%0 Journal Article %1 winter_modeling_2011 %A Winter, Andreas %A Jiao, Yan %A Browder, Joan A. %D 2011 %J Waterbirds %K Atlantic, Fisheries, bycatch, distribution modelling seabirds, species %N 3 %P 289--303 %R 10.1675/063.034.0304 %T Modeling Low Rates of Seabird Bycatch in the U.S. Atlantic Longline Fishery %U http://www.bioone.org/doi/abs/10.1675/063.034.0304 %V 34 %X Total annual seabird bycatch in the U.S. Atlantic pelagic longline fishery was estimated from observer data by means of alternative methods to address the low frequency and uneven distribution of bird bycatch observations. Models used for estimation included generalized additive models (GAM), generalized linear models (GLM) and GLM with spatial or spatio-temporally autocorrelated bycatch observations (s-GLM). Models were fitted separately to the probability of non-zero seabird capture (presence/absence) and to the numbers of seabirds per non-zero capture (positive bycatch); final estimates were obtained as the product of the two. Best-fitting models included latitude, longitude and quarter of year as covariates for presence/absence, and numbers of hooks per set for positive bycatch. Among the models compared, GLM gave the most consistent predictions of annual total seabird captures. For 2008, the most recent year modeled, GLM predicted 81 seabirds caught in 8,862 sets. The number is small on an Atlantic-wide or world-wide scale but is concentrated in an area of high species diversity that includes relatively small populations. GLM was recommended to be used in future Atlantic pelagic longline seabird bycatch estimation.

@article{winter_modeling_2011, abstract = {Total annual seabird bycatch in the U.S. Atlantic pelagic longline fishery was estimated from observer data by means of alternative methods to address the low frequency and uneven distribution of bird bycatch observations. Models used for estimation included generalized additive models (GAM), generalized linear models (GLM) and GLM with spatial or spatio-temporally autocorrelated bycatch observations (s-GLM). Models were fitted separately to the probability of non-zero seabird capture (presence/absence) and to the numbers of seabirds per non-zero capture (positive bycatch); final estimates were obtained as the product of the two. Best-fitting models included latitude, longitude and quarter of year as covariates for presence/absence, and numbers of hooks per set for positive bycatch. Among the models compared, GLM gave the most consistent predictions of annual total seabird captures. For 2008, the most recent year modeled, GLM predicted 81 seabirds caught in 8,862 sets. The number is small on an Atlantic-wide or world-wide scale but is concentrated in an area of high species diversity that includes relatively small populations. GLM was recommended to be used in future Atlantic pelagic longline seabird bycatch estimation.}, added-at = {2017-01-09T13:57:26.000+0100}, author = {Winter, Andreas and Jiao, Yan and Browder, Joan A.}, biburl = {https://www.bibsonomy.org/bibtex/22b8eb92f2bdfb55040f715c204b32e67/yourwelcome}, doi = {10.1675/063.034.0304}, interhash = {c183a6cb697e3654d4172aca1dd3a7ff}, intrahash = {2b8eb92f2bdfb55040f715c204b32e67}, issn = {1524-4695, 1938-5390}, journal = {Waterbirds}, keywords = {Atlantic, Fisheries, bycatch, distribution modelling seabirds, species}, month = sep, number = 3, pages = {289--303}, timestamp = {2017-01-09T14:01:11.000+0100}, title = {Modeling {Low} {Rates} of {Seabird} {Bycatch} in the {U}.{S}. {Atlantic} {Longline} {Fishery}}, url = {http://www.bioone.org/doi/abs/10.1675/063.034.0304}, urldate = {2012-07-26}, volume = 34, year = 2011 }