Tidal drift removes the need for area-restricted search in foraging Atlantic puffins

Bennison, Ashley; Quinn, John L.; Debney, Alison; Jessopp, Mark

doi:10.1098/rsbl.2019.0208

Cited by 14 publications

(13 citation statements)

References 60 publications

(60 reference statements)

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“…Flight costs are extremely high in auks (Elliott et al., 2013) so flight has a key impact on energy expenditure. Consistent with this, studies suggest that chick‐rearing puffins usually feed within 25 km of the colony (Bennison et al., 2019; Harris et al., 2012). However, in our study, puffins fed near the colony but also much further, and used a dual foraging mode combining short and long trips, with the negative relationship between trip range and breeding success holding for both types of trips.…”

Section: Discussionmentioning

confidence: 79%

“…Time in flight was strongly correlated with trip range (LMM,

χ_{1}^{2}

= 89.1, p < 0.001, R 2 = 0.57); therefore, flight time per trip differed between colonies (Figure 2c, LMM,

χ_{2}^{2}

= 21.9, p < 0.001, R 2 = 0.33). Most flight occurred in a few sustained bouts (short trips: 2.7 ± 0.1 bouts; long trips: 4.9 ± 0.4 bouts) suggesting that birds flew out to a feeding area, then spent most of the time sitting on the water and diving in a ‘tidal‐drift’ tactic (Bennison et al., 2019), rather than engaging in area‐restricted search (this is also visible from the tracks, Figure S5). Across all colonies, foraging effort was consistently higher on long trips than on short trips, but there were no differences between colonies (LMM, short vs. long:

χ_{1}^{2}

= 61.8, p < 0.001, R 2 = 0.48; colony:

χ_{2}^{2}

= 2.7, p = 0.253; R 2 = 0.48), although it seemed to increase on long trips from northern Iceland to Norway (Table 2; Figure 2d).…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Local prey shortages drive foraging costs and breeding success in a declining seabird, the Atlantic puffin

Fayet

Clucas

Anker‐Nilssen

et al. 2021

Journal of Animal Ecology

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As more and more species face anthropogenic threats, understanding the causes of population declines in vulnerable taxa is essential. However, long‐term datasets, ideal to identify lasting or indirect effects on fitness measures such as those caused by environmental factors, are not always available. Here we use a single year but multi‐population approach on populations with contrasting demographic trends to identify possible drivers and mechanisms of seabird population changes in the north‐east Atlantic, using the Atlantic puffin, a declining species, as a model system. We combine miniature GPS trackers with camera traps and DNA metabarcoding techniques on four populations across the puffins’ main breeding range to provide the most comprehensive study of the species' foraging ecology to date. We find that puffins use a dual foraging tactic combining short and long foraging trips in all four populations, but declining populations in southern Iceland and north‐west Norway have much greater foraging ranges, which require more (costly) flight, as well as lower chick‐provisioning frequencies, and a more diverse but likely less energy‐dense diet, than stable populations in northern Iceland and Wales. Together, our findings suggest that the poor productivity of declining puffin populations in the north‐east Atlantic is driven by breeding adults being forced to forage far from the colony, presumably because of low prey availability near colonies, possibly amplified by intraspecific competition. Our results provide valuable information for the conservation of this and other important North‐Atlantic species and highlight the potential of multi‐population approaches to answer important questions about the ecological drivers of population trends.

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Section: Discussionmentioning

confidence: 79%

“…Time in flight was strongly correlated with trip range (LMM,

χ_{1}^{2}

= 89.1, p < 0.001, R 2 = 0.57); therefore, flight time per trip differed between colonies (Figure 2c, LMM,

χ_{2}^{2}

χ_{1}^{2}

= 61.8, p < 0.001, R 2 = 0.48; colony:

χ_{2}^{2}

= 2.7, p = 0.253; R 2 = 0.48), although it seemed to increase on long trips from northern Iceland to Norway (Table 2; Figure 2d).…”

Section: Resultsmentioning

confidence: 99%

Local prey shortages drive foraging costs and breeding success in a declining seabird, the Atlantic puffin

Fayet

Clucas

Anker‐Nilssen

et al. 2021

Journal of Animal Ecology

View full text Add to dashboard Cite

show abstract

“…The speed threshold was chosen to account for the exceptional current speeds in the channel, regularly exceeding 3.5 m s −1 [45,57,58]. This means that birds drifting passively with the current, a behavior known as tidal drift, could realistically reach groundspeeds normally associated with flight [59][60][61]. An example R script for preparation, processing and analysis (steps 2-4 Figure 2) along with a dataset for one individual are provided in Appendix A and Supplementary Materials.…”

Section: Preparation and Processingmentioning

confidence: 99%

“…The blue shaded area (3.5-5 m/s) is the range of peak current speeds in the Pentland Firth [45,57,58]. Between 1 and 5 m/s, there is therefore a range of speeds that normally could be classified as flight but in this case could be tidal drift (bird sitting on the sea surface and drifting with the tide, [59][60][61]). The cautious approach would therefore be to set a speed threshold of >5 m/s.…”

Section: Appendix A3 Speedmentioning

confidence: 99%

The Use of Animal-Borne Biologging and Telemetry Data to Quantify Spatial Overlap of Wildlife with Marine Renewables

Isaksson

Cleasby

Owen

et al. 2021

JMSE

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The growth of the marine renewable energy sector requires the potential effects on marine wildlife to be considered carefully. For this purpose, utilization distributions derived from animal-borne biologging and telemetry data provide accurate information on individual space use. The degree of spatial overlap between potentially vulnerable wildlife such as seabirds and development areas can subsequently be quantified and incorporated into impact assessments and siting decisions. While rich in information, processing and analyses of animal-borne tracking data are often not trivial. There is therefore a need for straightforward and reproducible workflows for this technique to be useful to marine renewables stakeholders. The aim of this study was to develop an analysis workflow to extract utilization distributions from animal-borne biologging and telemetry data explicitly for use in assessment of animal spatial overlap with marine renewable energy development areas. We applied the method to European shags (Phalacrocorax aristotelis) in relation to tidal stream turbines. While shag occurrence in the tidal development area was high (99.4%), there was no overlap (0.14%) with the smaller tidal lease sites within the development area. The method can be applied to any animal-borne bio-tracking datasets and is relevant to stakeholders aiming to quantify environmental effects of marine renewables.

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“…Terns have a high level of variability in foraging modes (Eglington et al 2014) both within and across years, and appear to rely on trophic level segregation rather than spatial segregation to avoid competition (Robertson et al 2014). Although foraging auks are known to associate with discrete features in the environment, such as tidal currents (Waggitt et al 2016, Bennison et al 2019, auk distribution is generally closely linked to distance to colony (Johnston et al 2015). Furthermore, sympatric auk species also rely on niche segregation rather than spatial segregation during the breeding season (Linnebjerg et al 2013, Shoji et al 2015b).…”

Section: Comparison Of Foraging Radius Distributions With Aerial Survmentioning

confidence: 99%

Assessing the effectiveness of foraging radius models for seabird distributions using biotelemetry and survey data

et al. 2019

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Relatively simple foraging radius models have the potential to generate predictive distributions for a large number of species rapidly, thus providing a cost-effective alternative to large-scale surveys or complex modelling approaches. Their effectiveness, however, remains largely untested. Here we compare foraging radius distribution models for all breeding seabirds in Ireland, to distributions of empirical data collected from tracking studies and aerial surveys. At the local/colony level, we compared foraging radius distributions to GPS tracking data from seabirds with short (Atlantic puffin Fratercula arctica, and razorbill Alca torda) and long (Manx shearwater Puffinus puffinus, and European storm-petrel Hydrobates pelagicus) foraging ranges. At the regional/national level, we compared foraging radius distributions to extensive aerial surveys conducted over a two-year period. Foraging radius distributions were significantly positively correlated with tracking data for all species except Manx shearwater. Correlations between foraging radius distributions and aerial survey data were also significant, but generally weaker than those for tracking data. Correlations between foraging radius distributions and aerial survey data were benchmarked against generalised additive models (GAMs) of the aerial survey data that included a range of environmental covariates. While GAM distributions had slightly higher correlations with aerial survey data, the results highlight that the foraging radius approach can be a useful and pragmatic approach for assessing breeding distributions for many seabird species. The approach is likely to have acceptable utility in complex, temporally variable ecosystems and when logistic and financial resources are limited.

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Tidal drift removes the need for area-restricted search in foraging Atlantic puffins

Cited by 14 publications

References 60 publications

Local prey shortages drive foraging costs and breeding success in a declining seabird, the Atlantic puffin

Local prey shortages drive foraging costs and breeding success in a declining seabird, the Atlantic puffin

The Use of Animal-Borne Biologging and Telemetry Data to Quantify Spatial Overlap of Wildlife with Marine Renewables

Assessing the effectiveness of foraging radius models for seabird distributions using biotelemetry and survey data

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