A View of the Ocean from Pacific Predators

Block, Barbara A.; Costa, Daniel P.; Bograd, Steven J.

doi:10.1002/9781444325508.ch15

Cited by 5 publications

(4 citation statements)

References 72 publications

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“…Albatross tracking data were collected during the postbreeding seasons (March -November) of 2004-2006 by the Tagging of Pacific Predators research group [6]. Adult Laysan and black-footed albatrosses were fitted with Lotek LTD 2400 light level and temperature-based geolocator archival tags (for further description see [31]).…”

Section: (A) Datasetsmentioning

confidence: 99%

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Dynamic habitat models: using telemetry data to project fisheries bycatch

et al. 2011

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Fisheries bycatch is a recognized threat to marine megafauna. Addressing bycatch of pelagic species however is challenging owing to the dynamic nature of marine environments and vagility of these organisms. In order to assess the potential for species to overlap with fisheries, we propose applying dynamic habitat models to determine relative probabilities of species occurrence for specific oceanographic conditions. We demonstrate this approach by modelling habitats for Laysan (Phoebastria immutabilis) and black-footed albatrosses (Phoebastria nigripes) using telemetry data and relating their occurrence probabilities to observations of Hawaii-based longline fisheries in 1997 -2000. We found that modelled habitat preference probabilities of black-footed albatrosses were high within some areas of the fishing range of the Hawaiian fleet and such preferences were important in explaining bycatch occurrence. Conversely, modelled habitats of Laysan albatrosses overlapped little with Hawaii-based longline fisheries and did little to explain the bycatch of this species. Estimated patterns of albatross habitat overlap with the Hawaiian fleet corresponded to bycatch observations: black-footed albatrosses were more frequently caught in this fishery despite being 10 times less abundant than Laysan albatrosses. This case study demonstrates that dynamic habitat models based on telemetry data may help to project interactions with pelagic animals relative to environmental features and that such an approach can serve as a tool to guide conservation and management decisions.

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Section: (A) Datasetsmentioning

confidence: 99%

“…The development and use of a variety of electronic tags for animal tracking have revolutionized our knowledge of the spatio-temporal ecology of marine animals over the last decade (e.g. [5,6]), and conservation applications of these data are emerging (e.g. [7][8][9]).…”

Section: Introductionmentioning

confidence: 99%

Dynamic habitat models: using telemetry data to project fisheries bycatch

et al. 2011

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“…Broadly speaking, hotspots correspond to locations where an ‘out‐of‐the‐ordinary’ phenomenon takes place (Ord & Getis, ; Nelson & Boots, ). In this study, as is routinely the case with free‐ranging wildlife, we see it as a species' critical foraging ground, breeding site, or migratory corridor, although it can by extension refer to any region of high occupancy (Block, Costa & Bograd, ), high species richness (Worm et al ., ), or intense biological activity (Drazen et al ., ).…”

Section: Introductionmentioning

confidence: 99%

Topographic determinants of mobile vertebrate predator hotspots: current knowledge and future directions

et al. 2014

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Despite being identified as a driver of mobile predator aggregations (hotspots) in both marine and terrestrial environments, topographic complexity has long remained a challenging concept for scientists to visualise and a difficult parameter to estimate. It is only with the advent of high-speed computers and the recent popularisation of geographical information systems (GIS) that terrain attributes have begun to be quantitatively measured in three-dimensional space and related to wildlife dynamics, making the well-established field of geomorphometry (or 'digital terrain modelling') a discipline of growing appeal to biologists. Although a diverse array of numerical metrics is now available to describe the shape, geometry and physical properties of natural habitats, few of these are known to, or adequately used by, ecologists. In this review, we examine the nature and usage of 56 geomorphometrics extracted from the ecological modelling literature over a period of 32 years (1979-2011). We show that, in studies of mobile predators, numerous topographic variables have largely been overlooked in favour of single basic metrics that do not, on their own, fully capture the complexity of continuous landscapes. Based on a simulation approach, we assess the redundancy and correlation structure of these metrics and demonstrate that a majority are highly collinear. We highlight a suite of 7-8 complementary metrics which best explain topographic patterns across a bathymetric grid of the west Australian seafloor, and contend that field and analytical protocols should prioritise variables of these types, particularly when the responses of predator populations to physical habitat features are of interest. We suggest that prominent structures such as canyons, seamounts or mountain chains can serve as useful proxies for predator hotspots, especially in remote locations where access to high-resolution biological data is often limited.

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“…For example, individual Pacific salmon ( Oncorhynchus spp) were tracked over thousands of kilometers using tags that emit individually coded acoustic pulses to coastal receivers [6] . Via tags, how marine mammals use major oceanic features such as frontal zones under ice has been mapped [25] ; new rapid genomic techniques and databases (e.g., DNA barcoding, 454-pyrotag sequencing [26] and MICROBIS – http://icomm.mbl.edu/microbis/ ) are rewriting knowledge of marine biodiversity and marine-life abundance. The CReefs project of the Census developed a new automated structure, (Autonomous Reef Monitoring Structures (ARMS)), 500 of which are now deployed in the Pacific and Indian oceans and the Caribbean, collecting specimens and ecological data to monitor tropical coral reef biodiversity [27] .…”

Section: International Ocean Observation Systemsmentioning

confidence: 99%