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Economics of Invasive Species

Summary and Keywords

Introductions of non-native invasive species can harm ecosystems, heighten the risk of native species extinctions and population reductions, and lead to substantial economic damages on a worldwide scale. Increasingly, economists have made contributions that help other researchers, policymakers, and society better understand the economic implications of invasive species as well as the most economically efficient approaches for managing them. The complexity of invasive species management problems has pushed economists to ask novel economic questions and to develop new analytical approaches in order to address specific policy questions. There are three areas, in particular, where the economic analysis of invasive species management has led to significant innovations. First, there are substantial challenges to quantifying economic damages from invasive species for application in benefit−cost analysis. The challenges relate to defining the counterfactual state of an invaded ecosystem with and without management/policy and to the fact that, in a given ecosystem, estimates of economic damages are available for only a subset of the species and for only a subset of damages for any one species. Recent economic research has proposed innovative approaches to systematically dealing with these two issues in the context of invasive species that have implications for applied benefit−cost analysis more broadly. Second, unique among natural resource management problems, invasive species have the feature that their current and future extents are directly tied to a country’s participation in international trade. This feature has led to innovative research into the design of efficient measures to prevent or delay invasive species introductions along national borders, and into the trade-offs between these measures and the use of border controls as protectionist tools. The issues of optimal inspection policy and the use of nontariff barriers as a form of covert protectionism both have implications beyond invasive species management. Third, researchers have developed bioeconomic models that integrate economic and biological factors in order to analyze strategies to more cost-effectively reduce the damages caused by invasive species. These modeling efforts have dealt with issues related to temporal and spatial dynamics of the biological invasions, imperfect information regarding the extent of the invasion and the effectiveness of management, linkages between management applied at different stages of an invasion, and complications arising from ecosystems’ crossing over ecological thresholds due to invasions. In the face of increasingly rapid ecosystem change due to global climate change, increases in extreme weather, urban encroachment into wild lands, and other factors, many of these features of invasive species management problems are likely to become features of ecosystem management more broadly in the near future if they are not so already.

Keywords: invasive species, non-native species, invasive species economics, invasive species management, benefit−cost analysis, international trade, bioeconomic modeling

Introduction

Introductions of non-native invasive species can harm ecosystems, heighten the risk of native species extinctions and population reductions, and lead to substantial economic damages (Duraiappah, Naheem, Agardy, Ash, & Cooper, 2005; Guravitch & Padilla, 2004). Despite the magnitude of the threat from invasive species, however, relatively little economic analysis has been trained on this topic until recently. This article addresses three major topics in the economics of invasive species. First, invasive species impose substantial economic damages on human and natural systems and lead to mitigation expenditures by private citizens, firms, and governments. The article discusses the challenges to quantifying these economic damages for application in benefit−cost analysis. Second, the spread of invasive species in recent decades has been driven, in part, by the expansion of international trade. The article discusses the literature on linkages between international trade and invasive species with an eye toward the design of efficient measures to prevent or delay introductions of invasive species and the trade-offs between those measures and the use of border controls as protectionist tools. Third, advancements in bioeconomic modeling, which integrates economic and biological factors, can improve private and public decision makers’ abilities to more cost-effectively reduce the damages caused by invasive species. This article discusses the literature on bioeconomic modeling and the optimal management of invasive species with an eye toward how economists are striving to incorporate important elements of both social and natural systems into efforts to model and manage invasive species.

In this article, invasive species are defined as non-native or alien species whose introduction to an ecosystem causes, or is likely to cause, economic or environmental harm, including harm to human and animal health.1 This definition allows for the fact that many alien species are noninvasive because they either do not involve uncontrolled or unintended spread, cause negligible economic or environmental harm, or have economic or environmental benefits that outweigh any associated damages. Though some sources in the literature (e.g., Beck et al., 2008) consider non-endemic human and animal diseases as invasive species, this article does not discuss diseases aside from a few studies that address concepts relevant to invasive species more broadly.

Economists concerned with invasive species have drawn from the literature on diverse topics, including renewable resource management (fisheries, forestry, etc.), air and water pollution, and international trade and the environment. This article draws primarily on studies from economics and environmental science (e.g., ecology, weed science) that focus on invasive species and ignores studies that have methodological but not subject matter relevance. Further, the discussion in this article focuses on topics that are particularly significant to the economics of invasive species.

Development of the Topic Over Time

This section discusses how the three major topics in the economics of invasive species addressed in this article developed over time.

The Benefits and Costs of Invasive Species Management and Policy

Benefits and Costs: Introduction

Economics can play a critical role in the development of invasive species management strategies and regulatory policies by providing reliable estimates of the benefits (in terms of damages avoided) and costs of invasions. The scope and complexity of invasive species management problems, however, pose several challenges for benefit−cost analysis. This section addresses the literature on the benefits and costs of invasive species management in light of two of these challenges. First, credibly estimating the economic benefits of invasive species management or policy requires accurately defining the counterfactual states of the ecosystem (i.e., what the ecosystem would look like with and without the application of invasive species management or policy). Defining the counterfactual state of the ecosystem is a particular challenge for invasive species management problems because of the difficulty in defining (and modeling) what ecosystems will be invaded, when, and what will be the impacts of the invasion.

Second, it is almost inevitable that invasive species management or policy decisions will be made in the absence of complete information on economic benefits because it is often infeasible (and sometimes impossible) to quantify all of the relevant impacts of invasive species in monetary units (Branco, Videira, Branco, & Paiva, 2015) and because the large number of invasive species means that, in most cases, the benefits are estimated for only a fraction of the invasive species that affect a given ecosystem (Aukema et al., 2011). This endemic problem of missing information, if not addressed, will cause studies to systematically understate the economic damages from invasive species and can limit their utility in decision-making.

These two challenges to evaluating the benefits and costs of invasive species management or policy may not be unique to invasive species, but they are arguably more significant for invasive species than for other natural resource management problems. Additional challenges to benefit−cost analysis for invasive species that are broadly shared by all natural resource management problems include incorporating risk related to the timing, size, and damages from the invasion into the decision-making framework (see Keller, Lodge, & Finnoff, 2007; Leung et al., 2002), accounting for uncertainty (incomplete information) in the available data (see Aukema et al., 2011), and difficulties in estimating monetary damages for ecosystem services that are not traded in conventional markets (see Horsch & Lewis, 2009; Kovacs, Holmes, Englin, & Alexander, 2011; Provencher, Lewis, & Anderson, 2012).

There have been several previous review articles on the economics of invasive species that have touched on issues related to estimating benefits and costs of management or policy. These previous review articles have often been organized by the ecosystem (see Olson, 2006, for terrestrial ecosystems and Lovell, Stone, & Fernandez, 2006, for aquatic ecosystems) or ecosystem services (Pejchar & Mooney, 2009). In contrast, we focus on methodological challenges to performing benefit−cost analysis for all invasive species regardless of the ecosystem or ecosystem services affected. Further, previous review articles have chosen to distinguish between studies that analyze prevention versus control strategies and between ex ante (pre-invasion) versus ex post (post-invasion) evaluation perspectives (Born, Rauschmayer, & Bräuer, 2005). We choose not to organize the literature by management objective or evaluation perspective because the primary challenges to benefit−cost analysis are similar in all of these cases.

Estimating Benefits and Costs: Brief History

Studies valuing the economic impacts of invasive species first appeared in the 1980s (see Marbuah, Gren, & McKie, 2014). Many early studies valued the damages from invasive species in terms of the expenditures society (individuals, firms, regulatory agencies, etc.) was willing to undertake to avoid the damages. The rationale for this approach is that society would not devote resources to controlling invasive species unless the damages avoided were at least as great as the cost. Previous studies have employed a cost-based approach to assign damages from invasive mammal species (Redhead, Singleton, Myers, & Coman, 1991), invasive insects (Slater, Lewington, & Pratley, 1996), and wild rabbits (McKillop, Butt, Lill, Pepper, & Wilson, 1998). Perhaps more significantly, several national-scale assessments have based their estimates of invasive species impacts on studies that have employed cost-based approaches. This group includes national-scale assessments in Australia (Bomford & Hart, 2002; McLeod, 2004), Canada (Colautti, Bailey, van Overdijk, Amundsent, & MacIsaac, 2006), the United States (Pimentel, Lach, Zuniga, & Morrison, 2000; Pimentel, Zuniga, & Morrison, 2005), and Europe (Vila et al., 2009).

The cost-based approach has been roundly criticized in more recent years as environmental economists have trained more attention on the topic (see Born et al., 2005, and Holmes, Aukema, Von Holle, Liebhold, & Sills, 2009). Damage estimates from a cost-based approach can either understate damages (if, for example, there are significant external costs associated with species introductions or if regulatory agencies are budget constrained) or overstate damages (if, for example, control methods are ineffective, more cost-effective strategies are available, or if the individual, firm, or regulatory agency overestimates the potential damages from the invasive species and misallocates resources). Furthermore, estimates using cost-based approaches fail to account for uncertainty and often fall victim to double counting of costs.

The literature has moved away from cost-based studies toward studies that directly evaluate the market and nonmarket damages (the actual adverse impacts) from invasive species. Damage-based estimates are often based in economic theory and are generally viewed as more credible than cost-based estimates. Previous studies that have analyzed the damages of invasive species on market goods have considered production losses in forestry (Gren, Isacs, & Mattias, 2009), agriculture (Emmerson & McCulloch, 1994; Kehlenbeck & Krugener, 2014), and fisheries (Leung et al., 2002), as well as human health costs (Gren et al., 2009). Previous studies have estimated a diverse array of nonmarket damages from invasive species, including wildfire impacts (Taylor, Rollins, Kobayashi, & Tausch, 2013), tree death in residential neighborhoods (Kovacs et al., 2011), and lost and/or degraded recreational experiences (Zimmer, Boxall, & Adamowicz, 2012).

While cost-based studies do not require that the counterfactual state of the ecosystem with and without management/policy be explicitly defined, defining the counterfactual is of central importance to damage-based studies. Indeed, Born et al. (2005) argued that the failure to correctly specify the counterfactual renders estimates of the benefits of invasive species management or policy potentially meaningless. Studies of market damages have primarily focused on estimating industry supply curves in agriculture, forestry, fisheries, etc., with and without invasion (e.g., Emmerson & McCulloch, 1994; Kehlenbeck & Krugener, 2014). As discussed in the section “Current State of the Science,” the literature has only recently moved to applying modern nonmarket valuation techniques that explicitly define the counterfactual with and without management or policy to estimating invasive species damages.

An estimated 50,000 non-native species have been introduced into the United States (Pimentel et al., 2005). The large number of invasive species poses a challenge for economic analysis because, in general, benefits and costs are estimated for only a fraction of the invasive species that generate economic or environmental damages in a given ecosystem. Gren et al. (2009) claimed that economic data are available for only 1% to 2% of all invaders. Moreover, even for the species where benefits and costs of management actions have been estimated, estimates are typically available for only a subset of the relevant categories of damages. Excluding invasive species and categories of damages from an analysis because their economic impacts have not been quantified will bias the estimates of the benefits of management actions/policies downward and may substantively affect decision-support recommendations.

Missing information does not pose a challenge for cost-based studies because these studies do not attempt to distinguish between different categories of economic benefits and implicitly include as many species as are affected by the management action or policy whose costs are under consideration. National-scale assessments of the impact of invasive species—which often incorporate information from cost-based studies—attempt to provide as comprehensive a range of the economic impacts and species as possible (e.g., Branco et al., 2015; Colautti et al., 2006; Pimentel et al., 2005; van Wilgen et al., 2012). These studies, however, are typically performed to raise awareness of the economic significance of invasive species by assessing overall damages, so the challenge posed by missing information for decision-support is of lesser importance. Many damage-based studies focus on a narrow set of benefits (Kovacs et al., 2011) or affected species (Keller et al., 2007) in order to provide defensible estimates given available data. The narrow focus of many studies, while justified given their objectives, can limit their application in decision-support due to missing information. The section “Current State of the Science” describes an innovative approach to systematically dealing with the problem of missing information in economic evaluations of invasive species damages.

International Trade and Invasive Species

The link between international trade and invasive species introductions is well established (Costello, Springborn, McAusland, & Solow, 2007; Dalmazzone & Giaccaria, 2014; Essl et al., 2011). In some cases, new invasive species introductions are a result of intentional trade in products, such as horticultural goods, and in others the introduction is unintentional due to contamination of packing materials, shipping vessels, or tourists (Costello, Lawley, & McAusland, 2008). Indeed, among domestic natural resource management problems, an invasive species has the feature that its current and future extents are most directly tied to the home country’s participation in international commerce. Consistent with the historical link between international trade and establishment of invasive species, there is a long history of the use of import controls to prevent intentional and unintentional introductions of invasive species. Kreith and Golino (2003) described the evolution of early European and U.S. invasive species legislation intended to protect against entry of new pests and pathogens. Many of these import controls were introduced in the mid to late 1800s and typically took the form of bans on imported produce and quarantines applied to livestock.2

Significant interest in issues of international trade and invasive species emerged among economists beginning with the WTO (World Trade Organization) Agreement on the Application of Sanitary and Phytosanitary (SPS) Measures, which came into effect in January 1995 as a part of the 1994 WTO Agreement. SPS measures are the actions countries take to protect human, animal, or plant life from risks and damages due to the entry, establishment, and spread of pests, diseases, or disease-causing organisms (Roberts, 1998). The objective of the WTO SPS Agreement is to allow countries to protect against potential risks to human, animal, and plant life but not to use SPS measures as a form of disguised trade protectionism (Roberts, 1998).

The tension between protecting against risks due to damaging imports and the use of SPS measures as protectionist tools motivated much of the early research by economists into invasive species and international trade. Roberts and Orden (1995) described the criteria and procedures for establishing phytosanitary regulations (those relating to plant health) in the United States and described the potential for misuse of SPS measures due to regulatory capture of government agencies by domestic agricultural producer groups. Romano and Orden (1995) described the long-running dispute over nursery stock and ornamental plant imports, which are significant potential pathways for invasive species. They highlighted the role that interest group influence over regulatory decision makers played in delaying or preventing new regulations to allow nursery stock to enter the United States.

Consistent with the potential use of SPS measures as protectionist tools, several early studies examined the economic welfare consequences of border policies to protect against invasive pests. Orden and Romano (1996) provided evidence that the U.S. ban on avocado imports from Mexico was largely driven by regulatory capture of the policy process by U.S. avocado producers. Calvin and Krissoff (1998) presented evidence that Japanese SPS measures restricting U.S. apple exports are intended to protect Japanese domestic producers from import competition rather than to maximize social welfare. James and Anderson (1998) showed that removal of Australia’s ban on banana imports would increase net social welfare in Australia even in cases of very high potential infestation levels. In an analysis of the welfare implications of import restrictions to control invasive species, Peterson and Orden (2008) assessed the welfare consequences of a 2004 phytosanitary rule that removed seasonal and geographic restrictions on fresh Hass avocado imports from Mexico. They showed that the combination of low pest risk and substantial consumer benefits implies that removal of the import restriction increased U.S. net welfare by $77 million. More recently, literature has emerged that examines the international standards for treatment of wood destined to be used as wood packaging material. Strutt, Turner, Haack, and Olson (2013) estimated trade and economic impacts of International Standards for Phytosanitary Measures No. 15 (ISPM 15) and found that the standard is likely to have a small negative impact on trade and welfare for most countries. Haack et al. (2014) investigated the impact of ISPM 15 on pest interception rates for wood packaging material at U.S. ports of entry. The authors emphasized the importance of designing appropriate sampling programs before and after introduction of important new phytosanitary policies in order to accurately assess their effectiveness.

The earliest literature on invasive species and international trade was largely empirical, with a focus on the welfare consequences of import bans and other trade restrictions. A series of theoretical papers subsequently emerged, beginning with investigations of the use of tariffs to prevent introductions of invasive species. Paarlberg and Lee (1998) derived the optimal import tariff to prevent a foot and mouth disease (FMD) outbreak; the tariff includes both terms-of-trade incentives and a term that accounts for potential FMD damages due to imports.3 Wilson and Antón (2006) built on Paarlberg and Lee’s work (1998) by incorporating mitigation strategies into a model of import tariffs addressing a FMD risk.4

Whereas the early literature focused on risk-based tariffs and empirical assessments of the welfare consequences of import bans and quarantines, a new literature emerged in the 2000s that focused on optimal enforcement of import standards that restrict entry of contaminated shipments. McAusland and Costello (2004) considered the optimal mix of border inspections and tariffs to address damages due to invasive species introductions. A social welfare function consisting of consumer surplus, tariff revenue, and environmental damages was maximized. Several interesting results emerged from the theory. As the infection rate of shipments (the exogenous proportion of imported goods that are infected with invasive species) increases, the optimal tariff on imports increases, whereas beyond a threshold infection level, the optimal inspection intensity decreases. Two counteracting effects drive the latter result. First, as the infection rate increases, the productivity of inspections increases because it is easier to detect contaminated imports. Second, an assumption of the model is that contaminated goods detected through the course of inspections are subsequently destroyed; this increases the opportunity cost (to consumers) of inspections. The second effect dominates at high infection rates. With respect to damages (actual potential adverse monetary impacts, should the invasive species become established), the optimal inspection intensity should increase as damages increase, as one would expect.

McAusland and Costello (2004) also considered the impact of measures that might be undertaken by exporters to “pre-clean” shipments in an effort to reduce infection rates, and found that the joint welfare of importers and exporters is maximized if the import tariff and inspection intensity are made contingent on the infection rate. Mérel and Carter (2008) showed that, in the context of pre-export cleaning, a two-part tariff consisting of a uniform tariff imposed to cover inspection costs and a penalty imposed on detected contaminated shipments to internalize the invasive species externality is preferred to the infection-rate-contingent tariff considered in McAusland and Costello (2004).

Several recent studies have explored issues related to exporter responses to border policy aimed at preventing invasive species introductions. While it is not clear that the use of discriminatory tariffs (tariffs that vary by country of origin or exporter) is consistent with WTO rules, technical assistance is permitted under the WTO SPS Agreement, which allows donations of expertise, training, and equipment to help reduce the contamination rates of exports. Examples of technical assistance include programs funded by the North American Plant Protection Organization (comprised of Canada, Mexico, and the United States) and the U.S. Animal and Plant Health Inspection Service to pre-clean exports (Fernandez & Sheriff, 2013). Fernandez and Sheriff (2013) considered the use of technical assistance and inspection intensity in cases where the regulator observes neither exporter heterogeneity (differences among various exporters) in invasive species risk nor the cost of reducing that risk. Their theoretical model shows that technical assistance does not reduce trade and is economically justified when exporting firms have more information about their abatement costs than the regulator in the importing country. Ameden, Boxall, Cash, and Vickers (2009) used an agent-based model to explore exporter response to changes in inspection intensity. They found that some exporters will respond to increased inspection intensity at a port with more investment in pre-shipment cleaning, whereas others will respond by choosing an alternative port, a practice referred to as “port-shopping” in Ameden, Cash, and Zilberman (2007).

The dynamics of invasive species establishment and spread after introduction have received less attention in the trade literature than optimal tariffs and inspections. An exception is Olson and Roy (2010), who modeled prevention of invasive species introductions as an output of several potential SPS policies, including treatment, inspection, process standards, import restrictions, and tariffs. Olson and Roy (2010) showed that the optimal SPS policy depends on the growth rate of the invasive species and the control costs. An implication of this research is that technology that reduces the cost of domestic control of invasive species can facilitate reductions in trade barriers motivated by SPS concerns.

Bioeconomic Modeling and the Choice of Optimal Management Strategies

Beginning in the late 1990s, economists began to focus more intensively on the question of how to most efficiently manage invasive species (Buhle, Margolis, & Ruesink, 2005; Eiswerth & Johnson, 2002; Eiswerth & van Kooten, 2002; Epanchin-Niell, Brockerhoff, Kean, & Turner, 2014; Fernandez, 2007; Finnoff, Shogren, Leung, & Lodge, 2005, 2007; Homans & Horie, 2011; Horan, Perrings, Lupi, & Bulte, 2002; Hyytiäinen, Lehtiniemi, Niemi, & Tikka, 2013; Kim, Lubowski, Lewandrowski, & Eiswerth, 2006; Knowler & Barbier, 2000; Mehta, Haight, Homans, Polasky, & Venette, 2007; Olson & Roy, 2002, 2005; Perrings et al., 2002; Polasky, 2010; Rout, Moore, & McCarthy, 2014; Settle & Shogren, 2002; Shogren, 2000; Wu, 2000). Researchers have focused on analyzing and comparing the merits of different approaches, such as prevention, early detection and rapid response, eradication, control or mitigation, and adaptation, as well as modeling the optimal level of an approach or combination of approaches.5 In addition, the types of decisions that economists model often involve determining how much of a management control measure to implement, as opposed to a simpler decision of whether (or not) to fund a particular control program (Epanchin-Niell, 2017). Through advancements in bioeconomic modeling, researchers have enhanced the capabilities of decision makers to more efficiently manage invasive species.

Economists have concentrated on three primary factors in the development of bioeconomic models for invasive species management. First, they have focused on the importance of dynamic analysis and decision-making (i.e., accounting for how factors change over time). Second, in addition to considering time, it has been important to consider space: a variety of factors may be expected to vary spatially across the landscape, including the extent and growth rates of invasions, the likely success of potential management strategies, and so on. Third, economists have increasingly attempted to account for uncertainty and imperfect information on the part of decision makers when it comes to identifying the most efficient management approaches. Each of these three factors is discussed in turn below.

Accounting for Dynamic Processes

Different invasive species management strategies may yield benefits that occur at different points in time—one strategy may work relatively quickly, while another may take more time. In the same way, one strategy may involve mostly up-front expenditures, whereas others require future expenditures on an ongoing basis. Therefore, choice of strategy may depend on the future time horizon under consideration by the decision maker, as well as the rate at which future costs and benefits are discounted. Additionally, ecological factors change over time—for example, some invasive species spread rapidly, whereas others spread slowly, and the rates at which ecosystems change due to other factors (e.g., climate change or human uses) vary as well.

Dynamic optimization is a method used in economics and other disciplines to ascertain what a decision maker should do to maximize a defined objective function (e.g., profits) or to minimize a defined objective function (e.g., costs) over some future period. Variables chosen by the decision maker are termed control variables (e.g., expenditures on invasive species management), while variables with values that change over time are termed state variables (e.g., the size of an invasive species infestation). Two approaches employed to solve dynamic optimization problems in invasive species management are optimal control (OC) and stochastic dynamic programming (SDP). The former method (OC) often models state variables as changing continuously through time, as opposed to once every time period (e.g., year), as assumed in SDP. While OC is quite useful in terms of providing intuition and reaching general conclusions about optimal solutions, SDP provides a method for better handling uncertainty about model parameters and is appropriate when key variables can be successfully modeled as changing periodically, rather than continuously, over time.

An initial question that an economist faces when constructing a dynamic bioeconomic model is: what type of decision maker (e.g., a farmer, rancher, public agency) is being considered and what kinds of objectives does that decision maker have? Also, what are the constraints faced by that decision maker (e.g., budget limitations) in its efforts to manage invasive species? Previous studies have assumed a variety of different objective functions. Some studies have applied dynamic optimization techniques to help a decision maker minimize, over future time periods, the sum of its invasive species management costs plus the damages yielded by the invasive species (Eiswerth & Johnson, 2002; Epanchin‐Niell, Haight, Berec, Kean, & Liebhold, 2012; Finnoff, Potapov, & Lewis, 2010; Olson & Roy, 2002). Eiswerth and Johnson (2002) employed such an approach using an OC model, as did Olson and Roy (2002), who additionally incorporated uncertainty regarding the rate of invasive species spread. Buhle et al. (2005) used data on both invader population dynamics and control costs to determine least-cost approaches for preventing the spread of an aquatic invasive snail. Ranjan, Marshall, and Shortle (2008) determined the cost-minimizing strategies for allocating a fixed amount of money between preventing the introduction of an invasive species and mitigating damages once its introduction and establishment occurs. In a twist on previous efforts, Elofsson, Bengtsson, and Gren (2012) developed a bioeconomic model and showed how the success of managing an invasive species depends on its ability to reproduce and spread in its new habitat, which in turn depends on factors like birth and survival rates. Other studies have considered decision makers who wish to maximize future net benefits (benefits minus costs of managing invasive species) or, in the case of a private decision maker, future profits (Eiswerth & van Kooten, 2002; Huffaker & Cooper, 1995; Jones & Medd, 2000; Kobayashi, Rollins, & Taylor, 2014; Polasky, 2010).

Accounting for Spatial Factors

Accounting for spatial factors is important because, given limited resources for invasive species management, it is necessary to allocate the resources among different locations. Put simply, a decision maker might strive to allocate management efforts across space so as to maximize the net benefits that accrue. In attempting to do that, it often is useful to categorize sites based on the expected net benefits of management (as a function of degree and rate of spread of the infestation, human uses at various sites, the nature of the ecosystem, costs of management, etc.). As an example, Taylor et al. (2013) computed benefit−cost ratios to assess how management efforts (in the form of treatment of invasive plants that provide unwanted fuel for wildfires) should be allocated most efficiently among different types of rangeland sites. Similarly, researchers are able to categorize sites to determine how to efficiently allocate post-fire restoration efforts on land that has been degraded by invasive plants (Epanchin-Niell, Englin, & Nalle, 2009). More broadly, some researchers are taking spatial factors into account in assessing early detection and response approaches (Kaiser & Burnett, 2010), in constructing models that may accommodate a large number of heterogeneous sites (Touza, Drechsler, Johst, & Dehnen-Schmutz, 2010), and in developing methods to efficiently allocate monitoring efforts (Epanchin-Niell et al., 2012, 2014).

Accounting for spatial factors is important for a second reason: management efforts undertaken at one location may affect the rate of invasive species spread and efficacy of management elsewhere. Models incorporating such spatial aspects assist decision makers in efficiently allocating efforts across sites (see Epanchin-Niell & Hastings, 2010, for a review of selected studies). Researchers have used simulation models to identify how to allocate either management or search effort across different locations (Cacho & Hester, 2011; Cacho, Spring, Hester, & MacNally, 2010; Hester & Cacho, 2012). Also, researchers have shown how invasive species damages and costs may be lowered by directing an invasion front toward natural barriers, such as rivers or mountains (Epanchin-Niell & Wilen, 2012). Despite such research, the incorporation of spatial aspects in invasive species management models warrants substantial further efforts (Mehta et al., 2007; Touza et al., 2010). At the same time, accounting for spatial heterogeneity and interconnections becomes complex rather quickly, thereby requiring modelers to make simplifying assumptions about other key factors (e.g., dynamic processes, uncertainty, and ecological complexities).

Accounting for Uncertainty

In most instances, there is substantial uncertainty about invasive species, including: the likelihood that a particular species may invade an area in the future, the current extent of an already existing invasive species population and the rate at which it will spread, and the likely success rates of potential management approaches. Therefore, the question of how to better account for uncertainty in invasive species management has been a key part of the development of the literature (e.g., Finnoff et al., 2007; Finnoff & Shogren, 2004; Haight & Polasky, 2010; Horan et al., 2002; Hyytiäinen et al., 2013; Marten & Moore, 2011; Moffitt, Stranlund, & Osteen, 2008; Olson & Roy, 2002, 2005; Perrings, 2005; Ranjan et al., 2008; Regan, Chadès, & Possingham, 2011; Rout et al., 2014). SDP is particularly useful for incorporating uncertainty─for example, uncertainty related to the future evolution of an invasive species stock or effectiveness of management approaches. It has been applied fruitfully in many different contexts, including cropland weeds (Pandey & Medd, 1991), invasive rangeland weeds (Eiswerth & van Kooten, 2002), invasive annual grasses on rangelands (Kobayashi et al., 2014), aquatic invasive animals (Hyytiäinen et al., 2013; Timar & Phaneuf, 2009), and invasive species in general (Bogich & Shea, 2008; Leung et al., 2002; Polasky, 2010). Data for such models are most often scarce, requiring researchers to collect primary data via surveys of land managers, biologists, or other experts.

Researchers have employed SDP not only to incorporate uncertainty, but also to examine interesting features of invasive species management. For example, Hyytiäinen et al. (2013) simultaneously analyzed the optimal levels and timing of different strategies (prevention, control, eradication, and adaptation) that may be applied to the invasive species Corbicula fluminea L. (Asian clam). As another example, Kobayashi et al. (2014) applied SDP to incorporate the role of stochastic wildfire incidents that contribute to the spread of invasive Bromus tectorum (cheatgrass) on rangelands and, in turn, the potential crossing of ecological thresholds. These are two good examples of cases in which researchers have used SDP to incorporate complex features of either human decision-making or ecological trajectories.

Current State of the Science

This section addresses the current state of the science for the three major topics in the economics of invasive species.

The Benefits and Costs of Invasive Species Management and Policy

This section focuses on the current literature pertaining to two of the primary challenges in evaluating the benefits and costs of invasive species management or policy: accurately defining the counterfactual state of the ecosystem without management or policy and accounting for the endemic problem of missing information when estimating invasive species damages.

Recent studies have employed a variety of approaches to credibly define the counterfactual state of the ecosystem with and without management or policy in order to estimate invasive species damages. Four approaches, in particular, are worth highlighting. First, studies that have analyzed the cost of invasive species by estimating industry supply curves (e.g., supply curves for specific timber products, such as softwood lumber, or specific agricultural products, such as beef, tomatoes, etc.) with and without invasion often assumed a constant marginal price for the affected commodity, which implies a constant marginal damage from the invasive species. McDermott, Finnoff, & Shogren (2013) demonstrated that assuming a constant marginal price, rather than an endogenous price (i.e., allowing the price to increase when the quantity supplied to the market falls), will typically overestimate financial damages from an invasive species. Second, bioeconomic models are increasingly used to simulate the distribution of damages with and without the invasive species management action or policy in place (Epanchin-Niell et al., 2009; Taylor et al., 2013). Third, econometric studies have used within-sample variation in the extent of the invasion to estimate damages. These studies have primarily examined the impact of invasive species on residential property values (Kovacs et al., 2011; Horsch & Lewis, 2009). Fourth, contingent valuation studies, which estimate values by asking individuals about their willingness to pay for a change in environmental quality, have estimated invasive species damages by directly incorporating counterfactual scenarios in the survey design (Provencher, Lewis, & Anderson, 2012).

The literature has tentatively begun to address the challenge to benefit−cost analysis of invasive species posed by missing information. Indeed, Aukema et al. (2011) undertook the only study we are aware of that has attempted to systematically address this challenge. Aukema et al.’s approach was based on the proposition that in order to avoid downward bias in the estimates of the damages from invasive species, it is necessary to model the likely damages from species whose economic costs are unknown, rather than to assume the damages are zero. Aukema et al.’s approach had four steps. First, they grouped the invasive species that impact or could impact an ecosystem into categories based on similarities in types of damage, biological traits, and pathways of introduction. Second, they identified a “poster pest” that is the most damaging species in each category. Third, they considered five cost categories for each poster pest: (1) federal government expenditures, (2) local government expenditures, (3) household expenditures, (4) residential property value losses, and (5) timber value losses to forest landowners. While Aukema et al. did not consider nonmarket ecosystem services, these estimates could be readily incorporated into their framework if data are available. Fourth, using the information on damages from the poster pest and estimates of the probability of future introductions, they calculated the cumulative economic damages from all species in a given category. Aukema et al. provided a promising way forward to account for the endemic problem of missing information in the economic analysis of the benefits and costs of invasive species and their work should provide a template for future work.

International Trade and Invasive Species

Recent research on invasive species and international trade has built on the prior literature in several ways, and four streams at the frontier of the current literature are discussed here. First, there has been substantial research investigating optimal border inspection policy, with a focus on the role of learning and uncertainty in the design of inspection procedures. Springborn (2014) considered the role of adaptive management—learning from targeted inspections and repeated decisions over time—in border inspections for invasive species and found that the strongest argument for adaptive management arises out of its role as insurance against poor outcomes in the absence of active experimentation through inspections. Building on work by Springborn, Costello, and Ferrier (2010), Springborn (2014) investigated instances where the inspector might want to deviate from a rule that prioritizes high-risk imports and instead inspect imports that are low risk but have high uncertainty in order to gather information about those imports. Springborn, Romagosa, and Keller (2011) developed a risk assessment system for live trade in nonindigenous species that considers the trade-off between the benefits of successfully avoiding invaders and the costs due to unnecessarily rejecting non-invaders, where the benefits and costs are assessed based on the welfare benefits of species trade. Springborn, Lindsay, and Epanchin-Niell (2016) considered the role of exporter and producer responses to inspection regime and the use of “state-dependent” monitoring, wherein shipments are targeted based on historical interceptions. They showed that state-dependent targeting reduces the frequency of infested shipments by 20% when compared to a uniform inspection regime.

Second, several papers have examined the conditions under which the policies that limit trade in potentially infected goods may have the counterintuitive effect of increasing expected invasive species damages. Costello and McAusland (2003) showed that efforts to limit trade in goods potentially infected with invasive species may increase invasive species risk due to a larger import-competing sector that is vulnerable to invasive species introductions. For instance, many invasive species damage agricultural crops. A policy that limits imports of agricultural commodities will lead to an expansion of domestic agricultural production, which may increase exposure to domestic invasive species introductions that exceed the imported introductions that would have occurred in the absence of the policy. Building on work by Costello and McAusland (2003), Horan et al. (2015) examined the spread of infectious disease with a focus on livestock; they considered endogenously determined infection risk in a situation where all producers are at risk and showed that trade provides a mechanism for both buyers and sellers to manage their risk. Horan et al. (2015) identified prevalence arbitrage and cost arbitrage opportunities that arise out of trade. Prevalence arbitrage occurs when the proportion of infected animals in the buyer’s herd exceeds the proportion of infected animals in the seller’s herd. In this case, buyers are willing to pay a premium to acquire lower-risk animals, which reduces average herd prevalence of the disease. Cost arbitrage occurs when the infection rate among sellers exceeds the infection rate among buyers. Sellers are willing to accept a discount (a cost saving for buyers) up to their anticipated avoided losses due to infection. The results presented in Horan et al. (2015) (i.e., trade may help to lower risks) are in stark contrast to the conventional approach that limits imports of live animals, plants, and pets from infected regions.

Third, several papers integrated the focus on border inspections initiated by McAusland and Costello (2004) with the older literature that emphasized the political economy aspects of SPS trade policy. Margolis, Shogren, and Fischer (2005) incorporated an invasive species externality into the Grossman and Helpman (1994) political economy model. They showed that, in general, it is difficult to distinguish disguised protectionism from legitimate use of trade policy to prevent invasive species introductions. Margolis and Shogren (2012) extended the Grossman and Helpman (1994) model to examine the use of border inspections as a protectionist tool in the cases of a bound tariff (a bound tariff is constrained by international trade agreements to be below the “optimal” level) and an unbound tariff. They found that, if the tariff is bound below the level the government prefers in light of the invasive species externality and the political economy motives to protect domestic producers, then border inspection intensity is above its optimum. Essentially, if the government is constrained in its use of tariffs to meet its environmental and political economy objectives, it turns to the use of border inspection as a substitute policy.

Lawley (2013) built on the earlier theoretical work of McAusland and Costello (2004) and Margolis and Shogren (2012) to develop a structural econometric model of border inspections that incorporates terms of trade and political economy motives to protect domestic agricultural producers from import competition. Using a detailed data set documenting the outcomes of U.S. border inspections of vegetable imports, Lawley (2013) presented evidence that U.S. border inspections are conducted in a manner that places greater weight on the welfare of producers relative to consumers, and that terms-of-trade motives influence inspection intensity. This suggests that, in addition to mitigating invasive species risk, border inspections are used to protect domestic producers from import competition. Whereas the earlier literature focused on protectionism in the establishment of SPS trade restrictions, the results presented in Lawley (2013) indicated that enforcement of SPS standards is also subject to use as disguised protectionism.

Finally, recent advances have been made quantifying the trade restrictiveness of SPS regulations. Much of the earlier literature examining the impact of technical barriers to trade and SPS measures relied on somewhat coarse measures of trade restrictiveness, such as counts of the number of restrictions applied. Peterson, Grant, Roberts, and Karov (2013) examined the trade restrictiveness of SPS regulations on the U.S. fruit and vegetable sector. They devised a novel approach to assess the restrictiveness of phytosanitary measures: they combined a gravity model of United States−exporter trade data with a learning-by-doing model, where some exporters learn to adapt to phytosanitary restrictions. Their measure of trade restrictiveness is the fraction of exporters that are able to adapt to required phytosanitary treatments so that they are no longer a barrier to trade. Peterson et al. (2013) found that at least two thirds of all exporters adapt to phytosanitary treatments well enough that they are no longer a barrier to trade. Once again, this research points to the potential gains from providing technical assistance, as highlighted by Fernandez and Sheriff (2013).

Bioeconomic Modeling and the Choice of Optimal Management Strategies

This section deals with three current issues in the development of bioeconomic models and the choice of optimal management strategies: the need to account for linkages between management efforts expended at various stages of invasion, ecological thresholds, and imperfect information.

As described elsewhere in this article, the choice of optimal or preferred management approaches for invasive species depends on a number of factors. One factor is the current stage of an invasion.6 In addition, a complicating factor is that management efforts expended at one stage of invasion generally will affect the state of the system at subsequent stages. For example, management efforts undertaken during the introduction or establishment stages typically will influence the characteristics of the invasive species population (size, rate of spread, etc.) should it reach the “spread” or “saturation” stages—and thus actions taken during any given stage may change the optimal strategies to be undertaken (if any) at other stages. Accounting for this is complex—while previous studies have tended to concentrate on best approaches within a given phase of invasion (e.g., Barbier, 2001; Blackwood, Berec, Yamanaka, & Liebhold, 2012; Hastings, Hall, & Taylor, 2006; Settle & Shogren, 2002; Sharov & Liebhold, 1998; Wu, 2000), accounting for the impacts of management applied within one invasion stage on outcomes at other stages of invasion remains an important task for future studies (Epanchin-Niell, 2017). Similarly, linkages between strategies or policies implemented before invasion occurs (prevention) and those taken afterward have been examined by economists (e.g., Fernandez, 2007, 2011) and continue to be priority topics for economic analysis.

In addition to linkages between stages of invasion, it is sometimes important (but often difficult) to consider that an ecosystem may cross over an ecological threshold due to a biological invasion, and that this transition may be irreversible. An ecological threshold is a critical point at which small changes in one or more ecosystem variables can lead to sudden, extreme changes in ecosystem condition (Holling, 1973). Ecological thresholds are important to consider for invasive species management because, in some instances, a return of the ecosystem across a threshold to its previous state may only be achieved via expensive management initiatives, if at all. As an example of one relevant context, thresholds are quite important to consider for non-native annual invasive grass species on arid rangelands (Eiswerth, Epanchin-Niell, Rollins, & Taylor, 2016; Taylor et al., 2013), and a small number of economic studies to date have used the OC method to account for thresholds in this context (see Huffaker & Cooper, 1995; Finnoff, Strong, & Tschirhart, 2008). Such studies illustrate how a combination of economic and ecological factors determines whether a decision maker is likely to decide to maintain an ecosystem in a desired ecological state versus letting it proceed beyond a threshold to a degraded ecological state. In a more recent modeling exercise, Kobayashi et al. (2014) used SDP to account for ecological thresholds in the context of non-native annual invasive grasses on arid rangelands used for grazing. They investigated whether subsidies that lower the cost of rangeland rehabilitation techniques cause changes in ranch management that make it less likely for the rangelands to cross ecological thresholds to an invasive species-dominated state. Their results indicate that such subsidies may work best if focused on land managers whose land has been invaded by an invasive species but has not yet crossed the ecological threshold where the ecosystem will move to an invasive-species-dominated state after disturbance (e.g., wildfire).

As indicated by these studies, economists have made some efforts to consider ecological thresholds in bioeconomic modeling and as factors in the process of choosing optimal management strategies. However, these topics remain a priority area for future research and will stand to benefit from continued collaboration among economists, natural scientists, and land managers.

Imperfect information represents a third critical challenge in invasive species management: decision makers typically have limited information regarding (a) the current extent and future spread of an invasive species, and (b) the influence that alternative management techniques will have. Therefore, researchers are conducting work to illustrate the benefits and costs of detection and monitoring efforts. This is because the choice of optimal management strategies, the estimated probability that an infestation already exists, and the benefits and costs associated with eventual outcomes all depend on available (but imperfect) information regarding invasive species populations—information that can be augmented (at a cost) by active detection and monitoring efforts (Adams & Lee, 2012; Haight & Polasky, 2010; Regan et al., 2011; Rout et al., 2014). One way to reduce the costs of detection and monitoring is to encourage the public’s assistance in detecting the presence of invasive species (Cacho & Hester, 2011). Some researchers are using a real options approach to evaluate the benefits and drawbacks of a “wait and see” strategy that resource managers sometimes consider in order to learn more as time passes about an established invasive species’ spread rates and damages (Saphores & Shogren, 2005; Sims & Finnoff, 2013; Sims, Finnoff, & Shogren, 2016).

Economists are also striving to model how decision makers might better react in the typical context of imperfect information. For example, in analyzing the role of imperfect information faced by managers of a non-native invasive weed, Eiswerth and van Kooten (2007) compared the results of SDP modeling to those of a model that allows decision makers to learn over time, by attempting different strategies in different time periods and then observing the results (e.g., net benefits). In this type of adaptive management learning model, the decision maker adapts by revising the expected benefits of a specific management technique based on its observed success in previous periods. A different approach to imperfect information involves “fuzzy” modeling methods that assume, for example, that a decision maker subjectively classifies the state of a system (e.g., the size or density of an infestation) into discrete categories (e.g., very low, low, moderate, high, very high), rather than using continuous data, because of the unavailability or incompleteness of such data. Fuzzy methods can help to model how decisions are made in cases where the decision maker “sees” only these types of fuzzy categories rather than crisp, numerical data. For example, two land managers may categorize a particular infestation differently, depending on differences in their levels of experience, knowledge, and ways in which they account for the location, nature, or uses of the invaded site; one manager may consider an infestation to be low, while another might judge it as moderate or even higher. Therefore, invasive species stocks display characteristics associated with fuzzy variables, and can be modeled using “fuzzy membership functions” (see Zadeh, 1965, for background), which differ from conventional probability distributions (Kosko, 1992); see Eiswerth and van Kooten (2002) for an application of these methods to invasive species.

As suggested by such modeling efforts, economists are attempting to construct models that better incorporate imperfect information. They also are attempting to conduct analyses that may help decision makers better engage in adaptive management, whereby managers can react to the accumulation of more and better knowledge over time. However, these remain priority areas for future research. Feedback from, and close collaboration with, land and resource managers, as well as a broader spectrum of public and private stakeholders, will be key determinants of the degree of success that economists and natural scientists have in such future efforts.

Conclusions

Three topics are particularly significant for invasive species relative to other natural resource management problems: the challenges of quantifying the economic damages from invasive species, international trade and invasive species, and bioeconomic modeling and invasive species. This article traces how the literature on these topics has developed over time and describes recent studies that are at the research frontier of each strand of the literature.

The literature that quantifies the economic damages from invasive species and the economic benefits from management has evolved from cost-based studies that estimated damages from invasive species in terms of the expenditures society was willing to undertake to avoid the damages, to damage-based studies that directly evaluate the market and non-market damages from invasive species. The movement from cost-based to damage-based studies has enhanced the credibility of damage estimates, but has also increased the methodological complexity and data requirements. Two challenges to quantifying economic damages of invasive species through damage-based studies are emphasized in this chapter. First, damaged-based studies require that the researcher define the counterfactual state of the ecosystem with and without management or policy. While several studies have applied modern nonmarket valuation techniques that explicitly define these counterfactuals, their relatively narrow focus often can limit the generalizability of their conclusions. Second, it is almost always the case that, in a given ecosystem, estimates of economic damages are only available for a subset of the species and for a subset of damages for any one species. Aukema et al. (2011) proposed an innovative approach to systematically dealing with the problem of missing information in economic evaluations of invasive species damages that we believe should provide a template for future work.

Literature on the economics of international trade and invasive species emerged with early investigations of protectionist use of border restrictions to prevent entry of invasive species. These studies took the form of cost−benefit studies of border controls such as import bans and tariffs in response to the WTO SPS Agreement. A largely separate theoretical literature evolved some time later modeling optimal use of import tariffs and inspections. Subsequent developments have assessed different approaches to improve the efficiency of border restrictions, as well as theoretical and empirical studies of the use of border measures as protectionist tools. Future research should focus on refining some of the recent literature on these topics.

Third, we examine how the development over time of bio-economic modelling approaches has addressed key themes in decision-making for invasive species management. Important factors addressed in various strands of the literature include modeling processes that occur over time (e.g., how invasive species spread, and how humans learn, over time); accounting for how the benefits and costs of management vary spatially across landscapes; and learning how to better incorporate uncertainty, incomplete information, and ecological thresholds. Looking ahead, we believe that future priorities in research include increased collaboration between social and natural scientists; the development of models that include a broader spectrum of invasive species as well as their various adverse economic and environmental impacts; and the creation of models and decision-making tools that may be more easily used by policymakers and managers.

Acknowledgments

The authors thank Kristen M. Eiswerth and two anonymous peer reviewers for useful comments on earlier versions of the article. We also thank James R. Kahn for his encouragement and support of this contribution.

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                                                                                                                                                                                                                                                                              Notes:

                                                                                                                                                                                                                                                                              (1.) Economic harm may be considered to have occurred when humans incur out-of-pocket costs to manage the invasive species or suffer monetary damages from their presence. Environmental harm may be thought of as injuries to environmental systems or the functions and processes they perform, regardless of whether humans incur out-of-pocket costs to remedy those injuries and notwithstanding whether the injuries are perceived by humans.

                                                                                                                                                                                                                                                                              (2.) Among the earliest examples of legislation restricting pest entry is Germany’s 1875 ban on potato imports in reaction to a Colorado potato beetle outbreak a year earlier associated with imported potatoes (Kreith & Golino, 2003). The Destructive Insects Act was passed 2 years later in England. In the United States, the first quarantine and destruction program was introduced in Massachusetts in 1859 to control imports of infected cattle. Federally, U.S. Customs collectors imposed a 90-day quarantine on European cattle imports in 1879 (Kreith & Golino, 2003). In New Zealand, restrictions on plant and animal imports began in 1894 (Veitch & Clout, 2001).

                                                                                                                                                                                                                                                                              (3.) A country improves its terms of trade if the prices of the goods and services it imports fall relative to the prices of its exports. A country with market power in an imported good can reduce its demand for imports in an effort to reduce the price its consumers pay for the imports. One approach a large country can use to reduce import demand is an “optimal tariff” (see Limao, 2008, for a concise explanation of optimal tariffs and their impacts on terms of trade).

                                                                                                                                                                                                                                                                              (4.) Batabyal and Beladi (2009) showed that market structure influences the optimal import tariff. Batabyal and Nijkamp (2016) considered interactions between two monopolists located in two different countries and showed that the profits of the two monopolists may increase as a result of a costly environmental border protocol.

                                                                                                                                                                                                                                                                              (5.) At a finer level of detail, as advances in detection technologies have taken place (e.g., Asner et al., 2008; Egan et al., 2015; Keskin, Unal, & Atar, 2016), decision makers have acquired a broadened array of methods for detecting invasive species on land and in lakes, rivers, oceans, and materials used in trade (e.g., ballast water and wood packaging). Similarly, decision makers seeking to control an established invasion (e.g., of a non-native plant species) have a spectrum of approaches from which to choose (e.g., hand pulling, mechanical cultivation, chemical treatment, controlled burning, targeted livestock grazing, biocontrol, etc.).

                                                                                                                                                                                                                                                                              (6.) Biological invasions generally have four stages: introduction, establishment, spread, and saturation.