Foreseeing the importance of managing forests for climate change mitigation and sustainable development, the Royal Government of Cambodia has put strong commitment to managing its remaining forests under the new anticipated international climate change agreement on REDD+ mechanism. Forestry Administration in collaboration with Community Forestry International, and Terra Global Capital started a REDD project for Community Forestry sites in the northern province of Oddar Meanchey in 2007. Here, we report the methods and findings from our project and propose an appropriate framework for effective implementation in Cambodia. Ten drivers and six agents of deforestation and forest degradation were identified and each driver could be reduced by adopting appropriate project actions. Changes in deforestation, carbon stocks, and project emissions were estimated under baseline and project scenarios. Our results suggest that the project is likely to lead to the reduction of about 8.6 million tonne CO2 over 30-year project. Although policies and methods are available for implementing the project, sustained commitment and law enforcement play an increasingly important role in achieving real emission reduction and sustainable development.
Accounting for up to 25% of global carbon emissions, tropical deforestation and forest degradation have increasingly brought international attention. The recognition of reducing emissions from deforestation and forest degradation, forest conservation, sustainable forest management, and enhancing carbon sinks in tropical forests (REDD+) in the Copenhagen Accord and the pledge of $3.5 billion fast-start climate finance for REDD+ preparatory activities suggests that appropriate approaches to managing tropical forests become necessary. As REDD+ involves the carbon-based financial compensation, avoided carbon emissions from the forests needs to be assessed. Here, we develop a carbon stock model for projecting carbon stock changes under two management scenarios, namely the baseline (business-as-usual) and REDD+ management. Baseline scenario is the management of forest using conventional logging practice, while REDD+ scenario involves the use of reduced impact logging (RIL) and RIL plus liberation treatment (RIL+). Our results suggest that REDD+ scenario could avoid carbon emissions of 2.06 MgC ha−1 at the beginning of the management to 36.76-54.26 MgC ha−1 at year 60 of the management. The REDD+ revenues from carbon sales are estimated at just about $2 in the first year to $107 and $159 ha−1 under RIL and RIL+, respectively. REDD+ agreements will ensure the adoption of REDD+ scenario for managing tropical forests.
The objective of this study is to develop a forest landscape zoning method using the geographical information system (GIS). The method consists of landscape resources assessment procedures which include the inventory process for identifying landscape resources and the evaluation process for analyzing detailed landscape attributes. This method was applied to a case study of a forest scenery management project in the area of Mt. Sambong in South Korea. Initially, the natural and artificial landscape resources were identified and mapped using GIS. Next, the landscape sensitivity was measured in terms of visibility and visual absorption capability (VAC) using GIS to quantify the relative importance of the features identified in a landscape inventory. Then, the scenic attractiveness of the landscape unit was analyzed to estimate the landscape value. The landscape value was estimated as the function of the quality and quantity of various landscape resources as well as the intrinsic beauty of the scenery as influenced by historical and cultural features. Based on the landscape sensitivity and value obtained, the zoning of the mountain forest for landscape management was done.
Forest management changed markedly in the Czech Republic and Slovakia after 1989. Following the denationalization of forestlands, forest managers became more concerned about sustainable timber production and the environmental impact of harvest operations. Current national forest laws in both countries prescribe a shelterwood silvicultural system, but clear-cutting according to harvest scheduling by allowable cut indicators is still the most widely used management system. As an alternative to allowable cut indicators, we investigate spatially constrained harvest scheduling under a shelterwood system. Our study design considers both spatial and non-spatial constraints. The first spatial constraint concerns adjacency—managers cannot simultaneously harvest trees from adjacent areas. The second is an environmental requirement to reserve a specific portion of the stand. Non-spatial constraints include factors such as the upper limit of harvest determined by an owner’s harvest flow requirements. We developed and compared three alternatives, which employ different constraints to investigate their respective influence. We used integer programming to find the optimal solution for each alternative under spatially constrained harvest scheduling and compared these results with the allowable cut indicators method. Our results showed that total net present value is smaller for the alternative with a reserve constraint and even ﬂow harvest requirements. Moreover, in each simulation period, this alternative consistently minimized the diﬀerence in volume derived between the spatially constrained and allowable cut harvest scheduling systems. The diﬀerence in total cut and total net present value between the two harvest scheduling systems was 0.34% and 2.33%, respectively.
Wind damage to coniferous plantation forests containing sugi (Cryptomeria japonica) and hinoki (Chamaecyparis obtusa) was studied in Japan. Wind conditions determined using an air flow simulation model, historical wind disturbance records and remote sensing measurements were integrated within a geographic information system (GIS). Based on the data set, the relationships between wind disturbances, wind speed and stand height were analyzed. A logistic analysis technique was applied to assess the probability of wind disturbance in stands that remained intact or were damaged as a result of the typhoon. The results indicate that higher wind speeds and greater stand heights increase the probability of wind disturbance in both sugi and hinoki plantation forests. The logistic regression model enabled us to predict the likelihood of wind disturbance at our study site. Our results confirmed that it is possible, using wind condition prediction software, to analyse wind disturbance in sugi and hinoki plantation forests.
A single-tree selection system has been widely employed to manage natural forests in Hokkaido, Northern Japan. Tree marking is an essential component of this system; the procedure involves careful selection of trees for harvest according to forest management objectives. Practically speaking, forest managers make tree marking decisions based on their skills gained through training and experiences. While the information on where marked trees are located has traditionally been somewhat difficult to precisely document, recent advancements in global positioning system (GPS) technology could enable managers to pinpoint the geographic location. This paper presents a practical application of GPS technology for tree marking in a single-tree selection forest management system. A total of 1,565 trees were selected and marked for harvest within an area of 29.23 ha at the University of Tokyo Hokkaido Forest. A handheld GPS receiver was used to record the coordinates of all marked trees. To examine positional accuracy, we surveyed the coordinates of 43 marked trees using a closed traverse survey and laser rangefinder with an electronic compass module. Mean positional accuracy of the GPS receiver was 5.7 m, and we observed a variety of harvest intensities over the study site. Results suggest GPS technology is a useful tool for improving the precision of forest management activities under a single-tree selection system.
In searching for an appropriate time series model based on historical data we applied unit root tests and considered 12 different continuous-times stochastic models prices of six saw log and pulp wood products from two important species of Scots pine (Pinus.sylvesteris) and Norway spruce (Picea.abies), as well as, average softwood log prices for annual long run and shorter monthly time series in the Finnish wood market. For each product we conducted a comparative analysis between models on the basis of Akaike’s Information criteria (AIC), the mean square error (MSE) of the models after one period of forecasting, and a likelihood ratio test. Parameter estimation was performed by quasi maximum likelihood estimation and local linearization method. The unit root tests results showed that while in the long run the price of softwood is trend stationary, in short run it shows non-stationary behaviour. Our results also showed that the level of effect of state the variable on volatility has a major role in refining a general model in to simpler models. The model with a general form of diffusion and no drift yields the highest AIC for most products, and the diffusion part of the model plays an important role in ranking by AIC, while in ranking by MSE for one period of forecasting, the drift part of models plays important role.
The objective of this study is to modify the process-based stand growth model for Cryptomeria japonica in the photosynthetic production process so as to more reasonably represent the stand growth pattern after thinning. We introduce five leaf strata to the canopy structure, and then parameterize the light-curve for each leaf stratum by Bayesian calibration via the Markov Chain Monte Carlo (MCMC) method. We examine the behavior of the model using the estimated light-curve parameters through a simulation approach. We used the forest stand data derived from repeated measurements of three permanent plots. The posterior distribution of light-curve parameters derived from MCMC were well converged. We virtually applied three thinning scenarios, upper thinning, random thinning and lower thinning, and then simulated stand growth. The modified model could well reflect the changes in canopy structure derived from thinning on the growth pattern after thinning. The results suggest that the multiple light-curve model adopted in this study would be represent more realistic stand dynamics after thinning than single light-curve model adopted in the former model.
The objective of this research is to analyze the impact on the global forest sector of changes in China's domestic market and international trade in forest products. Price and income elasticities of demand for seven forest products are estimated using cluster analysis combined with panel data analysis. Cluster analysis is used to group countries by their levels of per capita gross domestic product (GDP), per capita consumption of forest products and forest coverage rates. Panel data analysis is then undertaken for each cluster, and price and income elasticities for every cluster are estimated. We used the estimated elasticities of demand and other exogenous parameters, including GDP growth, in the Global Forest Products Model (GFPM) to simulate the global forest sector through 2030. The GFPM is a dynamic economic equilibrium model encompassing 180 countries and 14 forest products. The GFPM results show that China is likely to continue to rely on foreign raw materials, leading to increases in consumption in Asia and throughout the world and in prices of forest products. A lower GDP growth for China would lead to lower world consumption of forest products and to lower prices. The GFPM results also show that Japan and South Korea (hereafter Korea) could take advantage of the lower prices to import more raw materials if China were to consume less. Increases in manufacturing costs in China could lead to a signiﬁcant decrease in consumption in China, to less of an impact in Japan and Korea and to greater consumption and fewer exports in Africa and Oceania.
While there is much interest by NGOs and environmental groups in the potential of non-timber forest products (NTFP) programs to simultaneously achieve conservation and poverty alleviation, there is not a great deal of understanding of whether they work in practice, and how incentives and local management do, indeed affect poverty and local resource use. In this paper I propose a methodology to analyze the potential impacts that price increases can have on the income that extractors receive from NTFP extraction. The case study illustrates how one could evaluate the effectiveness of different price scenarios. It also shows the kind of biologic and socioeconomic information that is needed to apply the methodology suggested. The more accurate the information is the more confident one can be about the policy recommendations. This is an area of opportunity where applied research between economists and ecologists can lead to concrete policy applications.
Cork oak (Quercus suber L.) woodlands (montado) consist of a multifunctional forest system that covers about 713,000 ha in Portugal. Today, its importance stems from cork production, with Portugal producing half of the cork in the world. As the main economic objectives may change with changes in markets and environment conservation concerns (e.g. biodiversity, water, carbon) there is a need for improved management tools. Spatial tree growth simulators are tools that enable the generation of tree growth scenarios dependent on site and competition status, that allow to simulate large scope management actions. In the present work it is presented a cork oak tree spatial growth simulator, CORKFITS, that was constructed with data generated by the monitoring system installed in 1995. The simulator was built assuming the potential increment modifier principle: z = zpot * modifier + ε, where zpot is the potential growth as function of site; modifier is the reduction factor as function of spatial competition index and the intensity of debark; ε is a random error. CORKFITS is composed by sub growth models (cork, stem, tree height and crown), cork production models and mortality models. Single trees are in cork oak woodlands subjected to natural (genetics and competition) and artificial (debark, crown pruning, root pruning) factors that affects their growth therefore there is a large amount of unexplained variability which creates problems in the modeling phase, the solutions for these problems will be discussed in the present work
New methods of forest management and the study of their impact on sustainability are strongly dependent on realistic mathematical modelling. The complexity of the models however, makes the use of computational power, and thus the incorporation of knowledge from computer science and research, indispensable. In this paper we wish to demonstrate the development of a simulator for the growth and production of cork oak woodlands –montados. The software is divided into three sub-modules, sharing a common core, with functions and mathematical operations. The desktop client allows for repeated operations for more intense calculations, and statistical operations for modelling purposes. The web version is intended to be used by final users in forest practice. It permits simulation of inventory data based on individual tree measurements, and inventory data based on plot description with a reduced amount of detail (number of trees per ha, diameter structure, etc.) The last module allows the incorporation of the cork model into other software by means of SOAP protocol, via web services. It conforms to the WS-I Basic Profile 1.1, to ensure interoperability among the largest number of clients. This module allows other developers to use the cork oak growth-model in their software, and the developers from other areas of expertise (management optimisation, decision support...) have the opportunity to test their techniques on real stands, with the most recently-updated model versions.