Are We Predicting the Actual or Apparent Distribution of Temperate Marine Fishes?
Planning for resilience is the focus of many marine conservation programs and initiatives. These efforts aim to inform conservation strategies for marine regions to ensure they have inbuilt capacity to retain biological diversity and ecological function in the face of global environmental change – p...
| Main Authors: | , , , , |
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| Format: | Journal Article |
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Public Library of Science
2012
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| Online Access: | http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0034558 http://hdl.handle.net/20.500.11937/24031 |
| _version_ | 1848751316651737088 |
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| author | Monk, J. Ierodiaconou, D. Harvey, Euan Rattray, A. Rattray, A. Versace, V. |
| author_facet | Monk, J. Ierodiaconou, D. Harvey, Euan Rattray, A. Rattray, A. Versace, V. |
| author_sort | Monk, J. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Planning for resilience is the focus of many marine conservation programs and initiatives. These efforts aim to inform conservation strategies for marine regions to ensure they have inbuilt capacity to retain biological diversity and ecological function in the face of global environmental change – particularly changes in climate and resource exploitation. In the absence of direct biological and ecological information for many marine species, scientists are increasingly using spatially-explicit, predictive-modeling approaches. Through the improved access to multibeam sonar and underwater video technology these models provide spatial predictions of the most suitable regions for an organism at resolutions previously not possible. However, sensible-looking, well-performing models can provide very different predictions of distribution depending on which occurrence dataset is used. To examine this, we construct species distribution models for nine temperate marine sedentary fishes for a 25.7 km2 study region off the coast of southeastern Australia. We use generalized linear model (GLM), generalized additive model (GAM) and maximum entropy (MAXENT) to build models based on co-located occurrence datasets derived from two underwater video methods (i.e. baited and towed video) and fine-scale multibeam sonar based seafloor habitat variables. Overall, this study found that the choice of modeling approach did not considerably influence the prediction of distributions based on the same occurrence dataset. However, greater dissimilarity between model predictions was observed across the nine fish taxa when the two occurrence datasets were compared (relative to models based on the same dataset). Based on these results it is difficult to draw any general trends in regards to which video method provides more reliable occurrence datasets. Nonetheless, we suggest predictions reflecting the species apparent distribution (i.e. a combination of species distribution and the probability of detecting it). Consequently, we also encourage researchers and marine managers to carefully interpret model predictions. |
| first_indexed | 2025-11-14T07:50:48Z |
| format | Journal Article |
| id | curtin-20.500.11937-24031 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T07:50:48Z |
| publishDate | 2012 |
| publisher | Public Library of Science |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-240312017-02-28T01:36:30Z Are We Predicting the Actual or Apparent Distribution of Temperate Marine Fishes? Monk, J. Ierodiaconou, D. Harvey, Euan Rattray, A. Rattray, A. Versace, V. Planning for resilience is the focus of many marine conservation programs and initiatives. These efforts aim to inform conservation strategies for marine regions to ensure they have inbuilt capacity to retain biological diversity and ecological function in the face of global environmental change – particularly changes in climate and resource exploitation. In the absence of direct biological and ecological information for many marine species, scientists are increasingly using spatially-explicit, predictive-modeling approaches. Through the improved access to multibeam sonar and underwater video technology these models provide spatial predictions of the most suitable regions for an organism at resolutions previously not possible. However, sensible-looking, well-performing models can provide very different predictions of distribution depending on which occurrence dataset is used. To examine this, we construct species distribution models for nine temperate marine sedentary fishes for a 25.7 km2 study region off the coast of southeastern Australia. We use generalized linear model (GLM), generalized additive model (GAM) and maximum entropy (MAXENT) to build models based on co-located occurrence datasets derived from two underwater video methods (i.e. baited and towed video) and fine-scale multibeam sonar based seafloor habitat variables. Overall, this study found that the choice of modeling approach did not considerably influence the prediction of distributions based on the same occurrence dataset. However, greater dissimilarity between model predictions was observed across the nine fish taxa when the two occurrence datasets were compared (relative to models based on the same dataset). Based on these results it is difficult to draw any general trends in regards to which video method provides more reliable occurrence datasets. Nonetheless, we suggest predictions reflecting the species apparent distribution (i.e. a combination of species distribution and the probability of detecting it). Consequently, we also encourage researchers and marine managers to carefully interpret model predictions. 2012 Journal Article http://hdl.handle.net/20.500.11937/24031 http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0034558 Public Library of Science restricted |
| spellingShingle | Monk, J. Ierodiaconou, D. Harvey, Euan Rattray, A. Rattray, A. Versace, V. Are We Predicting the Actual or Apparent Distribution of Temperate Marine Fishes? |
| title | Are We Predicting the Actual or Apparent Distribution of Temperate Marine Fishes? |
| title_full | Are We Predicting the Actual or Apparent Distribution of Temperate Marine Fishes? |
| title_fullStr | Are We Predicting the Actual or Apparent Distribution of Temperate Marine Fishes? |
| title_full_unstemmed | Are We Predicting the Actual or Apparent Distribution of Temperate Marine Fishes? |
| title_short | Are We Predicting the Actual or Apparent Distribution of Temperate Marine Fishes? |
| title_sort | are we predicting the actual or apparent distribution of temperate marine fishes? |
| url | http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0034558 http://hdl.handle.net/20.500.11937/24031 |