The Value of Information in Invasive Species Management

Resource /Energy Economics and Policy,

Valuing Monitoring Networks for Invasive Species: The Case of Soybean Rust

Crop Production/Industries,

The value of information in conservation planning

Conservation planning studies at small scales such as forest stands and below are uncommon. However, for retention forestry, developed during the last two decades and with current wide and increasing application in boreal and temperate regions, the need for cost-effective selection of individual trees is evident. In retention forestry certain trees are left at final harvest to promote flora and fauna. There is also a scarcity of studies on information costs and how these relate to the cost-effectiveness of conservation. We addressed both of these issues by studying whether decisions about the retention of aspen Populus tremula L. trees can be made more cost-effectively by including information about tree characteristics. We analyzed data from 12 recently harvested stands in middle Sweden containing 131 epiphytic lichen species (a biodiversity proxy) on 360 aspen trees. We related the presence of lichen species to bark and stem attributes and used those relationships to prioritize trees for retention. We estimated the value of using different sets of survey information (lichens, tree characteristics) to select retention trees to achieve various conservation goals. Depending on species or species groups of interest, and the type of tree information being collected, the value of collecting the information is up to 20% of the total value of all potential retention trees, which, given current labor costs, allows up to four hours for planning and selecting the right trees on an average-sized clearcut. The current practice of almost randomly selecting aspen trees to retain at final harvest can be improved by adding easily collected information on tree characteristics, such as black-colored bark, slow tree growth, inclining stems and speckled bark. This can lead to attainment of a given level of a conservation goal (like maximizing the number of lichen species of conservation concern) with fewer retention trees. Inventory of tree information often can be performed quickly, and if part of the gains from using such information to guide tree selection would be spent on additional conservation efforts, this would benefit biodiversity. Studies on more organism groups and tree species are needed to increase the applicability of results. (C) 2014 The Authors. Published by Elsevier B.V

PROVIDING EQUITABLE SPATIAL DISTRIBUTION OF PROTECTED NATURAL AREAS IN A METROPOLITAN SETTING: AN APPLICATION OF THE LOCATION SET-COVERING PROBLEM

We use the location set covering problem to define a natural area site selection model for use in the Chicago region. This framework allows us to explicitly consider the equity of site distribution by stipulating that each population center has access to a recreational space within a specified distance.Land Economics/Use,

EXPLORING GOAL TRADEOFFS IN METROPOLITAN NATURAL AREA PROTECTION

This study examines the issue of natural area protection in an urban environment. We report on the results of interviews conducted with a wide range of land use planners in the Chicago region. Of particular interest are the unique goals and challenges of land acquisition programs in a metropolitan area.Resource /Energy Economics and Policy,

Optimal timber harvesting in uneven-aged forest stands : a discrete-time optimal-control approach

The purpose of this dissertation is to formulate, analyze and numerically solve the dynamic harvesting problem for uneven-aged stands. The problem is to find the optimal numbers of trees to remove from diameter classes over a finite time horizon and is formulated as a discrete-time optimal-control problem with bounded control variables and free terminal point. A solution algorithm called the method of steepest descent is described and demonstrated with a whole-stand/diameter-class simulator for Wisconsin hardwood stands. Optimal management regimes that maximize present net worth (PNW) from harvests taken on a 5-year cutting cycle during a 150-year time horizon are developed for three stumpage value functions. Harvest regimes derived with the gradient method contradicted optimal steady-state management regimes determined with static analysis. Pontryagin's maximum principle is used to establish optimality conditons for the dynamic and static optimization problems. Comparison of these conditions shows that for a stand with any initial diameter distribution: (1) the optimal transition regime does not converge to the steady state that maximizes land expectation value defined by the Faustmann equation; (2) the PNW of the optimal transition and steady-state regime is greater than the PNW of the statically determined regime; and (3) the optimal steady-state regime is invariant. These results invalidate the use of investment-efficient diameter distributions. The gradient method produces stationary solutions for harvest control variables in the first period and beyond; however, because of large discount factors in distant periods, the algorithm fails to provide stationary solutions for long-term management within reasonable execution times. To avoid this problem, a restart procedure that takes advantage of the stability of the first-period solution and the sequential nature of the problem is developed. An economic model for harvesting forest stands is presented and used to contrast the two major timber harvesting systems: even-aged and uneven-aged management. In contrast to even-aged management, the value of uneven-aged stand harvesting cannot be separated into independent components for stand value and land value. Thus, conclusions about the most profitable harvesting system depend on the joint productivity of the land and existing timber. This result is demonstrated by developing optimal management regimes for Arizona ponderosa pine (Pinus ponderosa Laws.) stands

Optimizing Reserve Expansion For Disjunct Populations Of San Joaquin Kit Fox

Expanding habitat protection is a common strategy for species conservation. We present a model to optimize the expansion of reserves for disjunct populations of an endangered species. The objective is to maximize the expected number of surviving populations subject to budget and habitat constraints. The model accounts for benefits of reserve expansion in terms of likelihood of persistence of each population and monetary cost. Solving the model with incrementally higher budgets helps prioritize sites for expansion and produces a cost curve showing funds required for incremental increases in the objective. We applied the model to the problem of allocating funds among eight reserves for the endangered San Joaquin kit fox (Vulpes macrotis mutica) in California, USA. The priorities for reserve expansion were related to land cost and amount of already-protected habitat at each site. Western Kern and Ciervo-Panoche sites received highest priority because land costs were low and moderate amounts of already-protected habitat resulted in large reductions in extinction risk for small increments of habitat protection. The sensitivity analysis focused on the impacts of kit fox reproductive success and home range in non-native grassland sites. If grassland habitat is lower quality than brushland habitat resulting in higher annual variation in reproductive success or larger home ranges, then protecting habitat at the best grassland site (Ciervo-Panoche) is not cost–efficient relative to shrubland sites (Western Kern, Antelope Plain, Carrizo Plain). Finally, results suggested that lowest priority should be given to three relatively high-cost grassland sites (Camp Roberts, Contra Costa, and Western Madera) because protecting habitat at those sites would be expensive and have little effect on the expected number of surviving kit fox populations

Network metrics can guide nearly-optimal management of invasive species at large scales

Invasive species harm biodiversity and ecosystem services, with global economic costs of invasions exceeding $40 billion annually. Widespread invasions are a particular challenge because they involve large spatial scales with many interacting components. In these contexts, typical optimization-based approaches to management may fail due to computational or data constraints. Here we evaluate an alternative solution that leverages network science, representing the invasion as occurring across a network of connected sites and using network metrics to prioritize sites for intervention. Such heuristic network-guided methods require less data and are less computationally intensive than optimization methods, yet network-guided approaches have not been bench-marked against optimal solutions for real-world invasive species management problems. We provide the first comparison of the performance of network-guided management relative to optimal solutions for invasive species, examining the placement of watercraft inspection stations for preventing spread of invasive zebra mussels through recreational boat movement within 58 Minnesota counties in the United States. To additionally test the promise of network-based approaches in limited data contexts, we evaluate their performance when using only partial data on network structure and invaded status. Metric-based approaches can achieve a median of 100% of optimal performance with full data. Even with partial data, 80% of optimal performance is achievable. Finally, we show that performance of metric-guided management improves for counties with denser and larger networks, suggesting this approach is viable for large-scale invasions. Together, our results suggest network metrics are a promising approach to guiding management actions for large-scale invasions.Comment: 29 pages, 8 figures, 3 table

Deploying initial attack resources for wildfire suppression: spatial coordination, budget constraints, and capacity constraints

We combine a scenario-based, standard-response optimization model with stochastic simulation to improve the efficiency of resource deployment for initial attack on wildland fires in three planning units in California. The optimization model minimizes the expected number of fires that do not receive a standard response-defined as the number of resources by type that must arrive at the fire within a specified time limit-subject to budget and station capacity constraints and uncertainty about the daily number and location of fires. We use the California Fire Economics Simulator to predict the number of fires not contained within initial attack modeling limits. Compared with the current deployment, the deployment obtained with optimization shifts resources from the planning unit with highest fire load to the planning unit with the highest standard response requirements but leaves simulated containment success unchanged. This result suggests that, under the current budget and capacity constraints, a range of deployments may perform equally well in terms of fire containment. Resource deployments that result from relaxing constraints on station capacity achieve greater containment success by encouraging consolidation of resources into stations with high dispatch frequency, thus increasing the probability of resource availability on high fire count days.Nous combinons un modèle d'optimisation de la réponse standard basée sur différents scénarios a` une simulation stochastique pour améliorer l'efficacité du déploiement des ressources lors de l'attaque initiale des feux de forêt dans trois unités de gestion en Californie. Le modèle d'optimisation minimise le nombre attendu de feux qui ne reçoivent pas une réponse standard (définie comme la quantité de ressources de chaque type qui doit être déployée `a l'intérieur d'une certaine limite de temps) a` cause de contraintes de budget et de capacité des stations et de l'incertitude quant au nombre quotidien de feux et `a leur localisation. Nous utilisons le simulateur de l'aspect économique des feux en Californie pour prédire le nombre de feux qui ne sont pas maîtrisés a` l'intérieur des limites déterminées par la modélisation de l'attaque initiale. Comparativement au déploie-ment actuel, le déploiement obtenu par optimisation déplace des ressources de l'unité de gestion qui a le fardeau d'intervention le plus lourd vers l'unité de gestion qui a les exigences de réponse standard les plus élevées mais laisse le succès simulé de la maîtrise des feux inchangé. Ce résultat indique que dans les conditions actuelles de contraintes de budget et de capacité, différents déploiements peuvent avoir une aussi bonne performance en termes de maîtrise du feu. Les déploiements de ressources qui résultent de la réduction des contraintes de capacité des stations ont plus de succès dans la maîtrise des feux en favorisant la consolidation des ressources dans les stations qui ont une fréquence élevée de déploiement, augmentant par conséquent la probabilité que les ressources soient disponibles les jours où le nombre de feux est élevé. [Traduit par la Rédaction]Keywords: Allocation, Forest fires, Airtankers, Wildland fire suppression, Management, California, Stochastic representation, Containment, Protection planning mode