Natural selection by avian predators on size and colour of a freshwater snail (Pomacea flagellata)

Biological Journal of the Linnean Society (1999), 67: 331–342. With 4 figures Article ID: bijl.1998.0305, available online at http://www.idealibrary.com on

Natural selection by avian predators on size and colour of a freshwater snail (Pomacea flagellata) WENDY L. REED∗ AND FREDRIC J. JANZEN Department of Zoology and Genetics, Iowa State University, Ames, IA 50011, U.S.A. Received 18 September 1998; accepted for publication 20 December 1998

We identify two avian predators of the Neotropical apple snail, Pomacea flagellata, and estimate the strength, direction and form of multivariate natural selection by these predators on size and colour of snail shells. Limpkins are tactile predators and act as agents of disruptive selection on snail size, selecting average-sized snails disproportionately more often than small or large snails (c′=0.39, SE=0.08). In addition, we were able to identify variation in handling behaviours and snail size selection among individual limpkins. Individual limpkins showed preferences for snails of different sizes and punctured the snail shells opposite the aperture mainly when handling large snails. Snail kites are visual predators and seem to be agents of directional selection against lighter coloured snails (b′=0.66, SE=0.33). The ecological interaction between the apple snail and its predators provides a powerful system to further explore the role of predation in determining evolutionary changes in snail behaviour, morphology and life history.  1999 The Linnean Society of London

ADDITIONAL KEY WORDS:—limpkin – snail kite – disruptive selection.

CONTENTS

Introduction . . . . . . . . . . . . . . . . . Methods . . . . . . . . . . . . . . . . . . Study species . . . . . . . . . . . . . . . Collections and measurements . . . . . . . . . Statistical analyses . . . . . . . . . . . . . Results . . . . . . . . . . . . . . . . . . Limpkin predation . . . . . . . . . . . . . Mixed predators . . . . . . . . . . . . . . Discussion . . . . . . . . . . . . . . . . . Limpkins as agents of disruptive selection on snail size . Mixed predators as agents of differential selection on snail Acknowledgements . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . .

. . . . . . . . . . size . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . and colour . . . . . . . .

. . . . . . . . . . . .

332 333 333 333 334 335 335 336 337 337 339 340 341

∗ Corresponding author. E-mail: [email protected] 0024-4066/99/070331+12 $30.00/0

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W. L. REED AND F. J. JANZEN INTRODUCTION

A major focus of evolutionary ecology has been to understand predator–prey interactions (Cockburn, 1991). From an ecological perspective, extensive research has provided insight into how predator–prey assemblages interact to influence population dynamics (see Begon, Harper & Townsend, 1996 for review). We are also beginning to explore predator-prey interactions from a quantitative, microevolutionary perspective (e.g. Reznick & Endler, 1982; Rodd & Reznick, 1991). The combination of knowledge of the ecology of predators and prey, the strength and mode of selection by predators, and estimates of quantitative genetic parameters can provide a powerful tool for predicting microevolutionary change (Lande & Arnold, 1983; Wade & Kalisz, 1990; Brodie, Moore & Janzen, 1995; Grant & Grant, 1995; Reznick, Shaw & Rod, 1997). Thus, an important first step in developing an evolutionary understanding of predator–prey interactions is to evaluate predators and prey in the context of mortality selection in natural populations. Studies of selection in natural populations are numerous (Endler, 1986), and much of the historical information fundamental to our current understanding of natural selction has been generated by investigations of snail populations. For example, fluctuating selection (Sheppard, 1951; Wolda, 1963; Carter, 1968; Ha¨kkinen & Koponen, 1982), directional selection (Cain & Sheppard, 1954), frequencydependent selection (Harvey, Birley & Blackstock, 1975; Allen, Raymond & Geburtig, 1988), and disruptive selection (Bantock & Bayley, 1973; Bantock, Bayley & Harvey, 1975) have all been documented in snail populations. These studies are invaluable to our understanding of natural selection, however, most of them are incomplete due to a focus on the patterns of natural selection instead of on the mechanisms (see discussion in Wade & Kalisz, 1990). Moreover, most of these studies have analysed the results outside the context of statistical techniques that provide appropriate estimates of parameters used in predictive microevolutionary equations (Lande & Arnold, 1983; Brodie et al., 1995). An excellent predator–prey system for examining the mechanisms of mortality selection and the possible microevolutionary impact involves apple snails (Pomacea spp.) and their two main avian predators, the snail kite (Rostrhamus sociabilis, Vieillot) and the limpkin (Aramus guarauna, Linnaeus). Several studies have described the interactions between these birds and the apple snail (e.g. Snyder & Snyder, 1969; Haverschmidt, 1970; Collett, 1977; Beissinger, 1983; Bourne, 1993). One remarkable aspect of the interaction between these predators and the apple snail is the difference in foraging strategies between snail kites and limpkins. Snail kites are aerial predators and rely heavily on visual cues while hunting, either by flying slowly across a marsh or hovering while searching for snails (Snyder & Snyder, 1969; Haverschmidt, 1970; Beissinger, 1983). In contrast, limpkins rely on tactile cues during foraging by probing beneath vegetation and on the bottoms of marshes for apple snails (Snyder & Snyder, 1969). It is also noteworthy that the difference in foraging strategies between these two predators has been cited as the mechanism behind the observed difference in phenotypic distributions of snails eaten by snail kites versus those snails eaten by limpkins (Collett, 1977; Bourne, 1993). We conducted a short-term field study of a population of apple snails (Pomacea flagellata) in Costa Rica to investigate the strength, direction, form and ecological mechanisms of multivariate natural selection on shell size and colour. Specifically, we examine the possible evolutionary consequences of snail kites and limpkins acting

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as distinct agents of natural selection on apple snails. We exploited two key aspects of limpkin foraging behaviour: (1) their propensity to make holes in shells to procure their meal and (2) their individual habit of making piles of shells after consumption of snails. These behaviours allowed us to evaluate the role of individuals in contributing to the overall patterns of natural selection. Our study illustrates the tractability and strength of this predator–prey system for exploring important questions of evolutionary ecology regarding the mechanisms of selection and potential patterns of microevolutionary change.

METHODS

Study species Apple snails (Pomacea spp.) are large (25–77 mm in length) and occupy tropical and neotropical freshwater habitats, feeding on aquatic plants. The population of P. flagellata we studied (see below) exhibited considerable variation among individuals in both size and colour of shells. The two main predators of the apple snail at our site were the snail kite and limpkin. The snail kite is a medium-sized raptor that feeds almost exclusively on apple snails (Sykes, Rodgers & Bennetts, 1995). The limpkin is a medium-sized wading bird that feeds largely on mollusks. When available, apple snails seem to be a preferred food item for the limpkin (Snyder & Snyder, 1969). Collection and measurements We collected field data approximately one month after the wet season had ended. Water levels at the time of collection were approximately 1–1.5 m in depth and, thus, too high for limpkins to forage off the bottom of the marsh. We observed limpkins probing under, and adjacent to, floating vegetation with their bills. Once a snail was procured, the limpkins moved to a separate location on the aquatic vegetation and consumed the snail. Individual limpkins repeatedly went to the same area to consume snails and made piles of shells at these locations. Snail kites were the only other bird we observed foraging for, and consuming, snails in the marsh; however, most of the predation events we observed involved limpkins. We collected apple snail shells and live individuals in early February 1990, in the Palo Verde marsh at the Organization for Tropical Studies Research Station in Guanacaste, Costa Rica. Empty shells came from two distinct sources: either from piles created by limpkins or from individual shells scattered across the marsh. We collected all shells from 21 piles of apple snails (n=332 shells), 113 shells scattered through the marsh (unpiled shells), and 56 live snails. We distinguished snails that had experienced mortality during the 1989 dry season from those that had experienced mortality during the most recent wet season. Shells of snails that died in previous seasons were heavily damaged and covered with vegetation and periphyton and thus were ignored in our study. We only collected shells of snails that experienced mortality during the most recent wet season for this study. We walked transects placed approximately 3 m apart and searched for live snails under, and adjacent to, local vegetation (Eichhornia crassipes and Typha sp.).

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T 1. Summary statistics for morphometric measurements for each of the three groups of apple snail shells. Values are means±standard deviations

Sample size Aperture length (mm) Aperture width (mm) Spiral height (mm)

Live snails

Piled shells

Unpiled shells

56 28.17±3.57 17.09±2.33 24.00±3.13

332 28.02±2.40 16.98±1.73 23.60±2.42

113 27.85±2.55 16.77±1.81 23.61±2.44

Figure 1. Snails were placed in one of four categories based on shell colour from light (right, designated colour category 1) to dark (left, designated colour category 4). The shell on the extreme right has a hole typically made due to handling by limpkins. The distributions of snails in each colour category are as follows: 2% of the shells in category 1, 6% in category 2, 39% in category 3, and 52% in category 4.

We measured and recorded phenotypes of all snail shells collected. We measured aperture length, aperture width and spiral height to the nearest 0.1 mm with vernier calipers for all live snails and empty shells (Table 1). These three linear measurements of shell size were distributed normally and were highly correlated with one another. Thus, we used these data in a principal components analysis to produce uncorrelated size traits. We scored all shells for colour based on four relatively discrete colour categories, ranging from light to dark and ranking one to four, respectively (Fig. 1). Colour was distributed non-normally; however, colour was not transformed for the analyses of selection. Another character we recorded was the presence or absence of a hole for each empty shell. Limpkins often puncture shells while handling the snails and use the hole to gain access to the snail meal (Collett, 1977). This feeding behaviour allowed us to distinguish limpkin predation from other sources of mortality. Statistical analyses We evaluated differences in size and colour among three categories of snail shells (piled, unpiled, and live) using a one-way analysis of variance for principal components describing size and a G-test for the colour trait. We also assessed directional, stabilizing/disruptive, and correlational selection on snail phenotypes with three complementary analyses. First, we used multiple linear regression to evaluate the direction and strength of selection (Lande & Arnold, 1983). The slopes (i.e. selection gradients=b and c) derived from these analyses are readily interpretable in terms

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T 2. Results from a principal components analysis of aperture length, width and spiral height. Principal component 1 was responsible for 92% of the variation in the three linear measurements of shell size. The other two principal components explained little variation and seemed to account for several outliers in the data set, thus, neither PC2 nor PC3 were used in subsequent analyses of selection Component Eigenvalue Percent E Aperture length Aperture width Spiral height

1

2

3

2.77 92.21

0.17 5.81

0.06 1.97

0.59 0.58 0.57

−0.26 −0.53 0.81

−0.77 0.62 0.16

of microevolution when used in combination with estimates of the quantitative genetic bases of the traits (Lande & Arnold, 1983; Brodie et al., 1995). When using survival (either alive or dead) as the fitness response variable, the associated error variance is non-normal due to the bivariate nature of these data. This violates assumptions of inference in multiple linear regression analyses (Mitchell-Olds & Shaw, 1987; Brodie & Janzen, 1996). Therefore, multiple linear regression provides accurate estimates of selection gradients for microevolutionary interpretation, however, the significance tests are inappropriate. To address the problem of significance testing, we analysed the same data using logistic regression (e.g. Fairbairn & Preziosi, 1994; Grant & Grant, 1995; Kingsolver & Smith, 1995). Logistic regression describes S-shaped relationships between dichotomous and continuous traits. This relationship between response and predictor variables is a more appropriate model to describe the relationship between fitness data (i.e. survival) and phenotypic characters typically obtained in field studies of selection ( Janzen & Stern, 1998). Logistic regression also provides correct estimates of statistical significance. Finally, we used cubic splines to help visualize the forms of selection acting on snail phenotypes (Schluter, 1988). We generated these graphical representations only when multiple linear and logistic regressions first identified traits that significantly influenced snail survival. We analysed all data using JMP version 3 (SAS Institute Inc., 1994). RESULTS

All three morphometric measurements contributed positively and nearly equally to the first principal component, which explained 92% of the total character variation (Table 2). The other two principal components contributed little to the variation in shell size (eigenvalues <<1.0) and for this reason we did not use them in analyses of selection on snail phenotypes ( Jackson, 1993). Limpkin predation Individual limpkins, as represented by unique piles of shells, showed distinct size preferences (F(20,298)=1.61, P=0.05). Individual limpkins also differed in their tendency to puncture the shell during consumption (v2=46.09, df=20, P=0.0008). Over the population sampled, limpkins were more likely to puncture larger snail

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30

Frequency

25

A

20 15 10 5

Frequency

Pr(Survival)

0 –8

–6

–4

–2

0

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6

8

0.8 B 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 –8 –6

–4

–2

0

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4

6

8

6

8

90 C 80 70 60 50 40 30 20 10 0 –8 –6

–4 –2 0 2 4 Principal component 1 (shell size)

Figure 2. Disruptive selection on snail shell size in piled shells. A, distribution of PC1 scores for the live snails. B, cubic spline showing disruptive selection against average sized snails in the piled shells. The outer lines represent the 95% confidence interval for these data. C, distribution of PC1 scores for the shells found in the piles. Limpkins are responsible for the snails in these piles.

shells than smaller snail shells (F(1,317)=9.75, P=0.002). Multiple linear and logistic regression analyses indicated that the combined action of all limpkins resulted in significant disruptive selection on snail size (c′=0.39, SE=0.08, P=0.001, Fig. 2). In other words, snails with average shell sizes occurred more frequently in the piles than in the collection of live individuals. Individual limpkins had no preference for snail colour (v2=51.71, df=60, P= 0.77), nor did colour differ between shells with or without holes (v2=0.67, df=3, P=0.88). There appeared to be no selection by limpkins on snail colour or on its interaction with shell size as indicated by the piled shells. Mixed predators As with piled shells, there was a similar magnitude of disruptive selection on shell size in unpiled shells (c′=0.41, SE=0.10, P=0.04, Fig. 3). However, unlike the

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30

Frequency

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20 15 10 5 0 –8

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–4

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0.6 0.5 0.4 0.3 0.2 0.1 –8 30

Frequency

25

C

20 15 10 5 0 –8

–6

–4 –2 0 2 4 Principal component 1 (shell size)

Figure 3. Disruptive selection on snail shell size in the unpiled shells. A, distribution of PC1 scores for the live snails. B, cubic spline showing disruptive selection against average sized snails in the unpiled shells. The outer lines represent the 95% confidence interval for these data. C, distribution of PC1 scores for the unpiled shells. A mixed predator group is likely responsible for mortality of these snails.

shells from limpkin piles, unpiled shells did not exhibit a statistically significant relationship between shell size and presence or absence of a hole (F(1,110)=3.30, P= 0.07). Unpiled shells were significantly lighter in colour than live snails (F(1,167)=4.52, P=0.04), which resulted in significant directional selection against lighter coloured shells (b′=0.66, SE=0.33, P=0.05, Fig. 4). In other words, lighter coloured shells occurred more frequently in the unpiled shells than in the collection of live snails. DISCUSSION

Limpkins as agents of disruptive selection on snail size We were able to characterize the feeding habits of individual limpkins by examining distinct piles of apple snail shells. Individual limpkins differed in the size of snails

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Frequency

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25 20 15 10 5 0 0.5

Pr(Survival)

B 0.4 0.3 0.2 0.1

60

Frequency

50

C

40 30 20 10 0

1

2

3

4

Shell colour

Figure 4. Directional selection against lighter coloured snail shell size in the unpiled shells. A, distribution of shell colours for the live snails. B, cubic spline showing the shape of selection on snail shell colour. The outer lines represent the 95% confidence interval for these data. Snails with lighter colours (on the left hand side of the figure) were selected more often by predators contributing to the unpiled shells than snails with darker shells (on the right hand side of the figure). C, distribution of shell colours for the unpiled shells.

they consumed, and in their propensity to puncture shells before consuming snails. These results indicate that no single foraging pattern is exhibited by all limpkins in this study area. Snyder & Snyder (1969) also noted among-individual variation in feeding preferences and foraging strategies. Identifying and exploring variation in behaviour among individual animals is critical in understanding how animals optimize their life-history strategies (Davies, 1992). Despite the inter-individual variation in feeding behaviour, the overall foraging behaviour of limpkins resulted in disruptive selection on shell size in apple snails. We propose two equally plausible mechanisms responsible for this mode of selection: (1) size-dependent snail behaviour and snail sizes encountered by limpkins, and/or (2) preferential size selection by limpkins.

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Concerning size-dependent behaviour, snails in the genus Pomacea are known to exhibit an ontogenetic shift in predator avoidance strategies (Snyder & Snyder, 1971; Bourne, 1993). As snails age and pass into successively larger size classes, they change their vertical distribution in the water column and their primary behavioural defense against predators. Large apple snails (P. dolioides, Reeve) spend a higher percentage of their activity period at the water’s surface (Bourne, 1993). The change in vertical distribution with size is accompanied by an additional change in behaviour. Larger snails respond to mechanical disturbances by dropping off vegetation and burying themselves in the substrate more consisently, and more quickly, than smaller snails (Snyder & Snyder, 1971; Bourne, 1993). These behaviours should effectively decrease the frequency with which limpkins encounter large apple snails. Furthermore, because limpkins probe beneath the vegetation and are sensitive to tactile cues, the likelihood of encountering a snail should decrease with the diminishing size of the snail. Therefore, the lower probability of physically encountering smaller snails, in combination with the different predator avoidance behaviours of large snails, may be responsible for the tendency of limpkins to prey upon average sized snails more frequently than small or large snails. The second hypothesis for the observed patterns of selection by limpkins is that these birds preferentially select snails of average size due to decreasing energy gains at either end of the snail size distribution. We found that limpkins were more likely to puncture shells of large snails compared to shells of small snails. This shellpuncturing behaviour suggests that large snails may be more difficult to handle, requiring additional time and energy to puncture the shell and obtain a meal. The optimal prey size for limpkins might then be those snails small enough not to require a hole to procure a meal, but large enough to provide a worthwhile effort (e.g. Richardson & Verbeek, 1986). Our estimates of natural selection on snail size allow for an evaluation of the potential for microevolutionary change. In addition to an increase in the phenotypic variance of shell size, we predict that snails will begin breeding before reaching the risky intermediate size class or that snails may exhibit size-related growth rates that will speed them through this risky size class. These predictions are certainly testable and future experimental studies of limpkin foraging strategies and apple snail behaviour are needed to fully understand the life history implications of the observed pattern of selection against snails at the middle of the size distribution. Mixed predators as agents of differential selection on snail size and colour In contrast to piled shells, unpiled shells result from snail mortality due to multiple causes (i.e. numerous predators or parasite overload). Predators of adult apple snails include snail kites, limpkins, young alligators, crocodiles, and turtles (Snyder & Snyder, 1971). However, of these potential predators, only birds would leave the snail shell intact, whereas other predators would destroy the shell during handling. Thus, we are confident that the sample of unpiled shells represents apple snails either preyed upon by birds or those that died from parasites or other non-predatory causes. Snail kites do not puncture apple snail shells before or after consumption; therefore, we can further reduce the potential predator pool by attributing unpiled shells with holes to limpkin predation. Shells lacking holes represent mortality caused by the combined action of parasites, snail kites and possibly limpkins.

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If limpkins are responsible for a large number of these unpiled shells we expect to find similar patterns of shell size, colour and presence of holes as those shells found in the limpkin piles. We did observe disruptive selection against shell size in both piled and unpiled shells. However, we did not observe a significant relationship between shell size and presence or absence of a hole in unpiled shells, nor did we find a similar pattern with respect to snail colour. These differences in patterns of snail phenotypes between the piled and unpiled shells suggest that different agents were responsible for mortality in these two categories of shells. Snail kites are known to select large snails more often than small snails (Collett, 1977; Beissinger, 1983; Bourne, 1985). In addition to active size-biased snail kite predation, parasite loads may contribute to the vulnerability of larger snails to kite predation. Bourne (1993) found that large snails have more parasites. Furthermore, large snails spend more time at the water’s surface, which increases their probability of being detected by snail kites. Apple snails drop off vegetation and bury themselves in response to mechanical disturbances, but this behaviour is ineffective in avoiding predation by a visual predator hovering over the water. Numerous studies have addressed shell-colour variation in snails (e.g. Slotow & Ward, 1997; Atkinson & Warwick, 1983; see Clarke et al., 1978 for review). In general, lighter coloured snails are more often associated with warmer climates, where it is believed that the lighter coloration confers a thermoregulatory advantage (Clarke et al., 1978; Burla & Gosteli, 1993). Benefits of lighter coloration in apple snails may be countered by a disadvantage of being easily viewed by predators against the dark background of a marsh. In this study, we observed directional selection against light coloured snails in the unpiled shells, suggesting that the lighter coloured snails were taken more often by snail kites than were darker conspecifics. We have characterized the influence of two different predator assemblages exerting selection on shell size and colour in a Neotropical population of apple snails. Limpkins, which are tactile predators, selected snails at the middle of the size distribution, whereas snail kites, which are visual predators, appeared to choose larger and lighter-coloured apple snails. Within this general pattern of snail mortality, we also documented individual differences among limpkins in prey preference and foraging behaviour based on snail size, which may reflect variation in limpkin body size, bill size, foraging ability, age, sex or innate prey preferences. Our investigation of this system exemplifies the tractability of snails as study organisms in evaluations of microevolutionary processes like natural selection. A particular attraction of this system is the distinct differences in foraging modes of the two predators, which permits multivariate analyses of different sources of selection on the same traits. Future investigations of this apple snail system, incorporating experimental manipulations, should prove fruitful in evaluating the hypotheses derived from the patterns of selection detected in this study.

ACKNOWLEDGEMENTS

We are grateful to the Organization for Tropical Studies for making this project possible, and to Steve Shuster and BOP group members for making constructive comments on early drafts of the manuscript. We would like to extend special thanks to Brian Wiegmann for his help with the collection and synthesis of material needed

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for completion of this project. This project could not have been completed without his help. This research was completed with partial support from the University of Chicago, an Iowa State University Research Grant, and National Science Foundation grant DEB-9629529 to FJJ. This is Journal paper No. J-18160 of the Iowa Agriculture and Home Economics Experiment Station, Ames, IA. Project No. 3369, supported by the Hatch Act and State of Iowa Funds.

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