## How do you read an NMDS plot?

As a rule of thumb, an NMDS ordination with a stress value around or above 0.2 is deemed suspect and a stress value approaching 0.3 indicates that the ordination is arbitrary. Stress values equal to or below 0.1 are considered fair, while values equal to or below 0.05 indicate good fit.

**What do NMDS plots show?**

The goal of NMDS is to represent the original position of data in multidimensional space as accurately as possible using a reduced number of dimensions that can be easily plotted and visualized (like PCA).

**Is NMDS an ordination?**

Nonmetric multidimensional scaling (NMS, also abbreviated NMDS and MDS) is an ordination technique that differs in five important ways from nearly all other ordination methods. Most ordination methods calculate many axes, but they display only a few of those for reasons of practicality.

### What are the axes in NMDS?

The axis are essentially arbitrary, but display your data in a way which best represents their dissimilarity. Points on the graph that are closer together are more similar (less dissimilar).

**What is the difference between MDS and PCA?**

PCA is just a method while MDS is a class of analysis. As mapping, PCA is a particular case of MDS. On the other hand, PCA is a particular case of Factor analysis which, being a data reduction, is more than only a mapping, while MDS is only a mapping.

**What is NMDS1 and NMDS2?**

The axis NMDS1 and NMDS2, show the range of the distances reached between seasons in the three landscapes. Seasons are arranged so that the distances between them are as close to the real differences between the mean relative volume (%) of fruits, vertebrates and invertebrates consumed in each landscape.

## What is the difference between NMDS and PCoA?

NMDS is an iterative method which may return different solution on re-analysis of the same data, while PCoA has a unique analytical solution. The number of ordination axes (dimensions) in NMDS can be fixed by the user, while in PCoA the number of axes is given by the dataset properties (number of samples).

**What is the difference between MDS and NMDS?**

Multidimensional scaling (MDS) is a means of visualizing the level of similarity of individual cases (think e.g. sites) of a multivariate dataset. Benefits of NMDS: Rank-order (non-metric) approach well-suited for certain types of data (particularly counts of abundance).

**What does Bray Curtis measure?**

Named after J. Roger Bray and John Thomas Curtis, the Bray-Curtis Dissimilarity is a way to measure the dissimilarity between two different sites. It’s often used in ecology and biology to quantify how different two sites are in terms of the species found in those sites.

### What do PCoA axes mean?

PCoA starts by putting the first point at the origin, and the second along the first axis the correct distance from the first point, then adds the third so that the distance to the first 2 is correct: this usually means adding a second axis.

**What is the difference between MDS and Nmds?**

**What is the difference between PCA and MDS?**

## What is NMDS and how can it be used?

NMDS is a robust technique. It can: Figure 1: Schematic of a non-metric multidimensional scaling plot. Points represent objects. Objects that are more similar to one another are ordinated closer together. The axes are arbitrary as is the orientation of the plot. Stress values should always accompany an NMDS ordination.

**What is NMDS in gradient analysis?**

NMDS is an indirect gradient analysis approach which produces an ordination based on a distance or dissimilarity matrix. NMDS attempts to represent, as closely as possible, the pairwise dissimilarity between objects in a low-dimensional space. First two columns are direction cosines of the vectors, and r2 gives the squared correlation

**How do you know if an NMDS ordination is arbitrary?**

After an initial ordination, examine the stress values generated by the algorithm. As a rule of thumb, an NMDS ordination with a stress value around or above 0.2 is deemed suspect and a stress value approaching 0.3 indicates that the ordination is arbitrary.

### Are the axes of the NMDS plot arbitrary?

The axes are arbitrary as is the orientation of the plot. Stress values should always accompany an NMDS ordination. As NMDS is an iterative algorithm, it can quickly become computationally demanding for large data sets.