Terms of Reference

Habitat Suitability Modelling Best Practices for Canada’s Pacific Ocean

Regional Peer Review – Pacific Region

June 11-12, 2019
Nanaimo, BC

Chairperson: Steven Schut

Context

Habitat Suitability Models (HSMs) are a tool that can be used to predict the distribution of a species’ habitat by relating observations of species occurrence to environmental data. This class of models is diverse, and HSMs serve a range of applications, such as predicting habitat for vulnerable species (Rengstorf et al. 2013, Anderson et al. 2016, Rowden et al. 2017), determining important areas in the life history of fish (Le Pape et al. 2014, Rooper et al. 2019), identifying candidate areas for protection (Embling et al. 2009), and forecasting changes in aquatic species habitat due to climate change (Cheung et al. 2010). HSMs also have the potential to maximize the utility of future research efforts and funding by informing survey planning, and directing research towards existing knowledge gaps.

HSMs can therefore help meet conservation and management needs by filling some of these information gaps and increasing our understanding of species distributions for many marine spatial planning initiatives, such as marine protected area network design (Abecasis et al. 2014), oil spill response, and identification of ecologically and biologically significant areas (Beazley et al. 2016). However, HSMs can also be misapplied if species or environmental data are not appropriately screened and prepared, and proper model validation is not carried out (Roberts et al. 2017, Hawkins et al. 2003, Elith and Leathwick 2009).

The purpose of this peer review is to produce a comprehensive best practices framework to guide future development and application of HSMs, based on 12 species found in the Pacific Region. Although the framework will be developed using Pacific species, there is the potential to apply this framework to other species/regions. Discussions and guidance on appropriate data usage, pre-processing and data preparation, modelling approaches and development, model validation, interpretation of results, and how to convey underlying uncertainty will be provided.

DFO Pacific Science Branch proposes to develop a standardized approach to building HSMs based on best practices to ensure consistent quality and rigor in their use and application. The assessment and advice arising from this Canadian Science Advisory Secretariat (CSAS) Regional Peer Review (RPR) will be used to develop HSMs, and integrate them into science and policy decisions related to the management and conservation of marine species.

Objective

The following working paper will be reviewed and provide the basis for discussion and advice on the specific objectives outlined below.

Nephin, J., E.J. Gregr, C. St. Germain, C. Fields, J.L. Finney.  Habitat Suitability Modelling Best Practices for Canada’s Pacific Ocean. CSAP Working Paper 2018SCI01

The specific objectives of this review are to:

1. Provide background methods, challenges and current best practices for HSM development.
2. Assess the challenges associated with finding appropriate species and environmental data, and provide guidance on best practices for preparing data for HSMs.
3. Develop a framework that applies best practices to HSM development; including how to validate models and present model assumptions and uncertainty.
4. Demonstrate an application of the HSM framework using a case study in Pacific Regionz.
5. Examine findings relevant to building HSMs and provide recommendations for future applications.

Expected Publications

• Science Advisory Report
• Research Document
• Proceedings

Expected Participation

• Fisheries and Oceans Canada (Ecosystems and Oceans Science, Fisheries Management, Ecosystems Management)
• Academia
• Indigenous Groups
• Non Government Organizations

References

Abecasis, D., Afonso, P. and Erzini, K., 2014. Combining multispecies home range and distribution models aids assessment of MPA effectiveness. Marine Ecology Progress Series, 513, pp.155-169.

Anderson, O. F., Guinotte, J. M., Rowden, A. A., Tracey, D. M., Mackay, K. A., & Clark, M. R., 2016. Habitat suitability models for predicting the occurrence of vulnerable marine ecosystems in the seas around New Zealand. Deep-Sea Research Part I: Oceanographic Research Papers, 115, 265–292.

Beazley, L., Kenchington, E., Murillo, F.J., Lirette, C., Guijarro, J., McMillan, A. and Knudby, A., 2016. Species distribution modelling of corals and sponges in the maritimes region for use in the identification of Significant Benthic Areas. Canadian Technical Report of Fisheries and Aquatic Sciences 3171.

Cheung, W.W., Lam, V.W., Sarmiento, J.L., Kearney, K., Watson, R.E.G., Zeller, D. and Pauly, D., 2010. Large‐scale redistribution of maximum fisheries catch potential in the global ocean under climate change. Global Change Biology, 16(1), pp.24-35.

Elith, J., & Leathwick, J., 2009. Species distribution models: ecological explanation and prediction across space and time. Annual Review of Ecology, Evolution, and Systematics, 40, 677–697.

Embling, C. B., Gillibrand, P. A., Gordon, J., Shrimpton, J., Stevick, P. T., & Hammond, P. S., 2009. Using habitat models to identify suitable sites for marine protected areas for harbour porpoises (Phocoena phocoena). Biological Conservation, 143(2), 267–279.

Hawkins, D. M., Basak, S. C., & Mills, D., 2003. Assessing model fit by cross-validation. Journal of Chemical Information and Computer Sciences, 43(2), 579–586.

Le Pape, O., Delavenne, J., & Vaz, S., 2014. Quantitative mapping of fish habitat: A useful tool to design spatialised management measures and marine protected area with fishery objectives. Ocean and Coastal Management, 87, 8–19.

Rengstorf, A. M., Yesson, C., Brown, C., & Grehan, A. J., 2013. High-resolution habitat suitability modelling can improve conservation of vulnerable marine ecosystems in the deep sea. Journal of Biogeography, 40(9), 1702–1714.

Roberts DR, Bahn V, Ciuti S, Boyce MS, Elith J, Guillera‐Arroita G, Hauenstein S, Lahoz‐Monfort JJ, Schröder B, Thuiller W. 2017. Cross‐validation strategies for data with temporal, spatial, hierarchical, or phylogenetic structure. Ecography 40:913-929.

Rowden, A. A., Anderson, O. F., Georgian, S. E., Bowden, D. A., Clark, M. R., Pallentin, A., & Miller, A., 2017. High-Resolution Habitat Suitability Models for the Conservation and Management of Vulnerable Marine Ecosystems on the Louisville Seamount Chain, South Pacific Ocean. Frontiers in Marine Science, 4(October).

Rooper, C.N., Hoff, G.R., Stevenson, D.E., Orr, J.W. and Spies, I.B., 2019. Skate egg nursery habitat in the eastern Bering Sea: a predictive model. Marine Ecology Progress Series, 609, pp.163-178.