Cornell Laboratory of Ornithology

Laboratory of, United States

Cornell Laboratory of Ornithology

Laboratory of, United States
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Shirk J.L.,Cornell Laboratory of Ornithology | Ballard H.L.,University of California at Davis | Wilderman C.C.,Dickinson College | Phillips T.,Cornell Laboratory of Ornithology | And 7 more authors.
Ecology and Society | Year: 2012

Members of the public participate in scientific research in many different contexts, stemming from traditions as varied as participatory action research and citizen science. Particularly in conservation and natural resource management contexts, where research often addresses complex social-ecological questions, the emphasis on and nature of this participation can significantly affect both the way that projects are designed and the outcomes that projects achieve. We review and integrate recent work in these and other fields, which has converged such that we propose the term public participation in scientific research (PPSR) to discuss initiatives from diverse fields and traditions. We describe three predominant models of PPSR and call upon case studies suggesting that-regardless of the research context-project outcomes are influenced by (1) the degree of public participation in the research process and (2) the quality of public participation as negotiated during project design. To illustrate relationships between the quality of participation and outcomes, we offer a framework that considers how scientific and public interests are negotiated for project design toward multiple, integrated goals. We suggest that this framework and models, used in tandem, can support deliberate design of PPSR efforts that will enhance their outcomes for scientific research, individual participants, and social-ecological systems. © 2012 by the author(s).

Deruiter S.L.,University of St. Andrews | Boyd I.L.,University of St. Andrews | Claridge D.E.,Bahamas Marine Mammal Research Organisation | Clark C.W.,Cornell Laboratory of Ornithology | And 3 more authors.
Marine Mammal Science | Year: 2013

In 2007 and 2008, controlled exposure experiments were performed in the Bahamas to study behavioral responses to simulated mid-frequency active sonar (MFA) by three groups of odontocetes: false killer whales, Pseudorca crassidens; short-finned pilot whales, Globicephala macrorhynchus; and melon-headed whales, Peponocephala electra. An individual in each group was tagged with a Dtag to record acoustic and movement data. During exposures, some individuals produced whistles that seemed similar to the experimental MFA stimulus. Statistical tests were thus applied to investigate whistle-MFA similarity and the relationship between whistle production rate and MFA reception time. For the false killer whale group, overall whistle rate and production rate of the most MFA-like whistles decreased with time since last MFA reception. Despite quite low whistle rates overall by the melon-headed whales, statistical results indicated minor transient silencing after each signal reception. There were no apparent relationships between pilot whale whistle rates and MFA sounds within the exposure period. This variability of responses suggests that changes in whistle production in response to acoustic stimuli depend not only on species and sound source, but also on the social, behavioral, or environmental contexts of exposure. © 2012 by the Society for Marine Mammalogy.

PubMed | Cornell Laboratory of Ornithology and University of California at Davis
Type: Journal Article | Journal: Public understanding of science (Bristol, England) | Year: 2015

Over the past 20 years, thousands of citizen science projects engaging millions of participants in collecting and/or processing data have sprung up around the world. Here we review documented outcomes from four categories of citizen science projects which are defined by the nature of the activities in which their participants engage - Data Collection, Data Processing, Curriculum-based, and Community Science. We find strong evidence that scientific outcomes of citizen science are well documented, particularly for Data Collection and Data Processing projects. We find limited but growing evidence that citizen science projects achieve participant gains in knowledge about science knowledge and process, increase public awareness of the diversity of scientific research, and provide deeper meaning to participants hobbies. We also find some evidence that citizen science can contribute positively to social well-being by influencing the questions that are being addressed and by giving people a voice in local environmental decision making. While not all citizen science projects are intended to achieve a greater degree of public understanding of science, social change, or improved science -society relationships, those projects that do require effort and resources in four main categories: (1) project design, (2) outcomes measurement, (3) engagement of new audiences, and (4) new directions for research.

Huang J.-B.,University of Illinois at Urbana - Champaign | Caruana R.,Microsoft | Farnsworth A.,Cornell Laboratory of Ornithology | Kelling S.,Cornell Laboratory of Ornithology | Ahuja N.,University of Illinois at Urbana - Champaign
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition | Year: 2016

Bird migration is a critical indicator of environmental health, biodiversity, and climate change. Existing techniques for monitoring bird migration are either expensive (e.g., satellite tracking), labor-intensive (e.g., moon watching), indirect and thus less accurate (e.g., weather radar), or intrusive (e.g., attaching geolocators on captured birds). In this paper, we present a vision-based system for detecting migrating birds in flight at night. Our system takes stereo videos of the night sky as inputs, detects multiple flying birds and estimates their orientations, speeds, and altitudes. The main challenge lies in detecting flying birds of unknown trajectories under high noise level due to the low-light environment. We address this problem by incorporating stereo constraints for rejecting physically implausible configurations and gathering evidence from two (or more) views. Specifically, we develop a robust stereo-based 3D line fitting algorithm for geometric verification and a deformable part response accumulation strategy for trajectory verification. We demonstrate the effectiveness of the proposed approach through quantitative evaluation of real videos of birds migrating at night collected with near-infrared cameras.

Keen S.,Bioacoustics Research Program | Ross J.C.,Cornell Laboratory of Ornithology | Griffiths E.T.,Bioacoustics Research Program | Lanzone M.,Powdermill Avian Research Center | Farnsworth A.,Cornell Laboratory of Ornithology
Ecological Informatics | Year: 2014

Numerous methods are available for analysis of avian vocalizations, but few research efforts have compared recent methods for calculating and evaluating similarity among calls, particularly those collected in the field. This manuscript compares a suite of methodologies for analyzing flight calls of New World warblers, investigating the effectiveness of four techniques for calculating call similarity: (1) spectrographic cross-correlation, (2) dynamic time warping, (3) Euclidean distance between spectrogram-based feature measurements, and (4) random forest distance between spectrogram-based feature measurements. We tested these methods on flight calls, which are short, structurally simple vocalizations typically used during nocturnal migration, as these signals may contain important ecological or demographic information. Using the four techniques listed above, we classified flight calls from three datasets, one collected from captive birds and two collected from wild birds in the field. Each dataset contained an equal number of calls from four warbler species commonly recorded during acoustic monitoring: American Redstart, Chestnut-sided Warbler, Hooded Warbler, and Ovenbird. Using captive recordings to train the classification models, we created four similarity-based classifiers which were then tested on the captive and field datasets. We show that these classification methods are limited in their ability to successfully classify the calls of these warbler species, and that classification accuracy was lower on field recordings than captive recordings for each of the tested methods. Of the four methods we compared, the random forest technique had the highest classification accuracy, enabling correct classification of 67.6% of field recordings. To compare the performance of the automated techniques to manual classification, the most common method used in flight call research, human experts were also asked to classify calls from each dataset. The experts correctly classified approximately 90% of field recordings, indicating that although the automated techniques are faster, they remain less accurate than manual classification. However, because of the challenges inherent to these data, such as the structural similarity among the flight calls of focal species and the presence of environmental noise in the field recordings, some of the tested automated classification techniques may be acceptable for real-world applications. We believe that this comparison of broadly applicable methodologies provides information that will prove to be useful for analysis, detection and classification of short duration signals. Based on our results, we recommend that a combination of feature measurements and random forest classification can be used to assign flight calls to species, while human experts oversee the process. © 2014 Elsevier B.V.

Panda B.,Google | Riedewald M.,Northeastern University | Fink D.,Cornell Laboratory of Ornithology
Proceedings - International Conference on Data Engineering | Year: 2010

Modern science is collecting massive amounts of data from sensors, instruments, and through computer simulation. It is widely believed that analysis of this data will hold the key for future scientific breakthroughs. Unfortunately, deriving knowledge from large high-dimensional scientific datasets is difficult. One emerging answer is exploratory analysis using data mining; but data mining models that accurately capture natural processes tend to be very complex and are usually not intelligible. Scientists therefore generate model summaries to find the most important patterns learned by the model. We formalize the model-summary problem and introduce it as a novel problem to the database community. Generating model summaries creates serious data management challenges: Scientists usually want to analyze patterns in different "slices" and "dices" of the data space, comparing the effects of various input variables on the output. We propose novel techniques for efficiently generating such summaries for the popular class of tree-based models. Our techniques leverage workload structure on multiple levels. We also propose a scalable implementation of our techniques in MapReduce. For both sequential and parallel implementation, we achieve speedups of one or more orders of magnitude over the naive algorithm, while guaranteeing the exact same results. © 2010 IEEE.

Ross J.C.,Cornell Laboratory of Ornithology | Allen P.E.,Cornell Laboratory of Ornithology
Ecological Informatics | Year: 2014

Passive acoustic monitoring often leads to large quantities of sound data which are burdensome to process, such that the availability and cost of expert human analysts can be a bottleneck and make ecosystem or landscape-scale projects infeasible. This manuscript presents a method for rapidly analyzing the results of band-limited energy detectors, which are commonly used for the detection of passerine nocturnal flight calls, but which typically are beset by high false positive rates. We first manually classify a subset of the detected events as signals of interest or false detections. From that subset, we build a Random Forest model to eliminate most of the remaining events as false detections without further human inspection. The overall reduction in the labor required to separate signals of interest from false detections can be 80% or more. Additionally, we present an R package, flightcallr, containing functions which can be used to implement this new workflow. © 2013 Elsevier B.V.

Kelling S.,Cornell Laboratory of Ornithology | Lagoze C.,University of Michigan | Wong W.-K.,Oregon State University | Yu J.,Oregon State University | And 5 more authors.
AI Magazine | Year: 2013

EBird is a citizen-science project that takes advantage of the human observational capacity to identify birds to species, and uses these observations to accurately represent patterns of bird occurrences across broad spatial and temporal extents. eBird employs artificial intelligence techniques such as machine learning to improve data quality by taking advantage of the synergies between human computation and mechanical computation. We call this a human/computer learning network, whose core is an active learning feedback loop between humans and machines that dramatically improves the quality of both and thereby continually improves the effectiveness of the network as a whole. In this article we explore how human/computer learning networks can leverage the contributions of human observers and process their contributed data with artificial intelligence algorithms leading to a computational power that far exceeds the sum of the individual parts. Copyright © 2013, Association for the Advancement of Artificial Intelligence.

News Article | December 19, 2016

Two of the oldest and most influential professional ornithological societies in the world have legally merged, forming the American Ornithological Society (AOS), an organization devoted to advancing research focused on birds in the Western Hemisphere, promoting their conservation, and training the next generation of scientists. Nearly 3,000 members of the American Ornithologists' Union and the Cooper Ornithological Society approved the merger earlier this year in association with the North American Ornithological Conference held in Washington D.C. Under the leadership of executive director Melinda Pruett-Jones, AOS is based in Chicago at the Field Museum of Natural History. For more information on the new AOS and the merger process, visit http://www. . "Over the past six years we have actively collaborated as separate organizations: meeting together, publishing our journals jointly and working together to benefit the conservation of birds. After fact-finding and due diligence, and in response to the tremendous positive feedback from our membership, I am proud to announce a single merged society that will advance ornithology by combining our assets - human, financial and intellectual," said AOS president Steven Beissinger. The largest ornithological society in the Western Hemisphere, AOS produces scientific publications of the highest quality, hosts intellectually engaging and professionally vital meetings, serves ornithologists at every career stage, pursues a global perspective, and informs public policy on all issues important to ornithology and ornithological collections. AOS assets now exceed $10 million in support of ornithology, and it will invest nearly $1 million to advance its mission in its first year as a merged society. The new organization is undertaking new initiatives to help students, early professionals and international members and to address the needs of scientists, academics and conservation professionals in advancing knowledge, not only in the Western Hemisphere but across the globe. AOS also recently launched a program to encourage members to reach out to their local communities and showcase ornithology as a STEM (science, technology, engineering, math) field students might not have considered. "The society is redoubling past efforts to prepare future generations of scientists and conservation leaders. Success requires a multi-dimensional approach that integrates science, new technologies, public policy and citizen outreach; works with other ornithological and scientific communities; and collaborates with local, state, federal and international government entities," said former American Ornithologists' Union president Susan Haig, who began the merging effort in 2010. "AOS is distinguished by its tremendous collective expertise, eminent scientists, conservation practitioners, early career innovators, and students. The society will especially focus on attracting diversity in the profession," said former Cooper Ornithological Society president Martin Raphael. The first meeting of the new AOS will be held July 31 to August 5, 2017, on the campus of Michigan State University. The American Ornithological Society (AOS) is an international society devoted to advancing the scientific understanding of birds, enriching ornithology as a profession, and promoting a rigorous scientific basis for the conservation of birds. The AOS publishes two international journals--The Auk: Ornithological Advances, which has one of the highest scientific impact rankings among ornithological journals worldwide, and The Condor: Ornithological Applications. The AOS also publishes the book series Studies in Avian Biology. The society's checklists serve as the accepted authority for scientific nomenclature and English names of birds in North and Middle America, and in South America. The AOS also sponsors The Birds of North America Online in partnership with the Cornell Laboratory of Ornithology. For more information, see http://www.

News Article | November 30, 2016

It's a sparrow-sized marsh bird. It hardly ever flies, and gets around by creeping through dense wetland vegetation. The black rail is a blank spot on many a life list and even most of the sightings are really "hearings," the birder identifying the species by its call—which often comes from a dark swamp in the dead of night. "Most people haven't seen one. Most birders haven't seen one," Bryan Watts said. "It's one of those species that beats birders." Watts, the director of the Center for Conservation Biology, has assembled a report called "Status and distribution of the eastern black rail along the Atlantic and Gulf Coasts of North America." The report to the U.S. Fish and Wildlife Service is part of a 15-year effort spearheaded by the CCB to get the black rail on the federal register of endangered and threatened species. It's the definitive document on the state of this endangered bird in the eastern U.S., but even this definitive document contains a large amount of uncertainty, largely because the black rail has been flying below the radar of professional ornithologists and birders alike since Audubon's day. The study area covers the Atlantic and Gulf Coastal states from Maine to Texas, plus Vermont, West Virginia and Tennessee. The report gives a wide range in estimated black rail population in the area—455 to 1,315 breeding pairs. Just three states, South Carolina, Florida and Texas, account for three quarters of the overall total. Watts said that Florida and Texas population estimates carry a high uncertainty rating, because of the large expanses of likely, but unsurveyed, black rail habitat in those two states. "There has been all this mystery around black rails because birders just can't get onto them," Watts said. "They occur in all these places that are away from where birders have access to." Black rails were discovered breeding in Philadelphia more than 150 years ago, but today there are huge blank spots in even the most basic knowledge about the birds. Watts says that all of the information on the population existed in bits and pieces scattered throughout more than 100 years of journals, museum specimens and unpublished observations. "People ask, 'What's in the literature?' Well, what's in the literature is little, tiny bits and pieces," he said. "The literature goes back to the beginning, which was 1836 in North America." Spoiler: We don't know much about this bird Watts began by compiling a bibliography of black rail observations, wading through more than 6,000 journal issues, checking out museum collections and downloading black rail records from e-bird, the online birding checklist run by the Cornell Laboratory of Ornithology. Watts summed up his findings of looking through decades of ornithological research: Naturalists have never had a good handle on the black rail. There's never been a status assessment on the species, he said, because there isn't much survey data. "You go back to the very beginning; they didn't know anything about this bird," he said. "You come up to the present; we still don't know anything about this bird. It's because of how secretive it is." The birds spend their lives deep in tussocky marshes, making them an extremely challenging species to study. Very few black rails have been banded and their breeding habits are imperfectly understood. Black rails are not even particularly birdlike: Watt's report contains a quote that describes them as "a feathered mouse." "And that's the way they behave, too," he said. "They rarely take flight. They just scurry around. People get little, tiny glimpses of them scurrying between the vegetation. Rails are that way in general, but black rails are off the charts when it comes to how secretive they are." The black rail situation illustrates the degree to which the Center for Conservation Biology and other professional ornithologists rely on the reports of amateur birders. Their secretive habits, preference for out-of-the-way habitat and comparative rarity make the black rail a challenge for recreational birders. Very serious birders will go out of their way to list a black rail, but the black rail is not the least bit charismatic and not particularly attractive. So once a birder checks Laterallus jamaicensis off a life list, he or she is unlikely to go out of the way to look for more black rails. The habits of the birds, combined with the habits of birders, create a perfect drought of information. "We know the distribution of a lot of bird species because birders are good at documenting their location," Watts explained. "There are some exceptions to that, and the black rail is one, because they are so challenging and many birders aren't up to that." Watts said the CCB began its campaign to bring the black rail out of ornithological obscurity about 15 years ago. "We started the Eastern Working Group—I think it was in 2009—meeting with biologists throughout the range, trying to get momentum going," he said. "This particular effort was to compress 150 years of literature and bring us up to the present, so we can stop looking back and hopefully look forward." Despite the challenges posed by gathering patchy evidence on a secretive avian subject, Watts' report arrives at some pretty solid conclusions. Most importantly, he says, the black rail is in trouble as a species. "It looks like they're falling off a cliff," he said, adding that northern populations have experienced a particular crash in numbers. Overall, Watts said, the outlook isn't good for black rails anywhere in their range: The last record of a black rail observation in Virginia dates to 2014. Getting flooded out by sea level rise Secondly, the report notes that much of the bird's preferred habitat—or what's left of it—is doomed, mostly by sea-level rise. Watts said that black rails are known to use a variety of marshy areas, including inland wetlands, ponds, grassy fields and coastal prairies. But 60 percent of the documented sites in the study were classified as tidal salt marsh. To be precise, Watts said, black rails prefer high tidal marsh areas. "They don't like standing water," Watts said. "Now, a Virginia rail will build its nest right above standing water. Black rails won't do that. They want to have moist soil, but not be in the water. They occupy such a narrow hydrologic band of habitat." Watts said that rising sea levels will inundate the black rails' narrow hydrologic band, the area that's normally dampened by only the highest lunar tides. As the narrow band narrows further, the birds are forced out. In fact, Watts notes that much of the black rail's habitat has been long gone. Black rails were first discovered in 1836 by Thomas Rowan on a farm near Philadelphia. Rowan sent his specimens to one Titian Peale, who passed them along to John James Audubon himself. Those first-discovered birds were the basis of the black rail plate in Audubon's Birds of America. "That farm, where Rowan first discovered the species? It's now the Philadelphia airport," Watts said. It's just one example of the extensive loss of wetlands done in post-Civil War period in the name of reclamation, mostly for agricultural use. A crashing population and disappearing habitat make the black rail's prospects rather dim, and Watts acknowledges that the ornithological community and regulators are late in getting the bird's plight under serious consideration. Watts said that the CCB's report will give Fish & Wildlife the information they need to move forward with a designation as per the federal Endangered Species Act. He said he believes the black rail merits a "threatened" designation, denoting a species that is not at the brink of extinction, but is likely to be at the brink in the near future. After the black rail goes on the protected list, Watts said the next step would be to prepare a management plan to maintain the population. In the meantime, the black rails that remain in the east will have to rely on their old defense of extreme secrecy. Explore further: Sandy blows in rare birds (and brings out the birders)

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