Predator Prey Model

Predator Prey Model

According to a CSIR-NET study, antelopes reduce predation risk via:

Group formation reduces individual predation risk through several mechanisms. In a larger group, the probability that any one antelope is captured can fall through the dilution effect, while many eyes increase the chance of detecting an approaching predator early. Coordinated vigilance, alarm signals, confusion caused by many moving targets, and collective defense can further reduce attack success. Individuals may also occupy safer central positions, although competition and disease increase with group size. Speed remains important during pursuit, but grouping changes both encounter and capture probabilities at the population level. Chemical signaling and hibernation are not characteristic principal defenses for active antelope herds. The vague phrase “a CSIR-NET study” does not identify a particular experiment, so the general ecological principle is more defensible than any study-specific claim. Tests distinguish mechanisms by measuring vigilance, attack rate, and per-capita capture across group sizes while accounting for habitat and predator abundance. Grouping is favored when these antipredator gains exceed costs such as resource competition and conspicuousness.

Ref: Ecology: Concepts and Applications, Molles, 9th Ed., Ch. 14

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Predator Prey Model

Which of the following best represents predator-prey co-evolution?

Predator–prey coevolution involves reciprocal genetic change: adaptation in one species alters selection acting on the other. Improved prey escape traits, such as faster acceleration, vigilance, armor, toxins, or better camouflage, can reduce capture success. Predators may then be favored to evolve greater speed, enhanced sensory systems, detoxification, cooperative hunting, or altered tactics. This reciprocal escalation or counteradaptation is often called an evolutionary arms race, although trade-offs and ecological context can prevent indefinite improvement. Prey change alone demonstrates adaptation to predation; it becomes evidence of coevolution when predator populations subsequently evolve in response and the relevant traits are heritable. Predator extinction ends reciprocal interaction, constant prey growth ignores predation, and unchanged predator behavior provides no counterresponse. Coevolution can also be diffuse when several predator and prey species shape selection. Rigorous evidence compares traits and fitness across populations, uses common-garden or genomic approaches, and shows reciprocal selection rather than assuming it from correlated phenotypes. Better escape is therefore the clearest first step toward a coevolutionary dynamic.

Ref: Ecology: Concepts and Applications, Molles, 9th Ed., Ch. 14

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Predator Prey Model

Which ecological factor leads to unstable equilibrium?

Alternative prey with uncorrelated abundance do not generally lead to unstable equilibrium. They can buffer a generalist predator’s food supply because one prey may be abundant when another is scarce, and predator switching toward common prey can stabilize dynamics. They can also generate apparent competition or sustain predators that overexploit a rare prey, so the outcome depends on functional responses, switching, and interaction strengths; uncorrelated abundance alone has no fixed destabilizing sign. Predator saturation, by contrast, is a recognized destabilizing mechanism in many predator–prey models. With a saturating type II functional response, predation fails to increase proportionally at high prey density, allowing prey outbreaks, while continued predation at lower densities can deepen crashes. Stability must be evaluated from specified equations or Jacobian eigenvalues, not assigned from a single qualitative feature. Mimicry and dormancy may alter encounter rates or temporal structure but are not universal determinants either. KEY MISMATCH: the keyed alternative-prey statement is not generally valid, and predator saturation is the better-supported destabilizing factor among the choices.

Ref: Ecology: Concepts and Applications, Molles, 9th Ed., Ch. 14

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Predator Prey Model

Which behavior increases predator efficiency in group hunting?

Pack coordination can increase group-hunting efficiency by assigning complementary roles, synchronizing attacks, and reducing prey escape routes. Individuals may encircle prey, alternate pursuit, drive it toward ambushers, or coordinate the timing and direction of a final attack. These behaviors can raise capture probability, reduce duplicated effort, and permit capture of prey too large or dangerous for a solitary hunter. The net advantage depends on whether increased intake exceeds the costs of communication, competition, injury, and sharing the carcass; larger groups are not always more profitable per individual. Sleep cycles, solitary movement, and seasonal migration can affect predator ecology but do not constitute the within-hunt cooperation needed for coordinated capture. Communication through calls, posture, scent, or movement can maintain spatial roles and update partners as prey changes direction. Selection can favor such coordination through direct individual benefits, kin selection, or repeated cooperation. The mechanism is joint action that changes capture success or energetic cost, not mere simultaneous presence of several predators.

Ref: Ecology: Concepts and Applications, Molles, 9th Ed., Ch. 14

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Predator Prey Model

Which of the following supports MVT predictions?

Caenorhabditis elegans leaving a depleted food patch illustrates the marginal value theorem’s core prediction. The nematode commonly feeds on bacteria. As local bacteria are consumed, encounter rate and marginal food gain decline; continued residence eventually yields less than the expected return from dispersing and locating another patch. Sensory information about food concentration, recent intake, and environmental cues can regulate roaming and dwelling states, allowing departure behavior to track diminishing returns. The theorem predicts departure when current marginal gain falls to the habitat-wide average gain rate after travel costs are included. Paramecium growth with Didinium concerns predator–prey dynamics, not optimal patch residence. Tadpole cannibalism is a trophic interaction, and random diet change provides no evidence for an optimization rule. Strong support would require quantitative agreement between observed leaving times and manipulated patch quality or travel cost, not merely movement away from food. Nevertheless, leaving an experimentally depleted bacterial patch is the listed behavior most directly aligned with marginal-value reasoning.

Ref: Ecology: Concepts and Applications, Molles, 9th Ed., Ch. 14

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Predator Prey Model

Which factor determines prey2 rejection by a predator?

In the classic optimal diet model, rejection of a lower-ranked prey type depends on how quickly the predator expects to encounter the more profitable prey type. Search time for prey 1 is therefore decisive. If prey 1 is encountered frequently, rejecting prey 2 costs little time and preserves a high long-term intake rate. If prey 1 becomes rare and its expected search time increases, accepting prey 2 can raise average energy gain despite its lower E/h ranking. A notable prediction is that the abundance of prey 2 does not directly control the decision after prey 2 has already been encountered; diet breadth changes primarily with encounter rate of the superior item. Predator size and temperature may influence handling or metabolism, but they are not the specified threshold variable in the basic model. Formally, prey 2 is included when its profitability exceeds the expected average return from continuing to search for prey 1. This links a post-encounter choice to the opportunity cost imposed by future search.

Ref: Ecology: Concepts and Applications, Molles, 9th Ed., Ch. 14

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Predator Prey Model

In a prey-predator interaction graph, prey increase causes:

An increase in prey provides more feeding opportunities and energy to predators, so predator survival, fecundity, or recruitment typically rises after a time lag. In the Lotka–Volterra predator equation dP/dt = baNP − mP, increasing prey density N raises the positive consumption-and-conversion term baNP. When N exceeds m/(ba), energetic gains exceed predator mortality and the predator population grows. The lag reflects time needed for prey consumption to improve body condition, gestation, development, or recruitment, which is why predator peaks commonly follow prey peaks in time-series graphs. Predator decline is expected after prey scarcity, not abundance. A constant level or no change could occur temporarily if predators are limited by territory, disease, handling saturation, or another factor, but it is not the basic consumer–resource prediction. Very abundant prey can saturate intake, producing a plateau rather than unlimited predator growth. The mechanistic link remains a positive numerical response: increased resource availability raises predator population performance when food is limiting.

Ref: Ecology: Concepts and Applications, Molles, 9th Ed., Ch. 14

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Predator Prey Model

When a predator uses venom to catch prey, it's an example of:

Venom is a chemical predatory weapon because toxins delivered by a bite, sting, fang, harpoon, or nematocyst disrupt prey physiology. Components may block ion channels, impair neuromuscular transmission, damage membranes, alter coagulation, or initiate rapid tissue injury. Immobilization reduces escape and shortens pursuit or handling time, while digestive enzymes may begin extraoral processing. Calling this “chemical warfare” is informal, but it correctly distinguishes chemical incapacitation from purely mechanical capture. Mimicry relies on resemblance or deceptive signaling, ambush describes waiting concealed before attack, and group hunting depends on coordination among predators. A venomous predator may also ambush or hunt cooperatively, so these categories are not mutually exclusive; the feature specified is toxin use. Venom differs from poison because venom is actively delivered through specialized structures, whereas poison harms when touched or ingested. Natural selection can produce coevolutionary escalation as prey evolve resistance and predators evolve altered toxin composition or delivery, linking the biochemical mechanism to predator–prey arms races.

Ref: Ecology: Concepts and Applications, Molles, 9th Ed., Ch. 14

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Predator Prey Model

The prey isocline in Lotka-Volterra model represents:

A prey zero-growth isocline contains combinations of prey and predator densities for which the prey population’s instantaneous net growth is zero. In the basic Lotka–Volterra equation dN/dt = rN − aNP, setting the derivative to zero for positive N gives P = r/a. Below that predator density, prey births exceed losses to predation and prey increase; above it, prey decline. The isocline therefore summarizes how prey growth changes with predator density, which is the intended meaning of “prey population growth versus predator density.” It is not itself a predator-mortality relation or merely a predator–prey ratio. Nor is it automatically an extinction threshold, because a zero derivative at a particular state can be crossed in either direction and trajectories depend on both equations. If logistic prey growth is added, the isocline slopes downward with prey density because crowding also limits growth. Isoclines are phase-plane tools: their intersection locates an equilibrium, and the direction of change around them reveals the system’s dynamics.

Ref: Ecology: Concepts and Applications, Molles, 9th Ed., Ch. 14

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Predator Prey Model

Escape response in tadpoles is influenced by:

Tadpole antipredator behavior can be shaped by both personal experience and social learning. After exposure to predator odor paired with alarm cues from injured conspecifics, a tadpole may learn that the odor predicts danger and later show stronger refuge use, freezing, or escape. Naïve individuals can also acquire information by observing the responses of older or experienced group members or by detecting their chemical alarm signals. Social transmission is especially useful when direct sampling could be lethal, while prior exposure calibrates the reliability of environmental cues. Temperature and food availability can certainly alter activity and energetic trade-offs, but they do not capture the learning mechanism emphasized. Older individuals alone are not sufficient as a general explanation; what matters is the information their behavior or cues convey and the learner’s experience. The response is phenotypically plastic, allowing prey to balance the survival benefit of vigilance against costs such as reduced feeding and growth. Experimental designs separate these effects by independently manipulating cue exposure and social companions.

Ref: Ecology: Concepts and Applications, Molles, 9th Ed., Ch. 14

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Predator Prey Model

Tadpole study showed that escape response is highest when:

Prior predator exposure can produce learned recognition, while the presence of older, experienced tadpoles supplies social information about danger. Combining both sources can yield the strongest escape response: exposed individuals have formed an association between predator cues and risk, and experienced companions amplify or validate that information through alarm behavior. Tadpoles may detect chemical cues from injured conspecifics, predator odor, or changes in neighbors’ activity and then reduce movement, seek refuge, or perform rapid escape swimming. Naïve isolated animals lack both personal and social information; experienced but isolated animals lack group reinforcement; naïve animals with older conspecifics can learn socially but have no prior direct conditioning. The precise outcome depends on species, predator, cue concentration, and the behavioral metric used, and the generic reference given does not identify the claimed experiment. Nevertheless, the keyed combination is mechanistically plausible because multiple information channels can improve risk assessment. Such learning allows prey to express costly defenses selectively rather than maintaining maximum vigilance in safe conditions.

Ref: Ecology: Concepts and Applications, Molles, 9th Ed., Ch. 14

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Predator Prey Model

In a system with alternate prey, predator population may:

Alternative prey can maintain or increase predator numbers even while the principal prey declines because the predator’s energy intake depends on the total accessible resource base. Generalists may switch toward the alternative, and reproduction or survival supported by that food can offset losses caused by scarcity of the main prey. In a multispecies growth equation, positive contributions from alternative prey can keep predator per-capita growth above mortality. Predator abundance is therefore neither necessarily constant nor unaffected by the main prey’s decline. This subsidy can have an important indirect effect: sustained predators may continue attacking the depleted focal prey, creating apparent competition between prey species and potentially preventing recovery. If predators switch strongly away from rare prey, however, alternative food can stabilize coexistence. Outcomes depend on prey profitability, encounter rates, switching behavior, and whether prey abundances covary. The central prediction is energetic rather than categorical—when alternative prey contribute enough food, predator carrying capacity and population growth need not track the main prey alone.

Ref: Ecology: Concepts and Applications, Molles, 9th Ed., Ch. 14

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