Monitoring & Evaluation Guidebook 2010
WILDLIFE TERRESTRIAL HABITAT: MIS
16. Are population and habitat trends for Management Indicator Species (MIS)
consistent with expectations? Are these trends due to changes in habitat
conditions or other factors? If they are tied to habitat conditions, is there a direct
relationship with forest management, climate change, or other factors?
Terrestrial MIS include red squirrel, black bear, brown bear, marten, river otter,
Sitka black-tailed deer, mountain goat, gray wolf, Vancouver Canada goose, bald
eagle, red-breasted sapsucker, Hairy woodpecker and brown creeper.
Goals and Objectives
Maintain the abundance and distribution of habitats, especially old growth forests, to
sustain viable populations in the planning areas (USDA Forest Service 2008 p. 2-9).
Maintain habitat capability sufficient to produce wildlife populations that support the use
of wildlife resources for sport, subsistence and recreational activities (USDA Forest
Service 2008 p. 2-9).
Design and implement structural and non-structural wildlife habitat improvement
projects (USDA Forest Service 2008, p. 2-9).
Include a young-growth management program to maintain, prolong, and/or improve
understory forage production, and to improve habitat distribution, including future oldgrowth characteristics in young-growth timber stands for wildlife on both suitable and
unsuitable lands (USDA Forest Service 2008, p. 2-9).
Sampling / Reporting Period
Annual / 5 year
Evaluation Criteria
Changes in important habitats and population trends for MIS species (WILD1.II.B).
In 1999, an interagency group of specialists produced “A Reassessment of
Management Indicator Species for the Tongass National Forest.” This document
describes the process and provides rationale for the species chosen for Tongass MIS.
Due to the challenges and uncertainties associated with monitoring populations of many
MIS on the Tongass (e.g., spatial scale, rarity/difficulty to detect of some species, and
lack of correlation between population trends and management activities) and the
evolution of management concerns (e.g., increased focus on young-growth forest
management and climate change) the MIS list is currently under review. A list of six
wildlife species have been preliminarily identified by the interagency review group for
retention as MIS (Sitka black-tailed deer, marten, black bear, brown bear, mountain
goat, and bald eagle; Hayward and Jacobson 2011). Table 1 presents the current list of
MIS and associated habitat associations. Most species are associated with POG
habitats, and some are associated with estuarine, shoreline, and stream habitats which
are protected by Forest Plan standards and guidelines.
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Monitoring & Evaluation Guidebook 2010
Table 1. Current Tongass MIS, their habitats, and potential impacts.
MIS Species
Important Habitats
Potential Impacts of Forest
Service Activities
Sitka black-tailed
deer1
Low elevation (below 1,500 feet)
POG during winter.
Habitat loss
Marten1
Coastal habitats (beach fringe) and
riparian areas; upland POG below
1,500 feet in elevation in winter
Habitat loss/fragmentation;
changes in road access
Black bear1
POG and salmon streams
Habitat loss; changes in road
access especially along salmon
streams
Brown bear1
POG forest within 500 feet of Class I
salmon streams
Habitat loss; increased hunter
changes in road access, especially
along salmon streams
Mountain goat1
Cliffs, alpine and subalpine habitats
Disturbance due to helicopter
activity
Bald eagle1
High-volume POG near shorelines
Changes in POG forest along the
shoreline
Alexander
Archipelago wolf
Densities are closely tied to the
population levels of their prey
(primarily Sitka black-tailed deer)
Impacts to deer populations;
changes in road access
Brown creeper
Large-tree POG (SD 7 class)
Habitat loss/fragmentation
Hairy woodpecker
High-volume POG (SD 5S, 5N, 67
classes) and snags
Habitat loss/fragmentation
Red-breasted
sapsucker
Low volume POG (SD4 class) and
snags
Habitat loss/fragmentation
Red squirrel
POG including cone-producing trees
Habitat loss
River otter
POG adjacent to shorelines and
streams
Changes in shoreline and riparian
habitats
Vancouver
Canada goose
Wetlands (both forested and nonforested) in estuary, riparian, and
upland areas.
Changes in shoreline and riparian
habitats
1Idenfitied
by interagency review group as top candidates for retention as MIS species
Precision and Reliability
The precision of GIS-based evaluation criteria is high. However, reliability is tempered
by mapping errors and time lags in incorporating changes in forest resources due to
natural causes (e.g., windthrow) into the GIS database. These sources of error should
be improved during the life of the Forest Plan.
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The precision and reliability of evaluation criteria based on reviews of recent literature or
ongoing monitoring and research depend on the methods of data collection and level of
peer review. Sources of bias include inherent limitations of resource inventories.
Data Sources
Tongass National Forest GIS databases; project-level environmental documentation to
assess if important habitats have been impacted; ongoing monitoring and research
conducted by the Alaska Department of Fish and Game (ADF&G), U.S. Fish and
Wildlife Service (USFWS), and other entities as available; and the latest published and
grey literature. Table 2 identifies some of the data sources associated with each MIS.
Overtime, additional studies and monitoring efforts will be added as they become
available.
Changes in POG habitat will be derived from sampling undertaken for Monitoring
Protocol 9 – Biodiversity Ecosystem.
Sitka Black-tailed Deer
Scale of Analysis: Forest-wide/subsample of WAAs, areas below 1,500 feet elevation
Population Trends
Approach: Indices of abundance for black-tailed deer are available from the ongoing,
region-wide fecal pellet group monitoring program implemented by the ADF&G in
conjunction with the Forest Service. Monitoring transects are established throughout
southeast Alaska and surveys are conducted in the spring to estimate black-tailed deer
population trends (McCoy 2010, ADF&G 2011). Surveys are also conducted to estimate
spring mortality, which is helpful information for interpreting trends. This approach
provides a cost-effective, non-invasive way to monitor deer in forested landscapes and
across large spatial scales. However, population indices derived from fecal pellet group
counts can be biased by seasonal and weather-related variables that influence pellet
persistence, defecation rates, and pellet detectability (Brinkman et al. 2011).
In recent years, a DNA-based mark-recapture technique using fecal pellet group counts
has been tested on the Tongass (e.g., Prince of Wales Island [Brinkman et al. 2011]
and Chichagof Island [McCoy et al. 2011]). This technique involves the extraction of
DNA from the surface of fecal pellets and use of microsatellite markers to identify
individual deer. Although field, lab, and analytical methods are still undergoing
refinement, these studies indicate that such an approach successfully enables the
estimation of deer population abundance and density and may be appropriate for
monitoring on the Tongass. However, the monitoring costs of this technique are
relatively high because of lab/analytical costs
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Therefore, two options for monitoring deer populations are presented. First, is
continuing to monitor deer populations using pellet-group monitoring. In addition,
continue to utilize ADF&G deer harvest and hunter effort data and spring mortality
survey results. The second option is using DNA-based mark-recapture sampling
technique to assess black-tailed deer population trends in conjunction with pellet-group
monitoring and deer harvest analysis, if funding allows.
Sampling – Option 1: As noted above, monitoring transects are established throughout
southeast Alaska, primarily in deer winter range from sea level to 1,500 feet elevation
(Kirchhoff and Pitcher 1988), and surveys are conducted in the spring to estimate blacktailed deer population trends. Continue working cooperatively with ADF&G to monitor
these transects. In addition, ADF&G harvest data and spring mortality surveys will
continue to be analyzed in conjunction with hunter effort and weather information.
Sampling – Option 2: This option provides for using DNA-based mark-recapture
sampling techniques in conjunction with deer pellet-group monitoring and harvest and
effort data analysis.
A subsample of WAAs across the Tongass will be identified for monitoring. Sample
WAAs will be selected based on input from Forest Service, USFWS, and ADF&G
biologists; accessibility and other logistical constraints; and will be representative of a
range of environmental conditions, management intensities, predator guilds, and other
factors. Within the sample WAAs, the layout and spacing of monitoring transects will
follow methods described in McCoy et al. (2011) but may include establishment of
transects (1) in relation to deer trails (to increase pellet group detection rates; see
Brinkman et al. 2009); (2) on a grid or other systematic layout; or (3) in conjunction with
existing pellet transects. In general, sampling points or nodes are established from
which one or more transects radiate.
Field data collection and DNA extraction procedure will follow methods described in
Brinkman et al. (2010, 2011) and McCoy et al. (2011); however, methods will be
adapted over time based on the best available techniques. Surveys will be conducted
during late winter, between the beginning of snow melt and the onset of spring green up
(timing may vary between locations and years) to capture the period when deer exhibit
high site fidelity to their winter ranges. Each transect will be visited 2-3 times during the
season unless the results of ongoing pilot studies suggest a modified sampling intensity
(ADF&G is currently evaluating single replication mark-recapture approach; McCoy et
al. 2011).
Results: For Option 1, annually collect mean pellet-group densities by Game
Management Unit and subunit, in conjunction with ADF&G. Also, gather information on
the severity of winter weather, weather conditions during the surveys, and spring
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Monitoring & Evaluation Guidebook 2010
mortality surveys. In addition, gather results from ADF&G deer harvest and hunter
effort data by Game Management Unit and subunit.
For Option 2, annually report the results of DNA-based mark-recapture sampling
including the number of transects sampled and the number of deer pellet groups
collected per transect and node during each sample session by WAA and
biogeographic province, in addition to the efforts described above. Capture probabilities
will also be reported annually.
Analysis: For Option 1, annually compare mean pellet-group densities with results from
previous years by Game Management Unit and subunit. Consider the effects of winter
weather severity, weather conditions during surveys, and other factors influencing
pellet-group counts in making comparisons. In addition, compare results from ADF&G
deer harvest and hunter effort data by Game Management Unit and subunit, also
considering the effect of weather conditions and other influences and consider the
results from spring mortality surveys.
For Option 2, annually use the genotypes of individual deer to estimate population
abundance using mark-recapture methods (e.g., Program MARK), in addition to the
above efforts. Population density will also be calculated based on the estimates of
abundance. Population trends will be evaluated every five years. Abundance and
density estimates may be compared between regions, and other factors. Deer density
and abundance will be assumed to have changed between years if 95 percent
confidence intervals surrounding estimates do not overlap.
Supplemental Information: Deer population data will be supplemented with the results
the ongoing ADF&G study on the survivorship of Sitka black-tailed deer fawns in
southeast Alaska (ADF&G project 2.14). This study, which will continue through 2014,
is assessing the sources and rates of black-tailed deer fawn mortality and patterns of
habitat selection on Prince of Wales Island.
Habitat Trends
Approach: Deer habitat trends will be evaluated by quantifying changes in the amount
and distribution of deer winter habitat (high-volume POG less than 1,500 feet elevation)
on the landscape.
Sampling: Deer winter habitat (high-volume POG less than 1,500 feet elevation) will be
mapped using a GIS framework.
Results: Annually the amount of available habitat (in acres) will be summarized for the
Forest and by WAA.
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Monitoring & Evaluation Guidebook 2010
Analysis: Annually, changes in the amount of deer winter habitat will be determined for
the Forest and by WAA. Every five years, the levels of available habitat will be
compared to levels predicted in the 2008 Forest Plan FEIS (USDA Forest Service
2008b) and changes in habitat distribution will be evaluated by identifying the
biogeographic provinces with the declines in habitat.
Marten
Scale of Analysis: Forest-wide/WAA; subsample of areas with known populations
and/or suitable habitat.
Population Trends
Approach: Marten are a relatively uncommon, cryptic forest-associated species that can
be challenging to monitor. A variety of non-invasive monitoring methods for marten exist
that can be used over large areas, including track plates, snow-transect segments, use
of remote cameras over bait stations. These techniques produce population indices
(e.g., average number of detections per sample unit or the proportion of sample units
where a target species is detected), which can be used to track changes in a species’
distribution but lack power to detect trends in abundance (Zielinski et al. 1997, Strayer
1999). Additionally, because these techniques do not allow the identification of
individual animals they cannot be used to estimate density or absolute abundance.
More recently, DNA-based methods derived from hair samples have been evaluated for
estimating marten population size and distribution (Selkirk Mountains of British
Columbia; Mowat and Paetkau 2002) and dispersal rates and distances (Admiralty
Island; Pauli et al. 2012).
Due to the challenges associated with monitoring marten across a large landscape such
as the Tongass, development of a monitoring program for marten will begin with a pilot
study to assess the efficacy of implementing a large-scale hair capture DNA-based
monitoring effort, if funding allows.
In the interim, marten population trends will be assessed based on the ADF&G
management reports and anecdotal information included in the trapper questionnaire.
Although these sources of information do not provide population estimates or actual
trend data, they do give a general sense of population sustainability.
Pilot Study: Pilot study monitoring locations will be selected based on input from Forest
Service, USFWS, and ADF&G biologists; accessibility and other logistical constraints;
and will be representative of a geographic distribution of marten across the Tongass,
management intensities, variation in marten prey assemblages, and other factors.
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Monitoring & Evaluation Guidebook 2010
Study area boundaries will be delineated so that they following heights of land between
major watersheds, such that boundaries are likely to provide geographic closure to
marten during winter. Traplines will be established within each study area, along which
hair capture devices will be set. Methods for establishing and checking devices will
follow Mowat and Paetkau (2002). This effort will be initiated when sufficient funding is
available to conduct an adequate study.
Sampling: TBD based on results of pilot study.
Results: Collect and review ADF&G management reports and other available
information by Game Management Unit and subunit.
Results of pilot study will be reported in the monitoring report. Recommended
modifications for the monitoring protocol, lessons learned, and other information
pertaining to the efficacy of the monitoring approach will be reported.
Analysis: Annually compare the results of ADF&G marten harvest and effort data with
similar data from previous years by Game Management Unit and subunit. Consider the
effects of weather conditions, changes in reporting consistency, and other influences.
For the pilot study, assess the efficacy of using a hair capture technique. Determine if
additional or different study areas would increase monitoring success.
Habitat Trends
Approach: Marten habitat trends will be evaluated using the habitat quality ratings
developed by Suring (2012) which enable the ranking of a location on the landscape
from very low to very high habitat quality (the Habitat Index). The ratings for marten are
based on one variable, Size Density Model land cover class, which is representative of
factors associated with marten habitat selection including land cover, canopy cover, and
stand age (Suring 2012). The habitat index can be applied to each polygon on a map of
land cover class to evaluate marten habitat quality across the landscape. This enables
an evaluation of how the composition of the landscape changes in terms of its likelihood
of being used by marten (i.e., how much of the landscape has very high, high,
moderate, and low likelihood of being used).
Although there is no direct link between this type of habitat-based analysis and marten
population viability, in combination with demographic information, the marten habitat
model can be used to evaluate current management strategies. It should be noted that
the authors identify several limitations of the model and areas where additional
evaluation is needed. Therefore, this protocol may be modified over time to incorporate
the best available information related to marten habitat selection.
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Monitoring & Evaluation Guidebook 2010
Marten habitat trends will also be assessed by evaluating changes in the Forest Plan
conservation strategy and conducting an analysis of habitat fragmentation. Marten were
one of the design species considered during the development of the Forest Plan
conservation strategy. They also require large tracts of intact forest. Therefore, they
could be affected by changes in the conservation strategy that reduce connectivity
between reserves, or reduce the amount of POG included in the reserve system.
Sampling: Marten habitat will be mapped across the Tongass using the SDM (Suring
2012). NEPA documents will be reviewed to identify any changes to the Forest Plan
reserve system.
Results: Annually the amount of low, moderate, high and very high quality habitat
quality (in acres) will be summarized across the Forest and by WAA. Changes to the
reserve system will be identified.
Analysis: Annually, changes in the amount of high to very high quality habitat will be
determined for the Forest and by WAA. Changes in the reserve system will be
evaluated for potential impacts to marten. Every 5 years, changes in marten habitat
distribution will be evaluated by conducting a habitat fragmentation analysis using
FRAGSTATS. FRAGSTATS may be used to calculate cell by cell patch cohesion
(ranging from 0 to 100, measuring the physical connectedness land cover patches),
edge density, patch size, or other metrics using a moving-window analysis on a
rasterized version of the SDM land cover GIS database. The size of the moving window
will be determined based on marten home range size, minimum patch size
requirements, and/or dispersal abilities. Areas where marten occupancy or dispersal
may be limited will be identified based on the selected metrics.
Black Bears and Brown Bears
Scale of Analysis: Mainland and the islands south of Frederick Sound (black bears);
Mainland and the islands north of Frederick Sound (brown bears)
Population Trends
Approach: Black bear and brown bear population trends will initially be monitored by
reviewing ADF&G management reports. However, this information should be
interpreted with caution. In most GMUs coinciding with the Forest, no black bear
population studies have been conducted so there are no population estimates or actual
trend information available. Brown bear populations have received greater attention but
population estimates and trend information is still very limited and only available for
localized areas. For both species, the ADF&G collects information during sealing to
estimate total harvest, average skull size, male to female harvest ratio, and age
structure of the harvest which serve as general population trend indicators. Without
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Monitoring & Evaluation Guidebook 2010
demographic data there is no strong correlation between these measures and
population sustainability. Likewise, hunter information collected during sealing, and
based on the return of general season harvest tickets for black bears provides
information on harvest per unit effort (e.g., days hunted per bear). Hunter effort is
another source of information that can be used to identify where bear population
dynamics may be changing. However, this too, is a general indicator of population
change. The Forest assumes that if current hunting seasons or bag limits are
maintained, and the metrics collected by ADF&G indicate a stable population structure
and level of hunter effort, the population is assumed to be sustainable and no additional
monitoring is needed.
Where a black bear or brown bear population appears to be at unsustainable levels,
and where Forest Service management activities have the potential to affect that
population, the Forest Service will consider collaborating with ADF&G and other
partners to develop and implement a focused population study. Studies may include
biomarking, DNA-based methods, or other noninvasive techniques to estimate the size
of the focal population. The success of these methods has been demonstrated for
black bears on Kuiu Island (Peacock et al. 2007) and for brown bears on the Kenai
peninsula (Morton et al. 2013).
Sampling: Annually, ADF&G management reports will be reviewed for sealing and
hunter harvest and effort information.
Results: Average skull size, harvest ratio, age structure of harvested animals, and
hunter effort will be reported.
Analysis: Annually, based on the conclusions drawn in the ADF&G management report
drawn about population sustainability the need for additional monitoring will be
evaluated.
Habitat Trends
Approach: Black bears and brown bears have the potential to be impacted by changes
in road access (resulting in changes in hunter access), disturbance, and POG forest
(primarily black bears), along salmon-bearing streams. Forest plan standards and
guidelines protect riparian areas, estuaries, and the beach fringe where black bears and
brown bears forage. However, young-growth management and other restoration
activities, as well as road development can occur in the vicinity of these areas.
Sampling: Sampling will be GIS-based, and will involve the calculation of acres of POG
and miles of roads (open and closed) within 500 feet of Class I salmon streams.
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Results: The acres of POG and miles of road (open and closed) within 500 feet of Class
I salmon stream will be reported by WAA. Acres of young-growth management or other
restoration activities within these habitats will also be reported.
Analysis: Annually the change in aces of POG and miles of road within 500 feet of a
Class I salmon stream will be discussed. Every 5 years, the distribution of impacts to
habitat will be assessed.
Mountain Goat
Scale of Analysis: Hunt units within Game Management Units (GMU)
Population Trends
Approach: Mountain goat population trends will be monitored by tracking aerial survey
data collected by the ADF&G. Currently, the ADF&G, in collaboration with various
partners, is monitoring mountain goat populations in the Lynn Canal area (White et al.
2012), lower Cleveland Peninsula (White et al. 2010), the Haines/Skagway area (White
et al. 2011a) and on central Baranof Island (White et al. 2011b). These efforts involve
conducting routine aerial surveys in areas inhabited by radio-marked mountain goats.
Surveys yield information on population abundance and composition, as well as
reproductive and survival rates. However, to produce robust population estimates raw
survey data must be adjusted to account for bias associated with climatic,
environmental, and behavioral factors that influence the probability of sighting goats.
With funding from the Forest Service, ADF&G is currently developing a sightability
model for mountain goats in southeast Alaska which will be used to adjust aerial survey
data (White and Pendleton 2012).
Sampling: Data sets will be obtained from ADF&G every year.
Results: Counts of mountain goats from each study population will be reported in annual
reports.
Analysis: Annually, counts from aerial surveys from each study population, will be
compared with data from the previous year. When the sightability model is developed
and validated, counts will be extrapolated to estimate population size. Population trends
will be evaluated every 5 years.
Habitat Trends
Approach: Mountain goats are strongly associated with rocky, rough habitat which
serves as escape cover; however, the location of escape cover for some mountain goat
populations occurs in areas that may receive disturbance from concentrated human
activities (e.g., mining and helicopter flight-seeing and heli-skiing). Therefore, mountain
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Monitoring & Evaluation Guidebook 2010
goat habitat trends will be evaluated by tracking changes in permitted helicopter
activities (or other human uses) in the vicinity of known mountain goat populations.
Sampling: NEPA documents will be reviewed for new permitted helicopter activities in
the vicinity of mountain goat populations. Baseline (existing) helicopter activity levels
(e.g., flights per day or a similar metric) will be obtained from Forest Service permitting
specialists. Focus will be on mountain goat populations that are routinely surveyed by
ADF&G to enable comparison between population and habitat trends.
Results: Changes in the number of permits, new authorizations, and/or helicopter
activity levels in the vicinity of mountain goat populations will be reported by GMU. Any
projects with the potential for significant effects to mountain goats will be identified.
Analysis: Annually, the number of permits, authorizations, and/or helicopter activity
levels in the vicinity of mountain goat populations in each GMU will be compared to the
previous year. Every 5 years, population trends (above) will be compared with changes
in permitted helicopter activity (or other human uses). Substantial declines in mountain
goat numbers in areas with increased human disturbance will trigger a reevaluation of
local helicopter access management.
Bald Eagles
Scale of Analysis: Forest-wide
Population Trends
Approach: Bald eagle population trends will be monitored by tracking aerial survey data
collected by the USFWS.
Sampling: Data sets will be obtained from USFWS every year.
Results: Counts of bald eagles from each survey area will be reported in annual reports.
The number of nests and percent active nests will be reported.
Analysis: Annually, counts from aerial surveys from each survey area, will be compared
with data from the previous survey year. Population trends will be evaluated every 5
years.
Habitat Trends
Approach: Bald eagles generally nest within the beach fringe, and are, therefore,
sensitive to management activities within the beach fringe. Although beach fringe
standards and guidelines prohibit timber harvest, there has been recent focus on young-
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Monitoring & Evaluation Guidebook 2010
growth management and restoration of previously harvested beach fringe forest stands
develops.
Bald eagle habitat trends will be evaluated using the technique developed by Suring
(2012) which enables the ranking of a location on the landscape from very low to very
high habitat quality (the Habitat Index). The technique for bald eagles consists of two
variables which collectively produce an index of habitat quality, allowing the ranking of a
location on the landscape from very low to very high. A variable incorporating selectivity
indices for land cover classes at the nest site provide a probability of selection as a nest
site. A variable based on the weighted mean selectivity indices for the nest area is
combined with the nest site variable to produce an index of habitat quality for bald
eagles (Figure 1; Suring 2012). The habitat index can be applied to each polygon on a
map of land cover class to evaluate bald eagle habitat quality across the landscape.
This enables an evaluation of how the composition of the landscape changes in terms
of its likelihood of being used by bald eagles (i.e., how much of the landscape has Very
High, High, Moderate, and Low likelihood of being used).
Probability of Nesting
Nest Site SDM class
Nest Area Index
Habitat Selectivity Index
Figure 1. Variables incorporated in the Bayesian Belief Network for goshawk habitat
selection in southeast Alaska.
Although there is solid link between this type of habitat-based analysis and bald eagle
population viability, in combination with demographic information, the bald eagle habitat
model can be used to evaluate current management strategies. It should be noted that
the authors identify several limitations of the model and areas where additional
evaluation is needed. Therefore, this protocol may be modified overtime to incorporate
the best available information related to bald eagle habitat selection.
Sampling: Bald eagle habitat will be mapped using the technique developed by Suring
(2012) to calculate the habitat selectivity index across the Forest.
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Monitoring & Evaluation Guidebook 2010
Results: Annually the acres (and percent) of each bald eagle habitat selectivity index
category (very low, low, moderate, high, and very high) will be reported by
biogeographic province and for the Forest as a whole.
Analysis: Annually, changes in the acres of habitat selectivity index categories from the
previous year will be reported. Every 5 years, the distribution of very high, high, and
moderate quality bald eagle habitat across the Forest will be evaluated, as well as the
distribution of forest management activities within the beach fringe.
Alexander Archipelago Wolf
Scale of Analysis: Forest-wide; focus on local populations of concern
Population Trends
Approach: Wolf population trends will initially be monitored by reviewing ADF&G
management reports. However, this information should be interpreted with caution. In
most GMUs coinciding with the Forest, no wolf population studies have been conducted
so there are no population estimates or actual trend information available. Most
information comes from sealing records, the statewide trapper survey, and anecdotal
accounts. An exception is in GMU 2 where the Forest is currently partnering with ADFG
to establish protocols for estimating and monitoring wolf population status and trends.
The Forest assumes that if current hunting seasons or bag limits are maintained, and
the metrics collected by ADF&G indicate a stable population structure and level of
hunter effort, the population is assumed to be sustainable and no additional monitoring
is needed. Where ADF&G monitoring indicates concern for local populations, and where
Forest Service management activities have the potential to affect the local population
the Forest Service will consider collaborating with ADF&G and other partners to develop
and implement focused population studies.
Sampling: Annually, ADF&G management reports will be reviewed for sealing and
hunter harvest information as well as anecdotal accounts of wolf population status.
Results: Results from ongoing research wolf research in GMU 2 will be reported.
Analysis: Annually, based on the conclusions drawn in the ADF&G management report
about population sustainability the need for additional monitoring will be evaluated.
Habitat Trends
Approach: Wolves are habitat generalists and are closely tied to the populations of their
primary prey (deer). The link between wolf abundance and Forest Service habitat
management is indirect, relating to impacts on deer habitat. Therefore, deer habitat
trends will be used as a measure of trends in wolf habitat. In addition, wolf harvest
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Monitoring & Evaluation Guidebook 2010
levels are sensitive to road densities. Therefore, open and closed road densities will be
used to assess habitat trends in biogeographic provinces where changes in road
densities are occurring.
Sampling: See deer habitat trend analysis above. In addition, open and closed road
densities will be measured by GIS for biogeographic provinces where changes are
occurring.
Results: See deer habitat trend analysis above. Annually open and closed road
densities will be reported for biogeographic provinces where changes are occurring.
Analysis: Based on the results of the deer habitat trend analysis and changes in road
densities, the status and distribution of wolf habitat will be discussed.
Cavity nesting species (Hairy Woodpecker, Red-breasted Sapsucker) and Brown
Creeper
Scale of Analysis: Forest-wide
Population Trends
Approach: Population trends will be monitored based on the results of the North
American Breeding Bird Survey (BBS) and the Alaska Landbird Monitoring Survey
(ALMS). The BBS is a road-based monitoring program designed to track the status and
long-term trends of North American birds. The ALMS was developed to monitor
landbirds in roadless areas in Alaska and complements data collected from the BBS.
Sampling: BBS and ALMS data sets will be obtained from USGS every year.
Results: Regional counts of hairy woodpeckers, red-breasted sapsuckers, and brown
creepers will be reported.
Analysis: Annually, counts from ALMS and BBS surveys from each survey area, will be
compared with data from the previous survey year. Population trends, based on
findings of the BBS and ALMS programs, will be evaluated every 5 years.
Habitat Trends
Approach: Cavity nesting species and brown creepers are associated with POG forests
which they use for nesting and foraging sites, and may be affected by activities that
reduce large, mature trees. The assessment of habitat trends for this species tiers to
monitoring questions 9 and 11 which evaluate the amount of POG within the reserve
system and in the matrix, respectively.
Sampling: Refer to monitoring questions 9 and 11.
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Monitoring & Evaluation Guidebook 2010
Results: Refer to monitoring questions 9 and 11.
Analysis: Based on the analysis presented for monitoring questions 9 and 11, the status
and distribution of habitat available for these species will be discussed.
River Otter
Scale of Analysis: Forest-wide
Population Trends
Approach: Population trends will be monitored by reviewing ADF&G management
reports.
Sampling: Annually, ADF&G management reports will be reviewed for trapper harvest
information as well as anecdotal accounts of river otter population status.
Results: Results from river otter research studies in southeast Alaska will be reported.
Analysis: Annually, based on the conclusions drawn in the ADF&G management report
about population sustainability the need for additional monitoring will be evaluated.
Habitat Trends
Approach: River otters are widespread throughout southeast Alaska along coastal and
inland waters (MacDonald and Cook 1999). Tongass Forest Plan standards and
guidelines provide extensive protection for beach fringe habitats and riparian habitats
along Class I and II streams used by river otters. Because of their strong association
with these habitats and their protection by the Forest Plan, no specific habitat analysis
will be conducted, unless a change in availability of river otter habitat is indicated.
Sampling: Projects will be reviewed to determine if any are likely to significantly affect
river otter habitat.
Results: Results of the reviews will be reported.
Analysis: Based on the results, an analysis of effects on river otter habitat will be
conducted.
Vancouver Canada Goose
Scale of Analysis: Forest-wide
Population Trends
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Monitoring & Evaluation Guidebook 2010
Approach: Population trends will be monitored based on the results of the North
American Breeding Bird Survey (BBS) and the Alaska Landbird Monitoring Survey
(ALMS). The BBS is a road-based monitoring program designed to track the status and
long-term trends of North American birds. The ALMS was developed to monitor
landbirds in roadless areas in Alaska and complements data collected from the BBS.
Sampling: BBS and ALMS data sets will be obtained from USGS every year.
Results: Regional counts of the Vancouver Canada goose will be reported.
Analysis: Annually, counts from ALMS and BBS surveys from each survey area, will be
compared with data from the previous survey year. Population trends, based on
findings of the BBS and ALMS programs, will be evaluated every 5 years.
Habitat Trends
Approach: The Vancouver Canada goose is common throughout southeast Alaska.
Vancouver Canada geese are closely associated with water. However, the Vancouver
subspecies is unique in that they nest and raise their broods within the forest (Lebeda
and Ratti 1983; Mickelson 1984). During nesting and brood rearing this subspecies is
often associated with poorly drained habitats that have numerous, small freshwater
pools (Lebeda and Ratti 1983). Much Vancouver Canada goose habitat is protected by
Forest Plan standards and guidelines and timber harvest of goose nesting and brood
rearing habitat has generally been minimal because these sites are fairly unproductive.
Therefore, the assessment of habitat trends for this species will tier to monitoring
questions 9 and 11 which evaluate the amount of POG within the reserve system and in
the matrix, respectively.
Sampling: Refer to monitoring questions 9 and 11. In addition, projects will be reviewed
to determine if any are likely to significantly affect Vancouver Canada goose habitat.
Results: Refer to monitoring questions 9 and 11. In addition, report the results of
project reviews.
Analysis: Based on the results, an analysis of effects on Vancouver Canada goose
habitat will be conducted.
Feedback Mechanism
If monitoring results indicate significant effects, then evaluate permitted uses and/or
projects and plans, and change if needed.
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Monitoring & Evaluation Guidebook 2010
References Cited
Alaska Department of Fish and Game. 2011. Deer management report of surveyinventory activities 1 July 2008 – 30 June 2010. P. Harper, editor. Juneau, AK.
Brinkman, T. J., M. K. Schwartz, D. K. Person, K. Pilgrim, and K. J. Hundertmark.
2009a. Effects of time and rainfall on PCR success using DNA extracted from deer
fecal pellets. Conservation Genetics DOI 10.1007/s10592-09-9928-7.
Brinkman, T. J., D. K. Person, W. P. Smith, F. S. Chapin III, K. R. McCoy, M.
Leonawicz, and K. J. Hundertmark. 2010. Using DNA to test the utility of pellet-group
counts as indices of deer density. Alaska Department of Fish and Game, Division of
Wildlife Conservation, Wildlife Research Final Report. Juneau, AK.
Brinkman, T. J., D. K. Person, F. S. Chapin III, W. P. Smith, and K. J. Hundertmark.
2011. Estimating abundance of Sitka black-tailed deer using DNA from fecal pellets.
Journal of Wildlife Management 75:232-242.
Lebeda, C.S. and J.T. Ratti. 1983. Reproductive biology of Vancouver Canada goose
on Admiralty Island, Alaska. Journal of Wildlife Management. 47(2): 297-306.
MacDonald, S.O. and J.A. Cook. 1999. The mammal fauna of southeast Alaska.
University of Alaska Museum, Fairbanks, Alaska. 145 pages.
McCoy, K. 2010. Sitka black-tailed deer pellet-group surveys in Southeast Alaska, 2010
report. Alaska Department of Fish and Game, Juneau, AK 99811-0024.
Mickelson, P.G. 1984. Use of old-growth forest by Canada geese. Pages 303-307 in:
W.R. Meehan, T.R. Merrell, Jr. and T.A. Hanley, eds. Fish and wildlife relationships in
old-growth forests: proceedings of a symposium. American Institute of Fisheries
Research Biologists, Reintjes Publ. Morehead City, NC.
Mowat, G., and D. Paetkau. 2001. Estimating marten Martes americana population
size using hair capture and genetic tagging. Wildl. Biol. 8:201-209.
Pauli, J.N., W.P. Smith, and M. Ben-David. 2012. Quantifying dispersal rates and
distances in North American martens: a test of enriched isotope labeling. Journal of
Mammalogy 93:390-398.
Strayer, D.L. 1999. Statistical power of presence-absence data to detect population
declines. Conservation Biology 13:1034-1038.
Suring, L. H. 2012. Modeling the Habitat Relationships of Species of Conservation
Concern in Old Forests of Southeast Alaska, USA. Northern Ecologic L.L.C.
Technical Bulletin 2012–1.
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Monitoring & Evaluation Guidebook 2010
USDA Forest Service. 2008. Tongass National Forest Land and Resource
Management Plan. USDA Forest Service R10-MB-603b.
Zielinski, W.J.; Truex, R.L.; Ogan, C.V.; Busse, K. 1997. Detection surveys for fishers
and American martens in California, 1989-1994: Summary and interpretations. In:
Proulx, G.; Bryant, H.N.; Woodard, P.M., editors. Martes: Taxonomy, ecology,
techniques, and management. Edmonton, Alberta: Provincial Museum of Alberta;
372-392.
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