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生態(tài)多樣性及其測(cè)度參考書:E.C.Pielou1975,EcologicalDiversity文獻(xiàn)AnneE.magurran1988EcologicalDiversityanditsmeasurement李典謨1987,生態(tài)的多樣性度量生態(tài)學(xué)雜志,6(4):49-52馬克平第十章生物群落多樣性的測(cè)度方法中國(guó)科學(xué)院生物多樣性委員會(huì)主編“生物多樣性研究的原理與方法”1994Whydiversity?Therearethreereasonswhyecologistsareinterestedinecologicaldiversityanditsmeasurement.First,despitechangingfashionsandpreoccupations,diversityremainedacentralthemeinecology.Thewelldocumentedpatternsofspatialandtemporalvariationindiversitywhichintriguedtheearlyinvestigatorsofthenaturalworldcontinuetostimulatethemindsofecologiststoday.Second,measuresofdiversityarefrequentlyseenasindicatorsofthewellbeingofecologicalsystems.Thirdly,considerabledebatesurroundsthemeasurementofdiversity.Diversitymayappeartobeastraightforwardconceptwhichcanbequicklyandpainlesslymeasured.Thereishoweverasimpleexplanationwhydiversityissohardtodefine.Thatisbecausediversityconsistsofnotonebuttwocomponents.Thesearefirstthevarietyandsecondlytherelativeabundanceofspecies.一生態(tài)多樣性指數(shù)的概念(1)種數(shù)多少(2)各種之間相對(duì)豐富度首先是由Fisher提出,Williams引用(Fisheretal1943)所以,分布越均勻,V越小,p也越小,ln(1+p)越小,越大
大量的研究表明(magurran,1988):α是一個(gè)很好的多樣性指數(shù),即使對(duì)數(shù)級(jí)數(shù)模型不是最好的理論分布的時(shí)候也是如此。Magurran,A.E.1988.EcologicalDiversityandItsMeasurement.NewJersey:PrincetonUniversityPress2.多樣性的信息度量A1p1A2P2……AjPj……AsPs(3)A分類B分類A1p1…AjPj…AsPsB1q1BkqkBtqtA1B1π11AjAjBkπjkAsBtπskNoteonbiologicaldiversity,evennessandhomogeneitymeasuresT.O.Kvalsethetal1991OIKOS62:(1)一個(gè)可以接受的多樣性的測(cè)度至少應(yīng)具備:(1)合理地簡(jiǎn)單,便于計(jì)算和理解(2)從生物學(xué)、統(tǒng)計(jì)學(xué)或者數(shù)學(xué)上有適當(dāng)?shù)幕A(chǔ)(3)包含種數(shù)和均勻性兩個(gè)概念(4)有一個(gè)直觀合理的解釋(5)具有所希望的特性Kemoton(1979)notedthatdifferentdiversityindicesoftenproducedinconsistentorderingsofcommunities.Hedidhoweverconcludethatthisinconsistencyisrarerinfielddatathananalysesusingartificialandunrealisticdatasuggest.Thediscussionabovesupportsthisfindingprovidedthatindicesfromwithineitherthespeciesrichnessgrouporthedominance/evennessgrouparechosen.DiscriminantabilitySensitivitytosamplesizeRichnessorevennessdominanceCalculationWidelysued?α(logseries)
GoodlowrichnesssimpleYesλ(lognormal)GoodmoderaterichnesscomplexnoQ(statistic)GoodlowrichnesscomplexnoS(speciesrichness)GoodHighrichnesssimpleYesMargalefindexGoodHighrichnesssimplenoShannonindexmoderatemoderaterichnessintermediateYesBrillouinindexmoderatemoderaterichnesscomplexnoMcIntoshUindexGoodmoderaterichnessintermediatenoSimpsonindexmoderatelowdominanceintermediateYesBerger-ParkerindexpoorlowdominancesimplenoShannonevennesspoormoderateevennesssimplenoBrillouinevennesspoormoderateevennesscomplexnoMcIntoshDindexpoormoderatedominancesimplenoTable:AsummaryoftheperformanceandcharacteristicsofarangeofdiversitystatisticsSotheecologistfindingthatthediversity(calculatedusingtheShannonindex)ofthebirdfaunaintwowoodlandsisH’=2.31andH’=1.95isleftwonderingwhetherthewoodlandsarereallyquitesimilarintermsofdiversityorareinfactverydifferent.AnalysisofvarianceJack-knifingRepeatedestimatesofdiversityareusuallynormallydistributed.Indexcalculatedforlight-trapcatchesTheanalysisofvariancecanbeusedtotestforsignificantdifferencesinthediversityofsites.ForinstanceGaudreault
etal.(1986)usedthistechniquetoshowthattherewerenosignificantdifferencesbetweenmonthsinthediversityofthedietsofsticklebacks(Pungitius
pungitius).(SokalandRohlf,1981)Jack-knifinganindexofdiversityThebeautyofthemethodisthatitmakesnoassumptionsabouttheunderlyingdistribution,Instead,aseriesofjack-knifeestimatesandpseudo-valuesareproduced.Thesepseudovaluesarenormallydistributedandtheirmeanformsthebestestimateofthestatistic.Confidencelimitscanalsobeattachedtotheestimate.JACKKNIFETECHNIQUESTheadventofmoderncomputershasopenedupaseriesofnewstatisticaltechniquesthatareofgreatimportancetoecologistsbecausetheyreleaseusfromtworestrictiveassumptionsofparametricstatistics:(1)thenormalfrequencydistribution,and(2)musthavegoodtheoreticalproperties,sothatconfidencelimitscanbederivedmathematically.ThejackknifetechniquewasfirstsuggestedbyTukey(1958).Wewouldliketoknowhowmuchbetterourestimatewouldbeifwehadonemoresample,butwedonothaveanymoresamples,soweasktheconversequestion:Howmuchworsewouldwebeifwehadonelesssample?Beginningwithasetofnmeasurements,thejackknifeisdoneasfollows:Step1.
Recombinetheoriginaldata:Wedothisbyomittingoneofthenreplicatesfromthejackknifesample.Step2.
Calculatepseudovaluesoftheparameterofinterestforeachrecombiningofthedata:
Step3.
Estimatethemeanandstandarderroroftheparameterofinterestfromtheresultingpseudovalues.ThedataconsistofthenumberoffishcollectedinfivesectionsoftheUpperRegionofBlackCreek(24Species),Mississippi(Rossetal.,1987).SpeciesSection∑12345Esox
americanus14130010Ericymba
buccata1533562983Notropis
volucellus2613877431111---------------11360---4504---2074----------------UsingSimpson’sindextoestimatethediversityofallstationstogether:
Ds=4.96計(jì)算VPi=nV-[(n-1)VJj]其中VJj:jack-knifeestimate把第j樣去除后算得的多樣性指數(shù);
n:樣本數(shù).Excludedsection1VJiVPi14.895.2425.293.6434.935.0845.522.7254.636.28VPi的平均數(shù)是4.59,它是河中魚的最好的估計(jì)量.SEVP=SDVPi/Summary
Thelargenumberofdiversitystatisticsavailablemeansthatitmaybedifficulttoselectthemostappropriatemethodsofmeasuringdiversity.Whenappliedtorealisticdatasetsthesediversityindicescanbedividedintotwocategories.Ononehandtherearetheindiceswhichreflectthespeciesrichnesselementofdiversitywhileontheotherhandtherearemeasureswhichexpressthedegreeofdominance(evenness)onthedata.Asageneralobservation,indicesinthefirstcategoryarebetteratdiscriminatingbetweensamplesbutaremoreaffectedbysamplesizethanthedominance/evennesssetofdiversitymeasures.Forreasonsofstandardizationitwouldbeprudentifecologistswouldconcentrateononeorafewindices.Thelogseriesindexα,theBerger-Parkerdominanceindex,andameasureofspeciesrichness(eitherSortheMargalef
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