Economics of controlling a spreading environmental weed

Weeds can cause significant problems to natural ecosystems. Although there have been numerous studies on the economics of weed control, relatively few of these studies have focused on natural ecosystems. This paper addresses this gap in the literature by assessing the cost-effectiveness of a comprehensive range of control strategies for blackberry (Rubus anglocandicans) in natural environments in Australia. We developed a stochastic dynamic simulation model and a deterministic dynamic optimisation model. The stochastic model calculates the expected net present value (NPV) of a range of control strategies, including any combination of treatment options. The optimisation model identifies the treatment combination that maximises NPV. Both models represent the costs and efficacies of control options over 25 years. The results indicate that using rust (Phragmidium violaceum) as a biological control agent only marginally increases NPV and excluding rust does not affect the optimal choice of other control options. The results also show for a wide range of parameter values that a strategy which combines the herbicide grazon (Triclopyre and picloram) and mowing is optimal. If chemical efficacy decreases by 20 percent it becomes optimal to include grazing blackberry by goats in the control strategy.environment, economics, weed, stochastic, optimisation, management, Environmental Economics and Policy,

Economics of Controlling Invasive Species: A Stochastic Optimisation Model for a Spatial-Dynamic Process

Invasive species are significant threats to biodiversity, natural ecosystems and agriculture leading to large worldwide economic and environmental damage. Spread and control of invasive species are stochastic processes with important spatial dimensions. Most economic studies of invasive species control ignore spatial and stochastic aspects. This paper covers this gap in the previous studies by analysing a spatially explicit dynamic process of controlling invasive species in a stochastic setting. We show how stochasticity, spatial location of infestation and control can influence the spread, control efficiency and optimal control strategies. The main aim of this paper is to analyse the relationship between economic parameters and stochastic spatial characteristics of infestation and control. In the model used, there are two ways to control infestation: border control, under which the spread of invasive species from any of its infested neighbouring cell is prevented, and cell control, which removes the infestation from the existing cell. An integer optimisation model is applied to find the optimal strategies to deal with invasive species. Results show that it is optimal to eradicate or contain for a larger range of border control and cell control costs when the invasion is in the corner or on the edge as compared to the case where the initial infestation is in the middle of the landscape. Decrease in the probability of successful border control makes containment an unfavourable control option even for low border control costs. We show that decrease in the rate of spread can result in switching optimal strategies from containment to abandonment of control, or from eradication to containment. We also showed when the probability of successful cell control decreases, a lower eradication cost is required for eradication to remain the optimal strategy. In summary, this paper shows that in order to avoid providing misleading recommendations to environmental managers, it is important to include uncertainty in the spatial dynamic analysis of invasive species control.Environmental Economics and Policy, Land Economics/Use,

Biological control of invasive plant species: stochastic economic analysis

We analysed to what extent the stochastic effects of two biological control agents (i.e. weevils and mycoherbicides) affect the optimal choice of Californian thistle control. A stochastic, dynamic optimisation model was set up to analyse strategies that maximise the expected net present values. We analysed the cost-effective strategies to control the thistle for deterministic and stochastic cases. Results show that the stochasticity of the efficacy of weevils does not affect the optimal strategy. Compared to the deterministic case, however, mycoherbicides will be introduced at a higher level of weed density if we take the stochastic effect of mycoherbicides into account.Stochastic, Optimisation, Biological control, Californian thistle, Economics.,

Optimal Control for a Dispersing Biological Agent

A bioeconomic model is developed to analyze the optimal control management strategies for an introduced herbivore in a two-compartment ecosystem. This paper analyzes cost-effective control strategies that decrease the spillover effects of the herbivore on endangered plant species, thereby reducing extinction pressure and increasing benefits. The optimal level of control is presented in different circumstances. The level of optimal control is high if the herbivore has a relatively low attack rate on the target species, the nontarget host has a high biodiversity value, or the costs of controlling the herbivore are low

Willingness to pay to reduce health costs associated with bushfire smoke

Invasion of gamba grass in Northern Territory increases fire fuel and bushfire smoke. Increase in bushfire smoke decreases air quality and have negative health impacts. The aim of this study is to assess people’s willingness pay in order to control bushfire smoke and reduce its health risks. We also aim to assess what part of their willingness to pay is derived from altruism. To do this, we form two versions of a survey. The first version aims to assess willingness to pay which may consist of both altruism and personal benefits. The framing tells the respondents to assume that increases in bushfire smoke will affect their own personal health. In the second version of the survey that aims to assess only altruism, respondents will be limited to those who do not have asthma. We tell these respondents that increase in bushfire smoke will only affect people with asthma. Visual aides were used to enhance risk comprehension. Results showed that analysing altruistic value is important when valuing environmental assets. Altruistic value of statistical life is calculated at $5000,000. We showed that distinguishing paternalistic and non-paternalistic altruism is important.48$2600,000

Economics of controlling a spreading environmental weed

Weeds can cause significant problems to natural ecosystems. Although there have been numerous studies on the economics of weed control, relatively few of these studies have focused on natural ecosystems. This paper addresses this gap in the literature by assessing the cost-effectiveness of a comprehensive range of control strategies for blackberry (Rubus anglocandicans) in natural environments in Australia. We developed a stochastic dynamic simulation model and a deterministic dynamic optimisation model. The stochastic model calculates the expected net present value (NPV) of a range of control strategies, including any combination of treatment options. The optimisation model identifies the treatment combination that maximises NPV. Both models represent the costs and efficacies of control options over 25 years. The results indicate that using rust (Phragmidium violaceum) as a biological control agent only marginally increases NPV and excluding rust does not affect the optimal choice of other control options. The results also show for a wide range of parameter values that a strategy which combines the herbicide grazon (Triclopyre and picloram) and mowing is optimal. If chemical efficacy decreases by 20 percent it becomes optimal to include grazing blackberry by goats in the control strategy

Threshold effects on climate change policy

Climate change scientists have shown concerns about possible sudden changes due to crossing a temperature threshold. Many authors emphasized the importance of sea level rise due to melting ice sheets of Greenland and west Antarctica and its large economic consequences. We study the economic consequences and policy implications of assuming a certain and uncertain thresholds at 2oC of global warming where it could result in a sudden sea level rise. We introduce these thresholds to the Dynamic Integrated model of Climate and the Economy (DICE model, Nordhaus 2009) and assess their policy impacts. We further modify the DICE model and assess the impacts of the thresholds using a reactive damage function. Results show that certain and uncertain thresholds have different impact on the optimal policy for different years. If the threshold is uncertain, the optimal carbon tax before 2025 is higher than certain threshold. However, optimal carbon tax assuming a certain threshold becomes higher than uncertain threshold from year 2025 and sharply increases between years 2035 to 2100

Economics of Controlling Invasive Species: A Stochastic Optimisation Model for a Spatial-Dynamic Process

Invasive species are significant threats to biodiversity, natural ecosystems and agriculture leading to large worldwide economic and environmental damage. Spread and control of invasive species are stochastic processes with important spatial dimensions. Most economic studies of invasive species control ignore spatial and stochastic aspects. This paper covers this gap in the previous studies by analysing a spatially explicit dynamic process of controlling invasive species in a stochastic setting. We show how stochasticity, spatial location of infestation and control can influence the spread, control efficiency and optimal control strategies. The main aim of this paper is to analyse the relationship between economic parameters and stochastic spatial characteristics of infestation and control. In the model used, there are two ways to control infestation: border control, under which the spread of invasive species from any of its infested neighbouring cell is prevented, and cell control, which removes the infestation from the existing cell. An integer optimisation model is applied to find the optimal strategies to deal with invasive species. Results show that it is optimal to eradicate or contain for a larger range of border control and cell control costs when the invasion is in the corner or on the edge as compared to the case where the initial infestation is in the middle of the landscape. Decrease in the probability of successful border control makes containment an unfavourable control option even for low border control costs. We show that decrease in the rate of spread can result in switching optimal strategies from containment to abandonment of control, or from eradication to containment. We also showed when the probability of successful cell control decreases, a lower eradication cost is required for eradication to remain the optimal strategy. In summary, this paper shows that in order to avoid providing misleading recommendations to environmental managers, it is important to include uncertainty in the spatial dynamic analysis of invasive species control