An options based bioeconomic model for biological and chemical control of invasive species

Marten, Alex L.; Moore, Christopher C.

doi:10.1016/j.ecolecon.2011.05.022

Cited by 43 publications

(54 citation statements)

References 22 publications

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“…These studies optimize investments, explicitly accounting for the value of reduced uncertainty from those investments for improving management. Value of information also has been incorporated into other decision models for invasion management , and real options models consider the optimal timing of management investments accounting for how uncertainty about invasion damages may be alleviated over time (e.g., Marten and Moore 2011;Saphores and Shogren 2005;Sims and Finnoff 2013). Experience-weighted attraction learning models have been considered for improving invasion management by reducing uncertainty over time (Eiswerth and van Kooten 2007).…”

Section: Decision-making Under Uncertaintymentioning

confidence: 99%

“…Economists have analyzed this choice using a real options approach, accounting for uncertainties about the invader's impact, as well as the costs associated with responding to an invader that turns out to not be very damaging (Marten and Moore 2011;Saphores and Shogren 2005;Sims and Finnoff 2013). Saphores and Shogren (2005) evaluate the optimal timing of a fixed control investment and how much should be spent on research to learn about the species' ecological and economic characteristics.…”

Section: Optimal Control Of Established Invasionsmentioning

confidence: 99%

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Economics of invasive species policy and management

Epanchin‐Niell

2017

Biol Invasions

156

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This article examines the use of economic analysis to inform bioinvasion management, with particular focus on forest resources. Economics is key for understanding invasion processes, impacts, and decision-making. Biological invasions are driven by and affect economic activities at multiple scales and stages of an invasion. Bioeconomic modeling seeks to inform how resources can be optimally allocated across invasion management activities-including prevention, surveillance programs for early detection and management, and controlling invasion populations and spread-to minimize the long-term costs and damages. Economic analysis facilitates understanding of decisions by public and private decision-makers, gaps between these, and the design of policies to achieve socially desirable outcomes. Private decisionmakers may undercontrol invasions relative to socially optimal levels, because they generally account for their own costs and benefits of control but less often for broader ecosystem impacts or future spread across the landscape. Economic analysis considers approaches for increasing private invasion management and evaluates feedbacks between ecological and economic systems that can affect policy outcomes. Future research should continue evaluation and design of control strategies across the biosecurity continuum and across species to enhance cost-effectiveness, better incorporate uncertainty into policy design, increase focus on incentives and behavioral tools to influence private behaviors that affect invasion spread, and incorporate invasive species consideration within broader systems-focused science. In addition, challenges in valuing biodiversity and ecosystem service impacts and the costs and effectiveness of control measures are key data gaps. Greater collaboration between decision-makers and researchers will facilitate development and communication of usable economic research.

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Section: Decision-making Under Uncertaintymentioning

confidence: 99%

Section: Optimal Control Of Established Invasionsmentioning

confidence: 99%

Economics of invasive species policy and management

Epanchin‐Niell

2017

Biol Invasions

156

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“…The literature on this subject is substantial (Born andal. 2005, Marten andMoore 2011), but the lack of general guidelines generates a multitude of population models for each invader, as pointed out by Ramula et al (2008). These population models work according to the demographic processes based on survival, growth and fecundity.…”

Section: Introductionmentioning

confidence: 99%

“…(2005) indicates that uncertainty arising in the ecological context of the invasive process is not handled. Likewise, Marten and Moore (2011) emphasize that the absence of biological uncertainty in deterministic bioeconomic models leads to significant bias in management solutions. In this way, Olson and Roy (2002) show that stochastic shocks to the population growth affect the choice of management strategy.…”

Section: Introductionmentioning

confidence: 99%

Bayesian Population Dynamics of Spreading Species

Dragicevic

2014

Environ Model Assess

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The invasion of native species by exotic species is one of the most serious threats to biodiversity and ecosystem functioning. Despite a number of empirical and theoretical studies, there is still no general model about why or when settlement becomes invasion. The purpose of this work is to test a model of Bayesian population dynamics relying on bestresponse strategies that could help in resource management and bioeconomic modeling. Given the exotic species survival probability, our static game unveils a breaking-level probability in mixed-strategies, where it is in the interest of exotic species to invade and in the interest of native species to resist. In dynamic setting, we introduce a stochastic version of the balance equation based on conditional probabilities. When the exotic species survival probability and the availability of resources in the ecosystem are respectively high and low, the dynamics shows that the convergence of subpopulations toward steady-states operates at a high pace.

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“…This last point is crucial and demarcate our work from the typical approach in real options. In real options, one usually considers impulse controls that are governed by trigger levels (see Sarkar 2009 andMarten andMoore 2011 for relevant examples). The methodological advantage of impulse controls is that they can be treated as constants in the dynamic equations, and the corresponding differential equations that govern the value function take the form of linear differential equations, for example of the Euler type that has known closed form solutions.…”

Section: Introductionmentioning

confidence: 99%

Harvesting in a Fishery with Stochastic Growth and a Mean-Reverting Price

Kvamsdal

Poudel

Sandal

2014

Environ Resource Econ

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We analyze a continuous, nonlinear bioeconomic model to demonstrate how stochasticity in the growth of fish stocks affects the optimal exploitation policy when prices are stochastic, mean-reverting and possibly harvest dependent. Optimal exploitation has nonlinear responses to the price signal and should be conservative at low levels of biological stochasticity and aggressive at high levels. Price stochasticity induces conservative exploitation with little or no biological uncertainty, but has no strong effect when the biological uncertainty is larger. We further observe that resource exploitation should be conservative when the price reverts slowly to the mean. Simulations show that, in the long run, both the stock level and the exploitation rate are lower than in the deterministic solution. With a harvest-dependent price, the long-run price is higher in the stochastic system. The price mean reversion rate has no influence on the long-run solutions.

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An options based bioeconomic model for biological and chemical control of invasive species

Cited by 43 publications

References 22 publications

Economics of invasive species policy and management

Economics of invasive species policy and management

Bayesian Population Dynamics of Spreading Species

Harvesting in a Fishery with Stochastic Growth and a Mean-Reverting Price

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