Laia Rojano Doñate

Harbour porpoises (Phocoena phocoena) inhabit coastal areas with a great overlap of human activities, and therefore are likely to suffer from the effects of its disturbance. Additionally, as top predators in their shallow waters ecosystems, they exert an important role top-down regulating the energy flow through the ecosystem food webs. By using biologgers with acoustic and movement microprocessors (DTAGs) deployed in free-ranging individuals, I study the field energy expenses of these animals, and estimate how they manage their energy budgets both under regular conditions and when expose to anthropogenic disturbance.

The focus of my PhD is to investigate the mechanistic link between behavioural changes caused by anthropogenic disturbances and long-term effects on individual health and vital rates, and how these potential noise effects may lead to population consequences, using harbour porpoises as a model organism. I pursue this objective through a combination of laboratory experiments and innovative field techniques that allow me to i) develop methods for estimating field metabolic rates of captive and wild individuals (Rojano-Doñate et al., 2018), ii) quantify foraging performance (Wisniewska et al., 2016) as well as energy acquisition and expenditure of wild individuals to quantify how anthropogenic stressors affect energy budgets, and subsequently use previous results to iii) develop an agent-based model capable of predicting population dynamic consequences of the increasing levels of noise pollution on individual and population fitness. Results from this PhD are expected to help to improve current knowledge on the effects of anthropogenic disturbance on individual and populations of harbour porpoises, facilitating the creation of mitigation measurement to reduce the impacts of marine anthropogenic activities and improving conservation and management of wild populations of porpoises.


Rojano-Doñate et al (2018)

Wisniewska et al (2017)

Perez et al (2016)

Wisniewska et al (2016)

Christiansen et al (2016)

Dyndo et al (2015)

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