Novel host unmasks heritable variation in plant preference within an insect population.

Introductions of novel plant species can disturb the historical resource environment of herbivorous insects, resulting in strong selection to either adopt or exclude the novel host. However, an adaptive response depends on heritable genetic variation for preference or performance within the targeted herbivore population, and it is unclear how heritability of host-use preference may differ between novel and historical hosts. Pieris macdunnoughii butterflies in the Rocky Mountains lay eggs on the nonnative mustard Thlaspi arvense, which is lethal to their offspring. Heritability analyses revealed considerable sex-linked additive genetic variation in host preference within a population of this butterfly. This was contrary to general predictions about the genetic basis of preference variation, which are hypothesized to be sex linked between populations but autosomal within populations. Evidence of sex linkage disappeared when butterflies were tested on methanol-based chemical extracts, suggesting these chemicals in isolation may not be the primary driver of female choice among available host plants. Although unexpected, evidence for within-population sex-linked genetic variation in preference for T. arvense over native hosts indicates that persistent maladaptive oviposition on this lethal plant must be maintained by alternative evolutionary dynamics such as migration- or drift-selection balance or pleiotropic constraints.

Optimizing management of invasions in an uncertain world using dynamic spatial models.

Dispersal drives invasion dynamics of nonnative species and pathogens. Applying knowledge of dispersal to optimize the management of invasions can mean the difference between a failed and a successful control program and dramatically improve the return on investment of control efforts. A common approach to identifying optimal management solutions for invasions is to optimize dynamic spatial models that incorporate dispersal. Optimizing these spatial models can be very challenging because the interaction of time, space, and uncertainty rapidly amplifies the number of dimensions being considered. Addressing such problems requires advances in and the integration of techniques from multiple fields, including ecology, decision analysis, bioeconomics, natural resource management, and optimization. By synthesizing recent advances from these diverse fields, we provide a workflow for applying ecological theory to advance optimal management science and highlight priorities for optimizing the control of invasions. One of the striking gaps we identify is the extremely limited consideration of dispersal uncertainty in optimal management frameworks, even though dispersal estimates are highly uncertain and greatly influence invasion outcomes. In addition, optimization frameworks rarely consider multiple types of uncertainty (we describe five major types) and their interrelationships. Thus, feedbacks from management or other sources that could magnify uncertainty in dispersal are rarely considered. Incorporating uncertainty is crucial for improving transparency in decision risks and identifying optimal management strategies. We discuss gaps and solutions to the challenges of optimization using dynamic spatial models to increase the practical application of these important tools and improve the consistency and robustness of management recommendations for invasions.

Private land conservation decision-making: An integrative social science model.

Owners and managers of private lands make decisions that have implications well beyond the boundaries of their land, influencing species conservation, water quality, wildfire risk, and other environmental outcomes with important societal and ecological consequences. Understanding how these decisions are made is key for informing interventions to support better outcomes. However, explanations of the drivers of decision making are often siloed in social science disciplines that differ in focus, theory, methodology, and terminology, hindering holistic understanding. To address these challenges, we propose a conceptual model of private land conservation decision-making that integrates theoretical perspectives from three dominant disciplines: economics, sociology, and psychology. The model highlights how heterogeneity in behavior across decision-makers is driven by interactions between the decision context, attributes of potential conservation behaviors, and attributes of the decision-maker. These differences in both individual attributes and context shape decision-makers' constraints and the potential and perceived consequences of a behavior. The model also captures how perceived consequences are evaluated and weighted through a decision-making process that may range from systematic to heuristic, ultimately resulting in selection of a behavior. Outcomes of private land behaviors across the landscape feed back to alter the socio-environmental conditions that shape future decisions. The conceptual model is designed to facilitate better communication, collaboration, and integration across disciplines and points to methodological innovations that can expand understanding of private land decision-making. The model also can be used to illuminate how behavior change interventions (e.g., policies, regulations, technical assistance) could be designed to target different drivers to encourage environmentally and socially beneficial behaviors on private lands.

Approaches for estimating benefits and costs of interventions in plant biosecurity across invasion phases.

Nonnative plant pests cause billions of dollars in damages. It is critical to prevent or reduce these losses by intervening at various stages of the invasion process, including pathway risk management (to prevent pest arrival), surveillance and eradication (to counter establishment), and management of established pests (to limit damages). Quantifying benefits and costs of these interventions is important to justify and prioritize investments and to inform biosecurity policy. However, approaches for these estimations differ in (1) the assumed relationship between supply, demand, and prices, and (2) the ability to assess different types of direct and indirect costs at invasion stages, for a given arrival or establishment probability. Here we review economic approaches available to estimate benefits and costs of biosecurity interventions to inform the appropriate selection of approaches. In doing so, we complement previous studies and reviews on estimates of damages from invasive species by considering the influence of economic and methodological assumptions. Cost accounting is suitable for rapid decisions, specific impacts, and simple methodological assumptions but fails to account for feedbacks, such as market adjustments, and may overestimate long-term economic impacts. Partial equilibrium models consider changes in consumer and producer surplus due to pest impacts or interventions and can account for feedbacks in affected sectors but require specialized economic models, comprehensive data sets, and estimates of commodity supply and demand curves. More intensive computable general equilibrium models can account for feedbacks across entire economies, including capital and labor, and linkages among these. The two major considerations in choosing an approach are (1) the goals of the analysis (e.g., consideration of a single pest or intervention with a limited range of impacts vs. multiple interventions, pests or sectors), and (2) the resources available for analysis such as knowledge, budget and time.

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.

Eradication of Invading Insect Populations: From Concepts to Applications.

Eradication is the deliberate elimination of a species from an area. Given that international quarantine measures can never be 100% effective, surveillance for newly arrived populations of nonnative species coupled with their eradication represents an important strategy for excluding potentially damaging insect species. Historically, eradication efforts have not always been successful and have sometimes been met with public opposition. But new developments in our understanding of the dynamics of low-density populations, the availability of highly effective treatment tactics, and bioeconomic analyses of eradication strategies offer new opportunities for developing more effective surveillance and eradication programs. A key component that connects these new developments is the harnessing of Allee effects, which naturally promote localized species extinction. Here we review these developments and suggest how research might enhance eradication strategies.

A typology of time-scale mismatches and behavioral interventions to diagnose and solve conservation problems.

Ecological systems often operate on time scales significantly longer or shorter than the time scales typical of human decision making, which causes substantial difficulty for conservation and management in socioecological systems. For example, invasive species may move faster than humans can diagnose problems and initiate solutions, and climate systems may exhibit long-term inertia and short-term fluctuations that obscure learning about the efficacy of management efforts in many ecological systems. We adopted a management-decision framework that distinguishes decision makers within public institutions from individual actors within the social system, calls attention to the ways socioecological systems respond to decision makers' actions, and notes institutional learning that accrues from observing these responses. We used this framework, along with insights from bedeviling conservation problems, to create a typology that identifies problematic time-scale mismatches occurring between individual decision makers in public institutions and between individual actors in the social or ecological system. We also considered solutions that involve modifying human perception and behavior at the individual level as a means of resolving these problematic mismatches. The potential solutions are derived from the behavioral economics and psychology literature on temporal challenges in decision making, such as the human tendency to discount future outcomes at irrationally high rates. These solutions range from framing environmental decisions to enhance the salience of long-term consequences, to using structured decision processes that make time scales of actions and consequences more explicit, to structural solutions aimed at altering the consequences of short-sighted behavior to make it less appealing. Additional application of these tools and long-term evaluation measures that assess not just behavioral changes but also associated changes in ecological systems are needed.

Designing cost-efficient surveillance for early detection and control of multiple biological invaders.

Wood borers and bark beetles are among the most serious forest pests worldwide. Many such species have become successful invaders, often causing substantial, costly damages to forests. Here we design and evaluate the cost-efficiency of a trap-based surveillance program for early detection of wood borers and bark beetles at risk of establishing in New Zealand. Although costly, a surveillance program could lead to earlier detection of newly established forest pests, thereby increasing the likelihood of successful eradication and reducing control costs and damages from future invasions. We develop a mechanistic bioeconomic model that relates surveillance intensity (i.e., trap density) and invasion size to probabilities of detection and control. It captures the dynamics of invasive species establishment, spread, and damages to urban and plantation forests. We employ the model to design surveillance programs that provide the greatest net present benefits. Our findings suggest that implementing a surveillance trapping program for invasive wood borers and bark beetles would provide positive net benefits under all scenarios considered. The economically optimal trapping strategy calls for a very high investment in surveillance: about 10 000 traps in each year of the 30-year surveillance program, at a present value cost of US$54 million. This strategy provides a 39% reduction in costs compared with no surveillance, corresponding to an expected net present benefit of approximately US$300 million. Although surveillance may provide the greatest net benefits when implemented at relatively high levels, our findings also show that even low levels of surveillance are worthwhile: the economic benefits from surveillance more than offset the rising costs associated with increasing trapping density. Our results also show that the cost-efficiency of surveillance varies across target regions because of differences in pest introduction and damage accumulation rates across locales, with greater surveillance warranted in areas closer to at-risk, high-value resources and in areas that receive more imported goods that serve as an invasion pathway.

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.

Bioeconomic synergy between tactics for insect eradication in the presence of Allee effects.

Preventing the establishment of invading pest species can be beneficial with respect to averting future environmental and economic impacts and also in preventing the accumulation of control costs. Allee effects play an important role in the dynamics of newly established, low-density populations by driving small populations into self-extinction, making Allee effects critical in influencing outcomes of eradication efforts. We consider interactions between management tactics in the presence of Allee effects to determine cost-effective and time-efficient combinations to achieve eradication by developing a model that considers pesticide application, predator augmentation and mating disruption as control tactics, using the gypsy moth as a case study. Our findings indicate that given a range of constant expenditure levels, applying moderate levels of pesticides in conjunction with mating disruption increases the Allee threshold which simultaneously substantially decreases the time to eradication relative to either tactic alone. In contrast, increasing predation in conjunction with other tactics requires larger economic expenditures to achieve similar outcomes for the use of pesticide application or mating disruption alone. These results demonstrate the beneficial synergy that may arise from nonlinearities associated with the simultaneous application of multiple eradication tactics and offer new prospects for preventing the establishment of damaging non-native species.

Controlling established invaders: integrating economics and spread dynamics to determine optimal management.

We review studies that address economically optimal control of established invasive species. We describe three important components for determining optimal invasion management: invasion dynamics, costs of control efforts and a monetary measure of invasion damages. We find that a management objective that explicitly considers both costs and damages is most appropriate for determining economically optimal strategies, but also leads to large challenges due to uncertainty in components of the management problem. To address uncertainty, some studies have included stochasticity in their models; others have quantified the value of information or focused on decision-making with limited information. Our synthesis shows how invasion characteristics, such as costs, damages, pattern of spread and invasion and landscape size, affect optimal control strategies and goals in systematic ways. We find that even for simple questions, such as whether control should be applied at the centre of an invasion or to satellite patches, the answer depends on the details of a particular invasion. Future work should seek to better quantify key components of this problem, determine best management in the face of limited information, improve understanding of spatial aspects of invasion control and design approaches to improve the feasibility of achieving regional control goals.