R语言vegan包使用教程(20)

时间:2025-07-13

R语言中的外在软件包“Vegan”是专门用于群落生态学分析的工具。Vegan能够提供所有基本的排序方法,同时具有生成精美排序图的功能,版本更新很快。我们认为Vegan包完全可以取代CANOCO,成为今后排序分析的首选统计工具。

4.1Modelspeci cation13

21

22

16

14

Cal.vul

Bet.pub

Bar.lyc75

1

216

Led.pal

Dic.fusCla.botPti.cilIch.eri

182

C23CVac.myrCla.criCla.arb0Des.fle20Cla.defDic.polEmp.nigCla.fimSte.spVac.uliCla.amaCla.uncCet.islPin.sylCla.cocCla.ranVac.vit

Cla.graDip.mon0

Ple.schKPol.junCla.corPoh.nutPol.pilCet.eri

Cla.chlCla.sp1127

Nep.arc

Pel.aphCla.steAl

Hyl.splCla.phy

31

25

4

28

Dic.sp

12Cla.cer

210Cet.nivP

9

2

24

1

3 2 1

012

CCA1

4 3 2

3

1

AC2

C 4A0

C 3C1 2 1

2

0 1 23

3

4

3

2

1

1

2

3

CCA1

17

2

610

75

ManagementBF11

18

1

Viclat

ManagementHF2

TripraAchmil

Plalan19

1

Brohor

RumaceAntodo

Trirep

Hyprad

2

LolperPoapra

BelperLeoautAC0Brarut

JunartCPoatriElyrep

ManagementNM

EmpnigPotpalAirpraSalrepJunbufElepal

RanflaSagproCalcus

9Alogen

Agrsto1

3 4

15

14

ManagementSF

ChealbCirarv20

12

2 13

16

2 10

12

3

CCA1

4CONSTRAINEDORDINATION

thiswouldbetheproportionofvariance(orcorrelation).Thismayhaveaclearermeaning,buteveninthiscasemostofthetotalinertiamayberandomnoise.Itmaybebettertoconcentrateonresultsinsteadoftheseproportions.

Basicplottingworksjustlikeearlier:

>plot(a)

havesimilarinterpretationas ttedvectors:thearrowpointstothedirec-tionofthegradient,anditslengthindicatesthestrengthofthevariable

inthisdimensionalityofsolution.Thevectorswillbeofunitlengthinfullranksolution,buttheyareprojectedtotheplaneusedintheplot.Thereisalsoaprimitive3Dplottingfunctionordiplot3d(whichneedsuserinteractionfor nalgraphs)thatshowsallarrowsinfulllength:

>ordiplot3d(a,type="h")

Withfunctionordirglyoucanalsoinspect3Ddynamicplotsthatcanbespinnedorzoomedintowithyourmouse.

Theformulainterfaceworkswithfactorvariablesaswell:

>a<-cca(dune~Management,dune.env)>plot(a)>a

Call:cca(formula=dune~Management,data=dune.env)InertiaProportionRank

Total2.1151.000Constrained0.6040.2853Unconstrained1.5110.71516

InertiaismeansquaredcontingencycoefficientEigenvaluesforconstrainedaxes:CCA1CCA2CCA30.3190.1820.103

Eigenvaluesforunconstrainedaxes:

CA1CA2CA3CA4CA5CA6CA70.447370.203000.163010.134570.129400.094940.07904

CA8CA9CA10CA11CA12CA13CA140.065260.050040.043210.038700.023850.017730.00917

CA15CA160.007960.00416

FactorvariableManagementhadfourlevels(BF,HF,NM,SF).Internally

Rexpressedthesefourlevelsasthreecontrasts(sometimescalled“dummyvariables”).Theappliedcontrastslooklikethis:

ManagementHFManagementNMManagementSF

BF000SF001HF100NM

010

Wedonotneedbutthreevariablestoexpressfourlevels:ifthereis

numberoneinacolumn,theobservationbelongstothatlevel,andif

20

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