第5章生态多样性及其测度

生态多样性及其测度参考书：E.C.Pielou1975,EcologicalDiversity文献AnneE.magurran1988EcologicalDiversityanditsmeasurement李典谟1987，生态的多样性度量生态学杂志，6（4):49-52马克平第十章生物群落多样性的测度方法中国科学院生物多样性委员会主编“生物多样性研究的原理与方法”1994Whydiversity?Therearethreereasonswhyecologistsareinterestedinecologicaldiversityanditsmeasurement.First,despitechangingfashionsandpreoccupations,diversityremainedacentralthemeinecology.Thewelldocumentedpatternsofspatialandtemporalvariationindiversitywhichintriguedtheearlyinvestigatorsofthenaturalworldcontinuetostimulatethemindsofecologiststoday.Second,measuresofdiversityarefrequentlyseenasindicatorsofthewellbeingofecologicalsystems.Thirdly,considerabledebatesurroundsthemeasurementofdiversity.Diversitymayappeartobeastraightforwardconceptwhichcanbequicklyandpainlesslymeasured.Thereishoweverasimpleexplanationwhydiversityissohardtodefine.Thatisbecausediversityconsistsofnotonebuttwocomponents.Thesearefirstthevarietyandsecondlytherelativeabundanceofspecies.一生态多样性指数的概念（1）种数多少（2）各种之间相对丰富度首先是由Fisher提出，Williams引用（Fisheretal1943)所以，分布越均匀，V越小，p也越小，ln(1+p)越小，越大

大量的研究表明（magurran,1988):α是一个很好的多样性指数，即使对数级数模型不是最好的理论分布的时候也是如此。Magurran，A.E.1988.EcologicalDiversityandItsMeasurement.NewJersey:PrincetonUniversityPress2.多样性的信息度量A1p1A2P2……AjPj……AsPs(3)A分类B分类A1p1…AjPj…AsPsB1q1BkqkBtqtA1B1π11AjAjBkπjkAsBtπskNoteonbiologicaldiversity,evennessandhomogeneitymeasuresT.O.Kvalsethetal1991OIKOS62：（1）一个可以接受的多样性的测度至少应具备：（1）合理地简单，便于计算和理解（2）从生物学、统计学或者数学上有适当的基础（3）包含种数和均匀性两个概念（4）有一个直观合理的解释（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计算VPi=nV-[(n-1)VJj]其中VJj:jack-knifeestimate把第j样去除后算得的多样性指数;

n:样本数.Excludedsection1VJiVPi14.895.2425.293.6434.935.0845.522.7254.636.28VPi的平均数是4.59,它是河中鱼的最好的估计量.SEVP=SDVPi/Summary

Thelargenumberofdiversitystatisticsavailablemeansthatitmaybedifficulttoselectthemostappropriatemethodsofmeasuringdiversity.Whenappliedtorealisticdatasetsthesediversityindicescanbedividedintotwocategories.Ononehandtherearetheindiceswhichreflectthespeciesrichnesselementofdiversitywhileontheotherhandtherearemeasureswhichexpressthedegreeofdominance(evenness)onthedata.Asageneralobservation,indicesinthefirstcategoryarebetteratdiscriminatingbetweensamplesbutaremoreaffectedbysamplesizethanthedominance/evennesssetofdiversitymeasures.Forreasonsofstandardizationitwouldbeprudentifecologistswouldconcentrateononeorafewindices.Thelogseriesindexα,theBerger-Parkerdominanceindex,andameasureofspeciesrichness(eitherSortheMargalef