第5章生態(tài)多樣性及其測(cè)度

生態(tài)多樣性及其測(cè)度參考書(shū)：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(yú)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