Hi,

I model emergence of seedling counts (sp: spruce) in four canopy openings
created by a bark beetle calamity (random factor opening). Two openings were
fenced and two were not fenced (factor fence). Within openings plots were
placed in a stratified random manner to sample two different orographic
features: plateau and sinkhole (factor relief) and two positions within
canopy opening  (factor location). Sampling was repeated after seven years
(factor year). I sampled also several covariates (c1: rockiness; c2: ground
vegetation coverage).

The total dataset consist of: 2(fence)*2(relief)*2(location)*2(year)*30 =
480 plots.

 

I applied a negative binomial model:

nbm.sp <- glm.nb(sp  ~  fence  + relief + location + year+c1 +c2, link =
"log", data = krese2) Results seem OK, but I'm aware of pseudoreplication.

 

Therefore, I applied a mixed negative binomial model:

mnbm.sp <- glmmadmb(sp ~ fence  + relief + location + year + location:year +

                      (1 | opening), family="nbinom", data = krese2) 

 

Results are similar compared to the first model, with slightly larger std.
errors.

I understand that 4 openings are at the lower limit for calculation of
random effects.

Do the results below look OK?

Is this a correct approach? Namely, there is a fixed factor "fence"
connected to openings:

table(krese2$fence, krese2$opening)

         opening

         a   b   c  d

fenced   0   0 120 120

nonfenc 40 200   0   0

 

Call:

glmmadmb(formula = sp ~ fence  + relief + location + year + location:year +

                      (1 | opening), data = krese2, family = "nbinom")

AIC: 2933.7

Coefficients:

                Estimate Std. Error z value Pr(>|z|)

(Intercept)   1.588      0.194    8.20  2.4e-16 ***

reliefsink    0.243      0.170    1.43  0.15350

fencefe       0.488      0.211    2.31  0.02082 *

locationedge  0.785      0.172    4.56  5.0e-06 ***

year2013     -0.408      0.118   -3.46  0.00054 ***

reliefsink:locationedge   -0.541      0.240   -2.26  0.02413 *

Number of observations: total=480, opening=4 Random effect variance(s):

Group=Odd

            Variance StdDev

(Intercept)  0.02702 0.1644

Negative binomial dispersion parameter: 0.66844 (std. err.: 0.048389)

Log-likelihood: -1458.86

 

Any help would be greatly appreciated.

 

Best regards,

Jurij


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