23.1 ± 3.8 (95% interquantile range) Mg C ha^?1 year^?1 at age 14 years, and declines gradually to about 9.2 ± 0.8 Mg C ha^?1 year^?1 at 130 years, with an average NPP over 250 years of 11.4 ± 1.1 Mg C ha^?1 year^?1, a value similar to the most productive temperate and tropical forests around the world. We then applied the age‐class distribution of E. regnans resulting from relatively recent historical fires to estimate current NPP for the forest estate. Values of NPP were 40% higher (13 Mg C ha^?1 year^?1) than if forests were assumed to be at maturity (9.2 Mg C ha^?1 year^?1). The empirically derived NPP time series for the E. regnans estate was then compared against predictions from 21 global circulation models, showing that none of them had the capacity to simulate a post‐disturbance peak in NPP, as found in E. regnans. The potential importance of disturbance impacts on NPP was further tested by applying a similar approach to the temperate forests of conterminous United States and of China. Allowing for the effects of disturbance, NPP summed across both regions was on average 11% (or 194 Tg C/year) greater than if all forests were assumed to be in a mature state. The results illustrate the importance of accounting for past disturbance history and growth stage when estimating forest primary productivity, with implications for carbon balance modelling at local to global scales.     

Simulations of chlorophyll fluorescence incorporated into the Community Land Model version 4

Several studies have shown that satellite retrievals of solar‐induced chlorophyll fluorescence (SIF) provide useful information on terrestrial photosynthesis or gross primary production (GPP). Here, we have incorporated equations coupling SIF to photosynthesis in a land surface model, the National Center for Atmospheric Research Community Land Model version 4 (NCAR CLM4), and have demonstrated its use as a diagnostic tool for evaluating the calculation of photosynthesis, a key process in a land surface model that strongly influences the carbon, water, and energy cycles. By comparing forward simulations of SIF, essentially as a byproduct of photosynthesis, in CLM4 with observations of actual SIF, it is possible to check whether the model is accurately representing photosynthesis and the processes coupled to it. We provide some background on how SIF is coupled to photosynthesis, describe how SIF was incorporated into CLM4, and demonstrate that our simulated relationship between SIF and GPP values are reasonable when compared with satellite (Greenhouse gases Observing SATellite; GOSAT) and in situ flux‐tower measurements. CLM4 overestimates SIF in tropical forests, and we show that this error can be corrected by adjusting the maximum carboxylation rate (V_max) specified for tropical forests in CLM4. Our study confirms that SIF has the potential to improve photosynthesis simulation and thereby can play a critical role in improving land surface and carbon cycle models.     

A new seasonal‐deciduous spring phenology submodel in the Community Land Model 4.5: impacts on carbon and water cycling under future climate scenarios

A spring phenology model that combines photoperiod with accumulated heating and chilling to predict spring leaf‐out dates is optimized using PhenoCam observations and coupled into the Community Land Model (CLM) 4.5. In head‐to‐head comparison (using satellite data from 2003 to 2013 for validation) for model grid cells over the Northern Hemisphere deciduous broadleaf forests (5.5 million km²), we found that the revised model substantially outperformed the standard CLM seasonal‐deciduous spring phenology submodel at both coarse (0.9 × 1.25°) and fine (1 km) scales. The revised model also does a better job of representing recent (decadal) phenological trends observed globally by MODIS, as well as long‐term trends (1950–2014) in the PEP725 European phenology dataset. Moreover, forward model runs suggested a stronger advancement (up to 11 days) of spring leaf‐out by the end of the 21st century for the revised model. Trends toward earlier advancement are predicted for deciduous forests across the whole Northern Hemisphere boreal and temperate deciduous forest region for the revised model, whereas the standard model predicts earlier leaf‐out in colder regions, but later leaf‐out in warmer regions, and no trend globally. The earlier spring leaf‐out predicted by the revised model resulted in enhanced gross primary production (up to 0.6 Pg C yr^?1) and evapotranspiration (up to 24 mm yr^?1) when results were integrated across the study region. These results suggest that the standard seasonal‐deciduous submodel in CLM should be reconsidered, otherwise substantial errors in predictions of key land–atmosphere interactions and feedbacks may result.     

Soil carbon sequestration due to post‐Soviet cropland abandonment: estimates from a large‐scale soil organic carbon field inventory

The break‐up of the Soviet Union in 1991 triggered cropland abandonment on a continental scale, which in turn led to carbon accumulation on abandoned land across Eurasia. Previous studies have estimated carbon accumulation rates across Russia based on large‐scale modelling. Studies that assess carbon sequestration on abandoned land based on robust field sampling are rare. We investigated soil organic carbon (SOC) stocks using a randomized sampling design along a climatic gradient from forest steppe to Sub‐Taiga in Western Siberia (Tyumen Province). In total, SOC contents were sampled on 470 plots across different soil and land‐use types. The effect of land use on changes in SOC stock was evaluated, and carbon sequestration rates were calculated for different age stages of abandoned cropland. While land‐use type had an effect on carbon accumulation in the topsoil (0–5 cm), no independent land‐use effects were found for deeper SOC stocks. Topsoil carbon stocks of grasslands and forests were significantly higher than those of soils managed for crops and under abandoned cropland. SOC increased significantly with time since abandonment. The average carbon sequestration rate for soils of abandoned cropland was 0.66 Mg C ha^?1 yr^?1 (1–20 years old, 0–5 cm soil depth), which is at the lower end of published estimates for Russia and Siberia. There was a tendency towards SOC saturation on abandoned land as sequestration rates were much higher for recently abandoned (1–10 years old, 1.04 Mg C ha^?1 yr^?1) compared to earlier abandoned crop fields (11–20 years old, 0.26 Mg C ha^?1 yr^?1). Our study confirms the global significance of abandoned cropland in Russia for carbon sequestration. Our findings also suggest that robust regional surveys based on a large number of samples advance model‐based continent‐wide SOC prediction.     

Carbon pool densities and a first estimate of the total carbon pool in the Mongolian forest‐steppe

The boreal forest biome represents one of the most important terrestrial carbon stores, which gave reason to intensive research on carbon stock densities. However, such an analysis does not yet exist for the southernmost Eurosiberian boreal forests in Inner Asia. Most of these forests are located in the Mongolian forest‐steppe, which is largely dominated by Larix sibirica. We quantified the carbon stock density and total carbon pool of Mongolia's boreal forests and adjacent grasslands and draw conclusions on possible future change. Mean aboveground carbon stock density in the interior of L. sibirica forests was 66 Mg C ha^?1, which is in the upper range of values reported from boreal forests and probably due to the comparably long growing season. The density of soil organic carbon (SOC, 108 Mg C ha^?1) and total belowground carbon density (149 Mg C ha^?1) are at the lower end of the range known from boreal forests, which might be the result of higher soil temperatures and a thinner permafrost layer than in the central and northern boreal forest belt. Land use effects are especially relevant at forest edges, where mean carbon stock density was 188 Mg C ha^?1, compared with 215 Mg C ha^?1 in the forest interior. Carbon stock density in grasslands was 144 Mg C ha^?1. Analysis of satellite imagery of the highly fragmented forest area in the forest‐steppe zone showed that Mongolia's total boreal forest area is currently 73 818 km², and 22% of this area refers to forest edges (defined as the first 30 m from the edge). The total forest carbon pool of Mongolia was estimated at ~ 1.5?1.7 Pg C, a value which is likely to decrease in future with increasing deforestation and fire frequency, and global warming.     

Climatic variability,hydrologic anomaly,and methane emission can turn productive freshwater marshes into net carbon sources

Freshwater marshes are well‐known for their ecological functions in carbon sequestration, but complete carbon budgets that include both methane (CH₄) and lateral carbon fluxes for these ecosystems are rarely available. To the best of our knowledge, this is the first full carbon balance for a freshwater marsh where vertical gaseous [carbon dioxide (CO₂) and CH₄] and lateral hydrologic fluxes (dissolved and particulate organic carbon) have been simultaneously measured for multiple years (2011–2013). Carbon accumulation in the sediments suggested that the marsh was a long‐term carbon sink and accumulated ~96.9 ± 10.3 (±95% CI) g C m^?2 yr^?1 during the last ~50 years. However, abnormal climate conditions in the last 3 years turned the marsh to a source of carbon (42.7 ± 23.4 g C m^?2 yr^?1). Gross ecosystem production and ecosystem respiration were the two largest fluxes in the annual carbon budget. Yet, these two fluxes compensated each other to a large extent and led to the marsh being a CO₂ sink in 2011 (?78.8 ± 33.6 g C m^?2 yr^?1), near CO₂‐neutral in 2012 (29.7 ± 37.2 g C m^?2 yr^?1), and a CO₂ source in 2013 (92.9 ± 28.0 g C m^?2 yr^?1). The CH₄ emission was consistently high with a three‐year average of 50.8 ± 1.0 g C m^?2 yr^?1. Considerable hydrologic carbon flowed laterally both into and out of the marsh (108.3 ± 5.4 and 86.2 ± 10.5 g C m^?2 yr^?1, respectively). In total, hydrologic carbon fluxes contributed ~23 ± 13 g C m^?2 yr^?1 to the three‐year carbon budget. Our findings highlight the importance of lateral hydrologic inflows/outflows in wetland carbon budgets, especially in those characterized by a flow‐through hydrologic regime. In addition, different carbon fluxes responded unequally to climate variability/anomalies and, thus, the total carbon budgets may vary drastically among years.     

Forest biomass carbon sinks in East Asia,with special reference to the relative contributions of forest expansion and forest growth

Forests play an important role in regional and global carbon (C) cycles. With extensive afforestation and reforestation efforts over the last several decades, forests in East Asia have largely expanded, but the dynamics of their C stocks have not been fully assessed. We estimated biomass C stocks of the forests in all five East Asian countries (China, Japan, North Korea, South Korea, and Mongolia) between the 1970s and the 2000s, using the biomass expansion factor method and forest inventory data. Forest area and biomass C density in the whole region increased from 179.78 × 10⁶ ha and 38.6 Mg C ha^?1 in the 1970s to 196.65 × 10⁶ ha and 45.5 Mg C ha^?1 in the 2000s, respectively. The C stock increased from 6.9 Pg C to 8.9 Pg C, with an averaged sequestration rate of 66.9 Tg C yr^?1. Among the five countries, China and Japan were two major contributors to the total region's forest C sink, with respective contributions of 71.1% and 32.9%. In China, the areal expansion of forest land was a larger contributor to C sinks than increased biomass density for all forests (60.0% vs. 40.0%) and for planted forests (58.1% vs. 41.9%), while the latter contributed more than the former for natural forests (87.0% vs. 13.0%). In Japan, increased biomass density dominated the C sink for all (101.5%), planted (91.1%), and natural (123.8%) forests. Forests in South Korea also acted as a C sink, contributing 9.4% of the total region's sink because of increased forest growth (98.6%). Compared to these countries, the reduction in forest land in both North Korea and Mongolia caused a C loss at an average rate of 9.0 Tg C yr^?1, equal to 13.4% of the total region's C sink. Over the last four decades, the biomass C sequestration by East Asia's forests offset 5.8% of its contemporary fossil‐fuel CO₂ emissions.     

Compositional shifts in Costa Rican forests due to climate‐driven species migrations

Species are predicted to shift their distributions upslope or poleward in response to global warming. This prediction is supported by a growing number of studies documenting species migrations in temperate systems but remains poorly tested for tropical species, and especially for tropical plant species. We analyzed changes in tree species composition in a network of 10 annually censused 1‐ha plots spanning an altitudinal gradient of 70–2800 m elevation in Costa Rica. Specifically, we combined plot data with herbarium records (accessed through GBIF) to test if the plots' community temperature scores (CTS, average thermal mean of constituent species weighted by basal area) have increased over the past decade as is predicted by climate‐driven species migrations. In addition, we quantified the contributions of stem growth, recruitment, and mortality to the observed patterns. Supporting our a priori hypothesis of upward species migrations, we found that there have been consistent directional shifts in the composition of the plots, such that the relative abundance of lowland species, and hence CTS, increased in 90% of plots. The rate of the observed compositional shifts corresponds to a mean thermal migration rate (TMR) of 0.0065 °C yr^?1 (95% CI = 0.0005–0.0132 °C yr^?1). While the overall TMR is slower than predicted based on concurrent regional warming of 0.0167 °C yr^?1, migrations were on pace with warming in 4 of the 10 plots. The observed shifts in composition were driven primarily by mortality events (i.e., the disproportionate death of highland vs. lowland species), suggesting that individuals of many tropical tree species will not be able to tolerate future warming and thus their persistence in the face of climate change will depend on successful migrations. Unfortunately, in Costa Rica and elsewhere, land area inevitably decreases at higher elevations; hence, even species that are able to migrate successfully will face heightened risks of extinction.     

Autumn warming reduces the CO2 sink of a black spruce forest in interior Alaska based on a nine‐year eddy covariance measurement

Nine years (2003–2011) of carbon dioxide (CO₂) flux were measured at a black spruce forest in interior Alaska using the eddy covariance method. Seasonal and interannual variations in the gross primary productivity (GPP) and ecosystem respiration (RE) were associated primarily with air temperature: warmer conditions enhanced GPP and RE. Meanwhile, interannual variation in annual CO₂ balance was controlled predominantly by RE, and not GPP. During these 9 years of measurement, the annual CO₂ balance shifted from a CO₂ sink to a CO₂ source, with a 9‐year average near zero. The increase in autumn RE was associated with autumn warming and was mostly attributed to a shift in the annual CO₂ balance. The increase in autumn air temperature (0.22 °C yr^?1) during the 9 years of study was 15 times greater than the long‐term warming trend between 1905 and 2011 (0.015 °C yr^?1) due to decadal climate oscillation. This result indicates that most of the shifts in observed CO₂ fluxes were associated with decadal climate variability. Because the natural climate varies in a cycle of 10–30 years, a long‐term study covering at least one full cycle of decadal climate oscillation is important to quantify the CO₂ balance and its interaction with the climate.     

Land cover change and carbon emissions over 100 years in an African biodiversity hotspot

Agricultural expansion has resulted in both land use and land cover change (LULCC) across the tropics. However, the spatial and temporal patterns of such change and their resulting impacts are poorly understood, particularly for the presatellite era. Here, we quantify the LULCC history across the 33.9 million ha watershed of Tanzania's Eastern Arc Mountains, using geo‐referenced and digitized historical land cover maps (dated 1908, 1923, 1949 and 2000). Our time series from this biodiversity hotspot shows that forest and savanna area both declined, by 74% (2.8 million ha) and 10% (2.9 million ha), respectively, between 1908 and 2000. This vegetation was replaced by a fivefold increase in cropland, from 1.2 million ha to 6.7 million ha. This LULCC implies a committed release of 0.9 Pg C (95% CI: 0.4–1.5) across the watershed for the same period, equivalent to 0.3 Mg C ha^?1 yr^?1. This is at least threefold higher than previous estimates from global models for the same study area. We then used the LULCC data from before and after protected area creation, as well as from areas where no protection was established, to analyse the effectiveness of legal protection on land cover change despite the underlying spatial variation in protected areas. We found that, between 1949 and 2000, forest expanded within legally protected areas, resulting in carbon uptake of 4.8 (3.8–5.7) Mg C ha^?1, compared to a committed loss of 11.9 (7.2–16.6) Mg C ha^?1 within areas lacking such protection. Furthermore, for nine protected areas where LULCC data are available prior to and following establishment, we show that protection reduces deforestation rates by 150% relative to unprotected portions of the watershed. Our results highlight that considerable LULCC occurred prior to the satellite era, thus other data sources are required to better understand long‐term land cover trends in the tropics.     

Can carbon emissions from tropical deforestation drop by 50% in 5 years?

Halving carbon emissions from tropical deforestation by 2020 could help bring the international community closer to the agreed goal of <2 degree increase in global average temperature change and is consistent with a target set last year by the governments, corporations, indigenous peoples' organizations and non‐governmental organizations that signed the New York Declaration on Forests (NYDF). We assemble and refine a robust dataset to establish a 2001–2013 benchmark for average annual carbon emissions from gross tropical deforestation at 2.270 Gt CO₂ yr^?1. Brazil did not sign the NYDF, yet from 2001 to 2013, Brazil ranks first for both carbon emissions from gross tropical deforestation and reductions in those emissions – its share of the total declined from a peak of 69% in 2003 to a low of 20% in 2012. Indonesia, an NYDF signatory, is the second highest emitter, peaking in 2012 at 0.362 Gt CO₂ yr^?1 before declining to 0.205 Gt CO₂ yr^?1 in 2013. The other 14 NYDF tropical country signatories were responsible for a combined average of 0.317 Gt CO₂ yr^?1, while the other 86 tropical country non‐signatories were responsible for a combined average of 0.688 Gt CO₂ yr^?1. We outline two scenarios for achieving the 50% emission reduction target by 2020, both emphasizing the critical role of Brazil and the need to reverse the trends of increasing carbon emissions from gross tropical deforestation in many other tropical countries that, from 2001 to 2013, have largely offset Brazil's reductions. Achieving the target will therefore be challenging, even though it is in the self‐interest of the international community. Conserving rather than cutting down tropical forests requires shifting economic development away from a dependence on natural resource depletion toward recognition of the dependence of human societies on the natural capital that tropical forests represent and the goods and services they provide.     

Carbon cost of collective farming collapse in Russia

The collapse of collective farming in Russia after 1990 and the subsequent economic crisis led to the abandonment of more than 45 million ha of arable lands (23% of the agricultural area). This was the most widespread and abrupt land use change in the 20th century in the northern hemisphere. The withdrawal of land area from cultivation led to several benefits including carbon (C) sequestration. Here, we provide a geographically complete and spatially detailed analysis of C sequestered in these abandoned lands. The average C accumulation rate in the upper 20 cm of mineral soil was 0.96 ± 0.08 Mg C ha^?1 yr^?1 for the first 20 years after abandonment and 0.19 ± 0.10 Mg C ha^?1 yr^?1 during the next 30 years of postagrogenic evolution and natural vegetation establishment. The amount of C sequestered over the period 1990–2009 accounts to 42.6 ± 3.8 Tg C per year. This C sequestration rate is equivalent to ca. 10% of the annual C sink in all Russian forests. Furthermore, it compensates all fire and postfire CO₂ emissions in Russia and covers about 4% of the global CO₂ release due to deforestation and other land use changes. Our assessment shows a significant mitigation of increasing atmospheric CO₂ by prolonged C accumulation in Russian soils caused by collective farming collapse.