1. How do they get their food? Saw earlier in simple way, plants vs meat But is it that simple? What are some of the considerations in an individual actually selecting the food it eats? Chap 5 deals with this

2. How do they get their food? Basically “rules” in selecting food and where to forage for that food. Initial thing to keep in mind: Foraging animals know what they are doing!!! Why? Their life depends on it! Not just balls bouncing around!

3. “optimal” foraging theory IF they know what they are doing, then we should see some “optimization” occurring. What are they optimizing? Ratio between costs and benefits. Early theory developed with optimization in mind. Lot of critics…Why?

4. Arguments against optimizing Optimizing means eventually leading to the BEST way of doing it. Kind of like Evolution’s “survival of the fittest” Should lead to one “optimal” form. Better is: survival of adequate And: Adaptive foraging theory. Semantics? Reflects individual’s constant adjustment to changing conditions.

5. Ok, Adaptive foraging theory How do they do it? 4 possible areas where they can affect their energy intake vs costs of getting the energy. 1) What they eat: Diet 2) Where they eat: patch choice 3) How long they eat: Patch residence 4) Where do they go next: Patch movement

6. Foraging rules: diet selection All species have a specific range of food items they use: Why?? Some have very limited diets: specialists Others have wider diet range: generalists Why? “generalists” why do they choose specific foods at specific times? What are the “rules” in selecting a diet

7. Foraging rules! Diet selection: what factors to take into consideration? Caloric value: obviously Ease of handling: Pecans vs hickory nuts deer vs cow Risk: of being killed… of being injured. Will see later with patch use.

8. Rules “Generalists” rules Initial models developed from data on feeding response to food density Type II feeding response Forager can only eat so much!

9. Diet rules Basically, should broaden diet when principle prey 1 drops below a certain level. Considered “optimal” strategy. Here

10. General predictions Should rank food types relative to profitability Should always include most profitable prey and only expand to less profitable when 1 st does not meet needs Thus decision to switch is based on abundance of most profitable not less profitable All or none response: either always accept or never accept them.

11. Do they hold?? Most controlled experiments seem to produce expected results Great tits (small bird) Reduced use of large worms when reduced in number.

12. Do they hold? Works the best for herbivores or predators of sessile prey Not so well with predators and mobile prey Also not so well under predation risk. Does not include other needs e.g. minerals, proteins, etc. Not just all Kcal!

13. Predators and prey Even at zero rabbit abundance, coyotes still had 30% occurrence in their diet!!

14. Diet summary Know for sure: 1) all species have specific diets 2) some narrow, some broad 3) even broad diet, have preferred food Not so sure: 1) why they have the diet they do! 2) rules for selecting

15. Next is patch selection Why “patch” selection? Very few habitats uniform, habitat mosaic is often rule. So… if habitat is patchy, so will food availability. Thus, animals have to select among existing patches: which one to go to. Again, trying to balance gains and costs

16. Balance Benefits: How much and quality of food patch supplies: patch quality. Costs: How much energy needed to get to patch: central place foragers this is biggie Costs: How much energy needed to harvest food that is there. Again, not just quantity of food resource but how easy it is to get/handle, etc.

17. Patch selection Criteria? 1) Patch quality: resource quantity/quality Similar to diet selection: “should” pick “best” patch to feed in. What assumes? - animal’s knowledge of patch locations/quality: Reasonable? Perfect or imperfect information?

18. Criteria Other factors? - patch depletion rate: as patch is used or has been used, quality goes down. 1) herbivores: renewable/nonrenewable 2) Not so much reduction in # of prey but “catchability” of prey, will deal with later.

19. Other criteria - patch predation risk: Is it worth going to high quality patch where you might get killed? So not just patch quality food wise Introduces “predation risk” into foraging equation as a foraging cost. Actually transform risk into potential energy loss

20. Predation risk and patch choice H = C + P + MOC Harvest rate (H), what it can get out of the patch. C = what it needs for metabolism P =what it could lose (on average) from predation MOC Missed opportunity costs: energy used for other things instead of eating: grooming, displaying, etc.

21. What does this tell us? In patch selection, the patch has to be higher quality than just supplying metabolic needs This means forager can juggle C and P! E.g. could go to patch of lower quality IF had lower predation risk! E.g., could “take the chance” going to high quality/risk patch but for shorter time because of higher harvest rate!

22. What does this mean? Much more foraging options than just pure patch quality. Also affects how long they stay in patch, 3 rd area!

23. Patch residency Ok, will select a patch based on food quality that gives good balance when it enters the patch. But patch becomes depleted as it stays in the patch. When should it leave???

24. Options Could stay until all food harvested. But…. Diminishing returns, longer it harvests, less it gains per time/effort! Eventually, it would be better (more profitable) if it moved to another patch of now higher quality!!

25. Options But when should it do it??? “leaving rules”: when should an animal leave a patch? Early idea: Charnov 1976 proposed the “Marginal value theorem” as a leaving rule

26. Marginal value theorem Consider: 10 patches of different value. Can calculate average value of these ten patches (V1 +V2 + V3….+V10/10) Some will be above average Some below average. Assume (based on previous discussion) animal will first enter an above average patch.

27. Marginal value theorem As it forages, value of patch approaches overall average. MVT states that when the value of that patch reaches average of all patches, animal should leave Why? Because there are now other patches out there that are more valuable! Goes to one of these, harvest rate/time would be higher than if it stays!

28. Sound pretty simple! Is there support for this idea? Some, lots of studies looking at ”quitting harvest rates” and in general animals do leave BEFORE resource depleted, so there is some type of leaving rule Whether it is the MVT becomes debatable. Especially if we add predation risk!!

29. Predation risk and patch residence time How does the threat of being eaten affects how long you stay in a patch?? Again, not just food value of patch but probability of being killed

30. Patch safety In “safe” patch, animal can afford to stay longer,= lower quitting harvest rate. In “dangerous” patch, longer you stay the more likely you will be killed! Again, a balance between foraging and safety.

31. Measuring predation risk We know how we can measure food resources, saw earlier. How do we measure predation risk?? Obviously important in understanding/predicting patch selection and residency time.

32. Giving up densities As mentioned, safer areas should have lower quitting harvest rates: can measure but difficult. Need to observe animals and measure how much they are harvesting just before they leave. Brown 1988 demonstrated you can use not the harvest rate when they leave but what they leave behind, Giving up densities (GUDS)

33. Guds What?? Given any resource, animal will not eat all of it. Will leave some, gets to point not worth eating rest: What it leaves is its GUD More important Brown demonstrated that how much it leaves is related to predation risk!

34. How do you measure GUDs? Artificial feed trays/boxes: Mix in standard amount of seed/food Inedible substrate

35. They come Animals come and search for the seeds Give up depending on how dangerous it is!

36. Will work for deer too!

37. So what do you get?? Make comparisons between patch types. Identifies safe vs risky habitat for species

38. Patch selection and residence All this helps to adjust the patch selection and residence time rules. With these types of studies can adjust for predation risk. Leads to better understanding of how animals use the habitat they live in. Will see more later.

39. Patch movement rules Ok… have idea on why they might select patch and how long the might stay, but… Once you leave a patch, where do you go? This leads to 4 th concern, patch movement rules.

40. Patch movement What are factors to consider? Quality obviously Predation risk, obviously, Travel time is another one: if travel is energetically costly, distance figures in Travel risk: if you have to pass through dangerous area, becomes important in your decisions here

41. Dangerous travel, example Sheep often have to travel through wooded areas to get from one open area to the next.

42. Summary Have now seen that foragers need to consider the 4 aspects of foraging. Have seen that patch quality is dependent on food value and predation risk Result is a pattern of patch use by an individual

43. Patch use to habitat use Though we talk about patch use relative to foraging, patches represent habitats So… foraging represents or reflects a large part of the habitat use patterns of a species. Habitat use: spatial landscape use patterns of an individual related to the types of dominate vegetation in use and non-use areas.

44. What more is important? What other considerations relative to “patch use” (habitat use) are there? Move away from getting energy to the MOC’s

45. Missed Opportunity Costs From a foraging basis, these are all those things that “get in the way” of eating! Obviously important, more important at the appropriate time than eating!! What are they?

46. MOCs One big one is resting/sleeping! Although ruminants can combine resting and eating (re-eating), don’t take in new food. Few can eat and sleep at the same time! A large portion of the 24 hours is devoted to these different stages of rest (doing nothing with eyes open – sound sleeping

47. Rest and sleep Not concerned with reasons for nor physiology behind them but how do they affect habitat use. Where to rest/sleep? Often not same areas where you eat. Comfortable and/or safe (predation again!)

48. Resting and Sleeping Comfort: cool if it is hot, warm if it is cold So varies with season/weather Most species will have preferred warm/cold day resting or “loafing” sites. Nothing like a sunny rock on a cool day! When most likely to rest? After meals of course!

49. Resting/sleeping When most likely to sleep? For many, night-time (a lot of wildlife species are diurnal). Most birds, squirrels, primates, etc. For them, finding a sleeping spot that affords protection from night chill.

50. When do you sleep? For many, sleep during the day! Nocturnal or crepuscular. Cre..what! Most active around sunrise/sunset For these, daytime sleeping sites often are to alleviate daytime heat.

51. Why sleep in the daytime? Temperature extremes: too hot to eat! Safer, can see predators better. Brings us to predation risk while resting/sleeping

52. What is predation risk when resting/sleeping? Should be less than when foraging! Can choose “safe” places to rest/sleep Nests in trees, in trees, on the water, in burrows, hidden in shrubby areas, etc. Rest at vantage points, provide vista to see predators Disadvantage when asleep, can’t see the predator coming! Or can they?

53. Again predation risk! Risk of predation also influences where you rest, sleep and how you sleep!!

54. Sleeping with one eye open Unihemispheric sleep

55. Sleeping with one side awake! Ducks also: One foot keeps kicking, turns in circle.

56. Resting/sleeping in groups Group behavior, watch a herd of ungulates, some sleeping/usually at least one with head up. So resting/sleeping habitat important

57. Other MOC? Reproduction is a biggie!!! Male of many species forgo foraging when they are reproductively active. Can divide into: Courting/mating, parturition/egg laying, rearing of young At each stage, have different habitat requirements.

58. Courting For many birds, require specific habitat for courting Examples: tops of bushes, ruffed grouse, woodcock, leks, pronghorn, grebes

60. Courting What is important? Habitat that best displays your wares!! Can lose whole population if conditions for courting are not right: sage grouse Again, predation safety

61. Courting and predation Males often don’t have a clear focus!!! Become more susceptible to predation Bighorn sheep Often courting habitat has some safety feature Low cover may also be for ease of predator detection

62. Birth of young Birth/egg laying Again special habitat characteristics for environmental and predator protection of young. Nests, burrows, etc. designed for protection Birthing sites: bighorn sheep

63. Nest sites Bower birds Pileated woodpecker

64. Raising young Bed sites: deer/pronghorn Foraging shifts

65. MOC- migration Travel from one place to another Can be short: deer to winter yards Can be long: bird migrations Migratory species needs specific habitats at either end but also in the middle! Staging areas, stop-over sites, etc.

67. What does this all have to do with wildlife ecology and management? - Much of management is effort to provide adequate “habitat” for a species. “Adequate” now takes on a new meaning. It is just not food but predation risk, reproduction, climate, migration needs, etc.

68. Summary So foraging theory provides us with a base from which to examine a wide varieties of behaviors important for survival of wildlife. Food – Predation – MOC Includes all major drivers for habitat use patterns of a species. And all based in behavior of animals!

69. Summary Though in detail look at foraging etc., this has been a very brief view of animal behavior as it pertains to wildlife ecology and management. We manage by managing their behavior Will have more to say about other important behaviors later.

70. Ecology Now shift gears somewhat and look at ecological aspects of wildlife Difficult to separate behaviors from ecology but early ecologists did just that!! Reductionist: felt that getting rid of messy behaviors and treating animals like inanimate objects would help get at basis of ecological principles.

71. Nature through the eyes of an ecologist Mass action models mostly Stripped of behavior Looks mainly at outcomes Does give us a starting point to which we can add behaviors. Behavioral ecology

72. Where do we start? We looked at individual energy capture via foraging theory Now need to look at energy capture by the species: via reproduction How do species gain and loose energy? What are overall patterns? What are factors that affect this energy gain? here

73. Energy gain by the species First need to define our unit of consideration: before it was the individual Usually we can cluster members of a species into sometimes discreet, sometimes artificial groups: Populations Definition: group of individuals of a species living together in the same place at the same time.

74. Population Sometimes whole species Sometimes discreetly separated Often we define the limits to the population -often political units -anything we think is reasonable

75. Populations Review: how do populations add new energy? Reproduction Review: How do populations lose energy? Mortality Gains and loses of energy packets is the key Question: What are patterns of energy gain and lose of populations?

76. Gains and losses Review: know that populations grow exponentially N t = N 0 e rt

77. Express mathematically N t = N 0 e rt N t = population size at time t N 0 = population size at some starting time e = Natural exponent (2.72) r = exponential rate of increase (growth rate) t = time

78. Population Growth All have potential to grow exponentially by a %/cycle …so…. Need to consider the concept of doubling time: What is it? Time it takes a population to double its numbers (2-4), 10-12, 10000- 20000, etc.

79. Doubling time Can do it manually: If % growth is 20%, Have 20 animals, year 1 have 20*.2 = 4 or 24. year 2: 28.8, year 3: 33.6, year 4: 40.32, or double of start in 4 years. Holds for any starting number 2-2 gazillion In approximately 4 years, will have 4 or 4 gazillion.

80. Doubling times

81. Significance of it all? Each doubling time, it takes less time to add the same number as the time previous. Huh?? Use 20%, start with 1000 individual

82. Doubling times In 3.8 years we have 2000 individuals It took 3.8 years to add 1000 individuals In 3.8 more years we have 4000 individuals. In the same length of time, 3.8 years, we added twice the number of individuals (2000) as in the previous time period (1000)

83. Doubling times That is the significance of exponential growth: The more you have the faster you grow in the same length of time!

84. Why is this important?? The point is that given exponential growth, a population’s numbers increase more rapidly, the larger it is (at a given growth rate/doubling time) Increase r, decrease doubling time, population grows MUCH faster!

85. Year 65 70 75 80 85 90 95 00 0 20 40 60 80 100 120 % of the maximum deer harvest. % of the maximum estimate of pumas

86. Year 65 70 75 80 85 90 95 00 0 20 40 60 80 100 120 % of the maximum deer harvest. % of the maximum estimate of pumas

87. What is the mechanism? Ok, can grow exponentially but why?? Basic Math! If we start with 2 individuals (one male/one female), female gives birth to 2 young/year, 50:50 sex ratio. After first year: 2 + 2 = 4, 2 females Year 2: 2 + 2 + 4 = 8, 4 females Year 3: 2 + 2 +4 + 8 = 16, 8 females

88. Continue? Year 3: 2 + 2 + 4 + 8 + 16 = 32, 16 females. Start of exponential growth!

89. Works for any birthrate: only changes how fast it goes. Works if you remove original parents and subsequent ones, only slower.

90. Why? The mechanism is that each female contributes a given quantity of young, of which 50% are female so next generation has more females, giving birth to more, etc. result is exponential growth The more females you add, the more young added to population.

91. Significance? What this means is that females are important ones to population growth! Also, simple concept: all energy enters the population from bottom!! Natality Only source of new energy!

92. Do they always grow exponentially We know they don’t: aren’t covered knee deep with any species (except maybe humans!!) Fluctuate between growth and decline. Rarely stable Important point!

93. Examples

94. Year 65 70 75 80 85 90 95 00 0 20 40 60 80 100 120 % of the maximum deer harvest.

96. What does this mean? Exponential growth a built-in mechanism adapted to CHANGE! Good time-bad times. View exponential growth as way population adjusts to change.

97. Mortality So if they don’t always grow exponentially, why not?? What happens in bad times? Mortality happens!! Individual: loss of ability to capture energy Population: loss of energy packets

98. Mortality How does it occur? Where does it occur? How does it affect population growth?

99. How does it occur? Can divide mortality sources into various categories: First major one is: prenatal and postnatal Prenatal, don’t make it out of womb or egg Post natal, from point of birth to life span

100. Prenatal mortality Can be from: 1) failure to implant 2) re-absorption 3) still-born/addled (die while in shell)

101. Prenatal mortality Various reasons: most nutrition level of female/ egg – environmental (Happy Feet!) Of importance relative to population growth Less energy entering in the bottom! Will see later when we have all together

102. Postnatal mortality Four main ones are: 1) accidents 2) disease 3) starvation 4) predation Will look at more in detail but for now….

103. Postnatal mortality Important point is that these mortalities can happen ANYTIME from birth to life span. Where they happen and to whom they happen makes a difference!

104. Can view mortality as the governor of the population. Working against natality and exponential growth

105. General patterns N > M: population grows (exponentially) N =M : population stable N < M: population declining (exponentially) The lake model: one river coming in (natality), many rivers leaving (mortality)

106. How do we incorporate mortality? Traditional: Logistic equation dN/dt = rN(1-N/K) N number of animals r is growth rate t time K is carrying capacity (1-N/K) is representation of total mortality

107. Logistic equation Treat mortality (all sources and all ages) as an increasing function as we get to the “limits” of the environment: carrying capacity defined as the number of animals an area can support over time. Is good as an initial approach BUT it does not reflect reality

108. Logistic equation It REALLY does make a difference as to the sources of mortality and what ages and sexes it affects.

109. Mortality patterns Lets first take where the mortality is occurring Divide: male/female Divide: age groups – one is… Pre-reproductive Reproductive Post reproductive here

110. Mortality How do we estimate mortality? Directly Indirectly

111. Direct methods 1) Follow all individuals born one year (cohort) until last one dies! Can do this with small pops but difficult with large or secretive animals. 2) Follow a group of marked individuals represents a sample of the total. How do we follow them? - marked so we can identify them.

112. Marked individuals Capture-recapture: do over time and record those that show up AND those that don’t!! Aerial surveys: count number of marked animals. Difference between those you see and the starting number is number that died! Follow known aged individuals: accounting e.g. cougar data.

113. Indirect methods If you can’t follow a group of animals…? Take a snapshot! Live animals Dead animals

114. In both cases Use existing age structure as an estimate of how many are dying each time interval. Assumption: no significant change in mortality rates WITHIN a given age class. Assumption: birth rates do not change Example: If you have 100- one year olds but only 50 2-year olds, assume 50 died from age 1-2.

115. What does it give you? Gives you number of animals that died during each time interval from birth to death of last one. What do data look like?

116. Example Dall sheep in Alaska: Adolph Murie 1930’s-40’s: 608 sheep skulls

117. TABLE 6.—Skulls of 608 sheep which died before about 1937, showing number of diseased and nondiseased animals in annual age classes. Sexes of lambs and yearlings are combined since usually they are not known. Sex, age, and conditionLam bs Yearl ings Age in years Total 234567891011121314Misc ellan eous [1] Both sexes, no disease noted [2] Both sexes, diseased [2] Ewe, no disease noted [3] Ewe, diseased [3] Ram, no disease noted [3] Ram, diseased [3] 33 -- -- -- -- -- 85 3 -- -- -- -- -- -- 1 2 4 -- -- -- 2 -- 5 1 -- -- 2 2 3 -- -- -- 8 4 2 4 -- -- 6 14 3 5 -- -- 9 8 4 8 -- -- 11 7 15 9 -- -- 14 6 11 16 -- -- 20 8 33 6 -- -- 4 1 42 9 -- -- 2 -- 28 2 -- -- -- -- 1 -- -- -- 56 26 49 13 118 3 135 78 201 73 Total3388779182829 424767563211144 608 TABLE 6.—Skulls of 608 sheep which died before about 1937, showing number of diseased and nondiseased animals in annual age classes. Sexes of lambs and yearlings are combined since usually they are not known. The 144 were all 9+ years old

118. Sex, age, and conditionLambsYearlings2-8 years 9 years and older Total Both sexes, no disease noted [1] Both sexes, diseased [1] Ewe, no disease noted [2] Ewe, diseased [2] Ram, no disease noted [2] Ram, diseased [2] 33 -- -- -- -- -- 85 3 -- -- -- -- -- -- 39 37 36 27 -- -- 96 41 165 46 118 3 135 78 201 73 Total3388139364608. 1 Lambs and yearlings. 2 Adults.

119. Lets standardize it Put it on the basis of 1000 individuals to start with. 121 died in first year Or 19.9% So beginning of next year 801 left.

120. We can then depict graphically

121. What did they learn from this? Most mortality occurred in first year of life and after 8 years. Reproductive ages seemed buffered Why? Peak of health, hard for predators to get Predators (wolves) feeding on young and old.

122. Impact on energy flow in population? Energy enters in bottom BUT has to be produced by middle or reproductive individuals. As long as reproductive individuals are maintained, can loose a high percent of young and population will remain stable. Just need to replace losses in reproductive ages, which are the smallest!

123. Is it the same for all species?? This pattern seems common for many wildlife species, birds, mammals. But is not universal Other patterns found:

124. Variations Mud Turtles Whitecrowned Sparrows Phlox Rotifer High juvenile survival. Constant mortality rates

125. And so? Different energy loss patterns mean different strategies regarding balance between losses and gains. Becomes important to assess these patterns for given species How? Life tables

126. Life tables Accounting technique to identify where losses are occurring: Age Interval (yrs) x Number Alive at Start nx Number of Deaths dx Annual Mortality Rate (%) qx Annual Survival Rate (%) sx 0-1655416.3 a 93.7 1-261411719.180.9 2-3497102.098.0 3-448791.898.2 4-547891.998.1 5-6469234.995.1 6-7446347.692.4 7-8412379.091.0 8-93754812.887.2 9-103277924.275.8 10-112489237.162.9 11-121568856.443.6 12-13686494.15.9 13-1441.. 14-1533.. Total523965512.587.5 Life table for Dall Sheep in Mount McKinley National Park, Alaska, based on age grouping of skulls of animals dying of natural causes

127. What you can do with them Since these tables are based on field data, helps identify losses. Helps determine if population is ok or in trouble Helps identify where management of mortality rates might be needed.

128. But life tables are not just death! Other statistics can be calculated Note above: Survival rate – reciprocal of mortality rate What else?

129. Typical life table d x = percent of total dying q x = mortality rate percent that die each year l x = survivorship

130. Mentioned that new energy is produced by middle animals. So it is important to look at the capability of producing that energy Fecundity Annual fecundity: Number of young SUCCESSFULLY raised/yr.

131. Annual fecundity Increases directly with annual adult mortality Short lived species (smaller species) have high fecundity Long lived species (larger species) have low fecundity. Short lived also breed younger.

132. Table with fecundity m x = # young/female Note changes with age

133. Relationships: fecundity/life expectancy

134. Why is this all important? Age makeup of the population can vary. Growth depends on where females in population are. If high in age classes with low fecundity may not grow fast now but will in future If survival rates change for some reason, will have different affects with different ages.

135. Life time fecundity Another aspect of fecundity is the number of successful offspring you raise through your whole life! Related to life span Related to annual fecundity Question: what should lifetime fecundity be?

136. Interspecies comparisons Higher annual fecundity in short-lived vs lower annual for long-lived species: does it make a difference over lifetime? Is one method “better” than another?

137. Lifetime fecundity

138. Apparently not! Makes sense, IF populations are surviving, then each is doing enough or lifetime fecundity of females averages around 1! Then why all the differences?? One approach better?? Ideal clutch size, etc. Evolutionary factors

139. Evolution of reproductive strategies No one ideal litter/clutch size/reproductive strategy Each species faces its own suite of conditions for survival and adjusts approach Resource levels (where you are on food chain, how much is available, seasonal/annual abundance of food) have to be addressed Predation: On adults, on young

140. Summary Populations can grow exponentially Populations can decline exponentially Seem to do both over time, rarely stable Simple analogy is like a lake One inlet (reproduction), many outlets (mortality) More complex, especially mortality.

141. Summary Variety of sources Can occur at any age (many young and old) Reproduction: females most important Age specific fecundity Fecundity patterns differ depending on evolution of reproductive strategies Managing for the gains and control the loses.

142. Ok so that’s the additions and subtractions to a population. One thing to say they die and list the possible causes, but need more detail on those causes How important are they? In a management mode, can they be managed?