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Michelle McConnell
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RON REMPEL [rrempeI2@msn.com]
Saturday, January 24, 2009 10:46 AM
Michelle McConnell
PDSMP
Jefferson county.docx; species prioritizations
Ms McConnell-
Attached are my comments of the PDSMP
Ron Rempel
1
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Ronald D. Rempel
1151 Griffith Pt. Road
N ordland, W A
Subject: Preliminary Draft SMP (PD SMP)
Dear Ms. McConnell
Jefferson County should be complimented on its efforts to improve its Shoreline
Management Plan and its ongoing efforts to protect, enhance and restore its lands
and aquatic ecosystems. Having been professionally involved for over 32 years in
evaluating environmental impacts of development (including mitigation measures
to offset those impacts) and in evaluating the success in achieving specified
conservation goals, I can fully appreciate the efforts that have gone into developing
the PD SMP.
The goals specified in Article 3 1.B (1-4) are laudable goals but they are also
motherhood types of goals that are not easy to monitor or measure. As a result, it
will be difficult if not impossible to determine if the PD SMP actually succeeds in
achieving the goals and as a result the development requirements (setbacks, etc)
cannot be assessed over time to determine if they were inadequate, adequate or
more than is necessary.
Utilizing good science, conceptual models and new decision making tools could be
very beneficial in helping Jefferson County conserve and improve its aquatic and
shoreline resources. Utilizing decision making tools available today (which utilize
conceptual models) would allow the County and the public to select the best and
most cost effective ways to achieve specified goals. But to utilize any of the new
tools that have been developed, specific goals must be established which also means
that the current conditions must be clearly articulated and the relationships
between measured variables and the goals established. This is where utilizing
conceptual model(s) helps. While this may sound like a very difficult step, the
County could consider utilization of the information in the Watershed
Characterization ofJefferson County (May 2007) as the potential basis for
developing an initial model(s). There are several other concepts that could also be
utilized. Although it was focused primarily on upland habitats, the paper by H.
Regan et. al. provides some insights on how some of the thought processes in
approaching utilization of conceptual models might help create a more focused and
measurable approach to developing a SMP. A revised SMP could incorporate
measurable goals that lend themselves monitoring and adaptive management.
Another major advantage to utilizing a conceptual model approach and specific
goals it that various methods for achieving the goals can be considered and tradeoffs
and efficiencies considered. For example, could restoration of agricultural lands on
Marrowstone Island accomplish the same benefits to water quality as would be
achieved by greater setbacks of new residential development on shoreline
properties. Or for that matter, could permeable parking and walking surfaces for all
uncovered areas accomplish it. While a conceptual model could help with
understanding how various factors might interact and affect the desired end
condition, the real key to making a good decision is understanding the current
condition of the resource you are trying to protect. What metric( s) is going to be
measured to determine current and future condition?
While I support protecting and enhancing our shorelines and associated aquatic
resources, I think the approach being proposed (primarily setbacks and clearing
limits) may not necessarily achieve the desired outcomes or could be a more costly
way of achieving the desired outcomes than if other measures were implemented.
The problem is, we won't know if we have achieved anything unless specific goals
are adopted and appropriate monitoring is utilized to determine if they are met and
if not met, a feed back loop is utilized in an adaptive manner to modify required
measures.
Sincerely,
Ronald D. Rempel
Diversity and Distributions, (Diversity Distrib.) (2008) 14, 462-471
Species prioritization for monitoring and
management in regional multiple species
conservation plans
Helen M. Reganl,2*, Lauren A. Hiedl, Janet Franklin 1 ,Douglas H. Deutschmanl,
Heather L. Schmalbachlt, Clark S. WinchelP and Brenda S. Johnson4
I Department of Biology, San Diego State
University, 5500 Campanile Drive, San Diego,
CA 92182-4614, USA, 2Biology Department,
University of California, 900 University Avenue,
Riverside, CA 92521, USA, 3US Fish and Wildlife
Service, 6010 Hidden VaUey Road, Carlsbad,
CA 92011, USA, 4Habitat Conservation Branch,
California Department of Fish and Game,
1416 Ninth Street, 12th Floor, Sacramento,
CA 95814, USA
*Correspondence: H.M. Regan, Biology
Department, University of California Riverside,
900 University Avenue, CA 95251, USA.
Td.: +1-951-827-3961; Fax: +1-951-827-4286;
E-mail: hden.regan@ucr.edu
t Present address: California Department of Fish
and Game, 4949 Viewridge Road, San Diego,
CA 92123, USA
ABSTRACT
Successful conservation plans are not solely achieved by acquiring optimally
designed reserves. Ongoing monitoring and management of the biodiversity in
those reserves is an equally important, but often neglected or poorly executed, part
of the conservation process. In this paper we address one of the first and most
important steps in designing a monitoring program - deciding what to monitor.
We present a strategy for prioritizing species for monitoring and management in
multispecies conservation plans. We use existing assessments of threatened status, and
the degree and spatial and temporal extent of known threats to link the prioritization
of species to the overarching goals and objectives of the conservation plan. We consider
both broad and localized spatial scales to capture the regional conservation context
and the practicalities oflocal management and monitoring constraints. Spatial scales
that are commensurate with available data are selected. We demonstrate the utility of
this strategy through application to a set of 85 plants and animals in an established
multispecies conservation plan in San Diego County, California, USA. We use the
prioritization to identify the most prominent risk factors and the habitats associated
with the most threats to species. The protocol highlighted priorities that had not
previously been identified and were not necessarily intuitive without systematic
application of the criteria; many high-priority species have received no monitoring
attention to date, and lower-priority species have. We recommend that in the
absence of clear focal species, monitoring threats in highly impacted habitats may be
a way to circumvent the need to monitor all the targeted species.
Keywords
Endangered species, focal species, Habitat Conservation Plans, monitoring,
multispecies conservation, Natural Community Conservation Plans, systematic
conservation planning.
INTRODUCTION
With the shift from single-species to multispecies conservation,
systematic conservation planning has received much attention
in the academic literature and in on-the-ground programs to
protect biodiversity (Cowling etal., 1999; Pressey etal., 1999;
Margules & Pressey, 2000; Carroll et al., 2003; Noon et al., 2003;
Moffett & Sarkar, 2006; Wilson et aL, 2006). Successful conservation
plans, however, are not solely achieved by acquiring optimally
designed reserves. Ongoing monitoring and management of
species in those reserves is equally important but often neglected
or poorly executed (Olsen etaL, 1999; Yoccoz etaL, 2001; Noon,
2003; Barrows et al., 2005). Indeed, despite the large number of
systematic planning tools available, conservation planning has
been described as succumbing to an 'implementation crisis'
(Salafsky et al., 2002; Knight et al., 2006). As a result, the conser-
vation community is increasingly concerned with monitoring
and measuring success of conservation actions (e.g. Conservation
Measures Partnership, www.conservationmeasures.org). In this
paper we address one of the first and most important steps in
designing a monitoring program - deciding what to monitor.
Regional multispecies conservation plans have become a
major tool in response to the increasing number of endangered
and threatened species, communities and ecosystems. In the USA,
these plans often take the form of federal Habitat Conservation
Plans (Heps) (US Fish & Wildlife Service, 1996; Smallwood,
462
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Journal compilation @ 2007 Blackwell Publishing Ltd www.blackwellpublishing.comlddi
2000; Harding etal., 2001; Rahn etal., 2006). In an effort to
increase the conservation value of HCPs, the number of 'covered
species' included in these plans has grown from one species in
the 1980s to nearly 200 species for plans currently considered.
However, the ability of multispecies conservation plans to protect
biodiversity and ecosystem processes has largely been untested.
Monitoring and management often require more resources
and commitment than are usually acknowledged at the planning
stage. The importance of explicitly considering budgets in the
formulation and allocation phases of monitoring and manage-
ment has been highlighted in the literature (Haight et al., 2002;
Field et aI., 2004, 2005; Hauser et al., 2006). Most studies assume
that budgets are known and constant However, when monitoring
and management are conducted in an adaptive framework and
are administered by a consortium of government agencies, non-
government organizations, and private land owners, the total
budget for monitoring activities is often unknown at the outset,
changes over time, and depends somewhat on monitoring and
management priorities. Volunteer groups also play an increasing
role in monitoring and managing local biodiversity and can con-
tribute to ongoing monitoring with minimal to no expenditure
(Hoyer et al., 2001; Markovchick-Nicholls et al. in press), and
there may be other ways to leverage funding for monitoring.
Hence, while it is sensible to explicitly consider the available
budget in planning monitoring and management activities,
in practice it is prudent to devise a prioritization scheme for
monitoring that is flexible enough to deal with statutory standards
and realistic uncertainties and constraints.
Even when long-term monitoring is mandated and well
funded, monitoring plans can fail because of indecision, or
poorly made decisions, about what to monitor. Rarely can all
components of biodiversity be monitored: some triage must
occur at the outset (Possingham et al., 2001). This step is crucial
for the implementation of a monitoring plan because it lays
the foundation for all future activities and decisions. Once a
monitoring program has gained momentum it may be difficult
to change priorities because of perceived or actual 'return
on investments' in components for which the monitoring
budget has already been allocated. Hence, it is important to base
prioritization decisions on sound science and directly relate
them to the goals and objectives of the conservation plan as a
first step in structuring a monitoring program.
Conservation plans are developed for many purposes, and
before setting monitoring goals it is crucial that the objective of
the plan is well defined (Nicholson & Possingham, 2006). In this
paper we deal with the case where a primary objective of the
conservation plan is to conserve target species composed of two
main groups: (1) species deemed to be at risk of decline or
extinction under current conditions or future threats, and (2)
species intended to be focal species, the status and trend of which
should indicate change in a broader set of species or ecological
function. This objective essentially relates to minimizing
extinctions in an established conservation area.
According to Salzer & Salafsky (2006) there are two major
reasons for undertaking monitoring and evaluation. The first is
to assess the status of biodiversity, and the second is to measure
Species prioritization for monitoring
the effectiveness of management actions. These two motivations
are tightly linked - decisions to take management action will be
based on assessments of status and trends, while evaluations of
the impact of management rely on assessments of status and
trends in reference and managed scenarios. The major difference
is that evaluations of management impact may not necessarily
involve direct measurement of the intended beneficiary of the
action. For example, if the management action is the abatement
of a known threat, then the impact on the threat itself may be
measured. Hence, it is important to distinguish between these
two motivations for monitoring because this will determine
monitoring priorities. In this paper, we address the first of these,
prioritizing species for the purpose of monitoring status and
trends, because this is most certainly the precursor of informed
management decisions and links directly to monitoring of
management impacts.
We present a strategy for prioritizing species for monitoring
and management in regional multispecies conservation plans
that uses existing assessments of threat, and the degree and spatial
and temporal extent of known threats, to link prioritization of
species to the overarching goals and objectives of the conservation
plan. We consider both broad and local spatial scales to capture
the regional conservation context and the practicalities of local
management and monitoring constraints. We demonstrate the
utility of this strategy through application to a set of 85 plants
and animals in an established multispecies conservation plan in
San Diego County, California, USA. While this strategy is in a
similar vein as others proposed in the literature (Lambeck, 1997;
Committee of Scientists, 1999; Holthausen et al., 1999; Noon
etal., 1999; Hilty & Merenlender, 2000; Andelman etal., 2001;
Groves, 2003), we apply it to an established multispecies con-
servation plan to demonstrate its value for identifying monitoring
priorities in a systematic way.
STUDY AREA
California supports a vast proportion of biodiversity in the USA,
with more native plant and animal species, and more imperilled
native species, than any other state. The California floristic
province is a global biodiversity hotspot (Wilson, 1992; Stein
et al., 2000). The biodiversity of southern California is widely
regarded as the most highly threatened in the USA. Habitat
conversion and urban development are the most cited causes of
extirpation (Tennant et al., 2001).
As a result of the intersection of human population growth
and biodiversity, conservation planning in this region has been
considered at both the broad and the fine scale. The San Diego
Multiple Species Conservation Plan (MSCP) was one of the first
regional plans developed and approved under the California
Natural Community Conservation Planning Act. Its primary goal
is to conserve natural communities at the ecosystem scale before
species decline to the point of requiring protection under federal
or state Endangered Species Acts, while allowing 'compatible land
uses' (US Fish & Wildlife Service, 1996). The MSCP is also
intended to provide protection and management for species
already listed under the federal and state Endangered Species Acts
@ 2007 The Authors
Diversity and Distributions, 14,462-471 Journal compilation @ 2007 Blackwell Publishing Ltd
463
H, M. Regan et al.
to offset incidental take in developed areas outside the preserve. As
of 2004, over 51,800 ha had been included in the preserve and
lands continue to be added by the 14 participating jurisdictions
and wildlife agencies (San Diego Association of Governments,
HabiTrak GIS data). The 85 covered species targeted for
protection under the San Diego MSCP include 39 animal and
46 plant species (see Appendices S1 and S2 in Supplementary
Material). The covered species list comprises rare, threatened,
and endangered species, as well as common and endemic species
and species intended to serve as focal species and indicators of
reserve connectivity. For more details on the creation and
administration of the MSCP see Ogden Environmental and
Energy Services (1998) and Hierl et al. (2005).
Species-level biological monitoring goals have been a component
of the MSCP from its inception. However, meeting these goals
has been challenging due to a lack of resources to devote to all 85
covered species. Previous monitoring recommendations (Ogden
Environmental & Energy Services, 1996; Atkinson et al., 2004),
while well structured and motivated, have faltered in part
because of a perceived lack of explicit rationale and documented
justification for monitoring priorities. The MSCP Iists several
objectives for biological monitoring, each of which will require a
separate prioritization and monitoring program: document
ecological status and trends, evaluate the effectiveness of
management activities, provide new data on species populations
and wildlife movement, and evaluate the indirect impacts of
threats. Here, we present an explicit stepwise approach to priori-
tizing large sets of covered species for monitoring in multispecies
conservation plans that is concordant with many of the stated
MSCP monitoring objectives.
METHODS
The approach presented here was, modified from Andelman
et al:s (2001) recommended steps for USDA Forest Service species
prioritization for viability assessments under the National Forest
Management Act planning regulations (Federal Register, 2000;
65, 67,580-67,581; Andelman et al., 2004). This protocol
was intended to identify at-risk and focal species for viability
assessments. Since the overarching monitoring goals of the
MSCP are to monitor the status and trends of the covered species
and status and trends are directly related to viability, we used the
protocols recommended in Andelman et al. (2001) as a starting
point, and modified these as appropriate for the particular
application of prioritizing covered species for monitoring in the
MSCP. The ultimate goal is to prioritize the covered species into
two main groups: at-risk species that are those deemed to be at
risk of decline or extinction under current conditions or in the
face of short- or long-term threats, and focal species whose
'status and trend provide insights into the integrity of the larger
ecological system to which it belongs' (Federal Register
65, 67,580,2000). The first group is constructed by considering
those species that fall into the highest risk category as determined
by some at-risk categorization scheme (e.g. The World Con-
servation Union (IUCN) Red List, NatureServe, Federal or State
listings). Within the focal species group, the aim is to represent
all relevant combinations of habitat association and risk factor
(denoted generally as HNRF). Where multiple species occur for
each HNRF pair, further prioritization is achieved by considering
the spatial and temporal scale of threats, with the aim of selecting
a representative species that can serve as a focal species for that
HNRF pair.
Spatial scale is important when considering risk status. Global
scales are too broad to be of relevance to the MSCP, whereas the
incorporated preserve is too small a scale to capture true risk to
taxa. While monitoring and management will ultimately occur
only on MSCP preserve lands, it is important to consider risk
factors at a broader spatial scale, somewhat independently of the
preserve, so that assigned risk status and the resulting prioritiza-
tion is not purely an artefact of the way the preserve has been
designated. This is especially pertinent when all proposed areas
have not yet been incorporated into the preserve. In order to
implement the protocol at a spatial scale relevant to San Diego
County, we have chosen a two-tiered approach: the first tier
focuses on selecting species and allocating them to broad categories,
while the second tier ranks the species within each category. In
the first tier, species are assigned to broad risk categories using
State Ranks for California (and supplemented with Federal and
IUCN listings) to capture risk status at the broad scale of the
state. In the second tier, species are further prioritized within
each risk category according to the number, degree and spatial
extent of risk factors affecting the species within San Diego
County, both within and outside the preserve system.
The first tier to prioritizing species for monitoring is based on
at-risk and focal species prioritization recommendations from
Andelman et al. (2001) and the broader ecological monitoring
literature:
1 Apply an at-risk species classification using established risk
rankings.
2 For each at-risk group, allocate species to categories based on
the nature of the risk factor.
3 Using information on home ranges (or a surrogate such as
body size (Purvis et al., 2000)) or known distributions, further
classify species in each group according to their spatial scale of
response to risk factors.
4 Using information on life span or plant functional group (as a
surrogate for life span), further classify species in each group
according to their temporal scale of response to risk factors.
5 Select one or more focal species from each group that best
represent the rest of the species in the group.
6 Stop when each discrete vegetation community type is
represented by at least one focal species or when all risk factors
have been associated with at least one focal species.
The pertinent pieces of information needed to prioritize
the covered species according to steps 1-6 above are: (i) at-risk
category (based on applicable ranking systems), (ii) threats and
the degree and spatial extent of threats across a species' range
within San Diego County, (ill) habitat associations of species,
and (iv) temporal scale of the impact of threats. These are
described in more detail below. Information was compiled from
all known available sources (from the scientific literature, available
reports, electronic databases and opinion of acknowledged
464
@ 2007 The Authors
Diversity and Distributions, 14,462-471 Journal compilation @2007 Blackwell Publishing Ltd
experts where warranted) and systematically collated (see
Appendix S3 in Supplementary Material). For the complete set of
information sheets for all the covered species the reader is
referred to Regan et al. (2006).
(i) At-risk category
The species at-risk categories are based on federal or state listings
or at-risk classification protocols from the California Native
Plant Society (CNPS, for plants), Partners in Flight Species
Assessment (for birds), NatureServe, or lUCN databases. The
NatureServe database was used heavily as this provides the most
comprehensive list of ranked plant and animal species for the
USA. Species were assigned to one of three broad at-risk groups
(Risk Group 1,2, or 3 in descending order of risk level). Species
classified as federally endangered (FE), Gl (NatureServe global
ranks), and SI (state rankings) received a ranking of 1. Species
that were classified as endangered at the state level (SI) received a
ranking of 1 if they were also higWy ranked in another risk
classification scheme, Species received a ranking of 2 if they
were classified as S2 or G2. Subspecies presented a challenge for
prioritization due to inconsistencies across at-risk classification
protocols and because many of them are subject to ongoing
taxonomic debate. Where discrepancies existed across ranking
protocols, the state ranks were used to determine the at-risk
category. Risk categories for all MSCP covered species appear in
Appendices SI (plants) and S2 (animals).
(ii) Threats/risk factors
Any monitoring plan designed for the purpose of informing
future management activities must explicitly consider threats. In
San Diego County, natural populations are faced with myriad
threats that operate at different levels of intensity and spatial
scales. The important components of risk factors to consider are
the type and cause of the threat, the degree to which a risk factor
contributes to the overall risk a species faces, and the spatial and
temporal scale of the risk factor. It is important to note that the
risk factors considered here are both realized threats that are
currently affecting the status and trend of populations (e.g.
altered fire regime, recreation activities) and currently unrealized
threats that are expected to affect the status and trend of popula-
tions in the future. Risk factors are considered across the entirety
of San Diego County and not just within the MSCP.
Threats were identified for each of the covered species by
scouring available reports and the scientific literature. Twenty
different threat categories were identified and defined by modify-
ing The Nature Conservancy's Definitions of Sources of Stress
(The Nature Conservancy, 2004). A full description of the threat
categories is articulated in Regan e:t al. (2006) (for an alternative,
yet similar, classification of threats see the 'lUCN-CMP Unified
Classifications of Direct Threats and Conservation Actions'
http://conservationmeasures.orglCMP/lUCN/SitcPage.cfm).
Where discrepancies occurred, peer-reviewed scientific publications
outranked information available from reports if the scientific
publication was published after the dissenting report. For the
Species prioritization for monitoring
most part, reports and expert opinion were heavily relied upon
as these were the only sources of information available.
The degree to which the risk factor contributes to the overall
risk faced by the species within San Diego County was split into
three categories: high (H), moderate (M), and low (L). The spatial
scale of the risk factor across the County was also broadly catego-
rized: high (H = widespread across the species distribution
within San Diego County), moderate (M = moderately spread
across the species distribution), and low (L = low spread across
the species distribution).
Due to the subjectivity of assigning risk levels, and degree and
spatial extent of risks, a consensus had to be reached among three
assessors (HMR, LAH, and HLS). Those items that remained
uncertain were highlighted and brought to four experts (CSW
and see Acknowledgements) for verification.
(Hi) Habitat associations of species
Information on habitat associations of the covered species
was compiled from available data sources. Distribution maps
provided by the San Diego Multiple Species Conservation Program
were used to assess the range and spatial density for covered
plants. The San Diego Bird Atlas (Unitt, 2004) was used to assess the
spatial distribution of bird species. All known habitat associations
were recorded, as reported in the available literature.
(iv) Temporal response to risk factors
Temporal scale of response to the threats was also distinguished
as either short term (a response of within 5 to 10 years), or long
term (such as changes to hydrology or fire regime that may take
longer than 10 years to affect the species). These crude distinctions
are sufficient to capture general properties of the threats and
their effect on populations for the purpose of prioritization.
Because short-term responses to threats are more readily
observed, and more imminent, than long-term responses, we
rank species with short-term responses higher than those with
long-term responses.
(v) Second tier approach to ranking
We recommend a second tier approach to prioritizing the species
resulting from steps 1-6 of the first tier for a number of reasons.
First, the steps assume the pool of species is large, perhaps much
larger than the covered species list (as was the case for the USDA
Forest Service species viability assessments). Ideally, the first tier
approach to prioritization should be used to identify covered
species for a multispecies conservation plan at the outset (Margules
& Pressey, 2000; Groves, 2003). The MSCP covered species list is
already the result of an ad hoc prioritization. Hence, application
of steps 1-6 may not reduce the candidate species for monitoring
any further. Second, for species not listed as rare, threatened, or
endangered, it is highly uncertain that they actually do serve as
surrogates due to a lack of documented rationale and scientific
justification for their inclusion as covered focal species. Third,
insufficient resources may exist to monitor all species identified
@ 2007 The Authors
Diversity and Distributions, 14,462-471 Journal compilation @ 2007 Blackwell Publishing Ltd
465
H, M, Regan et al.
from steps 1-6 as at-risk or focal species. At the very least, the
MSCP should conserve (and monitor) at-risk species. The strategy
used for ranking the covered species within each Risk Group
according to degree and spatial extent of risk is as follows:
1 Species are grouped according to their at-risk ranking into
Risk Groups 1,2, and 3 in descending order of risk level (from i
above).
2 Species in each of the Risk Groups are ranked by the number
of high-level threats ('high' from ii above) facing each species,
then ranked further by their total number of threats. Temporal
response to threats is used as a tie breaker where necessary, with
species having short-term responses ranked higher.
RESULTS
The application of steps 1-6 identified most covered species as
candidates for monitoring. That is, given the numerous risk
factors and habitat associations of covered species, many HAlRF
groups comprised only one species. Furthermore, for HAlRF
groups with multiple species, no species stood out as obvious
focal species. This necessitated further ranking within the broad
risk groups using the second tier approach.
The prioritization of species according to degree of risk
(second tier) appears in Appendix S4. Within each risk group,
species experiencing more high-level threats should receive
higher priority for monitoring than those with fewer (indicated
by the order the species are listed, with highest priority from top
to bottom). At the very least, the MSCP should be protective
of species in Risk Group 1. Risk Group 1 species were further
prioritized to assist in decision-making in the face of limited
resources - species at the top of the list should be given higher
priority over lower-ranked species. If resources allow, as many
covered species as possible should be monitored. Again, species
in Risk Groups 2 and 3 have been prioritized according to risk
factors to assist in decision-making.
The most prominent threats to covered species can also be
highlighted with this approach (see Appendix 54 in Supplementary
Material). The top five threats to plants, in decreasing order of
occurrence and severity, are habitat loss, invasive species,
off-road vehicles, recreation/human disturbance, and altered fire
regime. The top five threats to animals are habitat loss, altered
hydrology, invasive species, predation, and recreation. The five
most prominent threats for plants and animals, respectively,
impact most of the covered plant and animal species.
Figure 1 shows the number of species that have been studied
or monitored to date, ranked by risk group (see also Appendices
SI and S2 in Supplementary Material). It is important to note
that these include a wide variety of data collection activities
including species inventories, baseline determinations of plant
cover, and population surveys. Data analysis for the purpose
of informing management decisions or future monitoring
direction has been patchy. So while data have been collected for
many of the covered species (see Appendices SI and S2 in
Supplementary Material) over the period of 1995-2005, they
have not been used in an integrated multispecies monitoring
program (see HierI et aI., 2005 for details of data collected). The
20
l3 15
1
th
'0 10
il
E
::s
Z 5
0
R1 R2 R3 Exc
Plants
_ Monitored
_ Not monitored
R1 R2 R3 Exc
Animals
Figure 1 Number of Multiple Species Conservation Plan
(MSCP) covered plants and animals that have been monitored over
1995-2005, as a function of risk group. Rl refers to the number of
species monitored and not monitored in Risk Group 1, etc. Exc.
refers to covered species that were excluded from the prioritization
due to taxonomic debate or because their occurrence is not
confirmed within the MSCP preserve.
results in Figure 1 showthat there is no obvious pattern or rationale
for current monitoring decisions in terms of how such decisions
relate to the goals and objectives of the MSCP. Indeed, many
highly at-risk species (Risk Group 1) receive no monitoring at all,
whereas half of the Risk Group 3 animal species are monitored.
Furthermore, data collection has been a priority for some covered
species that are not currently known to occur within the MSCP
reserve system (even though potentially suitable habitat for them
exists) .
Figures 2 (plants) and 3 (animals) display the number of
covered species and the number of threats they face in each
habitat type. When considering habitat types in conjunction
with the number of major threats experienced by species using
those habitats, riparian/riparian woodland areas rank the highest
for animals, followed by grassland and salt marsh, then coastal
sage scrub. For plants, chaparral and coastal sage scrub rank the
highest, followed by closed cone forest and vernal pools.
DISCUSSION
This study modified an existing methodology for the identification
of species for viability assessments and applied it to the prioriti-
zation of species for monitoring in a multispecies conservation
plan. While seemingly straight-forward to implement, this
approach has seldom been applied. This case study demonstrates
that such protocols for prioritization can be very useful for
detailed ranking of large sets of species according to risk.
Additionally, it provides a framework for organizing existing
relevant information on which to base informed and transparent
monitoring and management decisions.
Our findings are novel in that the protocol highlighted priorities
that had not previously been identified and were not necessarily
intuitive. Evidence of this is that many high-priority species have
466
@ 2007 The Authors
Diversity and Distributions, 14,462-471 Journal compilation @ 2007 Blackwell Publishing Ltd
Chaparral
Coastal sage scrub
Vernal pool
Closed cone forest
Maritime scrub
Riparian/Riparian woodland
Grassland
Southern maritime chaparral
Oak woodland
Mixed conifer
Salt marsh
Bluffs/coastal dunes
Cliffs
o
2
4 6 8 10 12 14 16 0
Number of threats
5
10 15 20 25 30 35
Number of species
Species prioritization for monitoring
__ Risk Group 1
k0\C,; ,'.1 Risk Group 2
1 '.1 Risk Group 3
c=::J Excluded
Figure 2 Number of Multiple Species Conservation Plan covered plant species and number of threats (Major = high-degree; Other = moderate
and low-degree threats) by habitat type. Note that the 'number of threats' refers to the number of distinct threats to species occurring in the
habitat type. Hence, in each bar a distinct threat only appears once.
received no monitoring attention to date, and lower-priority
species have (Fig. 1; see also Appendix 54 in Supplementary
Material). For instance, almost all of the animals in Risk Group 2
receive some monitoring, whereas less than half of the animals in
Risk Group 1 receive any monitoring at all. Plants fare slightly
better in that more Risk Group 1 species are currently monitored
than plants in the lower risk groups, but they fare worse than
animals in the number of species monitored, even though there
are more covered plants than animals. It is clear from this analysis
that undocumented biases currently exist in MSCP monitoring
priorities and that these need to be addressed in future monitoring
decisions.
In addition to the species prioritization, there are a number
of useful outcomes stemming from the application of the
step-down approach that can assist in monitoring decisions. The
information compiled in Figs 2 and 3 can assist in prioritizing
habitat types for monitoring based on threats to covered species.
It should be noted, however, that 'habitat' is a species-based
concept. For the purpose of MSCP species monitoring, it is only
relevant to prioritize habitats in terms of the covered species
occurring there and the threats those species face within their
habitat (as opposed to the threats to the habitat itself). While
threats to the habitat itself are significant risk factors, they are a
subset of the many threats covered species face. Species life-
history traits and their response to all major risk factors need
to be considered in designing habitat monitoring and such
monitoring should be performed in conjunction with other
species-specific monitoring. It will be insufficient to monitor
habitat cover through aerial photographs, for instance, when
predation is a major risk factor for a given species. Habitat
monitoring, performed in an appropriate way for the associated
covered species, could have the greatest value if performed in
areas where the most covered species occur.
The selection of focal species has received much attention in
the monitoring literature (Noss, 1990; Kremen, 1992; Pearson,
1994; Simberloff, 1998; Canterbury et aI., 2000). Despite many
years of effort, the utility of focal species remains controversial
(National Research Council, 1995; Niemi et aI., 1997; Linden-
meyer, 1999; Andelman & Fagan, 2000). We argue that even
though focal species concepts are often invoked in the selection of
conservation targets, a risk-based approach to species prioritization
is better justified for status and trend monitoring. This is because
of the necessity of directly managing and monitoring at-risk
species, the paucity of evidence establishing the validity of
focal species in many cases, and the difficulties in structuring a
monitoring plan to capture status and trends of focal species that
are meaningful for the broader biodiversity (Rubinoff, 2001;
Lindenmeyer et ai., 2002).
@ 2007 The Authors
Diversity and Distributions, 14,462-471 Journal compilation @ 2007 Blackwell Publishing Ltd
467
H. M. Regan et ai,
Riparian/Riparian woodland
Grassland
Salt marsh
Coastal sage scrub
Chaparral
Freshwater marsh
Bluffs/coastal dunes
Vernal pool
Beaches/salt flats/mud flats
Oak woodland
Closed cone forest
Mixed conifer
Montane meadow
Urban
Cliffs
_ Risk Group 1
_ Risk Group 2
Ilmmmmmlm1[Xl Risk Group 3
c::::J Excluded
- Major threats
,".',mm,m'w'l Other threats
o
2 4 6 8 10 12 14 16 18 0 2
Number of threats
4 6 8 10 12 14 16 18
Number of species
Figure 3 Number of Multiple Species Conservation Plan covered animal species and number of threats (Major = high-degree;
Other = moderate and low-degree threats) by habitat type. Note that the 'number of threats' refers to the number of distinct threats to species
occurring in the habitat type. Hence, in each bar a distinct threat only appears once.
In the absence of clear focal species and insufficient resources
to monitor all covered species, how can we gauge the status and
trends of species that are not high risk and cannot be monitored
directly? We suggest that the prioritization methods presented
here can be used to make monitoring decisions about an alternative
indicator of status and trend-threats. The results in Appendix 54
provide information on the most prominent threats and the
species impacted by them in the MSCP. Figures 2 and 3 reveal the
habitats containing the most threats to species. This information
can be used to identify the most serions threats to covered species
and where those threats occur. Six threats stand out as the most
serious for most of the covered species: habitat loss, invasive
species, off-road vehicles, recreation/human disturbance, altered
fire regime, and altered hydrology. While it is always preferable to
monitor the covered species directly if resources allow, threats
may be a more feasible alternative for monitoring status and trends.
They may also be more reliable and relevant than focal species for
a monitoring plan because they directly link to management (as
highlighted previously by Salafsky & Margoluis, 1999).
It is important to note that the prioritization presented here
forms only one component of a much larger adaptive manage-
468
ment framework (Salafsky & Margoluis, 1999; WIlhere, 2002;
Stem et aI., 2005; Williams et aI., 2007). While prioritization for
monitoring status and trends of target species is an important
first step in such a framework, it is insufficient on its own as a
tool for ensuring a successful conservation plan. Ongoing
management and subsequent evaluation will be necessary to
determine if the conservation plan is meeting its stated objectives.
It may also be necessary to monitor and evaluate additional
components of biodiversity, such as communities or ecosystems,
to determine if the objectives of the conservation plan are being
met. In an adaptive management framework, knowledge about
changes gained from managing biodiversity should be used to
update priorities for status and trend monitoring. If new threats
appear, or if the status of a species changes, monitoring priorities
should be revised accordingly.
Southern California has taken a leading role in regional
conservation planning in the USA, and San Diego's MSCP is at
the forefront. Strategies developed to improve the planning,
implementation, and monitoring of regional conservation
programs can benefit the many HCPs and other regional con-
servation programs currently under development. We believe
@ 2007 The Authors
Diversity and Distributions, 14, 462-471 Journal compilation @ 2007 Blackwell Publishing Ltd
that the methods presented in this paper, and applied to an estab-
lished conservation plan, go some way to ensuring scientifically
defensible monitoring programs that can gauge the success of
conservation plans.
ACKNOWLEDGEMENTS
This study was supported by a Local Assistance Grant (no.
P0450009) from the California Department of Fish and Game
(CDFG) and in cooperation with the MSCP Monitoring
Partners. We are grateful to the many people involved in this
effort. We thank. T. Regan and three anonymous reviewers for
commenting on a draft of this paper, and A. Widyanata who
assisted with data compilation. We also wish to thank. J. Rebman,
P. Unitt, and M. Mendelson for providing expert opinion on
many of the covered species. The opinions expressed and any
errors that remain in this paper are the authors'.
REFERENCES
Andelman, S.J., Beissinger, S., Cochrane, J.F., Gerber, L., Gomez-
Priego, P., Groves, c., Haufler, J., Holthausen, R, Lee, D.,
Maguire, L., Noon, B., Ralls, K. & Regan, H. (2001) Scientific
standards for conducting viability assessments under the
National Forest Management Act: Report and recommendations
of the NCEAS working group. National Center for Ecological
Analysis and Synthesis, Santa Barbara, California.
Andelman, S.J. & Fagan, W.F. (2000) Umbrellas and flagships:
efficient conservation surrogates or expensive mistakes?
Proceedings of the National Academy of Sciences USA, 97, 5954-
5959.
Andelman, S.J., Groves, C. & Regan, H.M. (2004) A review of
protocols for selecting species at risk in the context of US Forest
Service viability assessments. Acta Oecologica, 26, 75 - 83.
Atkinson, AJ., Trenham, P.C., Fisher, RN., Hathaway, S.A.,
Johnson, B.S., Torres, S.G. & Moore, Y.C. (2004) Designing
monitoring programs in an adaptive management context for
regional multiple species conservation plans. US Geological
Survey, Western Ecological Research Center, Sacramento,
California.
Barrows, C.W., Swartz, M.B., Hodges, W.L., Allen, M.F., Roten-
berry, J.T., Li, B.- L., Scott, T.A & Chen, X. (2005) A framework
for monitoring multiple-species conservation plans. Journal of
Wildlife Management, 69, 1333-1345.
Canterbury, G.B., Martin, T.E., Petit, D.R, Petit, L.J. & Bradford, D.F.
(2000) Bird communities and habitat as ecological indicators
of forest condition in regional monitoring. Conservation
Biology, 14,544-558.
Carroll, C., Noss, RB., Paquet, P.C. & Schumaker, N.H. (2003) Use
of population viability analysis and reserve selection algorithms
in regional conservation plans. Ecological Applications, 13,
1773-1789.
Committee of Scientists (1999) Sustaining the people's lands:
recommendations for stewardship of the National Forests and
Grasslands into the next century. US Department of Agriculture,
Washington, D.C.
Species prioritization for monitoring
Cowling, RM., Pressey, RL., Lombar, AT., Desmet, P.G. & Ellis,
AG. (1999) From representation to persistence: requirements
for a sustainable system of conservation areas in the species-rich
Mediterranean-climate desert of southern Africa. Diversity
and Distributions,S, 51-71.
Field, S.A., Tyre, A.J., Jonzen, N., Rhodes, J.R & Possingham,
H.P. (2004) Minimizing the cost of environmental manage-
ment decisions by optimizing statistical thresholds. Ecology
Letters, 7, 669~75.
Field, S.A., Tyre, A.J. & Possingham, H.P. (2005) Optimizing
allocation of monitoring effort under economic and
observational constraints. Journal of Wildlife Management, 69,
473-482.
Groves, C.R. (2003) Drafting a conservation blueprint: a
practitioner's guide to planning for biodiversity. Island Press,
Washington, D.C.
Haight, RG., Cypher, B., Kelly, P.A., Phillips, S., Possingham,
H.P., Ralls, K., Starfield, A.M., White, P.J. & Williams, D.
(2002) Optimizing habitat protection using demographic
models of population viability. Conservation Biology, 16,
1386-1397.
Harding, E.K., Crone, E.E., Elderd, B.D., Hoekstra, J.M.,
McKerrow, A.J., Perrine, J.D., Regetz, J., Rissler, L.)., Stanley,
A.G., Walters, E.L. & the Habitat Conservation Plan Working
Group of the National Center for Ecological Analysis and
Synthesis (2001) The scientific foundations of habitat conser-
vation plans: a quantitative assessment Conservation Biology,
15,488-500.
Hauser, C.E., Pople, AR. & Possingham, H.P. (2006) Should
managed populations be monitored every year? Ecological
Applications, 16,807-819.
Hierl, L.A., Regan, H.M., Franklin, J. & Deutschman, D. (2005)
Assessment of the biological monitoring plan for San Diego's
Multiple Species Conservation Program. Report to California
Department of Fish and Game. San Diego State University,
San Diego, California.
Hilty, J. & Merenlender, A (2000) Faunal indicator taxa selection
for monitoring ecosystem health -lessons from the US Forest
Service. Biological Conservation, 92,185-197.
Holthausen, RS., Raphael, M.G., Samson, F.B., Ebert, D.,
Hiebert, R & Menasco, K. (1999) Ecological stewardship: a
common reference for ecosystem management. Elsevier Science,
Oxford.
Hoyer, M.V., Winn, J. & Canfield, D.E. Jr (2001) Citizen moni-
toring of aquatic bird populations using a Florida lake. Lake
and Reservoir Management, 17,82-89.
Knight, A.T., Driver, A., Cowling, RM., Maze, K., Desmet, P.G.,
Lombard, A.T., Rouget, M., Botha, M.A., Boshoff, A.F.,
Castley, J.G., Goodman, P.S., Mackinnon, K., Pierce, S.M.,
Sims-Casdey, R, Stewart, WJ. & von Hase, A (2006) Designing
systematic conservation assessments that promote effective
implementation: best practice from South Africa. Conservation
Biology, 20, 739-750.
Kremen, C. (1992) Assessing the indicator properties of species
assemblages for natural areas monitoring. Ecological Applica-
tions, 2, 203-217.
@ 2007 The Authors
Diversity and Distributions, 14,462-471 Journal compilation @ 2007 Blackwell Publishing Ltd
469
H. M. Regan et al.
Lambeck, R.J. (1997) Focal species: a multi-species umbrella for
nature conservation. Conservation Biology, 11,849-856.
Lindenmeyer, D.B. (1999) Future directions for biodiversity con-
servation in managed forests: indicator species, impact studies
and monitoring programs. Forest Ecology and Management,
115,277-287.
Lindenmeyer, D.B., Manning, A.D., Smith, P.L., Possingham,
H.P., Fischer, J., Oliver, 1. & McCarthy, M.A. (2002) The focal
species approach and landscape restoration: a critique. Conser-
vation Biology, 16,338--345.
Margules, C.R. & Pressey, R.L. (2000) Systematic conservation
planning. Nature, 405, 243-253.
Markovchick-Nicholls, L., Regan, H.M., Deutschman, D.H.,
Widyanata, A., Martin, B., Noreke, L. & Hunt, T.A. (in press)
Relationships between human disturbance and wildlife land
use in urban habitat fragments. Conservation Biology, doi:
10.III1/j.1523-1739.2007.00846.x
Moffett, A. & Sarkar, S. (2006) Incorporating multiple criteria into
the design of conservation area networks: a minireview with
recommendations. Diversity and Distributions, 12, 125-137.
National Research Council (1995) Review ofEPA's environmental
monitoring and assessment program: overall evaluation.
National Academy Press, Washington, D.C.
Nicholson, E. & Possingham, H.P. (2006) Objectives for multiple-
species conservation planning. Conservation Biology, 20,871-
881.
Niemi, G.J., Hanowski, J.M., Lima, A.R., Nicholls, T. & Weiland,
N. (1997) A critical analysis on the use of indicator species in
management. Journal of Wildlife Management, 61, 1240-1252.
Noon, B.R. (2003) Conceptual issues in monitoring ecological
resources. Monitoring ecosystems: interdisciplinary approaches
for evaluating ecoregional initiatives (ed. by D.E. Busch and
J.C. Trexler), pp. 27-72. Island Press, Washington, D.C.
Noon, B.R., Murphy, D.D., Beissinger, S.R., Shaffer, M.L. &
DellaSala, D. (2003) Conservation planning for US national
forests: conducting comprehensive biodiversity assessments.
Bioscience, 53,1217-1220.
Noon, B.R., Spies, T.A. & Raphael, M.G. (1999) Conceptual basis
for designing an effectiveness monitoring program. The
strategy and design of the effectiveness monitoring program for
the Northwest forest plan (ed. by B.S. Mulder), pp. 21-48. US
Department of Agriculture Forest Service, Gen. Technical
Report PNW-GTR-437, Portland, Oregon.
Noss, R.F. (1990) Indicators for monitoring biodiversity: a
hierarchical approach. Conservation Biology, 4, 355-364.
Ogden Environmental and Energy Services. (1996) Biological
monitoring plan for the multiple species conservation pro-
gram. Prepared for City of San Diego, California Department
of Fish and Game, and US Fish and Wlldlife Service, San
Diego, California.
Ogden Environmental and Energy Services (1998) Final Multiple
Species Conservation Program: MSCP Plan. Prepared for City
of San Diego, California Department of Fish and Game, and
US Fish and Wildlife Service, San Diego, CA.
Olsen, A.R., Sedransk, J., Edwards, D., Gotway, C.A., Liggett, W.,
Rathbun, S., Reckhow, K.H. & Young, L.J. (1999) Statistical issues
for monitoring ecological and natural resources in the United
States. Environmental Monitoring and Assessment, 54, 1-45.
Pearson, D.L. (1994) Selecting indicator taxa for the quantitative
assessment of biodiversity. Philosophical Transactions of the
Royal Society of London Series B, Biological Sciences, 345, 75-
79.
Possingham, H.P., AndeIman, S.J., Noon, B.R., Trombulak, S. &
Pulliam, H.R. (2001) Making smart conservation decisions.
Conservation biology: research priorities for the next decade (ed.
by M.E. Soule and G.H. Orians), pp. 225-244. Island Press,
Washington D.C.
Pressey, R.L., Possingham, H.P., Logan, V.S., Day, J.R. & Williams,
P.H. (1999) Effects of data characteristics on the results of
reserve selection algorithms. Journal of Biogeography, 26, 179-
191.
Purvis, A., Gittleman, J.L., Cowlishaw, G. & Mace, G.M. (2000)
Predicting extinction risk in declining species. Proceedings of
the Royal Society of London Series B, Biological Sciences, 267,
1947-1952.
Rahn, M.E., Doremus, H. & Diffendorfer. J. (2006) Species
coverage in Multi Species Habitat Plans: where's the science?
Bioscience, 56, 613-619.
Regan, H.M., HierI, L.A., Franklin, J. & Deutschman, D. (2006)
Grouping and Prioritising the MSCP Covered Species. Report
to California Department of Fish and Game. San Diego State
University, San Diego, California.
Rubinoff, D. (2001) Evaluating the California Gnatcatcher as
an umbrella species for conservation of coastal sage scrub.
Conservation Biology, 15, 1374-1383.
Salafsky, N. & Margoluis, R. (1999) Threat reduction assess-
ment: a practical and cost-effective approach to evaluating
conservation and development projects. Conservation Biology,
13,830-841.
Salafsky, N., Margoluis, R., Redford, K.H. & Robinson, J.G.
(2002) Improving the practice of conservation: a conceptual
framework and research agenda for conservation science.
Conservation Biology, 16, 1469-1479.
Salzer, D. & Salafsky, N. (2006) Allocating resources between
taking action, assessing status, and measuring effectiveness of
conservation actions. Natural Areas Journal, 26, 310-316.
Simberloff, D. (1998) Flagships, umbrellas, and keystones:
is single species management passe in the landscape era?
Biological Conservation, 83, 247-257.
Smallwood, K. (2000) A crosswalk from the Endangered Species
Act to the HCP handbook and real HCPs. Environmental
Management, 26 (Suppl. 1),23-35.
Stein, B.A., Kutner, L.S. & Adams, J.S. (2000) Precious heritage:
the status of biodiversity in the United States. Oxford University
Press, Oxford.
Stem, C., Margoluis, R., Salafsky, N. & Brown, M. (2005) Moni-
toring and evaluation in conservation: a review of trends and
approaches. Conservation Biology, 19,295-309.
Tennant, T., Allen, M.F. & Edwards, F. (2001) Perspectives in
conservation biology in southern California: 1. Current extinction
rates and causes. University of California, Center for Conserva-
tion Biology, Riverside.
470
@ 2007 The Authors
Diversity and Distributions, 14,462-471 Journal compilation @ 2007 Blackwell Publishing Ltd
The Nature Conservancy (2004) Definitions of sources of stress
(threats) developed during the sequencing conservation
actions project, southern US Region. The Nature Conservancy,
Washington, D.C.
Unitt, P. (2004) San Diego County bird atlas. San Diego Natural
History Museum, San Diego, California.
US Fish and Wildlife Service (1996) Habitat conservation plan-
ning and incidental take permit processing handbook. US
Department of the Interior Fish and Wildlife Service and US
Department of Commerce National Oceanic and Atmospheric
Administration National Marine Fisheries Service. Accessed
4/3/2007 http://www,fws.gov/ endangeredlhcp/hcpbook.html.
Wilhere, G.P. (2002) Adaptive management in habitat conserva-
tion plans. Conservation Biology, 16,20-29.
Williams, B.K., Szaro, R.C. & Shapiro, C.D. (2007) Adaptive
management: the U.S. Department of Interior Technical
Guide. Adaptive Management Working Group, US Department
of the Interior, Washington, DC.
Wilson, E.O. (1992) The diversity of life. Norton, New York.
W1lson, K.A, McBride, M.P., Bode, M. & Possingham, H.P. (2006)
Prioritising global conservation efforts. Nature, 440,337-340.
Yoccoz, N.G., Nichols, J.D. & Boulinier, T. (2001) Monitoring of
biological diversity in space and time. Trends in Ecology &
Evolution, 16,446-453.
Species prioritization for monitoring
SUPPLEMENTARY MATERIAL
The following supplementary material is available for this article:
Appendix SI Table of MSCP covered plant species in PDF
format. They are sorted by number of threats and degree of risk.
Appendix S2 Table of MSCP covered animal species in PDF
format. They are sorted by number of threats and degree of risk.
Appendix S3 Information sheet for organizing species infor-
mation in PDF format.
Appendix S4 Species prioritization tables in MHTM format.
Rankings are based on at-risk status and threats facing the species.
This material is available as part of the online article from:
http://www.blackwell-synergy.comldoilabs/l0.l111/j.1472-
4642.2007.00447.x
(This link will take you to the article abstract).
Please note: Blackwell Publishing are not responsible for the
content or functionality of any supplementary materials supplied
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be directed to the corresponding author for the article.
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