ECONOMICS OF SPECIES PRESERVATION: THE SPOTTED OWL CASE

ECONOMICS OF SPECIES PRESERVATION: THE SPOTTED OWL CASE

CLAIRE MONTGOMERY AND GARDNER M. BROWN, JR.*

This paper describes efforts to build a supply curve for survival of the northern spotted owl in the wild. A survey of experts and a population dynamics simulation model relate species survival to habitat capacity. Home range studies provide the basis for determining the owl's area requirements. Cataloging land in the range of the owl in terms of suitability for owl habitat and for timber production provides the link between timber harvest and the probability of owl survival. Finally, an econometric model of stumpage and wood products markets predicts weyare impacts of timber harvest reductions. The supply curve relates the probability of northern spotted owl survival to the present value to consumers and producers of foregone timber harvest over time.

1. INTRODUCTION

While trade-offs are taken for granted in producing market goods, most people are reluctant to acknowledge that species preservation limits the production of other valuable commodities. The Endangered Species Act (ESA) explicitly bans economic considerations in the listing decision, and economists have failed to consider systematically the marginal trade- offs associated with species preservation.

Most relevant studies estimate loss of jobs and tax revenue likely to result from implementation of particular conservation strategies or recovery plans for target species. In the case of the northern spotted owl, Greber (1990), Lippke (1990), and

*Assistant Professor, School of Forestry, University of Montana, Missoula, and Professor, Department of Economics, University of Washington, Seattle, respec- tively. This is a revised version of a paper presented at the 66th Annual Western Economic Association In- ternational Conference, Seattle, WA, July 1991, in a ses- sion organized by Gregory M. Perry, Oregon State Uni- versity, Corvallis. The authors thank Barry Noon for generous guidance in owl biology, and gratefully acknowledge research support from the U.S.D.A. Forest Service Pacific Northwest Research Station.

Contemporary Policy Issues Vol. X, April 1992

Hamilton, et al., (1990) have analyzed an all-or-nothing choice between some level of habitat protection and no protection. They present policymakers with a plan for species preservation and an estimate of its regional and national costs. Unfortunately, the limited array of data gives policymakers little scope for making comparisons with other plans. More importantly, the data fail to provide a basis for assessing the costs or gains of moving incrementally toward more or less species protection. The lack of a traditional marginal frame- work for reasoned analysis of trade-offs further aggravates the adversarial debate between advocates of species preservation and those likely to bear its cost. Econo- mists can play a substantial role in this debate by providing much needed analysis to aid in evaluating marginal costs and marginal benefits of species protection. Species preservation is a public good and an example of why real world markets sometimes fail to achieve the optimal allocation of resources. Because the resulting market allocation does not meet the crite- rion for efficiency, species preservation justifies government intervention. For policymakers to make an optimal decision,

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@Western Economic Association International

2 CONTEMPORARY POLICY ISSUES

they must know the preference structures of individuals in society and the charac- teristics of production technologies em- bodied in the aggregate demand and supply functions.

Economists can improve decisions by estimating the shape of the relevant demand and supply relationships. They can help policymakers to choose an option in the vicinity of optimality or, more likely, to evaluate marginal trade offs about any point allowing, for instance, analysis of the cost of being wrong.

The study presented here describes the process of identifying a supply curve for survival of the northern spotted owl in the wild and offers preliminary analysis and results. It also sets forth future refinements and extensions. Estimating the supply function is only part of the economic analysis. The daunting task of identifying a demand function for survival of the northern spotted owl remains.

II. THE SUPPLY CURVE

Initially, spotted owl habitat was thought to be synonymous with ancient forest. However, recent studies of the spotted owl’s home range and dispersal be- havior reveal that spotted owl habitat and ancient forest are not the same (Thomas, et al., 1990). Some ancient forests do not provide suitable owl habitat and need not be included in any rational owl conservation strategy. Conversely, forests that are not “ancient” but do support the owl, particularly in the redwood zone of northern California, are not protected under an ancient forest preservation plan. Preserv- ing the spotted owl and preserving the ancient forest are separate issues and policymakers should address them sepa- rately, recognizing that some joint production does occur. The present model in- volves no attempt to incorporate ancient forest preservation.

The ESA is the legal instrument for assuring production of public goods re-

lated to northern spotted owl survival. Therefore, the debate has focussed on in- terpreting the ESA and identifying activities necessary to meet its requirements. For these reasons, the analysis presented here narrowly defines output as survival of the northern spotted owl in the wild. Because the ultimate goal of species survival is inherently uncertain, output in this study is the numerical probability that the northern spotted owl will survive for 150 years rather than such measures of effort as population size or habitat capacity. The amount of suitable habitat limits the probability of owl survival. Therefore, the study here defines a single input production process in which the probability of owl survival depends on the amount of suitable habitat that is protected. It measures survival as the number of owl pairs that the protected habitat can support when fully occupied.

Finally, the opportunity cost of protecting habitat is the value of the protected land in its next highest use. Currently, timber harvest and associated road con- struction are the only activities that will be seriously curtailed on some protected habitat. Reducing timber harvest may result in less geographical dispersion of rec- reation activity, and congestion may increase because of curtailed road construc- tion. Increased availability of roadless forest will partially offset these costs. Most biologists agree that highly certain protection of the owl and continued timber harvest are incompatible, although growing evidence suggests that in some areas, particularly northern California, timber harvest may not threaten owl survival. In any case, this study assumes complete prohi- bition of timber harvest activity within protected habitat. Therefore, the cost of owl survival is the value of foregone timber harvest, measured as the change in net benefit to society of reduced timber harvest.

The supply curve, which relates marginal cost to the probability of species

MONTGOMERY & BROWN: ECONOMICS OF SPECIES PRESERVATION 3

survival, consists of four components: (i) the probability of species survival as a function of the protected habitat capacity, (ii) the number of acres necessary to provide habitat for an owl pair as a function of the density of suitable habitat within a protected area and its geographic location, (iii) the reduction in timber inventory as a function of the amount of harvestable timber within protected areas, and (iv) the change in consumer and producer sur- pluses resulting from reductions in timber inventory.

A. The Probability of Species Survival Two approaches can lead to under-

standing the problematic relationship between habitat capacity and species survival. Both rely on biologists’ willingness to put their knowledge into a form useful for economic analysis. Any economic analysis of species preservation must rely on interdisciplinary cooperation.

The first approach surveys expert opinion from 22 biologists selected on the basis of their research record pertaining to the northern spotted owl or on the recommen- dation of their peers. They considered two scenarios, one requiring that the species be protected throughout its historical, geographic range and one not requiring distribution throughout its range. Respon- dents reported their level of confidence that the owl would not be extinct at the end of 150 years for any given habitat capacity. The response rate was 32 percent.

The scientists most intensely involved in the political debate surrounding the owl were the most likely to refuse to respond. Many who refused to respond explained that they had experienced harassment in court and in the media. A few stated that the questions were too simplistic. Others expressed a reluctance to base numerical probability estimates on opinion because, they argued, estimates that are not scientifically defensible are useless. However, scientifically defensible empirical esti-

mates of probability of survival do not exist, so the opinion of scientists who study the owl is an extremely valuable source of information. Estimates of experts having the most specialized knowledge about the species provide a far supe- rior basis for a policy decision than alter- natives likely to be used in the absence of those estimates.

The second approach uses the population dynamics simulation model developed at the U.S. Forest Service Pacific Southwest Research Station by Lamber- son, et al., (1989) primarily for analyzing the number of owl pairs in a contiguous habitat, the percentage of suitable habitat, and the ease with which juveniles find acceptable, unoccupied habitat. Lamber- son et al. did not design their population model to assess the prospects of viability, which is the objective of the study presented here. However, compared with expert opinion, that model might be able to produce a more credible picture of the relationship between habitat capacity and species survival when adjusted to include (i) a more realistic path toward extinction at low population levels, and (ii) coeffi- cients of variation on survival and fecun- dity rates to handle environmental stochasticity. The coefficient of variation of the random variable (X) is the ratio of its standard deviation to its mean. The reciprocal measures the signal-to-noise ratio of the random variable.

The adjusted model is based on four key sets of parameters: (i) the mean values of demographic parameters such as fecun- dity rate and survivorship, (ii) the coefficient of variation for those parameters over time in response to environmental variation, (iii) minimum viable population size, and (iv) the mapping of protected habitat.

Estimates of mean values of demographic parameters are from field data collected for a period of seven years (USDI, 1990). Dispersal, which refers to the ability of juvenile males to find an


TABLE 1 Demographic parameters and measures of variation.

Coefficient Standard Mean of variation deviation

Juvenile predispersal survival rate 0.60 60 % 0.36

Sub-adult and adult survival rate 0.903 10% 0.09

Fecunditv rate 0.34 60 % 0.20

unoccupied site, drives the population dynamics in this model. As habitat quality and quantity and population density vary, the dispersal success rate, and thus the juvenile survivorship, varies. The remaining population parameters (see table 1) should reflect a stable population. Unfor- tunately, empirical estimates of demographic parameters do not exist for a stable population because rapid changes in the amount of suitable habitat have placed the owl population in a state of adjust- ment. Consequently, the analysis uses demographic parameters of the more stable of the two areas for which estimates exist-Willow Creek in northern Califor- nia (Franklin, 1990).

Study of changes in demographic parameters arising from environmental variation over time is in its infancy. Changes in climate, in susceptibility of forests to disease, and in predator and prey popula- tions represent sources of environmental variation. Table 1 reports reasonable estimates along with mean values of demographic parameters. Future research will test the sensitivity of the results to environmental variability.

The model omits the Allee effect, which is a reduction in the probability of species survival at low population densities due to the difficulty of locating mates. Because of this omission, the model is overly optimistic at low population densities and rarely allows extinction. Some biologists

believe that a state called "quasi-extinction" occurs when population density falls below a threshold at which extinction is certain. Survey results indicate that biologists feel that an owl population of fewer than 500 pairs distributed over its historical range has a negligible probability of survival. Subsequent conversations with biologists tend to confirm that 500 owl pairs is a reasonable threshold level.

Finally, the model maps the system of habitat conservation areas (HCAs) pro- posed by the Interagency Scientific Com- mittee (ISC) on federal land (see Thomas, et al., 1990). Adjusting the size and quantity of HCA's maintains the skeleton of HCA's connecting the range for popula- tions of 500 to 4000 pairs. This study did not include testing variations of the origi- nal HCA system for feasibility in the field.

Figure 1 shows the mean probability of survival conditional on the amount of habitat capacity as predicted by both the survey and the population simulation model. Interestingly, the survey sample respondents believe that the ISC strategy gives the owl only a 35 percent to slightly more than a 50 percent probability of survival. The ISC proposal will protect habitat capable of supporting an expected 1,700 owl pairs at 100 percent occupancy on public land and an additional 200 pairs on private land. If all currently available habitat is protected and this area supports 4,000 owl pairs-a rough but reasonable


FIGURE 1 Mean Probability of Species Survival for Given Habitat Capacity-

Summary of Survey and Population Model Results

0.7 -

0.5 - > c.

0.2 -

0 2 4 (-rhousands)

Habitat capacity in thousand owl pairs

estimate according to Thomas, et al. (1990)-the owl has, at best, an 80 to 85 percent probability of survival according to the survey respondents. The population simulation model is considerably more optimistic, revealing the production function that underlies the recommendations of the ISC committee. Note that the ISC proposal of habitat for 1,700 to 2,000 pairs falls at a threshold. Diminishing returns to scale becomes pronounced at about 2,000 pairs, while reducing habitat capacity below 1,500 pairs becomes quite costly in terms of species survival.

B. Habitat Capacity The area necessary to support one owl

pair varies with both physiographic re-

gion and the amount of suitable habitat within the protected area (Thomas, et al., 1990). The study presented here deter- mines four physiographic regions from previous studies of home range size. Hab- itat requirements for each region are 4,600 acres in the Olympic Peninsula of Wash- ington, 3,300 acres in the west Cascades and southwestern Washington, 2,300 acres in the Douglas-fir and western hemlock zone of Oregon, and 1,600 acres in the mixed conifer zone of southwestern Ore- gon and northern California. The habitat protection accommodates clusters of owl pairs where possible. Table 2 shows acreage requirements for one owl pair in each of the four regions as a function of suitable habitat in a representative acre. These al-


TABLE 2 Acreage requirements per owl pair in four physiographic regions.

Percent suitable habitat 10 30 50 80 ~~ ~

Olympic peninsula 34500 11500 6900 4313

Washing ton-SW and Cascades

24750 8250 4950 3094

Douglas-fir and western 16500 5500 3300 2063 hemlock-Oregon

Mixed conifer-SW Oregon 10500 3500 2100 1313 and northern California

lotments allow for a 25 percent overlap in the home ranges of adjacent owl pairs but exclude other less essential considerations in determining habitat needs, such as frag- mentation of the suitable habitat within the home range and the elevation of the site. Table 2 gives general acreage requirements. Adding other biological criteria would add precision to the estimate.

A very rough estimate of suitable habitat availability was the basis for the relationship between total habitat capacity and the number of acres protected. Map measurements of percent suitable. habitat in four square mile blocks for public land and timber inventory data for private land will refine this relationship. Updating this element of the model can reflect evolving definitions of suitable habitat. The present version of the model adopts the definition used by agency biologists to generate maps for the ISC in the spring of 1990.

C. Timber Inventory To link habitat capacity to the number

of acres withdrawn from timber harvest, one must characterize the total land base within the owl's range by its suitability both for owl habitat and for timber pro-

duction. The assumption here is that all privately owned timber land is suitable for timber harvest, while all private non-timber land is unsuitable for timber harvest. Suitability for timber harvest on public land depends on allocation between competing uses by the managing agency. Re- served areas (primarily wilderness and National Parks) are completely unsuitable for timber harvest. Non-reserved areas on public land are classified into timber suitability categories based on map measurements of the percent area allocated to timber production within four square mile blocks.

Figure 2 shows preliminary 'marginal physical cost' curves for the probability of northern spotted owl survival based on very rough acreage estimates (available from authors) for the two probability functions depicted in figure 1. The number of acres withdrawn from timber harvest represent costs. On the low cost end lie acres that are highly suitable for owl habitat but are allocated to competing uses, including portions of the national parks and some wilderness areas. On the high cost end lie acres that are allocated solely to timber production and that offer poor owl habitat, either due to past harvest activities or

7 MONTGOMERY & BROWN ECONOMICS OF SPECIES PRESERVATION

FIGURE 2 Acres of Timber Land Withdrawn Per Pair as a Function of Total Habitat Capacity-

For Survey and Population Model Results

L .- m a z a

a

3

v)

$ U c

3 0

12

11

10

9

8

7

6

5

4

3

2

1

0

I I

0 0 2 0.4 0.6 0.8 1

Probability of survival

vegetation type. Most private timberland in Oregon and Washington falls into this category, and should be drawn into the protected habitat land base last.

The marginal cost curve in figure 2 depends on the very strong assumption that acres can be effectively added to the protected habitat land base sequentially in order of their impact on the timber base. In fact, spatial considerations do matter. The proximity of a protected habitat area to other protected areas, as well as the nature of the vegetation between areas, influences its effectiveness. Distribution requirements further impede basing the selection of areas solely on the opportunity cost of timber production. To the degree that these considerations matter, the marginal cost curve depicted in figure

2 gives a low bound on the cost of providing some level of habitat capacity. Future research will analyze spatial restrictions.

D. Measuring the Value of Foregone Timber Hizniest

One can use the Timber Assessment Market Model (TAMM) developed by Adams and Haynes (1980) to analyze the impact of reductions in the amount of timber available for harvest on stumpage markets, and to measure the corresponding changes in social welfare. The analysis must be partial because TAMM does not explicitly model markets for non-wood factors used in the production of stumpage and wood products-for instance,

CONTEMPORARY POUCY ISSUES

FIGURE 3 Stumpage Market for Area Within the Range of the Northern Spotted Owl

P

w . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A . - - - - - - - - - - - - -

Public sq@y

Public + private

labor-or export and import markets, with the exception of Canada. Conducting a parallel market analysis using the Global Trade Model (Cardellichio, et al., 1988) will facilitate evaluating the importance of global markets. The following discussion gives the flavor of the analysis incorporat- ing the TAMM results. Figure 3 diagrams the stumpage market in the owl region. Adams et al. (1991) argue that the supply of harvested timber from public land is price sensitive because its purchasers have some discretion in the timing of harvest. Nevertheless, public supply is assumed to be responsive only to the amount of timber available for harvest. Thus, a vertical line at the allowable sale quantity (ASQ) represents public supply. Average cost (AC) represents the cost to agencies of conducting timber sale and management programs. Surplus to the public sector is the area of rectangle A. Private supply is the marginal opportunity cost of selling timber for harvest now rather than later

xo

Timber harvest (mbf)

and depends principally on current and expected future stumpage price, the inter- est rate, and the amount of timber available for harvest. Adding private to public supply produces the total stumpage supply curve s. Because stumpage suppliers incur no extraction costs, producer surplus to private stumpage suppliers is the area of rectangle B. The demand curve is the derived demand for stumpage in the production of wood products. Triangle C represents surplus to wood products manufacturers. For simplicity, this discussion focuses only on changes in surplus measures resulting from habitat protection to stumpage markets. If one specifies the demand and supply functions with suffi- cient generality, surplus changes in factor and final output markets are incorporated into the surplus changes in the stumpage market (Just et al., 1982). In TAMM, the demand and supply functions are partial equilibrium functions, and each relevant market must be analyzed. Figure 4 illus-

9 MONTGOMERY & BROWN ECONOMICS OF SPECIES PRESERVATION

FIGURE 4 Stumpage Supply Shift Resulting from Protection of Habitat on Public Land

AsQl ASQO x1 xo


trates reduced ASQ and supply shifts that would occur if habitat were protected only on public land. Price rises and output falls. Because private supply responds to the price increase, output decreases less than ASQ. Total surplus decreases. Wood products manufacturers clearly lose, as do consumers of final products. Private stumpage suppliers produce more at a higher price and gain. One cannot determine the sign of the change in surplus to the public sector from the diagram. The change in surplus to the public sector depends on the elasticity of demand.

Figures 4 illustrates short-run impacts. In time, factors adjust to the change in stumpage supply. Of particular relevance are mill capacity and trade flows. Within the range of the owl, marginally operating mills close, while surviving mills look elsewhere for lower cost stumpage and consumers look elsewhere for lower cost wood products. Net export of logs and wood products from the region decreases.

Figure 5 illustrates the shift in stumpage demand in the region if habitat is protected only on public land. The initial increase in stumpage price becomes less marked. Gains to private stumpage suppliers decrease. The surplus to the public sector also decreases, and the public sector is much more likely to lose. Losses to wood products manufacturers increase. While not shown, losses to consumers of final products decrease as price falls.

At the same time, stumpage markets in other regions are changing. Higher final product prices motivate increases in mill capacity. Increased demand for stumpage from the remaining mills in the owl region and for other purchasers causes increases in trade flows from these regions. Derived demand for stumpage shifts out in these regions, as figure 6 shows. All players gain.

The appropriate measure of cost for a given level of owl habitat protection is the present value of the stream of changes in


P

$

Pi

PO

FIGURE 5 Shift in Derived Demand for Stumpage in the Region Within the

Range of the Northern Spotted Owl

s1 so

As01 ASQO x1 xo


surplus in all affected markets. One can use TAMM to analyze the impact of providing a range of levels of habitat protection and to compute the corresponding surplus changes. The supply curve for probability of spotted owl survival is the curve fitting through those observations.

The aggregate measure of surplus change is the appropriate cost to consider when deciding optimal owl habitat protection. However, the foregoing discussion highlights the uneven fashion in which the costs will be born. The policy debate also should address questions of distribution and compensation. Additional analysis will show the allocation of cost to various regions and individuals.

111. CONCLUDING REMARKS

Assume a target of 0.9 probability of survival for the northern spotted owl. The analysis summarized in figure 2 indicates

that a given amount of acreage must be protected, resulting in a given reduction in public timber supply, say ASQO-ASQ1 thousand board feet (figure 4). The dollar value of the acres is the area between the two supply curves in figure 4, or a,b,ASQO,ASQl. If society is satisfied that a 0.9 probability of survival is worth at least that much value, then these acres should be protected. However, thus far no one has estimated the value of the owl's probable survival to American citizens or to a broader geographic polity, largely because the actors in the political process want to make the judgment. Alternatively, one could derive estimates from contin- gent valuation surveys designed to elicit such values from a random sample drawn from the affected population. In any case, some evaluation must be made of how society values the benefits derived from different levels of certainty of species survival.


FIGURE 6 Shift in Derived Demand for Stumpage in Regions Outside the

Range of the Northern Spotted Owl

P1 w

xo X l


Although one cannot answer the ques- tion of how much protection to provide for a species solely on the basis of this analysis, the analysis does serve to iden- tify useful questions. Is there a threshold level of certainty of species survival at which the marginal cost of additional certainty increases dramatically? Or, at what cost would the certainty of survival gained from total cessation of timber harvest on suitable habitat be acceptable? In the absence of reliable information about society’s valuation of the benefits, questions of this nature help policymakers determine the cost of being wrong about the optimal allocation of resources to protecting spotted owl habitat.

The legal basis for species preservation implies that protecting a species from extinction is an all-or-nothing choice. Past economic analyses have proceeded from this assumption. In fact, because different levels of effort to protect a species generate different levels of certainty that the species will survive, the choice really in- volves how certain we want to be of its survival, not whether or not we want it to survive. This focus has been missing in past debates about species preservation. Making evaluation of marginal tradeoffs explicit will enhance the quality of these debates and the resulting resolutions.


REFERENCES

Adams, D. M., C. S. Binkley, and P. A. Cardellichio, "Is the level of National Forest Ti iber Harvest Sensitive to Price?" Land Economics, February 1991, 74-84.

Adams, Darius M., and Richard Haynes, "The 1980 Softwood Timber Assessment Market Model: Structure, Projections and Policy Simulations," F o m t Science, Monograph 22, September 1980.

Cardellichio, P., Y. Youn, C. Binkley, J. Vincent, and D. M. Adams, "An Economic Analysis of Short-Run Tiiber Supply Around the Globe," CINTRAFOR Working Paper #18, University of Washington, Seattle, Wash., 1988.

Franklin, A. B., J. A. Blakesley, and R. J. Gutierrez, "Population Ecology of the Northern Spotted Owl (Strix Occidentalis Cavrina) in Northwest Cal- ifornia: Preliminary Results," an unpublished report, 1990.

Greber, B. J., K. N. Johnson, and G. Lettman, "Conser- vation Plans for the Northern Spotted Owl and Other Forest Management Proposals in Oregon: The Economics of Changing Timber Availability, " Papers in Forest Policy 1, Forest Research Labo- ratory, Oregon State University, Corvallis, Oreg., 1990.

Hamilton, T., J. Zimmer, and others. "The Economic Effects of Implementing a Conservation Strategy for the Northern Spotted Owl Report of the In- teragency Economic Effects Team," an unpublished report, Portland, Oreg., 1990.

Just, R. E., D. L. Hueth, and A. Schmitz, Applied Weyare Economics and Public Policy, Prentice-Hall, Engle- wood Cliffs, N.J., 1982.

Lamberson, R. H., R. McKelvey, 8. R. Noon, and C. Voss, "The Effects of Varying Dispersal Capabil- ities on the Population Dynamics of the Northern Spotted Owl: Preliminary Results," an unpublished report, Humboldt State University, Arcata, Calif., 1989.

Lippke, B., K. GiIles, R. Lee, and P. Sommers, Three- State Impact of Spotted Owl Conservation and Other Timber Harvest Reductions: A Cooperative Evalva- tion of the Economic and Social Impacts, Institute of Forest Resources Contribution #69, University of Washington, Seattle, 1990.

Thomas, J. W., E. D. Forsman, J. B. Lint, E. C. Meslow, 8. R. Noon, and J. Verner, A Conservation Strategy for the Northern Spotted Owl: Report of the Infer- agency Scientific Committee to Address the Conser- vation of the Northern Spotted Owl, Document #1990-791-171/20026, U.S. Government Printing Office, Portland, Oreg., 1990.

US. Department of Interior, Fish and Wildlife Service. 1990 Status Review of the Northern Spotted Owl, Portland, Oreg., 1990.

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ECONOMICS OF SPECIES PRESERVATION: THE SPOTTED OWL CASE