Estimating rates of substitution for protecting values at risk for initial attack planning and budgeting

With changes in land management planning and a new federal fire policy, increased emphasis has been placed on protecting a broader set of resource values such as those associated with sensitive species habitat or cultural resources. Fire managers have long needed a system for assessing values at risk across the landscape that can be implemented in accordance with the budgeting and appropriation process and that can be updated annually or every several years. A viable system has to be operational at a reasonable cost and it must support strategic planning and budgeting. Currently available valuation methods, in their entirety, can be costly and time consuming making them problematic for these purposes. Consequently, managers have become accustomed to assessing values at risk without the direct support of structured economic analysis. This paper discusses an approach (Marginal Attribute Rate of Substitution) to assessing values at risk for initial attack planning and budgeting. MARS is an attribute based method for estimating rates of substitution among fire protection attributes in a spatial context. It consists of and builds upon specific elements from well known and peer-reviewed valuation methods for resource valuation. As such, MARS relies upon stated preference, expert opinion, the hedonic price equation and other familiar procedures. The paper concludes with an empirical example of the application of MARS to a forested area in California. As the first construction of this approach it has the potential for further modification and refinement for those that may find it of interest.     

Using Monte Carlo simulations to estimate relative fire ignition danger in a low-to-medium fire-prone region

A comprehensive assessment of fire ignition danger is nowadays a basic step towards the prioritization of fire management measures. In this study we propose performing a fire selectivity analysis using Monte Carlo simulations to statistically estimate the relative fire ignition danger in a low-to-intermediate fire-prone region such as Canton Ticino, Switzerland. We define fire ignition danger as the likelihood that at a given place a fire will be ignited. For each 25 m × 25 m pixel of the study area, landscape characteristics that may be related to the probability of fire ignition such as vegetation type, elevation, aspect, slope, urban-forest interface were first split into 9-12 categories. The selectivity of each category with respect to fire ignition was then statistically tested by means of Monte Carlo simulations. Finally, we proposed two different approaches for calculating the ignition danger index: cumulating the scores of the Monte Carlo simulations to a final index or producing synthetic scores by performing a principal component analysis of the Monte Carlo results. The validation of the resulting fire danger indices highlights the suitability of both proposed approaches. The PCA-option allows a slightly better discrimination between ignition and non-ignition points and may be of more general application.     

Modelling and mapping the suitability of European forest formations at 1-km resolution

Proactive forest conservation planning requires spatially accurate information about the potential distribution of tree species. The most cost-efficient way to obtain this information is habitat suitability modelling i.e. predicting the potential distribution of biota as a function of environmental factors. Here, we used the bootstrap-aggregating machine-learning ensemble classifier Random Forest (RF) to derive a 1-km resolution European forest formation suitability map. The statistical model use as inputs more than 6,000 field data forest inventory plots and a large set of environmental variables. The field data plots were classified into different forest formations using the forest category classification scheme of the European Environmental Agency. The ten most dominant forest categories excluding plantations were chosen for the analysis. Model results have an overall accuracy of 76%. Between categories scores were unbalanced and Mesophitic deciduous forests were found to be the least correctly classified forest category. The model’s variable ranking scores are used to discuss relationship between forest category/environmental factors and to gain insight into the model’s limits and strengths for map applicability. The European forest suitability map is now available for further applications in forest conservation and climate change issues.     

Economic vulnerability of fire-prone landscapes in protected natural areas: application in a Mediterranean Natural Park

Environmental services and landscape goods are rarely incorporated into economic valuation of natural resources, even though these resources may constitute a large proportion of the total ecosystem value, mainly in natural protected areas. The frequent occurrence of wildfires in Spanish protected areas requires a tool, which allows for the comprehensive management of landscape resource and mitigating the potential economic impacts caused by fire. In this paper, we extend the economic valuation theory to the concept of economic vulnerability. Geographic Information System was used to develop a framework for landscape impact assessment using annual landscape value, vegetation resilience and fire behavior. An economic approach of landscape susceptibility was provided by the integration of these three components. Once landscape susceptibility had been spatially characterized, landscape vulnerability was analyzed from criteria associated with landscape susceptibility and burn probability. There was a notable variation in landscape vulnerability ranging from 412,000 Euros to 1,200,000 Euros in Aracena Natural Park (186,828 ha) according to the selected contingent valuation scenario. The availability of cartography of landscape vulnerability could play a critical role in budget optimization and the decision-making process. In this sense, this approach helps managers to identify different efforts according to spatial distribution of the risk and fuel management strategies to increase economic efficiency of fire prevention activities.

     

Evaluation of the potential index model to predict habitat suitability of forest species: the potential distribution of mountain pine (<Emphasis Type="Italic">Pinus uncinata</Emphasis>) in the Iberian peninsula

Characterization of the suitability or potentiality of a territory for forest tree species is an important source of information for forest planning and managing. In this study, we compared a relatively simple methodology to generate potential habitat distribution areas that has been traditionally used in Spain (the potential index model) with a statistical modelling approach (generalized linear model). We modelled the potential distribution of mountain pine (Pinus uncinata) in the Iberian peninsula as a working example. The potential index model generated a map of habitat suitability according to the values of an index of potentiality, whose distribution has usually divided into four categories based on quartiles (from optimum to low suitability). Considering all values of the index of potentiality as presences of mountain pine resulted in a low to moderate degree of agreement between the potential index model and the generalized linear model according to the kappa coefficient. Using the cut-off value of the index of potentiality that maximized the degree of agreement between both modelling approaches resulted in a substantial similarity between the maps of the predicted distribution of mountain pine. This cut-off value did lie in the upper-third quartile of the potential index distribution (high suitability category), and roughly coincided with the upper 30th percentile. The use of statistical techniques, which have proved to be powerful and versatile for species distribution modelling, is recommended. However, the potential index model, together with the adjustments proposed here, could be a reasonably simple methodology to predict the potential distribution of forest tree species that forest managers should take into account when evaluating forestation and afforestation projects.     

Community and ecotourist perceptions of forest conservation benefits:a case study of Mabira Central Forest Reserve,Uganda

The different interests in forest resources by various stakeholders may result in differences in perceived value of forest conservation. In order to test this hypothesis, we compared the valuation by international ecotourists and local respondents of the perceived benefits of the Mabira Central Forest Reserve. The factors that influenced respondents’ valuation of forest conservation were also investigated. Describing a hypothetical scenario to elicit respondents’ willingness-to-pay (WTP) for forest conservation was the central part of the questionnaire. The WTP;income ratio was used to estimate respondents’ perceived value of forest conservation. A chi-square (χ ²) test indicated significant association between respondent category (local and tourist) and categories of perceived benefits (p-value = 0.001). The locals were more interested in direct-use values while the tourists showed greater interest in the indirect-use values. A Student's t-test showed that the WTP:income ratios of the locals were much higher than for the ecotourists (p-value < 0.001). This implies that the local communities had a higher valuation of forest conservation than the ecotourists. Regression analysis revealed that all other factors being constant, the WTP of respondents who perceived direct- and indirect-use value as the most important forest benefit was significantly higher (p < 0.05) than those who perceived no value by $5.8693 and $0.02628, respectively. The respondents who rated the contribution of the ecotourism project to community development as moderate had a significantly higher WTP compared to those who rated it as low by $6.6908. Overall, these results indicate that the benefits people derive from the forest either through direct or indirect uses influence valuation of forest conservation. Results also indicate that although ecotourismrelated benefits improved attitudes towards forest conservation, ecotourism alone may not be an adequate conservation tool because of the limited support it can provide to the local community.     

Mapping tree aboveground biomass and carbon in Omo Forest Reserve Nigeria using Landsat 8 OLI data

Protected areas in Nigeria are important ecosystems for carbon storage. The aim of this study was to estimate and map tree aboveground biomass (TAGB) and carbon (TAGC) within a tropical forest in Nigeria. Stepwise regression analysis was implemented to develop models for predicting TAGB in the forest stand, by integrating field TAGB data with Landsat 8 OLI data. Spectral variables used in the analysis include spectral bands, vegetation indices, tasseled cap indices and principal components. Model validation was performed using independent sample plots. The results showed that incorporating more than one category of spectral variables improved the prediction of TAGB. The best-fit model was applied to map the spatial distribution of TAGB and TAGC. The TAGC was estimated as 52.3% of TAGB, based on the average carbon content of tree species derived in this study. Average TAGB and TAGC estimates for the forest stand were 373.1 ± 165.4 t ha^?1 and 194 ± 82.7 t ha^?1, respectively. Reliable estimates of TAGB and TAGC for the forest reserve were obtained. This study provides important information required to manage the forest stand for optimal carbon sequestration.     

Future impacts of climate change on forest fire danger in northeastern China

Climate warming has a rapid and far-reaching impact on forest fire management in the boreal forests of China. Regional climate model outputs and the Canadian Forest Fire Weather Index (FWI) Sys- tem were used to analyze changes to fire danger and the fire season for future periods under IPCC Special Report on Emission Scenarios (SRES) A2 and B2, and the data will guide future fire management planning. We used regional climate in China (1961 1990) as our validation data, and the period (1991-2100) was modeled under SRES A2 and B2 through the weather simulated by the regional climate model system (PRECIS). Meteorological data and fire danger were interpolated to 1 km 2 by using ANUSPLIN software. The average FWI value for future spring fire sea- sons under Scenarios A2 and B2 shows an increase over most of the region. Compared with the baseline, FWI averages of spring fire season will increase by 0.40, 0.26 and 1.32 under Scenario A2, and increase by 0.60, 1.54 and 2.56 under Scenario B2 in 2020s, 2050s and 2080s, respectively. FWI averages of autumn fire season also show an increase over most of the region. FWI values increase more for Scenario B2 than for Scenario A2 in the same periods, particularly during the 2050s and 2080s. Average future FWI values will increase under both scenarios for autumn fire season. The potential burned areas are expected to increase by 10% and 18% in spring for 2080s under Scenario A2 and B2, respectively. Fire season will be prolonged by 21 and 26 days under ScenariosA2 and B2 in 2080s respectively.     

External economic benefits and social goods from prairie shelterbelts

Shelterbelts are a valuable resource to those who plant them and to other members of society. The external benefits to society can be worth as much as the private benefits to producers. However, the external benefits have not been quantified or monetized in a well-documented way. In this study, external benefits were estimated for tree seedlings distributed by the Agriculture and Agri-Food Canada Shelterbelt Centre in the Canadian Prairie Provinces for the period 1981–2001. Estimation of these benefits required information on the biophysical changes caused by shelterbelts and their valuation. Using literature, we estimated that the value of these external benefits amounted to over $140 million (2001 CDN$; CDN$1 = US$0.63). The majority of this value was derived from carbon sequestration ($73 million) and reduced soil erosion ($15 million) services with the remainder being contributed by biodiversity and water and air quality services. Other external benefits, such as health values, transportation safety, aesthetics and property values were identified but could not be estimated due to a lack of data. The estimated value for external benefits conferred by shelterbelts in this study indicates that they are large and suggests that both private and external benefits need to be considered in formulating policies or programs so that benefits to the society can be maximized.     

Precision Fire Hazard Divisions for Collective Forest in Southern China

This paper focuses on how to build the model of precision fire hazard divisions in the level of forest resources sub-compartment.Based on 3D GIS technology and characteristics of forest fires in collective forest of southern China,this study utilized Lin’an City,Zhejiang Province as the experimental area.Forest fire factors were divided into 11 indexes from the three categories(social and economic factors,forestry characteristics,and meteorological characteristics) and weighted for analysis.Next,three eigenvectors(one for each category) were created to build a nonlinear mathematical model called precision fire hazard divisions for forests.Then,the model was used to optimize and test forest fire hazard divisions with the least squares.Results showed that experimental and theoretical values of error were less than 0.1. Thus,in the experimental area this model and the fire occurrence history matched.     

不同基因型欧洲黑杨幼苗氮素利用效率差异及其机理初探

以104份欧洲黑杨不同基因型(无性系)为材料,通过生长量和生理指标的测定,研究土壤施氮和不施氮条件下其氮素利用效率的差异。结果表明:不同供氮水平下,不同基因型欧洲黑杨生长差异显著。根据2个供氮水平的苗木年平均材积生长量将欧洲黑杨群体划分为4个类型:双高效型、高氮高效型、低氮高效型和双低效型,并结合氮反应指数在双高效型与高氮高效型中分别筛选出8个氮素利用效率高、生长表现优良的基因型,具较高的育种价值。比较分析欧洲黑杨不同基因型氮素利用效率相关指标,发现双高效型的净光合速率、硝酸还原酶和谷氨酰胺合成酶活性、根系干质量、体积、比表面积均高于高氮高效型,初步揭示了不同类型欧洲黑杨氮利用效率存在差异的机理。     

Optical porosity and windspeed reduction by coniferous windbreaks in Southern Ontario

Relative windspeed reduction was measured behind nine relatively narrow, homogeneous windbreaks in southern Ontario, Canada to assess whether any characteristics of the windspeed reduction curve could be predicted from optical porosity. The latter was determined for each windbreak using high contrast black and white photographic silhouettes on a computer digitizing system. Minimum windspeeds behind the windbreaks ranged from 29 to 71% of open windspeed; these minima were located 2 to 6 multiples of windbreak height away from the windbreak. Optical porosities of the bottom half of the windbreak ranged from 0 to 31%. Multiple regression of the shelter parameters (location and value of minimum relative windspeed) on the independent variables (optical porosity, open windspeed, surface roughness, approaching wind direction relative to the windbreak, average tree diameter and average tree spacing) showed that the minimum relative windspeed could be predicted from the optical porosity of the bottom half of the windbreak. The results suggest that optical porosity can be used to predict minimum relative windspeeds and may therefore be useful as a guide in the field evaluation of windbreaks.     

Predicting stand damage and tree survival in burned forests in Catalonia (North-East Spain)

The study developed models for predicting the post-fire tree survival in Catalonia. The models are appropriate for forest planning purposes. Two types of models were developed: a stand-level model to predict the degree of damage caused by a forest fire, and tree-level models to predict the probability of a tree to survive a forest fire. The models were based on forest inventory and fire data. The inventory data on forest stands were obtained from the second (1989–1990) and third (2000–2001) Spanish national forest inventories, and the fire data consisted of the perimeters of forest fires larger than 20 ha that occurred in Catalonia between the 2nd and 3rd measurement of the inventory plots. The models were based on easily measurable forest characteristics, and they permit the forest manager to predict the effect of stand structure and species composition on the expected damage. According to the stand level fire damage model, the relative damage decreases when the stand basal area or mean tree diameter increases. Conversely, the relative stand damage increases when there is a large variation in tree size, when the stand is located on a steep slope, and when it is dominated by pine. According to the tree level survival models, trees in stands with a high basal area, a large mean tree size and a small variability in tree diameters have a high survival probability. Large trees in dominant positions have the highest probability of surviving a fire. Another result of the study is the exceptionally good post-fire survival ability of Pinus pinea and Quercus suber.     

手杖式测树仪立木树高量测研究

[目的]树高是森林经营决策中最重要的一个参量,常用于估计森林生长、年龄、材积、生物量和碳储量等立木参数,其精度对立木质量的评价及森林生长的预测分析影响重大.为解决传统的树高量测仪器移动不便,测量周期长,人力耗损大等问题.[方法]以近景摄影测量为基础,构建了一种以登山杖绑定安卓智能手机为测量平台的便携、快捷的树高测量装备...     

Factors affecting post-fire crown regeneration in cork oak (Quercus suber L.) trees

Cork oak (Quercus suber) forests are acknowledged for their biodiversity and economic (mainly cork production) values. Wildfires are one of the main threats contributing to cork oak decline in the Mediterranean Basin, and one major question that managers face after fire in cork oak stands is whether the burned trees should be coppiced or not. This decision can be based on the degree of expected crown regeneration assessed immediately after fire. In this study we carried out a post-fire assessment of the degree of crown recovery in 858 trees being exploited for cork production in southern Portugal, 1.5 years after a wildfire. Using logistic regression, we modelled good or poor crown recovery probability as a function of tree and stand variables. The main variables influencing the likelihood of good or poor crown regeneration were bark thickness, charring height, aspect and tree diameter. We also developed management models, including simpler but easier to measure variables, which had a lower predictive power but can be used to help managers to identify, immediately after fire, trees that will likely show good crown regeneration, and trees that will likely die or show poor regeneration (and thus, potential candidates for trunk coppicing).     

Exploring Agrobiodiversity on Farm: A Case from Middle–Hills of Nepal

A survey was conducted to examine agrobiodiversity status of farms in the Pokhare Khola watershed of Dhading district in the Middle-Hills of Nepal. A total of 53 farmland tree and one crop species from 22 families were documented. The most commonly found species were fruit and fodder species (on over 60 % farms) including banana (Musa paradisiaca), khasrato (Ficus hispida) and khanayo (Ficus semicordata). Tree density was highest (226/ha) on marginal farms (farm area ≤0.25 ha) and lowest (165/ha) on small farms (farm area 0.26–0.5 ha). For the study area as a whole, the Shannon-Wiener species diversity index was 3.26 and the species evenness index 1.89. Large farms (farm area >1 ha) had the greatest tree species diversity (4.47 ± 0.52) and marginal farms the lowest (2.18 ± 0.37), indicating the positive relationship between farm size and species diversity. A total of six types of cereals and 18 types of vegetable crops were grown in the study area. The major livestock component of each household was chickens (average 8/household) and goats (6/household). The mean value of livestock in the large farm category was estimated as $2235, significantly higher than that of the other three categories. A significant relationship was found between agrobiodiversity and livelihoods, irrespective of annual production, and the critical role of the farmed landscape in agrobiodiversity conservation was apparent.     

Pinus pinaster Ait. tree mortality following wildfire in Spain

Maritime pine (Pinus pinaster Ait.) is the tree species most affected by wildfire in the Iberian Peninsula. Prediction of the probability of fire-injured tree mortality is critical for management of burned areas, evaluation of the ecological and economic impact of wildfire and prescribed fire planning and application. Pine bark beetles (Scolytidae) frequently attack burned maritime pine stands and cause extensive post-fire mortality throughout the Iberian Peninsula. In the present study, maritime pine trees were monitored for three years following 14 wildfires in four ecotypes in Spain (11 fires in Galicia (Galician ecotype - NW Spain), one fire in Portillo (Meseta-Castellana ecotype - Central Spain), one fire in Rodenal (Rodenal ecotype - Central Spain), and one fire in Genalguacil (Sierra Bermeja ecotype - SW Spain)). Data on tree attributes, crown and bole injury, ground fire severity, Ips sp. presence and tree survival were obtained by examining 3085 trees. Logistic regression models for predicting the probability of delayed maritime pine mortality were developed by use of generalized estimated equations (GEE). An ample range of response to fire damage in mortality was evident among the four ecotypes and different models were fitted for each. The most important variables for predicting tree mortality were total crown volume damaged, presence of Ips sp. attack and cambium kill rating. The results highlight the extensive presence of Ips sp. in burned maritime pine forests and its importance in tree mortality process, the ample range of response of P. pinaster, in terms of post-fire mortality, as well as the need to develop site specific mortality models for the different ecotypes of this species following fire.     

Spatial variation and prediction of forest biomass in a heterogeneous landscape

Large areas assessments of forest biomass distribution are a challenge in heterogeneous landscapes, where variations in tree growth and species composition occur over short distances. In this study, we use statistical and geospatial modeling on densely sampled forest biomass data to analyze the relative importance of ecological and physiographic variables as determinants of spatial variation of forest biomass in the environmentally heterogeneous region of the Big Sur, California. We estimated biomass in 280 forest plots (one plot per 2.85 km2) and measured an array of ecological (vegetation community type, distance to edge, amount of surrounding non-forest vegetation, soil properties, fire history) and physiographic drivers (elevation, potential soil moisture and solar radiation, proximity to the coast) of tree growth at each plot location. Our geostatistical analyses revealed that biomass distribution is spatially structured and autocorrelated up to 3.1 km. Regression tree (RT) models showed that both physiographic and ecological factors influenced biomass distribution. Across randomly selected sample densities (sample size 112 to 280), ecological effects of vegetation community type and distance to forest edge, and physiographic effects of elevation, potential soil moisture and solar radiation were the most consistent predictors of biomass. Topographic moisture index and potential solar radiation had a positive effect on biomass, indicating the importance of topographically-mediated energy and moisture on plant growth and biomass accumulation. RT model explained 35% of the variation in biomass and spatially autocorrelated variation were retained in regession residuals. Regression kriging model, developed from RT combined with kriging of regression residuals, was used to map biomass across the Big Sur. This study demonstrates how statistical and geospatial modeling can be used to discriminate the relative importance of physiographic and ecologic effects on forest biomass and develop spatial models to predict and map biomass distribution across a heterogeneous landscape.