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#predator-prey

19 public questions tagged with this topic.

Top-down control exemplifies:

“Trophic cascade” for top-down control exemplifies. This relationship follows from the ecological mechanism represented by the terms in the item, not merely from an association between their names. The relevant inference should follow the pathway from resource supply to organismal uptake and then to ecosystem-level flux. Productivity, trophic transfer, decomposition, and nutrient regeneration are connected, but each measures a different part of that pathway. The remaining alternatives—“Nutrient cycling”, “Abiotic influence”, “Bottom-up model”—refer to different states, processes, or scales and therefore do not express the same causal relationship. Rates depend on temperature, moisture, substrate quality, consumer physiology, and the elemental balance between organisms and their food. These controls explain why the same process can differ among terrestrial, freshwater, and marine systems without changing its definition. Field observations could test this account by measuring the proposed driver and the demographic or ecosystem response while controlling plausible confounding factors.

Ref: Fundamentals of Ecology, Odum & Barrett, 5th Ed., Ch. 4

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

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

In Marginal Value Theorem, longer travel time implies:

Longer travel time between patches increases the optimal residence time within a profitable patch under the marginal value theorem. Travel is an unavoidable period with no food gain, so frequent departures would devote a large fraction of total foraging time to transit. A forager should therefore exploit each reached patch more thoroughly, remaining until its declining marginal gain rate equals the lower habitat-wide average created by the greater travel cost. Graphically, increasing travel time moves the tangent’s origin farther left on the cumulative gain curve and shifts the tangency point to a later departure time. This does not mean that total patch gain alone is maximized; the decision maximizes long-term gain per total time, including travel. Shorter residence would worsen the transit penalty, while increased patch discovery is unlikely when travel itself is longer. Risk can modify the prediction if travel or patch residence differs in danger, but risk is not the mechanism in the basic theorem. The result follows from diminishing returns combined with time lost between patches.

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

Which situation favors stable coexistence?

A predator with multiple prey can persist by switching toward whichever prey is relatively abundant, reducing pressure on a prey species when it becomes rare. This frequency-dependent switching can provide each prey a low-density refuge and dampen extreme consumer–resource cycles. A broader resource base also prevents immediate predator starvation when one prey declines, although persistent predator subsidy can instead create apparent competition and harm a rare focal prey. Stability therefore depends on switching strength, functional responses, and whether prey fluctuations are synchronized. Rapid prey reproduction alone does not guarantee coexistence; it may support recovery, but delayed density dependence can amplify oscillations. Lack of predator territory has no consistently stabilizing effect, and isolated prey may escape predation locally but do not by themselves establish dynamical coexistence. Among the alternatives, multiple prey provide the clearest mechanism for buffering food availability and distributing predation. The conclusion is conditional rather than universal: generalist predators stabilize coexistence most effectively when they preferentially attack common prey instead of maintaining heavy pressure on a declining species.

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

Predators are unable to drive prey to extinction if:

A limited predator carrying capacity prevents predator numbers from increasing without bound as prey become rare. If predator survival and reproduction depend strongly on the focal prey, declining prey reduces the resource base, causing predator decline before every prey individual can be removed. Refuges, handling constraints, territoriality, and alternative food webs may further permit persistence. This negative feedback can protect prey from extinction: low prey density supports fewer predators, reducing total predation pressure. Density-independent predator growth would remove that stabilizing response and could intensify prey loss. Mimicry may reduce capture probability for particular prey but is not the general condition described, while an absent prey population is already extinct. The statement is not an absolute law—predators introduced to naïve, spatially restricted prey can cause extinction, especially if predators are subsidized by alternative prey. In the intended single-resource system, however, resource-limited predator carrying capacity creates a numerical response that weakens predation as prey decline, favoring coexistence rather than complete elimination.

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

Which graph type best represents predator-prey oscillations?

Predator and prey time series are often represented by approximately sinusoidal waves because both populations rise and fall repeatedly, with the predator peak lagging behind the prey peak. When predators are scarce, prey increase; abundant prey then supports predator reproduction. The enlarged predator population depresses prey, after which food shortage causes predator decline and allows prey recovery. This negative feedback generates coupled cycles in the classical Lotka–Volterra model. A sine wave is only a visual approximation: actual trajectories need not be mathematically sinusoidal, and cycle amplitude and period can vary through seasonality, density dependence, refuges, stochasticity, or delayed responses. A linear increase cannot represent repeated reversals, a constant decline lacks recovery, and random scatter lacks the temporal coupling expected from consumer–resource feedback. Phase-plane plots provide another representation, showing orbits around an equilibrium rather than abundance through time. The important feature is regular, lagged oscillation, not perfect adherence to a particular trigonometric function.

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

Which of the following reduces the efficiency of a predator?

Long handling time reduces a predator’s feeding efficiency because time spent pursuing, subduing, processing, or digesting one prey item is unavailable for locating and consuming others. Profitability falls as E/h decreases, even if the prey contains substantial energy. At high prey density, handling can become the limiting step and produce a saturating Holling type II functional response: encounter opportunities increase, but consumption approaches a maximum of roughly one item per handling-time unit. Camouflage usually improves approach success for the predator, group hunting can increase capture probability or permit larger prey, and high prey density generally raises encounters until saturation. Efficiency should be defined using the relevant currency—energy per time, prey killed per effort, or reproductive gain—because group hunting also requires sharing food and camouflage may have costs. Nevertheless, with other variables held constant, increasing handling time lowers maximum intake rate and narrows the circumstances under which that prey is profitable. The effect links individual foraging decisions to population-level predator responses.

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

Which of these contributes to predator’s carrying capacity besides victim abundance?

Alternative prey can raise a predator population’s effective carrying capacity because they provide energy when the principal victim is scarce. A generalist predator may switch its foraging effort, maintain survival and reproduction, and persist at densities that the focal prey alone could not support. In population models, predator growth depends on the summed contributions of consumable prey, so an additional positive term can keep net growth above mortality. Refuge space generally protects prey and may lower predator intake rather than support more predators. Mutualism and migration can influence abundance in particular systems, but neither is the direct additional food resource specified. Alternative prey can also produce apparent competition: one prey species supports more predators, increasing predation on another species even though the prey do not compete for resources. Whether alternative prey stabilize dynamics depends on predator switching, prey synchrony, and functional responses. The central carrying-capacity mechanism is energetic subsidy—more total accessible prey biomass permits a larger equilibrium predator population than the main prey population could sustain alone.

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