In my initial exploration of the ESRI spatial statistics website, I focused on tools that might be useful in my proposed research of population structure and behavioral ecology of humpback whales (Megaptera novaeangliae) in Glacier Bay/Icy Strait, Alaska. One objective of my master’s thesis is investigating the mechanisms of population increase within Glacier Bay/Icy Strait, Alaska since the early 1970s/1980s. I was initially struck by the hot spot analysis, thinking it might be informative to visualize habitat use of humpback whales within Glacier Bay/Icy Strait. This region has undergone massive geological change in the past decades and has become deglaciated relatively recently, i.e. over the past 200 years. Visualizing the habitat use (depth, slope, distance from shore, etc.) of the contemporary population of humpback whales in Glacier Bay/Icy Strait might help inform why there has been an increase in abundance in this region. This would be done by importing layers of oceanographic features under humpback whale encounters to detect patterns of habitat use.
Links:
How to do it:
http://www.arcgis.com/home/item.html?id=dea008bcc77d4fd485abdf8121190b82
How it works:
TO DO: After visualizing my humpback whale encounters in ArcGIS, it occurred to me that what appear to be hot spots within Glacier Bay/Icy Strait, might actually be areas of increased field effort. My data was not collected using random transect lines and thus, this is going to complicate any potential hotspot analysis.
Hi Sophie,
I work mostly with human geography type of data, so forgive my ignorance here… in any case: you indicate differences in “field effort” might complicate interpretation of hot spot results. Does this mean that some places have been sampled more than others? If so, this should not create any problems for Hot Spot Analysis. In places with lots of samples, Gi* will produce a result with more information (so you are more confident in your result)… in locations with few samples, it will still produce the best result it can, but it will have less information to work with (so you may be less confident in your result). On the other hand, if the sample is biased from the perspective that only certain types of areas were sampled (places where you would also find LOTs of whales)… the results will still be accurate but they cannot be generalized beyond the certain type of areas sampled (your result shows you hot/cold spots among those places where there are lots of whales… only… you cannot generalize to places you didn’t look). Does that make sense? Hope so.
Very best wishes!
Lauren
Lauren,
Thank you so much for your response! I found it extremely helpful. I’m very new to spatial statistics and this is something that I hadn’t considered. Based on what you said, I feel that I could make these hot spot inferences within Glacier Bay National Park (it has a very extensive, evenly distributed sampling effort) but not to the unsampled regions of the rest of southeastern Alaska, which has a patchier distribution of sampling effort. Does that sound reasonable?
Again, thanks!
Sophie