What predicts your state's iNaturalist participation rate?

Of course we’re talking about population-wide trends here, but in the case of ME, you nailed it.

I love nature, and I grew up:

  1. In a liberal-leaning family
  2. On a property with lots of natural land (non-agricultural, non-developed)
  3. In a rural area

So you have accurately predicted my participation in iNaturalist.

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My impression of birders and naturalists generally is that they tend to be from the suburban middle-class sort of demographic. People who have the spare time and income to dedicate to weird hobbies (including spending a lot of time on the internet), combined with relatively easy access to natural areas.

Participation might be low in Vermont because in Canada and the northern states most plants and wildlife aren’t really active yet in late April.

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i think if you frame this as “participation”, you missing some of the story if you don’t look at observations vs observers. when you break things down this way, i think you can see the Vermont situation is related to a ton of observers (Wyoming, too, although I would guess it’s more tourism-related here), while California, Texas, DC, etc. have a lot of observations per observer.

State Observations Observers Population Area (sq km) Observations per Observer Diff vs Avg 50 States + DC Obervations per 10000 Pop Diff vs Avg 50 States + DC Observers per 10000 Pop Diff vs Avg 50 States + DC
Alabama 284,670 9,504 5,157,699 135,927.46 29.95 2.6 551.9 (37.9) 18.4 (3.1)
Alaska 100,452 4,177 740,133 1,704,340.35 24.05 (3.3) 1,357.2 767.4 56.4 34.9
Arizona 449,906 16,059 7,582,384 296,192.06 28.02 0.7 593.4 3.5 21.2 (0.4)
Arkansas 170,123 6,518 3,088,354 138,040.34 26.10 (1.3) 550.9 (39.0) 21.1 (0.5)
California 3,216,327 89,101 39,431,263 423,781.19 36.10 8.7 815.7 225.9 22.6 1.0
Colorado 392,715 18,115 5,957,493 270,036.30 21.68 (5.7) 659.2 69.4 30.4 8.8
Connecticut 172,634 8,128 3,675,069 14,354.23 21.24 (6.1) 469.7 (120.1) 22.1 0.6
Delaware 78,446 3,511 1,051,917 6,407.43 22.34 (5.0) 745.7 155.9 33.4 11.8
District of Columbia 78,085 4,602 702,250 177.25 16.97 (10.4) 1,111.9 522.1 65.5 44.0
Florida 1,048,846 41,532 23,372,215 170,497.52 25.25 (2.1) 448.8 (141.1) 17.8 (3.8)
Georgia 357,761 16,678 11,180,878 154,516.78 21.45 (5.9) 320.0 (269.8) 14.9 (6.6)
Hawaii 155,026 6,738 1,446,146 26,951.13 23.01 (4.3) 1,072.0 482.2 46.6 25.0
Idaho 116,439 5,365 2,001,619 216,187.34 21.70 (5.7) 581.7 (8.1) 26.8 5.2
Illinois 467,960 17,690 12,710,158 150,228.81 26.45 (0.9) 368.2 (221.6) 13.9 (7.6)
Indiana 231,645 10,034 6,924,275 94,261.72 23.09 (4.3) 334.5 (255.3) 14.5 (7.1)
Iowa 94,508 4,886 3,241,488 145,713.81 19.34 (8.0) 291.6 (298.3) 15.1 (6.5)
Kansas 99,190 4,513 2,970,606 213,658.58 21.98 (5.4) 333.9 (255.9) 15.2 (6.4)
Kentucky 163,162 7,551 4,588,372 104,853.22 21.61 (5.7) 355.6 (234.2) 16.5 (5.1)
Louisiana 185,294 6,989 4,597,740 136,012.22 26.51 (0.8) 403.0 (186.8) 15.2 (6.4)
Maine 212,436 9,951 1,405,012 91,575.13 21.35 (6.0) 1,512.0 922.2 70.8 49.3
Maryland 505,892 16,342 6,263,220 32,242.18 30.96 3.6 807.7 217.9 26.1 4.5
Massachusetts 601,460 22,485 7,136,171 27,287.26 26.75 (0.6) 842.8 253.0 31.5 9.9
Michigan 465,910 17,281 10,140,459 250,340.13 26.96 (0.4) 459.5 (130.4) 17.0 (4.5)
Minnesota 324,821 13,309 5,793,151 225,204.49 24.41 (2.9) 560.7 (29.1) 23.0 1.4
Mississippi 95,794 4,003 2,943,045 125,916.78 23.93 (3.4) 325.5 (264.3) 13.6 (8.0)
Missouri 244,877 10,368 6,245,466 180,898.11 23.62 (3.7) 392.1 (197.7) 16.6 (5.0)
Montana 90,478 4,730 1,137,233 380,774.01 19.13 (8.2) 795.6 205.8 41.6 20.0
Nebraska 61,101 3,125 2,005,465 200,521.70 19.55 (7.8) 304.7 (285.1) 15.6 (6.0)
Nevada 105,080 5,820 3,267,467 287,385.86 18.05 (9.3) 321.6 (268.2) 17.8 (3.8)
New Hampshire 185,375 7,613 1,409,032 24,213.98 24.35 (3.0) 1,315.6 725.8 54.0 32.5
New Jersey 337,135 13,737 9,500,851 22,617.31 24.54 (2.8) 354.8 (235.0) 14.5 (7.1)
New Mexico 214,553 8,007 2,130,256 315,620.57 26.80 (0.6) 1,007.2 417.4 37.6 16.0
New York 776,472 33,383 19,867,248 141,556.66 23.26 (4.1) 390.8 (199.0) 16.8 (4.8)
North Carolina 724,453 28,827 11,046,024 139,914.75 25.13 (2.2) 655.8 66.0 26.1 4.5
North Dakota 19,753 1,186 796,568 182,937.79 16.66 (10.7) 248.0 (341.8) 14.9 (6.7)
Ohio 627,136 21,354 11,883,304 116,260.31 29.37 2.0 527.7 (62.1) 18.0 (3.6)
Oklahoma 172,603 6,774 4,095,393 181,550.50 25.48 (1.9) 421.5 (168.4) 16.5 (5.0)
Oregon 531,826 19,189 4,272,371 254,577.90 27.72 0.4 1,244.8 655.0 44.9 23.4
Pennsylvania 650,366 26,732 13,078,751 119,388.34 24.33 (3.0) 497.3 (92.5) 20.4 (1.1)
Rhode Island 67,906 3,672 1,112,308 4,002.83 18.49 (8.9) 610.5 20.7 33.0 11.5
South Carolina 192,713 10,976 5,478,831 83,006.68 17.56 (9.8) 351.7 (238.1) 20.0 (1.5)
South Dakota 38,381 2,217 924,669 199,703.63 17.31 (10.0) 415.1 (174.7) 24.0 2.4
Tennessee 381,854 15,979 7,227,750 109,620.75 23.90 (3.5) 528.3 (61.5) 22.1 0.5
Texas 2,325,667 56,738 31,290,831 698,275.66 40.99 13.6 743.2 153.4 18.1 (3.4)
Utah 191,518 9,531 3,503,613 220,326.77 20.09 (7.3) 546.6 (43.2) 27.2 5.6
Vermont 206,912 7,908 648,493 24,927.65 26.16 (1.2) 3,190.7 2,600.8 121.9 100.4
Virginia 606,727 23,765 8,811,195 110,595.70 25.53 (1.8) 688.6 98.8 27.0 5.4
Washington 662,962 23,751 7,958,180 184,577.07 27.91 0.6 833.1 243.2 29.8 8.3
West Virginia 127,592 5,384 1,769,979 62,909.47 23.70 (3.7) 720.9 131.0 30.4 8.9
Wisconsin 378,283 13,311 5,960,975 169,549.04 28.42 1.1 634.6 44.8 22.3 0.8
Wyoming 69,125 4,214 587,618 253,391.55 16.40 (11.0) 1,176.4 586.5 71.7 50.2
20,060,350 733,353 340,110,988 9,823,808 27 - 589.8 - 21.6 -

because of the way folks learn about the platform through their networks, i don’t think the distribution you’re describing would be random.

i once posed a question about why Russia seems to have such a high level of research grade observations, and one of the responses i got makes that sort of point:

i think the above statement is supported by the numbers. although Russia does have fewer observations per capita than the US, the users it does have do make more observations per observer, and power users do seem to use the web rather than an app to make the bulk of their observations. so the typical Russian observer (based on how they use the platform) is very different from the typical US observer.

USA Verifiable Observations 2024

Observations % of All Observers % of All Obs per Observer population Observations per 10000 Pop Observers per 10000 Pop
All 20,059,814 100.0% 523,082 100.0% 38.35 340,110,988 589.8 15.4
iOS 9,272,209 46.2% 358,924 68.6% 25.83 272.6 10.6
Android 4,445,684 22.2% 116,333 22.2% 38.22 130.7 3.4
Seek 688,057 3.4% 43,196 8.3% 15.93 20.2 1.3
iOS + Android + Seek 14,405,949 71.8% 505,906 96.7% 28.48 423.6 14.9
Next 82,463 0.4% 872 0.2% 94.57 2.4 0.0

Russia Verifiable Observations 2024

Observations % of All Observers % of All Obs per Observer population Observations per 10000 Pop Observers per 10000 Pop
All 2,061,765 100.0% 14,281 100.0% 144.37 145,975,300 141.2 1.0
iOS 208,379 10.1% 3,981 27.9% 52.34 14.3 0.3
Android 567,465 27.5% 7,910 55.4% 71.74 38.9 0.5
Seek 12,621 0.6% 804 5.6% 15.70 0.9 0.1
iOS + Android + Seek 788,464 38.2% 12,435 87.1% 63.41 54.0 0.9
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For Russia, somewhere in the Forum is a comment - all university students have to do a biology course - and feeds into iNat obs.

PS it was a comment from fff but she is no longer active on the forum.

i don’t think that’s right. there are millions of university students in Russia, and even if only a fraction of them are taking a biology course at any given time, there’s simply not enough Russian observers in the data to support that. there is some discourse about how the Russian iNat community has grown here: https://forum.inaturalist.org/t/inaturalist-is-now-the-second-largest-contributor-of-gbif-mediated-data-for-russia/10039.

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This is an interesting discussion. Although, remembering the North Carolina map, it doesn’t correlate perfectly. Here, for reference, is that map:

Now, the mountains along the western edge include Great Smoky Mountains National Park and the Blue Ridge Parkway, which are major ecotourism draws – the Smokies, especially, are promoted for their extreme tree diversity. So that may fit with the tourism factor being discussed. It is possible that the Outer Banks may experience this effect, too, although beach tourism is less tightly coupled to nature tourism (not all beachgoers are there to look at organisms).

Similarly, the inner coastal plain, although rural, has extensive agricultural areas such as cotton, corn, soybean, and tobacco, and not a lot of public land. This would explain its extensive belt of dark purple color on the map.

The part that needs some explanation is the “island” of green in the center. This is the “Triangle Area” – Raleigh - Durham - Chapel Hill and environs. It is a major urban center, which would suggest fewer opportunities to observe wild organisms; but conversely, it is also the most highly educated part of the state, as the “Research Triangle” attracts large numbers of people in STEM careers and is home to prestigious universities such as Duke. This suggests that it would be interesting to parse out the relative influence of each of Bradley’s factors, and the extent to which there are interaction effects.

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I can confirm that the Minnesota Master Naturalist program often promotes iNaturalist and that volunteers can count identifying as volunteer time. I’ve actually never thought about if observations would count, but the requirements are fairly flexible (especially post-covid.)

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I think the biodiversity and rate of endemism definitely has some influence on the statistics. I know that at least for myself, the more species in an area the more observations I will make. At least for me, my species repeat percentage remains relatively constant no matter where I observe, with a exponential curve for species in an area and number of species with 2 or more observations. But that is also just my style of using the platform.

Bonap is only for plants but these maps are very helpful in visualizing the potential influence, and could be an entire thread of it’s own

Density Gradient of Native Vascular Plant Species per 10,000 km²

The Wyoming effect shows up again here: US Counties (in blue) with extensive floristic surveys/inventories plus those that house significant plant collections (herbaria/museums)

Density Gradient of “Endemic” (Range Limited <50,000 km²) Plant Species per 10,000 km²

Have fun with the rest of the maps:
http://bonap.org/2015_SpecialtyMaps/Density%20Gradient%202015/Density%20Gradient%202015.html
http://bonap.org/2015_SpecialtyMaps/State%20Flora%20Similarity%202015/State%20Flora%20Similarity%202015%209-21-15.html
http://bonap.org/2015_SpecialtyMaps/

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I make up 10% of the Iowa observations for 2024!

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Hey, where’s DC? I’m not making another observation until we’re included—No iNaturalization without Representation!

Okay okay, I’m not making observations because it’s 15° F outside right now, haha. Great post!

(Though maybe DC would be an interesting data point: highly urban/liberal, younger than average, racially/ethnically diverse, etc.)

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That is not correct. Only Natural Sciences students study biology in universities and even they mostly use iNat to outsource their task of plant IDing. Like there’s time of the year when my feed is literally flooded with hasty photos of plants and herbariums from under the desk.

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I’d be down with participating, assuming that the fields in question have local ownership. The bigger problem might be in recruiting landownwers and gaining permission, but I’ve spent a lot of time fantasizing about driving down farm roads to the house or barn, introducing myself, and asking about the possibility of photographing odes around the irrigation ditches and stock ponds.

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I wonder what sort of correlation there is between biodiverstity, iNat observations and agricultural land use. I might hypothesize that broad-acre cropping has poor biodiversity, open range ranching is better and mixed agriculture is the best.

From my experience living in a farming area there’s been falling biodiversity in broad acre farming due to the vast amounts of chemical use, as well as lack of permission to walk the acres looking for observations.

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Here is another interesting statistic from Australia. The two states (NSW and WA) with the highest wheat production also have the lowest observations per capita and the two states (NT and TAS) with no wheat production have the highest observations per capita.

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I am a casual observer living in a rural small town (pop approx. 1,500. 25 min. from closest city). I grew up in southern MN near the twin cities until high school. There was a significant interest in many students to attend school with a focus in environmental majors. There were many parks, as well as nature trail/hiking locations. Sidewalks were common and wooded areas, lakes, ponds, rivers were all easily accessible. I moved to and now reside in Alabama.

Sidewalks outside of major cities are rare. Getting to rural or untouched wooded areas can be difficult or dangerous to reach. Large acreage is more often protected with fencing or off limits to the public.

Our local major city is just now investing in large parks for the public as well as trails.

It is easier for me to go out of my way on a dirt road to make observations, but that is time consuming and difficult with the large family and lifestyle I have.

More often than not I am restricted to my back yard or the local cemetery for making observations.

This is a very interesting subject as well as data. This definitely needs to be a subject matter that is expanded upon. I would love to see more data in the following months that can be compared and built upon.

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thank you for the detailed analyses. I think iNaturalist will be a stronger organization because of the detailed look at variables at play. It speaks to the dynamics of observations in a demographic and geographic lens. But also to learn of the “observations per observer” factor in a given state. I was also good to get a refresher course on scatterplots and coefficient of determination (R squared) {OLS} - back to the graduate school days - a long time ago…but I have to say the visual output was awesome - and gotta love the maps for showing the outcomes.

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Three thoughts, regarding the CNC peak:

  • CNC was started in CA as a competition between LA and SF, so there has been longer participation, and a greater element of competitiveness.

  • CA, obviously, has more cities, which each have much greater populations than any in VT (or even the entire state.)
    The largest city in VT, Burlington, has a pop. around 45,000.
    The capital, Montpelier, has a pop. around 8,000.
    The total pop. of VT is around 650,000.

  • It’s barely Spring in Vermont in April, so there is not as much to observe. Bare twigs, lichens, and dead plants or emerging shoots are hard to identify, insects are largely dormant, many birds have not returned, and it’s not uncommon to have snow.

And yet, despite the long, cold winters, we are a mighty force on iNaturalist, as illustrated by the per-capita participation statistics that originally inspired this thread!

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I live in Rutherford County, which is the pale county, wider at the north than the south, on the border with South Carolina between the dark gray-blue Cleveland County on the east and the medium-dark gred Polk and Henderson counties on the west. I haven’t gone to the Blue Ridge Parkway to observe, though I’ve gone there to travel (less likely since Helene destroyed the road to the Hickory Nut Gap mountain pass). Most of my observations are either at home or at survey sites. My latest posted obs (I’ve since photoed a spider but haven’t gotten it from the camera) is a tree with a burl at or near a site I’ve finished surveying.

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