Aboveground Biomass Carbon Stocks Research Articles

Impacts of land use change due to biofuel crops on climate regulation services: Five case studies in Malawi, Mozambique and Swaziland

Understanding changes in carbon sequestration due to land conversion is key for elucidating the true potential of biofuel landscapes to provide climate regulation ecosystem services. In this study, we focus on the two most promoted biofuel crops in southern Africa, Jatropha and sugarcane, to analyse the land use change effects and associated carbon impacts of growing biofuel crops in five study sites in Mozambique, Malawi and Swaziland. We found that, considering a 20-year cycle, carbon stocks in aboveground biomass are higher for sugarcane than for Jatropha. However, as soil organic carbon (SOC) is generally the main carbon pool, total carbon stocks (considering biomass and soil) will highly depend on SOC. Our results show that, in our study sites, sugarcane replaced land uses with low carbon stocks (low-density forest and agriculture), and as a result carbon gains occurred due to land use change. In the Jatropha projects, carbon gains are observed in the smallholder scheme as agricultural land was converted to Jatropha, but carbon debts occurred in the Jatropha plantation as high-density forest was cleared to grow this feedstock. Finally we show that, if a plantation of sugarcane or Jatropha is envisioned to be located in the studied regions, more forested land could potentially be converted into sugarcane (30–44% of forest) than into Jatropha (24–32%), without creating carbon debts due to land conversion. To our knowledge, this is the first comparative study of the carbon impacts of land use change of the main biofuel crops in southern Africa.

Spatial Variation in Tree Density and Estimated Aboveground Carbon Stocks in Southern Africa

Variability in woody plant species, vegetation assemblages and anthropogenic activities derails the efforts to have common approaches for estimating biomass and carbon stocks in Africa. In order to suggest management options, it is important to understand the vegetation dynamics and the major drivers governing the observed conditions. This study uses data from 29 sentinel landscapes (4640 plots) across the southern Africa. We used T-Square distance method to sample trees. Allometric models were used to estimate aboveground tree biomass from which aboveground biomass carbon stock (AGBCS) was derived for each site. Results show average tree density of 502 trees·ha−1 with semi-arid areas having the highest (682 trees·ha−1) and arid regions the lowest (393 trees·ha−1). The overall AGBCS was 56.4 Mg·ha−1. However, significant site to site variability existed across the region. Over 60 fold differences were noted between the lowest AGBCS (2.2 Mg·ha−1) in the Musungwa plains of Zambia and the highest (138.1 Mg·ha−1) in the scrublands of Kenilworth in Zimbabwe. Semi-arid and humid sites had higher carbon stocks than sites in sub-humid and arid regions. Anthropogenic activities also influenced the observed carbon stocks. Repeated measurements would reveal future trends in tree cover and carbon stocks across different systems.

Aboveground live carbon stock changes of California wildland ecosystems, 2001–2010

The balance between ecosystem emissions of carbon to the atmosphere and removals from the atmosphere indicates whether ecosystems are exacerbating or reducing climate change. Forest ecosystems in the State of California, USA, contain carbon that reaches the highest densities (mass per unit area) in the world, but it has been unresolved whether California ecosystems currently comprise a net sink or source of carbon. The California Global Warming Solutions Act of 2006 established greenhouse gas reduction targets for fossil fuel-burning sectors and ecosystems, underscoring the importance of tracking ecosystem carbon. Here, we conduct statewide spatial inventories of the aboveground live carbon stocks of forests and other terrestrial ecosystems of California, excluding agricultural and urban areas. We analyzed biomass data from field measurements of the Forest Inventory and Analysis program, published biomass information and remote sensing data on non-forest vegetation, and spatial distributions of vegetation types, height, and fractional cover derived by the Landfire program from Landsat remote sensing at 30m spatial resolution. We conducted Monte Carlo analyses of the uncertainty of carbon stock change estimates from errors in tree biomass estimates, remote sensing, and estimates of the carbon fraction of biomass. The carbon stock in aboveground biomass was 850±230 Tg (mean±95% confidence interval) in 2010. We found a net aboveground live carbon stock change of −69±15 Tg from 2001 to 2010, a rate of change of −0.8±0.2%y−1. Due to slow decay of some dead wood, all of the live carbon stock change does not immediately generate emissions. Wildfires on 6% of the state analysis area produced two-thirds of the live carbon stock loss. This suggests that increased tree densities from a century of fire suppression have allowed the accumulation of fuel for carbon losses in recent wildfires. Remote sensing errors in vegetation classification accounted for most of the uncertainty in the carbon stock change estimates. Improvements are also needed to track spatial patterns of growth and dead wood. Our results establish the beginning of a time series for the state greenhouse gas inventory and provide information on the role of forest conservation and management in California in mitigating global climate change.

Shrub biomass accumulation and growth rate models to quantify carbon stocks and fluxes for the Mediterranean region

The importance of shrub formations in the Mediterranean area both in terms of area occupied and carbon sequestered by them is currently being recognized. However, due to the lack of suitable models to estimate biomass accumulation and growth rate in this region, the carbon sequestered by these formations is not included when computing the total carbon stocks in aboveground biomass in Mediterranean forest ecosystems, according to the IPCC guidelines. The aim of the present study is to develop equations to predict biomass accumulation and growth rate for the main shrub formations in the region of Andalusia (Southern Spain), using the fraction of canopy cover (FCCm) and the average height of the shrub formations (Hm) as predictors. To build these models, more than 800 plots were inventoried using destructive sampling; the mean value found in the region for biomass accumulation and annual growth rate being 16.73 Mg ha−1 and 1.14 Mg ha−1 year−1, respectively. Heathers and big-size Cistaceae formations were the ones that presented the highest values of biomass accumulation (24.99 and 21.01 Mg ha−1, respectively), while the highest values for annual growth rate were achieved by Leguminous gorse shrubs and, again, big-size Cistaceae bushes (1.49 and 1.64 Mg ha−1 year−1, respectively). The carbon content for the main shrub species and formations in the area was also obtained. The developed models provide the opportunity to estimate shrub carbon stocks in Mediterranean forest management from easy-to-obtain variables, namely FCCm and Hm. Moreover, the used shrub formations classifications and model structure allow their applicability to compute biomass accumulation and growth rate at regional and national level using as input data from the Spanish National Forest Inventory.

Forest aboveground biomass estimates in a tropical rainforest in Madagascar: new insights from the use of wood specific gravity data

To generate carbon credits under the Reducing Emissions from Deforestation and forest Degradation program (REDD+), accurate estimates of forest carbon stocks are needed. Carbon accounting efforts have focused on carbon stocks in aboveground biomass (AGB). Although wood specific gravity (WSG) is known to be an important variable in AGB estimates, there is currently a lack of data on WSG for Malagasy tree species. This study aimed to determine whether estimates of carbon stocks calculated from literature-based WSG values differed from those based on WSG values measured on wood core samples. Carbon stocks in forest biomass were assessed using two WSG data sets: (i) values measured from 303 wood core samples extracted in the study area, (ii) values derived from international databases. Results suggested that there is difference between the field and literature-based WSG at the 0.05 level. The latter data set was on average 16 % higher than the former. However, carbon stocks calculated from the two data sets did not differ significantly at the 0.05 level. Such findings could be attributed to the form of the allometric equation used which gives more weight to tree diameter and tree height than to WSG. The choice of dataset should depend on the level of accuracy (Tier II or III) desired by REDD+. As higher levels of accuracy are rewarded by higher prices, species-specific WSG data would be highly desirable.

Organic Carbon Storage in Evergreen Oak Forest Ecosystems of the Middle and High Moroccan Atlas Areas

We report carbon stock in biomass, litter and soil estimated for six locations in natural Quercus ilex L. stands of the Middle and High Moroccan Atlas. Twenty trees at each location were selected according to their diameter classes and felled to measure the biomass of trunk, branches, twigs and leaves and determine allometric relationships. Soil was sampled in five depths (0 - 15, 15 - 30, 30 - 50, 50 - 70 and 70 - 100 cm) and litterfall production measured in all tree stands. The total carbon stock in above-ground biomass ranged between 17 Mg&#183ha&#451 in A&#239t Aamar stand (High Atlas) and 91 Mg&#183ha&#451 in Ksiba stand (Middle Atlas). Perennial organs (trunk, branches and twigs) stored over 95% of the tree carbon stock. Soil organic carbon concentrations ranged from 0.01% (in 70 - 100 cm in all stands) to 8.1% (in 0 - 15 cm in the Ajdir stand in Middle Atlas). The total organic carbon stock in the soil ranged between 141.4 t&#183ha&#451 in Ajdir and 24.6 t&#183ha&#451 in Asloul. The litter contained 0.2 Mg C ha&#451 in the clearing (C2) stand of High Atlas and 14.3 Mg C ha&#451 in (Ajdir) of carbon. The best fitted model for predicting carbon stock in tree biomass was obtained by applying the allometric equation Y = aXb for each biomass fraction and stand, where Y is the aboveground biomass (dry weight) and X is the DBH (Mean diameter at breast height, 1.30 m). These previous data obtained in the present study confirm the important function of these natural forests as longterm C sinks, in forest biomass, litter and soil. The potential long term C storage of these systems is moderately high, especially in less-intensively managed forests that include large trees. The established relationship between DBH and carbon stock in different tree organs can be used for forest carbon accounting, and also synthesize available information on oak forest as a sink for atmospheric CO2, and identify the management options that may enhance the capacity for C capture/ storage in forest soils.

Measurement matters in managing landscape carbon

Carbon stocks and emissions are quantified using many different measures and metrics, and these differ in their surrogacy, measurement, and incentive value. To evaluate potential policy impacts of using different carbon measures, we modeled and mapped carbon in above-ground and below-ground stocks, as well as fluxes related to sequestration, oxidation and combustion in the Ex Mega Rice Project Area in Central Kalimantan, Indonesia. We identify significant financial and carbon emission mitigation consequences of proxy choice in relation to the achievement of national emissions reduction targets. We find that measures of above-ground biomass carbon stock have both high measurement and incentive value, but low surrogacy for potential emissions or the potential for emissions reductions. The inclusion of below-ground carbon increased stocks and flows by an order of magnitude, highlighting the importance of protecting and managing soil carbon and peat. Carbon loss and potential emissions reduction is highest in the areas of deep peat, which supports the use of deep peat as a legislative metric. Divergence in patterns across sub-regions and through time further emphasizes the importance of proxy choice and highlights the need to carefully consider the objectives of the application to which the measure of carbon will be applied.

Aboveground Biomass Carbon in the Alpine and Arctic Treeline Ecotones in the Ural Region

This paper reports on measured carbon stocks in the forests of two treeline ecotones of the Ural region where climate change might improve growing conditions. The first is an alpine ecotone that is represented by an altitudinal gradient of the spruce-dominated forests on the Western slope of the Tylaiskii Kamen Mountain (Western part of the Konzhakovskii-Tylaiskii-Serebryanskii Mountain system, 59030'N, 59000'E), at the alpine timber line that has risen from 864 to 960 m above sea level in the course of the last 100 years. The second is an arctic ecotone in larch-dominated forests at the lower course of the Pur River (670N, 780E), at the transition zone between closed floodplain forests and open or island-like communities of upland forests on tundra permafrost. According to our results, there are large differences in the carbon of the aboveground biomass of both ecotones across environmental gradients. In the alpine treeline ecotone, a 19-fold drop of the carbon stocks was detected between the lower and higher altitudinal levels. In the arctic ecotone the aboveground biomass carbon stock of forests of similar densities (1300 to 1700 trees per ha) was 7 times as much in the river flood bed, and 5 times as much in mature, dense forests as the low density forests at higher elevations.

Carbon stocks and changes in tropical secondary forests of southern Mexico

The role of tropical secondary forests in carbon accumulation has been widely acknowledged, but the rates of changes in carbon stocks still remain uncertain. The aim of this study was to analyze the changes in carbon pool sizes and accumulation rates associated with growth, recruitment and mortality of trees at different ages of forest succession in semi-evergreen tropical forests and relate these to the age of the secondary vegetation and prior land use intensity. The study was carried out in a chronosequence of secondary and mature forests around Calakmul Biosphere Reserve in southern Yucatan Peninsula, Mexico. Permanent monitoring plots were established and measured in 2011 and 2012 to account all carbon stocks and changes due to tree increments, establishment of new trees and tree mortality in different age classes of secondary forests.We found that carbon stocks in living tree biomass increased rapidly in the early stages and decreased in the older secondary forests. The annual carbon dynamics of trees were higher in younger secondary forest compared to older forests due to higher tree growth and recruitment. Growth functions predict that the secondary forests recover live aboveground biomass carbon stocks to pre-disturbance levels (99.56MgCha−1) at the age of about 125 years or more, while the basal area (33.2m2ha−1) regains this level at the age of about 85 years. The longer carbon recovery time can be explained by the fact that mature forests are dominated by hardwood species whereas secondary forests are composed of softwood species and that species composition turnover during succession is relatively slow. Secondary forests of 35 years look similar to mature forests in terms of basal area, but this is located in large number of small and medium sized trees, whereas in mature forests, most of the basal area is in trees of >20cm diameter. In addition, the intensity of slash and burn agriculture can negatively alter the velocity of carbon accumulation. These findings have important implications for national forest carbon monitoring systems, greenhouse gas emission inventories and regional level REDD+ strategies.

Soil macroinvertebrate communities and ecosystem services in deforested landscapes of Amazonia

Land use changes in the Amazon region strongly impact soil macroinvertebrate communities, which are recognized as major drivers of soil functions (Lavelle et al., 2006). To explore these relations, we tested the hypotheses that (i) soil macrofauna communities respond to landscape changes and (ii) soil macrofauna and ecosystem services are linked. We conducted a survey of macrofauna communities and indicators of ecosystem services at 270 sites in southern Colombia (department of Caqueta) and northern Brazil (state of Pará), two areas of the Amazon where family agriculture dominates. Sites represented a variety of land use types: forests, fallows, annual or perennial crops, and pastures. At each site we assessed soil macroinvertebrate density (18 taxonomic units) and the following ecosystem service indicators: soil and aboveground biomass carbon stock; water infiltration rate; aeration, drainage and water storage capacities based on pore-size distribution; soil chemical fertility; and soil aggregation. Significant covariation was observed between macrofauna communities and landscape metric data (co-inertia analysis: RV=0.30, p<0.01, Monte Carlo test) and between macrofauna communities and ecosystem service indicators (co-inertia analysis: RV=0.35, p<0.01, Monte Carlo test). Points located in pastures within 100m of forest had greater macrofauna density and diversity than those located in pastures with no forest within 100m (Wilcoxon rank sum test, p<0.01). Total macroinvertebrate density was significantly correlated with macroporosity (r2=0.42, p<0.01), as was the density of specific taxonomic groups: Chilopoda (r2=0.43, p<0.01), Isoptera (r2=0.30, p<0.01), Diplopoda (r2=0.31, p<0.01), and Formicidae (r2=0.13, p<0.01). Total macroinvertebrate density was also significantly correlated with available soil water (r2=0.38, p<0.01) as well as other soil-service indicators (but with r2<0.10). Results demonstrate that landscape dynamics and composition affect soil macrofauna communities, and that soil macrofauna density is significantly correlated with soil services in deforested Amazonia, indicating that soil macrofauna have an engineering and/or indicator function.

크리깅 기법을 이용한 단양군의 산림 탄소저장량 추정 - 지상부 바이오매스를 대상으로 -

본 연구에서는 크리깅 기법 중 가장 일반적으로 사용되고 있는 정규 크리깅(ordinary kriging)과 여러 보조 자료를 활용한 회귀 모델에 크리깅 기법을 결합한 형태인 회귀 크리깅(regression kriging)을 이용하여 지상부 바이오매스의 탄소저장량 추정을 시도하였다. 분석 결과 단양군의 산림 탄소저장량은 정규 크리깅의 경우 3,459,902 tonC, 회귀 크리깅의 경우 3,384,581 tonC로 추정되었으며 회귀 크리깅에 이용된 회귀 모델의 결정계수는 0.1033으로 나타났다. 표본점을 임상별로(활엽수림, 침엽수림&혼효림) 층화하여 회귀 크리깅을 수행한 경우에는 탄소저장량은 3,336,206 tonC로 가장 낮게 추정되었으며 회귀 모델의 결정 계수는 각각 0.35, 0.18로 표본점 전체를 이용했을 때보다 높은 값을 보였다. 각 기법의 교차 검증(cross validation) 결과 표본점 전체를 이용한 회귀 크리깅의 RMSE(22.32 ton/ha)가 가장 낮았으나 기법간의 차이(0.23 ton/ha)는 크지 않은 것으로 나타났다. The aim of this study is to estimate aboveground biomass carbon stocks using ordinary kriging(OK) which is the most commonly used type of kriging and regression kriging(RK) that combines a regression of the auxiliary variables with simple kriging. The analysis results shows that the forest carbon stock in Danyang is estimated at 3,459,902 tonC with OK and 3,384,581 tonC with RK in which the R-square value of the regression model is 0.1033. The result of RK conducted with sample plots stratified by forest type(deciduous, conifer and mixed) shows the lowest estimated value of 3,336,206 tonC and R-square value(0.35 and 0.18 respectively) is higher than that of when all sample plots used. The result of leave-one-out cross validation of each method indicates that RK with all sample plots reached the smallest root mean square error(RMSE) value(22.32 ton/ha) but the difference between the methods(0.23 ton/ha) is not significant.

Understanding the relationship between aboveground biomass and ALOS PALSAR data in the forests of Guinea-Bissau (West Africa)

Guinea-Bissau is one of the poorest countries in the world with a large proportion of its population living in rural areas. While industry is limited, over 70% of the territory is covered by forests, which can potentially be used to attract investment through forest-based projects that promote reductions in carbon emissions and sustainable management. These can be leveraged by producing accurate maps of forest aboveground biomass (AGB) at national level and by developing cost-effective mapping methods that allow reliable future updating for management and engagement in international mechanisms such as the United Nations (UN) Collaborative Program on Reducing Emissions from Deforestation and Forest Degradation (REDD) in developing countries.Using data from Japan's Advanced Land Observing Satellite (ALOS) Phased Array L-band Synthetic Aperture Radar (PALSAR), this study compared a semi-empirical and machine learning algorithm, with the latter based on bagging stochastic gradient boosting (BagSGB), for retrieving the AGB of woody vegetation thereby supporting estimation of national carbon stocks. AGB was estimated by using measurements of tree size collected from112 forest plots during two field campaigns (2007 and 2008) as input to published allometric equations.The BagSGB outperformed the semi-empirical algorithm, resulting in a coefficient of correlation (R) between observed and cross-validation predicted forest AGB values of 0.95 and in a root mean square error (RMSE) of 26.62Mgha−1. Furthermore, the BagSGB model produced also a measure of forest AGB prediction variability (coefficient of variation) on a pixel-by-pixel basis, with values ranging from 7 to 250% (mean=42%). An estimate of total forest AGB carbon stock of 96.93Mt C was obtained in this study for Guinea-Bissau, with a mean forest AGB value of 65.17Mgha−1. Although the mean error associated with this forest AGB map is still undesirably high, several issues were addressed. The heterogeneity of forest structural types, presence of palm trees, and dimension and type of field plots were identified as potential source of uncertainty that must be tackled in future studies. This study represents a step forward regarding the information currently available for Guinea-Bissau.

Carbon Stock of European Beech Forest; A Case at M. Pizzalto, Italy

In order to estimate carbon stock in above ground biomass (CS-AGB) of M. Pizzalto forest in the Central-Apennines in Italy, the moderate resolution imaging spectroradiometer (MODIS) vegetation index data (NDVI and EVI) were used in combination with field data. Biotic and abiotic parameters (slope angle, slope gradient, elevation, seasonal incoming solar radiation, length of growing season (LGS), soil type and forest management type) has been used in the modelling. NDVI and EVI values of field samples were extracted and used to estimate the LGS of beech forest for the six year period (2005-2010).Two management types, old-growth forest and young forest, showed average AGB and CS-AGB were 247 and 123 tons.ha-1 respectively in 2010 comparable to values for beech forests in the Apennines and Europe. LGS and management are the significant variables in a linear regression model for CS - AGB. Therefore, the forest authority can manage the young forest as sinks of carbon in agreement with the Kyoto protocol of the United Nations Framework Convention on Climate Change (UNFCCC).

EU-wide maps of growing stock and above-ground biomass in forests based on remote sensing and field measurements

The overall objective of this study was to combine national forest inventory data and remotely sensed data to produce pan-European maps on growing stock and above-ground woody biomass for the two species groups “broadleaves” and “conifers”. An automatic up-scaling approach making use of satellite remote sensing data and field measurement data was applied for EU-wide mapping of growing stock and above-ground biomass in forests. The approach is based on sampling and allows the direct combination of data with different measurement units such as forest inventory plot data and satellite remote sensing data. For the classification, data from the Moderate Resolution Imaging Spectroradiometer (MODIS) were used. Comprehensive field measurement data from national forest inventories for 98,979 locations from 16 countries were used for which tree species and growing stock estimates were available. The classification results were evaluated by comparison with regional estimates derived independently from the classification from national forest inventories. The validation at the regional level shows a high correlation between the classification results and the field based estimates with correlation coefficient r = 0.96 for coniferous, r = 0.94 for broadleaved and r = 0.97 for total growing stock per hectare. The mean absolute error of the estimations is 25 m 3/ha for coniferous, 20 m 3/ha for broadleaved and 25 m 3/ha for total growing stock per hectare. Biomass conversion and expansion factors were applied to convert the growing stock classification results to carbon stock in above-ground biomass. As results of the classification, coniferous and broadleaved growing stock as well as carbon stock of the above-ground biomass is mapped on a wall-to-wall basis with a spatial resolution of 500 m × 500 m per grid cell. The mapped area is 5 million km 2, of which 2 million km 2 are forests, and covers the whole European Union, the EFTA countries, the Balkans, Belarus, the Ukraine, Moldova, Armenia, Azerbaijan, Georgia and Turkey.

Temporal variations and distribution of carbon stocks in aboveground biomass of radiata pine and maritime pine pure stands under different silvicultural alternatives

In recent years there has been considerable interest in evaluating carbon budgets in forests because of the importance of these ecosystems as carbon sources and sinks. Quantifying forest net primary production (NPP) is critical to understanding the global carbon cycle because forests are responsible for a large portion of the total terrestrial NPP. The present study provides information about the temporal and spatial dynamics of carbon (C) stored in aboveground tree biomass in even-aged, pure stands of maritime pine and radiata pine managed under different silvicultural regimes in northwest Spain. Carbon budgets (storage calculations) for tree biomass provide useful information for characterizing forests as important C sinks and allow assessment of the potential effects of harvesting and logging residue management on forest C status. Stand dynamic growth models were used to estimate the amount of C accumulated in the remaining stand and the amount removed in thinning treatments throughout the whole rotation. For radiata pine, carbon sequestration in total aboveground tree biomass at stand level in the whole rotation (thinnings and clear-cutting at 30 years) ranged from 3.4 Mg ha −1 per year (the lowest initial stocking density, the worst site quality and 35% of thinning intensity) to 5.9 Mg ha −1 per year (the highest initial stocking density, the best site quality and 15% of thinning intensity). For maritime pine, the amount of tree biomass at stand level was significantly lower than in radiata pine stands, and mean annual carbon storage ranged from 2.3 to 4.6 Mg ha −1 per year for the same rotation length. The total aboveground and stem wood biomass C pools in these stands can be increased by increasing the rotation age and site quality and decreasing thinning intensity. Selection of the best site qualities, reduction of the thinning intensity and perhaps extension of the rotation length are therefore possible strategies for sustainable management of pine stands in Spain when the main objective is biomass production and C sequestration.

CREATING A VIRTUAL TROPICAL FOREST FROM THREE‐DIMENSIONAL AERIAL IMAGERY TO ESTIMATE CARBON STOCKS

Given the interest in implementing land‐use change and forestry projects for mitigating carbon dioxide emissions, there is potentially a large demand for a system to measure carbon stocks accurately and precisely in a cost‐effective manner. As terrestrial ecosystems tend to be heterogeneous, a large number of sample plots could be needed to attain the regulatory‐required levels of precision, thus resulting in a costly process. A potential way of reducing costs of measuring the carbon stocks of forests is to collect the key data remotely. We have designed a system (a multispectral three‐dimensional aerial digital imagery system, M3DADI) that collects high‐resolution overlapping stereo imagery (≤10 cm pixels) from which we can distinguish individual trees or shrubs. In essence, we created a virtual forest that we used to measure crown area and heights of all plant groups. We used this M3DADI system to estimate the carbon stocks in aboveground biomass for the pine savanna in the Rio Bravo Carbon Sequestration Pilot Project in Belize. Seventy‐seven plots were established on the images, and using a series of nested plots we digitized the crown area and heights of pine and broadleaf trees, palmettos, and shrubs. Based on standard destructive harvest techniques, we obtained highly significant allometric regression equations between biomass carbon per individual and crown area and height. Combining the image‐plot data with the allometric equations resulted in a mean carbon stock of 13.1 Mg/ha with a 95% confidence interval of 2.2 Mg C/ha or ±16% of the mean. The coefficient of variation was high for all vegetation types (range of 31–303%), reflecting the highly heterogeneous nature of the system. We estimated that 202 plots would need to be installed to achieve a 95% confidence interval of ±10% of the mean. We compared the cost‐effectiveness of the M3DADI approach with conventional field methods based on the total person‐hours needed by both approaches to collect the same set of data for 202 plots. We found that the conventional field approach took about three times more person‐hours than the M3DADI approach.

Pasture burning in Amazonia: Dynamics of residual biomass and the storage and release of aboveground carbon

Aboveground biomass in cattle pasture converted from tropical dense forest was studied both before and after reburning in Brazilian Amazonia. In a 7‐year‐old pasture studied in Apiaú, Roraima, the aboveground dry weight of biomass (live plus dead) exposed to burning consisted of 96.3 t ha−1 of original forest remains, 6.2 t ha−1 of secondary successional vegetation (woody invaders in the pasture), and 8.0 t ha−1 of pasture grass (carbon contents 48.2%, 45.4%, and 42.2%, respectively). In terms of carbon, burning efficiencies for these three categories were 13.2%, 66.7% and 94.6%, respectively. Net charcoal formation was 0.35 t C ha−1 or 0.63% of the carbon exposed to the reburn, while the total accumulated since conversion (including the initial burn) is estimated at 2.3 t ha−1 (1.82% of the predeforestation aboveground biomass carbon stock). The dynamics of the original forest remains were represented in simulations that included parameters such as charcoal formation, burning efficiency and carbon concentration in different biomass components. Releases from initial burning of the cleared forest (44.0 t C ha−1) plus releases over the course of the succeeding decade through combustion (12.5 t C ha−1) and decay (51.5 t C ha−1) total 92% of the original forest biomass carbon (126 t C ha−1). Of biomass carbon remaining after the initial burn (84.3 t C ha−1), 76.0% is released: 61.1% through decay and 14.9% through combustion in reburns, while 1.2% is net conversion to charcoal in the reburns. These results indicate an amount of charcoal accumulation that is smaller than some carbon calculations have assumed, therefore suggesting a greater impact on global warming from conversion of forest to pasture.

Comments and contents

Understanding changes in carbon sequestration due to land conversion is key for elucidating the true potential of biofuel landscapes to provide climate regulation ecosystem services. In this study, we focus on the two most promoted biofuel crops in southern Africa, Jatropha and sugarcane, to analyse the land use change effects and associated carbon impacts of growing biofuel crops in five study sites in Mozambique, Malawi and Swaziland. We found that, considering a 20-year cycle, carbon stocks in aboveground biomass are higher for sugarcane than for Jatropha. However, as soil organic carbon (SOC) is generally the main carbon pool, total carbon stocks (considering biomass and soil) will highly depend on SOC. Our results show that, in our study sites, sugarcane replaced land uses with low carbon stocks (low-density forest and agriculture), and as a result carbon gains occurred due to land use change. In the Jatropha projects, carbon gains are observed in the smallholder scheme as agricultural land was converted to Jatropha, but carbon debts occurred in the Jatropha plantation as high-density forest was cleared to grow this feedstock. Finally we show that, if a plantation of sugarcane or Jatropha is envisioned to be located in the studied regions, more forested land could potentially be converted into sugarcane (30–44% of forest) than into Jatropha (24–32%), without creating carbon debts due to land conversion. To our knowledge, this is the first comparative study of the carbon impacts of land use change of the main biofuel crops in southern Africa.