Evidence map›Paper›PMID 32082578›Full record

ArticleMovement ecology2020

Sex-differences in fine-scale home-range use in an upper-trophic level marine predator.

D C Lidgard, W D Bowen, S J Iverson

Abstract read
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Article in Movement ecology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

D C Lidgard1Department of Biology, Dalhousie University, B3H 4J1, Halifax, Nova Scotia Canada.ORCID 0000-0003-0927-9696
W D Bowen2Population Ecology Division, Bedford Institute of Oceanography, Department of Fisheries and Oceans, Dartmouth, Nova Scotia B2Y 4A2 Canada.
S J Iverson1Department of Biology, Dalhousie University, B3H 4J1, Halifax, Nova Scotia Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe distribution of prey in the ocean is spatially and temporally patchy. How predators respond to this prey patchiness may have consequences on their foraging success, and thus physical condition. The recent ability to record fine-scale movements of marine animals combined with novel home-range analyses that incorporate the dimension of time should permit a better understanding of how individuals utilise different regions of space and the consequences on their foraging success.

methodsOver a six-year study, we used T-LoCoH (Time-Local Convex Hull) home-range software to model archival GPS (Global Positioning System) data from 81 grey seals to investigate the fine-scale spatio-temporal use of space and the distribution of apparent foraging effort. Regions of home-ranges were classified according to the frequency of return visits (site fidelity) and duration of visits (intensity of use). Generalized linear mixed -effects models were used to test hypotheses on seasonal changes in foraging distribution and behaviour and the role of space-use and state on determining foraging success.

resultsMale grey seals had larger home-ranges and core areas than females, and both sexes showed a contraction in home-range and core area in fall leading up to the breeding season compared with summer. Heavier individuals had smaller core areas than lighter ones, suggesting access to higher quality habitat might be limited to those individuals with greater foraging experience and competitive ability. The size of the home-range or core area was not an important predictor of the rate of mass gain. A fine-scale spatio-temporal analysis of habitat use within the home-range provided evidence of intra-annual site fidelity at presumed foraging locations, suggesting predictably in prey distribution. Neither sex nor season were useful predictors for classifying behaviour. Rather, individual identity explained much of the variation in fine-scale behaviour.

conclusionsUnderstanding how upper-trophic level marine predators use space provides opportunities to explore the consequences of variation in foraging tactics and their success on fitness. Having knowledge of the drivers that shape this intraspecific variation can contribute toward predicting how these predators may respond to both natural and man-made environmental forcing.

Indexed as

Foraging behaviourForaging ecologyMarine mammalMovementPinnipedT-LoCoH

Identifiers

PMID32082578
PMCPMC7020581

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.