Optimal allocation of conservation effort among subpopulations of a threatened species: How important is patch quality?

Money is often a limiting factor in conservation, and attempting to conserve endangered species can be costly. Consequently, a framework for optimizing fiscally constrained conservation decisions for a single species is needed. In this paper we find the optimal budget allocation among isolated subpopulations of a threatened species to minimize local extinction probability. We solve the problem using stochastic dynamic programming, derive a useful and simple alternative guideline for allocating funds, and test its performance using forward simulation. The model considers subpopulations that persist in habitat patches of differing quality, which in our model is reflected in different relationships between money invested and extinction risk. We discover that, in most cases, subpopulations that are less efficient to manage should receive more money than those that are more efficient to manage, due to higher investment needed to reduce extinction risk. Our simple investment guideline performs almost as well as the exact optimal strategy. We illustrate our approach with a case study of the management of the Sumatran tiger, Panthera tigris sumatrae, in Kerinci Seblat National Park (KSNP), Indonesia. We find that different budgets should be allocated to the separate tiger subpopulations in KSNP. The subpopulation that is not at risk of extinction does not require any management investment. Based on the combination of risks of extinction and habitat quality, the optimal allocation for these particular tiger subpopulations is an unusual case: subpopulations that occur in higher-quality habitat (more efficient to manage) should receive more funds than the remaining subpopulation that is in lower-quality habitat. Because the yearly budget allocated to the KSNP for tiger conservation is small, to guarantee the persistence of all the subpopulations that are currently under threat we need to prioritize those that are easier to save. When allocating resources among subpopulations of a threatened species, the combined effects of differences in habitat quality, cost of action, and current subpopulation probability of extinction need to be integrated. We provide a useful guideline for allocating resources among isolated subpopulations of any threatened species. © 2010 by the Ecological Society of America.

Optimal eradication: When to stop looking for an invasive plant

The notion of being sure that you have completely eradicated an invasive species is fanciful because of imperfect detection and persistent seed banks. Eradication is commonly declared either on an ad hoc basis, on notions of seed bank longevity, or on setting arbitrary thresholds of 1% or 5% confidence that the species is not present. Rather than declaring eradication at some arbitrary level of confidence, we take an economic approach in which we stop looking when the expected costs outweigh the expected benefits. We develop theory that determines the number of years of absent surveys required to minimize the net expected cost. Given detection of a species is imperfect, the optimal stopping time is a trade-off between the cost of continued surveying and the cost of escape and damage if eradication is declared too soon. A simple rule of thumb compares well to the exact optimal solution using stochastic dynamic programming. Application of the approach to the eradication programme of Helenium amarum reveals that the actual stopping time was a precautionary one given the ranges for each parameter. © 2006 Blackwell Publishing Ltd/CNRS.

Optimizing search strategies for invasive pests: Learn before you leap

Strategic searching for invasive pests presents a formidable challenge for conservation managers. Limited funding can necessitate choosing between surveying many sites cursorily, or focussing intensively on fewer sites. While existing knowledge may help to target more likely sites, e.g. with species distribution models (maps), this knowledge is not flawless and improving it also requires management investment. 2.In a rare example of trading-off action against knowledge gain, we combine search coverage and accuracy, and its future improvement, within a single optimisation framework. More specifically we examine under which circumstances managers should adopt one of two search-and-control strategies (cursory or focussed), and when they should divert funding to improving knowledge, making better predictive maps that benefit future searches. 3.We use a family of Receiver Operating Characteristic curves to reflect the quality of maps that direct search efforts. We demonstrate our framework by linking these to a logistic model of invasive spread such as that for the red imported fire ant Solenopsis invicta in south-east Queensland, Australia. 4.Cursory widespread searching is only optimal if the pest is already widespread or knowledge is poor, otherwise focussed searching exploiting the map is preferable. For longer management timeframes, eradication is more likely if funds are initially devoted to improving knowledge, even if this results in a short-term explosion of the pest population. 5.Synthesis and applications. By combining trade-offs between knowledge acquisition and utilization, managers can better focus - and justify - their spending to achieve optimal results in invasive control efforts. This framework can improve the efficiency of any ecological management that relies on predicting occurrence. © 2010 The Authors. Journal of Applied Ecology © 2010 British Ecological Society.

Subpopulation triage: How to allocate conservation effort among populations

Threatened species often exist in a small number of isolated subpopulations. Given limitations on conservation spending, managers must choose from strategies that range from managing just one subpopulation and risking all other subpopulations to managing all subpopulations equally and poorly, thereby risking the loss of all subpopulations. We took an economic approach to this problem in an effort to discover a simple rule of thumb for optimally allocating conservation effort among subpopulations. This rule was derived by maximizing the expected number of extant subpopulations remaining given n subpopulations are actually managed. We also derived a spatiotemporally optimized strategy through stochastic dynamic programming. The rule of thumb suggested that more subpopulations should be managed if the budget increases or if the cost of reducing local extinction probabilities decreases. The rule performed well against the exact optimal strategy that was the result of the stochastic dynamic program and much better than other simple strategies (e.g., always manage one extant subpopulation or half of the remaining subpopulation). We applied our approach to the allocation of funds in 2 contrasting case studies: reduction of poaching of Sumatran tigers (Panthera tigris sumatrae) and habitat acquisition for San Joaquin kit foxes (Vulpes macrotis mutica). For our estimated annual budget for Sumatran tiger management, the mean time to extinction was about 32 years. For our estimated annual management budget for kit foxes in the San Joaquin Valley, the mean time to extinction was approximately 24 years. Our framework allows managers to deal with the important question of how to allocate scarce conservation resources among subpopulations of any threatened species. © 2008 Society for Conservation Biology.

Energy efficient home with price sensitive stochastically programmable TCAs

Introduction of dynamic pricing in present retail market, considerably affects customers with an increased cost of energy consumption. Therefore, customers are enforced to control their loads according to price variation. This paper proposes a new technique of Home Energy Management, which helps customers to minimize their cost of energy consumption by appropriately controlling their loads. Thermostatically Controllable Appliances (TCAs) such as air conditioner and water heater are focused in this study, as they consume more than 50% of the total household energy consumption. The control process includes stochastic dynamic programming, which incorporated uncertainties in price and demand variation. It leads to an accurate selection of appliance settings. It is followed by a real time control of selected appliances with its optimal settings. Temperature set points of TCAs are adjusted based on price droop which is a reflection of actual cost of energy consumption. Customer satisfaction is maintained within limits using constraint optimization. It is showed that considerable energy savings is achieved.

Priority threat management of non-native plants to maintain ecosystem integrity across heterogeneous landscapes

Invasive non-native plants have negatively impacted on biodiversity and ecosystem functions world-wide. Because of the large number of species, their wide distributions and varying degrees of impact, we need a more effective method for prioritizing control strategies for cost-effective investment across heterogeneous landscapes. Here, we develop a prioritization framework that synthesizes scientific data, elicits knowledge from experts and stakeholders to identify control strategies, and appraises the cost-effectiveness of strategies. Our objective was to identify the most cost-effective strategies for reducing the total area dominated by high-impact non-native plants in the Lake Eyre Basin (LEB). We use a case study of the ˜120 million ha Lake Eyre Basin that comprises some of the most distinctive Australian landscapes, including Uluru-Kata Tjuta National Park. More than 240 non-native plant species are recorded in the Lake Eyre Basin, with many predicted to spread, but there are insufficient resources to control all species. Lake Eyre Basin experts identified 12 strategies to control, contain or eradicate non-native species over the next 50 years. The total cost of the proposed Lake Eyre Basin strategies was estimated at AU$1·7 billion, an average of AU$34 million annually. Implementation of these strategies is estimated to reduce non-native plant dominance by 17 million ha – there would be a 32% reduction in the likely area dominated by non-native plants within 50 years if these strategies were implemented. The three most cost-effective strategies were controlling Parkinsonia aculeata, Ziziphus mauritiana and Prosopis spp. These three strategies combined were estimated to cost only 0·01% of total cost of all the strategies, but would provide 20% of the total benefits. Over 50 years, cost-effective spending of AU$2·3 million could eradicate all non-native plant species from the only threatened ecological community within the Lake Eyre Basin, the Great Artesian Basin discharge springs. Synthesis and applications. Our framework, based on a case study of the ˜120 million ha Lake Eyre Basin in Australia, provides a rationale for financially efficient investment in non-native plant management and reveals combinations of strategies that are optimal for different budgets. It also highlights knowledge gaps and incidental findings that could improve effective management of non-native plants, for example addressing the reliability of species distribution data and prevalence of information sharing across states and regions.

Ergodic control of partially observed Markov chains

The ergodic or long-run average cost control problem for a partially observed finite-state Markov chain is studied via the associated fully observed separated control problem for the nonlinear filter. Dynamic programming equations for the latter are derived, leading to existence and characterization of optimal stationary policies.

An optimal design for screening trials

Yao, Begg, and Livingston (1996, Biometrics 52, 992-1001) considered the optimal group size for testing a series of potentially therapeutic agents to identify a promising one as soon as possible for given error rates. The number of patients to be tested with each agent was fixed as the group size. We consider a sequential design that allows early acceptance and rejection, and we provide an optimal strategy to minimize the sample sizes (patients) required using Markov decision processes. The minimization is under the constraints of the two types (false positive and false negative) of error probabilities, with the Lagrangian multipliers corresponding to the cost parameters for the two types of errors. Numerical studies indicate that there can be a substantial reduction in the number of patients required.

A note on Gittins indexes for pharmaceutical research

The Bernoulli/exponential target process is considered. Such processes have been found useful in modelling the search for active compounds in pharmaceutical research. An inequality is presented which improves a result of Gittins (1989), thus providing a better approximation to the Gittins indices which define the optimal search policy.

Error bounds for calculation of the Gittins indices

For a wide class of semi-Markov decision processes the optimal policies are expressible in terms of the Gittins indices, which have been found useful in sequential clinical trials and pharmaceutical research planning. In general, the indices can be approximated via calibration based on dynamic programming of finite horizon. This paper provides some results on the accuracy of such approximations, and, in particular, gives the error bounds for some well known processes (Bernoulli reward processes, normal reward processes and exponential target processes).

Optimal eradication: when to stop looking for an invasive plant

The notion of being sure that you have completely eradicated an invasive species is fanciful because of imperfect detection and persistent seed banks. Eradication is commonly declared either on an ad hoc basis, on notions of seed bank longevity, or on setting arbitrary thresholds of 1% or 5% confidence that the species is not present. Rather than declaring eradication at some arbitrary level of confidence, we take an economic approach in which we stop looking when the expected costs outweigh the expected benefits. We develop theory that determines the number of years of absent surveys required to minimize the net expected cost. Given detection of a species is imperfect, the optimal stopping time is a trade-off between the cost of continued surveying and the cost of escape and damage if eradication is declared too soon. A simple rule of thumb compares well to the exact optimal solution using stochastic dynamic programming. Application of the approach to the eradication programme of Helenium amarum reveals that the actual stopping time was a precautionary one given the ranges for each parameter.

Optimal Interconnections in the Design of Microprocessors and Digital Systems

This paper recasts the multiple data path assignment problem solved by Torng and Wilhelm by the dynamic programming method [1] into a minimal covering problem following a switching theoretic approach. The concept of bus compatibility for the data transfers is used to obtain the various ways of interconnecting the circuit modules with the minimum number of buses that allow concurrent data transfers. These have been called the feasible solutions of the problem. The minimal cost solutions are obtained by assigning weights to the bus-compatible sets present in the feasible solutions. Minimization of the cost of the solution by increasing the number of buses is also discussed.

Optimal Interconnections in the Design of Microprocessors and Digital Systems

This paper recasts the multiple data path assignment problem solved by Torng and Wilhelm by the dynamic programming method [1] into a minimal covering problem following a switching theoretic approach. The concept of bus compatibility for the data transfers is used to obtain the various ways of interconnecting the circuit modules with the minimum number of buses that allow concurrent data transfers. These have been called the feasible solutions of the problem. The minimal cost solutions are obtained by assigning weights to the bus-compatible sets present in the feasible solutions. Minimization of the cost of the solution by increasing the number of buses is also discussed.

Essays on the Bioeconomics of the Northern Baltic Fisheries

World marine fisheries suffer from economic and biological overfishing: too many vessels are harvesting too few fish stocks. Fisheries economics has explained the causes of overfishing and provided a theoretical background for management systems capable of solving the problem. Yet only a few examples of fisheries managed by the principles of the bioeconomic theory exist. With the aim of bridging the gap between the actual fish stock assessment models used to provide management advice and economic optimisation models, the thesis explores economically sound harvesting from national and international perspectives. Using data calibrated for the Baltic salmon and herring stocks, optimal harvesting policies are outlined using numerical methods. First, the thesis focuses on the socially optimal harvest of a single salmon stock by commercial and recreational fisheries. The results obtained using dynamic programming show that the optimal fishery configuration would be to close down three out of the five studied fisheries. The result is robust to stock size fluctuations. Compared to a base case situation, the optimal fleet structure would yield a slight decrease in the commercial catch, but a recreational catch that is nearly seven times higher. As a result, the expected economic net benefits from the fishery would increase nearly 60%, and the expected number of juvenile salmon (smolt) would increase by 30%. Second, the thesis explores the management of multiple salmon stocks in an international framework. Non-cooperative and cooperative game theory are used to demonstrate different "what if" scenarios. The results of the four player game suggest that, despite the commonly agreed fishing quota, the behaviour of the countries has been closer to non-cooperation than cooperation. Cooperation would more than double the net benefits from the fishery compared to a past fisheries policy. Side payments, however, are a prerequisite for a cooperative solution. Third, the thesis applies coalitional games in the partition function form to study whether the cooperative solution would be stable despite the potential presence of positive externalities. The results show that the cooperation of two out of four studied countries can be stable. Compared to a past fisheries policy, a stable coalition structure would provide substantial economic benefits. Nevertheless, the status of the salmon stocks would not improve significantly. Fourth, the thesis studies the prerequisites for and potential consequences of the implementation of an individual transferable quota (ITQ) system in the Finnish herring fishery. Simulation results suggest that ITQs would result in a decrease in the number of fishing vessels, but enables positive profits to overlap with a higher stock size. The empirical findings of the thesis affirm that the profitability of the studied fisheries could be improved. The evidence, however, indicates that incentives for free riding exist, and thus the most preferable outcome both in economic and biological terms is elusive.

Land leasing, land degradation and agricultural productivity in Finland

This study analysed whether the land tenure insecurity problem has led to a decline in long-term land improvements (liming and phosphorus fertilization) under the Common Agricultural Policy (CAP) and Nordic production conditions in European Union (EU) countries such as Finland. The results suggests that under traditional cash lease contracts, which are encouraged by the existing land leasing regulations and agricultural subsidy programs, the land tenure insecurity problem on leased land reduces land improvements that have a long pay-back period. In particular, soil pH was found to be significantly lower on land cultivated under a lease contract compared to land owned by the farmers themselves. The results also indicate that land improvements could not be reversed by land markets, because land owners would otherwise have carried out land improvements even if not farming by themselves. To reveal the causality between land tenure and land improvements, the dynamic optimisation problem was solved by a stochastic dynamic programming routine with known parameters for one-period returns and transition equations. The model parameters represented Finnish soil quality and production conditions. The decision rules were solved for alternative likelihood scenarios over the continuation of the fixed-term lease contract. The results suggest that as the probability of non-renewal of the lease contract increases, farmers quickly reduce investments in irreversible land improvements and, thereafter, yields gradually decline. The simulations highlighted the observed trends of a decline in land improvements on land parcels that are cultivated under lease contracts. Land tenure has resulted in the neglect of land improvement in Finland. This study aimed to analyze whether these challenges could be resolved by a tax policy that encourages land sales. Using Finnish data, real estate tax and a temporal relaxation on the taxation of capital gains showed some potential for the restructuring of land ownership. Potential sellers who could not be revealed by traditional logit models were identified with the latent class approach. Those landowners with an intention to sell even without a policy change were sensitive to temporal relaxation in the taxation of capital gains. In the long term, productivity and especially productivity growth are necessary conditions for the survival of farms and the food industry in Finland. Technical progress was found to drive the increase in productivity. The scale had only a moderate effect and for the whole study period (1976–2006) the effect was close to zero. Total factor productivity (TFP) increased, depending on the model, by 0.6–1.7% per year. The results demonstrated that the increase in productivity was hindered by the policy changes introduced in 1995. It is also evidenced that the increase in land leasing is connected to these policy changes. Land institutions and land tenure questions are essential in agricultural and rural policies on all levels, from local to international. Land ownership and land titles are commonly tied to fundamental political, economic and social questions. A fair resolution calls for innovative and new solutions both on national and international levels. However, this seems to be a problem when considering the application of EU regulations to member states inheriting divergent landownership structures and farming cultures. The contribution of this study is in describing the consequences of fitting EU agricultural policy to Finnish agricultural land tenure conditions and heritage.