Cool stuff whimbrelbirder! When I looked at iNat data across Alaska boroughs (the equivalent of counties), here’s a twist that I found related to the relationship of iNat observations and people within a spatial unit at that scale:
More observers & more observations per borough → more taxa recorded on iNat. In general, there’s a positive relationship between the number of taxa recorded in boroughs on iNaturalist and the number of observers (R2=0.47) and observations (R2=0.87). For every additional observer in an area, roughly about 13 additional observations and 1.5 additional taxa are expected to be recorded on iNaturalist. The boroughs with the most observers? Anchorage (1,023 iNat observers; Alaska’s largest population center with almost three times the residents than the next biggest borough), followed by Kenai (910 observers). The boroughs with the most observations? Sitka (38,505 observations), followed by Kenai (12,526 observations). The boroughs with the most taxa recorded? Same pattern as observations: Sitka (2,740 unique taxa), followed by Kenai (1,680 unique taxa).
More people living or visiting a borough for nature → more iNat observers. What explains variation in iNat activity across Alaska boroughs? I spent a bit of time compiling datasets on factors that I suspected might be important: population size, area, visitor volume, visitor volume engaged in nature activities (including wildlife viewing, birdwatching, hiking), broadband service1. Of those, the two factors that seem the most predictive2 in terms of explaining # of iNat observers are (a) borough population, and (b) number of visitors that engaged in a wildlife viewing activity in the borough3. Multiple regression analysis indicated that those two predictors explained a decent 84% of the variance in the number of observers between boroughs. So, there are more iNaturalist observers in boroughs with more residents and more visitors that want to see wildlife – makes sense, right? This appears true even when controlling for other factors.
More people living or visiting a borough ≠ more iNat observations…. except…. . In contrast to iNat observers, the same pattern does not hold true for iNat observations when looking across all boroughs. In fact, none of the factors I looked at significantly explained differences in observations between boroughs EXCEPT when I dropped a single borough from the analysis. When I looked at all boroughs except for Sitka, the importance of population size and wildlife-viewing visitors re-emerged as significant variables, with a simple model explaining 75% of observation variance4. So, what makes Sitka special?
more at the journal post