MODELING IN THE COLUMBIA PLATEAU
included 9,693 km² in existing status category I and II lands
and 9,145 km² in the 105 subwatersheds identified as important
by the expert panels. The results of the alternatives are shown
in Table 4. The coarse-filter alternative only sought representation
of the vegetation alliances in each section as mapped by GAP, of
which 122 of the 195 target elements were considered vulnerable.
[Note that our use of the term ``vulnerable'' is based on representation
and is different than TNC's definition, which is based on global
distributions]. An additional 185 subwatersheds were selected to
achieve the representation goals (Figure 6), basically doubling
the total area of existing BMAs and core areas.
Comparison of alternatives
BMA area (km²)
core area of 105 subwatersheds (km²)
watershed area selected (km²)
of watersheds selected by BMAS
coarse- and fine-filter
Map of the coarse-filter alternative
the 359 rare species and plant associations that are vulnerable
required substantially more area (501 subwatersheds, Figure 7) because
the locations of these target elements tend to be widely scattered.
Whereas the area of the subwatersheds containing these rare elements
was approximately 160% greater than the area for representing GAP
alliances, the suitability index was more than 400% greater. Thus
even the most suitable subwatersheds containing rare elements (mean
index of 5.9) was much less suitable than those for alliances (mean
index of 3.1). This result indicates that there are many more options
of where alliances can be represented than the relatively few sites
available for rare elements. This lower overall site suitability
should also not be surprising because many of the rare elements
are only found in isolated habitat fragments in cultivated areas.
coarse- and fine-filter alternative found some efficiencies in representing
both sets of elements (481 vulnerable elements) simultaneously (Figure
8). The total area and number of subwatersheds selected were substantially
less than the sum of the coarse-filter and fine-filter alternatives
taken individually. Mean suitability index (5.7) was similar to
that of the fine-filter sites, however, because representing rare
elements does not leave much flexibility without selecting very
low suitability sites. In fact, 273 of the 359 rare target elements
occur at no more sites than required by the representation goals.
Thus all their occurrences had to be selected, making 321 of the
567 subwatersheds "irreplaceable."
Map of the fine-filter alternative
Map of the integrated coarse- and fine-filter alternative
and sweep analysis
The analysis of coarse- and fine-filter elements by the planning
units identified by the expert panel workshops is shown in Table
5 in terms of area and number of subwatersheds covered and number
of elements left vulnerable (i.e., with area below the representation
goal. The number associated with the expert alternative is the number
of workshops, out of six, that independently identified the planning
unit as a priority. Even if every planning unit identified by at
least one panel were selected, or 2,681 subwatersheds covering greater
than 63% of the ecoregion, 18 of the 195 vulnerable land-cover types
would remain vulnerable to some extent. If only the 105 subwatersheds
were selected in which at least 4 panels concurred, only 6% of the
ecoregion would be selected but 122 land-cover types would not reach
their representation goals. Thus while the expert panel approach
is unquestionably useful to identify some critical high priority
sites, it is inadequate, at least in the Columbia Plateau ecoregion,
as a means to represent other measures of biodiversity. At best,
it is inefficient with most of the ecoregion identified as a priority
for at least some taxonomic group (at the resolution of subwatersheds).
At worst, when only those sites on which the experts concur are
chosen, many other target elements are not adequately represented.
The policy question about the relative role of public and private
lands in assembling a conservation portfolio was addressed by comparing
the results of the integrated coarse- and fine-filter alternative
to a variation which strongly favored public lands. The public lands
alternative was only slightly less efficient than the baseline alternative.
Total area selected was 57,173 km², an increase of 1.5%, and
actually selected one less subwatershed. However, the two alternatives
shared 530 planning units in common, with only 36 unique to the
public lands alternative and 37 unique to the baseline. Further,
while the baseline had a public/private mix of 47.5/52.5%, the public
land alternative shifted this only to 49.1/50.9%. These findings
suggest that even with a very heavy weighting to favor public lands
in the BMAS solution, the outcome was quite similar to the baseline.
Evidently, the rarer elements occur primarily in habitat remnants
on private lands. This makes their planning units irreplaceable
in any portfolio with the given representation goals. Hence, for
the Columbia Plateau there is relatively little flexibility in achieving
this set of goals.
Results of the sweep analysis by the subwatersheds identified
by the expert panels.
of Expert Panels
core area (km²)
BMA Area including existing (km²)
subwatersheds selected by experts
remaining vulnerable land-cover types (out of 195)
AND RECOMMENDATIONS TO TNC
to research questions
At the beginning
of the report, we posed three questions that this research would
attempt to answer. Here we summarize our findings with respect to
set of assembly (i.e., decision) rules provides the most efficient
method for designing and assembling a portfolio of sites to maintain
all viable native species and community types within a target ecoregion
(i.e., how can TNC maximize the amount of biodiversity protected
within a given number of conservation sites or amount of land area)?
process used in this prototype developed a set of assembly rules
that generated the most efficient portfolio of sites that met TNC's
goals for coarse-filter representation of vegetation alliances and
fine-filter representation of rare species and plant associations.
In doing so, the modeling approach was able to select a set of highly
suitability sites that met the criteria of being relatively undisturbed
by human activities, more easily managed for biodiversity, and were
close to a set of core areas. In summary, the assembly rules ultimately
selected by the core planning team include:
all existing status 1 or 2 managed areas
2) Add all
subwatersheds in which at least four of the six expert panel workshops
identified sites as high priority for conservation
3) Use the
BMAS model to select a set of sites that complement the core areas
from rules #1 and #2 in meeting the specified coarse- and fine-filter
representation goals while maximizing efficiency and suitability.
To implement this rule, the core planning team also had to decide
upon rules for suitability factors and their weights, biodiversity
elements to represent, and their representation goals.
4) Modify the
BMAS set of sites as appropriate based on local knowledge of site
conditions or unresolveable socio-political issues
the TNC planning team, the new portfolio satisfied their intention
for greater representation beyond the known occurrences of rare
elements. The sites selected through the BMAS modeling process generally
made sense to the team when examined in detail for which elements
they contained. Some sites selected were ones the state offices
had been considering for inclusion in their portfolio but had not
yet done so. Many sites in the existing portfolio were not selected
in the new planning process, evidently because more efficient (and/or
suitable) sites were available to represent the same elements.
workshops is a popular approach for setting conservation priorities,
and one that is being used by TNC in several ecoregions. While not
used to assemble the portfolios from the six states in the Columbia
Plateau ecoregion, we wanted to examine how well the priorities
from the expert workshops swept the various biodiversity targets.
Because the experts were not asked to identify sites to represent
alliances, it is not surprising that these coarse-filter targets
were not swept well by the sites chosen by experts for other objectives.
Even if every site identified by any of the six workshops was in
a portfolio, covering 63% of the land area in the ecoregion, 18
of the 195 land-cover targets were inadequately represented and
hence would still be vulnerable. And the subwatersheds with sites
identified by at least four of the six workshops (i.e., the ones
used as core areas in the preferred alternative) left 63% of the
land-cover types vulnerable.
Thus the expert
opinion approach can identify sites with the best representatives
of the target elements studied by the group. The approach lacks
any explicit representation goals for measuring overall conservation
achievement. Incorporating the sites agreed upon by the most experts
from different biological specialties as core areas, as was done
in the Columbia Plateau study, takes advantage of the collective
knowledge of these experts while adding an objective means for meeting
all goals efficiently.
sensitive is the portfolio to the way in which biodiversity is measured
(e.g., what are the effects of using a coarse-filter (alliances
from Gap Analysis) or fine-filter (rare element occurrences for
species and plant associations from Heritage programs)?
portfolios based on cover types and rare elements yield vastly different
solutions in terms of number of subwatersheds and total area selected
and generally do not provide adequate representation, or sweep,
each other (Table 4). With the representation goals for rare elements
set by the TNC planning team, many sites are irreplaceable in both
the fine-filter and the integrated alternatives. Thus there is a
good deal of overlap for any alternatives involving rare elements.
Suitability of sites becomes a much less important consideration.
If the representation goals were set lower than the number of occurrences,
then the alternatives could become more sensitive, i.e., fewer irreplaceable
can TNC integrate programmatic, economic and socio-political factors
into the portfolio design process without sacrificing its biodiversity
primary mission of TNC is to protect biodiversity. Yet there are
a number of factors that constrain the manner in which the organization
is able to achieve its primary goals. Recognizing these constraints
in the portfolio design process will undoubtedly be more efficient
than having to respond to them during implementation. BMAS has been
formulated to enforce that biodiversity goals are achieved (in terms
of the desired level of representation, Mink) while minimizing
the impact of these other factors. We have attempted to address
these assorted factors through the use of the second objective in
the BMAS model, namely suitability. The suitability index has been
computed to integrate factors, derived from existing GIS coverages,
about the effects of roads, human settlements, and land ownership
and use. Collectively, these factors define the manageability of
each watershed for long-term maintenance of biodiversity, both in
terms of existing condition (and potentially of restoration needs)
and of the cost and political impact of establishing biodiversity
management areas. The use of weights in combining the various factors
into the overall index allows the relative importance of each factor
to TNC's design philosophy to be recognized. Further, the weighting
can be modified as part of a sensitivity analysis to determine either
the significance of individual factors or to explore alternative
themes. For instance, we greatly increased the weight on the percentage
of private land to evaluate the consequences of greatly favoring
public over private lands in the portfolio. Because the solution
was quite similar to the original integrated alternative, the distribution
of biodiversity in the Columbia Plateau ecoregion, particularly
rare elements, is such that private lands are critical for achieving
issues may be specific to certain sites known to TNC's planning
team but are not mappable across all sites in the ecoregion. An
example would be where a land owner's management objectives are
known to be in unresolveable conflict with TNC's. In such cases,
these planning units could be flagged as unavailable for selection
by the BMAS model (i.e., would be modeled as a constraint where
the appropriate Xj had to be equal to 0). In this project,
integration of local expertise was done through a site-by-site evaluation
by the planning team, with fine-tuning to modify the initial solution
from the computer model. Adding such detailed knowledge at this
step reduces the effort by the planning team which only has to deal
with reviewing candidate sites rather than trying to document everything
they know about the entire pool of planning units.
to The Nature Conservancy
The major purposes of a pilot study such as this are to learn
the advantages and limitations of the process, to recommend actions
for implementation of the prototype on a wider basis, and to identify
future research needs revealed by the study. This final section,
therefore, concludes with a set of recommendations for TNC's ecoregion
Although reserve selection algorithms produce solutions that may
not be the best when scrutinized using better data or additional
criteria, they have proven to be powerful indicative tools and very
effective at facilitating understanding, group planning and negotiation
(Pressey et al. 1995). The planning approach applied in the Columbia
Plateau ecoregion guarantees that specific representation goals
are achieved. While these goals may only be estimates of the effort
needed to conserve biodiversity, they at least are explicit in the
prototype process and can be modified in future revisions if new
information becomes available. Scoring and expert opinion approaches,
in contrast, are good at identifying high quality sites but do not
attempt to represent all varieties of biodiversity. They are also
labor-intensive and therefore do not lend themselves to exploration
of alternatives (e.g., changing the scoring system). We believe
that a BMAS type of modeling technique and the expert approach are
complementary and can be used effectively in tandem. The expert
process integrates knowledge of site quality that is not easily
incorporated into the modeling approach. Specifically we recommend:
use expert panels to identify a set of core areas that must be protected
in any portfolio, followed by the BMAS or a similar model to select
additional planning units as needed to meet the representation goals.
The BMAS model
can be formulated to cluster additional sites around these core
areas and to give extra weight to non-core areas that were nevertheless
identified by some of the experts. Alternatively, instead of assigning
core areas, the sites identified by many expert groups could be
given very high suitability weights to make it more likely, but
not guaranteed, that the model will select them.
The BMAS modeling
approach is a useful exploratory tool for evaluating the consequences
of alternative choices in targets, representation goals, suitability
factors, and policy questions. The BMAS model is able to sort through
large, complex, multi-dimensional data sets to maximize a balance
between efficiency and suitability, which would be beyond the capabilities
of a human analyst. We emphasize two critical points, however.
set of planning units selected by the model should not be accepted
on faith as an ideal portfolio. The model solution only forms a
starting point of a portfolio. The planning team members must still
apply their own intimate knowledge of specific sites to refine the
portfolio, using personal knowledge not explicitly in the GIS database
nor incorporated in the BMAS model. Ideally, more testing of model
assumptions and parameters will be undertaken to understand their
implications and trade-offs.
cartographic representation of the set of planning units (i.e.,
subwatersheds) is not a map of the precise boundaries of conservation
sites. The locational accuracy of the biological data is imperfect
and so some target elements may actually occur in adjacent planning
units. This selection error could be remedied during the design/implementation
phase. The use of standardized planning units is just an artificial
convenience for modeling purposes. Therefore the set of planning
units merely indicates general locations where appropriate management
strategies can be applied. In the extreme, a subwatershed may be
selected in which the only strategy required is to monitor the status
of a single target element occurrence at a small site within a planning
unit. In other words, displaying a portfolio from this prototype
planning process as a set of large planning units risks overstating
the magnitude of the conservation agenda and alarming other stakeholders.
We strongly urge caution in how TNC publicly portrays any portfolio
derived in part by BMAS modeling based on subwatersheds or other
such planning units. Noss (1996), in commenting on this question,
recommended that network proposals be presented to policymakers
and the general public as a staged sequence from the current system,
through intermediate stages, to the ultimate network. He felt that
presenting the ultimate vision was worth the risk because it may
stimulate others to conduct more detailed analyses in the design
The basic conservation
planning approach, including the BMAS model, has now been applied
in the Sierra Nevada Ecosystem Project for the U. S. Forest Service
and the Columbia Plateau ecoregion for TNC. Both of these ecoregions
were data-rich study sites, having been the focus of major federal
assessment efforts. Large GIS databases had already been assembled
for most of the essential spatial data layers such as suitability
factors and biodiversity target elements. Gap analysis had recently
been completed for both these regions which also provided important
data. As GAP is implemented in more regions, and as public-domain
GIS layers become more commonly available, lack of data for other
regions of the nation should diminish as a limitation. Perhaps more
significantly, both regions are largely in public ownership with
relatively limited area converted to development and cultivation.
Thus there remain substantial opportunities for proactive conservation
action. Because of the similarity of these two test sites, it remains
untested which circumstances would preclude the effective use of
the BMAS model. Obviously, in an extreme case of a highly altered
ecoregion in which all remaining fragments with rare elements were
known, all such sites would be in the portfolio and a more formal
modeling approach would add nothing useful. But what circumstances
define the threshold at which the BMAS model becomes an effective
planning tool? Therefore we recommend:
undertake additional pilot studies in ecoregions across a range
of management situations, including more highly altered landscapes
in the eastern half of the nation.
single greatest failing of the modeling approaches to date is that
they tend to treat sites as collections of species or communities
without accounting for the viability of the biota at each site or
over the set of sites. The goal of representation is only an approximation
of the true goal of maintaining viable populations of all native
species. Similarly, management status only approximates the actual
underlying threats to biodiversity. A second, related problem is
that none of the current selection models addresses the problem
of the spatial layout of the sites. Since sets of sites may all
be influenced, potentially in different ways, by the same large-scale
ecological processes (e.g., fire, floods), consideration of spatial
layout may relate to the long-term viability of the sites. Another
critical issue is whether conservation planning solutions developed
at the regional scale using spatially and biologically coarse data
provide reliable guidance when viewed from a more local perspective
with better data and understanding of ecological processes and management
concerns. Our final recommendation is:
should conduct or sponsor research to address three issues we consider
central to ecoregion-based conservation, namely: 1) development
of approaches and techniques for assessing species and community-level
viability under a particular conservation scenario, 2) development
of improved, multi-objective models for identifying the best set
of sites within a region for meeting the stated conservation goal
while addressing viability and spatial configuration, and 3) testing
of regional viability measures and siting solutions against more
detailed information on biotic composition and ecosystem processes
to establish the relationship between regional and local conservation
measures and approaches.
This research was supported by a contract from The Nature Conservancy
of Washington (WA-FO-101796). We appreciate the enthusiasm and energy
of the Columbia Plateau team leader, Sandy Andelman, who was willing
to take risks in exploring new planning directions. We also thank
the other TNC staff involved, particularly Elliot Marks, Director
of the Washington State Office; the planning team members; and Chris
Hansen for GIS assistance. The formulation of the BMAS model was
the vision of Dr. Richard Church at UCSB. Much of the spatial data
were compiled by the Interior Columbia Basin Ecosystem Management
Plan team and by the network of Natural Heritage Programs. We are
also grateful to the IBM Environmental Research Program for its
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