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State of the Birds Report

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Our Approach


Black-throated Sparrow by Lois Manowitz,



To determine the status of birds and bird habitats on private lands, we overlaid bird distribution and habitat information onto a map of private land ownership for the U.S. We estimated the percentage of each species’ distribution on private protected lands as well as all other private lands. Private protected lands are private lands known to have some protection for conservation via easement or ownership and are included in the Protected Areas Database for the U.S. (PAD-US; All other private lands have no known conservation protection.

For this report, we focused on habitat obligates (i.e., bird species restricted to a single primary seasonal habitat) and estimated their breeding and winter season distributions using occupancy data from eBird ( Primary habitat and ownership data were based on the National GAP Land Cover dataset ( and PAD-US. These nationwide databases allow us to evaluate how much each species uses private lands and assess the contribution private protected lands make towards species’ conservation.

eBird Checklist Data, 2004–2011

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This map shows the locations (green dots) of eBird checklists used to estimate species’ distributions for this report. More than 1.5 million checklists from 220,000 unique locations from the eBird Reference Dataset 4.0 (available at ) were analyzed. 


  Thank You to eBird Volunteers

Each State of the Birds report has relied on bird monitoring data collected by volunteers throughout the U.S. Our understanding of bird distributions has greatly improved thanks to the thousands of bird watchers who have contributed observations to This effort is especially important for tracking seasonal and fine-scale changes in bird distributions, which is not possible with other bird-monitoring programs. However, even this massive observation network provides only imperfect information for assessing the year-round status of birds in remote parts of the U.S., including Alaska, Hawai`i, and island territories.
  Image: Cornell Young Birders Event by Chris Wood  

Understanding Bird Distributions

Most birds are not evenly distributed across their ranges and these uneven distributions change dynamically through the year as many birds migrate. To estimate breeding and winter season distributions of U.S. birds in the lower 48 states, we used data from eBird, a rapidly growing citizen-science program administered by the Cornell Lab of Ornithology. For this report, we used more than 1.5 million bird checklists collected by eBird participants during 2004–2011, from more than 220,000 unique locations. For Alaska bird distributions, we used vegetation layers to modify bird breeding and year-round range data from the Alaska Gap Analysis Project and NatureServe. For Hawaiian birds species, Hawai`i biologists compiled and analyzed bird distributions. Bird distributions for Puerto Rico, U.S. Virgin Islands, Guam, and the Commonwealth of the Northern Mariana Islands were based on distribution of suitable habitat identified by local experts.

We determined distributions for 219 breeding and 65 wintering birds within the U.S. Breeding species include non-migratory residents. For each of 169 breeding species and 49 wintering species with sufficient eBird data, we fit a statistical model to associate patterns of observed occurrence with elevation and local land cover information (i.e., the 2006 National Land Cover Database) while accounting for gaps and biases in the eBird data. For each species modeled, 52 weekly distribution estimates of bird occupancy were created at each at 933,688 locations across a grid of 3-square-km blocks covering the continental U.S. Each species’ estimated occupancy distribution was evaluated for accuracy by experts at the Cornell Lab of Ornithology, and the most representative seasonal distribution was selected from among 52 weekly estimates. For an additional 16 wintering and 50 breeding species with very small ranges, we used the frequency of each species reported on eBird checklists to determine distributions. These frequency data were summarized across a coarse grid of 20-square-km blocks. Winter and breeding distributions were analyzed separately for migratory species within the U.S. To represent the breeding distribution of resident species we used data from throughout the year.

Examples of breeding distribution model-based estimates for obligate species in four habitats. Clockwise, from top left: Black- throated Gray Warbler in western forests; Dickcissel in grasslands; Black-throated Sparrow in aridlands; Wood Thrush in eastern forests. These maps show estimated occupancy during peak breeding season. Brighter areas indicate higher probability of occupancy. Occupancy estimates were based on bird observations from eBird and characteristics of the local environment from remote sensing data. See additional distribution maps.

  Thank you PAD-US contributors   
  The Protected Areas Database of the U.S. (PAD-US) is a spatially explicit inventory of protected areas based on data from authoritative sources, such as nongovernmental organizations and land trusts. The general public and professional land managers can use the PAD-US inventory in conservation, land management, planning, and recreation. The most recent version of PAD-US includes significant contributions from the National Conservation Easement Database. NCED is an initiative of the U.S. Endowment for Forestry and Communities with additional support from the Gaylord and Dorothy Donnelley Foundation, the Knobloch Family Foundation, the Graham Foundation, the U.S. Forest Service State and Private Forestry, the U.S. Fish and Wildlife Service Landscape Conservation Cooperatives, The Nature Conservancy, and Land Trust Alliance. We thank the NCED team consisting of The Trust for Public Land, Ducks Unlimited, Defenders of Wildlife, NatureServe, Conservation Biology Institute, U.S. Fish and Wildlife Service, Natural Resources Conservation Service, and the U.S. Forest Service for their contributions to PAD-US.  

Mapping Private Lands

We used the PAD-US (version 1.3) to determine land ownership categories for the continental U.S., Alaska, Hawai`i, Puerto Rico, and Virgin islands. PAD-US is a national spatial database created from authoritative sources by the U.S. Geological Survey’s Gap Analysis Program (USGS-GAP) in collaboration with the University of Idaho Gap Analysis Program (UI-GAP). To determine the total acreage of land ownership, we combined 15 ownership categories into four categories: private protected lands, other private lands (lands with no known protection), public lands (i.e., lands managed by federal, state, county, and city agencies), and tribal lands (i.e., lands owned by Native Americans). Private protected lands are known to have some protection for conservation via easement or ownership, as identified in PAD-US, which includes land trusts, nonprofit groups, and nongovernmental groups as well as private landowners who have protected their lands via easement or management practices. Area of private lands for Guam and the Commonwealth of the Northern Mariana Islands was determined by subtracting total area of federal and state land from the total territorial area. American Samoa was excluded because land tenure is communal and private land as defined in this report does not exist.

To estimate the extent of each primary habitat, we used the National GAP Land Cover dataset. This dataset of vegetation associations is available for the U.S., including Alaska, Hawai`i, Puerto Rico, and Virgin Islands. The 745 ecological systems, as well as vegetation and land use classes, were categorized into primary habitat designations for our analysis. These data were then overlaid with PAD-US to calculate the area of each primary habitat on private protected lands, other private lands, public lands, and tribal lands. Wetlands information came from a variety of sources, including the USGS National Water Summary on Wetland Resources.

PAD-US includes significant contributions from the National Conservation Easement Database. USGS-GAP relies on authoritative sources such as nongovernmental organizations and land trusts to provide valuable spatial and attribute data to improve the content of PAD-US. We encourage agencies and organizations with information on private protected lands to contact USGS-GAP ( PAD-US 1.3 is the newest version of this database and is available for viewing and downloading from

Protected Areas Database of the U.S. 

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Private protected, other private, public, and tribal lands of the US. Data based on Protected Areas Database of the U.S. (PAD-US) published by USGS-GAP and developed by UI-GAP (clockwise from above: contiguous 48 states, Alaska, Hawai`i, Puerto Rico, and U.S. Virgin Islands). Bird distributions and habitat information were overlaid onto PAD-US to determine area of each of the 4 categories of land represented here. 

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Determining Conservation Opportunities for Birds on Private Lands

To calculate the percentage of each species’ distribution within the four ownership categories for the continental U.S., we projected the occupancy or frequency distribution for each bird species onto PAD-US using two approaches. First, for the occupancy distributions estimated by the statistical modeling, we calculated percentage directly by summing predicted occupancies by the four ownership categories at the 933,688 sample point locations based on a 3-square km grid. Second, the frequency distributions, which provided coarser data, were summarized within 20-square-km blocks. We projected these blocks onto PAD-US to define percentage of lands as private protected, other private, public, or tribal within each block. For each species, we then summed occupancy among blocks, weighting by area of the ownership category within the blocks. In Alaska, the bird distributions were overlaid with PAD-US to determine the percentage of each ownership category within each species’ distribution.

For each primary habitat, we reported the average percentage of bird distributions on private protected, other private, public, and tribal lands across multiple obligate species.  



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