Research paper maps density patterns and hotspots of BC marine mammals

New research by Raincoast and partners implements novel spatial mapping methods for conservation planning on the coast of BC, Canada.

An assortment of figures from the paper, Quantifying marine mammal hotspots in British Columbia, Canada

Building on Raincoast Conservation Foundation’s five years spent surveying marine mammals on the BC coast, a new study by scientists at Raincoast, UVic, Dalhousie and Arizona State Universities has linked environmental conditions with marine mammal densities to identify regions on the BC coast important for marine mammal biodiversity.

Because of the diversity and density of marine mammals, and also because most of the marine mammals studied are listed under the Species at Risk Act (SARA), these regions are high value spots for conservation. We call these regions ‘hotspots’. The identification of these geographic hotspots that combines survey information, environmental variables and new spatial statistical methods offers a powerful technique for assessing marine mammal habitats and identifying important regions for conservation.

Read the full article: “Quantifying marine mammal hotspots in British Columbia, Canada.”

Abstract

Global biodiversity is undergoing rapid decline due to direct and indirect anthropogenic impacts to species and ecosystems. Marine species, in particular, are experiencing accelerated population declines leading to many species being considered at risk by regional, national, and international standards. As one conservation approach, decisions made using spatially explicit information on marine wildlife populations have the potential to facilitate recovery and contribute to national and international commitments toward conservation targets. Delineating areas of intense use by species at risk can inform future marine spatial planning and conservation efforts, including the identification of marine protected areas. Methods for detecting hotspots (e.g., areas with high density and/or abundance) enable categorical mapping of the most intensely used areas. Yet, many of the current methods for delineating hotspots, such as the top 5% threshold, are subjective and fail to account for spatial patterns. Our goal was to map spatially continuous distributions of marine mammal densities and employ quantitative statistical methods to extract hotspot locations on the northern coast of British Columbia. We integrated systematically surveyed species information with environmental variables using generalized additive models to predict marine mammal distribution and density. Hotspots were identified from the density surfaces using two approaches: aspatial top 5% method and spatially local Gi* statistic using three neighborhood definitions. Heterogeneous density patterns were observed for all species, and high-density regions were generally clustered in areas exhibiting oceanographic characteristics that may promote concentrated food resources. Combining species density surfaces and extracting hotspot locations identified regions important to multiple species and present candidate locations for future conservation efforts. Contributions from this research provide robust statistical methods to objectively map hotspot locations and generate GIS data products for informing coastal conservation decisions.

Citation

Harvey, G.K.A.,1,2 T.A. Nelson,3 C.H. Fox, 2,4 and P.C. Paquet 1,2. 2017. Quantifying marine mammal hotspots in British Columbia, Canada. Ecosphere 8(7):e01884. 10.1002/ecs2.1884

Affiliation

  1. Department of Geography, University of Victoria
  2. Raincoast Conservation Foundation
  3. School of Geographical Sciences & Urban Planning, Arizona State University
  4. Department of Oceanography, Dalhousie University

Select figures

A map of the study region, and transects, on the coast of BC, Canada

Figure 1: Maps illustrating (A) study region that is indicated in dark gray with passage and on-effort survey transects (2004–2008) and (B) key oceanographic regions.

 

Three illustrations comparing definitions of spatial contiguity, or spatial neighbourhood.

Figure 2: Illustration of two different ways to define a spatial neighborhood: (1) queen contiguity defined as first order (lag 1) and second order (lag 2) and (2) distance-based radius (range value from semivariogram).

 

Maps of the study region showing hotspots of nine marine mammals.

Figure 4: Continuous density surfaces generated from species-specific generalized additive models. Density is defined as the number of individuals per km2 and displayed on a hexagon grid (each hexagon is 13.86 km2). Abbreviations include Dall’s porpoise (DP), fin whale (FW), harbor porpoise (HP), harbor seal (HS), humpback whale (HW), killer whale (KW), common minke whale (MW), Pacific white-sided dolphin (PW), and Steller sea lion (SSL).

 

Comparison of hotspot maps using different methods for calculating densities.

Figure 5. Four hotspot outputs (top 5%, Gi*queen [lag 1], Gi* queen [lag 2], and Gi*distance) generated from normalized and summed density maps (first column) for cetaceans, pinnipeds, and all species combined.

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