A database of vegetation treatments in New Mexico, USA and surrounding regions.

Active management practices to reduce or promote particular vegetation, known as vegetation treatments, are a common part of environmental management and they are conducted for a variety of purposes including wildfire risk mitigation, invasive species management, and ecological restoration. Vegetation treatment for wildfire mitigation in particular have increased dramatically in the Western United States in the past several decades. While vegetation treatments are common, data regarding the timing, location, and type of treatments conducted are often only maintained by the organization that conducted the work, hampering the ability of managers and researchers to understand the distribution and timing of vegetation treatments across a landscape. This dataset is a collection of spatially referenced records of vegetation treatments such as mechanical thinning, prescribed burning, and herbicide applications that were conducted in the state of New Mexico, USA and adjacent parts of Colorado, Oklahoma, and Texas. Spatial data were collected through requests to the regional or state offices for the relevant agencies (e.g., The Bureau of Land Management, the U.S. Forest Service, New Mexico State Forestry Division). The accuracy of this data collection approach was assessed by conducting more intensive data collection in five randomly selected focal watersheds across New Mexico. In these watersheds local offices of the larger agencies were contacted, as well as any smaller groups (e.g., soil and water conservation districts, municipalities, and environmental non-profits), and in person visits were made to gather any information on vegetation treatments possible. The overall dataset includes records of treatments spanning a century and includes records of 9.9 million acres of treatments conducted by more than a dozen different organizations. In the five focal watershed that we surveyed the database contained 7.4 % fewer acres of treated land than the more intensive interview approach. This spatially extensive dataset on vegetation treatments will be useful for researchers quantifying or modelling the effect of vegetation management on fire risk and behaviour. Additionally, this data will be useful to ecologists studying the distribution, movement, and habitat associations of a variety of plant an animal species. Finally, this data will be useful for research on landscape conservation and management.

Understory fuel loads and the impact factors of Quercus mongolica natural secondary forest in Hebei Pro-vince, China.

We investigated understory fuel loads of Quercus mongolica natural secondary forests in Hebei Province, China. We analyzed the effects of stand factors, topographic factors, and ground cover factors on the quantity and composition of fuel, established the dynamic models of understory fuel loads, and proposed management measures. The results showed that the understory total fuel load in Q. mongolica natural secondary forests was 11.68 t·hm-2, which exceeded the forest fire potential threshold (10 t·hm-2). The understory dead fuel load was mainly humus, and the understory living fuel load was mainly shrubs. The 1 h time-lag fuel load increased significantly with increasing canopy density, stand density, stand age, and litter thickness. The 10 h time-lag fuel load increased signi-ficantly with increasing stand density, average tree height, and litter thickness. Humus load decreased significantly with increasing altitude and increased significantly with increasing humus thickness. Herb load increased significantly with increasing sunny slope orientation and herbal coverage. Shrub load increased significantly with increasing slope degree, shrub coverage, and humus thickness. Understory total fuel load decreased significantly with increasing altitude, and increased significantly with increasing stand density, humus thickness, and litter thickness. The results of stepwise regression analysis indicated that stand density, humus thickness, and altitude could better predict the understory total fuel load (Radj2=0.775). Therefore, more attention should be paid on the control of stand density of Q. mongolica natural secondary forest in Hebei Province. Cleaning of litters and humus on the ground would help prevent forest fires scientifically and effectively.

Evaluation of forest treatment planning considering multiple objectives.

Various tools and techniques are used by environmental managers and planning agencies to make land use decisions that balance different and often competing goals. Multiple goals, or objectives, are generally challenging to address because there is likely no single optimal solution, but rather a range of possible Pareto (or tradeoff) solutions. Considerable attention has focused on software and approaches that rely on heuristic methods to generate solutions for land use planning problems with multiple objectives. While fast and accessible, there remain uncertainties about the quality of solutions obtained by these heuristic methods and whether they are indeed meeting the needs of environmental managers. This paper explores forest treatment planning for wildfire risk mitigation seeking to balance multiple objectives when the spatial pattern of treatment is restricted. Solution quality of one widely employed forest planning tool is evaluated (using measures of completeness, inferiority, and maximum gap) under a range of geographic settings and problem sizes. The findings indicate that obtained solutions are suboptimal, and fail to represent the full spectrum of tradeoffs possible.

Short-term Macrochloa tenacissima response understory Pinus halepensis Mill forest after early prescribed burns in a semi-arid landscape.

Climate change has led to altered fire patterns in the Mediterranean basin due to rising temperatures and greenhouse gas emissions, diminishing the resilience of forest ecosystems. To address this threat, forest management increasingly employs preventive measures like controlled burns, aiming to mitigate wildfire damage. However, understanding the impact of prescribed burns on vegetation remains crucial. Our study focuses on assessing the ecological effects of early-season prescribed burns on Macrochloa tenacissima communities within Pinus halepensis Mill forests on the Iberian Peninsula. These forests, with southeast-facing slopes and arid soils, heavily rely on alpha grass for post-fire recovery, acting as a shield against runoff and erosion. Yet, the presence of highly flammable resprouting species can lead to rapid combustible material accumulation. We evaluated parameters like coverage, floral diversity (α-diversity), aboveground plant biomass, photosynthetic activity, and chemical leaf properties of alpha grass, a year after a low-intensity controlled burn. Comparing burnt and unburnt areas revealed significant changes in α-diversity and ecophysiology of Macrochloa tenacissima due to early-season prescribed burns. These short-term shifts underscore the need for further exploration of underlying mechanisms. Our analysis also showed distinct shifts in alpha grass leaf chemical composition between the two plot types, potentially impacting post-fire recovery strategies. Although prescribed burning might not be optimal for reducing fire risk in resprouting species-dominated forests, it conserves native plants and enhances ecosystem diversity, providing valuable ecological benefits. In conclusion, our research deepens our understanding of early-season burning's repercussions on flammable vegetation dynamics and combustible material availability in semi-arid landscapes. It contributes to standardized management protocols, aiding effective forest service administration and wildfire risk reduction.

A data-driven analysis and optimization of the impact of prescribed fire programs on wildfire risk in different regions of the USA.

In the current century, wildfires have shown an increasing trend, causing a huge amount of direct and indirect losses in society. Different methods and efforts have been employed to reduce the frequency and intensity of the damages, one of which is implementing prescribed fires. Previous works have established that prescribed fires are effective at reducing the damage caused by wildfires. However, the actual impact of prescribed fire programs is dependent on factors such as where and when prescribed fires are conducted. In this paper, we propose a novel data-driven model studying the impact of prescribed fire as a mitigation technique for wildfires to minimize the total costs and losses. This is applied to states in the USA to perform a comparative analysis of the impact of prescribed fires from 2003 to 2017 and to identify the optimal scale of the impactful prescribed fire programs using least-cost optimization. The fifty US states are classified into categories based on impact and risk levels. Measures that could be taken to improve different prescribed fire programs are discussed. Our results show that California and Oregon are the only severe-risk US states to conduct prescribed fire programs that are impactful at reducing wildfire risks, while other southeastern states such as Florida maintain fire-healthy ecosystems with very extensive prescribed fire programs. Our study suggests that states that have impactful prescribed fire programs (like California) should increase their scale of operation, while states that burn prescribed fires with no impact (like Nevada) should change the way prescribed burning is planned and conducted.

[Forest fire management in the United States]. / 美国林火管理概况及分析.

With the intensification of climate change and human activities, megafires frequently occur, with serious impacts on ecosystems, atmospheric environment, and human health. The United States has accumulated a large amount of practical experience in forest fire management. A comprehensive review of the framework of forest fire management in the United States can provide an inspiring reference for forest fire prevention in China. Starting from the process of historical evolution of forest fire policy, we systematically introduced the four stages of policy evolution and the characteristics of each stage in the US. Moreover, a comprehensive analysis of forest fire management situation in the US from four aspects was conducted, including the management of combustible fuels, administrative responsibility, fire suppression and forest fire management research support. We summarized relevant literature and proposed improvement strategies for future combustibles management, policy politics and fire fighting in the United States. Through the comprehensive analysis of forest fire management in the United States, we put forward some inspiring opinions on forest fire management in China to promote the establishment of a sound forest fire management system with Chinese characteristics.

Suppression resource decisions are the dominant influence on containment of Australian forest and grass fires.

Fire agencies aim to contain wildfires before they impact on life, property and infrastructure and to reduce the risk of damage to the environment. Despite the large cost of suppression, there are few data on the success of suppression efforts under varying weather, fuel and resource scenarios. We examined over 2200 forest and 4600 grass fires in New South Wales, Australia to determine the dominant influences on the containment of wildfires. A random forest modelling approach was used to analyse the effect of a range of human and environmental factors. The number of suppression resources per area of fire were the dominant influence on the containment of both forest and grass fires. As fire weather conditions worsened the probability of containment decreased across all fires and as fuel loads and slope increased the probability of containment decreased for forest fires. Environmental controls limit the effectiveness of wildfire management. However, results suggest investment in suppression resources and strategic fuel management will increase the probability of containment.

A model for solving the prescribed burn planning problem.

The increasing frequency of destructive wildfires, with a consequent loss of life and property, has led to fire and land management agencies initiating extensive fuel management programs. This involves long-term planning of fuel reduction activities such as prescribed burning or mechanical clearing. In this paper, we propose a mixed integer programming (MIP) model that determines when and where fuel reduction activities should take place. The model takes into account multiple vegetation types in the landscape, their tolerance to frequency of fire events, and keeps track of the age of each vegetation class in each treatment unit. The objective is to minimise fuel load over the planning horizon. The complexity of scheduling fuel reduction activities has led to the introduction of sophisticated mathematical optimisation methods. While these approaches can provide optimum solutions, they can be computationally expensive, particularly for fuel management planning which extends across the landscape and spans long term planning horizons. This raises the question of how much better do exact modelling approaches compare to simpler heuristic approaches in their solutions. To answer this question, the proposed model is run using an exact MIP (using commercial MIP solver) and two heuristic approaches that decompose the problem into multiple single-period sub problems. The Knapsack Problem (KP), which is the first heuristic approach, solves the single period problems, using an exact MIP approach. The second heuristic approach solves the single period sub problem using a greedy heuristic approach. The three methods are compared in term of model tractability, computational time and the objective values. The model was tested using randomised data from 711 treatment units in the Barwon-Otway district of Victoria, Australia. Solutions for the exact MIP could be obtained for up to a 15-year planning only using a standard implementation of CPLEX. Both heuristic approaches can solve significantly larger problems, involving 100-year or even longer planning horizons. Furthermore there are no substantial differences in the solutions produced by the three approaches. It is concluded that for practical purposes a heuristic method is to be preferred to the exact MIP approach.