Structure comparison and evenness test of biological communities: Several platform-independent computational tools


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Structure Comparison and Evenness Test of Biological Communities

Several Platform-independent Computational Tools

By W. J. Zhang

The user manual guide and suggested citation of this page:
Zhang W. J. 2024. Structure comparison and evenness test of biological communities: Several platform-independent computational tools. Computational Ecology and Software, 14(2): 119-136
Also, click here to download the corresponding offline tool.

CommStructComp: Between-community Structure Comparison

Choose a distance (or correlation) measure:
Euclidean Distance Manhattan Distance Pearson Correlation Point Correlation Quadratic Correlation Jaccard Coefficient

α value (Confidence level=(1-α)×100%):
0.01 0.05

Total number of species (s):

Number of samples (m) in community A:

Number of samples (n) in community B:

Number of randmizations (200, 500, 1000, etc.):

Data of two communities:

1         8    0    1    2    1        11   5    1   32    7   1    0   31
         2         0    3    0    0    0         0    0    1    4    1    3    5    1
         3         2    2    1    3    1         0    0    0    0    0    1    2    0
         4         1    0    0    0    0         0    0    0    0    0    1    0    0
         5         1    0    0    0    0         0    0    0    0    0    0    0    0
         6         0    0    0    0    0         0    0    0    0    0    0    0    0
         7         0    0    0    0    0         0    0    0    0    0    0    0    0
         8         0    1    1   16   13        7   12   3    8   43  29   38   22
         9         6    9   20   10   3         7   18  12   5   26  11   10    3
        10         0    3    0    0    2         4    9    4    3    7    8    7   11
        11         0    1    0    1    1         4    8    1    9    5    3    4   11
        12         2    1    1    0    4         1    1    3    0    1    3    2    0
        13         0    0    0    0    0         0    0    0    2    0    2    2    3
        14         1    0    0    0    1         0    1    0    5    0    1    1    3
        15         0    0    0    0    0         0    0    0    0    0    1    0    2
        16         1    7    0    1    1         2    0    0    0    1    0    3    2
        17         5    2    3    2    2         0    0    1    1    0    1    0    0
        18         0    0    0    0    0         0    0    0    0    0    1    0    1
        19         0    0    0    1    0         0    0    1    0    1    0    0    0
        20         0    0    0    0    0         0    0    0    0    0    0    0    1
        21         0    0    0    0    0         0    0    0    0    0    0    0    1
        22         0    0    0    0    0         0    0    0    0    0    0    0    1
        23         0    0    0    0    0         0    0    1    0    0    0    0    0
        24         0    0    0    0    0         0    0    0    0    0    0    0    0
        25         0    0    0    0    0         0    0    0    0    0    0    0    0
        26         0    0    0    0    0         0    0    0    0    0    0    0    0
        27         0    0    0    0    0         0    0    0    0    0    0    0    0
        28         0    0    0    0    0         0    0    0    0    0    0    0    0
        29         0    0    0    0    0         0    0    0    0    0    0    0    0
        30         0    0    0    0    0         0    0    0    0    0    0    0    0
        31         6   11   7   12   18      84   82  46  133  97  127  65  132
        32        15  15   26  24   55      30   15   4  256   7   50  135  121
        33         2    0    0    1    1        10   0   12   41   17  0    1   28
        34         0    0    0    1    1        10   0    0    14   32  4   24   10
        35        10   0    1    0    0         7    0    4    1    1    5    6    4
        36         0    1    1    4    1         1    1    1    1    0    5    2    2
        37         0    0    0    0    0         0    1    0    5    2    2    1    0
        38         0    0    0    0    0         1    0    0    0    0    0    0    9
        39         0    0    0    0    0         0    0    0    0    0    0    3    0
        40         1    2    3    1    8         0    0    1    0    0    0    0    0
        41         0    2    4    4    0         0    0    0    0    0    0    0    0
        42         0    0    0    0    0         0    0    0    0    0    0    0    0
        43         0    0    0    0    0         0    0    0    0    0    0    0    0
        44         0    0    0    0    0         0    0    0    0    0    0    0    0
        45         0    0    0    0    0         0    0    0    0    0    0    0    0
        46         0    0    0    0    0         0    0    0    0    0    0    0    0

Reset and enter or copy s lines of space delimited data into this area.
The 1st column is species IDs. Each ID represents an unique species.
The followed m columns (samples) are number of individuals of each species for the community A.
The last n columns (samples) are number of individuals of each species for the community B.

Results:

Traditional parametric statistical methods such as pairwise data comparison and multivariate sample difference testing require data to conform to a normal distribution. However, species - abundance relationships in nature are often severely skewed and often log-normal, or even a negative exponential distribution. Therefore, in community comparison, traditional parametric statistical methods cannot be used. The randomization methods are a type of non-parametric statistical methods, which are especially suitable for community comparison and difference testing. This tool uses a randomization test. In this tool, correlation based distance measures (including Jaccard coefficient) represent the trend similarity of abundance across species, while distance measures (including Euclidean distance and Manhattan distance) mainly represent the total difference in total species.

User manual guide:
Zhang W. J. 2024. Structure comparison and evenness test of biological communities: Several platform-independent computational tools. Computational Ecology and Software, 14(2): 119-136
Zhang W. J. 2011. A Java program for non-parametric statistic comparison of community structure. Computational Ecology and Software, 1(3): 183-185

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CommSpComp: Between-community Comparison of Species Composition

Choose a distance measure:
For interval values:
Euclidean Distance Manhattan Distance Chebyshov Distance Pearson Correlation Angular Cosine Correlation
For nominal values:
Contingency Coefficient I Contingency Coefficient II Contingency Coefficient III Contingency Coefficient IV

p value (Confidence level=(1-p)×100%):
0.01 0.05

Number of species (s):

Number of randmizations (200, 500, 1000, etc.):

Data of two communities:

Reset and enter or copy s lines of space delimited data into this area.
The 1st column is species IDs. Each ID represents an unique species.
The 2nd column is species abundance (number of individuals, plant coverage, etc.) of the community A.
The 3rd column is species abundance (number of individuals, plant coverage, etc.) of the community B.

Results:

Traditional parametric statistical methods such as pairwise data comparison and multivariate sample difference testing require data to conform to a normal distribution. However, species - abundance relationships in nature are often severely skewed and often log-normal, or even a negative exponential distribution. Therefore, in community comparison, traditional parametric statistical methods cannot be used. The randomization methods are a type of non-parametric statistical methods, which are especially suitable for community comparison and difference testing. This tool uses a randomization test.

User manual guide:
Zhang W. J. 2024. Structure comparison and evenness test of biological communities: Several platform-independent computational tools. Computational Ecology and Software, 14(2): 119-136
Zhang W. J. 2011. A Java algorithm for non-parametric statistic comparison of network structure. Network Biology, 1(2): 130-133

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CommEvenTest-I: Randomization Test of Community Evenness

Choose a diversity index:
Simpson Index Shaanon-Wiener Index McIntosh Index Berger-Parker Index Hurlbert Index

α value (Confidence level=(1-α)×100%):
0.001 0.01 0.05

Number of species (m):

Number of randmizations (200, 500, 1000, etc.):

Data of species abundance:

Reset and enter or copy m lines of space delimited data into this area.
The 1st column is species IDs. Each ID represents an unique species.
The 2nd column is species abundance (number of individuals, plant coverage, etc.).

Results:

This tool uses a randomization test.

User manual guide:
Zhang W. J. 2024. Structure comparison and evenness test of biological communities: Several platform-independent computational tools. Computational Ecology and Software, 14(2): 119-136

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CommEvenTest-II: Ewens-Caswell Test of Community Evenness

α value (Confidence level=(1-α)×100%):
0.001 0.01 0.05

Number of species (m):

Data of species abundance:

Reset and enter or copy m lines of space delimited data into this area.
The 1st column is species IDs. Each ID represents an unique species.
The 2nd column is species abundance (number of individuals, plant coverage, etc.).

Results:

If the community passes the Ewens-Caswell test, it follows Ewens-Caswell neutrality model. The community is even and no dominant species exits.

User manual guide:
Zhang W. J. 2024. Structure comparison and evenness test of biological communities: Several platform-independent computational tools. Computational Ecology and Software, 14(2): 119-136
Zhang W. J., Zheng H. 2012. A program for statistic test of community evenness. Computational Ecology and Software, 2(1): 80-82

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