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# General Ecology BIOL 2335

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This 0 page Class Notes was uploaded by Kyler Ondricka on Monday November 2, 2015. The Class Notes belongs to BIOL 2335 at Georgia Institute of Technology - Main Campus taught by Marc Weissburg in Fall. Since its upload, it has received 32 views. For similar materials see /class/233988/biol-2335-georgia-institute-of-technology-main-campus in Biology at Georgia Institute of Technology - Main Campus.

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Date Created: 11/02/15

05 Population parameters and life tables 1 What is an individual What de nes a population How large is a population What factors contribute to population size The tree trunks depicted in this stand of Populus tremuloides quaking aspen most likely represent A a population of aspen trees B a genet comprised of many p ramets C a clonal modular organism like a brain coral D A and B E B and C Conyngmluo hm wwwmdnspectrnmcum n w How large is a population it For decades citizenscientists have counted all bird observations individuals of each species annually Within 1 24hour period in a defined area For each bird species counted this is an example of A total population censuses B samples of the absolute density C relative densities in an open population D relative densities in a closed population E None ofthese Tuned mnuse 1 SM 1 909 BBC clm les where a Reparted 139 Nat repnrted httpweb4audubonorgbirdcbcWWLTuftedTitmousehtml 6 Markrecath re mVCDChbQJNA Markrecapture activity Create a group around a bean bin Capture and mark 10 beans Allow the population to equilibrate Sample s beans and record r recaptured Repeat with the second value of s Calculate N for each value of s Census your bean population Send up a representative to enter r10 r30 and your total N Markrecapture assumptions What contributes to population size Survivorship curve for US males and females in 2003 standardized to a cohort of 1000 peeps No alive 1 000 800 600 400 200 100 60 30 0 20 l l 40 60 Age years Females it Given that mortality rate is number of deaths per age group the data show that the US population 21 Has high juvenile mortality b Reproduces until age 40 60 on average c Has a constant rate of mortality d Has a nonlinear mortality rate e Has different patterns for males and females No suwivors x Survivorship and mortality rate curves 1000 a 10 E S as mu 395 CB 0 06 l 10 a 04 H 1 E S 02 1 E p IUII JUKJ P 2 4 a IL 5 2 17 E Age Age Figure 13 A 10000 1 000 Number of individuals a o o o Stableage distributions Nnnnl 712 Eventually all three age classes and the po ulation as a whole increase at aboul the same rate in the rsi few years the numbers oi individuals in the different age ciasses vary considerably Time years 3 Yearly rate of increase A 18 7 z 132 in me rsl few years A uctuates cansidereb y 2 3 4 5 6 7 8 9 10 11 Time years No survivors x Survivorship and mortality rate curves 1000 Type 1 100 IU Type 2 1 Iype 3 01 P1 2 E 10 Age Figure 86 Death rate per capita d 08 We 1 Type 3 Type 2 Age A 10000 1 000 Number of individuals a o o o Stableage distributions Nnnnl 712 Eventually all three age classes and the po ulation as a whole increase at aboul the same rate in the rsi few years the numbers oi individuals in the different age ciasses vary considerably Time years 3 Yearly rate of increase A 18 7 z 132 in me rsl few years A uctuates cansidereb y 2 3 4 5 6 7 8 9 10 11 Time years Demography quantitative population biology If the survival rate of adult eagles decreased 2 per year would the population decline lfjuvenile salmon survival increased 05 in the first year how would the adult population change We need some basic information about how births deaths immigration and emigration are changing the population Life tables Summarize mortality rates and age specific survival Summarize agespecific fertility Determine if a population is growing or shrinking Is the population increasing or decreasing Groups of 3 Handin one sheet for each group 1000 500 200 100 50 OW PWNHN CNNPoopquot it Why does the life table focus on females only 2 Females but not males are required for population growth b Males migrate out of the population before reproduction c Males do not contribute to parental care of offspring d We assume there are enough males present to mate with the reproductively active females e C and D In what age class do most females reach maturity a X 1 b x 2 c X 3 d x 4 e C and D How can you use the net reproductive rate to determine if a population is growing or shrinking a Growing populations have R0 lt 0 b Growing populations have R0 0 c Growing populations have R0 gt 0 d A and B e B and C Net Reproductive Rate R0 On average the number of females born to each female in her lifetime R0 Population increases by each generation ie NRO per generation 23 it If the initial population size was 80 individuals how large should the population be after 11 generations a 811 b 88 c 228 d 968 6 Not enough information 25 Summary Close your notes On a page to hand in write Your name and student ID A synopsis of how life tables are created How they are useful What assumptions we make What you are still confused about 26 Nuts and Bolts Pass back group activity sheet and nal writing exercise Purpose of the final writing exercise Arrange to meet with your group beforeafter class to discuss what you did Wiki annoucements information MW 27 07 09 Population Growth amp Density Regulation Geometric and Exponential Growth models Limits to population growth Logistic growth model Population dynamics Stochasticity Extinction Probabilities 28 If the initial population contained 100 females and each female has on average 23 daughters how large will the population be after 15 generations 29 Geometric Population Growth Model 30 Geometric Population Growth Model Nt1 ANt NI A NO R0 population growth rate per generation or net reproductive rate A per capita finite rate of increase Nt population size at time generation t 31 Number of individuals Stable age distribution when the age structure does not change from one year to the next Figure 98 Cain et al 2008 32 Yearly rate of increase in Stable age distribution when the age structure does not change from one year to the next Figure 983 Cain et al 2008 33 Assumptions of Geometric Growth 34 Exponential growth dN EZFN and NZ jvoert where N population size r per capita rate of population growth or intrinsic rate of natural increase b instantaneous birth rate cl instantaneous death rate 35 Exponential Population Growth Model 36 Population size gt How do population rates affect population size klt1 k1 kgt1 rlt0 r0 rgt0 Hmamp gt Hme gt me How can we estimate a population s growth rate r or k Figure 910 Cain et al 2008 37 Egggjgtion doubling time Geometric Assumptions Again 1 nonoverlapping discrete generations timesteps 2 9 is a xed value 9 implies a SAD 3 no limits on population size 4 no stoohastioity 39 What can limit population growth Densityindependent factors 40 Density independent factors influence population size in thrips Thrips imaginis insect Fluctuations in population size are correlated with temperature and rainfall Davidson and Andrewartha 1948 700 Observed number Predicted number 600 43 i4 U1 0 O O O O O I I Number of thrips per rose N V O O I O O 1932 1933 1934 1935 1936 1937 1938 1939 1940 1941 1942 1943 1945 1946 Year 0 Figure 912 Cain et al 2008 What can limit population growth Densitydependent factors 42 Density dependent effects on birth rate Song sparrows Melospiza melodia on Mandarte Island A 50 8239 85 g 40 8039 Fed 81 O 3 760 78 a 770 39 Du an 30 83 g 84 5 2 0 S 39 g 79 a 75 86 39 g 10 0 E 85 Control I I l l l 0 10 20 3O 40 50 6O 70 80 Number of breeding females 43 ECOLOGY Figure 914 Part 1 07 09 Population Growth amp Density Regulation Geometric and Exponential Growth models Limits to population growth Logistic growth model Population dynamics Stochasticity Extinction Probabilities 44 Population size gt How do population rates affect population size klt1 k1 kgt1 rlt0 r0 rgt0 Hmamp gt Hme gt me How can we estimate a population s growth rate r or k Figure 910 Cain et al 2008 45 How long will it take a Agepmoa on to double in size 46 Geometric Assumptions Again 1 nonoverlapping discrete generations timesteps 2 9 is a xed value 9 implies a SAD 3 no limits on population size 4 no stoohastioity 47 What can limit population growth Densityindependent factors 48 Density independent factors influence population size in thnps Thrips imaginis insect Fluctuations in population size are correlated with temperature and rainfall Davidson and Andrewartha 1948 700 Observed number Predicted number 600 43 hi U1 0 O O O O O I I Number of thrips per rose N V O O I O O 1932 1933 1934 1935 1936 1937 1938 1939 1940 1941 1942 1943 1945 1946 Year 0 Figure 912 Cain et al 2008 What can limit population growth Densitydependent factors 50 Density dependent effects on birth rate Song sparrows Melospiza melodia on Mandarte Island A 50 82 m 85 7g 40 8039 Fed 810 0 03 76 77 o 78 t so 3390 quot 830 g 84 gt g 20 79 C it 75 o 8639 o g 10 0 E 85 Control I I I I 0 10 20 30 4O 50 60 70 80 Number of breeding females 5 1 ECOLOGY Figure 914 Part 1 Density dependent effects on death rates Flour beetle Triboium confusum C 10 0 CD 5 5 06 39 B 0 Q 20 60 100 140 E gg density number tube 52 ECOLOGY Figure 914 Part 3 cm W Density dependence vs density independence 20 10 Population growth rate 7 0 Low High Population density ECOLOGY Figure 913 53 Density dependence vs density independence Both can be important Thrips again evidence for density independence shown earlier and density dependence t U1 1 o 0 U1 Number of thrips per rose in November Loglo 00 05 10 15 20 25 Number of thrips per rose in October Logw 54 ECOLOGY Figure 915 After Smith 1961 a Population regulation Population regulation the tendency of a population to increase when densities are low and decrease when numbers are high 55 Logistic growth Examples growth of willows Salix cinerea in Australia after rabbit removal 550 500 450 400 350 300 250 Number of trees 200 150 50 0 1 1 1 1 1 1 1 1 1 1 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 56 Year ECOLOGY Figure 917 111111111111 155 Logistic equation The logistic equation incorporates limits to population growth and shows how a population may stabilize at a maximum size the carrying capacity d N2rN 1 5 dt K 57 Logistic growth vs exponential growth Exponential growth 62 12 TN dN M Loglstlc growth dt rN 1 K Time t gt E 9 1 8 o 2009 stnauer Msaclates Inc PredatorPrey Dynamics 60 Interactions among species O PredatorPrey Activity Predators etc Predators kill and eat other organisms their prey Predation can have large effects Predation and herbivory can affect prey abundance prey distribution population dynamics community structure prey evolution 63 Predation and evolution Prey are under strong selection to avoid being eaten Predators and herbivores are under selection to overcome these defenses 64 Ways to avoid being eaten Unpalatable Palatable butterflies mimics from Danaidae genus Papiio How do predatorprey cycles happen Verbal model 66 How do predatorprey cycles happen Mathematical model N preyindividuals LotkaVolterra predatorprey model P1 4 preo39ator individua39s r prey population growth rate a predation capture efficiency f feeding efficiency d predator death rate 67 Assumptions of LotkaVolterra predator prey model 68 69 Solve for zero net growth isocHnes 7O Solve for zero net growth isocHnes 71 Predator and Prey Isoclines Predator abundance P Prey abundance N 72 Predator and Prey Isoclines Predator abundance P Prey abundance N 73 Predator and Prey Isoclines Predator abundance P Prey abundance N Predator and Prey Isoclines Predator abundance P Prey abundance gt Do natural populations cycle Which populations should cvcle Species with density dependence singlegeneration N cycles P Species with delayedfeedback cycles Consumerresource cycles A specialized consumer tight coupling with resource Predators P gt Prey N 75 How common are population cycles Global Population Dynamics Database 694 populations time series gt25 years d l E D nds Lynx population housa l l l v o m a w TAXON nloop Periodic m Birds 139 13 Mammals 328 33 Fish 129 43 Insects 79 16 Crustaceans 12 50 Gastropods 3 33 Bivalves 3 33 OVERALL 694 29 76 A grouse Kendall BE et al 1998 How common are population cycles Note Size of circle is proportional to the number of populations it represents 10 n a mammals o 08 Fraction that cycle 04 02 00 000 GD 0 o o u u n o 0 4O 50 60 70 MexicanUS borderLATnUDE arctic circle Kendall BE et al 1998 In 1934 Gause used Early laboratory experiments e No of individuals protozoans Paramecium and Didinium to test the models In 1958 Carl Huffaker used mites to test the models No oi individuals g 2 l 395 i g l g D P caudalum D nasulum l 2 3 4 5 Time days Huffaker thought Gause s protozoa were too simplistic Phytophagous planteating mite that infests oranges Predatory mite Habitat that increased in spatial complexity 1 orange 4O oranges 4 real oranges 36 fake oranges in different spatial arrangements Barriers to predatory mite movement 79 Predator miteeating mite Typhfodromus Prey V phytophagous mite E Graham ych us J a Population BizB of prey E sexmaculafusl r4 K3 3 10130 BOD 400 M aw Complex orange universe 252 orangegenerated cycles Barriers to predators Prey hop skip and jump to new habitat keep one step or one orange ahead of predators Predators efficiently decimate each colpny they find WI M l W I I I39 39I a 1 it 6 4 U 391 l39 ll l l W pqay 39t t f d Pi quotg I l 539 39 u 2r a I 39 a 6 u a in l o pquot R kiwi 11quot f i n d predator o i 1 u quotd u P a II IIQQIODIC I l l I I I I I 5 1 39339 1 5 EU a 4U 45 EU J EU Time weeks U I Population size of predator If T occidonfah39sl Huffaker 1963 Laboratory experiments required complexity to maintain both species Gause s protozoans collapsed down to O or 1 species unless he included immigrants for both species Huffaker s mites cycled with spatial complexity also called spatial heterogeneity or environmental patchiness World consists of various patches that are either good or bad for the predator or the Prey 82 Predation 3 Prey zero isocline is not realistic A Assumption 3 Growth of prey population 3 is limited only by predation 8 93 D Prey i 9 co 390 93 D V CD A Prey Including Prey Carrying Capacity Predators P 85 Prey zero isocline is not realistic Predators Predators 00 CD I K Prey Prey V LotkaVolterra assumption Individual predators can consume an infinite number of Prey More realistic V 87 Predator functional responses Holling 1959 Type response assumed in LV model a39 P N predation rate AK Type number prey eaten per predator a39 P N P Prey density N 88 Feeding rate is limited by handling time number prey eaten per predator V Prey density As prey density increases 89 Feeding rate depends on prey density Low prey density number prey eaten per High prey density predator Prey density 90 91 Humpshaped prey isocline Rosenzweig amp MacArthur 1963 Allee effect higher density increases reproduction gt group hunting predator avoidance Prey self limitation Predators V Prey 92 Effect on predatorprey dynamics Predators Effect of an inefficient predator 93 Predators 71 table equilibrium Effect of an efficient predator Efficient predator Prey predator Predators 94 95 Predators Paradox of enrichment Rosenzweig 1971 Prey predator 7 gt K Prey enrichment Modifying the predator isocline Predators V Prey 96 Predators 97 Shapes of predator zero isocHnes Lotka rrraa Limitation other 1 than food 1 1 1 I 1 l l 1 1 1 1 1 t 1 i 1 1 Predator is t More predators nota specialist T Prey require more pre 98 Paradox of enrichment revisited Limit cycle simple LV Prey 39 predator Predators Prey 99 More realistic predator isoclines Predators More realistic predator isocline stabilizes predator prey dynamics Limit cycle simple LV Prey 39 predator

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