Search

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Although wildfires are an important ecological process in forested regions worldwide, they can cause significant economic damage and frequently create widespread health impacts. We propose a network optimization approach to plan wildfire fuel treatments that minimize the risk of fire spread in forested landscapes under an upper bound for total treated area. We used simulation modeling to estimate the probability of fire spread between pairs of forest sites and formulated a modified Critical Node Detection (CND) model that uses these estimated probabilities to find a pattern of fuel reduction treatments that minimizes the likely spread of fires across a landscape. We also present a problem formulation that includes control of the size and spatial contiguity of fuel treatments. We demonstrate the approach with a case study in Kootenay National Park, British Columbia, Canada, where we investigated prescribed burn options for reducing the risk of wildfire spread in the park area. Our results provide new insights into cost-effective planning to mitigate wildfire risk in forest landscapes. The approach should be applicable to other ecosystems with frequent wildfires. [ABSTRACT FROM AUTHOR]

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. • The proposed methodology can assist restoration of linear disturbances in forest landscapes. • Optimization model supports restoration decisions by accounting for both operational and wildlife conservation objectives. • The two-tier approach addresses both the broad-scale policy goals and practical planning at the level of individual sites. • The approach is applicable in areas with presence of both resource extraction activities and endangered species populations. [ABSTRACT FROM AUTHOR]

Protecting wildlife within areas of resource extraction often involves reducing habitat fragmentation. In Canada, protecting threatened woodland caribou (Rangifer taranduscaribou (Gmelin, 1788)) populations requires preserving large areas of intact forest habitat, with some restrictions on industrial forestry activities. We present a linear programming model that assesses the trade-off between achieving an objective of habitat protection for caribou populations while maintaining desired levels of harvest in forest landscapes. The habitat-protection objective maximizes the amount of connected habitat that is accessible by caribou, and the forestry objective maximizes net revenues from timber harvest subject to even harvest flow, a harvest target, and environmental sustainability constraints. We applied the model to explore the habitat protection and harvesting scenarios in the Cold Lake caribou range, a 6726 km2 area of prime caribou habitat in Alberta, Canada. We evaluated harvest scenarios ranging from 0.1 Mm3·year–1 to maximum sustainable harvest levels over 0.7 Mm3·year–1 and assessed the impact of habitat protection measures on timber supply costs. Protecting caribou habitat by deferring or reallocating harvest increases the timber unit cost by Can$1.1–2.0 m–3. However, this impact can be partially mediated by extending the harvest to areas of oil and gas extraction to offset forgone harvest in areas of prime caribou habitat. [ABSTRACT FROM AUTHOR]

Detections of invasive species outbreaks are often followed by the removal of susceptible host organisms in order to slow the spread of the invading pest population. We propose the acceptance sampling approach for detection and optional removal of susceptible host trees to manage an outbreak of the emerald ash borer (EAB), a highly destructive forest pest, in Winnipeg, Canada. We compare the strategy with two common delimiting survey techniques that do not consider follow-up management actions such as host removal. Our results show that the management objective influences the survey strategy. The survey-only strategies maximized the capacity to detect new infestations and prioritized sites with high likelihood of being invaded. Comparatively, the surveys with subsequent host removal actions allocated most of the budget to sites where complete host removal would minimize the pest’s ability to spread to uninvaded locations. Uncertainty about the pest’s spread causes the host removal measures to cover a larger area in a uniform spatial pattern and extend to farther distances from already infested sites. If a decision maker is ambiguity-averse and strives to avoid the worst-case damages from the invasion, the optimal strategy is to survey more sites with high host densities and remove trees from sites at farther distances, where EAB arrivals may be uncertain, but could cause significant damage if not detected quickly. Accounting for the uncertainty about spread helps develop a more robust pest management strategy. The approach is generalizable and can support management programs for new pest incursions. [ABSTRACT FROM AUTHOR]

Surveillance programs to detect alien invasive pests seek to find them as soon as possible, but also to minimize the cost of damage from invasion. To examine the trade-offs between these objectives, we developed an economic model that allocates survey sites to minimize either the expected mitigation costs or the expected time until first detection of an invasive alien pest subject to a budget constraint on surveillance costs. We also examined strategies preferred by ambiguity-averse decision makers that minimize the expected and worst-case outcomes of each performance measure. We applied the model to the problem of detecting Asian longhorned beetle (Anoplophora glabripennis) in the Greater Toronto Area, Canada, one of the most harmful invasive alien insects in North America. When minimizing expected mitigation costs or expected time to detection, the trade-off between these survey objectives was small. Strategies that minimize the worst-case mitigation costs differed sharply and surveyed sites with high host densities using high sampling intensities whereas strategies that minimize the worst detection times surveyed sites across the entire area using low sampling intensities. Our results suggest that preferences for minimizing mitigation costs or time to detection are more consequential for ambiguity-averse managers than they are for risk-neutral decision-makers. • A spatial optimization model is proposed for early detection of biological invasions. • The model minimizes expected time to first detection and expected damage from invasion. • The approach is applied to detect Asian longhorned beetle in Toronto, ON. • We tested risk-neutral and risk-averse survey strategies that minimize the expected and expected worst-case outcomes. • Preferences for minimizing damage or time to detection are more consequential for risk-averse decision-makers. [ABSTRACT FROM AUTHOR]

Abstract Anthropogenic disturbances fragmenting wildlife habitat greatly contribute to extinction risk for many species. In western Canada, four decades of oil and gas exploration have created a network of seismic lines, which are linear disturbances where seismic equipment operates. Seismic lines cause habitat fragmentation and increase predator access to intact forest, leading to declines of some wildlife populations, particularly the threatened woodland caribou, Rangifer tarandus caribou. Restoration of forests within seismic lines is an important activity to reduce habitat fragmentation and recovery caribou. We present an optimization model with the objective of guiding landscape restoration strategies that maximize the area of connected habitat for a caribou population in a fragmented landscape. We use our model to find optimal strategies for seismic line restoration in the Cold Lake Area of Alberta, Canada, a 6726-km2 expanse of boreal forest that represents prime caribou habitat. We formulate mixed integer programming models that depict the landscape as a network of interconnected habitat patches. We develop and compare formulations that emphasize the population's local or long-distance access to habitat. Optimal restoration involves a mix of two strategies: the first establishes short-distance connections between forest patches with large areas of intact habitat and the second establishes corridors between areas with known species locations and large amounts of suitable habitat. Our approach reveals the trade-offs between these strategies and finds the optimal restoration solutions under a limited budget. The approach is generalizable and applicable to other regions and species sensitive to changes in landscape-level habitat connectivity. [ABSTRACT FROM AUTHOR]

Surveying multiple invasive pest species at the same time can help reduce the cost of detecting new pest invasions. In this paper, we describe a new method for mapping the relative likelihood of pest invasion via plant propagation material in a geographic setting. The method simulates the invasion of a range of pest species, including arrival in an uninvaded area, spread, and survival in a novel landscape, using information on the spatial and temporal distribution of the suitable host crop species and tentative knowledge of the spread and survival capacities of the target pests. The methodology is applied to a gridded map in which each map cell represents a site in a landscape. The method uses stochastic simulations to depict plausible realizations of the invasion outcomes and estimate the distribution of pest invasion likelihood for each cell in the area of concern. The method then prioritizes the cells based on the stochastic invasion outcomes using a pairwise stochastic dominance rule and a hypervolume indicator. We demonstrate the approach by assessing the relative likelihood of pest invasion for strawberry production in Finland. Our method helps to differentiate sites in a landscape using both the estimates of pest invasion risk and their uncertainty. It can be applied to prioritize sites for plant health surveys and allocate survey resources among large geographic regions. The approach is generalizable and can be used in situations where knowledge of the harmful pest species is poor or nonexistent. [ABSTRACT FROM AUTHOR]

Policy makers and investors often need to consider trade-offs between alternative biomass-based energy supply options. Supply cost potentials for three bioenergy feedstocks prevalent in Canada including agricultural residues, dedicated woody crops, and forest harvest residues are summarized. Each feedstock has its own particular cost characteristics depending on the quantities involved. Importantly, this synthesis revealed significant differences in the uncertainty associated with the cost estimates, with agricultural residues having the greatest variation, followed by woody crops and postharvest forest residues, respectively. One implication of this uncertainty is that the attractiveness of each feedstock option likely depends on local market demand conditions and producer circumstances, making definitive aggregate supply estimates challenging. [ABSTRACT FROM AUTHOR]

Uncertainty about future spread of invasive organisms hinders planning of effective response measures. We present a two-stage scenario optimization model that accounts for uncertainty about the spread of an invader, and determines survey and eradication strategies that minimize the expected program cost subject to a safety rule for eradication success. The safety rule includes a risk standard for the desired probability of eradication in each invasion scenario. Because the risk standard may not be attainable in every scenario, the safety rule defines a minimum proportion of scenarios with successful eradication. We apply the model to the problem of allocating resources to survey and eradicate the Asian longhorned beetle (ALB, Anoplophora glabripennis) after its discovery in the Greater Toronto Area, Ontario, Canada. We use historical data on ALB spread to generate a set of plausible invasion scenarios that characterizes the uncertainty of the beetle’s extent. We use these scenarios in the model to find survey and tree removal strategies that minimize the expected program cost while satisfying the safety rule. We also identify strategies that reduce the risk of very high program costs. Our results reveal two alternative strategies: (i) delimiting surveys and subsequent tree removal based on the surveys' outcomes, or (ii) preventive host tree removal without referring to delimiting surveys. The second strategy is more likely to meet the stated objectives when the capacity to detect an invader is low or the aspirations to eradicate it are high. Our results provide practical guidelines to identify the best management strategy given aspirational targets for eradication and spending. [ABSTRACT FROM AUTHOR]

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. • Recreational boats spread aquatic invasive species among waterbodies in the USA. • State planners allocate funds to county managers who design boat inspection programs. • Integer programming models optimize state planners' allocation of prevention funds. • Bi-level allocation of funds is less efficient than state-level prevention decisions. [ABSTRACT FROM AUTHOR]

Assessing risks of uncertain but potentially damaging events, such as environmental disturbances, disease outbreaks and pest invasions, is a key analytical step that informs subsequent decisions about how to respond to these events. We present a continuous risk measure that can be used to assess and prioritize environmental risks from uncertain data in a geographical domain. The metric is influenced by both the expected magnitude of risk and its uncertainty. We demonstrate the approach by assessing risks of human-mediated spread of Asian longhorned beetle (ALB, Anoplophora glabripennis ) in Greater Toronto (Ontario, Canada). Information about the human-mediated spread of ALB through this urban environment to individual geographical locations is uncertain, so each location was characterized by a set of probabilistic rates of spread, derived in this case using a network model. We represented the sets of spread rates for the locations by their cumulative distribution functions (CDFs) and then, using the first-order stochastic dominance rule, found ordered non-dominant subsets of these CDFs, which we then used to define different classes of risk across the geographical domain, from high to low. Because each non-dominant subset was estimated with respect to all elements of the distribution, the uncertainty in the underlying data was factored into the delineation of the risk classes; essentially, fewer non-dominant subsets can be defined in portions of the full set where information is sparse. We then depicted each non-dominant subset as a point cloud, where points represented the CDF values of each subset element at specific sampling intervals. For each subset, we then defined a hypervolume bounded by the outermost convex frontier of that point cloud. This resulted in a collection of hypervolumes for every non-dominant subset that together serve as a continuous measure of risk, which may be more practically useful than averaging metrics or ordinal rank measures. Overall, the approach offers a rigorous depiction of risk in a geographical domain when the underlying estimates of risk for individual locations are represented by sets or distributions of uncertain estimates. Our hypervolume-based approach can be used to compare assessments made with different datasets and assumptions. [ABSTRACT FROM AUTHOR]

Uncertainty about future outcomes of invasions is a major hurdle in the planning of invasive species management programs. We present a scenario optimization model that incorporates uncertainty about the spread of an invasive species and allocates survey and eradication measures to minimize the number of infested or potentially infested host plants on the landscape. We demonstrate the approach by allocating surveys outside the quarantine area established following the discovery of the Asian longhorned beetle (ALB) in the Greater Toronto Area (GTA), Ontario, Canada. We use historical data on ALB spread to generate a set of invasion scenarios that characterizes the uncertainty of the pest's extent in the GTA. We then use these scenarios to find allocations of surveys and tree removals aimed at managing the spread of the pest in the GTA. It is optimal to spend approximately one-fifth of the budget on surveys and the rest on tree removal. Optimal solutions do not always select sites with the greatest propagule pressure, but in some cases focus on sites with moderate likelihoods of ALB arrival and low host densities. Our approach is generalizable and helps support decisions regarding control of invasive species when knowledge about a species' spread is uncertain. [ABSTRACT FROM AUTHOR]

Large-scale delimiting surveys are critical for detecting pest invasions and often undertaken at different governance 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 governments (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. • We find optimal levels of cooperation between two levels of governments in pest survey campaigns. • Our model finds optimal cost-sharing strategy between a biosecurity agency and regional governments. • We demonstrate the approach for delimiting surveys of hemlock woolly adelgid in Ontario, Canada. • The approach can be adapted to improve a governance of biosecurity projects in other regions. [ABSTRACT FROM AUTHOR]

Aim We address the problem of geographically allocating scarce survey resources to detect pests in their pathways of introduction given information about their likelihood of movement between origins and destinations. We introduce a model for selecting destination sites for survey that departs from the aim of reducing propagule pressure (PP) in pest destinations and instead aims to increase monitoring of pest origins. The model is a maximum expected coverage problem (MECP), which maximizes the expected number of origins that are covered by the survey system, where an origin is covered if at least one of its transmission pathways connects to a surveyed destination. For comparison, we present two models that aim to reduce PP in destination sites. One model maximizes the expected number of transmission pathways that are covered by survey locations and the other maximizes the expected number of survey locations that have one or more pest introductions. Location United States, Canada. Methods We demonstrate the models by analysing the human-mediated spread of the emerald ash borer ( Agrilus planipennis Fairmaire), a major pest of ash trees in North America, by visitors to campgrounds in central Canada and the US Midwest. The models incorporate estimates of spread rates from a network of campers travelling from approximately 6500 invaded domains to 266 uninvaded campgrounds in three Canadian provinces (Ontario, Quebec and Manitoba) and three US states (Michigan, Minnesota and Wisconsin). Results The MECP and PP-based model solutions agreed for large surveillance budgets but exhibited differences when the budgets were small. These results stem from differences between the coverage-based objective in MECP and the PP-based metrics in the PP models. Main conclusions Our comparison of MECP and PP-based models reveals the trade-offs between objectives. Overall, the MECP is generic and can be adapted to survey species that are spread via other human-mediated vectors. [ABSTRACT FROM AUTHOR]

The pattern of forest land clearing in a region can be viewed as a gauge of sustainable (or unsustainable) use of agricultural and forest resources. In this study we examine the geographical distribution of land clearing potential in the Canadian agriculture–forestry interface and propose a new landscape-scale indicator that quantifies this potential. We consider the possibility that forested land will be cleared for agriculture as a trade-off between the land's capacity to support agriculture and its comparative value if it remains forested. However, this trade-off is complicated by the land's susceptibility to fragmentation (and subsequent conversion), which derives from the local pattern of forest, agriculture and other land cover types. We find the locations in the agriculture–forestry interface with the highest land clearing potential by delineating nested multi-attribute frontiers in the dimensions of the land's agricultural capacity, its estimated forest productivity and its fragmentation potential. The multi-attribute frontier concept addresses our lack of knowledge about the relative importance of these multiple drivers of land conversion by objectively combining them into a single-dimensional land clearing pressure metric in a geographical setting. Overall, our approach provides a simple yet informative indicator which reveals the geographical stratification of land clearing pressures across large regions. In general, the spatial delineation of areas with high land clearing potential agrees well with recent evidence of land clearing and deforestation events in Canada. [ABSTRACT FROM AUTHOR]

This study estimates the potential physical amounts and financial costs of post-harvest forest residue biomass supply in Canada. The analyses incorporate the locations of harvest activities in Canada, the geographical variation of forest productivity patterns and the costs associated with the extraction and transportation of residue feedstock to bioenergy facilities. We estimated the availability of harvest residues within the extent of industrial forest management operations in Canadian forests. Our analyses focused on the extraction of biomass from roadside harvest residues that involve four major cost components: pre-piling and aggregation, loading, chipping and transportation. The estimates of residue extraction costs also included representation of basic ecological sustainability and technical accessibility constraints. Annual supply of harvestable residual biomass with these ecological sustainability constraints were estimated to be approximately 19.2–23.3 Tg * year −1 and 16.5–20.0 Tg * year −1 in scenarios that included both ecological and technical accessibility limitations. These estimates appear to be less than other similar studies, due to the higher level of spatial details on inventories and ecological and operational constraints in our analyses. The amount of residual biomass available in baseline scenarios at a supply cost of $60 ODT −1 and $80 ODT −1 were 1.08 and 1.38 Tg year −1 and 7.82 and 10.14 Tg year −1 respectively. Decreasing residue extraction costs by 35% increased the amount of residues available at a $60 ODT −1 and $80 ODT −1 supply price by ∼5.5–5.7 and ∼1.5–1.6 times respectively. The assessment methodology is generic and could be extended to examine residue supplies for specialized biomass markets such as lignocellulosic ethanol production. [ABSTRACT FROM AUTHOR]

In this study we demonstrate how the notion of diversification can be used in broad-scale resource allocation for surveillance of invasive species. We consider the problem of short-term surveillance for an invasive species in a geographical environment. We find the optimal allocation of surveillance resources among multiple geographical subdivisions via application of a classical portfolio framework, which allocates investments among multiple financial asset types with uncertain returns in a portfolio that maximizes the performance and, by meeting the desired diversification targets, protects against errors in estimating the portfolio's performance. We illustrate the approach with a case study that applies a spatial transmission model to assess the risk of spread of the emerald ash borer (EAB), a significant pest in North America, with infested firewood that may be carried by visitors to campground facilities in central Canada. Adding the diversification objective yields an expected survey performance that is comparable with undiversified optimal allocation, but more importantly, makes the geographical distribution of survey priorities less subject to possible errors in the spread rate estimates. Overall, diversification of pest surveillance can be viewed as a viable short-term strategy for hedging against uncertainty in expert- and model-based assessments of pest invasion risk. [Copyright &y& Elsevier]

Long-distance dispersal pathways, which frequently relate to human activities, facilitate the spread of alien species. One pathway of concern in North America is the possible spread of forest pests in firewood carried by visitors to campgrounds or recreational facilities. We present a network model depicting the movement of campers and, by extension, potentially infested firewood. We constructed the model from US National Recreation Reservation Service data documenting more than seven million visitor reservations (including visitors from Canada) at campgrounds nationwide. This bi-directional model can be used to identify likely origin and destination locations for a camper-transported pest. To support broad-scale decision making, we used the model to generate summary maps for 48 US states and seven Canadian provinces that depict the most likely origins of campers traveling from outside the target state or province. The maps generally showed one of two basic spatial patterns of out-of-state (or out-of-province) origin risk. In the eastern United States, the riskiest out-of-state origin locations were usually found in a localized region restricted to portions of adjacent states. In the western United States, the riskiest out-of-state origin locations were typically associated with major urban areas located far from the state of interest. A few states and the Canadian provinces showed characteristics of both patterns. These model outputs can guide deployment of resources for surveillance, firewood inspections, or other activities. Significantly, the contrasting map patterns indicate that no single response strategy is appropriate for all states and provinces. If most out-of-state campers are traveling from distant areas, it may be effective to deploy resources at key points along major roads (e.g., interstate highways), since these locations could effectively represent bottlenecks of camper movement. If most campers are from nearby areas, they may have many feasible travel routes, so a more widely distributed deployment may be necessary. [ABSTRACT FROM AUTHOR]

Abstract: Long-distance introductions of alien species are often driven by socioeconomic factors, such that conventional “biological” invasion models may not be capable of estimating spread fully and reliably. In this study, we demonstrate a new technique for assessing and reconstructing human-mediated pathways of alien forest species entries to major settlements in Canada via commercial road transportation and domestic trade. We undertook our analysis in three steps. First, we used existing data on movement of commodities associated with bark- and wood-boring forest pests to build a probabilistic model of how the organisms may be moved from one location to another through a transportation network. We then used this model to generate multiple sets of predictions of species arrival rates at every location in the transportation network, and to identify the locations with the highest likelihood of new incursions. Finally, we evaluated the sensitivity of the species arrival rates to uncertainty in key model assumptions by testing the impact of additive and multiplicative errors (by respectively adding a uniform random variate or symmetric variation bounds to the arrival rate values) on the probabilities of pest transmission from one location to another, as well as the impact of the removal of one or more nodes and all connecting links to other nodes from the underlying transportation network. Overall, the identification of potential pest arrival hotspots is moderately robust to uncertainties in key modeling assumptions. Large urban areas and major border crossings that have the highest predicted species arrival rates have the lowest sensitivities to uncertainty in the pest transmission potential and to random changes in the structure of the transportation network. The roadside survey data appears to be sufficient to delineate major hubs and hotspots where pests are likely to arrive from other locations in the network via commercial truck transport. However, “pass-through” locations with few incoming and outgoing routes can be identified with lower precision. The arrival rates of alien forest pests appear to be highly sensitive to additive errors. Surprisingly, the impact of random changes in the structure of the transportation network was relatively low. [Copyright &y& Elsevier]

Pest risk maps are important decision support tools when devising strategies to minimize introductions of invasive organisms and mitigate their impacts. When possible management responses to an invader include costly or socially sensitive activities, decision-makers tend to follow a more certain (i.e., risk-averse) course of action. We presented a new mapping technique that assesses pest invasion risk from the perspective of a risk-averse decision maker. We demonstrated the method by evaluating the likelihood that an invasive forest pest will be transported to one of the U.S. states or Canadian provinces in infested firewood by visitors to U.S. federal campgrounds. We tested the impact of the risk aversion assumption using distributions of plausible pest arrival scenarios generated with a geographically explicit model developed from data documenting camper travel across the study area. Next, we prioritized regions of high and low pest arrival risk via application of two stochastic ordering techniques that employed, respectively, first- and second-degree stochastic dominance rules, the latter of which incorporated the notion of risk aversion. We then identified regions in the study area where the pest risk value changed considerably after incorporating risk aversion. While both methods identified similar areas of highest and lowest risk, they differed in how they demarcated moderate-risk areas. In general, the second-order stochastic dominance method assigned lower risk rankings to moderate-risk areas. Overall, this new method offers a better strategy to deal with the uncertainty typically associated with risk assessments and provides a tractable way to incorporate decisionmaking preferences into final risk estimates, and thus helps to better align these estimates with particular decision-making scenarios about a pest organism of concern. Incorporation of risk aversion also helps prioritize the set of locations to target for inspections and outreach activities, which can be costly. Our results are especially important and useful given the huge number of camping trips that occur each year in the United States and Canada. [ABSTRACT FROM AUTHOR]

Aim Risk assessments in applied scientific disciplines have evolved somewhat in isolation, adopting conventions, assumptions and tools from other disciplines almost haphazardly. This editorial provides background for the articles in this special issue, which sample six broad themes in risk assessment in conservation biology and presenting new innovations and applications. Location Global. Methods The articles in the special issue address themes related to species distribution modelling, population viability analysis, threatened species management, biosecurity, uncertainty analysis, cost-benefit analysis and foresight. We sought articles that address new and emerging topics in each of these areas. Results The articles identify new and potentially useful innovations in a variety of areas relevant to conservation biology. Collectively, they paint a picture of risk assessment as an important element in supporting transparent, rational decisions and effective policy. Main conclusions Policy makers and conservation managers aspire to set evidence-based priorities, and technical specialists aim to have their methods used in decision-making. Scientists will succeed if, as the articles in this issue exemplify, they develop a sound understanding of the context of the decisions in which their tools are to be used and shape them accordingly. [ABSTRACT FROM AUTHOR]

Aim Geographic mapping of risks is a useful analytical step in ecological risk assessments and in particular, in analyses aimed to estimate risks associated with introductions of invasive organisms. In this paper, we approach invasive species risk mapping as a portfolio allocation problem and apply techniques from decision theory to build an invasion risk map that combines risk and uncertainty in a single map product. Location Canada. Methods We divide the study area into a set of spatial domains and treat each domain as an individual 'portfolio' with a unique distribution of the expected impacts of invasion. The risk of invasion is then mapped by finding nested 'efficient' portfolio sets that identify the geographic areas exhibiting the worst combinations of the estimated risk of invasion and the uncertainty in that estimate. For Canadian municipalities, we apply the approach to quantify the risk that a given location will receive invasive forest pests with commercial freight transported via the North American road network. We compare risk allocation techniques that employ the concepts of nested mean-variance ( M-V) frontiers and second-degree stochastic dominance. Results While both methods based on M-V and the stochastic dominance principles identified similar areas of highest risk, they differed in how they demarcated moderate-risk areas. Furthermore, they address uncertainty in different ways, treating it as a risk premium (in the case of nested M-V frontiers) or producing risk-averse delineations (in the case of stochastic dominance). Main conclusions The portfolio-based approach offers a viable strategy for dealing with the typically wide variability in risk estimates caused by a lack of knowledge about a new invader. The methodology also provides a tractable way of incorporating decision-making preferences into the final risk estimates and thus better aligns risk assessments with particular decision-making scenarios about the organism of concern. [ABSTRACT FROM AUTHOR]

Species can sometimes spread significant distances beyond their natural dispersal ability by anthropogenic means. International shipping routes and the transport of shipping containers, in particular are a commonly recognised pathway for the introduction of invasive species. Species can gain access to a shipping container and remain inside, hidden and undetected for long periods. Currently, government biosecurity agencies charged with intercepting and removing these invasive species when they arrive to a county's border only assess the most immediate point of loading in evaluating a shipping container's risk profile. However, an invasive species could have infested a container previous to this point and travelled undetected before arriving at the border. To assess arrival risk for an invasive species requires analysing the international shipping network in order to identify the most likely source countries and the domestic ports of entry where the species is likely to arrive. We analysed an international shipping network and generated pathway simulations using a first-order Markov chain model to identify possible source ports and countries for the arrival of Khapra beetle (Trogoderma granarium) to Australia. We found Kaohsiung (Taiwan) and Busan (Republic of Korea) to be the most likely sources for Khapra beetle arrival, while the port of Melbourne was the most likely point of entry to Australia. Sensitivity analysis revealed significant stability in the rankings of foreign and Australian ports. This methodology provides a reliable modelling tool to identify and rank possible sources for an invasive species that could arrive at some time in the future. Such model outputs can be used by biosecurity agencies concerned with inspecting incoming shipping containers and wishing to optimise their inspection protocols. [ABSTRACT FROM AUTHOR]

Aim Uncertainty has been widely recognized as one of the most critical issues in predicting the expansion of ecological invasions. The uncertainty associated with the introduction and spread of invasive organisms influences how pest management decision makers respond to expanding incursions. We present a model-based approach to map risk of ecological invasions that combines two potentially conflicting goals: (1) estimating the likelihood of a new organism being established at a given locale and (2) quantifying the uncertainty of that prediction. Location Eastern and central Canada. Methods Our methodology focuses on the potential for long-distance, human-assisted spread of invasive organisms. First, we used a spatial simulation model to generate distributions of plausible invasion outcomes over a target geographical region. We then used second-degree stochastic dominance (SSD) criteria to rank all geographical locations in the target region based on these distributions. We applied the approach to analyze pathways of human-assisted spread (i.e., with commercially transported goods) of the emerald ash borer (EAB) ( Agrilus planipennis Fairmaire), a major pest of ash trees in North America. Results The projected potential of the pest to establish at remote locations is significantly shaped by the amount of epistemic uncertainty in the model-based forecasts. The estimates based on the SSD ranking identified major 'crossroads' through which the movement of the EAB with commercial transport is most likely to occur. The system of major expressways in Ontario and Quebec was confirmed as the primary gateway of the pest's expansion throughout the Canadian landscape. Main conclusions Overall, the new approach generates more realistic predictions of long-distance introductions than models that do not account for severe uncertainties and thus can help design more effective pest surveillance programmes. The modelling technique is generic and can be applied to assess other environmental phenomena when the level of epistemic uncertainty is high. [ABSTRACT FROM AUTHOR]

We present the idea of using potential infringements on annual allowable harvest targets as an approach to estimate threats from invasive species to the forest products sector. The approach uses present-day harvest levels as a reference level to estimate when and where the impact of a nonnative forest pest could become economically damaging. We use a generic model that simulates spread and damage by nonnative invasive species, basic harvest and forest growth through time. The concept is illustrated with a case study of a new nonnative invasive pest, Sirex noctilio Fabricius on pine resources in eastern Canada. Impacts of invasion on wood supply, in particular, the point at which present-day harvest levels are not attainable, were identified for 77 non-overlapping geographical regions that delimit the primary wood supply areas around large mills and wood processing facilities in eastern Canada. The results identify the minimum area of a pest outbreak that could trigger harvest shortages (approximately 12.5–14 M ha of pine forests in Ontario and Quebec). Beyond this level, the amount of host resource available for harvesting in any given year declines rapidly. The failure to sustain broad-scale harvest targets may be an attractive and intuitive indicator for policy makers and regulators interested in developing control and “slow-the-spread” programs for non-native forest pests. [Copyright &y& Elsevier]

Abstract: This study explores the economic feasibility of fossil fuel substitution with biomass from short-rotation willow plantations as an option for greenhouse heating in southern Ontario, Canada. We assess the net displacement value of fossil fuel biomass combustion systems with an integrated purpose-grown biomass production enterprise. Key project parameters include greenhouse size, heating requirements, boiler capital costs and biomass establishment and management costs. Several metrics have been used to examine feasibility including net present value, internal rate of return, payback period, and the minimum or break-even prices for natural gas and heating oil for which the biomass substitution operations become financially attractive. Depending on certain key assumptions, internal rates of return ranged from 11–14% for displacing heating oil to 0–4% for displacing natural gas with woody biomass. The biomass heating projects have payback periods of 10 to >22 years for substituting heating oil and 18 to >22 years for replacing a natural gas. Sensitivity analyses indicate that fossil fuel price and efficiency of the boiler heating system are critical elements in the analyses and research on methods to improve growth and yield and reduce silviculture costs could have a large beneficial impact on the feasibility of this type of bioenergy enterprise. [ABSTRACT FROM AUTHOR]

Integrated pest risk maps and their underlying assessments provide broad guidance for establishing surveillance programs for invasive species, but they rarely account for knowledge gaps regarding the pest of interest or how these can be reduced. In this study we demonstrate how the somewhat competing notions of robustness to uncertainty and potential knowledge gains could be used in prioritizing large-scale surveillance activities. We illustrate this approach with the example of an invasive pest recently detected in North America, Sirex noctilio Fabricius. First, we formulate existing knowledge about the pest into a stochastic model and use the model to estimate the expected utility of surveillance efforts across the landscape. The expected utility accounts for the distribution, abundance and susceptibility of the host resource as well as the value of timely S. noctilio detections. Next, we make use of the info-gap decision theory framework to explore two alternative pest surveillance strategies. The first strategy aims for timely, certain detections and attempts to maximize the robustness to uncertainty about S. noctilio behavior; the second strategy aims to maximize the potential knowledge gain about the pest via unanticipated (i.e., opportune) detections. The results include a set of spatial outputs for each strategy that can be used independently to prioritize surveillance efforts. However, we demonstrate an alternative approach in which these outputs are combined via the Pareto ranking technique into a single priority map that outlines the survey regions with the best trade-offs between both surveillance strategies. [Copyright &y& Elsevier]

This study explores the economic attractiveness of afforestation as a strategy for the joint production of fibre, carbon storage and biosolids (treated municipal sewage sludge) disposal for municipalities in Southern and Central Ontario, Canada. We use a spatial, stochastic model, the Canadian Forest Service Afforestation Feasibility Model (CFS-AFM), to simulate a range of spatial biosolids application scenarios in hybrid poplar afforestation projects. Results suggest that such joint afforestation strategies could be financially attractive. Significant cost savings can be expected through decreases in transportation distances and avoided waste disposal fees. Sensitivity analysis is used to examine the effects of variations in critical model parameters on net present values. Our findings indicate that waste disposal savings from application of biosolids on hybrid poplar plantations combined with incentives for landowners to sequester carbon can easily compete with agricultural land rental values in some regions of Ontario. Social acceptance of this kind of activity, however, may be an impediment to adoption. [Copyright &y& Elsevier]

In this paper we provide an overview of an integrated approach to modelling the risks and impacts associated with non-indigenous forest pest species. This is a broad and important topic given the scale of ecological and economic consequences associated with non-indigenous species in North America and elsewhere. Assessments of risks and impacts remain difficult due to complexities and interactions between the many factors driving invasions and outcomes. These processes occur across various spatial and temporal scales, and are often influenced and complicated by human activities. For each component of an ecological invasion (i.e., arrival, establishment, and spread), we review general approaches for modelling the phenomenon and identify data and knowledge gaps. With the greater availability of various spatial data and computational power we suggest the possibility of linking the models for each invasion component into a more integrated framework, thus allowing interactions and feedbacks between components to be better incorporated into risk modelling efforts. The approach is illustrated using examples from current work with Sirex noctilio Fabricius — a relatively new invasive wood wasp in eastern North America. [ABSTRACT FROM AUTHOR]

This study presents a model that assesses the potential impact of a new alien insect species, Sirex noctilio Fabricius, on pine timber supply and harvest activities in eastern Canada. We integrate the spread of S. noctilio with a broad-scale growth and harvest allocation model. Projections of pine mortality range between 25 × 106 and 115 × 106 m3 over 20 years depending on S. noctilio spread and impact assumptions. Our model suggests Ontario could experience the highest, most immediate losses (78% of the potential losses across eastern Canada), with Quebec sustaining most of the rest of the losses over the next 20 years. Potential losses of $86 to $254 million per year are simulated after 20 years. The net present value of total harvest losses after 28 years of outbreak ranges between $0.7 to $2.1 billion. Adaptation policies decrease short-term losses by 46%–55% and delay larger harvest failures by 9–11 years. Without harvest adaptation, failures to maintain annual allowable cut levels may occur once the total area infested exceeds 15 × 106 ha. While better understanding and representing S. noctilio behaviour will involve a significant effort, there is a strong demand by policy makers for this kind of information. [ABSTRACT FROM AUTHOR]

Abstract: This study explores the economic feasibility of biomass for bioenergy from fast-growing hybrid poplar plantations established on agricultural lands in Canada. Using a spatial bio-economic afforestation feasibility model, we report break-even supply costs for two broad scenarios: first with only merchantable fibre having value and secondly, a “fibre-plus-carbon” scenario with carbon sequestered valued at $5t−1 CO2−e. Five levels of biomass processing capacities were examined in each scenario (90, 230, 450, 1500 and 3000ktonnes per year) using 241 settlements across Canada as potential locations for bioenergy facilities. Supply costs here include plantation establishment, maintenance, agricultural land rent, harvest and transportation to nearest community. In relative terms three geographic regions had the most promise: the northern Prairies, central Ontario and parts of the Maritime Provinces. Smaller-scale bioenergy projects were attractive for Eastern Canada (Ontario and the Maritimes). The Prairie Provinces were most attractive for larger facilities with break-even supply costs exceeding 5$GJ−1. Adding carbon incentives at 5$t−1 CO2 decreases average costs of delivered biomass by 0.57–1.38$GJ−1; however, these cost estimates are still above the current delivered costs of sub-bituminous coal. [Copyright &y& Elsevier]

We have developed a spatial cost–benefit afforestation model that includes the tracking of five carbon pools. In this application we represent three possible afforestation strategies that could be implemented in Canada using plantations of hybrid poplar, hardwoods, and softwoods with average expected growth rates of 12–14, 5–7, and 5–7 m3· ha–1·year–1 respectively. The model provides spatially explicit insights into the cost effectiveness of afforestation as a carbon sequestration tool. Here we develop an elasticity metric and experiment to assess model sensitivity and use the results to make recommendations about research priorities. The most important biological variables across all scenarios include site suitability, which is related to refining the spatial estimates of potential yields, biomass to carbon ratios, and wood density. The most important economic variables include refinement and lowering of establishment costs and agricultural opportunity costs. Parameters that have a low impact on the break-even carbon price, suggesting refinements in knowledge in these areas would be relatively less beneficial, include decay rates for forest products, stand senescence age (the age when stand mortality reaches its maximum), bioenergy and pulpwood prices, and mean residual time for leaf litter. Less importance was also placed on the proportions of forest products in the total harvest and refining a fossil fuel substitution coefficient. [ABSTRACT FROM AUTHOR]

Afforestation is one of several possible mechanisms available to sequester carbon and help reduce greenhouse gas concentrations. We have developed a spatial Monte Carlo-based simulation model, Canadian Forest Service—Afforestation Feasibility Model (CFS-AFM) to help assess the financial attractiveness of afforestation as a means of carbon storage in Canada. The model tracks five carbon pools and simulates costs and benefits of plantation investments. In this paper we simulate three afforestation scenarios that could be used in Canada; plantations using hybrid poplar, hardwoods, and softwoods with average growth rates of 14 and 6–7 m3/ha/year, respectively. The attractiveness of afforestation is driven by regional cost and plantation productivity variation and carbon price expectations. The results indicate that afforestation would be an attractive investment in many areas of the country at carbon prices of $10 per metric ton of CO2 or higher. However, with a zero carbon price, very little afforestation would be financially viable. Thus, with low carbon price expectations, other co-benefits may be required to make afforestation more attractive to Canadian investors. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Invasive pests, such as emerald ash borer or Asian longhorn beetle, have been responsible for unprecedented ecological and economic damage in eastern North America. These and other wood-boring invasive insects can spread to new areas through human transport of untreated firewood. Behaviour, such as transport of firewood, is affected not only by immediate material benefits and costs, but also by social forces. Potential approaches to reduce the spread of wood-boring pests through firewood include raising awareness of the problem and increasing the social costs of the damages incurred by transporting firewood. In order to evaluate the efficacy of these measures, we create a coupled social-ecological model of firewood transport, pest spread, and social dynamics, on a geographical network of camper travel between recreational destinations. We also evaluate interventions aimed to slow the spread of invasive pests with untreated firewood, such as inspections at checkpoints to stop the movement of transported firewood and quarantine of high-risk locations. We find that public information and awareness programs can be effective only if the rate of spread of the pest between and within forested areas is slow. Direct intervention via inspections at checkpoints can only be successful if a high proportion of the infested firewood is intercepted. Patch quarantine is only effective if sufficiently many locations can be included in the quarantine and if the quarantine begins early. Our results indicate that the current, relatively low levels of public outreach activities and lack of adequate funding are likely to render inspections, quarantine and public outreach efforts ineffective. [ABSTRACT FROM AUTHOR]

Land use change models based on historical behavior have proven useful in predicting and understanding determinants of change. Such approaches are not possible where land use change data are absent. In this paper, we develop a normative spatial model that considers option values associated with land conversion between agriculture and forestry and their differing time scales. The model is applied in a case study regarding the potential for a cellulosic biofuel industry in Alberta. Results indicate the importance of future patterns of prices in influencing decisions to switch from agriculture to bioenergy production, and suggest that cellulosic plantations are not likely to prevail over agricultural land uses. Les modèles de changement d'affectation des terres basés sur les comportements historiques se sont avérés utiles pour la prédiction et la compréhension des facteurs de changements. Ces approches sont impossibles là où les données concernant les changements d'affectation des terres sont absentes. Cet article présente un modèle normatif spatial qui tient compte des valeurs d'option associées à la conversion des terres agricoles en terres forestières et à leurs différentes échelles de temps. L'application du modèle se fait dans une étude de cas au sujet du potentiel pour une industrie du biocarburant cellulosique en Alberta. Les résultats montrent l'importance de l'influence des futures structures de prix sur le choix de passer de l'agriculture à la production de bioénergie, et suggèrent que les plantations cellulosiques ne l'emporteront pas sur les affectations agricoles des terres. [ABSTRACT FROM AUTHOR]

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. [Display omitted] • The model generates solutions for multiple sites with different management objectives. • Users can select a budget, number of species to plant, and ecosystem functions to prioritize. • The model selects the species that are the most cost-effective to meet management goals. • Users can explore solutions that vary in terms of species composition and ecosystem function. • The model was used to create an interactive planning tool to help design restoration programs. [ABSTRACT FROM AUTHOR]

Graph: Fig 4 Efficacy of social incentives on infestation after time T.Inset graph shows an example of cross-section along the line f = 0.11 The influence of infestation on transport strategy, f, can hinder the intervention by public outreach, in the long-term (after approximately 20 years). In Fig 4 the inset plot is missing. [Extracted from the article]

The article discusses a study on the estimates of the potential cost of emerald ash borer or Agrilus planipennis Faimaire, in Canadian urban areas. The areas were identified through a digital version of Canada's urban areas cartographic boundary file. As an additional focus, probable effects to backyard trees were included. The types of costs that were integrated into the study are removal costs, replacement costs, treatment costs, and community overhead costs.

Invasive species pose significant threats to forest ecosystems. Early intervention strategies are the most cost-effective means to control biological invasions, but are reliant on robust biosurveillance. State-of-the-art genomic approaches can provide an unprecedented opportunity to access detailed information on the invasion process and adaptive potential of invasive insects that pose an immediate threat to forests environments. Genomics can improve diagnostics of the invader and identify its route of invasion by determining the source population(s), assess its probability of establishment and patterns of spread, as well as provide evidence of adaptation. Applied biosurveillance efforts by plant health regulatory agencies will benefit substantially from the detailed insights that genomic data bring to our understanding of biological invasions. [ABSTRACT FROM AUTHOR]

Early intervention, effective management, and regulations are essential to mitigate the potential negative impacts of invasive forest insects. Biosurveillance provides the necessary knowledge to inform management, and regulatory practices. Genomic approaches can contribute valuable information to this process. Unfortunately, adoption and incorporation of genomic tools into biosurveillance frameworks is not straightforward. To realize the full potential of genomic knowledge, researchers must work together with end users to ensure full  adoption, standardization, validation, and interpretation of genomic results. [ABSTRACT FROM AUTHOR]

More than 1180 non-native species, mostly of Palaearctic origin, have been recorded from the boreal zone of Canada, with the highest diversity on the island of Newfoundland and in the southern boreal zone of Ontario and Quebec. The non-native biota of the boreal zone (and of Canada in general) is poorly known in terms of species composition and distribution. A large proportion of species are associated with disturbed anthropogenic habitats such as urban areas, agricultural landscapes, transportation and communication corridors, and industrial developments. Natural habitats in the boreal zone have a high degree of resistance to invasion compared with those of other Canadian zones, likely owing to harsh climates, low light levels, poor soil nutrient availability, low soil pH, low productivity, and dense covering of the ground by plants, especially bryophytes. Of the relatively few non-native species that have successfully colonized the boreal zone, many decline greatly in abundance after a few years, suggesting biotic resilience. To date the boreal zone has shown the least resistance and resilience to large vertebrates (moose and white-tailed deer) translocated to islands, diseases of vertebrates, and earthworms. In general, the ecological impacts of non-native species on the boreal zone have been poorly studied, and there are few examples where such impacts are evident. Likewise, there has been little attempt to quantify the economic impacts of non-native species in either the boreal zone or in Canada as a whole. In the few cases where management measures have been implemented for highly destructive non-native species, results have been somewhat successful, especially where classical biological control measures have been implemented against insects on trees. Chemical and mechanical management measures have had only limited success in localized situations. Management resources are most effectively applied to reducing the risk of introduction. The risk to the boreal zone posed by future new non-native species is increasing with the warming climate and the fast and direct transport of goods into the boreal zone from points of origin. Five recommendations are provided to address recognized gaps concerning non-native species. [ABSTRACT FROM AUTHOR]

Agriculture has the potential to supply considerable amounts of biomass for renewable energy production from dedicated energy crops as well as from crop residues of existing production. Bioenergy production can contribute to the reduction of greenhouse gas (GHG) emissions by using ethanol and biodiesel to displace petroleum-based fuels and through direct burning of biomass to offset coal use for generating electricity. We used the Canadian Economic and Emissions Model for Agriculture to estimate the potential for renewable energy production from biomass, the impacts on agricultural production, land use change and greenhouse gas emissions. We explored two scenarios: the first considers a combination of market incentives and policy mandates (crude oil price of $120 bbl -1 ; carbon offset price of $50 Mg -1 CO 2 equivalent and policy targets of a substitution of 20% of gasoline by biomass-based ethanol; 8% of petroleum diesel by biodiesel and 20% of coal-based electricity by direct biomass combustion), and a second scenario considers only carbon offset market incentives priced at $50 Mg -1 CO 2 equivalent. The results show that under the combination of market incentives and policy mandates scenario, the production of biomass-based ethanol and electricity increases considerably and could potentially cause substantial changes in land use practices. Overall, agriculture has considerable potential to generate biomass for energy and a significant potential for GHG emission reductions, however the proportional mix of policy and market incentives would have a large impact on the type of bioenergy produced. [ABSTRACT FROM AUTHOR]

Abstract: Short rotation woody crops (SRWC) have not been widely adopted as a viable feedstock for bioenergy production. We discuss three major information needs for R&D Managers improving adoption prospects for SRWC: (1) Understand how R&D affects the economics of SRWC – particularly “unit costs” of production; (2) Prices and trends for energy and environmental improvement and how these compare to SRWC costs; (3) Integrated biological and economic models. To enhance adoption prospects for SRWC R&D Managers should seek to lower unit costs to make these types of plantations more competitive with other energy alternatives. If non-market values are used as an argument to justify SRWC R&D investments managers still need to address adoption impediments. Even if non-market values are significant, adoption is required for society to realize benefits. We also argue that bioeconomic models can help identify needs, opportunities and challenges and illustrate some of these principles with an empirical example from Canada. [Copyright &y& Elsevier]

Aim AquaticHealth.net is an open-source aquatic biosecurity intelligence gathering and analysis application. The system collects information in much the same way as other similar systems (e.g. HealthMap, Bio Caster). However, the information collected undergoes minimal automated analysis, and analysis is largely left to Aquatic Health.net's users. The result is an automated system of intelligence gathering, combined with a manual system of intelligence analysis. This approach relies on a large number of users, and so Aquatic Health.net relies on an open-intelligence analysis method: any user can publish their own analyses for all to see and analyse further. By combining automated data collection and human analysis, Aquatic Health.net will provide fast and accurate forecasts, accompanied with nuanced explanations. These methods can be applied to other areas of biosecurity and disease surveillance. Location Canberra, Australia; College Park, Maryland, USA; Melbourne, Australia. Methods Automated: Aquatic Health.net performs hourly scans of an array of RSS feeds, blogs, social networks and news sites. It analyses this information and removes redundancies and applies taxonomy and geospatial tags. The information is then pushed to the Daily Scan, where users then analyse it further. Manual: Users assess the information for inaccuracies and its importance. They decide whether an article should be a disease alert, which is emailed to all users. Users can change tags, edit reports, add commentary, apply rankings, change search terms and summarize issues in the Emerging Issues blog (formerly a wiki). Results Aquatic Health.net publishes seven daily reports and 2 weekly disease alerts (on average). Ninety per cent of CEFAS's (www.cefas.defra.gov.uk) Emerging Disease Updates cite Aquatic Health.net. The Australian Sub- Committee for Aquatic Animal Health ( SCAAH) uses the system to compile quarterly reports. The Australian Department of Agriculture, Fisheries and Forestry ( DAFF) uses Aquatic Health.net to make forecasts-for example, used aquaculture equipment is a high-risk pathway for Os HV. Aquatic Health.net's users forecasted an increase in emerging marine finfish disease outbreaks in Southeast Asia and are actively watching this issue. Main conclusions Aquatic Health.net's open-intelligence approach has proven to be an effective and flexible biosecurity forecasting method. [ABSTRACT FROM AUTHOR]

Aim Decision-making for conservation management often involves evaluating risks in the face of environmental uncertainty. Models support decision-making by (1) synthesizing available knowledge in a systematic, rational and transparent way and (2) providing a platform for exploring and resolving uncertainty about the consequences of management decisions. Despite their benefits, models are still not used in many conservation decision-making contexts. In this article, we provide evidence of common objections to the use of models in environmental decision-making. In response, we present a series of practical solutions for modellers to help improve the effectiveness and relevance of their work in conservation decision-making. Location Global review. Methods We reviewed scientific and grey literature for evidence of common objections to the use of models in conservation decision-making. We present a set of practical solutions based on theory, empirical evidence and best-practice examples to help modellers substantively address these objections. Results We recommend using a structured decision-making framework to guide good modelling practice in decision-making and highlight a variety of modelling techniques that can be used to support the process. We emphasize the importance of participatory decision-making to improve the knowledge-base and social acceptance of decisions and to facilitate better conservation outcomes. Improving communication and building trust are key to successfully engaging participants, and we suggest some practical solutions to help modellers develop these skills. Main conclusions If implemented, we believe these practical solutions could help broaden the use of models, forging deeper and more appropriate linkages between science and management for the improvement of conservation decision-making. [ABSTRACT FROM AUTHOR]

Aim Biosecurity responses to incursions aim to achieve pest- or disease-free status as quickly as possible. One of the critical initial response activities involves tracing known movements (trace events) to and from an infected or infested property ( IP) that could spread the pest or pathogen. During an incursion response, managers allocate surveillance resources to follow up trace events in order of priority. Prioritizing trace events is difficult and typically subjective. We present a simulation model where several dispersal mechanisms spread a pest between areas. We use model outputs to test different search strategies, using citrus canker (caused by Xanthomonas citri) as a case study. Model scenarios are based on an outbreak of citrus canker that occurred in Queensland in 2004. Location Australia. Methods Model parameters were extracted from published scientific reports and elicited from experts. We used model outputs to assess three search strategies to determine how best to monitor citrus canker spread. Parameters governing disease detectability and host susceptibility were varied in a sensitivity analysis. Results In all simulation scenarios, the 'adaptive radius' rule performed best, whereby a circular search area was placed around the IP where the disease outbreak was first detected, with a radius proportional to the estimated number of months the property was infected. Importantly, none of the search rules tested detected all IPs without searching all areas with susceptible hosts in the region. Main conclusions We identify a simple rule of thumb for searching during a citrus canker outbreak that is robust to uncertainty. We cannot generalize the results of this study for tracing other pests or pathogens. The model has created a framework that may be used to explore other contexts and disease dynamics, leading perhaps to more general rules for disease outbreak management. [ABSTRACT FROM AUTHOR]

Aim We aim to explore the capacity of MCDA methods to successfully capture social impacts and integrate stakeholders' participation into environmental decision applications. We follow a theoretical framework that deconstructs the concept of social impact into two components: human impacts and social change processes. Location Global. Methods We systematically reviewed the literature on MCDA in the Web of Science ( ISI) database, finding 119 papers that meet our search criteria. For each paper, we identified the social change processes or human impacts objectives, along with the attributes that measured them. We also recorded the degree of stakeholder participation in each phase of the MCDA stages. Results We found that MCDA practitioners have increasingly integrated social concerns in the analysis of environmental problems, estimating the potential impacts, and developing participative procedures for stakeholders. We identified 252 objectives that represent human impacts or social change processes. Constructed attributes were the most commonly employed (56%), although natural (20%) and proxy (24%) attributes were also relevant. Estimating human impacts or social change processes can involve public participation, but is not a requirement for MCDA: 42% of papers ( n = 50) include stakeholder engagement in one or more stages of the decision-making process. We found that stakeholders engage differently across case studies, demonstrating that this process is neither simple nor homogenous. Main conclusions Our review suggests that MCDA methods are appropriate techniques to integrate a wide range of social objectives and stakeholder engagement, supporting well informed and democratic decisions. [ABSTRACT FROM AUTHOR]