eBird Occurrence Maps
We are excited to display the preliminary results of
our modeling research using eBird data. These maps, which are called
STEM (Spatio-Temporal Exploratory Model) maps, use eBird checklists
that report all species and include effort. The location of each
checklist is associated with remotely-sensed information on habitat,
climate, human population, and demographics. Fine-scale patterns of
species occurrence relative to these variables (over 1000) are
generated both regionally and temporally, to produce predicted
occurrence at some 30,000 locations for every day of a single year
(2008 in this case). This massive volume of information is then
summarized on maps, which in many cases provide unprecedented
information about the annual cycles of North American birds. These maps
showcase the power of eBird – year-round, continental-scale monitoring
of all species.
Each species map is displayed with a text overview of the broad-scale migration patterns, along with an interesting biological story to consider. Of course, every map has many more stories to tell, and we invite you to provide your comments and reactions on the eBird blog.
Recent Additions: December 3, 2010
Provide comments on any of these maps on the eBird 'Chip Notes' blog
*NEW* Northern Cardinal (Cardinalis cardinalis)Year-round animation.
*NEW*
American Pipit (Anthus rubescens)
Year-round animation.
*NEW*
Brown-headed Nuthatch (Sitta pusilla)
Static map for 24 May.
*NEW* Red-headed Woodpecker (Melanerpes erythrocephalus)Year-round animation.
*NEW* Western
Tanager (Piranga ludoviciana)
Year-round animation.
*NEW* Wood
Thrush (Hylocichla mustelina)
Year-round animation.
*NEW*
Swainson's Hawk (Buteo swainsoni)
Year-round animation.
*NEW* Dickcissel
(Spiza americana)
Year-round animation.
*NEW*
Grasshopper Sparrow (Ammodramus savannarum)
Year-round animation.
*NEW* Olive-sided Flycatcher (Contopus cooperi)Year-round animation.
While some of these maps match the known distribution of birds very
well, some maps extrapolate into areas where we know the species does
not occur. Often this is caused by regions of sparse eBird data, such
as northern Minnesota, northern Maine, much of Nevada, sparsely-settled
regions in the upper Great Plains, Montana, and elsewhere. In some
other cases (south Florida for example), the habitat information seems
to be insufficient to understand the landscape as it relates to bird
occurrence. In all of these cases, however, we believe that more eBird
checklists from these regions will improve the model’s ability to
understand bird occurrence. So we strongly encourage you to
check out our story that discusses the weaknesses in our eBird
coverage in the United States, and to contribute any checklists you
have from these regions.
Please remember that these maps tend to focus attention on areas where
the species occurs at high frequency. Birders are very tuned in to rare
birds at the fringes of their ranges. For example, we tend to consider
south Texas to be the northern limit for Hook-billed Kite and Brown Jay
(even though fewer than ten pairs occur along a 100-mile stretch of the
Rio Grande); in fact, Brown Jay may no longer breed on the United
States side of the river. Similar examples of isolated and very small
populations at the extreme fringes of their ranges (e.g., Cerulean
Warbler in Massachusetts and New Hampshire, Hooded Warbler in
Minnesota, Bobolink in Nevada, and American Redstart in California) are
reflected in field guide range maps, but in reality reflect extremely
small populations that may consist of only a few pairs of birds. While
birders may consider these to be "within the normal range of a
species," in reality they are extremely localized exceptions, and these
very faint signals are typically not shown on the STEM maps. STEM is
fundamentally showing the probability of encountering the species at a
randomly selected point on the landscape, so these locally isolated
populations really should not be shown on these maps in many cases.
Please keep in mind the frequency scale (see the scale on the right --
best visible in the 'large' versions of theses maps), try to consider
the probability of encountering the species at random, and we think you
will find that these maps are very accurate.
We do invite comment. The maps are not perfect and it is an ongoing research project to improve them. We are currently incorporating additional landscape variables, including hydrology and satellite 'greening' data, which we hope will further improve results. In addition, more eBird checklists from more diverse locations really help these models perform. Please drop in to the eBird 'Chip Notes' blog to share your thoughts on these maps or comments on the analysis.
