Ecological Economics 38 (2001) 259– 274
                                                www.elsevier.com/locate/ecolecon




                            ANALYSIS


       Maximizing conserved biodiversity: why ecosystem
           indicators and thresholds matter
               Mark E. Eiswerth a,*, J. Christopher Haney b
          a
           Department of Applied Economics and Statistics, Uni6ersity of Ne6ada, Reno NV 89557, USA
   b
     Conser6ation Science Di6ision. The Nature Conser6ancy, 4245 N, Fairfax Dri6e, Suite 100, Arlington VA 22203, USA.

          Received 05 June 2000; received in revised form 24 January 2001; accepted 30 January 2001




Abstract

 Accounting for biodiversity is important in several different types of constrained choice problems, including public
and private decisions for habitat and species conservation, the establishment of recreational parks and natural areas,
mitigation banking, and natural resource damage assessment (particularly primary and/or compensatory restoration
planning and scaling). In such applications it is important to give careful consideration to (1) the choice of
biodiversity indicator(s) to be used, and (2) the role of discontinuous, nonlinear ecological processes in light of the
decisionmaker’s chosen time horizon. The former is important because the choice of indicator(s) can substantially
influence decisions about conservation priority-setting and planning. The latter is critical for the same reason,
notwithstanding that dynamic ecosystem processes have rarely been considered sufficiently, if at all, in such
applications (in part because the processes usually are poorly understood or measured). In this manuscript we use
avian diversity data, collected by one of the authors, from hardwood forest ecosystems in the eastern United States.
We couple these data with estimates of species prevalence factors to construct a case study of how indicator choice
and consideration of ecological thresholds influence the outcomes of biodiversity preservation problems. We show
that (1) the choice of indicator(s) is critical, (2) failure to account for nonlinear, threshold effects in an ecosystem’s
future progression alters preservation decisions and ignores important information, (3) the effect of choosing different
time horizons depends on the indicator used, and (4) for any given biodiversity indicator, dynamic solutions can
depend on the time horizon chosen but not necessarily in monotonic or simple fashion. Our case study highlights the
importance of further system-specific research on dynamic ecological progressions as well as uncertainty regarding
future supply and demand for ecosystem service flows. © 2001 Elsevier Science B.V. All rights reserved.

Keywords: Biodiversity; Conservation; Preservation; Habitat; Forests; Birds



                                  1. Introduction
 * Corresponding author. Tel.: + 1-775-3275085; fax: + 1-
                                    Despite the existence of accepted general defini-
775-7841342.
                                  tions of biodiversity, debate continues over just
 E-mail address: eiswerth@unr.edu (M.E. Eiswerth).


0921-8009/01/$ - see front matter © 2001 Elsevier Science B.V. All rights reserved.
PII: S 0 9 2 1 - 8 0 0 9 ( 0 1 ) 0 0 1 6 6 - 5
            M.E. Eiswerth, J.C. Haney / Ecological Economics 38 (2001) 259–274
260

                              2. Background
what biodiversity is, how it should be measured,
and why it is important. Ecologists have
                              2.1. Rele6ant literature
defined a number of different types, or levels,
of biodiversity, with an increasing consensus
                                Biodiversity has long been recognized to be a
that no one indicator can or should be relied
                              multidimensional attribute of natural systems,
upon to characterize it. Different measures
                              with scientists referring to different levels of bio-
provide different indications of the variety
                              diversity including ecosystem, species, and ge-
and integrity of ecosystems, however, and the
                              netic diversity (Office of Technology Assessment,
choice of measures to use in a given context
                              1988; McNeely et al., 1990; National Research
depends on the research or policy objectives at
                              Council, 1992). Several years ago, Ray (1988)
hand.
                              observed that an ‘‘accounting of species alone
  In previous research, we compared the out-
                              can be highly misleading as a yardstick of diver-
comes from applying different biodiversity indi-
                              sity’’, which led him to emphasize the impor-
cators to constrained choice problems of
                              tance of higher-order taxonomic diversity.
ecosystem/habitat preservation (Eiswerth and        Atkinson (1989) placed this consideration in
Haney, 1992; Haney and Eiswerth, 1992). In         clear perspective by stating that ‘‘given two
more recent research, one of the authors col-        threatened taxa, one a species not closely related
lected a substantial amount of plant and animal       to other living species and the other a subspe-
data from hardwood forest ecosystems in the         cies of an otherwise widespread and common
eastern United States. The data collection pro-       species, it seems reasonable to give priority to
ject was designed to investigate the ecological       the taxonomically distinct form.’’
importance of old growth via comparisons to          Observations such as these have encouraged
younger seral (successional) stages of hemlock-       the development of measures that use taxonomic
northern hardwood forest (Haney, 1994, 1995;        information (May, 1990; Altschul and Lipman,
                              1990; Vane-Wright et al., 1991) or information
Haney and Schaadt, 1995). In this manuscript
                              from limited molecular sequences (Crozier, 1992;
we use a portion of these data to construct a
                              Faith, 1992). Researchers have also used genetic
case study of how the choice of biodiversity in-
                              distinctiveness data to indicate biodiversity, by
dicators may affect constrained choice problems,
                              incorporating genome-wide data and linking
for example, public decisions related to habitat
                              composite information about an organism’s en-
conservation, restoration, or mitigation activi-
                              tire genetic makeup to data on species richness
ties. In addition, this case study illustrates the
                              (Eiswerth and Haney, 1992). This is the kind of
dynamic considerations that are important to
                              information that can be useful in many contexts,
such decisions. The forest ecosystem we focus
                              including (but not limited to) the search for spe-
on is characterized by nonlinear changes over
                              cies that have pharmaceutical and other values
time in structure and function, with discontinu-
                              (e.g. Reid et al., 1993a; Simpson et al., 1994).
ities occurring as the ecosystem moves from one
                                In setting priorities for conservation, relevant
developmental stage to the next. As a result,
                              metrics may include combinations of indicators
biodiversity in this system is a discontinuous
                              that reflect both diversity and the amount of
function of time. This has implications for         diversity at risk. For example, species risk fac-
problems in which the desired outcome            tors can be combined with taxonomic distinc-
is to maximize the flow of future services pro-       tiveness indicators to yield a layered proxy (e.g.
vided by biodiversity. We show how the dy-         Haney and Eiswerth, 1992). Such layered indica-
namic solution to a biodiversity preservation        tors illustrate how decisions comparing diversity
problem may depend significantly on the time         among regions can change as more (and better)
horizon considered and the biodiversity indica-       information is considered in addition to simply
tor used.                          species richness. Reid et al. (1993b) provided an
             M.E. Eiswerth, J.C. Haney / Ecological Economics 38 (2001) 259–274          261

informative summary of a wide range of indicators       tion banking, and (5) natural resource damage
useful for policymakers, including ones that em-       assessment (NRDA), particularly primary and/or
body risk. Such indicators are important in applied      compensatory restoration planning and scaling.
decision-making because direct measures of ecosys-        Forest biodiversity receives wide attention be-
tem value are in most cases unavailable, insuffi-       cause of the multiple ecological, social, and eco-
cient, or too expensive to develop using standard       nomic values associated with forest ecosystems
valuation methods (King, 1997). Indicators that        (National Research Council, 1998). Our case study
are easy to use, are applicable to large areas, and      involving eastern forests is particularly relevant
have a close linkage with specific elements, pro-       given that decision-makers are currently attempt-
cesses, or qualities of ecosystem integrity are likely    ing to determine the optimal mix of management
to be the most useful (Bradford et al., 1998; Miller     regimes for sustainable forests. For example, indi-
et al., 1998/1999).                      viduals in Maine recently expressed an interest in
  To model ecological attributes of ecosystems        purchasing lands from timber companies to create
realistically, it is necessary to consider dynamic      a large reserve in which forests would stand undis-
thresholds and other nonlinear processes in system      turbed (Northern Forest Alliance, 2000). In this
structure and function. Such dynamic processes are      and related situations, one of the relevant choice
rarely considered sufficiently, if at all, in exercises    problems is, or at least ought to be: ‘Given a set
such as habitat protection, restoration, or conser-      of forest tracts and a budget constraint for preser-
vation planning. Nonlinear, threshold processes        vation, what is the optimal mix of conservation
are considered even less frequently, in part because     efforts (or more broadly, management regimes)
they usually are poorly understood or measured.        that maximizes the preservation of biodiversity?’
The importance of such processes is sometimes at       The answer depends on the way in which the
least recognized in the literature (e.g. King, 1997),     problem is formulated and the characteristics of the
but to date their incorporation in decision-making      candidate conservation areas. While this
is woefully inadequate.                    manuscript deals solely with indicators of biodiver-
                               sity rather than the broader (and more complex) set
2.2. Pertinent concepts and applications           of potential indicators of all ecosystem functions
                               and services, we recognize that in many decision
  Concepts about biodiversity that we explore in       contexts such broader indicators are generally of
this manuscript include: (1) the choice of biodiver-     interest. We focus on biodiversity per se as one
sity indicator does matter, and can drive conserva-      characteristic of natural systems, and show that
tion decisions, (2) it is important to account for      consideration of even one such characteristic is in
dynamic ecosystem processes, and decision rules        itself a complex step.
that do so may yield quite different results from
those that do not, (3) for any given indicator of
biodiversity, investments in conservation may de-       3. Case study forest areas: characteristics and
pend on the time horizon considered, but not         data
necessarily in monotonic fashion, and (4) the effect
on the dynamic solution of changes in the time          This case study is based on avian data collected
horizon may depend upon the biodiversity indica-       from over 20 study plots in hemlock-northern
tor used.                           hardwood forest. Numerical values for avian pop-
  These concepts have relevance for a number of       ulations and communities were obtained from field
different activities and decisions. Examples include:     studies conducted in Clearfield, Potter, and McK-
(1) decisions related to the purchase of land for       ean counties on the Allegheny Plateau, Pennsylva-
conservation easements, (2) the establishment of       nia (unpubl. data, J.C. Haney, collected
new recreational parks or natural areas, (3) agency      1992–1994; Dessecker and Yahner, 1984). Cen-
priority-setting for habitat and/or species conserva-     suses were conducted in each of five forest age
tion expenditures, (4) decisions involved in mitiga-     classes: 4, 9, 50, 120, and 300+ years. Forest age
             M.E. Eiswerth, J.C. Haney / Ecological Economics 38 (2001) 259–274
262

was computed as the time elapsed since the last       first derived from random subsampling of study
stand-replacing disturbance (either catastrophic       plots available from this forest type (N= 21).
windthrow or even-aged timber harvest). These        Because there are other potential biases to c,
five classes are termed early, transitional, mid-suc-     estimates also conformed to the following criteria:
cessional, late successional, and old growth, re-      visiting or wandering bird species were eliminated;
spectively. Hemlock-northern hardwood forest         data collection was standardized by sampling fre-
displays temporal discontinuities in vegetation       quency (eight visits) and area (each plot was of
structure, threshold effects, and other nonlinear      equal size — 6 hectares (James and Rathbun,
patterns in successional development (see, e.g.       1981); sampling was conducted wholly within a
Tyrrell and Crow, 1994).                   single habitat type; and study plots were located
  Taxonomic groups can be used as indicators in       within large tracts of consolidated forest that were
two fundamentally different ways: as proxies for       not in close proximity to other habitats (Remsen,
biodiversity and as proxies for environmental con-      1994).
ditions. For a variety of reasons, focusing on a        Following application of the criteria above, the
diverse taxon such as birds is useful since a num-      resulting data were combined with other informa-
ber of structural and functional elements of the       tion sources to develop multiple indicators of
environment are automatically integrated. As a        biodiversity as well as biodiversity at risk. First,
group, birds require very diverse microhabitats       numbers of bird species (S) and higher taxa (gen-
arising from structural attributes related to stand     era [G], families [F]) were computed for each of
and floristic composition, snag availability, foliage     the five forest age classes. Next, we calculated a
height diversity, horizontal complexity, core area,     layered proxy (Sa) that combined species richness
and local moisture conditions (Wiens, 1989). Bird      with local (physiographic province) population
communities also exhibit marked, well-docu-         species prevalences derived from Breeding Bird
mented differences in assemblage structure associ-      Atlas programs in nine contiguous states in the
ated with forest developmental sequences           northeastern United States (Laughlin and Kibbe,
(Lanyon, 1981; Smith and MacMahon, 1981;           1985; Andrle and Carroll, 1988; Brauning, 1992;
May, 1982; Glowacinski and Weiner, 1983; Helle,       Bevier, 1994; Buckelew and Hall, 1994; Foss,
1984). Compared to other taxonomic groups,          1994; Palmer-Ball, 1996; Robbins and Blom,
birds perform quite well as indicators of specific      1996; Nicholson, 1997). This layered proxy Sa was
environmental conditions (Morrison, 1986;          computed as:
Croonquist and Brooks, 1991). However, because           Si
                               Sa = % [1− LPi ]
a few species do not always serve as accurate                                 (1)
                                  i=1
substitutes for many others (Niemi et al., 1997),
we make no assumption that this single taxon         where LPi denotes the prevalence factor for spe-
serves as a suitable proxy for other species group-     cies i at the local (physiographic province) scale.
ings or biodiversity in general (but see Pharo et      The prevalence factor from the Breeding Bird
al., 1999).                         Atlas data can assume any value between 0 and 1,
  We used bird species richness derived from        inclusive. For example, a value of 0.50 for local
breeding bird census methodology (Lowe, 1995)        species prevalence means that the species is found
as the initial proxy for forest biodiversity. A       on 50% of the land area at the level of the
number of approaches have been proposed to          physiographic province studied (in this case, the
estimate total species richness, C, within an area      Appalachian Plateau of Pennsylvania). As the
(Bunge and Fitzpatrick, 1993). For comparisons        average prevalence of a collection of species rises,
across forest development (seral) stages, however,      the value of Sa for the collection falls. Weighting
we required only a bias-free estimate of relative      species richness in this manner thus provides us
species richness, c. This approach is equivalent to     with an indication of not only (1) the number of
the data-analytic class of methods reviewed by        species present in our study area, but also (2) the
Bunge and Fitzpatrick. Point estimates of c were       subset of those species present that are not preva-
                M.E. Eiswerth, J.C. Haney / Ecological Economics 38 (2001) 259–274                263

lent at a larger geographic scale. This metric              of the five different forest age classes (seral
provides information somewhat similar to that              stages). The values for each of these indicators, by
offered by specificity indicators reflecting the oc-            forest stage, are shown in Table 1. Table 1 also
currence (abundance) of species within a given              indicates the percentage of species that were
geographic space or ‘cluster’ of sites (Dufrene and           uniquely detected within each seral stage. This
Legendre, 1997; Legendre and Legendre, 1998).              illustrates that each forest seral stage displays its
  Finally, we computed a similar indicator (Sb)             own particular set of species.
by weighting species richness again, this time by              Of course there are additional indicators that
regional population prevalence as calculated from            one could develop and use. For example, one of
the Breeding Bird Atlas programs. Sb was com-              the factors that a conservation planner may wish
puted as:                                to consider might involve the relative scarcity of
                                     different forest types, in combination with the
    Si
Sb = % [1− RPi ]                        (2)    number of species unique to each type. Such a
   i=1
                                     metric would provide somewhat different infor-
                                     mation when compared to indicators Sa and Sb.
where RPi denotes the prevalence factor for spe-
                                     However, note that Sa and Sb do explicitly incor-
cies i at the regional scale. This indicator weights
                                     porate the underlying relative scarcity of habitat
species richness to reflect those species present in
                                     types that play host to each particular species
our study area that are not common at the re-
                                     considered. These indicators do this by weighting
gional level (in this case, across the northeastern
                                     each species by the percentage of land (on either a
United States). As the number of species in a
                                     local or regional basis) on which the species is
forest age class that are not prevalent regionally
                                     estimated to occur (and hence the percentage of
goes up, Sb rises as well.
                                     land that currently provides habitat suitable to
  The work described above yields multiple indi-
cators of diversity or diversity/prevalence for each           each particular species). To the extent that a

Table 1
Indicators of biodiversity in Pennsylvania hemlock-northern hardwood forest plots of different seral stagesa

                    Forest seral stageb,c
Indicators

                    Early (15.2%)   Transitional    Mid-successional Late successional Old growth
                             (31.2%)       (41.2%)     (12.0%)      (0.4%)

Total number of bird species      9         17         20       34         20
% Bird species uniquely detected in  22         24         10       29         40
 seral stage
Total number of bird genera       9         17         16       25         15
Total number of bird families      2         9          8       11         10
Species richness weighted by      2.5        4.3         5.9      12.9        10.1
 physiographic province (local)
 population prevalence (Sa)
Species richness weighted by      2.6        5.0         7.2      15.9        11.5
 regional population prevalence
 (Sb)

 a
  Sources of data: J.C. Haney, unpubl. data collected 1992–1994; Dessecker and Yahner, 1984; Laughlin and Kibbe, 1985; Andrle
and Carroll, 1988; Brauning, 1992; Bevier, 1994; Buckelew and Hall, 1994; Foss, 1994; Palmer-Ball, 1996; Robbins and Blom, 1996;
Nicholson, 1997.
 b
  Early seral stage = stand age of 4 years; transitional = 9 years; mid-successional =approx. 50 years; late successional = approx.
120 years; old growth =300+ years.
 c
  The relative prevalence of each seral stage forest type found in Pennsylvania (as a percentage of total forestland) is given in
parentheses under the seral stage names. These relative prevalence values are derived from Alerich (1993).
             M.E. Eiswerth, J.C. Haney / Ecological Economics 38 (2001) 259–274
264

particular species is associated with (unique to)      however, at least one of the forest types contained
only one forest type, Sa and Sb embody the          species not commonly found elsewhere, then Sa
relative scarcity of that forest type.            and Sb would hold great meaning for objectives
  As a second example, a relative measure such as      such as preserving population sources, preventing
Sa/S, where S denotes number of species, may be       further habitat fragmentation, increasing wildlife
of value in certain situations with particular con-     corridors, and providing recreational services (i.e.
servation management objectives. Such a relative       viewing rare species) even to visitors from far
measure could provide a higher indicator value        away.
for a region that has very few species (e.g. 10) but
where a high percentage of those species are rare,
as compared to a region with many more species        4. Static approach and results
(e.g. 100) but relatively few rare ones. Some con-
                               4.1. Static illustration 1: choice of biodi6ersity
servation decision contexts may call for placing a
premium on rarity (and ignoring the absolute         indicator can dri6e habitat rankings and thus
number of species) and in such cases a measure        discrete choices regarding habitat conser6ation
such as Sa/S may be useful. At the same time, the
attraction of Sa by itself is that it does combine       The simplest problem involves a discrete choice
two different kinds of information: species rich-      problem of conservation. In such cases a decision-
ness and species rarity.                   maker may be interested in choosing a subset of
  We do not attempt in this manuscript to iden-       all geographic areas (one, in the simplest case) in
tify any one best indicator; indeed, indicators       which to devote habitat conservation efforts. This
need to be matched carefully to management ob-        situation may occur when available funding for
jectives since the choice of indicator will influence     conservation is sufficiently constrained. It also
the decision outcome. Various alternative indica-      may occur in processes that involve mitigation
tors, including but not limited to those in Table 1,     banking or compensatory restoration for lost nat-
have different meanings with respect to conserva-      ural resource service flows.
tion objectives and social/economic values. As an        Table 1 reveals several points relevant to rank-
example, a skilled birdwatcher may attach a great      ing our case study forest types. Perhaps the most
deal of importance to the sheer number of species      apparent feature is that regardless of the indicator
that he or she is able to see, on average, upon       chosen, the decision-maker would rank the late
visiting the forest. In contrast, an avid hiker or      successional forest first in terms of biodiversity as
angler untrained in birdwatching may derive plea-      well as biodiversity weighted by prevalence. This
sure from the incidental viewing of a wide variety      forest stage dominates the others in species rich-
of birds while recreating, but may be unable to       ness (34 species), higher taxa diversity (25 genera),
discern (or uninterested in noticing) differences      species richness weighted by physiographic
among species that are closely related. Such an       province (local) prevalence, and species richness
individual may attach more importance to the         weighted by regional prevalence.
indicators in Table 1 that relate to the total         Rankings of forest stages below the late succes-
number of bird genera or families, rather than        sional are more problematic. If number of species
species richness.                      is used as a biodiversity indicator, the decision-
  Similarly, the importance of indicators such as      maker’s second choice for conservation efforts
Sa and Sb in comparison with the others depends       could be either the mid-successional or old-
largely on the extent to which the conser-          growth seral stage. If, however, the number of
vation planner’s objectives are tied to a broader      genera were used as an indicator of higher taxo-
spatial (e.g. regional) context. If none of the spe-     nomic diversity, the decision-maker would pick
cies under consideration is rare in terms of preva-     the transitional age class over both the mid-suc-
lence within a larger spatial area, then the         cessional and old growth as the second priority
meaning of Sa and Sb would be minimal. If,          for conservation efforts.
             M.E. Eiswerth, J.C. Haney / Ecological Economics 38 (2001) 259–274          265

  Consideration of species prevalence factors        from one another, or with differences in visitor
yields even more interesting results. First, on aver-     profiles across the areas. Public preferences may
age, species found in the early, transitional, and      also be of a type such that it is important that
mid-successional forest types have high prevalence      natural attributes (such as species) can be enjoyed
values (relative to older forests) and correspond-      in multiple areas, even when the areas are not that
ingly lower species rarity factors. In contrast, on      far apart. If demand for natural areas and the
average, species found in older forests are less       service flows (e.g. birdwatching) that they offer is
prevalent at broader spatial scales. If the indicator     high relative to supply (this is the case in many
is defined as species richness weighted by preva-       wildlife refuges today), then congestion comes
lence at either the physiographic province (Sa) or      into play to make the presence of a species in one
regional (Sb) levels, then the old growth forest age     area a poor substitute for its presence in another.
class becomes the clear second choice for conser-       Consideration of risk and uncertainty provides an
vation efforts.                        additional basis for this assumption. As discussed
  The usefulness of Sa and Sb as indicators is now      in King (1997), uncertainty exists regarding the
clear, in that they attach a premium to forest age      effects on ecosystems of future natural and an-
classes containing species that are not common.        thropogenic changes. Since we do not know how
Such forest areas are potential population          future natural changes or human activities close
‘sources’ (Pulliam, 1988) of species not prevalent      to natural areas may affect their structure and
at broader scales. In Section 3 we also mentioned       function, a motivation exists to expend conserva-
other possible indicators, including relative mea-      tion efforts in multiple areas, even if they offer
sures such as Sa/S that attach complete impor-        similar ecosystem services today.
tance to relative species rarity with no weight         Given this assumption, a decision-maker that is
attached to the number of species. Such indicators      concerned with habitat conservation in multiple
would give a higher priority to old growth forests.      areas may wish to maximize the sum of biodiver-
                               sity across the areas, subject to a budget con-
4.2. Static illustration 2: choice of biodi6ersity      straint for conservation efforts. Consider the
indicator can significantly influence the allocation      following relationship between conservation ex-
of conser6ation expenditures among multiple          penditures and an indicator of biodiversity:
geographic areas
                               bi = ki + fi (Mi )                (3)
 In some instances a decision-maker may need         where bi is the expected value of a biodiversity
                               indicator in area i, ki E 0 is the expected value of
to make decisions regarding the allocation of
habitat conservation efforts in multiple geo-         a biodiversity indicator in area i given no conser-
graphic areas, rather than a discrete choice of        vation expenditures in area i, Mi denotes conser-
which area(s) to conserve. Such decision-making        vation expenditures in area i, and where
                               f %(Mi )\ 0, f %%(Mi )B 0. The function fi (Mi ) de-
requirements provide a richer context for analysis.       i      i
 We assume that characteristics of one geo-         notes the addition to the level of the biodiversity
graphic area are not substitutes for the same         indicator expected to result from conservation
characteristics found in another geographic area.       expenditures Mi.
In our case study this means, for example, that          Eq. (3) and the equations that follow are writ-
the presence of a species in a forest of a given       ten in the standard economic format of maximiz-
seral stage is not a substitute for its presence in      ing a variable subject to a constraint on
another forest area of a different stage. This is not     expenditures (M). However, the term M can also
a restrictive assumption, but rather is consistent      be interpreted more broadly as a money metric
with a number of real-world contexts. For exam-        equivalent of efforts devoted to conserving biodi-
ple, it is consistent with a situation in which a       versity. Similarly, it is possible to interpret the
decision-maker is interested in devoting efforts to      term b in (1) as a function of conservation efforts
natural or recreation areas some distance apart        rather than expenditures. One reviewer of this
             M.E. Eiswerth, J.C. Haney / Ecological Economics 38 (2001) 259–274
266

article has wisely pointed out that some important
conservation management steps may require less
out-of-pocket expenditure and more good (and
timely) planning, relative to alternative manage-
ment efforts. However, the standard economic
view is that such good and timely planning would
come at an opportunity cost, for example, hiring a
well-trained (and presumably well paid) ecologist
or wildlife biologist to spend part of his or her
time on the conservation planning process. For
this reason as well as ease of exposition, we refer
to M as conservation expenditure while realizing
that a more complex indicator of conservation
effort is also possible.                   Fig. 1. General shape of illustrative function linking expected
                               biodiversity to conservation expenditure.
  Consider a case in which a decision-maker is
interested in two different geographic areas in
                               make the simplifying assumption that k1 = k2 = 0.
different forest age classes. If the decision-maker
                               Relaxation of this assumption could change the
is interested in allocating conservation expendi-
                               numerical solution to the problem, but would not
tures between these areas, a relevant constrained
                               change the flavor of the concepts and results upon
maximization problem is:
                               which we focus in this manuscript.
Max[k1 + f1(M1)+k2 +f2(M2)]                   Second, we assume for illustration that the
                               conservation expenditures necessary to set the ex-
s.t.:M1 +M2 =M                   (4)    pected level of the biodiversity indicator equal to
                               the baseline (existing) level of biodiversity are
where M denotes the total resources available to
                               equal across the two geographic areas. For exam-
the decision-maker.
                               ple, if conservation expenditures involve purchas-
  As an illustration of the way in which the
                               ing land, this assumption would denote that land
choice of biodiversity indicators affects the solu-
                               costs are equal for the two areas. For our illustra-
tion, we consider a specific case of the generalized
                               tions, we use a specification that is consistent with
problem. First, assume for simplicity that k1 =
                               these assumptions as well as the standard eco-
k2 = 0; that is, in both areas, the indicator of
                               nomic assumption of diminishing returns to
biodiversity is expected to be zero if conservation
                               expenditures:
efforts are zero. This is a special case of the more
general case ki E 0 and corresponds to a situation      fi (Mi )= (b 0)(M) − 1/2(Mi )1/2              (5)
                                      i
where a decision-maker is interested in protecting
                               where i denotes forest area i and b 0 the baseline
all or a portion of a land area from complete
development, e.g. total conversion of land into        (current) level of biodiversity there. The general
housing subdivisions, a relevant scenario in many       shape of this function is shown graphically in Fig.
parts of the United States. That is, the special case     1, which illustrates that additional conservation
is that if the decision-maker makes no conserva-       efforts purchase a higher level of expected biodi-
tion expenditures, then complete habitat destruc-       versity but at a diminishing rate. Though we
tion will occur. We certainly recognize that in        assume for simplicity in our numerical analyses
                               that ki = 0, Fig. 1 depicts the more general case in
reality biodiversity does not necessarily equal zero
                               which ki \ 0 (some biodiversity will remain if no
even when land is completely developed. How-
ever, we have not collected data on biodiversity       conservation efforts are undertaken).
for our case study bird species in a formerly          The first-order condition, which gives the solu-
comparable area (e.g. close to our study sites) that     tion to the constrained maximization problem
has been deforested and developed. Therefore we        (noneconomists may see Chiang (1974) for an
               M.E. Eiswerth, J.C. Haney / Ecological Economics 38 (2001) 259–274          267

introduction to constrained maximization) shown          conservation planning. Some natural systems have
in Eq. (4), is:                          a very large number of species but relatively low
                                 diversity at higher taxonomic levels. In contrast,
(b 0)(M1) − 1/2 =(b 0)(M2) − 1/2.             (6)   some systems, for example, some marine and
  1        2

                                 coastal ecosystems, are strikingly rich in their
  To show the implications of using alternative         endowment of diverse families with relatively few
indicators of biodiversity as input to the con-          species representing each of those families (Ray,
strained maximization problem, we consider the          1988).
case in which forest areas 1 and 2 are currently in         When species richness is weighted by regional
transitional and mid-successional stages, respec-         population prevalence (to form the indicator Sb),
tively. The comparison between these two stages
                                 the allocation of expenditures shifts substantially
is interesting because neither one dominates in
                                 toward the older (mid-successional) forest. Using
terms of biodiversity.
                                 this indicator, 68% of total conservation expendi-
  The results from using alternative indicators are
                                 tures will be targeted toward the mid-successional
summarized in Fig. 2. Clearly the choice of indi-
                                 forest class. This outcome reflects the area’s abil-
cator can influence decisions on how to allocate
                                 ity to act as a source for species that are not
efforts. In our illustration, the difference between
                                 highly prevalent on a wider regional basis. As
using species richness and a higher taxa diversity
                                 shown in Fig. 2, for the three indicators exam-
indicator is significant (33% more expenditures
                                 ined, the outcome may range from a low of 44%
devoted to the transitional forest area using a
                                 to a high of 68% of total available conservation
higher-taxa indicator rather than species richness).
                                 expenditures being devoted to the older forest
For the subclass of problems where a decision-
                                 area. The sensitivity of the solution to the choice
maker is interested in purchasing land or prevent-
                                 of indicator illustrates the potential volatility of
ing development so as to preserve biodiversity,
                                 decision-making processes to the types of infor-
even the differential found in our illustration
                                 mation considered.
would lead to a difference in the portfolio of
forest areas that the planner chooses to buy/pro-
tect. In some cases, the choice between these two
indicators can have a substantial influence on
                                 5. Dynamic approach and results

                                   The relatively small subset of structural at-
                                 tributes that exhibit temporal linearity, and the
                                 threshold changes that occur in forests during
                                 succession, create distinct stages in forest ecosys-
                                 tems. To adequately characterize such ecosystems,
                                 time-varying stages and threshold effects must be
                                 taken into account. As in other ecosystems, diver-
                                 sity in our case study system is time-scale depen-
                                 dent, that is, dependent upon time from the most
                                 recent disturbance.
                                   As a result, it is important to consider not only
                                 the current levels of diversity in particular areas,
                                 but also the diversity levels that the areas can
                                 potentially offer society in the future. The general
                                 problem may be viewed as choosing management
                                 options to maximize the expected ‘flow’ of diver-
                                 sity from the present to some point in the future,
Fig. 2. Allocation of conservation expenditures: static frame-
                                 subject to a budget constraint.
work.
             M.E. Eiswerth, J.C. Haney / Ecological Economics 38 (2001) 259–274
268

  Forests can experience abrupt structural          seral stage. If the decision-maker is interested in
changes in either of two directions. Successional       maximizing biodiversity over this period, then the
changes occur as the forest moves through growth       relevant maximization problem is:
phases (seres), each consisting of varying intervals
                                  T
when structure is relatively constant but where
                               Max % [ f 1(M 1)+ f 2(M 2)]
                                    t     t
rapid transition occurs between seres. Succession         t=1
can also be reversed, and the entire set of ecolog-
                               s.t.: M 1 + M 2 = M
ical processes renewed, when catastrophic distur-                                (7)
bance (either man-made or natural) shifts forest
                               where M 1, M 2, and M may be thought of as the
structure back to an earlier sere. In the forests
used in our analysis, natural disturbances that        discounted present values of the opportunity costs
completely remove canopy trees occur very rarely,       of conservation that are incurred between now
about every 1200 years (Canham and Loucks,          and period T (expressed in this way to simplify
1984; Frelich and Lorimer, 1991). At large land-       the exposition). As with the static case, M is the
scape scales all successional stages can be main-       total amount of resources available for conserva-
                               tion, and M 1 and M 2 are the amounts to be
tained in perpetuity, although not always in the
same amount or location (Shugart, 1984). In          allocated to forest areas 1 and 2, respectively.
other words, by protecting relatively large areas of       For most natural systems, scientists have not
forest, it is possible to ‘purchase’ increased levels     collected continuous data on the ways in which
of certainty that a forest area will progress as       various indicators of biodiversity change over
anticipated through its natural growth phases.        time. At best, a limited set of observations may
  In this section we provide illustrations of the      exist for particular stand ages in forests, for exam-
relevance of natural dynamic processes. Section        ple. In other cases, very little direct information is
5.1 illustrates the importance of recognizing that      available. For our case study, we have the benefit
change may not be linear, and highlights the need       of possessing standardized observations of bird
for better data on how and when ecosystems          diversity in forests that are very similar (in terms
encounter thresholds. Section 5.2 shows that         of climate, geographic zone, etc.) except that they
choice of time horizon and biodiversity indicator       are of different ages.
may affect the dynamic solution to preservation,         To illustrate the importance of knowing how
but not necessarily in the expected ways. Section       natural systems evolve, suppose for a moment
5.3 illustrates how a dynamic approach may dif-        that all that we knew about the problem was the
ferentiate natural areas that look equivalent from      current number of species and higher taxa for
a static viewpoint.                      both areas, as well as the same information for
                               the late successional stage that both areas are
5.1. Dynamic illustration 1: the importance of        expected to evolve into over the next 100 years.
                               Assume further that diversity is expected to in-
accounting for nonlinear, discontinuous ecological
                               crease in linear fashion over time in either forest
processes
                               area. In this case, the choice problem would in-
                               volve choosing M 1 and M 2 to maximize the sum
  Consider the case in which a decision-maker
wishes to maximize the sum of a biodiversity         of the areas under the (linear) biodiversity time
indicator across two different forest areas, the first     paths in the two forests. Solution of this problem,
stand of 30 years and the second stand of 90         using species as a biodiversity indicator and the
years. We assume that, for each of the seral stages      same diversity–expenditure functional forms
we examine, diversity is characterized by the ob-       shown in Eq. (5), would provide the answer that
servations shown in Table 1. Suppose that the         42% of the available resources (opportunity costs)
decision-maker’s time horizon, T, is 100 years. It      for conservation would be devoted to forest area
is expected that, by time T, both of these forest       1 (transitional), and 58% to forest area 2 (mid-
areas will have evolved to the late successional       successional).
               M.E. Eiswerth, J.C. Haney / Ecological Economics 38 (2001) 259–274               269

Table 2
Allocation of conservation expenditures among transitional and mid-successional forest areas, under alternative time horizons and
indicators of biodiversitya,b

Time horizon        Number of species   Number of families   Species richness indicator
              indicator (S)     indicator (F)      weighted by regional population prevalence (Sb)

Time horizon= 50      Area  1:  44%    Area  1:  55%     Area  1:  36%
              Area  2:  56%    Area  2:  45%     Area  2:  64%
Time horizon= 100     Area  1:  37%    Area  1:  47%     Area  1:  29%
              Area  2:  63%    Area  2:  53%     Area  2:  71%
Time horizon= 150     Area  1:  41%    Area  1:  47%     Area  1:  36%
              Area  2:  59%    Area  2:  53%     Area  2:  64%

 a
  Forest area 1 is currently in the transitional seral stage with a stand age of 10 years. Forest area 2 is currently in the
mid-successional seral stage with a stand age of 50 years.
 b
  Each percentage in the table denotes the percentage of total conservation expenditures that will be devoted to a forest area,
according to the solution of the dynamic constrained maximization problem defined in the text.




                                  5.2. Dynamic illustration 2: the choice of time
  Now consider the problem given our knowledge
                                  horizon and biodi6ersity indicator may ha6e a
that the biodiversity time path more closely re-
                                  significant impact on the dynamic solution, but
sembles a step function than a linear function. It
                                  not necessarily in monotonic fashion
is intuitively clear that forest area 2, currently at
stand age 90, will enter the late successional seral
                                    Consider once again the allocation of conserva-
stage significantly sooner than forest area 1. Once
                                  tion expenditures between a current transitional
the late successional stage is reached, the forest
                                  forest area and a current mid-successional area.
area will exhibit higher levels of biodiversity as
                                  Given the knowledge that the biodiversity time
measured by numbers of species, genera, or
                                  path is subject to discontinuities as forests move
families. Therefore, one would expect that, if we
                                  from one seral stage to the next, how does the
take account of the step function nature of the
                                  choice of time horizon affect the solution to the
biodiversity time path, a premium would be
                                  problem in Eq. (7)? And how does the choice of
placed on conservation efforts in forest area 2.
                                  biodiversity indicator influence the result? We
Solution of the maximization problem accounting
                                  consider three alternative time horizons (50, 100,
for a stepwise progression bears this out: using
                                  and 150 years) and three alternative indicators (S,
species again as an indicator of biodiversity, the
                                  F, and Sb). The solutions to the problem under
solution would involve only 33% of conservation
                                  these conditions are shown in Table 2.
efforts in forest area 1 (vs. 42% assuming a linear
                                    Three main points emerge from Table 2. First,
time path), with 67% of efforts now devoted to
                                  conservation allocation outcomes vary signifi-
forest area 2.
                                  cantly according to choice of indicator and time
  The difference in solutions under linear and
                                  horizon, from a low of 29% to a high of 55% of
step function approaches is perhaps not that strik-
                                  total expenditures devoted to forest area 1. Sec-
ing for the particular example we have chosen,
                                  ond, the dynamic solutions depend on the time
though it is significant. The salient point is that
                                  horizon chosen but not necessarily in monotonic
the incorporation of information on threshold
                                  fashion. For example, Fig. 3 illustrates how the
effects can affect the decision-making process.
                                  allocation of expenditures varies according to T
Certainly there are cases in which accounting for
                                  when species richness is used as an indicator of
these effects may have a substantial bearing on
                                  biodiversity. The optimal percentage of resources
the planner’s decision, depending on the natural
                                  to be devoted to forest area 1 (transitional) first
systems and time horizons considered.
               M.E. Eiswerth, J.C. Haney / Ecological Economics 38 (2001) 259–274
270

                                 50 to 100 (Table 2), for the same reasons de-
declines as the time horizon is increased from 50
                                 scribed above for species. However, extension of
to 100 years, then rises as T goes from 100 to 150.
                                 T from 100 to 150 leaves the solution unchanged
This is because the expected passage of both
                                 with number of families as the indicator, unlike
forest areas into the late successional stage, which
                                 the pattern under the species indicator. This is due
exhibits markedly high biodiversity, is considered
                                 to the way in which species appear and disappear
to varying degrees according to the chosen time
                                 as the forest moves through seral stages. Specifi-
horizon. With T=50, passage to the late succes-
                                 cally, the number of species may increase or de-
sional stage is considered for neither forest area,
                                 crease through time without there occurring a
and so the current levels of biodiversity largely
                                 change in diversity as measured at higher taxo-
drive the result. With T = 100, passage of forest
                                 nomic levels. The same kind of pattern can occur
area 2 to the late successional stage is taken into
                                 for genetic diversity, i.e. if closely related species
account while that of forest area 1 is not. As a
                                 appear or disappear through time, species diver-
result, a premium is attached to conserving forest
                                 sity may change significantly while genetic diver-
area 2 and the percentage of total expenditures
                                 sity does not.
devoted to it rises. With T = 150, the passage of
both forest areas to the late successional is consid-
                                 5.3. Dynamic illustration 3: a dynamic approach
ered, and so emphasis shifts back toward a some-
                                 may differentiate areas that are equi6alent from a
what higher level of emphasis on forest area 1.
                                 static perspecti6e
While the shifts in expenditures for this illustra-
tion may not be dramatic, they are indicative of
                                  Now consider the allocation of expenditures
the implications of choice of T for preservation
                                 between two forest areas both currently in the late
decisions in general.
                                 successional stage but that have different stand
  Third, the influence of altering T depends on
                                 ages. Specifically, consider forest areas 1 and 2,
the indicator of biodiversity that is used. For
                                 which have stand ages of 125 and 250 years,
example, using number of bird families as an
                                 respectively. Assume that these areas display simi-
indicator, conservation efforts devoted to forest
                                 lar numbers of species, genera, and families. The
area 2 (mid-successional) increase as T goes from
                                 main difference between them is that forest area 2
                                 will evolve into an old growth forest 125 years
                                 sooner than forest area 1.
                                  Of course, if the two areas currently are similar
                                 in terms of biodiversity, a static approach would
                                 give them equal weight regardless of the indicator
                                 used. However, one does not necessarily give
                                 them equal weight if dynamics are taken into
                                 account. The solutions to Eq. (7) for this problem
                                 are shown in Table 3. With T= 50 years, the two
                                 areas have equal weight because neither one will
                                 have progressed out of the late successional seral
                                 stage. With T= 100 or 150, however, the younger
                                 forest area (1) will be accorded a significantly
                                 higher percentage of conservation efforts (61 and
                                 66% of the total for T=100 and T= 150, respec-
                                 tively). As the time horizon increases, then, a
                                 decision-maker interested solely in maximizing the
                                 biodiversity indicator will attach more importance
Fig. 3. Allocation of expenditures may be nonmonotonic with
                                 to conserving the younger late successional forest
respect to time horizon T: dynamic framework using species
                                 area.
richness.
               M.E. Eiswerth, J.C. Haney / Ecological Economics 38 (2001) 259–274          271

Table 3                              argument against conserving old growth. How-
Allocation of conservation expenditures between two late suc-
                                 ever, it does indicate strongly that decision-mak-
cessional forest areas of different stand age: dynamic
                                 ers should clearly and deliberately prioritize
frameworka
                                 conservation objectives on a site-specific basis, as
                                 well as recognize that particular objectives may
Time horizon   Relative expenditures by area, using
         species richness indicator            sometimes lead to decisions that run counter to
                                 conventional wisdom.
         Area of stand     Area of stand
         age =125        age =250

                                 6. Conclusions
50 years     50%          50%
100 years    61%          39%
150 years    66%          34%             We have used data from forest ecosystems to
                                 illustrate several key concepts relevant to biodi-
 a
  Each percentage in the table denotes the percentage of
                                 versity. First, the solution to a static biodiversity
total conservation expenditures that will be devoted to the
                                 preservation problem may depend significantly on
corresponding forest area, according to solution of the dy-
namic constrained maximization problem defined in the text.    the biodiversity indicator used. This is an impor-
                                 tant concept for decision-makers to understand
  This result may stand at odds with expecta-          and assess, particularly at the site-specific level.
tions, given that the older forest area (2) will         The use of alternative indicators to examine the
progress to old growth 125 years sooner, and           multiple attributes of natural systems, and the
given the importance that society generally associ-        extent to which those attributes are at risk, can
ates with old growth forest. The result is driven         force a useful reexamination of conservation ob-
by the fact that the old growth seral stage is          jectives. The choice of final indicators to use as
actually less diverse (as measured both by number         guides may vary greatly from case to case and will
of species and number of higher taxa) than the          depend on the context of the problem and the
late successional seral stage. Therefore, conserva-        ecosystem services that are most highly valued by
tion decisions made solely on the basis of antici-        the public.
pated biodiversity will tend to favor the late            Second, for any given indicator, dynamic solu-
successional stage over old growth, and therefore         tions may differ from the static solution, depend-
result in the conservation of younger forests. This        ing on the time horizon chosen by the
is an issue that may arise in a number of different        decision-maker. This forces a reexamination of
types of forest systems since evidence suggests          the timeframes that we wish to take into account
similar patterns in a variety of forest types.          when considering future streams of ‘biodiversity
  Clearly, there may be other reasons to value old        services’, or ecosystem functions and services
growth forest besides numbers of species or higher        more broadly. This is a simple concept, but the
taxa (Brunson and Shelby, 1992). For example,           existing literature does not adequately address it,
note that in Table 1 we show that a relatively          particularly for cases in which ecosystems are
large number of the species found in old growth          expected to display discontinuous processes in the
were uniquely detected in that forest type. Second,        future. Our analysis also highlights the need for
a relative measure such as Sa/S (which prioritizes        dynamically adaptive management, rather than a
areas solely according to the percentages of their        long-term fixed formula for conservation, since
species collections that are not prevalent at a          the portfolio of biodiversity and forest types will
broader scale) would attach high importance to          continue to change as time passes.
old growth. Third, individuals may exhibit prefer-          Third, for any given indicator, dynamic solu-
ences for recreation in old growth forest because         tions can depend on the time horizon chosen, but
of factors totally unrelated to biodiversity. The         not necessarily in monotonic fashion. This is a
counterintuitive result of this illustration certainly      characteristic not common to well-behaved dy-
is not (and in no way is intended to be) an            namic models and therefore merits special atten-
             M.E. Eiswerth, J.C. Haney / Ecological Economics 38 (2001) 259–274
272

tion. Fourth, the effect of changes in the time        goods) may affect future patterns of demand.
horizon on the dynamic solution is dependent on        Such changes are equally uncertain.
the indicator used, which reinforces the need to         Future research might assess the relative impor-
consider multiple proxies.                  tance of different sources of uncertainty in factors
  This manuscript does not deal with choosing        affecting supply and demand. This is likely to be
any one indicator over another, but rather em-        quite site specific. In some instances, uncertainty
phasizes that the choice of indicator certainly does     regarding future demand for environmental
matter and should be linked to conservation ob-        amenities may swamp that connected with future
jectives. At the same time, the issue of indicator      ecosystem processes. As mentioned above in con-
reliability will be important in actual decision-       nection to forests, catastrophic disturbance (either
making applications. Reliability is largely a statis-     man-made or natural) can reverse the successional
tical issue and depends on criteria such as          process. In the forests we examined, however,
sensitivity, specificity, and predictability. A signifi-    natural widespread disturbances rarely occur and
cant literature exists to help guide practitioners on     many types of preservation efforts can effectively
this point (e.g. Murtaugh, 1996; Dufrene and         insulate areas from major anthropogenic effects
Legendre, 1997; Legendre and Legendre, 1998).         such as land development. Therefore, uncertainty
  Our analysis is illustrative in nature in that it     in ecosystem service supply may be small relative
relies upon an example relationship between con-       to uncertainty in future demand for environmen-
servation effort and conserved biodiversity, rather      tal amenities. In other types of systems, where
than an empirically estimated function between        disturbance is more likely and vulnerability to
these two variables. The impact of conservation        disturbance may be higher (some coastal ecosys-
effort on any given biodiversity indicator will vary     tems may fall into this category), there may be
from site to site and potentially through time for      substantial uncertainty in forecasting the supply
any particular site. Future ecological research to      of ecosystem services for several years into the
examine the biodiversity ‘returns’ from increased       future.
conservation activities, as well as the way that this
relationship varies by indicator, would be quite
useful.                            Acknowledgements
  We intentionally have not incorporated uncer-
tainty in any fashion in this analysis, primarily to       Financial support was provided by the Center
avoid detracting from the major points of interest.      for Rural Pennsylvania (CRP), DuBois Educa-
Incorporation of this factor, however, represents       tional Foundation Fund for Academic Excellence,
an important avenue for further research. For any       Pennsylvania State University Research and De-
given natural area, uncertainty exists regarding       velopment funds, the USDA Cooperative State
the future demand for and supply of various          Research, Education, and Extension Service, and
ecosystem functions and services. Natural forces,       a Challenge Grant from the Migratory Bird
as well as future anthropogenic change (e.g.         Office, Region 5, US Fish and Wildlife Service
changes in patterns of adjacent human develop-        (USFWS). D. DeCalesta, J. Palmer, and S. Stout
ment or changes in effects from pollutants trans-       (US Forest Service), L. Lentz, J. Sowl, and D.
ported into the area), may change the supply of        Wright (CRP), T. Mountain and D. Pence (US-
amenities that the ecosystem offers. However the       FWS), C. Schlentner (Cook Forest State Park),
directions, magnitudes, and timing of such poten-       and C. Schaadt provided logistic support, access
tial future changes, as well as the ways in which       to study areas, or other assistance that greatly
the area will respond, are uncertain (King, 1997).      facilitated this study. J. Lydic and R. Williams
In the same way, a host of factors (changes in        performed many of the summary analyses. For
human population distributions, demographics,         their help with the breeding bird censuses and
preferences for goods and services, and the rela-       other field work, we thank B. Allison, J. Cheek,
tive prices of environmental amenities and other       L. Hepfner, R. Kaufmann, J. Lydie, C. Schaadt,
                M.E. Eiswerth, J.C. Haney / Ecological Economics 38 (2001) 259–274               273

                                  Faith, D.P., 1992. Conservation evaluation and phylogenetic
J. Seachrist, J. Smreker, S. Weilgosz, S. Wetzel,
                                   diversity. Biological Conservation 61, 1 – 10.
and R. Williams. We thank S. Ragland and three
                                  Foss, C.R., 1994. Atlas of Breeding Birds in New Hampshire.
anonymous reviewers for comments on previous             Audubon Society of New Hampshire. Arcadia-Chalford
versions of this manuscript.                     Publishing, Dover, NH.
                                  Frelich, L.E., Lorimer, C.G., 1991. Natural disturbance
                                   regimes in hemlock-northern hardwood forests of the Up-
                                   per Great Lakes Region. Ecological Monographs 61, 145 –
                                   164.
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