My consulting work continues to be focused on coastal systems in British Columbia, Canada, where I can leverage my deep knowledge of this region to understanding species distributions, the classification of marine systems, and the services they provide to people.
With colleagues at Fisheries and Oceans Canada, we produced a framework for rapid production of species distribution models to support marine spatial planning. We are now working on producing defensible, high-resolution classification of bottom type – a predictor layer that is critical for coastal systems.
Refining our recent work on sea otter-fisheries interactions in coastal British Columbia, I am now exploring how the costs and benefits are distributed across the coast. There are encouraging signs that spatial management strategies may improve the co-existence of sea otters and humans along the coast.
I continue to work on a trans-disciplinary effort with colleagues from Academia, Fisheries and Oceans Canada, and communities on the effective characterisation of cumulative impacts on valued species.
My academic work focused in part on how the changes in resource distribution caused by an expanding sea otter population influence the ecosystem services provided to people. This work combined models of kelp forests, sea otter populations, and trophic interactions to explore trade-offs among between different sea otter management alternatives. This of course begs the question of how much confidence we should have in the models that we develop - a question I never stop asking.
Some of the above work is represented in the following publications.
Gregr, E.J., V. Christensen, L. Nichol, R. Martone, R. Markel, J.C. Watson, C.D.G. Harley, E.A. Pakhomov, J.B. Shurin, and K.M.A. Chan. 2020. Cascading social-ecological costs and benefits triggered by a recovering keystone predator. Science. DOI:science.sciencemag.org/cgi/doi/10.1126/science.aay5342.
This synthetic analysis combined ecology and economic analysis in a social-ecological model of the West Coast of Vancouver Island, where recovering sea otters are transforming the coastal ecosystem by reducing populations of benthic invertebrates and releasing kelp forests from grazing pressure. While the recovering sea otters threaten established shellfish fisheries, our results suggest that sea otter presence will result in 37% more ecosystem biomass annually, increasing the value of finfish by 9.4M CA$, and providing 2.2M CA$ in carbon sequestration. Otter presence will also boost ecotourism by as much as 42M CA$ a year. If fully realized, these benefits will well exceed the annual loss to invertebrate fisheries (-$7.3M CA$).
However, these costs and benefits will not be equitably distributed and non-monetary costs, in particular the loss of subsistence harvest to remote coastal communities, are also real and potentially catastrophic in light of already exploited finfish stocks. The equity of potential management alternatives will be explored in a follow-up publication on local sea otter management.
Gregr, E.J., D.M. Palacios, A. Thompson, and K.M.A. Chan, 2019. Why less complexity produces better forecasts: an independent data evaluation of kelp habitat models. Ecography, 42(3), pp.428-443.
This work asks why habitat suitability models continue to see limited use in resource management, and addresses the question of vague model objectives and inadequate evaluation methods using habitat models for canopy kelps (Macrocystis pyrifera and Nereocystis luetkeana). We examined a series of increasingly complex habitat suitability models looking for limits to model complexity, and to explore the relationship between model complexity and forecast skill.
In addition to confirming the importance of established predictors of coastal kelp distributions (i.e. depth, bottom type, bottom slope, and exposure), we also identified additional factors including salinity, and interactions between exposure and salinity, and slope and tidal energy.
Methodologically, we showed how cross‐validation can lead to over‐fitting, and how independent data evaluation can identify the appropriate model complexity for generating habitat forecasts. Our results also show that predictions from simpler models can out‐perform those from more complex models. The continued development of methods and metrics for evaluating model forecasts with independent data, and the explicit consideration of model objectives and assumptions, promise to increase the utility of model forecasts to decision makers.
Davies, S.C., E.J. Gregr, J. Lessard, P. Bartier, and P. Wills. 2019. Coastal digital elevation models integrating ocean bathymetry and land topography for marine ecological analyses in Pacific Canadian waters. Can. Tech. Rep. Fish. Aquat. Sci. 3321: vi + 38 p.
Accurate predictors are essential to credible maps of species distributions. We developed a series of five 20 m coastal digital elevation models (DEMs) for Canada's Pacific region to support spatial analysis, specifically for the nearshore domain, extending from the high intertidal to 50 m depth. These bathymetric products are at a higher resolution and greater extent in shallow waters than previously available DEMs for the area. They provide a critical foundational layer for modelling species, habitats, and environmental variables across Canada's Pacific region and will benefit marine spatial planning initiatives such as Marine Protected Areas and oil spill response strategies.
Gregr, E.J. and K.M.A. Chan 2015. Leaps of Faith: How implicit assumptions compromise the utility of ecosystem models for decision-making. Bioscience 65(1): 43-54.
All models have assumptions. But not all assumptions are equal, and different assumptions are appropriate in different contexts, and for different questions. In this review, we show that uncertainties and design assumptions are mostly ignored in the popular modelling literature, illustrate the importance of model assumptions in assessing model uncertainty, and offer a conceptual model to support more consistent model design decisions.
The editor liked the article so much he wrote an editorial entitled ‘Models are not Toys’, where he called our results “shocking”. You can read the full editorial here https://academic.oup.com/bioscience/article/65/1/3/379449.
Nephin, J., E.J. Gregr, C. St. Germain, C. Fields, and J.L. Finney. 2020. Development of a Species Distribution Modelling Framework and its Application to Twelve Species on Canada’s Pacific Coast. DFO Can. Sci. Advis. Sec. Res. Doc. 2020/004. xii + 107 p.
Species distribution models (SDMs) are a valuable tool for the management and conservation of marine resources and places. In this work we address critical aspects of SDM development and uncertainty assessment that are routinely overlooked. This framework was prepared as both a tool and a set of guidelines and methods for the development of consistent, interpretable, and defensible SDMs to support DFO’s contribution to Canada's ocean policies.
SDMs were built for twelve benthic species to illustrate the application of the framework, and contribute to emergency oil spill response planning in Pacific Canada. We built three models of increasing complexity using a suite of best available environmental predictors. Knowledge-based envelope models were produced for all species, and emphasized for those found to be data deficient. These models can be used to evaluate uncertainty in model predictions, and provide an avenue for engaging First Nations and species experts in the process. Data-driven generalized linear (GLM) and boosted regression tree (BRT) models were generated, along with a corresponding ensemble model, for the eight species found to have adequate observational data.
Thirteen recommendations were conceived as part of the development of the framework and its application to provide guidance on the application of SDM methods related to data selection and preparation, model development and evaluation. Development of SDMs for additional species in Pacific Canada will be greatly facilitated by the set of common predictors, methods, and evaluation tools assembled here.