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Items: 7

1.

Using accelerometers to develop time-energy budgets of wild fur seals from captive surrogates.

Ladds MA, Salton M, Hocking DP, McIntosh RR, Thompson AP, Slip DJ, Harcourt RG.

PeerJ. 2018 Oct 26;6:e5814. doi: 10.7717/peerj.5814. eCollection 2018.

2.

Creating functional groups of marine fish from categorical traits.

Ladds MA, Sibanda N, Arnold R, Dunn MR.

PeerJ. 2018 Oct 23;6:e5795. doi: 10.7717/peerj.5795. eCollection 2018.

3.

Proxies of energy expenditure for marine mammals: an experimental test of "the time trap".

Ladds MA, Rosen DAS, Slip DJ, Harcourt RG.

Sci Rep. 2017 Sep 18;7(1):11815. doi: 10.1038/s41598-017-11576-4.

4.

Intrinsic and extrinsic influences on standard metabolic rates of three species of Australian otariid.

Ladds MA, Slip DJ, Harcourt RG.

Conserv Physiol. 2017 Feb 21;5(1):cow074. doi: 10.1093/conphys/cow074. eCollection 2017.

5.

The utility of accelerometers to predict stroke rate in captive fur seals and sea lions.

Ladds MA, Rosen DA, Slip DJ, Harcourt RG.

Biol Open. 2017 Sep 15;6(9):1396-1400. doi: 10.1242/bio.027029.

6.

Seeing It All: Evaluating Supervised Machine Learning Methods for the Classification of Diverse Otariid Behaviours.

Ladds MA, Thompson AP, Slip DJ, Hocking DP, Harcourt RG.

PLoS One. 2016 Dec 21;11(12):e0166898. doi: 10.1371/journal.pone.0166898. eCollection 2016.

7.

Swimming metabolic rates vary by sex and development stage, but not by species, in three species of Australian otariid seals.

Ladds MA, Slip DJ, Harcourt RG.

J Comp Physiol B. 2017 Apr;187(3):503-516. doi: 10.1007/s00360-016-1046-5. Epub 2016 Nov 1.

PMID:
27803974

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