- Top of page
- Materials and methods
Population fluctuations of animals are explained through a combination of intrinsic and extrinsic mechanisms such as the demography of the population and stochastic environmental effects (Leirs et al. 1997; Coulson et al. 2001). Long-term population studies are often based on data from harvested populations, for example Canada lynx (Lynx canadensis, Kendall, Prendergast & Bjørnstad 1998; Stenseth et al. 1999). Harvesting is often assumed to be random, simply another source of mortality which can reduce population size. However, including the effect of harvesting in studies of population dynamics is important if we are to understand population dynamics of exploited species, as harvesting can perturb dynamics and create population fluctuations (Jonzén, Ripa & Lundberg 2002; Jonzén et al. 2003; Cameron & Benton 2004). Furthermore, many populations currently face high anthropogenic off-takes leading to overharvesting and extinction (IUCN Red List 2007). Therefore including harvesting in ecological studies can foster new insight into population dynamics and can help in the management of exploited populations (Lande, Saether & Engen 1997, 2003).
Hunting often purposely targets a specific age, sex or size class (e.g. in trophy hunting, fisheries). Evidence for the short and long term effects of this practice on the phenotype and life-history of vertebrates (Coltman et al. 2003; Hutchings 2005; Garel et al. 2007), and on the demographic structure, and therefore on the growth rate, of a population can be significant (Ginsberg & Milner-Gulland 1994; Cameron & Benton 2004; Hutchings 2005; Milner, Nilsen & Andreassen 2007). Most studies on hunting selectivity compare different hunting strategies (Martinez et al. 2005; Mysterud, Tryjanowski & Panek 2006) or harvested and nonharvested areas (Coltman et al. 2003); they do not, however, compare the age and sex structure of the bag with the population before harvesting to assess susceptibility to shooting according to age, sex and density.
While the effects of selective harvesting in trophy hunting and fisheries are relatively well studied (reviews in Festa-Bianchet 2003; Coltman 2008; Hutchings & Fraser 2008), in monomorphic species it is often assumed that shooting is unselective, as hunters cannot consciously select during shooting. However, in the monomorphic Canada goose (Branta canadensis), young of the year are more vulnerable to harvesting than older individuals (Chapman, Henny & Wight 1969; Grieb 1970; Mowbray et al. 2002). Hörnell-Willebrand et al. (2006) and Hudson (1985, 1986) addressed unintentional harvesting selectivity in two monomorphic grouse species, the willow grouse Lagopus lagopus (Linnaeus, 1758) and the red grouse L. lagopus scoticus (Latham, 1787), respectively. Adults of both sexes and adult males were over-represented in the bag when compared with counts before the hunting season respectively. The willow grouse study made the assumption that the population consisted of equal numbers of males and females and both studies did not link selectivity to any other covariates important for the study of population dynamics and management, e.g. density or timing of the season.
At high grouse densities, we predict that during driven shooting, old males will return to their territories rather than flying over the line of hunters. This is due to territoriality or high parasite load, both as consequences of increased density and of aggressiveness. In contrast, we expect that young grouse are more likely to cross the line of hunters at high grouse densities because they have not been able to secure a territory and do not suffer from high parasite loads (reduced mobility). Therefore, we predict that with increasing grouse numbers more young grouse are shot than expected from the counts. Conversely, old males escape being shot by returning to their territories before they reach the line of hunters. We also expect that shooting selectivity will become more biased towards females later in the season when males have invested heavily in territorial behaviour and may be more reluctant to leave their territory.
In this study, we test the above predictions by comparing the age–sex ratios of birds shot at different times during the season and at different densities, with the population composition estimated from counts made just before shooting. We analysed data on grouse shooting using hierarchical mixed effects models to be able to decompose the total variation of the data into different spatial scales (Börger et al. 2006a,b; Sims et al. 2006). Using this method, we investigate the effect of management units (moors and drives within moors) on harvesting selectivity and the correlation of number of grouse shot and grouse density.
- Top of page
- Materials and methods
In this study, we predicted that with increasing grouse numbers more young grouse are shot than expected from the counts. We have been able to show that susceptibility of young grouse to shooting increased with bag size, which is in agreement with our first hypothesis. At low bag numbers the relative young-old ratio was below zero indicating that more old grouse were shot than expected from the counts before shooting (Fig. 2). We found support for our second hypothesis that old males were more susceptible to shooting at early shooting events. We also showed that old males relative to old females increased in their susceptibility to shooting with bag size (Fig. 3).
Males fly over the line of hunters as singletons while females tend to fly in family groups and single birds are more likely to be shot (Hudson 1986). Old males establish territories earlier than young of the year that are still organized in family groups (Hudson 1986) and this might be more pronounced at high densities when aggressiveness and territorial behaviour is high (Moss et al. 1996). In addition, in low density years, red grouse nests hatch later (Jenkins et al. 1967) and thus young of the year have less flight ability at the start of the shooting season and are less likely to reach the line of hunters because of the exhausting effect of flying long distances. This might explain the finding that old birds are less likely to be shot at high densities (Fig. 2). High off-takes of old males and increased territorial behaviour might explain the low proportion of old males and the higher proportion of females in the bag later in the shooting season. There was no direct effect of date on the susceptibility of shooting of different age- and sex-classes, but the first shooting event was always before the second and that before the third/fourth, so there might be an interaction of timing of the season and shooting per se that affects the behaviour of red grouse during shooting. When males pass the line of hunters, they do so as singletons and are therefore more susceptible to shooting than old females particularly at high density when territorial behaviour is likely to be more important (Fig. 3). Detailed observations of marked animals during the shooting events are required to clarify behavioural mechanisms behind the observed results.
It could be hypothesized that the age composition of the bag would not be expected to reflect the composition of the population at the July count due to differential mortality rates of young and old grouse or of males and females within the old age class between the time of counting and the shooting season. However, the time period between counts (throughout July) and data collection (mid-August–end of September) was short and mortality in red grouse during this period has been shown to be low for both young and old birds (Hudson, Newborn & Robertson 1997). Also, Smith & Willebrand (1999) did not find any differences in mortality between male and female willow grouse during the period July until September. Results in this study depend on unbiased July counts of the age- and sex- ratio and density of the population. One could hypothesize that the July counts might be biased and be confounded by similar variables as the bag data. However, the grouse count methodology used in this study has been shown to deliver reliable estimates of the age and sex ratio and the density of the population (Jenkins et al. 1963).
This study applied mixed effects models to the data to investigate the effect of variation in spatial scale on the shooting data. The comparison of count and bag data showed considerable variation at the moor and drive level (Table 3). These results suggest that the management units moor and drive have significant influence on the number of grouse shot per area at a given density. Variation might be added by differences in harvest targets between moors and drives set by gamekeepers and moor owners and by the hunter quality: significantly, more grouse shot at a given density with experienced hunters. Less variation due to moor and drive was found when fitting mixed effects models to the relative age and sex ratio. This indicates that the smallest scale possible (individual drives) was appropriate for the analysis.
Hudson (1985, 1986) studied the harvest rates of red grouse on the scale of the entire moor and found that the off-take was between 20% and 48% at the end of the season and that the harvest rate increased with the number of grouse counted in July. In this study, the harvest rates were calculated to have a mean of 16% (range 8–32%) for the first shooting event. There was no change in harvest rate with the number of grouse counted in July, suggesting that the increase in harvest rate observed in the study by Hudson (1985, 1986) for an entire moor depends on the number of times an area was shot and probably the overall number of areas that are shot.
The ratios of young-to-old and female-to-male birds were collected from counts in the same areas as the shooting took place and this allowed for a direct comparison of the structure of the population with the age and sex ratio of the bag. Cattadori et al. (2003) showed that total bag numbers for a whole moor for one season correlate well with actual population numbers estimated by the same counting method used in this study. A comparable trend was also shown in this study but on a smaller scale where the number of grouse shot in a single shooting event (drive) correlated consistently with grouse numbers obtained by counts in the same area before shooting (Fig. 1). Our study further suggests that to study shooting susceptibility, the number of grouse shot per square kilometre on a single drive is a better surrogate than the July density because it reflects density at the actual shooting event. The July density would overestimate density at the current shooting event if a considerable number of grouse were shot earlier in the season.
The ratio of juveniles to adults in the bag is a common and cost-effective method for estimating productivity in a given year. Flanders-Wanner, White & McDaniel (2004) found no trend in age ratio with time in the shooting season in a study on sharp-tailed grouse Tympanuchus phasianellus jamesi (Lincoln, 1917) and greater prairie chicken Tympanuchus cupido pinnatus (Linnaeus, 1758), which validated the use of the age-ratio method for these species. However, Hörnell-Willebrand et al. (2006) showed that this method is not useful for willow grouse in Sweden and Norway, because the proportion of juveniles is generally underestimated in the bag. Considerable variation in the young-to-old estimate has been observed in the same study and the proportion of juveniles seems to be higher in the bag in years with low breeding success. This study on red grouse demonstrates differences in the age-ratio and the adult sex ratio between the count and the bag, the existence of an interaction with density, and an increase within the shooting season of the ratio of old females in the bag. Therefore, harvest data need to be treated with great caution as a proxy for the underlying population structure. Age and sex ratios obtained from harvest data need to be checked against count data collected before the harvesting season at a range of population densities before considering them as proxies for population productivity.
In a variable environment, detailed knowledge of the population size and structure are important, as uncertainty increases the chance of overexploitation and local extinction. Hauser, Pople & Possingham (2006) showed that in exceptional years (e.g. extreme weather) the monitoring effort to estimate population size has to increase, so that the management strategy can be adjusted appropriately. However, it is not just the effort put into monitoring that is important. The data that are collected determines whether the difference in population size and structure is detected by the monitoring regime. Katzner, Milner-Gulland & Bragin (2007) demonstrate that the predictive power of monitoring for population size and growth depends on the life stage that is monitored. This stresses the importance of monitoring important age and sex classes. For red grouse, the sex of old birds might be crucial to monitor because the overall assumption of equal numbers of males and females in the population might not be valid due to selective shooting as shown in this study and through the acknowledgement of the sex differences in dispersal distances (Warren & Baines 2007). A skewed sex ratio might decrease population size and harvest yield in a monogamous species where equal numbers of females and males are needed to ensure reproduction. Therefore, monitoring adult sex ratio in spring before the start of the breeding season might facilitate a first estimate of the expected number of young of the year and thus of the harvestable population.
The results of this study encourage further speculation and hypotheses regarding the effects of shooting on red grouse population fluctuations. The study showed that at high bag numbers, used as a proxy for population density, young grouse are more susceptible to shooting than old grouse. Consequently, shooting can bias the population structure towards old birds when population density is high. Given that old grouse harbour more parasites (Hudson et al. 1992), that parasites are accumulated at high grouse densities and that parasites reduce over winter survival (Hudson et al. 1992; Moss et al. 1993) and can generate population fluctuations (Hudson et al. 1998), shooting might therefore add to population crashes by leaving old, highly parasitized birds in the population at peak density. Thus shooting might be a factor in creating rather than dampening red grouse cycles. Theoretically, in a highly fluctuating species with high off-takes like red grouse, harvesting might be expected to dampen cycles. Support for the dampening effect of harvesting comes from experimental work by Watson et al. (1988) and Moss et al. (1996) who showed that experimental removal of old males prevented a population decline. In contrast, our study showed that shooting selected for young birds at high density and therefore did not remove old territorial males. Indeed, that harvesting can create cycles has already been shown in a theoretical study on willow grouse (Jonzén et al. 2003) and in an empirical study on moose Alces alces (Linnaeus, 1758). The mean age of adult females increased because of the selective harvest of young moose. This led to an increase in productivity, which is closely related to age in moose. The mean age then decreased after years of high recruitment, and so productivity dropped, thus generating cycles (Solberg et al. 1999). Selective harvesting for large size can also magnify population fluctuations in fish due to changes in demographic parameters and instability of the population dynamics (Anderson et al. 2008). Hudson & Dobson (2001) found that harvesting apparently did not dampen red grouse cycles, and our findings may now provide an explanation for this contrast between theory and empirical data.