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Coordinating investments in habitat management and economic development

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Journal of Bioeconomics

Abstract

Development generates environmental externalities when it degrades or destroys habitat and damages ecosystems services. In practice, governments and industry control these externalities by restricting development and/or practicing environmental management. This paper uses bioeconomic theory to examine strategies that optimally balance economic production and habitat management. Our results suggest that while habitat management may be an ecological substitute for less economic development, the efficient coordinated conservation scheme in the social planner’s problem treats them as economic complements over the course of a recovery program, such as for imperiled species. However, resource managers should substitute toward habitat management if they cannot efficiently coordinate habitat management and economic development. We illustrate our results with an application to the lesser prairie chicken, an imperiled bird species in the U.S. Great Plains.

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All source code can be retrieved from the Open Science Framework (osf.io/3ysh4).

Notes

  1. As pointed out by a reviewer, alternatively one could write \(g\left( \cdot \right)x\left( t \right) = G\left( \cdot \right)\), where \(G\left( \cdot \right)\) is quadratic in \(x\left( t \right)\). Doing so will change the general expressions of the model, but plugging in functional forms yields the same results (Supplemental Material D). This observation is supported by Conrad and Clark (1987) and Conrad (1999), who use a variety of notations depending on the problem and the intuition that can be obtained by adopting one or the other. We find that using the form \(g\left( \cdot \right)x\left( t \right)\) allows us to better simplify our results into economically meaningful groups.

  2. This is often done in the United States through federal assistance programs run by the Natural Resources Conservation Service. For example, in the case of the lesser prairie chicken there is a five-state range-wide plan that offers voluntary conservation incentives (Van Pelt et al., 2013).

  3. These dynamics imply the population is evenly distributed over the landscape. This assumption keeps the model tractable, but it precludes insights into how the spatial density of reserves and development may be altered to conserve wildlife (Sanchirico & Wilen, 1999). In practice, an agency may want to take advantage of habitat heterogeneity in regulating development (Polasky et al., 2005).

  4. The latter could correspond to the case in which a private owner possesses property rights to species habitat, which is not protected under the ESA. In this case, the private property owner would seek to choose the level of economic investment to maximize (4) subject to (2). The solution to this problem is presented in Supplemental Material B.

  5. From the necessary first order condition in (17), it would seem that the levels of economic investment in (20) could depend on the shadow value of economic capital (sensu Horan & Wolf (2005)). However, following Conrad and Clark (1987) and Clark (2010), the control variable must be able to efficiently regulate the state variable in order to be optimal. That is, the control should be able to regulate the state variable to its equilibrium and then hold it at that equilibrium via the singular solution. It can be shown that this is not the case when (20) is regulated by the shadow value of economic infrastructure. See Supplemental Material B for details.

  6. The maximum amount of capital investment is bounded by the capacity of the developer and its suppliers, though it is not obvious what this limit should be. We therefore follow the approach of Conrad and Clark (1987) and allow for an arbitrary large \(I_{{MAX}}\) such that the developer can effectively adjust the stock of economic infrastructure.

  7. It is worth recalling that in the uncoordinated conservation program the level of economic infrastructure is taken as given or exogenous. In the absence of habitat management there exists a threshold in the level of economic infrastructure, \(\bar{K} = {L \mathord{\left/ {\vphantom {L {s_{2} }}} \right. \kern-\nulldelimiterspace} {s_{2} }}\), over which the species population will decline and die out. In this case habitat management is required for the species to persist. If \(\bar{K} < {L \mathord{\left/ {\vphantom {L {s_{2} }}} \right. \kern-\nulldelimiterspace} {s_{2} }}\), as is the case for the developer’s optimum (Supplemental Material B), then economic infrastructure scales the species’ carrying capacity and habitat management is chosen solely to maximize the net present-value benefits of the species.

  8. While it is possible that a corner solution would be optimal, we assume that the extra biomass of prairie chickens associated with an interior solution makes the interior equilibrium preferable.

  9. This behavior is consistent with nonlinear feedback rules characteristic of multiple control systems and the switching between multiple singular arcs, depending on initial conditions (Bryson & Ho, 1975; Conrad & Clark, 1987; Horan & Wolf, 2005).

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Authors and Affiliations

  1. School of Environmental Sustainability, Loyola University Chicago, Chicago, IL, USA

    Richard T. Melstrom

  2. Université de Lorraine, Université de Strasbourg, AgroParis Tech, Centre National de la Recherche Scientifique (CNRS), Institut National de Recherche Pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Bureau d’Economie Théorique et Appliquée (BETA), 14 Rue Girardet - CS 14216, 54042, Nancy Cedex, France

    David W. Shanafelt

  3. Department of Agricultural Economics, Purdue University, West Lafayette, IN, USA

    Carson J. Reeling

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Melstrom, R.T., Shanafelt, D.W. & Reeling, C.J. Coordinating investments in habitat management and economic development. J Bioecon 24, 67–91 (2022). https://doi.org/10.1007/s10818-021-09318-8

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