Summary Mounting scientific evidence suggests newly imposed disturbance and/or alterations to exi... more Summary Mounting scientific evidence suggests newly imposed disturbance and/or alterations to existing disturbances facilitate invasion. Several empirical studies have explored the role of disturbance in invasion, but little work has been done to fit current understanding into a format useful for practical control efforts. We are working towards addressing this shortcoming by developing a metapopulation model couched in a decision theory framework.
Summary This study outlines a method for supporting decisions to declare that an eradication prog... more Summary This study outlines a method for supporting decisions to declare that an eradication program has been successful. Previous approaches to this problem have depended on an estimate of the detectability of the species in a standard survey. This study circumvents this issue by analysing the record of 'absence'results. The problem is solved by minimising the net expected cost of the decision.
Finding efficient ways to manage the threat of invasive species helps make the most of limited re... more Finding efficient ways to manage the threat of invasive species helps make the most of limited resources. Different management actions reduce the impact of invasions differently: preventing invasion eliminates impacts entirely, surveillance can facilitate early detection and eradication, and removing individuals can reduce future impact. Few studies have examined the trade-off between all three facets of invasion management. Using a simple model of island invasion, we find how resources should be allocated to each action to minimise the total cost of management and impact. We use a case study of black rat (Rattus rattus) invasion on Barrow Island, Western Australia. The optimal amount to invest in each management action depends on the effectiveness of each action, and the magnitude of impact caused by different stages of invasion. If the pest is currently absent, it is more cost-effective to prevent impacts through prevention or surveillance. If the pest is already widespread, it can sometimes be cost-effective to give up rather than attempting eradication. This model of invasion can provide useful decision support by identifying the trade-offs inherent in each candidate management strategy, the thresholds that alter optimal strategies, and the parameters for which we need more information.
Statements of extinction will always be uncertain because of imperfect detection of species in th... more Statements of extinction will always be uncertain because of imperfect detection of species in the wild. Two errors can be made when declaring a species extinct. Extinction can be declared prematurely, with a resulting loss of protection and management intervention. Alternatively, limited conservation resources can be wasted attempting to protect a species that no longer exists. Rather than setting an arbitrary level of certainty at which to declare extinction, we argue that the decision must trade off the expected costs of both errors. Optimal decisions depend on the cost of continued intervention, the probability the species is extant, and the estimated value of management (the benefit of management times the value of the species). We illustrated our approach with three examples: the Dodo (Raphus cucullatus), the Ivory-billed Woodpecker (U.S. subspecies Campephilus principalis principalis), and the mountain pygmy-possum ( Burramys parvus). The dodo was extremely unlikely to be extant, so managing and monitoring for it today would not be cost-effective unless the value of management was extremely high. The probability the Ivory-billed woodpecker is extant depended on whether recent controversial sightings were accepted. Without the recent controversial sightings, it was optimal to declare extinction of the species in 1965 at the latest. Accepting the recent controversial sightings, it was optimal to continue monitoring and managing until 2032 at the latest. The mountain pygmy-possum is currently extant, with a rapidly declining sighting rate. It was optimal to conduct as many as 66 surveys without sighting before declaring the species extinct. The probability of persistence remained high even after many surveys without sighting because it was difficult to determine whether the species was extinct or undetected. If the value of management is high enough, continued intervention can be cost-effective even if the species is likely to be extinct.
Removing pests from islands, and then keeping them pest free, is a common management goal. Given ... more Removing pests from islands, and then keeping them pest free, is a common management goal. Given that goal we face a decision: how much effort should we invest in quarantine to reduce the risk of a pest arriving vs. surveillance, looking for the pest on the island with the view of eradicating it before it gets out of control. We use models of an island under threat of invasion by a pest (animal, plant or disease) and a cost minimisation approach to optimally allocate management resources between quarantine and surveillance. In the optimal allocations joint investment in both quarantine and surveillance is uncommon. Investment in quarantine is optimal if quarantine is more effective than surveillance or if large costs associated with pest impact and eradication are incurred at low pest density. Investment in quarantine is also favoured as our ability to eradicate a pest declines. Surveillance is optimal if it is considerably more cost-effective than quarantine and we can generate significant savings through early detection of the pest population. We illustrate how theses models are useful ways to examine these trade-offs by applying the model to the prevention of black rat (Rattus rattus) invasion on Barrow Island, Western Australia. Our model predicts an optimal strategy different to the management strategy currently being used on the island. We suggest that this is due to a risk-averse tendency in managers and the difficulty of estimating costs that combine management, environmental and social factors.
Adaptive management has a long history in natural resource management literature, but despite thi... more Adaptive management has a long history in natural resource management literature, but despite this few practitioners have developed adaptive strategies to conserve threatened species. Active adaptive management provides a framework for valuing learning by measuring the degree to which it improves long-run management outcomes. The challenge of an active adaptive approach is to find the correct balance between gaining knowledge to improve management in the future and achieving the best short-term outcome based on current knowledge. We develop and analyze a framework for active adaptive management of a threatened species. Our case study concerns a novel facial tumour disease affecting the Australian threatened species Sarcophilus harrisii; the Tasmanian devil. We use stochastic dynamic programming with Bayesian updating to identify the management strategy that maximizes the Tasmanian devil population growth rate, taking into account improvements to management through learning to better understand disease latency and the relative effectiveness of three competing management options. Exactly which management action we choose each year is driven by the credibility of competing hypotheses about disease latency and by the 48 population growth rate predicted by each hypothesis under the competing management actions. We discover that the optimal combination of management actions depends on the number of sites available and the time remaining to implement management. Our approach to active adaptive management provides a framework to identify the optimal amount of effort to invest in learning to achieve long-run conservation objectives.
1. Invasive species threaten biodiversity, and their eradication is desirable whenever possible. ... more 1. Invasive species threaten biodiversity, and their eradication is desirable whenever possible. Deciding whether an invasive species has been successfully eradicated is difficult because of imperfect detection. Two previous studies [Regan et al., Ecology Letters, 9 (2006), 759; Rout et al., Journal of Applied Ecology, 46 (2009), 110] have used a decision theory framework to minimize the total expected cost by finding the number of consecutive surveys without detection (absent surveys) after which a species should be declared eradicated. These two studies used different methods to calculate the probability that the invasive species is present when it has not been detected for a number of surveys. However, neither acknowledged uncertainty in this probability, which can lead to suboptimal solutions.
2. We use info-gap theory to examine the effect of uncertainty in the probability of presence on decision-making. Instead of optimizing performance for an assumed system model, info-gap theory finds the decision among the alternatives considered that is most robust to model uncertainty while meeting a set performance requirement. This is the first application of info-gap theory to invasive species management.
3. We find the number of absent surveys after which eradication should be declared to be relatively robust to uncertainty in the probability of presence. This solution depends on the nominal estimate of the probability of presence, the performance requirement and the cost of surveying, but not the cost of falsely declaring eradication.
4. More generally, to be robust to uncertainty in the probability of presence, managers should conduct at least as many surveys as the number that minimizes the total expected cost. This holds for any nominal model of the probability of presence.
5. Synthesis and applications. Uncertainty is pervasive in ecology and conservation biology. It is therefore crucial to consider its impact on decision-making; info-gap theory provides a way to do this. We find a simple expression for the info-gap solution, which could be applied by eradication managers to make decisions that are robust to uncertainty in the probability of presence.
1. A major challenge for eradication managers is deciding when a programme can be deemed successf... more 1. A major challenge for eradication managers is deciding when a programme can be deemed successful. Regan
et al. (2006) were the first to pose this problem within a decision theory framework, minimizing the net expected cost of the decision. The optimal time to declare eradication was based on the number of consecutive surveys in which the species was not found (‘absent surveys’). Their formulation used estimates of detectability and persistence – parameters that are often difficult to estimate – to calculate the probability that the invasive species is still present.
2. Here we use a similar decision-making framework but instead predict presence based on the pattern of sightings, using a method developed by Solow (1993a) that assumes a constant sighting rate. This method does not require estimates of detectability and persistence. We find the number of absent surveys after which eradication should be declared, using three approaches: a stochastic dynamic program, which finds the exact optimal solution, a rule of thumb, and an approximation. We then compare these results with a method assuming a declining sighting rate.
3. Both the rule of thumb and approximation give results that are close to the exact optimal solution. The rule of thumb with the declining sighting rate method generally gives a larger optimal number of absent surveys.
4. Synthesis and applications. Analysing this problem within a decision theory framework enables us to minimize the expected cost of declaring eradication. By using the more readily available sighting data, we make this framework applicable to a wider range of invasive species. Our approximation is a simple calculation, making it an accessible tool that could be applied by managers of eradication programmes for invasive species.
Conservation management actions and decisions are often defined by the location of ecological bou... more Conservation management actions and decisions are often defined by the location of ecological boundaries, for example, the present range of invasive or threatened species. The position of these boundaries can be cryptic, and managers must therefore directly sample sites, an expensive and time consuming process. While accurate boundary location techniques have been considered by ecological theorists, the issue of cost-effective, or optimal boundary location has not. We propose a general framework for boundary location which incorporates both cost-efficiency and uncertainty. To illustrate its application, we use it to help locate an infectious disease front in the endangered Tasmanian devil population. The method ensures optimal spatial sampling by maximizing the expected information gained from each sample. When resources are limited, our method provides more accurate estimates of the boundary location than traditional sampling protocols. Using a formal decision theory sampling design encourages economically efficient actions, and provides defensible and transparent rationale for management actions.
Active adaptive management (AAM) is an approach to wildlife management that acknowledges our impe... more Active adaptive management (AAM) is an approach to wildlife management that acknowledges our imperfect understanding of natural systems and allows for some resolution of our uncertainty. Such learning may be characterized by risky strategies in the short term. Experimentation is only considered acceptable if it is expected to be repaid by increased returns in the long term, generated by an improved understanding of the system. By setting AAM problems within a decision theory framework, we can find this optimal balance between achieving our objectives in the short term and learning for the long term.We apply this approach to managing the translocation of the bridled nailtail wallaby (Onychogalea fraenata), an endangered species from Queensland, Australia. Our task is to allocate captive-bred animals, between two sites or populations to maximize abundance at the end of the translocation project. One population, at the original site of occupancy, has a known growth rate. A population potentially could be established at a second site of suitable habitat, but we can only learn the growth rate of this new population by monitoring translocated animals. We use a mathematical programming technique called stochastic dynamic programming, which determines optimal management decisions for every possible management trajectory. We find optimal strategies under active and passive adaptive management, which enables us to examine the balance between learning and managing directly. Learning is more often optimal when we have less prior information about the uncertain population growth rate at the new site, when the growth rate at the original site is low, and when there is substantial time remaining in the translocation project. Few studies outside the area of optimal harvesting have framed AAM within a decision theory context. This is the first application to threatened species translocation.
Due to their impact on natural systems, eradication of invasive species is preferable whenever po... more Due to their impact on natural systems, eradication of invasive species is preferable whenever possible. Deciding whether a species has been successfully eradicated is difficult because of imperfect detection. There are two ways that the decision to declare eradication can go wrong: if the species is declared eradicated when still present its population may grow undetected, incurring large economic and environmental costs; alternatively, continuing surveys when the species is already gone involves unnecessary survey costs. By analyzing this dilemma as an explicit decision problem, managers can balance the risk of these errors, and above all, make decisions that are transparent and justifiable. In this paper I summarize current work in the development and application of decision theory for declaring eradication.
1. Invasive plants have negative impacts on ecosystems worldwide. Several ecological studies have... more 1. Invasive plants have negative impacts on ecosystems worldwide. Several ecological studies have identified disturbance as a causative mechanism of plant invasions. Changes to natural disturbances and/or newly imposed disturbances can favour an invader over native species especially those that are better adapted to prior conditions. 2. To link the disturbance ecology of invasives to their management, we investigated the benefit of incorporating actions that manipulate disturbance (natural or imposed) into control efforts. We developed a simple model that describes the dynamics of an invader whose establishment is preferentially favoured by disturbance. 3. The model includes the probability of disturbance differentially affecting sites occupied by natives and invaders. Invaded sites are disturbed by alternative control measures, which act to kill and/or remove above-ground biomass and reduce the seed bank. We couched the model in a decision theory tool, stochastic dynamic programming, and applied it to the management of Mimosa pigra, a pan-tropical invasive perennial shrub. 4. We found that targeting the above-ground biomass of the invader (current population) was optimal when the probability of disturbance of native sites and the invader seed bank size were low to moderate. When both the rate of disturbance of native sites and invader seed banks were high, the best measure was that with the highest probability of reducing the seed bank (future populations). This measure was optimal despite its trade-off of having the highest probability of reinvasion. 5. Synthesis and applications. Manipulation of disturbance regimes in both native and invaded sites can simplify control efforts. If there is a high probability that native vegetation will be disturbed, then management efforts should focus on future populations by attempting to reduce the size of the invader seed bank. This complicates control, as seed bank size is difficult to measure and reducing it requires intensive actions, which are likely to also negatively affect the seed bank of native species. If, however, the probability of disturbance of native sites can be reduced, practitioners can shift control from future populations to the current population, which is more straightforward to implement and monitor.
Translocation is a useful management option for conservation of threatened animal species. It can... more Translocation is a useful management option for conservation of threatened animal species. It can be used to increase the range of a species, augment the numbers in a critical population, or establish new populations and hence spread the risk of extinction through local catastrophes. As it is an important and expensive conservation tool, translocation management decisions must be carefully considered, with the objective of the translocation project in mind. By analysing the translocation problem within a decision-theory framework, we find optimal management decisions that are rational and transparent. We illustrate our approach using a case study of the bridled nailtailwallaby (Onychogalea fraenata). Our particular translocation question is: if we have a set number ofwallabies to translocate in each time period and two translocation sites, how many wallabies should we put at each site given the state of each population to maximise the benefit to the species? We model the translocated populations with first-order Markov chain stochastic population models, and use stochastic dynamic programming to determine the optimal management decisions. We look at two sites with different growth rates – one increasing and one decreasing – and compare the optimal strategies for two different objective functions. The first is a long-term persistence objective function, which maximises the persistence of translocated populations a large number of time steps after the end of the translocation program. The second maximises total population size at the end of the translocation program. Although these objective functions are similar, they generate surprisingly different optimal translocation strategies. When maximising the long-term persistence of the translocated populations, translocation decisions are not important as long as an increasing population is established. This indicates that site quality – rather than the number and timing of translocations – primarily determines the long-term persistence of populations. When maximising total population size, the optimal strategy is to add to the increasing population unless it is above a size where it is likely to reach its carrying capacity over the planning time frame. As translocation decisions are important in fulfilling the objective, this objective function is more useful in creating practical advice for translocation managers. The discrepancy between the optimal strategies given by the two objectives demonstrates the importance of careful consideration when specifying the goals of a project. This observation applies not only to translocation programs, but any project where clear decision-making is needed.
Summary Mounting scientific evidence suggests newly imposed disturbance and/or alterations to exi... more Summary Mounting scientific evidence suggests newly imposed disturbance and/or alterations to existing disturbances facilitate invasion. Several empirical studies have explored the role of disturbance in invasion, but little work has been done to fit current understanding into a format useful for practical control efforts. We are working towards addressing this shortcoming by developing a metapopulation model couched in a decision theory framework.
Summary This study outlines a method for supporting decisions to declare that an eradication prog... more Summary This study outlines a method for supporting decisions to declare that an eradication program has been successful. Previous approaches to this problem have depended on an estimate of the detectability of the species in a standard survey. This study circumvents this issue by analysing the record of 'absence'results. The problem is solved by minimising the net expected cost of the decision.
Finding efficient ways to manage the threat of invasive species helps make the most of limited re... more Finding efficient ways to manage the threat of invasive species helps make the most of limited resources. Different management actions reduce the impact of invasions differently: preventing invasion eliminates impacts entirely, surveillance can facilitate early detection and eradication, and removing individuals can reduce future impact. Few studies have examined the trade-off between all three facets of invasion management. Using a simple model of island invasion, we find how resources should be allocated to each action to minimise the total cost of management and impact. We use a case study of black rat (Rattus rattus) invasion on Barrow Island, Western Australia. The optimal amount to invest in each management action depends on the effectiveness of each action, and the magnitude of impact caused by different stages of invasion. If the pest is currently absent, it is more cost-effective to prevent impacts through prevention or surveillance. If the pest is already widespread, it can sometimes be cost-effective to give up rather than attempting eradication. This model of invasion can provide useful decision support by identifying the trade-offs inherent in each candidate management strategy, the thresholds that alter optimal strategies, and the parameters for which we need more information.
Statements of extinction will always be uncertain because of imperfect detection of species in th... more Statements of extinction will always be uncertain because of imperfect detection of species in the wild. Two errors can be made when declaring a species extinct. Extinction can be declared prematurely, with a resulting loss of protection and management intervention. Alternatively, limited conservation resources can be wasted attempting to protect a species that no longer exists. Rather than setting an arbitrary level of certainty at which to declare extinction, we argue that the decision must trade off the expected costs of both errors. Optimal decisions depend on the cost of continued intervention, the probability the species is extant, and the estimated value of management (the benefit of management times the value of the species). We illustrated our approach with three examples: the Dodo (Raphus cucullatus), the Ivory-billed Woodpecker (U.S. subspecies Campephilus principalis principalis), and the mountain pygmy-possum ( Burramys parvus). The dodo was extremely unlikely to be extant, so managing and monitoring for it today would not be cost-effective unless the value of management was extremely high. The probability the Ivory-billed woodpecker is extant depended on whether recent controversial sightings were accepted. Without the recent controversial sightings, it was optimal to declare extinction of the species in 1965 at the latest. Accepting the recent controversial sightings, it was optimal to continue monitoring and managing until 2032 at the latest. The mountain pygmy-possum is currently extant, with a rapidly declining sighting rate. It was optimal to conduct as many as 66 surveys without sighting before declaring the species extinct. The probability of persistence remained high even after many surveys without sighting because it was difficult to determine whether the species was extinct or undetected. If the value of management is high enough, continued intervention can be cost-effective even if the species is likely to be extinct.
Removing pests from islands, and then keeping them pest free, is a common management goal. Given ... more Removing pests from islands, and then keeping them pest free, is a common management goal. Given that goal we face a decision: how much effort should we invest in quarantine to reduce the risk of a pest arriving vs. surveillance, looking for the pest on the island with the view of eradicating it before it gets out of control. We use models of an island under threat of invasion by a pest (animal, plant or disease) and a cost minimisation approach to optimally allocate management resources between quarantine and surveillance. In the optimal allocations joint investment in both quarantine and surveillance is uncommon. Investment in quarantine is optimal if quarantine is more effective than surveillance or if large costs associated with pest impact and eradication are incurred at low pest density. Investment in quarantine is also favoured as our ability to eradicate a pest declines. Surveillance is optimal if it is considerably more cost-effective than quarantine and we can generate significant savings through early detection of the pest population. We illustrate how theses models are useful ways to examine these trade-offs by applying the model to the prevention of black rat (Rattus rattus) invasion on Barrow Island, Western Australia. Our model predicts an optimal strategy different to the management strategy currently being used on the island. We suggest that this is due to a risk-averse tendency in managers and the difficulty of estimating costs that combine management, environmental and social factors.
Adaptive management has a long history in natural resource management literature, but despite thi... more Adaptive management has a long history in natural resource management literature, but despite this few practitioners have developed adaptive strategies to conserve threatened species. Active adaptive management provides a framework for valuing learning by measuring the degree to which it improves long-run management outcomes. The challenge of an active adaptive approach is to find the correct balance between gaining knowledge to improve management in the future and achieving the best short-term outcome based on current knowledge. We develop and analyze a framework for active adaptive management of a threatened species. Our case study concerns a novel facial tumour disease affecting the Australian threatened species Sarcophilus harrisii; the Tasmanian devil. We use stochastic dynamic programming with Bayesian updating to identify the management strategy that maximizes the Tasmanian devil population growth rate, taking into account improvements to management through learning to better understand disease latency and the relative effectiveness of three competing management options. Exactly which management action we choose each year is driven by the credibility of competing hypotheses about disease latency and by the 48 population growth rate predicted by each hypothesis under the competing management actions. We discover that the optimal combination of management actions depends on the number of sites available and the time remaining to implement management. Our approach to active adaptive management provides a framework to identify the optimal amount of effort to invest in learning to achieve long-run conservation objectives.
1. Invasive species threaten biodiversity, and their eradication is desirable whenever possible. ... more 1. Invasive species threaten biodiversity, and their eradication is desirable whenever possible. Deciding whether an invasive species has been successfully eradicated is difficult because of imperfect detection. Two previous studies [Regan et al., Ecology Letters, 9 (2006), 759; Rout et al., Journal of Applied Ecology, 46 (2009), 110] have used a decision theory framework to minimize the total expected cost by finding the number of consecutive surveys without detection (absent surveys) after which a species should be declared eradicated. These two studies used different methods to calculate the probability that the invasive species is present when it has not been detected for a number of surveys. However, neither acknowledged uncertainty in this probability, which can lead to suboptimal solutions.
2. We use info-gap theory to examine the effect of uncertainty in the probability of presence on decision-making. Instead of optimizing performance for an assumed system model, info-gap theory finds the decision among the alternatives considered that is most robust to model uncertainty while meeting a set performance requirement. This is the first application of info-gap theory to invasive species management.
3. We find the number of absent surveys after which eradication should be declared to be relatively robust to uncertainty in the probability of presence. This solution depends on the nominal estimate of the probability of presence, the performance requirement and the cost of surveying, but not the cost of falsely declaring eradication.
4. More generally, to be robust to uncertainty in the probability of presence, managers should conduct at least as many surveys as the number that minimizes the total expected cost. This holds for any nominal model of the probability of presence.
5. Synthesis and applications. Uncertainty is pervasive in ecology and conservation biology. It is therefore crucial to consider its impact on decision-making; info-gap theory provides a way to do this. We find a simple expression for the info-gap solution, which could be applied by eradication managers to make decisions that are robust to uncertainty in the probability of presence.
1. A major challenge for eradication managers is deciding when a programme can be deemed successf... more 1. A major challenge for eradication managers is deciding when a programme can be deemed successful. Regan
et al. (2006) were the first to pose this problem within a decision theory framework, minimizing the net expected cost of the decision. The optimal time to declare eradication was based on the number of consecutive surveys in which the species was not found (‘absent surveys’). Their formulation used estimates of detectability and persistence – parameters that are often difficult to estimate – to calculate the probability that the invasive species is still present.
2. Here we use a similar decision-making framework but instead predict presence based on the pattern of sightings, using a method developed by Solow (1993a) that assumes a constant sighting rate. This method does not require estimates of detectability and persistence. We find the number of absent surveys after which eradication should be declared, using three approaches: a stochastic dynamic program, which finds the exact optimal solution, a rule of thumb, and an approximation. We then compare these results with a method assuming a declining sighting rate.
3. Both the rule of thumb and approximation give results that are close to the exact optimal solution. The rule of thumb with the declining sighting rate method generally gives a larger optimal number of absent surveys.
4. Synthesis and applications. Analysing this problem within a decision theory framework enables us to minimize the expected cost of declaring eradication. By using the more readily available sighting data, we make this framework applicable to a wider range of invasive species. Our approximation is a simple calculation, making it an accessible tool that could be applied by managers of eradication programmes for invasive species.
Conservation management actions and decisions are often defined by the location of ecological bou... more Conservation management actions and decisions are often defined by the location of ecological boundaries, for example, the present range of invasive or threatened species. The position of these boundaries can be cryptic, and managers must therefore directly sample sites, an expensive and time consuming process. While accurate boundary location techniques have been considered by ecological theorists, the issue of cost-effective, or optimal boundary location has not. We propose a general framework for boundary location which incorporates both cost-efficiency and uncertainty. To illustrate its application, we use it to help locate an infectious disease front in the endangered Tasmanian devil population. The method ensures optimal spatial sampling by maximizing the expected information gained from each sample. When resources are limited, our method provides more accurate estimates of the boundary location than traditional sampling protocols. Using a formal decision theory sampling design encourages economically efficient actions, and provides defensible and transparent rationale for management actions.
Active adaptive management (AAM) is an approach to wildlife management that acknowledges our impe... more Active adaptive management (AAM) is an approach to wildlife management that acknowledges our imperfect understanding of natural systems and allows for some resolution of our uncertainty. Such learning may be characterized by risky strategies in the short term. Experimentation is only considered acceptable if it is expected to be repaid by increased returns in the long term, generated by an improved understanding of the system. By setting AAM problems within a decision theory framework, we can find this optimal balance between achieving our objectives in the short term and learning for the long term.We apply this approach to managing the translocation of the bridled nailtail wallaby (Onychogalea fraenata), an endangered species from Queensland, Australia. Our task is to allocate captive-bred animals, between two sites or populations to maximize abundance at the end of the translocation project. One population, at the original site of occupancy, has a known growth rate. A population potentially could be established at a second site of suitable habitat, but we can only learn the growth rate of this new population by monitoring translocated animals. We use a mathematical programming technique called stochastic dynamic programming, which determines optimal management decisions for every possible management trajectory. We find optimal strategies under active and passive adaptive management, which enables us to examine the balance between learning and managing directly. Learning is more often optimal when we have less prior information about the uncertain population growth rate at the new site, when the growth rate at the original site is low, and when there is substantial time remaining in the translocation project. Few studies outside the area of optimal harvesting have framed AAM within a decision theory context. This is the first application to threatened species translocation.
Due to their impact on natural systems, eradication of invasive species is preferable whenever po... more Due to their impact on natural systems, eradication of invasive species is preferable whenever possible. Deciding whether a species has been successfully eradicated is difficult because of imperfect detection. There are two ways that the decision to declare eradication can go wrong: if the species is declared eradicated when still present its population may grow undetected, incurring large economic and environmental costs; alternatively, continuing surveys when the species is already gone involves unnecessary survey costs. By analyzing this dilemma as an explicit decision problem, managers can balance the risk of these errors, and above all, make decisions that are transparent and justifiable. In this paper I summarize current work in the development and application of decision theory for declaring eradication.
1. Invasive plants have negative impacts on ecosystems worldwide. Several ecological studies have... more 1. Invasive plants have negative impacts on ecosystems worldwide. Several ecological studies have identified disturbance as a causative mechanism of plant invasions. Changes to natural disturbances and/or newly imposed disturbances can favour an invader over native species especially those that are better adapted to prior conditions. 2. To link the disturbance ecology of invasives to their management, we investigated the benefit of incorporating actions that manipulate disturbance (natural or imposed) into control efforts. We developed a simple model that describes the dynamics of an invader whose establishment is preferentially favoured by disturbance. 3. The model includes the probability of disturbance differentially affecting sites occupied by natives and invaders. Invaded sites are disturbed by alternative control measures, which act to kill and/or remove above-ground biomass and reduce the seed bank. We couched the model in a decision theory tool, stochastic dynamic programming, and applied it to the management of Mimosa pigra, a pan-tropical invasive perennial shrub. 4. We found that targeting the above-ground biomass of the invader (current population) was optimal when the probability of disturbance of native sites and the invader seed bank size were low to moderate. When both the rate of disturbance of native sites and invader seed banks were high, the best measure was that with the highest probability of reducing the seed bank (future populations). This measure was optimal despite its trade-off of having the highest probability of reinvasion. 5. Synthesis and applications. Manipulation of disturbance regimes in both native and invaded sites can simplify control efforts. If there is a high probability that native vegetation will be disturbed, then management efforts should focus on future populations by attempting to reduce the size of the invader seed bank. This complicates control, as seed bank size is difficult to measure and reducing it requires intensive actions, which are likely to also negatively affect the seed bank of native species. If, however, the probability of disturbance of native sites can be reduced, practitioners can shift control from future populations to the current population, which is more straightforward to implement and monitor.
Translocation is a useful management option for conservation of threatened animal species. It can... more Translocation is a useful management option for conservation of threatened animal species. It can be used to increase the range of a species, augment the numbers in a critical population, or establish new populations and hence spread the risk of extinction through local catastrophes. As it is an important and expensive conservation tool, translocation management decisions must be carefully considered, with the objective of the translocation project in mind. By analysing the translocation problem within a decision-theory framework, we find optimal management decisions that are rational and transparent. We illustrate our approach using a case study of the bridled nailtailwallaby (Onychogalea fraenata). Our particular translocation question is: if we have a set number ofwallabies to translocate in each time period and two translocation sites, how many wallabies should we put at each site given the state of each population to maximise the benefit to the species? We model the translocated populations with first-order Markov chain stochastic population models, and use stochastic dynamic programming to determine the optimal management decisions. We look at two sites with different growth rates – one increasing and one decreasing – and compare the optimal strategies for two different objective functions. The first is a long-term persistence objective function, which maximises the persistence of translocated populations a large number of time steps after the end of the translocation program. The second maximises total population size at the end of the translocation program. Although these objective functions are similar, they generate surprisingly different optimal translocation strategies. When maximising the long-term persistence of the translocated populations, translocation decisions are not important as long as an increasing population is established. This indicates that site quality – rather than the number and timing of translocations – primarily determines the long-term persistence of populations. When maximising total population size, the optimal strategy is to add to the increasing population unless it is above a size where it is likely to reach its carrying capacity over the planning time frame. As translocation decisions are important in fulfilling the objective, this objective function is more useful in creating practical advice for translocation managers. The discrepancy between the optimal strategies given by the two objectives demonstrates the importance of careful consideration when specifying the goals of a project. This observation applies not only to translocation programs, but any project where clear decision-making is needed.
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Papers by Tracy Rout
2. We use info-gap theory to examine the effect of uncertainty in the probability of presence on decision-making. Instead of optimizing performance for an assumed system model, info-gap theory finds the decision among the alternatives considered that is most robust to model uncertainty while meeting a set performance requirement. This is the first application of info-gap theory to invasive species management.
3. We find the number of absent surveys after which eradication should be declared to be relatively robust to uncertainty in the probability of presence. This solution depends on the nominal estimate of the probability of presence, the performance requirement and the cost of surveying, but not the cost of falsely declaring eradication.
4. More generally, to be robust to uncertainty in the probability of presence, managers should conduct at least as many surveys as the number that minimizes the total expected cost. This holds for any nominal model of the probability of presence.
5. Synthesis and applications. Uncertainty is pervasive in ecology and conservation biology. It is therefore crucial to consider its impact on decision-making; info-gap theory provides a way to do this. We find a simple expression for the info-gap solution, which could be applied by eradication managers to make decisions that are robust to uncertainty in the probability of presence.
et al. (2006) were the first to pose this problem within a decision theory framework, minimizing the net expected cost of the decision. The optimal time to declare eradication was based on the number of consecutive surveys in which the species was not found (‘absent surveys’). Their formulation used estimates of detectability and persistence – parameters that are often difficult to estimate – to calculate the probability that the invasive species is still present.
2. Here we use a similar decision-making framework but instead predict presence based on the pattern of sightings, using a method developed by Solow (1993a) that assumes a constant sighting rate. This method does not require estimates of detectability and persistence. We find the number of absent surveys after which eradication should be declared, using three approaches: a stochastic dynamic program, which finds the exact optimal solution, a rule of thumb, and an approximation. We then compare these results with a method assuming a declining sighting rate.
3. Both the rule of thumb and approximation give results that are close to the exact optimal solution. The rule of thumb with the declining sighting rate method generally gives a larger optimal number of absent surveys.
4. Synthesis and applications. Analysing this problem within a decision theory framework enables us to minimize the expected cost of declaring eradication. By using the more readily available sighting data, we make this framework applicable to a wider range of invasive species. Our approximation is a simple calculation, making it an accessible tool that could be applied by managers of eradication programmes for invasive species.
2. To link the disturbance ecology of invasives to their management, we investigated the benefit of incorporating actions that manipulate disturbance (natural or imposed) into control efforts. We developed a simple model that describes the dynamics of an invader whose establishment is preferentially favoured by disturbance.
3. The model includes the probability of disturbance differentially affecting sites occupied by natives and invaders. Invaded sites are disturbed by alternative control measures, which act to kill and/or remove above-ground biomass and reduce the seed bank. We couched the model in a decision
theory tool, stochastic dynamic programming, and applied it to the management of Mimosa pigra, a pan-tropical invasive perennial shrub.
4. We found that targeting the above-ground biomass of the invader (current population) was optimal when the probability of disturbance of native sites and the invader seed bank size were low to moderate. When both the rate of disturbance of native sites and invader seed banks were high, the best measure was that with the highest probability of reducing the seed bank (future populations). This measure was optimal despite its trade-off of having the highest probability of reinvasion.
5. Synthesis and applications. Manipulation of disturbance regimes in both native and invaded sites can simplify control efforts. If there is a high probability that native vegetation will be disturbed, then management efforts should focus on future populations by attempting to reduce the size of the invader seed bank. This complicates control, as seed bank size is difficult to measure and reducing it requires intensive actions, which are likely to also negatively affect the seed bank of native species. If, however, the probability of disturbance of native sites can be reduced, practitioners can shift control
from future populations to the current population, which is more straightforward to implement and monitor.
2. We use info-gap theory to examine the effect of uncertainty in the probability of presence on decision-making. Instead of optimizing performance for an assumed system model, info-gap theory finds the decision among the alternatives considered that is most robust to model uncertainty while meeting a set performance requirement. This is the first application of info-gap theory to invasive species management.
3. We find the number of absent surveys after which eradication should be declared to be relatively robust to uncertainty in the probability of presence. This solution depends on the nominal estimate of the probability of presence, the performance requirement and the cost of surveying, but not the cost of falsely declaring eradication.
4. More generally, to be robust to uncertainty in the probability of presence, managers should conduct at least as many surveys as the number that minimizes the total expected cost. This holds for any nominal model of the probability of presence.
5. Synthesis and applications. Uncertainty is pervasive in ecology and conservation biology. It is therefore crucial to consider its impact on decision-making; info-gap theory provides a way to do this. We find a simple expression for the info-gap solution, which could be applied by eradication managers to make decisions that are robust to uncertainty in the probability of presence.
et al. (2006) were the first to pose this problem within a decision theory framework, minimizing the net expected cost of the decision. The optimal time to declare eradication was based on the number of consecutive surveys in which the species was not found (‘absent surveys’). Their formulation used estimates of detectability and persistence – parameters that are often difficult to estimate – to calculate the probability that the invasive species is still present.
2. Here we use a similar decision-making framework but instead predict presence based on the pattern of sightings, using a method developed by Solow (1993a) that assumes a constant sighting rate. This method does not require estimates of detectability and persistence. We find the number of absent surveys after which eradication should be declared, using three approaches: a stochastic dynamic program, which finds the exact optimal solution, a rule of thumb, and an approximation. We then compare these results with a method assuming a declining sighting rate.
3. Both the rule of thumb and approximation give results that are close to the exact optimal solution. The rule of thumb with the declining sighting rate method generally gives a larger optimal number of absent surveys.
4. Synthesis and applications. Analysing this problem within a decision theory framework enables us to minimize the expected cost of declaring eradication. By using the more readily available sighting data, we make this framework applicable to a wider range of invasive species. Our approximation is a simple calculation, making it an accessible tool that could be applied by managers of eradication programmes for invasive species.
2. To link the disturbance ecology of invasives to their management, we investigated the benefit of incorporating actions that manipulate disturbance (natural or imposed) into control efforts. We developed a simple model that describes the dynamics of an invader whose establishment is preferentially favoured by disturbance.
3. The model includes the probability of disturbance differentially affecting sites occupied by natives and invaders. Invaded sites are disturbed by alternative control measures, which act to kill and/or remove above-ground biomass and reduce the seed bank. We couched the model in a decision
theory tool, stochastic dynamic programming, and applied it to the management of Mimosa pigra, a pan-tropical invasive perennial shrub.
4. We found that targeting the above-ground biomass of the invader (current population) was optimal when the probability of disturbance of native sites and the invader seed bank size were low to moderate. When both the rate of disturbance of native sites and invader seed banks were high, the best measure was that with the highest probability of reducing the seed bank (future populations). This measure was optimal despite its trade-off of having the highest probability of reinvasion.
5. Synthesis and applications. Manipulation of disturbance regimes in both native and invaded sites can simplify control efforts. If there is a high probability that native vegetation will be disturbed, then management efforts should focus on future populations by attempting to reduce the size of the invader seed bank. This complicates control, as seed bank size is difficult to measure and reducing it requires intensive actions, which are likely to also negatively affect the seed bank of native species. If, however, the probability of disturbance of native sites can be reduced, practitioners can shift control
from future populations to the current population, which is more straightforward to implement and monitor.