- Title
- Integrating state-space modelling and systematic conservation planning to recommend penguin-fishery management zones in Algoa Bay, South Africa
- Creator
- Stockdale, Victoria
- Creator
- Goodall, Victoria
- Creator
- Clifford-Holmes, Jia
- Subject
- Biodiversity conservation -- South Africa -- Port Elizabeth
- Subject
- Natural resource conservation
- Subject
- Marine ecology
- Date Issued
- 2023-12
- Date
- 2023-12
- Type
- Master's theses
- Type
- text
- Identifier
- http://hdl.handle.net/10948/62611
- Identifier
- vital:72828
- Description
- Direct anthropogenic impacts on vulnerable marine ecosystems are growing and require effective conservation measures. Integrating the cost impacts of conservation interventions and optimising the spatiotemporal scale of management interventions may improve cohesion between opposing marine users. This study aimed to integrate spatial and temporal models to advise dynamic penguin-fishery management plans in Algoa Bay, off Gqeberha, South Africa, that would maximise penguin foraging success while minimising the impact on the fishing industry. Determining the foraging locations important to breeding penguins is fundamental when understanding the relationship between fisheries and prey availability. Using Global Positioning System (GPS) data gathered from feeding trips of breeding African penguins between 2012 and 2017, and a hidden Markov model, three behavioural states (foraging, commuting, transitioning) were inferred and used as conservation targets in spatial prioritisation using the prioritizr package in R. The cost to the fishery was estimated using the catch of pelagic fish by the fishing industry between 2012 and 2015 as the proxy. The energetic cost to penguins was the distance they travelled from their breeding colony. Nine prioritisation scenarios, varying in levels of conservation for penguins, spatial cohesion and costs to fisheries, were developed using all year’s combined data to explore an ‘optimal’ closure configuration. The optimal closure was determined as an area which met the targets for penguin conservation, with a low cost to the fishery, close to the breeding colony and spatially clumped. The best solution from each scenario was isolated and the solution for the conservation target of 20% foraging habitat, 10% commuting habitat and 10% transitioning habitat and a boundary penalty of 0.01 (a dimensionless value that is used to reduce spatial fragmentation – increasing the value of the parameter signals that it is important to minimise the total exposed boundary of the prioritisation by favouring solutions where units are clumped together) was chosen as the optimal closure. This configuration was used as a static closure and applied to individual fishing seasons to estimate how the cost of a static closure design to the fishery would vary between seasons. Subsequently, a dynamic closure was designed using the same optimal configuration criteria every year, and the cost to the fishing industry was compared seasonally with the cost of a static closure. The cost to fisheries of dynamic closures was consistently lower than that of a static closure and the area required to meet the penguin feeding targets was drastically reduced. While dynamic closure scenarios show promise to minimise costs to the industry while meeting penguin conservation targets, these configurations were designed retrospectively with data collected after the end of the fishery seasons. For efficient management, the closures need to be designed by using data collected at an appropriate temporal scale. For that, the critical missing dimension to this study is the addition of real-time data on pelagic fish positions, areas of fishing intensity and sites of penguin foraging to create appropriate recommendations for up-to-date fishery exclusion zones. Therefore, the priority now is to explore methods of collecting real-time data on pelagic fish abundance, feeding behaviour of penguins at sea, site and mass of pelagic fishery catch, and using these data to delineate real-time, dynamic closures, coupled with a governance and management strategy that can implement dynamic closures.
- Description
- Thesis (MSc) -- Faculty of Science, School of Environmental Sciences, 2023
- Format
- computer
- Format
- online resource
- Format
- application/pdf
- Format
- 1 online resource (152 pages)
- Format
- Publisher
- Nelson Mandela University
- Publisher
- Faculty of Science
- Language
- English
- Rights
- Nelson Mandela University
- Rights
- All Rights Reserved
- Rights
- Open Access
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NMU School of Environmental Sciences
| Thumbnail | File | Description | Size | Format | |||
|---|---|---|---|---|---|---|---|
| View Details Download | SOURCE1 | Stockdale, VA.pdf | 5 MB | Adobe Acrobat PDF | View Details Download |