Resource partitioning and niche hyper-volume ... - Wiley Online Library

Functional Ecology 2010, 24, 646–657

doi: 10.1111/j.1365-2435.2009.01654.x

Resource partitioning and niche hyper-volume overlap in free-living Pygoscelid penguins Rory P. Wilson* Institute of Environmental Sustainability, School of the Society and Environment, Swansea University, Singleton Park, Swansea, SA2 8PP, Wales, UK

Summary 1. Species potentially competing for the same resource are considered to be able to co-exist if they occupy different niches. In an apparent example of this, Ade´lie, Chinstrap and Gentoo penguins all feed predominantly on krill Euphausea superba at certain sites of sympatry in Antarctica and are proposed to exploit different niche hyper-volumes via differential area and depth utilization. 2. Patterns of foraging for 49 of these penguins breeding in sympatry were assessed using deadreckoning loggers to examine foraging niche overlap. 3. Area use overlaps were 0Æ29 for Ade´lie \ Chinstrap, 0Æ44 for Ade´lie \ Gentoo, and 0Æ40 for Chinstrap \ Ade´lie and depth use overlaps were 0Æ69 for Ade´lie \ Chinstrap, 0Æ48 for Ade´lie \ Gentoo, and 0Æ52 for Chinstrap \ Gentoo Penguins. 4. Foraging efficiency was greatest for Ade´lie Penguins diving near surface waters (0–15 m) while Chinstraps were most efficient at medium depths (15–60 m) and Gentoo Penguins most efficient at deeper depths (> 60 m). There appear to be physiological reasons for this. Penguins primarily exploited those depths where they were most efficient. 5. The overlap for foraging periods was 0Æ47 for Ade´lie \ Chinstrap, 0Æ26 for Ade´lie \ Gentoo, and 0Æ40 for Chinstrap \ Gentoo Penguins. Chinstraps foraged primarily at night, Gentoos during the morning and Ade´lies in the afternoon. Temporal differences in foraging may result in the three species exploiting krill at those depths where it is best adapted to pursue it, this being mediated by the diel vertical migration of krill. 6. Integration of all measured parameters together gives minimal overlap between species with total overlaps of 0Æ09 for Ade´lie \ Chinstrap, 0Æ05 for Ade´lie \ Gentoo, and 0Æ08 for Chinstrap \ Gentoo Penguins so it appears that these penguins conform to conventional theory in avoiding competition in areas of sympatry. However, a model incorporating prey movement between hyper-volumes indicates that penguins may still compete, even in the virtual absence of hypervolume overlap. 7. This study shows that Pygoscelid penguin do indeed exploit different hypervolumes in areas of sympatry but that such exploitation of different niches by sympatric species feeding on a common resource does not necessarily result in reduced competition if the mobility of prey is high. Key-words: Antarctica, foraging ecology, Pygoscelis adeliae, Pygoscelis antarctica, Pygoscelis papua, ecological segregation, interspecific competition, diving behaviour, area utilization, temporal differences

Introduction Competition between species for resources drives population changes and shapes communities (e.g. Hardin 1960; Seabloom et al. 2003) and competition for food is a major element of this (Hutchinson 1959; MacArthur & Levins *Correspondence author. E-mail: [email protected]

1967; Connell 1983; Schoener 1983; McDonald 2002; Ainley et al. 2004). Indeed, the extent of consumption competition appears to modulate the likelihood of species co-existence (cf. Gause 1934) so much that niche shifts have been invoked to explain co-existence in sympatric competing species (cf. Hutchinson 1958, 1959, 1978; Priviter et al. 2008). For example, MacArthur’s seminal paper (MacArthur 1958) proposed that sympatric warblers could co-exist

2009 The Author. Journal compilation 2009 British Ecological Society

Competition in sympatric penguins 647 using the same food types by simply foraging at different heights in the same trees. This study conforms with others published since then (cf. Hodgson et al. 1997) in tending to consider inter-specific patterns along a single dimension (foraging height in MacArthur’s warbler study). In fact, the large number of possible axes in the n-dimensional niche hyper-volume (sensu Hutchinson 1958) means that there is huge potential for niche differences between potentially competing species, particularly since minor differences in a number of different axes can result in a substantial overall difference (cf. Priviter et al. 2008). Such differences are exacerbated when competition is to be considered in nature where the availability of different sections of dimensions varies both with the changes in the environment, e.g. weather, as well as with animal choice (cf. Olson, Young & Blinkoff 2003). Does the large number of potential dimensions not always allow ‘competing’ species to be considered to be somehow operating in different hyper-volumes? Beyond this, do species operating in species-specific hypervolumes genuinely not compete if they feed on the same prey? To examine these questions I used technology based on advances in bio-telemetry (e.g. Cooke et al. 2004) to examine the extent of niche hyper-volume overlap in three sympatric penguin species, all of which feed primarily on a single food source. The study aimed to define the spatial and temporal foraging patterns (3-dimensional spatial axes and 1-dimensional temporal axis) of each of the species and uses a simple model to examine how prey movement between species-specific hyper-volumes might relate to the degree of competition between species, potentially negating niche shifts which should normally lead to reduced competition. Three congeneric penguins, the Ade´lie Pygoscelis adeliae, Chinstrap P. antarctica and Gentoo Penguin P. papua occur primarily in allopatry around Antarctica but also, rarely, in sympatry at, for example, two colonies (Croxall & Kirkwood 1979; Woehler 1993; Hinke et al. 2007), on King George Island, Antarctica. King George Island and its immediate surrounds hosts large numbers of Pygoscelid penguins in single species or two-species colonies (Croxall & Kirkwood 1979; Woehler 1993). Putative foraging ranges of the three species (Trivelpiece, Trivelpiece & Volkman 1987) and the tight spacing of colonies, some containing tens of thousands of birds (Croxall & Kirkwood 1979; Woehler 1993), means that there is high potential for direct competition, including from birds in adjacent colonies (cf. Trivelpiece, Trivelpiece & Volkman 1987). Here, at the end of December, when the energy requirements of breeding adults are considered to be particularly great (Trivelpiece, Trivelpiece & Volkman 1987; Alonzo, Switzer & Mangel 2003), birds from all three species feed their chicks on their main dietary item, Antarctic Krill Euphausea superba: This crustacean accounts for about 99, 99 and 84Æ5% of the wet mass of the diet of Ade´lie, Chinstrap and Gentoo Penguins, respectively, in this region (Volkman, Presler & Trivelpiece 1980; cf. Miller & Trivelpiece 2007) although in other regions fish may be an important compo-

nent (see, e.g. Jansen, Russell & Meyer 2002). The similarity of the species is striking and it is hard to envisage co-existence (Schoener 1974; Huston 1994; cf. Hutchinson 1959) without substantial consumptive competition (Schoener 1985; Abramski, Rosenzweig & Subach 2001; Salewski, Bairlein & Leisler 2003) and although there are some differences in beak morphology between species (cf. Lack 1947, 1971), there is little evidence to suggest this provides a morphological impetus that might lead to differential prey selection (cf. Jablonski & Lee 1998). Indeed, dietary studies demonstrate that interspecific differences are minimal (Volkman, Presler & Trivelpiece 1980; Wauters et al. 2001; Lynnes et al. 2002; Miller & Trivelpiece 2007) although Gentoos may sometimes eat larger krill than Chinstraps which, in turn, sometimes eat larger krill than Ade´lies (e.g. Volkman, Presler & Trivelpiece 1980; but see Lynnes et al. 2002) so that, given the limited foraging ranges of the species (see Williams 1995), competition should be extreme (cf. Connell 1983; Schoener 1983). In a detailed study of the breeding situation at King George Island, Trivelpiece, Trivelpiece & Volkman (1987), concluded that displaced breeding seasons may reduce inter-specific competition (Klopfer 1962), and that the situation is further alleviated because the species appear to forage at different sites and depths. Different penguin species foraging at different depths to reduce competition is exactly analogous to MacArthur’s warblers foraging at different heights in the trees (MacArthur 1958; cf. MacArthur 1964; Ricklefs 1966), particularly because both involve interspecific differences in the vertical axis, and might explain, therefore, how species can co-exist using the same food resource.

Materials and methods STUDY SPECIES AND AREA

Penguins were studied at Ardley Island (6213¢S, 5855¢W), King George Island, Antarctica between December 1991 and January 1992. This island has colonies of Ade´lie, Chinstrap and Gentoo Penguins breeding side by side with even some intermingling of species. All used in the study were tending chicks at the time and a total of 18 Ade´lie, 17 Chinstrap and 14 Gentoo Penguins was equipped with loggers to record aspects of their foraging behaviour. Care was taken to ensure no time-bias (either over the season or with respect to time of day) in the equipment of birds.

METHODS

The loggers (DKLOG 101, Dreisen & Kern GmbH, Bad Bramstedt, Germany) had maximum dimensions of 150 · 57 · 37 mm, were given a streamlined shape following Bannasch, Wilson & Culik (1994), and weighed 168 g. The units had 64 kbyte memories and recorded the following parameters: (a) Depth, up to a pressure of 20 Bar (ca. 200 m) using a mediumseparated transducer with 10 bit resolution giving an accuracy of better than 0Æ5 m (b) Penguin heading, determined using a fluid-filled compass with 2 Hall sensors placed at 90 to each other equitorially around the compass. These sensors indicated needle orientation via differential signal

2009 The Author. Journal compilation 2009 British Ecological Society, Functional Ecology, 24, 646–657

648 R. P. Wilson strength due to the field generated by the magnet in the system (Wilson et al. 1993; Benvenuti et al. 1998). (c) Swim speed was measured by counting the number of rotations of a paddle wheel. Units were calibrated both on model penguins in a water flume to speeds of up to 4 m s)1 and on living birds. For this, penguins were taken from the shore at Ardley Island, equipped with loggers and allowed to swim underwater up and down a 21 m long swim canal at will. Real time observations of the birds’ positions within the canal were tied in with logger readings so as to derive a calibration curve of swim speed against differential pressure (for details see Culik, Wilson & Bannasch 1994). (d) Temperature and light intensity were also measured, temperature being used to correct other sensors for temperature-dependent drift. Other than this, the output of these sensors is not used here. The loggers were programmed to sample data at a rate of once every 10 or 15 s and units were deployed on birds for a minimum of one foraging trip and attached using tape (Wilson et al. 1997) to the dorsal midline of the back, placed posteriorly so as to minimize drag (Bannasch, Wilson & Culik 1994). Upon recovery of the devices, data were downloaded onto computer using an RS 232 interface and these data subject to various programmes for analysis.

Representation of resource partitioning In the discussion on resource partitioning, it is considered that utilization of a dimension by a particular species can be schematized as defined within a circle so that overlap between the three species in utilization of the dimension under consideration can be represented by a standard Venn diagram of three overlapping circles. Each circle is taken as comprising an area of 1. Within any one dimension considered, the degree of overlap is referred to in standard Venn diagram terms with ‘A’ representing Ade´lie Penguins, ‘C’ Chinstrap and ‘G’ Gentoo Penguins. Here, overlap, and non-overlap, between species can be considered as fractions of 1 based on the proportion of the circle of area 1 incorporated in the overlap. In the final treatise, multi-dimensional overlapping Venn diagrams, describing a hyper-volume (sensu Hutchinson 1958) will be considered, with overlaps calculated based on the area system above (cf. Levins 1968), but cases which involve, time, area and depth overlaps are defined as they occur.

Results DEVICE EFFECTS

Calculation of area usage Bird movements were determined by analysing speed, depth and heading to a vectorial program using dead reckoning ROUTE10.0 (Jensen Software Systems, Laboe, Germany). This program was supplied with the geographic co-ordinates defining the point where the equipped birds entered the water and then used vectors to integrate the recorded parameters for movement so as to produce a three dimensional route of the birds during foraging trips (Wilson et al. 1993; Wilson & Culik 1995; Wilson 2001). Putative drift due to currents and surface swimming, which was not recorded by the loggers, was corrected by superimposing the start and end positions of the foraging trips and correcting all intermediate data to accord assuming that the magnitude of the drift was equal at all times during the foraging trip. The actual accuracy of the system could be alluded to by examination of the error in the return position calculated by the system compared to that known to have been the case (Wilson et al. 2002a, 2007). The course of the birds was defined as a series of x, y and z co-ordinates at intervals corresponding to movement North ⁄ South, East ⁄ West and depth. These co-ordinates were summed for each species in a matrix defining the total amount of time spent by all birds of that species in kilometre quadrats round the island. To allow interspecific comparisons, these matrices were converted into fractions of a total time (standardized to 1, to facilitate Venn comparisons, see below) spent per km quadrate and displayed using a topographic program (Surfer golden software).

Calculation of depth usage Depth utilization and diving behaviour were determined primarily by analysing the data with ANDIVE8.0 (Jensen Software Systems, Laboe, Germany) which calculates, among other things, the following parameters for each dive: the time of day when the dive was initiated, the duration of the descent phase, the maximum depth reached during the dive, the duration of the bottom phase and the duration of the ascent. The post-dive recovery period can be calculated by subtracting the total time spent underwater during the dive from the difference between the time of initiation of two adjacent dives.

All devices were recovered from all penguins and all birds appeared in good health having executed a total of 42, 25 and 38 foraging trips for Ade´lie, Chinstrap and Gentoo Penguins, respectively. All Ade´lie penguins conducted at least two foraging trips and 6 birds conducted three, seven chinstrap penguins conducted two trips while 10 conducted only one and all gentoo penguins conducted at least two foraging trips while 10 birds conducted three. There was no obvious link between foraging areas or depths in consecutive trips for individuals where data for multiple trips were undertaken. I was able to ascertain that many birds had fed while at sea by watching for chick-feeding behaviour although it was not possible to control all birds at all times. There was no evidence that birds that had worn the devices for longer were in different condition than the others (though this was not formalized by specific measures of body condition) and, superficially, birds appeared to behave in much the same way as unequipped conspecifics.

AREA USAGE

All equipped penguins foraged within 35 km of Ardley Island (Fig. 1) but the only common areas used (A \ C, A \ G, and C \ G), were within about 10 km of the breeding site and almost all common time was used within 5 km of the island (Fig. 2). The degree of area overlap for the species (cf. Levins 1968), considered pair-wise, and given by:

0

n ¼ ð25; 38Þ ðSpa SpbÞ n ¼ ð0; 0Þ

eqn1

where Sp represents the proportion of the total of a species (total maximum = 1 per species, see above) occupying any


Competition in sympatric penguins 649

Adelie Penguins

Chinstrap Penguins

Gentoo Penguins

Fig. 1. Foraging area utilization by the three Pygoscelid penguin species breeding at Ardley Island during 1991 ⁄ 2. The 3-d plots represents the fraction of total time spent per square kilometre in the vertical axis for all bird positions at sea. Ardley Island is located at the co-ordinates (5, 5) (cf. Fig. 2).

particular quadrate defined by kilometre vectors (corresponding to distance South and East, respectively)) was only 0Æ29 for A \ C, 0Æ44 for A \ G and 0Æ40 for C \ G. Although time spent in the immediate vicinity of Ardley accounted for an appreciable portion of the time spent at sea by all birds, there were areas that were visited almost exclusively by one species or another, leading to speciesexclusive zones. Although all species moved away from the island in a generally south-easterly direction, Ade´lie Penguins used virtually exclusively the sea area extending from about 28 km to 40 km south-south-east of Ardley Island, in a strip some 3 km wide, Chinstrap Penguins spent proportionately much more of their time between 8 and 24 km south-south-east of the island in a strip some 6 km wide, and Gentoo Penguins spent most of their time in a spot of

radius 6 km with its centre about 5Æ5 km directly south-east of the island (cf. Fig. 1).

DIVING BEHAVIOUR

The diving behaviour of the penguins was superficially similar in all species. The maximum depth reached during any dive was 106 m (by a Gentoo Penguin) although, in all species, more than 50% of the dives terminated at depths less than 40 m (Fig. 3). There were significant differences in the frequencies of maximum dive depths, however (v2 = 369Æ8, d.f. = 18, P < 0Æ001, Cc = 0Æ31), with chinstraps tending to terminate dives at lesser depths than the other two species although over 60% of all Gentoo penguin dives terminated between 20 and 50 m (Fig. 3). Consideration of the


650 R. P. Wilson (a)

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total time spent underwater at the various depths [converted to percentages and then treated in the same way as the areas (above)] showed that the overlap between species in the depth ranges exploited was appreciable but not complete, being 0Æ69 for A \ C, 0Æ48 for A \ G and 0Æ52 for C \ G. There were marked relationships between dive depth and dive parameters in all species, the parameters being descent

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Competition in sympatric penguins 651 Table 1. Summary of dive parameters (y) as a function of depth (x) for the three Pygoscelids Variable Adelie Best fit r2 a-value b-value F-value P Chinstrap Best fit r2 a-value b-value F-value P Gentoo Best fit r2 a-value b-value F-value P

Descent duration

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y = a + (bx) 0Æ54 14Æ2 0Æ389 720 < 0Æ001

y = a + (b ⁄ x) 0Æ26 30Æ79 )76Æ23 200 < 0Æ001

y = a + b(x^0Æ5) 0Æ42 9Æ133 4Æ009 356 < 0Æ001

y = a + b(x^0Æ5) 0Æ29 4Æ47 4Æ825 411 < 0Æ001

y = (a + bx)^2 0Æ53 3Æ50 0Æ041 1098 < 0Æ001

y = a + bln(x) 0Æ48 )6Æ21 10Æ458 564 < 0Æ001

y = a + (bx) 0Æ50 12Æ66 0Æ45 1103 < 0Æ001

y = a + b(x^2) 0Æ20 19Æ80 0Æ0086 79 < 0Æ001

y = a + (bx) 0Æ40 17Æ31 0Æ46 480 < 0Æ001

y = a + bln(x) 0Æ17 )7Æ57 10Æ365 144 < 0Æ001

y = a + (bx) 0Æ22 20Æ77 0Æ35 206 < 0Æ001

y = a + b(x^2) 0Æ10 20Æ97 0Æ0049 58 < 0Æ001

duration, bottom duration, ascent duration and post dive recovery time although the best fits were not always linear (Fig. 4) (Table 1). There was a fair amount of scatter in regressed parameters, particularly in the case of dive depth and post-dive surface interval (Fig. 4d). Due to the difficulties in assessing which post-dive recovery intervals were likely to be necessarily associated with dives and which were simply resting periods at the surface (during which birds might preen etc. for extended periods) [see (Kooyman 1989a) for definitions of dive bouts], extinction curves of frequency against surface interval were plotted and points of inflection determined. These occurred at 90, 100 and 100 s for Ade´lie, Chinstrap and Gentoo Penguins, respectively, and subsequently only points that were less than these values were considered in the regression.

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Time of day (h) Fig. 5. Percentage time spent actively diving as a function of time of day for Pygoscelid penguins breeding at Ardley Island during 1991 ⁄ 2. Darkest bars show Chinstrap, lightest Gentoo, and intermediate bars show Ade´lie Penguins.

Discussion TEMPORAL PATTERNS OF FORAGING

Although birds were away from nests and apparently at sea at all times of the day, consideration of the times that the birds were actually diving showed that there were quite marked inter-specific differences (v2 = 80Æ1, d.f. = 46, P < 0Æ01, Cc = 0Æ39). Ade´lie Penguins dived throughout the whole 24 h period although more birds utilized the afternoon periods than at other times, Chinstrap Penguins spent proportionately more time diving overnight and in the early morning while Gentoo Penguins spent most time actively diving between early and mid-morning (Fig. 5). If the time spent at sea actively diving per species is divided into hourly sections and the total standardized to 1 (see above), the total overlap in time between Ade´lie and Chinstrap Penguins (A \ C) = 0Æ47, that between Ade´lie and Gentoo Penguins (A \ G) = 0Æ26 and that between Chinstrap and Gentoo Penguins (C \ G) = 0Æ40.

THE ROLE OF DIVING CAPACITY IN DETERMINING DEPTH USE

There is extensive literature on the depths used by three Pygoscelid penguin species which shows considerable variance according to locality and time (e.g. Miller & Trivelpiece 2008; http://polaris.nipr.ac.jp/~penguin/penguiness/ and refs therein). The results of this study show a great deal of overlap in the depths at which the three penguin species forage (e.g. Fig. 3) but, in order to consider the potential competitive advantages of the various species as a function of depth, it is necessary to examine the diving behaviour more closely. There is good evidence to suggest that penguins feed primarily on discreet patches of prey at specific depths, ingesting multiple prey underwater until oxygen deficit causes them to return to the surface (e.g. Falla (cited in Zusi (1975)) and Ropert-Coudert et al. (2002) for Ade´lie


652 R. P. Wilson

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Penguins, Wilson & Wilson (1990) for Spheniscus penguins), and that this behaviour results in the observed Ushape of dives with appreciable bottom phase durations. Thus, the duration of the bottom phase of the dives can be taken as a measure of time during which the birds may acquire prey (Wilson & Wilson 1990). The time taken in transit from the surface to the foraging depths and back to the surface is not directly used appreciably for acquiring prey and neither is the post-dive recovery duration at the surface. This approach was developed by Ydenberg & Clark (1989) and subsequently used by a variety of authors for examining optimal dive behaviour under different conditions (e.g. Ydenberg & Forbes 1988; Houston & Carbone 1992; Carbone & Houston 1994, 1996) because these parameters can be used as a measure of time invested in foraging. Indeed, maximization of time at the foraging depth is considered critical for diving endotherms attempting to optimizing foraging (Shepard et al. 2009). Summarizing the approach taken by these authors (op. cit.), the foraging efficiency with respect to time of any particular penguin can be represented by the bottom duration divided by the dive cycle duration (including the post-dive pause at the surface) (Ydenberg & Clark 1989). Note that this formulation does not consider many potential features, such as oxygen loading curves and their relationship with swim speed and prey encounter rates, which might render the general utility of this approach much less accessible (Thompson, Hiby & Fedak 1993; Wilson, Ropert-Coudert & Akiko 2002b). It is assumed that the rate at which prey can be acquired by any species is simply proportional to the time that the birds can allocate to the bottom phase of a dive. In this treatment, therefore, the relationship between dive parameters and maximum depth reached during the dive (Table 1) can be used to derive the time use efficiency of the various species as a function of maximum dive depth. The graphic representation of this (Fig. 6a) shows that Ade´lie Penguins appear to be the most efficient species at the shallow depths (< 20 m), the Chinstrap Penguins the most efficient at the intermediate depths (20–60 m) while the Gentoo Penguins are apparently the most efficient at depths in excess of 60 m. The effect that this may have on interspecific abilities to harvest krill may confer differential advantages according to the diel cycle since krill is considered by some authors to show diel vertical migration (e.g. Ichii et al. 1998). When krill is at greater depths, the penguin species with a greatest efficiency at exploiting these depths will be favoured whereas, as krill rises in the water column, it will eventually move into depths that are best exploited by another species, giving the new species the competitive advantage at this time. This can be demonstrated by using the species-specific calculations for diving efficiency found here to derive a proxy for harvesting rate dependent on the krill vertical density distribution that moves up and down the water column according to time of day as has been proposed by Godlewska & Klusek (1987). If the form for the krill distribution is given by:

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Depth (m) Fig. 6. (a) Relative efficiency of the three species of Pygoscelid penguins foraging from Ardley Island during 1991 ⁄ 2 as a function of dive depth. Points (black triangles – Ade´lie, grey circles – Chinstrap, crosses – Gentoo). The efficiency is calculated by dividing the bottom duration during dives (when birds consume prey) by the total time spent during one dive cycle for that particular depth (see text). (b) Relative efficiency of the three Pygoscelid penguins feeding on krill distributed at different depths [symbols as in (a)]. Here, the efficiency is defined by dividing the bottom duration, multiplied by a measure of prey abundance during dives (see eqn 2 in text) by the total time spent during one dive cycle for that particular depth (see text).

y¼

1 :e05ððx0Þ=rÞ2 ro2p

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(where y is the proportion of krill found at a specific depth, x is the depth under consideration, 0 the mean depth and r the standard deviation) then the extent to which the various species can benefit from the distribution is given by multiplying the dive efficiency by this term, the graphical representation of which is shown in Fig. 6b. In fact, whether krill does show diel vertical migration or not, and this appears equivocal (see Ichii et al. 1998), is perhaps of lesser importance for the consequences of the model here than the observation that krill distributes itself unevenly throughout the water column so that whether one Pygoscelid penguin species has a competitive advantage depends on that. In fact, the literature on krill vertical distribution indicates a large temporal and spatial variability and it may be that the distribution of Pygoscelid colonies accords with the conditions that most suit the species in question. Where species occur in sympatry, such as at Ardley, we might expect the species to seek areas or times when krill distribution concurs with their maximized foraging efficiencies and this might explain the differences observed in these parameters. In this respect it is interesting that birds apparently most often dive to those depths where they are most efficient (Ade´lie; Rs = 0Æ99, Z = 2Æ96: Chinstrap; Rs = 0Æ99, Z = 2Æ96:


Competition in sympatric penguins 653 Gentoo; Rs = 0Æ95, Z = 2Æ85) (Fig. 7) implying either that they primarily forage at the depths where they are most efficient or that they actively seek out conditions that lead to krill at that depth or a combination of both. The times of day at which birds forage needs be addressed in this context. It is notable that Hutchinson’s (1958) original treatise regarding warblers and foraging heights in the vegetation had neither a time-specific context, as noted by MacArthur (1968), nor did it consider that warbler prey might move vertically within the vegetation, in a manner analogous to that of krill (Godlewska & Klusek 1987). This might have been appropriate for his situation. However, in cases where prey species are mobile, and particularly where this mobility leads to variation in vertical distribution, the inclusion is important. Here, temporal differences in foraging behaviour, tied in with inter-specific patterns in selected foraging depth (where birds optimize on time at depth efficiencies - see above), could expose Pygoscelid penguins to quite different vertical prey distributions, even when the three species forage in the same areas conferring appropriate advantages on the species concerned. The reasons why differing Pygoscelids should have different efficiencies during dives to different depths are complex

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0·25

Fig. 7. Relationship between the frequency of dives to particular depths (see Fig. 3) and the calculated efficiency for the birds at that depth (means over the depth range considered) (see Fig. 6a). Data for dives to less than 5 m have been omitted since these depths are primarily used by birds to travel (Wilson 1995).

and likely to be dependent to a large extent on the physiology, and the allometry, of this in the birds. Chinstrap Penguins are the smallest of the Pygoscelids weighing between 3Æ0 and 5Æ3 kg, Ade´lie Penguins weigh between 3Æ6 and 5Æ5 kg, while Gentoos are the largest weighing between 4Æ9 and 7Æ4 kg (data for guard and cre`che periods only; summarized in Williams 1995). Mass-specific metabolic rate decreases with increasing body mass (Aschoff & Pohl 1970; Peters 1983) while body oxygen stores change little, or even increase, specifically, with body mass (Peters 1983; Kooyman 1989a; Butler & Jones 1997) so that larger animals can theoretically dive longer (e.g. Hudson & Jones 1986; Boyd & Croxall 1996) and therefore have time to dive deeper, something they apparently do (e.g. Burger 1991; Wilson 1995). However, the speed at which an animal can recover from a dive and repay its oxygen debt is likely to be inversely related to body mass since the difference in oxygen partial pressure between the lung and the blood is reduced in larger animals (summarized in Peters 1983) and a combination of mass-specific increasing heart stroke volumes and decreasing frequency results in scaling of blood flow and cardiac output to Mass0Æ75 (summarized in Peters 1983). In addition to this, oxygen consumption due to locomotion (and possibly heat loss) should be considered. Larger animals can swim faster (and thus descend and ascend the water column most efficiently) at a relatively lower metabolic rate because drag increases with surface area or with length2, whereas power increases according to muscle volume or length3 (Beamish 1978; Kooyman 1989b). Finally, the situation is further complicated by possible hunting strategies where travel at the lowest cost of transport is not always the optimal solution (Videler & Nolet 1990; Thompson, Hiby & Fedak 1993) so that energy expenditure, and consequent time spent at depth (cf. Williams et al. 2000 for further complexities in this) may vary. Whatever the reasons for the observed interspecific patterns, it is interesting that the differential efficiencies of the penguins at different depths appear to stem primarily from physiological limitations, perhaps related to body size. Actual observations of dive depths of the different species in different conditions need careful interpretation though because the environment and the distribution of prey may act to blur the effects of allometry. For instance, Ade´lie penguins from Lutzow-Holm Bay have mean maximum dive depths of ca. 10 m when foraging under ice (Watanuki et al. 1993) while birds of the same species in Prydz Bay may reach depths in excess of 180 m in open water (Whitehead 1989). To date, observations on differential habitat use by potentially competing species have been either based on morphological (e.g. (Lack 1971; Denno, McClure & Ott 1995; McDonald 2002) or behavioural (MacArthur 1958; Churchfield, Nesterenko & Shvarts 1999) differences.

PYGOSCELID COMPETITION

In the scenario presented there are a number of elements which tend to obscure apparent inter-specific similarities in time ⁄ space utilization. Specifically, for the birds breeding at


654 R. P. Wilson Ardley Island, which is enclosed within the Maxwell Bay, the only appreciable direction in which foraging birds can initially move is out towards the open sea in a South Easterly direction (Fig. 1). With increasing distance from the island, however, the fanning out of birds and general dilution of a fixed number of birds in an ever increasing volume of water will tend to decrease bird density with increasing distance. Thus, a high bird density (and consequently high bird time) is to be expected for all species close to Ardley Island (see Fig. 1) because the penguins must move through this area twice per foraging trip in order to access both breeding sites and foraging areas. This does not mean, however, that the areas close to the island where the inter-specific area overlap is highest, reflects foraging. Similarly, birds diving to specific depths must repeatedly move through the upper water layers, thus accumulating time at depths which might not be preferred. The values given for overlap in these cases are thus likely to be maxima. The classic scenario for avoidance of inter-specific competition lies in potential competitors utilizing different prey types or areas (e.g. Churchfield, Nesterenko & Shvarts 1999). In the case considered here (cf. Lynnes, Reid & Croxall 2004), and for the King George Island region as a whole, it is clear that these three Pygoscelid penguins do feed on essentially the same prey, although minor differences might be observed with respect to the frequency of different length classes etc. (see e.g. Volkman, Presler & Trivelpiece 1980; Trivelpiece, Trivelpiece & Volkman 1987; Williams 1995). In keeping with traditional theory, however, differential utilization of areas (e.g. (Schoener 1968; Richards et al. 2000), and time [e.g. Klopfer 1962; but see MacArthur 1964; Ricklefs 1966)] has been proposed to minimize competition and thus serve as a mechanism to allow co-existence (Trivelpiece, Trivelpiece & Volkman 1987). The data presented here support the contention that the Pygoscelis penguins at King George Island have differences in their space-time foraging patterns. Overlap between species varies between 0Æ29 and 0Æ44 horizontally, 0Æ48 and 69, vertically and 0Æ26 and 0Æ47 temporally. If we assume that differences in utilization of one resource axis are not specifically related to particular features in another axis, then total overlap is determined by multiplying these values together so that

TotalðA \ BÞ ¼ VerticalðA \ BÞ HorizontalðA \ BÞ TemporalðA \ BÞ where Total(A \ B) is the total overlap in all dimensions and the terms on the right hand side refer to the depth, area and temporal overlaps, respectively. Total overlap values are thus 0Æ09 for (A \ C), 0Æ05 for (A \ G) and 0Æ08 for (C \ G), all of which are remarkably small and would superficially seem to support the non-competition contention as originally laid down by MacArthur (1958). But do inter-specific temporally- and spatially-discrete patterns of foraging really lead to absence of competition in animals that utilize the same resource?

The main problem is that before interspecific competition for a common food resource can be ruled out it is necessary to determine the mobility of prey in relation to the difference between resource axis utilization by competitors. Here, the Venn diagram analogy is unhelpful because there is no indication of the degree of difference in mutually-discreet areas. In any event, such a representation would only be useful if it could be put into context by a prey mobility factor. This can be illustrated by a simplistic case using Pygoscelid penguins. Suppose, for example, that we have two adjacent hypervolumes (A and B) [and here we extend the hyper-volume to include temporal differences (Hutchinson 1958; MacArthur 1968)], each being exclusively utilized, respectively, by two species feeding, otherwise, on the same prey. If there is no prey movement between hyper-volumes, then prey depletion (assuming for the sake of simplicity that there is no reproduction or influx from elsewhere) will depend entirely on the amount consumed by each of the predator populations in each hyper-volume and be approximately linear over time (assuming, again for simplicity, that reduced prey density does not lead to extended search times and consequent increased consumption) (dotted line in Fig. 8a). However, if prey are mobile and able to move between hyper-volumes and, more particularly, if differences in prey densities between the two hyper-volumes lead to such movement, then birds feeding in mutually exclusive hyper-volumes may compete. This can be displayed this graphically. For example, prey consumption in hyper-volume A can be taken to be less than that of hyper-volume B (by a factor of 2 in the example in Fig. 8a) and prey considered to move only from high densities to lower densities (i.e. here from A to B). Here, if the rate of transfer is dependent on the difference between the prey numbers in A and B, the rate of transfer of prey from A to B (dx ⁄ dt) can be given by: dx=dt ¼ klðNA NB Þ

eqn 3

where NA and NB are the numbers of prey in hyper-volumes A and B, respectively and the value k1 is the rate constant. This might be analogous to, for example, predation in hyper-volume B reducing krill populations so that phytoplankton levels increase making this area attractive to animals from area A (this ignores the fact that by moving to hyper-volume B, prey might increase their chances of mortality which might, in any event, be balanced by enhanced fecundity). Note that k1 is critical in influencing the rate of transfer and may be directly likened to prey mobility. Graphically, the linear decreases in prey populations due to predation in both A and B represent the non-movement scenario (Fig. 8a) (note that the effort necessary to forage by the predators is assumed to be directly proportional to prey density). Departures from this are due to competition which stems from predator-induced differential density leading to prey movement (Fig. 8a). These departures, a direct measure of competition, become more radical with increasing prey mobility (Fig. 8a) and are best visualized as being specifically due to competition by subtracting the projected prey


Competition in sympatric penguins 655

Prey in hypervolume A

(a) 1000

K1 = 0·01 K1 = 0·03 K1 = 0·1 K1= 0·3

900

800

700

(b)

2

4

6

8

10 12 Time

14

16

Perceived competition in hyper-volume A

100

18

t = 20

t = 15 50 t = 10

t=5 0

0

0·1 0·2 0·3 Rate of movement between hyper-volumes

Fig. 8. (a) Changes in prey populations over time in one of two mutually-exclusive hyper-volumes (A and B) being exploited by two predators, each of these being exclusively faithful to one hyper-volume. The scenario assumes that consumed prey are not replaced and that consumption rates in B are twice those of A. The rate of prey movement from A to B is given by: dx ⁄ dt = k1(XA)XB), where XA and XB is the number of prey in hyper-volumes A and B, respectively and k1 is the rate constant (see text). The dotted line shows the situation when k1 = 0, the continuous lines with increasingly larger circles represent constants of 0Æ01, 0Æ03, 0Æ1 and 0Æ3, respectively. Note that in both 8a and 8b the time is given in relative units. (b) Perceived effect of inter-specific competition in hyper-volume A using the scenario depicted in (a) as a function of rate constant (k) for a variety of times since movement between the hyper-volumes occurred. The perceived competition is determined by subtracting the putative changes in prey densities over time during conditions of no prey movement from those of where prey are mobile (see text).

populations of mobile prey from those of the projected nonmobile prey according to; Perceived competition ¼ NAðtþ1Þ ððdN=dtÞ:tÞ þ ðððklðNA NB ÞÞtÞ

In fact, prey movement may be expressed in a variety of ways. Movement between adjacent hyper-volumes is assumed to be instantaneous, however, with increasing distance between hyper-volumes the rate of movement may be manifest as a time lag so that competition only manifests itself after this lag has passed. A further conceptual development of this will make it apparent that even inter-specific dietary differences, apparent as different prey length frequency distributions (cf. Southwood 1978), can also be treated under the mobility issue since within a prescribed time, smaller prey become larger and thus effectively move into the field of consideration. The speed with which this happens in relation to predator consumption rates and other factors such as migration etc. decides the extent to which this may be a issue relating to competition or not. Although simplistic, this approach indicates that it is not enough to state that animals feeding on the same resource may avoid competition by utilizing different hyper-volumes. Rather, that the mobility of the prey in relation to the distance between hyper-volumes and the time scale over which animals will be using the resource is critical in determining this. It may be that, given the speed of movement of krill (Kanda, Takagi & Seki 1982), the differences observed in the hyper-volumes used by Pygoscelid penguins breeding at Ardley Island are enough to reduce, or even avoid, inter-specific competition. However, the complexity of the calculation to determine this, which should be based on rates of renewal of prey stocks in the relevant areas, aspects of diel vertical migration etc. would auger for no simple solution in the foreseeable future. In conclusion, although the premise that different species utilizing a common resource might experience reduced competition by exploiting different niches is well established, practical demonstration that this is the case in the wild can be problematic. The potentially large number of axes making up the hyper-volume that defines a speciesspecific niche means that even small interspecific differences in a large number of axes will tend towards apparent overall separation of the niches. Although this augurs for a reduction in interspecific competition, this effect can be negated if the food source is mobile and able to move along niche axes in time, in spatial distribution, or even in different growth stages. Future studies will need to consider the complexity of the issue carefully.

eqn 4

where NA(t+1) is the number of prey in hypervolume A at time t + 1, and the ((dN ⁄ dt).t) and (((k1(NA)NB))t) terms refer to the number of prey removed by the predators in hypervolume A and the numbers of prey leaving for hypervolume B, respectively by time t (Fig. 8b). Consideration of Fig. 8b indicates that the degree of perceived competition in A is particularly sensitive to small values of k1, the tendency of the prey to move between the two areas. Thus, despite the simplistic nature of this scenario, it would seem that even a small degree of prey mobility leading to movement between spatially-discrete predator foraging areas, can lead to substantial competition.

Acknowledgements This study was supported by the Deutsche Forschungsgemeinschaft and the Japanese Ministry for Education Science and Culture. I am grateful to the Alfred Wegener Institute and Base Marsh for logistic support as well as to Rudi Bannasch and Boris Culik for help in diverse ways. Thanks are also extended to Akiko Kato, Shingo Minamikawa, Yasuhiko Naito, Yan Ropert-Coudert and Antje Steinfurth for support, both knowingly and unknowingly.

References Abramski, Z., Rosenzweig, M.L. & Subach, A. (2001) The costs of interspecific competition in two gerbil species. Journal of Animal Ecology, 70, 561– 567.


656 R. P. Wilson Ainley, D.G., Ribic, C.A., Ballard, G., Heath, S., Gaffney, I., Karl, B.J., Barton, K.J., Wilson, P.R. & Webb, S. (2004) Geographic structure of Ade´lie Penguin populations: Overlap in colony-specific foraging areas. Ecological Monographs, 74, 159–178. Alonzo, S.H., Switzer, P.V. & Mangel, M. (2003) Ecological games in space and time: The distribution and abundance of Anarctic krill and penguins. Ecology, 84, 1598–1607. Aschoff, J. & Pohl, H. (1970) Rhythmic variations in energy metabolism. 29, 1541–1552. Davis, California, USA, Federation Proceedings. Bannasch, R., Wilson, R.P. & Culik, B. (1994) Hydrodynamics aspects of design and attachment of a back-mounted device in penguins. Journal of Experimental Biology, 194, 83–96. Beamish, F.W.H. (1978) Swimming capacity. In:Fish Physiology, Vol. III (eds W.S. Hoar & D. Randall), pp. 101–187. Academic Press, New York. Benvenuti, F., Bonadonna, L., Dall’Antonia & Gudmundsson, G.A. (1998) Foraging flights of breeding thick-billed murres (Uria lomvia) as revealed by bird-borne direction recorders. Auk, 115, 57–66. Boyd, I.L. & Croxall, J.P. (1996) Dive durations in pinnipeds and seabirds. Canadian Journal of Zoology, 74, 1696–1705. Burger, A.E. (1991) Maximum diving depths and underwater foraging in alcids and penguins. In:Studies of High-Latitude Seabirds. 1. Behavioural, Energetic and Oceanographic Aspects of Seabird Feeding Ecology (eds W.A. Montevecchi & J.A. Gaston), pp. 9–15. Canadian Wildlife Service, Ottawa. Butler, P.J. & Jones, D.R. (1997) Physiology of diving of birds and mammals. Physiological Reviews, 77, 837–899. Carbone, C. & Houston, A.I. (1994) Patterns in the diving behaviour of the Pochard Athya ferina: a test of an optimality model. Animal Behaviour, 48, 457–465. Carbone, C. & Houston, A.I. (1996) The optimal allocation of time over the dive cycle: an approach based on aerobic and anaerobic respiration. Animal Behaviour, 51, 1247–1255. Churchfield, S., Nesterenko, V.A. & Shvarts, E.A. (1999) Food niche overlap and ecological separation amoungst six species of coexisitng forest shrews (Insectivora: Soricidae) in the Russian Far East. Journal of Zoology London, 248, 349–359. Connell, J.H. (1983) On the prevalence and relative importance of interspecific competition: evidence from field experiments. American Naturalist, 122, 661–696. Cooke, S.J., Hinch, S.G., Wikelski, M., Andews, R.D., Kuchel, L.J., Wolcott, T.G. & Butler, P.J. (2004) Biotelemetry: a mechanistic approach to ecology. Trends in Ecology and Evolution., 19, 334–343. Croxall, J.P. & Kirkwood, E.D. (1979) The Distribution of Penguins on the Antarctic Peninsula and Islands of the Scotia Sea. British Antarctic Survey, Cambridge. Culik, B.M., Wilson, R.P. & Bannasch, R. (1994) Underwater swimming at low energetic cost by pygoscelid penguins. Journal of Experimental Biology, 197, 65–78. Denno, B.F., McClure, M.S. & Ott, J.R. (1995) Interspecific interactions in phytophagous insects: competition re-examined and resurrected. Annual Review of Entomology, 40, 297–331. Gause, G.F. (1934) The Struggle for Existence. Williams and Wilkins, Baltimore. Godlewska, M. & Klusek, Z. (1987) Vertical distribution and diurnal migrations of krill Euphausia superba Dana from hydroacoustic obervations SIBEX, December 1983 ⁄ January 1984. Polar Biology, 8, 17–22. Hardin, G. (1960) The competitive exclusion principle. Science, 131, 1292– 1297. Hinke, J.T., Salwicka, K., Trivelpiece, S.G., Watters, G.M. & Trivelpiece, W.Z. (2007) Divergent responses of Pygoscelis penguins reveal a common environmental driver. Oecologia, 153, 845–855. Hodgson, J.R., He, X., Schindler, D.E. & Kitchell, J.F. (1997) Diet overlap in a piscivore community. Ecology of freshwater fish, 6, 144–149. Houston, A.I. & Carbone, C. (1992) The optimum allocation of time during the dive cycle. Behavioural Ecology, 3, 255–265. Hudson, D.M. & Jones, D.R. (1986) The influence of body mass on the endurance to restrained sub-mergence in the Pekin duck. Journal of Experimental Biology, 120, 351–367. Huston, M.A. (1994) Biological Diversity: The Coexistence of Species in Changing Landscapes. Cambridge University Press, Cambridge. Hutchinson, G.E. (1958) Concluding remarks. Cold Spring Harbour Symposium on Quantitative Biology, 22, 417–427. Hutchinson, G.E. (1959) Homage to Santa Rosalia, or why are there so many different kinds of animals? American Naturalist, 93, 145–159. Hutchinson, G.E. (1978). An Introduction to Population Ecology. Yale Univ. Press, New Haven ⁄ London.

Ichii, T., Katayama, K., Obitsu, N., Ishii, H. & Naganobu, M. (1998) Occurrence of Antarctic krill (Euphausia superba) concentrations in the vicinity of the South Shetland Islands: relationship to environmental parameters. Deep-sea Research, 1, 1235–1262. Jablonski, P.G. & Lee, S.D. (1998) Foraging niche differences between species are correlated with body-size differences in mixed-species flocks near Seoul, Korea. Ornis Fennica, 76, 17–23. Jansen, J.K., Russell, R.W.. & Meyer, W.R. (2002) Seasonal shifts in the provisioning behavior of chinstrap penguins Pygoscelis Antarctica. Oecologia, 131, 306–318. Kanda, K., Takagi, K. & Seki, Y. (1982) Movement of the larger swarms of Antarctic krill Euphausia superba off Enderby land during the 1976-77 season. Journal of Tokyo University Fisheries, 68, 24–42. Klopfer, P.H. (1962) Behavioural Aspects of Ecology. Prentice Hall, Englewood Cliffs, New Jersey. Kooyman, G.L. (1989a) Diverse Divers :Physiology and Behavior. SpringerVerlag, Berlin. Kooyman, G.L. (1989b) Hydrodynamics, swim velocity and power requirements. In: Diverse Divers (eds W. Burggren, S. Ishii, H. Langer, G. Neuweiler & D. Randall), pp. 129–142, Springer-Verlag, Berlin Heidelberg. Lack, D. (1947) Darwin’s Finches. Cambridge University Press, Cambridge. Lack, D. (1971) Ecological Isolation in Birds. Harvard University Press, Cambridge, Mass. Levins, R. (1968) Evolution in Changing Environments.Princeton Unversity Press, Princeton. Lynnes, A.S., Reid, K. & Croxall, J.P. (2004) Diet and reproductive success of Ade´lie and chinstrap penguins: linking response of predators to prey population dynamics. Polar Biology, 27, 544–554. Lynnes, A.S., Reid, K., Croxall, J.P. & Trathan, P.N. (2002) Conflict or co-existence?. Foraging distribution and competition for prey between Ade´lie and chinstrap penguins Marine Biology, 141, 1165–1174. MacArthur, R.H. (1958) Population ecology of some warblers of northeastern coniferous forests. Ecology, 39, 599–619. MacArthur, R.H. (1964) Environmental factors affecting bird species diversity. American Naturalist, 98, 387–397. MacArthur, R.H. (1968) The theory of the niche. In Population biology and evolution (ed R.C. Lewontin), pp. 159–176. Syracuse University Press, Syracase, New York, USA. MacArthur, J.W. & Levins, R. (1967) The limiting similarity, convergence and divergence of co-existing species. American Naturalist, 101, 377–385. McDonald, R.A. (2002) Resource partitioning among British and Irish mustelids. Journal of Animal Ecology, 71, 185–200. Miller, A.K. & Trivelpiece, W.Z. (2007) Cycles of Euphausia superba recruitment evident in the diets of Pygoscelid penguins and net trawls in the South Shetland Islands, Antarctica. Polar Biology, 30, 1615–1623. Miller, A.K. & Trivelpiece, W.Z. (2008) Chinstrap penguins alter foraging and diving behavior in response to the size of their principle prey, Antarctic krill. Marine Biology, 154, 201–208. Olson, M:.H., Young, B.P. & Blinkoff, K.D. (2003) Mechanisms underlying habitat use of juvenile largemouth bass and smallmouth bass. Transactions of the American Fisheries Society, 132, 398–405. Peters, R.H. (1983) The Ecological Implications of Body Size. Cambridge University Press, Cambridge. Priviter, D., Chiantore, M., Mangialajo, L., Glavic, N., Kozul, W. & CattaneoVietti, R. (2008) Inter- and intra-specific competition between Paracentrotus lividus and Arbacia lixula in resource-limited barren areas. Journal of Sea Research, 60, 184–192. Richards, S.A., Nisbet, R.M., Wilson, W.G. & Possingham, H.P. (2000) Grazers and diggers: exploiting competition among foragers with different feeding strategies on a single resource. American Naturalist, 155, 266–279. Ricklefs, R.E. (1966) The temporal component of diversity among species of birds. Evolution, 20, 235–242. Ropert-Coudert, Y., Kato, A., Bost, C.-A., Rodary, D., Sato, K., Le Maho, Y. & Naito, Y. (2002) Do Ade´lie Penguins modify their foraging behaviour in pursuit of different prey. Marine Biology, 140, 647–652. Salewski, V., Bairlein, F. & Leisler, B. (2003) Niche partitioning of two Plaearctic passerine migrants with Afrotropical residents in their West African winter quarters. Behavioral Ecology, 14, 493–502. Schoener, T.W. (1968) The Anolis lizards of Bimini: resource partitioning in a complex fauna. Ecology, 49, 704–726. Schoener, T.W. (1974) Resource partitioning in ecological communities. Science, 185, 27–39. Schoener, T.W. (1983) Field experiments on interspecific competition. American Naturalist, 122, 240–285.


Competition in sympatric penguins 657 Schoener, T.W. (1985) Some comments on Connell’s and my reviews of field experiments in interspecific competition. American Naturalist, 125, 730– 740. Seabloom, E.W., Harpole, W.S., Reichman, O.J. & Tilman, D. (2003) Invasion, competition dominance, and resource use by exotic and native California grassland species. Proceedings of the National Academy of Sciences USA, 100, 13384–13389. Shepard, E.L.C., Wilson, R.P., Quintana, F., Gomez Laich, A. & Forman, D.W. (2009). Pushed for time or saving on fuel: fine-scale energy budgets shed light on currencies in a diving bird. Proceedings of the Royal Society B. doi: 10.1098/rspb.2009.0683 Southwood, T.R.E. (1978) Ecological Methods With Particular Reference to the Study of Insect Populations, 2nd edn. Methuen, London. Thompson, D., Hiby, A. & Fedak, M. (1993) How fast should I swim? Behavioural implications of diving physiology. Symposium of the Zoological Society of London, 66, 349–368. Trivelpiece, W.Z., Trivelpiece, S.G. & Volkman, N.J. (1987) Ecological segregation of Adelie, Gentoo and chinstrap penguins at King Geogre Island, Antarctica. Ecology, 68, 351–361. Videler, J.J. & Nolet, B.A. (1990) Costs of swimming measured at optimum speed: scale effects, differences between swimming styles, toxonomic groups and submerged and surface swimming. Compative Biochemistry and Physiology A, 97, 91–99. Volkman, N.J., Presler, P. & Trivelpiece, W.Z. (1980) Diets of pygoscelid penguins at King George Island, Antarctica. Condor, 82, 373–378. Watanuki, Y., Kato, A., Mori, Y. & Naito, Y. (1993) Diving performance of Ade´lie penguins in relation to food availability in fast sea ice areas – comparison between years. Journal of Animal Ecology, 62, 634–646. Wauters, L.A., Hurnell, J., Martinoli, A. & Tosi, G. (2001) Does interspecific competition with introduced grey squirrels affect foraging and food choice of Eurasian red squirrels? Animal Behaviour, 61, 1079–1091. Whitehead, M.D. (1989) Maximum diving depths of the Ade´lie penguin, Pygoscelis adeliae, during the chick-rearing period in Prydz Bay, Antarctica. Polar Biology, 9, 329–332. Williams, A. (1995) The Penguins Spheniscidae. Oxford University Press, Oxford. Williams, T.M., Davis, R.W., Fuiman, L.A., Francis, J., Le Boeuf, B.J., Horning, M., Calambokidis, J. & Croll, D.A. (2000) Sink or swim: strategies for cost-efficient diving by marine mammals. Science, 288, 133–136. Wilson, R.P. (1995) Foraging Ecology. In: Bird Families of the World: The penguins Spheniscidae (eds C. Perrins, W. Bock & J. Kikkawa), pp. 81–106, Oxford University Press, Oxford.

Wilson, R.P. (2001) Beyond rings on birds for determination of movements, Whither the archival tag? Ardea, 89, 231–240. Wilson, R.P. & Culik, B.M. (1995) Energy studies of free-living seabirds: do injections of doubly labeled water affect Gentoo Penguin behavior? Journal of Field Ornithology, 66, 484–491. Wilson, R.P., Ropert-Coudert, Y. & Akiko, K. (2002b) Rush and grab strategies in foraging marine endotherms: The case for haste in penguins. Animal Behaviour, 63, 85–95. Wilson, R.P. & Wilson, M.-P.T.J. (1990) Foraging ecology of breeding Spheniscus penguins. In:Penguin Biology (eds L.S. Davis & J. Darby), pp. 181– 206, Academic Press, Orlando, California. Wilson, R.P., Culik, B.M., Bannasch, R. & Driesen, H.H. (1993) Monitoring penguins at sea using data loggers. Proceedings of the 12th International Symposium on Biotelemetry. Biotelemetry, 12, 205–214. Wilson, R.P., Pu¨tz, K., Peters, G., Culik, B.M., Scolaro, J.A., Charrassin, J.-B. & Ropert-Coudert, Y. (1997) Long-term attachment of transmitting and recording devices to penguins and other seabirds. Wildlife Society Bulletin, 25, 101–106. Wilson, R.P., Gre´millet, D., Syder, J., Kierspel, M.A.M., Garthe, S., Weimerskirch, H., Scha¨fer-Neth, C., Scolaro, J.A., Bost, C.-A., Plo¨tz, J. & Nel, D. (2002a) Remote-sensing systems and seabirds: Their use and abuse and potential for monitoring marine environmental variables? Marine Ecology Progress Series, 228, 241–261. Wilson, R.P., Liebsch, N., Davies, I.M., Flavio Quintana, F., Weimerskirch, H., Storch, S., Lucke, K., Siebert, U., Zankl, S., Muller, G., Ilka Zimmer, I., Scolaro, A., Campagna, C., Plotz, J., Bornemann, H., Teilmann, J. & McMahon, C.R. (2007) All at sea with animal tracks; methodological and analytical solutions for the resolution of movement. Deep Sea Research, 54, 193–210. Woehler, E.J. (1993) The distribution and abundance of Antarctic and sub-Antarctic penguins. Scientific Committee on Antarctic Research, Cambridge. Ydenberg, R.C. & Clark, C.W. (1989) Aerobiosis and anaerobiosis during diving by Western Grebes: an optimal foraging approach. Joournal of Theoretical Biology, 139, 437–439. Ydenberg, R.C. & Forbes, L.S. (1988) Diving and foraging in the Western Grebe. Ornis Scandinavica, 19, 129–133. Zusi, L. (1975) An interpretation of skull structure in penguins. In:The Biology of Penguins (ed B. Stonehouse), pp. 59–84, MacMillan Press, London. Received 5 June 2009; accepted 17 September 2009 Handling Editor: Daniel Costa
