Priority Conservation Areas
Priority Conservation Areas (PCAs) are areas of trinational importance due to their ecological significance, threatened nature and opportunities for conservation.
These areas were defined on the basis of high biodiversity and continental uniqueness, incorporating aspects of ecological value, anthropogenic threat, and opportunity for conservation. One or several MPAs may exit within a PCA.
To read more about this process, see the document on Marine Priority Conservation Areas in the Baja California to Bering Sea Region (B2B). Note the Baja California to Bering Sea Region (B2B) is one of fourteen Ecologically Significant Regions, identified by a group of leading ecologists convened by the CEC in 2000. To date, NAMPAN has focused many of its activities on the Baja California to Bering Sea Region (B2B) as it connects the marine realms of the three countries and offers concrete opportunities for collaboration.
From the Gulf of California, with its deep canyons, nutrient-rich upwellings and high levels of endemism, to the 20,000 kilometers of bays, inlets and inland drainage systems of the Pacific Northwest, to the high productivity of the Bering Sea, the west coast of North America is home to unique and important shared marine environments. It is also home to a great number of shared marine species—such as Pacific gray and blue whales, leatherback sea turtles, bluefin tuna, black brant geese and Heermann’s gulls—that migrate thousands of kilometers, moving across national borders without hesitation. Hence, be it through shared species or ecosystems, the marine environments of Canada, Mexico and the United States are intimately linked. Accordingly, action or inaction on one side of a border will have consequences for the shared living organisms occupying ecosystems with no such definite boundaries.
In recent years, conservation strategists, noting past failures to stem the tide of extinctions, have focused to a great degree on large-scale ecosystem approaches (e.g., Wildlands Strategy, World Wildlife Fund’s Global 200). Efforts such as these recognize four critical aspects necessary to conserve species and processes: 1) conserving species and processes that require the greatest area to persist, 2) conserving widespread species and continental phenomena, 3) quantifying patterns of beta diversity and endemism, and 4) predicting the location and intensity of threats to biodiversity (Olson et al. 2002). Largescale efforts also require the mapping of important areas for conservation, such as biodiversity hotspots and other conservation priorities, in order to set priorities for action (e.g., Hixon et al. 2001, Roberts et al. 2002).
Although many conservation efforts and sustainable development initiatives exist at different scales along the Pacific Coast of North America, they generally work independently of each other. Unless these efforts are coordinated, species numbers will continue to decline and ecosystem integrity will continue to be at risk. The successful conservation of the North American seascape, therefore, requires cooperative action from all three countries and from diverse sectors of society. The CEC is able to provide this coordinating role for the three countries, Canada, Mexico and the United States. The CEC was created to address common environmental concerns by the governments of Canada, Mexico and the United States under the North American Agreement for Environmental Cooperation, a side agreement to the North American Free Trade Agreement (NAFTA). The North American Marine Protected Areas Network (NAMPAN) represents one initiative to facilitate collaboration to safeguard ecological linkages, and conserve marine biodiversity and productivity throughout the exclusive economic zones (EEZs) of the three nations. Many organizations and agencies contribute to this initiative, including the Marine Conservation Biology Institute (MCBI). This initiative is also in line with the World Summit for Sustainable Development, where participating governments, including Canada, Mexico and the United States, committed to implementing networks of representative MPAs by 2012.
Goal of the Priority Conservation Areas Project
Defining priority conservation areas (PCAs) marks the fulfillment of a workplan by the three nations to identify opportunities to work collaboratively on marine conservation at the North American level. Over the course of this project, the definition of PCAs was refined to reflect the goals of the CEC process, the variable nature of data available in the three nations and the spatial scale of the Baja California to the Bering Sea (B2B) region. The PCAs project represents one of several marine initiatives sponsored by the CEC. Other initiatives advance a framework for mapping marine ecoregions, identify and help protect species of common conservation concern, and work to provide a common understanding as well as a coordinated and complementary use of institutions, initiatives and tools in each nation so as to implement an integrated Marine Protected Area (MPA) Network in North America. This PCA initiative seeks to detail where conservation action is immediately necessary, thereby charting a course for future conservation alliances and action in the B2B region.
History of the Process
In 2000, the CEC identified the Baja California to Bering Sea region as one of its Priority Regions for Biodiversity Conservation of North America1—this region is defined as the west coast EEZs of Mexico, the United States and Canada from 22°N latitude to 65°N latitude. The B2B region was also advanced as the first test case for the CEC to implement its strategic plan in the marine environment.2 In May 2001, MCBI and the CEC convened a workshop in Monterey, California, United States, where scientific experts, resource users and marine conservationists from the three countries addressed the goals and identified the types of baseline data that are required for conservation in the B2B region.3 They agreed on the need to identify PCAs as a step in a larger continental-scale conservation effort. They also reached a consensus that the overarching goal of a PCA is to conserve biodiversity as well as provide benefits to fisheries, cultural values, recreation and scientific research.
These experts agreed to develop a geographic information system (GIS) based on common physical data for the entire region to serve as a framework for integrating other information. The GIS includes benthic and pelagic physical data to be used as a tool for research and analysis of species diversity, incorporating information from ongoing CEC projects (Marine Species of Common Conservation Concern and Ecosystem Mapping), and integrating ongoing and existing protected area designation processes. Experts also addressed issues of size and spatial scale, incorporating previous priority-setting efforts and knowledge of anthropogenic threats (Morgan and Etnoyer 2002).
In June 2002, MCBI, in collaboration with the CEC, Ecotrust and Surfrider Foundation, organized a “Data Potluck” workshop in Portland, Oregon, United States. In this workshop, nearly 80 representatives from 30 organizations offered and exchanged data sets that appeared relevant to the spatial scale of the B2B region. The participants agreed that the concept of conservation priority must include not only biodiversity value, but also threats to and opportunities for the area.
In January 2003, a technical review of the geographic information system, the data analyses and the overall methodology to define PCAs was conducted in San Francisco, California, United States. The CEC and MCBI held this review to seek input and advice from various governmental agencies and nongovernmental organizations as to what further information could be synthesized for the B2B region. This consultation reviewed data sets and analyses, as well as previous decisions and recommendations.
This process culminated in April of 2003 with an experts’ workshop, held at Simon Fraser University in Burnaby, British Columbia, Canada, to map North American PCAs, summarized herein.
The methodology selected for identifying PCAs relied on teaming experts’ knowledge with the development of a geographic information system. The GIS included appropriate spatial data sets and selected analyses available for the B2B region at a common resolution, as well as smaller subsets of regional information. Analyses focused on translating several of these data sets in order to highlight regions where physical processes lead to unique features or concentrations of species. At the final
PCA identification workshop, experts reviewed the aggregated data sets and analyses to inform their judgments of ecological value and conservation priority.
Throughout all consultations, those involved in this process attempted to interact with the appropriate federal agencies in each of the CEC countries rather than directly involving state, provincial or regional governing bodies (though these offices were involved to differing degrees). This led to a number of significant restrictions on this project. For example, the use of local ecological knowledge was discussed and considered. During our consultative process it was agreed that this type of information was clearly an important component of local conservation efforts, but that at the continental scale it should be left to additional regional and local efforts. This constraint of top-down efforts highlights the necessity of eventually matching this project with a community-based action plan involving members of the communities within the PCAs.
What is a PCA?
Priority conservation areas are defined on the basis of high biodiversity and continental uniqueness, incorporating aspects of ecological value, anthropogenic threat, and opportunity for conservation (i.e., existing designations and conservation initiatives). No comprehensive measure of biodiversity exists for the B2B region. Experts were, therefore, asked to assess biodiversity indirectly, relying on their accumulated knowledge of species, habitats and ecological processes. This includes the diversity of many different factors: 1) subregional and regional physiographic and oceanographic features important for continental planning (features on the order of 10–1,000 square kilometers); 2) high beta-level biological diversity (between-habitat diversity); 3) continental endemism; 4) key habitats — concentration areas such as breeding and feeding sites or migration routes—for Marine Species of Common Conservation Concern; 5) critical habitats of other umbrella and charismatic species that require large areas to persist; 6) areas that provide whole-region benefits, e.g., seasonally productive areas, migration corridors; and 7) areas of high biomass and/or productivity, e.g., coastal upwelling centers.
These criteria are consistent with other approaches that suggest capturing areas that contain regional representation of major habitats, diverse types of habitats, rare and threatened species and habitats, and endemic species. At the same time, it is important to capture oceanographic processes and ecological linkages that interconnect these habitats.
The geographic scope of the project (EEZ from 22°N latitude to 65°N latitude) included estuaries and islands, but not upland areas or freshwater environments. We also emphasize transboundary areas, owing to the international aspect of this project.
We developed a geographic information system (GIS) based on common physical data for the entire region to serve as a framework for integrating other data sets. Five data sets—bathymetry, shoreline and satellite-derived measures of productivity (chlorophyll-A), sea surface temperature, and altimetry (sea surface height used to derive surface currents)—offered reasonable potential for a B2B-scale analysis. Based on the input of the experts at workshops held in Monterey in 2001 and Portland in 2002 and after consultations with other experts, we assembled additional physical, biological and social data sets. The mandate given to the project was to use existing sources. Thus, no new data were collected, although significant efforts to digitize certain data sets did occur. In several cases, we included previous priority- setting exercises conducted on regional scales. All data sets were compiled onto a CD-ROM, in GIS format (Etnoyer et al. 2002).
Marine Species of Common Conservation Concern
In an initiative parallel to the identification of PCAs, the CEC convened an advisory group to identify the first list of Marine Species of Common Conservation Concern (MSCCC). See complete list of MSCCC. The goal of this project was to focus on key conservation actions and protected areas needed to support these populations. These umbrella species captured a different conservation perspective by shifting the focus to processes that affect species as well as the places they inhabit. Compulsory criteria focused the initiative towards species that were: 1) transboundary or migratory, and 2) at high risk of extinction, given their current status or trends, their inherent natural vulnerability and their susceptibility to anthropogenic threats. Using secondary or recommended criteria, priority was then given to species: 1) deemed ecologically significant, e.g., umbrella, keystone, or indicator taxa; 2) officially listed as being of conservation concern by one of the three North American countries, by the World Conservation Union (IUCN), or by the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES); 3) whose recovery or management was feasible, including re-establishment potential, as well as the opportunity to strengthen management and learn from successes; and 4) which had a high potential for public engagement (i.e., flagship species). Key habitats for these species, as identified in the CEC’s report on Species of Common Conservation Concern (Wilkinson et al., Species..., in prep.), were included as criteria for PCAs.
Several data analyses were conducted in order to highlight the significance of selected data sets to the conservation priority-setting exercise. These analyses include: 1) benthic complexity—a measure similar to rugosity; 2) sea surface temperature fronts—areas known to aggregate a wide-variety of pelagic sealife including fishes, sea turtles, birds and mammals; 3) primary productivity; and 4) sea-surface height—a measure of currents and eddies which also serve to transport nutrients and aggregate ocean life.
Benthic complexity is a unique measure related to both slope and roughness. Generally speaking, it is a measure of the intricacy of the seafloor, that is, how much it changes in a given unit of area. This is in many ways similar to “rugosity.” However, unlike rugosity, complexity is not greatly affected by large unidirectional changes in depth, such as cliffs.
Methodology described by Ardron (2002) was initially used as a way to identify complex seafloor of the British Columbia coast that previous measures, such as slope and relief, had not. It differs from slope and relief by differentiating between uniformly steep features, such as fjords, and those features that display more topographic complexity, such as rocky reefs, seamounts, and archipelagos. The latter are especially known for their ecological significance.
For the purposes of our analysis, bathymetry with sufficiently high resolution was not uniformly available throughout the B2B region. High-resolution bathymetry was available for three areas: 1) British Columbia; 2) coastal California, Oregon and Washington; and 3) Baja California. The results of this analysis indicate that the areas of highest benthic complexity are the shelf slope, canyons, gullies, island archipelagos and seamounts.
Sea Surface Temperature Frontal Density
Oceanographic fronts can be some of the most persistent features in the pelagic realm, and they are known to perform vital habitat functions for fishes (Schick 2002), sea turtles (Polovina et al. 2000), seabirds (Decker and Hunt 1996) and marine mammals (Davis et al. 2002). Fronts are characterized by the interaction of two dissimilar water masses, such as cold water and warm water, freshwater and saltwater, or nutrient-rich water and nutrient-poor water. This interaction can bring deepwater nutrients to the surface, where sunlight and warm water stimulate a phytoplankton bloom, often followed by a zooplankton bloom, producing a pulse of resources for species at higher levels.
The multi-channel sea surface temperature (MCSST) data are derived from the five-channel advanced veryhigh-resolution radiometers (AVHRR) on board the National Oceanic and Atmospheric Administration’s (NOAA) polar-orbiting satellites. Clouds hinder frontal detection by radiometry. Cloud-free, interpolated sea surface temperature (SST) data are available at coarse scales. We tested satellite-derived SST data at three different resolutions to examine the effect of scale upon edge-detection algorithms. We found that the coarse-scale, cloud-free MCSST-interpolated data underestimated the total linelength of frontal features from finer scale raw AVHRR at nine-kilometer resolution, and Coastwatch data at two-kilometer resolution. However, MCSST data can reliably detect the strongest, most persistent temperature fronts within the B2B extent. We examined monthly MCSST data over a four-year period, from 1996–1999. This “cloudless” temporal window captured a strong El Niño, a La Niña and two “normal” years.
Using new analysis methods to detect temporal variation in SST frontal concentrations (Etnoyer et al. 2004), we found less than one percent of the Northeast Pacific shows active temperature fronts across seasons and between years. We identified three of these large features— offshore Los Cabos (Mexico), Point Conception (United States), and the southern California Channel Islands (United States). The frontal density signature off northern Baja California (Ensenda Front) appeared weaker and closer to shore in an El Niño year, and stronger and more offshore during a normal year. Satellite telemetry data and fisheries statistics demonstrate that these pelagic habitats are important to migrating blue whales (Balaenoptera musculus), swordfish (Xiphias gladius) and striped marlin (Tetrapturus audax).
Sea Surface Height: Currents, Gyres and Eddies
At the scale of an ocean basin, the sea surface is not flat. Warm water expands, producing higher than average surface heights (hills), while cool water contracts, registering lower than average surface heights (valleys). Orbital satellites such as TOPEX/Poseidon use pulses of radar to measure minute differences in sea surface height. This is known as “altimetry.” In an altimetry map, wind and waves are averaged, and sea surface height is expressed as an “anomaly”—a negative or a positive difference from the mean sea surface height.
These small differences in water height translate into current movement. Warm-core eddies, areas with higher than average sea surface heights, spin clockwise or anticyclonically. Lower than average sea surface heights, or cold-core eddies, spin counterclockwise or cyclonically. Furthermore, cold-core eddies create upwelling conditions that bring nutrients to the surface, and may result in trophic cascades and plankton blooms. Eddies can form when large freshwater flows from terrestrial rivers spill into the saline waters of the sea. The Haida Eddy (Pacific Canada) is a three-dimensional “swirling freshwater tornado” about the size of Lake Michigan that transports coastal nutrients (such as iron) to nutrientpoor offshore waters, fertilizing the environment and creating a plankton bloom (Crawford and Whitney 1999). The Haida Eddy appears strongest in El Niño winters off British Columbia. The footprint of the Haida Eddy varies within El Niño Southern Oscillation cycles, and appears weakest in La Niña years.
For this analysis, we used altimetry to study surface current patterns in the Gulf of Alaska. The Colorado Center for Atmospheric Research provided four years of biweekly averaged surface current magnitude and velocity, derived from a blended product of TOPEX/ Poseidon, and ERS-1 and ERS-2 satellites. We masked all but the highest waters or the greatest slope and sequenced the data to reveal the location and trajectory of warm core rings in the Gulf of Alaska.
We identified the 1998 Haida Eddy and tracked it from Gwaii Haanas (Queen Charlotte Islands) in a southwesterly direction to beyond the Canadian EEZ. The feature persisted for more than a year, beginning at a size of 100 kilometers in diameter, then dissipating down to 75 kilometers for much of the year. We identified an equally impressive anti-cyclonic feature that seemed to originate in Shelikof Strait and to propagate westward along the Aleutian Archipelago, gaining strength as it passed. This feature traveled more than 400 kilometers in the course of six months. Several Sitka Eddies came and went in the Gulf of Alaska throughout the four-year investigation period. These eddies represent a transboundary export of nutrients and larvae between British Columbia, Canada, and Alaska, United States. It is also possible that these retentive eddies could concentrate and transport inorganic pollutants and contaminants to rare and delicate seamount ecosystems.
Measuring synoptic chlorophyll distribution in the global ocean is only possible with satellite ocean color sensors. Sea-viewing wide field-of-view sensor (SeaWiFS) and moderate-resolution imaging spectroradiometer (MODIS) satellites provide one- to two-day coverage of the entire earth, allowing study of regional and global ocean color patterns. The primary data product from the sensors is the surface chlorophyll concentration (in mg/m3). Combined with the SST data obtained from satellites with an AVHRR, primary production can also be estimated from empirical models.
Net primary productivity (NPP) can be estimated from three parameters: chlorophyll, photosynthetically available radiation (PAR) and SST. We estimate the NPP in g C m-2 month-1 (Behrenfeld and Falkowski 1997). Monthly chlorophyll data for the region bounded by 12°N–72°N and 180°W–100°W between September 1997 and June 2002 were obtained from the US National Aeronautics and Space Administration (NASA) Distributed Active Archive Center,5 PAR data from SeaWiFS,6 and monthly SST data from NASA’s Jet Propulsion Laboratory.
Atmospheric effects were removed and chlorophyll concentration was estimated. To estimate primary production, the model takes into account the depth-dependent chlorophyll and light profile, and estimates the primary production per unit chlorophyll from SST, using an empirical relationship. Based on the NPP monthly results for each location, we estimated the number of occurrences (frequency) in a year when NPP exceeded a predefined number (10 g C m-2 month-1). The number was chosen according to visual examination of the difference between oligotrophic and productive waters, but is somewhat arbitrary. The results serve as an index to describe how long enhanced productivity exists at a location.