Download presentation

Presentation is loading. Please wait.

Published byKayla Guthrie Modified over 2 years ago

1
Gradient Analysis Approach to Ordination

2
Models of Species Response to Gradients

3
Models of Species Response There are (at least) two models:- Linear - species increase or decrease along the environmental gradient Unimodal - species rise to a peak somewhere along the environmental gradient and then fall again

4
A Theoretical Model

5
Linear

6
Unimodal

7
Alpha and Beta Diversity alpha diversity is the diversity of a community (either measured in terms of a diversity index or species richness) beta diversity (also known as species turnover or differentiation diversity) is the rate of change in species composition from one community to another along gradients; gamma diversity is the diversity of a region or a landscape.

8
A Short Coenocline

9
A Long Coenocline

10
Inferring Gradients from Species (or Attribute) Data

11
Indirect Gradient Analysis Environmental gradients are inferred from species data alone Three methods: Principal Component Analysis - linear model Correspondence Analysis - unimodal model Detrended CA - modified unimodal model

12
PCA - linear model

13

14
Terschelling Dune Data

15
PCA gradient - site plot

16
PCA gradient - site/species biplot

17
Reciprocal Averaging Site A B C D E F Species Prunus serotina Tilia americana Acer saccharum Quercus velutina Juglans nigra

18
Reciprocal Averaging Site A B C D E F Species Score Species Iteration 1 Prunus serotina Tilia americana Acer saccharum Quercus velutina Juglans nigra Iteration Site Score

19
Reciprocal Averaging Site A B C D E F Species Score Species Iteration 1 2 Prunus serotina Tilia americana Acer saccharum Quercus velutina Juglans nigra Iteration Site Score

20
Reciprocal Averaging Site A B C D E F Species Score Species Iteration Prunus serotina Tilia americana Acer saccharum Quercus velutina Juglans nigra Iteration Site Score

21
Reciprocal Averaging Site A B C D E F Species Score Species Iteration Prunus serotina Tilia americana Acer saccharum Quercus velutina Juglans nigra Iteration Site Score

22
Reordered Sites and Species Site A C E B D F Species Species Score Quercus velutina Prunus serotina Juglans nigra Tilia americana Acer saccharum Site Score

23
Lake Nasser Invertebrates

24

25
CA - unimodal model Protozoa Rotifera Cladocera Copepoda Insecta Turbellaria Tardigrada Annelida Nematoda

26
Arches - Artifact or Feature?

27
The Arch Effect What is it? Why does it happen? What should we do about it?

28
From Alexandria to Suez

29
CA - with arch effect (species)

30
CA - with arch effect (sites)

31
Long Gradients ABCD

32
Gradient End Compression

33
CA - with arch effect (species)

34
Detrending by Segments

35
DCA - modified unimodal

36
Making Effective Use of Environmental Variables

37
Direct Gradient Analysis Environmental gradients are constructed from the relationship between species environmental variables Three methods: Redundancy Analysis - linear model Canonical (or Constrained) Correspondence Analysis - unimodal model Detrended CCA - modified unimodal model

38
CCA - site/species joint plot

39
CCA - species/environment biplot

40
Removing the Effect of Nuisance Variables

41
Partial Analyses Remove the effect of covariates variables that we can measure but which are of no interest e.g. block effects, start values, etc. Carry out the gradient analysis on what is left of the variation after removing the effect of the covariates.

42
Testing Significance in Ordination

43
Randomisation Tests

44

45
Randomisation Example Model: cca(formula = dune ~ Moisture + A1 + Management, data = dune.env) Df Chisq F N.Perm Pr(>F) Model < *** Residual Signif. codes: 0 *** ** 0.01 * 0.05

46

Similar presentations

© 2016 SlidePlayer.com Inc.

All rights reserved.

Ads by Google