Forests In Cambodia Research Articles

Governing Cambodia's Forests: The International Politics of Policy Reform

Governing Cambodia's Forests: The International Politics of Policy Reform

Seasonal and height-related changes in leaf morphological and photosynthetic traits of two dipterocarp species in a dry deciduous forest in Cambodia

Background: Dry deciduous forest (DDF) is distributed throughout the monsoon area of South-east Asia. Leaf morphological and photosynthetic traits are essential for adaptation to the environmental variability and usually change with tree height and season.Aims: To clarify the differences in leaf traits as influenced by tree height, light conditions and season for two dominant dipterocarps of DDF: Dipterocarpus tuberculatus and Shorea obtusa.Methods: We measured changes in leaf traits with tree height, namely leaf mass per area (LMA), maximum photosynthetic rate (Amax), stomatal conductance (gs) and nitrogen concentration (N), in the rainy and early and mid-dry seasons. To identify the effects of height and light intensity on leaf traits, we conducted multiple regression analyses using leaf traits as the dependent variables and the height, light and season as independent variables.Results: Tree height was more important for gradients in most leaf traits, especially in LMA in both species, than light intensity. Tall canopy tree leaves had greater LMA, Amax and N than shorter tree leaves in the rainy and early dry seasons, although gs was almost constant. The lowest Amax and gs were recorded in immature leaves, sampled in the mid-dry season, at all tree heights.Conclusions: The two dipterocarp species achieved high Amax by having high gs, LMA and N in a high-light canopy environment, whereas larger, thinner leaves with low respiratory costs may contribute to efficient light capture under low-light conditions in the understorey.

Incorporating Canopy Cover for Airborne-Derived Assessments of Forest Biomass in the Tropical Forests of Cambodia.

This research examines the role of canopy cover in influencing above ground biomass (AGB) dynamics of an open canopied forest and evaluates the efficacy of individual-based and plot-scale height metrics in predicting AGB variation in the tropical forests of Angkor Thom, Cambodia. The AGB was modeled by including canopy cover from aerial imagery alongside with the two different canopy vertical height metrics derived from LiDAR; the plot average of maximum tree height (Max_CH) of individual trees, and the top of the canopy height (TCH). Two different statistical approaches, log-log ordinary least squares (OLS) and support vector regression (SVR), were used to model AGB variation in the study area. Ten different AGB models were developed using different combinations of airborne predictor variables. It was discovered that the inclusion of canopy cover estimates considerably improved the performance of AGB models for our study area. The most robust model was log-log OLS model comprising of canopy cover only (r = 0.87; RMSE = 42.8 Mg/ha). Other models that approximated field AGB closely included both Max_CH and canopy cover (r = 0.86, RMSE = 44.2 Mg/ha for SVR; and, r = 0.84, RMSE = 47.7 Mg/ha for log-log OLS). Hence, canopy cover should be included when modeling the AGB of open-canopied tropical forests.

Allometric Equations for Tropical Seasonal Deciduous Forests in Cambodia: A Method of Estimating Belowground Tree Biomass with Reduced Sampling Loss of Roots

Allometric Equations for Tropical Seasonal Deciduous Forests in Cambodia: A Method of Estimating Belowground Tree Biomass with Reduced Sampling Loss of Roots

Assessment of carbon stocks of semi-evergreen forests in Cambodia

Understanding carbon stocks relative to tree species is important for managing tropical forests in a way that will result in the carbon emission reductions and biodiversity conservation required under the REDD+ scheme. Here we analyse inventory data from 179 sample plots in semi-evergreen forests of three provinces in Cambodia. Across all study sites, 5,995 trees with a diameter at breast height (DBH) ≥10 cm, comprising 79 species from 38 families, were analysed. Tree species of the Dipterocarpaceae were most common (10 species), followed by the species of Caesalpinaceae, Combretaceae and Ebenaceae. Analysis of relative carbon stocks (RCS) suggested that Lagerstroemia calyculata Kurz (RCS=14.3%), Syzygium sp. (6.8%), Shorea vulgaris (5.0%), Irvingia malayana (4.8%), Anisoptera costata Kort (4.6%), Vatica astrotricha (4.2%), and Dehaasia cuneata Blume (3.8%) together accounted for 43.6% of the total average carbon stocks of 99.8±4.8 MgC ha−1. We found that carbon stock is highly correlated to basal area (R2=0.993) but not to stem density (R2=0.153). Using carbon stock values, we estimated the carbon emission due to deforestation of semi-evergreen forests to be 8.3 TgCO2 year−1 in Cambodia between 2002 and 2010. These emissions and the loss of 79 tree species in our study sites could be avoided if financial incentives were available for protecting semi-evergreen forests in Cambodia.

Estimating aboveground carbon using airborne LiDAR in Cambodian tropical seasonal forests for REDD+ implementation

We developed an empirical model to estimate aboveground carbon density with variables derived from airborne Light Detection and Ranging (LiDAR) in tropical seasonal forests in Cambodia, and assessed the effects of LiDAR pulse density on the accurate estimation of aboveground carbon density. First, we tested the applicability of variables used for estimating aboveground carbon density with the original LiDAR pulse density data (26 pulse m−2). Aboveground carbon density was regressed against variables derived from airborne LiDAR. Three individual height variable models were developed along with a canopy density model, and three other models combined canopy height and canopy density variables. The influence of forest type on model accuracy was also assessed. Next, the relationship between pulse density and estimation accuracy was investigated using the best regression model. The accuracy of the models were compared based on seven LiDAR point densities consisting of 0.25, 1, 2, 3, 4, 5 and 10 pulse m−2. The best model was obtained using the single mean canopy height (MCH) model (R2 = 0.92) with the original pulse density data. The relationship between MCH and aboveground carbon density was found to be consistent under different forest types. The differences between predicted and measured residual mean of squares of deviations were less than 1.5 Mg C ha−1 between each pulse density. We concluded that aboveground carbon density can be estimated using MCH derived from airborne LiDAR in tropical seasonal forests in Cambodia even with a low pulse density of 0.25 pulse m−2 without stratifying the study area based on forest type.

Mapping Above-Ground Biomass in a Tropical Forest in Cambodia Using Canopy Textures Derived from Google Earth

This study develops a modelling framework for utilizing very high-resolution (VHR) aerial imagery for monitoring stocks of above-ground biomass (AGB) in a tropical forest in Southeast Asia. Three different texture-based methods (grey level co-occurrence metric (GLCM), Gabor wavelets and Fourier-based textural ordination (FOTO)) were used in conjunction with two different machine learning (ML)-based regression techniques (support vector regression (SVR) and random forest (RF) regression). These methods were implemented on both 50-cm resolution Digital Globe data extracted from Google Earth™ (GE) and 8-cm commercially obtained VHR imagery. This study further examines the role of forest biophysical parameters, such as ground-measured canopy cover and vertical canopy height, in explaining AGB distribution. Three models were developed using: (i) horizontal canopy variables (i.e., canopy cover and texture variables) plus vertical canopy height; (ii) horizontal variables only; and (iii) texture variables only. AGB was variable across the site, ranging from 51.02 Mg/ha to 356.34 Mg/ha. GE-based AGB estimates were comparable to those derived from commercial aerial imagery. The findings demonstrate that novel use of this array of texture-based techniques with GE imagery can help promote the wider use of freely available imagery for low-cost, fine-resolution monitoring of forests parameters at the landscape scale.

Bat populations in lowland dry evergreen forests of the Central Cardamom Protected Forest in Cambodia

This study was conducted to clarify the characteristics of bat populations in lowland dry evergreen forests of the Central Cardamom Protected Forest in Cambodia during the rainy seasons of 2011–2013 and the dry seasons of 2012–2013. In five study sites of the forest, data from 160 individuals of six bat species were recorded. The Sunda short-nosed fruit bat (Cynopterus brachyotis Sunda) was the most dominant species in all study sites. Most captured bats were adults, and captured females outnumbered captured males. In this study, populations of the bats, except for that of the Sunda short-nosed fruit bats, were not stable. Therefore, forest loss and degradation should be prohibited in the study areas to ensure stable bat populations. Further studies are required to investigate the ecological characteristics of fruit bats in various forest types for the conservation of the mammals and their habitats.

Natural Forest Biomass Estimation Based on Plantation Information Using PALSAR Data

Forests play a vital role in terrestrial carbon cycling; therefore, monitoring forest biomass at local to global scales has become a challenging issue in the context of climate change. In this study, we investigated the backscattering properties of Advanced Land Observing Satellite (ALOS) Phased Array L-band Synthetic Aperture Radar (PALSAR) data in cashew and rubber plantation areas of Cambodia. The PALSAR backscattering coefficient (σ0) had different responses in the two plantation types because of differences in biophysical parameters. The PALSAR σ0 showed a higher correlation with field-based measurements and lower saturation in cashew plants compared with rubber plants. Multiple linear regression (MLR) models based on field-based biomass of cashew (C-MLR) and rubber (R-MLR) plants with PALSAR σ0 were created. These MLR models were used to estimate natural forest biomass in Cambodia. The cashew plant-based MLR model (C-MLR) produced better results than the rubber plant-based MLR model (R-MLR). The C-MLR-estimated natural forest biomass was validated using forest inventory data for natural forests in Cambodia. The validation results showed a strong correlation (R2 = 0.64) between C-MLR-estimated natural forest biomass and field-based biomass, with RMSE = 23.2 Mg/ha in deciduous forests. In high-biomass regions, such as dense evergreen forests, this model had a weaker correlation because of the high biomass and the multiple-story tree structure of evergreen forests, which caused saturation of the PALSAR signal.

Spectral normalization of SPOT 4 data to adjust for changing leaf phenology within seasonal forests in Cambodia

As cloud cover exacerbates the application of optical satellite data for forest monitoring in tropical wet and dry regions during the rainy season, data acquisition is mainly restricted to the dry season. When analyzing wide areas, large numbers of single scenes obtained at different times of the dry season are often handled. Such imagery is characterized by changes of spectral reflectance due to vegetation phenology, varying atmospheric effects and solar geometries. In order to allow batch processing with automatic classification techniques, inter-scene comparability is required and data have to be radiometrically normalized. Cambodia is characterized by a mixture of evergreen, semi-evergreen and deciduous forest types, the latter two experiencing at least partial leaf shedding over the course of the dry season. Using spatial medium resolution SPOT 4 data and a manually delineated base map a season adjustment model was developed. The model is adapting the land cover specific spectral signatures of a slave scene (acquired in the middle of the dry season with its seasonal forests defoliated) to an adjacent master scene (from the beginning of the dry season, showing the same forest types with leafs). The relative position of every pixel reflectance was determined in relation to the mean reflectance and its standard deviation for each land cover type and sensor band of the unadjusted slave scene. For seasonality adjustment these pixel reflectance values were transformed (rescaled) to the corresponding position in spectral space defined by the band mean reflectance and standard deviation derived from the corresponding land cover class of the master scene. While the variability of spectral profiles of the pixels in the slave scene is rescaled, the mean reflectance value of the land cover class in the slave scene is conformed to the mean reflectance of the corresponding land cover class in the master scene. The Transformed Divergence (TD) separability index was used to indicate the performance of the adjustment process by characterizing the spectral distance for each land cover type comparing a reference dataset to the uncorrected and to the seasonality corrected scene respectively. While the TD values of all forest types showed a sharp decline, highlighting the good performance of the model, the TD values of the agriculture/urban class remained high, indicating limited normalization of this heterogeneous land cover type. In order to further demonstrate the performance of the model, an object-based land cover classification was applied to the unadjusted as well as to the corresponding adjusted scene. A comparison of the results showed a highly significant improvement of overall accuracy from 32.2% to 75.8% when applying seasonality adjustment.

Instruments and Observation Methods for Water Vapor Exchange Measurement Over a Forest in Cambodia

Instruments and Observation Methods for Water Vapor Exchange Measurement Over a Forest in Cambodia

Experimental test of a conservation intervention for a highly threatened waterbird

Human exploitation and disturbance often threaten nesting wildlife. Nest guarding, a technique that employs local people to prevent such interference, is being applied to an increasing number of species and sites, particularly in South-East Asia. Although research has begun to assess the cost-effectiveness of nest guarding, case–control studies are rare and the circumstances in which the schemes are most useful remain unclear. We experimentally tested the effect of nest guarding for the critically endangered white-shouldered ibis (Pseudibis davisoni), a species exploited opportunistically for food and now largely confined to dry forests in Cambodia. We randomly applied guarded and unguarded (control) treatments to 24 and 25 nests, respectively, at a single site over 2 years. Nest guarding had no detectable effect on nest success, with an overall probability of nest success of 0.63–0.86 at guarded and 0.55–0.82 at unguarded nests. Nest monitoring across 4 study sites over 3 breeding seasons found a combination of natural predation, weather, and anthropogenic activities (robbery and vandalism) responsible for nest failure, although causes of failure remained unknown at 58% of nests. Nest guarding itself increased nest destruction at 1 site, indicating that this intervention needs cautious implementation if only a small proportion of the local community gains benefit. Comparison with other studies suggests that nest guarding effectiveness may be context-specific and differ between species that are exploited opportunistically, such as white-shouldered ibis, and those routinely targeted for trade. © 2013 The Wildlife Society.

Factors Affecting Forest Area Changes in Cambodia: An Econometric Approach

Clarifying factors affecting forest area changes is critical to implementing REDD+ scheme properly. We analyzed some socio-economic factors and clarified their relationships with deforestation in Cambodia for the period of 2002 to 2010. A panel data analysis was conducted for 18 provinces, while six other provinces were deleted from the list because only a small amount of their land was forested. Time effects, cross-sectional dependence, serial correlation in idiosyncratic errors, and heteroskedasticity were tested, and robust variance matrix estimations were obtained to solve the problems of heteroskedasticity and serial correlation. The model estimation results showed that population, gross agricultural production and large-scale plantation development have negative impacts on forest area changes. On the other hand, the impacts of rice cultivation, gross industrial production, household income and house floor area by household were found not to be significant. Overall, however, the results indicated that forests in Cambodia still face pressure from the increases in population, agriculture production, and the enlargement of land development. As the increase in productivity of agriculture gives a better use of current agricultural land and lessens the pressure on forest, intensifying agriculture is important. It is also important to develop industry and other economic ventures to grow national economy while not imposing pressure on forest. This research reminds decision makers to use discretion when developing large-scale plantations.

Soil physicochemical properties and moisture dynamics of a large soil profile in a tropical monsoon forest

Evergreen forests in tropical monsoon Asia experience a severe dry season lasting several months. Deep soil moisture is responsible for evergreen forest transpiration during this season. This study provides preliminary information on soil physicochemical properties in a large soil profile (800cm deep) and evaluated the influences of deep-soil moisture dynamics on the transpiration of evergreen forests in Cambodia using a water flow model. In general, changes in soil physicochemical properties with depth were small, excluding topsoil. The soil texture in the large soil profile was characterized by very little gravel and a large sand fraction. The soil carbon stock was 71.7 and 130.1Mg Cha−1 at depths of 0–150 and 0–800cm, respectively. The coarse pore volume (−100≤ψ<−0.2cm) and saturated hydraulic conductivity (Ks) clearly decreased with depth from 100 to 600cm and were extremely low at 600–700cm. In the water flow simulation, a rooting depth deeper than 400cm was necessary for the evergreen forest to maintain transpiration during the dry season. On the other hand, when the Ks of deep soil (550–750cm depth) was assumed to be higher than that estimated by the cylinder sample, a rooting depth of 800cm was necessary, since most of the soil water that was replenished during the rainy season was rapidly lost during the dry season. Also, it was necessary for evergreen forests to effectively use soil water within the deep root zone (400–800cm depth). The compacted deep soil horizons played an important role in maintaining the moist conditions in the root zone of an evergreen tropical monsoon forest in Asia that experienced a severe dry season.

Reducing Carbon Emissions through Improved Forest Management in Cambodia

Carbon emissions from selectively logged forests in the tropics are strongly affected by logging practices. Although tropical forests are mainly managed under the concession system, only a handful of studies were done to assess the impact of logging practices on emission reductions and future timber supply. In this report, carbon stocks, timber supply, and carbon emission reductions under conventional logging (CVL), reduced-impact logging (RIL), and RIL with special silvicultural treatments (RIL+) were assessed in 3.4 million ha of concession forests for a 55-year project time span. Carbon emissions under a 25-year CVL practiced in Cambodia were estimated at 12.4 TgCO2 year-1 for 55 years. We then tested four cutting cycles of selective logging and our results suggest that a 45-year selective cutting cycle was appropriate for managing concession forests in Cambodia in terms of maintaining commercial timber supply and reducing carbon emissions. By considering RIL or RIL+ as a new logging practice for improving forest management in the tropics, carbon credits from selective logging in Cambodia were estimated at 6.2 - 7.9 TgCO2 or about $31.0 - 39.5 million annually if carbon is priced at $5. It is concluded that RIL or RIL+ should be adopted for “sustainable management of forests” element of the REDD+ scheme.

Tree Biomass Carbon Stock Estimation using Permanent Sampling Plot Data in Different Types of Seasonal Forests in Cambodia

As a feasibility study for applying a simplified method to estimate CO2 emissions from deforestation and forest degradation in tropical forests, we estimated the nationwide forest tree biomass carbon stock using data from 100 permanent sampling plots (PSPs) set by the Forestry Administration, Cambodia in seasonal forests in Cambodia. Averaged tree carbon stocks and SE-Standard error were at 158.8 ± 7.3 Mg C ha-1 for evergreen and semi-evergreen forests and 55.2 ± 6.9 Mg C ha-1 for deciduous forests in 1998 (the first census) and for the second census in 2000-2001, 163.8 ± 7.8 Mg C ha-1 and 56.2 ± 6.7 Mg C ha-1, respectively. The averaged tree biomass carbon stock differed significantly between the two forest types. Using the forest cover for 2006 and the averaged carbon stock for 2000-2001, the national-level forest tree carbon stock in the early to mid-2000s was estimated at 824.2 ± 39.2 Tg C for evergreen forests and 263.9 ± 31.3 Tg C for deciduous forests, and 1,088.1 ± 50.2 Tg C in total. By repeating this calculation for all forest areas by remote sensing and averaged tree carbon stock via ground-based measurement with PSPs, we could monitor the total tree carbon stock in nationwide forests in Cambodia. We also presented the possible reasons for uncertainty related to the present tree biomass carbon stock of forests and recommendations in order to improve the accuracy of the carbon stock using PSP systems in Cambodia.

Estimating Reference Emission Level and Project Emission Level for REDD Projects in Tropical Forests

The REDD+ scheme of the United Nations Framework Convention on Climate Change is a carbon-based compensation for projects that resulted in reducing carbon emissions or enhancing carbon sinks or both in tropical forests. However, estimating such emissions and sinks remains challenging, and thus making it impossible to estimate carbon revenues from managing tropical forests. Here, we estimated the reduced emissions and sinks by developing models for setting Reference Emission Level (REL) and Project Emission Level (PEL) for REDD+ projects in concession forests taking emissions under conventional logging (CVL) scenario as that of REL, and emissions under reduced impact logging (RIL) and RIL with liberation treatment (RIL+) scenarios as that of PEL. By choosing Cambodia as a case study, REL under the current logging system of 25-year cutting cycle was estimated at 23.1 TgCO2 year -1 . To determine an appropriate cutting cycle, we tested our models with four cutting cycles and found that a 50-year cutting cycle is more appropriate. Taking this 50-year cutting cycle for REDD+ project, PELs were estimated at 0.4 TgCO2 and -3.3 TgCO2 year -1 under RIL and RIL+, respectively (- means sinks). After subtracting REL with PEL and leakages, annual carbon credits from managing 3.4 million ha of concession forests in Cambodia were estimated at 15.9-18.5 TgCO2 depending on chosen scenario. With a carbon price of $5 MgCO2 -1 , total revenues from the sales of carbon credits alone are $79.5-92.5 million annually. To ensure continued flow of wood supply from tropical forests while mitigating climate change, we suggest that new climate agreements adopt RIL or RIL+ for sustainable forest management in tropical countries.

Evergreen swamp forest in Cambodia: floristic composition, ecological characteristics, and conservation status

As part of recent field studies, a hitherto undescribed type of evergreen freshwater swamp forest was discovered in Stung Treng Province, Cambodia. The swamp forest occurs in at least six disjunct localities and is dominated by hydrophytic trees (Eugenia spp., Ficus spp., Litsea spp., Macaranga triloba, Myristica iners and Pternandra caerulescens). Although these same genera also occur in upland forests, most are represented by different species in the swamps. Livistona saribus emerges from the canopy as an indicator species of this vegetation type while dense stands of other palms (Calamus, Areca, Licuala) and sporadic, dense populations of tree ferns (Cibotium barometz) dominate the understory. Pneumatophores, stilt roots, and aerial roots characterize the hydrophytes. The floristic composition indicates that the forest type is distinct compared to other swamp forests described from the region and worthy of protection based on its rarity and ecological uniqueness.

Carbon Stock Estimation by Forest Measurement Contributing to Sustainable Forest Management in Cambodia

A simplified method for estimating CO 2 emissions from deforestation is the calculation of carbon stock change by monitoring forest land and periodically summing up the land area and its averaged carbon stock for important forest types. As a feasibility study for applying this methodology to a tropical dry-land forest, we estimated carbon stock and its chronosequential change in 4 carbon pools (aboveground and belowground biomass, deadwood, and litter) of tropical dry-land natural forests in Cambodia. Carbon stock differed among forest types. Most of the carbon stock (84 ± 12% (SD)) existed in tree biomass. Growth of carbon stock has a positive relationship to the carbon stock itself. By moderately classifying forest types, determining averaged tree biomass of each forest type, and using land-area data on each forest type, a reasonably accurate estimation of carbon stock can be expected. However, considering that rapidly progressing deforestation and wood extraction may reduce the carbon stock in forests, systematic sampling with a sufficient number of extra plots and frequent updating of forest land area and averaged carbon stock data are vital for an accurate estimation of CO 2 emissions from forests under pressure of land-use change and forestry activities.

Conservation and utilization of threatened hardwood species through reforestation ? an example of Afzelia xylocarpa (Kruz.) Craib and Dalbergia cochinchinensis Pierre in Cambodia

The leguminaceous rosewoods, Afzelia xylocarpa (Caesalpiniodeae) and Dalbergia cochinchinensis (Faboideae) are threatened by habitat loss and exploitation for their extremely highly-prized timber throughout their range. This paper examines the current conservation status of A. xylocarpa and D. cochinchinensis in Cambodia, draws together information on silviculture and trade, and summarizes current conservation measures in the country. Urgent measures are required to conserve and sustainably use the remaining genetic resources. Opportunities and challenges for achieving these goals, through use of the two threatened species in reforestation, are discussed. The suitability of the species for reforestation combined with increasing domestic and international prices for rosewood provide an opportunity for promotion of the species in planting programmes. This would not only alleviate the pressure on their natural habitats, but also bring about economic benefit. The paper outlines some important steps in the development of domestication strategies including testing and improving silvicultural practices, and increasing the supply of genetically superior seeds from seed production areas and/or seed orchards. As a first step, a network of in situ gene banks has been established in natural forests in Cambodia. A wide range of stakeholders need to participate in such programmes in order to address socio-economic development and poverty reduction. This is in line with the main objective of the National Forest Programme of Cambodia.