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Changes in roe deer (Capreolus capreolus L.) population density in response to forest habitat succession
Fores;i;ology Management ForestEeoiogyandManagementLB(1996)31-41
Changes in roe deer (Cqwe~Zm capreohs L.) population density in response to forest habitat succession R.M.A. Gill a9* , A.L. Johnson ‘*‘, A. Francis cp2,K. Hiscocks ‘, A.J. Peacea a Foresiry
Commission Research Division, Alice Halt Lodge, Wreccleshum, Surrey, ’ 5 Orchard Way, Misterton, Crewkerne, Dorset, TAl8 8NN. UK ’ Low Knap, Halstock, Dorset, UK ’ 4 Francolin Close, Wooa%avenS Durban. 4001, South Africa
GUlO
4LH.
UK
Abstract In spite of several studies showing that roe deer typically achieve higher population densities in openings or younger forest stands, there do not appear to be any reporting the responseof a single population to forest habitat change. In this paper the results of a 25-year study of a roe deer population, which was not subject to significant levels of culling, predation or ungulate competition are presented.Following planting with conifers (which was mostly in 1961-621, the canopy cover increased, most mpidly between 8 and 15 years after planting. Ground vegetation cover was negatively correlated with canopy cover. The deer population increasedfrom 46 km-* to 76 km-* between 4 and 13 yearsafter planting, after which it declined sharply to 34 kin*. A significant negative cross-correlationwas found between conifer canopy cover and deer density with a lag of 6 years, indicating that the decline in deer numbers lagged behind the decline in browse supply. The rate of recruitment was correlated with the conifer canopy cover without any indication of a significant lag. The decline in cover of the main food plant species (bramble Rubus fiurkxx~~), was much greater than the decline in deer density, implying that the deer were forced to change their diet and perhaps also their patterns of habitat selection in responseto the change in habitat structure. Keywords:
Time-series; Population Iags; Mark-recapture; Habitat selection; Vegetation communities; Browsing; Diet
1. Introduction
It has long been recognised that deer populations are influenced by a regime of forest clearance and subsequent regeneration (Leopold, 1950; K&rig and Gossow, 197% Staines and Welch, 198% Ratcliffe, * Corresponding author. Tel: 44 1420 22255; fax 44 1420 23653.
’ Deceased. * Deceased.
1987). Clearing, whether natural or man-made, is typically followed by a pronounced increase in the availability of browse and cover which subsequently declines as the next tree canopy closes over (Halls and Alcaniz, 1968; Irwin and Peek, 1979; Doerr and Sandburg, 1986). Investigations of habitat selection by deer indicate that the use of different forest habitats corresponds broadly with differences in food plant biomass (Cibien and Semp&& 1989; Welch et al., 1990) and this appears to be the main reason why young stands,
0378- 1127/%/$15.00 Copyright 0 1996 Elsevier Science B.V. All rights reserved. I’ll SO378I 127(96)03807-8
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or forest rides or edges are used relatively more than older stands (Henry, 1981; Staines and Welch, 1984; Welch et al., 1990). Other studies, making use of pellet counts and cull data (Batcheler, 1960) or drive counts carried out in stands of varying age @ucek et al., 19751, have provided some evidence that roe deer populations will decline as the stand ages. Loudon (19871 reported that females shot from forest areas containing a high proportion of young forest stands were heavier and more fecund, despite higher deer densities in these areas. In spite of the evidence suggesting that roe and other deer species are affected by changes in forest structure, the authors are not aware of any long-term studies where the response of an ungulate population to marked habitat succession has been monitored in detail. Little is therefore known of how quickly the deer population respnds to habitat change, nor whether the change in deer density is proportional to the change in food plant biomass, or lagged some years behind as some authors suggest (Konig and Gossow, 1979). Further, it is not clear how diet and patterns of habitat selection are affected by the habitat succession. In this paper the results of a long-term study of a roe deer population inhabiting a small forest (149 ha) in southern England are reported. The study was started in the 1960s shortly after planting and continued for over 25 years, when the forest was in the pole stage, embracing periods of both very good and very poor habitat conditions.
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imum January temperatures at the nearest weather station were 7.6OC and 1.8OCrespectively, forI%& 1989. Approximately 75% of the woodland was cleared and re-planted between 1961 and 1970. mostly m 1961-62, leaving a few of the original broadleaved stands scattered mainly around the periphery. Most of the newly-planted trees were Norway spruce P&a abies, although several other coniferous species were used, a well as beech Fagus syluatka and oak Quercus robur, which were planted in small groups or in mixture with the conifers. Agricultural activities in the neighbouring fields were limited to permanent pasture or hay meadows. Investigations of ranging behaviour ~Bramley, 1970; authors’ data) indicated that deer made relatively little use of these fields for feeding and it is assumed that responses of the deer population are due ro changes in the woodland environment, not to changes in nearby farming practices. With the exception of 1968 when 15 roe deer were shot (Bramley, 1970), the population in the wood was only subjected to very occasional culling. No definite cases of predation were reported, aithough on three occasions dogs or foxes Vulpes wipes were found with the remains of kids. Dispersal away from the study area was limited primarily by the lack of adjacent woodland cover rather than physical barriers, although a nearby fenced railway line restricted movement in a northwesterly direction. 2.2, Assessment oj* vegetation changes
2. Methods 2.1. The study area
The study area included 149 ha of woodland (Chedington Woods), and adjacent farmland in Dorset, England (52’52’N, 2’43’W). These woods are situated in an area devoted to pastoral farming and therefore relatively isolated from nearby woodland and deer populations of comparable size, although one other wood of almost 100 ha lies 2 km to the northeast. The site covers predominantly northfacing terrain, 75-150 m above sea level, on poorly drained, base-rich soil and experiences an oceanic climate with mild winters. Mean maximum and min-
Tree canopy cover was assessed from a set of vertical aerial photographs, taken in June 1965, July 1967, June 1970, April 1973, September 1986 and May 1989. The scale of these photographs ranged from 1:7500 to 1: 12 000. In addition, a set of oblique aerial colour photographs taken in the summer of 1977 was also used. The study area was divided.into 89 smaller, relatively homogenous areas on the basis of sub-compartment boundaries or other distinguishable features, and the proportion of canopy cover was estimated from each photograph within each area. Making use of stereoscopic pairs of photographs and a X 10 magnification, the canopy cover was further subdivided into conifer or broadleaf and
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two height classes, namely trees approximately 2-5 m in height (referred to as ‘short’ trees) and those > 5 m tall. In the summer of 1989, the ground vegetation was surveyed in the main part of the wood. The woodland vegetation was stratified into four main types present at that time (rides, scrub, broadleaved stands and coniferous stands) and percentage cover of each species or species group was assessed in quadrats spaced at 10 m intervals along transects in each stratum (18 transects and 422 quadrats in total). Cover was assessedfor plants O-50 cm above ground in 1 m x 1 m quadrats and for those between 50 cm and 120 cm in 3 m X 3 m quadrats, positioned with a common northeastern comer. Each transect was started at a random location within the stratum. Along rides, quadrats were positioned alternately on the edge and in the centre of the ride. In 1971, Hosey (1974h Hosey (1981) investigated the diet of the rce deer and surveyed the ground vegetation in the study area, reporting the cover of two major species, bracken Pteridium aquilinum and bramble Rubus fi~ticosns. In the lowland parts of northwest Europe, these two species are generally found to represent an unpalatable and very palatable species respectively (Henry, 1978; Jackson, 1980; Hearney and Jennings, 1983; Diakite, 1983; Maizeret and Tran Namh Sung, 1984 Boisaubert et al., 1985; Maillard and Picard, 1987). In this study area bramble was found to be the single most important species in the diet, which ranged from 25% in June to 85% in February (Hosey, 1974; Hosey, 1981). Conifer needles, in contrast, formed only a minor component of the diet (approximately 3%) and although no comparisons with protected trees were made, browsing did not appear to limit growth of the conifers. 2.3. Capture and marking of deer
Kids less than a few weeks old were marked with numbered ear tags or ear flashes. Adults and kids more than 6 months old were caught in nets (Cockbum, 19791 and marked with both ear tags and neck collars. The collars were made of ‘Darvic’, a type of plastic that does not fade, and were usually fitted with one or two coloured tabs on each side, to ensure each deer had a unique colour combination. Deer captures were carried out every winter, usu-
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ally on two dates in March, from 1961 to 1989. Altogether, 335 animals were ear-tagged and 244 of these were also fitted with collars at some time during their lives. From time to time, loss of collars or ear tags was reported. In total, 17 deer were reported to lose a collar (all of them bucks) and three without collars lost both ear tags. However, collar loss was not considered a serious bias because a large proportion (15) had the collar replaced at a later date, and in many cases, identification was still possible in the interim by ear tags. In addition to the marked animals, a further 58 unmarked adults were recognisable from individual characteristics (antlers, coat colour and ear or rump tufts) and 164 unmarked kids were recognisable by association with a marked mother or sibling. 2.4. Estimates of deer population size and recruitment
Population estimates were calculated by two methods. From 1967 to 1980, regular counts of marked and unmarked animals were made in springtime, making it possible to estimate density using mark-resighting methods (a ‘Lincoln index’) (Seber, 1982; White and Garrott, 1990). Estimates for other periods were based on the minimum number known to be alive, calculated as the total number of marked and recognisable unmarked animals alive during each quarter between 1966-1989. Recruitment was estimated from the ratio of kids to females 2 years old or more, amongst the marked and recognisable unmarked animals each spring. Estimates based on mark-resighting were calculated using the joint hypergeometric maximum likelihood estimator (White and Garrott, 1990). This method requires several independent counts of marked and unmarked animals to be made and carries the assumption of population closure. The product of the hypergeometric likelihood function can be numerically opti@ed to estimate N. The estimator is the value of N that maxim&s the expression:
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The values in parentheses are binomial coefftcients e.g.
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were calculated on the area of woodland sampled, not the total study area. 2.5. Analysis of the response of deer density to vegeiation chunges
and ni and mi are the total number of animals and number of marked animals respectively, seen on occasion i, i = 2,. . . , k+ 1, and &l is the total number ?f marked animals in the population. Estimation of N was achieved using a SAS program Statistical Analysis Systems Institute Inc. program modified from White and Garrott ( 1990). Counts of the ratios of marked and unmarked animals were made in March and April, before the period of sub-adult dispersal, and were further limited to dates when the numbers of marked animals in the wood were, as far as known, constant. In an effort to ensure equal sightability and to minimise any possible bias due dependency between counts, estimates of population size were based on only the southern section of the wood, which comprixd 63% of the total area and connected to the rest of the wood by a narrow strip. This area was more thoroughly covered during capture attempts as well as on subsequent counting days and it was therefore possible to use a large sample of censuses (ranging from 14 to 36) to estimate density. Further, nearly all marked yearlings and adults using this area received collars, so identification did not have to rely on ear tags. Habitat conditions were similar in all parts of the study area. Visibility across the study area was excellent during the 1960s and early 1970s but subsequently deteriorated as the trees grew taller. This effect was, however, fairly uniform across the study area and the ride network, and many vantage points still provided good opportunities for observing deer. It is assumed that changes in visibility did not affect the ratio of marked to unmarked animals sighted. Observations of deer have been disregarded if the head and neck were not visible enough for any possible mark to be seen, or if they were seen to be marked but otherwise unidentifiable. In view of the fact that use of adjacent fields by deer was relatively minor in comparison with use of the woodland habitats, population density estimates
To identify any significant delayed response in deer density, the lagged cross-coflelations were calculated between deer density, recruitment and total conifer tree cover. In view of the fact that cross-correlations are affected by autocorrelation in each variable (Box and Newbold, 1971; Chatfield, 19&9), it was first necessary to remove the autocorrelation by fitting an ARIMA model and then calculating~the cross-correlation coefficients from the residuals. ARIMA model selection was based initially on inspection of the autocorrelation function of the residuals and then choosing the model with the minimum innovation variance. An ARIMA (1 ,O,O)model (with one autoregressive term) was selected for deer density and recruitment, and an ARIMA (1,1,4) model (one autoregressive, one differencing and four moving average terms) was selected for total conifer cover (Box and Jenkins, 1976). All models and cross correlations were estimated using GENSTAT (Genstat 5 Committee, 19931.
3. Results 3. I. Changes in tree cover The most important aspect of the vegetation change was clearly the increase in coniferous tree canopy cover, which represented almost 70% of the woodland area by 1989 (Fig. I). The total coniferous canopy cover changed most rapidly between 8 and 1.5 years after planting (1970-771, increasing from 4.3% to 48.1% of the woodland area in only 7 years. Change in the cover of ‘short’ trees was most rapid at this time, indicating that the woodland vegetation was progressing through the thicket stage during this period. The ‘pre-thicket’ stage, normally considered optimum habitat for roe deer, would have occurred between about 5 and 8 years after planting {1%7-701. In comparison with the conifer cover, the area of broadleaf cover remained relatively constant, at between 14% and 27% of the total.
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in ground vegetation
The results of the 1989 survey revealed that under mature conifer stands, vascular plants were almost entirely absent, except in the few canopy gaps (Table 1). A few herbs, ivy Hedera heZix and bramble were present under the mature broadleaved stands although here too, the cover was sparse in view of the preponderance of beech in the canopy. The only areas containing a significant ground vegetation were the patches of scrub woodland and the rides and other openings, such as the edges of roads and ponds. In these areas the vegetation was also more diverse: in total, 69 species were recorded in the quadrats, excluding grasses. However even here, the vegetation was dominated largely by grasses and pendulous sedge Carex pendula which as noted later, are not particularly important food plants for rm deer. A regression of total ground vegetation cover (V 1 on canopy cover revealed that both conif-
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Fig. 2. Changes in the cover of bramble (black) and bracken (white) between 1971 and 1989. Vertical bars represent the difference (between 1971 and 1989) in proportion of the woodland area with high ( > 30%), medium (lo-30%). low ( < 10%) or no (0%) ground cover respectively.
erous (c) and deciduous (d) tree cover had a significant influence (V = 126.6 - 1.263~ - 0.589d, F = 128.9, 2,63 d.f., r* = 0.809, P < 0.0001). There was clearly a dramatic decline in understorey vegetation cover between 197 1, the date of the first survey, and 1989 (Fig. 2). In this assessment, the cover of bramble and bracken averaged approximately 23% and 21% respectively over the study area, in contrast to averages of 1.4% and 2.5% respectively for 1989. In the case of bramble, this represents at least a 16-fold reduction in cover. 3.3. Changes in deer popuZation size and recruitment
XEY
Broadleaf Broadleaf Cmlfer Conifer
(Short (Tall) Short) t Tall)
Fig. I. Changes in the proportion of tree canopy cover, expressed as a percentage of total woodland area (149 ha), for the years when aerial photographs are available. Short trees were estimated to be 2-5m in height; tall tnzes > Sm.
The estimates of population sixe in spring calculated by the joint hypergeometric method reveal marked year to year changes in density (Fig. 3). The population increased from 46 km-* in 1967 to 76 km-* in 1975 (between 5 and 14 years after planting) and then fell sharply to 34 km-* in 1979-80. A small decline is also evident in the late 1968 and
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early 1969, after a number of animals were shot in the study area (see Bramley, 1970). The confidence intervals reveal that the population in 1975 and 1976 was significantly greater than in 1967, 1%9, 197 1 and also in the years after 1977. The population remained low during the 1980s. although some increase was evident after 1984. In view of the fact that some unmarked deer could be recognised and not all were seen during the census period, the minimum number known to be alive was occasion-
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ally greater than the lower confidence interval of the estimate. Estimates made from the joint hypergeometric maximum likelihood method were closely cormlated with the minimum numbers known to be alive for the years 1967-80 (constant = 2.819, coefficient = 1.073, F = 147.5, d.f.= 12; r2 = 0.925; P < O.OOOl~,as well as the numbers marked ~constant = -0.376, coefficient = 1.361, F = 101.1, d.f; = 12, t-‘= 0.894, P < 0.0001). This suggests that the
Table 1 The species composition of vegetation up to 1.2 m above ground in 1989 Grasses
Bare ground Car.2
pet&la
Other species Mosses Mercuralis perennis Pteridium aquilinum Rubus endular Crateagus monogyna Pulicaria dysenterica Glechoma hederacea Equisetwn arvense Vrtica dioica Prunus spinosa Corylus avellana Lotus corniculatw Juncus efisus Mentha arvensis Potennlla repens Hedera helix Primula veris Ranunculus sp. Leon&on hispidus Circaea lutetiana Betonica ojicinalis Lonicera periclymenum Plantago lanceolata Geranium robertianum Alnus glutinosa Frcwinus excelsior Tr$olium sp.
Carexjlacca Eupatorium cannabiman Euphorbia amygdalxndes Ilex aquifolium Potentilla anserina
Rides and scrub (30 ha) 27.0 20.8 13.0 12.7 9.2 7.2 6.2 5.7 3.7 3.7 3.5 2.8 2.6 2.4 2.1 1.5 1.5 1.4 I.4 1.1 1.1 1.0 I .o 0.9 0.9 0.8 0.8 0.8 0.8 0.7 0.7 0.7 0.6 0.4 0.3 0.3
Figures represent mean percent cover in each habitat type.
Broadleaf stands ( 16 ha)
Conifer stands @3Zjha)
5.3 52.2 5.2 4.9 24.0 4.3 0.2 1.6 0.3
0.6 61.9 1.9 1.8 31.0 0.2 0.7 0. I 0.6
0.9 0.1
1.2
0.7
2.1
0.4 0.2
1.0 0.1
0.8
2.2
0.4
0.3 0.3
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marked and known unmarked animals usually formed the bulk of the population and could be used as a correlate of total density for the years 1982-1989 when Lincoln indices could not be calculated. The sharp peaks in population size calculated from the minimum number alive (Fig. 3) are mainly due to the annual birth pulses and reveal a general trend from high to low rates of recruitment as canopy cover closed over. Recruitment rate was highest in 1968 at 1.36 kids doe- ‘, but averaged 0.83 between 1970-74 and only 0.27 between 1975 and 1983, before increasing slightly to 0.48 between 1984-88. Recruitment was negatively correlated to the total conifer canopy cover (F = 41.13, 1,21 d.f., r* = 0.662, P < 0.001). 3.4. Response of the deer population to forest habitat change
The results of the cross correlation analyses revealed that total conifer cover was negatively correlated with deer density with a lag of 6 years (rb = -0.517, P < 0.05, Fig. 4). This indicates that deer numbers were high approximately 6 years after es-
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0 0
1.2-.o tJ.10.0
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2
0.
0
l
m
430
-0.1-
u*.
-0.2-
-
- o".
-0.3j
”
CJ
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~oo.oe”~e 0.
0
l 0
Fig. 4. Cross conelation coefftcients calculated for deer density (solid points) and recruitment (open circles), each lagged O-20 years against total conifer cover. Coefficients were calculated on the residuals after first removing the autocorrelation in each variable. Points above or below the dashed lines indicate significant cross-conelation (p < 0.05).
tablishment, when tree cover is very sparse and likewise, density was low a similar period after conifer tree cover was high, during the late thicket phase. The was no significant lag in response of recruitment to changes in conifer cover.
4. Discussion 80
4.1. Density estimates
70 60 SO 40 30 20
IO-666677777777776~68~~~~~~9
67B90123456789012.34567890 YEAR
Fig. 3. Changes in population density (deer km-* 1 1966-89. Solid circles and associated vertical bars represent estimates and 95% contidence intervals calculated by tbe joint hypergeometric maximum likelihood method (White and Garrett, 1990). The continuous line represents the density based on the minimum number known to be ushtg the main study area, htcluding both marked and unmarked animals. The dashed line is the total number of marked animals only.
Previous attempts to use mark-recapture methods to obtain estimates of population density have reported the difficulties of complying with all of the conditions (Seber, 1982). These include no loss of marks, no emigration or immigration, equal sightability of all animals and that each census should be independent. Although complete compliance with all of these conditions was not possible, the effect of any bias on the estimate is limited when a high percentage of the population is marked (Strangaard, 1%7). In this study, the proportion marked (of the minimum number alive) ranged from 64% in 1966 to 89% in 1976, remaining above 78% in most years (Fig. 3). Unequal sightability, a common problem with a relatively sedentary species, is usually reported to yield under-estimates (Rice and Harder,
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1977; Otis et al., 1978; Bartmann et al,, 1987). Thus if any bias did occur, it is likely to be towards a slight under-estimate. In comparison with figures published for other roe deer populations, the density of 76 kmm2 in 1975 is clearly very high. Estimates reported from a number of other localities in Europe extend up to only 65.0 km-* (Andersen, 1953; Prior, 1968; Strangaard, 1972; Prusaite et al., 1973; Pucek et al., 1975; Fruzinski and Labudski, 1982; Bideau et al., 1992; Boutin et al., 19921, typically with lower densites (7.0-17.0 km-*) in farmland habitats (Zejda and Homolka, 1980; Kaluzinski, 1982; Maublanc, 1986; Denis, 1992) or where wolves Canis lupus are present (0.7-19.0 km-*; Pucek et al., 1975; SaezRoyuela and Telleria, 1991; Danilkin et al., 1992; Danilkin, 1992; Mattioli et al., 1992; Jedrzejewski et al., 1992). However, none of these studies aplxar to have reported densities from forests almost entirely within a favourable stage of habitat succession and there is no reason to believe that the population densities of 50-100 km-* are not commonplace where roe deer occupy good habitat and are also free from competition, severe winter weather and a significant level of shooting or predation. 4.2. Changes in habitat
Measurements of light intensity have shown that approximately 95% of solar radiation and 99% of light in the visible wavelengths is absorbed before reaching the ground in pole-stage Norway spruce stands (Brasseur and de Sloover, 19731. The reduction in grotmd vegetation biomass between planting and mid-rotation is understandably, therefore, substantial. The 16fold reduction in the cover of bramble recorded in this study exceeds that reported in many other comparisons of understorey biomass between shaded and unshaded stands, although still within the range of recorded variability (Halls and Alcaniz, 1%8; Perzanowski et al., 1982; Doerr and Sandburg, 1986). Light attenuation by an even-aged spruce canopy is so efficient that almost no vascular plants survive at ground level except under gaps or stand edges. Besides the effect of shade, the species composition of the vegetation at the end of the study pro-
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vided strong indications that the deer-themseives also had a marked impact on the vegetation. Herbaceous species that were common in the diet m 1971 @‘Xfolium sp., Potentilla sp., meadowsweet Eupatorium cannabinum, Plantago sp., Rumex sp. and hogweed Heracleum spondylium) formed only a very small part of the vegetation cover in i989. Instead, species that are known to be avoided by roe deer, including pendulous sedge Carex pendula, dog’s mercury Mercuralis perennis, ground ivy Glechoma hederacea, fleabane Pulicaria dysenterica, horsetails Equisetum arvense and mint Mentha arvensis, were relatively abundant. Many of these species are known to be toxic to other ungulates (Cooper and Johnson, 19841, which may explain why they appear to be unpalatable to roe deer. The fact that bramble decreased in cover more than bracken (another unpalatable species) between 1971 and 1989 also suggests that browsing, in addition to shade, was depleting the abundance of food plants. 4.3. Response of the roe deer population succession
to habitut
These results reveal that deer numbers responded dramatically, although with a distinct lag, to changes in coniferous canopy cover. Numbers increased while tree cover was sparse, only peaking when conifer cover reached approximately 40% of the woodland area, but then declined rapidly. For a brief period (1970-751, both deer density and canopy cover were increasing together. Given that the ground vegetation was so strongly suppressed by the growth of the canopy, this confirms that the deer population increased temporarily while food availability declined. When the population levelled after canopy closure, density remained approximately 25-40% of the highest density. This indicates that density was not reduced as much as the ground vegetation cover or the main food plant species, bramble, although recruitment rates remained low at this time, perhaps as a result of reduced food availability. The main reason for the lag appears to be because recruitment was more directly sensitive to changes in the ground vegetation than population density. The initial decline in recruitment was not sufficient to prevent a continued but gradual increase in density.
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In view of the fact that approximately 69% of juvenile growth is completed by the end of the first winter, it is not surprising that recruitment rates were so closely correlated with year to year changes in canopy cover and therefore presumably also changes in food availability. Amongst ungulates in general, juvenile survival is typically lower than adult survival (Caughley, 1966; Gaillard et al., 19931, as well as more sensitive to environmental conditions (Glutton-Brock et al., 1982). The period of low recruitment was also associated with delayed birth dates, reduced weight gain in kids and poor kid survival (Gill, 1994). In addition to the effect of tree canopy shade on ground vegetation, other factors, such as weather or shelter may have contributed to the lagged response in density. The young conifers would have provided some cover that may have partly compensated for a reduction in food availability. However, with a mild winter climate, the beneficial effect of shelter is not likely to be marked. The lag in response to habitat change has a number of implications for the relationship of the deer to their habitat. In particular, it suggests that competition for food would intensify as availability is restricted and that density-dependent responses in tbe deer population would be most acute at this time. It is also likely that changes in diet, habitat use, and behaviour occur at this time. Although the timing of changes in the ground vegetation community was not monitored, it is likely that these changes are also most acute as canopy closure restricts food availability. The decline of the most palatable species and damage to tree seedlings, where they remain, may accelerate at this time, indicating that regeneration will be most difficult in forests containing extensive areas of pole or mature stage trees and only very small or infrequent openings. The response of a deer population to forest habitat change is therefore more complex than a simple change in density. Changes in performance are also involved, and very likely also changes in diet, habitat use, as well as ground vegetation composition. At any moment in time, the relationship between deer and their habitat will depend on the sequence of forest and deer population changes, not merely current conditions.
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Acknowledgements We would like to thank J. Rowe and Dr. P. Ratcliffe for help with organising this project; F. Guinness, G. Jessop, helped with fieldwork P. Lewis, R. Prior, Lt. Col. J. Cockburn, H. Pepper, B. Maybe, and many others for catching deer; E. Colyer helped with aerial photo interpretation. Dr. S.D. Albon, Prof. T.H. Clutton-Brock and an anonymous referee gave helpful comments on earlier versions of this work.
References Andersen, J., 1953. Analysis of the Danish roe deer population based on the extermination of the total stock. Dan. Rev. Game Biol., 2: 127-1.55. Bartmann, R.M., White., G.C., Carpenter, L.H. and Gatrott, R.A., 1987. Aerial mark-recapturn estimates of confined mule deer in pinyon-juniper wocdland. J. Wildl. Manage., 51: 41-46. Batcheler, C.L., 1960. A study of the relations between roe, red and fallow deer, with special reference to Dmmmond Hill forest, Scotland. J. Anim. Ecol. 29: 375-384. Bideau, E., Vincent, J.P., Gerard, J.F. and Maublanc, M.L., 1992. Influence of sex and age on space occupation by roe deer (Capreohs capreohs L.J. Jn F. Spitz, G. Janeau, G. Gonzalez and S. Aulagnier (Editors), Gngules/Ungulates, 91, 2-6 September 1991, Toulouse, France, pp. 263-266. Boisaubert, B., Maillard, D. and Maim, M.H., 1985. Etude du regime alimentaire du Chevreuil en for& de Haye. XVEth Congress of the International Game Biologists. BNS~&, 17-21 September 1985, pp. 421-429. Boutin, J.M., Gaillard, J.M., Delorme, D., Van Laere, G., Doitran, B.B. and Bodani, S., 1992. Home ranges and movements of roe deer fawns (Capreolus capreolus L.). In: F, Spitz, G. Janeau, G. Gonzalez and S. Aulagnier (Editors), Gngules/Ungulates, 91, 2-6 September 1991, Toulouse, France, pp. 277278. Box, G.E.P. and Jenkms, G.M., 1976. Time Series Analysis: Forecasting and Control. Holden-Day, San Francisco, CA. Box, G.E.P. and Newbold, P., 1971. Some comments on a paper of Coen, Gomme and Kendall. J. R. Stat. See., Ser. A. 1341 229-240. Bramley, P.S., 1970. Territoriality and reproductive behaviour of roe deer. J. Reprod. FertiI., Suppl. I I: 43-70. Brasseur, F. and de Sloover, J.R., 1973. Interception of total solar radiation an visible light in two forest communities in the Belgian Haute-Ardenne. Bull. Sot. R. Bot. Belg., 106~ 219236. Caughley, G., 1966. Mortality patterns in mammals. Ecology, 47: 906-918, Chatfield, C., 1989. The Analysis of Time Series-an hnroduction. Chapman and Hall, London.
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Cibien, C. and Sempeti, A., 1989. Food availability as a factor in habitat use by rce deer. Acta lheriol., 34 I 1I - 124. Clutton-Brock, T.H. Guinness, F.E. and Albon, S.D., 1982. Red Deer: Behaviour and Ecology of Two Sexes. University of Chicago Press, 377 pp. Cockbum, R.H.A., 1979. Catching roe deer alive in long nets. I&r, 3: 434-439. Cooper, M.R. and Johnson, A.W., 1984. Poisonous plants in Britain and their effects on animals and man. Ministry of Agriculture, Fisheries and Food, HMSO, London. Danilkin, A.A., 1992. Population structure. In: V.E. Sokolov (Editor), European and Siberian Roe Deer. Nauka, Moscow, pp. ItlO- 184 (in Russianl. Danilkin, A.A., Dannan, YuA. and Minayev, A.N., 1992. The seasonal migrations of a Siberian roe deer population. Rev. Ecol. (Terre Vie). 47: 231-243. Denis, M., 1992. Some data on a high density population of field roe deer. In: F. Spitz, G. Janeau, Cl. Gonzalez and S. Aulagnier @ditors). Gngules/Ungulates, 91, Toulouse, France, 2-6 September 1991, pp. 519-521. Diakite, M.M., 1983. A study of the winter diet of roe deer in Alice Holt forest. MSc. Thesis, University of London, London. Doerr, J.G. and Sandburg, N.H., 1986. Effects of prwommercial thinning on understorey vegetation and deer habitat utilization on Big Level island in Southeast Alaska. For. Sci., 32: 10921095. Fruzinski, B. and Labudski, L., 1982. Demographic processes in a forest roe deer population. Acta ‘lheriol., 27: 365-375. Gaillard, J.M., Delorme, D., Boutin, J.M., Van Laere, G., Boisaubert, B. and Pmdel, R., 1993. Roe deer survival patterns -a comparative analysis of contrasting populations. J. Anim. Ecol., 62 778-791. Cienstat 5 Committee, 1993. Genstatrr” 5, Release 3, Reference Manual. Clarendon Press, Oxford. Gill, R.M.A., 1994. The population dynamics of roe deer (Capreolus capreo/us L.1 in relation to forest habitat succession. PhD. Thesis, Open University, Milton Keynes, 191 pp. Halls, L.K. and Alcaniz, R., 1%8. Browse plants yield best in forest openings. J. Wild]. Manage., 32: 185-186. Heamey, A.W. and Jemings, T.J., 1983. Annual foods of the red deer (Ceruus elqhus) and the roe deer (Capreolus cupreolus) in the east of England. J. Zool. (Land.), 201: 565-570. Henry, B.A.M., 1978. Diet of roe deer in an English conifer forest. J. Wildl. Manage., 42: 937-940. Henry, B.A.M., 1981. Dlsbibution patterns of roe deer (Capreolus capreolus) related to the availability of food and cover. J. Zool. (Land.), 194 271-275. Hosey, G.R., 1974. The food and feeding ecology of the roe deer (Cupreolus capreolus). PhD. Thesis, University of Manchester, Manchester. Hosey, G.R., 1981. Ammal foods of the roe deer (Capreolus capreolus) in the south of England. J. ZooI. (Lond.1, 42: 276-278. Irwin, L.L. and Peek, J.M., 1979. Shrub production and biomass trends following five logging treatments within the cedarhemlock zone of northern Idaho. For. Sci., 25: 415-426.
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Jackson, J., 1980. The annual diet of the roe deer (Ckpreolus capreolud in dre New Forest, Hampahlre, as determined by rumen content analysis. J. ZooI. (Lo&, 192: 71-83. Jedrzejewski, W., Jedtzejewska, B., Gkarma, H. and Rupmcht, A.L., 1992. Wolf predation and snow cover as mortality factors in the ungulate commmtity of the BiaIowieza National Park, Poland. Gecologia, % 27-36. Kaluzinski, J., 1982. Dynamics and structure of a tleld roe deer population. Acta Theriol., 27 385-408. K&rig, E. and Gossow, H., 1979. Even-aged stat-idsas habitat for deer in Central Europe. In: E.D. Fotd, DC. Malcolm and J. Atterson @litor& The Ecology of Even-aged Pbmtritions. Institute of Terrestrial Ecology, Cambridge, pp. 429-451. Leopold, AS., 1950. Deer in relation to plant successions.J. For., 48: 67.5-678. Loudon, A.S.I., 1987. The influence of forest habitat structure on growth, body size and reproduction in roe deer (Capreolu.5 capreolus L.1. In: C. Wemmer @ditorI, BioIogy and Management of the Cervidae Front Royal, Virginia, l-5 August 1982, pp. 559-567. Smithsonian Institution Press, Washington, DC. Maillard, D. and Picard, J.F., 1987. Autumn and winter diets of roe deer (Capreolus cupreolus) in a calcicole beech forest, as determined by rumen content analysis. Gibier F&me Sauvage, 6: l-30 tin French). Maizeret, C. and Tran Namh Sung, 1984. Study of the Diet and Feeding Selectivity of Roe Deer in the Landes of Gascony (France). Gibier Faune Sauvage, 3: 63-103 (in French). Mattioli, L., Lovari, C., Mazzarone, V., Pedone, P. and Siemoni, N., 1992. Ecological ape& of the roe deer (Capreolus capreo1~s) population of the Casentinesi Forests National Park. In: F. Spitz, G. Janeau, G. Gonzalez and S. Aulagmer @ditors), Gngules/Ungulates, 91, 2-6 September 1991, Toulouse+ France pp. 527-530. Maublanc, M.L., 1986. Use of space by roe deer (Capreok~ capreolus) in an open environment Gibier Fatme Sauvage, 5: 297-3 I 1 tin French). Otis, D.L., Burnham, K.P., White, G.C. and Anderson, D.R., 1978. Statistical inference from capture data on closed animal populations. Wildl. Monogr., 62: 1- 135. Perzanowski, K., PradeI, A., Sikorski, M.D. and Mydian, J., 1982. Food resources for deer in Niepolomicka forest. Acta ‘Iheriol.,
27: 509-5
19.
Prior, R., 1968. The RIX Deer of Cranboume Chase. Oxfonf University Press, London. Prusaite, J., Blazys, A., Mickus, A. and Bluzma, P., 1973. Number dynamics and structure of the unhunted roe deer popmation. Lith. Acad. Sci., Ser. C, 62 I 15- 125 (in Russian). Pucek, Z., Bobek, B., Labudski, L., Milkowski, L., Morow, K. and Tomek, A., 1975. Estimates of density and number of ungulates. Pol. Ecol. Stud., 1: 121-135. Ratcliffe, P.R., 1987. The management of red deer in the commercial forests of Scotland related to pop&&on dynamics and habitat changes. PhD. Thesis, University of London, London. Rice, W.R. and Harder, J.D., 1977. Apphcation of multiple aeria1 sampling to a mark-recapture census of white-tailed deer. J, Wildl. Manage., 41: 197-206. Saez-Royuela. C. and Telleria, J.L,> 1991. Roe Deer (Capredus
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cupreoIus) Distribution in Central Spain. Folia Zool., m 37-4.5. Seber, G.A.F., 1982. The Estimation of Animal Abundance. Charles Griftin, London Staines, B.W., Welch, D., 1984. Habitat selection and impact of red deer and roe deer in a Sitka spruce plantation. Prcc. R. sot. Edin., 82: 303-319. Strangaard, H., 1%7. Reliability of the Petersen method tested on a roe deer population. J. Wildl. Manage. 3 1: 643-65 1. Strangaard, H., 1972. The roe deer population at Kalo and the factors regulating its size. Dan. Rev. Game Biol,, 7: l-205.
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Welch, D., Staines, B.W., Catt, D.C. and Scott, D., 1990. Habitat usage by red (Ceruus elaphus) and roe (Capreoh capreoh) deer in a Scottish Sitka spruce phuttation. J. Zool. (Load.), 22 1: 453-476. White, G.C. and Garrett, R.A., 1990. Analysis of Wildlife Radiotracking Data. Academic Press, London. Zejda, J. and Homolka, M., 1980. Habitat selection and population density of field roe deer (Cqreolas capreolud outside the growing season. Folia Zool., 29 107- 11.5.
Changes in roe deer (Cqwe~Zm capreohs L.) population density in response to forest habitat succession R.M.A. Gill a9* , A.L. Johnson ‘*‘, A. Francis cp2,K. Hiscocks ‘, A.J. Peacea a Foresiry
Commission Research Division, Alice Halt Lodge, Wreccleshum, Surrey, ’ 5 Orchard Way, Misterton, Crewkerne, Dorset, TAl8 8NN. UK ’ Low Knap, Halstock, Dorset, UK ’ 4 Francolin Close, Wooa%avenS Durban. 4001, South Africa
GUlO
4LH.
UK
Abstract In spite of several studies showing that roe deer typically achieve higher population densities in openings or younger forest stands, there do not appear to be any reporting the responseof a single population to forest habitat change. In this paper the results of a 25-year study of a roe deer population, which was not subject to significant levels of culling, predation or ungulate competition are presented.Following planting with conifers (which was mostly in 1961-621, the canopy cover increased, most mpidly between 8 and 15 years after planting. Ground vegetation cover was negatively correlated with canopy cover. The deer population increasedfrom 46 km-* to 76 km-* between 4 and 13 yearsafter planting, after which it declined sharply to 34 kin*. A significant negative cross-correlationwas found between conifer canopy cover and deer density with a lag of 6 years, indicating that the decline in deer numbers lagged behind the decline in browse supply. The rate of recruitment was correlated with the conifer canopy cover without any indication of a significant lag. The decline in cover of the main food plant species (bramble Rubus fiurkxx~~), was much greater than the decline in deer density, implying that the deer were forced to change their diet and perhaps also their patterns of habitat selection in responseto the change in habitat structure. Keywords:
Time-series; Population Iags; Mark-recapture; Habitat selection; Vegetation communities; Browsing; Diet
1. Introduction
It has long been recognised that deer populations are influenced by a regime of forest clearance and subsequent regeneration (Leopold, 1950; K&rig and Gossow, 197% Staines and Welch, 198% Ratcliffe, * Corresponding author. Tel: 44 1420 22255; fax 44 1420 23653.
’ Deceased. * Deceased.
1987). Clearing, whether natural or man-made, is typically followed by a pronounced increase in the availability of browse and cover which subsequently declines as the next tree canopy closes over (Halls and Alcaniz, 1968; Irwin and Peek, 1979; Doerr and Sandburg, 1986). Investigations of habitat selection by deer indicate that the use of different forest habitats corresponds broadly with differences in food plant biomass (Cibien and Semp&& 1989; Welch et al., 1990) and this appears to be the main reason why young stands,
0378- 1127/%/$15.00 Copyright 0 1996 Elsevier Science B.V. All rights reserved. I’ll SO378I 127(96)03807-8
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or forest rides or edges are used relatively more than older stands (Henry, 1981; Staines and Welch, 1984; Welch et al., 1990). Other studies, making use of pellet counts and cull data (Batcheler, 1960) or drive counts carried out in stands of varying age @ucek et al., 19751, have provided some evidence that roe deer populations will decline as the stand ages. Loudon (19871 reported that females shot from forest areas containing a high proportion of young forest stands were heavier and more fecund, despite higher deer densities in these areas. In spite of the evidence suggesting that roe and other deer species are affected by changes in forest structure, the authors are not aware of any long-term studies where the response of an ungulate population to marked habitat succession has been monitored in detail. Little is therefore known of how quickly the deer population respnds to habitat change, nor whether the change in deer density is proportional to the change in food plant biomass, or lagged some years behind as some authors suggest (Konig and Gossow, 1979). Further, it is not clear how diet and patterns of habitat selection are affected by the habitat succession. In this paper the results of a long-term study of a roe deer population inhabiting a small forest (149 ha) in southern England are reported. The study was started in the 1960s shortly after planting and continued for over 25 years, when the forest was in the pole stage, embracing periods of both very good and very poor habitat conditions.
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imum January temperatures at the nearest weather station were 7.6OC and 1.8OCrespectively, forI%& 1989. Approximately 75% of the woodland was cleared and re-planted between 1961 and 1970. mostly m 1961-62, leaving a few of the original broadleaved stands scattered mainly around the periphery. Most of the newly-planted trees were Norway spruce P&a abies, although several other coniferous species were used, a well as beech Fagus syluatka and oak Quercus robur, which were planted in small groups or in mixture with the conifers. Agricultural activities in the neighbouring fields were limited to permanent pasture or hay meadows. Investigations of ranging behaviour ~Bramley, 1970; authors’ data) indicated that deer made relatively little use of these fields for feeding and it is assumed that responses of the deer population are due ro changes in the woodland environment, not to changes in nearby farming practices. With the exception of 1968 when 15 roe deer were shot (Bramley, 1970), the population in the wood was only subjected to very occasional culling. No definite cases of predation were reported, aithough on three occasions dogs or foxes Vulpes wipes were found with the remains of kids. Dispersal away from the study area was limited primarily by the lack of adjacent woodland cover rather than physical barriers, although a nearby fenced railway line restricted movement in a northwesterly direction. 2.2, Assessment oj* vegetation changes
2. Methods 2.1. The study area
The study area included 149 ha of woodland (Chedington Woods), and adjacent farmland in Dorset, England (52’52’N, 2’43’W). These woods are situated in an area devoted to pastoral farming and therefore relatively isolated from nearby woodland and deer populations of comparable size, although one other wood of almost 100 ha lies 2 km to the northeast. The site covers predominantly northfacing terrain, 75-150 m above sea level, on poorly drained, base-rich soil and experiences an oceanic climate with mild winters. Mean maximum and min-
Tree canopy cover was assessed from a set of vertical aerial photographs, taken in June 1965, July 1967, June 1970, April 1973, September 1986 and May 1989. The scale of these photographs ranged from 1:7500 to 1: 12 000. In addition, a set of oblique aerial colour photographs taken in the summer of 1977 was also used. The study area was divided.into 89 smaller, relatively homogenous areas on the basis of sub-compartment boundaries or other distinguishable features, and the proportion of canopy cover was estimated from each photograph within each area. Making use of stereoscopic pairs of photographs and a X 10 magnification, the canopy cover was further subdivided into conifer or broadleaf and
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two height classes, namely trees approximately 2-5 m in height (referred to as ‘short’ trees) and those > 5 m tall. In the summer of 1989, the ground vegetation was surveyed in the main part of the wood. The woodland vegetation was stratified into four main types present at that time (rides, scrub, broadleaved stands and coniferous stands) and percentage cover of each species or species group was assessed in quadrats spaced at 10 m intervals along transects in each stratum (18 transects and 422 quadrats in total). Cover was assessedfor plants O-50 cm above ground in 1 m x 1 m quadrats and for those between 50 cm and 120 cm in 3 m X 3 m quadrats, positioned with a common northeastern comer. Each transect was started at a random location within the stratum. Along rides, quadrats were positioned alternately on the edge and in the centre of the ride. In 1971, Hosey (1974h Hosey (1981) investigated the diet of the rce deer and surveyed the ground vegetation in the study area, reporting the cover of two major species, bracken Pteridium aquilinum and bramble Rubus fi~ticosns. In the lowland parts of northwest Europe, these two species are generally found to represent an unpalatable and very palatable species respectively (Henry, 1978; Jackson, 1980; Hearney and Jennings, 1983; Diakite, 1983; Maizeret and Tran Namh Sung, 1984 Boisaubert et al., 1985; Maillard and Picard, 1987). In this study area bramble was found to be the single most important species in the diet, which ranged from 25% in June to 85% in February (Hosey, 1974; Hosey, 1981). Conifer needles, in contrast, formed only a minor component of the diet (approximately 3%) and although no comparisons with protected trees were made, browsing did not appear to limit growth of the conifers. 2.3. Capture and marking of deer
Kids less than a few weeks old were marked with numbered ear tags or ear flashes. Adults and kids more than 6 months old were caught in nets (Cockbum, 19791 and marked with both ear tags and neck collars. The collars were made of ‘Darvic’, a type of plastic that does not fade, and were usually fitted with one or two coloured tabs on each side, to ensure each deer had a unique colour combination. Deer captures were carried out every winter, usu-
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ally on two dates in March, from 1961 to 1989. Altogether, 335 animals were ear-tagged and 244 of these were also fitted with collars at some time during their lives. From time to time, loss of collars or ear tags was reported. In total, 17 deer were reported to lose a collar (all of them bucks) and three without collars lost both ear tags. However, collar loss was not considered a serious bias because a large proportion (15) had the collar replaced at a later date, and in many cases, identification was still possible in the interim by ear tags. In addition to the marked animals, a further 58 unmarked adults were recognisable from individual characteristics (antlers, coat colour and ear or rump tufts) and 164 unmarked kids were recognisable by association with a marked mother or sibling. 2.4. Estimates of deer population size and recruitment
Population estimates were calculated by two methods. From 1967 to 1980, regular counts of marked and unmarked animals were made in springtime, making it possible to estimate density using mark-resighting methods (a ‘Lincoln index’) (Seber, 1982; White and Garrott, 1990). Estimates for other periods were based on the minimum number known to be alive, calculated as the total number of marked and recognisable unmarked animals alive during each quarter between 1966-1989. Recruitment was estimated from the ratio of kids to females 2 years old or more, amongst the marked and recognisable unmarked animals each spring. Estimates based on mark-resighting were calculated using the joint hypergeometric maximum likelihood estimator (White and Garrott, 1990). This method requires several independent counts of marked and unmarked animals to be made and carries the assumption of population closure. The product of the hypergeometric likelihood function can be numerically opti@ed to estimate N. The estimator is the value of N that maxim&s the expression:
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The values in parentheses are binomial coefftcients e.g.
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were calculated on the area of woodland sampled, not the total study area. 2.5. Analysis of the response of deer density to vegeiation chunges
and ni and mi are the total number of animals and number of marked animals respectively, seen on occasion i, i = 2,. . . , k+ 1, and &l is the total number ?f marked animals in the population. Estimation of N was achieved using a SAS program Statistical Analysis Systems Institute Inc. program modified from White and Garrott ( 1990). Counts of the ratios of marked and unmarked animals were made in March and April, before the period of sub-adult dispersal, and were further limited to dates when the numbers of marked animals in the wood were, as far as known, constant. In an effort to ensure equal sightability and to minimise any possible bias due dependency between counts, estimates of population size were based on only the southern section of the wood, which comprixd 63% of the total area and connected to the rest of the wood by a narrow strip. This area was more thoroughly covered during capture attempts as well as on subsequent counting days and it was therefore possible to use a large sample of censuses (ranging from 14 to 36) to estimate density. Further, nearly all marked yearlings and adults using this area received collars, so identification did not have to rely on ear tags. Habitat conditions were similar in all parts of the study area. Visibility across the study area was excellent during the 1960s and early 1970s but subsequently deteriorated as the trees grew taller. This effect was, however, fairly uniform across the study area and the ride network, and many vantage points still provided good opportunities for observing deer. It is assumed that changes in visibility did not affect the ratio of marked to unmarked animals sighted. Observations of deer have been disregarded if the head and neck were not visible enough for any possible mark to be seen, or if they were seen to be marked but otherwise unidentifiable. In view of the fact that use of adjacent fields by deer was relatively minor in comparison with use of the woodland habitats, population density estimates
To identify any significant delayed response in deer density, the lagged cross-coflelations were calculated between deer density, recruitment and total conifer tree cover. In view of the fact that cross-correlations are affected by autocorrelation in each variable (Box and Newbold, 1971; Chatfield, 19&9), it was first necessary to remove the autocorrelation by fitting an ARIMA model and then calculating~the cross-correlation coefficients from the residuals. ARIMA model selection was based initially on inspection of the autocorrelation function of the residuals and then choosing the model with the minimum innovation variance. An ARIMA (1 ,O,O)model (with one autoregressive term) was selected for deer density and recruitment, and an ARIMA (1,1,4) model (one autoregressive, one differencing and four moving average terms) was selected for total conifer cover (Box and Jenkins, 1976). All models and cross correlations were estimated using GENSTAT (Genstat 5 Committee, 19931.
3. Results 3. I. Changes in tree cover The most important aspect of the vegetation change was clearly the increase in coniferous tree canopy cover, which represented almost 70% of the woodland area by 1989 (Fig. I). The total coniferous canopy cover changed most rapidly between 8 and 1.5 years after planting (1970-771, increasing from 4.3% to 48.1% of the woodland area in only 7 years. Change in the cover of ‘short’ trees was most rapid at this time, indicating that the woodland vegetation was progressing through the thicket stage during this period. The ‘pre-thicket’ stage, normally considered optimum habitat for roe deer, would have occurred between about 5 and 8 years after planting {1%7-701. In comparison with the conifer cover, the area of broadleaf cover remained relatively constant, at between 14% and 27% of the total.
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in ground vegetation
The results of the 1989 survey revealed that under mature conifer stands, vascular plants were almost entirely absent, except in the few canopy gaps (Table 1). A few herbs, ivy Hedera heZix and bramble were present under the mature broadleaved stands although here too, the cover was sparse in view of the preponderance of beech in the canopy. The only areas containing a significant ground vegetation were the patches of scrub woodland and the rides and other openings, such as the edges of roads and ponds. In these areas the vegetation was also more diverse: in total, 69 species were recorded in the quadrats, excluding grasses. However even here, the vegetation was dominated largely by grasses and pendulous sedge Carex pendula which as noted later, are not particularly important food plants for rm deer. A regression of total ground vegetation cover (V 1 on canopy cover revealed that both conif-
ii
i3
Fig. 2. Changes in the cover of bramble (black) and bracken (white) between 1971 and 1989. Vertical bars represent the difference (between 1971 and 1989) in proportion of the woodland area with high ( > 30%), medium (lo-30%). low ( < 10%) or no (0%) ground cover respectively.
erous (c) and deciduous (d) tree cover had a significant influence (V = 126.6 - 1.263~ - 0.589d, F = 128.9, 2,63 d.f., r* = 0.809, P < 0.0001). There was clearly a dramatic decline in understorey vegetation cover between 197 1, the date of the first survey, and 1989 (Fig. 2). In this assessment, the cover of bramble and bracken averaged approximately 23% and 21% respectively over the study area, in contrast to averages of 1.4% and 2.5% respectively for 1989. In the case of bramble, this represents at least a 16-fold reduction in cover. 3.3. Changes in deer popuZation size and recruitment
XEY
Broadleaf Broadleaf Cmlfer Conifer
(Short (Tall) Short) t Tall)
Fig. I. Changes in the proportion of tree canopy cover, expressed as a percentage of total woodland area (149 ha), for the years when aerial photographs are available. Short trees were estimated to be 2-5m in height; tall tnzes > Sm.
The estimates of population sixe in spring calculated by the joint hypergeometric method reveal marked year to year changes in density (Fig. 3). The population increased from 46 km-* in 1967 to 76 km-* in 1975 (between 5 and 14 years after planting) and then fell sharply to 34 km-* in 1979-80. A small decline is also evident in the late 1968 and
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early 1969, after a number of animals were shot in the study area (see Bramley, 1970). The confidence intervals reveal that the population in 1975 and 1976 was significantly greater than in 1967, 1%9, 197 1 and also in the years after 1977. The population remained low during the 1980s. although some increase was evident after 1984. In view of the fact that some unmarked deer could be recognised and not all were seen during the census period, the minimum number known to be alive was occasion-
88 (19%)
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ally greater than the lower confidence interval of the estimate. Estimates made from the joint hypergeometric maximum likelihood method were closely cormlated with the minimum numbers known to be alive for the years 1967-80 (constant = 2.819, coefficient = 1.073, F = 147.5, d.f.= 12; r2 = 0.925; P < O.OOOl~,as well as the numbers marked ~constant = -0.376, coefficient = 1.361, F = 101.1, d.f; = 12, t-‘= 0.894, P < 0.0001). This suggests that the
Table 1 The species composition of vegetation up to 1.2 m above ground in 1989 Grasses
Bare ground Car.2
pet&la
Other species Mosses Mercuralis perennis Pteridium aquilinum Rubus endular Crateagus monogyna Pulicaria dysenterica Glechoma hederacea Equisetwn arvense Vrtica dioica Prunus spinosa Corylus avellana Lotus corniculatw Juncus efisus Mentha arvensis Potennlla repens Hedera helix Primula veris Ranunculus sp. Leon&on hispidus Circaea lutetiana Betonica ojicinalis Lonicera periclymenum Plantago lanceolata Geranium robertianum Alnus glutinosa Frcwinus excelsior Tr$olium sp.
Carexjlacca Eupatorium cannabiman Euphorbia amygdalxndes Ilex aquifolium Potentilla anserina
Rides and scrub (30 ha) 27.0 20.8 13.0 12.7 9.2 7.2 6.2 5.7 3.7 3.7 3.5 2.8 2.6 2.4 2.1 1.5 1.5 1.4 I.4 1.1 1.1 1.0 I .o 0.9 0.9 0.8 0.8 0.8 0.8 0.7 0.7 0.7 0.6 0.4 0.3 0.3
Figures represent mean percent cover in each habitat type.
Broadleaf stands ( 16 ha)
Conifer stands @3Zjha)
5.3 52.2 5.2 4.9 24.0 4.3 0.2 1.6 0.3
0.6 61.9 1.9 1.8 31.0 0.2 0.7 0. I 0.6
0.9 0.1
1.2
0.7
2.1
0.4 0.2
1.0 0.1
0.8
2.2
0.4
0.3 0.3
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marked and known unmarked animals usually formed the bulk of the population and could be used as a correlate of total density for the years 1982-1989 when Lincoln indices could not be calculated. The sharp peaks in population size calculated from the minimum number alive (Fig. 3) are mainly due to the annual birth pulses and reveal a general trend from high to low rates of recruitment as canopy cover closed over. Recruitment rate was highest in 1968 at 1.36 kids doe- ‘, but averaged 0.83 between 1970-74 and only 0.27 between 1975 and 1983, before increasing slightly to 0.48 between 1984-88. Recruitment was negatively correlated to the total conifer canopy cover (F = 41.13, 1,21 d.f., r* = 0.662, P < 0.001). 3.4. Response of the deer population to forest habitat change
The results of the cross correlation analyses revealed that total conifer cover was negatively correlated with deer density with a lag of 6 years (rb = -0.517, P < 0.05, Fig. 4). This indicates that deer numbers were high approximately 6 years after es-
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88 (1996~ 31-41
-
0.40.3 -
0 0
1.2-.o tJ.10.0
37
2
0.
0
l
m
430
-0.1-
u*.
-0.2-
-
- o".
-0.3j
”
CJ
0.
~oo.oe”~e 0.
0
l 0
Fig. 4. Cross conelation coefftcients calculated for deer density (solid points) and recruitment (open circles), each lagged O-20 years against total conifer cover. Coefficients were calculated on the residuals after first removing the autocorrelation in each variable. Points above or below the dashed lines indicate significant cross-conelation (p < 0.05).
tablishment, when tree cover is very sparse and likewise, density was low a similar period after conifer tree cover was high, during the late thicket phase. The was no significant lag in response of recruitment to changes in conifer cover.
4. Discussion 80
4.1. Density estimates
70 60 SO 40 30 20
IO-666677777777776~68~~~~~~9
67B90123456789012.34567890 YEAR
Fig. 3. Changes in population density (deer km-* 1 1966-89. Solid circles and associated vertical bars represent estimates and 95% contidence intervals calculated by tbe joint hypergeometric maximum likelihood method (White and Garrett, 1990). The continuous line represents the density based on the minimum number known to be ushtg the main study area, htcluding both marked and unmarked animals. The dashed line is the total number of marked animals only.
Previous attempts to use mark-recapture methods to obtain estimates of population density have reported the difficulties of complying with all of the conditions (Seber, 1982). These include no loss of marks, no emigration or immigration, equal sightability of all animals and that each census should be independent. Although complete compliance with all of these conditions was not possible, the effect of any bias on the estimate is limited when a high percentage of the population is marked (Strangaard, 1%7). In this study, the proportion marked (of the minimum number alive) ranged from 64% in 1966 to 89% in 1976, remaining above 78% in most years (Fig. 3). Unequal sightability, a common problem with a relatively sedentary species, is usually reported to yield under-estimates (Rice and Harder,
38
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1977; Otis et al., 1978; Bartmann et al,, 1987). Thus if any bias did occur, it is likely to be towards a slight under-estimate. In comparison with figures published for other roe deer populations, the density of 76 kmm2 in 1975 is clearly very high. Estimates reported from a number of other localities in Europe extend up to only 65.0 km-* (Andersen, 1953; Prior, 1968; Strangaard, 1972; Prusaite et al., 1973; Pucek et al., 1975; Fruzinski and Labudski, 1982; Bideau et al., 1992; Boutin et al., 19921, typically with lower densites (7.0-17.0 km-*) in farmland habitats (Zejda and Homolka, 1980; Kaluzinski, 1982; Maublanc, 1986; Denis, 1992) or where wolves Canis lupus are present (0.7-19.0 km-*; Pucek et al., 1975; SaezRoyuela and Telleria, 1991; Danilkin et al., 1992; Danilkin, 1992; Mattioli et al., 1992; Jedrzejewski et al., 1992). However, none of these studies aplxar to have reported densities from forests almost entirely within a favourable stage of habitat succession and there is no reason to believe that the population densities of 50-100 km-* are not commonplace where roe deer occupy good habitat and are also free from competition, severe winter weather and a significant level of shooting or predation. 4.2. Changes in habitat
Measurements of light intensity have shown that approximately 95% of solar radiation and 99% of light in the visible wavelengths is absorbed before reaching the ground in pole-stage Norway spruce stands (Brasseur and de Sloover, 19731. The reduction in grotmd vegetation biomass between planting and mid-rotation is understandably, therefore, substantial. The 16fold reduction in the cover of bramble recorded in this study exceeds that reported in many other comparisons of understorey biomass between shaded and unshaded stands, although still within the range of recorded variability (Halls and Alcaniz, 1%8; Perzanowski et al., 1982; Doerr and Sandburg, 1986). Light attenuation by an even-aged spruce canopy is so efficient that almost no vascular plants survive at ground level except under gaps or stand edges. Besides the effect of shade, the species composition of the vegetation at the end of the study pro-
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vided strong indications that the deer-themseives also had a marked impact on the vegetation. Herbaceous species that were common in the diet m 1971 @‘Xfolium sp., Potentilla sp., meadowsweet Eupatorium cannabinum, Plantago sp., Rumex sp. and hogweed Heracleum spondylium) formed only a very small part of the vegetation cover in i989. Instead, species that are known to be avoided by roe deer, including pendulous sedge Carex pendula, dog’s mercury Mercuralis perennis, ground ivy Glechoma hederacea, fleabane Pulicaria dysenterica, horsetails Equisetum arvense and mint Mentha arvensis, were relatively abundant. Many of these species are known to be toxic to other ungulates (Cooper and Johnson, 19841, which may explain why they appear to be unpalatable to roe deer. The fact that bramble decreased in cover more than bracken (another unpalatable species) between 1971 and 1989 also suggests that browsing, in addition to shade, was depleting the abundance of food plants. 4.3. Response of the roe deer population succession
to habitut
These results reveal that deer numbers responded dramatically, although with a distinct lag, to changes in coniferous canopy cover. Numbers increased while tree cover was sparse, only peaking when conifer cover reached approximately 40% of the woodland area, but then declined rapidly. For a brief period (1970-751, both deer density and canopy cover were increasing together. Given that the ground vegetation was so strongly suppressed by the growth of the canopy, this confirms that the deer population increased temporarily while food availability declined. When the population levelled after canopy closure, density remained approximately 25-40% of the highest density. This indicates that density was not reduced as much as the ground vegetation cover or the main food plant species, bramble, although recruitment rates remained low at this time, perhaps as a result of reduced food availability. The main reason for the lag appears to be because recruitment was more directly sensitive to changes in the ground vegetation than population density. The initial decline in recruitment was not sufficient to prevent a continued but gradual increase in density.
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In view of the fact that approximately 69% of juvenile growth is completed by the end of the first winter, it is not surprising that recruitment rates were so closely correlated with year to year changes in canopy cover and therefore presumably also changes in food availability. Amongst ungulates in general, juvenile survival is typically lower than adult survival (Caughley, 1966; Gaillard et al., 19931, as well as more sensitive to environmental conditions (Glutton-Brock et al., 1982). The period of low recruitment was also associated with delayed birth dates, reduced weight gain in kids and poor kid survival (Gill, 1994). In addition to the effect of tree canopy shade on ground vegetation, other factors, such as weather or shelter may have contributed to the lagged response in density. The young conifers would have provided some cover that may have partly compensated for a reduction in food availability. However, with a mild winter climate, the beneficial effect of shelter is not likely to be marked. The lag in response to habitat change has a number of implications for the relationship of the deer to their habitat. In particular, it suggests that competition for food would intensify as availability is restricted and that density-dependent responses in tbe deer population would be most acute at this time. It is also likely that changes in diet, habitat use, and behaviour occur at this time. Although the timing of changes in the ground vegetation community was not monitored, it is likely that these changes are also most acute as canopy closure restricts food availability. The decline of the most palatable species and damage to tree seedlings, where they remain, may accelerate at this time, indicating that regeneration will be most difficult in forests containing extensive areas of pole or mature stage trees and only very small or infrequent openings. The response of a deer population to forest habitat change is therefore more complex than a simple change in density. Changes in performance are also involved, and very likely also changes in diet, habitat use, as well as ground vegetation composition. At any moment in time, the relationship between deer and their habitat will depend on the sequence of forest and deer population changes, not merely current conditions.
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39
Acknowledgements We would like to thank J. Rowe and Dr. P. Ratcliffe for help with organising this project; F. Guinness, G. Jessop, helped with fieldwork P. Lewis, R. Prior, Lt. Col. J. Cockburn, H. Pepper, B. Maybe, and many others for catching deer; E. Colyer helped with aerial photo interpretation. Dr. S.D. Albon, Prof. T.H. Clutton-Brock and an anonymous referee gave helpful comments on earlier versions of this work.
References Andersen, J., 1953. Analysis of the Danish roe deer population based on the extermination of the total stock. Dan. Rev. Game Biol., 2: 127-1.55. Bartmann, R.M., White., G.C., Carpenter, L.H. and Gatrott, R.A., 1987. Aerial mark-recapturn estimates of confined mule deer in pinyon-juniper wocdland. J. Wildl. Manage., 51: 41-46. Batcheler, C.L., 1960. A study of the relations between roe, red and fallow deer, with special reference to Dmmmond Hill forest, Scotland. J. Anim. Ecol. 29: 375-384. Bideau, E., Vincent, J.P., Gerard, J.F. and Maublanc, M.L., 1992. Influence of sex and age on space occupation by roe deer (Capreohs capreohs L.J. Jn F. Spitz, G. Janeau, G. Gonzalez and S. Aulagnier (Editors), Gngules/Ungulates, 91, 2-6 September 1991, Toulouse, France, pp. 263-266. Boisaubert, B., Maillard, D. and Maim, M.H., 1985. Etude du regime alimentaire du Chevreuil en for& de Haye. XVEth Congress of the International Game Biologists. BNS~&, 17-21 September 1985, pp. 421-429. Boutin, J.M., Gaillard, J.M., Delorme, D., Van Laere, G., Doitran, B.B. and Bodani, S., 1992. Home ranges and movements of roe deer fawns (Capreolus capreolus L.). In: F, Spitz, G. Janeau, G. Gonzalez and S. Aulagnier (Editors), Gngules/Ungulates, 91, 2-6 September 1991, Toulouse, France, pp. 277278. Box, G.E.P. and Jenkms, G.M., 1976. Time Series Analysis: Forecasting and Control. Holden-Day, San Francisco, CA. Box, G.E.P. and Newbold, P., 1971. Some comments on a paper of Coen, Gomme and Kendall. J. R. Stat. See., Ser. A. 1341 229-240. Bramley, P.S., 1970. Territoriality and reproductive behaviour of roe deer. J. Reprod. FertiI., Suppl. I I: 43-70. Brasseur, F. and de Sloover, J.R., 1973. Interception of total solar radiation an visible light in two forest communities in the Belgian Haute-Ardenne. Bull. Sot. R. Bot. Belg., 106~ 219236. Caughley, G., 1966. Mortality patterns in mammals. Ecology, 47: 906-918, Chatfield, C., 1989. The Analysis of Time Series-an hnroduction. Chapman and Hall, London.
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Cibien, C. and Sempeti, A., 1989. Food availability as a factor in habitat use by rce deer. Acta lheriol., 34 I 1I - 124. Clutton-Brock, T.H. Guinness, F.E. and Albon, S.D., 1982. Red Deer: Behaviour and Ecology of Two Sexes. University of Chicago Press, 377 pp. Cockbum, R.H.A., 1979. Catching roe deer alive in long nets. I&r, 3: 434-439. Cooper, M.R. and Johnson, A.W., 1984. Poisonous plants in Britain and their effects on animals and man. Ministry of Agriculture, Fisheries and Food, HMSO, London. Danilkin, A.A., 1992. Population structure. In: V.E. Sokolov (Editor), European and Siberian Roe Deer. Nauka, Moscow, pp. ItlO- 184 (in Russianl. Danilkin, A.A., Dannan, YuA. and Minayev, A.N., 1992. The seasonal migrations of a Siberian roe deer population. Rev. Ecol. (Terre Vie). 47: 231-243. Denis, M., 1992. Some data on a high density population of field roe deer. In: F. Spitz, G. Janeau, Cl. Gonzalez and S. Aulagnier @ditors). Gngules/Ungulates, 91, Toulouse, France, 2-6 September 1991, pp. 519-521. Diakite, M.M., 1983. A study of the winter diet of roe deer in Alice Holt forest. MSc. Thesis, University of London, London. Doerr, J.G. and Sandburg, N.H., 1986. Effects of prwommercial thinning on understorey vegetation and deer habitat utilization on Big Level island in Southeast Alaska. For. Sci., 32: 10921095. Fruzinski, B. and Labudski, L., 1982. Demographic processes in a forest roe deer population. Acta ‘lheriol., 27: 365-375. Gaillard, J.M., Delorme, D., Boutin, J.M., Van Laere, G., Boisaubert, B. and Pmdel, R., 1993. Roe deer survival patterns -a comparative analysis of contrasting populations. J. Anim. Ecol., 62 778-791. Cienstat 5 Committee, 1993. Genstatrr” 5, Release 3, Reference Manual. Clarendon Press, Oxford. Gill, R.M.A., 1994. The population dynamics of roe deer (Capreolus capreo/us L.1 in relation to forest habitat succession. PhD. Thesis, Open University, Milton Keynes, 191 pp. Halls, L.K. and Alcaniz, R., 1%8. Browse plants yield best in forest openings. J. Wild]. Manage., 32: 185-186. Heamey, A.W. and Jemings, T.J., 1983. Annual foods of the red deer (Ceruus elqhus) and the roe deer (Capreolus cupreolus) in the east of England. J. Zool. (Land.), 201: 565-570. Henry, B.A.M., 1978. Diet of roe deer in an English conifer forest. J. Wildl. Manage., 42: 937-940. Henry, B.A.M., 1981. Dlsbibution patterns of roe deer (Capreolus capreolus) related to the availability of food and cover. J. Zool. (Land.), 194 271-275. Hosey, G.R., 1974. The food and feeding ecology of the roe deer (Cupreolus capreolus). PhD. Thesis, University of Manchester, Manchester. Hosey, G.R., 1981. Ammal foods of the roe deer (Capreolus capreolus) in the south of England. J. ZooI. (Lond.1, 42: 276-278. Irwin, L.L. and Peek, J.M., 1979. Shrub production and biomass trends following five logging treatments within the cedarhemlock zone of northern Idaho. For. Sci., 25: 415-426.
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Jackson, J., 1980. The annual diet of the roe deer (Ckpreolus capreolud in dre New Forest, Hampahlre, as determined by rumen content analysis. J. ZooI. (Lo&, 192: 71-83. Jedrzejewski, W., Jedtzejewska, B., Gkarma, H. and Rupmcht, A.L., 1992. Wolf predation and snow cover as mortality factors in the ungulate commmtity of the BiaIowieza National Park, Poland. Gecologia, % 27-36. Kaluzinski, J., 1982. Dynamics and structure of a tleld roe deer population. Acta Theriol., 27 385-408. K&rig, E. and Gossow, H., 1979. Even-aged stat-idsas habitat for deer in Central Europe. In: E.D. Fotd, DC. Malcolm and J. Atterson @litor& The Ecology of Even-aged Pbmtritions. Institute of Terrestrial Ecology, Cambridge, pp. 429-451. Leopold, AS., 1950. Deer in relation to plant successions.J. For., 48: 67.5-678. Loudon, A.S.I., 1987. The influence of forest habitat structure on growth, body size and reproduction in roe deer (Capreolu.5 capreolus L.1. In: C. Wemmer @ditorI, BioIogy and Management of the Cervidae Front Royal, Virginia, l-5 August 1982, pp. 559-567. Smithsonian Institution Press, Washington, DC. Maillard, D. and Picard, J.F., 1987. Autumn and winter diets of roe deer (Capreolus cupreolus) in a calcicole beech forest, as determined by rumen content analysis. Gibier F&me Sauvage, 6: l-30 tin French). Maizeret, C. and Tran Namh Sung, 1984. Study of the Diet and Feeding Selectivity of Roe Deer in the Landes of Gascony (France). Gibier Faune Sauvage, 3: 63-103 (in French). Mattioli, L., Lovari, C., Mazzarone, V., Pedone, P. and Siemoni, N., 1992. Ecological ape& of the roe deer (Capreolus capreo1~s) population of the Casentinesi Forests National Park. In: F. Spitz, G. Janeau, G. Gonzalez and S. Aulagmer @ditors), Gngules/Ungulates, 91, 2-6 September 1991, Toulouse+ France pp. 527-530. Maublanc, M.L., 1986. Use of space by roe deer (Capreok~ capreolus) in an open environment Gibier Fatme Sauvage, 5: 297-3 I 1 tin French). Otis, D.L., Burnham, K.P., White, G.C. and Anderson, D.R., 1978. Statistical inference from capture data on closed animal populations. Wildl. Monogr., 62: 1- 135. Perzanowski, K., PradeI, A., Sikorski, M.D. and Mydian, J., 1982. Food resources for deer in Niepolomicka forest. Acta ‘Iheriol.,
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Prior, R., 1968. The RIX Deer of Cranboume Chase. Oxfonf University Press, London. Prusaite, J., Blazys, A., Mickus, A. and Bluzma, P., 1973. Number dynamics and structure of the unhunted roe deer popmation. Lith. Acad. Sci., Ser. C, 62 I 15- 125 (in Russian). Pucek, Z., Bobek, B., Labudski, L., Milkowski, L., Morow, K. and Tomek, A., 1975. Estimates of density and number of ungulates. Pol. Ecol. Stud., 1: 121-135. Ratcliffe, P.R., 1987. The management of red deer in the commercial forests of Scotland related to pop&&on dynamics and habitat changes. PhD. Thesis, University of London, London. Rice, W.R. and Harder, J.D., 1977. Apphcation of multiple aeria1 sampling to a mark-recapture census of white-tailed deer. J, Wildl. Manage., 41: 197-206. Saez-Royuela. C. and Telleria, J.L,> 1991. Roe Deer (Capredus
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cupreoIus) Distribution in Central Spain. Folia Zool., m 37-4.5. Seber, G.A.F., 1982. The Estimation of Animal Abundance. Charles Griftin, London Staines, B.W., Welch, D., 1984. Habitat selection and impact of red deer and roe deer in a Sitka spruce plantation. Prcc. R. sot. Edin., 82: 303-319. Strangaard, H., 1%7. Reliability of the Petersen method tested on a roe deer population. J. Wildl. Manage. 3 1: 643-65 1. Strangaard, H., 1972. The roe deer population at Kalo and the factors regulating its size. Dan. Rev. Game Biol,, 7: l-205.
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Welch, D., Staines, B.W., Catt, D.C. and Scott, D., 1990. Habitat usage by red (Ceruus elaphus) and roe (Capreoh capreoh) deer in a Scottish Sitka spruce phuttation. J. Zool. (Load.), 22 1: 453-476. White, G.C. and Garrett, R.A., 1990. Analysis of Wildlife Radiotracking Data. Academic Press, London. Zejda, J. and Homolka, M., 1980. Habitat selection and population density of field roe deer (Cqreolas capreolud outside the growing season. Folia Zool., 29 107- 11.5.