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BIOS 6150: Ecology - Dr. S. Malcolm. Week 6: Predation and predatory behavior Slide - 1

BIOS 6150: Ecology Dr. Stephen Malcolm, Department of Biological Sciences

•  Week 6: Predation and predatory behavior:

•  Lecture summary: •  Nature of predation. •  Diet breadth & choice. •  Optimal foraging. •  Functional responses •  Mutual interference. •  Aggregative response. •  Marginal value theorem.

J. Kobalenko. 1997. Forest Cats Of North America. Firefly Books

http://www.americazoo.com/goto/index/mammals/134.htm

Snowshoe hare and lynx.


2. Predation:

•  Is a description of the interaction between predator foraging behavior and prey defense.

•  This includes both behavior and population dynamics.

•  Fig. 20.1 from Malcolm (1992) in “Natural Enemies” edited by M.J. Crawley (Blackwell).


3. Predation literature:

•  Very strong emphasis on predator foraging behavior and prey-predator dynamics.

•  Defense is mostly relegated to the realms of natural history description.

•  Predator foraging behavior is a description of:

•  where they feed. •  what they feed on. •  how they are influenced by other predators. •  how they are influenced by prey density.


4. Diet composition and food preference:

•  Predators can be: •  Monophagous:

•  single prey type and have a large impact on prey population dynamics

•  Oligophagous: •  few prey types, or,

•  Polyphagous: •  many prey types and probably have little impact on

the population dynamics of any one species.


5. Prey choice:

•  Within different diet breadths predators choose more profitable prey preferentially (Table 9.1) and so food can also be assessed by predators as either: •  Ranked food resources that are most valuable or

“perfectly substitutable” •  see Figs. 9.14 and 9.15, or,

•  Balanced food resources that are integral or “complementary”

•  Usually necessary to balance required nutrients that may be absent from high ranked foods.


6. Switching:

•  Predators can also “switch” their food preference as in Fig. 9.15: •  Perhaps through learned abilities to handle prey

more profitably: •  More efficient balance among search, pursuit, and

handling behaviors before consumption: •  This may be facilitated by specific “search images”.

•  Such changes in diet may also be seasonal or on shorter time scales that may be associated with the induction of physiologies better suited to exploiting the food resource.


7. “Optimal foraging” and diet width:

•  Why are real diets "narrower" than potential diets? •  If energy maximization is the primary criterion that correlates

well with fitness then optimal foraging theory is useful. •  MacArthur & Pianka (1966) initiated the influential

optimal foraging theory approach for the description of the evolutionary ecology of predatory behavior based on:

•  Maximization of the net rate of energy intake: •  gross energy intake - energetic costs of obtaining that energy.

•  Predators incur energy and time costs of: •  Searching for prey •  Handling prey:

•  Includes: detection, pursuit, acceptance, subjugation & consumption


8. Optimal foraging theory:

•  The aim is to predict the expected foraging “strategy” under specified conditions (Fig. 9.17):

•  Is it a “tactic” or a “strategy”? •  Generalist costs:

•  Low time search costs but higher costs of handling both unprofitable and profitable prey.

•  Specialist costs: •  High time costs but lower costs of handling profitable

prey.


9. Diet profitability:

•  MacArthur & Pianka argued that a prey item (i) should be included (and diet width expanded) if it is equal to, or more profitable than, the average profitability of the present diet, thus if: •  Ei /hi ≥ E/(s + h) •  where i is the next most profitable prey item •  E = energy content •  h = handling time (therefore E/h = profitability) •  s = search time


10. Foraging guilds:

•  Handling time < search time = generalists: •  e.g. foliage gleaning bird guild:

•  A guild is a group of individuals that exploit the same resource in the same way (after Root).

•  Handling time > search time = specialists: •  e.g. lions living near prey:

•  Note: handling time includes pursuit time! •  See text – these don’t make sense to me, despite

discussing this with Mike Begon!


11. Foraging constraints:

•  Abiotic and Biotic: •  More dimensions of “realized” niches! •  Biotic:

•  see Figures 9.18 and 9.19 •  Abiotic:

•  e.g. the interaction between temperature and oxygen constrains Notonecta foraging for submerged or floating prey according to dissolved oxygen levels (see Figs 2 & 4 from Cockrell (1984) Journal of Animal Ecology 53(2): 519-532.)


12. Functional Responses:

•  Describe the relationship between an individual predator’s consumption rate and prey density:

•  After Solomon (1949) but developed by Holling (1959).

•  3 kinds recognized by Holling: •  Type 1 (linear). •  Type 2 (asymptotic). •  Type 3 (sigmoid).


13. Type 2 Functional Response:

•  Type 2 functional response is most frequently observed (see Figs 10.9 & 9.7):

•  Handling t stays constant but search t decreases with increasing prey density.

•  Thus total handling time increases. •  Handling time Th determines the height of the

curve plateau. •  Attack rate a determines rate that plateau is

reached.


14. Types 1 & 3 Functional Responses:

•  Type 1 functional response (slope = a) as in filter-feeding Daphnia (Fig. 10.8).

•  Type 3 functional responses as in vertebrate predators capable of learning (Fig. 10.10) and showing “switching” behaviors:

•  Increased attack rate and increased searching time or decreased handling time.


15. Holling's “disc” equation:

•  The functional response relationship is described by Holling's “disc” equation in which: •  Prey eaten, Pe = a TsN

•  where Ts is the period of searching time during which Pe prey are eaten, and

•  N = prey density •  but, Ts = T - ThPe •  where T = total time

•  and so, Pe = a (T - ThPe)N •  Y = a(T - bY)X, in Tostowaryk (1972)

•  or, rearranging, Pe = aNT/1 + aThN


16. Michaelis-Menten-Holling equation:

•  Holling’s disc equation is the same as the continuous form: •  b(N) = mN/(w + N),

•  where m is the maximum predator attack rate, •  b = rate of change of N due to the interaction, and, •  w is prey density where attack rate is half saturated.

•  This is also the same as the Michaelis-Menten equation that describes the kinetics of enzyme catalyzed reactions:

•  vo = VmaxS/Km + S, where, •  Km = w, S = N, Vmax = m


17. Effects of functional responses on population dynamics:

•  1) Decelerating consumption rate results in destabilization because it is inversely density dependent:

•  All 3 functional responses at high density.

•  2) Accelerating consumption rate results in density-dependent stabilization:

•  Type 3 functional response at low density.


18. Predator density - mutual interference:

•  Mutual interference - effects of competition: •  Effects of territoriality, or resource defense, or direct

interference competition, or indirect exploitative competition, can all increase with increased predator density:

•  Figure 9.10 shows density dependent changes when searching efficiency a (=attack rate) is plotted against predator density:

•  The slope of this relationship m is the coefficient of interference. This negative slope tends to stabilize predator-prey dynamics.

•  In contrast to social facilitation at low predator density: •  e.g. foraging dolphins.


19. Prey density - aggregative responses by predators to prey “patches”:

•  Aggregative response •  Predators spend more time in high density prey

patches than low density patches (where spatial distribution varies) (Fig. 9.11).

•  Combined functional and aggregative responses (Fig. 9.22).

•  Impact on population dynamics: •  Partial prey refuges at both high and low prey

density: •  Lowered probability of attack tends to stabilize

predator-prey population dynamics (Fig. 5.19)


20. The “ideal free distribution” of predators and prey:

•  Aggregation + interference may combine to generate: •  An ideal free distribution (Fig. 9.27), or, •  Patchiness in time and space can generate

stability: •  As in Huffaker's orange+mites experiment:

•  Through equal (“ideal”) patch profitabilities after (“free”) redistribution.

•  Interaction between competition and predation!


21. The Marginal Value Theorem:

•  Based on the work of Charnov (1976) and Parker & Stuart (1976) to predict the behavior of an optimal forager in patches of food of different profitabilities:

•  The forager should maximize its overall intake of a resource (energy) per time spent foraging in habitats with food distributed patchily: •  How long should the forager spend in patches of

varying profitability? •  Fig. 9.22 illustrates the model and Fig. 9.23 is a test

of the model (Cowie).


Table 9.1 (3rd ed.):


Figure 9.14: Selection of the most profitable prey by crabs and wagtails


Figure 9.15: Preference (a & c), switching (b) and switching + learning (d & e)


Figure 9.17: Predictions and observations of diet choice in great tits and bluegill sunfish


Figure 9.18: Seasonal variation in predicted and observed habitat profitabilities for bluegill sunfish.


Figure 9.19: Effect of largemouth bass on sunfish feeding distribution.


Figure 2: Effect of water temperature on time spent submerged by foraging Notonecta (Cockrell, 1984):

Journal of Animal Ecology 53(2): 519-532.)


Figure 4:

Cockrell, B.J. 1984. Journal of Animal Ecology 53(2): 519-532.)

Mean length of time spent submerged by Notonecta and number of attacks on flies at the surface and Asellus on the bottom of water tanks at 3 dissolved oxygen concentrations.


Figure 10.9: Type 2 functional responses of (a) damselfly nymphs and (b) bank voles.


Figure 9.7 (3rd ed.): Type 2 functional responses in a parasitoid and effect of experience


Figure 10.8: Type 1 functional response in Daphnia filter-feeding yeast.


Figure 10.10:

Type 3 functional response in: (a) shrews & mice, (b,d) flies, (c,e) wasp parasitoid


Figure 9.10 (3rd ed.): Negative impact of mutual interference increases with forager density


Figure 9.11 (3rd ed.): Aggregative responses of foragers to host or prey density


Figure 9.22 (3rd ed.): Interaction between aggregative and functional responses


Figure 5.19: Effect of tide fluctuations on the distributions of predatory whelks and their barnacle prey.

Begon, Mortimer & Thompson (1996)


Figure 9.27: Ideal-free distribution in foraging ducks


Figure 9.22:

The marginal value theorem


Figure 9.23: Predicted and observed foraging times spent by great tits in prey patches with different traveling times.

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Week 6: Predation and predatory behavior: Lecture summaryhomepages.wmich.edu › ... › Lectures › 6150Week06.pdf · BIOS 6150: Ecology - Dr. S. Malcolm. Week 6: Predation and