Expanding human population and economic growth have lead to large-scale conversion of natural habitat to human-dominated landscapes with consequent large-scale declines in biodiversity. Conserving biodiversity, while at the same time meeting expanding human needs, is an issue of utmost importance. In this paper we develop a spatially explicit landscape-level model for analyzing the biological and economic consequences of alternative land-use patterns. The spatially-explicit biological model incorporates habitat preferences, area requirements and dispersal ability between habitat patches for terrestrial vertebrate species to predict the likely number of species that will be sustained on the landscape. The spatially explicit economic model incorporates site characteristics and location to predict economic returns in a variety of potential land uses. We use the model to search for efficient land-use patterns that maximize biodiversity conservation objectives for a given level of economic returns, and vice-versa. We apply the model to the Willamette Basin, Oregon, USA. By thinking carefully about the arrangement of activities, we find land-use patterns that sustain high biodiversity and economic returns. Compared to the current land-use pattern, we show that both biodiversity conservation and the value of economic activity could be increased substantially.

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Summary1. Under increasing environmental and financial constraints, ecologists are faced with making decisions about dynamic and uncertain biological systems. To do so, stochastic dynamic programming (SDP) is the most relevant tool for determining an optimal sequence of decisions over time.2. Despite an increasing number of applications in ecology, SDP still suffers from a lack of widespread understanding. The required mathematical and programming knowledge as well as the absence of introductory material provide plausible explanations for this. 3. Here, we fill this gap by explaining the main concepts of SDP and providing useful guidelines to implement this technique, including R code. 4. We illustrate each step of SDP required to derive an optimal strategy using a wildlife management problem of the French wolf population. 5. Stochastic dynamic programming is a powerful technique to make decisions in presence of uncertainty about biological stochastic systems changing through time. We hope this review will provide an entry point into the technical literature about SDP and will improve its application in ecology.

Habitat loss and fragmentation are major threats to biodiversity. Establishing formal protected areas is one means of conserving habitat, but socio-economic and political constraints limit the amount of land in such status. Addressing conservation issues on lands outside of formal protected areas is also necessary. In this paper we develop a spatially explicit model for analyzing the consequences of alternative land-use patterns on the persistence of various species and on market-oriented economic returns. The biological model uses habitat preferences, habitat area requirements, and dispersal ability for each species to predict the probability of persistence of that species given a land-use pattern. The economic model uses characteristics of the land unit and location to predict the value of commodity production given a land-use pattern. We use the combined biological and economic model to search for efficient land-use patterns in which the conservation outcome cannot be improved without lowering the value of commodity production. We illustrate our methods with an example that includes three alternative land uses, managed forestry, agriculture, and biological reserve (protected area), for a modeled landscape whose physical, biological, and economic characteristics are based on conditions found in the Willamette Basin in Oregon (USA). We find that a large fraction of conservation objectives can be achieved at little cost to the economic bottom line with thoughtful land-use planning. The degree of conflict between conservation and economic returns appears much less using our joint biological and economic modeling approach than using a reserve-site selection approach, which assumes that species survive only inside of reserves and economic activity occurs only outside of reserves.

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Unintended effects of recreational activities in protected areas are of growing concern. We used an adaptive-management framework to develop guidelines for optimally managing hiking activities to maintain desired levels of territory occupancy and reproductive success of Golden Eagles (Aquila chrysaetos) in Denali National Park (Alaska, U.S.A.). The management decision was to restrict human access (hikers) to particular nesting territories to reduce disturbance. The management objective was to minimize restrictions on hikers while maintaining reproductive performance of eagles above some specified level. We based our decision analysis on predictive models of site occupancy of eagles developed using a combination of expert opinion and data collected from 93 eagle territories over 20 years. The best predictive model showed that restricting human access to eagle territories had little effect on occupancy dynamics. However, when considering important sources of uncertainty in the models, including environmental stochasticity, imperfect detection of hares on which eagles prey, and model uncertainty, restricting access of territories to hikers improved eagle reproduction substantially. An adaptive management framework such as ours may help reduce uncertainty of the effects of hiking activities on Golden Eagles.

A method for evaluating the reliability of option-based price probability assessments is developed based on the calibration concept. Empirical tests using goodness-of-fit criteria are applied to four agricultural commodities. Results suggest that assessments in the com and live cattle markets are reliable, but such assessments overstate the volatility of soybean prices and understate the location of hog prices.

We use a regulatory model with resistance evolution in two pests to insecticidal Bt cotton and pyrethroids (a conventional insecticide) to examine non-Bt cotton (refuge) planting requirements designed to manage Bt-resistance evolution in the midsouth. Our analysis suggests that reduced refuge requirements would enhance producer profitability, sprayed refugia are more cost effective than unsprayed refugia, and producers would receive slightly higher returns under dynamic relative to static refuge policies. Pyrethroid susceptibility in one of the pests was a renewable resource, and toxin-mixture effects associated with pyrethroid use in Bt cotton were important considerations for midsouth refuge policies. Copyright 2004, Oxford University Press.