Optimal Spatial Allocation of Initial Attack Resources for Firefighting in the Republic of Korea Using a Scenario Optimization Model

【Title】 This study explores the optimal spatial allocation of initial attack resources for firefighting in the Republic of Korea. To improve the effectiveness of Korean initial attack resources with a range of policy goals, we create a scenario optimization model that minimizes the expected number of fires not receiving a predefined response. In this study, the predefined response indicates the number of firefighting resources that must arrive at a fire before the fire escapes and becomes a large fire. We use spatially explicit GIS-based information on the ecology, fire behavior, and economic characterizations important in Korea. The data include historical fire events in the Republic of Korea from 1991 to 2007, suppression costs, and spatial information on forest fire extent. Interviews with forest managers inform the range of we address in the decision model. Based on the geographic data, we conduct a sensitivity analysis by varying the parameters systematically. Information on the relative importance of the components of the settings helps us to identify “rules of thumb” for initial attack resource allocations in particular ecological and policy settings.

Crown Fuel Characteristics and Carbon Emission from Japanese Red Pine Stands Burned by Crown Fire in Mt. Palgong, South Korea

Carbon emissions from forest fires are considered an important factor of ecosystem carbon balance and global climate change. Carbon emissions from Japanese red pine stands （Pinus densiflora S. et Z.） burned by crown fire were estimated at Mt. Palgong in Daegu Metropolitan City, and crown fuel characteristics, including crown bulk density, crown base height, and fuel moisture content of Japanese red pine, were analyzed. Total biomass combusted was calculated by subtracting the biomass of burned stands from that of unburned stands exhibiting similar stand structures and site environments. Ten trees in the unburned area and five trees in the burned area were cut by using direct harvesting techniques to estimate crown layer biomass. All biomass sampled was oven-dried and weighed. The dry weight ratios of stems, branches, and needles were 7o%, 21%, and 9%, respectively. The available fuel load susceptible to combustion during the crown fire spread was equivalent to 55% of the crown layer biomass. The crown bulk density was 0.24 kg/m3 on average. The estimated amount of CO2 was 23,454 kg CO2/ha for the crown layer. These results will be useful for calculating the amount of CO2 emitted from forest fires and for developing a forest carbon model in P. densiflora forests.

Modeling Biodiversity Benefits and External Costs from a Keystone Predator Reintroduction Policy

In this paper, an economic model was constructed to determine the optimal wolf population and distribution across the Northern Rocky Mountains. Both ecological and economic concepts were incorporated in an implicitly spatial social welfare maximization problem. This interdisciplinary model relies on multiple data sources, including current wolf population and distribution information, opportunity cost to local landowners, and contingent valuation studies to determine willingness-to-pay for wolves. Economic models tend to externalize ecological concerns and ecological models often omit the complex human dimensions of conservation policy. Accordingly, this model can serve as a guide for integrating best practices from both fields. The model presented here is sufficiently general to apply to wolves in other ecosystems and to other highly interacting species such as beavers and bison. The Northern Rocky Mountain wolf was used as an example of how this economic model works, but this model can be applied far more broadly.

Tradeoff between the number of firefighting resources and the level of fire ignition prevention efforts in the Republic of Korea

This study explores the tradeoff relationship between the number of initial attack firefighting resources and the level of fire ignition prevention efforts mitigating the probability of human-made fires in the Republic of Korea,where most fires are caused by human activities.To examine this tradeoff relationship,we develop a hybrid model that combines a robust optimization model with a stochastic simulation model.The robust optimization minimizes the expected number of fires not receiving a pre-defined response,such as the number of firefighting resources that must arrive at the fire within half an hour,subject to budget constraints and uncertainty about the daily number and location of fires.The simulation model produces a set of fire scenarios in which a combination of number,location,ignition time,and intensity of fires occur.Results show that fire ignition prevention is as cost-effective as initial attack firefighting resources given the current budget in the Republic of Korea for reducing the expected number of fires not covered by the predefined response.The mixed policy of fire suppression and fire prevention may produce some gains in efficiency relative to the dominant policy of strong fire suppression strategies.