Assessing the activity of predators in relation to capercaillie hen ...

Scottish Natural Heritage
Commissioned Report No. 415
Assessing the activity of predators in
relation to capercaillie hen densities
and breeding performance

COMMISSIONED REPORT
Commissioned Report No. 415
Assessing the activity of predators in relation to
capercaillie hen densities and breeding
performance
For further information on this report please contact:
Rob Raynor
Scottish Natural Heritage
Great Glen House
INVERNESS
IV3 8NW
Telephone: 01463-725 200
E-mail: Robert.Raynor@snh.gov.uk
This report should be quoted as:
Baines, D., Aebischer, N., MacLeod, A. & Woods, J. (2011). Report title. Scottish Natural
Heritage Commissioned Report No.415.
This report, or any part of it, should not be reproduced without the permission of Scottish Natural Heritage. This
permission will not be withheld unreasonably. The views expressed by the author(s) of this report should not be taken
as the views and policies of Scottish Natural Heritage. This report is from a partnership project with partners: the
Game and Wildlife Conservation Trust, the Royal Society for the Protection of Birds and Scottish Natural Heritage.
© Scottish Natural Heritage 2011.
i

COMMISSIONED REPORT
Summary
Assessing the activity of predators in relation to
capercaillie hen densities and breeding performance
Commissioned Report No. 415 (iBids n o 7820)
Contractor: The Game & Wildlife Conservation Trust
Year of publication: 2011
BACKGROUND
Pine martens Martes martes are considered to have increased in abundance in Scottish forests
in recent decades and have been demonstrated to be the main cause of nest loss in capercaillie
Tetrao urogallus in Abernethy Forest. To consider whether martens, and other potential
predators of capercaillie, have increased, 11 of 14 forests surveyed for predators in 1995 were
resurveyed in 2009, together with an additional five forests where capercaillie brood counts
have been conducted in recent years. Survey techniques followed those used in 1995.
MAIN FINDINGS
A total of 414 scats representing 30% of those collected and identified in the field as being from
either fox or marten were sent to Forest Research for identification confirmation through DNA
analysis. In all, 77% of scats had been identified correctly by the two observers, with no
difference between individual observers. However of those incorrectly identified, there was a
bias towards identifying marten scats as fox. DNA confirmation was used to calculate correction
indices of x 0.49 for scats identified in the field as fox and x 1.30 for those identified as martens.
No similar indices were available for 1995.
Since 1995, marten distribution had expanded and the mean abundance index had increased
3.7-fold, whereas that of fox Vulpes vulpes had increased 2.7-fold. Given the bias in scat
misidentification in favour of martens, these results could be considered speculative. It is
however assumed that the level of misidentification would be similar between the two periods.
This assumption could not be tested, but the significance of the increase in both fox and marten
remained irrespective of whether correction indices were applied to neither or both years.
Accordingly, correction indices have not been applied when considering relationships of fox and
marten with capercaillie. Indices of Carrion crow Corvus corone and raptors showed no change.
In 2009, forests with more foxes also had more crows, and those with more crows had more
raptors. Those forests with more crows and raptors had fewer martens. There was no
relationship between fox and marten indices. Capercaillie breeding success was considered in
two periods; 1991-95, which was related to the predator survey of 1995, and 2005-09, which
was related to predator abundance in 2009. In 1991-95, broods per hen and brood size were
significantly less in forests with higher crow and higher fox indices respectively. In 2005-09,
chicks per hen and brood size were lower in forests with higher crow indices. Indices of hen
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densities in 1991-95 were positively correlated with fox indices. Density indices in 2005-09 were
57% lower than in 1991-95 and fewer hens were found in forests with more foxes, crows and
raptors. Conversely, more hens were found in forests with higher marten indices. Reductions in
hen density between the two periods occurred in forests where either indices of fox or raptors
had increased. This survey found no evidence to suggest that martens are impacting upon
capercaillie breeding success.
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ACKNOWLEDGEMENTS
We would like to thank the numerous land managers and their staff for access to their forests.
Capercaillie brood counts were also conducted by Mark Andrew, Paul Baker, Lois Canham,
Mick Canham, Norman Cobley, Kathy Fletcher, Isla Graham, Rupert Hawley, Andrew Hoodless,
David Howarth, David Lambie, Fiona Leckie, Robert Moss, Raymond Parr, Adam Smith, Philip
Warren and staff at RSPB Abernethy & Craigmore. Stewart A’Hara of Forest Research
undertook DNA analysis of the scats. We thank Megan Davies, Susan Haysom, Rob Raynor,
Ron Summers and Jerry Wilson for helpful comments on the draft report. The study was funded
by Scottish Natural Heritage, RSPB and the Game & Wildlife Conservation Trust.
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Table of Contents
Page
BACKGROUND............................................................................................................................1
METHODS ....................................................................................................................................2
RESULTS .....................................................................................................................................6
DISCUSSION................................................................................................................................8
REFERENCES ...........................................................................................................................11
TABLES......................................................................................................................................14
FIGURES ....................................................................................................................................26
Table 1. Location and characteristics of the forests
Table 2. Scat DNA testing confirmation
Table 3. Breakdown of scats misidentified in the field
Table 4. Indices of predator abundance
Table 5. Predator indices
Table 6. Relationships between predator indices
Table 7. Effects of forest and year on capercaillie breeding success
Table 8. Mean breeding success of capercaillie
Table 9. Capercaillie breeding success in relation to predator indices
Table 10. Changes in capercaillie breeding success in relation to predator indices
Table 11. Mean indices of hen capercaillie density
Table 12. Hen capercaillie density indices in relation to predator indices
Figure 1. Location of the 19 study forests
Figure 2. Capercaillie breeding success in relation to predator indices
Figure 3. Capercaillie hen density indices in relation to predator indices
Figure 4. Changes in capercaillie hen density indices and changes in predator indices
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BACKGROUND
Capercaillie Tetrao urogallus numbers have declined in Scotland since the mid 1970s, (Moss,
1994; Catt et al., 1998), but the last survey in 2003-04 suggested that, although capercaillie
remain seriously threatened, population size may now have stabilised at about 2000 birds
(Eaton et al., 2007). The rapid decline had been linked with poor breeding success (Moss et al.,
2000) associated with both changes in weather patterns (Moss et al., 2001) and with increases
in generalist predators that may predate eggs and chicks (Baines et al., 2004; Summers et al.,
2004). Simultaneous to this, mortality of full-grown birds through flying into deer fences, has
become a significant source of mortality (Catt et al., 1998; Baines & Summers, 1997; Baines &
Andrew, 2003). That the population appears to have now stabilised is probably attributable to
considerable funding being dedicated to removing or marking deer fences and thus reducing
deaths following collisions.
Substantial collaborative habitat management, predator control and disturbance management
work through the LIFE Nature Project "Urgent Conservation Management for Scottish
Capercaillie", the capercaillie Species Action Framework and other initiatives has sought to
deliver progress towards the UKBAP targets of increasing the population of capercaillie in
Scotland to 5000 birds and increasing their range from 40 to 45 occupied 10 km squares by
2010. Meeting this target has not been possible, but the possibility of meeting any future
optimistic targets will also rely on improving breeding success. The principal cause of poor
breeding success relates to weather, either temperature change in April (Moss et al., 2001) or
rainfall in June (Moss, 1986). However even when weather patterns appear suitable for
successful breeding, productivity is often only modest and varies markedly between forests in
relation to habitat quality and indices of fox and crow abundance (Baines et al., 2004).
In Scandinavia, pine martens Martes martes reduce capercaillie breeding success through
predating both clutches and chicks (Marcstrom et al., 1988; Kastdalen & Wegge, 1989; Kurki et
al., 1997). Both pine martens and capercaillie numbers increased in parallel when an outbreak
of sarcoptic mange reduced fox abundance, thus indicating that foxes may be more important
as predators of capercaillie and other small game than martens (Smedshaug et al., 1999). In
Scotland, pine martens were historically persecuted by man to protect gamebirds, but legal
protection within the last 25 years has allowed martens and other predators to recover much of
their former range and abundance (Tapper, 1999). Although increasing in numbers and range,
the pine marten, also a UK BAP priority species, is still rare in Scotland as a whole, with only an
estimated 3,500 adults, representing at least 95% of the British population (Birks, 2002).
Capercaillie were already in steep decline before martens became numerous once again and
breeding success was not correlated with an index of marten abundance 1 in 1995 in a study of
14 forests (Baines et al., 2004). There is however subsequent evidence from one of those
forests (Abernethy) that martens have become more numerous since the 1995 survey
(Summers et al., 2004). Here, where crows and foxes are controlled, a recent study of
capercaillie nest outcomes showed that of 20 nests, pine martens predated 33-57%, depending
on the interpretation of the data (Summers et al., 2009). The Abernethy study indicates that
martens can be significant predators of capercaillie clutches, but it is not known to what extent
this effect occurs elsewhere within the bird’s range in Scotland. It is likely that similar increases
in marten abundance have occurred in other forests since the mid 1990s and it has been
suggested that this may have resulted in increased levels of predation on capercaillie. In an
attempt to determine whether marten numbers have increased and whether they may now
1
There is debate over whether the term “index of activity” is more accurate in this context – see Discussion and Birks et al., (2004).
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significantly impact upon capercaillie breeding success, it was decided to repeat the 1995
survey of predator indices including martens. This report compares predator indices from the
two surveys 1995 and 2009 and considers relationships between predator indices and
measures of capercaillie breeding success and indices of hen density.
OBJECTIVES
The objectives of this work are:
1. to consider whether indices of predator abundance have changed since the 1995
survey;
2. to investigate whether differences in measures of capercaillie and their breeding success
amongst forests are related to indices of predator activity; and
3. to compare these with measures from the 1990s.
METHODS
Forest selection
Eleven of the 14 forests originally surveyed for predator indices, including pine marten, in 1995
(Baines et al., 2004) were re-surveyed in 2009. These forests not only had original predator
survey data from 1995, but also had data on capercaillie breeding success from the 1990s and
more recently. These combinations of data allowed changes in indices of pine martens and
other predators to be related to any changes in measures of abundance and breeding success
of capercaillie.
Of the original 14 forests from 1995, three forests (E, C and R) were omitted because brood
counts were largely discontinued in the early 1990s and the latter forest has since been clearfelled.
The 11 forests retained however included three forests (J, K and U) where capercaillie
were considered to be locally extinct. These 11 forests were supplemented with five additional
forests (B, N, W, X and Y), where brood counts have been conducted in more recent years,
bringing the total number of forests surveyed for predator indices in 2009 to 16 (Table 1) (Figure
1). These 16 forests showed a range of forest types and exhibited a geographical range that
encompassed several Special Protection Areas which include capercaillie as a qualifying
interest as well as both core and peripheral parts of the perceived pine marten distribution.
Scat collection, handling and storage
Within each forest, approximately 10 km of unsurfaced vehicle tracks were searched for
mammal scats. All original routes had been retained in paper map form from the previous
survey in 1995, and wherever possible the same routes were used again. The tracks were
walked five times, initially during a clear-up round in the second half of April to count and
remove all scats, then twice in May (middle and end of the month) and twice in June (middle
and end of the month). The observer simultaneously scanned both sides of vehicular tracks for
scats at a slow walking pace. The location of all scats was recorded as a 10 figure grid
reference using a GPS.
All scats were initially classified as “fox”, “marten” or “other” in the field when characteristic
elements of their morphology had not been altered by handling. Prior to handling, a digital
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photograph was taken of the scat in situ with a ruler placed adjacent for scale. All scats were
collected. Two different observers (AM & JW) collected scats in the field, but to try to reduce the
observer error a secondary check of identification was performed on the collected scats by the
more experienced observer (AM), whose correct classification during a previous survey had
been verified by DNA analysis to be high at 88% (R. Trout, pers. comm.).
A total of 414 scats, representing 30% of those collected, was sent to Forest Research for DNA
analysis in order to verify their originator. A positive identification was obtained for 311 of the
414 scats. These included 217 scats that could not be confidently allocated to species using
field characteristics, 88 scats where the fieldworkers had a high certainty of correct identification
as either pine marten or fox and six scats that were neither marten nor fox. Those scats sent for
DNA analysis were a randomly selected sub-set from within each of the four observer-certainty
categories. To reduce the risk of contaminating the DNA through handling, scats were collected
in individual plastic bags, with the bag inverted to pick up the scat, then reverted, sealed and
labelled with the date, site and a unique scat specific code number that cross referenced with
the data recording sheet containing other parameters including: location from GPS, collector’s
name, time, corresponding digital photograph reference number, initial classification (‘marten’,
‘fox’, ‘other/unsure’), collection round (eg. ‘1 st round, May’). The bagged scat was then double
bagged for storage in a freezer.
DNA was extracted from each scat, then a short section (380 bases) of the mitochondrial
genome was amplified by polymerase chain reaction (PCR) and subsequently sequenced. The
sequences obtained were compared to those in the Genbank database to make positive
identification. The 103 remaining scats which did not provide a positive identification either did
not yield DNA of sufficient quality or quantity to amplify in the PCR reaction (65 scats), produced
a double band in the PCR reaction indicating that DNA from two different species were present
(usually host and prey) making a clean sequence impossible (18 scats), had a very faint band
not considered suitable for sequencing (8 scats), or failed to sequence (12 scats). As a further
control on positive identification, 44 scats (33 marten and 11 fox) were re-tested using a second
molecular assay, a real time PCR method. This method confirmed the earlier test for all
samples.
Crows and raptors
Approximately 5 km of the same tracks used for scat surveys were also used as transects along
which carrion crows Corvus corone, C. cornix and raptors were counted. Bird counts were
conducted just after dawn (i.e. within 2 hours of sunrise), twice monthly in May and June and
immediately preceded the scat collection round on the same day. Sightings and calls were given
a GPS position. Ideally, these transects would have been much longer, so as to provide more
data. However, in order to enable direct comparison with a previous similar study (Baines et al.,
2004) it was decided to apply the same methodology.
Counts of capercaillie
Measures of capercaillie breeding success and indices of adult densities were obtained in July
and August from a total of 19 forests where predator indices were also collected either in 1995,
2009 or in both years. Counts were undertaken annually between 1991 and 2009, but not all
forests were counted in each year and instead the number of forests counted per year varied
from 11 to 20, or a total area searched of 31 to 78 km 2 per year. Areas were searched using
trained pointing dogs, but areas were not selected at random for practical operative reasons and
hence are not necessarily representative of each forest as a whole. Instead, areas selected for
3

survey were often perceived to be those of better breeding habitat, preferred by capercaillie.
The area searched within each forest tended to be consistent between years, but varied from
0.6 to 11.0 km 2 between forests and averaged 3.9 km 2 .
Not all hens may breed in their first spring, but as there was no way of distinguishing between
hens that did not breed and hens that bred but failed to rear chicks, all hens seen were
assumed to have bred. Three measures of reproductive success were calculated each year in
each forest: the proportion of hens with at least one chick was “broods per hen”, the number of
chicks per hen that had at least one chick was “brood size” and the overall measure of breeding
success was the number of “chicks per hen”.
The number of hens encountered in each forest in relation to the area searched in each year
was used as an index of hen density. Typically, the same areas of forest were searched in each
year that a forest was surveyed. Where this was not the case, such as at Forest A where the
count method and count site changed over time, the data were removed from analysis of hen
density. Annual estimates of breeding success at Forest A were however retained as the
number of hens encountered remained a high proportion of those estimated to be present and
hence representative of the forest as a whole and well above the threshold level of 10 hens
which formed an initial constraint in the selection of study forests (Baines et al., 2004). When,
such as at Forest G the area searched differed between years, the change in effort was taken
into account when calculating indices of density.
DATA ANALYSIS
Predator indices
Indices of predator activity were derived for each forest. The total number of scats found in each
forest for each mammal species over the four visits (during May and June), but excluding those
found on the clear-up round, were divided by the exposure period in days (i.e. the time interval
between the end of the clear-up round and the final visit). To adjust for differences in transect
route length between forests, the number of scats per day was divided by the transect length.
The indices were presented as scats 10 km -1 day -1 , which were then multiplied by 100 for ease
of presentation. Similarly, the number of crows and raptors were summed for the four visits and
expressed as the number of sightings 10km -1 visit -1 .
Subsequent analyses addressed whether indices of mammal and predatory bird activity have
changed in the same suite of forests since 1995 using generalised linear models with Poisson
error, log link, adjusted for over-dispersion, with mammal (pine marten or fox) scat or bird
(carrion crow or raptor) sightings as the dependent variable, log e (transect length*time interval)
as an offset and forest and year as factors. The described analysis was done twice, initially on
uncorrected mammal indices and then repeated with corrected indices derived from the DNA
analysis. Relationships between individual uncorrected predator indices (fox, marten, carrion
crow and raptors) were compared by Pearson correlations on log e (index + 1) transformed
predator data.
Capercaillie breeding success and predator indices
Data on capercaillie breeding success were split into two periods; 1991-1995 and 2005-09,
which related to the collection of the predator indices in 1995 and 2009 respectively. No hens
4

were found in 2005-09 for three of the forests (J, K and U) and were excluded from analyses for
that period. The selection of the range of years within these periods was a compromise between
obtaining a sufficiently robust sample of capercaillie breeding success based on enough hens
by combining years, whilst the grouped years were still sufficiently few to represent the year
when predator indices were collected, and whilst maximising the period between surveys and
hence the independence between the two periods. Generalised linear models (GLM) were used
to assess the effects of explanatory forest and year variables on breeding success. Variations in
chicks per hen were considered by setting the numbers of chicks seen in each forest in each
year as the response variable and forest and year as factors in Poisson regressions (Poisson
distribution, log link, adjusted for over-dispersion, with the natural logarithm of the number of
hens as an offset). Brood size was analysed in the same way, but by excluding hens with no
chicks and setting the logarithm of the numbers of broods as the offset. The proportion of hens
with broods (broods per hen) was modelled using logistic regression with the number of hens
with a brood (i.e. one or more chicks) as the response variable (binomial distribution with a logit
link), and the total number of hens as the binomial denominator. Differences in the three
measures of breeding success between the two study periods were considered by a similar
series of GLMs, but this time with forest and period as fixed effects. Only nine forests which
were surveyed for capercaillie in both periods were included.
Capercaillie and predator indices
Not all forests were surveyed in each year defined by the two periods, so mean predicted values
of chicks per hen, brood size and broods per hen were generated from each GLM output for
each forest for each period of years. Mean values of breeding success over the grouped period
of years were used rather than an average of annual values because very small sample sizes
made annual estimates for each forest unreliable. A single predicted mean was derived for each
of the three measures of capercaillie breeding success in each forest in each period to match
the equivalent dataset of uncorrected predator indices (i.e. one per forest per period). In this
way, capercaillie breeding success was related to the log e transformed predator indices by
linear regression for each study period. Changes in capercaillie breeding success between
periods were related to similar changes in predator indices by linear regression, dividing values
for period 2 (+ 0.1) by those for period 1 (+ 0.1), followed by log e transformation and checking
for normality of residuals.
Hen density
A similar approach was adopted when considering densities of capercaillie hens. Again a GLM
was used for each period, with the number of hens seen in each forest in each year set as the
response variable and forest and year as factors in Poisson regressions (Poisson distribution,
log link adjusted for over dispersion, and the log of the area (km 2 ) surveyed as the offset). A
further GLM with forest and period as fixed effects considered differences in hen density
between periods. Only forests surveyed in each period were included. Mean predicted values of
hen density for each period generated from the GLM, and changes in hen density between
periods, were related to predator indices in each period and changes in predator indices
between periods.
There were no habitat data, equivalent to those collected in 1995, for recent years and it is likely
that habitat will have changed considerably in both structure and composition at some sites in
the interim. Inclusion of habitat parameters was restricted to simple structural forestry
classifications as defined in Baines et al., (2004).
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RESULTS
DNA verification of scats
A total of 414 scat samples were collected, field identified and sent for DNA testing. However
103 samples could not be identified through DNA analysis leaving a sample size of 311. The
observers focused their scat identification to fox (116 samples) and pine marten (195 samples),
whereas, the DNA demonstrated that there were also scat samples for dog (3), hedgehog (2)
and cat (1), which accounted for 2% (6) of the scat samples. These 2% have not been
considered further.
Of the remaining 305 scats, 236 (77%) were correctly identified by the observers (Table 2). The
level of accuracy did not differ between observers when certainty categories were combined (χ 2 1
= 0.48, P > 0.1). Eighty eight of the samples sent for analyses were of high certainty for field
identification, with 217 of low certainty. Of those scats of high field certainty, 93% were identified
correctly, compared to only 71% of those of low field certainty. There was a between-observer
difference in relation to the proportion of correct identifications across certainty categories, with
observer JW correctly identifying all scats of high certainty, but only 61% of those of low
certainty (χ 2 3 = 23.79, P < 0.001). The more experienced observer AM showed no difference in
the proportion correctly identified between certainty categories (χ 2 1 = 1.67, P > 0.1).
A total of 69 scats were misidentified in the field, with an equal split between the two observers
(Table 3). Of the 69 scats, 64 were misclassified as fox in the field when they were actually
marten. Misclassification of marten as fox was broadly consistent between observers (χ 2 1 = 0.79,
P > 0.1). Whilst 116 of the sampled scats in the field were identified as fox, DNA confirmation
found that only 52 of those were actually from fox, plus a further five scats misidentified as
marten in the field, giving a total of 57. Conversely, 195 scats were classified as marten in the
field, but 254 by DNA analysis (195 plus the 64 misidentified as fox, minus the five identified as
marten, but actually fox). Thus the observers over identified the scat samples to be fox and
thereby under-identified pine marten scat samples. Conversion rates of x 0.49 (57 / 116) and x
1.30 (254 / 195) were calculated for fox and marten indices respectively. However these could
only have been applied uniformly across all forests and would not have altered relationships
between mammal indices and capercaillie. Essentially, therefore, they are summarised
correction factors for all forests and both observers derived from just one season of scat
verification data. There needs to be further research into how accuracy of identification varies
between forests, observers and over time. To prevent potential confusion with 1995 indices,
when no conversion rates were available, they were not applied in analyses involving
capercaillie.
Predator indices
In the 1995 survey, the number of scats found on the initial clear-up round (x) was a very good
predictor of the numbers of scats found on the subsequent four survey rounds (y) (pine marten:
y = 2.53 + 2.02x, r 2 = 0.76, P < 0.001, fox: y = -1.14 + 0.75x, r 2 = 0.91, P < 0.001). In 2009, the
relationships between scats on the clear up round and on subsequent rounds were not as
strong. These were still significant for martens (y = 8.34 + 1.39x, r 2 = 0.42, P = 0.004)), but not
for fox (r 2 = 0.17, P = 0.06).
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Predator indices in each forest are given in Table 4. Signs of martens were found in all but two
of the forests (88%) in 2009, compared to only eight out of 14 (57%) in 1995, indicating a
spread in range as well as a likely increase in abundance. However, the difference is less when
only the subset of 11 sites that were surveyed for predators in both years are compared. Thus,
in 2009, 9/11 sites (82%) had signs of pine marten, compared with 8/11 in 1995 (73%), (Table
5b). Changes in mammalian scat abundance between years were considered first by excluding
scats collected on the clear-up round. Predator indices from the 1995 survey of 14 forests and
the 2009 survey of 16 forests are compared in Table 5a. Statistical tests are based on data from
forests surveyed in both years (n = 11) (Table 5b). There was a 3.7-fold increase in marten
scats across forests (F 1,10 = 8.39, P = 0.016) and a 2.7-fold increase in fox scat abundance (F 1,10
= 14.34, P=0.004). These relationships remained the same, irrespective of whether corrected or
uncorrected mammal indices were used. If corrected values were applied to the 2009 indices,
but not to the 1995 indices, then the level of change for martens increased (F 1,10 = 11.29, P =
0.008), but that of fox decreased and became non-significant (F 1,10 = 1.18, P = 0.31), but this
makes the assumption that no correction was necessary in 1995. There were no changes in
carrion crow or raptor (chiefly buzzards Buteo buteo) sightings between surveys (F 1,10 = 0.01, P
= 0.91 and F 1,10 = 0.85, P = 0.38 respectively). The analysis for marten and fox was repeated
including scat data from clear-up rounds. The marten scat index was still higher in 2009 than in
1995 (F 1,10 = 13.14, P = 0.005), but there was no difference in the fox scat index (F 1,10 = 1.10, P
= 0.32).
In the 1995 survey we found no significant correlation between indices of the four predators
(Table 6a). However in 2009, several indices of predator abundance were inter-correlated
(Table 6b). Foxes were positively correlated with crows, whilst martens were negatively
correlated with both crows and raptors. Raptors were positively correlated with crows.
Capercaillie breeding success and predator indices
In the period 1991-95, chicks per hen and mean brood size differed significantly between
forests. Chicks per hen and broods per hen differed between years (Table 7). In contrast, in the
second period (2005-09), the forest effect was not significant in explaining variation in any
measure of capercaillie breeding success, but the year effect explained variation in both chicks
per hen and broods per hen. All three measures of breeding success differed significantly
between the two periods, with chicks per hen averaging 1.00 in 1991-95, but only 0.43 in 2005-
09. The mean (+ SE) predicted values of each measure of breeding success for each period are
given in Table 8.
In the period 1991-95, broods per hen was negatively correlated with crows (F 1,12 = 4.56, P =
0.05) and fox indices were negatively correlated with “brood size” (F 1,12 = 6.94, P = 0.02) (Table
9). In contrast, in the later period 2005-09, both chicks per hen and broods per hen were
negatively correlated with the index of crow abundance (F 1,11 = 7.73, P = 0.018 and F 1,11 =
10.58, P = 0.008 respectively) (Fig. 2). Neither the marten nor the raptor abundance index
showed any relationship with any of the three measures of capercaillie breeding success in
either period. Between period changes in capercaillie breeding success in eight forests
surveyed in both periods were not significantly related to any changes in predator indices in
those forests over the same period (Table 10).
In both periods, hen densities differed significantly between forests, but not between years
(Table 11). Hen densities more than halved from an average of 4.2 hens km -2 in 1991-95 to only
1.8 in 2005-09 (F 1,65 = 31.90, P < 0.001). Hen densities in 1991-95 were positively correlated
7

with fox indices (F 1,12 = 5.53, P = 0.04), but in 2005-09 were negatively correlated with fox
indices (F 1,13 = 8.51, P = 0.012) and also those of crows (F 1,13 = 5.08, P = 0.042) and raptors
(F 1,13 = 13.36, P = 0.003) and positively correlated with martens (F 1,13 = 9.82, P = 0.008) (Table
12) (Figs 3a-d). A single outlying point, where neither signs of martens, nor capercaillie, were
observed in one forest was excluded (Fig 3e), but the relationship remained significant (F 1,12 =
5.64, P = 0.035). Changes in hen densities in 10 forests between the two periods were
negatively related to changes in fox (F 1,8 = 9.09, P = 0.017) and raptor indices (F 1,8 = 9.47, P =
0.015) (Figs. 4a-d).
DISCUSSION
In our study, pine marten and fox indices of abundance were solely derived from scat collections
along forest tracks. Consequently, their use in deriving either estimates of abundance or
population size can be limited and open to different interpretation (Webbon et al., 2004). Scat
deposition and decay rates are likely to differ according to diet related differences in defecation
rates and seasonal and habitat differences in deposition (Davison et al., 2002) and can be
confounded by differences in persistence times due to weather (Laing et al., 2003). That said,
many of these potential biases were overcome by standardising survey timing and duration so
that scat abundance was compared only within one season and on one substrate type within
forest habitats only and, with exception of the sites at K, J and R 2 , within one geographic area;
the Scottish Highlands. By restraining these conditions as tightly as possible and using the
same sampling regime, both in terms of timing of survey and the tracks themselves, we
consider that in comparing the 1995 and 2009 surveys we generally compared changes in
abundance as opposed to changes in activity, but see Birks et al., (2004). However the precise
nature of the relationship between predator numbers and scat density is unknown, is unlikely to
be collinear and hence reported magnitudes of increase in predator indices may not equate to
the same levels of increase in abundance. One potential source of bias that could not be
overcome was that of observer error, both in detection rates and assigning the scat originator.
Given a 14 year gap between surveys, different observers had to be used, but the 2009 field
observers were trained in the methods by one of the original observers from 1995. A DNA check
on scat originator was performed in 2009, but this technique was not available for scats
collected in 1995. Using either corrected or uncorrected indices did not affect the results.
Marten and fox indices increased 3.7-fold and 2.7-fold respectively between 1995 and 2009.
That the mean marten index and the number of forests where marten sign was encountered had
both increased was predictable from a similar magnitude of increase already reported from one
of the forests (Abernethy) in this survey (Summers et al., 2004; Summers et al., 2009). This
increase is likely to reflect martens re-colonising much of the former range following their legal
protection in 1988. Perhaps less predictable was the likely doubling of the fox index relative to
1995, particularly when many of the sample forests had participated in the Capercaillie LIFE
Project and had received money to improve their levels of fox control. That both martens and
foxes increased does not readily fit with current understanding of intraguild predator
relationships where typically there is a negative relationship between the abundance of larger
predators such as the fox and those of mesopredators such as martens (Lindstrom et al., 1995;
Smedshaug et al., 1999) and stoats Mustela erminea (Warren & Baines, 2004). This is however
not always the case and Kurki et al., (1998) found no such negative relationship, whilst
Summers et al., (2004) showed a marten increase whilst fox cubs were being controlled but
2
These 3 sites in Perth & Kinross are south of the Highlands.
8

adult numbers maintained similar at Abernethy. Despite both marten and fox indices both
increasing between surveys, their indices of abundance showed no correlation.
Despite Summers et al., (2009) finding that martens were the major predator of capercaillie
clutches at Abernethy, this study found no evidence of a relationship between the marten index
and any of the three measures of capercaillie breeding success in either period of observation 3 .
Indeed, the marten index was positively correlated with hen densities in 2005-09. This lack of
agreement could result from marten abundance not yet being fully restored in many of the study
forests. To this end, marten indices in 2009 were on average almost five-fold higher in
Abernethy than amongst other study forests, with increase rates subsequent to 1995 being on
average eight–fold higher than in other forests. At what level of abundance marten start to
impact upon capercaillie breeding success, akin to that described at Abernethy, remains
undetermined. The findings of this study would suggest that other predators, in particular crows,
may be more important in determining breeding success, probably through predation of
clutches, and that foxes and raptors may be linked to changes in breeding densities, possibly
through predation of hens. However the raptor index is based on relatively few sightings and
hence any statistical association between capercaillie and raptors is speculative.
Alternatively, marten, or indeed fox abundance, deemed by scat collection may be providing
false indices of true relative abundance. Interpretation of mammalian predator indices based on
field identification of scats as collected during this study must be treated with caution. Analysis
of DNA from scats has shown there is considerable scope for misidentification when only scat
field characteristics are taken into consideration. Although in this study second appraisals of
scat identification were conducted by an experienced observer, errors appear to occur even with
recognised topic experts (Davison et al., 2002).
To overcome morphological misclassification, 414 field identified scats, representing 30% of the
total collected, were sent for confirmation by DNA analysis. These techniques confirmed that
suspected misidentification was prevalent, with 23% of scats being misidentified. Importantly,
there was a distinct tendency for marten scats to be misidentified as fox as opposed to vice
versa. Thus, without DNA verification, martens are being under-estimated relative to fox. DNA
techniques were not used in the previous 1995 survey to confirm scat identification. Accordingly,
the verified data in the 2009 survey cannot be used to derive a comparison of appropriate
correction factors between this and the previous surveys, but will be utilised in any future
surveys. Instead, it can only be assumed that misclassification rates were comparable between
the two surveys and consistent across forests and as such formed no known source of error or
bias. However if this assumption was not followed and instead all fox scats were considered as
correctly identified in 1995 and correction indices only applied in 2009, then under this
somewhat implausible scenario, any significant relationship of fox with capercaillie may be
considered invalid.
It was high fox and crow indices in the 1995 survey, rather than the marten index, that were
associated with poor capercaillie breeding success (Baines et al., 2004). Despite an increase in
the fox index in the 2009 survey, no such correlation between breeding success and fox was
found in this latter period. Conversely, although crows did not increase between surveys, they
were linked with poor breeding success in the second period of study, but not the first.
3
The analyses undertaken in this study consider statistical associations between measures of capercaillie breeding success and
predator indices only. No other environmental variables, such as weather, were included. A separate, but related analysis,
undertaken in parallel to this study found evidence of a negative relationship between the pine marten index and capercaillie
productivity (broods per hen and chicks per hen), when certain weather parameters are taken into account. See SNH
Commissioned Report 435 for details.
9

It has been well documented that the principal factor limiting annual breeding success is high
rainfall in June at and just after hatching (Moss, 1986; Moss et al., 2001; Summers et al., 2004).
Whilst this analysis does not attempt to disentangle the effects of weather and predator
abundance on levels of capercaillie breeding success within the two study periods under
consideration, it is acknowledged that within the latter period there have been two very poor
breeding years; 2007 and 2008, related to wet June weather (MacLeod et al., 2007, 2008),
which may mask any contribution made by a potential increase in mammalian predators.
Increases in fox and raptor indices were significantly correlated with declines in capercaillie
abundance measured by changes in indices of hen density. This correlation, suggesting that fox
abundance may limit capercaillie populations, is supported by evidence from Abernethy, where
increases in capercaillie occurred during an experimental period of fox control (Summers et al.,
2004). Similarly, capercaillie increased in Scandinavia when fox abundance was reduced
followed an outbreak of mange (Smedhaugh et al., 1999) and lower breeding success and
population densities were found in areas with more foxes following higher levels of forest
fragmentation (Kurki et al., 1997, 2000).
The evidence base from this study suggests that there is an increase in fox abundance in
Scottish forests. Caution is needed when drawing conclusions based on untested statistical
associations. In this case, the fox index was related to the hen density in both 1995 and 2009,
but it switched from being a positive relationship to a negative one. The change in hen density
and the fox index was also a negative relationship, so it may be suggested that as foxes
increase, hen densities decline. Furthermore, a case study at Abernethy clearly suggests, albeit
with a restricted sample size, that martens can limit hatching success of clutches and thus
negatively influence breeding success (Summers et al., 2009). This study, whilst not finding any
correlation between marten indices and breeding success, found that crows, and to a lesser
extent foxes, were linked to poor breeding success, whilst fewer hens in 2005-09 were found
where predator (fox, crow and raptor) indices were higher. Declines in capercaillie breeding
population size as measured by changes in hen density between observation periods, were
negatively associated with changes in fox and raptor indices of abundance.
Numbers and distribution of several predator species in Scotland, including both marten and
fox, have been limited, legally or illegally, by gamekeepers whose objective has been to
conserve gamebirds, particularly red grouse Lagopus lagopus scoticus, but also capercaillie, for
sport shooting (Redpath & Thirgood, 1997; Tapper, 1999; Whitfield et al., 2004). Recent
declines in red grouse and driven grouse shooting (McGilvray, 1995) are often associated with
reductions in gamekeeper numbers and predator management. This in turn has probably
improved the conservation status of the now protected pine marten, but has also resulted in
increases in foxes and possibly crows. Reaching the UKBAP Capercaillie Species Action Plan
population size and range targets may depend upon improving breeding success through
continued reductions in predator abundance, but not in isolation, or in the absence of the other
available management options.
10

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woodland grouse. Biological Conservation, 110, 169-176.
Baines, D., Moss, R. & Dugan, D. 2004. Capercaillie breeding success in relation to forest
habitat and predator abundance. Journal of Applied Ecology, 41, 59-71.
Birks, J. 2002. The Pine Marten. The Mammal Society, London. 27 pp.
Birks, J., Messenger, J., Braithwaite, T., Davison, A., Brookes, R. & Strachan, C. 2004. Are scat
surveys a reliable method for assessing distribution and population status of pine martens?
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in Human Altered Environments. Springer, London, UK.
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distribution of capercaillie Tetrao urogallus in Scotland 1992-94. Biological Conservation, 85,
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surveys: estimating decay rates. Journal of Applied Ecology, 40, 1102-1111.
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interactions: a case of intraguild predation? Annales Zoologici Fennici, 32, 123-130.
11

MacLeod, A., Moss, R. & Baines, D. 2007. The productivity of breeding capercaillie Tetrao
urogallus at sites across their Scottish range 2007. Unpublished report to Scottish Natural
Heritage Project No. FO3AC301a.
MacLeod, A., Canham, L. & Baines, D. 2008. The productivity of breeding capercaillie Tetrao
urogallus at sites across their Scottish range 2008. Unpublished report to Scottish Natural
Heritage Project No. FO3AC301a.
Marcstrom, V., Kenward, R.E. & Engren, E. 1988. The impacts of predation on boreal tetraonids
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McGilvray, J. 1995. An economic study of grouse moors. Game Conservancy Ltd,
Fordingbridge, Hampshire.
Moss, R. 1986. Rain, breeding success and distribution of capercaillie Tetrao urogallus and
black grouse Tetrao tetrix in Scotland. Ibis, 128, 65-72.
Moss, R. 1994. Decline of capercaillie (Tetrao urogallus) in Scotland. Gibier Faune Sauvage,
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Moss, R., Picozzi, N., Summers, R. & Baines, D. 2000. Capercaillie Tetrao urogallus in Scotland
– demography of a declining population. Ibis, 142, 159-167.
Moss, R., Oswald, J. & Baines, D. 2001. Climate change and breeding success: decline of the
capercaillie in Scotland. Journal of Animal Ecology, 70, 47-61.
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Proctor, R. & Summers, R.W. 2002. Nesting habitat, clutch size and nest failure of capercaillie
Tetrao urogallus in Scotland. Bird Study, 49, 190-192.
Smedshaug, .A., Selaes, V., Lund, S.E. & Sonerud, G.A. 1999. The effects of a natural
reduction of fox Vulpes vulpes on small game hunting bags in Norway. Wildlife Biology, 5, 157-
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Summers, R.W., Green, R.E., Proctor, R., Dugan, D., Lambie, D., Moncrieff, R., Moss, R. &
Baines, D. 2004. An experimental study of the effects of predation on the breeding productivity
of capercaillie and black grouse. Journal of Applied Ecology, 41, 513-525.
Summers, R.W., Willi, J. & Selvidge, J. 2009. Capercaillie Tetrao urogallus nest loss and
attendance at Abernethy Forest, Scotland. Wildlife Biology, 15, 319-327.
Tapper, S. 1999. A question of balance: Game animals and their role in the British countryside.
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Warren, P. & Baines, D. 2004. Black grouse in northern England: stemming the decline. British
Birds 97: 183-189.
12

Webbon, C.C., Baker, P.J. & Harris, S. 2004. Faecal density counts for monitoring changes in
red fox numbers in rural Britain. Journal of Applied Ecology, 41, 768-779.
Whitfield, D.P., Fielding, A.H., McLeod, D.R.A. & Haworth, P.F. 2004. The effects of persecution
on age of breeding and territory occupation in golden eagles in Scotland. Biological
Conservation, 118, 249-259.
13

TABLES
Table 1. Location and characteristics of the forests 4 surveyed for predator indices in either 1995
and / or 2009 and capercaillie breeding success. Forest type: 1, open canopy as in native
pinewoods; 2, mature Scots pine plantation, canopy sufficiently open for some dwarf shrubs; 3,
mixed species plantation with closed canopy, often with some clear-felled areas and restocked
ground.
____________________________________________________________________________
Capercaillie brood
Forest Region Forest type Predator survey count years______
A Strathspey 1 1995, 2009 1991-2009
B Perth & Kinross 3 2009 2001-2009
C Strathspey 1 1995 1991-1993, 2005-09
E Aberdeenshire 1 1995 1991-1994, 98-2001
G Strathspey 2 1995, 2009 1991-2009
H Moray 3 1995, 2009 1991-1993, 2001-09
I Perth & Kinross 2 1995, 2009 1991-2009
J Perth & Kinross 2 1995, 2009 1991-2001, 2009
K Perth & Kinross 3 1995, 2009 1991-2001, 2009
L Aberdeenshire 1 1995, 2009 1991-2009
N Strathspey 2 2009 2002-2009
Q Strathspey 3 1995, 2009 1992-2000, 2005-09
R Perth & Kinross 3 1995 1991-1993
S Strathspey 1 1995, 2009 1992-1999, 2001-09
U Aberdeenshire 1 1995, 2009 1991-2007, 2009
W Easter Ross 3 2009 2000-2009
X Easter Ross 3 2009 2000-2009
Y Aberdeenshire 2 2009 2003-2009
Z Strathspey 1 1995, 2009 1992-2009
____________________________________________________________________________
4
The forest codes follow an irregular sequence because they are the same site codes that are used in SNH Commissioned reports
434 and 435 and form a subset of the latter.
14

Table 2. The frequency of scat identification in the field being subsequently confirmed as correct
by DNA analysis for each observer and each field assigned certainty category, n = the number
of scats tested.
Scat category Both observers Observer AM Observer JW
n % n % n %
All scats 305 77% 177 80% 128 74%
High certainty 88 93% 44 86% 44 100%
Low certainty 217 71% 133 77% 84 61%
____________________________________________________________________________
15

Table 3. Breakdown of scats misidentified in the field in relation to subsequent DNA
confirmation according to species (fox or pine marten) for each of the two observers in each
field assigned identification certainty category.
_______________________________________________________________________
Both observers Observer AM Observer JW
No. wrong % No. wrong % No. wrong. %
_______________________________________________________________________
All scats 69 36 33
Field - fox, DNA - marten 64 93% 32 89% 32 94%
Field - marten, DNA - fox 5 7% 4 11% 1 6%
High certainty 6 6 0
Field - fox, DNA - marten 5 83% 5 83% -
Field - marten, DNA - fox 1 17% 1 17% -
Low certainty 63 30 33
Field - fox, DNA – marten 59 94% 27 90% 32 94%
Field – marten, DNA – fox 4 6% 3 10% 1 6%
16

Table 4. Indices of predator abundance from forest transects walked between April and June in
1995 (from Baines et al., 2004) and 2009 in the forest areas where capercaillie brood counts
were conducted. Values for fox and pine marten are mean scats 10 km -1 day -1 10 2 and exclude
the clearance round. Those for crows and raptors are mean observations 10 km -1 visit -1 . These
values refer to initial identifications. Corrections from DNA testing can be applied by multiplying
fox indices by 0.45 and marten indices by 1.3.
___________________________________________________________________________
Fox Marten Crow Raptor
Forest 1995 2009 1995 2009 1995 2009 1995 2009
A 9.3 57.5 7.0 221.9 0.9 1.5 0 0
B - 54.6 - 31.4 - 0 - 2.0
C 0 - 0 - 2.5 - 2.8 -
E 5.1 - 0 - - - -
G 13.4 36.2 4.5 158.3 1.2 1.7 0.7 0
H 8.7 45.5 36.0 39.0 1.4 4.4 0.2 1.3
I 9.0 25.1 47.8 40.2 0.9 1.2 0.4 1.2
J 1.8 43.9 3.5 0 0.8 5.5 2.1 3.9
K 60.5 86.1 1.8 4.8 5.4 4.2 1.1 1.9
L 4.9 14.9 0 93.3 0.7 0 0.2 0
N - 29.2 - 53.0 - 0 - 0.9
Q 11.0 5.4 26.5 5.4 0.3 1.4 0 0
R 125.1 - 0 - 5.7 - 0.9 -
S 11.1 17.2 25.9 31.9 0 0 0.5 0
U 19.8 141.1 0 0 1.3 11.3 0.2 2.4
W - 105.7 - 120.8 - 2.5 - 0
X - 12.1 - 46.9 - 2.0 - 0.5
Y - 6.4 - 42.8 - 2.6 - 0.6
Z 8.1 5.7 0 30.3 1.3 0 0.2 0
___________________________________________________________________________
17

Table 5a. Predator indices, (means + 1SE) from 14 forests used by breeding capercaillie in
1995 and 16 forests in 2009. Mammal indices are scats 10 km -1 day -1 x 100 and exclude scats
from the clear-up round. Bird indices are sightings 10 km -1 visit -1 .
____________________________________________________________________________
1995 (n = 14 forests) 2009 (n = 16 forests)
Predator Forests with sign Abundance Forests with sign Abundance
Index
Index
____________________________________________________________________________
Red fox 13 (93%) 21.8 + 9.0 16 (100%) 42.9 + 9.7
Pine marten 8 (57%) 12.0 + 4.6 14 (88%) 57.8 + 15.4
Carrion crow 13 (93%) 3.1 + 0.8 11 (69%) 2.4 + 0.7
Raptors 12 (86%) 1.7 + 0.6 9 (56%) 0.9 + 0.3
____________________________________________________________________________
Table 5b. Predator indices, (means + 1SE) from 11 forests used by breeding capercaillie
surveyed in both 1995 and 2009. Mammal indices are scats 10 km -1 day -1 x 100 and exclude
scats from the clear-up rouind. Bird indices are sightings 10 km -1 visit -1 .
____________________________________________________________________________
1995 2009
Predator Forests with sign Abundance Forests with sign Abundance
Index
Index
____________________________________________________________________________
Red fox 11 (100%) 15.9 + 5.2 11 (100%) 43.5 + 12.2
Pine marten 8 (73%) 15.3 + 5.5 9 (82%) 57.3 + 21.8
Carrion crow 10 (91%) 2.7 + 0.7 8 (73%) 2.9 + 1.0
Raptors 9 (82%) 1.5 + 0.7 5 (45%) 1.0 + 0.4
____________________________________________________________________________
18

Table 6. Pearson correlation coefficients between predator indices (log e (index + 1) in a) 1995
(14 forests) and b) 2009 (16 forests). Significant relationships are given in bold, * P

Table 7. Effects of forest and year on capercaillie breeding success from a generalised linear
model with both forest and year as fixed effects. Tests for differences in breeding success
between the two periods were made from nine forests counted in both periods.
_______________________________________________________________________
Forest
Year
Response variable Period F df P F df P____
Chicks per hen 1991-95 2.17 13,42 0.03 3.07 4,42 0.03
2005-09 1.46 13,45 0.17 9.56 4,45 0.001
Difference 8.47 1,66 0.006
Broods per hen 1991-95 1.74 13,42 0.09 3.20 4,42 0.02
2005-09 1.91 13,45 0.06 12.53 4,45 0.001
Difference 4.54 1,66 0.04
Mean brood size 1991-95 2.38 13,34 0.02 1.59 4,34 0.20
2005-09 0.67 12,29 0.77 0.93 4,29 0.46
Difference 7.21 1,52 0.01
__________________________________________________________________
20

Table 8. Mean breeding success of capercaillie predicted from generalised linear models with
forest and year as fixed effects in forests where predator indices were obtained either in the
period 1991-95 (n=14 forests) or 2005-09 (n=13 forests, no hens were encountered in three
additional forests (J, K and U) and were excluded). (SE) are based on the residual deviance and
since the model is not linear are approximated.
____________________________________________________________________________
Chicks per hen Broods per hen Brood size
Forest 1991-95 2005-09 1991-95 2005-09 1991-95 2005-09_
A 1.1(0.3) 0.5(0.1) 0.37(0.08) 0.22(0.04) 2.9(0.3) 1.9(0.3)
B - 1.3(0.6) - 0.60(0.16) - 2.0(0.6)
C 0.9(0.7) - 0.25(0.23) - 3.3(1.2) -
E 1.4(0.5) - 0.67(0.12) - 2.1(0.3) -
G 0.8(0.3) 0.6(0.2) 0.44(0.10) 0.31(0.08) 1.8(0.3) 1.8(0.4)
H 1.4(0.5) 0.0 0.41(0.14) 0.00 3.3(0.5) -
I 0.4(0.2) 1.1(0.9) 0.26(0.10) 0.44(0.21) 1.7(0.4) 2.3(1.3)
J 0.7(0.2) - 0.32(0.09) - 2.2(0.3) -
K 0.2(0.2) - 0.13(0.09) - 1.8(0.6) -
L 0.9(0.2) 0.3(0.2) 0.41(0.09) 0.20(0.11) 2.1(0.3) 1.2(0.7)
N - 1.1(0.2) - 0.44(0.06) - 2.3(0.3)
Q 2.1(0.7) 0.7(0.3) 0.68(0.16) 0.36(0.11) 3.1(0.5) 1.7(0.5)
R 0.2(0.2) - 0.21(0.16) - 1.0(0.5) -
S 1.2(0.4) 0.6(0.2) 0.45(0.11) 0.32(0.06) 2.8(0.4) 1.2(0.6)
U 0.3(0.2) - 0.17(0.10) - 1.7(0.5) -
W - 0.4(0.2) - 0.15(0.08) - 2.9(1.0)
X - 0.5(0.3) - 0.28(0.13) - 1.7(0.7)
Y - 0.3(0.2) - 0.21(0.11) - 1.2(0.6)
Z 1.8(0.5) 1.1(0.3) 0.60(0.13) 0.48(0.09) 2.9(0.4) 2.3(0.4)
Forest means 1.00(0.14) 0.43(0.16) 0.41(0.03) 0.29(0.04) 2.46(0.12) 1.91(0.12)
____________________________________________________________________________
21

Table 9. Three measures of mean capercaillie breeding success in relation to indices of
predator abundance (log e (index + 1) in 14 forests in period 1 (1991-95) and 13 forests in period
2 (2005-09). Measures are slopes from linear regressions (SE). Significant relationships are
given in bold, * P

Table 10. Changes in three measures of capercaillie breeding success (log e success index)
between the periods 1991-95 and 2005-09 in relation to changes in log e predator indices
between the same periods in eight forests. Values presented are slopes from linear regressions
(SE). No relationships were significant.
____________________________________________________________________________
Chicks per hen Broods per hen Brood size
____________________________________________________________________________
Fox -0.198 (0.453) -0.123 (0.258) 0.073 (0.155)
Marten 0.022 (0.142) 0.017 (0.081) -0.016 (0.048)
Crow -0.081 (0.296) -0.056 (0.169) 0.003 (0.100)
Raptor -0.167 (0.282) -0.091 (0.162) 0.014 (0.106)
____________________________________________________________________________
23

Table 11. Mean (+ SE) hen capercaillie density indices (hens km -2 ) predicted from generalised
linear models with forest and year as fixed effects in forests where predator indices were
obtained in either the period 1991-95 (n=14 forests) and / or 2005-09 (n=16 forests). SE are
based on the residual deviance and since the model is not linear are approximated.
_________________________________________________________________
Hen density (birds km -2 )
Forest 1991-95 2005-09
A 2.7 + 0.4 -
B - 0.6 + 0.2
C 0.6 + 0.3 1.5 + 0.8
E 1.9 + 0.4 -
G 7.4 + 1.3 4.8 + 0.9
H 3.7 + 0.9 0.1 + 0.1
I 2.7 + 0.5 0.5 + 0.2
J 2.0 + 0.5 0
K 2.0 + 0.5 0
L 4.9 + 0.8 4.5 + 0.7
N - 2.1 + 0.3
Q 9.7 + 2.8 4.6 + 1.2
R 4.1 + 1.3 -
S 2.0 + 0.4 1.5 + 0.2
U 7.8 + 1.8 0
W - 0.6 + 0.1
X - 5.0 + 1.5
Y - 1.6 + 0.4
Z 1.0 + 0.2 0.7 + 0.1
_____________________________________________________________
Mean from GLM output 4.2 + 0.5 1.8 + 0.3
Effect of forest F 13,42 = 9.63, P < 0.001 F 15,45 = 12.08, P < 0.001
Effect of year F 4,42 = 1.42, P = 0.25 F 4,45 = 1.74, P = 0.16
24

Table 12. Hen capercaillie density indices (birds km -2 ) in relation to four predator indices (log e
(index +1)) during the periods 1991-95 (n = 14 forests) and 2005-09 (n = 15 forests) and
changes in hen density index (log e (density + 0.1)) in relation to changes in predator indices
between the two periods (n = 11 forests). Values are slopes from linear regressions (SE).
Significant relationships are given in bold, * P < 0.05, ** P < 0.01.
_________________________________________________________________________
Mean hen densities
1991-95 2005-09 Change_______
Fox 0.268 (0.114) * -0.840 (0.288) * -0.930 (0.308) *
Marten 0.078 (0.083) 0.402 (0.128) ** 0.156 (0.150)
Crow -0.119 (0.359) -0.915 (0.406) * -0.424 (0.303)
Raptor -0.562 (0.325) -1.834 (0.502) ** -0.715 (0.232) *
____________________________________________________________________________
25

FIGURES
Figure 1. Location of the 19 forests in which predators were surveyed in either 1995 and / or
2009 and capercaillie were counted.
26

Figure 2. Capercaillie breeding success (chicks per hen) based on outputs from Poisson
regressions involving forest and year as fixed effects in the period 2005-09 and indices of
predator (log e (index + 0.1)) in 2009 in 13 forests. The fitted line is from a linear regression.
a) Carrion crow r 2 = 0.33
1.5
Chicks per hen
1.0
0.5
0.0
-2.5 -1.0 0.5 2.0
Crow index
b) Raptors r 2 = 0.04
1.5
Chicks per hen
1.0
0.5
0.0
-2.5 -1.5 -0.5 0.5 1.5
Raptor index
27

c) Fox r 2 = 0.01
1.5
Chicks per hen
1.0
0.5
0.0
1.5 2.2 2.9 3.6 4.3 5.0
Fox index
d) Pine marten r 2 = 0.09
1.5
Chicks per hen
1.0
0.5
0.0
2 3 4 5 6
Marten index
28

Figure 3. Capercaillie hen density indices (log (hens km -2 + 0.1)) in the period 2005-09 and
predator indices (log e (index + 0.1)) in 2009 from 16 forests. The fitted lines are from linear
regressions.
a) Carrion crow r 2 = 0.28
2.0
Hen density
0.5
-1.0
-2.5
-2.5 -1.5 -0.5 0.5 1.5 2.5
Crow index
b) Raptors r 2 = 0.49
2.0
Hen density
0.5
-1.0
-2.5
-2.5 -1.5 -0.5 0.5 1.5
Raptor index
29

c) Fox r 2 = 0.37
2.0
Hen density
0.5
-1.0
-2.5
1.5 2.2 2.9 3.6 4.3 5.0
Fox index
d) Pine marten r2 = 0.41
2.0
Hen density
0.5
-1.0
-2.5
-2.5 -0.8 0.9 2.6 4.3 6.0
Marten index
30

e) Pine marten, with outlier point excluded
2
1
Hen density
0
-1
-2
-3
0 2 4 6
Marten index
31

Figure 4. Changes in capercaillie hen density indices(log (hens km -2 + 0.1) between 1991-95
and 2005-09 and changes in indices of predator abundance (log e (index + 0.1)) in the same 11
forests over the same period. The fitted lines are from linear regressions.
a) Carrion crow r 2 = 0.16
1.0
Change in hen index
-0.1
-1.2
-2.3
-3.4
-4.5
-3.5 -2.4 -1.3 -0.2 0.9 2.0
Change in crow index
b) Raptors r 2 = 0.37
1.0
Change in hen index
-0.1
-1.2
-2.3
-3.4
-4.5
-3.5 -2.5 -1.5 -0.5 0.5 1.5
Change in raptor index
32

c) Fox r 2 = 0.31
1.0
Change in hen index
-0.1
-1.2
-2.3
-3.4
-4.5
-1 0 1 2 3
Change in fox index
d) Pine marten r 2 = 0.16
1.0
Change in hen index
-0.1
-1.2
-2.3
-3.4
-4.5
-4.0 -1.8 0.4 2.6 4.8 7.0
Change in marten index
33

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© Scottish Natural Heritage 2011
ISBN: 978-1-85397-701-5
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