Análise comportamental e distribuição da atividade pesqueira no Arquipelágo de Fernando de Noronha (Nordeste, BR) baseada em dados de GPS
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Tipo de documento: | Dissertação |
Idioma: | por |
Título da fonte: | Biblioteca Digital de Teses e Dissertações da UFRPE |
Texto Completo: | http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/8424 |
Resumo: | Information on the temporal dynamics of the fishing fleets has been widely used to infer many aspects of fisheries science, such as the evaluation of species distribution patterns, investigate impacts on habitats due to fishing effort, in distribution of fishing vessels, among others. In this work we described the spatial distribution and catch composition of the artisanal and recreational fleets of the Fernando de Noronha Archipelago, based on GPS data. For the description of the spatial distribution, a Hidden Markov model was applied in order to segment the trajectories in different activities, called behavioral states. Onboard observer’s data from 21% of the trips monitored via GPS were used to validate the prediction of the models. Values of accuracy over and underestimation of fishing activity estimated by the modeling were calculated through confusion matrixes. In addition, random forest models were applied to define which variables (subset, interpolation period, number of states, step distribution family and angular distribution family) were most important in the accuracy, over and underestimation. According to distribution results, both fleets occupy similar areas, tending to perform fishing at points traditionally known by fishermen. However, although sharing similar fishing zones the composition and structure of catches differ among fishery fleet. The artisanal fleet concentrates its catch on medium-sized individuals, mainly barracudas (Sphyraena barracuda) and rainbow runner (Elagatis bipinnulata), while the recreative catches fish of more varied sizes, mainly barracudas and tunas. Regarding the modeling of the fishing trajectories, the models generally obtained good values of accuracy between 58% and 79%. In addition, the mean overestimation and mean underestimation of fishing activity were approximately 21% and 6%, respectively. According to results from the random forests, the subset, number of states and period of interpolation were considered the most influential variables for accuracy, overestimation and underestimation of catching state. It was observed that the models tended to overestimate fishing events in high sinuosity and high-speed segments. In addition, models also underestimated fishing in portions of the trajectory where boats sailed straight and at moderate speed. In relation to the number of states, the addition of a third behavioral state resulted in better accuracy results, but it did not mean the increment of a new behavioral state serving only to refine the estimation of the fishing state. In general, the results obtained in this work can help to understand the spatial dynamics of the fishing fleets of Fernando de Noronha, highlighting important fishing areas that mostly surround the limits of the Marine National Park. The information presented here may serve to better clarify the particularities of the artisanal and recreational fishermen of the archipelago and also in the forecast the impacts that changes in the conservation units could cause in the distribution of the vessels. |
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BERTRAND, Sophie Annick Nathalie LancoFERREIRA, Beatrice PadovaniANDRADE, Humber Agrelli dehttp://lattes.cnpq.br/2345443656412096COSTA, Tatiana Beltrão Alves da2019-12-10T15:24:05Z2019-05-17COSTA, Tatiana Beltrão Alves da. Análise comportamental e distribuição da atividade pesqueira no Arquipelágo de Fernando de Noronha (Nordeste, BR) baseada em dados de GPS. 2019. 55 f. Dissertação (Programa de Pós-Graduação em Recursos Pesqueiros e Aquicultura) - Universidade Federal Rural de Pernambuco, Recife.http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/8424Information on the temporal dynamics of the fishing fleets has been widely used to infer many aspects of fisheries science, such as the evaluation of species distribution patterns, investigate impacts on habitats due to fishing effort, in distribution of fishing vessels, among others. In this work we described the spatial distribution and catch composition of the artisanal and recreational fleets of the Fernando de Noronha Archipelago, based on GPS data. For the description of the spatial distribution, a Hidden Markov model was applied in order to segment the trajectories in different activities, called behavioral states. Onboard observer’s data from 21% of the trips monitored via GPS were used to validate the prediction of the models. Values of accuracy over and underestimation of fishing activity estimated by the modeling were calculated through confusion matrixes. In addition, random forest models were applied to define which variables (subset, interpolation period, number of states, step distribution family and angular distribution family) were most important in the accuracy, over and underestimation. According to distribution results, both fleets occupy similar areas, tending to perform fishing at points traditionally known by fishermen. However, although sharing similar fishing zones the composition and structure of catches differ among fishery fleet. The artisanal fleet concentrates its catch on medium-sized individuals, mainly barracudas (Sphyraena barracuda) and rainbow runner (Elagatis bipinnulata), while the recreative catches fish of more varied sizes, mainly barracudas and tunas. Regarding the modeling of the fishing trajectories, the models generally obtained good values of accuracy between 58% and 79%. In addition, the mean overestimation and mean underestimation of fishing activity were approximately 21% and 6%, respectively. According to results from the random forests, the subset, number of states and period of interpolation were considered the most influential variables for accuracy, overestimation and underestimation of catching state. It was observed that the models tended to overestimate fishing events in high sinuosity and high-speed segments. In addition, models also underestimated fishing in portions of the trajectory where boats sailed straight and at moderate speed. In relation to the number of states, the addition of a third behavioral state resulted in better accuracy results, but it did not mean the increment of a new behavioral state serving only to refine the estimation of the fishing state. In general, the results obtained in this work can help to understand the spatial dynamics of the fishing fleets of Fernando de Noronha, highlighting important fishing areas that mostly surround the limits of the Marine National Park. The information presented here may serve to better clarify the particularities of the artisanal and recreational fishermen of the archipelago and also in the forecast the impacts that changes in the conservation units could cause in the distribution of the vessels.Informações sobre a dinâmica espaço temporal das frotas pesqueiras vem sendo amplamente utilizada para inferir sobre diversos aspectos da ciência pesqueira, como na avaliação de padrões de distribuição de espécies, investigar impactos sobre habitats devido ao esforço pesqueiro, na distribuição das embarcações de pesca, entre outros. Neste trabalho descrevemos a distribuição espacial e a composição de captura de acordo das frotas artesanal e recreativa do Arquipélago de Fernando de Noronha, baseando-se em dados de GPS. Para descrição da distribuição espacial foi aplicado um modelo Oculto de Markov a fim de segmentar as trajetórias em diferentes atividades, denominadas estados comportamentais. Para validar a predição dos modelos foram utilizados dados de observador de bordo que acompanharam 20% das viagens monitoradas via GPS. Valores de acurácia sobre e subestimação da atividade pesqueira estimadas pela modelagem foram calculados através de matrizes de confusão. Além disso, foram aplicados modelos de florestas aleatórias para definir quais variáveis (banco de dados, período de interpolação, número de estados, família de distribuição dos passos e família de distribuição dos ângulos) eram mais importantes na acurácia, sobre e subestimação da pesca de acordo com modelos. De acordo com resultados de distribuição, ambas frotas ocupam áreas similares, tendendo a desempenhar a pesca em pontos tradicionalmente conhecidos pelos pescadores. No entanto, ainda que compartilhando zonas pesqueiras parecidas as composição e estrutura das capturas diferem-se. A frota artesanal concentra sua captura em indivíduos de tamanho médio, principalmente barracudas (Sphyraena barracuda) e peixe-rei (Elagatis bipinnulata), enquanto que a pesca esportiva captura peixes de tamanhos mais variados, sendo eles principalmente barracudas e tunídeos. Quanto a modelagem das trajetórias pesqueiras, de modo geral os modelos obtiveram bons valores de acurácia entre 58% e 79%. Além disso, sobre estimação e subestimação média da atividade de pesca ficaram em aproximadamente 21% e 6.5%, respectivamente. Segundo resultados das florestas aleatórias, o tipo de banco de dados, número de estados e período de interpolação foram consideras as variáveis mais influentes para variação da acurácia, sobre estimação e subestimação do estado de captura. Foi observado que os modelos tenderam a sobrestimar eventos de pesca em percursos com alta sinuosidade e alta velocidade. Em adição, modelos também subestimaram a pesca em porções da trajetória onde os barcos navegavam em linha reta e em velocidade moderada. Em relação ao número de estados, a adição de um terceiro estado comportamental não significou o incremento de um novo estado comportamental servindo apenas para o refinamento da estimação do estado de pesca. No geral, os resultados adquiridos nesse trabalho podem auxiliar o entendimento da dinâmica espacial das frotas pesqueiras de Fernando de Noronha, salientando importantes zonas de pesca que em sua maioria circundam os limites do Parque Nacional Marinho. As informações aqui apresentadas podem servir para melhor esclarecer as particularidades dos pescadores artesanais e recreativos de Fernando de Noronha e também na previsão de quais impactos alterações nas unidades de conservação poderiam causar na distribuição das embarcações.Submitted by Mario BC (mario@bc.ufrpe.br) on 2019-12-10T15:24:05Z No. of bitstreams: 1 Tatiana Beltrao Alves da Costa.pdf: 979592 bytes, checksum: 54c37ea241291a14a08677cc3fda61b5 (MD5)Made available in DSpace on 2019-12-10T15:24:05Z (GMT). No. of bitstreams: 1 Tatiana Beltrao Alves da Costa.pdf: 979592 bytes, checksum: 54c37ea241291a14a08677cc3fda61b5 (MD5) Previous issue date: 2019-05-17application/pdfporUniversidade Federal Rural de PernambucoPrograma de Pós-Graduação em Recursos Pesqueiros e AquiculturaUFRPEBrasilDepartamento de Pesca e AquiculturaFrota pesqueiraAtividade pesqueiraFernando de Noronha (PE)GeolocalizaçãoCIENCIAS AGRARIAS::RECURSOS PESQUEIROS E ENGENHARIA DE PESCAAnálise comportamental e distribuição da atividade pesqueira no Arquipelágo de Fernando de Noronha (Nordeste, BR) baseada em dados de GPSinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesis80217415640343225476006006007231936942857037408-6131750198709519811info:eu-repo/semantics/openAccessreponame:Biblioteca Digital de Teses e Dissertações da UFRPEinstname:Universidade Federal Rural de Pernambuco (UFRPE)instacron:UFRPEORIGINALTatiana Beltrao Alves da Costa.pdfTatiana Beltrao Alves da Costa.pdfapplication/pdf979592http://www.tede2.ufrpe.br:8080/tede2/bitstream/tede2/8424/2/Tatiana+Beltrao+Alves+da+Costa.pdf54c37ea241291a14a08677cc3fda61b5MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-82165http://www.tede2.ufrpe.br:8080/tede2/bitstream/tede2/8424/1/license.txtbd3efa91386c1718a7f26a329fdcb468MD51tede2/84242019-12-10 12:24:05.148oai:tede2: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Biblioteca Digital de Teses e Dissertaçõeshttp://www.tede2.ufrpe.br:8080/tede/PUBhttp://www.tede2.ufrpe.br:8080/oai/requestbdtd@ufrpe.br ||bdtd@ufrpe.bropendoar:2024-05-28T12:36:57.495151Biblioteca Digital de Teses e Dissertações da UFRPE - Universidade Federal Rural de Pernambuco (UFRPE)false |
dc.title.por.fl_str_mv |
Análise comportamental e distribuição da atividade pesqueira no Arquipelágo de Fernando de Noronha (Nordeste, BR) baseada em dados de GPS |
title |
Análise comportamental e distribuição da atividade pesqueira no Arquipelágo de Fernando de Noronha (Nordeste, BR) baseada em dados de GPS |
spellingShingle |
Análise comportamental e distribuição da atividade pesqueira no Arquipelágo de Fernando de Noronha (Nordeste, BR) baseada em dados de GPS COSTA, Tatiana Beltrão Alves da Frota pesqueira Atividade pesqueira Fernando de Noronha (PE) Geolocalização CIENCIAS AGRARIAS::RECURSOS PESQUEIROS E ENGENHARIA DE PESCA |
title_short |
Análise comportamental e distribuição da atividade pesqueira no Arquipelágo de Fernando de Noronha (Nordeste, BR) baseada em dados de GPS |
title_full |
Análise comportamental e distribuição da atividade pesqueira no Arquipelágo de Fernando de Noronha (Nordeste, BR) baseada em dados de GPS |
title_fullStr |
Análise comportamental e distribuição da atividade pesqueira no Arquipelágo de Fernando de Noronha (Nordeste, BR) baseada em dados de GPS |
title_full_unstemmed |
Análise comportamental e distribuição da atividade pesqueira no Arquipelágo de Fernando de Noronha (Nordeste, BR) baseada em dados de GPS |
title_sort |
Análise comportamental e distribuição da atividade pesqueira no Arquipelágo de Fernando de Noronha (Nordeste, BR) baseada em dados de GPS |
author |
COSTA, Tatiana Beltrão Alves da |
author_facet |
COSTA, Tatiana Beltrão Alves da |
author_role |
author |
dc.contributor.advisor1.fl_str_mv |
BERTRAND, Sophie Annick Nathalie Lanco |
dc.contributor.referee1.fl_str_mv |
FERREIRA, Beatrice Padovani |
dc.contributor.referee2.fl_str_mv |
ANDRADE, Humber Agrelli de |
dc.contributor.authorLattes.fl_str_mv |
http://lattes.cnpq.br/2345443656412096 |
dc.contributor.author.fl_str_mv |
COSTA, Tatiana Beltrão Alves da |
contributor_str_mv |
BERTRAND, Sophie Annick Nathalie Lanco FERREIRA, Beatrice Padovani ANDRADE, Humber Agrelli de |
dc.subject.por.fl_str_mv |
Frota pesqueira Atividade pesqueira Fernando de Noronha (PE) Geolocalização |
topic |
Frota pesqueira Atividade pesqueira Fernando de Noronha (PE) Geolocalização CIENCIAS AGRARIAS::RECURSOS PESQUEIROS E ENGENHARIA DE PESCA |
dc.subject.cnpq.fl_str_mv |
CIENCIAS AGRARIAS::RECURSOS PESQUEIROS E ENGENHARIA DE PESCA |
description |
Information on the temporal dynamics of the fishing fleets has been widely used to infer many aspects of fisheries science, such as the evaluation of species distribution patterns, investigate impacts on habitats due to fishing effort, in distribution of fishing vessels, among others. In this work we described the spatial distribution and catch composition of the artisanal and recreational fleets of the Fernando de Noronha Archipelago, based on GPS data. For the description of the spatial distribution, a Hidden Markov model was applied in order to segment the trajectories in different activities, called behavioral states. Onboard observer’s data from 21% of the trips monitored via GPS were used to validate the prediction of the models. Values of accuracy over and underestimation of fishing activity estimated by the modeling were calculated through confusion matrixes. In addition, random forest models were applied to define which variables (subset, interpolation period, number of states, step distribution family and angular distribution family) were most important in the accuracy, over and underestimation. According to distribution results, both fleets occupy similar areas, tending to perform fishing at points traditionally known by fishermen. However, although sharing similar fishing zones the composition and structure of catches differ among fishery fleet. The artisanal fleet concentrates its catch on medium-sized individuals, mainly barracudas (Sphyraena barracuda) and rainbow runner (Elagatis bipinnulata), while the recreative catches fish of more varied sizes, mainly barracudas and tunas. Regarding the modeling of the fishing trajectories, the models generally obtained good values of accuracy between 58% and 79%. In addition, the mean overestimation and mean underestimation of fishing activity were approximately 21% and 6%, respectively. According to results from the random forests, the subset, number of states and period of interpolation were considered the most influential variables for accuracy, overestimation and underestimation of catching state. It was observed that the models tended to overestimate fishing events in high sinuosity and high-speed segments. In addition, models also underestimated fishing in portions of the trajectory where boats sailed straight and at moderate speed. In relation to the number of states, the addition of a third behavioral state resulted in better accuracy results, but it did not mean the increment of a new behavioral state serving only to refine the estimation of the fishing state. In general, the results obtained in this work can help to understand the spatial dynamics of the fishing fleets of Fernando de Noronha, highlighting important fishing areas that mostly surround the limits of the Marine National Park. The information presented here may serve to better clarify the particularities of the artisanal and recreational fishermen of the archipelago and also in the forecast the impacts that changes in the conservation units could cause in the distribution of the vessels. |
publishDate |
2019 |
dc.date.accessioned.fl_str_mv |
2019-12-10T15:24:05Z |
dc.date.issued.fl_str_mv |
2019-05-17 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.citation.fl_str_mv |
COSTA, Tatiana Beltrão Alves da. Análise comportamental e distribuição da atividade pesqueira no Arquipelágo de Fernando de Noronha (Nordeste, BR) baseada em dados de GPS. 2019. 55 f. Dissertação (Programa de Pós-Graduação em Recursos Pesqueiros e Aquicultura) - Universidade Federal Rural de Pernambuco, Recife. |
dc.identifier.uri.fl_str_mv |
http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/8424 |
identifier_str_mv |
COSTA, Tatiana Beltrão Alves da. Análise comportamental e distribuição da atividade pesqueira no Arquipelágo de Fernando de Noronha (Nordeste, BR) baseada em dados de GPS. 2019. 55 f. Dissertação (Programa de Pós-Graduação em Recursos Pesqueiros e Aquicultura) - Universidade Federal Rural de Pernambuco, Recife. |
url |
http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/8424 |
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por |
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por |
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info:eu-repo/semantics/openAccess |
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openAccess |
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application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Federal Rural de Pernambuco |
dc.publisher.program.fl_str_mv |
Programa de Pós-Graduação em Recursos Pesqueiros e Aquicultura |
dc.publisher.initials.fl_str_mv |
UFRPE |
dc.publisher.country.fl_str_mv |
Brasil |
dc.publisher.department.fl_str_mv |
Departamento de Pesca e Aquicultura |
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Universidade Federal Rural de Pernambuco |
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