Spatial Plant Clusters
Current analysis and lists at Google docs:
NOTE - I am still actively trying to decide the best geographic parameters and cutoffs for cluster definitions, so these lists will be changing from time to time for now.
See https://en.wikipedia.org/wiki/Species_distribution_modelling
This is partially reproducing more academic schemes/clusters but I think this will still have value because it leverages this huge new crowd-sourced data set, which is growing by about 2x every year as of 2021. (Plus so far it seems to be hell trying to figure out where/how to access previous information. Scientific publication has its values but accessibility to the non-professional is not among them.)
I am building up quite a catalog of these, still not very well documented but quantitatively valid (they are output from clustering software, not personal lists). I list a few here and most are on Google Doc, indirectly linked above.
Most of these come out of a complete spatial analysis of western US plants (roughly west of Denver), the south half of BC, and a moderate slice of northern Mexico, based on research grade iNaturalist spatial data (so far at a grid resolution of about 4 km). Occasional taxa have a confusing name because the data come from GBIF, which seems to use older taxonomic names.
The lists may exclude taxa you expect to see (mostly when the number of observations is too small), and they may include taxa you did not expect (for example in the Wenatchee Serpentine cluster, Anemone drummondii is not serpentine specific, but it grows well on serpentine in the Wenatchee Mountains). They also may include taxa that are highly correlated with the community, but only over a part of the community range. If the geographic bounds used to do the original graph analysis cut through the range of a taxon, the correlations reported will not account for observations outside those bounds (there might be taxa that have a much broader range, though within the geographic bounds used the correlation is valid). Finally, there is an issue with taxa that are automatically obscured because the reports intentionally introduce random error in their positions.
Edge weight in the correlation graph is defined as 1 / (1 - PearsonCorrelationCoefficient), capped at 100. For example, nearly perfect correlated taxa have a connection (edge) weight of 100, correlation 0.9 gives weight 10.0, correlation 0.75 gives weight 4.0, correlation 0.5 gives weight 2.0, etc.
This will likely be an ongoing project and volunteers to help (especially interpreting what the heck these cluster are or mean) are welcome. I have a ton of data not shown here and am also happy to share software.
calcareous (cedar) glade communities of Tennessee and Kentucky region failed to be useful because the large majority of endemics are listed as endangered and the coordinate uncertainty associated with such observations is much larger than the typical calcareous glade itself. (plus most of them are under buildings now anyway)
Comentarios
Agregar un comentario