Class Note for ECOL 406R with Professor Bonine at UA 3
Class Note for ECOL 406R with Professor Bonine at UA 3
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Date Created: 02/06/15
Conservation Lecture i924 0e12qu CHE Genetics cw Pupulatiuns Gene Cunseryatiun Eiulugy ECOL AUERSEIER Univeisdy eiAnzena Fall 2 ms Kevin Benine Kathy ceisi PVA etc Lab this Week 7arn 27729 7pm October ORPl Pinacate CEDO 3 fund see Website rer iae readings Global Climate Change Lecture Series All lectures Will take piaee at M Centennial Hall me Mann45 mm mm mmw an mm cuatxxllzm h mund Mu emhee no 39cos anzona edu xuixumum cuma e shun E14 m M he Domitian 9n mammmeme hemmed eme E14 mm x m e mengypsummludzvh thLH xmr eme E14 my 4mm rmcm gamma heme 123 332371 dunnmmgaemmm heme eme E14 mutant Mun mm x humanw heme must ash nlwhwhru Hem n numcmpwmnp ndhaunmm 2 Applications of Genetics to Conservation Biology 7M ulecularTaxunumy rPupulatiuns Gene Fluvv aniegeegraenv Relatedness Paternity lndividual lD ani UA Housekeeping 24 OctuberZDDB ueeerning Readings tedav TeXtCn a and 7 F39VA Puma conesor Tners IE on Guy NePnersen vvee furclirnate enange reading Tues 3i on Ed Mull lung vvee reading Tners DZ Nev Exam Tvvu Tues D7 Nev Den Falk vvee reading Tnurs DB Nev Cunservatiun Practices cn lEI Denlan EA ZEIEIS snen eiai presentatiuns 24 0d ceii and Ruben ma Nev Jun and Laura M Nev Dan and Lane 28 Nev Arnanda and Fred 2 Cori and Robert will speak for 10 minutes on xx Molecular Taxonomy Molecules versus Morphology Cryptic species sibling species Morphological variation without genetic variation Relatedness Kinship Paternity and Individual ID Application ofmolecular genetic techniques using hypervan39able repetitive DNA ie microsatellites minisatellites to questions of kinship paternity or individual ID NonInvasive Sampling Allows sampling without disturbance to individual Rare or hard to capture species Examples hair scat feathers salivacheek swab regurgitated pellets dried blood biopsy dart museum tissues 32 Puma subspecies as of the early 1900s Populations Gene Flow Phylogeography Compare genetic traits among populations Resolve substructure among populations nfer movement patterns among individuals nfer historical events for species 8 Subspecies Taxonomy Phylogeography Gene Flow Puma cougar mountain lion Obj ectives Does current population differentiation re ect 7 Trrnnrnrai descnpunns7 7 Physical or ecnlngical barners7 7 isolation by distance7 Are current levels of genetic variation the same within each population Does popu1ation structure and genetic variation ret1ect 7 Hrstnnernrgatrnnsv 7 Histnnc dispersals7 r HlStnnEbnt EnEEks7 Modern and Molecular Methods Used museum puma samples collected total of 315 Mitochondrial gene sequencing r ISSrRNA r NADHS r A39I39PaseS Nuclear microsatellite length determination r 10 domestic eat mierosatellite loci Mitochondrial DNA Haplotypes in a geographical cline Neutral Markers often studied Relevance to natural selection and adaptation filial i Ultimately source of a variation is mutation mutation rate 10 10395 is l llll39lllllgilll l Microsatellite Alleles at FCA008 Ancestral haplotypes 2 historical nadiaiions NA is most recently founded population Mlnlmnm Evanon thunnozoemmg Tm w mmmmmmam Mammal Pmmnm m an mm mm rGeugraphlc clustaing ufindividuals Harmannu esix gruups identi ed 2 distancemethuds agree aluminum e1 remain a uwaum t v t t u t FISIFITIFST New Me e scamuznnn Summary 5 groups identi ed using microsatellites mtDNA haplotypes overlayed onto map Supports 5 groups Location on ancestral haplotypes We We a Major restrictions quotmm to gene ow quotml Amazon River can Rio Parana m Rio Negro Andes7 Mlnlmum Eynllmen N hhel 4mnlnn Ymu m mumnun m userme Hmnlm nl gated mum subspecies assuciate mm same a guups Statistical suppun 39umbuutstxap values ez distance methods agree Wright s Fst Estimates and Slntkin s lv grntion Estimates m 013 mus o9sa mm 031 0335 3 nm mm 0240 mass tht near 0 little divergence niizs n126 niaa Fossil Record versus Molecular Divergence Estimates Oldest fossils in North and South America date to 0203 Mya From mtDNA mutation rate of 115My divergence for extant puma lineages is 390000 years ago From mutation rate of5 x 10399yr for microsatellite anking regions pumas are less than 230000 years old Historical Inferences Extant pumas originated in Brazillian Highlands ancestral haplotypes Fossil record suggests dispersal to NA soon after the common origin in Brazil 2 historical radiation events occurred 2 Major historical radiation One locally distributed one broad ranging Fin Rldlillunl Puma Conclusions Pumas originated in Brazil approximately 300000 years ago possible extirpation and recolonization in North America Pleistocene age Molecular data does not support 32 subdivisions instead 6 groups Pumas are fairly panmictic within 6 groups Ancestor to puma crosses landbridge 23 Mya Puma origin in Brazilian Highlands 300000 ya Puma Bottlenecks Subspecieslevel 7 North America low overall genetic variation Populationlevel 7 Florida monomorphic at 810 microsatellite loci 7 Olympic Peninsula and Vancouver Island monomorphie at 510 mierosatellite loci Conservation Implications Maintain habitat connectivity within 5 large groups Management should consider effects ofbottlenecked populations Eastem cougar Florida panther and Yuma puma management take into account revised subspecies Population What is population viability Dynamics analysis PVA Thanks to Margaret Evans 2003 Bmam We snmuznnn populations are dynamic not static populations are dynamic not static WhalesintheAntarcnc Lemmings s a VFm whales r 2 t 1 e l r t a e a 39 y e SEtwhiles i i i i i i i 3 H32 19339 mi vsv s 93 ms ms my tea was the met me W2 5 P van E V M cause at Wells change in mutilation not 9 m new mm eempieteivuneeisteee Cvcle length avevage 3 a V9315 Mass mlgvalinn in vespnnse te high densilv Wm necveasmg 33 3 tune sumin mmetimes swmmmg involved M thi aff t 111 t39 39 Population sizes change over time any gs ec pep a 10m SIZE competition population when Why structure m7spems What causes change in population size 01m inmactjons What regulates population size Wedahm wame chancc eventsg POPIllatlorl WNW m damagaphm size If we can answer these questions we might be W able to make changes that increase populations of declining endangered species habitat attributes enqunrfental Hum wallth succession or vmauon cm gixman ma sesame teams 35 swam disturbance at l Exponential growth densityindependent deterministic 2w alllhmellc In a closed population no immigration or emigration population growth is a function of birth and death rates papulalmn sue diabew 7 13 n n 3 ngenzckedphzasmt 37 memeaemsm 2 Logistic growth densitydependent deterministic m 7 W intxaspeci c competition d t Y T stabilizes population size nmiees gs mm mm mamas gem mmimnaammmmm see E mu H m i m eammtm a Allee effect HOW l n a mi in animals rguup defense against predaturs rguup attaek efpiey emates drf culttu nd emncal number te stimulate breeding behavlur in plants rpullmatur limitatien rselfrmcump abbility einbieeaing depresslun exponential growth an unrealistic model Humans un planet Earth Altem ative 1y The population growth rate may increase with population size positive densitydependence Allee effect minimum viable population size Allee effect H 0W gmup defense against predaturs mum mm mm t The two categories ofmodels we have considered thus far assurne that all individuals in apopulation have the same hinh and death rates nu genetae develuprnental urphyslulugcal differenees amung individuals under sums eireurnstanees this might eause us tn inaeeurately prediet pustulaan size mu 5 suruivnl data In redeeeekadad wnnanasxeis in di uml reproductive sugu min warms 1550 r t m and of s thalnumhav M havemnn Jugs aimquotm aria Alive iwvms Melvi nuing fill 14 ll u strum mile m 5U 52 weer hthmst 27 M int Merlin mils w 2m w n 7 rlutlm 9 u iit U a Life Tables 3 Densityindependent deterministic structured population growth What else ean structured population models tell us39 Sens39 39 39tx The senslhmty nuts eaeh matrix element desenhes huw rnueh 7twlll he affected by achange in that transian prubahlllty Would ithe better to focus eonservation efforts on improving the survival ofhatchlings orlarge juveniles or adults Larnhda population growth rate 7 3 Structured population models densityindependent deterministic This is the type ofmodel most otten used in population viability analysis What is meant by structure Apupulauun is unstructuredlfall individuals have the same rates ufsurvlval and femllty Apupulauun is Strucmredlfdlfferences arnungindividualsin age develuprnental mge ur size eause therntu have different survival ur femllty rates shun ummtttatttntt Whenlambda is greater than 1 the population increases in size When lambda is less than 1 the population decreases in size 3 Densityindependent deterministic structured population growth What else can structured population models tell us Elasticity Elasticities quantify the proportional change e g 1 in the asymptotic growth rate that can be expected given a particular change 1 in each life history transition 49 Population Viability Analysis Amman mm mm minim tmmymw swmm Gmum Metre amp Carroll 2on5 Panther Article on PVAs over time VORTEX data popuation size source and sink inbreeding problems captive breeding introgression time scale HABlTAT LOSS Van Dyke p 178 Four Horsemen of the Extinction Apocalypsequot 1 Genetic Stochasticity 2 Environmental Stochasticity 3 Demographic Stochasticity 4 Natural Catastrophes Ecmh un quotI Vol l ilion inlwilil ucwmenh fur llu lTiuridn Paulim lulliprI39spcrlhv ppmuLl mix Iwm i w39 l v r quotmHlnuml ill 39I lvw I39 will 17va V l m m Population Viability Analysis Steven R Beissmger and Dale R McCullough eds Umv quhtczgu Press Chicago xvi 577 pps will l mum him my aunts i rpm win it Linn lHgtv mu inn ism Hu imprint v Hr39l39l Last thoughts on PVA PVA requires lots of data which takes time work and money whereas managers want answers predictions about extinction now Few specieswill get thorough PVA When should PVA be used and what type of PVA how complex Predictions from PVA can only be as good as the data that go into the analysis We can only have degrees ofcon dence in the predictions from PVA Populations should not be managed to their minimum viable population size One ofthe greatest strengths ofPVA is the ability to play what itquot games with the model That is what if management were to increase patch sizes or connectivity What if adult survival were improved Ndata time scale END 10
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