Mt. Meager complex
Mt. Meager mountain goat aerial survey and DNA census, 2009
Prepared for:
British Columbia Conservation Foundation
206 - 17564 56A Avenue
Surrey, BC V3S 1G3
Prepared by:
Kim G. Poole1 and Darryl M. Reynolds2
March 2010
1
2
Aurora Wildlife Research, 2305 Annable Road, Nelson BC V1L 6K4; [email protected]
Ministry of Environment, Lower Mainland Region, P.O. Box 950 Stn. Prov. Govt., Sechelt, BC V0N 3A0;
[email protected]
Mt. Meager mountain goat aerial and DNA inventory, 2009
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ABSTRACT
Mountain goats (Oreamnos americanus) are managed as a big game species in British Columbia,
and as such estimates of population size are required to document population trend and to establish
hunting quotas. Here we estimated population size in the Mt. Meager complex of southwestern British
Columbia, using both conventional aerial survey techniques, and an estimate derived from identification
of individuals using DNA obtained from faecal pellet and hair samples collected on the mountain complex
during 3 sampling sessions.
We followed standard techniques for the aerial survey using a Bell 206B helicopter. On 21 July
2
2009 we used 2.2 hrs of helicopter survey time and surveyed a 90-km census zone of potential goat
2
habitat under good conditions. Overall survey effort averaged 1.4 min/km , with greater effort on the south
side of mountain complex where goats typically reside. We observed 60 goats (48 adults, 12 kids) in 15
groups. Kids comprised 20% of total goats (25 kids:100 adults [non-kids]). Groups were distributed from
1,700 to 2,450 m elevation. Based on past research, we subjectively applied a sightability of 0.70 to
2
derive an estimate of 86 goats (69 adults) (density of 0.95 goats/km ).
Population trends over the past 2–3 decades are difficult to determine because of differences in
techniques, timing, and survey effort. At best, survey data suggest a possible increase in recent years,
but possibly lower numbers than found during the 1980s and early 1990s. The causes of changes in
population size over time are unknown, but may involve a comparatively high female harvest and
influences of wolf (Canis lupus) predation.
For the DNA inventory, sampling crews collected 490 samples over 3 sampling sessions between
mid-July and early September 2009, of which 91% were pellet samples and the remaining were hair.
Using 7 markers, we identified 55 individuals from 170 samples that were successfully genotyped. We
used a Jackknife heterogeneity model to estimate a population of 77 mountain goats (SE =7.4, 95% CI
68–96, CV = 9.6). The mean capture probability was 0.38 per session. Genotyping success was higher
for pellets (56%) than for hair (32%), and was lower for pellets during session 2 (31%) compared with
sessions 1 and 3 (63–68%), likely related to heavy rain events in the week prior to session 2 collection.
The estimate from the aerial survey with sightability correction applied was higher than the DNAderived estimate. However, the DNA-derived estimate was associated with a measure of variance not
available from the aerial survey. The DNA-derived estimate suggested sightability of 0.78 during the
aerial survey.
Our innovative technique using non-invasive sample collection in a mark-recapture design proved
one of the first estimates of abundance of an ungulate species using DNA derived from faecal pellets. We
suggest this technique can be applied in a number of situations, for example where ungulates occupy a
moderately discrete area with low sightability (such as in heavily forested areas) and reasonable access.
Costs and effectiveness can be optimized using rigorous field and laboratory protocols. Non-invasive
sample collection and DNA genotyping of ungulate pellets will provide managers with rigorous and
statistically quantified estimates that can be used for conservation and management.
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TABLE OF CONTENTS
ABSTRACT ................................................................................................................................................... ii
INTRODUCTION........................................................................................................................................... 1
STUDY AREA ............................................................................................................................................... 2
STUDY DESIGN AND METHODOLOGY ..................................................................................................... 4
Aerial survey ............................................................................................................................................. 4
DNA sampling ........................................................................................................................................... 4
Population estimate from DNA sampling .................................................................................................. 6
Harvest data .............................................................................................................................................. 6
RESULTS...................................................................................................................................................... 6
Aerial survey ............................................................................................................................................. 6
DNA sampling ........................................................................................................................................... 7
Population estimate from DNA sampling ................................................................................................ 10
Genotyping success................................................................................................................................ 10
Harvest data ............................................................................................................................................ 12
DISCUSSION .............................................................................................................................................. 13
Aerial survey ........................................................................................................................................... 13
Population estimate from DNA sampling ................................................................................................ 14
Management recommendations ............................................................................................................. 16
ACKNOWLEDGEMENTS ........................................................................................................................... 16
LITERATURE CITED .................................................................................................................................. 17
APPENDIX 1. Personnel participating in the Mt. Meager mountain goat study, 2009. .............................. 21
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INTRODUCTION
Mountain goats (Oreamnos americanus) are an important species in British Columbia, valued by
First Nations and recreational hunters, and viewed as a symbol of rugged mountains and true
wilderness. Over half of the world population occurs in the province. While widespread throughout much
of the province, the Lower Mainland Region (Region 2) in southwestern British Columbia contains only
an estimated 3% (1,000–1,700 mountain goats) of the provincial total (Shackleton 1999, Mountain Goat
Management Team 2010). Although inventory data are sparse, it is perceived that goat populations are
stable or declining in much of the region (D. Reynolds, BC Environment, unpubl. data). General open
seasons for hunting mountain goats occur only in the northwestern half of the region, although difficulty
of access has resulted in an average harvest of about 2 animals annually. Periodic surveys are required
to update population estimates to ensure that harvests are sustainable.
Accurate estimates of mountain goat populations are difficult to obtain. Helicopter are generally
used to conduct total counts of mountain goats within most areas of British Columbia, with a sightability
correction applied afterwards for animals missed during the survey (RISC 2002, Poole 2007b). No
measures of variance are available with this technique. Other techniques used to estimate population
size are less developed (Poole 2007b). Reliable mark-resight techniques have not been well tested and
tend to produce wide confidence limits (Smith and Bovee 1984, Cichowski et al. 1994, Poole et al. 2000,
Pauley and Crenshaw 2006). Regression-based sightability correction models have only recently begun
to be developed for mountain goats (Poole 2007b, Rice et al. 2009), where group size, terrain
obstructions and vegetation cover are principle factors affecting sightability.
Non-invasive collection of tissue samples to obtain DNA for microsatellite genotyping required to
identify individuals and produce estimates of population size has been used for a number of wildlife
species, mainly carnivores (e.g., Woods et al. 1999, Mowat and Paetkau 2002, Paetkau 2003). Most
studies have obtained DNA from hair collected using barbed wire or glue. Collection of faecal pellet
samples (hereafter pellets) is attractive because of the ease of collection, potential for obtaining large
sample sizes, and reduced disturbance to the focal species. However, pellets may yield low quality and
quantity of DNA (Waits and Paetkau 2005, Brinkman and Hundertmark 2009), in part a result of time
since deposition, sensitivity to weather factors, and DNA contamination by micro-organisms (Maudet et
al. 2004, Piggot 2004, Murphy et al. 2007, Brinkman et al. 2009).
Non-invasive DNA sampling of ungulate populations is uncommon (Eggert et al. 2003, Piggott
and Taylor 2003, Maudet et al. 2004, van Vliet et al. 2008), in part because tissue samples are often
readily available from hunters. Ungulate tissue samples have been used to examine genetic diversity
and population/subspecies questions (McFarlane et al. 2009), and pellets collected in the field have
contributed to understanding of phylogenetics and population genetics (Gebremedhin et al. 2009). While
population estimates have been obtained from collection of carnivore scat (Bellemain et al. 2005), only
recently have pellets been used to provide population estimates of ungulates using a mark-recapture
study design (Eggert et al. 2003, Brinkman et al. submitted).
The Mt. Meager complex, within Management Unit 2-11 west of Pemberton in southwestern
British Columbia, harbours a population of mountain goats of regional importance. The Mt. Meager area
is one of few remaining hunted populations of goats with reasonable access within the Lower Mainland
Region. Ground-based counts during the 1980s and early 1990s suggested upwards of 70–80 goats
inhabited the mountain complex. The most recent aerial survey in 2007 counted 54 individuals (D.
Reynolds, BC Environment, unpubl. data). Since the recommendation is not to hunt populations with
<50 goats or adults in British Columbia (Hatter 2005, Mountain Goat Management Team 2010), it is
important to verify goat numbers to ensure conservation of this population and continue hunting
opportunities.
The objectives of this study were two-fold: firstly, to determine the number of mountain goats on
the Mt. Meager complex using conventional aerial survey techniques and compare these results with
historic data, and secondly, to demonstrate the utility of a method to produce a DNA-based population
estimate of mountain goats using a mark-recapture study design. We compared estimates derived from
these 2 methodologies, which enabled an indication of sightability for the aerial survey, and tested the
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feasibility of conducting DNA-based estimates. This study tested an innovative technique that can
contribute to long term monitoring and management of mountain goats and other ungulates, and can be
used to support current harvest management strategies.
STUDY AREA
The Mt. Meager study area is located in the Pacific ranges of the Coast Mountains, in the
southern submaritime moisture regime of the former Vancouver Forest Region (Green and Klinka 1994)
(now Coastal Forest Region). The Lillooet River forms the northern boundary of the study area, and is
often considered the division between coastal and interior ecosystems. The Mt. Meager complex was
formed by the Meager Creek volcanic complex, 9 volcanic assemblages of the Garibaldi group (Read
1977). This volcanic formation has produced hot springs and high landslide potential, being the most
unstable volcanic massif in Canada. Mt. Meager's most recent volcanic eruption occurred 2,350 years
ago.
Mountain goats in coastal ecosystems inhabit primarily higher elevation alpine areas during
summer, and winter on lower elevation, steep, south-facing forested slopes (Taylor et al. 2006).
Potential summer goat habitat in the study area is made up primarily of 2 biogeoclimatic zones: the
Mountain Hemlock (MH) zone and the Alpine Tundra (AT) zone above tree line (Green and Klinka
1994). Tree line is generally located at 1,600 m, and mountain peaks rise to 2,680 m (Figs. 1, 2).
Glaciers cover approximately one quarter of the alpine area. July and January mean temperatures for
Whistler, 60 km southeast of the study area, are 15.9ºC and –3.0ºC, respectively (Environment Canada
climate normals, unpubl. data). Whistler receives an average of 1,230 mm of precipitation annually
including 410 cm of snowfall. We used the Whistler Mountain high elevation station (1,640 m) to obtain
total precipitation and mean temperatures for the 7 and 14-day periods prior to field sample collections.
High on the valley sides, mountain hemlock (Tsuga mertensiana), Pacific silver fir (Abies
amabilis), and western hemlock (T. heterophylla) dominate, with scattered stands of yellow-cedar
(Chamaecyparis nootkatensis) (Green and Klinka 1994) (Fig. 1).
Figure 1. A portion of the Mt. Meager complex. Mountain goat habitat encompassed primarily alpine
meadows and barren areas above tree line, but also ridgelines and cliff areas below the upper extent of
forested habitat. (Photo: K. Poole)
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Mt. Meager mountain goat aerial and DNA inventory, 2009
Figure 2. Location of mountain goats observed during the aerial survey of the Mt. Meager complex, 21
July 2009, and of transects surveyed to collect goat pellets during capture sessions 1, 2, and 3, 2009.
Green shading denotes forested areas, white shading denotes alpine areas, and grey shading denotes
glaciers.
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STUDY DESIGN AND METHODOLOGY
Aerial survey
Study design and methodology for the aerial survey generally followed RISC standards (RISC
2002, Poole 2007b), and consisted of a total count survey, with sightability correction subjectively
applied afterwards. A census zone of potential goat habitat was surveyed, which generally included
steep, cliff or open habitat above 1,550 m elevation. We used a Bell 206B Jet Ranger helicopter with
pilot, navigator, and 2 observers. All occupants participated in locating mountain goats, and all
observers had extensive experience at aerial surveys. We surveyed all alpine, open subalpine, and
forested cliff habitats. We surveyed approximately 200–300 m in from the edge of glaciers, but not the
ice mass centres. We flew roughly 150–200 m contour lines at 80–120 km/hr, 75–100 m out from the
hillsides. Based on past experience with the goat distribution on the complex (D. Reynolds and S.
Rochetta, BC Environment, unpubl. data), we applied greater effort on the south side of the mountain
complex and less effort on the north side. We mapped approximate flight lines and survey coverage on
1:50,000 scale topographical maps and calculated the census zone from the maps based on the area
surveyed. For each goat group sighting we also recorded broad habitat type, and elevation from the
helicopter’s altimeter (estimated to the nearest 30 m). Goat locations (corrected to the location of the
group relative to the helicopter) and helicopter flight tracks were recorded with a hand-held global
positioning system (GPS) unit, which were later downloaded to a computer. We classified goats only into
kids and non-kid (yearlings and older; hereafter called adults) based on body size (Smith 1988) to
reduce survey time, to minimize harassment (Côté 1996), and because researchers familiar with
classification from aircraft agree more detailed age and sex classification is not reliable (Houston et al.
1986, Stevens and Houston 1989, Gonzalez-Voyer et al. 2001, S. Côté, Université de Sherbrooke, pers.
comm.). We calculated mean group size, as well as “typical” group size, an animal-centred measure of
the group size within which the average animal finds itself (Jarman 1974, Heard 1992). Incidental wildlife
sightings were also recorded.
DNA sampling
We conducted 3 1-day sessions of DNA sample collections. Originally designed at 3-week
intervals, weather delays for session 2 resulted in 26 and 16 days between sessions (22 Jul, 17 Aug, 2
Sep). We assembled 25–30 volunteers per session and provided orientation to the project and sampling
protocols prior to being deployed in the field (Fig. 3). We used a helicopter to place 12–16 crews of
normally 2 individuals to cover all accessible goat habitat across the mountain complex, primarily on
ridgelines and adjacent to escape terrain. A truly systematic design to coverage of the study area was
not possible because of the rugged terrain. Although sampling was biased towards potential goat habitat
where a helicopter can land and humans can walk safely, we assumed all individual goats move through
milder terrain at some point in their daily and weekly
movements.
Field crews were instructed to cover broad
areas of potential goat habitat or trails searching for
hair and pellets. A GPS track file of movements was
collected for each crew, which later was downloaded
to a laptop computer. Samples were most often
collected along trails and near beds, which were
generally located in areas where goats had a clear
view of surrounding areas below them. During each
field session, crews also collected information on
mountain goats observed, noting group composition
and distance and direction to the goat group.
Incidental observations (tracks, dens, etc.) were also
recorded.
Figure 3. Volunteer personnel. (Photo: K.
Poole)
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We emphasized collections of pellets, as preliminary testing suggested that most hair observed
in alpine areas at this time of year was passively shed from the spring/summer moult, with
correspondingly lower success of DNA amplification than plucked hair (Gagneux et al. 1997, D.
Paetkau, Wildlife Genetics International, pers. comm.). Faecal pellets can be roughly aged by colour and
dryness (e.g., Prugh and Ritland 2005). To maximize the success of DNA extraction (Brinkman et al.
2009), we instructed field personnel to attempt to collect only recently deposited pellets (less than ~1–2
weeks of age). We termed pellets as ‘fresh’ if they were wet in appearance with a mucus sheen. Very
fresh samples from animals eating succulent forage were more mass-like in appearance. ‘Recent’
pellets in general appeared dark and shiny, but lacked a wet appearance. Dull brown and dried pellets,
or those with mould or vegetation growth were deemed as ‘moderate’ age, ‘old’ or ‘dry’ and were
generally not collected. Generally 4 pellets were collected from each pellet pile and placed in a paper
coin envelope, which was labelled with crew information and the GPS waypoint. Since goats tend to be
in groups of >1 individuals and we had no reliable way of subsampling for a single individual, samples
were collected from all fresh and recent pellet piles observed, regardless of adjacency with other piles.
We also collected some hair samples, primarily in areas of fresh mountain goat sign (tracks) but no
pellets. We emphasized hair snagged on alpine vegetation, hoping that hair pulled from an animal would
contain non-shed hair and would have greater success at DNA extraction (because of an attached root)
than shed hair on the ground (Gagneux et al. 1997). We collected a minimum of 10 hairs for a sample,
although often the coin envelope was filled.
Sample envelopes were stored in paper bags, and within 36 hours of collection were dried in a
convection oven at ~150–160°C for 6–8 hours. Samples from session 2 were dried in warm (35ºC)
sunshine for 2 days, followed by 3–4 hours in a convection oven. All samples were sent to Wildlife
Genetics International (Nelson, BC, Canada) for microsatellite genotyping. Samples were subjected to
commercial DNA extraction methods and then genotyped using an automated DNA sequencing
machine using publicly available microsatellite markers. All samples were screened for DNA analysis,
with the exception of samples from 2 crews along 1 ridge system during the second session who
collected 170 samples (74% of the samples collected from that session, 143 samples which were
deemed potentially useable by the lab). These collections were randomly subsampled to reduce the
sampling down to 72 samples.
DNA was extracted using QIAGEN’s DNeasy Blood and Tissue Kits (www.qiagen.com). For hair
samples we clipped roots from up to 10 hairs and then processed the samples like any tissue sample.
For the pellets we placed 1 to 6 pellets, depending on size, into a test tube and then covered them with
QIAGEN’s ATL digest buffer to wash off the mucus containing intestinal cells. We agitated these tubes
by gentle swirling several times during incubation, and then removed the pellets after 1 hour. DNA
purification followed QIAGEN’s protocol, with volumes of ethanol and buffer AL scaled in proportion to
the amount of ATL left after pellet removal (generally 500 µl).
Eight microsatellite markers originally developed for cow (Bos spp) and caribou (Rangifer
tarandus) and selected from work on mountain goats in the Stikine River area in northwestern British
Columbia (G. Mowat, BC Environment, unpubl. data) were used to identify individuals. One marker (Rt5)
was dropped after session 1 because of low marker variability. Samples from species other than
mountain goats were identified from amplified alleles not seen in goats, and were removed from further
analysis. The genotyping process followed the template of Paetkau (2003), except that samples of
intermediate quality were analyzed 4 times at all markers. To summarize, after the first attempt at
multilocus microsatellite genotyping, individual (single-locus) genotypes were classified as high or low
confidence based on a series of objective (signal strength) and subjective (appearance) traits, after
which both hair and pellet samples were stratified into 3 categories: 1) hopeless samples with high
confidence scores for <3 markers were culled; 2) high quality samples with ≤1 low-confidence score
were only reanalyzed at the low-confidence marker, if any; and 3) intermediate quality samples were reanalyzed 3 more times at all markers, and then a quality index (sensu Luikart et al. 2008) was used to
cull lower quality samples. When intermediate quality samples passed the specified quality threshold,
but had not yet produced 2 matching high-confidence scores for each markers, additional rounds of
single-locus analysis were applied until this standard was satisfied for all markers (or the sample was
culled).
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Error-checking involved re-analysis of mismatching markers in pairs of genotypes that matched
at all-but-one or all-but-two markers (‘1MM-‘ and ‘2MM-pairs’; Paetkau 2003), an approach that has
been shown capable of effectively preventing the identification of false individuals through genotyping
error (Kendall et al. 2009).
Once individual identification was complete, we selected 1 sample per individual for analysis of
gender using the amelogenin marker also used for bears (Ursus spp) (Ennis and Gallagher 1994).
Population estimate from DNA sampling
We used closed mark-recapture models to estimate population size (Otis et al. 1978). Multiple
captures of individuals were pooled into 1 capture per session. Our emphasis on collection of pellet
samples would have overcome any heterogeneity in detection as a result of sex or age differences in the
timing of shedding of hair (Côté and Festa-Bianchet 2003). Kids do not shed in their first year and would
generally be missed in hair collections, but we frequently collected small pellets that likely originated
from kids. The passive nature of sample collection and the approximately systematic sampling effort
(Fig. 2) negated either form of behaviour response and therefore we did not consider behaviour models
during model choice. We considered models that accommodated capture variation among sessions and
individuals.
Harvest data
Harvest data were obtained from BC Environment hunter sample reports from 1977 to 2008,
updated with interviews with hunters from the 2009 season (D. Reynolds, BC Environment, pers.
comm.).
RESULTS
Aerial survey
We conducted the aerial survey on 21 July 2009. Survey conditions and lighting were excellent
with clear skies and light winds. The survey was conducted between 8:05 am and 11:00 am.
Temperatures within the census zone were roughly 12–15°C at survey time. We used 2.2 hrs of
2
helicopter time during the survey, and surveyed a census zone of 90 km (Table 1). Overall survey
2
intensity averaged 1.4 min/km , with greater effort on the south side of the mountain than on the north
side, where historically goats had generally been observed.
2
We observed 60 goats in 15 groups (Fig. 2), for an average observed density of 0.67 goats/km
(Table 1). No goats were observed on the north side of the mountain complex. Group size ranged from 1
to 11 goats and averaged 4.0 ± 0.73 ( x ± SE). Typical group size was 5.9 (± 0.41). Three-quarters
(73%) of goat groups consisted of 1–5 animals, but only 3 groups accounted for almost half (43%) of the
total animals observed. We counted 12 kids (20% of total goats), a 25 kids:100 adults ratio. Based on
other research (summarized in Poole 2007b, Rice et al. 2009) and considering the survey effort and
habitat, we subjectively applied a sightability of 0.70 to derive an estimate of 86 goats for the census
2
zone (69 adults and 17 kids; density of 0.95 goats/km ).
Table 1. Mountain goats observed at Mt. Meager complex, 21 July 2009. “Adults” refers to non-kids
(yearlings and older).
Area
1
South
Total Adults Kids
60
48
12
Kid:100 ad
Time on
Census area Survey effort
2
2
ratio
survey (min)
(km )
(min/km )
25
92
53.2
1.7
Density
2
(goats/km )
1.13
North
0
0
0
0
38
36.9
1.0
0
Total
60
48
12
25
130
90.1
1.4
0.67
1
Area refers to south and north sides of the Mt. Meager complex.
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Goat groups were distributed from 1,700 to 2,450 m elevation (median = 1,950 m), with 73% of
groups observed between 1,850 and 2,100 m. We observed 60% of goat groups in barren alpine habitat
(n = 15 groups). Other habitats used included snow and glacier edge (20%), and alpine meadow,
scree/talus, and ridgeline (20%).
The only other wildlife observed during the survey was a cow and calf moose (Alces alces) on
the edge of a glacier at 2,200 m elevation.
DNA sampling
Field crews collected 490 samples; 91% were pellet samples
(Table 2). Although more crews were used during the last session,
several of these involved doubling up on existing areas, thus collection
effort was generally even among sessions. As best as could be
calculated, and accounting for multiple observations of the same
groups of goats by different crews, ground crews observed between 34
and 47 individual goats during each session (Fig. 4).
Most other observations during sampling sessions consisted of
grizzly bear (Ursus arctos) sign (tracks, digs, scat, and 3 dens), evident
in many areas of the mountain. Additional tracks were 2 observations
of cow and calf moose tracks, and single observations of tracks or scat
from wolf (Canis lupus), cougar (Felis concolor), and wolverine (Gulo
gulo).
Figure 4. Young billy. (Photo:
A. Inniger)
Seventy-seven pellet samples (16%) were not suitable for analysis (primarily crushed or broken
apart, or the inside exposed), while 170 samples produced high-confidence scores for all 7 markers that
were in use after session 1. Prior to re-analysis in the context of error-checking, the dataset contained
11 1MM-pairs, all of which were found to be caused by genotyping error (there were no 1MM-pairs in the
final dataset). The 6 2MM-pairs in the dataset were all replicated during error-checking, indicating that
they were not created by genotyping error. Despite the higher level of replication in samples of
intermediate quality (4 repeats of multilocus analysis rather than 1), only 3 of 11 errors were detected in
the higher quality samples that were only analyzed once. This is consistent with the notion that error
rates scale inversely with DNA concentration (Taberlet et al. 1996), and supports our strategy of
focusing data replication efforts on lower quality samples.
Table 2. Summary of mountain goat samples collected from the Mt. Meager complex, 2009.
No. of crews
No. pellet
samples
No. hair
samples
No. of goats
observed
22 Jul 09
12
105
23
34
17 Aug 09
13
228
11
45
2 Sep 09
16
115
8
47
448
42
Session
Collection date
1
2
3
Total
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We identified 55 individuals from 170 samples that were assigned individual identifications
(Table 3). For mark-recapture analysis, data for individual captures were pooled for each session,
resulting in 88 unique captures among sessions. The largest number of individual captures occurred in
session 1, with smaller but similar numbers captured in sessions 2 and 3. Twenty-one of the 27
individuals (78%) captured in session 3 were recaptures from sessions 1 and 2. Six individuals were
captured in all 3 sessions. Each genotype was detected an average of 3.1 times (range 1–9); 33% were
captured only once (Fig. 5). Successful DNA samples were concentrated in 2 areas of the mountain
complex (Fig. 6). Males comprised 40% of the individuals identified (Table 3). Based on the very small
size of some pellets collected in the field, we assumed 14 individuals were kids.
Table 3. Summary of individual mountain goat captures from the Mt. Meager complex, 2009.
Session
Captures
New captures (%)
Males (%)
1
35
35 (100)
13 (37)
2
26
14 (54)
10 (38)
3
27
6 (22)
8 (30)
Total
88
55
22 (40)
20
18
16
Frequency
14
12
10
8
6
4
2
0
1
2
3
4
5
6
7
8
9
No. of captures
Figure 5. Frequency of number of captures for individual mountain goats (n = 55) identified through DNA
samples, Mt. Meager complex, 2009.
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Mt. Meager mountain goat aerial and DNA inventory, 2009
Figure 6. Location of mountain goats identified from DNA samples in relation to goats observed during
the July aerial survey, and transect locations during capture sessions 1, 2, and 3, Mt. Meager complex,
2009.
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Population estimate from DNA sampling
Capture success was highest in the first session and the detection of new individuals declined in
a linear fashion (Fig. 7). We chose to use a model that accommodated variation among individuals for
population estimation because it is likely there were differences in capture probabilities among
individuals due to differences in movement among sexes and ages and perhaps with respect to the
sample coverage. The population estimate was 77 mountain goats (SE =7.4, 95% CI 68–96, CV = 9.6).
This Jackknife heterogeneity model generated a higher population estimate than the best fit time varying
model (Nhat = 65, SE =5.2, 95% CI 59–81, CV = 8.0). This result is logical because time models are
negatively biased low when heterogeneity is measurable (Otis et al. 1978). A time varying model that
accommodated sexes explicitly suggested that 40% of the estimated population were males. The mean
capture probability was 0.38 per session (range 0.34–0.45).
40
100
Captures
% New
30
25
80
60
20
40
15
10
% New captures
No. of captures
35
20
5
0
0
1
2
3
Session
Figure 7. The number of individual goats captured in each capture session and the proportion of those
individuals that had been detected in the previous session during 3 sessions of pellet and hair collection,
Mt. Meager complex, 2009.
Genotyping success
Genotyping success was lower for hair samples (32%, n = 38) than for pellet samples (56%, n =
282). Nine individuals were identified 12 times from hair samples. Four of these individuals (3 males, 1
female) were only detected in hair samples and only once each. For extracted pellet samples, field
classifications of fresh, recent and ‘other’ (which included pellets termed moderate age, older, or dry)
were associated with success rates of 91%, 67% and 27%, respectively. Proportions of these categories
differed among sessions, with 84% of extracted samples from sessions 1 and 3 being classified ‘fresh’
or ‘recent’ in the field, as compared to 17% of extracted samples from session 2. This in turn was
reflected in session-specific genotyping success rates of 68%, 31% and 63%, respectively. Heavy
precipitation occurred in the week prior to session 2 collections (Table 4).
The heterozygosity of the 7 markers used to identify individuals averaged 0.66 (excluding Rt5),
which is at the lower end of the range preferred for 7-locus individual identification (Table 5; Paetkau
2003).
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Table 4. Precipitation and mean temperatures in the 7 and 14 days prior to mountain goat sample
collections from the Mt. Meager complex, 2009. Weather data were obtained from the Whistler Mountain
high elevation station (1,640 m).
Total precipitation (mm)
Session
Mean temperature (ºC)
Date
7 days prior
14 days prior
7 days prior
14 days prior
1
22 Jul 09
0.0
4.8
12.9
12.0
2
17 Aug 09
58.6
59.6
7.5
10.2
3
2 Sep 09
3.2
6.6
13.9
12.7
Table 5. Measures of variability for 8 loci used to genotype 55 mountain goats (33 for Rt5), Mt. Meager
complex, 2009. HE = expected heterozygosity; HO = observed heterozygosity; A = number of alleles.
Locus
HE
HO
A
Reference
BM1225
0.62
0.67
5
Bishop et al. 1994
BM203
0.76
0.75
6
Bishop et al. 1994
BM4107
0.64
0.60
5
Bishop et al. 1994
BM4513
0.75
0.76
6
Bishop et al. 1994
BMC1009
0.61
0.69
4
Bishop et al. 1994
Rt1
0.57
0.60
6
Wilson et al. 1997
Rt27
0.61
0.64
6
Wilson et al. 1997
Rt5
0.46
0.45
3
Wilson et al. 1997
Mean
0.63
0.65
5.1
Twenty pellet samples were collected on snowfields, of which 8 were not suitable for analysis.
All but 1 of the 12 remaining samples run for genetic analysis failed. All but 1 of the 17 samples (15
pellets and 2 hair) collected on the north side of the mountain that were run for genetic analysis also
failed. The lone mountain goat identified on the north side (a male) was not detected elsewhere during
the study.
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Mt. Meager mountain goat aerial and DNA inventory, 2009
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Harvest data
Between 1977 and 2009, 34 mountain goats ( x = 1.03/year) were harvested from Management
Unit 2-11 (Fig. 8). Harvest was highest from the late 1970s to the end of the 1980s. Prior to 1984, the 21
animals harvested were taken from throughout the management unit. Beginning in 1984, all harvested
animals (n = 13) were taken from the current limited entry hunting (LEH) subzone 2-11A encompassing
the Mt. Meager complex. Since 1990, an average of 0.25 goats per year were harvested (1 every 4
years), and no goats have been harvested in the past 7 years. From the late 1990s to 2006 a total of 6
LEH authorizations were issued each year for 2-11A; beginning in 2007 only 3 authorizations were
issued annually. Discussion with hunters in 2008 and 2009 indicated no hunting effort was expended in
either year (D. Reynolds, BC Environment, pers. comm.). Hunter effort in 2009 may have been affected
by a road closure on the Mt. Meager Forest Service Road at Capricorn Creek caused by a massive
mudslide in mid-September.
Females comprised 56% of the harvest since 1977. Considering only the harvest from Mt.
Meager complex beginning in 1984, 62% of the harvest was female.
4
No. of goats harvested
Male
Female
3
2
1
19
77
19
79
19
81
19
83
19
85
19
87
19
89
19
91
19
93
19
95
19
97
19
99
20
01
20
03
20
05
20
07
20
09
0
Figure 8. Mountain goat harvest data from 1977 to 2009 for Management Unit 2-11.
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Mt. Meager mountain goat aerial and DNA inventory, 2009
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DISCUSSION
Aerial survey
We observed 60 mountain goats (48 adults, 12 kids) during the survey. Past counts of the Mt.
Meager complex have used different techniques (ground-based counts, aerial surveys), timing (winter
and summer), and unknown but likely variable survey effort. Ground-based counts during the 1980s and
early 1990s suggested upwards of 70–80 goats inhabited the mountain. Four helicopter-based aerial
surveys between 1997 and 2005 appeared to be partial coverage or rapid surveys, 2 of them during
winter, that resulted in counts of 12–47 animals (S. Rochetta, BC Environment, unpubl. data). The most
recent and possibly only complete previous aerial survey was conducted in 2007 and counted 54
individuals (39 adults, 15 kids), using likely similar survey effort and coverage (D. Reynolds, BC
Environment, unpubl. data). The distribution of goats observed during this 2007 survey (D. Reynolds,
BC Environment, unpubl. data) was generally more concentrated on the south side of the mountain
complex than the distribution observed in 2009. Given the paucity of comparable surveys, it is difficult to
accurately determine long-term trends in the population. At best, survey data suggest a possible
increase in recent years, but possibly lower numbers than found during the 1980s and early 1990s.
Although the temperature was slightly above seasonal norms during the survey, visibility was
good and we had no indication that the goats were not visible in cliffs or forests to escape the heat.
2
Survey effort used on the south side of the mountain complex (1.7 min/km ) was comparable to recent
goat surveys in the Kootenay Region (Poole and Klafki 2005) and in the North Thompson (Poole
2
2006)(range 1.8–2.1 min/km ). Based on several empirical studies (Poole 2007b), a sightability of 0.60–
0.65 has been applied in most surveys recently conducted in the East Kootenay. Rice et al. (2009)
modeled 0.85 sightability for an interior population in Washington, but lower sightability is assumed for
most coastal populations (0.46: Smith and Bovee 1984; Alaska 0.45–0.65: K. White, Alaska Department
of Fish and Game, pers. comm.). Although the terrain on the Mt. Meager complex was convoluted and
broken, we subjectively applied 0.70 sightability because of little apparent association of goats with
forested habitats and moderate survey effort. Although standardized surveys have greater utility in being
used as indicators of broad population trend over time, rather than absolute estimates of population size
(Gonzalez-Voyer et al. 2001, Poole 2007b), management agencies still require estimates of population
size based on infrequent surveys.
If the broad population trend in goat numbers on the Mt. Meager complex is accurate (higher in
the 1980s and early 1990s, lower from the mid-1990s to the early 2000s, and increasing since the early
2000s), we can only speculate on potential causes driving changes in numbers. The high numbers and
proportion of females in the harvest may have negatively influenced the population. Harvested females
are often the dominant animals of the most productive age group, which has a significant impact on
recruitment (Festa-Bianchet et al. 1994, Côté and Festa-Bianchet 2001). Older females, those of the
highest social rank, and females of the highest body mass account for most of the kid production and
recruitment of yearlings to the population (Côté and Festa-Bianchet 2001, Festa-Bianchet and Côté
2008). Three of the 7 females harvested on the Mt. Meager complex since 1984 where age was known
were ≥6 years old. The low harvest in the Mt. Meager area over the past 10 years (only 2 goats) may
have contributed to the possible increase in numbers during that time.
Predation may also have influenced the population. General increases in predator numbers, or a
few individual predators specializing on goats, could reduce numbers and kid survival. Wolf numbers
appear to have increased in the area since the mid-1990s (D. Reynolds, BC Environment, unpubl. data),
and wolves have been observed feeding on mountain goats on Mt. Meager complex winter range (S.
Rochetta, BC Environment, pers. comm.). In the nearby Cayoosh area, wolves were suspected in 2 of 3
natural mortalities not attributed to humans during a study in the late 1990s (Lemke 1999).
The overall kid:adult ratio (25:100, or 20% of the population) was on the low side of ratios
documented in the adjacent Fraser region (Poole 2007a), and slightly lower than the average kid ratio
from previous summer/fall surveys of the Mt. Meager complex since 1968 (32:100; 24%). A kid:adult
ratio of 40:100 (29%) was observed during a survey of the Cayoosh area southwest of Lillooet in July
2008 (Poole 2008). Kid production appears to be negatively associated with winter severity during
pregnancy (Smith 1977, Adams and Bailey 1982, Swenson 1985) and April–May snowfall and snow
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Mt. Meager mountain goat aerial and DNA inventory, 2009
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depth (Thompson 1980, Hopkins et al. 1992). June kid ratios at Caw Ridge, Alberta, averaged 23:100
over 15 years (range 15–30:100), during a period when the population increased by approximately 50%
(Festa-Bianchet and Côté 2008). Since much kid mortality can occur over winter and goats generally do
not reproduce until 3–4 years of age, moderate to high kid ratios can provide an expectation of some
recruitment, but are limited in their utility to predict population change (Côté and Festa-Bianchet 2003).
Alternatively, low kid ratios may still result in increased populations if yearling and older mortality is low;
if adult mortality is high, then higher recruitment is required to maintain a population.
Population estimate from DNA sampling
Identification of individual mountain goats from non-invasive pellet sampling provided a rigorous
and relatively precise estimate of the abundance of mountain goats on the Mt. Meager complex. This
study is one of the first estimates of abundance of an ungulate species using DNA derived from faecal
pellets (Eggert et al. 2003, Brinkman et al. submitted), and suggests the technique can be applied to
other situations where direct observation of individuals is difficult or estimates are imprecise.
We are encouraged by the similarity of the DNA-derived estimate with the estimate obtained
from the aerial survey observations corrected with application of a sightability correction factor. Although
the sightability correction was loosely based on empirical data (Poole 2007b), the accuracy of aerial
surveys for mountain goats are known to vary among surveys, likely related to changes in sightability
(Gonzalez-Voyer et al. 2001). Differences in habitat, topography, and animal behaviour may also
influence sightability among areas. Using the point DNA-derived estimate and the number of goats
observed during the survey, the calculated sightability for the survey was 0.78, not the 0.70 assumed.
Rice et al. (2009) estimated a mean sightability of 0.85 for individual animals in recent studies in the
Cascade and Olympic ranges of Washington (range 0.75–0.91 in areas with low to high sightability,
respectively). Use of 0.85 sightability would have underestimated the number of mountain goats in the
population compared to the DNA-derived estimate.
Our DNA-derived estimate was relatively precise (CV = 9.6), a result of the 3-session design
and comparatively high capture probabilities. Precision of estimates will vary with number of sessions
and capture probability (Mulders et al. 2007), and will likely be unique for most situations. Until capture
probabilities are known for the species of interest in the area of interest, it will be difficult to model
optimum sampling effort.
Properly designed mark-recapture studies require that all individuals in a population have a non-zero
probability of capture. If the pellets of some individuals had no probability of being collected then
population estimates would be negatively biased. Sampling effectiveness also requires that encounter
rates with viable samples be maximized. Limitations on safe human travel resulted in a comparatively
small portion of the mountain complex and potential mountain goat habitat being sampled each session.
However, given the time between sessions it seemed highly probable that most animals potentially could
have travelled to ridgelines or slopes where sampling occurred. Examination of movements of GPScollared mountain goats over a 14-day period in August from a southeastern British Columbia dataset
(Poole et al. 2009) suggested most animals travelled over at minimum a 2 km wide area, and some up
to 7 km, during that period. Mt. Meager complex mountain goats detected more than once during the
study were captured an average of 1,020 m (SE = 147; range 13–3,500 m) apart at the most distant
locations. Given the high capture success (0.38), we suggest most individuals in the population travelled
to areas where sampling could be safely conducted at least some time during the capture sessions.
During the aerial survey 3 groups accounted for 43% of the animals observed (7–11
individuals/group). The gregarious nature of mountain goats and tendency for nanny groups to be larger
than bachelor groups during summer (Festa-Bianchet and Côté 2008), suggests that grouping may
influence population estimates because of the clumped distribution. However, in the central portion of
the sampling area (the general area where 38 goats in 9 groups were observed during the aerial
survey), 43 goats were captured at least once among the 3 sessions, but only 6 animals were captured
in each session. Changes in mean group size occur over the summer (Festa-Bianchet and Côté 2008),
which would tend to alter group make-up and dynamics. Thus, group movements, dynamics and mixing
of individuals over the course of a summer may be large enough such that individuals may be a realistic
sample unit.
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Mt. Meager mountain goat aerial and DNA inventory, 2009
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Billies tend to be more sedentary and make larger use of forested habitats than nanny groups
during summer (Festa-Bianchet and Côté 2008). Our sampling would not have detected bachelor
groups if they had been localized in areas not covered by sampling crews. However, 40% of the
genotyped individuals in our study were males, similar to the average 38% adult males compared to all
adults in the Caw Ridge, Alberta, population between 1999 and 2003 (Festa-Bianchet and Côté 2008).
Thus it appears unlikely that we missed a significant segment of the male populations because of
behavioural isolation.
Although field crews were placed in generally similar areas for each session (because of
limitations to areas where humans can safely travel), no instructions were given on what route to follow
or how to survey each area. With the exception of 1 field crew, no personnel surveyed the same area
among sessions. Track files from GPS data suggested little overlap on areas travelled or samples
collected. Assuming time to degradation of pellet DNA is affected by precipitation and sun exposure,
there was likely little chance of successful double sampling of the same pellet group. Brinkman et al.
(2009) suggested samples >14–21 days old will fail to provide DNA in wet environments. Although we
had planned for 21 days between sessions, weather delays resulted in 16 days between sessions 2 and
3.
Geographic closure, potentially the most important assumption of mark-recapture models, is
violated if there is movement of individuals on and off the study area among capture sessions (White et
al. 1982). Although we did not account for population closure in our estimate for the area, the Mt.
Meager complex is a fairly discrete block of habitat surrounded on 3 sides by deep, forested valleys.
High-elevation connections exist only to the southwest. Biologists knowledgeable with the area have not
detected mountain goats in the area immediately adjacent to the Mt. Meager complex (D. Reynolds and
S. Rochetta, BC Environment, unpubl. data). Mountain goats residing on the mountain during the
summer may tend to remain there year round, but the degree of seasonal interchange or dispersal
between adjacent areas is not known. Dispersal is most common with 2–3 year old males during late
summer (Festa-Bianchet and Côté 2008).
As expected (Gagneux et al. 1997, D. Paetkau, Wildlife Genetics International, pers. comm.),
genotyping success from pellets (56%) was higher than from hair samples (32%), confirming that
mountain goat samples should concentrate on pellet collection during summer. However, 4 of the 55
individuals identified (3 males, 1 female) were only detected in hair samples, suggesting that hair
collection can be valuable as a supplement to the pellet collections.
Advances in DNA extraction laboratory protocols for pellets likely contributed to the higher
genotyping success. In addition, the differences in genotyping success among pellets classified as
‘fresh’ (91%), ‘recent’ (67%), and ‘older’ (27%) clearly demonstrates that DNA quality can be assessed
during collections in the field to optimize laboratory costs and effectiveness. Brinkman et al. (2010)
found similar results for decreased genotyping success over time and recommended field classification
of Sitka black-tailed deer (Odocoileus hemionus sitkensis) pellets in coastal Alaska. We were unable to
quantify pellet age with age category, and DNA degradation will vary with exposure and environmental
conditions, but it is likely that most successful samples were <2 weeks of age (Brinkman et al. 2009).
Genotyping success during session 2 (31%) was far lower than success encountered in
sessions 1 and 3 (63–68%). Although difficult to qualify and requiring testing to clarify (e.g., Brinkman et
al. 2009), it is likely that the heavy rain events in the week prior to collection largely contributed to the
lower success. The lower genotyping success may have been a result of rain washing off some of the
mucus which contain the epithelial cell DNA from the outside of pellets, or increased DNA degradation
rates (Brinkman et al. 2009).
A majority of the pellets collected on snowfields failed during genotyping procedures. These
results were surprising, as we had believed that cooler conditions would slow DNA degradation and
increase genotyping success rates (Belant et al. 2007). Maudet et al. (2004) found much lower
genotyping error rates in wild ungulate faeces sampled in winter compared to spring, but attributed the
difference to diet resulting in lower DNA content during spring compared with winter. Although we had
greater difficulty accurately aging pellets on snowfields, our low success may be related to the relatively
high moisture encountered on snowfield during summer temperatures with melting conditions that
degraded the DNA or rinsed the mucus coating from pellets (Brinkmen et al. 2009).
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Mt. Meager mountain goat aerial and DNA inventory, 2009
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Management recommendations
The aerial survey suggested upward of 69 adults may inhabit the Mt. Meager complex. Based
on recently developed Ministry of Environment recommendations on sustainable mountain goat hunting,
populations of <50 adult mountain goats should not be hunted (Mountain Goat Management Team
2010). Small populations should be carefully managed, as they are at higher risk of decrease simply by
being relatively few in number. Thus, survey data suggest that a limited harvest could continue in the Mt.
Meager complex, as long as management personnel pay particular attention to numbers and sex of
harvested animals. Spikes in harvest or continued high proportion of females in the harvest may require
additional restrictions to hunting opportunities to ensure long-term viability of this accessible population.
Pellet and hair collections provided samples of sufficient quality to identify individual goats using
DNA and produce a statistically robust population estimate for the area. This study provided an
opportunity to test the field techniques and methodologies, but in this situation the costs involved in
moving field crews around the mountain may not have been the most effective use of the technique. We
used approximately 5 hours of helicopter time to conduct the aerial survey (positioning and ferry time
included), and approximately 14 hours to transport field crews on and off the mountain during the 3
sample collection sessions (again, positioning time for each day included). Coupled with $20,000 in DNA
analysis costs, the DNA-based estimate cost nearly 6 times more in base costs than the aerial survey
derived estimate. However, DNA sampling provided a rigorous estimate with a quantifiable level of
confidence around the estimate, as opposed to the end result of the aerial survey, which was a minimum
count with a relatively subjective sightability correction applied. Thus, although the costs differ markedly,
the outcome of each method also differs, and as such direct cost comparisons may not be valid.
DNA sampling of ungulates can be applied to a number of situations, for example where
ungulates occupy a moderately discrete area with low sightability (such as in heavily forested areas) and
reasonable access. Identification of individuals can provide minimum population counts, or with proper
design and multiple capture sessions, be used to develop a population estimate. Examples of more
applicable situations may include mountain goats living in forested river/canyon habitats, small
populations of goats in low-elevation winter range within the forest matrix, or a population of woodland
caribou (Rangifer tarandus caribou) existing at low densities in an area where sampling can be done
rapidly and effectively. Sampling in winter prior to spring melt conditions may extend the viable life of
usable samples; sampling on snow fields during summer and early fall is not recommended because of
low genotyping success. Pellet samples should be classified according to age in the field to facilitate
cost-effective extractions in the laboratory. Once sampled, pellet groups could be crushed/scuffed out to
minimize the likelihood of resample during subsequent sampling sessions.
We suggest that during summer researchers should concentrate on pellet collections because
of the higher genotyping success from pellets as compared to hair, which may be primarily shed. Based
on studies of genotyping success over time since deposition, 14–21 days between sampling sessions
appears to be a reasonable period to maximize pellet deposition and capture probabilities and maximize
genotyping success, while minimizing the risk of repeat sampling of the same pellet groups (because of
likely low genotyping success on samples >14–21 days of age; Brinkman et al. 2009). Brinkman et al.
(submitted) suggested an optimum 10-day sampling interval for sampling of Sitka black-tailed deer
pellets in a wet, coastal environment. Given the apparent reduction in genotyping success following
heavy rain events, it may be prudent to delay collections to allow sufficient deposition of pellets with
quality DNA.
ACKNOWLEDGEMENTS
Peter Kiewit Sons Co. provided funding for this project by donation to British Columbia
Conservation Foundation, who administered the project under the guidance of J. Neilson. Blackcomb
Helicopters provided safe flying to and from the mountain. Approximately 55 volunteers (Appendix 1),
primarily associated with the Pemberton Wildlife Association and BC Environment, participated in the
field study, and we thank them for their enthusiasm and assistance. We especially thank A. Mitchell for
logistics and keeping us all safe, and A. McEwan for pulling together so many keen volunteers. J. Chan,
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Mt. Meager mountain goat aerial and DNA inventory, 2009
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Integrated Land Management Bureau, provided background GIS base data. We are especially grateful
to D. Paetkau and J. Benson, Wildlife Genetics International, for their interest and diligence with this
project. D. Paetkau also reviewed a draft of the document and contributed clarification on genotype
error-checking methodology and results. G. Mowat, BC Environment, kindly provided inspiration, advice
and conducted the mark-recapture analysis. G. Kuzyk provided helpful comments on an earlier draft of
the report.
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APPENDIX 1. Personnel participating in the Mt. Meager mountain goat study, 2009.
Abe Inniger
Dawn Johnson
John Tisdale
Peter Nash
Aimee Mitchell
Eric Craige
John Tschopp
Rachel Shapard
Alan Leblanc
Gerry Kuzyk
Julie-Ann Chapman
Raymond Krumme
Alan McEwan
Greg Ferguson
Katy Chambers
Roger Inniger
Alexandre Desjardins
Greg George
Kendra Wood
Ross Neuman
Bill Williams
Hank Lipsett
Kevin Haberl
Saad Hasan
Cam McEwan
Ian Jackson
Kim Poole
Shane Mathieson
Chris Currie
Jason Bryan
Lori Homstol
Sonia Southam
Chris Williams
Jason McEwan
Marcia Danielson
Steve Rochetta
Clarke Gatehouse
Jeanette Helmer
Mary Mitchell
Tanya Bryan
Cliff Nietvelt
Jen Avey
Marty Holloway
Tom Dudley
Darryl Reynolds
Jerry Desmond
Nicola Brabyn
Trevor Ross
Dave Southam
JJ Lemieux
Norm Williams
Vicki Haberl
David Harkley
John Corrigan
Peter Deese
Zdenek Los
Aurora Wildlife Research