The seafloor-character map, GLMs, and the Marine Geospatial Ecology Tool (MGET; <http://mgel.env.duke.edu>)
in ArcGIS were used to develop predictive probability maps of occurrence per 12 sq m of seafloor for selected invertebrate
taxa. The 12 sq m area was calculated by multiplying the average width of the video images by the average distance
covered during the 10-second samples. The seafloor-character map provided the habitat class data.
Short sea pen
taxa~Class + Depth + I(Depth^2) + Block + Class:Depth + Depth:Block # Class + Depth + I(Depth^2) + Block + Class:Depth + Depth:Block tryCatch(taxa39.glm <- glm(taxa~Class + Depth + I(Depth^2) + Block + Class:Depth + Depth:Block, family=binomial(link="logit"), data=taxa.df),
warning = function(x) { output.df[39,"flag"] <<- 1 },
finally = taxa39.glm <- glm(taxa~Class + Depth + I(Depth^2) + Block + Class:Depth + Depth:Block, family=binomial(link="logit"),
data=taxa.df)
)
summary(taxa39.glm)
MODEL SUMMARY:
==============
Call:
glm(formula = sea_pen ~ factor(Class) + Depth + I(Depth^2) + factor(Block) + factor(Class):Depth + Depth:factor(Block), family = binomial(link="logit"), data = na.omit(d))
Deviance Residuals:
Min 1Q Median 3Q Max
-1.4645 -0.7480 -0.3860 0.9540 2.9356
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) -3.138e+00 6.630e-01 -4.733 2.21e-06 ***
factor(Class)2 -9.053e+00 3.949e+00 -2.293 0.0219 *
factor(Class)3 -1.622e+01 1.872e+03 -0.009 0.9931
Depth 1.337e-01 2.207e-02 6.059 1.37e-09 ***
I(Depth^2) -1.420e-03 1.907e-04 -7.446 9.63e-14 ***
factor(Block)2 -4.692e-01 5.494e-01 -0.854 0.3930
factor(Block)3 -5.054e+00 9.788e-01 -5.163 2.43e-07 ***
factor(Class)2:Depth 1.005e-01 4.916e-02 2.045 0.0409 *
factor(Class)3:Depth -1.080e-02 3.493e+01 -0.000309 0.9998
Depth:factor(Block)2 2.188e-02 8.514e-03 2.570 0.0102 *
Depth:factor(Block)3 9.206e-02 1.755e-02 5.246 1.56e-07 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 1097.53 on 922 degrees of freedom
Residual deviance: 861.56 on 912 degrees of freedom
AIC: 883.56
Number of Fisher Scoring iterations: 16
Analysis of Deviance Table
Model: binomial, link: logit
Response: sea_pen
Terms added sequentially (first to last)
Df Deviance Resid. Df Resid. Dev
NULL 922 1097.53
factor(Class) 2 63.96 920 1033.57
Depth 1 15.64 919 1017.93
I(Depth^2) 1 78.00 918 939.92
factor(Block) 2 44.71 916 895.21
factor(Class):Depth 2 6.68 914 888.53
Depth:factor(Block) 2 26.97 912 861.56
resample to 10 meters
Krigsman, L.M., M.M. Yoklavich, E.J. Dick, and G.R. Cochrane (2012) Models and maps: predicting the distribution of corals and other benthic macro-invertebrates in shelf habitats. Ecosphere 3:1-16.