This simprof plot is the diversity of an ecosystem sampled monthly (one year) used Primer version 6. i may wonder if any one help me to interpret and provides some documents to do the same.
Sileesh,
These two papers may help you understand SIMPROF better, hope this helps.
Tom
+The Simprof Plot documents that the data set has the typical pattern associated with the majority of the iterations lying within the confidence limits (aka reported as expected in PRIMER). These data when further processed with nMDS ordination, or ANOSIM are reasonable representations of the Bray Curtis Similarity matrix.
Also explained in the PRIMER user manual as well as Changes in Marine Communities
Clarke et al. (2008) described similarity profile analysis (SIMPROF) as a new method of exploratory data analysis that employs null hypothesis testing to detect structure in ecological communities. A similarity profile is constructed from a set of species abundance and composition data by first creating a similarity matrix using an ecologically appropriate resemblance measure (e.g, the Bray-Curtis metric). The lower tridiagonal of this matrix is then unwrapped as a vector and sorted by magnitude. This sorted list of similarities provides a profile of the structure underlying the observed data and is visualized using a simple line plot. An iterative permutation procedure, based on randomly shuffling the original raw data, is then used to generate a mean permuted similarity profile, which represents the profile expected under the null model. The congruence between the observed similarity profile and the null model is measured using the pi statistic, as the sum of the absolute differences between corresponding elements of the two profiles. The pi statistic is then assessed via a permutation test, if it is statistically significant the null hypothesis that no multivariate structure exists within the data is rejected at the appropriate alpha level.
Stated another way, similarity profile analysis examines whether the similarities observed in the data are smaller and/or larger than those expected by chance. These conditions are visualized by plotting a similarity profile over the corresponding mean permuted profile. Sections of the plot where the observed profile extends beyond the 99% confidence envelope of the mean permuted profile correspond to similarities that are either larger or smaller than those expected under null conditions—this suggests the presence of true structure within the data.
The value of SIMPROF is realized when it is used to objectively identify the members of “real” groups present in the results returned from a classical hierarchical agglomerative clustering method. This provides a compelling alternative to more traditional methods that rely on subjective assignment of arbitrary cut-off levels. While the SIMROF method was originally derived to identify structure within ecological communities, if paired with an appropriate resemblance measure it can be used to examine a variety of other data types. Software implementing the SIMPROF method include: (1) Fathom Toolbox for Matlab, (2) clustsig package for R, and (3) PRIMER.
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