Establishing at-sea habitat preferences as a means of delineating EBSAs for threatened species: an example of the identification of Important Bird Areas (IBAs) in the Bering Sea for the Short-tailed Albatross (Phoebastria albatrus)
Integrating different distributional datasets (especially from remote-recording instruments and at-sea surveys) is likely to be important in identifying EBSAs for a variety of top predators found on the high seas. In this example we look at how satellite tracking data and vessel survey data can be used to identify IBAs based on habitat preferences for a threatened seabird, the Short-tailed Albatross.
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BirdLife International is the IUCN Red List authority for birds, and conducts a comprehensive review of the status of all species ever four years, with annual reviews of the most threatened. The BirdLife Important Bird Areas (IBA) Programme uses the Red List assessment to define one of the global IBA criteria for identifying IBAs (Category A1), such that sites critical for the conservation of the most threatened species are identified.
The IBA criteria explicitly require the demonstration of “presence of significant numbers of birds” and the “regular use” at a site in order for it to qualify as an IBA. Whenever possible, data from multiple years are used to provide justification.
The Short-tailed Albatross (Phoebastria albatrus) breeds on the island of Torishima (Japan), and on Minami-kojima in the Senkaku Islands (claimed by Japan, the People's Republic of China and the Republic of China on Taiwan). Historically, there are believed to have been at least nine colonies to the south of Japan and in the East China Sea. The species declined dramatically during the 19th and 20th centuries, and was believed extinct in 1949, until rediscovered in 1951. The current population is estimated to be 2,364 individuals, with 1,922 birds on Torishima and 442 birds on Minami-kojima (BirdLife International 2009a).
Satellite tracking has indicated that during the breeding season (December - May) it is found in highest densities around Japan. In the post-breeding season, and for sub-adults during the entire year, its marine range covers most of the northern Pacific Ocean, but it occurs in highest densities in areas of upwelling along shelf waters of the Pacific Rim (Suryan et al. 2006). During the post-breeding period females spend most of their time in shelf waters of the Exclusive Economic Zones (EEZ) belonging to Japan and Russia, while males and juveniles spend their time in similar habitats in the EEZs around the Aleutian Islands, Bering Sea and the coast of North America.
This species is currently listed as Vulnerable (BirdLife International 2009a) because, although conservation efforts have resulted in a steady population increase (US Fish & Wildlife Service 2008), it has a very small breeding range, rendering it highly susceptible to stochastic events and human impacts. Away from the breeding colonies mortality caused by fisheries is a major threat, and environmental contaminants at sea (oil-based compounds) may also be an issue. Threats at sea are exacerbated by the fact that birds concentrate at predictable hotspots.
This example looks at the methods available for determining where these predictable hotspots are located, and what environmental variables may be responsible for them. Although we focus on the Short-tailed Albatross, which is mostly tied to the EEZs of several nations, the methodologies are applicable to any threatened oceanic top predator that occurs at predictable hotspots, including those on the high seas.
How the area of importance for the threatened Short-tailed Albatross was identified
It has been proposed (BirdLife 2009b) that a regularly used hotspot identified solely on tracking data should be required to meet the following conditions:
“Areas visited by birds from more than one site or during different periods (seasons or years)”
To determine the areas within the Short-tailed Albatross tracking dataset that met these conditions of ‘regular use’, the data were split according to season. This allows us to identify sites of importance during both the breeding and non-breeding seasons. Within each season, data were only used if they were available in at least two different years and for a minimum of 4 birds in each year. This is because smaller sample sizes can have an undue influence on the overall areas identified. For each year a Kernel Density Estimation (KDE) was applied, Utilisation Distributions (UDs) were calculated, and the 50% UDs were used to represent core areas of activity. The same process was applied for each life-history stage and each year with sufficient data. These layers were then combined to create a map of ‘regular use’ and the number of tracked birds visiting each site was determined (see Figure 2)
Figure 2: Map of tracking data showing areas of ‘regular use’ during different seasons, and the number of tracked birds using each area (numbers on map). Areas outside of the ‘regular use’ sites had up to 6 birds using them, though they did not do so repeatedly.
Opportunistic at-sea sightings of Short-tailed Albatross were compiled from vessel-based observations in the North Pacific (Pacific Pelagic Seabird Database 2007) for the years 1994 – 2004. The data indicate the location of sightings and the number of birds seen on each occasion, but the dataset represents presence-only data, and has not been compiled from standardised, systematic surveys, so has limitations. However, it represents a useful additional, comparative dataset from which certain inferences can be made of the number of birds likely to be using an area of ‘regular use’ identified from the tracking data. The vessel data were overlaid with a 1 degree square grid and the maximum group size of birds sighted within each cell was calculated. The number of years for which a cell had positive sightings was also calculated to investigate consistency between years.
Figure 3: Map showing areas of ‘regular use’ during different seasons (identified from tracking data), the maximum number of birds counted within a 1 degree square obtained from opportunistic at-sea sightings, and the number of years a sighting was made within each square between 1994 and 2004.
It is clear that some areas, such as that in the Bering Sea and the middle of the Aleutian Chain, have higher counts of Short-tailed Albatross than others. However, because of the opportunistic nature of the vessel sightings it is difficult to delimit areas based on these data alone. Conversely, while tracking data do allow areas to be delimited, they do not enable estimates of abundance to be made. Using a combination of both data sources it is possible to delimit areas and determine their overall importance based on the number of birds present. Integrating satellite tracking data and vessel survey data has proved a successful method for identifying and delimiting IBAs in Portugal (Ramirez et al. 2008) and Spain (SEO/BirdLife 2009).
Suryan et al. (2006) conducted first-passage time analysis (FPT; Fauchald & Tveraa 2003) on Short-tailed Albatross tracked in the Aleutian Islands to reveal the location and spatial scale of area restricted search (ARS) patterns. They found that, on average, ARS occurred within a 70km radii, which means that once an area of suitable habitat has been found, searching occurs within 70km of this point. To ensure that adequate habitat is included in hotspots identified, boundaries of these sites should therefore include a 70km buffer either side of suitable habitats, which is illustrated in Figure 1.
In Figure 1, showing the Bering Sea shelf break IBA, 8 of the 41 tracked birds (20%) were found to use this area extensively, with birds present between June and November. The vessel survey data agree with this, with most sightings in June and September. The seasonality of occurrence here can be partly explained by the fact that the ocean in these latitudes is covered by sea ice at other times of the year. In this example both the tracking data and the vessel data indicate that birds are congregating around the shelf break between 250 and 1000m depth. The shelf within this area has a maximum 21° slope angle, and the mean annual water temperature is around 1°C. Suryan et al. (2006) also confirmed the importance of the shelf break and slope regions as hotspots of activity. They also found that at all scales, wind speed, depth, slope, and chlorophyll a had a significant effect on FPT.
This example shows a method for identifying key habitats for a threatened species in territorial waters; similar methods could be applied to threatened species on the high seas to identify potential EBSAs.
Sources of data
For this illustration, we used tracking data obtained from the Global Procellariiform Tracking Database held by the Global Seabirds Programme of Birdlife International. Data for Short-tailed Albatross were provided to the database by Dr Rob Suryan (Oregon State University, USA).
The Global Procellariiform Database holds tracking data information provided by 57 scientists from 11 countries on 28 species of albatross and petrels. Up to the end of 2008 it held 3,764 tracks obtained from Platform Transmitter Terminal (PTT) & Global Positioning Satellites (GPS) totaling 957,148 hours at sea, as well as 721 tracks obtained from Geolocators (GLS) totaling 61,832 days. A complete analysis of the Procellariiform database would reveal a number of EBSAs on the high seas.
Tracking datasets exist for numerous other seabird species, pinnipeds, cetaceans, turtles and pelagic fish, and the methodologies outlined here could be applicable to these other datasets. (see e.g. Tagging of Pacific Predators (TOPP), Seaturtle.com, Falabella et al 2009)
To conduct the most complete tracking data analysis requires an adequate sample size of tracked birds within each life-history stage. Most seabird species do not have a complete dataset covering all life-history stages; however for many some form of between-years or between-seasons comparison would be possible.
Short-tailed Albatross at-sea sightings were obtained from the North Pacific Pelagic Seabird Database (2007). This database was compiled by the U.S. Geological Survey and U.S. Fish and Wildlife Service to provide comprehensive geographic data on the pelagic distribution of seabirds in Alaska and the North Pacific and includes data from researchers in Canada, Russia, and the USA gathered between 1972 and 2003.
Vessel-survey data are held in a variety of datasets around the world, though few attempt to include data collected on the high seas or create regional or global coverage. Of those that do, the following are examples that may hold information of use in the identification of EBSAs on the high seas:
- The North Pacific Pelagic Seabird Database has information available on a wide range of seabirds occurring in the North Pacific.
- Ocean Biogeographic Information System Spatial Ecological Analysis of Megavertebrate Populations (OBIS-SEAMAP) is a spatially referenced online database, aggregating marine mammal, seabird and sea turtle data from across the globe (Halpin et al. 2006).
- Surveys conducted by the Minerals Management Service (MMS) Cetaceans, Sea Turtles and Seabirds in the Northern Gulf of Mexico: Distribution, Abundance and Habitat Associations (Davis et al. 2000)
- The European Seabirds at Sea (ESAS) database was established in the early 1980s using a common format. It contains the results of ship-based and aerial seabird surveys in Northwest European waters, collected using standard methods (Camphuysen & Garthe 2004).
Identification of biologically significant areas for the various life-history stages of wide-ranging species depends upon compilation and analysis of the distribution patterns of marine biodiversity. Seabirds are one of the best taxa for this purpose, because as top predators they are excellent indicators of the state of the wider marine environment, they are easily observed, readily identified and widely surveyed and monitored. In addition they are often linked to a specific range of habitat features, and thus identifying important sites for seabirds is likely to include areas and habitats of importance for a wider range of taxa.
Interpreting tracking data is of vital importance in identifying potential EBSA on the high seas. Care needs to be taken in analysis of data to ensure that a consistent and comparable approach is used to identifying and delimiting sites. The ecology of individual species needs to be considered at all stages of an analysis to ensure that any variation is accounted for in the sites identified, and that the species’ ecology is amenable to a site- based approach during each life-history stage.
Representative sample sizes are especially important for identification of potential EBSAs based solely on tracking data. Bootstrapping (e.g. Manly 2006) may be a useful method for determining if the sample size of tracked birds is representative of the wider population. Adequate sample sizes are likely to vary greatly between species and geographic regions. For studies with small sample sizes, pseudo-replication can be an issue, as the foraging behaviour of a single individual on a single trip can produce hotspots in regions not frequented by any other individual from the same colony or dataset (Seamen et al. 1999). The possibility of missing hotspots should also be borne in mind when interpreting maps, irrespective of the sample size.
For analysis of vessel survey data, at-sea densities and habitat modeling should only be attempted with data collected from designated surveys using appropriate methodologies. Surveys that collect presence only data can provide a useful additional data source, though identification of EBSAs using only this type of data should be approached with caution due to the potential biases involved.
Only through identifying, protecting, and managing a network of sites, both on land and at sea, are populations of threatened seabird species likely to recover to former levels, and allow for the re-colonisation of previously occupied sites.
For best results when addressing these considerations, consult tracking experts and seabird biologists familiar with your region and species of interest.