Local search in the housefly Musca domestica after feeding on sucrose

Local search behaviour of the housefly, Musca domestica, released by ingestion of sucrose, was recorded on a bitpad digitizer. Local search is characterized by an initial increase in turning rate and a decrease in locomotory rate followed by an exponential return to control (unfed) levels for both functions. Greater variation in the slope of the exponential return to control levels was observed between runs of different flies than between runs of an individual fly, suggesting a possible internal basis for locomotory and turning functions. The local search pattern, based on decrease in relative turning rate generates a spiral configuration. A zig-zag component increases path width and increases the chances of a fly relocating the drop residue. Looping patterns correlate with successive recontacts with the drop residue and associated changes in turn direction and stopping. The results are discussed with respect to sources of internal and external orientation information controlling local search.     

Search orientation of Musca domestica in patches of sucrose drops

ABSTRACT. The searching tactics of the housefly, Musca dormestica L. (Diptera: Muscidae), have been delineated from digitized pathways of flies walking in patches of sucrose drops arranged in linear (ROW) and hexagonal (HEX) arrays. The areas covered by flies in ROW and HEX patches are distinctly different, but flies seem not to employ different tactics for the two types of resource arrays. The number of drops located, if at least one drop is found, does not differ between ROW and HEX. Most quantitative measures of local search remain constant after the first interdrop interval, although feeding time decreases as flies sample successive drops. Local search intensifies after each drop is ingested, with locomotory rate decreasing and turning rate increasing, followed by decay of both measures toward ranging levels. Searching can be characterized by two movement tendencies resulting from specific, definable, locomotory functions: a forward-moving tendency is expressed by the fly as it leaves a resource in approximately the same direction as it arrives; and local search is characterized by looping, rather than straight walking, with a variable turning rate that generates a rough ‘zigzag’ superimposed on looping. The two movement tendencies, combined, allow flies to locate resources in a linear arrangement, because of the forward-moving tendency, and to locate resources not arranged in a linear array because of the ‘noisy’ loop. M. domestica does not appear to retain and use information gained from one patch of drops in another, so the search tactic of the fly seems therefore to be a compromise between straight movement and circular movement that may be adaptive for an environment subject to frequent changes in the spatial distribution of resources. Giving-up-time, the period between ingesting the last drop and leaving the patch, is a function of the rate of change in the transition from local search to ranging, which is constant in our experiments. If a fly does not encounter another drop while ranging, during which it walks relatively straight, the fly moves out of and away from the patch.     

Individual constancy of local search strategies in the giant tropical ant,Paraponera clavata (Hymenoptera: Formicidae)

Paraponera clavata workers engage in a period of local search after encountering a small amount of artificial nectar. Giving-up times from local search are not distributed normally; there is a strong skew to longer times. There is no statistically significant relationship between the amount of time required to collect the food and the subsequent search time. Giving-up time in response to the first reward presented to an ant is positively correlated with that ant's response to a second such reward. However, giving-up times diminish when an ant is presented with a series of rewards. Local search is a function of individual strategies, which remain relatively constant in the short term.     

The efficiency of adaptive search tactics for different prey distribution patterns: a simulation model based on the behaviour of juvenile plaice

Juvenile plaice Pleuronectes platessa are particularly useful for studying forager search behaviour because their search paths are essentially two dimensional, and punctuated by natural stops. Their prey occur in a range of natural distributions from highly aggregated to over‐dispersed. Juvenile plaice use area‐restricted search near aggregated prey and extensive search, consisting of longer moves and fewer turns, between aggregations and when searching for dispersed prey. They search for less conspicuous prey items mainly in the pauses between movements. This saltatory search behaviour contrasts with the continuous search that is usually assumed in search models. A simulation model of saltatory search behaviour showed that a strategy combining extensive and intensive search allows the efficient exploitation of a range of natural prey distribution patterns, and that it is particularly effective when the search behaviour is controlled by perceived prey density. This allows the predator to respond to the localized aggregations which often occur in nature. The selective use of intensive search was more efficient than the continuous use of extensive search even in prey distribution patterns that were statistically over‐dispersed.     

Sources of variability in the transition from extensive to intensive search in coccinellid predators (Homoptera: Coccinellidae)

In an environment structured by habitats, prey patches, and prey, predators such as coccinellids have two movement modes. The extensive search and the intensive search which results from prey capture are adopted for patch localization and exploration, respectively. The variability of changes from extensive search to intensive search was studied in larvae of the aphidophagous coccinellidSemiadalia undecimpunctata to find out their possibility of adaptation to a fluctuating environment. The temporal organization of coccinellid movements appears far more complicated than the generally accepted succession of extensive search, feeding, and intensive search. Their paths are characterized by the presence of time intervals devoted to intensive search before feeding, a highly variable path response after prey consumption (larvae may adopt intensive search immediately, later, or never), and the alternation of time periods devoted to either extensive search or intensive search after prey ingestion. This interindividual variability suggests that coccinellids have the ability to adapt to heterogeneity or short-term changes in environmental conditions, particularly in prey distribution. These results are in favor of the use of these predators in biological control programs.     

Adaptive search in juvenile plaice foraging for aggregated and dispersed prey

Juvenile plaice Pleuronectes platessa in a laboratory arena used intensive search behaviour, characterized by short movements and frequent turning, in the five movements before and after attacking a prey in an aggregated distribution. They used extensive search behaviour with, on average, longer movements and less turning at all other times. Intensive search was, apparently, triggered by a high local density of prey but not by isolated prey. This response to local prey density resulted in area-restricted search when prey were aggregated and win-shift behaviour when prey were dispersed. There was no evidence that the use of intensive search increased with experience of aggregated prey. It therefore appears that the fish were able to exploit encountered prey distribution patterns using their immediate perceptions rather than prior experience.     

The consequences of partially directed search effort

Search effort is undirected when a forager has a stereotypical searching behaviour that results in fixed encounter rates with its prey (e.g. diet choice models), and is directed when the forager can bias its encounter with a ‘chosen’ prey. If the bias is complete, search is totally directed (e.g. habitat selection models). When the bias is incomplete (i.e. search modes are not exclusive to a single prey type), search is partially directed. The inclusion of a prey type in the diet is then the result of two decisions: (1) which prey to search for and (2) which prey to handle. The latter decision is determined by the ratio of energy to handling time and the abundance of the preferred prey. The former decision is a function of the encounter probabilities and densities of all potential prey types in addition to their ratio of energy to handling time. Assuming two prey types, there are three distinct behavioural strategies: (1) search for the preferred prey/forage selectively; (2) search for the preferred prey/forage opportunistically; and (3) search for the non-preferred prey/forage opportunistically. If prey are depletable (i.e. prey occur in resource patches), the forager may switch search modes such that prey are depleted to the point where the marginal values of the search modes are equalized. This revised version was published online in July 2006 with corrections to the Cover Date.     

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     

Saltatory search: a theoretical analysis

Many animal search in a saltatory fashion: they move forward,pause briefly, and move forward again. Although many optimal-foragingmodels have been developed, most do not address how an animalsearches for food. We view search strategies as "time-distance"functions to allow not only for the possibility of oscillationsin body speed, as implied by saltatory search, but other movementpatterns as well, including cruise search. The key feature ofour models is distinguishing between the body position and thescan position (where the forager is looking). We see the varyingmovement of saltatory search as a consequence of the curvaturein the functions that relate body speed to benefits (Jensen'sinequality)     

Increased turning per unit distance as an area-restricted search mechanism in a pause-travel predator, juvenile plaice, foraging for buried bivalves

During searching, discovery of a prey patch by juvenile plaice Pleuronectes platessa was associated with a change from extensive to intensive search behaviour several moves before an attack on a prey. Intensive search behaviour was characterized by reduced distance of moves, a greater rate of turning per unit distance and shorter pauses between moves. The increase in turn rate was associated with area-restricted seaching, while a decrease in distances moved suggests that plaice search more efficiently for prey when stationary than while moving. The klinokinetic mechanism that appears to regulate search behaviour in juvenile plaice should allow efficient exploitation of a range of prey distribution patterns based on localized cues alone. Such a mechanism is especially useful to a migratory predator, like plaice, whose foraging is subject to time constraints imposed by tidally available feeding areas.     

A geomagnetic declination compass for horizontal orientation in fruit flies

The Earth's geomagnetic field (GMF) is known to act as a sensory cue for magnetoreceptive animals such as birds, sea turtles, and butterflies in long‐distance migration, as well as in flies, cockroaches, and cattle in short‐distance movement or body alignment. Despite a wealth of information, the way that GMF components are used and the functional modality of the magnetic sense are not clear. A GMF component, declination, has never been proven to be a sensory cue in a defined biological context. Here, we show that declination acts as a compass for horizontal food foraging in fruit flies. In an open‐field test, adopting the food conditioning paradigm, food‐trained flies significantly orientated toward the food direction under ambient GMF and under eastward‐turned magnetic field in the absence of other sensory cues. Moreover, a declination change within the natural range, by alteration only of either the east–west or north–south component of the GMF, produced significant orientation of the trained flies, indicating that they can detect and use the difference in these horizontal GMF components. This study proves that declination difference can be used for horizontal foraging, and suggests that flies have been evolutionarily adapted to incorporate a declination compass into their multi‐modal sensorimotor system.     

A search theory model of patch-to-patch forager movement with application to pollinator-mediated gene flow

We present a spatially implicit analytical model of forager movement, designed to address a simple scenario common in nature. We assume minimal depression of patch resources, and discrete foraging bouts, during which foragers fill to capacity. The model is particularly suitable for foragers that search systematically, foragers that deplete resources in a patch only incrementally, and for sit-and-wait foragers, where harvesting does not affect the rate of arrival of forage. Drawing on the theory of job search from microeconomics, we estimate the expected number of patches visited as a function of just two variables: the coefficient of variation of the rate of energy gain among patches, and the ratio of the expected time exploiting a randomly chosen patch and the expected time travelling between patches. We then consider the forager as a pollinator and apply our model to estimate gene flow. Under model assumptions, an upper bound for animal-mediated gene flow between natural plant populations is approximately proportional to the probability that the animal rejects a plant population. In addition, an upper bound for animal-mediated gene flow in any animal-pollinated agricultural crop from a genetically modified (GM) to a non-GM field is approximately proportional to the proportion of fields that are GM and the probability that the animal rejects a field.     

Upside-down spiders build upside-down orb webs: web asymmetry,spider orientation and running speed in Cyclosa

Almost all spiders building vertical orb webs face downwards when sitting on the hubs of their webs, and their webs exhibit an up–down size asymmetry, with the lower part of the capture area being larger than the upper. However, spiders of the genus Cyclosa, which all build vertical orb webs, exhibit inter- and intraspecific variation in orientation. In particular, Cyclosa ginnaga and C. argenteoalba always face upwards, and C. octotuberculata always face downwards, whereas some C. confusa face upwards and others face downwards or even sideways. These spiders provide a unique opportunity to examine why most spiders face downwards and have asymmetrical webs. We found that upward-facing spiders had upside-down webs with larger upper parts, downward-facing spiders had normal webs with larger lower parts and sideways-facing spiders had more symmetrical webs. Downward-facing C. confusa spiders were larger than upward- and sideways-facing individuals. We also found that during prey attacks, downward-facing spiders ran significantly faster downwards than upwards, which was not the case in upward-facing spiders. These results suggest that the spider''s orientation at the hub and web asymmetry enhance its foraging efficiency by minimizing the time to reach prey trapped in the web.     

Honey bee orientation behaviour and the influence of flower distribution on foraging movements

ABSTRACT.

• 1 Directional movement by foraging honey bees (Apis mellifera L.) was studied on several flower arrays. The most frequent move among equidistant flower stalks was straight ahead from stalk to stalk with frequencies decreasing for increasing turn angles. Turns to the left were about equal in frequency to turns to the right.
• 2 Bees maintained directionality when moving from flower stalks that had been rotated 90° counterclockwise while the bee was on the stalk (no difference between moves from rotated stalks and unrotated controls). Thus, directionality is maintained by the bee and is not an artefact of flower distribution.
• 3 Bees also maintained directionality when the entire array was rotated around the flower stalk the bee was on. Thus, bees use an external cue to orientate in a given direction rather than fixing on an inflorescence within the flower array.
• 4 Bees foraging on very different flower arrays differed in patterns of directionality and in distances flown between flower stalks. Therefore, even though bees maintain directionality using external cues, flower distribution can nevertheless influence flight patterns.

     

Limited attention: the constraint underlying search image

Recent models of predator search behavior integrate proximate neurobiological constraints with ultimate economic considerations.These models are based on two assumptions, which we have criticallyexamined in experiments with blue jays searching for artificialprey images presented on a computer monitor. We found, first,that when jays had to switch between searching for two distinctprey types, they showed no reduction in detection rates comparedto no-switching to no-switching conditions, and second, that when jays divided attention between searching for two prey typesat the same time, they had lower detection rates than whenthey focused attention on one prey type at a time. Our resultssuggest that limited attention strongly affects predator searchpatterns and diet choice, including the ubiquitous tendencyto form search images.     

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.