I’ve spent some time refining projects whose borders represent some notable former territories and empires. I find it both fun and amusing (“how would these empires compare with the n° observations next to large modern countries if they still existed today?”), but also insightful from an anthropological perspective, as iNat activity highly correlates with population density, GDP per capita, and HDI, as well as the degree of cooperation with the US and western tourist arrivals. I use iNat maps regularly to get insight into these metrics, but it is even more interesting to compare the figures with historical empires and see how they played a role in countries’ development. For example, the former territory of the Holy Roman Empire is one of the densest observation regions in Europe, reflecting both population density and development.
In the case of former Yugoslavia, you can clearly see how Croatia and Slovenia are much denser that the rest of the territory, indicating the long trend of higher GDP per capita in those countries compared to the rest of the Balkans, and the reason they were the first to declare independence in the 90s.
See the full list here (it took some time to be precise with subdivisions (like in the case of the Roman Empire!), but it is not entirely full-proof for all projects, so do note suggestions and fixes):
Roman Empire | Holy Roman Empire | Austria-Hungary | USSR | British Empire | Spanish Empire | Ottoman Empire | Mongol Empire | Yugoslavia | and maybe a few more to come…
And my other projects: https://www.inaturalist.org/journal/marinolinic/107652-marinolinic-s-projects
That’s so cool!! And really interesting!
Inca, Maya, Aztec, Olmec, Wari, etc empires would be interesting to see, as well as some of the pre-colonial African empires.
East and West Germany would be interesting.
I think I want to be more selective about these projects yet to not overwhelm with links, but I’ll do an analysis right now.
Looking at this picture, you don’t quite notice a huge discrepancy, and when we look at the data:
We see that East Germany (excl. Berlin) is actually overrepresented in the German iNat dataset, with the exception of Thuringia and Saxony-Anhalt.
It’s interesting to think about why that is. It could be that being more empty and having more natural as opposed to urban landscape, East German residents either encounter more organisms or are encouraged to visit nature more often. It could also be that having an older demographic leads to a higher per capita number of observations (which is unintuitive, but a lot of the most active users are retired). It also seems likely that East Germany has caught up culturally, but lags behind economically.
There are two extremely active users in Saxony (and one in Berlin) who may somewhat skew the statistics.
Brandenburg and Mecklenburg-Vorpommern probably have tourism effects (low population density, visitors from Berlin and other parts of Germany).
Biogeographically there are probably some interesting differences in what species are most common in former East vs. former West Germany. The Harz Mountains near the East-West border create distinct ecological regions on either side and I know of a number of species where the range borders run through former East Germany.
Very creative use of the platform, nice work!
Two quick thoughts:
- Determining the borders of historical empires (especially as you go further back in time) will never be an exact exercise, as borders were always changing (you’d have to pick one specific moment in each empire’s history to be precise) and not necessarily defined to the same extent as they may be nowadays in the first place.
- East Germany is only overrepresented relative to its population, but in terms of surface area it’s actually severely underrepresented (therefore data skew may be explained by people being more likely to upload nature observations in less densely populated areas, as you suggested.
@schoenitz this conversation had inspired me to take a few hours to learn how to do this in QGIS. The map represents areas where there are fewer or more observations than expected relative to population density.
Very interesting, thank you. So there’s a clear gradient but not an obvious correlation with the historic GDR/FRG boundary. I suppose it shows that it has been 35 years. France is surprising though.
Just curiosity – what are the values behind that color scale?
There’s 100 classes here, spaced with natural breaks / Jenks. I manually made 4 around the middle white.
For non-scientists for example the green in Switzerland is more than expected? Or less?
The red along North African coast?
It is above average, yes. Green means there are more observations per person in that hexagon.
What I essentially did was take a map of population density and iNaturalist data from GBIF, convert them into the same projection, create a grid where each hexagon takes the mean value (density) of both population and iNaturalist observations within it, and then subtract population density from observation density, getting values anywhere from -1 to 1, where red is below 0, and green is above 0.
I manually calculated observations per person right now in this table:
Some values are unintuitive given the map, and part of that is that when I was making the color classes, I didn’t generate them linearly. This was because a lot of values were extreme, especially outside Europe. So you have a more granular picture for the less intense area in either direction, but the extremes are not as obvious. Notice just how low Morocco is—compared to that, all of Europe is super dense.
But that also means that you can’t quite tell that Denmark actually has 3x as many observations as Switzerland per person, or that France has just a little more than Germany (clearly because of the many more tourists to the southeast and Paris!! XD). I presume that this is because iNaturalist activity is more centralized in these countries. We can notice that some of those central regions in France are half as much as the national average per person in this table. Norway is just a little higher per person than Germany, as most of it is just under 0, but most hexagons are probably very close to 0 and it’s another case of centralization.
I’ll get back to this project some day in the future and do a better map.
OK that answers my remaining questions, thanks! 0.1 obs/person is really much higher than I’d have expected.
Interesting to pair your - green for tourists in mountains and on beaches, or in cultural cities - with https://forum.inaturalist.org/t/locals-and-tourists-on-inaturalist-a-data-visualization-project/68982
Thank you so much for this map! This is incredibly interesting and exactly what I was looking for.
And here I tend to think of the Roman Empire as fairly late! A bit of background in Biblical history will do that – Nebuchadnezzar’s vision of the statue represents a sequence from Babylonia, Medo-Persia, Alexander the Great, to the Roman Empire last of all. Of course the Babylonian Empire itself absorbed and expanded on the earlier Assyrian Empire.
