Using the penguin watch network to examine phenology and breeding success in pygoscelis penguins
<p>Remote time-lapse cameras can facilitate high-frequency monitoring of wild animal populations over large spatial and temporal scales, yet the volume of imagery they produce can be overwhelming for small research teams. As ecological studies transition towards a ‘big data’ approach, we must...
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| Other Authors: | |
| Format: | Thesis |
| Language: | English |
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2019
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| _version_ | 1826305508451024896 |
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| author | Jones, FM |
| author2 | Hart, T |
| author_facet | Hart, T Jones, FM |
| author_sort | Jones, FM |
| collection | OXFORD |
| description | <p>Remote time-lapse cameras can facilitate high-frequency monitoring of wild animal populations over large spatial and temporal scales, yet the volume of imagery they produce can be overwhelming for small research teams. As ecological studies transition towards a ‘big data’ approach, we must develop ways to deal with the ‘data deluge’, in the form of integrated processing frameworks. In this thesis, I present and examine data-processing pipelines for the Penguin Watch project – a network of approximately 80 time-lapse cameras positioned in penguin colonies across the Scotia Arc region of the Southern Ocean. I show that both the Penguin Watch online citizen science project and the Pengbot computer vision algorithm are efficient and reliable image annotation tools, which can be used in combination to maximise output and minimise error. I present new methodologies to extract biologically meaningful metrics from citizen science annotations, and show that spatial data – for example ‘nearest neighbour distances’ – can be used to examine behaviour, such as chick huddling.</p>
<p>Seabirds, including penguin species, are often considered indicators of marine health. As such, effective monitoring of their populations offers an invaluable opportunity to assess the health of the wider marine ecosystem. An essential part of this process is obtaining baseline data, and here I use the Penguin Watch project to extract phenological dates for a number of new Chinstrap penguin (Pygoscelis antarcticus) colonies and seasons – a species which has historically been understudied. Through a ‘virtual’ mark-recapture study I examine breeding success in Gentoo penguin (P. papua) colonies across a substantial part of their range in the Atlantic sector of the Southern Ocean. Investigation of the impact of three key anthropogenic stressors (precipitation, the krill fishery, and tourism) on breeding success revealed no significant effects over the study period. However, there is evidence that the relationship between chick survival and precipitation could be highly non-linear, with severe precipitation events associated with high chick mortality. This has implications for a number of Southern Ocean bird species, and with precipitation levels expected to increase under climate-change scenarios, continued monitoring is essential. Repetition of this study on Adélie (P. adeliae) and Chinstrap penguins – species which have a higher dependency on krill than Gentoos – is a key future research priority.</p> |
| first_indexed | 2024-03-07T06:33:54Z |
| format | Thesis |
| id | oxford-uuid:f6f3be64-5854-4e65-bc8f-56edb78e85a5 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T06:33:54Z |
| publishDate | 2019 |
| record_format | dspace |
| spelling | oxford-uuid:f6f3be64-5854-4e65-bc8f-56edb78e85a52022-03-27T12:38:55ZUsing the penguin watch network to examine phenology and breeding success in pygoscelis penguinsThesishttp://purl.org/coar/resource_type/c_db06uuid:f6f3be64-5854-4e65-bc8f-56edb78e85a5BiologyBig data in ecologyMarine biologyEnglishHyrax Deposit2019Jones, FMHart, TLintott, C<p>Remote time-lapse cameras can facilitate high-frequency monitoring of wild animal populations over large spatial and temporal scales, yet the volume of imagery they produce can be overwhelming for small research teams. As ecological studies transition towards a ‘big data’ approach, we must develop ways to deal with the ‘data deluge’, in the form of integrated processing frameworks. In this thesis, I present and examine data-processing pipelines for the Penguin Watch project – a network of approximately 80 time-lapse cameras positioned in penguin colonies across the Scotia Arc region of the Southern Ocean. I show that both the Penguin Watch online citizen science project and the Pengbot computer vision algorithm are efficient and reliable image annotation tools, which can be used in combination to maximise output and minimise error. I present new methodologies to extract biologically meaningful metrics from citizen science annotations, and show that spatial data – for example ‘nearest neighbour distances’ – can be used to examine behaviour, such as chick huddling.</p> <p>Seabirds, including penguin species, are often considered indicators of marine health. As such, effective monitoring of their populations offers an invaluable opportunity to assess the health of the wider marine ecosystem. An essential part of this process is obtaining baseline data, and here I use the Penguin Watch project to extract phenological dates for a number of new Chinstrap penguin (Pygoscelis antarcticus) colonies and seasons – a species which has historically been understudied. Through a ‘virtual’ mark-recapture study I examine breeding success in Gentoo penguin (P. papua) colonies across a substantial part of their range in the Atlantic sector of the Southern Ocean. Investigation of the impact of three key anthropogenic stressors (precipitation, the krill fishery, and tourism) on breeding success revealed no significant effects over the study period. However, there is evidence that the relationship between chick survival and precipitation could be highly non-linear, with severe precipitation events associated with high chick mortality. This has implications for a number of Southern Ocean bird species, and with precipitation levels expected to increase under climate-change scenarios, continued monitoring is essential. Repetition of this study on Adélie (P. adeliae) and Chinstrap penguins – species which have a higher dependency on krill than Gentoos – is a key future research priority.</p> |
| spellingShingle | Biology Big data in ecology Marine biology Jones, FM Using the penguin watch network to examine phenology and breeding success in pygoscelis penguins |
| title | Using the penguin watch network to examine phenology and breeding success in pygoscelis penguins |
| title_full | Using the penguin watch network to examine phenology and breeding success in pygoscelis penguins |
| title_fullStr | Using the penguin watch network to examine phenology and breeding success in pygoscelis penguins |
| title_full_unstemmed | Using the penguin watch network to examine phenology and breeding success in pygoscelis penguins |
| title_short | Using the penguin watch network to examine phenology and breeding success in pygoscelis penguins |
| title_sort | using the penguin watch network to examine phenology and breeding success in pygoscelis penguins |
| topic | Biology Big data in ecology Marine biology |
| work_keys_str_mv | AT jonesfm usingthepenguinwatchnetworktoexaminephenologyandbreedingsuccessinpygoscelispenguins |