Tropical Forest Carbon Research Articles

Asynchronous carbon sink saturation in African and Amazonian tropical forests.

Structurally intact tropical forests sequestered about half of the global terrestrial carbon uptake over the 1990s and early 2000s, removing about 15 per cent of anthropogenic carbon dioxide emissions1-3. Climate-driven vegetation models typically predict that this tropical forest 'carbon sink' will continue for decades4,5. Here we assess trends in the carbon sink using 244 structurally intact African tropical forests spanning 11 countries, compare them with 321 published plots from Amazonia and investigate the underlying drivers of the trends. The carbon sink in live aboveground biomass in intact African tropical forests has been stable for the three decades to 2015, at 0.66 tonnes of carbon per hectare per year (95 per cent confidence interval 0.53-0.79), in contrast to the long-term decline in Amazonian forests6. Therefore the carbon sink responses of Earth's two largest expanses of tropical forest have diverged. The difference is largely driven by carbon losses from tree mortality, with no detectable multi-decadal trend in Africa and a long-term increase in Amazonia. Both continents show increasing tree growth, consistent with the expected net effect of rising atmospheric carbon dioxide and air temperature7-9. Despite the past stability of the African carbon sink, our most intensively monitored plotssuggest a post-2010 increase in carbon losses, delayed compared to Amazonia, indicating asynchronous carbon sink saturation on the two continents. A statistical model including carbon dioxide, temperature, drought and forest dynamics accounts for the observed trends and indicates a long-term future decline in the African sink, whereas the Amazonian sink continues to weaken rapidly. Overall, the uptake of carbon into Earth's intact tropical forests peaked in the 1990s. Given that the global terrestrial carbon sink is increasing in size, independent observations indicating greater recent carbon uptake into the Northern Hemisphere landmass10 reinforce our conclusion that the intact tropical forest carbon sink has already peaked. This saturation and ongoing decline of the tropical forest carbon sink has consequences for policies intended to stabilize Earth's climate.

Lianas reduce biomass accumulation in early successional tropical forests.

Early successional tropical forests could mitigate climate change via rapid accumulation of atmospheric carbon. However, liana (woody vine) abundance and biomass has been increasing in many tropical forests over the past decades, which may slow the speed at which secondary forests accumulate biomass. Lianas decrease biomass accumulation in tropical forests, and may have a particularly strong effect on young forests by stalling tree growth. As forests mature, trees may outgrow or shed lianas, thus escaping some of the negative effects of lianas. Alternatively, lianas may have the strongest effect in older successional forests if the effect of lianas is commensurate with their density, which increases dramatically in the first decades of forest succession. We tested these two hypotheses using a landscape liana-removal experiment in 30 forest stands that ranged from 10 to 35yr old in Central Panama. We measured tree growth and biomass accumulation in the stands every year from 2014 to 2017. We found that the effect of liana removal on large trees (≥20-cm diameter) decreased with forest age, supporting the hypothesis that lianas have the strongest negative effects on trees, and thus biomass uptake and carbon storage, in very young successional forests. Large trees accumulated more biomass in the absence of lianas in younger forests than in older forests (compared to controls) even after accounting for the effect of canopy completeness and crown illumination, implying that the detrimental effects of lianas go well beyond resource availability and crown health. There was no significant effect of lianas on small trees (1-20-cm diameter), likely because lianas seek light and thus do not deploy their leaves on small trees that are trapped in the forest understory. Our results show that high liana density early in forest succession reduces forest biomass accumulation by negatively impacting large trees, thus decreasing the capacity of young secondary forests to mitigate climate change. Although the negative effects of lianas on forest biomass diminish as forests age, they do not disappear, and thus lianas are an important component of tropical forest carbon budgets throughout succession.

Tropical forest soil carbon stocks do not increase despite 15 years of doubled litter inputs

Soil organic carbon (SOC) dynamics represent a persisting uncertainty in our understanding of the global carbon cycle. SOC storage is strongly linked to plant inputs via the formation of soil organic matter, but soil geochemistry also plays a critical role. In tropical soils with rapid SOC turnover, the association of organic matter with soil minerals is particularly important for stabilising SOC but projected increases in tropical forest productivity could trigger feedbacks that stimulate the release of stored SOC. Here, we demonstrate limited additional SOC storage after 13–15 years of experimentally doubled aboveground litter inputs in a lowland tropical forest. We combined biological, physical, and chemical methods to characterise SOC along a gradient of bioavailability. After 13 years of monthly litter addition treatments, most of the additional SOC was readily bioavailable and we observed no increase in mineral-associated SOC. Importantly, SOC with weak association to soil minerals declined in response to long-term litter addition, suggesting that increased plant inputs could modify the formation of organo-mineral complexes in tropical soils. Hence, we demonstrate the limited capacity of tropical soils to sequester additional C inputs and provide insights into potential underlying mechanisms.

Tropical carbon sink accelerated by symbiotic dinitrogen fixation

A major uncertainty in the land carbon cycle is whether symbiotic nitrogen fixation acts to enhance the tropical forest carbon sink. Nitrogen-fixing trees can supply vital quantities of the growth-limiting nutrient nitrogen, but the extent to which the resulting carbon–nitrogen feedback safeguards ecosystem carbon sequestration remains unclear. We combine (i) field observations from 112 plots spanning 300 years of succession in Panamanian tropical forests, and (ii) a new model that resolves nitrogen and light competition at the scale of individual trees. Fixation doubled carbon accumulation in early succession and enhanced total carbon in mature forests by ~10% (~12MgC ha−1) through two mechanisms: (i) a direct fixation effect on tree growth, and (ii) an indirect effect on the successional sequence of non-fixing trees. We estimate that including nitrogen-fixing trees in Neotropical reforestation projects could safeguard the sequestration of 6.7 Gt CO2 over the next 20 years. Our results highlight the connection between functional diversity of plant communities and the critical ecosystem service of carbon sequestration for mitigating climate change.

Monitoring tropical forest carbon stocks and emissions using Planet satellite data

Tropical forests are crucial for mitigating climate change, but many forests continue to be driven from carbon sinks to sources through human activities. To support more sustainable forest uses, we need to measure and monitor carbon stocks and emissions at high spatial and temporal resolution. We developed the first large-scale very high-resolution map of aboveground carbon stocks and emissions for the country of Peru by combining 6.7 million hectares of airborne LiDAR measurements of top-of-canopy height with thousands of Planet Dove satellite images into a random forest machine learning regression workflow, obtaining an R2 of 0.70 and RMSE of 25.38 Mg C ha−1 for the nationwide estimation of aboveground carbon density (ACD). The diverse ecosystems of Peru harbor 6.928 Pg C, of which only 2.9 Pg C are found in protected areas or their buffers. We found significant carbon emissions between 2012 and 2017 in areas aggressively affected by oil palm and cacao plantations, agricultural and urban expansions or illegal gold mining. Creating such a cost-effective and spatially explicit indicators of aboveground carbon stocks and emissions for tropical countries will serve as a transformative tool to quantify the climate change mitigation services that forests provide.

Lightning is a major cause of large tree mortality in a lowland neotropical forest.

The mortality rates of large trees are critical to determining carbon stocks in tropical forests, but the mechanisms of tropical tree mortality remain poorly understood. Lightning strikes thousands of tropical trees every day, but is commonly assumed to be a minor agent of tree mortality in most tropical forests. We use the first systematic quantification of lightning-caused mortality to show that lightning is a major cause of death for the largest trees in an old-growth lowland forest in Panama. A novel lightning strike location system together with field surveys of strike sites revealed that, on average, each strike directly kills 3.5 trees (>10cm diameter) and damages 11.4 more. Given lightning frequency data from the Earth Networks Total Lightning Network and historical total tree mortality rates for this site, we conclude that lightning accounts for 40.5% of the mortality of large trees (>60cm diameter) in the short term and probably contributes to an additional 9.0% of large tree deaths over the long term. Any changes in cloud-to-ground lightning frequency due to climatic change will alter tree mortality rates; projected 25-50% increases in lightning frequency would increase large tree mortality rates in this forest by 9-18%. The results of this study indicate that lightning plays a critical and previously underestimated role in tropical forest dynamics and carbon cycling.

The response of stomatal conductance to seasonal drought in tropical forests.

Stomata regulate CO2 uptake for photosynthesis and water loss through transpiration. The approaches used to represent stomatal conductance (gs ) in models vary. In particular, current understanding of drivers of the variation in a key parameter in those models, the slope parameter (i.e. a measure of intrinsic plant water-use-efficiency), is still limited, particularly in the tropics. Here we collected diurnal measurements of leaf gas exchange and leaf water potential (Ψleaf ), and a suite of plant traits from the upper canopy of 15 tropical trees in two contrasting Panamanian forests throughout the dry season of the 2016 El Niño. The plant traits included wood density, leaf-mass-per-area (LMA), leaf carboxylation capacity (Vc,max ), leaf water content, the degree of isohydry, and predawn Ψleaf . We first investigated how the choice of four commonly used leaf-level gs models with and without the inclusion of Ψleaf as an additional predictor variable influence the ability to predict gs , and then explored the abiotic (i.e. month, site-month interaction) and biotic (i.e. tree-species-specific characteristics) drivers of slope parameter variation. Our results show that the inclusion of Ψleaf did not improve model performance and that the models that represent the response of gs to vapor pressure deficit performed better than corresponding models that respond to relative humidity. Within each gs model, we found large variation in the slope parameter, and this variation was attributable to the biotic driver, rather than abiotic drivers. We further investigated potential relationships between the slope parameter and the six available plant traits mentioned above, and found that only one trait, LMA, had a significant correlation with the slope parameter (R2 =0.66, n=15), highlighting a potential path towards improved model parameterization. This study advances understanding of gs dynamics over seasonal drought, and identifies a practical, trait-based approach to improve modeling of carbon and water exchange in tropical forests.

Testing for changes in biomass dynamics in large-scale forest datasets.

Tropical forest responses to climate and atmospheric change are critical to the future of the global carbon budget. Recent studies have reported increases in estimated above-ground biomass (EAGB) stocks, productivity, and mortality in old-growth tropical forests. These increases could reflect a shift in forest functioning due to global change and/or long-lasting recovery from past disturbance. We introduce a novel approach to disentangle the relative contributions of these mechanisms by decomposing changes in whole-plot biomass fluxes into contributions from changes in the distribution of gap-successional stages and changes in fluxes for a given stage. Using 30years of forest dynamic data at Barro Colorado Island, Panama, we investigated temporal variation in EAGB fluxes as a function of initial EAGB (EAGBi ) in 10×10m quadrats. Productivity and mortality fluxes both increased strongly with initial quadrat EAGB. The distribution of EAGB (and thus EAGBi ) across quadrats hardly varied over 30years (and seven censuses). EAGB fluxes as a function of EAGBi varied largely and significantly among census intervals, with notably higher productivity in 1985-1990 associated with recovery from the 1982-1983 El Niño event. Variation in whole-plot fluxes among census intervals was explained overwhelmingly by variation in fluxes as a function of EAGBi , with essentially no contribution from changes in EAGBi distributions. The high observed temporal variation in productivity and mortality suggests that this forest is very sensitive to climate variability. There was no consistent long-term trend in productivity, mortality, or biomass in this forest over 30years, although the temporal variability in productivity and mortality was so strong that it could well mask a substantial trend. Accurate prediction of future tropical forest carbon budgets will require accounting for disturbance-recovery dynamics and understanding temporal variability in productivity and mortality.

Factors affecting woody carbon stock in Sirso moist evergreen Afromontane forest, southern Ethiopia: implications for climate change mitigation

Among the many other factors that would be taken as one of the most important options for climate change mitigation is forest wood carbon stock. Hence, the aim of this study was to examine the carbon stock potential of woody species and how it varies by community types and topographic aspects, along altitudinal and slope gradients in Sirso moist evergreen Afromontane vegetation ecosystem of southern Ethiopia. To collect data, a systematic sampling procedure was employed. Five transects were laid out across altitudinal gradients which aligned parallel at 2 km intervals, and 50 sample plots (20 m × 20 m) were laid along transects at 100 m altitudinal interval. Carbon stock was estimated based on the equations and conversion factors formulated for tropical forest carbon stock measurement. The results showed that the total carbon stock of woody species in Sirso moist evergreen Afromontane forest was 384.44 ton/ha. The carbon stock of woody species varied among community types, along altitudinal and slope gradients, while topographic aspect had no significant effect. The carbon stock was higher for the community type of Dracaena fragrans–Rytigynia neglecta, for mid-altitude (1934–2319 m.a.s.l.), and upper slope class (58–75%). Schefflera abyssinica, Syzygium guineense, and Ficus sur contributed 49% of the total carbon stock. Our study suggests that selecting a certain forest as the mitigation option for climate change needs to consider the determinants including vegetation composition and topographic features such as altitude and slope gradients.

A Spatial and Temporal Risk Assessment of the Impacts of El Niño on the Tropical Forest Carbon Cycle: Theoretical Framework, Scenarios, and Implications

Strong El Niño events alter tropical climates and may lead to a negative carbon balance in tropical forests and consequently a disruption to the global carbon cycle. The complexity of tropical forests and the lack of data from these regions hamper the assessment of the spatial distribution of El Niño impacts on these ecosystems. Typically, maps of climate anomaly are used to detect areas of greater risk, ignoring baseline climate conditions and forest cover. Here, we integrated climate anomalies from the 1982–1983, 1997–1998, and 2015–2016 El Niño events with baseline climate and forest edge extent, using a risk assessment approach to hypothetically assess the spatial and temporal distributions of El Niño risk over tropical forests under several risk scenarios. The drivers of risk varied temporally and spatially. Overall, the relative risk of El Niño has been increasing driven mainly by intensified forest fragmentation that has led to a greater chance of fire ignition and increased mean annual air temperatures. We identified areas of repeated high risk, where conservation efforts and fire control measures should be focused to avoid future forest degradation and negative impacts on the carbon cycle.

Modeling the impact of liana infestation on the demography and carbon cycle of tropical forests.

There is mounting empirical evidence that lianas affect the carbon cycle of tropical forests. However, no single vegetation model takes into account this growth form, although such efforts could greatly improve the predictions of carbon dynamics in tropical forests. In this study, we incorporated a novel mechanistic representation of lianas in a dynamic global vegetation model (the Ecosystem Demography Model). We developed a liana‐specific plant functional type and mechanisms representing liana–tree interactions (such as light competition, liana‐specific allometries, and attachment to host trees) and parameterized them according to a comprehensive literature meta‐analysis. We tested the model for an old‐growth forest (Paracou, French Guiana) and a secondary forest (Gigante Peninsula, Panama). The resulting model simulations captured many features of the two forests characterized by different levels of liana infestation as revealed by a systematic comparison of the model outputs with empirical data, including local census data from forest inventories, eddy flux tower data, and terrestrial laser scanner‐derived forest vertical structure. The inclusion of lianas in the simulations reduced the secondary forest net productivity by up to 0.46 tC ha−1 year−1, which corresponds to a limited relative reduction of 2.6% in comparison with a reference simulation without lianas. However, this resulted in significantly reduced accumulated above‐ground biomass after 70 years of regrowth by up to 20 tC/ha (19% of the reference simulation). Ultimately, the simulated negative impact of lianas on the total biomass was almost completely cancelled out when the forest reached an old‐growth successional stage. Our findings suggest that lianas negatively influence the forest potential carbon sink strength, especially for young, disturbed, liana‐rich sites. In light of the critical role that lianas play in the profound changes currently experienced by tropical forests, this new model provides a robust numerical tool to forecast the impact of lianas on tropical forest carbon sinks.

Changes in seasonal precipitation distribution but not annual amount affect litter decomposition in a secondary tropical forest.

In the tropics of South China, climate change induced more rainfall events in the wet season in the last decades. Moreover, there will be more frequently spring drought in the future. However, knowledge on how litter decomposition rate would respond to these seasonal precipitation changes is still limited. In the present study, we conducted a precipitation manipulation experiment in a tropical forest. First, we applied a 60% rainfall exclusion in April and May to defer the onset of wet season and added the same amount of water in October and November to mimic a deferred wet season (DW); second, we increased as much as 25% mean annual precipitation into plots in July and August to simulate a wetter wet season (WW). Five single‐species litters, with their carbon to nitrogen ratio ranged from 27 to 49, and a mixed litter were used to explore how the precipitation change treatments would affect litter decomposition rate. The interaction between precipitation changes and litter species was not significant. The DW treatment marginally accelerated litter decomposition across six litter types. Detailed analysis showed that DW increased litter decomposition rate in the periods of January to March and October to December, when soil moisture was increased by the water addition in the dry season. In contrast, WW did not significantly affect litter decomposition rate, which was consistent with the unchanged soil moisture pattern. In conclusion, the study indicated that regardless of litter types or litter quality, the projected deferred wet season would increase litter decomposition rate, whereas the wetter wet season would not affect litter decomposition rate in the tropical forests. This study improves our knowledge of how tropical forest carbon cycling in response to precipitation change.

Carbon stocks in mangrove forests of the Colombian Pacific

Mangrove forests occupy less than 1% of tropical forest areas, but they represent approximately 3% of worldwide tropical forest carbon capture. The present study quantified carbon stocks in mangrove forests in two bays in the Colombian Pacific, and evaluated the effect of forest structure on variations of carbon storage in the different ecosystem compartments. Significant differences were found in carbon stocks between the stations of Málaga Bay (a national marine park) and Buenaventura Bay (the main harbor area). Belowground biomass and sediment represented the greatest carbon stocks in the forest. Carbon reserves in mangroves in the Colombian Pacific were similar compared with other tropical mangrove areas. These results highlight the importance of evaluating carbon storage in these ecosystems and of formulating conservation and management strategies integrated with the mangrove forest in the Colombian Pacific.

Accounting tropical forest carbon stock with synergistic use of space-borne ALOS PALSAR and COSMO-Skymed SAR sensors

The objective of this study is to precisely quantify the forest aboveground biomass (AGB) and carbon stock in a tropical deciduous forest with synergistic use of space-borne L-band ALOS PALSAR and X-band COSMO-Skymed SAR data, along with field inventory data. AGB serves as a decisive parameter for preparing global decision making policy targeting the impact of reducing emissions from deforestation and forest degradation and climate change. The study proposed optimal regression models for assessing above-ground bole biomass over tropical deciduous mixed forests of Munger (Bihar, India) with synergistic use of ALOS PALSAR and COSMO-Skymed sigma nought images. Coefficient of determination (r2) of 0.89 and RMSE of 15.12 Mg ha−1 were calculated for the best fit integrated model. On validation, the integrated model produced a model accuracy of 78%, r2 = 0.89, RMSE = 16.64 Mg ha−1 and Willmott’s index of agreement of 0.934. Resulting modeled AGB were converted to carbon and carbon dioxide equivalents using conversion factors. L-band showed higher accuracy in the estimation in comparison to X-band; but the estimation accuracy improved with the synergistic use of both X- and L-band SAR data. Hence, the study recommends the combined use of X- and L-band SAR with exceptional capabilities for improved assessment of tropical forest stand AGB and carbon with significant contribution towards operational forestry and policy making.

Estimates and determinants of stocks of deep soil carbon in Gabon, Central Africa

Despite the importance of tropical forest carbon to the global carbon cycle, research on carbon stocks is incomplete in major areas of the tropical world. Nowhere in the tropics is this more the case than in Africa, and especially Central Africa, where carbon stocks are known to be high but a scarcity of data limits understanding of carbon stocks and drivers. In this study, we present the first nation-wide measurements and determinants of soil carbon in Gabon, a nation in Central Africa. We estimated soil carbon to a 2-m depth using a systematic, random design of 59 plots located across Gabon. Soil carbon to a 2-m depth averaged 163 Mg ha−1 with a CV of 61%. These soil carbon stocks accounted for approximately half of the total carbon accumulated in aboveground biomass and soil pools. Nearly a third of soil carbon was stored in the second meter of soil, averaging 58 Mg ha−1 with a CV of 94%. Lithology, soil type, and terrain attributes were found to be significant predictors of cumulative SOC stocks to a 2-m depth. Current protocols of the IPCC are to sample soil carbon from the surface 30 cm, which in this study would underestimate soil carbon by 60% and underestimate ecosystem carbon by 30%. A nonlinear model using a power function predicted cumulative soil carbon stocks in the second meter with an average error of prediction of 3.2 Mg ha−1 (CV = 915%) of measured values. The magnitude and turnover of deep soil carbon in tropical forests needs to be estimated as more countries prioritize carbon accounting and monitoring in response to accelerating land-use change.

Biodiversity Observation for Land and Ecosystem Health (BOLEH): A Robust Method to Evaluate the Management Impacts on the Bundle of Carbon and Biodiversity Ecosystem Services in Tropical Production Forests

The Forest Stewardship Council (FSC) has initiated a new sustainability mechanism, the ecosystem-services certification. In this system, management entities who wish to be certified for the maintenance of ecosystem services (carbon, biodiversity, watershed, soil and recreational services) must verify that their activities have no net negative impacts on selected ecosystem service(s). Developing a robust and cost-effective measurement method is a key challenge for establishing a credible certification system. Using a single method to evaluate a bundle of ecosystem services will be more efficient in terms of transaction costs than using multiple methods. We tested the efficiency of a single method, “biodiversity observation for land and ecosystem health (BOLEH)”, to simultaneously evaluate biodiversity and carbon density on a landscape scale in FSC-certified tropical production forests in Sabah, Malaysia. In this method, forest intactness based on the tree-generic compositional similarity with that of a pristine forest was used as an index of biodiversity. We repeated BOLEH in 2009 and 2014 in these forests. Our analysis could detect significant spatiotemporal changes in both carbon and forest intactness during these five years, which reflected past logging intensities and current management regimes in these forests. Enhancement of these ecosystem services occurred in the forest where sustainable management with reduced-impact logging had long been implemented. In this paper, we describe the procedure of the BOLEH method, and results of the pilot test in these forests.

Pan‐tropical prediction of forest structure from the largest trees

AbstractAimLarge tropical trees form the interface between ground and airborne observations, offering a unique opportunity to capture forest properties remotely and to investigate their variations on broad scales. However, despite rapid development of metrics to characterize the forest canopy from remotely sensed data, a gap remains between aerial and field inventories. To close this gap, we propose a new pan‐tropical model to predict plot‐level forest structure properties and biomass from only the largest trees.LocationPan‐tropical.Time periodEarly 21st century.Major taxa studiedWoody plants.MethodsUsing a dataset of 867 plots distributed among 118 sites across the tropics, we tested the prediction of the quadratic mean diameter, basal area, Lorey's height, community wood density and aboveground biomass (AGB) from the ith largest trees.ResultsMeasuring the largest trees in tropical forests enables unbiased predictions of plot‐ and site‐level forest structure. The 20 largest trees per hectare predicted quadratic mean diameter, basal area, Lorey's height, community wood density and AGB with 12, 16, 4, 4 and 17.7% of relative error, respectively. Most of the remaining error in biomass prediction is driven by differences in the proportion of total biomass held in medium‐sized trees (50–70 cm diameter at breast height), which shows some continental dependency, with American tropical forests presenting the highest proportion of total biomass in these intermediate‐diameter classes relative to other continents.Main conclusionsOur approach provides new information on tropical forest structure and can be used to generate accurate field estimates of tropical forest carbon stocks to support the calibration and validation of current and forthcoming space missions. It will reduce the cost of field inventories and contribute to scientific understanding of tropical forest ecosystems and response to climate change.

Effects of Sample Plot Size and GPS Location Errors on Aboveground Biomass Estimates from LiDAR in Tropical Dry Forests

Accurate estimates of above ground biomass (AGB) are needed for monitoring carbon in tropical forests. LiDAR data can provide precise AGB estimations because it can capture the horizontal and vertical structure of vegetation. However, the accuracy of AGB estimations from LiDAR is affected by a co-registration error between LiDAR data and field plots resulting in spatial discrepancies between LiDAR and field plot data. Here, we evaluated the impacts of plot location error and plot size on the accuracy of AGB estimations predicted from LiDAR data in two types of tropical dry forests in Yucatán, México. We sampled woody plants of three size classes in 29 nested plots (80 m2, 400 m2 and 1000 m2) in a semi-deciduous forest (Kiuic) and 28 plots in a semi-evergreen forest (FCP) and estimated AGB using local allometric equations. We calculated several LiDAR metrics from airborne data and used a Monte Carlo simulation approach to assess the influence of plot location errors (2 to 10 m) and plot size on ABG estimations from LiDAR using regression analysis. Our results showed that the precision of AGB estimations improved as plot size increased from 80 m2 to 1000 m2 (R2 = 0.33 to 0.75 and 0.23 to 0.67 for Kiuic and FCP respectively). We also found that increasing GPS location errors resulted in higher AGB estimation errors, especially in the smallest sample plots. In contrast, the largest plots showed consistently lower estimation errors that varied little with plot location error. We conclude that larger plots are less affected by co-registration error and vegetation conditions, highlighting the importance of selecting an appropriate plot size for field forest inventories used for estimating biomass.

A long-term decrease in the persistence of soil carbon caused by ancient Maya land use

The long-term effects of deforestation on tropical forest soil carbon reservoirs are important for estimating the consequences of land use on the global carbon cycle, but are poorly understood. The Maya Lowlands of Mexico and Guatemala provide a unique opportunity to assess this question, given the widespread deforestation by the ancient Maya that began ~4,000 years ago. Here, we compare radiocarbon ages of plant waxes and macrofossils in sediment cores from three lakes in the Maya Lowlands to record past changes in the mean soil transit time of plant waxes (MTTwax). MTTwax indicates the average age of plant waxes that are transported from soils to lake sediments, and comparison of radiocarbon data from soils and lake sediments within the same catchment indicates that MTTwax reflects the age of carbon in deep soils. All three sediment cores showed a decrease in MTTwax, ranging from 2,300 to 800 years, over the past 3,500 years. This decrease in MTTwax, indicating shorter storage times for carbon in lake catchment soils, is associated with evidence for ancient Maya deforestation. MTTwax never recovered to pre-deforestation values, despite subsequent reforestation, implying that current tropical deforestation will have long-lasting effects on soil carbon sinks.

Impact of Nitrogen Deposition on Tropical Forest Biomass and Carbon Sequestration

Undoubtedly, nitrogen (N) is an essential component of proteins and nucleic acid of cells but in the last few decades it has undergone dramatic changes. Now move nitrogen has come into circulation and thus it has now become an environmental problem. Ndeposition is not always undesirable, in areas with N- limitation , N–deposition enhances the plant growth. Besides, it sequesters more CO into the plant biomass there by 2 lowering greenhouse gas emission into the atmosphere. Forest ecosystems all around the globe have experienced N- deposition and are becoming an important C-sink which has been shown in the table 1of this review article. The C-sink capacity of forest ecosystems have been determined using many approaches which are stochiometric scaling, dynamic global vegetation models and biomass weighting method. All these method used C:N response ratio as a predictor for future rate of C-sequestration in response to N- addition. Nutrient availability increases the production of biomass per unit of photosynthesis and decreases heterotrophic respiration in forests. Nutrient availability also determines net ecosystem productivity (NEP) and ecosystem carbon use efficiency (CUE). Biomass production was found higher in the nutrient rich forests, Increase in biomass production was more in woody biomass while foliage and root biomass production remain unchanged. Indeed, the potential of forest C-sink depends upon the partitioning of the carbon uptaken during photosynthesis. In terrestrial ecosystems, C –sequestration predominantly occur in forests ecosystems. Both C:N ratio and nitrogen use efficiency (NUE) are crucial for determining C-sequestration in different forest types. C-sequestration in response to N-addition shows variation with kind of mycorrhizal association. N-deposition benefitted trees with arbuscular mycorrhizal fungi rather than ectomycorrhizal fungi. Thus, after going thoroughly across number of research articles, we arrived at the conclusion that it is the C:N ratio, NUE, forest type, nutrient availability which determine the C sequestration by forest biomass.