Tsuyoshi Kajisa

Importance of rubberwood in wood export of Malaysia and Thailand

AbstractsWe examined the contribution of rubberwood to the timber export markets of Malaysia and Thailand. In Malaysia, rubberwood has grown from 26% of total exported wood products in 1998 to 35% in 2007. A high proportion of furniture products (80%) is rubberwood, whereas the contribution of rubberwood to other wooden products is less than 20%. Only 10% of sawn timber and logs is rubberwood. In Thailand, rubberwood contributes to around 60% of total exported wood products, arising from a high share of not only furniture products (70%) but also other wood products (around 50%) and sawn timber and logs, which have increased in share from 40% in 1998 to 79% in 2007. We conclude that the high proportion of rubberwood products in the wood export markets of these two countries is a result of: (1) scarcity of raw wood materials because of strict controls on the logging of natural forests; and (2) governmental support to rubberwood production, including financial support to rubber planters and technical assistance to downstream timber processors.

Deforestation and forest degradation as measures of Popa Mountain Park (Myanmar) effectiveness

The effectiveness of protected areas (PAs) has often been measured by comparing deforestation or land cover loss before and after PA establishment or within and outside the PA. Such evaluations ignore forest degradation or the decline in quality of the ecological values of the forest. Landsat image processing and geographical information systems were used to study forest cover changes in and around Popa Mountain Park (central Myanmar). Deforestation inside the Park was lower than outside the Park, but forest degradation, namely the net area that changed from dense forest to open forest, within the Park had grown at rates exceeding those outside the Park. The effectiveness of the PA was overestimated by adopting deforestation as the only indicator of conservation effectiveness. Forest degradation studies can be used to evaluate the effectiveness of PAs.

effects of logging and recruitment on community phylogenetic structure in 32 permanent forest plots of kampong thom, cambodia

Ecological communities including tropical rainforest are rapidly changing under various disturbances caused by increasing human activities. Recently in Cambodia, illegal logging and clear-felling for agriculture have been increasing. Here, we study the effects of logging, mortality and recruitment of plot trees on phylogenetic community structure in 32 plots in Kampong Thom, Cambodia. Each plot was 0.25 ha; 28 plots were established in primary evergreen forests and four were established in secondary dry deciduous forests. Measurements were made in 1998, 2000, 2004 and 2010, and logging, recruitment and mortality of each tree were recorded. We estimated phylogeny using rbcL and matK gene sequences and quantified phylogenetic α and β diversity. Within communities, logging decreased phylogenetic diversity, and increased overall phylogenetic clustering and terminal phylogenetic evenness. Between communities, logging increased phylogenetic similarity between evergreen and deciduous plots. On the other hand, recruitment had opposite effects both within and between communities. The observed patterns can be explained by environmental homogenization under logging. Logging is biased to particular species and larger diameter at breast height, and forest patrol has been effective in decreasing logging.

Estimation of Airborne Lidar-Derived Tropical Forest Canopy Height Using Landsat Time Series in Cambodia

In this study, we test and demonstrate the utility of disturbance and recovery information derived from annual Landsat time series to predict current forest vertical structure (as compared to the more common approaches, that consider a sample of airborne Lidar and single-date Landsat derived variables). Mean Canopy Height (MCH) was estimated separately using single date, time series, and the combination of single date and time series variables in multiple regression and random forest (RF) models. The combination of single date and time series variables, which integrate disturbance history over the entire time series, overall provided better MCH prediction than using either of the two sets of variables separately. In general, the RF models resulted in improved performance in all estimates over those using multiple regression. The lowest validation error was obtained using Landsat time series variables in a RF model (R2 = 0.75 and RMSE = 2.81 m). Combining single date and time series data was more effective when the RF model was used (opposed to multiple regression). The RMSE for RF mean canopy height prediction was reduced by 13.5% when combining the two sets of variables as compared to the 3.6% RMSE decline presented by multiple regression. This study demonstrates the value of airborne Lidar and long term Landsat observations to generate estimates of forest canopy height using the random forest algorithm.

Estimating forest canopy density of tropical mixed deciduous vegetation using Landsat data: a comparison of three classification approaches

Although a number of image classification approaches are available to estimate forest canopy density (FCD) using satellite data, assessment of their relative performances with tropical mixed deciduous vegetation is lacking. This study compared three image classification approaches – maximum likelihood classification (MLC), multiple linear regression (MLR) and FCD Mapper – in estimating the FCD of mixed deciduous forest in Myanmar. The application of MLC and MLR was based on spectral reflectance of vegetation, whereas FCD Mapper was operated on integrating the biophysical indices derived from the reflectance of the vegetation. The FCD was classified into four categories: closed canopy forest (CCF; FCD ≥ 70%), medium canopy forest (MCF; 40% ≥ FCD < 70%), open canopy forest (OCF; 10% ≥ FCD < 40%) and non-forest (NF; FCD < 10%). In the three classification approaches, producers and users accuracies were higher for more homogeneous vegetation such as NF and CCF than for heterogeneous vegetation density (VD) such as OCF and MCF. FCD Mapper produced the best overall accuracy and kappa coefficient. This study revealed that only spectral reflectance is not enough to get good results in estimating FCD in tropical mixed deciduous vegetation. This study indicates that FCD Mapper, an inexpensive approach because it requires only validation data and thus saves time, can be applied to monitor tropical mixed deciduous vegetation over time at lower cost than alternative methods.

Object-Based Mapping of Aboveground Biomass in Tropical Forests Using LiDAR and Very-High-Spatial-Resolution Satellite Data

Developing countries that intend to implement the United Nations REDD-plus (Reducing Emissions from Deforestation and forest Degradation, and the role of forest conservation, sustainable management of forests, and enhancement of forest carbon stocks) framework and obtain economic incentives are required to estimate changes in forest carbon stocks based on the IPCC guidelines. In this study, we developed a method to support REDD-plus implementation by estimating tropical forest aboveground biomass (AGB) by combining airborne LiDAR with very-high-spatial-resolution satellite data. We acquired QuickBird satellite images of Kampong Thom, Cambodia in 2011 and airborne LiDAR measurements in some parts of the same area. After haze reduction and atmospheric correction of the satellite data, we calibrated reflectance values from the mean reflectance of the objects (obtained by segmentation from areas of overlap between dates) to reduce the effects of the observation angle and solar elevation. Then, we performed object-based classification using the satellite data (overall accuracy = 77.0%, versus 92.9% for distinguishing forest from non-forest land). We used a two-step method to estimate AGB and map it in a tropical environment in Cambodia. First, we created a multiple-regression model to estimate AGB from the LiDAR data and plotted field-surveyed AGB values against AGB values predicted by the LiDAR-based model (R2 = 0.90, RMSE = 38.7 Mg/ha), and calculated reflectance values in each band of the satellite data for the analyzed objects. Then, we created a multiple-regression model using AGB predicted by the LiDAR-based model as the dependent variable and the mean and standard deviation of the reflectance values in each band of the satellite data as the explanatory variables (R2 = 0.73, RMSE = 42.8 Mg/ha). We calculated AGB of all objects, divided the results into density classes, and mapped the resulting AGB distribution. Our results suggest that this approach can provide the forest carbon stock per unit area values required to support REDD-plus.

The Importance of Tree Height in Estimating Individual Tree Biomass while Considering Errors in Measurements and Allometric Models

This study evaluated the uncertainty of individual tree biomass estimated by allometric models by both including and excluding tree height independently. Using two independent sets of measurements on the same trees, the errors in the measurement of diameter at breast height and tree height were quantified, and the uncertainty of individual tree biomass estimation caused by errors in measurement was calculated. For both allometric models, the uncertainties of the individual tree biomass estimation caused by the use of a specific allometric model were also calculated. Finally, the overall uncertainty of individual tree biomass by combining the two uncertainties was calculated. The allometric model including tree height was 6 % more accurate than that excluding tree height when the uncertainty caused by allometric models became the only consideration. However, in terms of the uncertainty caused by measurement, the allometric model excluding tree height was three times more accurate than allometric model including tree height. As a result, the allometric model excluding tree height was 5 % more accurate than the allometric model including tree height when both causes of uncertainty, the allometric model and measurement errors were considered. In conclusion, errors in tree height measurement have the potential to increase the error of aboveground biomass estimation.

The effect of weeding frequency and timing on the height growth of young sugi (Cryptomeria japonica) in southwestern Japan

ABSTRACT This study investigated the effect of weeding on the height growth of planted sugi (Cryptomeria japonica) saplings in southwestern Japan. First, we developed stand-level sugi and weed annual height growth models that accounted for tree spacing, slope aspect, and mean sugi height at the end of prior growing season and mean weed height just after weeding. Then, we simulated sugi heights after the sixth growing season under 64 different weeding schedules, using the developed model to examine the effects of the weeding frequency and the timing of weeding. The selected model for sugi height growth was expressed in terms of mean sugi height, mean weed height, slope aspect, and the relative height of weeds to sugi. In the case of weeds, the selected model was expressed in terms of mean sugi height, slope aspect, and the relative height of weeds to sugi. The simulation showed that sugi height decreased approximately 20% for every one-time reduction in the number of weeding. The simulation also showed that earlier, rather than later, weeding yielded better sugi growth. In conclusion, not only weeding frequency but also weeding schedules are important for sugi height growth.

Using a tree-based approach to evaluate logging damage in a tropical mixed deciduous forest of Myanmar: comparison with cases in Cambodia

ABSTRACT Logging damage to residual trees is an important parameter when considering the sustainability of selective logging in tropical natural forests. Here, we applied a proposed tree-based approach to evaluate logging damage in a tropical mixed deciduous forest in Bago Yoma, Myanmar and compared the cases with semi-evergreen forests of Cambodia. The logging damage was assessed in twenty 0.1-ha plots, each of which contained the stump and crown of one felled tree, and multinomial logistic regression was used to quantify the probability of the felled tree causing severe, slight, or no damage to residual trees. In both cases of Myanmar and Cambodia, severe damage was dependent on the size of the residual and felled trees, while slight damage was independent of the size of felled trees. There was no slight damage of residual trees with ≥50 cm diameter at breast height (DBH) in Myanmar, whereas slight damage increased with residual tree size in Cambodia and in tropical rain forests of other countries. This difference could be attributed to the sparseness of standing trees (98 trees ha−1) in our study site in Myanmar, which made it easier to control the felling direction to avoid damage to larger residual trees. Additionally, the probability of increasingly severe damage with increasing DBH of the felled trees was higher in Myanmar than in Cambodia; one of the reasons may be the steeper terrain at the Myanmar site.

Effects of Directional Felling, Elephant Skidding and Road Construction on Damage to Residual Trees and Soil in Myanmar Selection System

SUMMARY Reduced-impact logging (RIL) is widely expected to maximize conservation values of selectively logged tropical forests; however, there remains a lack of supporting data to confirm the effectiveness of individual RIL practices. This study evaluates the extent of damage to residual stands and soil caused by directional felling, elephant skidding, and road construction in a tropical mixed deciduous forest under the Myanmar Selection System (MSS). The felling damage number was consistently larger for bamboo clumps than for trees over the range of felled tree size and felling intensity. Soil disturbed by road construction made up 4.6% of the 9-ha study area, but no visible damage to residual trees and soil from elephant skidding was found three months after the operation. Directional felling toward bamboos and elephant skidding of MSS are effective as RIL practices, producing the lowest level of damage to residual trees and soil as compared with other RIL studies.