CESIMAR - CENPAT   25625
CENTRO PARA EL ESTUDIO DE SISTEMAS MARINOS
Unidad Ejecutora - UE
congresos y reuniones científicas
Título:
Whale watching as a socio-biological system
Autor/es:
CHALCOBSKY B.A.; CHALCOBSKY B.A.; COSCARELLA, M.A.; COSCARELLA, M.A.; CRESPO, E.A.; CRESPO, E.A.
Lugar:
La Spezia
Reunión:
Workshop; IDENTIFYNG KEY RESEARCH QUESTIONS FOR THE MODELLING AND ASSESSMENT OF WHALE WATCHING IMPACTS (MAWI); 2018
Institución organizadora:
International Whaling Commission (SC/67B/REP03 Rev1)
Resumen:
Coscarella gave a presentation on a holistic approach to studying whale watching as part of a ?sociobiological? system (i.e., the interaction between the human socio-political system and the biological system facing whale watching pressure). He offered a case study for how researchers? direct involvement in management increased the influence of whale watching studies on the subsequent behaviour of managers and operators (see also Chalcobsky et al. 2017). Whale watching targeting southern right whales began in Península Valdés, Argentina,in 1973. Building a long-term collaboration with stakeholders, including managers, has allowed the sustainable development of whale watching in this location. This holistic approach focused on setting Limits of AcceptableChange by assessing indicators in four dimensions: Social, Political, Economic and Biological. Social indicators include the percentage of acceptance of whale watching by local inhabitants; attitude changes in people on conservation issues affecting whales; and the importance of the whales in daily life. Political indicators include regulations and governance. Economic indicators include inclusion in the provincial budget of whale watching ?credits? and incentives to whale watching operators. Biological indicators include whale respiration rates (observed from land via theodolite) in the presence and absence of whale watching vessels and an evaluation of the proportion of whales being affected by the activity. Respiration rate data indicate that the presence of whale watching vessels is the only variable influencing changes; collecting these data is a first step toward building bioenergetic models to assess the mid- to long-term impacts of whale watching. All of these indicators will be incorporated into a Bayesian Decision framework.