HON BIO SCI II
HON BIO SCI II BSC 2011
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This 44 page Class Notes was uploaded by Kari Harber Jr. on Thursday September 17, 2015. The Class Notes belongs to BSC 2011 at Florida State University taught by Staff in Fall. Since its upload, it has received 18 views. For similar materials see /class/205431/bsc-2011-florida-state-university in Biological Sciences at Florida State University.
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Date Created: 09/17/15
BSC 201103 Outline lecture 31 Spring 2006 Density dependent growth What causes density dependence Density affects birth Density affects death Density affects both Per Per Per capita capita capita rate rate rate N density N density N density when birthdeath population won t change will be at K Factors that cause birth death to change with density Limited food Limited space nest or settlement sites shelters Limitation by predators or disease Examples Figs 5216 and 5217 Note to have density dependence density must affect percapita rates not just number Aside Percapita information more useful than raw numbers for understanding things in general Example The Logistic model Deriving logistic growth model limited growth Assume some limit to growth due to limited resources for example food K carrying capacity Start with exponential growth unlimited dNdt rN Add a term that will decrease r as N gets bigger 1 NK Logistic model limited growth dNdt rmaxN 1 NK r is now rmax the highest rate of increase possible when N is very small Predictions When N lt K When N K When N gt K Graphing logistic growth growth with limits N0equot 1N0equot 1K Logistic growth results in an Sshaped curve when r is positive Rearrange to get NT on one side Nt Effect of K Effect of r Important assumption of logistic Summary of two models of population growth 1 Exponential model 2 Logistic model Patterns of population dynamics in nature All populations have some yeartoyear variation in size Density independent and dependent factors both affect populations Density dependent factors Examples discussed earlier Keep population centered around K Regulate populations Regulation Density independent factors Examples Can keep population far from K Can t regulate populations All populations have some K BSC 201103 Outline lecture 11 Meiosis Spring 2006 Overview of Meiosis Meiosis l two cell divisions one round of DNA replication A cells produced are not identical A Meiosis is not a random division of the chromosomes 1st division reduction division second just like mitosis 0 Steps of Meiosis 1 Meiosis1 Prophase 1 in meiosis prophase and prometaphase are lumped synapsis tetrads homologous chromosomes align Metaphase 1 Tetrads move to metaphase plate kinetochore fibers attach to homologous chromosomes Which pole each chromosome attaches to is random Anaphase 1 Homologous pairs pulled to each pole no division of centromeres Telophase1 cytokinesis Products of meiosis 1 are haploid Products of meiosis 1 differ genetically chromosomes are already replicated 2 Meiosis 2 just like mitotic division starting with the haploid nucleus from Meiosis 1 a Prophase 2 chromosomes recondense b Metaphase 2 paired chromatids on equator c Anaphase 2 centromeres divide sister chromatids separate d Telophase 2 4 haploid nuclei form 0 Review of differences between meiosis and mitosis Genetic variation Why bother with sex Sex produces variation among offspring in three ways 0 Independent assortment 0 Crossing over Chiasma recombinant parental 1 Random pairing of gametes at fertilization BSC 201103 Outline lecture 28 Behavior Spring 2006 Behavioral biologyecology Behavior basics StimulusResponse Example Sow bugs Behaviors can evolve Two kinds of questions asked by behavioral biologists How questions about mechanistic basis of behavior Identify stimuli that cause behaviors Example Document physiologicalneurological basis ofthe behavior Example Why questions about the evolution of behavior Is a behavior an adaptation does it increase tness Example Genetic basis of behavior Not a single gene for most behaviors behavior a complex trait Example 1 Moths See also sticklebacks g 513 in book Example 2 Lovebird nest building g 511 Learning affects behavior Example Portia spiders Example Swamp Sparrow Experiment raise birds with different songs see what they sing as adults Treatment song played Result bird s song as adult Conclusion No song Very basic swamp sparrow song not complete Swamp sparrow song Normal swamp sparrow song Song sparrow song Messed up swamp sparrow song Learning results in higher tness There is a genetic component to what is learned Flexibility in behavior What conditions should make species not be flexible not use learning Behaviors needed right away Mistakes very costly What conditions should make species flexible Environment is variable OUTLINE 20 I The Concept of Evolution up to Darwin s Time A Greek Philosophy B Christian Theology C The Enlightenment II Evolution Before Darwin A Lamarck B State of knowledge at Darwin s time 111 Darwin and the theory of Evolution By Natural Selection A Voyage of the Beagle B Formulation of the theory IV The Theory A Essential elements B Contrast with views of the time V Darwin s Evidence A Arti cial selection B The fossil record C Comparative anatomy D Embryology E Biogeography Nothing in biology makes sense except in the light of evolution T Dozhansky Greek Philosophy Essentialism James Hutton 1726 1797 Gradualism Natural laws are invariant Change results from the accumulation of slow continuous processes Charles Lyell 1797 1875 Uniformitarianism the rate of geological activity on Earth is constant Similarity among the limb bones of organisms that use them for different purposes Human Cat Whale Bat Dapy ghiu Pearson Education Ina publishing aa Benjamin Cummings J ean Baptiste de Lamarck 1744 1829 time and favorable conditions are the two principal means which nature has employed in giving existence to all her productions We know that for her time has no limit and that consequently she always has it at her disposal Charles Darwin 18091882 Voyage of the HMS Beagle cquot l sf1 I v 39 l 1 Lll If my Cape of f 39 f Gland IIfn 39 e t Tasmania if Cape Hum Maw Tlarra dell Fmga Zealand Capy ghlm Paarsnn Edueallen Inn publishing as Benjamin Bummings Finches 0f the Galapagos Islands Cactus Small ground tree Medlum WDDEIPECKET Medium finch finch tree flnch flnch ground a c c finch 55 G scandens c pawulus C pauper C pailidus Large G fortis L Small Lar ccactus life ctarlan 53999 Green Grail round ground gro nd finch fingh 3993 anal ave warbler warble finch quot1 finch finch 6 r G liiginosa G confrosfn39s 43w magnrrosms Sharpbaade ground finch G df lcms cactu Seed eaters flower I cattle5 Ground nches Bonus GE Spiza I b The Galapagos finches Copyright Pearson Educaiion Ina pubishing as Benjamin ummings ff crassi C rosfris Emil Insect eaters Genus Gamarhynchus Cerfhfdea Certhidea r3 psiffacula hefiobaies ofivacea fusca Warbler nches Tran finches Bonus Ce hfdca Common ancestor from South American mainland Thomas Malthus 1766 1834 Populations can increase faster than their resources Alfred R Wallace 1823 1913 T HE URIGIN 0F SPECIES 31 mm DP NATURAL smr39rm Di TIER I39llFESlZEWA JTIDE 111quot FAV39UILEHEH ACES IN THE STRUGGLE P03 LIFE Ha CHARLES DARWEN MAquot FEW II III WI39SL Inklihflili lk LIEEJJX FIE TIRED 1 Of JOL ESAL M lim lhl i mum IL i I 40111 QTAI JIC Imam IIIIE wuluum39 L 0 N 130 2 1 JOEE MURRAY A l h h ELE STREET 135173 11 riglirrf rwn nha J v M11111 More offspring are born than can survive to reproduce Parent Offspring Parent Individuals Within a species vary Traits are heritable Parent Offspring O gt 0 Parent Offspring O Individuals with some traits reproduce more than others Parent Offspring O gt 0 Parent Offspring Traits that enhance reproduction become more common each generation parents offspring parents offspring generation generation generation eneration g 1 1 2 2 Artificial selection has produced different true breeding varieties of fancy pigeons from a single ancestral form Jacobih Jawbm Norwidn mam a r 6 3 kirk Paulcv Fossils preserved evidence of previously living things Fig 2217 i fossil Whale with hind legs my i i 7 r I Homology similarity caused by common ancestry Human Cat Whale Bat copyright 9 Pearson Educarlon Inc publishan as Benjamin Cummings Evidence for evolution from comparative embryology Fish Salamander Tortoise Rabbit Human Early embryos of diverse groups share many features As development proceeds embryonic forms diverge and become more similar to adults of their own species von Baer s law BSC 201103 Outline lecture 30 Spring 2006 Survivorship curves g 523 Type I Examples Type II Examples Type III Examples Percent surviving Relative age Life table data can be used to calculate population growth but techniques are complex Now simpler ways to think about population dynamics Population dynamics Examples Why study population dynamics How do we study population dynamics Census data Mathematical or computer models Example Make a model of how population size changes with time What affects the size of a population A very simple model of population dynamics would then be Parameters Basic strategy for understanding a model 0 Figure it out in words 0 Figure out how each parameter affects result by asking what is result ifthis parameter is very large and if it is very small 0 Graph it can use second strategy to gure out graph Know assumptions Models of population growth assume no immigration or emigration Exponential Model Deriving exponential growth model unlimited growth Start with earlier model ANAt BD assuming no or E Then switch from B number of births in population to b birth rate of the population B bN Similarly D dN Now ANAt bN dN or ANAt bdN Simplify by making new variable r bd r the intrinsic rate of increase book also calls r max Exponential growth model dNdt rN dNdt population growth rate dNdtN r percapita population increase Important note don t confuse population growth rate with the per capita rate Predictions effects of parameter r When r gt 0 When r 0 When rlt 0 BSC 201103 Outline lecture 29 Spring 2006 Ecology Three kinds of interactions of organisms with their environment Organismal ecology Two topics of study in organismal ecology there are others How traits affect distribution of organisms Example Carnivorous plants Example Mimulus plants How traits evolve through natural selection to t environment Life history Life history includes Variation in life history patterns among organisms Sun ower reproduction thickness salmon offs rin Songbird p g Loggerhead Human Oak Birth 1 3 10 30 100 300 1000 Age years log scale Why not start reproducing right away and continue forever Tradeoffs Example 1 Tradeoff between survival and reproduction see g 526 Example 2 Tradeoff between offspring number and offspring size Example Parus caeruleus 94 012 92 o 01 o g g 0 08 O m 88 g Fu 0 00 E 86 g z t 0 g 39 E 004 E 84 39S 2 5 o lt 82 390 002 O 8 0 0 5 10 15 20 6 8 10 12 Clutch size eggs Nestling weightg Tradeoffs can constrain evolution Population ecology Population Properties of Populations distribution density dispersion clumped aggregated Examples uniform Examples random Example sex ratio age structure Example human age structures fig 5222 How does population size change through time Demography Life table Cohort Basic data in life table other data are sometimes included Age or age group Xage Number of individuals of age X Nx Fecundity bx Survival Ix Example hypothetical organism Total lifetime reproduction 2lxbx fecundity and survival both important for population growth both change with age OUTLINE 8 VIII THE CELL CYCLE A The Prokaryotic Cell Cycle B The Eukaryotic Cell Cycle 1 Interphase a G1 phase b S phase c G2 phase 2 Mitosis Cytokinesis C Control of the Cell Cycle 1 Two early hypotheses 2 Experimental evidence 3 Cytoplasmic signal molecules a Cyclins b Cdk 4 Example of control of cell cycle Fig 1210 miniquot mm The Prokaryotic Cell Cycle Emuquot n mm on mm M nrlgln mnvumv opy of m on n Imam by Move Inward Ina Olhnrunu of m cm Origin Orlnm B R Imauon cwunua Om cnPy ol ma orlnln Is nnw amen m onquot Dell 9 Repnmlon umshes the Plasma membrane 9quot mm quota quot9 cell wall ls deposited o Ywu Gauguin ullls mun mynumc Pearson gammy m vvubumlnnuEs lzmmCummmgs The Eukaryotic Cell Cycle F1g 124 8 DNA synthesis Owyllvchemsnn Eauullon m Dubllshlnuasae lzmm Cummmgs Fig 1214 Control of the Eukaryotic Cell Cycle Relalive concentration rime 1a Fluctunuan ol MFF acuvny and cycnn during thl cell cycl cummaws 0W 5 15K I 3Z chackpoinl m Mnlecular mechanisms cwwma Peamon Euumnon w Dubllshlnuz EE lammcummmgs Fig 1212 Results of a cell fusion experiment mynymanusm 2mm m puhhwwas m39ammmmmms
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