eBird checklists and miles traveled

One of the tasks that eBird reviewers find difficult is dealing with checklists that involve long, traveling counts.  Such checklists often stand out because they tend to rack up relatively large numbers of individual species, thus tickling the relevant filter and getting particular species entries flagged.  However, a large percentage of such checklists have no flags, thus do not see review until and unless a reviewer goes searching for anomalous eBird locations of habitat-restricted species, such as, say, White-tailed Ptarmigan.  In fact, these habitat- and range-restricted species are the primary argument for having checklists with as precise a location as possible, else the resultant eBird maps show occurrence in areas or habitats in which the species does not occur.

Unfortunately, the most comprehensive treatment of the subject is not that comprehensive and does not provide any hard-and-fast ground rules.  Granted, hard-and-fast rules when dealing with biology are nearly impossible, but eBird does care, and care strongly, about checklist locations.  In fact, I'm sure that if it were possible, eBird would prefer a checklist and associated precise location for every individual bird.  Of course, that is not going to happen, at least, not anytime soon.  However impossible the every-bird-is-its-own-checklist pipe dream might be, there are definite and very strong advantages to eBird of having checklists cover as little distance as we can get from eBirders.

The best guidance that I have found in the eBird 'Help' tab is the "Traveling Counts" section of a general-purpose essay on making checklists more useful:

Traveling counts have proven to be the most effective type of observation for modeling bird populations at large scales.  By doing these counts, birders often detect a good proportion of the birds in a given habitat.  It is critical, however, that your traveling counts not be too long.  Our analysts are able to effectively use traveling counts that are ≤5 miles [emphasis added].  Most birding that is conducted on foot easily falls within this window, but traveling counts by car can often be longer.  Please consider breaking up your long traveling counts into shorter-distance ones. It's best if these shorter counts are in a relatively consistent habitat, or do not pass through habitats that are too different. For example, a logical point to break a longer route into segments would be a transition between forest and farmland, as the birds found in these two habitat types are vastly different. Doing so would make information associated with each location — such as vegetation information from satellite images — more informative.  Plot your location at the center of the area traveled, not at the start point or end point.  It's okay to stop and spend time searching flocks of birds more thoroughly on traveling counts, as we are not assuming that you are traveling at a constant speed.  You're birding after all!

I here note that eBird Central has repeatedly stressed that this "five-mile limit" should NOT be considered cause, in and of itself, for checklist invalidation, that the limit is simply one that is very useful in particular types of analyses, such as the STEM maps of migration of individual species.  Checklists covering trips of a reasonable longer distance are certainly permitted in eBird and most such provide perfectly valid and useful data.  The problem that eBird reviewers face is where to draw the line on "reasonable."

Certainly, any eBirder should recognize that a checklist covering 650 miles on I-80 and crossing a state boundary (possibly, multiple state boundaries) and who knows now many dozens of county boundaries, does not provide data useful to anyone other than the observer.  In fact, such would provide misleading information, as almost no matter where such a checklist were plotted, the list of birds could well include species not regularly found at or near the plotted location.  But where lies the "reasonable" cutoff between 650 miles and five miles?  Unfortunately, this illusory line is dependent upon where you are and what sort of areas are covered by the checklist.

In much of the flatlands of Wyoming and Colorado, a checklist covering 15 miles might include just one or two habitats (e. g., native grassland and winter-wheat fields) that share a large proportion of bird species present in the area, and thus provide reasonable eBird data.  However, in places like southwestern Huerfano County, Colorado, traveling on the road from Highway 12 toward Trinchera Peak -- the straight-line distance of which is just over 4 miles (though the road distance is a fair bit longer) -- one's elevation changes from roughly 9250 feet to over 12,100 feet.  This road takes one from about the upper limit of elevational range of species like Pygmy Nuthatch and Black-headed Grosbeak and the lower elevational limit of Gray Jay and Pine Grosbeak to the above-timberline habitat of White-tailed Ptarmigan and American Pipit.  Thus, any checklist covering the whole road will, perforce, require plotting some of the birds encountered in habitat different from that in which they typically occur.

The above brings us back to the aforementioned eBird guideline about traveling distance and its emphasis on habitat.  Though not stated precisely in the guideline, eBird is very much interested in checklist locations being fairly specific to the habitats of the species included on the checklist.  Thus, in areas of the two-state region in which many habitats meet and mingle -- particularly obviously differing habitats, such as grassland and woodland or conifer forest and alpine tundra, the more precisely that locations are plotted and the shorter distances that are covered by individual checklists the better.  With the eBird application (app) for smart phones (about which, please read the best-practices essay), this becomes quite easy to manage.  Granted, cell coverage in much of the two states leaves much to be desired, but there is a simple work-around when planning a trip to an area of poor cell coverage.  One can modify this technique when already out and unexpectedly (or otherwise) run into poor cell reception, by using an existing checklist in the app on which to base the new one.  It is important to remember in such cases that county boundaries are often filter-region boundaries and species that are expected in some counties (thus, not flagged by occurrence, alone) may be unusual in a neighboring county, which may cause some slight disconnects between what species one sees and the "allowable" list of species on the current active checklist on the app.

Most eBirders understand the need to separate sightings in one county from those in another into different checklists.  While this is less of a problem in Wyoming than it is in Colorado (mostly due to the many fewer counties in Wyoming), both states host birding locations that cross county borders, with Yellowstone N. P. being the mother of all examples in the two-state region (heck, the Park even straddles multiple state borders!).  In Colorado, particular problem children birding sites include Chatfield S. P., Jumbo Reservoir, and Comanche N. G.  However, the single most-recalcitrant problem child is the area around Denver International Airport (DIA).

The DIA problem was created when the airport was first proposed, because Denver County was allowed to annex a sizable chunk of what was then Adams County in order to build the airport and the access road (Peña Boulevard). This action created a long, snaking corridor of Denver cutting through Adams.  Were it not for Denver County's small size and its near-complete lack of native habitat, the DIA problem would not be a problem.  However, with birders' interest in county listing, this long snake of a Denver extension travels through some excellent habitat otherwise lacking in the county and providing access to species that have been extirpated from the original county boundary... such as Burrowing Owl.  The whole eBird-review problem here is based on the fact that this corridor of Denver is so narrow, just 1.3 miles wide at its narrowest, thus it is nearly impossible on a birding jaunt of the area to not cross into and out of Adams County, sometimes multiple times.  This all means that most (if not nearly all) eBird checklists submitted from the DIA environs cover an area claimed by multiple counties, something that is not "permissible" in eBird.

In summary, I provide what I think are some reasonable guidelines on when to end the current eBird checklist and start a new one.

• When a state boundary is crossed
• When a county boundary is crossed
• When crossing an obvious boundary between open habitat and wooded or forested habitat
• When arriving at a birding location (particularly one that is an eBird hotspot) that has well defined borders and that is managed by a particular government agency or non-governmental organization (e. g., a state park, a national wildlife refuge, a private preserve)
• When leaving a birding location (particularly one that is an eBird hotspot) that has well defined borders and that is managed by a particular government agency or non-governmental organization (e. g., a state park, a national wildlife refuge, a private preserve)
• When leaving the "understood" area of an eBird hotspot, even if that hotspot lacks well defined borders (e. g., "Yellowstone NP--Midway Geyser Basin" or "Rocky Mountain NP--Endovalley")
• When accruing 15 miles of distance in relatively homogeneous habitat in open country (such as in sage shrubsteppe, grassland, agriculture)
• When accruing 5 miles of distance in relatively homogeneous forested habitat without significant (≤750 feet) elevational change
• When accruing 2 miles of distance when encountering relatively significant elevational change (>750 feet, ≤1500 feet)
• When accruing 1 mile of distance when encountering significant elevational change (>1500 feet)
• When accruing two hours of observation (one hour would be even better)

Update on Colorado and Wyoming filters

It has been more than long enough for another post on this venue, and I apologize for that for myself and the rest of the two states' eBird reviewers.  Personally, long work days and many other writing commitments can be blamed.  Of course, if I didn't go birding, I'd have more time to write about birding.

As I alluded in a previous post, eBird is interested in pursuing more and better habitat-based filter regions, rather than the current system of using geopolitical boundaries to define them.  As part and parcel of that interest, Don Jones (a member of the Wyoming review team) will be putting together a proposal for such for Wyoming as part of his undergraduate work (as the Brits would say) at university.  I have spent some time in designing such a system for Colorado, and have nearly completed a first-draft version for eastern Colorado.  Though Colorado's plains may seem to be easier to deal with in this regard than is the rest of the state, the reverse is actually true.  The extreme topography gradients in western Colorado actually preclude making small, tight filter regions (one would need 100s of the things!), so fairly large filter regions will still be the easiest way to treat that part of the state.  In eastern Colorado, however, there are numerous large reservoirs that attract a very different avifauna compared to most of the rest of the area.  In addition, the large urban area with their de rigeur tree canopy also make for very different bird habitat than found on the rest of the plains.  My current map has 26 regions defined from east of the Front Range-Wet Mountains-Sangre de Cristos Mountains line, where there are currently 20 regions, eight of which extend well up into the mountains.  eBird is not yet ready to greatly expand the number of "arbitrary polygons" used as filter-region boundaries, but when they are ready, Colorado and Wyoming will be ready, too.

Since February 2015, I have split Cheyenne and Kiowa counties out of the former Southeast Region into their own regions, bringing us to 39 current Colorado eBird filter regions, and with the Southeast Region no longer named such, as the remaining multi-county region is now titled Bent and Prowers.  I had plans to split those last two counties, but have decided to spend the necessary time on designing arbitrary polygons, instead, which will (hopefully soon) negate any effort to make individual filters specific to Bent and Prowers counties.

Finally, I continue to fine tune existing filters, which may cause some to many data that may have resided comfortably in eBird for years to suddenly get flagged.  Please do not be alarmed when you receive a request from one of us regarding a sighting from last year or from five years ago.  This is a normal process, one that is greatly aided by the great increase in amount of eBird data available to analyze how filters might be made more precise.  That is, thanks to you, eBird becomes stronger and stronger in its ability to define geographic and temporal bird occurrence in Colorado and Wyoming and the rest of the world.

Colorado filter news

While this post will have little or no bearing on Wyoming birders, I write to inform the Colorado birding community that oversight of Kiowa County eBird entries is now managed by a county-specific filter rather than the broad (but getting less broad by the month) southeast Colorado filter.  This means that various species that are of regular occurrence in general in the southeast, but rare in Kiowa County will have more-meaningful filter limits.

Kiowa County eBird data include reports of 288 species, but many birders might be surprised by the number and variety of species for which there are no acceptable eBird reports from the county.  This list includes:

Lesser Prairie-Chicken

Black-chinned Hummingbird

Rufous Hummingbird

Red-bellied Woodpecker

Red-eyed Vireo

Pine Warbler

and

Black-throated Gray Warbler.

Other species are so rare in the Kiowa eBird data set as to make for the seemingly preposterous phenomenon that there are more records for Reddish Egret than (among many others) such species as Red-breasted Merganser, Northern Bobwhite, Virginia Rail, Wilson's Snipe, White-winged Dove, Yellow-billed Cuckoo, Black-capped Chickadee, White-breasted Nuthatch, Brown Creeper, Eastern Bluebird, Sage Thrasher, Indigo Bunting, and Baltimore Oriole.

The next items on my to-do list are filters for Cheyenne (it is not particularly similar to anything else in the former southeast filter -- Baca, Bent, Crowley, Kiowa, Otero, and Prowers; note the water aspect of those counties), Archuleta and La Plata, and Lake.

Bird-ID links

I write a very short note to announce the publishing of a page on this blog that provides links to various online bird-ID literature relevant to Colorado & Wyoming.  If you have suggestions of online papers to which you believe we should provide links, please enter such in the comments.

Stone Age to Industrial Age: The evolution of eBird's filter system

Did you ever wonder why eBird asks for details about a report of American Dipper from Adams County, Colorado, but lets the same report from Park County, Wyoming, sail through without a twitch? I just want to say one word to you; just one word... "filters."

A filter is what creates the list of species (and non-species entries) that you see when you enter a checklist into eBird. Imagine, with the current world-wide scope of eBird, having to rummage through the entire list of the world's 10,000± species of birds just to enter the seven species that you saw in a nine-minute jaunt through your yard. Ugh. No one would use eBird. Thus, filters were created from the program's inception in order to streamline the data-entry process.

Filters have at least a couple other purposes, which go hand in hand with the primary purpose. The first of these is to call attention to the eBirder entering data that a species is not expected at the location, which helps point out possible data-entry errors. I've done it; you've done it. You meant to enter an American Bittern, but you got the number in the box for Least Bittern. Oops. eBird will point that out to you when it asks you to confirm the entry, as the species is rare in this region. Filters also involve abundance limits, which, again, enables the software to point out possible data-entry errors. This one I've done numerous times with my fat fingers. You meant to enter 1 American Bittern, but you accidentally also hit the zero on the number pad resulting in 10 American Bitterns. With the filter set at something less than 10, eBird will point out that error when it asks you to confirm the number, which is atypical for anywhere in this region.

In the beginning (2002), eBird was a very simple and simplistic world. The first iterations of filters were state-/province-based things (the program was originally restricted to the U.S. and Canada) that provided gross estimates of numbers acceptable for that state in each of the 12 months of the calendar. They were created as Excel spreadsheets, with species down and months across, each cell filled with an integer that was a gross approximation of what was thought to be the realistic maximum that one might encounter in a day's birding in the state/province; no matter where in the state/province. Abundant species, such as Red-winged Blackbird, might have a cell (or each of the 12 cells) filled with 100,000.

Chris Wood (currently the eBird Project Manager, but then "just" a Colorado birder with a strong knowledge of the state's bird distribution) and I constructed the first Colorado filter in 2001 and we did not really think through the ramifications of those cell entries. We did not consider data-entry errors. We did not consider what those cell entries might mean regarding permitting some fairly outlandish numbers to skip the review process. At the time, there were no non-species entries. That is, no spuhs, slashes, hybrids, subspecies. There were just species.

As eBird has become more refined with much more capacity and capability (thanks to Jeff Gerbracht and the rest of eBird's architect team), filters have become incredibly more complex. First, was the separation of the statewide filter into regional filters, using the county as the basic block, at least in the Lower 48. Circa 2005, Chris and I divided Colorado's statewide filter into five regional filters in which we lumped counties with similar avifauna: Northeast, Southeast, Mountains, Northwest, and Southwest. That, obviously, required some fine-tuning of each of those five filters to more-closely match each subregion's avifauna, such as excluding Northern Bobwhite from the three western filters and excluding Gunnison Sage-Grouse from the two eastern filters and the Northwest filter.

Next was the addition of various above-species-level entries, the spuhs (e. g., "goose sp.") and the slashes (e. g., "Semipalmated/Western Sandpiper"). That meant going through each of the five then-extant filters and adding those non-species entries relevant to each filter, which I did (Chris was now working at eBird) on a fairly conservative basis, putting in just the really common non-specific entries, such as "Snow/Ross's Goose" and "accipiter sp." That wasn't too bad. Tedious, but not too bad, and at the time, I was the only person working on Colorado's eBird filters. Due to Wyoming's low human population (thus birder population), the state did not then have a resident filter meister; the Stone Age (statewide) filter was established and maintained at eBird Central at the Cornell Lab of Ornithology.

At some point after the addition of non-species-level entries, I started splitting the five Colorado filter regions into smaller ones in order to account for the complexity of bird distribution in the state, such as taking the species-rich and well-birded counties of Boulder and Larimer out of the northeastern filter and constructing a new filter that could be more tightly focused on that smaller region's avifauna. With available time, the number of Colorado filter regions grew, cracking double digits and never looking back.

In 2007, the addition of Marshall Iliff as the third member of the eBird management team (Team eBird; Brian Sullivan and Chris Wood being the other two), eBird's abilities expanded further, with a more-in-depth taxonomy that was to cover the entire planet (2010). (I find it very interesting that Brian, Chris, and Marshall all worked for me at Rocky Mountain Bird Observatory at various times and that all worked on the same project in Mexico with me one year!) Hybrids were added, as were many, many, many more non-species entries, such that there are now nearly as many non-species-level entries available in the ABA area as species-level entries, some used exceedingly rarely, some widely used.

Then, eBird tackled the "April problem." Those of us in the filter and record-review aspects of eBird had for years complained that the rigid monthly structure to the filters made for some major problems, with April being the poster child for such problems. In much of the ABA area, particularly the Lower 48, filter makers/editors had to decide between filtering out all occurrences of a migrant species that arrived in the filter region in the last few days of April, or allow all occurrences in the month of such species, even in early April when they were unknown. In Colorado, MacGillivray's Warbler is an excellent case in point, with the vast bulk of migrants arriving in May, but with a small number typically noted in the last week of April, but unknown in the state prior to the 22nd or so.

The solution was to throw out the monthly framework, replacing it with up to 13 individually adjustable time periods. The new system allowed chopping up, particularly, the short, intense spring migration of most migrant species into periods as small as five days, with each period allowed its own abundance limit (a number that is "permitted," with any larger number of birds of that species in that time period requiring review). As example, the Lincoln County, Colorado, filter has five filter periods covering the spring migration of Clay-colored Sparrow, each with its own abundance limit (in parentheses): 22-30 April (1), 1-7 May (9), 8-14 May (29), 15-21 May (15), and 22-31 May (9). The filters are also now constructed online, a move nearly enforced by the new system (Fig. 1); think about trying to construct an Excel spreadsheet that does this.


Figure 1. Abundance and seasonal limits of a variety of sparrow species (and non-species entries), January through about 15 August in Lincoln County, Colorado, as indicated by the current eBird filter for that county. Click on image to see larger version. Note that the short lengths of some of the temporal periods of the filter mean that values of more than one digit are partially hidden by the scroll arrows in each period (see Clay-colored Sparrow). Note that there are three non-species entries, two subspecies of Brewer's Sparrow (neither of which is allowed without review, as identification is quite difficult) and a spuh (Spizella sp.). One can quickly determine from this filter those species of this selection that are known to breed in the county, just Cassin's and Vesper sparrows. Note also that the individual abundance limits of the spuh entry allow for all temporally-occurring species of the genus, as it is fairly easy to imagine most of a large flock of mixed Spizella not being identified to species. Finally, the grayed '+' buttons indicate entries (Chipping Sparrow, Clay-colored Sparrow, Spizella sp.) for which all of the possible 13 temporal periods are used; that is, the occurrence patterns represented in the filter cannot be further divided.

As something of an aside, an abundance limit is the result of a decision about a tenuous balance between the number that might occur and catching data-entry errors, and such decisions need to be made for as many as 13 temporal periods for each of the species and non-species entries in each filter (the current Boulder County, Colorado, filter -- split off from the Boulder/Larimer filter a few years back -- lists 413 species and 231 non-species entries).

While the new filter system allows great flexibility in constructing species- and location-specific filter limits, it is also much more complex and much more time-consuming to construct. It takes me something like 5-20 hours of tedious effort per filter, whether constructing a new filter from scratch or completely overhauling an existing filter.

In the early years of this decade, big changes came about in the Wyoming birding community and in Wyoming eBird review and filters. First, Shawn Billerman arrived to attend to graduate studies at University of Wyoming. Before arrival, though, he had already been shanghaied by Team eBird (he did come straight from school at Cornell, so was already known by the powers-that-be) into tackling the state's eBird review. James Maley arrived a year later (working at University of Wyoming) and was quickly added to what was then a two-person team. Perhaps more importantly, though, they took on the task of bringing Wyoming eBird into the Industrial Age, as far as filters go. They divided the statewide filter into seven filter regions (Fig. 2).

Figure 2. The seven Wyoming filter regions.

Meanwhile, Colorado, with its considerably more-substantial eBird data set (and, perhaps, a filter meister with a wee bit more time on his hands), has 37 filter regions. As depicted in Figure 3, these regions are, generally, individual counties, though with a few two-county regions. The large, multi-county regions are in the process of being broken up into smaller units, with the Southeast region being an excellent example. Just in late February 2015, I have split the old large and unwieldy version of the Southeast filter into three regions: Baca, Crowley and Otero, and the rest of the counties. The San Luis Valley region, though large, is fairly homogeneous, so will not be broken up into smaller regions until some rather major changes in how eBird deals with filter regions come to pass (see below).

Figure 3. The 37 Colorado filter regions.

As it always has been, the primary impetus to establish a new filter region is to fine-tune filters to the landscape and the avifaunal occurrence (both spatial and temporal) thereon. Perhaps one of the best examples of the need for such new filters is Phillips County, Colorado (Fig. 3). At the time that I constructed the filter, the county was covered by the general Northeast filter (which also included Weld at the time). Note that all of those counties but Phillips has at least part of a major water body in it, while the largest water body in Phillips is probably a sewage pond (at Haxtun). Thus, Phillips County data were "allowed" to include large numbers of waterbird species that are actually fairly rare there.

However, just because a particular filter covers just one county does not mean that there aren't still difficult decisions about filtering to be made, and Wyoming is the epitome of that problem. Because of the state's low human population, its counties are overly large. The state's geography is also more varied and, well, eccentric. The combination of these two factors means that, unlike eastern Colorado, most of Wyoming's counties contain both low-elevation "flat" lands and high mountains, which makes for a wonderfully varied avifauna from a birding standpoint, but a nightmare from an eBird-filter point of view.

One of the best examples of this problem is Big Horn County, which combines the spine of the Big Horn Mountains (and the associated suite of subalpine forest species) and the low-elevation Big Horn Basin (and the associated grassland and shrubsteppe species). Because one would not expect to encounter Long-billed Curlew in the forest near the pinnacle of the Big Horn Mountains nor White-winged Crossbill in the open country northeast of Greybull, eBird really should not "allow" such occurrences. However, with county-based filter regions, such problems are encountered frequently. In the long term, the solution is filter regions based on physiognomy and habitat, not geopolitical boundaries -- what we might term Space Age filters. Though there have been arbitrarily defined filter regions in the past (e. g., most or all of the California coastal counties have "offshore" regions), Team eBird is moving in that direction in a general fashion. However, the process will be long, involved, and tedious, and will not happen tomorrow.

As more and more data are entered into eBird, the data sets for individual filter regions become more robust and allow for more-precise filter limits and temporal periods, so reviewers are constantly fine-tuning filters. However, as noted above, this is a slow process. Thus, you may encounter remnants of previous filter strategies mixed with more-"modern" strategies on individual filters in both states when entering data into eBird, simply because no one has found the free time to completely revamp older filters. So, when you encounter something that a filter flags that you believe should not be flagged, please let us know (politely!) in the species's comment field. That goes the same for occurrences that you feel ought to be flagged, but aren't. Most of you know your local area much better than any of us do; we're happy to learn such bits of information, particularly in Wyoming, which has many fewer data backing the various filters.

As eBird continues to grow in popularity, demands on its programming, design, and operations will also grow. With the very recent addition of Ian Davies to the management team and the resultant spreading of the workload at eBird Central, we can expect further enhancements, even radically new capability, to come online in the near-term future. I cannot wait to see the changes!

[This essay is largely based on a previous version that I posted to Cobirds, the Colorado birds listserve. Thanks to Team eBird and various members of the Colorado and Wyoming review teams for comments on an earlier version of this essay.]

Tony Leukering

Lead Colorado eBird reviewer and senior author of the Colorado & Wyoming column in North American Birds

The Colorado and Wyoming eBird blog, a new era for eBirders in the region

Welcome to the first post in a new blog that is focused on eBird in Colorado and Wyoming. If you wandered here and found yourself wondering, "What the heck is eBird," then you might want to check it out. The eBird review teams of the two states mean for this to be a way to impart information about all aspects of the eBird review process to the region's eBirders, with its primary purpose of making the review system at least translucent. There will be essays on how eBird filters work, how they are created, and what they mean for your entry of data into eBird. However, there is a strong secondary purpose: to show eBirders how they can get more out of eBird and put more into eBird, through helpful hints on a variety of topics. Such may include essays on ways to make their data more meaningful from a scientific point of view, how to use eBird's output features to increase their knowledge and understanding of both spatial and temporal distribution, and when and how to use non-species entries, among a host of other possibilities.

All of us are quite busy with eBird review and birding, in addition to all of those other things that "normal" people do (going to school, working, sleeping, lazing around putting jigsaw puzzles together), so this will not be a blog that's updated daily. Or even weekly. But, give us a bit of time and a few posts and then we'd be happy to tailor future essays to questions about or problems with eBird that you encounter. Realize, though, that there is an extensive FAQ (that's "frequently asked questions" for you analog dinosaurs like me out there) at eBird that may well be able to answer your question(s).

Tony Leukering

Lead Colorado eBird reviewer and senior author of the Colorado & Wyoming column in North American Birds