Develop a multi-periods fuel treatments allocation model to fragment landscape high hazard fuel patches

2013 Summer.Includes bibliographical references.Increased forest fuel loading and continuity have led to more large fires that can potentially cause the loss of property, life and forest resources in certain forest ecosystems. Strategically fragmenting landscape fuel patches with the potential of carrying high intensity or crown fires helps mitigate the future fire risks. This research develops a mathematic integer programming model to optimally locate fuel treatment locations across a landscape for multiple decades. Solutions are aimed at strategically fragmenting high fire hazard fuel patches that support high intensity fires or crown fires. This model can be used to schedule treatments in each stand by reacting to fire ignition probability, potential fire damages to wildland urban interface (WUI), streams, lakes, and the cost of fuel treatment. A set of prototype test cases based on artificial data are used to demonstrate the model performance and support preliminary analyses. This theoretical model can be extended to study a variety of fuel treatment related management concerns across space and time when realistic data become available

Comparing the effects of fuel treatment layouts in fragmenting large contiguous fuel patches under different fire duration assumptions

Includes bibliographical references (pages 16-18).Fuel treatment is an important component of wildland fire management. Fuel treatments can fragment large and contiguous fuel patches with high fire intensity potentials. This research applied a mathematical programming model to compare the effects of different fuel treatment layouts in fragmenting fuel patches, and controlling the future fire sizes under different fire durations assumptions. Analyses suggested that fuel treatment aimed at controlling fires of longer duration could effectively lower the risk of fires with shorter duration. However, fuel treatment layouts aimed at shorter fire durations might not perform well when the future fire duration is much longer. Fuel treatment layout designed under the assumption of infinite fire duration can effectively fragment high fire hazard fuel patches and provide reasonable support for future fire control

An optimisation approach for fuel treatment planning to break the connectivity of high-risk regions

Uncontrolled wildfires can lead to loss of life and property and destruction of natural resources. At the same time, fire plays a vital role in restoring ecological balance in many ecosystems. Fuel management, or treatment planning by way of planned burning, is an important tool used in many countries where fire is a major ecosystem process. In this paper, we propose an approach to reduce the spatial connectivity of fuel hazards while still considering the ecological fire requirements of the ecosystem. A mixed integer programming (MIP) model is formulated in such a way that it breaks the connectivity of high-risk regions as a means to reduce fuel hazards in the landscape. This multi-period model tracks the age of each vegetation type and determines the optimal time and locations to conduct fuel treatments. The minimum and maximum Tolerable Fire Intervals (TFI), which define the ages at which certain vegetation type can be treated for ecological reasons, are taken into account by the model. Examples from previous work that explicitly disconnect contiguous areas of high fuel load have often been limited to using single vegetation types implemented within rectangular grids. We significantly extend such work by including modelling multiple vegetation types implemented within a polygon-based network to achieve a more realistic representation of the landscape. An analysis of the proposed approach was conducted for a fuel treatment area comprising 711 treatment units in the Barwon-Otway district of Victoria, Australia. The solution of the proposed model can be obtained for 20-year fuel treatment planning within a reasonable computation time of eight hours

Fuel treatment planning: Fragmenting high fuel load areas while maintaining availability and connectivity of faunal habitat

Reducing the fuel load in fire-prone landscapes is aimed at mitigating the risk of catastrophic wildfires but there are ecological consequences. Maintaining habitat for fauna of both sufficient extent and connectivity while fragmenting areas of high fuel loads presents land managers with seemingly contrasting objectives. Faced with this dichotomy, we propose a Mixed Integer Programming (MIP) model that can optimally schedule fuel treatments to reduce fuel hazards by fragmenting high fuel load regions while considering critical ecological requirements over time and space. The model takes into account both the frequency of fire that vegetation can tolerate and the frequency of fire necessary for fire-dependent species. Our approach also ensures that suitable alternate habitat is available and accessible to fauna affected by a treated area. More importantly, to conserve fauna the model sets a minimum acceptable target for the connectivity of habitat at any time. These factors are all included in the formulation of a model that yields a multi-period spatially-explicit schedule for treatment planning. Our approach is then demonstrated in a series of computational experiments with hypothetical landscapes, a single vegetation type and a group of faunal species with the same habitat requirements. Our experiments show that it is possible to fragment areas of high fuel loads while ensuring sufficient connectivity of habitat over both space and time. Furthermore, it is demonstrated that the habitat connectivity constraint is more effective than neighbourhood habitat constraints. This is critical for the conservation of fauna and of special concern for vulnerable or endangered species

Temporal optimisation of fuel treatment design in blue gum (Eucalyptus globulus) plantations

Aim of study: This study was conducted to support fire and forest management planning in eucalypt plantations based on economic, ecological and fire prevention criteria, with a focus on strategic prioritisation of fuel treatments over time. The central objective was to strategically locate fuel treatments to minimise losses from wildfire while meeting budget constraints and demands for wood supply for the pulp industry and conserving carbon. Area of study: The study area was located in Serra do Socorro (Torres Vedras, Portugal, covering ~1449 ha) of predominantly Eucalyptus globulus Labill forests managed for pulpwood by The Navigator Company. Material and methods: At each of four temporal stages (2015-2018-2021-2024) we simulated: (1) surface and canopy fuels, timber volume (m3 ha-1) and carbon storage (Mg ha-1); (2) fire behaviour characteristics, i.e. rate of spread (m min-1), and flame length (m), with FlamMap fire modelling software; (3) optimal treatment locations as determined by the Landscape Treatment Designer (LTD). Main results: The higher pressure of fire behaviour in the earlier stages of the study period triggered most of the spatial fuel treatments within eucalypt plantations in a juvenile stage. At later stages fuel treatments also included shrublands areas. The results were consistent with observations and simulation results that show high fire hazard in juvenile eucalypt stands. Research highlights: Forest management planning in commercial eucalypt plantations can potentially accomplish multiple objectives such as augmenting profits and sustaining ecological assets while reducing wildfire risk at landscape scale. However, limitations of simulation models including FlamMap and LTD are important to recognise in studies of long term wildfire management strategiesinfo:eu-repo/semantics/publishedVersio

A landscape-scale optimisation model to break the hazardous fuel continuum while maintaining habitat quality

Wildfires have demonstrated their destructive powers in several parts of the world in recent years. In an effort to mitigate the hazard of large catastrophic wildfires, a common practice is to reduce fuel loads in the landscape. This can be achieved through prescribed burning or mechanically. Prioritising areas to treat is a challenge for landscape managers. To help deal with this problem, we present a spatially explicit, multiperiod mixed integer programming model. The model is solved to yield a plan to generate a dynamic landscape mosaic that optimally fragments the hazardous fuel continuum while meeting ecosystem considerations. We demonstrate that such a multiperiod plan for fuel management is superior to a myopic strategy. We also show that a range of habitat quality values can be achieved without compromising the optimal fuel reduction objective. This suggests that fuel management plans should also strive to optimise habitat quality. We illustrate how our model can be used to achieve this even in the special case where a faunal species requires mature habitat that is also hazardous from a wildfire perspective. The challenging computational effort required to solve the model can be overcome with either a rolling horizon approach or lexicographically. Typical Australian heathland landscapes are used to illustrate the model but the approach can be implemented to prioritise treatments in any fire-prone landscape where preserving habitat connectivity is a critical constraint