Coral Species distribution and Benthic Cover type He’eia HI By: Ashley Fossett
How are coral species correlated with different benthic cover types? Montipora capitata Porites compressa Reef building corals Pocillopora damicornis Leptastrea purpurea Resilient / Successional corals Ho: There is no pattern between coral species and benthic cover type Ha: There is a significant pattern between coral species and benthic cover type
Dataset Description Main Matrix 60 samples and 4 species Samples were taken along a varying gradient of coral cover 4 species identified: %MC Montipora capitata %PC Porites compressa %PD Pocillopora damicornis %LP Leptastrea purpurea Second Matrix 60 samples and 4 Benthic cover types 4 types of Benthic cover: TCC Total Coral Cover Hsub Hard Substrate Rubble Dead Coral/ Rock Piece Sand/Silt Bare ground
Data Processing Outlier Analysis : Same for 1st and 2nd matrix Main Matrix: Species Row Summary: Average Skewness: 1.624 240 cells in main matrix Percent of cells empty = 18.750 Matrix total = 0.59997E+02 Matrix mean = 0.24999E+00 2nd Matrix data: Benthic Cover Row Summary: Average Skewness:1.152 240 cells in main matrix Percent of cells empty = 10.833 Matrix total = 0.60002E+04 Matrix mean = 0.25001E+02 Outlier Analysis : Same for 1st and 2nd matrix No samples were recognized as outliers given cutoff of 2.0 standard deviations from the grand mean.
Screening #2 – Data Summary I do not have outliers in my data but I do have a lot of zeros. I am tying to assume a normal distribution of my species therefore I performed a general relativization and an arcsine transformation. I used an arcsine transformation because I am dealing with percent cover data that range from 0-1 with 1 being 100% of the coral in a survey. Main Matrix: Species Row Summary: Average Skewness: 1.624 240 cells in main matrix Percent of cells empty = 18.750 Matrix total = 0.59997E+02 Matrix mean = 0.24999E+00 Main Matrix: Species Row Summary: Average Skewness: 1.234 240 cells in main matrix Percent of cells empty = 18.750 Matrix total = 0.25585E+01 Matrix mean = 0.10661E-01
Scatterplot Patterns Due to the fact that coral compete for space and the data are comparing percent coral cover, by design PC and MC are negatively correlated. If there is more PC this takes up space for MC However, based on these species making up total coral cover it turns out that MC is negatively correlated with TCC while PC is positively correlated with TCC Whereas the opposite is true for sand/silt substrate
Results of PCA
Results Interpretation correlation matrix (Main) Pearson and Kendall Correlations with Ordination Axes N= 60 Axis: 1 2 3 r r-sq tau r r-sq tau r r-sq tau % MC -.976 .953 -.890 .211 .044 .355 -.018 .000 -.198 % PC .977 .955 .945 .206 .042 -.185 -.017 .000 .144 % PD -.124 .015 -.108 -.803 .644 -.080 .530 .281 .583 % LP -.027 .001 -.116 -.966 .934 -.279 -.224 .050 -.223 correlation matrix (second) Axis: 1 2 3 r r-sq tau r r-sq tau r r-sq tau TCC .598 .357 .513 .337 .114 .039 .099 .010 .102 HSub .065 .004 -.165 -.148 .022 .025 .002 .000 .066 Rubble -.034 .001 .005 -.689 .475 -.318 -.381 .145 -.068 Sand -.723 .522 -.592 -.174 .030 .093 -.037 .001 -.081 Look at the r values ( axis 1 is strongly correlated with %MC (neg.) and %PC(pos.)), while (axis 2 is strongly correlated with PD and LP “neg. correlated”) For the second matrix, (axis 1 is strongly correlated with TCC (pos.) and sand (neg.), while (axis 2 is strongly correlated with rubble (neg.))
Results Interpretation It looks like my data is only correlated with Axis 1. Coefficients of determination for the correlations between ordination distances and distances in the original n-dimensional space: R Squared Axis Increment Cumulative 1 .897 .897 2 .102 .999 3 .000 1.000 Increment and cumulative R-squared were adjusted for any lack of orthogonality of axes. Axis pair r Orthogonality,% = 100(1-r^2) 1 vs 2 0.000 100.0 1 vs 3 0.000 100.0 2 vs 3 0.000 100.0 Number of entities = 60 Number of entity pairs used in correlation = 1770 Distance measure for ORIGINAL distance: Euclidean (Pythagorean)
Discussion These results indicate a positive relationship between my species distribution and benthic cover type Specifically a difference between the two major reef building coral species This multivariate approach described an underlying hypotheses that Montipora capitata are better at dealing with higher levels of sedimentation and a more turbid habitat compared to Porites compressa.
Next Steps I would like to further this investigation and establish a Weighted Average between species and run the analysis again. With this knowledge that MC is more associated with a sandy substrate I hope to identify more patterns between the more resilient coral species. Pocillopora damicornis Leptastrea purpurea Resilient / Successional corals