Analysis of Hawaiian Invertebrate Communities With Respect to Seagrass Sediment Cores - Dariyus Z Kabraji MARS 6300 Project Seagrasses Halophila hawaiiana Halophila decipiens Marine plants from the Alismatales family Primary producers in marine ecosystems They are engineering species, i.e. capable of altering their habitat They attract a variety of species, offer protection from predators, food for herbivores, support epiphytes

Images obtained from the UH Botany Department Given Data Seagrass sediment cores collected from eight different locations on Oahu. Core samples were chilled in formalin to preserve the species. Sediment core types affected by seagrass presence, or absence. Bare sediment selected as control. Species data: 66 species (quantitative) from 8 locations, 2 seagrass species per location. Environmental variables: 6 sediment textural groups-presence (categorical) from 8 locations , 2 seagrass species per location. Kaneohe Bay Sandbar Kaneohe Bay Sampan Channel

Maunalua Bay 1 Waikiki Wailupe Maunalua Bay 2 Kahala Maunalua Bay 3 Objective Characterize the Hawaiian seagrass infaunal invertebrate community Confirm that the presence of seagrasses affect the abundance and diversity of associated invertebrates by comparing invertebrates within sediment core samples beneath the seagrass species to samples from a bare habitat. Hypotheses:

Abundance of invertebrate species will vary according to the textural group of the sediment cores. There will be significant evidence of competition between the worms and crustacean species. Data Matrix Locations: Sp = Kaneohe Bay Sampan Channel Sp = Kaneohe Bay Sandbar M1 = Maunalua Bay Niukuki M2 = Maunalua Bay Paiko M3 = Maunalua Bay Kuliouou beach park Wk = Waikiki Wa = Wailupe beach park KH = Kahala First attempt: arranged a full matrix with genus and species only.

Suffix to locations: h = Halophila hawaiiana Sediment cores d = Halophila decipiens Sediment cores b = bare surfaces Data Summary 1056 cells in main matrix Percent of cells empty = 69.223 Matrix total = 0.41117E+06 Matrix mean = 0.38936E+03

Variance of totals of species = 0.43892E+09 CV of totals of species = 336.29% Skewness Kurtosis Averages: 2.612 7.354 Data Summary Outliers: 3 -----------------------------------------------------------ENTITY RANK NAME AVERAGE STANDARD DISTANCE DEVIATIONS -----------------------------------------------------------1 Leptochelia dubia 0.97566 2.09819 65 Paragrubia vorax 0.79381 -2.02055 66 Munna acarina

0.78825 -2.14649 ------------------------------------------------------------ Direct NMS-Texture groups Compared full species abundance with sediment core consistencies observed in various locations: STRESS IN RELATION TO DIMENSIONALITY (Number of Axes) -------------------------------------------------------------------Stress in real data Stress in randomized data 50 run(s) Monte Carlo test, 50 runs ------------------------- ----------------------------------Axes Minimum Mean Maximum Minimum Mean Maximum p -------------------------------------------------------------------1

24.309 40.296 54.006 23.995 44.873 54.006 0.0392 2 13.586 14.882 36.596 12.554 16.939 36.592 0.1569 -------------------------------------------------------------------- Direct NMS-Texture groups

Compared full species abundance with sediment core consistencies observed in various locations: MANTEL TEST RESULTS: Mantel`s asymptotic approximation method -----------------------------------------------------------0.163693 = r = Standardized Mantel statistic 0.683858E+02 = Observed Z (sum of cross products) 0.666572E+02 = Expected Z 0.229742E+01 = Variance of Z 0.151572E+01 = Standard error of Z 0.114046E+01 = t Ho: no relationship between matrices 0.254457 = p (type I error) ------------------------------------------------------------ Data Transformations As per the instructions in data manipulation and transformation for count data, a constant (1) can be added so fx = log(0+1) The logarithmic transformation f(x) is conducted since there are

large amounts of zero values and a high degree of variation between the samples. Outliers: 2 ENTITY AVERAGE STANDARD RANK NAME DISTANCE DEVIATIONS ------------------------------------------------------------------1 Leptochelia dubia 0.59748 3.10979 2 Armandia intermedia 0.55879 2.06024

------------------------------------------ Data Modification Relativization by maximum conducted on column species General Relativization conducted as a test run in case there is considerable noise generated by the rarer species in relativization by maximum. Since the data is not normal, conducting NMDS. Data Modification (General Relativization) STRESS IN RELATION TO DIMENSIONALITY (Number of Axes) -------------------------------------------------------------------Stress in real data Stress in randomized data 50 run(s) Monte Carlo test, 999 runs ----------------------------------------------------------Axes Minimum Mean Maximum Minimum Mean Maximum p

----------------------------------------------------------------------------------------------1 36.101 47.926 53.863 34.577 49.721 54.010 0.0050 2 20.246 22.723 36.590 20.070 26.046 36.640 0.0030 -----------------------------------------------------------------------------------------------p = proportion of randomized runs with stress < or = observed stress i.e., p = (1 + no. permutations <= observed)/(1 + no. permutations) Conclusion: a 2-dimensional solution is recommended. Species Diversity H. hawaiiana only H. decipiens only Bare sediment only Amphliochidae sp. B Oligochaeta sp. B

Cirratulidae sp. A Elasmopus spp. Spionidae sp. A Amphipoda sp. A Eursiroides diplonyx Isopoda sp. A Photis spp. Smaragdia bryanae Phoxichillidiidae sp. A

Aspidosiphon spp. Sipuncula sp. C Sipuncula sp. B Halophila hawaiiana did not support greater species biodiversity, even though it is an endemic species Relation between Crustaceans and Worm Species Split the matrix into crustacean species data and annelid, phoronid, nemerted, sipunculate data. 2 matrices, 33 species each

STRESS IN RELATION TO DIMENSIONALITY (Number of Axes) -------------------------------------------------------------------Stress in real data Stress in randomized data 50 run(s) Monte Carlo test, 50 runs ------------------------- ----------------------------------Axes Minimum Mean Maximum Minimum Mean Maximum p -------------------------------------------------------------------1 26.453 40.827 54.006 26.787 46.109 54.005 0.0196

2 14.478 15.893 34.146 9.233 17.271 35.349 0.2941 -------------------------------------------------------------------p = proportion of randomized runs with stress < or = observed stress i.e., p = (1 + no. permutations <= observed)/(1 + no. permutations) Relation between Crustaceans and Worm Species

MANTEL TEST RESULTS: Mantel`s asymptotic approximation method ----------------------------------------------------------0.385575 = r = Standardized Mantel statistic 0.694247E+02 = Observed Z (sum of cross products) 0.673680E+02 = Expected Z 0.627768E+00 = Variance of Z 0.792318E+00 = Standard error of Z 0.259588E+01 = t Ho: no relationship between matrices 0.009572 = p (type I error) --------------------------------------------------------

Further Analysis Obtain the original datasets of leaf biomass and rhizome biomass. Conduct correlation studies between them, and ordination with the species data to determine species abundance with respect to seagrass abundance. Also conduct MRPP with species data against environmental variables. Data source Matthew Spielmans Thesis: Benthic Community Structure of Hawaiian Seagrass Habitats (2011).