Trophic relationships and oceanography on and around a small offshore bank

Tidal-stream habitats present periodically fast-flowing, turbulent conditions. Evidence suggests that these conditions benefit top predators such as harbour porpoises Phocoena phocoena, presumably allowing them to optimise exploitation of prey resources. However, clear demonstration of this relationship is complicated by the fact that strong tidal flows often occur near-simultaneously across a wide area. The Great Race of the Gulf of Corryvreckan (western Scotland, UK) is a jetting tidal system where high-energy conditions persist across a broad range of tidal phases in a localised, moving patch of water. Porpoises can therefore actively enter or avoid this habitat, facilitating study of their usage of adjacent high-and low-energy environments. The distribution of harbour porpoises was studied using passive acoustic porpoise detectors (C-PODs) deployed on static moorings (~35 d) and on Lagrangian drifters moving freely with the current (up to ~48 h). This dual approach provided complementary perspectives on porpoise presence. C-PODs moored in the path of the Great Race registered a significant increase in detections during the passing of the energetic tidal jet. Encounter durations recorded by drifting C-PODs were longer than those recorded by moored C-PODs, suggesting that porpoises tended to move downstream with the flow rather than remaining stationary relative to the seabed or moving upstream. The energetic, turbulent conditions of the Great Race are clearly attractive to porpoises, and they track its movement with time; however, their structured movements in response to the evolving tidal situation cannot simply be represented as a direct relationship between current speed and porpoise presence.

Section: Introductionmentioning

confidence: 58%

Riding the tide: use of a moving tidal-stream habitat by harbour porpoises

Benjamins

Dale²,

Geel³

et al. 2016

“…Although some species congregate in relatively discrete areas (e.g. Rayner et al 2007, Stevick et al 2008, challenges arise when estimating abundance for species that undertake extensive seasonal migrations and range over large, poorly defined areas. For long-lived, slow-breeding species with large home ranges, such as baleen whales, there are several challenges to estimating abundance, especially when managing recovering populations (Hammond 1990, Stevick et al 2003.…”

Section: Introductionmentioning

confidence: 99%

Abundance of humpback whales in Oceania using photo-identification and microsatellite genotyping

Constantine¹,

Jackson²,

Steel³

et al. 2012

Estimating the abundance of long-lived, migratory animals is challenging but essential for managing populations. We provide the first abundance estimates of endangered humpback whales Megaptera novaeangliae from their breeding grounds in Oceania, South Pacific. Using fluke photo-identification (1999−2004, n = 660 individuals) and microsatellite genotypes (1999−2005, n = 840 individuals), we estimated abundance with open capture-recapture statistical models. Total Oceania abundance and trends were estimated from 4 primary and 5 secondary sampling sites across the region. Sex-specific genotype data enabled us to account for the difference in capturability of males and females, by doubling male-specific estimates of abundance derived from genotypes. Abundance estimates were congruent between primary-and secondaryregion data sets, suggesting that the primary regions are representative of all Oceania. The best estimate of total abundance was 4329 whales (3345−5313) in 2005, from a sex-specific POPAN super-population model, which includes resident whales and those migrating through the surveyed areas. A doubled-male POPAN abundance estimate from 2003 (n = 2941, 95% CI = 1648−4234) was considered the most plausible for the 4 primary survey areas and was similar to the 2003 doubled-male estimate derived from Pradel capture probabilities (n = 2952, 95% CI = 2043−4325). Our results confirm that Oceania is the least abundant humpback whale breeding population in the southern hemisphere. Pradel models showed no significant trend in abundance, which contradicts the recovery seen in most other populations throughout the world. Thus we suggest that the whales in this area warrant continued study and management attention.KEY WORDS: Megaptera novaeangliae · South Pacific · Capture-recapture · Genotyping · Endangered speciesResale or republication not permitted without written consent of the publisher

“…Alling et al 1991, Fiedler et al 1998, Palacios 1999, Hucke-Gaete et al 2003, Croll et al 2005, Etnoyer et al 2006, Branch et al 2007, which occur at multiple spatio-temporal scales (Watkins 2000). The use of appropriate scales is central to ecological studies (Levin 1992), and scales of oceanographic features that aggregate prey vary greatly, from the macro-scale Antarctic Circumpolar Current (Tynan 1998) to mesoscale coastal upwellings (Croll et al 2005) and more fine-scale bathymetric features such as individual banks (Stevick et al 2008).…”

Section: Introductionmentioning

confidence: 99%

Blue whale habitat selection and within-season distribution in a regional upwelling system off southern Australia

Gill¹,

Morrice²,

Page³

et al. 2011

103

104

Blue whales Balaenoptera musculus aggregate to feed in a regional upwelling system during November-May between the Great Australian Bight (GAB) and Bass Strait. We analysed sightings from aerial surveys over 6 upwelling seasons (2001-02 to 2006-07) to assess within-season patterns of blue whale habitat selection, distribution, and relative abundance. Habitat variables were modelled using a general linear model (GLM) that ranked sea surface temperature (SST) and sea surface chlorophyll (SSC) of equal importance, followed by depth, distance to shore, SSC gradient, distance to shelf break, and SST gradient. Further discrimination by hierarchical partitioning indicated that SST accounted for 84.4% of variation in blue whale presence explained by the model, and that probability of sightings increased with increasing SST. The large study area was resolved into 3 zones showing diversity of habitat from the shallow narrow shelf and associated surface upwelling of the central zone, to the relatively deep upper slope waters, broad shelf and variable upwelling of the western zone, and the intermediate features of the eastern zone. Density kernel estimation showed a trend in distribution from the west during November-December, spreading south-eastward along the shelf throughout the central and eastern zones during January-April, with the central zone most consistently utilised. Encounter rates in central and eastern zones peaked in February, coinciding with peak upwelling intensity and primary productivity. Blue whales avoided inshore upwelling centres, selecting SST ~1°C cooler than remotely sensed ambient SST. Whales selected significantly higher SSC in the central and eastern zones than the western zone, where relative abundance was extremely variable. Most animals departed from the feeding ground by late April.