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.
tall 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_whip ~ 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
-2.6752 -0.4688 0.2572 0.7440 2.4073
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) -6.5020723 0.8018151 -8.109 5.10e-16 ***
factor(Class)2 1.1795472 1.0172347 1.160 0.246227
factor(Class)3 2.0205740 1.4088511 1.434 0.151515
Depth 0.1701365 0.0217273 7.831 4.86e-15 ***
I(Depth^2) -0.0006330 0.0001684 -3.759 0.000171 ***
factor(Block)2 2.1135103 0.7460851 2.833 0.004614 **
factor(Block)3 0.5578155 0.9309282 0.599 0.549037
factor(Class)2:Depth -0.0228452 0.0141944 -1.609 0.107518
factor(Class)3:Depth -0.0796149 0.0216159 -3.683 0.000230 ***
Depth:factor(Block)2 -0.0528564 0.0118935 -4.444 8.83e-06 ***
Depth:factor(Block)3 -0.0458373 0.0162593 -2.819 0.004815 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 1277.16 on 922 degrees of freedom
Residual deviance: 724.72 on 912 degrees of freedom
AIC: 746.72
Number of Fisher Scoring iterations: 6
Analysis of Deviance Table
Model: binomial, link: logit
Response: sea_whip
Terms added sequentially (first to last)
Df Deviance Resid. Df Resid. Dev
NULL 922 1277.16
factor(Class) 2 52.31 920 1224.84
Depth 1 391.71 919 833.13
I(Depth^2) 1 33.91 918 799.22
factor(Block) 2 41.53 916 757.70
factor(Class):Depth 2 10.41 914 747.29
Depth:factor(Block) 2 22.57 912 724.72
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.