Evaluating the use of drones for monitoring waterbird nest abundance and nest survival

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dc.contributor.advisorGawlik, Dale
dc.contributor.authorMirzadi, Rostam
dc.contributor.committeeMemberStunz, Greg
dc.contributor.committeeMemberStarek, Michael
dc.creator.orcidhttps://orcid.org/0000-0001-9592-1440
dc.date.accessioned2023-08-07T20:01:53Z
dc.date.available2023-08-07T20:01:53Z
dc.date.issued2022-12
dc.descriptionA Thesis Submitted In Partial Fulfillment of the Requirements for the Degree of MASTER OF SCIENCE in Biology Department of Life Sciences from Texas A&M University-Corpus Christi.
dc.description.abstractSurveys of colonial waterbirds are used to monitor species’ population dynamics, contaminant levels, and to derive metrics that can be used to assess wetland ecosystem restoration and management. Previous studies have found that drone surveys provide accurate estimates of nest abundance and survival for ground-nesting waterbird species such as terns (Laridae Spp.), but drones have not been used to estimate survival for waterbirds nesting in a canopied marsh habitat, and potential sources of bias in drone surveys have not been examined in depth. We examined potential visibility biases associated with using a drone to survey colonies of wading birds (Ciconiiformes and Pelecaniformes) in marsh habitat in Florida in 2020 and 2021. Monthly nest counts and survival were compared between traditional (combination of fixed-wing aircraft and ground surveys) and drone survey methods. Ground-based and drone nest transect surveys were conducted to estimate survival and detection probabilities of each species and plumage color. Generalized linear mixed-effects models were used to quantify the degree to which visual occlusion of nests in?uenced detectability. Estimates of white-colored waterbird nests were significantly greater for drone surveys than those derived from traditional survey methods but estimates of dark-colored waterbirds from drone surveys were biased low. Variation in detection was best explained by canopy cover, plumage color, and nest stage. Overall, there was no difference between survival estimates from either method. However, drone-derived estimates of dark-colored waterbirds had lower accuracy. Our results suggest that drone surveys are a viable method to conduct monthly nest surveys and estimate survival of waterbirds breeding in marsh habitat, but researchers should consider their study area and species before choosing a survey method.
dc.description.collegeCollege of Science
dc.description.departmentBiology
dc.format.extent74 pages
dc.identifier.urihttps://hdl.handle.net/1969.6/96900
dc.language.isoen_USen_US
dc.rightsThis material is made available for use in research, teaching, and private study, pursuant to U.S. Copyright law. The user assumes full responsibility for any use of the materials, including but not limited to, infringement of copyright and publication rights of reproduced materials. Any materials used should be fully credited with its source. All rights are reserved and retained regardless of current or future development or laws that may apply to fair use standards. Permission for publication of this material, in part or in full, must be secured with the author and/or publisher.
dc.rightsThis material is made available for use in research, teaching, and private study, pursuant to U.S. Copyright law. The user assumes full responsibility for any use of the materials, including but not limited to, infringement of copyright and publication rights of reproduced materials. Any materials used should be fully credited with its source. All rights are reserved and retained regardless of current or future development or laws that may apply to fair use standards. Permission for publication of this material, in part or in full, must be secured with the author and/or publisher.en_US
dc.titleEvaluating the use of drones for monitoring waterbird nest abundance and nest survivalen_US
dc.typeText
dc.typeTexten_US
dc.type.genreThesis
dc.type.genreThesisen_US
thesis.degree.disciplineBiologyen_US
thesis.degree.grantorTexas A & M University--Corpus Christi
thesis.degree.grantorTexas A & M University--Corpus Christien_US
thesis.degree.levelMastersen_US
thesis.degree.nameMaster of Scienceen_US

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