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Foraging tactics of an aquatic insect: Partial consumption of prey
Anita. Behav., 1984, 32, 774-781
FORAGING TACTICS OF AN AQUATIC INSECT: PARTIAL CONSUMPTION OF PREY BY DANIEL R. FORMANOWICZ JR.* Biology Department, St. Lawrence University, Canton, New York 13617, U.S.A. Abstract. Optimal patch foraging theory has recently been used to model partial consumption of prey by predators (Cook & Coekrell 1978; Sih 1980). I tested several predictions of this model with larvae of the predaceous diving beetle Dytiscus verticalis, which are predators of anuran tapdoles. The results of the study supported the qualitative predictions of the model. The prediction of decreasing search time with increasing prey density was confirmed. Handling time and the amount ingested per prey item also decreased with decreasing search time. A quantitative test of the optimal foraging model revealed that it accurately predicted handling times when prey densities were high but failed to do so at low prey densities. Two hypotheses based on mean extraction rates are proposed in an attempt to explain these results. Introduction Some predators do not consume their prey intact but instead take a series of bites or otherwise extract the contents of their prey. This mode of feeding behaviour has been termed partial consumption (Sih 1980) or 'wasteful killing' (Johnson et al. 1975). Three models have been proposed to explain the foraging behaviour of predators exhibiting partial consumption of prey. The general predictions of these models are that as prey density increases, the handling time per prey item and the amount ingested by the forager per prey item will decrease (Cook & CockreU 1978; DeBenedictis et al. 1978; Sih 1980). Although the predictions of the three models are qualitatively similar, the hypothesized mechanisms involved in partial consumption are quite different. DeBenedictis et al. (1978) suggested that active or highly mobile foragers, such as hummingbirds, are limited in the size of their optimal meal by the effect of the added weight of the meal on the forager's cost of mobility. An efficient forager acting under this constraint should partially consume food items in such a way as to minimize the weight of the meal and hence the cost of subsequent movement while maintaining a sufficient energy intake. Johnson et al. (1975) proposed a model that represents an extension of Holling's (1966) hypothesis of gut limitation on the number of prey items that could be killed by a predator. Their model postulated a two-gut-compartment system to explain 'wasteful killing' of Daphnia by damselfly (Zygoptera) nymphs. The hypothesis stated that partial consumption of prey should
occur whenever the foregut of a nymph was full and the midgut only partially full. Hunger in the foregut was thought to be associated with prey capture and subsequent feeding responses, whereas hunger in the midgut and the foregut may be responsible for the prey-capture response (Johnson et al. 1975). Therefore, an insect predator may strike at prey because of midgut hunger, but only consume part of the prey because the foregut is relatively full. Sih (1980) noted that both of the above models have limited applications. The model on decreased efficiency of movement (DeBenedictis et al. 1978) assumes that the added weight of the meal must significantly increase the energetic cost of carrying that meal (Sih 1980). Johnson et al.'s (1975) two-gut-compartment model may only apply when predators are at or near satiation. Cook & Cockrell (1978) and Sih (1980) proposed an alternative model to explain partial consumption, based on optimal foraging theory. In this model, each prey item was considered to be a patch and the foraging strategy of a predator would include the 'choice' of continuing to feed on an already captured prey item or searching for a new item (Cook & Cockrell 1978; Sih 1980). They presented graphical models (based on Parker & Stuart 1976) to predict how long a predator should feed on a prey item (handling time) and its ingestion rate as a function of the length of the search time. The partial consumption model assumes that: (1) the ingestion rate is a curvilinear function (g(t); Fig. 1) of feeding time such that as the feeding time increases, the ingestion rate increases at a decreasing rate to an asymptote, which corresponds to the total amount of food contained in the prey item; (2)
*Presentaddress:BiosphericsInc., 4928WyacondaRoad, Rockville, MD 20852, U.S.A. 774
FORMANOWICZ: AQUATIC INSECT FORAGING
g(t)
'~1
t2
"rhlTh2
t
Fig. 1. The optimal foraging theory graphical model of partial consumption of prey. Adapted from Cook & Cockrell (1978) and Sih (1980). T~-=handling time, t= search time, thl=predicted handling time, g(t)=energy extracted. the amount of food ingested by a predator increases as feeding time increases; and (3) the search time is a decreasing function of prey availability. This last assumption is based on the idea that as prey availability increases, the amount of time it takes to find prey (search time) decreases (Fig. 1). Although these assumptions appear to be seriously restrictive, they clearly fit for notonectids (Hemiptera) (Cook & Cockrell 1978; Sih 1980). The specific predictions generated by the model are: (1) the search time of a partially consuming predator should decrease as prey availability increases; and (2) the feeding time per prey item captured and the amount of each prey item ingested by a predator should decrease as prey availability increases and hence search time decreases. There appear to be few available data for testing these predictions. Cook & Cockrell (1978) found that for notonectids the ingestion rate was a decreasing function of time spent handling prey; the mean feeding time decreased as the average inter-catch interval decreased, but feeding times on individual prey did not decrease. Sih (1980), also working with notonectids, presented data indicating that the proportion of each prey item eaten decreased as the average prey density increased, but he did not report handling times or search times. Giller (1980) found that notonectids exhibited a positive correlation between handling time and the inter-catch interval, but his experimental design was such that he could not distinguish between the gut-limitation hypothesis and the optimal foraging model. Larvae of the predaceous diving beetle Dytiscus verticalis (Coleoptera: Dytiscidae) feed
775
by sucking out the contents of their prey through enlarged, specialized mandibles (see Formanowicz & Brodie 1981, 1982). Since these beetle larvae, by virtue of their feeding mode, are partial consumers of their prey, they were used to test the following predictions of the optimal foraging model for partial consumption (based on Cook & Cockrell 1978 and Sih 1980). (1) The search time per prey item will decrease as prey density increases. (2) The handling time per prey item and the amount of each prey ingested by the predator will decrease as prey density increases. If prediction (1) is true, then handling time and ingestion will also decrease as search time decreases. (3) Larger predators will ingest more of each prey item but have shorter handling times per prey item than smaller conspecifies. This last hypothesis refers to Cook & Cockrell's (1978) data concerning the effects of prey size on partial consumption. Predator size would be expected to have an effect similar to that of prey size on handling time and ingestion. Methods The Dytiscus verticalis larvae and anuran tadpoles (Rana sylvatica, Ranidae and Hyla crucifer, Hylidae) were collected from ponds on or near the E.N. Huyck Preserve, Rensselaerville, Albany County, New York. The larvae were held in circular plastic chambers (15cm in diameter, 6.5 cm deep, containing 4-5 cm of water) under natural lighting conditions and were fed three 0.4-ml tadpoles daily until tested. All larvae and tadpoles were sized by displacement (volume) to minimize the risk of injuring them during handling (Brodie et al. 1978). Three sizes (instars) of D. verticalis larvae were chosen for the experiments, and were designated small (0.1 ml), medium (0.5 ml) and large (1.0 ml). All of the tadpoles used as prey were approximately 0.4 ml in size. Two species of tadpole were used because of the large numbers of prey that were needed. The two species were not mixed in any of the test chambers, and preference experiments (Formanowicz 1982) indicated that the beetle larvae exhibited no preference for either species. Handling time and the amount of each prey ingested by the beetle larvae were measured at five prey densities (25, 50, 100, 200 and 400 tadpoles/pool) during the second 24 h of functional response experiments (Formanowicz 1982). The pools used as test chambers were 1 m in diameter and contained approximately 90 litres of water. One beetle larva was introduced into each pool and allowed to forage for 24 h at
ANIMAL
776
BEHAVIOUR,
one of the five prey densities before data were taken. Sample sizes for handling time and amount ingested per prey can be found below in the legend to Figs 2 and 4 respectively. When a D. verticalis larva was observed capturing prey, I recorded the time from seizure of the prey item to the release of the remains of the killed prey item (the handling time TH). The remains were collected and immediately preserved in 70% alcohol. These remains were later weighed on a Mettler balance. I also preserved 10 intact R. sylvatiea and 10 intact H. crueifer tadpoles (ca 0.4 ml) in 70 % alcohol and weighed these on the Mettler balance. The weight of the prey remains was subtracted from the mean weight of the intact tadpoles to obtain the amount of each tadpole that had been ingested by the beetle larva (I1,). Handling time data were collected for small, medium and large larvae at all five prey densities. The ingestion data were available in sufficient sample sizes for statistical analyses only for the medium and large larvae. Using data on the handling time and the amount of each prey item ingested at the five prey densities, I was able to estimate the extraction rates of the medium and large larvae with the following equation: Ip E=-
(1) T~I
where E = the extraction rate (g/min) and Ip = the amount of prey (g) ingested by a beetle larva during a given handling time Ta~. The search time per prey item was calculated for the medium and large larvae at all five prey densities using the equation for the attack rate derived from Real's (1977) form of the functional response model: NA a=
(2) No TT--NAT~No
where a is the attack rate, NA is the number of prey killed, No is the prey density, and TT is the total foraging time. Equation (2) can be rearranged as follows: 1
TT--T~NA -
aNo
(3)
Na
The numerator of the right side of (3) represents the search time, which when divided by NA gives the search time per prey item. Equation (3) can therefore be simplified to:
32,
3 1
rs=--
(4)
aNo where Ts is the search time per prey. The values for a and N• were taken from Formanowicz (1982), and N o = 2 5 , 50, 100, 200 and 400. Single-classification analysis of variance and Student-Newmans-Keuls tests (SNK; a posteriori tests) were used to test for differences in handling time, grams ingested per prey item, extraction rates, and search times across prey densities and between larval sizes (Sokal & Rohlf 1969; a=0.05). Pearson product-moment correlation coefficients (r) and least-squares regression analysis were also used to analyse some of the data (Sokal & Rohlf 1969). Curvilinear regression and least-squares fits were used to analyse the grams ingested and handling time (the ingestion function) data. Linear and curvilinear regression analyses were done on the raw data in all cases. Parametric statistics were appropriate because the data were homoscedastic (Bartlett's test of homogeneity of variance) and independent. Results Handling Time
There was a significant negative correlation between handling time and prey density for all three instars of D. verticalis larvae (Fig. 2; small, r = --0.77; medium, r = --0.67; large, r = --0.67; P<0.05). Single-classification analysis of variance also indicated a significant effect of prey density on handling time for the three instars of beetle larvae (P < 0.001; Fig. 2). The SNK comparisons of the handling times indicate significant differences between all of the prey densities for all three instars (P<0.05), except between densities of 25 and 50 for the medium and large larvae. When the handling times at each prey density were compared across the three larval sizes (ANOVA and SNK tests), there were no significant differences found at prey densities of 25, 50 or 400 ( P > 0.05). There were, however, significant difibrences (P<0.01) in handling time between the three larval instars at tadpole densities of 100 and 200 (Fig. 2). At a prey density of 100, the medium larvae had a significantly longer handling time (P < 0.05; SNK tests) than either the small or large beetle larvae, but there were no significant differences in handling time between the small and large larvae at this prey density ( P > 0.05). At a prey density of 200, the large larvae had significantly shorter handling times
FORMANOWICZ:
50
~
AQUATIC INSECT FORAGING
777
small
medium
5O x
+'-~ ....
medium
large
5O
large 25 50
100
Prey
200
400"
Density
Fig. 2. T h e h a n d l i n g time per prey item captured (T~) as a function o f prey density for three instars o f Dytiscus verticatis. T h e s y m b o l s represent m e a n s ; vertical lines are 95 ~ confidence intervals. (a) Small larvae; N = 8 at prey densities o f 25, 100, 200 a n d 400 a n d N = t O at 50. (b) M e d i u m larvae; N = 1 0 at 25, 50 a n d 200, N = 1 6 at 100 a n d N = 1 9 at 400. (c) Large larvae; N = 1 0 at 25, 50 a n d 200 a n d N = 11 at 100 a n d 400.
than the two smaller instars (P < 0.05), but there were no significant differences in handling times of the small and medium larvae at this prey density (P > 0.05).
25 50
200
Prey
400
Density
Fig. 3. The a m o u n t ingested (g) per prey item c a p t u r e d by two sizes o f Dytiscus verticalis larvae as a f u n c t i o n o f prey density. Symbols are m e a n s a n d vertical lines are 95 ~o confidence intervals. (a) M e d i u m larvae; N = 10 at 50 a n d 100, N = l l at 25, a n d N = 1 3 at 200 a n d 400. (b) Large larvae; N = 8 at 50 a n d 200, N = 9 at 100 a n d 400, a n d N = 1 2 at 25.
Table I. Student-Newman-Keuls Comparisons of the Amount of Prey Ingested for Two Sizes of Beetle Larvae Larval size M e d i u m (0.5 ml)
Ingestion There was a significant negative correlation between the amount of each prey ingested and prey density for the medium and large larvae (P<0.05; medium, r=--0.69; large, r=--0.71; Fig. 3). The data for the small larvae were not sufficient for statistical analysis. Single-classification analysis of variance indicated that the amount ingested was significantly affected by prey density for both sizes of beetle larvae (P < 0.005). The SNK comparisons are presented in Table I. In general, the amount of each prey item ingested decreased as prey density increased. There was no significant difference between the medium and large larvae in the amount ingested per prey item at any of the five densities. Curvilinear regression analysis and leastsquares fits of the handling time and ingestion
100
Large (1.0 ml)
Prey density
25
50
100
25 50 100 200 400
-NS * * *
-NS * *
-* *
25 50 100 200 400
-Ns
--
NS
NS
* *
* *
200
-
400
-
NS
--
--
* *
-
-
NS
--
*Difference significant at P < 0 . 0 5 . NS: n o t significant, P > 0 . 0 5 .
data indicated that for both the medium and large beetle larvae, a second-order function of the form y = a + b x + c x 2 explained significantly more of the variance in the ingestion function (P < 0.05, medium, y = 0.0033 + 0.15x--0.002x 2; P < 0.01, large, y=0.064 + 1.74x--0.025x z) than linear regression (Fig. 4). The relationship bet-
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778
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ween handling time and amount ingested for both sizes of beetle larvae was consistent with the form of the ingestion function assumed by the optimal foraging model of partial consumption (Fig. 1). Extraction Rate
There were significant differences in the extraction rate (g/rain) among the five prey densities for both the medium and large D. verticalis larvae (P < 0.05; A N O V A and S N K tests; Fig. 5). The medium larvae showed a significantly higher extraction rate (P < 0.05) at a prey density of 400 than at densities of 25 and 50. N o other comparisons of extraction rate for the medium larvae were significant (P>0.05). The large larvae showed a significantly higher extraction rate (P<0.05) at prey densities of 100, 200 and 400 than at densities of 25 or 50, but there were no significant differences in extraction rate (P > 0.05) between 25 and 50. It appears that the extraction rate or feeding rate (E) increased after a density of 50 and then levelled off at densities of 100,
~ :" :'-
32,
3
200 and 400 (Fig. 5). These data indicate that the rate of extraction was at least partially dependent on the prey density. Either the beetle larvae were able to adjust the speed with which they extracted food from a prey item, or some of the prey contents were more difficult to remove than other contents. Search Time
The search time per prey item captured (Ts) for the small, medium and large larvae was calculated from the attack rate a and the prey density NA using eqnation 4. The values for the attack rate are from Formanowicz (1982)9 The relevant data on attack rate, prey density, and search time per prey are presented in Table II. In general, the search time per prey (Ts) decreased as prey density increased for all three sizes of beetle larvae. Dis cussien
The results of this study support some of the qualitative predictions of the optimal foraging model describing partial consumption of prey by certain types of predators (Cook & Cockrell 1978; Sih 1980). As predicted, the handling time, amount ingested, and search time per prey item
"..
ta)
9
3,
medium
%" : 9
(a)
+ 2
~15
hrge (b)
lH
30
Fig. 4. The ingestion functions (the amount ingested per prey, Ip, plotted against T~x, the handling time) for the (a) medium; y=0.0033-t-O.15x-0.002x 2 and (b) large; y=0.64+ 1.74x--0.025x ~ D. verticalis larvae. Symbols are the individual data points. The two curves were fitted using the least-squares method to the equation y=aqbx + cx~.
7~
60
2 5 50
100
~00
400
Pre~ ~ensit~
Fig. 5. The extraction rate as a function of prey density for medium (a) and large (b) beetle larvae. Symbols are means and vertical lines are 95 % confidence intervals.
FORMANOWICZ: AQUATIC INSECT FORAGING
779
Table H. The Search Time per Prey Item (Ts) Calculated from Equation 4
Dytiscus verticalis size
0.1 ml Prey density 25 50 100 200 400
0.5 ml
1.0 ml
a
Ts
a
Ts
a
Ts
96.6 152 131.7 95.9 51.5
414.1 131.6 75.9 52.1 48.5
275.6 267.2 163.6 124.9 50.1
145.1 74.9 61.1 40.0 49.9
298 279.3 174.3 103,7 61.4
137.9 71.6 57.4 48.7 40.7
a is the attack rate: values are x 10-6. Ts is time in min. captured by the beetle larvae decreased as prey density increased. However, there were no consistent differences in handling times between the three sizes of beetle larvae, or in the amount ingested per prey item by the medium and large larvae. This fails to support the third hypothesis posed earlier in this paper concerning the potential effects of predator size. The above result is somewhat surprising in light of the effect of prey size on the amount of each prey ingested by notonectids. Cook & Cockrell (1978) found that the amount of each prey item ingested increased and feeding time decreased as prey size decreased relative to predator size. Differences in predator size would be expected to have an effect analogous to that of prey size on partial consumption, with handling time decreasing and the amount ingested increasing as predator size increased. Since this was not the case in this study, there may be additional factors involved in the relationship between handling time, amount ingested and predator size. Gut size or gut limitation mechanisms can be ruled out as factors influencing partial consumption of prey by these beetle larvae. The medium and large larvae consumed essentially the same amount of prey (total for 48 h) at the five prey densities, even though their guts are substantially different in size (Formanowicz 1982). This suggests that there could be differences in the processing time of food in the gut which could result in similar ingestion amounts for the two instars of larvae. There is, however, no information available on food passage time through the guts of D. verticalis larvae. The Model
The graphical model of Parker & Stuart (1976) (Fig. 1) which qualitatively predicted the trends in the handling time, search time, and amount
ingested per prey item found in this study, was also examined quantitatively. The data on search time, handling time and amount ingested were put into the form of the optimal foraging model (Fig. 6). The handling times predicted b y the model were then determined by drawing a line tangent to the ingestion function from the appropriate search time. As Fig. 6 illustrates for the large beetle larvae, the model underestimated the length of the handling time at the two lowest prey densities (25 and 50) when search times were long. The observed mean handling times for prey densities of 25 and 50 were 49.6 and 44.4 min respectively. The handling times predicted from the model (Fig. 6, thl, tit2) were approximately 26.4 and 19.2 min respectively for densities of 25 and 50. In both cases, the predicted handling times were not within the 95 ~ confi-
Ip
150
thl th2
TS
50
Tu Min
Fig. 6. The data on search times, handling times and grams extracted put into the form of the optimal foraging model of partial consumption. Ts=the search time per prey, Ta=handling time, 1p=grams extracted, tin=the predicted handling time at a prey density of 50, tn2=the predicted handling time at a density of 25, solid dot 1= the observed handling time at 50, solid dot 2=observed handling time at 25, and lines 1 and 2=tangents from the search times for prey densities of 50 and 25 respectively.
780
ANIMAL
BEHAVIOUR,
dence intervals of the observed mean handling times. The model did however predict the handling times for prey densities of 100, 200 and 400 within the 95 ~ confidence intervals of the observed means at these densities. Therefore, the optimal foraging model of partial consumption proposed by Cook & Cockrell (1978) and Sih (1980) (Fig. 1) predicted handling times fairly accurately when search times per prey were short and prey densities were high, but underestimated the handling times when search times were long and prey densities were low. The failure of the model to predict the handling times at low prey densities may be the result of the relationship between the extraction rate and prey density (Fig. 5). The extraction rate was significantly higher at prey densities of 100, 200 and 400 than at densities of 25 and 50. In other words, the mean rate of removal of food from a prey item by beetle larvae was higher at the three highest prey densities than at the low prey densities. There are two hypotheses that could explain the lower extraction rates found in this study at low prey densities. (1) A prey item may contain food of different qualities. A portion of the food may be easily removed, yielding low handling times and high extraction rates, while other portions may be more difficult to remove, requiring longer handling times and lower extraction rates. At high prey densities (low search time) the predator may only be ingesting the easily extracted portions, while at low prey densities (high search times) the predator may be removing both the easy and hard-to-remove portions. This would result in the mean extraction rate being lower at low prey densities than at high prey densities. This hypothesis is based on the 'last dreg theory' proposed by Whitham (1977) to explain the feeding behaviour of bumblebees foraging on flowers that contained easily removed nectar in pools and hard-toremove nectar in grooves. (2) The second hypothesis is based on the premise that all of the food in the prey item is of equal quality. The predator may be sucking or extracting food from a prey item at a lower rate at low prey densities than at high prey densities. If we assume that the energetic cost of extracting or sucking food from a prey item is important to the overall energy budget of the predator, the following hypothesis can be proposed. A predator that is searching at a high rate, at low prey densities, and therefore has a high energetic cost o f searching, may utilize a low extraction rate while feeding on a
32,
3
prey item in order to minimize the cost of extraction and perhaps decrease overall energetic costs, thereby increasing net energetic gains. This could result in longer handling times than predicted by the model. At high prey densities, when search costs are tow, a predator may utilize a more costly energetic tactic of higher extraction rates, which could minimize the handling time. Essentially the predators may be minimizing extraction time and therefore handling time (and costs), but within the constraints of search costs. This would create a trade-off situation between search costs and extraction costs for predators that partially consume their prey.
Acknowledgments This research was supported by research fellowships from the E.N. Huyck Preserve Inc. and N S F DEB78-11196 (E. D. Brodie Jr.). K. Able, E. D. Brodie, Jr., J. Brown, S. Brown, R. G. Jaeger and H. R. Pulliam provided helpful comments and advice on the research, R. G. J., H. R. P. and S. D. Strahl read the manuscript. The suggestions of L. Real and an anonymous reviewer are greatly appreciated. M. S. Bobka helped in collection of data, experimental design, and preparation of the manuscript.
REFERENCES Brodie, E. D., Jr., Formanowicz, D. R., Jr. & Brodie, E. D. III. 1978. The development of noxiousness of Bufo americanus tadpoles to aquatic insect predators. Herpetologica, 34, 302-306. Cook, R. M. & Cockrell, B. J. 1978. Predator ingestion rate and its bearing on feeding time and the theory of optimal diets. J. Anita. Ecol., 47, 529-547. DeBenedictis, P. A., Gill, F. B., Hainsworth, F. R. & Pyke, G. H. 1978. Optimal meal size in hummingbirds. Am. Nat., 112, 301-316. Formanowicz, D. R., Jr. 1982. Foraging dynamics of an aquatic insect: relationships between predatory behavior and functional response. Ph.D. thesis, State University of New York at Albany. Formanowicz, D. R., Jr. & Brodie, E. D., Jr. 1981. Prepupation behavior and a description of pupation in the predaceous diving beetle Dytiscus verticalis Say (Coleoptera: Dytiscidac). J. N.Y. entomol. Soc., 89, 152-157. Formanowicz, D. R., Jr. & Brodie, E. D., Jr. 1982. Relative palatabilities of a larval amphibian community. Copeia, 1982, 91-97. Giller, P. S. 1980. The control of handling time and its effects on the foraging strategy of a Heteropteran predator Notonecta. J. Anita. Ecol., 49, 699-712. Holling, C. S. 1966. The functional response of invertebrate predators to prey density. Mem. entomol. Soc. Can., 48, 1-86. Johnson, D. M., Akre, B. G. & Crowley, P. H. 1975. Modeling predation in arthropods: wasteful killing by damselfly naiads. Ecology, 56, 1081-1093.
F O R M A N O W I C Z : A Q U A T I C INSECT F O R A G I N G Parker, G. A. & Smart, R. A. 1976. Animal behavior as a strategy: evolution of resource assessment strategies and optimal emigration thresholds. Am. Nat., 110, 1055-1076. Real, L. 1977. The kinetics of functional response. Am. Nat., 111, 289-300. Sih, A. 1980. Optimal foraging: partial consumption of prey. Am. Nat., 116, 281-290.
781
Sokal, R. R. & Rohlf, F. J. 1969. Biometry. San Franeisco: W. H. Freeman. Whitham, T. G. 1977. Coevolution of foraging in Bombus and nectar dispensing in Chilopsis: a last dreg theory. Science, N.Y., 197, 593-596.
(Received 24 June 1983; revised 13 October 1983; MS. number: A4023)
FORAGING TACTICS OF AN AQUATIC INSECT: PARTIAL CONSUMPTION OF PREY BY DANIEL R. FORMANOWICZ JR.* Biology Department, St. Lawrence University, Canton, New York 13617, U.S.A. Abstract. Optimal patch foraging theory has recently been used to model partial consumption of prey by predators (Cook & Coekrell 1978; Sih 1980). I tested several predictions of this model with larvae of the predaceous diving beetle Dytiscus verticalis, which are predators of anuran tapdoles. The results of the study supported the qualitative predictions of the model. The prediction of decreasing search time with increasing prey density was confirmed. Handling time and the amount ingested per prey item also decreased with decreasing search time. A quantitative test of the optimal foraging model revealed that it accurately predicted handling times when prey densities were high but failed to do so at low prey densities. Two hypotheses based on mean extraction rates are proposed in an attempt to explain these results. Introduction Some predators do not consume their prey intact but instead take a series of bites or otherwise extract the contents of their prey. This mode of feeding behaviour has been termed partial consumption (Sih 1980) or 'wasteful killing' (Johnson et al. 1975). Three models have been proposed to explain the foraging behaviour of predators exhibiting partial consumption of prey. The general predictions of these models are that as prey density increases, the handling time per prey item and the amount ingested by the forager per prey item will decrease (Cook & CockreU 1978; DeBenedictis et al. 1978; Sih 1980). Although the predictions of the three models are qualitatively similar, the hypothesized mechanisms involved in partial consumption are quite different. DeBenedictis et al. (1978) suggested that active or highly mobile foragers, such as hummingbirds, are limited in the size of their optimal meal by the effect of the added weight of the meal on the forager's cost of mobility. An efficient forager acting under this constraint should partially consume food items in such a way as to minimize the weight of the meal and hence the cost of subsequent movement while maintaining a sufficient energy intake. Johnson et al. (1975) proposed a model that represents an extension of Holling's (1966) hypothesis of gut limitation on the number of prey items that could be killed by a predator. Their model postulated a two-gut-compartment system to explain 'wasteful killing' of Daphnia by damselfly (Zygoptera) nymphs. The hypothesis stated that partial consumption of prey should
occur whenever the foregut of a nymph was full and the midgut only partially full. Hunger in the foregut was thought to be associated with prey capture and subsequent feeding responses, whereas hunger in the midgut and the foregut may be responsible for the prey-capture response (Johnson et al. 1975). Therefore, an insect predator may strike at prey because of midgut hunger, but only consume part of the prey because the foregut is relatively full. Sih (1980) noted that both of the above models have limited applications. The model on decreased efficiency of movement (DeBenedictis et al. 1978) assumes that the added weight of the meal must significantly increase the energetic cost of carrying that meal (Sih 1980). Johnson et al.'s (1975) two-gut-compartment model may only apply when predators are at or near satiation. Cook & Cockrell (1978) and Sih (1980) proposed an alternative model to explain partial consumption, based on optimal foraging theory. In this model, each prey item was considered to be a patch and the foraging strategy of a predator would include the 'choice' of continuing to feed on an already captured prey item or searching for a new item (Cook & Cockrell 1978; Sih 1980). They presented graphical models (based on Parker & Stuart 1976) to predict how long a predator should feed on a prey item (handling time) and its ingestion rate as a function of the length of the search time. The partial consumption model assumes that: (1) the ingestion rate is a curvilinear function (g(t); Fig. 1) of feeding time such that as the feeding time increases, the ingestion rate increases at a decreasing rate to an asymptote, which corresponds to the total amount of food contained in the prey item; (2)
*Presentaddress:BiosphericsInc., 4928WyacondaRoad, Rockville, MD 20852, U.S.A. 774
FORMANOWICZ: AQUATIC INSECT FORAGING
g(t)
'~1
t2
"rhlTh2
t
Fig. 1. The optimal foraging theory graphical model of partial consumption of prey. Adapted from Cook & Cockrell (1978) and Sih (1980). T~-=handling time, t= search time, thl=predicted handling time, g(t)=energy extracted. the amount of food ingested by a predator increases as feeding time increases; and (3) the search time is a decreasing function of prey availability. This last assumption is based on the idea that as prey availability increases, the amount of time it takes to find prey (search time) decreases (Fig. 1). Although these assumptions appear to be seriously restrictive, they clearly fit for notonectids (Hemiptera) (Cook & Cockrell 1978; Sih 1980). The specific predictions generated by the model are: (1) the search time of a partially consuming predator should decrease as prey availability increases; and (2) the feeding time per prey item captured and the amount of each prey item ingested by a predator should decrease as prey availability increases and hence search time decreases. There appear to be few available data for testing these predictions. Cook & Cockrell (1978) found that for notonectids the ingestion rate was a decreasing function of time spent handling prey; the mean feeding time decreased as the average inter-catch interval decreased, but feeding times on individual prey did not decrease. Sih (1980), also working with notonectids, presented data indicating that the proportion of each prey item eaten decreased as the average prey density increased, but he did not report handling times or search times. Giller (1980) found that notonectids exhibited a positive correlation between handling time and the inter-catch interval, but his experimental design was such that he could not distinguish between the gut-limitation hypothesis and the optimal foraging model. Larvae of the predaceous diving beetle Dytiscus verticalis (Coleoptera: Dytiscidae) feed
775
by sucking out the contents of their prey through enlarged, specialized mandibles (see Formanowicz & Brodie 1981, 1982). Since these beetle larvae, by virtue of their feeding mode, are partial consumers of their prey, they were used to test the following predictions of the optimal foraging model for partial consumption (based on Cook & Cockrell 1978 and Sih 1980). (1) The search time per prey item will decrease as prey density increases. (2) The handling time per prey item and the amount of each prey ingested by the predator will decrease as prey density increases. If prediction (1) is true, then handling time and ingestion will also decrease as search time decreases. (3) Larger predators will ingest more of each prey item but have shorter handling times per prey item than smaller conspecifies. This last hypothesis refers to Cook & Cockrell's (1978) data concerning the effects of prey size on partial consumption. Predator size would be expected to have an effect similar to that of prey size on handling time and ingestion. Methods The Dytiscus verticalis larvae and anuran tadpoles (Rana sylvatica, Ranidae and Hyla crucifer, Hylidae) were collected from ponds on or near the E.N. Huyck Preserve, Rensselaerville, Albany County, New York. The larvae were held in circular plastic chambers (15cm in diameter, 6.5 cm deep, containing 4-5 cm of water) under natural lighting conditions and were fed three 0.4-ml tadpoles daily until tested. All larvae and tadpoles were sized by displacement (volume) to minimize the risk of injuring them during handling (Brodie et al. 1978). Three sizes (instars) of D. verticalis larvae were chosen for the experiments, and were designated small (0.1 ml), medium (0.5 ml) and large (1.0 ml). All of the tadpoles used as prey were approximately 0.4 ml in size. Two species of tadpole were used because of the large numbers of prey that were needed. The two species were not mixed in any of the test chambers, and preference experiments (Formanowicz 1982) indicated that the beetle larvae exhibited no preference for either species. Handling time and the amount of each prey ingested by the beetle larvae were measured at five prey densities (25, 50, 100, 200 and 400 tadpoles/pool) during the second 24 h of functional response experiments (Formanowicz 1982). The pools used as test chambers were 1 m in diameter and contained approximately 90 litres of water. One beetle larva was introduced into each pool and allowed to forage for 24 h at
ANIMAL
776
BEHAVIOUR,
one of the five prey densities before data were taken. Sample sizes for handling time and amount ingested per prey can be found below in the legend to Figs 2 and 4 respectively. When a D. verticalis larva was observed capturing prey, I recorded the time from seizure of the prey item to the release of the remains of the killed prey item (the handling time TH). The remains were collected and immediately preserved in 70% alcohol. These remains were later weighed on a Mettler balance. I also preserved 10 intact R. sylvatiea and 10 intact H. crueifer tadpoles (ca 0.4 ml) in 70 % alcohol and weighed these on the Mettler balance. The weight of the prey remains was subtracted from the mean weight of the intact tadpoles to obtain the amount of each tadpole that had been ingested by the beetle larva (I1,). Handling time data were collected for small, medium and large larvae at all five prey densities. The ingestion data were available in sufficient sample sizes for statistical analyses only for the medium and large larvae. Using data on the handling time and the amount of each prey item ingested at the five prey densities, I was able to estimate the extraction rates of the medium and large larvae with the following equation: Ip E=-
(1) T~I
where E = the extraction rate (g/min) and Ip = the amount of prey (g) ingested by a beetle larva during a given handling time Ta~. The search time per prey item was calculated for the medium and large larvae at all five prey densities using the equation for the attack rate derived from Real's (1977) form of the functional response model: NA a=
(2) No TT--NAT~No
where a is the attack rate, NA is the number of prey killed, No is the prey density, and TT is the total foraging time. Equation (2) can be rearranged as follows: 1
TT--T~NA -
aNo
(3)
Na
The numerator of the right side of (3) represents the search time, which when divided by NA gives the search time per prey item. Equation (3) can therefore be simplified to:
32,
3 1
rs=--
(4)
aNo where Ts is the search time per prey. The values for a and N• were taken from Formanowicz (1982), and N o = 2 5 , 50, 100, 200 and 400. Single-classification analysis of variance and Student-Newmans-Keuls tests (SNK; a posteriori tests) were used to test for differences in handling time, grams ingested per prey item, extraction rates, and search times across prey densities and between larval sizes (Sokal & Rohlf 1969; a=0.05). Pearson product-moment correlation coefficients (r) and least-squares regression analysis were also used to analyse some of the data (Sokal & Rohlf 1969). Curvilinear regression and least-squares fits were used to analyse the grams ingested and handling time (the ingestion function) data. Linear and curvilinear regression analyses were done on the raw data in all cases. Parametric statistics were appropriate because the data were homoscedastic (Bartlett's test of homogeneity of variance) and independent. Results Handling Time
There was a significant negative correlation between handling time and prey density for all three instars of D. verticalis larvae (Fig. 2; small, r = --0.77; medium, r = --0.67; large, r = --0.67; P<0.05). Single-classification analysis of variance also indicated a significant effect of prey density on handling time for the three instars of beetle larvae (P < 0.001; Fig. 2). The SNK comparisons of the handling times indicate significant differences between all of the prey densities for all three instars (P<0.05), except between densities of 25 and 50 for the medium and large larvae. When the handling times at each prey density were compared across the three larval sizes (ANOVA and SNK tests), there were no significant differences found at prey densities of 25, 50 or 400 ( P > 0.05). There were, however, significant difibrences (P<0.01) in handling time between the three larval instars at tadpole densities of 100 and 200 (Fig. 2). At a prey density of 100, the medium larvae had a significantly longer handling time (P < 0.05; SNK tests) than either the small or large beetle larvae, but there were no significant differences in handling time between the small and large larvae at this prey density ( P > 0.05). At a prey density of 200, the large larvae had significantly shorter handling times
FORMANOWICZ:
50
~
AQUATIC INSECT FORAGING
777
small
medium
5O x
+'-~ ....
medium
large
5O
large 25 50
100
Prey
200
400"
Density
Fig. 2. T h e h a n d l i n g time per prey item captured (T~) as a function o f prey density for three instars o f Dytiscus verticatis. T h e s y m b o l s represent m e a n s ; vertical lines are 95 ~ confidence intervals. (a) Small larvae; N = 8 at prey densities o f 25, 100, 200 a n d 400 a n d N = t O at 50. (b) M e d i u m larvae; N = 1 0 at 25, 50 a n d 200, N = 1 6 at 100 a n d N = 1 9 at 400. (c) Large larvae; N = 1 0 at 25, 50 a n d 200 a n d N = 11 at 100 a n d 400.
than the two smaller instars (P < 0.05), but there were no significant differences in handling times of the small and medium larvae at this prey density (P > 0.05).
25 50
200
Prey
400
Density
Fig. 3. The a m o u n t ingested (g) per prey item c a p t u r e d by two sizes o f Dytiscus verticalis larvae as a f u n c t i o n o f prey density. Symbols are m e a n s a n d vertical lines are 95 ~o confidence intervals. (a) M e d i u m larvae; N = 10 at 50 a n d 100, N = l l at 25, a n d N = 1 3 at 200 a n d 400. (b) Large larvae; N = 8 at 50 a n d 200, N = 9 at 100 a n d 400, a n d N = 1 2 at 25.
Table I. Student-Newman-Keuls Comparisons of the Amount of Prey Ingested for Two Sizes of Beetle Larvae Larval size M e d i u m (0.5 ml)
Ingestion There was a significant negative correlation between the amount of each prey ingested and prey density for the medium and large larvae (P<0.05; medium, r=--0.69; large, r=--0.71; Fig. 3). The data for the small larvae were not sufficient for statistical analysis. Single-classification analysis of variance indicated that the amount ingested was significantly affected by prey density for both sizes of beetle larvae (P < 0.005). The SNK comparisons are presented in Table I. In general, the amount of each prey item ingested decreased as prey density increased. There was no significant difference between the medium and large larvae in the amount ingested per prey item at any of the five densities. Curvilinear regression analysis and leastsquares fits of the handling time and ingestion
100
Large (1.0 ml)
Prey density
25
50
100
25 50 100 200 400
-NS * * *
-NS * *
-* *
25 50 100 200 400
-Ns
--
NS
NS
* *
* *
200
-
400
-
NS
--
--
* *
-
-
NS
--
*Difference significant at P < 0 . 0 5 . NS: n o t significant, P > 0 . 0 5 .
data indicated that for both the medium and large beetle larvae, a second-order function of the form y = a + b x + c x 2 explained significantly more of the variance in the ingestion function (P < 0.05, medium, y = 0.0033 + 0.15x--0.002x 2; P < 0.01, large, y=0.064 + 1.74x--0.025x z) than linear regression (Fig. 4). The relationship bet-
ANIMAL
778
BEHAVIOUR,
ween handling time and amount ingested for both sizes of beetle larvae was consistent with the form of the ingestion function assumed by the optimal foraging model of partial consumption (Fig. 1). Extraction Rate
There were significant differences in the extraction rate (g/rain) among the five prey densities for both the medium and large D. verticalis larvae (P < 0.05; A N O V A and S N K tests; Fig. 5). The medium larvae showed a significantly higher extraction rate (P < 0.05) at a prey density of 400 than at densities of 25 and 50. N o other comparisons of extraction rate for the medium larvae were significant (P>0.05). The large larvae showed a significantly higher extraction rate (P<0.05) at prey densities of 100, 200 and 400 than at densities of 25 or 50, but there were no significant differences in extraction rate (P > 0.05) between 25 and 50. It appears that the extraction rate or feeding rate (E) increased after a density of 50 and then levelled off at densities of 100,
~ :" :'-
32,
3
200 and 400 (Fig. 5). These data indicate that the rate of extraction was at least partially dependent on the prey density. Either the beetle larvae were able to adjust the speed with which they extracted food from a prey item, or some of the prey contents were more difficult to remove than other contents. Search Time
The search time per prey item captured (Ts) for the small, medium and large larvae was calculated from the attack rate a and the prey density NA using eqnation 4. The values for the attack rate are from Formanowicz (1982)9 The relevant data on attack rate, prey density, and search time per prey are presented in Table II. In general, the search time per prey (Ts) decreased as prey density increased for all three sizes of beetle larvae. Dis cussien
The results of this study support some of the qualitative predictions of the optimal foraging model describing partial consumption of prey by certain types of predators (Cook & Cockrell 1978; Sih 1980). As predicted, the handling time, amount ingested, and search time per prey item
"..
ta)
9
3,
medium
%" : 9
(a)
+ 2
~15
hrge (b)
lH
30
Fig. 4. The ingestion functions (the amount ingested per prey, Ip, plotted against T~x, the handling time) for the (a) medium; y=0.0033-t-O.15x-0.002x 2 and (b) large; y=0.64+ 1.74x--0.025x ~ D. verticalis larvae. Symbols are the individual data points. The two curves were fitted using the least-squares method to the equation y=aqbx + cx~.
7~
60
2 5 50
100
~00
400
Pre~ ~ensit~
Fig. 5. The extraction rate as a function of prey density for medium (a) and large (b) beetle larvae. Symbols are means and vertical lines are 95 % confidence intervals.
FORMANOWICZ: AQUATIC INSECT FORAGING
779
Table H. The Search Time per Prey Item (Ts) Calculated from Equation 4
Dytiscus verticalis size
0.1 ml Prey density 25 50 100 200 400
0.5 ml
1.0 ml
a
Ts
a
Ts
a
Ts
96.6 152 131.7 95.9 51.5
414.1 131.6 75.9 52.1 48.5
275.6 267.2 163.6 124.9 50.1
145.1 74.9 61.1 40.0 49.9
298 279.3 174.3 103,7 61.4
137.9 71.6 57.4 48.7 40.7
a is the attack rate: values are x 10-6. Ts is time in min. captured by the beetle larvae decreased as prey density increased. However, there were no consistent differences in handling times between the three sizes of beetle larvae, or in the amount ingested per prey item by the medium and large larvae. This fails to support the third hypothesis posed earlier in this paper concerning the potential effects of predator size. The above result is somewhat surprising in light of the effect of prey size on the amount of each prey ingested by notonectids. Cook & Cockrell (1978) found that the amount of each prey item ingested increased and feeding time decreased as prey size decreased relative to predator size. Differences in predator size would be expected to have an effect analogous to that of prey size on partial consumption, with handling time decreasing and the amount ingested increasing as predator size increased. Since this was not the case in this study, there may be additional factors involved in the relationship between handling time, amount ingested and predator size. Gut size or gut limitation mechanisms can be ruled out as factors influencing partial consumption of prey by these beetle larvae. The medium and large larvae consumed essentially the same amount of prey (total for 48 h) at the five prey densities, even though their guts are substantially different in size (Formanowicz 1982). This suggests that there could be differences in the processing time of food in the gut which could result in similar ingestion amounts for the two instars of larvae. There is, however, no information available on food passage time through the guts of D. verticalis larvae. The Model
The graphical model of Parker & Stuart (1976) (Fig. 1) which qualitatively predicted the trends in the handling time, search time, and amount
ingested per prey item found in this study, was also examined quantitatively. The data on search time, handling time and amount ingested were put into the form of the optimal foraging model (Fig. 6). The handling times predicted b y the model were then determined by drawing a line tangent to the ingestion function from the appropriate search time. As Fig. 6 illustrates for the large beetle larvae, the model underestimated the length of the handling time at the two lowest prey densities (25 and 50) when search times were long. The observed mean handling times for prey densities of 25 and 50 were 49.6 and 44.4 min respectively. The handling times predicted from the model (Fig. 6, thl, tit2) were approximately 26.4 and 19.2 min respectively for densities of 25 and 50. In both cases, the predicted handling times were not within the 95 ~ confi-
Ip
150
thl th2
TS
50
Tu Min
Fig. 6. The data on search times, handling times and grams extracted put into the form of the optimal foraging model of partial consumption. Ts=the search time per prey, Ta=handling time, 1p=grams extracted, tin=the predicted handling time at a prey density of 50, tn2=the predicted handling time at a density of 25, solid dot 1= the observed handling time at 50, solid dot 2=observed handling time at 25, and lines 1 and 2=tangents from the search times for prey densities of 50 and 25 respectively.
780
ANIMAL
BEHAVIOUR,
dence intervals of the observed mean handling times. The model did however predict the handling times for prey densities of 100, 200 and 400 within the 95 ~ confidence intervals of the observed means at these densities. Therefore, the optimal foraging model of partial consumption proposed by Cook & Cockrell (1978) and Sih (1980) (Fig. 1) predicted handling times fairly accurately when search times per prey were short and prey densities were high, but underestimated the handling times when search times were long and prey densities were low. The failure of the model to predict the handling times at low prey densities may be the result of the relationship between the extraction rate and prey density (Fig. 5). The extraction rate was significantly higher at prey densities of 100, 200 and 400 than at densities of 25 and 50. In other words, the mean rate of removal of food from a prey item by beetle larvae was higher at the three highest prey densities than at the low prey densities. There are two hypotheses that could explain the lower extraction rates found in this study at low prey densities. (1) A prey item may contain food of different qualities. A portion of the food may be easily removed, yielding low handling times and high extraction rates, while other portions may be more difficult to remove, requiring longer handling times and lower extraction rates. At high prey densities (low search time) the predator may only be ingesting the easily extracted portions, while at low prey densities (high search times) the predator may be removing both the easy and hard-to-remove portions. This would result in the mean extraction rate being lower at low prey densities than at high prey densities. This hypothesis is based on the 'last dreg theory' proposed by Whitham (1977) to explain the feeding behaviour of bumblebees foraging on flowers that contained easily removed nectar in pools and hard-toremove nectar in grooves. (2) The second hypothesis is based on the premise that all of the food in the prey item is of equal quality. The predator may be sucking or extracting food from a prey item at a lower rate at low prey densities than at high prey densities. If we assume that the energetic cost of extracting or sucking food from a prey item is important to the overall energy budget of the predator, the following hypothesis can be proposed. A predator that is searching at a high rate, at low prey densities, and therefore has a high energetic cost o f searching, may utilize a low extraction rate while feeding on a
32,
3
prey item in order to minimize the cost of extraction and perhaps decrease overall energetic costs, thereby increasing net energetic gains. This could result in longer handling times than predicted by the model. At high prey densities, when search costs are tow, a predator may utilize a more costly energetic tactic of higher extraction rates, which could minimize the handling time. Essentially the predators may be minimizing extraction time and therefore handling time (and costs), but within the constraints of search costs. This would create a trade-off situation between search costs and extraction costs for predators that partially consume their prey.
Acknowledgments This research was supported by research fellowships from the E.N. Huyck Preserve Inc. and N S F DEB78-11196 (E. D. Brodie Jr.). K. Able, E. D. Brodie, Jr., J. Brown, S. Brown, R. G. Jaeger and H. R. Pulliam provided helpful comments and advice on the research, R. G. J., H. R. P. and S. D. Strahl read the manuscript. The suggestions of L. Real and an anonymous reviewer are greatly appreciated. M. S. Bobka helped in collection of data, experimental design, and preparation of the manuscript.
REFERENCES Brodie, E. D., Jr., Formanowicz, D. R., Jr. & Brodie, E. D. III. 1978. The development of noxiousness of Bufo americanus tadpoles to aquatic insect predators. Herpetologica, 34, 302-306. Cook, R. M. & Cockrell, B. J. 1978. Predator ingestion rate and its bearing on feeding time and the theory of optimal diets. J. Anita. Ecol., 47, 529-547. DeBenedictis, P. A., Gill, F. B., Hainsworth, F. R. & Pyke, G. H. 1978. Optimal meal size in hummingbirds. Am. Nat., 112, 301-316. Formanowicz, D. R., Jr. 1982. Foraging dynamics of an aquatic insect: relationships between predatory behavior and functional response. Ph.D. thesis, State University of New York at Albany. Formanowicz, D. R., Jr. & Brodie, E. D., Jr. 1981. Prepupation behavior and a description of pupation in the predaceous diving beetle Dytiscus verticalis Say (Coleoptera: Dytiscidac). J. N.Y. entomol. Soc., 89, 152-157. Formanowicz, D. R., Jr. & Brodie, E. D., Jr. 1982. Relative palatabilities of a larval amphibian community. Copeia, 1982, 91-97. Giller, P. S. 1980. The control of handling time and its effects on the foraging strategy of a Heteropteran predator Notonecta. J. Anita. Ecol., 49, 699-712. Holling, C. S. 1966. The functional response of invertebrate predators to prey density. Mem. entomol. Soc. Can., 48, 1-86. Johnson, D. M., Akre, B. G. & Crowley, P. H. 1975. Modeling predation in arthropods: wasteful killing by damselfly naiads. Ecology, 56, 1081-1093.
F O R M A N O W I C Z : A Q U A T I C INSECT F O R A G I N G Parker, G. A. & Smart, R. A. 1976. Animal behavior as a strategy: evolution of resource assessment strategies and optimal emigration thresholds. Am. Nat., 110, 1055-1076. Real, L. 1977. The kinetics of functional response. Am. Nat., 111, 289-300. Sih, A. 1980. Optimal foraging: partial consumption of prey. Am. Nat., 116, 281-290.
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Sokal, R. R. & Rohlf, F. J. 1969. Biometry. San Franeisco: W. H. Freeman. Whitham, T. G. 1977. Coevolution of foraging in Bombus and nectar dispensing in Chilopsis: a last dreg theory. Science, N.Y., 197, 593-596.
(Received 24 June 1983; revised 13 October 1983; MS. number: A4023)