The conservation value of oil palm plantation estates, smallholdings and logged peat swamp forest for birds

The expansion of industrial oil palm cultivation threatens tropical biodiversity globally, especially in developing countries. Driven by plans to generate economic revenue, large-scale plantations are emerging in Southeast Asia, Africa and Brazilian Amazon. However, the ecological impacts of the sector are poorly studied with respect to oil palm management system, and recommended conservation measures are based on limited data. We studied avifauna in oil palm landscapes in Peninsular Malaysia under different management systems (large plantation estates versus smallholdings) and age classes (uniform age versus mixed-age stands). We sampled 41 large plantation estates and 14 smallholdings, as well as 20 sites in an extensively logged peat swamp forest, the type of natural forest prior to conversion to oil palms. Compared with logged peat swamp forest, our results showed that forest conversion to oil palm cultivation may have eliminated 48-60% of bird species. We also found: (i) plantation estates and smallholdings supported similar bird assemblages but the latter supported significantly more species (P = 0.007); and (ii) despite reduced species richness in oil palm landscapes, we found high abundance of some individual bird species in specific types of stands including some forest, migratory, and wetland species. Conversion of natural forest to oil palm landscapes should not occur in the future through clearing of primary or secondary native forests. To complement conventional conservation approaches (e.g. the establishment of protected areas) in palm oil-producing countries, existing plantation estates and smallholdings should be managed in ways to promote improved conservation outcomes, although oil palm landscapes maintained a fraction of the original forest biodiversity. Managing habitat heterogeneity at both a local and a landscape-level is highly recommended in oil palm landscapes to maintain and/or enhance avian biodiversity.     

Estimation of biomass and carbon stocks in plants,soil and forest floor in different tropical forests

An accurate characterization of tree carbon (TC), forest floor carbon (FFC) and soil organic carbon (SOC) in tropical forest plantations is important to estimate their contribution to global carbon stocks. This information, however, is poor and fragmented. Carbon contents were assessed in patula pine (Pinus patula) and teak (Tectona grandis) stands in tropical forest plantations of different development stages in combination with inventory assessments and soil survey information. Growth models were used to associate TOC to tree normal diameter (D) with average basal area and total tree height (H_T), with D and H_T parameters that can be used in 6–26 years old patula pine and teak in commercial tropical forests as indicators of carbon stocks. The information was obtained from individual trees in different development stages in 54 patula pine plots and 42 teak plots. The obtained TC was 99.6 Mg ha⁻¹ in patula pine and 85.7 Mg ha⁻¹ in teak forests. FFC was 2.3 and 1.2 Mg ha⁻¹, SOC in the surface layer (0–25 cm) was 92.6 and 35.8 Mg ha⁻¹, 76.1 and 19 Mg ha⁻¹ in deep layers (25–50 cm) in patula pine and teak, respectively. Carbon storage in trees was similar between patula pine and teak plantations, but patula pine had higher levels of forest floor carbon and soil organic carbon. Carbon storage in trees represents 37 and 60% of the total carbon content in patula pine and teak plantations, respectively. Even so, the remaining percentage corresponds to SOC, whereas FFC content is less than 1%. In summary, differences in carbon stocks between patula pine and teak trees were not significant, but the distribution of carbon differed between the plantation types. The low FFC does not explain the SOC stocks; however, current variability of SOC stocks could be related to variation in land use history.     

Soil seed banks in four 22-year-old plantations in South China: Implications for restoration

To better understand the potentials of the soil seed banks in facilitating succession towards a more natural forest of native tree species, we quantified the size and composition of the soil seed banks in established plantations in South China. The seed banks were from four typical 22-year-old plantations, i.e., legume, mixed-conifer, mixed-native, and Eucalyptus overstory species. Species diversity in the seed banks was low, and the vegetation species differed from those found in the seed bank in each plantation. A total of 1211 seedlings belonging to eight species emerged in a seedling germination assay, among which Cyrtococcum patens was most abundant. All species detected were shrubs and herbs, and no viable indigenous tree seeds were found in soil samples. Size and species composition of the seed banks might be related to the overstory species compositions of the established plantations. The seed bank density in soils was highest in the mixed-conifer plantation followed by Eucalyptus, mixed-native, and legume plantations. Species richness among the seed banks of plantations was ranked as follows: Eucalyptus > mixed-conifer > mixed-native = legume. The results indicated that the soil seed banks of the current plantations are ineffective in regenerating the former communities after human disturbances. Particularly, the absence of indigenous tree species seeds in the seed banks would limit regeneration and probably contribute to arrested succession at the pioneer community stage. It would appear from these data that the soil seed banks under the current plantations should not be considered as a useful tool leading the succession to more natural stages. Introduction of target indigenous species by artificial seeding or seedling planting should be considered to accelerate forest regeneration.     

Robust relationships for simple plantation growth models based on sparse data

Three equations predicting height H = β₁(t − 0.5)^0.5, diameter D = β₂(H − 1.3)/ln N, and mortality dN/N = −2(G/G_max)³dD/D from plantation age (t), stocking (N) and basal area (G) can be calibrated with few data (even a single observation) for plantations in which re-measured data and growth models are unavailable. Despite having only three parameters to be estimated, these equations extrapolate reliably and allow objective forecasts of future plantation growth performance that may serve as useful first approximations until more precise growth models can be developed.     

Radiation use efficiency in adjacent hardwood and pine forests in the southern Appalachians

The efficiency with which trees convert photosynthetically active radiation (PAR) to biomass has been shown to be consistent within stands of an individual species, which is useful for estimating biomass production and carbon accumulation. However, radiation use efficiency (?) has rarely been measured in mixed-species forests, and it is unclear how species diversity may affect the consistency of ?, particularly across environmental gradients. We compared aboveground net primary productivity (ANPP), intercepted photosynthetically active solar radiation (IPAR), and radiation use efficiency (? = ANPP/IPAR) between a mixed deciduous forest and a 50-year-old white pine (Pinus strobus L.) plantation in the southern Appalachian Mountains. Average ANPP was similar in the deciduous forest (11.5 Mg ha⁻¹ y⁻¹) and pine plantation (10.2 Mg ha⁻¹ y⁻¹), while ? was significantly greater in the deciduous forest (1.25 g MJ⁻¹) than in the white pine plantation (0.63 g MJ⁻¹). Our results demonstrate that late-secondary hardwood forests can attain similar ANPP as mature P. strobus plantations in the southern Appalachians, despite substantially less annual IPAR and mineral-nitrogen availability, suggesting greater resource-use efficiency and potential for long-term carbon accumulation in biomass. Along a 260 m elevation gradient within each forest there was not significant variation in ?. Radiation use efficiency may be stable for specific forest types across a range of environmental conditions in the southern Appalachian Mountains, and thus useful for generating estimates of ANPP at the scale of individual watersheds.     

Topographic and biotic regulation of aboveground carbon storage in subtropical broad-leaved forests of Taiwan

There is a growing need to understand, and ultimately manage, carbon storage by forest ecosystems. Broad-leaved evergreen forests of Taiwan provide an outstanding opportunity to examine factors that regulate ecosystem carbon storage. We utilized data from three Taiwan Forest Dynamics Plots (FS, LHC, and PTY) in which every tree is identified, measured, tagged and mapped, to examine factors regulating carbon storage as estimated from aboveground biomass. Allometric equations were used to estimate the aboveground biomass of each tree, and a model building procedure was used to examine relationships between plot-level aboveground biomass (AGB; Mg/ha) and a suite of topographic and biotic factors. We found that our study sites have AGB values comparable to some of the most carbon dense forests in the world. Across all three sites, maximum biomass was contained in the taxonomic families Fagaceae, Lauraceae and Theaceae. In the FS site, we identified slope convexity (P = 0.03) and elevation (P < 0.001) as topographic predictors of AGB and found that maximum AGB was found in topographically flat areas. In FS, stem density (P < 0.001) was a significant biotic predictor of AGB and the maxima occurred at intermediate densities. In LHC, we found that convexity (P < 0.001) and slope (P < 0.001) were significantly related to AGB which was maximized along a topographic ridge in the plot. Species richness (P < 0.001) was a significant biotic predictor of AGB in LHC, and the relationship indicated slightly higher AGB at higher levels of species richness. The only significant factor related to AGB in PTY was species richness (P = 0.02). Further work is needed to seek a mechanistic understanding of topographic factors and species richness as drivers of carbon storage in forests.     

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 m³/ha for coniferous, 20 m³/ha for broadleaved and 25 m³/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 km², of which 2 million km² are forests, and covers the whole European Union, the EFTA countries, the Balkans, Belarus, the Ukraine, Moldova, Armenia, Azerbaijan, Georgia and Turkey.     

Validation of plantation transpiration in south-eastern Australia estimated using the 3PG+ forest growth model

Forest plantations for wood production are an increasingly important land use in southern Australia, and there are potentially important hydrologic consequences of what is mostly a change in land use from agriculture to silviculture. An ability to predict, with some degree of accuracy, the impact of plantation expansion on surface water and groundwater resources is essential. A validated process-based modelling approach, integrating the many interacting environmental and management factors which may influence plantation growth and transpiration, can be used for this purpose. The 3PG forest growth model has been evaluated for a number of species from widely differing climate and site conditions. While growth predictions have been validated, little attention has been given to testing the accuracy of the transpiration predictions or the model's representation of the water balance. We enhanced the 3PG forest growth model (known as 3PG+) and then integrated it into the Catchment Analysis Tool (CAT), so that it now interfaces with a more detailed multi-layered, daily time step representation of the soil water balance. Simulated transpiration using 3PG+ in CAT was compared with field measurements in 30 plots (across 15 sites) representing 5 common plantation species (Eucalyptus globulus, E. nitens, E. grandis, E. regnans and Pinus radiata) across ages 2–31 years. Mean daily plot transpiration during the measurement periods ranged between 0.4 and 4.2 mm day⁻¹ (average 2.0 mm day⁻¹). Simulated mean daily plot transpiration using 3PG+ in CAT for Eucalyptus was good (coefficient of efficiency = 0.80; R² = 0.81). While the model tended to slightly under-predict transpiration at higher measured rates (>3.5 mm day⁻¹), predictions at monthly timescales had acceptable accuracy. The integration of 3PG+ into CAT resulted in an improvement in accuracy and applicability of CAT, and provides for the spatial application of 3PG+ across diverse and mixed land use catchments for investigation into carbon and water movement in forest systems.     

Assessment of ecosystem services as an opportunity for the conservation and management of native forests in Chile

This paper quantifies two important native forest ecosystem services in southern Chile: water supply and recreational fishing opportunities. We analyzed streamflow in relation to forest cover in six watersheds located in the Valdivian Coastal Range (39°50′–40°05′S), the effect of forest management on streamflow in two watersheds in the Valdivian Andes (600–650 m of elevation; 39°37′S), and fish abundance as a function of forest cover in 17 watersheds located in the Coastal Range and the Central Depression (39°50′–42°30′S). We found that the annual direct runoff coefficient (quickflow/precipitation) and total streamflow/precipitation in the dry summer season were positively correlated with native forest cover in the watershed (R² = 0.67 and 0.76; ^*P = 0.045 and 0.027, respectively) during four years of observations. Conversely, a negative correlation was found between summer runoff coefficients (total streamflow/precipitation) and cover of Eucalyptus spp. and Pinusradiata plantations (R² = 0.84; ^*P = 0.010). We estimated a mean increase of 14.1% in total summer streamflow for every 10% increase in native forest cover in the watershed. The analysis of streamflow changes between two paired watersheds dominated by native secondary Nothofagus stands, one thinned with 35% of basal area removal and a control, showed that the former had a 40% increase during summer (four years of observations). The best correlation between fish abundance and forest cover was found between trout abundance (%) and secondary native forest area in 1000 m × 60 m stream buffers (R² = 0.65, ^***P < 0.0001). We estimated a 14.6% increase in trout abundance for every 10% increase of native forest cover in these buffers. Similar approaches to quantify forest ecosystem services could be used elsewhere and provide useful information for policy and decision-making regarding forest conservation and management.     

A nutrient balance model (NuBalM) to predict biomass and nitrogen pools in Pinus radiata forests

Forest managers are increasingly required to enhance the productivity and profitability of plantation management while simultaneously reducing the negative ecological effects associated with forest operations. NuBalM (from Nutrient Balance Model) is presented here as a decision support tool that has the potential to assist forest managers in meeting these requirements in Pinus radiata D. Don (radiata pine) plantations. NuBalM incorporates nutrient dynamics and allocation into projections of growth, allowing management techniques to be optimised for productivity and nutrient pool retention over single or multiple rotations.NuBalM was developed using data from biomass, nutrient allocation and soil nutrient dynamics studies conducted in New Zealand radiata pine plantations. The capability of NuBalM to predict stem wood mass based on nitrogen supply and demand was tested against data from multiple trial sites established to examine the effects of variations in stocking, thinning and fertilization regimes. NuBalM satisfactorily predicted stem wood masses across a range of stand ages, with the exception of a trial examining ultra-high applications of nitrogen fertilizer. With the exclusion of the data from this trial, the predicted stem wood masses underestimated the observed figures by a mean value of 1.1 ± 1.0 t ha⁻¹ (95% CI, n = 92).The utility of NuBalM as a tool to predict biomass allocation in radiata pine and nitrogen pools in the forest floor and soil was assessed using comprehensive biomass, nutritional and site data collected from two radiata pine trial sites subjected to differences in organic matter removal at site establishment. NuBalM performed acceptably, generating accurate estimates of stem mass (mean overestimate of 5.5 ± 7.4 t ha⁻¹, 95% CI, n = 6) and total above ground biomass (mean overestimate of 3.1 ± 9.6 t ha⁻¹, 95% CI, n = 6). The effects of organic matter removal and fertilization on total nitrogen pools were also predicted with a reasonable degree of accuracy (mean overestimate of 52 ± 53 kg N ha⁻¹, 95% CI, n = 9).From these results we conclude that NuBalM can be utilised to provide projections of productivity and nitrogen pools in radiata pine plantations, and enables the effects of various management practices to be predicted with a reasonable degree of confidence.     

Simulating age-related changes in carbon storage and allocation in a Chinese fir plantation growing in southern China using the 3-PG model

Chinese fir [(Cunninghamia lanceolata (Lamb.) Hook (Taxodiaceae)] plantations are helping to meet China's increasing demands for timber, while, at the same time, sequestering carbon (C) above and belowground. The latter function is important as a means of slowing the rate that CO₂ is increasing in the atmosphere. Available data are limited, however, and even if extensive, would necessitate consideration of future changes in climatic conditions and management practices. To evaluate the contribution of Chinese fir plantations under a range of changing conditions a dynamic model is required. In this paper, we report successful outcome in parameterizing a process-based model (3-PG) and validating its predictions with recent and long-term field measurements acquired from different ages of Chinese fir plantations at the Huitong National Forest Ecosystem Research Station. Once parameterized, the model performed well when simulating leaf area index (LAI), net primary productivity (NPP), biomass of stems (W_S), foliage (W_F) and roots (W_R), litterfall, and shifts in allocation over a period of time. Although the model does not specifically include heterotrophic respiration, we made some attempts to estimate changes in root C storage and decomposition rates in the litterfall pool as well as in the total soil respiration. Total C stored in biomass increased rapidly, peaking at age 21 years in unthinned stands. The predicted averaged above and belowground NNP (13.81 t ha⁻¹ a⁻¹) of the Chinese fir plantations between the modeling period (from 4 to 21-year-old) is much higher than that of Chinese forests (4.8–6.22 t ha⁻¹ a⁻¹), indicating that Chinese fir is a suitable tree species to grow for timber while processing the potential to act as a C sequestration sink. Taking into account that maximum LAI occurs at the age of 15 years, intermediate thinning and nutrient supplements should, according to model predictions, further increase growth and C storage in Chinese fir stands. Predicted future increases (approximately 0–2 °C) in temperature due to global warming may increase plantation growth and reduce the time required to complete a rotation, but further increases (approximately 2–6 °C) may reduce the growth rate and prolong the rotational age.     

A comparative analysis of forest cover and catchment water yield relationships in northern China

During the past few decades, China has implemented several large-scale forestation programs that have increased forest cover from 16.0% in the 1980s to 20.4% in 2009. In northern China, water is the most sensitive and limiting ecological factor. Understanding the dynamic interactions between forest ecosystems and water in different regions is essential for maximizing forest ecosystem services. We examined forest cover and runoff relationships in northern China using published data from a variety of sources. In the Loess Plateau region, forest cover is not correlated with annual precipitation (r = 0.08, p > 0.05) at micro (<50 km²) and meso scales (50-1000 km²), while they are positively correlated at macro (>1000 km²) scale (r = 0.77, p < 0.05). Moreover, forest cover is negatively correlated with the runoff coefficient (r = −0.64, p < 0.05). In Northwest China, natural forest distribution is highly correlated with annual precipitation (r = 0.48, p < 0.05) but not with the runoff coefficient (r = −0.09, p > 0.05). In Northeast China, we found a positive relationship between forest cover and the runoff coefficient (r = 0.77, p < 0.05), but the correlation between forest cover and precipitation was not significant (r = 0.28, p > 0.05). The multiple stepwise regression analysis indicated that runoff was influenced by altitude, annual precipitation, forest cover, and PET (potential evapotranspiration) in Northeast China. We concluded that geographic differences could mask the true role of forests in the partitioning of rainfall into runoff and evapotranspiration (ET) in a catchment. In determining the forest-water relationship, one must consider climatic controls on ET in addition to forest cover. Forests could potentially enhance the complementary relationship between ET and PET. Therefore, a greater amount of ET in forested areas may decrease the PET on a regional scale.     

Use of 3-PG and 3-PGS to simulate forest growth dynamics of Australian tropical rainforests: II. An integrated system for modelling forest growth and scenario assessment within the wet tropics bioregion

Regional model analyses of forest growth are critical for capturing global aspects of tropical rainforest carbon exchange. This research presents the development of a multi-model approach for assessing forest growth and biomass accumulation within the wet tropics bioregion (WTB) based on 10 years of available data and existing model parameter sets. The Tropical Rainforest Growth (TRG) model system employs the 3-PG and 3-PGS models to account for both old-growth rainforest and forest regeneration from seedlings in response to human-induced and natural disturbances. Above-ground biomass (AGB) stocks of the mature forest throughout the WTB for 2000 were estimated to be ∼202 t C/ha. Replacement of areas of old-growth with commercial timber plantations decreased overall AGB stocks to approximately 146 t C/ha. However, plantation carbon accumulation rates were higher than the mature rainforest, representing their potential to accumulate more biomass over a longer analysis time period. As tropical cyclones may significantly alter the carbon stocks of old-growth rainforests, the effect of tropical cyclone Rona on the WTB was assessed. The cyclone had a minimal impact on total AGB stocks within the region, yet these systems are an important factor to be considered in carbon and forest regeneration modelling activities in the tropics. The TRG system is an advanced modelling tool providing a rapid process-based assessment of biomass stocks and accumulation dynamics within Australia's tropical rainforest bioregion and has the potential for application in tropical forest ecosystems at both national and international levels.     

Estimating forest data for analyses of forest production and utilization possibilities at local level by means of multi-source National Forest Inventory

The sample plot data of National Forest Inventories (NFI) are widely used in the analysis of forest production and utilization possibilities to support national and regional forest policy. However, there is an increasing interest for similar impact and scenario analyses for strategic planning at the local level. As the fairly sparse network of field plots only provides calculations for large areas, satellite image data have been applied to produce forest information for smaller areas. The aim of this study was to test the feasibility of generating forest data for a Finnish forest analysis tool, the MELA system, by means of the Landsat satellite imagery and the NFI sample plot data. The study was part of the preparation of a local forestry programme, where a strategic scenario analysis for the forest area of two villages (ca 8000 ha) was carried out. Management units that approximate forest stands were delineated by image segmentation. Stand volume and other parameters for each forest segment were estimated from weighted means of the NFI sample plots, where the individual sample plot weights were estimated by the k nearest neighbour (kNN) method. Two different spectral features were tested: single pixel values and average pixel values within a segment. The estimated forest data were compared with the forest data based on independent stand-level field assessments in two subareas, a national park and an area of forest managed for timber production.In the national park, the estimated mean volume of the growing stock from both spectral feature sets (about 160 m³ ha⁻¹) was clearly lower than that obtained from stand-level field assessment (186 m³ ha⁻¹). Using average pixel values within a segment resulted in a higher proportion of pine and a lower proportion of spruce volume than using single pixel values. It also resulted in an estimated felling potential nearly 10% higher over the first 10-year period in the scenario analysis of the area dedicated to timber production. However, the maximum long-term sustainable removal was at the same level (about 30,000 m³ year⁻¹) for both feature sets over the simulated 30-year period. The resulting annual felling area in the first 10-year period was 12% lower when the segment averages were applied, but the difference subsequently levelled off. The kNN approach in estimating initial forest data for scenario analyses at the local level was found promising.     

Past,present and future land-use in Xishuangbanna,China and the implications for carbon dynamics

Land use/land cover change is an important driver of global change and changes in carbon stocks. Estimating the changes in carbon stocks due to tropical deforestation has been difficult, mainly because of uncertainties in estimating deforestation rates and the biomass in the forest that have been cut. In this study, we combined detailed land-use change over a 27-year period based on satellite images and forest inventory data to estimate changes in biomass carbon stocks in the Xishuangbanna prefecture (1.9 million ha) of China. Xishuangbanna is located in southwestern China in the upper watershed of the Mekong River, and the major forest types are tropical seasonal rain forest, mountain rain forest, and subtropical evergreen broadleaf forest. In the past when the region was completely forested the total biomass carbon would have been approximately 212.65 ± 8.75 Tg C. By 1976 forest cover had been reduced to 70%, and in addition many forests had been degraded resulting in a large decrease in the total biomass carbon stocks (86.97 ± 3.70 Tg C). From 1976 to 2003, the mean deforestation rate was 13 722 ha year⁻¹ (1.12%), and this resulted in the loss of 370,494 ha of forest, and by 2003 total biomass carbon stocks had been reduced to 80.85 ± 2.64 Tg C. The annual carbon emissions due to land-use change, mainly forest conversion to agriculture and rubber plantations, were 0.37 ± 0.03 Tg C year⁻¹ between 1976 and 1988 and 0.13 ± 0.04 Tg C year⁻¹ between 1988 and 2003. During the next 20 years, if rubber plantations expand into forests outside of reserves, shrublands, grasslands, and shifting cultivation below 1500 m the total biomass carbon stocks of Xishuangbanna will decrease to 76.45 ± 1.49 Tg C in 2023. This would reflect a loss of 4.13 ± 1.14 Tg C between 2003 and 2023, or an annual loss of 0.21 ± 0.06 Tg C year⁻¹. Alternatively, if rubber plantations only expand into areas of shifting cultivation below 1500 m, and all areas presently in shrublands and grasslands are allowed to recover into secondary forests, total biomass carbon stock of the region would increase to 92.65 ± 3.80 Tg C in 2023. Under this scenario, the growth of existing forests and the expansion of new forests would result in a net sequestration of 0.60 ± 0.06 Tg C year⁻¹. This study demonstrates that the uncertainty of biomass estimates can be greatly reduced if detailed land-use analyses are combined with forest inventory data, and that slight changes in future land-use practices can have large implications for carbon fluxes.     

Retrieval of forest attributes in complex successional forests of Central Indonesia: Modeling and estimation of bitemporal data

Quantification of forest parameters in different successional stages is required because of its importance as a source of global emissions and ecosystem changes. This study focuses on a successional tropical forest under logging practices in East Kalimantan province, Indonesia. We modeled the forest attributes using both a parametric multiple linear regression analysis and neural networks approach, with Landsat ETM data acquired in 2000 (ETM00). We compiled sample plot data using forest inventory data collected from 1997 to 1998. A total of 226 plots were used to train the models and 112 plots were used for the validation. The remote sensing data (spectral values, vegetation indices, texture, etc.) coupled with digital elevation model (DEM) were experimented with and selectively used to model basal area, stem volume and above ground biomass (AGB). We investigated the possibility to estimate the forest attributes from bitemporal ETM data by calibrating radiometric properties of the ETM image from 2003 (ETM03) using the multivariate alteration detection method. The Pearson correlations showed that the mean texture index is strongly correlated with the forest attributes. We show that neural networks resulted in a higher coefficient of determination (r²) and lower RMSE than multiple regressions for predicting the forest attributes. The estimated forest properties increased with the forest succession advancement (i.e. from the open forest to advanced secondary forest classes). The modeled basal area, stem volume and AGB varied from 10.7–15.1 m² ha⁻¹, 123.2–181.9 m³ ha⁻¹, and 132.7–185.3 Mg ha⁻¹, respectively. The RMSE_r values of model fitting ranged from 11.2% to 13.3%, and the test dataset estimated slightly higher RMSE_r which varied from 12% to 14.1%. The ETM03 forest attributes revealed favorable estimates, showing considerably higher estimates than the ETM00. The estimation of forest properties using neural networks makes Landsat data a valuable source of information for forest management, mainly with the recent free access to its historical dataset.     

Wood density in forests of Brazil's ‘arc of deforestation’: Implications for biomass and flux of carbon from land-use change in Amazonia

Wood density is an important variable in estimates of forest biomass and greenhouse-gas emissions from land-use change. The mean wood density used in estimates of forest biomass in the Brazilian Amazon has heretofore been based on samples from outside the “arc of deforestation”, where most of the carbon flux from land-use change takes place. This paper presents new wood density estimates for the southern and southwest Brazilian Amazon (SSWA) portions of the arc of deforestation, using locally collected species weighted by their volume in large local inventories. Mean wood density was computed for the entire bole, including the bark, and taking into account radial and longitudinal variation. A total of 403 trees were sampled at 6 sites. In the southern Brazilian Amazon (SBA), 225 trees (119 species or morpho-species) were sampled at 4 sites. In eastern Acre state 178 trees (128 species or morpho-species) were sampled at breast height in 2 forest types. Mean basic density in the SBA sites was 0.593 ± 0.113 (mean ± 1 S.D.; n = 225; range 0.265–0.825). For the trees sampled in Acre the mean wood density at breast height was 0.540 ± 0.149 (n = 87) in open bamboo-dominated forest and 0.619 ± 0.149 (n = 91) in dense bamboo-free forest. Mean wood density in the SBA sites was significantly higher than in the bamboo dominated forest but not the dense forest at the Acre site. From commercial wood inventories by the RadamBrasil Project in the SSWA portion of the arc of deforestation, the wood volume and wood density of each species or genus were used to estimate average wood density of all wood volume in each vegetation unit. These units were defined by the intersection of mapped forest types and states. The area of each unit was then used to compute a mean wood density of 0.583 g cm⁻³ for all wood volume in the SSWA. This is 13.6% lower than the value applied to this region in previous estimates of mean wood density. When combined with the new estimates for the SSWA, this gave an average wood density of 0.642 g cm⁻³ for all the wood volume in the entire Brazilian Amazon, which is 7% less than a prior estimate of 0.69 g cm⁻³. These results suggest that current estimates of carbon emissions from land-use change in the Brazilian Amazon are too high. The impact on biomass estimates and carbon emissions is substantial because the downward adjustment is greater in forest types undergoing the most deforestation. For 1990, with 13.8 × 10³ km² of deforestation, emissions for the Brazilian Amazon would be reduced by 23.4–24.4 × 10⁶ Mg CO₂-equivalent C/year (for high- and low-trace gas scenarios), or 9.4–9.5% of the gross emission and 10.7% of the net committed emission, both excluding soils.     

Soil changes induced by Acacia mangium plantation establishment: Comparison with secondary forest and Imperata cylindrica grassland soils in South Sumatra,Indonesia

Acacia plantation establishment might cause soil acidification in strongly weathered soils in the wet tropics because the base cations in the soil are translocated rapidly to plant biomass during Acacia growth. We examined whether soils under an Acacia plantation were acidified, as well as the factors causing soil acidification. We compared soils from 10 stands of 8-year-old Acacia mangium plantations with soils from 10 secondary forests and eight Imperata cylindrica grasslands, which were transformed into Acacia plantations. Soil samples were collected every 5–30 cm in depth, and pH and related soil properties were analyzed. Soil pH was significantly lower in Acacia plantations and secondary forests than in Imperata grasslands at every soil depth. The difference was about 1.0 pH unit at 0–5 cm and 0.5 pH unit at 25–30 cm. A significant positive correlation between pH and base saturation at 0–20 cm depth indicated that the low pH under forest vegetation was associated with exchangeable cation status. Using analysis of covariance (ANCOVA), with clay content as the covariate, exchangeable Ca (Ex-Ca) and Mg (Ex-Mg) stocks were significantly lower in forested areas than in Imperata grasslands at any clay content which was strongly related to exchangeable cation stock. The adjusted average Ex-Ca stock calculated by ANCOVA was 249 kg ha⁻¹ in Acacia plantations, 200 kg ha⁻¹ in secondary forests, and 756 kg ha⁻¹ in Imperata grasslands at 0–30 cm. Based on a comparison of estimated nutrient stocks in biomass and soil among the vegetation types, the translocation of base cations from soil to plant biomass might cause a decrease in exchangeable cations and soil acidification in Acacia plantations.     

Formulating allometric equations for estimating biomass and carbon stock in small diameter trees

Biomass and carbon sequestration rate of a young (four year old) mixed plantation of Dalbergia sissoo Roxb., Acacia catechu Willd., and Albizia lebbeck Benth. growing in Terai region (a level area of superabundant water) of central Himalaya was estimated. The plantation is seed sown in the rainy season of year 2004 and spread over an area of 44 ha. Allometric equations for both above and below ground components were developed for three tree species. The density of trees in the plantation was 1322 trees ha⁻¹ The diameters of trees were below 10 cm. Five diameter classes were defined for D. sissoo and A. catechu and 3 for A. lebbeck. 5 trees were harvested in each diameter class. Individual tree allometry was exercised for developing the allometric equations relating tree component (low and above ground) biomass to d.b.h. Post analysis equations were highly significant (P > 0.001) for each component of all species. In the plantation Holoptelia integrifolia Roxb. (Family Ulmaceae) has been reduced to shrub form because of frost. Only the aboveground biomass of H. integrifolia and other shrubs were estimated by destructive harvesting method. Herbaceous forest floor biomass and leaf litter fall were also estimated. The total forest vegetation biomass was 10.86 Mg ha⁻¹ in 2008 which increased to 19.49 Mg ha⁻¹ in 2009. The forest is sequestering carbon at the rate of 4.32 Mg ha⁻¹ yr⁻¹.     

Aboveground carbon biomass of plantation-grown American chestnut (Castanea dentata) in absence of blight

Forest management activities may help reduce global net CO₂ concentrations by capturing and storing atmospheric CO₂. Research related to carbon sequestration potential of plantations in North America has focused predominantly on conifers, with relatively little emphasis thus far on temperate deciduous forest tree species. American chestnut (Castanea dentata (Marsh.) Borkh.), a former dominant tree species in eastern North America until its demise associated with the introduced chestnut blight (Cryphonectria parasitica (Murr.) Barr.), is a temperate deciduous species that holds promise for future carbon sequestration programs with expected availability of blight-resistant backcross hybrids. We quantified aboveground biomass and bole carbon of American chestnut interplanted with black walnut (Juglans nirga L.) and northern red oak (Quercus rubra L.) across four blight-free experimental sites varying in site quality and/or age (8, 8, 12, and 19 years) isolated from the native American chestnut range in the Coulee Region of southwestern Wisconsin, USA. American chestnut exhibited more rapid growth and greater aboveground biomass and bole carbon than either of the other interplanted species. Aboveground biomass ranged from 46.9, 60.7, 55.0, and 179.9 Mg ha⁻¹ for the 8-, 8-, 12-, and 19-year-old sites, respectively, while bole carbon content ranged from 13.6, 18.6, 14.1, and 60.1 Mg ha⁻¹ for the 8-, 8-, 12-, and 19-year-old sites, respectively. Cross-referencing our data to studies conducted within this same physiographic region using other important forestry species (i.e., Populus tremuloides Michx., Pinus resinosa Ait., and Pinus strobus L.) showed that American chestnut compared favorably in growth and carbon uptake. Incorporating American chestnut into carbon sequestration plantations provides additional ecological and economic benefits associated with consistent production of quality nuts for wildlife, valuable timber, and contribution toward species restoration. Our data lend support to building evidence demonstrating rapid and sustained growth of American chestnut and the potential role of plantation-grown American chestnut in helping to mitigate climate change through carbon sequestration.