Large wildfires are a dominant type of disturbance in North American forests that have caused significant environmental impacts and economic damages. A potential approach to mitigate wildfire spread risk is to segment the landscape with fuel breaks or similar areas with reduced fuel content. However, fragmenting the landscape may undermine other ecosystem services, such as the provision of wildlife migration routes. We present a mixed-integer programming fuel break planning model that minimizes wildfire hazard while protecting migration routes for an endangered wildlife species population (woodland caribou, Rangifer tarandus caribou ). Our model applies the network optimization concept and minimizes the expected burn area in the landscape while protecting a target proportion of the wildlife migration routes. We depict the landscape as a network of patches with fuel and track the impact of fuel breaks across a large set of predicted fire spread scenarios where each scenario is conceptualized as a fire propagation graph. We formulated the fuel break allocation as a scenario-based, mixed-integer optimization problem and used the fuel break widths to track the potential failures of the fuel breaks to contain the fire spread. We also considered a planning problem that minimized the expected area of the largest fires and fuel connectivity in the landscape. For given fire hazard reduction goals, the optimal solutions are those with the least disruptive impacts on the wildlife migration routes. We implemented the approach for the planning of wildfire mitigation in the Red Rock-Prairie Creek area of Alberta (Canada), a fire-prone landscape with the presence of caribou populations. The proposed approach reduced the wildfire spread potential in the area with a trade-off of moderate impacts on known caribou migration routes. Such a methodology is timely to help develop strategies for reducing wildfire hazard in fire-prone forest landscapes while achieving conservation management goals in other regions.

Forest management in North American montane and boreal biomes is facing multiple challenges, including climate change, wildfires and pest outbreaks. Mountain pine beetle (MPB, Dendroctonus ponderosae) is a notable example of a major threat to forest health in western North America whose impacts are compounded by warmer winters, which allowed it to establish further north and east of its historical distributional range. In western Canada, delimiting surveys and control of range-expanding MPB populations are managed through collaborative intergovernmental initiatives. While this approach has been shown to effectively slow MPB spread, these management efforts were planned without assessments of the long-term impacts of survey and control decisions on future rates of MPB spread. Here, we compared the current approach to managing MPB populations driven by recent detections and short-term forecasts against an optimisation-assisted approach that finds a MPB management strategy by factoring in the long-term impacts of survey and management decisions on future spread. We also evaluated a reduced-complexity approach where MPB spread forecasts are factored into decisions without tracking the long-term impacts from future management actions. We found that strategic long-term management could help reduce the future MPB-infested area by 65%-112% compared to the current short-term management strategy. Also, the reduced-complexity approach helped reduce the MPB-invaded area by 16%-77% compared to the conventional short-sighted approach. These results demonstrate the substantial benefits of incorporating longer-term pest spread forecasts and feedback from future management decisions into spatial prioritisations of MPB management efforts.

Wildfires increasingly threaten structures and communities in the wildland-human interface of forested biomes. We present an integrated fuel break placement optimization model that is designed to assist with the planning of landscape scale fuel break configuration to mitigate wildfire risk to structures. The model combines three components: a burn probability simulation model, a structural loss rate model, and a network-based optimization model for fuel break placement. We applied the models to a fire-prone forest landscape encompassing a military training base with frequent ignitions and restricted access zones, and its surrounding communities and residential structures. We evaluated 198 scenarios with different budget levels, management priorities, and jurisdictional constraints to find optimal fuel break placement solutions. Our results show significant fire hazard and risk reduction potential even at modest fuel treatment budgets. Fire risk to structures is reduced most when fuel breaks are placed inside and outside the jurisdiction of the military base. The proposed framework offers a workable decision-support tool for land managers and allows accommodating for real-world jurisdictional constraints, budget limitations, and risk reduction priorities in fire-prone regions.

Large wildfires, the dominant natural disturbance type in North American forests, can cause significant damage to human infrastructure. One well-known approach to reduce the threat of wildfires is the strategic removal of forest fuels in linear firebreaks that segment forest landscapes into distinct compartments. However, limited human and financial resources can make it difficult to plan compartmentalization effectively. In this study, we developed a simulation-optimization approach to assist with the planning of wildfire risk mitigation efforts in the Red Rock-Prairie Creek area of Alberta, Canada, a rugged, fire-prone landscape. First, we used a spatial fire growth model to calculate a matrix of fire spread likelihoods between all pairs of locations in the landscape and used this matrix to guide the allocation of firebreaks. Then, we formulated a firebreak compartmentalization problem to reduce the fire spread potential in the landscape. We depicted the landscape as a network of patches containing hazardous fuels and solved a critical edge removal linear programming problem (CERP) to partially fragment the landscape and minimize the potential of wildfires to spread to adjacent areas. We compared the CERP with other fuel treatment strategies intended to minimize fire-threat measures such as burn likelihood and fuel exposure. Compared to these strategies, the CERP solutions demonstrated better capacity to segment the landscape into evenly spaced compartments and effectively minimized fire spread along the prevailing wind paths. Our solutions provide several strategies for reducing the risk of wildfires to forest habitat and could assist strategic planning of wildfire mitigation activities in other regions.

Firebreaks and fuel treatments are critical means for the reduction of wildfire threat and damage to human infrastructure in forest landscapes. However, the uncertain behavior of wildfires makes the planning of firebreaks challenging, especially when available resources are insufficient to treat all locations under wildfire threat. We present a fire propagation graph approach that utilizes directed acyclic graphs to track the possible spread of wildfires from their ignition locations and estimate the impacts of firebreak placement on the possible burn area. The fire propagation graphs depict plausible fire spread within the fire footprints created with a spatial fire growth model. We integrated the fire propagation graph concept into an optimization model that allocates firebreaks in a complex landscape. We compared two firebreak planning strategies. The first strategy reduces the overall connectivity between patches with fuel and minimizes the number of location pairs between which wildfire spread is possible. The second strategy minimizes the possible burn area across the landscape by tracking the impact of firebreaks on the potential fire spread through a large set of fire propagation graphs that depict plausible fire scenarios. We also evaluated the problem that combines both strategies.We illustrated the approach with the planning of wildfire mitigation measures in the Red Rock-Prairie Creek area of Canada, a complex fire-prone landscape. The firebreak solutions were effectively able to reduce both the potential burn area and the connectivity between locations with fuel. The graph-based depiction of the uncertain wildfire spread helped assess the landscape-level impacts of local firebreak allocation decisions and uncover the tradeoffs between different firebreak planning strategies. The approach could assist wildfire mitigation planning in other regions.

Managed forests are a significant contributor to Canada's economic wealth. However, forestry activities increase landscape fragmentation and impact wildlife species, such as Canada's woodland caribou, that depend on large areas of undisturbed habitat. Proposed conservation policies for caribou in Canada aim to retain 65% or more of caribou ranges as undisturbed landscapes, which would help achieve a 60% likelihood of self-sufficiency of caribou populations. This level of habitat protection may require moving some forest areas out of industrial forestry use and into habitat protection. We have assessed the extent to which this level of range protection would affect timber supply to forest mills in Canada at present-day harvest levels. For the six largest Canadian provinces (British Columbia, Alberta, Saskatchewan, Manitoba, Ontario, and Quebec), we solved an optimization problem that allocated harvest sites across the industrial forestry zone to forest mills at present-day harvest levels with and without caribou conservation and under present and future climate conditions. Retaining 65% of each caribou range area under protection generated moderate timber supply reductions in Quebec and Alberta, with smaller reductions in British Columbia. Sensitivity analyses revealed modest timber supply shortages in Ontario, Saskatchewan, and Manitoba at range retention levels as high as 75%-80%. The estimated timber supply shortages from implementing caribou conservation measures were similar to, or smaller than, those resulting from climate change.

Wildfire is an important natural disturbance agent in Canadian forests, but it has also caused significant economic damage nationwide. Spatial fire growth models have emerged as important tools for representing wildfire dynamics across diverse landscapes, enabling the mapping of key wildfire hazard metrics such as location-specific burn probabilities or likelihoods of fire ignition. While these summary metrics have gained popularity, they often fall short in capturing the directional spread of wildfires and their potential spread distances. The metrics depicting the directional spread of wildfire can be derived from raw outputs generated with fire growth models, such as the perimeters and ignition locations of individual fires, but extracting this information requires complex data processing. To address this data gap, we present PostBP, an open-source Python package designed for post-processing the raw outputs of fire growth models — the ignition locations and perimeters of individual fires simulated over multiple stochastic iterations — into a matrix of fire spread likelihoods between all pairs of forest patches in a landscape. The PostBP also generates several other summary outputs, such as the source-sink ratio and the fire spread rose diagram. We provide an overview of PostBP's capabilities and demonstrate its practical application to a forested landscape. • Wildfire growth models generate large amounts of outputs, which are hard to summarize for practical decision-making. • The PostBP package calculates the summary metrics characterizing the directional spread of wildfires. • The fire risk summaries generated with PostBP can support the assessments of wildfire risk and mitigation measures.

Abstract The invasive emerald ash borer (Agrilus planipennis) causes damage to street trees which is estimated to reach US$ 900 million over the next 30 years. Although millions of dollars are spent annually to control this species, spatiotemporal management plans are often based on rules of thumb that ignore future pest dispersal. Here, we reveal an optimal management strategy to protect urban trees in North America from A. planipennis. To achieve this, we embedded a pest dispersal model within a mixed integer programming framework. We discovered that optimized strategies consistently outperformed those based on rules of thumb, potentially resulting in the protection of an additional nearly 1 million street trees and savings of $ 629 million. Critically, the best management strategies always relied on quarantines and biological control (constituting 98–99% and 1–2% of the project budget, respectively), in contrast with current practices, where federal spending has been diverted to biological control. Our findings serve to inform future pest control efforts and can help protect many more trees from this invasive species.

Industrial forestry activities can increase landscape fragmentation, impacting wildlife populations, particularly Canada's woodland caribou, Rangifer tarandus caribou. To protect caribou in areas with forestry activities, the province of Ontario, Canada, implemented a Dynamic Caribou Harvest Schedule (DCHS). The DCHS spatially aggregates harvest disturbance into regions and distributes them across the landscape to maintain forest patch size-age distributions consistent with a natural variation range. However, the DCHS may negatively impact the cost of timber supply. We compared the DCHS with an alternative zoning approach that assigned the harvest deferral and operational management zones within a large forest area. We compared these approaches using an optimization model that combined harvest scheduling, access road construction, and caribou protection sub-problems. We formulated the protection of caribou habitat and road construction as network flow problems, while the harvesting problem incorporated the ecological constraints prescribed by the forest management plan. We compared the DCHS and zoning approaches in the Wabadowgang Noopming Forest of Ontario, a boreal area within the caribou distribution zone. For the same volume of sustainable harvest, the zoning approach protected less total area but more habitat and old-growth stands over the long term, and yielded lower timber costs by 1.2-2.2 $.m(-3) than the DCHS.

In boreal forests of North America, land managers often carry out preventive treatments of forest fuel for the protection of human infrastructure from wildfires. However, these treatments may negatively affect other ecosystem services, such as the capacity to sustain wildlife populations. Here, we examine the efficacy of a strategy aimed at preserving a critical movement corridor for boreal woodland caribou ( Rangifer tarandus caribou ) in northern Québec, Canada, by raising high-voltage power line conductors above the forest canopy. To assess the interplay between the caribou protection objectives and a reduction in power line's exposure to wildfires, we developed an optimization model that combines the objectives of protecting the power line from wildfires via fuel treatments and maintaining a suitable movement corridor for caribou. The model combines a critical node detection (CND) problem with a habitat connectivity problem that allocates a minimum-resistance fixed-width habitat corridor between isolated wildlife refuges. Our results identify the best locations to perform fire fuel treatments to lessen the threat of fire damage to human infrastructure while maintaining a connectivity corridor for caribou in present and future climate scenarios. The selected fuel treatment locations aimed to mitigate wildfire exposure to a power line. In small-budget solutions, the exposure of power line infrastructure to wildfires was reduced by 36–39% in current climate conditions and by 20–31% in future climate, compared with no-treatment scenarios. Despite the detrimental effects of wildfire on both the industrial asset and caribou habitat, the approach provides strategies that help achieve a compromise between these two values. Such knowledge is timely to help mitigate the negative impacts of climate change on human livelihoods and natural ecosystems.

Abstract The invasive emerald ash borer (Agrilus planipennis) causes damages to street trees estimated to reach US$ 900 million over the next 30 years.Although millions of dollars are spent annually to control this species, such approaches are often based on heuristics. Here, we reveal an optimal management strategy to protect urban trees in North America from A. planipennis. To achieve this, we embedded a pest dispersal model within a mixed integer programming framework. We discovered that optimized strategies consistently outperformed those based on heuristics, potentially resulting in the protection of an additional nearly one million street trees and savings of $ 627 million. Critically, the best management strategies always relied on quarantines and biological control (constituting 83-95% and 5-17% of the project budget, respectively), in contrast with current practices, which have shifted responsibility for quarantines to state authorities. Our findings serve to inform future pest control efforts, and can potentially protect many more trees from this invasive species.

Recreational boats are important vectors of spread of aquatic invasive species (AIS) among waterbodies of the United States. To limit AIS spread, state and county agencies fund watercraft inspection and decontamination stations at lake access points. We present a bi-level model for determining how a state planner can efficiently allocate inspection resources to county managers, who independently decide where to locate inspection stations. In our formulation, each county manager determines a set of optimal plans for the locations of inspection stations under various resource constraints. Each plan maximizes inspections of risky boats that may carry AIS from infested to uninfested lakes within the county. Then, the state planner selects the set of county plans (i.e., one plan for each county) that maximizes the number of risky boats inspected throughout the state subject to a statewide resource constraint. We apply the model using information from Minnesota, USA, including the infestation status of 9182 lakes and estimates of annual numbers of boat movements from infested to uninfested lakes. Comparison of solutions of the bi-level model with solutions of a state-level model where a state planner selects lakes for inspection stations statewide shows that when state and county objectives are not aligned, the loss in efficiency at the state-level can be substantial.

In western Canada, decades of oil-and-gas exploration have fragmented boreal landscapes with a dense network of linear forest disturbances (seismic lines). These seismic lines are implicated in the decline in wildlife populations that are adapted to function in unfragmented forest landscapes. In particular, anthropogenic disturbances have led to a decline of woodland caribou populations due to increasing predator access to core caribou habitat. Restoration of seismic lines aims to reduce the landscape fragmentation and stop the decline of caribou populations. However, planning restoration in complex landscapes can be challenging because it must account for a multitude of diverse aspects. To assist with restoration planning, we present a spatial network optimization approach that selects restoration locations in a fragmented landscape while addressing key environmental and logistical constraints. We applied the model to develop restoration scenarios in the Redrock-Prairie Creek caribou range in northwestern Alberta, Canada, which includes a combination of caribou habitat and active oil-and-gas and timber extraction areas. Our study applies network optimization at two distinct scales to address both the broad-scale restoration policy planning and project-level constraints at the level of individual forest sites. We first delineated a contiguous set of coarse-scale regions where restoration is most cost-effective and used this solution to solve a fine-scale network optimization model that addresses environmental and logistical planning constraints at the level of forest patches. Our two-tiered approach helps address the challenges of fine-scale spatial optimization of restoration activities. An additional coarse-scale optimization step finds a feasible starting solution for the fine-scale restoration problem, which serves to reduce the time to find an optimal solution. The added coarse-scale spatial constraints also make the fine-scale restoration solution align with the coarse-scale landscape features, which helps address the broad-scale restoration policies. The approach is generalizable and applicable to assist restoration planning in other regions fragmented by oil-and-gas activities.

Large-scale delimiting surveys are critical for detecting pest invasions and often undertaken at different gover- nance levels. In this study, we consider two-level hierarchical planning of surveys of harmful invasive pests including a government agency with a mandate to report the spatial extent of an invasion, and regional gov- ernments (counties) concerned about the possible threat of an outbreak. The central agency plans delimiting pest surveys across multiple administrative subdivisions. Counties could participate in these surveys if funds become available. Our goal is to find the optimal levels of cooperation between the central agency and regional governments in the form of the central agency sharing funds with regional governments in a way that benefits both it and the other entities. We propose a Stackelberg game model that finds optimal levels of collaboration between two levels of government in large-scale pest survey campaigns. We apply the model to surveillance of hemlock woolly adelgid, a harmful pest of hemlock trees in Ontario, Canada. Our solutions help anticipate the underperformance of surveys conducted by regional governments because their goals do not fully align with the central agency survey objective. The methodology can be adapted to explore governance hierarchies in other regions and political jurisdictions.

Non‐renewable resource extraction contributes greatly to degradation of wildlife habitats in boreal landscapes. In western Canada, oil and gas exploration and extraction have left a dense network of linear disturbances (seismic lines) and abandoned well pads that have fragmented boreal forest. Among multiple ecological effects, these disturbances have increased predator access to the preferred habitat of some wildlife taxa, most notably boreal woodland caribou, resulting in population declines. Restoration of seismic lines and abandoned well pads is a critical activity to improve the recovery of woodland caribou populations. We present a linear programming model that optimally allocates restoration efforts to maximize the access of caribou to nearby undisturbed habitat in a fragmented landscape. We applied the model to examine restoration scenarios in the Cold Lake First Nations area in northeastern Alberta, Canada, which includes caribou habitat but also areas of active oil and gas extraction. The model depicts the landscape as a network of interconnected habitat patches and combines three network flow sub‐problems. The first sub‐problem enforces the spatial connectivity of the remaining network of unrestored sites. The second sub‐problem maximizes access to suitable habitat from the restored locations and the third sub‐problem ensures the allocation of restoration activities in as few spatially contiguous restoration projects as possible. The approach is generalizable and applicable to assist restoration planning in other resource extraction regions and for other taxa.

We present an applied model that helps restoration practitioners select an ideal mix of species to plant in order to meet their restoration objectives. The model generates virtual plant communities designed to optimize the delivery of multiple ecosystem functions. We used an optimization approach to find the most cost-effective combinations of species to plant to optimize the delivery of four ecosystem functions: rapid establishment of vegetation cover, soil building, biological soil health and resistance to invasion. We used trait-function relationships to characterize species' effects on ecosystem functions. This model accounts for key operational constraints selected by the user, including budget, the number of species to plant, and which functions to consider. The user can also decide whether or not to maximize the functional diversity of the species mix to increase its resilience to global environmental change. To demonstrate the practicality of this approach, we derived optimal species mixtures for the restoration of forests damaged by Cu-Ni smelters in the City of Greater Sudbury (Ontario, Canada). The species mixtures generated by the model varied according to which functions and operational constraints were selected. Results show that the species mixtures that were the most effective at delivering multiple functions were also cost-effective, but were less functionally diverse. This tool provides restoration practitioners with cost-effective restoration strategies for managing the recovery of multi-faceted socio-economic and environmental values in disturbed landscapes.

AbstractWhile the subset of introduced species that become invasive is small, the damages caused by that subset and the costs of controlling them can be substantial. This chapter takes an in-depth look at the economic damages non-native species cause, methods economists often use to measure those damages, and tools used to assess invasive species policies. Ecological damages are covered in other chapters of this book. To put the problem in perspective, Federal agencies reported spending more than half a billion dollars per year in 1999 and 2000 for activities related to invasive species ($513.9 million in 1999 and $631.5 million in 2000 (U.S. GAO 2000)). Approximately half of these expenses were spent on prevention. Several states also spend considerable resources on managing non-native species; for example, Florida spent $127.6 million on invasive species activities in 2000 (U.S. GAO 2000), and the Great Lakes states spend about $20 million each year to control sea lamprey (Petromyzon marinus) (Kinnunen 2015). Costs to government may not be the same as actual damages, which generally fall disproportionately on a few economic sectors and households. For example, the impact of the 2002 outbreak of West Nile virus exceeded $4 million in damages to the equine industries in Colorado and Nebraska alone (USDA APHIS 2003) and more than $20 million in public health damages in Louisiana (Zohrabian et al. 2004). Zebra mussels (Dreissena polymorpha) cause $300–$500 million annually in damages to power plants, water systems, and industrial water intakes in the Great Lakes region (Great Lakes Commission 2012) and are expected to cause $64 million annually in damages should they or quagga mussels (Dreissena bugensis) spread to the Columbia River basin (Warziniack et al. 2011).

Industrial forestry in boreal regions increases fragmentation and may decrease the viability of some wildlife populations, particularly the woodland caribou,Rangifer tarandus caribou. Caribou protection often calls for changes in forestry practices, which may increase the cost and reduce the available timber supply. We present a linear programming model that assesses the trade-off between habitat protection and harvesting objectives by combining harvest scheduling and optimal habitat connectivity problems. We formulate the habitat connectivity model as a network flow problem that maximizes the amount of habitat connected over a desired time span in a forested landscape, while the forestry objective maximizes net undiscounted revenues from timber harvest subject to even harvest flow and environmental sustainability constraints. We applied the approach to explore the trade-off between caribou habitat protection and harvesting goals in the Armstrong-Whitesand Forest, Ontario, Canada, a boreal forest area with prime caribou habitat. Our model also incorporates Dynamic Caribou Harvesting Scheduling (DCHS), a harvest policy currently in a place in Ontario that aims to balance the forest management and caribou protection goals in northern boreal regions. In our study area, the implementation of DCHS appears to have relatively minor impact on timber supply cost. By comparison, maximizing the protection of caribou habitat would lead to a noticeable increase of the mill gate timber cost by $3.3 m(-3)on average, while enabling habitat protection in an additional 5.0%-9.5% of the range area. Our model is generalizable and can be adapted for assessing habitat recovery and harvest goals in other regions. Recommendations for Resource Managers: Incorporating the concept of long-term habitat connectivity into forest planning can help reduce the negative impacts of harvest activities on caribou populations. Prioritizing habitat connectivity leads to a small increase in the overall harvest area because harvest has to be allocated to less productive and more geographically isolated sites to protect prime wildlife habitat containing old conifer stands. Maximizing the habitat protection would lead to a noticeable increase of the timber supply cost (by $3.3 m(-3)on average), while enabling moderate increase of the protected habitat area (i.e., an additional 5.0%-9.5% of the range area). Implementation of Dynamic Caribou Harvest Schedules, which is the current harvesting policy in Ontario's boreal forests when caribou populations are present, causes only a minor increase of the timber supply cost in our study area.

Protecting wildlife corridors is a common management problem in regions of industrial forestry. In boreal Canada, human disturbances have negatively affected woodland caribou populations (Rangifer tarandus caribou), which prefer to function in large undisturbed areas. We present a linear programming model that allocates a fixed-width corridor between isolated caribou ranges and estimates its impact on harvest activities. Our corridor placement problem minimizes total resistance for caribou passing through the corridor, which is protected by a prohibition on all economic activities. We link this corridor placement problem with a harvest planning problem that maximizes the net revenues from harvest minus the cost of building and maintaining forest access roads. We depict gradual expansion of the forest road network over time as a multi-temporal network flow problem. We applied our approach to explore corridor options for connecting caribou populations in the Lake Superior Coast Range, with the Nipigon and Pagwachuan Ranges in the Kenogami-Pic Forest, in northern Ontario, Canada. Our results revealed two locations where corridor placement is cost-effective. Optimal corridor placement depends on the perception of the severity of the impact of roads on caribou populations and decision-making objectives. When the negative impact of roads is perceived to be high and/or maximizing harvest revenues is important, the optimal corridor location is in the eastern part of the study area. However, it is optimal to place the corridor in the western part of the area when the negative impact of roads is perceived to be small or the shortest corridor is desired.