第5章生態(tài)多樣性及其測度

生態(tài)多樣性及其測度參考書：E.C.Pielou1975,EcologicalDiversity文獻AnneE.magurran1988EcologicalDiversityanditsmeasurement李典謨1987，生態(tài)的多樣性度量生態(tài)學雜志，6（4):49-52馬克平第十章生物群落多樣性的測度方法中國科學院生物多樣性委員會主編“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是一個很好的多樣性指數(shù)，即使對數(shù)級數(shù)模型不是最好的理論分布的時候也是如此。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）一個可以接受的多樣性的測度至少應具備：（1）合理地簡單，便于計算和理解（2）從生物學、統(tǒng)計學或者數(shù)學上有適當?shù)幕A（3）包含種數(shù)和均勻性兩個概念（4）有一個直觀合理的解釋（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量.SEVP=SDVPi/Summary

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