Current Forest Area Research Articles

ANALISIS EVALUASI EKONOMI SUMBER DAYA ALAM DAN LINGKUNGAN DI KABUPATEN KONAWE SELATAN

The condition of natural resources of forests and agricultural land, especially in South Konawe Regency, is currently quite a concern. South Konawe Regency has a forest area with a total area of 475,953 hectares, consisting of natural reserve forests, protected forests, production forests, limited production forests, other use areas, water bodies, community plantation forests, urban forests, mangrove forests and conservation forests. Among the total current forest area, there are 31,874 hectares of critical land and 6,606 hectares of very critical land. The aim of the research is to inventory the potential and management problems as well as the economic value of natural forest and agricultural land resources in South Konawe Regency. The research approach uses 5 (five) approach models, namely the political approach, the technocratic approach, the integrated top-down policy bottom-up planning approach, the participatory approach, and the regional finance approach. The type of research used in this research is qualitative research with a case study method. Research data needs were collected using questionnaires and field surveys. The data analysis methods used include Natural Resource Potential Analysis, Identification of natural resources in forests and agricultural land, as well as total economic analysis or total economic value (TEV) obtained from the sum of values based on use and values based on indirect use. The research results show that the potential forest resources of South Konawe Regency with samples from Wolasi, Laeya, and Tinanggea subdistricts are divided into 4 forest area function classes, namely protected forests, permanent production forests, limited production forests, and national parks. Protected forests covering an area of 11,273.58 ha, limited production forests covering an area of 2,860.99 ha, permanent production forests covering an area of 14,931.17 ha, and national parks covering an area of 9,246.96 ha. Meanwhile, the agricultural potential of South Konawe Regency from the research sample consists of mixed dry land farming covering an area of 14,787.73 ha, dry land farming covering an area of 1,684.39 ha, rice fields covering an area of 17,014.23 ha, and plantations covering an area of 553.44 ha. The economic value of South Konawe district's forest resources is IDR 64,152,630,168.15 per year, while the economic value of agricultural land resources is IDR 9,342,541,716/year.

Forestation at the right time with the right species can generate persistent carbon benefits in China

Previous evaluations on the biophysical potential of forest carbon sink have focused on forestation area distribution and the associated carbon stock for equilibrium-state forests after centuries-long growth. These approaches, however, have limited relevance for climate policies because they ignore the near-term and mid-term decadal carbon uptake dynamics and suitable forest species for forestation. This study developed a forestation roadmap to support China's "carbon neutrality" objective in 2060 by addressing three key questions of forestation: where, with what forest species, and when to afforest. The results yielded a high-confidence potential forestation map for China at a resolution of 1 km with the identified optimal native forest type or species. Our analysis revealed an additional 78 Mha suitable for forestation up to the 2060s, a 43% increase on the current forest area. Selecting forest species for maximal carbon stock in addition to maximizing local environmental suitability enabled almost a doubling in forest carbon sink potential. Progressive forestation of this area can fix a considerable amount of CO2 and compensate for the carbon sink decline in existing forests. Altogether, the entire forest ecosystem can support a persistent biophysical carbon sink potential of 0.4 Pg C y-1 by 2060 and 0.2 Pg C y-1 by 2100, offsetting 7 to 14% of the current national fossil CO2 emissions. Our research provides an example of building a forestation roadmap toward a sustained forest carbon sink, which creates a critical time window for the emission cuts required by the goal of carbon neutrality.

Monitoring Illegal Logging Using Google Earth Engine in Sulawesi Selatan Tropical Forest, Indonesia

Forest destruction has been found to be the cause of natural disasters in the form of floods, landslides in the rainy season, droughts in the dry season, climate change, and global warming. The high rate of forest destruction is caused by various factors, including weak law enforcement efforts against forestry crimes, such as illegal logging events. However, in Indonesia, illegal logging is only discovered when the perpetrator has distributed the wood products. The lack of monitoring of the overall condition of the forest has an impact on the current high level of forest destruction. Through this research, the problems related to environmental damage due to illegal logging will be described through remote sensing technology, which is currently mainly developed on the basis of artificial intelligence and machine learning, namely Google Earth Engine (GEE). Monitoring of illegal logging events will be analysed using Sentinel 1 and 2 data. Obtaining satellite imagery with relatively small cloud cover for tropical regions, such as Indonesia, is remarkably difficult. This difficulty is due to the presence of a radar sensor on Sentinel 1 images that can penetrate clouds, allowing for observation of the forest condition even in the presence of clouds. Using the random forest classification algorithm of the GEE platform, data on forest conditions in 2021 were obtained, covering an area of 2,843,938.87 ha or 63% of the total area of Sulawesi Selatan Province. An analysis using a map of the function of forest areas revealed that of the current forest area, 38.46% was non-forest estates and 61.54% was forest areas. The continued identification of illegal logging events also found 1971 spots of forest change events in the vulnerable time of the first period (January–April) with the second period (April–August), and 1680 spots of forest change events in the vulnerable period of the second period (April–August) with the third period (September–December), revealing a total incident area of 7599.28 ha.

Historical landscape matters for threatened species in French mountain forests

Ancient forests are known to host a biodiversity of high ecological distinctiveness and are likely to provide habitat for red-listed species. Yet, few studies have investigated the role of forest continuity for the conservation of threatened species. We used species-presence data on red-listed species from 12 taxonomic groups (Spermatophyta, Pteridophyta, Bryophyta, Lichens, Chiroptera, Aves, Squamata, Amphibia, Coleoptera, Lepidoptera, Odonata and Orthoptera) to ascertain if ancient forests are an important habitat for threatened species in five mountain and subalpine protected areas in France. We compared the effect of the amount of historical forest (1853–1860) with the effect of the amount of current forest on the distribution of red-listed species in six circular landscape buffers ranging in radius from 100 to 1500 m. We showed that the amount of historical forest in the landscape had a positive effect on forest Spermatophyta, Bryophyta, Coleoptera and edge forest Pteridophyta with a better predictive power than current forest area, highlighting a colonization credit in recent forests. Conversely, edge-forest lepidopterans were more negatively affected by historical than by current forest area, highlighting an extinction debt in recent forests. Our findings underline that implementing protective measures of ancient forests would be a better strategy than afforestation to preserve threatened forest species in mountain and subalpine forest landscapes.

Comparative life cycle assessment of cross laminated timber building and concrete building with special focus on biogenic carbon

This study conducted a consequential Life Cycle Assessment (LCA) on two similar mid-rise apartment buildings applying either concrete or cross laminated timber (CLT) as the main structural material. The study further investigated inclusion of biogenic carbon and how this affects environmental impacts related to Global warming. Thus, two assessment scenarios were applied: A Base scenario, without accounting for biogenic carbon and a Biogenic carbon scenario that include a GWPbio factor to account for the use of biogenic carbon. The CLT building had the lowest impact score in 11 of 18 impact categories including Global warming. Operational energy use was the main contributor to the total impact with some variation across impact scores, but closely followed by impacts embodied in materials (incl. End-of-Life). An evaluation of the potential forest transformations required for fulfilling future projections for new building construction in 2060 showed that about 3% of current global forest area would be needed. This share was essentially independent of the selected building material as the main driver for forest transformation was found to be energy use during building operation. Thus, focus should primarily be on reducing deforestation related to energy generation rather than deforestation from production of building materials.

Investigation of the Change of Wooded Aareas in Forest Land in Raudone Eldership

Under the conditions of a global reduction in forest areas and climate change, it is important to preserve as many tree-covered areas as possible and understand change trends. The article purpose – aims at identifying forest area change trends of 19th-20th c. in the current forest land of the eldership Raudonė. In the research, historical topographic maps compiled during different periods, and 2019 data from the forest registry are used. The research method of a comparative analysis is employed. The change in forest areas was analysed, and forest areas that remained unchanged for 200 years were identified. The comparison of current forest areas reflected in the cadastral data and forest areas of the considered period allowed identifying the tendency of assigning land the purpose of forest land. During the research, the period with largest forest areas was determined to be the 19th c., and with the smallest – 1st half of the 20th c. During the Soviet period, forests areas were increasing, but did not achieve the same level as in the 19th c.

Enhancing the precision of broad-scale forestland removals estimates with small area estimation techniques

Abstract National Forest Inventories (NFI) are designed to produce unbiased estimates of forest parameters at a variety of scales. These parameters include means and totals of current forest area and volume, as well as components of change such as means and totals of growth and harvest removals. Over the last several decades, there has been a steadily increasing demand for estimates for smaller geographic areas and/or for finer temporal resolutions. However, the current sampling intensities of many NFI and the reliance on design-based estimators often leads to inadequate precision of estimates at these scales. This research focuses on improving the precision of forest removal estimates both in terms of spatial and temporal resolution through the use of small area estimation techniques (SAE). In this application, a Landsat-derived tree cover loss product and the information from mill surveys were used as auxiliary data for area-level SAE. Results from the southeastern US suggest improvements in precision can be realized when using NFI data to make estimates at relatively fine spatial and temporal scales. Specifically, the estimated precision of removal volume estimates by species group and size class was improved when SAE methods were employed over post-stratified, design-based estimates alone. The findings of this research have broad implications for NFI analysts or users interested in providing estimates with increased precision at finer scales than those generally supported by post-stratified estimators.

Desa’a national forest reserve susceptibility to fire under climate change

Climate change influences spreading and occurrence of forest fire. Forest fire modeling is one of the most important tasks to fight forest fires. Climate data of current (1980–2010) was projected to near (2010–2039), mid (2040–2069) and end-term (2070–2099) using Representative Concentration Pathway (RCP4.5 and 8.5) of an ensemble of twenty General Circulation Models using R-software. Current and projected climate data were used to determine the impact of climate change on current and future forest fire using Keetch-Byram Drought Index. Current and future forest fire-vulnerable areas were mapped and weighed using Inverse Distance Weighting. The result indicates that, while no forest fire occurrence in the current, there might be a high forest fire risk in near-term. It might be become very high in mid and end-term. The size of forest fire-vulnerable areas might be increased to 12.85, 18.8, 17.1 and 46.26% in Mid-RCP4.5, Mid-RCP8.5, End-RCP4.5 and End-term-RCP8.5 respectively. Fire may occurred in winter and spring seasons. The risk might be move to higher elevation of the forest. This directs increase of forest fire occurrence and spread due to climate change. The study recommends that forest fire management should be applied before fire happened to sustain the forest and its products.

Forest management practice for enhancing carbon sequestration in national forests of Korea

This paper examines forest management planning and its possible outcomes using linear programing (LP). More specifically, the most appropriate forest harvesting schedule was selected that can maximize the carbon sequestration in the current forest areas considering forest manager’s income. The LP model allows the managers to segment forests into cutting units under rotation basis logging activities. Through harvest prescription from LP, we derived the balanced age-class distribution that constitutes improved conditions for sustainable use of forest resource. However, the solutions from LP did not achieve normal forests with perfectly even aged distribution. Instead, it produced a left-skewed age-class distribution due to the cost restriction of management ruling out the achievement of a normal forest as an optimal solution. The results from our LP model also confirm that the forest management activities will enhance yearly carbon sequestration in forests for all scenarios compared to baseline, and the shorter rotation ages tend to call for more carbon sequestration and economic profit. However, it is difficult to ensure that 50 years rotation is the optimal rotation age for the target forests, since we do not consider the benefit of biodiversity conservation.

An ecosystem risk assessment of temperate and tropical forests of the Americas with an outlook on future conservation strategies

AbstractForests of the Americas and the Caribbean are undergoing rapid change as human populations increase and land use intensifies. We applied the IUCN Red List of Ecosystems (RLE) criteria and simple cost‐efficiency analyses to provide the first regional perspective on patterns of relative risk integrated across multiple threats. Based on six indicators of ecosystem distribution and function, we find that 80% of the forest types and 85% of the current forest area is potentially threatened based on RLE criteria. Twelve forest types are Critically Endangered due to past or projected future deforestation, and Tropical Dry Forests and Woodland have highest threat scores. To efficiently reduce risks to forest ecosystems at national levels, scenario analyses show that countries would need to combine large forest protection measures with focused actions, tailored to their sociopolitical context, to help restore ecological functions in a selection of threatened forest types.

Responses of the Carbon Storage and Sequestration Potential of Forest Vegetation to Temperature Increases in Yunnan Province, SW China

The distribution of forest vegetation and forest carbon sequestration potential are significantly influenced by climate change. In this study, a map of the current distribution of vegetation in Yunnan Province was compiled based on data from remote sensing imagery from the Advanced Land Observing Satellite (ALOS) from 2008 to 2011. A classification and regression tree (CART) model was used to predict the potential distribution of the main forest vegetation types in Yunnan Province and estimate the changes in carbon storage and carbon sequestration potential (CSP) in response to increasing temperature. The results show that the current total forest area in Yunnan Province is 1.86 × 107 ha and that forest covers 48.63% of the area. As the temperature increases, the area of forest distribution first increases and then decreases, and it decreases by 11% when the temperature increases from 1.5 to 2 °C. The mean carbon density of the seven types of forest vegetation in Yunnan Province is 84.69 Mg/ha. The total carbon storage of the current forest vegetation in Yunnan Province is 871.14 TgC, and the CSP is 1100.61 TgC. The largest CSP (1114.82 TgC) occurs when the temperature increases by 0.5 °C. Incremental warming of 2 °C will sharply decrease the forest CSP, especially in those regions with mature coniferous forest vegetation. Semi-humid evergreen broad-leaved forests were highly sensitive to temperature changes, and the CSP of these forests will decrease with increasing temperature. Warm-hot coniferous forests have the greatest CSP in all simulation scenarios except the scenario of a 2 °C temperature increase. These results indicate that temperature increases can influence the CSP in Yunnan Province, and the largest impact emerged in the 2 °C increase scenario.

Assessment of various practices of the mitigation of N2O emissions from the arable soils of Poland

Abstract This review assesses the adaptability and effectiveness of the basic practices to mitigate the N2O emissions from the arable land in the climate, soil and agricultural conditions of Poland. We have analyzed the decrease in the nitrogen-based fertilization, selection of the fertilizer nitrogen forms, use of biological inhibitors of nitrogen transformation in the soil, control of the acidic soil reaction, reduction in the natural fertilizers use and afforestation of the low productive soils. The challenge evaluating the effectiveness of mitigation practices lies in the inadequacy of the national data on N2O soil emissions in particular agrotechnical conditions. In Poland, circumstances that favor intensive N2O emissions from the arable soils occur uncommonly, as shows the analysis of the literature reporting on the country climate, soil and agricultural conditions alongside the N2O emissions from soils under various cultivation conditions. Consequently, the effectiveness of mitigation practices that relies on an extensification of plant production may be insufficient. It can be assumed that, at the doses of nitrogen fitting the nutritional needs of crops, the soil N2O emissions are low and do not meaningfully differ from the emissions from untreated soils (literature data point to limited N2O emission from arable soils treated with N doses of ≤150-200 kg N·ha-1). The effectiveness of the nitrogen fertilization reduction as an N2O emissions mitigation practice is restricted to intensive farming. A universal registry of the mineral and natural fertilization use could help identify the agricultural holdings with a potential for high N2O emission and foster a targeted application of mitigation practices. It is suggested that normalization and maintenance of the optimum (i.e. close to neutral) soil pH should become a more common practice of N2O emissions mitigation in Poland in view of the extent of arable soils acidification and the literature data that indicate elevated N2O emissions from acid soils. Application of urease and nitrification inhibitors alongside nitrogen fertilization can be considered an effective practice of N2O emissions mitigation. Owing to economic reasons the use of nitrogen fertilizers with such additives is currently limited to non-agricultural segments of plant production. Afforestation of the low productive soils offers an attractive opportunity for mitigation of N2O emissions. Whereas N2O emissions from forest soils are considerably lower compared with those from the arable ones, the literature indicates that no N2O emissions mitigation is attained through a conversion of arable land to agroforestry. Considering the current forest area of Poland (24.9% of the total area) and the plans to increase the afforestation rate (to 33% in 2050) the measurable effects of this mitigation practice will only be seen in a long-term perspective. Besides identifying and excelling the mitigation practices the authors postulate a review of the algorithms employed by the National Centre for Emissions Management (KOBiZE) for the calculation of the GHG emissions. Solutions applied by KOBiZE appear to address mainly the area - or population-related aspects and, to a much lesser degree, the actual N2O production. In this context, the effects of certain N2O emissions mitigation practices might be difficult to be taken into consideration. The application of national statistics of the use of mineral and natural fertilizers to the calculation of the N2O emissions from the arable soils might be questioned given that the N2O emissions are driven by the actual local N dose.

Assessing soil organic carbon stocks under current and potential forest cover using digital soil mapping and spatial generalisation

Forest soils are important components in the global C-cycle. Regional soil organic carbon (SOC) stock assessments are hampered by low spatial densities of routine soil inventories. In this study, we estimated the SOC stock in the upper meter of forest in the region of Flanders (N. Belgium) using four digital soil mapping techniques, i.e. multiple linear regression (MLR), boosted regression trees (BRT), artificial neural networks (ANN) and least-squares support vector machines (LS-SVM), and compared them with the results of a multi-level spatial generalisation (MLSG) approach.Applied to a collection of 276 soil profiles, we identified the highest groundwater level, clay fraction, tree genus and soil type as key predictors of the SOC stock in the upper 100cm under forests. Overall, BRT was the most informative as it obtained the best fit (training R2 of 0.68, cross-validated R2 of 0.22) and provided insights in the soil system by showing average predictor effects in partial dependence plots. With BRT, the total stock in the upper meter of forest soil (153,544ha) was estimated to be 26.99 Mt OC, or 17.58kgm−2 on average. MLSG provided an estimate for only 90% of the forest area and resulted in a larger average stock of 18.22kgm−2 due to larger predictions for Histosols. As a null model, i.e. assuming that the potential natural dominant tree genus would occur according to the present soil conditions, the SOC stock in the current forest area was estimated at 30.00 Mt OC, or 21.26kgOCm−2 on average. When the complete non-built-up territory (1,168,850ha) would be forested analogously, 255.28MtOC would be stored, which is more than double the amount of predictions under the actual land cover. The results highlight the importance to conserve and restore carbon hotspots like alluvial forests. New soil inventories should focus on these and other data-scarce land units. Future modelling approaches can benefit from explicitly taking the soil type and tree genus into account as predictors.

ЭКОНОМИЧЕСКАЯ ОЦЕНКА ЭКОСИСТЕМНЫХ УСЛУГ В ТАВУШСКОЙ ОБЛАСТИ РЕСПУБЛИКИ АРМЕНИЯ

The paper analyses the processes of soil degradation which are caused by deforestation and agricultural expantion in Tavushskaya oblast' of Armenia. This includes soil compaction, plant formation loss, intense water and wind erosion on grazelands caused by increase of sheep herd; and soil nutrition losses as a result of drawbacks of land cultivation on hillside cropland. Following the reasons of soil erosion we suggest three scenarios of agricultural and forest land application. The first scenario depicts the current growth rates of deforestation and transforming these areas into cropland, but with time limits of land use because of continuous soil nutrition loss. The second scenario shows the consequences of stopping deforestation and saving current forest area. Finally the third scenario keeps the current forest areas and transforms the degraded grazelands into forestland with a 10% growth rate per decade. Using TEEB methodology for each scenario we calculate the economic value of local ecosystem services, which could be provided from 1 ha in this region for the bext thirty years. The results show that the first scenario gives $ 16 202, the second $32 776 – 1 312 561, and the third $33 904 – 1 359 678 diapason value of potential ecosystem services per 1 hectare. This all means that it is reasonable to save and regenarate forest land, which help to resist soil erosion and thus have positive effect on food security in the region.

Potential change in forest types and stand heights in central Siberia in a warming climate

Previous regional studies in Siberia have demonstrated climate warming and associated changes in distribution of vegetation and forest types, starting at the end of the 20th century. In this study we used two regional bioclimatic envelope models to simulate potential changes in forest types distribution and developed new regression models to simulate changes in stand height in tablelands and southern mountains of central Siberia under warming 21st century climate. Stand height models were based on forest inventory data (2850 plots). The forest type and stand height maps were superimposed to identify how heights would change in different forest types in future climates. Climate projections from the general circulation model Hadley HadCM3 for emission scenarios B1 and A2 for 2080s were paired with the regional bioclimatic models. Under the harsh A2 scenario, simulated changes included: a 80%–90% decrease in forest-tundra and tundra, a 30% decrease in forest area, a ∼400% increase in forest-steppe, and a 2200% increase in steppe, forest-steppe and steppe would cover 55% of central Siberia. Under sufficiently moist conditions, the southern and middle taiga were simulated to benefit from 21st century climate warming. Habitats suitable for highly-productive forests (≥30–40 m stand height) were simulated to increase at the expense of less productive forests (10–20 m). In response to the more extreme A2 climate the area of these highly-productive forests would increase 10%–25%. Stand height increases of 10 m were simulated over 35%–50% of the current forest area in central Siberia. In the extremely warm A2 climate scenario, the tall trees (25–30 m) would occur over 8%–12% of area in all forest types except forest-tundra by the end of the century. In forest-steppe, trees of 30–40 m may cover some 15% of the area under sufficient moisture.

Design of a New Energy Efficient L4 Leach Protocol based Visual Sensor Network for Forest Monitoring System

Current Forest area monitoring systems often rely on building regulations for maximum sensor nodes to maintaining proper logging. However, in many situations, there are sensor nodes that are used infrequently, and may be drained or detached from the network needlessly. Having knowledge regarding power consumption and being able to accurately predict usage patterns may allow significant energy-savings by intelligent control of the management systems. In this paper, we report on the deployment of a grid based wireless visual sensor network architecture for collecting data which may be used to detect unauthenticated logging, animal census, weather monitoring in a large multi-forest environment that estimates livelihood with an accuracy of 70%. The framework system consist improved L4 Leach protocol for promoting effective energy consumption. Using data collected from this framework, we can construct agent based models for predicting mobility patterns in the forest with support of our L4 Leach protocol. Our simulation indicates a 14% reduction in energy usage by having an optimal control strategy based on energy draining parameters estimates and usage patterns.

Environmental flow provision: Implications for agricultural water and land-use at the global scale

Human activity has led to freshwater ecosystem degradation in the past and is likely to continue doing so if no appropriate protection mechanisms are implemented. One potential protection measure is the reallocation of water from human use to environmental purposes – also called environmental flows. Such reallocation may decrease the availability of irrigation water with possible adverse effects on agricultural production. In this analysis, we provide an initial quantitative estimate of how the allocation of annual volumes of water for environmental flow protection (EFP) might influence the food production system on a global scale. The application of a spatially explicit global land and water-use allocation model (MAgPIE) allows us to explore the effect of EFP on agricultural water withdrawals. We will also examine associated reactions in terms of land-use changes and agricultural intensification. Our results suggest that the implications of conserving annual volumes of water for EFP on the land-use system are moderate on an aggregate global level. Cropland expansion into unmanaged land arising from increased food demand up to 2045 is higher by a factor 5–9 than cropland expansion induced by EFP. Global forest losses associated with EFP remain below 1% of current forest area. Production reallocation and associated land-use change hotspots suggest that local effects are of more concern than aggregate cropland expansion and deforestation.

A multi-model assessment of climate change impacts on the distribution and productivity of ecosystems in China

Potential twenty-first century changes in vegetation distribution and net primary production in China were assessed using three different vegetation models, including new process-oriented but observationally based models for net primary production and vegetation distribution. Climate change projections were derived from a set of seven global climate model outputs, pattern scaled to yield a 2 °C global warming by mid-century. The effects of the climate changes were assessed for the last three decades of the century, by which time global warming has reached 4 °C, with atmospheric carbon dioxide concentration ([CO2]) prescribed at 750 ppm. This scenario results in a limited northward expansion of tropical forests along China’s southern coast, and a larger northward shift of subtropical forest into the current temperate forest and crop areas. Alpine vegetation on the Tibetan Plateau is largely replaced by boreal and subalpine forest or shrubland. The largest uncertainties (differences between climate and/or vegetation models) occur in northeastern China. However, all models agree on shrinkage of boreal forests in the northeast and the effects of [CO2] in promoting woody vegetation at the expense of grasslands. The current cropping systems in North China extend further northward and westward. The productivity of forests in South China increases in all models, although the magnitude of the [CO2] effect remains uncertain.

Simulating Future Forest Cover Changes in Pakxeng District, Lao People’s Democratic Republic (PDR): Implications for Sustainable Forest Management

Future forest cover changes were simulated under the business-as-usual (BAU), pessimistic and optimistic scenarios using the Markov-cellular automata (MCA) model in Pakxeng district, Lao People’s Democratic Republic (PDR). The Markov chain analysis was used to compute transition probabilities from satellite-derived forest cover maps (1993, 1996, 2000 and 2004), while the “weights of evidence” procedure was used to generate transition potential (suitability) maps. Dynamic adjustments of transition probabilities and transition potential maps were implemented in a cellular automata (CA) model in order to simulate forest cover changes. The validation results revealed that unstocked forest and current forest classes were relatively well simulated, while the non-forest class was slightly underpredicted. The MCA simulations under the BAU and pessimistic scenarios indicated that current forest areas would decrease, whereas unstocked forest areas would increase in the future. In contrast, the MCA model projected that current forest areas would increase under the optimistic scenario if forestry laws are strictly enforced in the study area. The simulation scenarios observed in this study can be possibly used to understand implications of future forest cover changes on sustainable forest management in Pakxeng district.

Spatial Simulation Modelling of Future Forest Cover Change Scenarios in Luangprabang Province, Lao PDR

Taking Luangprabang province in Lao Peoples’s Democratic Republic (PDR) as an example, we simulated future forest cover changes under the business-as-usual (BAU), pessimistic and optimistic scenarios based on the Markov-cellular automata (MCA) model. We computed transition probabilities from satellite-derived forest cover maps (1993 and 2000) using the Markov chains, while the “weights of evidence” technique was used to generate transition potential maps. The initial forest cover map (1993), the transition potential maps and the 1993–2000 transition probabilities were used to calibrate the model. Forest cover simulations were then performed from 1993 to 2007 at an annual time-step. The simulated forest cover map for 2007 was compared to the observed (actual) forest cover map for 2007 in order to test the accuracy of the model. Following the successful calibration and validation, future forest cover changes were simulated up to 2014 under different scenarios. The MCA simulations under the BAU and pessimistic scenarios projected that current forest areas would decrease, whereas unstocked forest areas would increase in the future. Conversely, the optimistic scenario projected that current forest areas would increase in the future if strict forestry laws enforcing conservation in protected forest areas are implemented. The three simulation scenarios provide a very good case study for simulating future forest cover changes at the subnational level (Luangprabang province). Thus, the future simulated forest cover changes can possibly be used as a guideline to set reference scenarios as well as undertake REDD/REDD+ preparedness activities within the study area.