Forestry Economics: Principles and Practice

This review discusses bioeconomic models of the forest and uses them to explore policy options for forest management. The main type of bioeconomic model used is based on a biomass model of the growth of the forest, similar to the biomass model widely used in fishery economics. However a more detailed model, similar to the cohort-based models of fish stocks, which simulates the growth of subsections of the forest is also referred to. The bioeconomic models are based on simple assumptions about prices and costs - mainly that the forest industry, as a small part of the economy, is a price taker in both output and input markets. The models were initially used to examine the harvesting policy which would maximise the net present value of the timber produced by the forest. However it was recognised that non-timber values are becoming increasingly important and must be accounted for in the development of an optimal forest strategy. Case Studies consider some of the issues raised in the paper in greater detail.

USING LAND AS A CONTROL VARIABLE IN DENSITY-DEPENDENT BIOECONOMIC MODELS

The bioeconomic analysis of endangered species without consumptive values can be problematic when analysed with density-dependent models that assume a fixed environment size. Most bioeconomic models use harvest as a control variable, yet when modelling non-harvestable species, frequently the only variable under control of conservationists is the quantity of habitat to be made available. The authors explore the implications of this in a model developed to analyse the potential population recovery of New Zealand's yellow-eyed penguin. The penguin faces severe competition with man for the terrestrial resources required for breeding and has declined in population to perilously low levels. The model was developed to estimate the land use required for recovery and preservation of the species and to compare the results to current tourism-driven conservation efforts. It is demonstrated that land may serve as a useful control variable in bioeconomic models and that such a model may be useful for determining whether sufficient incentives exist to preserve a species. However, the model may generate less useful results for providing a specific estimate of the optimal allocation of land to such a species.Land Economics/Use,

Open-access Fishery Performance When Vessels Use Goal Achievement Behavior

While most bioeconomic models assume that vessel operators use profit maximizing behavior, it is sometimes argued that participants use other operational goals. The purpose of this paper is to compare how vessel behavior, the bioeconomic equilibrium, and the path to achieve it are changed if participants use goal achievement behavior. It is shown that, depending on the operational rule used to achieve the goal, there can be significant differences in the amount of individual vessel effort at different stock sizes, and this can affect the location and the stability of the bioeconomic equilibrium. In addition, goal achievement behavior will generally lead to a larger open-access overshoot in terms of fleet size.profit maximizing behavior, goal achievement behavior, open-access fishery behavior, Resource /Energy Economics and Policy, Q22,

Endogenous Fishing Mortalities: a State-Space Bioeconomic Model

A methodology that endogenously determines catchability functions that link fi shing mortality with contemporaneous stock abundance is presented. We consider a stochastic age-structured model for a fishery composed by a number of fi shing units (fleets, vessels or métiers) that optimally select the level of fishing effort to be applied considering total mortalities as given. The introduction of a balance constrain which guarantees that total mortality is equal to the sum of individual fi shing mortalities optimally selected, enables total fishing mortality to be determined as a combination of contemporaneous abundance and stochastic processes affecting the fishery. In this way, future abundance can be projected as a dynamic system that depends on contemporaneous abundance. The model is generic and can be applied to several issues of fisheries management. In particular, we illustrate how to apply the methodology to assess the floating band target management regime for controlling fishing mortalities which is inspired in the new multi-annual plans. Our results support this management regime for the Mediterranean demersal fishery in Northern Spain.This work was funded by the European Commission as part of the MINOUW project (H2020-SFS-2014-2, number 634495) and the Spanish Ministry of Economy, Industry and Competitiveness (ECO2016-78819-R, AEI/FEDER, UE

Stochastic Bioeconomics: A Review of Basic Methods and Results

Basic bioeconomic models which incorporate uncertainty are reviewed to show and compare the principal methods used and results reported in the literature. Beginning with a simple linear control model of stock uncertainty, we proceed to discuss more complex models which explicitly recognize risk preferences, firm and industry behavior, and market price effects. The effects of uncertainty on the results of bioeconomic analysis are rarely unambiguous, and in some instances differ little from corresponding deterministic results. This review is presented to enhance readers' appreciation of the papers to follow in this and the next issue of the journal.Environmental Economics and Policy, International Development, Resource /Energy Economics and Policy, Risk and Uncertainty,

Biomass Supply from Alternative Cellulosic Crops and Crop Residues: A Preliminary Spatial Bioeconomic Modeling Approach

This paper introduces a spatial bioeconomic model for study of potential cellulosic biomass supply at regional scale. By modeling the profitability of alternative crop production practices, it captures the opportunity cost of replacing current crops by cellulosic biomass crops. The model draws upon biophysical crop input-output coefficients, price and cost data, and spatial transportation costs in the context of profit maximization theory. Yields are simulated using temperature, precipitation and soil quality data with various commercial crops and potential new cellulosic biomass crops. Three types of alternative crop management scenarios are simulated by varying crop rotation, fertilization and tillage. The cost of transporting biomass to a specific demand location is obtained using road distances and bulk shipping costs from geographic information systems. The spatial mathematical programming model predicts the supply of biomass and implied environmental consequences for a landscape managed by representative, profit maximizing farmers. The model was applied and validated for simulation of cellulosic biomass supply in a 9-county region of southern Michigan. Results for 74 cropping systems simulated across 39 sub-watersheds show that crop residues are the first types of biomass to be supplied. Corn stover and wheat straw supply start at $21/Mg and$27/Mg delivered prices. Perennial bioenergy crops become profitable to produce when the delivered biomass price reaches $46/Mg for switchgrass,$118/Mg for grass mixes and $154/Mg for Miscanthus giganteus. The predicted effect of the USDA Biomass Conversion Assistance Program is to sharply reduce the minimum biomass price at which miscanthus would become profitable to supply. Compared to conventional crop production practices in the area, the EPIC-simulated environmental outcomes with crop residue removal include increased greenhouse gas emissions and reduced water quality through increased nutrient loss. By contrast, perennial cellulosic biomass crops reduced greenhouse gas emissions and improved water quality compared to current commercial cropping systems.biomass production, bioenergy supply, biofuel policy, bioenergy, cellulosic ethanol, agro-ecosystem economics, ecosystem services economics, agro-environmental trade-off analysis, mathematical programming, EPIC, Agricultural and Food Policy, Crop Production/Industries, Environmental Economics and Policy, Land Economics/Use, Production Economics, Resource /Energy Economics and Policy, Q16, Q15, Q57, Q18,

THE CALIFORNIA ROCKFISH CONSERVATION AREA AND GROUNDFISH TRAWLERS AT MOSS LANDING HARBOR

This article uses a bioeconomic model and data for groundfish trawlers at Moss Landing Harbor in Central California to analyze effects of spatial closures that were implemented recently by West Coast fishery managers to reduce bycatch of overfished groundfish stocks. The model has a dynamic linear rational expectations structure, and estimates of its parameters exhibit spatial variation in microeconomic and ecological factors that affect decisions about where and when to fish. Test results show that variation in marginal costs of crowding externalities and biological rates of stock productivity are the most significant factors to consider in the spatial management of roundfish trawlers at Moss Landing.Resource /Energy Economics and Policy,

Bayesian Bioeconomics of Marine Reserves

We use Bayesian econometric methods to estimate dynamic bioeconomic models of marine reserve formation using simulated data and real data from the Gulf of Mexico reef fish fishery. We test the effects of reserves on fish growth and catchability.Resource /Energy Economics and Policy,