Benthic Biodiversity Model Outputs from Chatham Rise
Using seafloor image data to build single-taxon and community distribution models for seabed fauna in New Zealand waters.
Understanding the spatial distributions of seabed biodiversity is essential for effective management of the effects of human activities including fishing and mining. To improve understanding of seabed fauna distributions, we are developing a new database of benthic invertebrate occurrences in New Zealand waters by assembling quantitative data from all available seabed photographic surveys. By modelling the spatial relationships between taxon occurrences and environmental gradients across the region, we are able to predict the likelihood of individual taxa and communities being present in as-yet unsampled areas. In the first phase of the project, we concentrated on Chatham Rise; a region of high importance to commercial fisheries and with the highest density of available seabed imagery. Predictions from the models developed here are the first abundance-based models of benthic distributions in the New Zealand region and are the best-informed representations of seabed distributions on Chatham Rise to date, providing a resource that will have applications in marine environmental management and ecosystem research.
All rasters are in a geotiff format at a 1000 m resolution cell size and projected to WGS 84 / Mercator 41 - EPSG:3994 coordinate system.
Simple
- Date (Publication)
- 2020-05-13T02:30:00
- Cited responsible party
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Organisation name Individual name Electronic mail address Role National Institute of Water and Atmospheric Research (NIWA)
Resource provider
- Other citation details
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The citation in a list of references is: "NIWA [year-of-data-download], [Title], [data-access-URL], accessed [date-of-access]."
- Purpose
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Distributions of individual species, patterns of variability in species richness and abundance, and locations of sensitive or vulnerable habitats are essential inputs into marine spatial planning and risk assessment processes. Chatham Rise is an important deep-sea fishing region in New Zealand. Lying at the convergence of Sub-Tropical and Sub-Antarctic water masses, it has a highly diverse and dynamic physical environment, supporting high levels of biological production and encompassing a broad range of benthic habitats and fauna. Existing knowledge about seabed faunal distributions on Chatham Rise comes from records of museum specimens, fisheries and research trawl bycatch, and increasing from photographic surveys. Data from museum and trawl databases have been used to build models that predict species and community distributions in unsampled space but because the models are based on presence-only data from disparate sources and do not incorporate population density data, their predictions are considered uncertain.
To reduce uncertainty in predictions, we developed a new, spatially extensive, fully quantitative, and taxonomically consistent dataset of benthic invertebrate occurrence by merging data from five seabed photographic surveys, including an extensive dedicated survey (TAN1701) as part of this project (Bowden et al., 2019a). We then used this dataset to inform development of improved predictive models for Chatham Rise at both single-taxon and community levels, yielding maps of predicted population densities, beta-diversity (rate of change of community composition), and community classifications (Bowden et al., 2019b). Two independent modelling methods were used for each level: Boosted Regression Trees (BRT, De’ath 2007) and Random Forests (RF, Breiman 2001) for single-taxa, and Regions of Common Profile (RCP, Foster et al. 2013) and Gradient Forests (GF, Ellis et al. 2012) for communities, enabling ensemble model predictions for single taxa and comparison between classification methods for communities. For single-taxon models, the ‘hurdle’ model technique was used, combining predictions from presence-absence and abundance models to reduce bias associated with zero-inflated data. Sets of explanatory environmental variables (12 for single-taxon models, 18 for GF, and 9 for RCP) were selected from an initial set of 58 candidate layers and the 354 invertebrate taxa identified from the seabed image surveys were condensed into a set of 69 taxa by aggregation to higher taxonomic levels and exclusion of rarer and non-benthic taxa. Single-taxon models were produced for 20 taxa, selected according to their sensitivity or vulnerability to human-induced environmental impacts, while all 69 taxa were included in community models.
Outputs from the single-taxon models are presented as maps showing predicted occurrences as densities (individuals 1000 m-2) with associated estimates of model precision (CV) and cross-validation metrics. All models performed well by these criteria but a comparison using invertebrate bycatch data from the trawl database was inconclusive for most taxa modelled because of inadequate abundance information in the test data. While predictions for most of the taxa modelled have clear similarities with those of previous models, they also show differences, often driven by inclusion of density data. Outputs from the community models are presented as spatial classifications of the study area, analogous to existing spatial classifications such as the Marine Environments Classification (MEC, Snelder et al. 2007, Leathwick et al. 2012) and derivatives. RCP divided the area into 7 classes, whereas a hierarchical clustering method allowed GF results to be assessed at class levels from 7 to 50 classes and compared visually against existing classifications.
These predictions are the best-informed representations of seabed distributions at regional scales in the New Zealand Exclusive Economic Zone to date and provide a resource that will have applications in marine environmental management and ecosystem research. Potential applications include quantification of benthic impacts from bottom-contact fishing gear and other anthropogenic agencies, informing spatial management of biodiversity through, for example, the design of marine protected areas, and informing research into ecosystem linkages between water-column and seabed processes. A further obvious application and test of the predictions will be to use the modelled relationships developed here to predict faunal distributions across seabed areas beyond Chatham Rise.
This study is funded by Fisheries New Zealand (FNZ) under projects ZBD2016-11 and ZBD2019-01, with governance at FNS by Mary Livingston. The Principal investigator is David Bowden ( David.Bowden@niwa.co.nz ) and the full team includes: Owen Anderson; Caroline Chin; Malcolm Clark; Niki Davey; Alan Hart; Andrea Mari; Andrew Miller; Ashley Rowden and Brent Wood.
References:
Bowden, D.A.; Rowden, A.A.; Anderson, O.F.; Clark, M.R.; Hart, A.; Davey, N., . . . Chin, C. (2019a). Quantifying Benthic Biodiversity: developing a dataset of benthic invertebrate faunal distributions from seabed photographic surveys of Chatham Rise. Aquatic Environment and Biodiversity Report No. 221. 35 p.
Bowden, D.; Anderson, O.; Escobar-Flores, P.; Rowden, A.; Clark, M. (2019b). Quantifying benthic biodiversity: using seafloor image data to build single-taxon and community distribution models for Chatham Rise, New Zealand. Aquatic Environment and Biodiversity Report No. 235. 67 p.
Breiman, L. (2001). Random forests. Machine Learning 45(1): 5-32
De'ath, G. (2007). Boosted trees for ecological modelling and prediction. Ecology 88(1): 243-251.
Ellis, N.; Smith, S.J.; Pitcher, C.R. (2012). Gradient forests: calculating importance gradients on physical predictors. Ecology 93(1): 156-168.
Foster, S.D.; Givens, G.H.; Dornan, G.J.; Dunstan, P.K.; Darnell, R. (2013). Modelling biological regions from multi-species and environmental data. Environmetrics 24(7): 489-499.
Leathwick, J.; Rowden, A.; Nodder, S.D.; Gorman, A.R.; Bardsley, S.; Pinkerton, M., . . . Goh, A. (2012). A Benthic-Optimised Marine Environment Classification (BOMEC) for New Zealand waters. New Zealand Aquatic Environment and Biodiversity Report No. 88. 54 p.
Snelder, T.H.; Leathwick, J.R.; Dey, K.L.; Rowden, A.A.; Weatherhead, M.A.; Fenwick, G.D., . . . Zeldis, J.R. (2007). Development of an ecologic marine classification in the New Zealand region. Environmental Management 39(1): 12-29.
- Credit
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NIWA
See:
Bowden, D.A.; Rowden, A.A.; Anderson, O.F.; Clark, M.R.; Hart, A.; Davey, N., . . . Chin, C. (2019a). Quantifying Benthic Biodiversity: developing a dataset of benthic invertebrate faunal distributions from seabed photographic surveys of Chatham Rise. Aquatic Environment and Biodiversity Report No. 221. 35 p.
Bowden, D.; Anderson, O.; Escobar-Flores, P.; Rowden, A.; Clark, M. (2019b). Quantifying benthic biodiversity: using seafloor image data to build single-taxon and community distribution models for Chatham Rise, New Zealand. Aquatic Environment and Biodiversity Report No. 235. 67 p.
- Status
- Completed
- Point of contact
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Organisation name Individual name Electronic mail address Role National Institute of Water and Atmospheric Research (NIWA)
Dr David Bowden
Principal investigator
- Maintenance and update frequency
- Not planned
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AODN Geographic Extents Vocabulary
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Global / Oceans | South West Pacific Ocean
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- Place
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Countries | New Zealand
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Chatham Rise
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- Theme
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Biodiversity
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Taxon
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Habitat
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Seabed fauna
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Distribution models
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- Distance
- 1000 1000 m
- Language
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eng
- Topic category
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- Biota
- Description
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New Zealand regional waters, encompassing the Exclusive Economic Zone and the Continental Shelf
))
- Distribution format
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Name Version GeoTIFF
1.0
CSV-file
1.0
MS Excel
Version 2002
PDF
1.5 (Acrobat 6.x)
- OnLine resource
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Protocol Linkage Name WWW:LINK-1.0-http--metadata-URL
https://nzodn.nz/geonetwork/srv/en/metadata.show?uuid=ee2c94b6-5d4b-4e36-a18b-c300c5139158 OGC:WMS-1.1.1-http-get-map
https://nzodn.nz/geoserver/nzodn/wms nzodn:biological_map
IMOS:AGGREGATION--bodaac
https://nzodn.nz/geoserver/ows biological_map#url
Metadata
- File identifier
- ee2c94b6-5d4b-4e36-a18b-c300c5139158 XML
- Metadata language
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eng
- Character set
- UTF8
- Hierarchy level
- Dataset
- Date stamp
- 2021-07-28T03:26:50
- Metadata standard name
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ISO 19115:2003/19139
- Metadata standard version
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1.0
- Metadata author
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Organisation name Individual name Electronic mail address Role National Institute of Water and Atmospheric Research (NIWA)
Distributor