Optimal Foraging 2024 PDF
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Uploaded by AdoredNirvana3473
Hong Kong International School
Dr. Benoit Guénard
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These lecture notes cover Optimal Foraging Theory. The document details different aspects from the definition of foraging to the profitability of prey to consumers. Focuses on the key factors that affect foraging decisions in animals.
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Optimal foraging: What to eat, where, when and how? Ecology & Evolution BIOL2306 Dr. Benoit Guénard Foraging Definition: The suite of activities involved in the exploitation of a resource. The term is mostly used for food resources but can be used...
Optimal foraging: What to eat, where, when and how? Ecology & Evolution BIOL2306 Dr. Benoit Guénard Foraging Definition: The suite of activities involved in the exploitation of a resource. The term is mostly used for food resources but can be used for other resources such as nesting material, finding mates… Danchin, Giraldeau & Cezilly. 2008 Foraging modes of predators Foraging mode Sit & Wait (ambush) Active (cursorial) Capture rate Low High Metabolic cost Low High Physiology Low endurance High endurance Learning capacity Low High Diet breath High Low Let’s talk about food Food resources vary in many ways: Spatially – most food resources are available in an unpredictable fashion, few are spatially constant (e.g. fruits on particular trees, honeydew from sap-sucking insects) Temporally – food supplies are generally available in an unpredictable fashion In terms of quality – while foraging, organism encounter prey of unequal value (e.g. small vs. large worms) In terms of accessibility – close or far from the nest, areas with low or high competition/predation Optimal Foraging Theory Problem How to forage optimally & maximize the net rate of energy gain? Main questions What should be included in the diet? Where should animal feed? How long should they spend there? At the core of optimal foraging theory is the hypothesis that natural selection should favor “efficient” foragers - individuals that maximize their energy or nutrient intake per unit of effort Use of an economic approach to answer these questions: Benefits – Costs relationship Optimal Foraging Theory Several parameters to consider: Benefits (B): should be measured in terms of fitness gain (difficult) – measure energy available in food (joules) - simple to quantify Costs (C): search and acquisition (handling) - harder to measure and can be expressed in Energy or Time (other costs may exist) Optimal foraging should thus maximize B over C, so that B/C >1 B/C = Energy Gained / (Search cost + Handling cost) With formula being either expressed as: Eg / (Es + Eh) or Eg / (Ts + Th) Optimal Foraging Theory Animal diet: what to eat from a variety of resources? Two kinds of preys (P1) and (P2) with two different net energy gains (E1) & (E2) and handling costs (Th1) & (Th2) Profitability defined as E1/Th1 & E2/Th2 – the net energy gained per unit handling time for both preys (P1 & P2) P1 is more profitable than P2 : E1/Th1 > E2/Th2 Optimal foraging theory predicts that P1 should be preferred to P2 Is it observed in nature? Optimal Foraging Theory Dung flies Pied wagtail Dung (Motacilla alba) beetles Potential preys available have different size range (5-10 mm) Most abundant preys around 8 mm Davies N. 1977. Journal of Animal Ecology 46: 37-57. Optimal Foraging Theory Dung flies Pied wagtail Dung (Motacilla alba) beetles The Pied wagtail show a preference for medium size preys around 7 mm and nearly ignore smaller and larger preys Why? Davies N. 1977. Journal of Animal Ecology 46: 37-57. Optimal Foraging Theory E/Th When profitability is calculated, then the optimal preys average 7 mm size Small preys do not provide enough energy (but low handling time – low Th) Large preys require too much handling time and effort (high handling time Th) relative to the energy gained Animals should select the most profitable preys available – the simplest model of optimal foraging But are there cases in which animals select suboptimal resources? Davies N. 1977. Journal of Animal Ecology 46: 37-57. Increasing the types of prey consumed As the number of prey types increases, Time cost per unit return the average searching time decreases As the number of prey types increases, Se g in ar the average handling time increases dl ch an in H g An optimum is found when both searching and handling times intersects representing the best Optimum strategy in terms of prey types Number of resource types optimization Ts + Th or Es + Eh are kept to a minimum, so B/C is maximized To eat or not to eat? P1 is more profitable than P2 : E1/Th1 > E2/Th2 Predator searching for P1, but finding P2. Should P2 be eaten or should the predator keeps looking for P1? Profitability P2: E2/Th2 Profitability P1: E1/(Th1 + Ts1) If: If: Eat P2 Keep searching for P1 (ignore P2) Strong weight of Ts1: the searching time for P1 (relative to the abundance of P1) Let’s see an example To eat or not to eat? Which species will be preferred in feeding experiments? Chitons: 24.52 Kj What if the gull finds an urchin? urchins Net gain urchin (E/Th): 7.45/8.3 = 0.9 chitons Net gain chiton E/(Ts +Th): 24.52/(3.1+37.9) = 0.6 glaucous-winged gull mussels 0.9 (urchin) > 0.6 (chiton) Gull should eat the urchin Irons D et al. 1984. Ecology 67:1460–1474 To eat or not to eat? Which species will be preferred in feeding experiments? Chitons: 24.52 Kj What if the gull finds a mussel? urchins Net gain mussel (E/Th): 1.42/2.9 = 0.5 chitons Net gain chiton E/(Ts +Th): 24.52/(3.1+37.9) = 0.6 glaucous-winged gull mussels 0.5 (mussel) < 0.6 (chiton) Gull should keep searching for chiton Irons D et al. 1984. Ecology 67:1460–1474 Why do animals need to maximize energy gain? To maximize time budget use and different functions to accomplish Higher net energy gain is beneficial for: - Growth (size & rate) - Reproduction (frequency & offspring size/number) - Defense - Repair (e.g. resting) - Storage (fat, etc.) A consumer (e.g. predator) optimising its effort should choose the most profitable food –which yields the highest energy gain per unit of time (not always largest item) Predictions about diet (1) Assuming that consumers maximise their net rate of energy gain, we can make predictions about food types included in the diet of an optimal animal 1) A consumer should eat only the most valuable prey type if the encounter rate is high (because inclusion of other types with lower food value would decrease the rate of energy gain) – be more specialist 2) If the most valuable prey is encountered at a low frequency, a consumer should expand the range of preys eaten to include the next most valuable type (& so on) – be more generalist Predictions about diet (2) The optimal animal should eat any food item it finds unless, during the time spent handling or eating it, there is a good chance of finding a more valuable type of food item - The diet should broaden as productivity of the environment declines (frequency of encounter with most valuable prey type falls) - Animals in unproductive environments will be generalists (otherwise too much time spent searching) - Animals in productive environments will be specialists (high encounter frequency allows focus on prey types with low handling time or high energy content) Where to eat? & For how long? Where is the best place to eat? Landscapes are a mixture or mosaic of more-or less-valuable patches (= areas of distinct habitat type) separated in space My best pick Scale dependent Where is the best place to eat? Optimal foraging theory: organisms should maximize profitability - energy gained per unit of time spent foraging in a given patch (rate of energy gain) If consumer gains more in exploiting highly profitable patches, the question is when should they leave it (as resources deplete)? Marginal value theorem (developed by Charnov, 1976) predicts the length of time an individual should stay in a resource patch before leaving and seeking another, based on 3 variables: Richness of the food patch (prey density) Time required to get there (travel time) Time required to extract the resource (acquisition) Marginal value theorem 1 1) Initial time cost associated with traveling 3 to the patch (no energy gain) 2) Once foraging is initiated, the rate of 2 energy gain is high 3) As resources deplete, rate of energy gain decreases The rate of return is defined as the cumulative value of G divided by the combined travel time (t) and foraging time (T) When should the consumer leave the patch? Marginal value theorem The maximum rate of energy gain is represented by the line that is tangent to the curve of cumulative gain with time (here shown as Gopt: G optimal) G1: Rate of return per unit of time still increasing G2: Rate of return per unit time is declining So past Gopt, it is optimal for an organism to leave the patch Let see how distance to the patch & patch quality influence consumers Marginal value theorem & Distance Here both patches have the same quality but differ in their distance to consumer: travelling time t2>t1 The marginal value theorem predicts that consumer should then spend more time to exploit resources (foraging) in patch 2 than in patch 1 In other words, increasing travelling time increases exploitation time required to optimally use a patch Marginal value theorem & Patch quality Here patches are at similar distance but have different resource values The marginal value theorem predicts that consumer should then spend more time to exploit the patch with higher resources value than the one with low resources value Animals prefer to feed in the richest patches & so these patches will attract most animals (& they will stay longer). Animals ignore poor patches if richer patches are available Marginal value theorem & Patch quality Female can discriminate between healthy and already attacked hosts (eggs) Trichogramma brassicae Created patches of 9 eggs with different ratio of healthy/attacked eggs: - 9 attacked / 0 healthy eggs Poor quality patch - 6 attacked / 3 healthy eggs - 3 attacked / 6 healthy eggs - 0 attacked / 9 healthy eggs High quality patch Wajnberg E. et al. 2000. Behavioral Ecology 11: 577–586 Marginal value theorem & Patch quality Use the Marginal value Observed results theorem to develop a Simulation mathematical model on patch exploitation Results: Females spent more time on patches of higher quality All patches were reduced to the same level of profitability before being left by females Wajnberg E. et al. 2000. Behavioral Ecology 11: 577–586 Conclusions - Animal foraging behaviour “appears” to depend upon a few simple decisions that result in them behaving optimally (other factors: influence of competitors/predators, prey defense not shown here) - The fact that we can predict how they will behave means that we have good understanding of factors determining their behaviour - Optimal foraging models predict behaviour on the assumption that animals maximize B/C & thus maximize rate of energy gain (to increase fitness) - Maximizing B/C may underlie all adaptations