Failure of simple optimal foraging models to predict residence time when patch quality is uncertain

Blue jays (Cyanocitta cristata) were presented with a foragingsituation in which half of the patches they encountered containedno prey and half contained a single prey item. Experimentallydetermined probability distributions controlled prey arrivaltimes in those patches that contained prey. Patch residencein empty patches was studied during four experiments. In thefirst, prey arrival was exponentially distributed. Residencetimes increased with travel time as predicted by a rate-maximizationmodel, but the bird stayed in empty patches much longer thanpredicted. During the second experiment, prey arrival was uniformlydistributed. The jays again stayed longer than optimal, andpatch residence times increased as travel time increased, althoughthe residence time that maximized rate of intake was independentof travel time under these conditions. In the third experiment,exponential and uniform patches were randomly intermixed. Thejays showed larger travel-time effects in the exponential thanin the uniform patch. However, the travel-time effect in theuniform patch was contrary to rate-maximization predictions,and the birds again overstayed in both patch types. In the fourthexperiment, prefeeding at the start of each foraging bout slightlyincreased overstaying rather than decreasing overstaying, aswould be expected if overstaying were due to underestimatingenvironmental quality. Consistent and dramatic overstaying anda travel-time effect under conditions where travel time hasno effect on optimal residence times suggest that the rate-maximizationapproach does not apply to foraging problems involving patchuncertainty.     

Profitability, encounter rates, and prey choice of African lions

The prey preferences of African lions (Panthera leo) in SerengetiNational Park, Tanzania, were examined in three ways. First,lion encounter rates with prey types were measured and comparedwith a random sample of the prey population. Lions encounteredmore wart hogs (Phacochoerus aethiopicus), Grant's gazelles(Gazella granti), wildebeests (ConnochaeUs taurinus), and zebras(Equus burchelli) than expected. Second, preferred prey typesof lions were identified using conditional logit analysis. Lionspreferred to hunt small prey groups, groups that were closerthan 200 m, and groups that contained wart hogs, wildebeests,or zebras. Third, a risk-minimization optimal foraging modeland a rate-maximization model were used to predict lion preferences.The foraging theory models predict that preferences should changewith season and with lion group size. Qualitative support wasfound for most of these predictions.     

Relationships between food resources, foraging patterns, and reproductive success in the water pipit, Anthus sp. spinoletta

A basic but rarely tested assumption in optimal foraging theoryis that positive relationships exist between the foraging patternof an animal, its short-term benefits in feeding, and its long-termfitness. We present evidence for these relationships for a centralplace foraging situation. We studied the foraging behavior ofadult water pipits (Anthus sp. spinoletta) feeding nestlingsin an Alpine habitat near Davos, Switzerland, with the followingresults: (1) searching effort decreases with increasing distancefrom the nest, (2) the amount of prey and the proportion oflarge items brought to the nest increases with increasing foragingdistance, (3) water pipits do not forage according to habitatavailability, but prefer vegetation types with the highest fooddensity (mainly grass and herbs) and avoid those with the lowest,and (4) this selectivity is only expressed when the birds foragemore than 50 m from the nest, i.e., usually outside the territory.Among the several potential interpretations of these results,the most parsimonious is that foraging decisions are based onprofitability, i.e., on the net energy gain per time unit. Additionally,we found that food conditions translate into fitness: the numberof fledglings per nest is related positively to the averageprey biomass at the foraging place and negatively to the averagedistance between the foraging place and the nest. Maximum economicdistances, which were predicted from this food-fitness relationship,agreed well with the actual foraging distances observed. Thissuggests a dose connection between foraging decisions and fitness.In addition to the theoretical issues, some conservation issuesare also briefly discussed.     

Testing optimal foraging theory in a penguin–krill system

Food is heterogeneously distributed in nature, and understanding how animals search for and exploit food patches is a fundamental challenge in ecology. The classic marginal value theorem (MVT) formulates optimal patch residence time in response to patch quality. The MVT was generally proved in controlled animal experiments; however, owing to the technical difficulties in recording foraging behaviour in the wild, it has been inadequately examined in natural predator–prey systems, especially those in the three-dimensional marine environment. Using animal-borne accelerometers and video cameras, we collected a rare dataset in which the behaviour of a marine predator (penguin) was recorded simultaneously with the capture timings of mobile, patchily distributed prey (krill). We provide qualitative support for the MVT by showing that (i) krill capture rate diminished with time in each dive, as assumed in the MVT, and (ii) dive duration (or patch residence time, controlled for dive depth) increased with short-term, dive-scale krill capture rate, but decreased with long-term, bout-scale krill capture rate, as predicted from the MVT. Our results demonstrate that a single environmental factor (i.e. patch quality) can have opposite effects on animal behaviour depending on the time scale, emphasizing the importance of multi-scale approaches in understanding complex foraging strategies.     

The survival-rate-maximizing policy for Bayesian foragers: wait for good news

We present a model of the survival-maximizing foraging behaviorof an animal searching in patches for hidden prey with a clumpeddistribution. We assume the forager to be Bayesian: it updatesits statistical estimate of prey number in the current patchwhile foraging. When it arrives at the parch, it has an expectationof the patch's quality, which equals the average patch qualityin the environment While foraging, the forager uses its informationabout the time spent searching in the patch and how many preyhas been caught during this time. It can estimate both the instantaneousintake rate and the potential intake rate during the rest ofthe parch visit. When prey distribution is clumped, potentialintake rate may increase with time spent in the parch if preyis caught in the near future. Being optimal, a Bayesian foragershould therefore base its patch-leaving decision on the estimatedpotential patch value, not on the instantaneous parch value.When patch value is measured in survival rate and mortalitymay occur either as starvation or predation, the patch shouldbe abandoned when the forager estimates that its potential survivalrate dining the rest of the patch visit equals the long termsurvival rate in the environment This means that the instantaneousintake rate, when the patch is left, is nor constant but isan increasing function of searching time in the patch. Therefore,the giving-up densities of prey in the patches will also behigher the longer the search times. The giving-up densitiesare therefore expected to be an increasing, but humped, functionof initial prey densities. These are properties of Bayesianforaging behavior not included in previous empirical studiesand model tests.     

Predator search pattern and the strength of interference through prey depression

We develop a model of predators foraging within a single patch,on prey that become temporarily immune to predation (depressed)after detecting a predator. Interference through prey depressionoccurs because the proportion of vulnerable prey (and henceintake rate) decreases as predator density increases. Predatorsin our model are not forced to move randomly within the patch,as is the case in other similar models, but can avoid areasof depressed prey and so preferentially forage over vulnerableprey. We compare the extent to which different avoidance rules(e.g., move more quickly over depressed prey or turn if approachingdepressed prey) influence the amount of time spent foragingover depressed and vulnerable prey, and how this influencesthe strength of interference. Although based on a different mechanism, our model produces two similar general predictionsto interference models based on direct interactions betweenpredators: the strength of interference increases with (1)increased competitor density and (2) decreased prey encounterrate. This suggests that there are underlying similarities in the nature of interference even when it arises through differentprocesses. Not surprisingly, avoidance of depressed prey cansubstantially reduce the strength of interference comparedwith random foraging. However, we identify the region of themodel's parameter space in which this reduction is particularlylarge and show that the only system for which suitable dataare available, redshank Tringa totanus feeding on Corophium volutator, falls within this region. The model shows that, byadjusting its search path to avoid areas of depressed prey,a predator can substantially reduce the amount of the interferenceit experiences and that this applies over a wide range of parameterspace, including the region occupied by a real system. Thissuggests that behavior-based interference models should consider predator search pattern if they are to accurately predict thestrength of the interference.     

Knowing your habitat: linking patch-encounter rate and patch exploitation in parasitoids

According to optimal foraging theory, animals should decidewhether or not to leave a resource patch by comparing the currentprofitability of the patch with the expected profitability ofsearching elsewhere in the habitat. Although there is abundantevidence in the literature that foragers in general are wellable to estimate the value of a single resource patch, theirdecision making has rarely been investigated with respect tohabitat quality. This is especially true for invertebrates.We have conducted experiments to test whether parasitic waspsadjust patch residence time and exploitation in relation tothe abundance of patches within the environment. We used thebraconid Asobara tabida, a parasitoid of Drosophila larvae,as our model species. Our experiments show that these waspsreduce both the residence time and the degree of patch exploitationwhen patches become abundant in their environment, as predictedby optimal foraging models. Based upon a detailed analysis ofwasp foraging behavior, we discuss proximate mechanisms thatmight lead to the observed response. We suggest that parasitoidsuse a mechanism of sensitization and desensitization to chemicalsassociated with hosts and patches, in order to respond adaptivelyto the abundance of patches within their environment.     

Energetic constraints and foraging efficiency

Previous research considers foraging options that differ interms of their gross rate of gain b and rate of energy expenditurec. This research argues that maximizing efficiency b/c willmaximize net energetic gain when there is an upper limit onthe amount of energy that can be assimilated. This analysisdoes not include the expenditure during the time for which theanimal is unable to forage because of this constraint. Whenthis expenditure is included, maximizing efficiency is no longeroptimal. Instead the best feeding option is the one with thehighest value of b/(c – c₁), where c, is the metabolicrate when the animal is not foraging.     

The Predatory Mite Phytoseiulus persimilis Adjusts Patch-leaving to Own and Progeny Prey Needs

Integration of optimal foraging and optimal oviposition theories suggests that predator females should adjust patch leaving to own and progeny prey needs to maximize current and future reproductive success. We tested this hypothesis in the predatory mite Phytoseiulus persimilis and its patchily distributed prey, the two-spotted spider mite Tetranychus urticae. In three separate experiments we assessed (1) the minimum number of prey needed to complete juvenile development, (2) the minimum number of prey needed to produce an egg, and (3) the ratio between eggs laid and spider mites left when a gravid P. persimilis female leaves a patch. Experiments (1) and (2) were the pre-requirements to assess the fitness costs associated with staying or leaving a prey patch. Immature P. persimilis needed at least 7 and on average 14±3.6 (SD) T. urticae eggs to reach adulthood. Gravid females needed at least 5 and on average 8.5±3.1 (SD) T. urticae eggs to produce an egg. Most females left the initial patch before spider mite extinction, leaving prey for progeny to develop to adulthood. Females placed in a low density patch left 5.6±6.1 (SD) eggs per egg laid, whereas those placed in a high density patch left 15.8±13.7 (SD) eggs per egg laid. The three experiments in concert suggest that gravid P. persimilis females are able to balance the trade off between optimal foraging and optimal oviposition and adjust patch-leaving to own and progeny prey needs.     

State dependent behavior and the Marginal Value Theorem

The Marginal Value Theorem (MVT) is the dominant paradigm inpredicting patch use and numerous tests support its qualitativepredictions. Quantitative tests under complex foraging situationscould be expected to be more variable in their support becausethe MVT assumes behavior maximizes only net energy-intake rate.However across a survey of 26 studies, foragers rather consistently"erred" in staying too long in patches. Such a consistent directionto the errors suggests that the simplifying assumptions ofthe MVT introduce a systematic bias rather than just imprecision. Therefore, I simulated patch use as a state-dependent responseto physiological state, travel cost, predation risk, prey densities,and fitness currencies other than net-rate maximization (e.g.,maximizing survival, reproductive investment, or mating opportunities).State-dependent behavior consistently results in longer patchresidence times than predicted by the MVT or another foragingmodel, the minimize µ/g rule, and these rules fail to closely approximate the best behavioral strategy over a widerange of conditions. Because patch residence times increasewith state-dependent behavior, this also predicts mass regulationbelow maximum energy capacities without direct mass-specificcosts. Finally, qualitative behavioral predictions from theMVT about giving-up densities in patches and the effects oftravel costs are often inconsistent with state-dependent behavior.Thus in order to accurately predict patch exploitation patterns,the model highlights the need to: (1) consider predator behavior(sit-and-wait versus actively foraging); (2) identify activitiesthat can occur simultaneously to foraging (i.e., mate searchor parental care); and (3) specify the range of nutritional states likely in foraging animals. Future predictive modelsof patch use should explicitly consider these parameters.     

Seeing is believing: information content and behavioural response to visual and chemical cues

Predator avoidance and foraging often pose conflicting demands. Animals can decrease mortality risk searching for predators, but searching decreases foraging time and hence intake. We used this principle to investigate how prey should use information to detect, assess and respond to predation risk from an optimal foraging perspective. A mathematical model showed that solitary bees should increase flower examination time in response to predator cues and that the rate of false alarms should be negatively correlated with the relative value of the flower explored. The predatory ant, Oecophylla smaragdina, and the harmless ant, Polyrhachis dives, differ in the profile of volatiles they emit and in their visual appearance. As predicted, the solitary bee Nomia strigata spent more time examining virgin flowers in presence of predator cues than in their absence. Furthermore, the proportion of flowers rejected decreased from morning to noon, as the relative value of virgin flowers increased. In addition, bees responded differently to visual and chemical cues. While chemical cues induced bees to search around flowers, bees detecting visual cues hovered in front of them. These strategies may allow prey to identify the nature of visual cues and to locate the source of chemical cues.     

The Relative Importance of Habitat Structure and of Prey Characteristics for the Foraging Success of Water Pipits (Anthus spinoletta)*

While many studies on foraging have related energy gain to the density and the size of prey, only few have investigated whether and how habitat structure modifies the gain through affecting foraging success. In this study, the influences of habitat structure and prey characteristics on the foraging success of water pipits, Anthus spinoletta, were investigated experimentally. The birds take longer to find prey in tall than in short vegetation. The effects of vegetation on searching times differ between prey types. These differences are probably caused by variation in prey behaviour and in cryptic colouration, but not by prey size. Searching times increase with decreasing density for mealworms and tipulids, but not for caterpillars. Handling large prey items requires more time than handling smaller prey. Tipulids and caterpillars, which were offered alive, are handled for a longer time than dead mealworms of corresponding size. The success of attacks on flying insects is probably influenced by the prey's flight speed: fast houseflies are missed more often than slow tipulids. Overall, the results show that the time costs of foraging water pipits are influenced to a comparable degree by vegetation structure, by prey density and by other specific prey characteristics such as camouflage, hiding behaviour or agility. The amount of food gathered per unit time is determined primarily by factors that affect searching times, and less by handling and travelling times. Insertion of our data into an optimal diet model leads to the prediction that water pipits should be generalist foragers, which agrees with the observed behaviour.     

The use of optimal foraging theory in the understanding of fishing strategies: A case from Sepetiba Bay (Rio de Janeiro State,Brazil)

The community of Gamboa is located on Itacuruçá Island, Sepetiba Bay (State of Rio de Janeiro, Brazil) and includes 26 families, mostly of artisanal fishermen who use paddled or motor canoes, and encircling nets for fishing. In this study, predictions from optimal foraging theory (patch model), in particular of patch residence time, are compared to the observed behavior of fishermen on fishing trips. Fishermen's strategies differ depending on their intended prey. They spend more time in patches and use fewer patches for shrimp than for fish. Gamboa's fishermen tend to leave a patch later than predicted by the model. The difficulty in evaluating stock availability, the comparatively few patches available for shrimp, and the competitive aspects of fishing contribute to the explanation of this behavior.     

Optimal Bayesian foraging policies and prey population dynamics-some comments on Rodriguez-Girones and Vasquez

In this paper we show the density-dependent harvest rates of optimal Bayesian foragers exploiting prey occurring with clumped spatial distribution. Rodríguez-Gironés and Vásquez (1997) recently treated the issue, but they used a patch-leaving rule (current value assessment rule) that is not optimal for the case described here. An optimal Bayesian forager exploiting prey whose distribution follows the negative binomial distribution should leave a patch when the potential (and not instantaneous) gain rate in that patch equals the best long-term gain rate in the environment (potential value assessment rule). It follows that the instantaneous gain rate at which the patches are abandoned is an increasing function of the time spent searching in the patch. It also follows that the proportion of prey harvested in a patch is an increasing sigmoidal function of the number of prey initially present. In this paper we vary several parameters of the model to evaluate the effects on the forager's intake rate, the proportion of prey harvested per patch, and the prey's average mortality rate in the environment. In each case, we study an intake rate maximizing forager's optimal response to the parameter changes. For the potential value assessment rule we find that at a higher average prey density in the environment, a lower proportion of the prey is taken in a patch with a given initial prey density. The proportion of prey taken in a patch of a given prey density also decreases when the variance of the prey density distribution is increased and if the travel time between patches is reduced. We also evaluate the effect of using predation minimization, rather than rate maximization, as the currency. Then a higher proportion of the prey is taken for each given initial prey density. This is related to the assumption that traveling between patches is the most risky activity. Compared to the optimal potential value assessment rule, the current value assessment rule performs worse, in terms of long-term intake rate achieved. The difference in performance is amplified when prey density is high or highly aggregated. These results pertain to the foraging patch spatial scale and may have consequences for the spatial distribution of prey in the environment.     

Risky decisions: a test of risk sensitivity in socially foraging flocks of Lonchura punctulata

Group foraging allows for individuals to exploit the food discoveriesof other group members. If searching for food and searchingfor exploitation opportunities within a group are mutually exclusivealternatives, the decision to use one or the other is modeledas a producer-scrounger game because the value of each alternativeis frequency dependent. Stochastic producer-scrounger modelsgenerally assume that producer provides a more variable anduncertain reward than does the scrounger and hence is a riskierforaging alternative. Socially foraging animals that are attemptingto reduce their risk of starvation should therefore alter theiruse of producer and scrounger alternatives in response to changesin energy budget. We observed flocks of nutmeg mannikins (L.punctulata) foraging in an indoor aviary to determine whethertheir use of producer and scrounger alternatives were risk sensitive.Analyses of the foraging rewards of three flocks of seven birdsconfirm that producer is a riskier foraging strategy than isscrounger, although the difference in risk is rather small.We then submitted two other flocks to two different energy budgetsand observed the foraging decision of four focal birds in eachflock. All but one bird increased their relative use of theriskier producer strategy in the low food reserve treatment,but the overall use of producer did not differ significantlybetween treatments, providing evidence for a small but consistenteffect.     

Foraging efficiency of juvenile bluegill, Lepomis macrochirus, among different vegetated habitats

Optimal foraging theory is devoted to understanding how organisms maximize net energy gain. However, both the theory and empirical studies lack critical components, such as effects of environmental variables across habitats. We addressed the hypothesis that energetic returns of juvenile bluegill are affected by environmental variables characteristic of the vegetated habitats. Predicted optimal diet breadths were calculated and compared to prey items eaten by juvenile bluegill to determine if bluegill were foraging to maximize energetic gain. Differences in habitat profitability among vegetated sites were determined by comparing predictions of maximized energetic return rates (cals^-1) with prey contents of bluegill stomachs. Sizes of most prey items eaten by juvenile bluegill throughout the vegetated sites were smaller than the predicted optimal diet breadths. However, inclusion of smaller prey items in the diet did not seem to affect rate of energetic gain. Energetic return rates were maximized at the 1.5 and 2mm prey size classes and declined only slightly with inclusion of smaller prey sizes. Predicted energetic return rates and average mass in bluegill stomachs were related negatively. Average mass in bluegill stomachs also was associated negatively with Elodea canadensis stem densities and percent of light transfer, suggesting that foraging efficiency of bluegill decreased as plant density and percent of light increased. Results of our research indicate that maximization of energetic return rates is dependent upon availability of prey sizes that contribute to optimal foraging. Thus, determination of those habitats that provide the highest availability of benthic invertebrate prey with the least interference by stems is critical. Enhanced foraging capabilities can promote recruitment, faster growth, better body condition and survival.     

Foraging rate versus sociality in the starling Sturnus vulgaris

It is well established that social conditions often modify foraging behaviour, but the theoretical interpretation of the changes produced is not straightforward. Changes may be due to alterations of the foraging currency (the mathematical expression that behaviour maximizes) and/or of the available resources. An example of the latter is when both solitary and social foragers maximize rates of gain over time, but competition alters the behaviour required to achieve this, as assumed by ideal free distribution models. Here we examine this problem using captive starlings Sturnus vulgaris. Subjects had access to two depleting patches that replenished whenever the alternative patch was visited. The theoretical rate-maximizing policy was the same across all treatments, and consisted of alternating between patches following a pattern that could be predicted using the marginal value theorem (MVT). There were three treatments that differed in the contents of an aviary adjacent to one of the two patches (called the 'social' patch). In the control treatment, the aviary was empty, in the social condition it contained a group of starlings, and in a non-specific stimulus control it contained a group of zebra finches. In the control condition both patches were used equally and behaviour was well predicted by the MVT. In the social condition, starlings foraged more slowly in the social than in the solitary patch. Further, foraging in the solitary patch was faster and in the social patch slower in the social condition than in the control condition. Although these changes are incompatible with overall rate maximization (gain rate decreased by about 24% by self-imposed changes), if the self-generated gain functions were used the MVT was a good predictor of patch exploitation under all conditions. We discuss the complexities of nesting optimal foraging models in more comprehensive theoretical accounts of behaviour integrating functional and mechanistic perspectives.     

Optimal Bayesian Foraging Policies and Prey Population Dynamics—Some Comments on Rodríguez-Gironés and Vásquez

In this paper we show the density-dependent harvest rates of optimal Bayesian foragers exploiting prey occurring with clumped spatial distribution. Rodríguez-Gironés and Vásquez (1997) recently treated the issue, but they used a patch-leaving rule (current value assessment rule) that is not optimal for the case described here. An optimal Bayesian forager exploiting prey whose distribution follows the negative binomial distribution should leave a patch when the potential (and not instantaneous) gain rate in that patch equals the best long-term gain rate in the environment (potential value assessment rule). It follows that the instantaneous gain rate at which the patches are abandoned is an increasing function of the time spent searching in the patch. It also follows that the proportion of prey harvested in a patch is an increasing sigmoidal function of the number of prey initially present. In this paper we vary several parameters of the model to evaluate the effects on the forager's intake rate, the proportion of prey harvested per patch, and the prey's average mortality rate in the environment. In each case, we study an intake rate maximizing forager's optimal response to the parameter changes. For the potential value assessment rule we find that at a higher average prey density in the environment, a lower proportion of the prey is taken in a patch with a given initial prey density. The proportion of prey taken in a patch of a given prey density also decreases when the variance of the prey density distribution is increased and if the travel time between patches is reduced. We also evaluate the effect of using predation minimization, rather than rate maximization, as the currency. Then a higher proportion of the prey is taken for each given initial prey density. This is related to the assumption that traveling between patches is the most risky activity. Compared to the optimal potential value assessment rule, the current value assessment rule performs worse, in terms of long-term intake rate achieved. The difference in performance is amplified when prey density is high or highly aggregated. These results pertain to the foraging patch spatial scale and may have consequences for the spatial distribution of prey in the environment.     

Behavioral responses to prey density by three acarine predator species with different degrees of polyphagy

Behavioral responses by three acarine predators, Phytoseiulus persimilis, Typhlodromus occidentalis, and Amblyseius andersoni (Acari: Phytoseiidae), to different egg and webbing densities of the spider mite Tetranychus urticae (Acari: Tetranychidae) on rose leaflets were studied in the laboratory. Prey patches were delineated by T. urticae webbing and associated kairomones, which elicit turning back responses in predators near the patch edge. Only the presence of webbing affected predator behavior; increased webbing density did not increase patch time. Patch time increased with increased T. urticae egg density in the oligophagous P. persimilis, but was density independent in the polyphagous species T. occidentalis and A. andersoni. Patch time in all three species was more strongly correlated with the number of prey encounters and attacks than with the actual prey number present in the patch. Patch time was determined by (a) the turning back response near the patch edge; this response decayed through time and eventually led to the abandonment of the patch, and (b) encounters with, and attacks upon, prey eggs; these prolonged patch time by both an increment of time spent in handling or rejecting prey and an increment of time spent searching between two successive prey encounters or attacks. Although searching efficiency was independent of prey density in all three species, the predation rate by P. persimilis decreased with prey density because its searching activity (i.e. proportion of total patch time spent in searching) decreased with prey density. Predation rates by T. occidentalis and A. andersoni decreased with prey density because their searching activity and success ratio both decreased with prey density. The data were tested against models of predator foraging responses to prey density. The effects of the degree of polyphagy on predator foraging behavior were also discussed.     

Flexible search tactics and efficient foraging in saltatory searching animals

Summary Foraging is one of the most important endeavors undertaken by animals, and it has been studied intensively from both mechanistic-empirical and optimal foraging perspectives. Planktivorous fish make excellent study organisms for foraging studies because they feed frequently and in a relatively simple environment. Most optimal foraging studies of planktivorous fish have focused, either on diet choice or habitat selection and have assumed that these animals used a cruise search foraging strategy. We have recently recognized that white crappie do not use a cruise search strategy (swimming continuously and searching constantly) while foraging on zooplankton but move in a stop and go pattern, searching only while paused. We have termed thissaltatory search. Many other animals move in a stop and go pattern while foraging, but none have been shown to search only while paused. Not only do white crappie search in a saltatory manner but the components of the search cycle change when feeding on prey of different size. When feeding on large prey these fish move further and faster after an unsuccessful search than when feeding on small prey. The fish also pause for a shorter period to search when feeding on large prey. To evaluate the efficiency of these alterations in the search cycle, a net energy gain simulation model was developed. The model computes the likelihood of locating 1 or 2 different size classes of zooplankton prey as a function of the volume of water scanned. The volume of new water searched is dependent upon the dimensions of the search volume and the length of the run. Energy costs for each component of the search cycle, and energy gained from the different sized prey, were assessed. The model predicts that short runs produce maximum net energy gains when crappie feed on small prey but predicts net energy gains will be maximized with longer runs when crappie feed on large prey or a mixed assemblage of large and small prey. There is an optimal run length due to high energy costs of unsuccessful search when runs are short and reveal little new water, and high energy costs of long runs when runs are lengthy. The model predicts that if the greater search times observed when crappie feed on small prey are assessed when they feed on a mixed diet of small and large prey, net energy gained is less than if small prey are deleted from the diet. We believe the model has considerable generality. Many animals are observed to move in a saltatory manner while foraging and some are thought to search only while stationary. Some birds and lizards are, known to modify the search cycle in a manner similar to white crappie.Components of the search cycle and dimensions of the location space SST (sec) Successful search time — the average time stationary prior to a pursuit - USST (sec) Unsuccessful search time — the average time stationary prior to a run - PT (sec) Pursuit time-PL/SS — the time to pursue prey at a given distance away. It is calculated by dividing the pursuit distance by swim speed - RT (sec) Run time-RL/SS — the time to complete a run of a given length. It is calculated by dividing the run length, by swim speed - PL (cm) Pursuit length-distance moved to attack prey - RL (cm) Run length-distance moved between consecutive searches - SS (cm/sec) Swim speed — the speed of movement during a pursuit or run - LS (l) Location space — the area or volume within which prey are located. In the case of white crappie the search space is shaped like a pie wedge with the fish positioned at the apex of the wedge - LA (^o) Location angle—the angle of the wedge-shaped search space - LH (cm) Location height—the height of the wedge-shaped search space - LD (cm) Location distance—the length of long axis of the wedge-shaped search space. Components of the location probability model RND Random number-random number generated through BASICA - SV (l) Search volume—the volume of water actually searched after one run of given length - SV_MAX (l) Maximum search volume—the greatest search volume that can be based upon LA, LH, LD and unaffected by the previous search - SV_R (l) Search volume researched—that volume of SV_MAX that is researched where RLo Search volume unsearched—that volume of SV_MAX not previously searched - AD (#/1) Absolute density—the density of zooplankton prey in numbers per liter - VD (#) Visual density—the number of zooplankton prey in the search volume - LP (%) Location probability—the probability that one or more prey are in the search volume Components of the net energy gain model NEG (cal/sec) Net energy gain-total calories ingested, less total calories used, divided by total time. - E _e (cal) Energy expended on the search cycle - E _i (cal) Energy intake - e _p (cal) Energy content of a given individual prey - P _i Total number of prey ingested - e _r (cal) Energy expended while searching - e _s (cal) Energy expended while swimming - T _t (sec) Total time-time expended to eat a given number of prey