# Through murky waters: conservation implications from evaluating the drivers of diversity and abundance on coral reef communities in Cambodia



### Description of the data and file structure



Written and compiled by Fiona Chong (f.chong@leeds.ac.uk) on 3rd July 2026.



This folder contains the data (.csv) and code (.R) to accompany the manuscript “Through murky waters: Conservation implications from evaluating the drivers of diversity and abundance on coral reef communities in Cambodia”.



### Files and variables



**envvar.csv** (90 observations, 18 variables: KTA8 and KTA9 have the same lat/long, so only 90 entries despite 91 sites). This file contains the summaries (max, min, mean and standard deviation) of kd490, a proxy for turbidty, SST (sea surface temperature) and chla (chlorophyll a  concentration from January 2004-2014, across our 90 unique lat/longs).



\-          Location



\-          Survey.site



\-          Lat (decimal degree latitude)



\-          Long (decimal degree longitude)



\-          Category (shore category: offshore or nearshore)



\-          siteID (Location\_Survey.site)



\-          kd490



	o   \_max



	o   \_min



	o   \_mean



	o   \_sd



\-          SST



	o   \_max



	o   \_min



	o   \_mean



	o   \_sd



\-          Chla



	o   \_max



	o   \_min



	o   \_mean



	o   \_sd



**summary\_metadata.csv** (91 observations, 12 variables). This file contains the Location, siteID, PCA axes scores, shore category, protection status, MPA zonation designations, lat/long, field survey dates, survey water depth and underwater visibility of the survey day



\-          Location



\-          siteID



\-          PC1 (principal component analysis axis 1 scores)



\-          PC2 (principal component analysis axis 2 scores)



\-          Category (shore category, offshore or nearshore)



\-          Protection (Yes/No)



\-          MPA Zoning (Conservation, Fish refugia, Multiple-use, Non-enforced, Protected, Recreation, or NA)



\-          Lat (decimal degree latitude)



\-          Long (decimal degree longitude)



\-          Survey Date (DD/MM/YYYY)



\-          Depth\_m (depth in metres)



\-          Visbility\_m (visibility in metres)



**fish\_multivariate.csv** (91 observations, 69 variables (site meta data and 62 taxa))



**benthic\_multivariate.csv** (91 observations, 36 variables (site meta data and 29 taxa))



**inverts\_multivariate.csv** (91 observations, 25 variables (site meta data and 16 taxa))



**maindf.csv** (91 observations, 15 variables)



\-   Location



\-   siteID



\-   PC1 (principal component analysis axis 1 scores)



\-   PC2 (principal component analysis axis 2 scores)



\-   Category (shore category, offshore or nearshore)



\-   Protection (Yes/No)



\-   MPA Zoning (Conservation, Fish refugia, Multiple-use, Non-enforced, Protected, Recreation, or NA)



\-   HC: hard coral cover (0-1)



\-   Fish\_simpson: Fish Simpson’s diversity index (0-1)



\-   Fish\_sp\_abun: Fish species (taxa) abundance



\-   Fish\_total\_abun: Fish total abundance (number of fish in total)



\-   Invert\_simpson: Invertebrates Simpson’s diversity index (0-1)



\-   Invert\_sp\_abun: Invertebrates species (taxa) abundance



\-   Invert\_total\_abun: Invertebrates total abundance (number of invertebrates in total)



\-   Total\_site\_biomass: parrot fish and grouper biomass in grams

### 

### Code/software



**glmm\_r2.R**: the R script needed to create figures 4, 5 and 6. All GL(M)M model statistics, including Table 1, Tables S13-15, and residuial test plots Figures S4-7. It calls the data file 'maindf.csv'.



**dbrda\_r2.R**: the R script needed to create Figure 3 and the test statistics (Tables S4-12), it calls the data files: fish\_multivariate.csv (91 observations, 69 variables); benthic\_multivariate.csv (91 observations, 36 variables); inverts\_multivariate.csv (91 observations, 25 variables).