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Atsushi Yoshimoto 《Journal of Forest Research》2001,6(1):21-30
The objective of this paper is to investigate potential use of a spatially constrained harvest scheduling model for biodiversity
concerns. Change in the degree of biodiversity is represented only by spatial characteristics of harvesting patterns of forest
stands with different exclusion periods applied to adjacent forest stands. A spatially constrained harvest scheduling model
called SSMART (Scheduling System of Management Alternatives foR Timber-harvest) is used for the analysis. It is one of the
heuristics to solve a spatially constrained harvest scheduling problem by using the partitioning heuristic. The algorithm
incorporated into SSMART is designed to seek a solution for a multicriteria problem with present net value maximum, meeting
spatial feasibility and minimizing period-to-period harvest flow fluctuation, approximating even-flow constraints within the
0–1 integer programming framework. Our experimental analysis shows that the longer exclusion period, the less the harvest
flow level and the total present net value are derived and the more heterogeneous the forest structure becomes in terms of
the forest stand age distribution. It is also shown that the three exclusion period results in a stable forest stand age distribution
over the time horizon for our experimental forest.
This research supported by the Grants-in-Aid for Scientific Research (No. 09041071) from the Ministry of Education, Science,
Sports, and Culture of Japan. 相似文献
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The protection of people, buildings and infrastructure against natural hazards is one of the key functions of mountain forests. Since the protective function strongly depends on small-scale local conditions such as terrain and stand characteristics, spatially explicit evaluation methods are necessary to provide information required for an effective and cost-efficient forest management. Risk analyses are recognized as the best method for estimating the danger from various natural hazards. Currently, however, risk-based strategies are rarely addressed in the management of protection forest. We present and discuss a risk-based approach to evaluate the protective effect of mountain forests in a spatially explicit manner to demonstrate the advantages of future risk-based protection forest management. We illustrate the approach by performing a GIS-based risk analysis in the case study area ‘Bannwald of Andermatt’ (Switzerland) for a 300-year snow avalanche event. Classifying forest structures based on aerial photographs allowed developing different forest cover scenarios and modeling potential avalanche release areas within the forest. Potential avalanche release areas above the forest and the avalanche run-out distances under five different scenarios of forest cover were calculated by using a two-dimensional avalanche simulation model. We calculated the annual collective risk for each scenario and compared the change in risk to reveal the spatial distribution of the protective effect of the forest. Resulting risks differed strongly between forest cover change scenarios. An enlargement of an existing wind-disturbed area within lower parts of the slope resulted only in a slight increase of risk. In contrast, the effect of an unforested area in the upper parts of the observed forest more than doubled the risk. These results show how a risk-based approach can help to quantify and illustrate the impact of differences in forest cover on the protective effect of mountain forests. It is a promising approach to determine the economic value of protection forests and thus provide quantitative and qualitative information for cost-efficient forest maintenance planning. With regard to the achievements of research to date, the presented approach may serve as a valuable method to support decision-making in a future protection forest management. 相似文献
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Understanding both historic and current fire regimes is indispensable to sustainable forest landscape management. In this paper, we use a spatially explicit landscape simulation model, LANDIS, to simulate historic and current fire regimes in the Great Xing’an Mountains, in northeastern China. We analyzed fire frequency, fire size, fire intensity, and spatial pattern of burnt patches. Our simulated results show that fire frequency under the current fire scenario is lower than under the historic fire scenario; total area burnt is larger with lower fire intensity under the historic fire scenario, and smaller with higher fire intensity under the current fire scenario. We also found most areas were burned by high intensity fires under the current fire scenario, but by low to moderate fires under the historic fire scenario. Burnt patches exhibit a different pattern between the two simulation scenarios. Large patches burnt by high intensity class fires dominate the landscape under the current fire scenario, and under historic fire scenario, patches burnt by low to moderate fire intensity fires have relatively larger size than those burnt by high intensity fires. Based on these simulated results, we suggest that prescribed burning or coarse woody debris reduction should be incorporated into forest management plans in this region, especially on north-facing slopes. Tree planting may be a better management option on these severely burned areas whereas prescribed burning after small area selective cutting, retaining dispersed seed trees, may be a sound forest management alternative in areas except for the severely burned patches. 相似文献
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Shlomit Paz Yohay CarmelFaris Jahshan Maxim Shoshany 《Forest Ecology and Management》2011,262(7):1184-1188
The recent devastating wildfire on Mt. Carmel provided a unique opportunity to evaluate a fire-risk map constructed for the region, published two years ago in this journal. This largest forest fire in the history of Israel, occurred during December 2010, covering 2180 ha, burning more than half-million trees and causing the loss of life of 45 people.A study of fire risk in this area was conducted between 2007 and 2009 utilizing a combination of Monte Carlo simulation of spatial spread of fire ignition with fire behavior model (FARSITE). The fire risk map produced in 2009 is assessed here with reference to the area burnt during December 2010. The results showed that most of burnt areas corresponded to high risk levels in the risk map. According to a null model, the five lower risk levels taken together would have corresponded to 50% of the burnt area, while in fact they were presented in only 5.6% of the area. In contrast, the three highest risk levels, for which the null model expectation would be a representation of 30%, were represented in 87% of the area. Comparing the fire risk map against the map of the real recent fire provided support to the general approach, and strengthened the confidence of our fire risk model. 相似文献
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There is a lack of knowledge to identify and classify forest structures according to the risk of crown fires, especially in
Mediterranean regions. In this study, for the first time, we use real information, obtained after a wildfire that burnt under
extreme meteorological conditions, to classify forest structures of Pinus halepensis into fuel types as a function of crown fire potential. We identified fourteen forest structures which characterize many forest
types in Western Mediterranean areas depending on canopy closure, number of tree layers, percent of each tree layer and overall
tree density. By using the pattern of fire types that burnt the most numerous forest structures, we have identified four fire
hazard groups of forest structures which are considered different fuel types. The first two had the lowest risk of active
crown fires and they differed in the proportion of surface fires and passive crown fires. The third fuel type was the threshold
between structures with low and high extreme fire behavior; while the fourth had a high risk of active crown fires. Firefighters
and forest managers who are demanding this kind of schema, will test and upgrade this classification of fuel types in function
of crown fire potential during future wildfires. 相似文献
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Analysis of the seasonal characteristics of forest fires in South Korea using the multivariate analysis approach 总被引：2，自引：0，他引：2
For efficient forest fire management, special precautions are required in dry and strong-wind seasons vulnerable to severe
forest fires. To extract the seasonal characteristics of forest fires in South Korea, the statistics over the past 16 years,
1991 through 2005, were investigated. The daily records of the number of fire occurrences, the total area burned and the average
burned area per occurrence were examined to identify the seasonal patterns of forest fires using cluster analysis and principal
component analysis; the risk of daily fires was also assessed using the ordered logit model. As a result, the fire patterns
were classified into five clusters and a general danger index for forest fires was derived from the first principal component,
showing relatively large-scaled fire regimes in spring, and frequent small-scaled fire regimes in autumn and winter. In connection
with the ordered logit model, the probability for the five ranks of forest fire risk was calculated and the threshold for
high-risk fires was detected. As an implementation of the results above, the proper forest fire precautionary period in South
Korea was estimated, and consequently October 21 through May 17 was recognized as a dry season at a high risk of forest fires.
This period began 10 days earlier in autumn and extended into midwinter (late December and January) as opposed to the existing
precautionary period, indicating the need of more cautious forest fire management earlier in autumn and continuing through
midwinter. 相似文献
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我国森林火灾发生的时空规律研究 总被引：5，自引：0，他引：5
森林火灾对森林生态系统有重要影响,可能给森林生态系统带来毁灭性的损害,但在森林生态系统演替中又具有重要和积极的影响。研究森林火灾发生规律是森林火灾预测预报的基础,也是指导森林防火与补救工作的重要科学依据,具有重要的理论与现实意义。受气候变化等因素的影响,近年来森林火灾有多发的趋势,关于森林火灾发生及其生态影响成为研究的热点。文中在参考国外研究成果的基础上,从森林火灾发生的不同时间尺度和不同空间尺度上评述我国森林火灾发生的时空分布规律,总结我国森林火灾发生的一些总体规律性,指出现有研究存在的问题,并对未来的研究方向进行展望。 相似文献
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Mikko Kurttila Eero Muinonen Pekka Leskinen Harri Kilpeläinen Jouni Pykäläinen 《European Journal of Forest Research》2009,128(1):37-50
A proper forest planning process includes the assessment of the decision-makers’ preferences concerning the future forest
use. For some owners, it may be a difficult task to express their preferences exactly and in the form that is required for
planning calculations. This study presents a new kind of approach for analyzing the effects of preferential uncertainty. The
approach consists of examination of the differences in the actual decision variables in forest planning, i.e. selected treatments
for stands between holding-level forest plans. In example calculations, the preferential uncertainty was examined from three
different viewpoints: the uncertainty in the weights of the objective variables; the uncertainty in the partial utility function;
and the combination of these two uncertainty sources. One thousand preference realizations were generated for each of these
uncertainty sources. More than one treatment schedules are proposed for stands that are affected by preferential uncertainty.
These stands were detected from among the resulting set of 1,000 forest plans. With this done, two potential decision-making
strategies, an adaptive behavior strategy and a threshold proportion strategy, were applied as guides in decision-making for
stands, which have more than one treatment alternative selected in the produced optimal forest plans. The adaptive behavior
technique required that the forest owner select one treatment alternative for at least one stand that has more than one proposed
treatment alternative. The treatment alternatives having frequencies exceeding the given threshold frequency were all accepted
simultaneously in the threshold strategy. The main benefit of the approach is to present the effects of uncertainties in a
way that can be easily understood by the actual decision-makers. It is a promising tool for practical decision-making situations
because at least Finnish non-industrial private forest owners quite often focus on making stand-level forest management decisions.
It is also suitable for examinations of other uncertainty sources such as timber prices or inventory data. 相似文献
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根据德国北部挪威云杉林相邻林分问的特定地理关系,包括林分重心间的距离和共同边界的长度,建立了德国北部挪威云杉林经营的一个空间优化模型,该模型是一种新的空间优化方法.地理数据从GIS中获得并保存到数据库中,数据库还包括林分选项和相应的目标方程值等内容.首先使用了一个由41个林分组成的林班,每个林分21个选项,采用模拟退火的方法来分别和综合优化经济模型、均衡产出模型和空间模型,并将它们的结果方案与具最大净现值的方案进行比较.当均衡产出和空间2个组成部分逐一加入到目标方程后,它们显著地改进了结果方案,而经济目标只有中等程度的下降. 相似文献
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David R. Gray 《Annals of Forest Science》2017,74(3):48
Key message
Natural disturbance can disrupt the anticipated delivery of forest-related ecosystem goods and services. Model predictions of natural disturbances have substantial uncertainties arising from the choices of input data and spatial scale used in the model building process, and the uncertainty of future climate conditions which are a major driver of disturbances. Quantifying the multiple contributions to uncertainty will aid decision making and guide future research needs.Context
Forest management planning has been able, in the past, to rely on substantial empirical evidence regarding tree growth, succession, frequency and impacts of natural disturbances to estimate the future delivery of goods and services. Uncertainty has not been thought large enough to warrant consideration. Our rapidly changing climate is casting that empirical knowledge in doubt.Aims
This paper describes how models of future spruce budworm outbreaks are plagued by uncertainty contributed by (among others): selection of data used in the model building process; model error; and uncertainty of the future climate and forest that will drive the future insect outbreak. The contribution of each to the total uncertainty will be quantified.Methods
Outbreak models are built by the multivariate technique of reduced rank regression using different datasets. Each model and an estimate of its error are then used to predict future outbreaks under different future conditions of climate and forest composition. Variation in predictions is calculated, and the variance is apportioned among the model components that contributed to the epistemic uncertainty in predictions.Results
Projections of future outbreaks are highly uncertain under the range of input data and future conditions examined. Uncertainty is not uniformly distributed spatially; the average 75% confidence interval for outbreak duration is 10 years. Estimates of forest inventory for model building and choice of climate scenario for projections of future climate had the greatest contributions to predictions of outbreak duration and severity.Conclusion
Predictions of future spruce budworm outbreaks are highly uncertain. More precise outbreak data with which to build a new outbreak model will have the biggest impact on reducing uncertainty. However, an uncertain future climate will continue to produce uncertainty in outbreak projections. Forest management strategies must, therefore, include alternatives that present a reasonable likelihood of achieving acceptable outcomes over a wide range of future conditions.13.
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A key challenge in modern wildfire mitigation and forest management is accurate mapping of forest fuels in order to determine spatial fire hazard, plan mitigation efforts, and manage active fires. This study quantified forest fuels of the montane zone of Boulder County, CO, USA in an effort to aid wildfire mitigation planning and provide a metric by which LANDFIRE national fuel maps may be compared. Using data from 196 randomly stratified field plots, pre-existing vegetation maps, and derived variables, predictive classification and regression tree models were created for four fuel parameters necessary for spatial fire simulation with FARSITE (surface fuel model, canopy bulk density, canopy base height, and stand height). These predictive models accounted for 56–62% of the variability in forest fuels and produced fuel maps that predicted 91.4% and 88.2% of the burned area of two historic fires simulated in the FARSITE model. Simulations of areas burned based on LANDFIRE national fuel maps were less accurate, burning 77.7% and 40.3% of the historic fire areas. Our results indicate that fuel mapping efforts that utilize local area information and biotic as well as abiotic predictors will more accurately simulate fire spread rates and reflect the inherent variability of forested environments than do current LANDFIRE data products. 相似文献
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Forest fire is a major cause of changes in forest structure and function. Among various floristic regions, the northeast region of India suffers maximum from the fires due to age-old practice of shifting culti- vation and spread of fires from jhum fields. For proper mitigation and management, an early warning of forest fires through risk modeling is required. The study results demonstrate the potential use of remote sens- ing and Geographic Information System (GIS) in identifying forest fire prone areas in Manipur, southeastern part of Northeast India. Land use land cover (LULC), vegetation type, Digital elevation model (DEM), slope, aspect and proximity to roads and settlements, factors that influ- ence the behavior of fire, were used to model the forest fire risk zones. Each class of the layers was given weight according to their fire inducing capability and their sensitivity to fire. Weighted sum modeling and ISODATA clustering was used to classify the fire zones. To validate the results, Along Track Scanning Radiometer (ATSR), the historical fire hotspots data was used to check the occurrence points and modeled forest fire locations. The forest risk zone map has 55 63% of agreement with ATSR dataset. 相似文献
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Stavros Sakellariou Stergios Tampekis Fani Samara Athanassios Sfougaris Olga Christopoulou 《林业研究》2017,28(6):1107-1117
Forest ecosystems are our priceless natural resource and are a key component of the global carbon budget. Forest fires can be a hazard to the viability and sustainable management of forests with consequences for natural and cultural environments, economies, and the life quality of local and regional populations. Thus, the selection of strategies to manage forest fires, while considering both functional and economic efficiency, is of primary importance. The use of decision support systems (DSSs) by managers of forest fires has rapidly increased. This has strengthened capacity to prevent and suppress forest fires while protecting human lives and property. DSSs are a tool that can benefit incident management and decision making and policy, especially for emergencies such as natural disasters. In this study we reviewed state-of-the-art DSSs that use: database management systems and mathematical/economic algorithms for spatial optimization of firefighting forces; forest fire simulators and satellite technology for immediate detection and prediction of evolution of forest fires; GIS platforms that incorporate several tools to manipulate, process and analyze geographic data and develop strategic and operational plans. 相似文献
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林火作为干扰因子, 影响着森林演替、森林生物量和生产力以及生物地球化学循环。森林燃烧所释放的含碳温室气体对全球气候变化具有重要影响。对森林火灾释放的含碳气体进行有效估算, 可以弄清林火产生的含碳气体对全球碳循环的影响。文中介绍了2种林火碳排放模型, 即基于有效可燃物模型和火干扰下碳循环模型。通过对这2种估算方法的比较, 指出未来林火碳排放估算方法的发展趋势。 相似文献
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以可视化开发环境Visual Basic6．0与Map Objects控件作为系统开发平台,建立以东北林业大学帽儿山实验林场为研究区域的林火蔓延可视化系统。根据影响林火行为的各项因素,将空间信息和属性数据结合在一起,并将GIS技术成功应用到系统中,实现了在栅格地形背景图上进行林火蔓延的动态模拟,获得同一燃点在不同蔓延模型下的林火蔓延扩展图像。 相似文献