Nine 2017 Articles from The Condor: Ornithological Applications. ALL ARTICLES ARE OPEN ACCESS.

Celebrating the North American Breeding Bird Survey

Philip C Stouffer
Editor-in-Chief, The Condor: Ornithological Applications
School of Renewable Natural Resources, Louisiana State University

Citizen science has become part of our 21st century research vocabulary. Information gathered by enthusiastic volunteers over broad spatial areas following standard methods has taken the informal research networks of past centuries to a level that allows rigorous analysis and strong inference about patterns and processes. Birds both inspire and permit citizen science; we can find them, we can identify them, and we can count them. And many people will happily get up early to do so. This Special Collection focuses on data derived from the North American Breeding Bird Survey (BBS), one of the most significant projects in the realm of what we now call citizen science. The papers we include take us from the inception of the BBS through the most recent advances in application and analyses—a 50-year legacy. There's something for anyone interested in distribution or population trends of North American birds.

Any summary of the BBS has to begin with Chandler Robbins, the iconic ornithologist who had the audacious idea of a continent-wide survey in the 1960s. We are the poorer for Chan's passing in 2017, but Keith Pardieck (2017) provides a tribute to a man whose energy and ethics serve as worthy models beyond his contribution to our discipline.

Chan Robbins on a Breeding Bird Survey in about 1985. Photo credit: Barbara Dowell. See Pardieck (2017).

The motivation and early years of the BBS are also summarized in a contribution by John Sauer and collaborators (2017).

BBS data are only as useful as the analyses that can be applied to them. Thankfully, some extraordinary statisticians have applied their skills to the long-term dataset. Sauer describes some advances in the methods, including the most up-to-date analysis of large-scale trends. Another paper by Link and colleagues (2017) provides a comparative look at model selection and computational requirements. The only way a survey of the scale of the BBS can work is to do it along roads.

 

Factors influencing North American Breeding Bird Survey data. Counts reflect an underlying population that is changing through space and time, but counting is influenced by observers and random environmental noise. See Link et al. 2017.

Joseph Veech and colleagues (2017) tackle implications of this design in their paper on how well road-based points represent the larger landscape. Development of land cover data and spatial analysis tools permit BBS data to be combined with landscape-level analyses, as was done by Veech et al. (2017).

Another spatial analysis in this Special Collection, by Neil Neimuth and colleagues (2017), leads to predictive models of species occurrence across the northern Great Plains.

 

Locations of Breeding Bird Survey (BBS) routes included in analysis of grassland bird occurrence in the Great Plains of Montana, North Dakota, Wyoming, South Dakota, Nebraska, Colorado, and Kansas, USA; inset shows location of study states in central North America. See Niemuth et al. (2017).

Predicted occurrence of (A) Upland Sandpiper, (B) Sprague's Pipit, (C) Lark Bunting, (D) Savannah Sparrow, (E) Grasshopper Sparrow, (F) Bobolink, and (G) Eastern Meadowlark in the U.S. Northern Great Plains. Gray indicates areas outside the region of analysis. See Niemuth et al. (2017).

Some of the most creative extensions of the BBS involve combining it with other sources of data on birds. The density of both roads and people to survey birds thins considerably at the northern limit of the BBS. Colleen Handel and John Sauer (2017) present results and interpretation of combined on-road and off-road surveys in Alaska that allow the trackless North to be integrated with the rest of the BBS area.

Location of roadside Breeding Bird Survey (BBS) routes (thick lines; 1993–2015) and off-road Alaska Landbird Monitoring Survey blocks (open squares; 2003–2015) sampled in the Northwestern (NW) Interior Forest (white, dashed border) and Northern (N) Pacific Rainforest (white, gray border) Bird Conservation Regions in Alaska, USA. Areas of federal (light gray) and state (cross-hatched) conservation and resource lands administered by the USDA Forest Service, U.S. Fish and Wildlife Service, National Park Service, Bureau of Land Management, Department of Defense, and State of Alaska are shown for the entire state relative to lands under other jurisdictions (dark gray). Major roads (thin lines) are concentrated in east-central and south-central Alaska, but local roads and a few slow-moving rivers were used for the BBS in other areas. See Handel and Sauer (2017).

Expanding data types, not spatial scale, can also enhance the value of the BBS. For game species, additional data include harvest and banding data. Guthrie Zimmerman and colleagues (2017) combine these sources of information to parameterize an integrated population model for Wood Ducks in the Eastern Flyway, allowing estimation of an elusive but coveted result—total population size.

Bird Conservation Regions (BCRs) and spatial coverage of the Atlantic Flyway Breeding Waterfowl Survey (AFBWS; states with hatch marks) in the Atlantic Flyway. The Breeding Bird Survey (BBS) occurs in all states throughout the Atlantic Flyway. See Zimmerman et al. 2017.

 

Full integrated population model and data used to estimate Wood Duck annual breeding population size (NBPOP,t) in the Atlantic Flyway, 1998–2015. Ovals surround data sources and boxes surround parameters estimated from data. BBS = Breeding Bird Survey; AFBWS = Atlantic Flyway Breeding Waterfowl Survey; NFPOP,t = fall population size; S = survival (S = annual, SS–F = Spring−Fall, SF–S = Fall−Spring); and R = recruitment. Differential vulnerability refers to the vulnerability difference between juveniles and adults. Parameters are indexed by age (adult vs. juvenile), sex, and time (categorical year, t) effects when included in the model. See Zimmerman et al. 2017.

Concern over population declines in familiar birds motivated Chan Robbins and his early collaborators in the U.S. and Canada to develop the BBS. From these roots, application of the data to conservation questions remains central to participants, analysts, and conservation planners. Two papers in this Special Collection describe how BBS data are used for conservation. Ken Rosenberg and colleagues (2017) describe how population trends from the BBS drive prioritization decisions in Canada, the U.S., and Mexico by the conservation consortium Partners in Flight.

Marie-Anne Hudson and colleagues (2017) review applications of BBS data for conservation actions, from listing species for legal protection to managing harvest of game species.

An illustration of the flow of information and steps required for the species conservation cycle. The North American Breeding Bird Survey (BBS) contributes information to the assessment of species status, the identification of species at risk, the development of conservation targets and plans, and the evaluation of conservation actions. The identification, assessment, and protection of species at risk flow from the main species conservation cycle, and feed back into it. Data from the BBS also help to identify drivers of population change, which can then inform conservation actions and legal listing processes. See Hudson et al. 2017.

We are happy to share these papers published in The Condor: Ornithological Applications as a way of acknowledging the first 50 years of the BBS. Congratulations to all who have participated!

Breeding Bird Survey Articles – All Open Access

In Dedication to Chandler S. Robbins (1918–2017) by Keith L. Pardieck. The Condor 119(3):505. Published July 26, 2017.

The first 50 years of the North American Breeding Bird Survey by J. R. Sauer, Keith L. Pardieck, David J. Ziolkowski, Jr., Adam C. Smith, Marie-Anne R. Hudson, Vicente Rodriguez, Humberto Berlanga, Daniel K. Niven, and William A. Link. The Condor 119(3):576–593. Published July 26, 2017.

Model selection for the North American Breeding Bird Survey: A comparison of methods by William A. Link, John R. Sauer, and Daniel K. Niven. The Condor 119(3):546–556. Published July 26, 2017.v

How well do route survey areas represent landscapes at larger spatial extents? An analysis of land cover composition along Breeding Bird Survey routes by Joseph A. Veech, Keith L. Pardieck, and David J. Ziolkowski, Jr. The Condor 119(3):607–615. Published July 26, 2017.

Developing spatial models to guide conservation of grassland birds in the U.S. Northern Great Plains by Neal D. Niemuth, Michael E. Estey, Sean P. Fields, Brian Wangler, Andy A. Bishop, Pamela J. Moore, Roger C. Grosse, and Adam J. Ryba. The Condor 119(3):506–525. Published July 26, 2017.

Combined analysis of roadside and off-road breeding bird survey data to assess population change in Alaska by Colleen M. Handel and John R. Sauer. The Condor 119(3):557–575. Published July 26, 2017.

Integrating Breeding Bird Survey and demographic data to estimate Wood Duck population size in the Atlantic Flyway by Guthrie S. Zimmerman, John R. Sauer, G. Scott Boomer, Patrick K. Devers, and Pamela R. Garrettson. The Condor 119(3):616–628. Published July 26, 2017.

Use of North American Breeding Bird Survey data in avian conservation assessments by Kenneth V. Rosenberg, Peter J. Blancher, Jessica C. Stanton, and Arvind O. Panjabi. The Condor 119(3):594–606. Published July 26, 2017.

The role of the North American Breeding Bird Survey in conservation by Marie-Anne R. Hudson, Charles M. Francis, Kate J. Campbell, Constance M. Downes, Adam C. Smith, and Keith L. Pardieck. The Condor 119(3):526–545. Published July 26, 2017.