Statistical appendix for:

Microbial impacts on survival and settlement of coral planulae

Vermeij, et al

Table S1 – Parameter estimations for density and antibiotic effects on pre-settlement survival probabilities of M. capitata planulae. Plotted representations of the best-fit model (parameters and maximum likelihood [ML] are in bold) are presented in Figure 1A.

Parameter constraints / # of est. parameters / (-AMP) / (-AMP) / (+AMP) / (+AMP) / ML
(-AMP) = (+AMP);
(-AMP) = (+AMP) = 0 / 1 / 0.293 / 0 / 0.293 / 0 / -1354.02
(-AMP) = (+AMP);
(-AMP) = 0 / 2 / 0.249 / 0 / 0.249 / 0.002 / -1453.27
(-AMP) = (+AMP);
 (+AMP) = 0 / 2 / 0.576 / -0.035 / 0.576 / 0 / -204.19
(-AMP) = (+AMP);
(-AMP) = (+AMP) ≠ 0 / 2 / 0.471 / -0.002 / 0.471 / -0.002 / -1294.81
(-AMP) = (+AMP) / 3 / 0.872 / -0.037 / 0.872 / -0.001 / -97.53
(-AMP) = (+AMP) = 0 / 2 / 0.016 / 0 / 0.570 / 0 / -278.64
(-AMP) = 0 / 3 / 0.016 / 0 / 0.868 / -0.001 / -208.80
 (+AMP) = 0 / 3 / 0.938 / -0.037 / 0.570 / 0 / -167.22
(-AMP) = (+AMP) / 3 / 0.026 / -0.002 / 0.893 / -0.002 / -193.40
None / 4 / 0.934 / -0.037 / 0.868 / -0.001 / -97.38

Table S2 – Parameter estimations for density and antibiotic effects on post-settlement survival probabilities of M. capitata planulae. Plotted representations of the best-fit model (parameters and maximum likelihood [ML] are in bold) are presented in Figure 1B.

Parameter constraints / # of est. parameters / (-AMP) / (-AMP) / (+AMP) / (+AMP) / ML
(-AMP) = (+AMP);
(-AMP) = (+AMP) = 0 / 1 / 0.873 / 0 / 0.873 / 0 / -200.35
(-AMP) = (+AMP);
(-AMP) = 0 / 2 / 0.860 / 0 / 0.860 / 0.000 / -228.92
(-AMP) = (+AMP);
 (+AMP) = 0 / 2 / 0.940 / -0.000 / 0.940 / 0 / -119.75
(-AMP) = (+AMP);
(-AMP) = (+AMP) ≠ 0 / 2 / 0.971 / -0.000 / 0.971 / -0.000 / -158.06
(-AMP) = (+AMP) / 3 / 0.975 / -0.001 / 0.975 / -0.000 / -70.86
(-AMP) = (+AMP) = 0 / 2 / 0.809 / 0 / 0.938 / 0 / -109.20
(-AMP) = 0 / 3 / 0.809 / 0 / 0.985 / -0.000 / -100.63
 (+AMP) = 0 / 3 / 0.952 / -0.000 / 0.938 / 0 / -78.07
(-AMP) = (+AMP) / 3 / 0.026 / -0.002 / 0.893 / -0.002 / -193.40
None / 4 / 0.952 / -0.001 / 0.985 / -0.000 / -69.50

Table S3 – Parameter estimations for planular survival models for algae x antibiotic factorial treatments. Statistical significance denoted on Figure 2 is based on selection of best-fit model (parameters and maximum likelihood [ML] are presented here in bold).

-algae/ -AMP / -algae/ +AMP / +algae/ -AMP / +algae/ +AMP
Parameter constraints / # of est. parameters / s0 / s1 / s2 / s3 / ML
s0 = s1 = s2 = s3 / 1 / 0.509 / 0.509 / 0.509 / 0.509 / -166.48
s0 = s3; s1 = s2 / 2 / 0.556 / 0.457 / 0.457 / 0.556 / -156.14
s0 = s2; s1 = s3 / 2 / 0.459 / 0.562 / 0.459 / 0.562 / -155.23
s0 = s1; s2 = s3 / 2 / 0.621 / 0.621 / 0.386 / 0.386 / -107.17
s1 = s2 = s3 / 2 / 0.611 / 0.469 / 0.469 / 0.469 / -148.85
s0 = s1 = s3 / 2 / 0.580 / 0.580 / 0.279 / 0.580 / -94.90
s0 = s2 = s3 / 2 / 0.469 / 0.633 / 0.469 / 0.469 / -145.41
s0 = s1 = s2 / 2 / 0.514 / 0.514 / 0.514 / 0.491 / -166.07
s2 = s3 / 3 / 0.611 / 0.633 / 0.386 / 0.386 / -106.89
s1 = s3 / 3 / 0.611 / 0.562 / 0.279 / 0.562 / -93.00
s1 = s2 / 3 / 0.611 / 0.457 / 0.457 / 0.491 / -148.05
s0 = s3 / 3 / 0.556 / 0.633 / 0.279 / 0.556 / -90.54
s0 = s2 / 3 / 0.459 / 0.633 / 0.459 / 0.491 / -144.69
s0 = s1 / 3 / 0.621 / 0.621 / 0.279 / 0.491 / -82.73
None / 4 / 0.611 / 0.633 / 0.279 / 0.491 / -82.45

Table S4 – Parameter estimations for planular settlement models for algae x antibiotic factorial treatments. Statistical significance denoted on Figure 3 is based on selection of best-fit model (parameters and maximum likelihood [ML] are presented here in bold).

-algae/ -AMP / -algae/ +AMP / +algae/ -AMP / +algae/ +AMP
Parameter constraints / # of est. parameters / s0 / s1 / s2 / s3 / ML
s0 = s1 = s2 = s3 / 1 / 0.070 / 0.070 / 0.070 / 0.070 / -133.13
s0 = s3; s1 = s2 / 2 / 0.074 / 0.065 / 0.065 / 0.074 / -132.96
s0 = s2; s1 = s3 / 2 / 0.136 / 0.005 / 0.136 / 0.005 / -87.94
s0 = s1; s2 = s3 / 2 / 0.070 / 0.070 / 0.071 / 0.071 / -133.12
s1 = s2 = s3 / 2 / 0.120 / 0.043 / 0.043 / 0.043 / -122.47
s0 = s1 = s3 / 2 / 0.052 / 0.052 / 0.176 / 0.052 / -120.27
s0 = s2 = s3 / 2 / 0.095 / 0.009 / 0.095 / 0.095 / -115.25
s0 = s1 = s2 / 2 / 0.089 / 0.089 / 0.089 / 0.001 / -113.47
s2 = s3 / 3 / 0.120 / 0.009 / 0.071 / 0.071 / -112.54
s1 = s3 / 3 / 0.120 / 0.005 / 0.176 / 0.005 / -86.44
s1 = s2 / 3 / 0.120 / 0.065 / 0.065 / 0.001 / -109.52
s0 = s3 / 3 / 0.074 / 0.009 / 0.176 / 0.074 / -108.40
s0 = s2 / 3 / 0.136 / 0.009 / 0.136 / 0.001 / -86.46
s0 = s1 / 3 / 0.070 / 0.070 / 0.176 / 0.001 / -105.55
None / 4 / 0.120 / 0.009 / 0.176 / 0.001 / -84.97

Table S5 – Parameter estimations for planular survival models for comparison across four algal species. Statistical significance denoted on Figure 4 is based on selection of best-fit model (parameters and maximum likelihood [ML] are presented here in bold).

Ulva / Acantophora / Pterocladiella / Sargassum
Parameter constraints / # of est. parameters / s0 / s1 / s2 / s3 / ML
s0 = s1 = s2 = s3 / 1 / 0.327 / 0.327 / 0.327 / 0.327 / -129.00
s0 = s3; s1 = s2 / 2 / 0.352 / 0.302 / 0.302 / 0.352 / -127.98
s0 = s2; s1 = s3 / 2 / 0.325 / 0.329 / 0.325 / 0.329 / -128.99
s0 = s1; s2 = s3 / 2 / 0.558 / 0.558 / 0.121 / 0.121 / -47.98
s1 = s2 = s3 / 2 / 0.588 / 0.249 / 0.249 / 0.249 / -97.38
s0 = s1 = s3 / 2 / 0.410 / 0.410 / 0.099 / 0.410 / -93.26
s0 = s2 = s3 / 2 / 0.263 / 0.529 / 0.263 / 0.263 / -108.85
s0 = s1 = s2 / 2 / 0.391 / 0.391 / 0.391 / 0.144 / -107.83
s2 = s3 / 3 / 0.588 / 0.529 / 0.121 / 0.121 / -47.39
s1 = s3 / 3 / 0.588 / 0.329 / 0.099 / 0.329 / -77.68
s1 = s2 / 3 / 0.588 / 0.302 / 0.302 / 0.144 / -88.59
s0 = s3 / 3 / 0.352 / 0.529 / 0.099 / 0.352 / -85.86
s0 = s2 / 3 / 0.325 / 0.529 / 0.325 / 0.144 / -97.79
s0 = s1 / 3 / 0.558 / 0.558 / 0.099 / 0.144 / -47.06
None / 4 / 0.588 / 0.529 / 0.099 / 0.144 / -46.47

Table S6 – Parameter estimations for planular settlement models for algae x antibiotic factorial treatments. The two most statistically supported models are presented in bold italics. Note that based on the assumption of equal Bayesian prior probabilities of each model, the relative fit of the two models cannot be statistically discriminated from one another.

Ulva / Acantophora / Pterocladiella / Sargassum
Parameter constraints / # of est. parameters / s0 / s1 / s2 / s3 / ML
s0 = s1 = s2 = s3 / 1 / 0.022 / 0.022 / 0.022 / 0.022 / -31.94
s0 = s3; s1 = s2 / 2 / 0.014 / 0.030 / 0.030 / 0.014 / -30.86
s0 = s2; s1 = s3 / 2 / 0.011 / 0.033 / 0.011 / 0.033 / -29.82
s0 = s1; s2 = s3 / 2 / 0.045 / 0.045 / 0.003 / 0.003 / -23.58
s1 = s2 = s3 / 2 / 0.024 / 0.022 / 0.022 / 0.022 / -31.92
s0 = s1 = s3 / 2 / 0.031 / 0.031 / 0.001 / 0.031 / -27.05
s0 = s2 = s3 / 2 / 0.009 / 0.064 / 0.009 / 0.009 / -24.61
s0 = s1 = s2 / 2 / 0.028 / 0.028 / 0.028 / 0.005 / -29.76
s2 = s3 / 3 / 0.024 / 0.064 / 0.003 / 0.003 / -21.95
s1 = s3 / 3 / 0.024 / 0.033 / 0.001 / 0.033 / -26.88
s1 = s2 / 3 / 0.024 / 0.030 / 0.030 / 0.005 / -29.68
s0 = s3 / 3 / 0.014 / 0.064 / 0.001 / 0.014 / -22.59
s0 = s2 / 3 / 0.011 / 0.064 / 0.011 / 0.005 / -24.36
s0 = s1 / 3 / 0.045 / 0.045 / 0.001 / 0.005 / -23.04
None / 4 / 0.024 / 0.064 / 0.001 / 0.005 / -21.42