Aboveground Biomass Loss Research Articles

Loss of aboveground forest biomass and landscape biomass variability in Missouri, US

Disturbance regimes and forests have changed over time in the eastern United States. We examined effects of historical disturbance (circa 1813 to 1850) compared to current disturbance (circa 2004 to 2008) on aboveground, live tree biomass (for trees with diameters ≥13cm) and landscape variation of biomass in forests of the Ozarks and Plains landscapes in Missouri, USA. We simulated 10,000 one-hectare plots using random diameters generated from parameters of diameter distributions limited to diameters ≥13cm and random densities generated from density estimates. Area-weighted mean biomass density (Mg/ha) for historical forests averaged 116Mg/ha, ranging from 54Mg/ha to 357Mg/ha by small scale ecological subsections within Missouri landscapes. Area-weighted mean biomass density for current forests averaged 82Mg/ha, ranging from 66Mg/ha to 144Mg/ha by ecological subsection for currently forested land. Biomass density of current forest was greater than historical biomass density for only 2 of 23 ecological subsections. Current carbon sequestration of 292TgC on 7 million ha of forested land is less than half of the estimated historical total carbon sequestration of 693TgC on 12 million ha. Cumulative tree cutting disturbances over time have produced forests that have less aboveground tree biomass and are uniform in biomass compared to estimates of historical biomass, which varied across Missouri landscapes. With continued relatively low rates of forest disturbance, current biomass per ha will likely increase to historical levels as the most competitive trees become larger in size and mean number of trees per ha decreases due to competition and self-thinning. Restoration of large diameter structure and forested extent of upland woodlands and floodplain forests could fulfill multiple conservation objectives, including carbon sequestration.

Impacts of tropical selective logging on carbon storage and tree species richness: A meta-analysis

Over 400 million hectares of tropical forest are currently designated as logging concessions. This practice is an important source of timber, but there are concerns about its long-term sustainability and impacts on biodiversity and carbon storage. However, logging impacts vary widely, making generalisation and, consequently, policy implementation, difficult. Recent syntheses of animal biodiversity have indicated that differences in logging intensity – the volume of wood removed ha−1 – might help to explain some of these disparities. In addition, it has widely been assumed that reduced impact logging (RIL) might minimise some of the negative effects of logging; though in practice, this has rarely been tested. To test the hypothesis that RIL reduces negative impacts of selective logging once intensity is controlled for, we used meta-analyses of selective logging impact studies, focusing specifically on (1) residual tree damage, (2) aboveground biomass and (3) tree species richness. Our results indicate that RIL appears to reduce residual tree damage when compared to conventional methods. However, changes in aboveground biomass were negatively related to logging intensity. Any effect of RIL, independent of logging intensity, was difficult to discern since it was carried out at relatively low intensities. Tree richness appeared to increase at low intensities but decreased at higher intensities and any effect of RIL was difficult to detect. Our results tentatively support the hypothesis that RIL reduces the negative impacts of logging on tree damage, but do not support suggestions that RIL reduces loss of aboveground biomass or tree species richness. However, this lack of support may be a result of the relative paucity of data on the topic. Based on our results, we suggest that better evidence is needed to assess the differences between the impacts of RIL and conventional logging. Studies that consider plot-level differences in logging intensity are required to fill this knowledge gap. In addition, there must be clarification of whether RIL is an inherently low intensity practice so that this can be factored into management.

The fate of Amazonian ecosystems over the coming century arising from changes in climate, atmospheric CO2, and land use.

There is considerable interest in understanding the fate of the Amazon over the coming century in the face of climate change, rising atmospheric CO2 levels, ongoing land transformation, and changing fire regimes within the region. In this analysis, we explore the fate of Amazonian ecosystems under the combined impact of these four environmental forcings using three terrestrial biosphere models (ED2, IBIS, and JULES) forced by three bias-corrected IPCC AR4 climate projections (PCM1, CCSM3, and HadCM3) under two land-use change scenarios. We assess the relative roles of climate change, CO2 fertilization, land-use change, and fire in driving the projected changes in Amazonian biomass and forest extent. Our results indicate that the impacts of climate change are primarily determined by the direction and severity of projected changes in regional precipitation: under the driest climate projection, climate change alone is predicted to reduce Amazonian forest cover by an average of 14%. However, the models predict that CO2 fertilization will enhance vegetation productivity and alleviate climate-induced increases in plant water stress, and, as a result, sustain high biomass forests, even under the driest climate scenario. Land-use change and climate-driven changes in fire frequency are predicted to cause additional aboveground biomass loss and reductions in forest extent. The relative impact of land use and fire dynamics compared to climate and CO2 impacts varies considerably, depending on both the climate and land-use scenario, and on the terrestrial biosphere model used, highlighting the importance of improved quantitative understanding of all four factors - climate change, CO2 fertilization effects, fire, and land use - to the fate of the Amazon over the coming century.

Limiting factors for nomadic pastoralism in Mongolian steppe: A hydrologic perspective

In this study, limiting factors for continuing nomadic pastoralism in steppe areas were studied based on a hydrologic perspective. Two small watersheds in central Mongolia were selected for an assessment of water balance and hydrologic processes. We determined that the majority of annual precipitation, ∼88–96 mm, was lost by evaporation (82%) while only a small proportion went to groundwater discharge, surface runoff, and groundwater consumption by nomadic activities. The soil column was found to absorb large fluctuations in precipitation although its connection to groundwater was very weak. Groundwater recharge was, therefore, very small and occurred only rarely during heavy rainfall events in valley bottoms. However, current water storage in shallow groundwater was determined to be quite sufficient for continuing nomadic pastoralism when compared to the drinking water requirements of livestock. The main limiting factors identified were a temporal lack of feed to animals due to a loss of aboveground biomass resulting from soil moisture shortages during drought conditions, and a decline in the number and maintenance level of the traditional well network that, due to access to shallow groundwater, has allowed herders to migrate to areas with better conditions in remote Mongolian steppe.

Genetic versus environmental contributions to variation in seedling resprouting in Nothofagus obliqua

Resprouting is an almost universal functional trait in temperate angiosperms and confers persistence at an individual level after the loss of above-ground biomass. The importance of genetic versus environmental sources of intraspecific variation in resprouting traits is largely unknown. We conducted two genetic field trials, 400 m apart in altitude, in order to sequentially assess seedling resprouting in four environmentally contrasting Argentinean populations of Nothofagus obliqua Mirb. (Oerst). We also performed one nursery test to determine whether populations differed in early root/shoot biomass partition, a key trade-off affecting resprouting. Initial resprouting vigour and final survival were higher in our warmer test site, located 300 m below the core range of the species. The main contrasts between populations were found for pre-clipping seedling size and resprouting profusion, the latter trait showing a clear trade-off with resprouting vigour. Site × population interactions were due mainly to the behaviour of the highest altitude population, suggesting its divergent adaptive trajectory and higher plasticity for resprouting traits. Within populations, trait heritability was low, in general. Episodic frost, which may limit resprouting vigour and final success, had a lower incidence in the altitudinal and xeric limit populations. Overall, our work revealed genetic variation between populations of N. obliqua in traits that determine the success of seedling resprouting, probably associated with divergent selection. Low trait heritability suggests limited in situ micro-evolutionary capacities for resprouting traits under ongoing climate warming; phenotypic plasticity may play an important role in population persistence at the low positions of the elevation gradients N. obliqua currently inhabits.

Forest response to increased disturbance in the central Amazon and comparison to western Amazonian forests

Abstract. Uncertainties surrounding vegetation response to increased disturbance rates associated with climate change remains a major global change issue for Amazonian forests. Additionally, turnover rates computed as the average of mortality and recruitment rates in the western Amazon basin are doubled when compared to the central Amazon, and notable gradients currently exist in specific wood density and aboveground biomass (AGB) between these two regions. This study investigates the extent to which the variation in disturbance regimes contributes to these regional gradients. To address this issue, we evaluated disturbance–recovery processes in a central Amazonian forest under two scenarios of increased disturbance rates using first ZELIG-TROP, a dynamic vegetation gap model which we calibrated using long-term inventory data, and second using the Community Land Model (CLM), a global land surface model that is part of the Community Earth System Model (CESM). Upon doubling the mortality rate in the central Amazon to mirror the natural disturbance regime in the western Amazon of ∼2% mortality, the two regions continued to differ in multiple forest processes. With the inclusion of elevated natural disturbances, at steady state, AGB significantly decreased by 41.9% with no significant difference between modeled AGB and empirical AGB from the western Amazon data sets (104 vs. 107 Mg C ha−1, respectively). However, different processes were responsible for the reductions in AGB between the models and empirical data set. The empirical data set suggests that a decrease in wood density is a driver leading to the reduction in AGB. While decreased stand basal area was the driver of AGB loss in ZELIG-TROP, a forest attribute that does not significantly vary across the Amazon Basin. Further comparisons found that stem density, specific wood density, and basal area growth rates differed between the two Amazonian regions. Last, to help quantify the impacts of increased disturbances on the climate and earth system, we evaluated the fidelity of tree mortality and disturbance in CLM. Similar to ZELIG-TROP, CLM predicted a net carbon loss of 49.9%, with an insignificant effect on aboveground net primary productivity (ANPP). Decreased leaf area index (LAI) was the driver of AGB loss in CLM, another forest attribute that does not significantly vary across the Amazon Basin, and the temporal variability in carbon stock and fluxes was not replicated in CLM. Our results suggest that (1) the variability between regions cannot be entirely explained by the variability in disturbance regime, but rather potentially sensitive to intrinsic environmental factors; or (2) the models are not accurately simulating all tropical forest characteristics in response to increased disturbances.

Have ozone effects on carbon sequestration been overestimated? A new biomass response function for wheat

Abstract. Elevated levels of tropospheric ozone can significantly impair the growth of crops. The reduced removal of CO2 by plants leads to higher atmospheric concentrations of CO2, enhancing radiative forcing. Ozone effects on economic yield, e.g. the grain yield of wheat (Triticum aestivum L.), are currently used to model effects on radiative forcing. However, changes in grain yield do not necessarily reflect changes in total biomass. Based on an analysis of 22 ozone exposure experiments with field-grown wheat, we investigated whether the use of effects on grain yield as a proxy for effects on biomass under- or overestimates effects on biomass. First, we confirmed that effects on partitioning and biomass loss are both of significant importance for wheat yield loss. Then we derived ozone dose response functions for biomass loss and for harvest index (the proportion of above-ground biomass converted to grain) based on 12 experiments and recently developed ozone uptake modelling for wheat. Finally, we used a European-scale chemical transport model (EMEP MSC-West) to assess the effect of ozone on biomass (−9%) and grain yield (−14%) loss over Europe. Based on yield data per grid square, we estimated above-ground biomass losses due to ozone in 2000 in Europe, totalling 22.2 million tonnes. Incorrectly applying the grain yield response function to model effects on biomass instead of the biomass response function of this paper would have indicated total above-ground biomass losses totalling 38.1 million (i.e. overestimating effects by 15.9 million tonnes). A key conclusion from our study is that future assessments of ozone-induced loss of agroecosystem carbon storage should use response functions for biomass, such as that provided in this paper, not grain yield, to avoid overestimation of the indirect radiative forcing from ozone effects on crop biomass accumulation.

Size dependency of post-disturbance recovery of multi-stemmed resprouting trees.

In frequently burned ecosystems, many plants persist by repeated resprouting from basal or belowground buds. This strategy requires that plants reach a balance between biomass loss and recovery, which depends on the shape of the relationship between pre- and post-fire size. Previous analyses of this relationship, however, have focused on the size of the largest stem, which ignores the importance of the multi-stem growth habit that is common in pyrogenic ecosystems. We hypothesized that the presence of multiple stems causes a substantial shift in the relationship between pre- and post-fire size and in the relationship between pre-fire size and size recovery. We measured the height and basal diameter, then calculated volume and biomass, of all stems of six tree species before and nine months after complete removal of aboveground biomass via coppicing. The number of resprouts was correlated with the original number of stems for four species. For all species, the relationship between pre-coppicing and resprout size fit a positive curvilinear function, and the shape of this curve did not differ for maximum and total stem size. Smaller individuals recovered a larger proportion of their pre-coppicing size than larger individuals, but the shape of the size recovery curves were the same regardless of whether the analysis was performed with all stems or only the largest stem. Our results indicate that measuring only the largest stem of multi-stemmed individuals is sufficient to assess the ability of individuals to recover after complete loss of aboveground biomass and persist under frequent burning.

Vegetation, land surface brightness, and temperature dynamics after aspen forest die‐off

AbstractForest dynamics following drought‐induced tree mortality can affect regional climate through biophysical surface properties. These dynamics have not been well quantified, particularly at the regional scale, and are a large uncertainty in ecosystem‐climate feedback. We investigated regional biophysical characteristics through time (1995–2011) in drought‐impacted (2001–2003), trembling aspen (Populus tremuloides Michx.) forests by utilizing Landsat time series green and brown vegetation cover, surface brightness (total shortwave albedo), and daytime land surface temperature. We quantified the temporal dynamics and postdrought recovery of these characteristics for aspen forests experiencing severe drought‐induced mortality in the San Juan National Forest in southwestern Colorado, USA. We partitioned forests into three categories from healthy to severe mortality (Healthy, Intermediate, and Die‐off) by referring to field observations of aspen canopy mortality and live aboveground biomass losses. The vegetation cover of die‐off areas in 2011 (26.9% of the aspen forest) was significantly different compared to predrought conditions (decrease of 7.4% of the green vegetation cover and increase of 12.1% of the brown vegetation cover compared to 1999). The surface brightness of the study region 9 years after drought however was comparable to predrought estimates (12.7–13.7%). Postdrought brightness was potentially influenced by understory shrubs, since they became the top layer green canopies in disturbed sites from a satellite's point of view. Satellite evidence also showed that the differences of land surface temperature among the three groups increased substantially (≥45%) after drought, possibly due to the reduction of plant evapotranspiration in the Intermediate and Die‐off sites. Our results suggest that the mortality‐affected systems have not recovered in terms of the surface biophysical properties. We also find that the temporal dynamics of vegetation cover holds great potential for assessing propensity of subsequent mortality during drought itself, which could provide effective monitoring and potentially a much needed “early warning” of drought‐induced tree mortality.

Size and frequency of natural forest disturbances and the Amazon forest carbon balance

Forest inventory studies in the Amazon indicate a large terrestrial carbon sink. However, field plots may fail to represent forest mortality processes at landscape-scales of tropical forests. Here we characterize the frequency distribution of disturbance events in natural forests from 0.01 ha to 2,651 ha size throughout Amazonia using a novel combination of forest inventory, airborne lidar and satellite remote sensing data. We find that small-scale mortality events are responsible for aboveground biomass losses of ~1.7 Pg C y−1 over the entire Amazon region. We also find that intermediate-scale disturbances account for losses of ~0.2 Pg C y−1, and that the largest-scale disturbances as a result of blow-downs only account for losses of ~0.004 Pg C y−1. Simulation of growth and mortality indicates that even when all carbon losses from intermediate and large-scale disturbances are considered, these are outweighed by the net biomass accumulation by tree growth, supporting the inference of an Amazon carbon sink.

Assembly patterns of plant functional traits in alpine meadow under disturbances by mowing and fertilization

Aims Fully understanding the assembly patterns of plant functional traits in plant communities is a big challenge in the study of community ecology. The assembly patterns in alpline meadow and driving factors are still poorly known. In this study, experiments with different mowing intensities and various treatments of fertilization were conducted in alpline meadow for the purpose of improving the understanding of the assembly patterns of plant functional traits in plant community. Methods Data on functional diversity of 10 traits for 33 species from 108 quadrats (with varying combinations of mowing and fertilization) were analyzed by randomizations tests, ANCOVA and regression analysis, respectively, for the trait convergence/divergence. Important findings None of the traits studied showed consistently significant convergence or divergence pattern in integral gradients of fertilization and mowing treatments, while the ratios of quadrats assembled under deterministic and stochastic processes were 82.7% and 17.3%, respectively. Among the functional traits tested, growth form, life cycle, aboveground dry mass per plant, leaf area and leaf dry mass showed a stochastic pattern of assembly, but they were not affected by variations in mowing treatments and community characteristics (i.e. aboveground net primary productivity, biomass loss and vegetation height). Convergence or divergence patterns were shown in traits such as plant inclination, reproductive modes, nitrogen fixation, plant height and specific leaf area, which were affected by variations in mowing treatments and community characteristics. Among them, assembly patterns of plant inclination and specific leaf area were only affected by community characteristics, while nitrogen fixation, reproductive modes and plant height were affected by both mowing treatments and community characteristics. Moreover, the patterns of assembly varied by traits. Aboveground net primary productivity and biomass 吕美强等: 刈割与施肥干扰下高寒草甸植物功能性状的构建模式 917 doi: 10.3724/SP.J.1258.2014.00086 loss well explained variations in the assembly pattern of plant functional traits. Mowing and fertilization showed the reversed effects on the assembly pattern of plant height, while no significant interaction was found between mowing and fertilization. The results suggested that there were different assembly patterns of functional traits in the community: stochastic pattern of assembly was the primary, and the deterministic pattern was secondary. Deterministic pattern was trait-dependent and correlated with variations in mowing treatments and community characteristics. The balancing effect of opposite selection forces, on the other hand, could lead to stochastic assembly patterns in plant functional traits.

Carbon dynamics and stability between native Masson pine and exotic slash pine plantations in subtropical China

Afforestation and ecological restoration have often been carried out with fast-growing exotic tree species because of their high apparent growth and yield. Moreover, fast-growing forest plantations have become an important component of mitigation measures to offset greenhouse gas emissions. However, information on the long-term performance of exotic and fast-growing species is often lacking especially with respect to their vulnerability to disturbance compared to native species. We compared carbon (C) storage and C accumulation rates in vegetation (above- and belowground) and soil in 21-year-old exotic slash pine (Pinus elliottii Engelm.) and native Masson pine (Pinus massoniana Lamb.) plantations, as well as their responses to a severe ice storm in 2008. Our results showed that mean C storage was 116.77 ± 7.49 t C ha−1 in slash pine plantation and 117.89 ± 8.27 t C ha−1 in Masson pine plantation. The aboveground C increased at a rate of 2.18 t C ha−1 year−1 in Masson pine and 2.23 t C ha−1 year−1 in slash pine plantation, and there was no significant difference in C storage accumulation between the two plantation types. However, we observed significant differences in ice storm damage with nearly 7.5 % of aboveground biomass loss in slash pine plantation compared with only 0.3 % loss in Masson pine plantation. Our findings indicated that the native pine species was more resistant to ice storm because of their adaptive biological traits (tree shape, crown structure, and leaf surface area). Overall, the native pine species might be a safer choice for both afforestation and ecological restoration in our study region.

Potential above-ground biomass losses from severe soil rutting during wet weather timber harvests of coastal plain loblolly pine (Pinus taeda) plantations mitigated by mechanical site preparation

Extensive areas of pine forests on wet mineral soils in the southeastern United States are harvested during nearly saturated soil conditions. Harvest trafficking during wet conditions can alter soil physical properties related to forest productivity, however mechanical site preparation can potentially ameliorate harvest induced trafficking disturbances. In 1996 three loblolly pine (Pinus taeda) stands were harvested in the coastal plain during Wet and Dry conditions (30–40% vs 10–15% volumetric soil moisture). Five treatment combinations of harvest conditions-site preparation (Wet-Flat, Dry-Flat, Wet-Bed, Dry-Bed, Wet-Mole Plow) were operationally replicated three times. Study objectives were to quantify treatment effects on above-ground productivity 16years post treatment. After 16years, above-ground biomass was greater (p-value⩽0.05) in the intensive Wet-Mole Plow treatment (402.9Mgha−1, ±6.72Mgha−1). Wet-Flat (372.7Mgha−1± 6.59Mgha−1), Dry-Flat (368.6Mgha−1, ±7.14Mgha−1), and Wet-Bed (368Mgha−1±6.8Mgha−1) produced significantly less biomass than Wet-Mole Plow, but were not significantly different from each other. Dry-Bed produced the least above-ground biomass (319.3Mgha−1±6.76Mgha−1). Wet treatments were severely disturbed, yet comparisons of Wet and Dry site preparation indicated few long-term productivity effects. Exact mechanisms of recovery were likely influenced by inherent site fertility, mixed clay mineralogy, and drought during stand establishment. Overall, this research indicates that above-ground productivity was increased by drainage/aeration effects of Wet-Mole Plow and wet weather harvesting and severe soil disturbance had minimal long-term effects on aboveground productivity of loblolly pine.

Detection of large above-ground biomass variability in lowland forest ecosystems by airborne LiDAR

Abstract. Quantification of tropical forest above-ground biomass (AGB) over large areas as input for Reduced Emissions from Deforestation and forest Degradation (REDD+) projects and climate change models is challenging. This is the first study which attempts to estimate AGB and its variability across large areas of tropical lowland forests in Central Kalimantan (Indonesia) through correlating airborne light detection and ranging (LiDAR) to forest inventory data. Two LiDAR height metrics were analysed, and regression models could be improved through the use of LiDAR point densities as input (R2 = 0.88; n = 52). Surveying with a LiDAR point density per square metre of about 4 resulted in the best cost / benefit ratio. We estimated AGB for 600 km of LiDAR tracks and showed that there exists a considerable variability of up to 140% within the same forest type due to varying environmental conditions. Impact from logging operations and the associated AGB losses dating back more than 10 yr could be assessed by LiDAR but not by multispectral satellite imagery. Comparison with a Landsat classification for a 1 million ha study area where AGB values were based on site-specific field inventory data, regional literature estimates, and default values by the Intergovernmental Panel on Climate Change (IPCC) showed an overestimation of 43%, 102%, and 137%, respectively. The results show that AGB overestimation may lead to wrong greenhouse gas (GHG) emission estimates due to deforestation in climate models. For REDD+ projects this leads to inaccurate carbon stock estimates and consequently to significantly wrong REDD+ based compensation payments.

Quantifying Dynamics in Tropical Peat Swamp Forest Biomass with Multi-Temporal LiDAR Datasets

Tropical peat swamp forests in Indonesia store huge amounts of carbon and are responsible for enormous carbon emissions every year due to forest degradation and deforestation. These forest areas are in the focus of REDD+ (reducing emissions from deforestation, forest degradation, and the role of conservation, sustainable management of forests and enhancement of forest carbon stocks) projects, which require an accurate monitoring of their carbon stocks or aboveground biomass (AGB). Our study objective was to evaluate multi-temporal LiDAR measurements of a tropical forested peatland area in Central Kalimantan on Borneo. Canopy height and AGB dynamics were quantified with a special focus on unaffected, selective logged and burned forests. More than 11,000 ha were surveyed with airborne LiDAR in 2007 and 2011. In a first step, the comparability of these datasets was examined and canopy height models were created. Novel AGB regression models were developed on the basis of field inventory measurements and LiDAR derived height histograms for 2007 (r2 = 0.77, n = 79) and 2011 (r2 = 0.81, n = 53), taking the different point densities into account. Changes in peat swamp forests were identified by analyzing multispectral imagery. Unaffected forests accumulated on average 20 t/ha AGB with a canopy height increase of 2.3 m over the four year time period. Selective logged forests experienced an average AGB loss of 55 t/ha within 30 m and 42 t/ha within 50 m of detected logging trails, although the mean canopy height increased by 0.5 m and 1.0 m, respectively. Burned forests lost 92% of the initial biomass. These results demonstrate the great potential of repetitive airborne LiDAR surveys to precisely quantify even small scale AGB and canopy height dynamics in remote tropical forests, thereby featuring the needs of REDD+.

Forecasting deforestation and carbon emissions in tropical developing countries facing demographic expansion: a case study in Madagascar.

Anthropogenic deforestation in tropical countries is responsible for a significant part of global carbon dioxide emissions in the atmosphere. To plan efficient climate change mitigation programs (such as REDD+, Reducing Emissions from Deforestation and forest Degradation), reliable forecasts of deforestation and carbon dioxide emissions are necessary. Although population density has been recognized as a key factor in tropical deforestation, current methods of prediction do not allow the population explosion that is occurring in many tropical developing countries to be taken into account. Here, we propose an innovative approach using novel computational and statistical tools, including R/GRASS scripts and the new phcfM R package, to model the intensity and location of deforestation including the effect of population density. We used the model to forecast anthropogenic deforestation and carbon dioxide emissions in five large study areas in the humid and spiny-dry forests of Madagascar. Using our approach, we were able to demonstrate that the current rapid population growth in Madagascar (+3.39% per year) will significantly increase the intensity of deforestation by 2030 (up to +1.17% per year in densely populated areas). We estimated the carbon dioxide emissions associated with the loss of aboveground biomass to be of 2.24 and 0.26 tons per hectare and per year in the humid and spiny-dry forest, respectively. Our models showed better predictive ability than previous deforestation models (the figure of merit ranged from 10 to 23). We recommend this approach to reduce the uncertainty associated with deforestation forecasts. We also underline the risk of an increase in the speed of deforestation in the short term in tropical developing countries undergoing rapid population expansion.

Forest degradation and recovery in a miombo woodland landscape in Zambia: 22 years of observations on permanent sample plots

Because dry tropical forests cover 40% of tropical forest area and contain considerable biomass and carbon stocks, deforestation and forest degradation of these forests have global significance. However, in most developing countries with dry forests there is no quantitative information on past trends of forest degradation so that the development of historical reference levels is virtually impossible. This study assessed impacts of forest practices on forest degradation from 1990 to 2012 using data from destructive tree sampling and permanent sample plots in a miombo woodland landscape in central Zambia. Aboveground live wood biomass was estimated using allometric equations developed from 113 felled trees. Resprouting was a major source of regeneration on clear-cut subplots and the rate of aboveground wood biomass accumulation was much higher on re-growth sites than on old-growth sites. Changes in aboveground live wood biomass on uncut subplots were linked to biomass loss due to fire, harvesting and conversion to crop cultivation on the one hand and biomass increment due to growth of remaining trees on the other hand. Forest degradation was estimated to cause aboveground wood biomass loss of 0.3tha−1year−1 on the least impacted site to 4.0tha−1year−1 on the most impacted site. Control of fire and harvesting for charcoal production is recommended if miombo woodland is to be managed for biomass and carbon storage and sequestration. The study also found that negative trends in woody biomass accumulation rate and standing stocks are good indicators of forest degradation while positive trends in species diversity indices and standing wood biomass are useful indicators of forest recovery. However, the application of these indicators requires repeated inventories at permanent sample plots to establish reference levels against which changes in these indicator variables can be compared.

Resprouting as a key functional trait: how buds, protection and resources drive persistence after fire

Resprouting as a response to disturbance is now widely recognized as a key functional trait among woody plants and as the basis for the persistence niche. However, the underlying mechanisms that define resprouting responses to disturbance are poorly conceptualized. Resprouting ability is constrained by the interaction of the disturbance regime that depletes the buds and resources needed to fund resprouting, and the environment that drives growth and resource allocation. We develop a buds-protection-resources (BPR) framework for understanding resprouting in fire-prone ecosystems, based on bud bank location, bud protection, and how buds are resourced. Using this framework we go beyond earlier emphases on basal resprouting and highlight the importance of apical, epicormic and below-ground resprouting to the persistence niche. The BPR framework provides insights into: resprouting typologies that include both fire resisters (i.e. survive fire but do not resprout) and fire resprouters; the methods by which buds escape fire effects, such as thick bark; and the predictability of community assembly of resprouting types in relation to site productivity, disturbance regime and competition. Furthermore, predicting the consequences of global change is enhanced by the BPR framework because it potentially forecasts the retention or loss of above-ground biomass.

Above ground biomass estimation across forest types at different degradation levels in Central Kalimantan using LiDAR data

The quantification of tropical forest carbon stocks is a key challenge in creating a basic methodology for REDD (reducing emissions from deforestation and degradation in developing countries) projects. Small-footprint LiDAR (light detection and ranging) systems have proven to successfully correlate to above ground biomass (AGB) estimates in boreal and temperate forests. Their applicability to two different tropical rainforest types (lowland dipterocarp and peat swamp forest) in Central Kalimantan, Indonesia, was tested by developing multiple regression models at plot level using full waveform LiDAR point cloud characteristics. Forest inventory data is barely available for Central Kalimantan's forests. In order to sample a high number of field plots the angle count method was applied which allows fast sampling. More laborious fixed-area plots (three nests of circular shape) were used as a control and approved the use of the angle count method. AGB values, calculated by using existing allometric models, were in the range of 15–547Mgha−1 depending on forest type, degradation level and the model used for calculation. As expected, logging resulted in significant AGB losses in all forest types. AGB-prediction models were established for each forest type using statistical values of the LiDAR point clouds and the forest inventory plots. These regression models were then applied to six LiDAR tracks (altogether with a size of 5241ha) covering unlogged, logged and burned lowland dipterocarp and peat swamp forest. The regression analysis showed that the 45th and 65th percentiles and the standard error of the mean explain 83% of the variation in lowland dipterocarp forest plots (RMSE=21.37%). The best model for peat swamp forest could only explain 32% of the AGB variation (RMSE=41.02%). Taking both forest types together explained 71% (RMSE=33.85%). Calculating AGB for whole LiDAR tracks demonstrated the ability of this approach to quantify not only deforestation but also especially forest degradation and its spatial variability in terms of biomass change in different forest ecosystems using LiDAR transects. Concluding it can be stated that the combined approach of extensive field sampling and LiDAR point cloud analysis have high potential to significantly improve current estimates of carbon stocks across different forest types and degradation levels and its spatial variation in highly inaccessible tropical rainforests in the framework of REDD.

The effect of cassava-based bioethanol production on above-ground carbon stocks: A case study from Southern Mali

Increasing energy use and the need to mitigate climate change make production of liquid biofuels a high priority. Farmers respond worldwide to this increasing demand by converting forests and grassland into biofuel crops, but whether biofuels offer carbon savings depends on the carbon emissions that occur when land use is changed to biofuel crops. This paper reports the results of a study on cassava-based bioethanol production undertaken in the Sikasso region in Southern Mali. The paper outlines the estimated impacts on above-ground carbon stocks when land use is changed to increase cassava production. The results show that expansion of cassava production for bioethanol will most likely lead to the conversion of fallow areas to cassava. A land use change from fallow to cassava creates a reduction in the above-ground carbon stocks in the order of 4–13MgCha−1, depending on (a) the age of the fallow, (b) the allometric equation used and (c) whether all trees are removed or the larger, useful trees are preserved. This ‘carbon debt’ associated with the above-ground biomass loss would take 8–25 years to repay if fossil fuels are replaced with cassava-based bioethanol.