Introduction

During fieldwork you each walked a transect from dune crest down into the slack, recording the species in each quadrat and measuring environmental variables.

Now comes the detective work: how do we make sense of all those numbers? How do we reduce a messy table of species × plots into something we can actually interpret?

This is where ordination comes in. Ordination methods take complex community data and project it into two dimensions so we can see the hidden gradients. In this practical, you’ll use your own data to explore:

What ecological gradients structure the dune vegetation?
Which environmental factors explain these gradients?
Do the patterns in the ordination match what you saw in the field?

The Tools

We will compare three ordination methods. Each reduces multidimensional data into a simpler map, but they differ in assumptions:

PCA (Principal Components Analysis): linear method, best for short gradients.
DCA (Detrended Correspondence Analysis): unimodal method, suited to long gradients with strong turnover.
NMDS (Non-metric Multidimensional Scaling): flexible, rank-based method, fewer distributional assumptions.

As you look at each ordination, ask yourself: which one gives the clearest ecological story for your data?

By the end of this practical you should be able to

Distinguish between PCA, DCA, and NMDS and know when each is appropriate.
Interpret ordination diagrams (sites, species, axes) in ecological terms.
Link vegetation patterns to measured environmental gradients.

Remember that there are different ways of setting up the data table. Recall the difference between long and wide data formats.
- In long format, each row records a single observation (quadrat–species–abundance).
- In wide format, each row is a quadrat and each column is a species, with the entries giving abundances.

Ordination methods in vegan (e.g. PCA, DCA, NMDS) require the wide format: a quadrat × species matrix.
Below is a sample of that matrix from your dataset (showing only a subset of quadrats and species for clarity).

Sample of the species × quadrat matrix (abundances). The total matrix is 45 quadrats (rows) by 54 species (columns).
	Anthaeth	Crasfili	Euclrace	Heligymn	Oleaexas	Resteleo	Sporvirg	Dasisuff
H01a	10	1	15	1	25	0	0	0
H01b	0	5	50	0	25	0	0	5
H01c	0	0	40	0	55	5	0	0
H02a	0	0	25	1	30	5	0	0
H02b	0	12	10	0	25	5	1	5
H02c	0	1	8	0	30	3	0	0

Generating the ordinations for each method

### PCA
# Hellinger transform is often sensible for community data before PCA
dune_hel <- decostand(vegdat_wide, method = "hellinger")
pca <- rda(dune_hel)

### DCA
dca <- decorana(vegdat_wide)


### NMDS
nmds <- metaMDS(vegdat_wide,trace=0,k=5,try=50,trymax=1000)

Interpreting Ordination Axes

Our sampling design followed a transect from dune crest to slack, capturing the full topographic gradient in vegetation structure. During fieldwork we observed marked shifts in composition: crest plots were distinct from slopes and slacks, with characteristic sets of species at each zone.

The first ordination axis is therefore expected to capture the dominant ecological signal: the transition in community composition from crest → slope → slack.

The second ordination axis reflects the within-zone variation among transects. While the broad crest–slope–slack pattern was consistent, each zone showed slight compositional differences, and these are expressed along the second axis.

In the ordinations below, can you see the pattern described above?

PCA

DCA

NMDS

Reporting the Quality of an Ordination

When you look at the ordination summaries above, you’ll see that each method reports different statistics. These values tell us how well the ordination represents the original data. But the catch is: each ordination type has its own measures of “goodness.”

Task:
- Go and find out what metrics are used for PCA, DCA, and NMDS, and what they mean.
- Write a short statement for each ordination in your report, reporting its quality using the appropriate measure(s).

Hints:

PCA: Look at eigenvalues / proportion of variance explained. Report how much variation in species data is captured by the first few axes.
DCA: Check axis lengths and eigenvalues. Long axis lengths (>4 SD units) imply strong species turnover, while shorter ones suggest weaker gradients.
NMDS: Report the stress value. A stress <0.1 is excellent, <0.2 is usable, >0.3 is poor. Always mention stress in your write-up.

Notice how there isn’t a single universal statistic across ordinations — you must use the metric that belongs to that method.

Below are the outputs from each ordination…

pca

## Call: rda(X = dune_hel)
## 
##               Inertia Rank
## Total          0.6872     
## Unconstrained  0.6872   44
## Inertia is variance 
## 
## Eigenvalues for unconstrained axes:
##     PC1     PC2     PC3     PC4     PC5     PC6     PC7     PC8 
## 0.15231 0.09120 0.07906 0.06392 0.04863 0.03748 0.02969 0.02442 
## (Showing 8 of 44 unconstrained eigenvalues)

dca

## 
## Call:
## decorana(veg = vegdat_wide) 
## 
## Detrended correspondence analysis with 26 segments.
## Rescaling of axes with 4 iterations.
## Total inertia (scaled Chi-square): 6.172 
## 
##                        DCA1   DCA2   DCA3   DCA4
## Eigenvalues          0.6468 0.5655 0.3486 0.2970
## Additive Eigenvalues 0.6468 0.5658 0.3483 0.2972
## Decorana values      0.6551 0.4860 0.2860 0.1788
## Axis lengths         4.6112 4.3446 2.8434 2.4423

nmds

## 
## Call:
## metaMDS(comm = vegdat_wide, k = 5, try = 50, trymax = 1000, trace = 0) 
## 
## global Multidimensional Scaling using monoMDS
## 
## Data:     wisconsin(sqrt(vegdat_wide)) 
## Distance: bray 
## 
## Dimensions: 5 
## Stress:     0.09162841 
## Stress type 1, weak ties
## Best solution was repeated 3 times in 50 tries
## The best solution was from try 30 (random start)
## Scaling: centring, PC rotation, halfchange scaling 
## Species: expanded scores based on 'wisconsin(sqrt(vegdat_wide))'

As you can see above, each ordination method has its own way of reporting how well it represents the data.
When writing up your results, make sure you report the appropriate statistic(s).

Use the details below to extract the necessary information from the R output above.

PCA (Principal Components Analysis)
- Report the eigenvalues and the percentage of variance explained by the first few axes.
- Example: calculate % variance = eigenvalue / total inertia × 100.
- Always state how much of the total variation is captured by the ordination axes you interpret (e.g. “The first two axes capture 39% of the total variation”.)
DCA (Detrended Correspondence Analysis)
- Report the eigenvalues of the first axes.
- Also report axis lengths (in SD units) — values > 4 indicate complete species turnover, values around 3 indicate substantial turnover, shorter lengths suggest weaker gradients.
- Mention what this means ecologically for your transect.
NMDS (Non-metric Multidimensional Scaling)
- Report the stress value (a measure of fit between the ordination and the distance matrix).
- Rules of thumb: <0.1 = excellent; 0.1–0.2 = usable; >0.3 = poor.
- Always include the number of dimensions used and whether the solution was stable across random starts.

What Else Should Be Reported?

In addition to the formal metrics, think about these:
- Number of dimensions chosen: Did you use 2, 3, or more axes? Why?
- Interpretability: Does the ordination separate crest, slope, and slack in a way that matches your ecological knowledge?
- Biological meaning: Even if an ordination has a “good” metric, it must still make ecological sense.

In other words, don’t just report numbers — explain what they mean for your dune transect dataset.

Adding Group Structure to Ordinations

A raw ordination plot of points is often hard to interpret on its own. To make patterns clearer, ecologists overlay group structures that summarise how plots relate to one another. Common options include:

Convex hulls: draw the smallest polygon around all plots in a group, showing their overall spread.
Ordispiders: connect each plot to its group centroid, highlighting variation within groups.
Ellipses: plot statistical confidence regions around group centroids, showing the “core space” of each group.

These tools make ordinations far more useful by helping us see whether groups of plots (e.g. crest, slope, slack) are distinct, overlapping, or highly variable. In other words, ordination visualisation usually requires adding these layers — the raw scatter of points alone rarely tells the full story.

Below are the ordination plots with convex hulls.
A convex hull is the smallest polygon that encloses a set of points, helping us visualise the overall spread of quadrats belonging to the same habitat group.

For this analysis, quadrats were grouped as follows:

Crest: quadrats 1–3
Slope: quadrats 5–8
Slack: quadrats 12–15

Because the transects were not identical, quadrats 4 and 9–11 were excluded.
This provides the clearest representation of the crest, slope, and slack habitats.

PCA

DCA

NMDS

In addition to convex hulls, another useful way to show group structure in ordinations is with ordispiders.
An ordispider draws straight lines from the group centroid (the average position of all plots in that group) to each of the individual plots.

This allows you to see:

how tightly or loosely the plots in a group cluster around their centroid,
whether some plots are outliers compared to the rest of the group, and
differences in spread between groups (e.g., crest vs. slope vs. slack).

In ecological terms, a shorter set of spider lines means the group is relatively homogeneous in species composition, while longer lines suggest more variation within that habitat type.

PCA

DCA

NMDS

Exploring plant species in ordinations

In this section we focus on the species (the “descriptors”) in ordination space—how they are plotted, what their positions mean, and how to interpret them.

In the first tab, the ordination is shown with species points added (green dots with names, except where labels would be too crowded). The quadrats are shown as grey dots in the background for context.
In the next tab, I present the results of an envfit() analysis, which tests how strongly each species correlates with the ordination axes.
In the following tab, the ordination is also displayed with species coloured, to aid interpretation, according to whether their correlation is statistically significant (here, p < 0.10) or not.

Task: Find species in the ordination plots and compare their placement with their statistics in the envfit table. Which species positions are strongly supported by the data, and which are not?

PCA 1

PCA Species scores

The table shows the direction cosines of each species vector (PC1 and PC2), the coefficient of determination (r²) indicating the strength of correlation with the ordination, and the permutation-based p-value for significance.
Species	PC1	PC2	r2	p_value	sig_codes
Albunels	0.8199	0.5726	0.01	0.976
Anthaeth	0.9998	0.0182	0.07	0.124
Arctpopu	0.9641	-0.2654	0.11	0.039
Aspaaeth	0.4115	0.9114	0.01	0.864
Carpdeli	-0.7616	-0.6480	0.02	0.828
Chaecamp	-0.0579	-0.9983	0.03	0.554
Colepulc	-0.6271	-0.7789	0.59	0.001	***
Colpcomp	0.9582	-0.2862	0.07	0.200
Crasfili	0.9962	0.0875	0.10	0.085	.
Crasumbe	0.9999	0.0155	0.05	0.417
Cussthyr	0.0959	0.9954	0.00	1.000
Cynaelli	-0.1150	0.9934	0.09	0.092	.
Dasisuff	0.9997	0.0251	0.09	0.092	.
Ehrherec	0.9210	-0.3897	0.19	0.012
Ericglum	-0.9567	0.2911	0.03	0.672
Erucstri	-0.7020	-0.7122	0.04	0.491
Euclrace	0.9680	0.2509	0.45	0.001	***
Feliechi	-0.3275	0.9449	0.09	0.038
Ficilate	-0.8052	0.5930	0.08	0.204
Ficiramo	0.5410	-0.8410	0.01	0.761
Gamocoar	0.9551	-0.2962	0.06	0.327
Gastacin	0.9999	0.0155	0.05	0.417
Heligymn	-0.0762	0.9971	0.18	0.002	**
Helinudi	-0.1983	-0.9801	0.08	0.164
Helipeti	-0.2796	-0.9601	0.03	0.753
Helitere	0.8494	-0.5278	0.09	0.115
Indiglau	0.5426	-0.8400	0.03	0.706
Isolannu	0.8091	-0.5876	0.06	0.325
Jamemicr	-0.3780	-0.9258	0.07	0.142
Kedrnana	0.9388	-0.3444	0.00	0.992
Laurtetr	-0.1660	-0.9861	0.03	0.583
Lobeance	-0.6395	-0.7688	0.09	0.064	.
Metamuri	-0.3641	0.9313	0.46	0.001	***
Morequer	-0.5803	0.8144	0.22	0.004	**
Oleaexas	0.9791	-0.2031	0.60	0.001	***
Oxaldepr	0.0121	0.9999	0.09	0.055	.
Oxalimbr	0.9725	0.2327	0.03	0.544
Oxalsp	0.9209	0.3898	0.07	0.210
Passcory	-0.7031	-0.7111	0.14	0.027
Pelacapi	-0.8074	-0.5900	0.11	0.080	.
Phyleric	-0.8412	0.5408	0.20	0.006	**
Rapagill	-0.8285	0.5599	0.06	0.278
Resteleo	-0.4563	0.8899	0.40	0.001	***
Robsmari	0.5426	-0.8400	0.03	0.706
Searcren	0.9513	0.3081	0.03	0.598
Searglau	-0.7384	0.6743	0.06	0.343
Searlaev	-0.3163	0.9487	0.09	0.129
Searpter	-0.9195	-0.3930	0.09	0.131
Seneangu	0.9209	0.3898	0.07	0.210
Seneilic	0.8450	-0.5347	0.05	0.415
Sporvirg	-0.5718	0.8204	0.16	0.015
Tracrevo	0.7678	-0.6407	0.04	0.505
Zalucape	0.9921	-0.1255	0.05	0.376
Zalumari	0.0115	0.9999	0.04	0.503

PCA 2

DCA

DCA species scores

The table shows the direction cosines of each species vector (DCA1 and DCA2), the coefficient of determination (r²) indicating the strength of correlation with the ordination, and the permutation-based p-value for significance.
Species	DCA1	DCA2	r2	p_value	sig_codes
Albunels	0.6280	0.7782	0.01	0.808
Anthaeth	0.8904	-0.4552	0.02	0.475
Arctpopu	0.9997	0.0241	0.11	0.138
Aspaaeth	0.0542	-0.9985	0.05	0.306
Carpdeli	0.5211	-0.8535	0.00	0.948
Chaecamp	0.5839	0.8118	0.03	0.477
Colepulc	-0.3855	0.9227	0.10	0.120
Colpcomp	0.9965	0.0838	0.09	0.167
Crasfili	0.9462	0.3236	0.03	0.522
Crasumbe	0.8982	-0.4396	0.02	0.507
Cussthyr	0.9993	-0.0365	0.16	0.094	.
Cynaelli	-0.3791	-0.9254	0.08	0.190
Dasisuff	0.9714	0.2373	0.02	0.602
Ehrherec	0.9954	0.0953	0.22	0.013
Ericglum	-0.6072	-0.7945	0.16	0.124
Erucstri	-0.4707	0.8823	0.25	0.007	**
Euclrace	0.9186	-0.3953	0.24	0.003	**
Feliechi	-0.5037	-0.8639	0.10	0.174
Ficilate	-0.5843	-0.8116	0.11	0.086	.
Ficiramo	-0.2605	0.9655	0.16	0.028
Gamocoar	0.8691	0.4946	0.02	0.675
Gastacin	0.8982	-0.4396	0.02	0.507
Heligymn	-0.6439	-0.7651	0.06	0.249
Helinudi	-0.0560	0.9984	0.14	0.042
Helipeti	-0.0115	0.9999	0.02	0.576
Helitere	0.6888	0.7250	0.06	0.241
Indiglau	0.9811	0.1937	0.04	0.343
Isolannu	0.9974	0.0717	0.05	0.265
Jamemicr	0.2854	0.9584	0.02	0.640
Kedrnana	0.9997	0.0250	0.21	0.013
Laurtetr	0.0151	0.9999	0.05	0.273
Lobeance	-0.1807	0.9835	0.01	0.838
Metamuri	-0.6911	-0.7227	0.12	0.076	.
Morequer	-0.5037	-0.8639	0.58	0.001	***
Oleaexas	0.9770	-0.2134	0.29	0.003	**
Oxaldepr	-0.3178	-0.9481	0.07	0.204
Oxalimbr	0.9768	-0.2140	0.01	0.856
Oxalsp	0.8050	-0.5933	0.03	0.431
Passcory	-0.4639	0.8859	0.51	0.001	***
Pelacapi	-0.4589	0.8885	0.60	0.001	***
Phyleric	-0.5294	-0.8484	0.49	0.001	***
Rapagill	-0.5068	0.8621	0.11	0.096	.
Resteleo	-0.5290	-0.8486	0.44	0.001	***
Robsmari	0.9811	0.1937	0.04	0.343
Searcren	0.9941	-0.1081	0.26	0.006	**
Searglau	-0.8183	0.5748	0.08	0.187
Searlaev	-0.4261	-0.9047	0.17	0.034
Searpter	-0.8473	-0.5311	0.02	0.589
Seneangu	0.8050	-0.5933	0.03	0.431
Seneilic	0.9320	0.3625	0.05	0.308
Sporvirg	-0.6517	-0.7585	0.06	0.271
Tracrevo	0.9533	0.3020	0.06	0.253
Zalucape	0.9743	-0.2251	0.06	0.206
Zalumari	-0.2926	-0.9562	0.03	0.403

DCA 2

NMDS

NMDS species scores

The table shows the direction cosines of each species vector (NMDS1 and NMDS22), the coefficient of determination (r²) indicating the strength of correlation with the ordination, and the permutation-based p-value for significance.
Species	NMDS1	NMDS2	r2	p_value	sig_codes
Albunels	-0.6396	0.7687	0.04	0.596
Anthaeth	-0.6619	-0.7496	0.11	0.010	**
Arctpopu	-0.9993	-0.0385	0.13	0.012
Aspaaeth	0.0729	-0.9973	0.09	0.118
Carpdeli	0.8153	-0.5790	0.01	0.842
Chaecamp	-0.4427	0.8967	0.08	0.184
Colepulc	0.6584	0.7526	0.18	0.016
Colpcomp	-0.9974	0.0718	0.09	0.074	.
Crasfili	-0.9350	0.3545	0.13	0.038
Crasumbe	-0.8269	-0.5624	0.05	0.441
Cussthyr	-0.1114	-0.9938	0.01	0.934
Cynaelli	0.2921	-0.9564	0.05	0.356
Dasisuff	-0.9250	0.3799	0.10	0.104
Ehrherec	-0.9974	-0.0714	0.22	0.006	**
Ericglum	0.8379	-0.5459	0.07	0.198
Erucstri	0.2257	0.9742	0.15	0.023
Euclrace	-0.8938	-0.4486	0.42	0.001	***
Feliechi	0.5762	-0.8173	0.03	0.594
Ficilate	0.6840	-0.7295	0.23	0.002	**
Ficiramo	-0.1108	0.9938	0.16	0.019
Gamocoar	-0.8504	0.5261	0.09	0.147
Gastacin	-0.8269	-0.5624	0.05	0.441
Heligymn	0.3177	-0.9482	0.11	0.038
Helinudi	-0.0649	0.9979	0.26	0.001	***
Helipeti	-0.0894	0.9960	0.04	0.553
Helitere	-0.6969	0.7172	0.24	0.003	**
Indiglau	-0.9999	-0.0147	0.03	0.763
Isolannu	-0.9696	-0.2448	0.06	0.363
Jamemicr	-0.0829	0.9966	0.04	0.497
Kedrnana	-0.9653	-0.2611	0.01	0.879
Laurtetr	-0.2070	0.9783	0.07	0.186
Lobeance	0.5887	0.8083	0.03	0.708
Metamuri	0.7655	-0.6435	0.12	0.068	.
Morequer	0.6387	-0.7695	0.33	0.001	***
Oleaexas	-0.8989	-0.4381	0.51	0.001	***
Oxaldepr	0.2039	-0.9790	0.06	0.231
Oxalimbr	-0.9497	0.3132	0.05	0.409
Oxalsp	-0.5951	-0.8036	0.07	0.253
Passcory	0.3551	0.9348	0.30	0.001	***
Pelacapi	0.3858	0.9226	0.37	0.001	***
Phyleric	0.7288	-0.6847	0.42	0.001	***
Rapagill	0.5488	0.8359	0.10	0.093	.
Resteleo	0.6287	-0.7776	0.32	0.001	***
Robsmari	-0.9999	-0.0147	0.03	0.763
Searcren	-0.5543	-0.8323	0.06	0.267
Searglau	0.9928	0.1198	0.04	0.497
Searlaev	0.4674	-0.8841	0.12	0.040
Searpter	0.8726	-0.4885	0.11	0.058	.
Seneangu	-0.5951	-0.8036	0.07	0.253
Seneilic	-0.9633	0.2683	0.06	0.254
Sporvirg	0.8862	-0.4633	0.08	0.190
Tracrevo	-0.9635	0.2677	0.06	0.258
Zalucape	-0.7620	-0.6476	0.06	0.375
Zalumari	0.1733	-0.9849	0.03	0.654

NMDS 2

Species positions vs. significance in ordinations

A common misconception is that the location of a species point in the ordination plot automatically indicates its importance.
This is not the case.

Species scores (the positions in the ordination diagram) show the average composition-weighted location of that species relative to the quadrats. They tell you where a species tends to occur, but not how strongly it drives the overall pattern.
Significance and r² values from envfit quantify how well a species’ distribution aligns with the main gradients captured by the ordination axes.
- A species might plot far from the origin simply because it is tied to a few unusual plots, but that does not mean it explains much of the overall variation.
- Conversely, another species might sit near the origin yet still show a strong, statistically significant fit if its distribution matches the major ecological gradients.

In other words:
- Position = where the species occurs.
- Significance (r², p-value) = whether that species explains the main gradients.

Analogy

Think of an ordination like a lecture hall: two students might be sitting right next to each other. One is paying close attention and contributes insightful questions that shape the discussion (high r², significant). The other is catching up on their social media and not paying attention, present but not really influencing the direction of the lecture (low r², not significant).

The same applies to species in ordination space — proximity alone doesn’t tell you their importance. What matters is whether their pattern of occurrence actually aligns with the major ecological gradients captured by the analysis.

Understanding Species Coordinates

To deepen your understanding of species points in ordination space, examine the plots below.

Each panel shows one species.
The green diamond marks the species’ ordination coordinate (its statistical “summary position”).
Quadrats where the species is present are plotted, with point size and colour scaled to percentage cover.
Grey crosses mark quadrats where the species is absent.

Task:
1. Compare the location of the species coordinate (diamond) to the distribution of its quadrats.
- Does the coordinate lie near the centre of where the species is most abundant?
- Can you find examples where two species have nearby coordinates, but very different abundance patterns?

Go back to the envfit results table for species.
- Look at the r² values (strength of relationship with the ordination axes).
- Look at the p-values (significance of the relationship).
Reflect:
- Do species with high r² and low p show clearer, more interpretable patterns in the ordination plots?
- Do species with low r² or high p look more scattered or less aligned with the ordination axes?

This exercise will help you connect the visualisation of species occurrence with the statistical tests that quantify their importance in shaping ordination patterns.
:::

PCA all species

DCA all species

NMDS all species

Writing Up Your Report

Your final task is to write up the Methods, Results, and a short Discussion for this practical.
Use this document as your data source: you may quote numbers from the summaries, copy plots, or crop figures to support your points. You must generate a hand-drawn ordination, with some grouping of the plots (e.g. by zone), include the environmental variables and some of the important species.

What to Include

Methods: Briefly describe how the vegetation and environmental data were collected, how the quadrat × species matrix was set up, and which ordination methods were used. Keep this short and clear.
Results: Present your ordination outputs. You must primarily use your hand-drawn ordination, but you can additionally use plots provided here (whole figures or cropped sections) and report the quality statistics (i.e., variance explained, axis lengths, stress). Highlight the main ecological patterns you see.
Discussion: Reflect on the strengths and weaknesses of PCA, DCA, and NMDS for this dataset. Which method gives the clearest story of crest → slope → slack? Why?
- Point out the most important environmental variables and how they relate to the vegetation patterns.
- Identify some species that strongly match the gradients and others that do not.
- Comment on whether the ordinations confirm what you observed in the field.

Key Reminder

Numbers and plots are essential, but your write-up should explain their meaning in plain language. Focus on telling the ecological story of the dune system rather than just repeating output.

Raw ordination data

Below are the Eigenvalues for each of the ordinations - these can be used to draw your ordination on graph paper. You can find the environmental variables above.

PCA

##                    PC1           PC2   score    label
## Anthaeth  5.527242e-02 -0.0007240926 species Anthaeth
## Crasfili  7.962437e-02  0.0055931594 species Crasfili
## Euclrace  5.262118e-01  0.1547695697 species Euclrace
## Heligymn  1.039643e-02  0.0477062456 species Heligymn
## Oleaexas  6.399612e-01 -0.1686106504 species Oleaexas
## Resteleo -1.820529e-01  0.2769592199 species Resteleo
## Sporvirg -2.678640e-02  0.0483996192 species Sporvirg
## Dasisuff  3.860440e-02  0.0009895147 species Dasisuff
## Ficiramo -1.128564e-03 -0.0352893116 species Ficiramo
## Gamocoar  3.723846e-02 -0.0088609369 species Gamocoar
## Helinudi -5.539802e-03 -0.1143911402 species Helinudi
## Helitere  1.301002e-01 -0.1022223598 species Helitere
## Arctpopu  7.811149e-02 -0.0432607572 species Arctpopu
## Aspaaeth  2.988805e-02  0.0224823874 species Aspaaeth
## Ehrherec  2.467923e-01 -0.0735086563 species Ehrherec
## Metamuri -1.845322e-01  0.4950646964 species Metamuri
## Oxalsp    2.574076e-02  0.0108960187 species   Oxalsp
## Seneangu  9.100732e-03  0.0038523244 species Seneangu
## Ficilate -6.775459e-02  0.0733915477 species Ficilate
## Morequer -1.407801e-01  0.1759284320 species Morequer
## Oxaldepr  6.120800e-04  0.0395394734 species Oxaldepr
## Phyleric -1.742293e-01  0.1419615780 species Phyleric
## Laurtetr  1.148108e-02 -0.0527752549 species Laurtetr
## Oxalimbr  2.966318e-02  0.0078789156 species Oxalimbr
## Tracrevo  1.914202e-02 -0.0104385747 species Tracrevo
## Crasumbe  1.144953e-02  0.0001775148 species Crasumbe
## Gastacin  2.560194e-02  0.0003969350 species Gastacin
## Isolannu  5.257960e-02 -0.0247823910 species Isolannu
## Colepulc -5.021292e-01 -0.4642774185 species Colepulc
## Cynaelli -5.184016e-03  0.0337872006 species Cynaelli
## Feliechi -5.392935e-03  0.0155597159 species Feliechi
## Searcren  9.994949e-02  0.0235637509 species Searcren
## Carpdeli -4.270463e-03 -0.0252235253 species Carpdeli
## Zalucape  8.669966e-03 -0.0010966651 species Zalucape
## Searlaev -6.435766e-03  0.0174309425 species Searlaev
## Zalumari  9.343146e-05  0.0081515790 species Zalumari
## Albunels  1.140645e-02  0.0079661234 species Albunels
## Chaecamp -1.147848e-03 -0.0179338380 species Chaecamp
## Rapagill -6.398857e-02  0.0357532259 species Rapagill
## Colpcomp  2.504890e-02 -0.0095086989 species Colpcomp
## Indiglau  2.588798e-03 -0.0040071975 species Indiglau
## Robsmari  2.588798e-03 -0.0040071975 species Robsmari
## Seneilic  2.282483e-02 -0.0387964952 species Seneilic
## Searglau -5.919490e-02  0.0582422622 species Searglau
## Erucstri -1.574060e-02 -0.0390881646 species Erucstri
## Searpter -2.821738e-02 -0.0081886839 species Searpter
## Helipeti -5.200742e-03 -0.0178575222 species Helipeti
## Kedrnana  3.270960e-03 -0.0440589792 species Kedrnana
## Passcory -1.462814e-01 -0.1453554872 species Passcory
## Pelacapi -1.067868e-01 -0.0757446615 species Pelacapi
## Cussthyr  1.602136e-04  0.0016625424 species Cussthyr
## Jamemicr -7.915904e-03 -0.0193888237 species Jamemicr
## Lobeance -9.223845e-03 -0.0110880799 species Lobeance
## Ericglum -3.832593e-02  0.0116601413 species Ericglum
## H01a      5.845754e-01  0.0286999584   sites     H01a
## H01b      5.374257e-01  0.0067506246   sites     H01b
## H01c      5.470554e-01  0.2315676039   sites     H01c
## H02a      2.464715e-01  0.6026322678   sites     H02a
## H02b      4.547488e-01  0.0181829906   sites     H02b
## H02c      5.191744e-01  0.0080493332   sites     H02c
## H03a     -2.297057e-01  0.6627477933   sites     H03a
## H03b      4.588692e-01 -0.0102249165   sites     H03b
## H03c      5.167819e-01 -0.0653678136   sites     H03c
## H04a      5.509511e-03  0.4806862082   sites     H04a
## H04b      1.430287e-01  0.0998894685   sites     H04b
## H04c      3.331412e-01 -0.3183352600   sites     H04c
## H05a     -6.929665e-02  0.4418054414   sites     H05a
## H05b      1.465192e-01 -0.2359111374   sites     H05b
## H05c      2.343440e-01 -0.3627407860   sites     H05c
## H06a     -3.292570e-01  0.5266941417   sites     H06a
## H06b     -5.899472e-02  0.3117710682   sites     H06b
## H06c      5.240361e-01 -0.0394070466   sites     H06c
## H07a     -2.464067e-01  0.8119089656   sites     H07a
## H07b     -3.317555e-01  0.0095029185   sites     H07b
## H07c     -3.446541e-02 -0.5644719088   sites     H07c
## H08a     -4.664628e-01 -0.3938592524   sites     H08a
## H08b      1.717162e-01 -0.2092655609   sites     H08b
## H08c      4.067640e-01 -0.3157015699   sites     H08c
## H09a     -4.514998e-01 -0.0875783618   sites     H09a
## H09b     -1.689636e-01 -0.4655969795   sites     H09b
## H09c      4.921804e-01 -0.1713748587   sites     H09c
## H10a     -4.280965e-01  0.2925441616   sites     H10a
## H10b     -1.113734e-01 -0.3824170715   sites     H10b
## H10c      8.380078e-02 -0.4256397898   sites     H10c
## H11a      2.606079e-01  0.5332343999   sites     H11a
## H11b     -3.872637e-01 -0.1167734819   sites     H11b
## H11c      3.254486e-01  0.1623059858   sites     H11c
## H12a     -4.204928e-01  0.1119678635   sites     H12a
## H12b     -2.197650e-01  0.0651487810   sites     H12b
## H12c      9.610454e-03  0.0997280217   sites     H12c
## H13a     -4.412897e-01  0.1857618731   sites     H13a
## H13b     -2.428236e-01 -0.3527809018   sites     H13b
## H13c     -2.344070e-01 -0.5741448345   sites     H13c
## H14a     -3.150476e-01  0.4477489291   sites     H14a
## H14b     -2.426023e-01 -0.1549738559   sites     H14b
## H14c     -4.421705e-01 -0.5315377884   sites     H14c
## H15a     -4.133110e-01  0.1257442518   sites     H15a
## H15b     -3.886067e-01 -0.4799568639   sites     H15b
## H15c     -3.277516e-01 -0.0070130116   sites     H15c

DCA

##                  DCA1        DCA2        DCA3          DCA4   score    label
## H01a      1.180980426 -0.34050983 -0.42085829  1.4718919890   sites     H01a
## H01b      0.675525740  0.20679848  0.37739406  1.1398201818   sites     H01b
## H01c      0.905884497 -0.39284440 -0.12812920  0.5270938018   sites     H01c
## H02a     -0.187793655 -0.85490102  0.01924155  0.3431340256   sites     H02a
## H02b      0.655565984  0.01984629  1.00077158  0.5290149073   sites     H02b
## H02c      1.047481548 -0.28822029  0.12375944 -0.2296937020   sites     H02c
## H03a     -1.221576707 -1.26330720  0.53002653 -0.1814754128   sites     H03a
## H03b      0.909235492 -0.16690791  0.03186018  0.4441776019   sites     H03b
## H03c      1.488595616 -0.16724666  0.11446038  0.1259808842   sites     H03c
## H04a     -0.467827524 -0.86989065  0.32311258  0.1757253311   sites     H04a
## H04b      0.363416616  0.27844916  1.44525468 -0.3477640450   sites     H04b
## H04c      0.992507749  0.05181458 -0.07125486 -0.1123838027   sites     H04c
## H05a      0.006516664 -0.18737976  0.40703274 -0.4097571621   sites     H05a
## H05b      0.285384374  0.28713471  0.10230469  0.4419968943   sites     H05b
## H05c      1.200098056  0.18228008  0.15820449 -0.9653003428   sites     H05c
## H06a     -0.683306767 -0.34963214  0.68396326 -0.8101059060   sites     H06a
## H06b     -0.279434104 -0.31535951  0.70187496 -0.5975848598   sites     H06b
## H06c      1.500276258  0.08488942  0.21213349 -0.3830583278   sites     H06c
## H07a     -1.070412624 -0.48403057  0.65972252 -0.5381656726   sites     H07a
## H07b     -1.327176800  1.29221839 -0.06525494 -0.4040876136   sites     H07b
## H07c      0.339981881  0.31634136 -0.95428624  0.0002653417   sites     H07c
## H08a     -0.553405780  0.07698459 -1.39815957 -0.1783279905   sites     H08a
## H08b     -0.420775160  1.57065294  1.31809865  1.4583491703   sites     H08b
## H08c      0.772036952 -0.10365591 -0.45007733  0.8490965180   sites     H08c
## H09a     -0.452086652 -0.11772525 -1.14482332  0.0579792557   sites     H09a
## H09b     -0.057000600  0.86407476 -0.10638200  0.1101573555   sites     H09b
## H09c      0.867855340 -0.25508755 -0.32813814  0.7811449209   sites     H09c
## H10a     -0.636911093 -0.34781443  0.08874246 -0.6262454833   sites     H10a
## H10b      0.023918052  0.75606949  0.23434993  0.7547878826   sites     H10b
## H10c      0.267786101  0.25646903 -0.72656364  0.0578849844   sites     H10c
## H11a      0.258351326 -0.90025548 -0.05191354  0.3640684542   sites     H11a
## H11b     -0.537827297  0.53303002 -0.37296807 -0.5130009782   sites     H11b
## H11c      1.731151685 -0.15862335 -0.24335358  0.2218295916   sites     H11c
## H12a     -1.194624930 -1.32375577 -0.60476960 -0.0161792236   sites     H12a
## H12b     -1.792217756  2.18979834  0.23927686 -0.1544950140   sites     H12b
## H12c      2.564992688  0.02173374 -0.27216435 -0.4871993480   sites     H12c
## H13a     -1.551980636 -1.60493065 -0.45491899  0.1910993639   sites     H13a
## H13b     -1.547396650  1.99354235  0.03540803  0.4332784140   sites     H13b
## H13c      0.372978777  0.71044667 -1.00858813 -0.5418239536   sites     H13c
## H14a     -2.046185071 -2.15476175 -0.10390794  0.2832436679   sites     H14a
## H14b     -1.070678912  1.82062010  0.91843583  1.4770298195   sites     H14b
## H14c     -0.137575364  0.55054163 -1.33936445 -0.3798648421   sites     H14c
## H15a     -1.994016084 -1.60658733 -0.18770479  0.4042064378   sites     H15a
## H15b     -1.576697495  1.84967058 -0.69807947 -0.4789974004   sites     H15b
## H15c     -1.480695741 -0.02442627 -0.01436494 -0.2645260041   sites     H15c
## Anthaeth  2.221749349 -0.47895335 -1.65085796  3.8723363850 species Anthaeth
## Crasfili  0.900794395  0.10208002  2.16975305  0.5267871218 species Crasfili
## Euclrace  1.014140239 -0.49636243 -0.10480832  0.8401836391 species Euclrace
## Heligymn -0.862739223 -0.97848489  0.08927470  1.6626807719 species Heligymn
## Oleaexas  0.957733197 -0.18380545 -0.24251818  0.9209118838 species Oleaexas
## Resteleo -1.491247621 -1.62654036  0.54582730  0.1803156253 species Resteleo
## Sporvirg -1.119650899 -0.92444085  1.09176085 -1.1235912565 species Sporvirg
## Dasisuff  1.129599556  0.50482204  1.66695800  1.4462087471 species Dasisuff
## Ficiramo -0.652759160  2.21490735  0.60965728  1.9797563990 species Ficiramo
## Gamocoar  0.572869758  0.14077908  1.19124292  1.3415841977 species Gamocoar
## Helinudi -0.240028055  2.00272601  1.66140894  2.1477347335 species Helinudi
## Helitere  0.407998816  0.70553715  1.64405306  1.5343814821 species Helitere
## Arctpopu  2.047637129  0.16283084  0.10883286 -1.5263491013 species Arctpopu
## Aspaaeth -0.007238167 -1.54366091 -1.08428199 -0.7659781638 species Aspaaeth
## Ehrherec  1.830976570  0.18781632  1.07528122 -1.2430880769 species Ehrherec
## Metamuri -0.669292061 -0.56641693  1.06372983 -0.9299981835 species Metamuri
## Oxalsp    1.779301707 -0.67873524 -0.86259033 -1.1192405244 species   Oxalsp
## Seneangu  1.779301328 -0.67873531 -0.86259027 -1.1192403302 species Seneangu
## Ficilate -1.287062602 -1.44717349 -1.59708590  0.4915825996 species Ficilate
## Morequer -2.521173239 -2.50210193  0.19434838  0.2189090948 species Morequer
## Oxaldepr -0.639773100 -1.56294194  1.01549673  0.9358794043 species Oxaldepr
## Phyleric -1.922129081 -2.39221421 -0.72162168  0.4645161239 species Phyleric
## Laurtetr -0.016228516  1.43128002  1.55292320 -0.1369551873 species Laurtetr
## Oxalimbr  0.410214151 -0.23863984  2.03763113 -0.9484655504 species Oxalimbr
## Tracrevo  1.265149444  0.35255185  1.78663721 -2.7664442086 species Tracrevo
## Crasumbe  1.948954694 -0.60485360  0.58409345 -2.5311166913 species Crasumbe
## Gastacin  1.948955015 -0.60485360  0.58409332 -2.5311166536 species Gastacin
## Isolannu  1.914155158  0.18373004  0.73298806 -3.3092476914 species Isolannu
## Colepulc -0.252047295  0.58172450 -1.41239319 -0.3820846218 species Colepulc
## Cynaelli -0.999244573 -1.61563314  1.19138862  1.0082456944 species Cynaelli
## Feliechi -1.990532006 -2.11104512  1.08142116  0.2433387743 species Feliechi
## Searcren  2.615104482 -0.28586420  0.01342299 -0.1523317040 species Searcren
## Carpdeli  0.055784486 -0.28919066 -2.30483027  1.7120775970 species Carpdeli
## Zalucape  2.460824504 -0.23843215  0.17124696  1.5287824956 species Zalucape
## Searlaev -1.924597839 -1.95201347  0.71822442  0.7326805407 species Searlaev
## Zalumari -0.527631515 -1.46744763  1.23344253  1.2234218355 species Zalumari
## Albunels  0.321774785  0.07557859  3.33235520 -1.1596450298 species Albunels
## Chaecamp  0.416083657  0.77931062  1.29493210 -1.9168241372 species Chaecamp
## Rapagill -1.182243592  1.95861934  1.12512207 -1.3370677056 species Rapagill
## Colpcomp  2.319995056  0.40104443  0.59374266 -1.8062128485 species Colpcomp
## Indiglau  1.895583766  0.58773181  0.80414290 -3.6983177882 species Indiglau
## Robsmari  1.895583766  0.58773181  0.80414290 -3.6983177882 species Robsmari
## Seneilic  1.439190314  0.79003312 -0.97896739 -0.9208831971 species Seneilic
## Searglau -2.079933036  1.86457386 -0.14176879 -0.7769208928 species Searglau
## Erucstri -1.892917980  2.44305644  1.26256770  1.8955017491 species Erucstri
## Searpter -1.408887832 -1.42316195 -3.27999636  1.2460716480 species Searpter
## Helipeti  0.034628489  1.49341211  1.67732384  2.4326467516 species Helipeti
## Kedrnana  2.847446453  0.30763192 -0.55803952 -0.7006226205 species Kedrnana
## Passcory -2.233793918  2.38256558 -0.60078363 -1.0025481396 species Passcory
## Pelacapi -2.437794858  2.75053106  0.44368023  1.1312642791 species Pelacapi
## Cussthyr  3.272007297  0.05590154  0.18330927 -0.0121847147 species Cussthyr
## Jamemicr  0.367940910  1.38166708 -3.38366870 -2.2286285667 species Jamemicr
## Lobeance -0.271507548  1.11855622 -3.43993620 -1.7366337226 species Lobeance
## Ericglum -3.254505744 -1.98597444  0.47620265  1.2257466571 species Ericglum
##          weight
## H01a       52.0
## H01b      117.0
## H01c      119.5
## H02a      113.0
## H02b      101.0
## H02c       68.0
## H03a      120.0
## H03b       93.0
## H03c      117.5
## H04a      115.0
## H04b      182.0
## H04c      128.0
## H05a      125.0
## H05b      116.0
## H05c      135.5
## H06a      100.0
## H06b      105.0
## H06c      115.0
## H07a      134.0
## H07b       83.0
## H07c       94.0
## H08a      108.0
## H08b       18.0
## H08c       56.0
## H09a       75.0
## H09b      132.0
## H09c      107.0
## H10a      115.0
## H10b       91.0
## H10c      118.0
## H11a       44.0
## H11b       98.0
## H11c       77.0
## H12a       59.0
## H12b       80.0
## H12c      119.0
## H13a       73.0
## H13b       86.0
## H13c       87.0
## H14a       77.0
## H14b       32.0
## H14c       76.0
## H15a      100.0
## H15b       97.0
## H15c       47.0
## Anthaeth   11.0
## Crasfili   25.0
## Euclrace  427.0
## Heligymn    8.0
## Oleaexas  611.0
## Resteleo  219.0
## Sporvirg   13.0
## Dasisuff   10.0
## Ficiramo   44.0
## Gamocoar   13.0
## Helinudi   74.0
## Helitere   98.0
## Arctpopu   32.0
## Aspaaeth   21.5
## Ehrherec  202.0
## Metamuri  554.0
## Oxalsp      8.0
## Seneangu    1.0
## Ficilate   42.0
## Morequer  113.0
## Oxaldepr    7.0
## Phyleric  112.0
## Laurtetr   69.0
## Oxalimbr   19.0
## Tracrevo    8.0
## Crasumbe    1.0
## Gastacin    5.0
## Isolannu   30.0
## Colepulc  828.0
## Cynaelli    7.0
## Feliechi    2.0
## Searcren   94.0
## Carpdeli   24.5
## Zalucape    1.0
## Searlaev    2.0
## Zalumari    1.0
## Albunels   35.0
## Chaecamp    4.5
## Rapagill   47.0
## Colpcomp    7.0
## Indiglau    0.5
## Robsmari    0.5
## Seneilic   22.0
## Searglau   60.0
## Erucstri   21.0
## Searpter    5.0
## Helipeti    6.0
## Kedrnana  124.0
## Passcory  140.0
## Pelacapi   65.0
## Cussthyr    1.0
## Jamemicr    3.0
## Lobeance    1.0
## Ericglum   26.0

NMDS

##                NMDS1        NMDS2        NMDS3        NMDS4        NMDS5
## H01a     -0.82943737 -0.650899970  0.464708640 -0.276571695 -0.010686920
## H01b     -0.79427016  0.318873538  0.286587431  0.451191349 -0.058441642
## H01c     -0.62309431 -0.588096738  0.111496246  0.223817739  0.016180187
## H02a      0.03738147 -0.740580441  0.203184248  0.099981468 -0.025150737
## H02b     -0.73730358  0.120760116  0.322725965  0.541637223 -0.292835543
## H02c     -0.67851472 -0.322538356 -0.053336488  0.242453507 -0.679772230
## H03a      0.43511838 -0.431413524  0.300993630  0.604695861 -0.049400329
## H03b     -0.53901567 -0.181162993  0.322130662 -0.261243535  0.158151726
## H03c     -0.70099158 -0.416376418 -0.275047116 -0.034882699  0.235639471
## H04a      0.13404619 -0.532493769  0.303148588  0.651267207  0.003100766
## H04b     -0.50040497  0.420339894  0.330036202  0.227353206  0.314360122
## H04c     -0.47232740 -0.156579905 -0.258584678 -0.361138868  0.145653572
## H05a      0.10589163 -0.126082613  0.097787006 -0.175557926  0.735670749
## H05b     -0.38378646  0.339079726  0.304628924  0.050466462 -0.108272433
## H05c     -0.61011215 -0.006277959 -0.659997305  0.025530913 -0.475079260
## H06a      0.57694091 -0.092970025  0.306785221  0.066332656  0.509011661
## H06b     -0.04667000  0.028555114  0.487122031 -0.467118856  0.323645313
## H06c     -0.94744095  0.062437075 -0.449608332  0.049932404 -0.010779292
## H07a      0.59130846 -0.574060074  0.796799028  0.183338507 -0.028638896
## H07b      0.48476078  0.352869136  0.836799779 -0.371896023 -0.059788621
## H07c     -0.17231080  0.039107505 -0.389019913 -0.741287015 -0.022767185
## H08a      0.83875521 -0.160664302 -0.491017120 -0.510327872  0.128492500
## H08b     -0.33686649  0.795941298  0.734932067 -0.001034018 -0.370784338
## H08c     -0.52384587 -0.035563255 -0.060586260 -0.435807095 -0.367542402
## H09a      0.66109534 -0.074479245 -0.005782876 -0.695106673  0.070970884
## H09b      0.03441100  0.520767370  0.301314292 -0.540068702 -0.145983969
## H09c     -0.49245471 -0.446137307  0.079211442 -0.508913404 -0.109554409
## H10a      0.76174340 -0.257499774  0.211408864 -0.361920123  0.296152813
## H10b     -0.07621361  0.593554845  0.273367364 -0.272470093 -0.444765622
## H10c     -0.34030625  0.171862994 -0.303414981 -0.233891505  0.111790391
## H11a     -0.11075613 -0.602099258 -0.072988334 -0.061587578  0.588185246
## H11b      0.38388016  0.423853774  0.092917672 -0.264071517  0.482841945
## H11c     -0.77683735  0.129104251 -0.487911708  0.366301099  0.648847169
## H12a      0.67692222 -0.516050046 -0.089893750 -0.005466775 -0.607261520
## H12b      0.53475914  0.776890810  0.020725965  0.600269947  0.627272102
## H12c     -0.05178732 -0.322923117 -0.911757438  0.698841896  0.537671996
## H13a      0.84637139 -0.415145261 -0.201135725  0.122565799 -0.314615356
## H13b      0.28748510  0.844129455  0.111162124  0.478301449 -0.075088156
## H13c     -0.07240935  0.608018413 -0.701872385 -0.243085004 -0.167966920
## H14a      0.81330904 -0.720001819 -0.201004222  0.352860280 -0.305075415
## H14b      0.45964733  0.712021064  0.188176986  0.669345823 -0.196021405
## H14c      0.41953458  0.402595395 -0.588582812 -0.420731691 -0.358096643
## H15a      0.84586800 -0.385145158 -0.270475035  0.143964124 -0.375153244
## H15b      0.53507292  0.796790044 -0.527306189  0.019294230  0.236737630
## H15c      0.35285452  0.297689511 -0.488827708  0.374435520 -0.510853758
## Anthaeth -0.98541072 -0.780910511  0.530799628 -0.554043680 -0.055191564
## Crasfili -0.95026273  0.004916711  0.435104500  0.432090988 -0.186680704
## Euclrace -0.59168900 -0.252001479 -0.071962364  0.007841455  0.310357544
## Heligymn  0.03894972 -0.803942159  0.772725701  0.141981917 -0.031388633
## Oleaexas -0.53516478 -0.127446885  0.088190814 -0.328724271 -0.068261386
## Resteleo  0.53395601 -0.276632994 -0.076999306  0.495203741 -0.332264932
## Sporvirg  0.68123446 -0.241719211  0.386299143  0.045070654  0.461049858
## Dasisuff -1.01061847  0.300633613  0.429270043  0.820930820 -0.261963148
## Ficiramo  0.10472624  0.819030874  0.228594456  0.813572160  0.144183028
## Gamocoar -0.77785734  0.347011198  0.433890837  0.498725656 -0.247106571
## Helinudi -0.05130886  0.763164293  0.462823105  0.160643292 -0.299538247
## Helitere -0.49949012  0.400749038  0.039418972  0.050906318 -0.286116675
## Arctpopu -0.57842855  0.002665710 -0.471611548 -0.138740898 -0.335600235
## Aspaaeth -0.12482386 -0.555321176  0.160898267 -0.151268310 -0.383886015
## Ehrherec -0.71233905 -0.085892108 -0.244973259 -0.061879018  0.192126451
## Metamuri  0.31471358 -0.133023508  0.418268976 -0.179566927  0.432885836
## Oxalsp   -0.81855293 -0.761992862  0.158258259  0.374335080  0.026295046
## Seneangu -0.81855293 -0.761992862  0.158258259  0.374335080  0.026295046
## Ficilate  0.84063142 -0.583079777 -0.060459234 -0.108839593 -0.016348342
## Morequer  0.88633317 -0.690536347 -0.126174650  0.385062212 -0.481776461
## Oxaldepr  0.23858951 -0.738921985  0.386068103  0.787010613 -0.030884462
## Phyleric  0.77591519 -0.555199608 -0.175118340 -0.106848842 -0.098930455
## Laurtetr -0.11347545  0.519023186  0.633121331 -0.418931517 -0.051248535
## Oxalimbr -0.41418316  0.141709240  0.576096325 -0.117933880  0.100264073
## Tracrevo -0.79874620  0.193159392 -0.193845826  0.346225692 -0.325207751
## Crasumbe -0.89135819 -0.417910709 -0.075706044  0.405503394 -1.104724064
## Gastacin -0.89135819 -0.417910709 -0.075706044  0.405503394 -1.104724064
## Isolannu -0.84767022 -0.218685901 -0.494353596  0.229116105 -0.942994359
## Colepulc  0.28861628  0.167990226 -0.152331792 -0.424480520 -0.025626916
## Cynaelli  0.35528982 -0.630610900  0.428904612  1.053954588 -0.033617116
## Feliechi  0.57161078 -0.558979509  0.427231673  1.011353589 -0.080282380
## Searcren -0.34309088 -0.352282826 -0.478145677  0.046253690  0.600247778
## Carpdeli  0.17295579 -0.147162420 -0.070973291 -0.833366681 -0.062563685
## Zalucape -0.92088582 -0.539496034 -0.390403079 -0.058341300  0.382946791
## Searlaev  0.75822798 -0.848442643 -0.036540423  0.763657829 -0.321684561
## Zalumari  0.17609517 -0.689948480  0.430290431  1.089244146  0.005039175
## Albunels -0.65737715  0.544631482  0.468454827  0.380248148  0.510878757
## Chaecamp -0.35719964  0.603769251 -0.570181385 -0.117536375 -0.121481449
## Rapagill  0.49337516  0.333939143  0.102984525  0.031918274  0.870814673
## Colpcomp -1.11438264  0.054728126 -0.725956554  0.071515512 -0.239316086
## Indiglau -0.80149839 -0.008134308 -0.936803058  0.042700441 -0.772069625
## Robsmari -0.80149839 -0.008134308 -0.936803058  0.042700441 -0.772069625
## Seneilic -0.33210542  0.302200477 -0.628727033 -0.492125396  0.073186349
## Searglau  0.68425947  0.050203895  1.168516308 -0.307297353 -0.080009548
## Erucstri  0.13290557  0.840870162  0.889464902 -0.037214898 -0.310750720
## Searpter  1.00763057 -0.412274763 -0.444585372 -0.479252759 -0.321175448
## Helipeti -0.10012107  0.769064893  0.388018831 -0.455706122 -0.722805763
## Kedrnana -0.40142017  0.101859406 -0.933451962  0.476309785  0.609597728
## Passcory  0.44044628  0.802574703 -0.475975385  0.360578930  0.082707780
## Pelacapi  0.60410939  0.942943193 -0.081887518  0.551009059  0.338208451
## Cussthyr -0.06803249 -0.418409241 -1.294152492  1.168812795  0.873791494
## Jamemicr -0.09512346  0.787805237 -0.996240729 -0.406559573 -0.272969518
## Lobeance  0.55113850  0.521640059 -0.835437015 -0.703673586 -0.581956664
## Ericglum  1.11120857 -0.499029908 -0.383913447  0.240779940 -0.609676004
##            score    label
## H01a       sites     H01a
## H01b       sites     H01b
## H01c       sites     H01c
## H02a       sites     H02a
## H02b       sites     H02b
## H02c       sites     H02c
## H03a       sites     H03a
## H03b       sites     H03b
## H03c       sites     H03c
## H04a       sites     H04a
## H04b       sites     H04b
## H04c       sites     H04c
## H05a       sites     H05a
## H05b       sites     H05b
## H05c       sites     H05c
## H06a       sites     H06a
## H06b       sites     H06b
## H06c       sites     H06c
## H07a       sites     H07a
## H07b       sites     H07b
## H07c       sites     H07c
## H08a       sites     H08a
## H08b       sites     H08b
## H08c       sites     H08c
## H09a       sites     H09a
## H09b       sites     H09b
## H09c       sites     H09c
## H10a       sites     H10a
## H10b       sites     H10b
## H10c       sites     H10c
## H11a       sites     H11a
## H11b       sites     H11b
## H11c       sites     H11c
## H12a       sites     H12a
## H12b       sites     H12b
## H12c       sites     H12c
## H13a       sites     H13a
## H13b       sites     H13b
## H13c       sites     H13c
## H14a       sites     H14a
## H14b       sites     H14b
## H14c       sites     H14c
## H15a       sites     H15a
## H15b       sites     H15b
## H15c       sites     H15c
## Anthaeth species Anthaeth
## Crasfili species Crasfili
## Euclrace species Euclrace
## Heligymn species Heligymn
## Oleaexas species Oleaexas
## Resteleo species Resteleo
## Sporvirg species Sporvirg
## Dasisuff species Dasisuff
## Ficiramo species Ficiramo
## Gamocoar species Gamocoar
## Helinudi species Helinudi
## Helitere species Helitere
## Arctpopu species Arctpopu
## Aspaaeth species Aspaaeth
## Ehrherec species Ehrherec
## Metamuri species Metamuri
## Oxalsp   species   Oxalsp
## Seneangu species Seneangu
## Ficilate species Ficilate
## Morequer species Morequer
## Oxaldepr species Oxaldepr
## Phyleric species Phyleric
## Laurtetr species Laurtetr
## Oxalimbr species Oxalimbr
## Tracrevo species Tracrevo
## Crasumbe species Crasumbe
## Gastacin species Gastacin
## Isolannu species Isolannu
## Colepulc species Colepulc
## Cynaelli species Cynaelli
## Feliechi species Feliechi
## Searcren species Searcren
## Carpdeli species Carpdeli
## Zalucape species Zalucape
## Searlaev species Searlaev
## Zalumari species Zalumari
## Albunels species Albunels
## Chaecamp species Chaecamp
## Rapagill species Rapagill
## Colpcomp species Colpcomp
## Indiglau species Indiglau
## Robsmari species Robsmari
## Seneilic species Seneilic
## Searglau species Searglau
## Erucstri species Erucstri
## Searpter species Searpter
## Helipeti species Helipeti
## Kedrnana species Kedrnana
## Passcory species Passcory
## Pelacapi species Pelacapi
## Cussthyr species Cussthyr
## Jamemicr species Jamemicr
## Lobeance species Lobeance
## Ericglum species Ericglum

Dune transects and ordinations

Prof. Alastair Potts

2026-09-11

Introduction

The Tools

By the end of this practical you should be able to

Generating the ordinations for each method

Interpreting Ordination Axes

PCA

DCA

NMDS

Reporting the Quality of an Ordination

Hints:

What Else Should Be Reported?

Adding Group Structure to Ordinations

PCA

DCA

NMDS

PCA

DCA

NMDS

Exploring plant species in ordinations

PCA 1

PCA Species scores

PCA 2

DCA

DCA species scores

DCA 2

NMDS

NMDS species scores

NMDS 2

Species positions vs. significance in ordinations

Analogy

Understanding Species Coordinates

PCA all species

DCA all species

NMDS all species

Writing Up Your Report

What to Include

Key Reminder

Raw ordination data

PCA

DCA

NMDS