1. Latitudinal Gradients in Avian Clutch Size Daylength Hypothesis Prey Diversity Hypothesis (search images) Spring Bloom or Competition Hypothesis Nest Predation Hypothesis (Skutch) Hazards of Migration Hypothesis Please study Handouts 1, 2, 3, and 4 in preparation for next Thursday’s exam

2. Evolution of Death Rates, Senescence, old age, genetic dustbin Medawar’s Test Tube Model, Lactose intolerance Recession of time of expression of the overt effects of a detrimental allele Precession of time of expression of the positive effects of a beneficial allele Pearl-Verhulst Logistic Equation: Sigmoidal Population Growth Density Dependence versus Density Independence Density Dependent versus Density Independent Selection Equilibrium, Opportunistic, and Fugitive Species r-strategists versus K-strategists

3. What starts off slow, finishes in a flash...

6. S - shaped sigmoidal population growth

7. Verhulst-Pearl Logistic Equation dN/dt = rN – rN (N/K) = rN – {(rN 2 )/K} dN/dt = rN {1– (N/K)} = rN [(K – N)/K] dN/dt = 0 when [(K – N)/K] = 0 [(K – N)/K] = 0 when N = K dN/dt = rN – (r/K)N 2

8. Inhibitory effect of each individual On its own population growth is 1/K

11. At equilibrium, birth rate must equal death rate, b N = d N b N = b 0 – x N d N = d 0 + y N b 0 – x N = d 0 + y N Substituting K for N at equilibrium and r for b 0 – d 0 r = (x + y) K or K = r/(x +y)

13. Derivation of the Logistic Equation Derivation of the Verhulst–Pearl logistic equation is easy. Write an equation for population growth using the actual rate of increase r N dN/dt = r N N = (b N – d N ) N Substitute the equations for b N and d N into this equation dN/dt = [(b 0 – xN) – (d 0 + yN)] N Rearrange terms, dN/dt = [(b 0 – d 0 ) – (x + y)N)] N Substituting r for (b – d) and, from above, r/K for (x + y), multiplying through by N, and rearranging terms, dN/dt = rN – (r/K)N 2

14. Density Dependence versus Density Independence Dramatic Fish Kills, Illustrating Density-Independent Mortality _______________________________________________________ Commercial Catch Percent ––––––––––––––––––––– LocalityBeforeAfterDecline _______________________________________________________ Matagorda 16,9191,089 93.6 Aransas55,2242,552 95.4 Laguna Madre12,016 149 92.6 ________________________________________________________ Note: These fish kills resulted from severe cold weather on the Texas Gulf Coast in the winter of 1940.

15. Parus major

16. Fugitive species

17. Some of the Correlates of r- and K-Selection _______________________________________________________________________________________ r-selection K-selection ______________________________________________________________________________________________________________________________ ClimateVariable and unpredictable; uncertain Fairly constant or predictable; more certain MortalityOften catastrophic, nondirected, More directed, density dependent density independent SurvivorshipOften Type IIIUsually Types I and II Population sizeVariable in time, nonequil-Fairly constant in time, ibrium; usually well belowequilibrium; at or near carrying capacity of envi-carrying capacity of the ronment; unsaturated com-environment; saturated munities or portions thereof; communities; no recolon- ecologic vacuums; recolon-ization necessary ization each year Intra- and inter-Variable, often laxUsually keen specific competition Selection favors1. Rapid development1. Slower development 2. High maximal rate of2. Greater competitive ability increase, r max 3. Early reproduction3. Delayed reproduction 4. Small body size4. Larger body size 5. Single reproduction5. Repeated reproduction 6. Many small offspring6. Fewer, larger progeny Length of lifeShort, usually less than a year Longer, usually more than a year Leads toProductivityEfficiency Stage in successionEarlyLate, climax ________________________________________________________________________________________________________________________________

18. Kirk Winemiller

19. From Molles and Cahill, Ecology: Concepts and Applications

20. Population Regulation [Ovenbird example]

21. Frequencies of Positive and Negative Correlations Between Percentage Change in Density and Population Density for a Variety of Populations in Different Animal Groups ___________________________________________________________________ Numbers of Populations in Various Categories ____________________________________________ Positive Positive Negative Negative Negative Taxon(P<.05) (Not sig.) (Not sig.) (P<.10) (P <.05) Total ___________________________________________________________________ Inverts 0 0 0 0 4 4 Insects 0 0 7 1 7 15 Fish 0 1 2 0 4 7 Birds 0 2 32 16 43 93 Mammals 1* 0 4 1 13 19 Totals 1* 3 45 18 71 138 ___________________________________________________________________ * Homo sapiens (the “sap”)

22. Negative correlations between percentage change in density and population density for a variety of populations in different animal groups except for Homo the sap 4 and 10 year population “cycles” microtines and snowshoe hares Sunspot Hypothesis — dark tree ring marks Time Lags Stress Phenomena Hypothesis Predator-Prey Oscillations Epidemiology-Parasite Load Hypothesis Food Quantity Hypothesis Nutrient Recovery Other Food Quality Hypotheses Genetic Control Hypothesis – Optimal reproductive tactics Could optimal reproductive tactics drive population cycles?

23. Notice apparent 10-year periodicity

24. Microtines: Voles and lemmings: 4 year cycles Fabled lemming marches into the sea Snowy owls

25. Disney’s “White Wilderness” movie

26. Dennis Chitty Charles Krebs A. Sinclair

27. Population “Cycles” Sunspot Hypothesis Time Lags Stress Phenomena Hypothesis Predator-Prey Oscillations Epidemiology-Parasite Load Hypothesis Food Quantity Hypothesis Nutrient Recovery Other Food Quality Hypotheses Genetic Control Hypothesis Bb:Read Krebs et al. “What drives the 10-year cycle of snowshoe hares?”