What I did on my summer vacation.... learned (more) R? (last update)

Our final meeting will be on June 28, and the topic is Occupancy Models. I know this is of great interest to students (and faculty) who do research with animals.  However, can it also be of interest to us plant people? 
Imagine you are interested in characterizing seedlings densities of Bertholletia excelsa (Brazil nut ). You lay out four 9 ha plots, and sub-sample in smaller, 25m x 25m plots, enumerating the seedlings you find. However, you are deep in the Amazon, in thick rainforest, with occasional dense patches of bamboo. The forest floor is a mosaic of vegetation types, and you often are faced with a sea of plants. The seedlings you are looking for are <1 m tall, their leaves are alternate, simple, entire (or crenate), oblong, 20–35 cm (when mature).  And... they look nearly identical to many other species (e.g., Couratari tauari , a species in the same family as Brazil nut and one which is far more common in this region). This is the situation I found myself in a few years ago.  I was lucky to be accompanied by some of the best técnicos in the state of Acre.  But even so, was the data 'perfect'?  When we found zero seedlings, can we be certain there was not one layered under other vegetation?  And when we came back the next year to a plot where we recorded 3 seedlings in the previous year, but we only found 2,  could we be certain that there was mortality? As the surveys were repeated for 5 consecutive years, we realized our data was not perfect, especially as we noted B. excelsa's uncanny ability to re-sprout after being seemingly broken beyond repair. 
Occupancy models were developed to solve the problems created by imperfect detectability.  This week, we will get a short introduction and learn about some techniques to use R for these kinds of analyses.  Notes are here.