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- Materials and methods
1. We contrast the value of four different models to predict variation in territory size as follows: resource density (the ideal free distribution), population density, group size and intruder pressure (relative resource-holding potential). In the framework of the resource dispersion hypothesis, we test the effect of resource abundance and spatial variation in resource distribution on the age/sex composition of social groups.
2. We explore these drivers of territory size and group size/composition in Ethiopian wolves Canis simensis in the Bale Mountains, Ethiopia, using fine-scale distribution maps of their major prey species based on satellite-derived vegetation maps.
3. The number of adult males is correlated with territory size, while prey density, wolf population density and intruder pressure are not associated with territory size. On average, each additional adult male increases territory size by 1·18 km2.
4. Prey abundance increases with territory size (average biomass accumulation of 6·5 kg km−2), and larger territories provide greater per capita access to prime foraging habitat and prey.
5. The age/sex composition of wolf packs is more closely related to territory quality than territory size. Subordinate adult females are more likely to be present in territories with greater proportions of prime giant molerat Tachyoryctes macrocephalus habitat (i.e. >80% of Web Valley territories and >20% in Sanetti/Morebawa), and more yearlings (aged 12–23 months) occur in territories with greater overall prey biomass.
6. Wolf packs with restricted access to good foraging habitat tend to defend more exclusive territories, having a lower degree of overlap with neighbouring packs.
7. The greater per capita access to prey in large groups suggests a strong evolutionary advantage of collaborative territorial defence in this species, although the relative costs of territorial expansion vs. exclusion depend upon the spatial distribution of resources. We propose a model whereby territory size is determined by the number of adult males, with the presence of subordinate females and yearlings dependent on the quality of habitat, and the abundance and distribution of prey, incorporated within territory boundaries.
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- Materials and methods
Various models have been proposed to explain variation in territory size and group composition among conspecific breeding units. These range from the ecological, such as resource density (the ideal free distribution, Fretwell & Lucas 1969) and dispersion (the resource dispersion hypothesis (RDH), Macdonald 1983), to the social, including constraints such as the resource-holding potential of residents vs. intruders (Stamps 1990). Here, we investigate the power of these models to explain patterns in Ethiopian wolf Canis simensis (Rüppell 1835) territory size and overlap, and the size and age/sex composition of wolf social groups.
If animals operate under an ideal free distribution, all territories will have the same per capita food availability (Fretwell & Lucas 1969) for the primary occupants. At a population and individual level, smaller home ranges are therefore predicted in areas of higher resource abundance, provided the resources are uniformly distributed or accessible (Johnson et al. 2002). This has been demonstrated in many and diverse species such as Townsend’s voles Microtus townsendii (Taitt & Krebs 1981), ovenbirds Seiurus aurocapillarus (Smith & Shugart 1987) and brown bears Ursos arctos (McLoughlin et al. 2000). However, this model may not pertain to situations where territories are contiguous or perennially occupied. Range contraction in response to increasing resources may be undesirable because neighbour pressure may prevent re-expansion or result in escalating conflict at times of food stress (Patterson 1980; von Schantz 1984). In such situations, population density rather than resource abundance may determine territory size through increasing intruder pressure (Wolff 1993). Alternatively, the resource-holding potential of residents relative to intruders (Stamps 1990) may become the prime influence on territory size. Intruders are more likely to be tolerated in ranges where, or at times when, food is abundant, and this is likely to alter the degree of exclusivity of territories. The relationship between population density, resource availability, territory size and overlap is potentially intricate, and may influence, and be influenced by, group size and composition in social species. Thus, we consider in parallel the drivers of variation in social group size and composition.
The minimum defensible territory is the smallest area sufficient to contain the resources necessary for survival and reproduction of the minimum breeding unit (Krebs & Davies 1993) and configured to minimize cost/benefit ratios (Davies & Houston 1984). Social groups may form when benefits accrue from group living through, for example, cooperative hunting (Packer & Ruttan 1988) or communal breeding (Solomon & French 1997). However, these benefits are not necessarily a prerequisite of group formation. In heterogeneous environments, the minimum defensible territory may encompass sufficient resources to give additional animals a degree of food security (Carr & Macdonald 1986), allowing spatial groups (sensuMacdonald 1983) to form. The RDH (Macdonald 1983) posits that while territory size will depend upon the dispersion of foraging patches, group size will be determined by patch richness. Our use of the term ‘patch’ here does not necessitate an arbitrary delineation of patches in an unproductive matrix; the RDH may also be applied to a continuous surface of foraging resources (Blackwell 2007).
Under a contractionist scenario (Kruuk & Macdonald 1985), the presence of additional, non-breeding individuals within a given minimum defensible territory may vary with temporal fluctuations in resource availability. Where resources are more homogeneous, groups may instead adopt an expansionist strategy, relying on greater corporate strength to increase territory size beyond the minimum required by a breeding unit (Kruuk & Macdonald 1985). The spatial extent of foraging habitats could also influence group size if interference competition reduces food intake of subordinates.
Here, we contrast the following factors as determinants of territory size: (i) density of food resources, (ii) population density, (iii) group size and (iv) intruder pressure. Laying the groundwork for our analysis of group composition, we explore how the availability of foraging habitat and food scales with territory size. We test whether the following measures of territory quality can predict group size and composition: (i) total prey abundance in the territory, (ii) the areal extent of different foraging habitats within each territory and (iii) spatial variability in prey abundance. We investigate the benefits of territorial expansion and how territorial overlap varies with resource abundance.
Ethiopian wolves Canis simensis in the highly productive Afroalpine grasslands of the Bale Mountains represent a revealing system to investigate socio-ecological factors influencing group composition and territory configurations. Packs of 2–13 adults (≥2 years old) and yearlings (12–23 months) breed cooperatively and defend a common territory. Where food resources are rich, packs occupy small, stable home ranges that neatly tessellate, covering all available habitat (Sillero-Zubiri & Macdonald 1997), and territory size is correlated with pack size (Sillero-Zubiri & Gottelli 1995b; Marino 2003). In contrast, individuals in resource-poor areas have larger territories and are members of smaller packs. Resources other than prey, such as water, mates and denning sites, are unlikely to be limiting: numerous alpine streams/lakes characterize the high plateaux, suitable denning sites abound, and multi-male groups, floater females, and opportunities for extra-pack copulations (Sillero-Zubiri, Gottelli & Macdonald 1996, Randall et al. 2007) ensure the ready availability of mates.
We test our hypotheses on data from three distinct sub-populations of Ethiopian wolves, from areas that vary in the abundance and distribution of the wolves’ prey. Three rodent species, the giant molerat Tachyoryctes macrocephalus (Rüppell 1842) and murine rodents Arvicanthis blicki (Frick 1914) and Lophuromys melanonyx (Petter 1972), are endemic to the southern highlands of Ethiopia (Yalden & Largen 1992) and comprise 88·8% of the wolves’ diet by volume (Sillero-Zubiri & Gottelli 1995a).
Previous work indicates that Ethiopian wolves adopt an expansionist strategy (Marino 2003) and that relative intruder pressure is a factor in territorial defence. Sillero-Zubiri & Gottelli (1995b) remark that wolf territories expand when neighbouring pack size falls, and larger groups usually win territorial disputes (Sillero-Zubiri & Macdonald 1998). Given that the contribution to territorial defence varies by age/sex class (Sillero-Zubiri & Macdonald 1998) and the costs and benefits of territorial expansion may depend on age and social status, adult males and dominant females are likely to exert the greatest outward pressure with subordinate females/yearlings having less impact. We examine how benefits might accrue to members of larger social groups, promoting the evolution of the expansionist strategy in this species.
Given the site fidelity and foraging behaviour of Ethiopian wolf packs (Sillero-Zubiri & Gottelli 1995b), we predict that this translates into greater tolerance of range overlap where prey densities are high and spatially homogeneous. Packs defending low-quality territories may have to maintain exclusive use of a larger proportion of their range to secure reliable access to sufficient resources. We therefore test whether the degree of overlap between neighbouring territories is higher in areas of abundant, uniformly distributed food.
In addition, we investigate whether shared areas differ in quality from areas that are exploited by only one wolf pack. Two opposing scenarios can be imagined. Areas of range overlap may represent low-quality zones that do not merit the defence effort required to expel intruders. Packs are predicted to invest more in acquiring and defending high-quality areas, maintaining exclusive use of only the best patches. Alternatively, ranges might overlap in the most productive areas, which attract the greatest number of incursions and therefore have the highest defence costs. In the latter case, the benefits of exclusion may also be lower because additional competitors are less likely to depress prey acquisition rates to the extent where it is not worth sharing them. As scant data exist to choose between these alternatives a priori, we simply contrast the productivity of overlap vs. exclusive areas.
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- Materials and methods
The three Bale Mountains study sites, Web Valley, Morebawa and Sanetti Plateau, are depicted in Fig. 1. Sites varied in the abundance and distribution of the three prey species (Tallents 2007) and in their overall biomass density, Fig. 2. Morebawa and Sanetti had similar levels of prey biomass density, with the lower abundance of A. blicki and T. macrocephalus in high-altitude Sanetti compensated for by greater prevalence of L. melanonyx. The Web Valley represented an exceedingly rich area, with c. 75% greater biomass per square kilometre than the higher altitude sites, Fig. 2d. Giant molerats contributed more to prey biomass in the Web Valley (37·8% vs. 23·5% in Morebawa and 12·9% in Sanetti). Prey biomass was more homogeneously distributed in Sanetti (SD of kg ha−1 pixel values in Web: 2·60; Morebawa: 3·04; Sanetti: 2·16; Fmax59,824 = 1·98, P < 0·001).
Figure 1. Digital elevation model of the Bale Mountains, showing study sites. Elevations from the Shuttle Radar Topography Mission imagery (Geographic Coordinate System, WGS84) are clipped at 2900 m (black) to delineate the Afroalpine zone. Maximum elevation is 4385 m (white).
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Figure 2. Rodent densities by study site, based on 2002–2005 NDVI-adjusted predictions (Tallents 2007). Densities are individuals per square kilometre and biomass is kg km−2. Bars show mean ± SD, (a) AB = Arvicanthis blicki, (b) LM = Lophuromys melanonyx, (c) TM = Tachyoryctes macrocephalus and (d) biomass of all species combined. MOR, Morebawa; SAN, Sanetti Plateau; WEB, Web Valley.
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Table 2 presents the relationship between site, territory size and the area of each habitat quality class. The three study sites differed in the extent of unproductive habitats (Mur0, TM0 and Bio0; equating to swamps and heather slopes) within territories. Web had the least of all the unproductive habitat categories, while Morebawa had the greatest extent of habitats classed as unsuitable for murine rodents, and Sanetti had the most habitat from which molerats were largely absent. After accounting for the effect of site, all territories had roughly the same area of unproductive habitats regardless of territory size. The area of low-quality habitat in terms of total prey biomass (Bio1) remained constant in all territory sizes, regardless of site.
Table 2. Site and territory size as predictors of the area of foraging habitat quality class (see Table 1 for definitions)
|Habitat quality||GLM Model||Territory size P||Coefficient (% of territory)||95% CI of coefficient||Site P||Site order (decreasing)||R2||Error d.f.|
|AB1||Territory size + site||0·024||0·09||0·01–0·17||<0·001||San, Mor, Web||0·70||24|
|AB34||Territory size + site||0·005||0·21||0·07–0·35||<0·001||Web, Mor, San||0·48||24|
|LM34||Territory size + site||0·018||0·23||0·04–0·42||0·006||Web, San, Mor||0·30||24|
|Mur0||Site||NS||N/A||N/A||0·001||Mor, San, Web||0·39||25|
|Mur1||Territory size + site||0·004||0·07||0·03–0·12||<0·001||San, Mor, Web||0·56||24|
|TM0||Site||NS||N/A||N/A||<0·001||San, Mor, Web||0·63||25|
|TM1||Territory size + site||0·012||0·30||0·07–0·53||0·036||San, Mor, Web||0·40||24|
|TM2||Territory size + site + (territory size*site)||0·008†||0·25||0·13–0·37||N/A||Mor, Web, San||0·79||22|
|TM34||Territory size + site + (territory size*site)||<0·001†||0·20||0–0·54||N/A||Web, Mor, San||0·88||22|
|Bio0||Site||NS||N/A||N/A||0·001||Mor, San, Web||0·38||25|
|Bio1||Site||NS||N/A||N/A||0·026||San, Mor, Web||0·19||25|
|Bio2||Territory size + site||0·003||0·40||0·15–0·65||<0·001||San, Mor, Web||0·57||24|
|Bio3||Territory size + site||0·001||0·35||0·17–0·53||0·047||Web, Mor, San||0·44||24|
|Bio4||Territory size + site + (territory size*site)||0·012†||0·08||0–0·28||N/A||Web, Mor, San||0·76||22|
|Bio34||Territory size + site + (territory size*site)||0·030†||0·42||0·14–0·71||N/A||Web, Mor, San||0·73||22|
In general, the proportion of each habitat quality category within a territory varied by site but not by territory size, reflecting the differing productivity of the three sites. Territories in Web had the greatest proportion of Bio34 (Kruskal–Wallis χ2 = 20·1, P < 0·001, n = 28) and the lowest proportion of unproductive habitats (Bio0: Kruskal–Wallis χ2 = 17·7, P < 0·001, n = 28), while Sanetti had the lowest proportion of good foraging habitats, and Morebawa had the highest proportion of unproductive land.
Mean pack size (adults plus yearlings) was 6·4 ± 2·3 SD (range 2–12, Table 3). The number of adult females varied little, with 13 of 28 packs (46·4%) having two adult females, one pack having three and the remaining 50% each having a single adult female. All other age/sex categories contributed to variation in pack size, and the number of adult males was not significantly correlated with the abundance of other age/sex categories.
Table 3. Pack size and composition by site, averaged over all pack-years
|Web||9||1·3 ± 0·5||2·9 ± 1·4||1·0 ± 0·9||1·6 ± 1·3||0||6·8 ± 3·3|
|Morebawa||10||1·6 ± 0·7||3·6 ± 1·1||0·8 ± 1·1||0·2 ± 0·3||0·1 ± 0·3||6·1 ± 1·9|
|Sanetti||9||1·6 ± 0·5||3·0 ± 0·7||1·1 ± 0·9||0·7 ± 0·8||0||6·4 ± 1·8|
|Overall||28||1·5 ± 0·6||3·2 ± 1·1||0·9 ± 0·9||0·8 ± 1·0||0 ± 0·2||6·4 ± 2·3|
Wolf population densities (adults plus yearlings) were roughly equivalent in Web (1·27 adults plus yearlings km−2 in 2002–2003) and Sanetti (1·23 km−2 in 2003–2004), and lower in Morebawa (0·86 km−2 in 2003–2004). Mean territory size for the two lone breeding pairs in the Web Valley, Sodota and Wolla was 3·6 km2, predicted to contain 18 340 murine rodents and 1684 giant molerats; a total biomass of 2987 kg. This may indicate the minimum defensible territory in optimal habitat.
Determinants of territory size
Of the alternative hypotheses for drivers of territory size (prey density, wolf population density, pack size and intruder pressure), the number of adult males plus the dominant female was the only significant correlate of territory size (Table 4), with larger multi-male groups being associated with larger territories. Territory size increased in parallel with most age/sex categories (Fig. 3), but the trend was steepest for adult males (plus the dominant female). Furthermore, once the influence of adult males had been accounted for, no other age–sex class or combination of classes had a significant impact on territory size.
Table 4. Correlates of territory size. Spearman’s rank correlations based on 28 packs
|Dependent variable||Independent variables||ρ||P|
|Territory size||Mean prey biomass density||−0·164||0·404|
|Wolf population density||−0·188||0·337|
|Relative intruder pressure||−0·276||0·155|
|Total pack size||0·330||0·086|
|AMs + dominant AF||0·456||0·015|
Figure 3. Territory size is determined by the number of adult males. Figures show territory size against: (a) pack size, (b) number of subordinate females, (c) number of adult males plus the dominant female and (d) number of other wolves in the pack (subordinate females plus yearlings).
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Relationship between territory size and quality
Larger territories had greater areas of all habitat classes except the unproductive habitats and Bio1, Table 2. The relationship between territory size and the area of prime foraging habitat (TM34, Bio4 and Bio34) depended on site (interaction term, Table 2). The area of both TM34 and Bio4 per territory was relatively constant in Sanetti and Morebawa, but in the Web Valley larger territories secured proportionately greater areas of the best foraging habitats. In all sites larger territories secured greater areas of Bio34, but the slope was steepest in Web, where almost entire territories consisted of good habitat, while the slope of the relationship was intermediate in Morebawa and shallowest in Sanetti, Fig. 4.
Figure 4. Area of the highest quality foraging habitat (Bio34, see Table 1) increases with territory size. Crosses indicate packs in Morebawa; filled circles are Sanetti packs, and open circles are Web Valley packs.
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The relationship between territory size and total number of prey varied by prey species and by site, Fig. 5. Larger territories always held more murine rodents: this relationship was site invariant for L. melanonyx (territory size: F1,24 = 130·6, P < 0·001, R2 = 0·83, n = 28, Fig. 5b), but the number of A. blicki within a territory increased steeply with territory size in Web, and more gradually in Sanetti (territory size/site interaction: F2,22 = 8·8, P = 0·002, R2 = 0·93, n = 28, Fig. 5a). Giant molerats within a territory remained roughly constant in Sanetti but increased sharply with territory size in Web and at an intermediate rate in Morebawa (territory size/site interaction: F2,22 = 3·6, P = 0·043, R2 = 0·91, n = 28, Fig. 5c). The species-specific patterns resulted in differing rates of prey accumulation by site, with biomass increments per unit area greater in Web than in Morebawa or Sanetti (territory size/site interaction: F2,22 = 8·3, P = 0·002, R2 = 0·91, n = 28, Fig. 5d).
Figure 5. Territory size predicts total prey abundance. Crosses indicate packs in Morebawa; filled circles are Sanetti packs, and open circles are Web Valley packs. Figures show: (a) AB = Arvicanthis blicki, (b) LM = Lophuromys melanonyx, (c) TM = T. macrocephalus and (d) biomass.
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Determinants of pack composition
The biomass available per wolf at any one time, averaged over all breeding packs, was 729·9 ± 266·3 kg SD (n = 26). Pack size (adults plus yearlings) was more strongly correlated with total rodent biomass in a territory than with territory size (total biomass: Spearman ρ28 = 0·57, P < 0·001; territory size: Spearman ρ28 = 0·40, P = 0·037). The correlation between biomass and the number of adult males did not reach significance (Spearman ρ28 = 0·34, P = 0·081).
The relatively constant number of adult females per pack means that there was no significant correlation between number of females and total number of rodents in a territory (Spearman ρ28 = −0·13, P = 0·51). The presence of an additional adult female could only be predicted once the single pack with three adult females (Fulbana in Morebawa) was removed from the dataset. A second adult female was more likely to be found in territories that had a higher proportion of the best giant molerat habitat (TM34), after site differences in habitat had been accounted for (residuals from the GLM of per cent cover of TM34 against site: F1,25 = 6·5, P = 0·017, R2 = 0·17, n = 27, Fig. 6).
Figure 6. Prime molerat habitat per territory determines the number of adult females. The proportion of the territory that is prime habitat for giant molerats is contrasted between packs with a single, dominant adult female (empty boxes) and packs with an additional, subordinate adult female (shaded boxes). MOR, Morebawa; SAN, Sanetti Plateau; WEB, Web Valley. Boxes illustrate median and interquartile range, whiskers show full range.
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The number of yearlings, however, was positively correlated with rodent abundance (yearling females: ρ28 = 0·48, P = 0·01; yearling males: ρ28 = 0·61, P < 0·001). More yearling females were found in territories in which biomass was distributed homogeneously (SD of biomass per territory: Spearman ρ28 = −0·42, P = 0·026). The number of yearling males was positively related to the mean biomass within a territory (i.e. a measure of prey richness that does not change with territory size: Spearman ρ28 = 0·39, P = 0·039). Site was a significant predictor of the number of yearling males in a pack (Kruskal–Wallis χ2 = 7·3, P = 0·026, n = 28) with the most in the Web Valley and the least in Morebawa. No other age/sex categories varied significantly by site.
Benefits of the expansionist strategy
Wolf density within territories decreased as territory size increased (Spearman ρ26 = −0·63, P = 0·001). Sodota and Wolla had small territories but high biomass per wolf because of their small pack size. When these two outliers were removed, biomass per wolf increased with territory size (Spearman ρ26 = 0·53, P = 0·005). For giant molerats, this relationship was only significant after accounting for site differences in molerat abundance (site: F2,22 = 24·2, P < 0·001; territory size: F1,22 = 4·8, P = 0·04; R2 = 0·68, n = 26). Sanetti had the fewest molerats per wolf, and Web the most. For murine rodents combined and for total biomass, prey availability per wolf remained similar in each site, with differences between packs explained partly by territory size.
After removing Sodota and Wolla, territories were configured to contain equal amounts of the best foraging habitat (Bio4) per wolf, within the constraints of site differences in its distribution. However, larger territories in all sites had proportionately greater areas of the next best foraging habitat (Bio3) per wolf (Spearman ρ26 = 0·39, P = 0·048).
Influence of habitat quality on territorial overlap
Larger territories tended to have larger exclusive areas (Spearman ρ28 = 0·77, P < 0·001), so the percentage area used solely by the resident pack remained relatively constant with territory size (mean = 67·6% ± 20·8 SD, Spearman ρ28 = 0·17, P = 0·39). Territory size and the size of exclusive areas were not significantly different among sites, but the size of overlap areas between neighbouring packs did vary significantly (Kruskal–Wallis χ2 = 6·8, P = 0·033, n = 28, Table 5), with the largest shared areas in Morebawa, and the smallest in Sanetti. In Sanetti and Morebawa, but not in resource-rich Web, the degree of exclusivity was negatively correlated with the proportion of the territory covered by the best foraging ground (Bio34: Spearman ρ18 = −0·66, P = 0·003, Fig. 7).
Table 5. Territory size by site. Numbers indicate mean ± SD (range), averaged over all years for each pack. Areas of convex polygons are presented for comparison with previous studies.
|Territory size (concave polygons, km2)||6·43 ± 2·40 (2·96–10·18)||8·61 ± 3·21 (3·96–14·39)||7·04 ± 1·77 (3·75–8·89)||7·41 ± 2·64 (2·96–14·39)|
|Exclusive area (km2)||4·28 ± 2·43 (1·51–9·07)||5·38 ± 3·32 (0·65–12·34)||5·68 ± 1·65 (3·56–8·12)||5·12 ± 2·57 (0·65–12·34)|
|Proportion exclusive (%)||63·5 ± 16·4 (42·4–89·2)||59·1 ± 24·1 (16·5–87·9)||81·1 ± 15·1 (60·4–100·0)||67·6 ± 20·8 (16·5–100·0)|
|Territory size (convex polygons, km2)||7·58 ± 2·71 (3·00–12·18)||11·62 ± 4·54 (4·00–19·63)||8·38 ± 1·85 (5·63–11·16)||9·28 ± 3·65 (3·00–19·63)|
Figure 7. Territory exclusivity vs. territory quality. Exclusivity is quantified by the proportion of the territory that does not overlap with neighbours, and quality is measured by the proportional extent of the best foraging habitat, Bio34 (see Table 1 for a definition). Crosses indicate packs in Morebawa; filled circles are Sanetti packs, and open circles are Web Valley packs. Ovals indicate the negative trend in Morebawa and Sanetti (continuous line), and lack of a relationship in Web (dashed line).
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Areas of territory overlap had significantly more predictable and higher average biomass than did exclusive areas (overlap areas: 6·73 kg ha−1 ± 2·19 SD; exclusive areas: 6·41 kg ha−1 ± 2·35; Wilcoxon Z5 = −2·02, P = 0·043, for both mean and SD of biomass). The trend for overlap areas to harbour a greater proportion of the richest biomass habitats (Bio34) approached significance (overlap areas: 58·2% ± 29·8 SD; exclusive areas: 54·0% ± 30·9; Wilcoxon Z5 = −1·75, P = 0·08).