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Showing content with the highest reputation on 08/01/2023 in all areas

  1. It’s a Eurasian Collared-Dove. You can see the black collar in the photo.
    8 points
  2. Got my best photo of a Wrentit to date on Saturday. It was very briefly visible nearly free of obstruction on a cliffside as we walked by.
    7 points
  3. I honestly thought I had some better pictures of them. This picture is by far my favorite though. Farmer Mockingbird, working hard in the rain. https://macaulaylibrary.org/asset/550806421
    6 points
  4. Okay, so I’ve been thinking about data quality and coverage patterns a lot lately. Felt like starting a discussion though I won’t be surprised if no one responds. First of all, I want to say that I think eBird is an excellent resource both for birders and for researches and for those who manage conservation efforts. Comparing eBird data to iNaturalist data, I think eBird data must be way better. One of the fundamental issues with iNaturalist is that it collects presence/absence data but not relative abundance data. The other issue - and this is a big one - is that it requires observations to be photographed. This leads to major biases in the data, since certain species are much more difficult to photograph than others. The result - small birds flitting around way up in a tree get ignored, but oh! Look at that perched Bald Eagle over there posing for a pic. But eBird is not without its issues. Mainly, I think that large and easily detectable species are over represented in the data, while smaller less detectable species are underrepresented by comparison. A great example of this in my area would be Golden Eagles and Oak Titmice in the Interior Coast Range of California. Golden Eagle, when soaring, can be visible from a mile away. So if you are anywhere within a one-mile-radius circle of that Golden Eagle, chances are you’ll detect it. Meanwhile, there may be dozens and dozens of Oak Titmice in that same area, but only the ones you pass close by are detected. So, you end up with checklists that have like 5-10 Golden Eagles (probably the same 2 or 3 highly detectable birds seen repeatedly) and only have 5-10 Oak Titmice (even though there are probably many more in the general area that went undetected). Obviously Oak Titmice are actually more numerous, but since the data is biased by detectability, the true relative abundance is hard to figure out. Perhaps a bigger data quality issue is chasing rare birds. Simply put the mob mentality and fear of missing out that birders have leads to over-reporting of rare birds relative to common ones. So how can these issues be rectified? I think part of the responsibility falls on us, the users, and part of the responsibility falls on eBird. As eBird users, I think we should be less conservative when counting or estimating common species, especially those that are less detectable. Perhaps in some cases it is better to err on the side of being liberal than conservative with counts. Be conservative with the big super detectable stuff, but liberal with the smaller less detectable stuff. And then chasing rare birds - I hesitate to condemn it as I’ve done plenty of it. But maybe try to minimize it? At the end of the day your list size doesn’t matter as much as the quality of the data. Anyone have anything to add? Agree/disagree? Other issues I didn’t mention? Other methods for improving our data quality as users? Want to defend iNat?
    4 points
  5. I think you've left out a third group that bears some of the responsibility: the researchers using the data. Ebird may not be a good way to calculate the relative number of Golden Eagles and Oak Titmice. But it can be useful for for estimating whether there are more or less Golden Egles or Oak Titmice present in a specific time span. A good scientist should thoroughly understand how the data is produced and what its limits are.
    4 points
  6. Agree wholeheartedly. However, I don’t fully grasp wanting to report 10 Oak Titmice if you detected 7 for sure. I see where your conjunctivitis from with that though. EBird wants us to report everything we saw and heard, not everything that we knew was there but didn’t detect. Heck, every checklist would be a lot higher species count wise if that were the case. Bird places that aren’t birded often. Go on eBird and enter a common bird in your area. See where there are gaps in the data where it hasn’t been reported. If house finch hasn’t been reported at a spot in my area, nothing has. Find a park or something in that area and go. Discover new places. Don’t chase every rarity. Don’t only go to a place and bird the best area there. There is a hotpsot by me that is one of, if not the top birded hotspots in the state. However, hardly anybody checks the back half of the place. Only the front 7 ponds are checked frequently. The back 4 are often completely ignored. Bird underbirded sites. Spend a longer time at a hotpsot, see how many birds you can find. Spend less time a hotpsot, see how many birds you can find. Think outside the box.
    4 points
  7. All of these are Barn Swallows, mostly young ones. I'm not sure what the topmost bird is, perhaps a Cliff, it seems to have a dark throat and white forehead, but I'm not totally sure.
    4 points
  8. Hi Neighbor!! 🙂I appreciate your help, and Alex's input too! I snapped this photo right before dark, and then had to do some adjustments for the lighting. It's not the best exposure, and the detailing is minimal; even so, I think we can feel pretty comfortable in ID'ing it as a California Thrasher.
    4 points
  9. Backgrounds a little busy, but I still like it. Thoughts appreciated: https://macaulaylibrary.org/asset/598819311
    4 points
  10. The owl likes to sit on a particular post, so I trimmed under the Oak tree to get a better view of it tonight when it came to the yard.
    4 points
  11. This is a huge topic, and one I find very interesting. Thanks for the thoughtful post, Alex. I’ll be happy to contribute to this thread and have some initial thoughts. First, data quality is an ever evolving topic, one warranting numerous PhD dissertations and endless study, but at a very general level, my feeling is that one big data problem for eBird is simply the system itself. At present, There are over 900,000 eBirders and almost 83 million complete checklists. To the best of my knowledge there are less than 4,000 regional reviewers worldwide. The math simply doesn’t check out. While reviewers don’t review every sighting, the filters do. And the filters are overseen by reviewers. Yet, the task over overseeing all the data is simply hurculean. For example, in my county there are three active reviewers and over 500 species in the filter, plus hybrids, slashes, and spuhs. It would be virtually impossible to go through every single species filter one by one, fine tune it (this alone is something that could be a whole topic), then run it and review all the records that end up in the queue. On top of that, there is daily monitoring of checklists for duration, distance, correct protocol use, and accuracy in location. There is also the task of checking species maps for status and distribution, and monitoring media that is submitted (that’s a female CITE, not a BWTE). These are just some of the issues, plus many smaller ones. These problems are not unique to my county, so multiply that by how many filters regions there are globally, add in some unique issues that others face that my county doesn’t, and voila, you have eBird. In essence, the dataset is just too big. I don’t know much about statistics, but my sense is that some of the large scale data lies outside of acceptable error rates. As far as users go, anyone with internet access can submit eBird data. One suggestion I have heard thrown around is to require all users to take a short course and and answer a survey or questionnaire. I doubt tha would really be effective. Without opening Pandora’s box, I’ll say that I think the answer lies with AI and computer trained models. I can envision one day where reviewers are not needed, and users don’t need to flag incorrect media, the computer is smart enough to do it for us. I don’t want to go too far down this rabbit hole, but this may be the only way to effectively create really good, accurate data for eBird. I don’t know iNat, so I won’t comment there, but I appreciate hearing what people think are it’s greatest strengths as well as it’s shortcomings. I was just recently asking a well-known reviewer about eBird data and how scientist use it, and they didn’t really know. This is a very valid question and one I would love to know more about.
    3 points
  12. Really happy with the way it turned out!
    3 points
  13. Pass on the flycatcher, odd looking bird. 2. Blue-gray Gnatcatcher.
    3 points
  14. Some of my better photos of NOMO that I wanted to post in the Pic of a Bird Sp.
    3 points
  15. I was looking at your other observations and found this one. And the award for best name goes to the Prairie Boopie! https://www.inaturalist.org/observations/172346024
    3 points
  16. Hi folks! The coloring book is slowly coming together. I have some fact-checking to do, but I'd love to get some feedback at this point. If you'd like to see the whole book, let me know and I'll send you a digital copy. Alternately, you can see the cover and the "Activities" page below, which is near the end of the book. Any suggestions? Are there any other activities I should add? Thanks to everyone!
    3 points
  17. It's an Eastern Towhee. White on the primaries is quite common for Eastern Towhee, and Spotted Towhees have much more significant spotting on the wing, but it's primarily on the coverts and back versus the primaries. A hybrid would be almost impossible at this location as there is little range overlap between the two species and hybrids are primarily documented where their ranges overlap, in places like Nebraska.
    3 points
  18. The tail is too long and the wings too short for a Merlin, proportionately. They are also largely absent from the Bay Area this time of year. Probably it’s a Cooper’s Hawk?
    3 points
  19. Looks like a Hooded Merganser, probably a young one with that dark eye and hint of a crest.
    3 points
  20. American Bumble Bee North American Wheel Bug
    3 points
  21. One of those birds that doesn't like Vermont. 🙄 Right when you cross the border into NY you see them everywhere...
    3 points
  22. 2 points
  23. Yeah, I found their name comical as well!
    2 points
  24. My favorite bird birdie 🦢 #438: 🟩⬛⬛⬛⬛⬛ https://birdiegame.net/
    2 points
  25. Maybe just a bit of a give away there. birdie 🦆 #438: 🟩⬛⬛⬛⬛⬛ https://birdiegame.net/
    2 points
  26. Bro, nice shots! BTW, your signature line is cracking me up. Duuuuuude. 😂
    2 points
  27. What exactly do you mean by "confirm hybrid?" How would they do that? The 2021 report isn't out yet, but I speculate that there were doubts about the purity of the bird and where to draw the line at species. Sometimes when vocalizations of both species are present, definitive ID can be a challenge. BRC members tend to vote conservatively in situations such as that, and rightfully so.
    2 points
  28. That was my thought - white tipped, barred tail. Streaked chest suggests juvenile.
    2 points
  29. birdie 🦆 #437: 🟩⬛⬛⬛⬛⬛ https://birdiegame.net/
    2 points
  30. Welcome to Whatbird Forums, jlashwell! I agree with RobinHood that you photographed a (young) Hooded Merganser.
    2 points
  31. There is also an 'Overflow' thread now, too.
    2 points
  32. Abundant in Florida but I also saw a number of them in Colorado. The photo below is from Florida but before we actually moved here. I have a ton of good photos of this bird as they are not shy and even seem to enjoy hamming it up for the camera. I have Bahama Mockingbird too (only seen one and not a great photo) it would be nice to be able to include it.
    2 points
  33. Arizona Woodpecker
    2 points
  34. Cleveland, Ohio, 2017, which I'm mentioning only because when I was a kid in the Cleveland area, we didn't see these birds.
    2 points
  35. https://macaulaylibrary.org/asset/598866181
    2 points
  36. Ratings appreciated: https://macaulaylibrary.org/asset/598815431
    2 points
  37. Not the best, but I like its silly expression.
    2 points
  38. 2 points
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