A bi-level model for state and county aquatic invasive species prevention decisions.

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.

AIS explorer: Prioritization for watercraft inspections-A decision-support tool for aquatic invasive species management.

Invasions of aquatic invasive species have caused significant economic and ecological damage to global aquatic ecosystems. Once an invasive population has established in a new habitat, eradication can be financially and logistically impossible, motivating management strategies to rely heavily upon prevention measures to reduce the introduction and spread. To be productive, on-the-ground management of aquatic invasive species requires effective decision-making surrounding the allocation of limited resources. Watercraft inspections play an important role in managing aquatic invasive species by preventing the overland transport of invasive species between waterbodies and providing education to boaters. In this study, we developed and tested an interactive web-based decision-support tool, AIS Explorer: Prioritization for Watercraft Inspections, to guide AIS managers in developing efficient watercraft inspection plans. The decision-support tool is informed by a network-based algorithm that maximized the number of inspected watercraft that move from AIS infested to uninfested lakes within and between counties in Minnesota, USA. It was iteratively built with stakeholder feedback, including consultations with county managers, beta-testing of the web-based application, and workshops to educate and train end-users. The co-development and implementation of data-driven decision support tools demonstrate how interdisciplinary methods can be used to connect science and management to support decision-making. The AIS Explorer: Prioritization for Watercraft Inspections application makes optimized research outputs accessible in multiple dynamic forms that maintain pace with discovery of new infestations and local needs. In addition, the decision support tool has supported improved and closer communication between AIS managers and researchers on this topic.

Optimal invasive species surveillance in the real world: practical advances from research.

When alien species make incursions into novel environments, early detection through surveillance is critical to minimizing their impacts and preserving the possibility of timely eradication. However, incipient populations can be difficult to detect, and usually, there are limited resources for surveillance or other response activities. Modern optimization techniques enable surveillance planning that accounts for the biology and expected behavior of an invasive species while exploring multiple scenarios to identify the most cost-effective options. Nevertheless, most optimization models omit some real-world limitations faced by practitioners during multi-day surveillance campaigns, such as daily working time constraints, the time and cost to access survey sites and personnel work schedules. Consequently, surveillance managers must rely on their own judgments to handle these logistical details, and default to their experience during implementation. This is sensible, but their decisions may fail to address all relevant factors and may not be cost-effective. A better planning strategy is to determine optimal routing to survey sites while accounting for common daily logistical constraints. Adding site access and other logistical constraints imposes restrictions on the scope and extent of the surveillance effort, yielding costlier but more realistic expectations of the surveillance outcomes than in a theoretical planning case.

Managing biological invasions in urban environments with the acceptance sampling approach.

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.

Optimal Inspection of Imports to Prevent Invasive Pest Introduction.

The United States imports more than 1 billion live plants annually-an important and growing pathway for introduction of damaging nonnative invertebrates and pathogens. Inspection of imports is one safeguard for reducing pest introductions, but capacity constraints limit inspection effort. We develop an optimal sampling strategy to minimize the costs of pest introductions from trade by posing inspection as an acceptance sampling problem that incorporates key features of the decision context, including (i) simultaneous inspection of many heterogeneous lots, (ii) a lot-specific sampling effort, (iii) a budget constraint that limits total inspection effort, (iv) inspection error, and (v) an objective of minimizing cost from accepted defective units. We derive a formula for expected number of accepted infested units (expected slippage) given lot size, sample size, infestation rate, and detection rate, and we formulate and analyze the inspector's optimization problem of allocating a sampling budget among incoming lots to minimize the cost of slippage. We conduct an empirical analysis of live plant inspection, including estimation of plant infestation rates from historical data, and find that inspections optimally target the largest lots with the highest plant infestation rates, leaving some lots unsampled. We also consider that USDA-APHIS, which administers inspections, may want to continue inspecting all lots at a baseline level; we find that allocating any additional capacity, beyond a comprehensive baseline inspection, to the largest lots with the highest infestation rates allows inspectors to meet the dual goals of minimizing the costs of slippage and maintaining baseline sampling without substantial compromise.

A safety rule approach to surveillance and eradication of biological invasions.

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.

Estimating the economic value of cultural ecosystem services in an urbanizing area using hedonic pricing.

A need exists to increase both knowledge and recognition of the values associated with ecosystem services and amenities. This article explores the use of hedonic pricing as a tool for eliciting these values. We take a case study approach, valuing several services provided by ecosystems, namely aesthetic quality (views), access to outdoor recreation, and the benefits provided by tree cover in Dakota County, Minnesota, USA. Our results indicate that these services are valued by local residents and that hedonic pricing can be used to elicit at least a portion of this value. We find that many aspects of the aesthetic environment significantly impact home sale prices. Total view area as well as the areas of some land-cover types (water and lawn) in views positively influenced home sale prices while views of impervious surfaces generally negatively influenced home sale price. Access to outdoor recreation areas significantly and positively influenced home sale prices as did tree cover in the neighborhood surrounding a home. These results illustrate the ability of hedonic pricing to identify partial values for ecosystem services and amenities in a manner that is highly relevant to local and regional planning. These values could be used to increase policy-maker and public awareness of ecosystem services and could improve their consideration in planning and policy decisions.

Optimal surveillance and eradication of invasive species in heterogeneous landscapes.

Cost-effective surveillance strategies are needed for efficient responses to biological invasions and must account for the trade-offs between surveillance effort and management costs. Less surveillance may allow greater population growth and spread prior to detection, thereby increasing the costs of damages and control. In addition, surveillance strategies are usually applied in environments under continual invasion pressure where the number, size and location of established populations are unknown prior to detection. We develop a novel modeling framework that accounts for these features of the decision and invasion environment and determines the long term sampling effort that minimises the total expected costs of new invasions. The optimal solution depends on population establishment and growth rates, sample sensitivity, and sample, eradication, and damage costs. We demonstrate how to optimise surveillance systems under budgetary constraints and find that accounting for spatial heterogeneity in sampling costs and establishment rates can greatly reduce management costs.

Economic impacts of non-native forest insects in the continental United States.

Reliable estimates of the impacts and costs of biological invasions are critical to developing credible management, trade and regulatory policies. Worldwide, forests and urban trees provide important ecosystem services as well as economic and social benefits, but are threatened by non-native insects. More than 450 non-native forest insects are established in the United States but estimates of broad-scale economic impacts associated with these species are largely unavailable. We developed a novel modeling approach that maximizes the use of available data, accounts for multiple sources of uncertainty, and provides cost estimates for three major feeding guilds of non-native forest insects. For each guild, we calculated the economic damages for five cost categories and we estimated the probability of future introductions of damaging pests. We found that costs are largely borne by homeowners and municipal governments. Wood- and phloem-boring insects are anticipated to cause the largest economic impacts by annually inducing nearly $1.7 billion in local government expenditures and approximately $830 million in lost residential property values. Given observations of new species, there is a 32% chance that another highly destructive borer species will invade the U.S. in the next 10 years. Our damage estimates provide a crucial but previously missing component of cost-benefit analyses to evaluate policies and management options intended to reduce species introductions. The modeling approach we developed is highly flexible and could be similarly employed to estimate damages in other countries or natural resource sectors.

The influence of satellite populations of emerald ash borer on projected economic costs in U.S. communities, 2010-2020.

The invasion spread of the emerald ash borer (Agrilus planipennis Fairmaire) (Coleoptera: Buprestidae) is characterized by the formation of satellite populations that expand and coalesce with the continuously invading population front. As of January 2010, satellite infestations have been detected in 13 states and two Canadian provinces. Understanding how newly established satellite populations may affect economic costs can help program managers to justify and design prevention and control strategies. We estimate the economic costs caused by EAB for the 10-yr period from 2010 to 2020 for scenarios of fewer EAB satellite populations than those found from 2005 to 2010 and slower expansion of satellite populations found in 2009. We measure the projected discounted cost of treatment, removal, and replacement of ash trees (Fraxinus spp.) growing in managed landscapes in U.S. communities. Estimated costs for the base scenario with the full complement of satellites in 2005-2010 and no program to mitigate spread is $12.5 billion. Fewer EAB satellites from 2005 to 2010 delay economic costs of $1.0 to 7.4 billion. Slower expansion of 2009 satellite populations delays economic costs of $0.1 to 0.7 billion. Satellite populations that are both distant from the core EAB infestation and close to large urban areas caused more economic costs in our simulations than did other satellites. Our estimates of delayed economic costs suggest that spending on activities that prevent establishment of new satellite EAB populations or slow expansion of existing populations can be cost-effective and that continued research on the cost and effectiveness of prevention and control activities is warranted.

Assessing the cost of an invasive forest pathogen: a case study with oak wilt.

Economic assessment of damage caused by invasive alien species provides useful information to consider when determining whether management programs should be established, modified, or discontinued. We estimate the baseline economic damage from an invasive alien pathogen, Ceratocystis fagacearum, a fungus that causes oak wilt, which is a significant disease of oaks (Quercus spp.) in the central United States. We focus on Anoka County, Minnesota, a 1,156 km(2) mostly urban county in the Minneapolis-Saint Paul metropolitan region. We develop a landscape-level model of oak wilt spread that accounts for underground and overland pathogen transmission. We predict the economic damage of tree mortality from oak wilt spread in the absence of management during the period 2007-2016. Our metric of economic damage is removal cost, which is one component of the total economic loss from tree mortality. We estimate that Anoka County has 5.92 million oak trees and 885 active oak wilt pockets covering 5.47 km(2) in 2007. The likelihood that landowners remove infected oaks varies by land use and ranges from 86% on developed land to 57% on forest land. Over the next decade, depending on the rates of oak wilt pocket establishment and expansion, 76-266 thousand trees will be infected with discounted removal cost of $18-60 million. Although our predictions of removal costs are substantial, they are lower bounds on the total economic loss from tree mortality because we do not estimate economic losses from reduced services and increased hazards. Our predictions suggest that there are significant economic benefits, in terms of damage reduction, from preventing new pocket establishment or slowing the radial growth of existing pockets.

Predicting the economic costs and property value losses attributed to sudden oak death damage in California (2010-2020).

Phytophthora ramorum, cause of sudden oak death, is a quarantined, non-native, invasive forest pathogen resulting in substantial mortality in coastal live oak (Quercus agrifolia) and several other related tree species on the Pacific Coast of the United States. We estimate the discounted cost of oak treatment, removal, and replacement on developed land in California communities using simulations of P. ramorum spread and infection risk over the next decade (2010-2020). An estimated 734 thousand oak trees occur on developed land in communities in the analysis area. The simulations predict an expanding sudden oak death (SOD) infestation that will likely encompass most of northwestern California and warrant treatment, removal, and replacement of more than 10 thousand oak trees with discounted cost of $7.5 million. In addition, we estimate the discounted property losses to single family homes of $135 million. Expanding the land base to include developed land outside as well as inside communities doubles the estimates of the number of oak trees killed and the associated costs and losses. The predicted costs and property value losses are substantial, but many of the damages in urban areas (e.g. potential losses from increased fire and safety risks of the dead trees and the loss of ecosystem service values) are not included.

Habitat acquisition strategies for grassland birds in an urbanizing landscape.

Habitat protection for grassland birds is an important component of open space land acquisition in suburban Chicago. We use optimization decision models to develop recommendations for land protection and analyze tradeoffs between alternative goals. One goal is to acquire (and restore if necessary) as much grassland habitat as possible for a given budget. Because a viable habitat for grassland birds consists of a relatively large core area with additional parcels of grassland habitat nearby, the second goal is to minimize total pairwise distance between newly protected parcels and large existing reserves. We also use the concept of an effective grassland habitat area, which considers influences that neighboring land covers have on grassland habitat suitability. We analyze how the parcels selected for protection change as total protected effective area is traded off against total distance. As area is weighted more heavily, the selected parcels are scattered and unconnected. As total distance is weighted more heavily, the selected parcels coalesce around core reserves but protect less area. The differences in selected parcels as we change the objective function weights are caused by the differences in price per unit of effective habitat area across parcels. Parcels located in close proximity to the existing cores have relatively high prices per hectare of effective grassland area as a consequence of high restoration costs and adverse influences from roads, urban areas and/or forestland. As a result, these parcels have lower priority for selection when the area objective is weighted more heavily for a given budget.

Conservation and control strategies for the wolf (Canis lupus) in western Europe based on demographic models.

Securing the long-term acceptance of large carnivores such as the wolf (Canis lupus) in Europe and North America raises a difficult challenge to conservation biologists: planning removals to reduce depredations on livestock while ensuring population viability. We use stochastic-stage-structured population models to investigate wolf population dynamics and to assess alternative management strategies. Among the various management strategies advocated by agencies, zoning that involves eliminating wolves outside a restricted area should be designed with caution, because probabilities of extinction are extremely sensitive to the maximum number of packs that a zone can support and to slight changes in stage specific survival probabilities. In a zoned population, viability is enhanced more by decreasing mortality rates in all classes than by increasing wolf zone size. An alternative to zoning is adaptive management, where there is no limit on pack number but population control can be operated whenever some predefined demographic conditions are met. It turns out that an adaptive management strategy that removes a moderate percentage (10%) of the population following each year of more than 5% of total population growth would provide visible actions addressing public concerns while keeping extinction probability low.