Use this URL to cite or link to this record in EThOS:
Title: Integration of multiple sparse and limited datasets helps to inform spatial conservation for an endangered marine species
Author: Pinto, Cecilia
ISNI:       0000 0004 5918 0464
Awarding Body: University of Aberdeen
Current Institution: University of Aberdeen
Date of Award: 2015
Availability of Full Text:
Access from EThOS:
Full text unavailable from EThOS. Please try the link below.
Access from Institution:
To develop spatial conservation strategies for endangered species it is necessary to understand the drivers of their population dynamics through time and space. When dealing with data limited species it is fundamentally important to develop and apply methods that identify which parameters future data collection should focus on to fill critical knowledge gaps which hinder robust decision making for spatial management. The aim of this study was to integrate data from independent sources in the parameterisation of a spatially realistic individual-based model to explore the potential of defining conservation measures for an endangered species. The case study species in this thesis is Dipturus sp. intermedia (flapper skate), a species that is the focus of conservation attention especially off the West Coast of Scotland. In order to estimate annual survival and transition probabilities between sampling sites, a multisite capture-mark-recapture model was developed in a Bayesian framework, accounting for the heterogeneous effort and individual heterogeneity in the data. Annual survival for the flapper skate was estimated to have been strongly decreasing in the last 30 years. The population showed high residency between sampling sites but connectivity is still present along the sea lochs of the West coast of Scotland. Vertical movement behaviour of flapper skate was found to be mainly driven by the cycle of spring and neap tides. An environmental suitability model suggested that flapper skate distribution is mainly driven by depth and distance from the coast. A novel approach was taken to validate the suitability predictions by using geolocated locations obtained from the vertical movement data. Finally the parameters estimated in the previous chapters were integrated in a last chapter applying an individual based spatial dynamic model to test its potential in defining conservation measures. To illustrate the potential of this approach for conservation planning, nine different scenarios were run testing different levels of fishing mortality and different spatial extent of fishing mortality. This work has demonstrated that, even when individual data sources are of moderate or low quality, combining multiple data types with analysis using contemporary statistical methods and the use of emerging spatial demographic models can provide a valuable approach to inform urgent conservation decisions.
Supervisor: Not available Sponsor: University of Aberdeen ; School of Biological Sciences ; Marine Scotland Science
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Dipturus