I have a point dataset for sea turtles. Each point represents a single trawl where 0-10 turtles were collected. There are 4500+ points, most of which have 0 catch. The study area encompasses the southeast. We want to know if 1.) there is clustering of turtles and 2.) if there is clustering of the high catch numbers. We want to know this for the overall area and by region (there are four smaller regions). 1.) Would Moran's I and Hot Spot Analysis be the best tools in the spatial stats toolset to answer these questions?

We tried aggregating the data into 1 x 1 min grids, but when we ran the 'Incremental Spatial Autocorrelation' the Z score never peaked and kept going up and up. We ran it again on the

individual points, and got a peak. 2.) Is it appropriate to run either of these tools on incident data or would it be better to try to find a finer scale on which to aggregate?

Some of the Hot Spot Analysis information I read suggested that for datasets with 3000+ features, it would be advisable to construct a spatial weights matrix file. 3.) How is this better than choosing one of the other spatial relationships listed (e.g. fixed distance)?

Thanks!!

Jessica B.

We tried aggregating the data into 1 x 1 min grids, but when we ran the 'Incremental Spatial Autocorrelation' the Z score never peaked and kept going up and up. We ran it again on the

individual points, and got a peak. 2.) Is it appropriate to run either of these tools on incident data or would it be better to try to find a finer scale on which to aggregate?

Some of the Hot Spot Analysis information I read suggested that for datasets with 3000+ features, it would be advisable to construct a spatial weights matrix file. 3.) How is this better than choosing one of the other spatial relationships listed (e.g. fixed distance)?

Thanks!!

Jessica B.

Interesting research!

Just curious, how did you decide where to trawl? Are the locations based on a random sampling scheme? I ask, because if there are any biases in your sampling scheme (you only collected turtles where it was convenient, or where you knew you would find them, etc... vs systematically, or using some kind of random sampling scheme), this may impact how you can interpret your results.

I'm also curious about what motivates your questions:

Is there clustering of turtles?

Is there clustering of high catches?

How is knowing that information helpful to your broader research (I ask because it is interesting to me, but also because sometimes it impacts how you set your data up for analysis)?

When you say "Is there clustering of turtles?" I'm wondering how that differs from "Is there clustering of high catches?" Are you looking at two different datasets? Are you considering presence/absense (rather than the number of turtles found at each point) for the "clustering of turtles" part of the analysis?

I look forward to learning more about your research and will happily help if I can.

Best wishes,

Lauren

Lauren M. Scott, PhD

Esri

Geoprocessing, Spatial Statistics