Bycatch is the portion of catch that is neither targeted nor retained by fishermen. It threatens the survival of many marine mammal populations globally, and it occurs in nearly every fishing gear type. Despite its widespread occurrence, observations of bycatch are rare, and scientific data on marine mammal bycatch are limited. Difficulties result in developing models that accurately depict the interactions. This study focuses on developing methodology to combine disparate data sources, specifically data from fishery observer programs and interviews of fishermen, to better understand these interactions and to identify effective mitigation measures. As a case study, this research investigates the spatial and temporal patterns associated with Atlantic white-sided dolphin (Lagenorhynchus acutus) bycatch in the New England bottom trawl fishery for groundfish to aid in the development of an effective bycatch reduction plan. A quasi-binomial model of the fishery observer data was developed using environmental and fishing-related covariates to describe the probability of dolphin bycatch in this fishery. Significant variables in describing dolphin bycatch included sea surface temperature (p<0.001), depth (p<0.001), and an interaction between bottom slope and depth (p<0.05). The model was mapped using geographic information systems and incorporated into interviews with bottom trawl fishermen to facilitate discussion on patterns of bycatch. Thirty-one bottom trawl fishermen were interviewed, and results were consistent with the probability model that bycatch was rare and was more likely to occur in offshore fishing areas. Interviewed fishermen did not relate bycatch to environmental variables and did not provide consistent responses regarding spatial or temporal patterns associated with these events. As a result, this study was unable to develop methodology to spatially combine these data sources. However, fishermen did provide useful information to scientists and fishermen. For instance, interview results suggested that area-based management would not be effective in this fishery, contrary to the results of the probability model, due to the occurrence of bycatch throughout the fishing area. Instead broad-scale measures, coupled with incentives, would be a more effective mitigation measure in this fishery. Collaborative research between fishermen and scientists or gear technologists is recommended to better understand operational patterns associated with bycatch.
","abstract_html":"<p>Bycatch is the portion of catch that is neither targeted nor retained by fishermen. It threatens the survival of many marine mammal populations globally, and it occurs in nearly every fishing gear type. Despite its widespread occurrence, observations of bycatch are rare, and scientific data on marine mammal bycatch are limited. Difficulties result in developing models that accurately depict the interactions. This study focuses on developing methodology to combine disparate data sources, specifically data from fishery observer programs and interviews of fishermen, to better understand these interactions and to identify effective mitigation measures. As a case study, this research investigates the spatial and temporal patterns associated with Atlantic white-sided dolphin (Lagenorhynchus acutus) bycatch in the New England bottom trawl fishery for groundfish to aid in the development of an effective bycatch reduction plan. A quasi-binomial model of the fishery observer data was developed using environmental and fishing-related covariates to describe the probability of dolphin bycatch in this fishery. Significant variables in describing dolphin bycatch included sea surface temperature (p<0.001), depth (p<0.001), and an interaction between bottom slope and depth (p<0.05). The model was mapped using geographic information systems and incorporated into interviews with bottom trawl fishermen to facilitate discussion on patterns of bycatch. Thirty-one bottom trawl fishermen were interviewed, and results were consistent with the probability model that bycatch was rare and was more likely to occur in offshore fishing areas. Interviewed fishermen did not relate bycatch to environmental variables and did not provide consistent responses regarding spatial or temporal patterns associated with these events. As a result, this study was unable to develop methodology to spatially combine these data sources. However, fishermen did provide useful information to scientists and fishermen. For instance, interview results suggested that area-based management would not be effective in this fishery, contrary to the results of the probability model, due to the occurrence of bycatch throughout the fishing area. Instead broad-scale measures, coupled with incentives, would be a more effective mitigation measure in this fishery. Collaborative research between fishermen and scientists or gear technologists is recommended to better understand operational patterns associated with bycatch.</p>","abstract_has_math":false,"creators":["Zollett, Erika A"],"institution":null,"degree_name":"Doctor of Philosophy","degree_level":"Dissertation","degree_discipline":null,"degree_department":null,"school":null,"contributors":["Andrew A Rosenberg"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2008,"date_issued":"2008-01-01T08:00:00Z","date_published":"2008-01-01T08:00:00Z","updated_at":"2026-07-24T05:22:25Z","subjects":["Environmental Sciences","Agriculture","Fisheries and Aquaculture","Biology","Oceanography"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://scholars.unh.edu/dissertation/465","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Andrew A Rosenberg"]},{"key":"dc:creator","label":"Author","values":["Zollett, Erika A"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Environmental Sciences","Agriculture","Fisheries and Aquaculture","Biology","Oceanography"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://scholars.unh.edu/dissertation/465"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Bycatch is the portion of catch that is neither targeted nor retained by fishermen. It threatens the survival of many marine mammal populations globally, and it occurs in nearly every fishing gear type. Despite its widespread occurrence, observations of bycatch are rare, and scientific data on marine mammal bycatch are limited. Difficulties result in developing models that accurately depict the interactions. This study focuses on developing methodology to combine disparate data sources, specifically data from fishery observer programs and interviews of fishermen, to better understand these interactions and to identify effective mitigation measures. As a case study, this research investigates the spatial and temporal patterns associated with Atlantic white-sided dolphin (Lagenorhynchus acutus) bycatch in the New England bottom trawl fishery for groundfish to aid in the development of an effective bycatch reduction plan. A quasi-binomial model of the fishery observer data was developed using environmental and fishing-related covariates to describe the probability of dolphin bycatch in this fishery. Significant variables in describing dolphin bycatch included sea surface temperature (p<0.001), depth (p<0.001), and an interaction between bottom slope and depth (p<0.05). The model was mapped using geographic information systems and incorporated into interviews with bottom trawl fishermen to facilitate discussion on patterns of bycatch. Thirty-one bottom trawl fishermen were interviewed, and results were consistent with the probability model that bycatch was rare and was more likely to occur in offshore fishing areas. Interviewed fishermen did not relate bycatch to environmental variables and did not provide consistent responses regarding spatial or temporal patterns associated with these events. As a result, this study was unable to develop methodology to spatially combine these data sources. However, fishermen did provide useful information to scientists and fishermen. For instance, interview results suggested that area-based management would not be effective in this fishery, contrary to the results of the probability model, due to the occurrence of bycatch throughout the fishing area. Instead broad-scale measures, coupled with incentives, would be a more effective mitigation measure in this fishery. Collaborative research between fishermen and scientists or gear technologists is recommended to better understand operational patterns associated with bycatch.
"]},{"key":"dc:title","label":"Title","values":["Conserving dolphins and fishermen: Combining science and local knowledge to reduce cetacean bycatch"]}]}],"canonical_facts":{"dc:contributor":["Andrew A Rosenberg"],"dc:creator":["Zollett, Erika A"],"dc:description.abstract":["Bycatch is the portion of catch that is neither targeted nor retained by fishermen. It threatens the survival of many marine mammal populations globally, and it occurs in nearly every fishing gear type. Despite its widespread occurrence, observations of bycatch are rare, and scientific data on marine mammal bycatch are limited. Difficulties result in developing models that accurately depict the interactions. This study focuses on developing methodology to combine disparate data sources, specifically data from fishery observer programs and interviews of fishermen, to better understand these interactions and to identify effective mitigation measures. As a case study, this research investigates the spatial and temporal patterns associated with Atlantic white-sided dolphin (Lagenorhynchus acutus) bycatch in the New England bottom trawl fishery for groundfish to aid in the development of an effective bycatch reduction plan. A quasi-binomial model of the fishery observer data was developed using environmental and fishing-related covariates to describe the probability of dolphin bycatch in this fishery. Significant variables in describing dolphin bycatch included sea surface temperature (p<0.001), depth (p<0.001), and an interaction between bottom slope and depth (p<0.05). The model was mapped using geographic information systems and incorporated into interviews with bottom trawl fishermen to facilitate discussion on patterns of bycatch. Thirty-one bottom trawl fishermen were interviewed, and results were consistent with the probability model that bycatch was rare and was more likely to occur in offshore fishing areas. Interviewed fishermen did not relate bycatch to environmental variables and did not provide consistent responses regarding spatial or temporal patterns associated with these events. As a result, this study was unable to develop methodology to spatially combine these data sources. However, fishermen did provide useful information to scientists and fishermen. For instance, interview results suggested that area-based management would not be effective in this fishery, contrary to the results of the probability model, due to the occurrence of bycatch throughout the fishing area. Instead broad-scale measures, coupled with incentives, would be a more effective mitigation measure in this fishery. Collaborative research between fishermen and scientists or gear technologists is recommended to better understand operational patterns associated with bycatch.
"],"dc:identifier":["https://scholars.unh.edu/dissertation/465"],"dc:subject":["Environmental Sciences","Agriculture","Fisheries and Aquaculture","Biology","Oceanography"],"dc:title":["Conserving dolphins and fishermen: Combining science and local knowledge to reduce cetacean bycatch"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Doctor of Philosophy"]},"updated_at":"2026-07-24T05:22:25Z"}