Literature DB >> 30804188

Memory and resource tracking drive blue whale migrations.

Briana Abrahms1, Elliott L Hazen2,3, Ellen O Aikens4,5, Matthew S Savoca6, Jeremy A Goldbogen6, Steven J Bograd2, Michael G Jacox2,7, Ladd M Irvine8,9, Daniel M Palacios8,9, Bruce R Mate8,9.   

Abstract

In terrestrial systems, the green wave hypothesis posits that migrating animals can enhance foraging opportunities by tracking phenological variation in high-quality forage across space (i.e., "resource waves"). To track resource waves, animals may rely on proximate cues and/or memory of long-term average phenologies. Although there is growing evidence of resource tracking in terrestrial migrants, such drivers remain unevaluated in migratory marine megafauna. Here we present a test of the green wave hypothesis in a marine system. We compare 10 years of blue whale movement data with the timing of the spring phytoplankton bloom resulting in increased prey availability in the California Current Ecosystem, allowing us to investigate resource tracking both contemporaneously (response to proximate cues) and based on climatological conditions (memory) during migrations. Blue whales closely tracked the long-term average phenology of the spring bloom, but did not track contemporaneous green-up. In addition, blue whale foraging locations were characterized by low long-term habitat variability and high long-term productivity compared with contemporaneous measurements. Results indicate that memory of long-term average conditions may have a previously underappreciated role in driving migratory movements of long-lived species in marine systems, and suggest that these animals may struggle to respond to rapid deviations from historical mean environmental conditions. Results further highlight that an ecological theory of migration is conserved across marine and terrestrial systems. Understanding the drivers of animal migration is critical for assessing how environmental changes will affect highly mobile fauna at a global scale.

Entities:  

Keywords:  marine megafauna; migration; movement ecology; resource wave; spatial memory

Mesh:

Year:  2019        PMID: 30804188      PMCID: PMC6431148          DOI: 10.1073/pnas.1819031116

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  24 in total

1.  Migrating whales depend on memory to exploit reliable resources.

Authors:  William F Fagan
Journal:  Proc Natl Acad Sci U S A       Date:  2019-02-25       Impact factor: 11.205

2.  Prey encounters and spatial memory influence use of foraging patches in a marine central place forager.

Authors:  Virginia Iorio-Merlo; Isla M Graham; Rebecca C Hewitt; Geert Aarts; Enrico Pirotta; Gordon D Hastie; Paul M Thompson
Journal:  Proc Biol Sci       Date:  2022-03-02       Impact factor: 5.349

3.  Baleen whale prey consumption based on high-resolution foraging measurements.

Authors:  Matthew S Savoca; Max F Czapanskiy; Shirel R Kahane-Rapport; William T Gough; James A Fahlbusch; K C Bierlich; Paolo S Segre; Jacopo Di Clemente; Gwenith S Penry; David N Wiley; John Calambokidis; Douglas P Nowacek; David W Johnston; Nicholas D Pyenson; Ari S Friedlaender; Elliott L Hazen; Jeremy A Goldbogen
Journal:  Nature       Date:  2021-11-03       Impact factor: 49.962

4.  Evolutionary causes and consequences of ungulate migration.

Authors:  Joel O Abraham; Nathan S Upham; Alejandro Damian-Serrano; Brett R Jesmer
Journal:  Nat Ecol Evol       Date:  2022-05-05       Impact factor: 19.100

5.  Environmental variability, reliability of information and the timing of migration.

Authors:  Silke Bauer; John M McNamara; Zoltan Barta
Journal:  Proc Biol Sci       Date:  2020-05-06       Impact factor: 5.349

6.  Rorqual Lunge-Feeding Energetics Near and Away from the Kinematic Threshold of Optimal Efficiency.

Authors:  J Potvin; D E Cade; A J Werth; R E Shadwick; J A Goldbogen
Journal:  Integr Org Biol       Date:  2021-03-16

Review 7.  Using natural travel paths to infer and compare primate cognition in the wild.

Authors:  Karline R L Janmaat; Miguel de Guinea; Julien Collet; Richard W Byrne; Benjamin Robira; Emiel van Loon; Haneul Jang; Dora Biro; Gabriel Ramos-Fernández; Cody Ross; Andrea Presotto; Matthias Allritz; Shauhin Alavi; Sarie Van Belle
Journal:  iScience       Date:  2021-04-15

8.  Animal tag technology keeps coming of age: an engineering perspective.

Authors:  Mark D Holton; Rory P Wilson; Jonas Teilmann; Ursula Siebert
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2021-06-28       Impact factor: 6.671

9.  E-scape: Consumer-specific landscapes of energetic resources derived from stable isotope analysis and remote sensing.

Authors:  W Ryan James; Rolando O Santos; Jennifer S Rehage; Jennifer C Doerr; James A Nelson
Journal:  J Anim Ecol       Date:  2021-11-24       Impact factor: 5.606

10.  Both real-time and long-term environmental data perform well in predicting shorebird distributions in managed habitat.

Authors:  Erin E Conlisk; Gregory H Golet; Mark D Reynolds; Blake A Barbaree; Kristin A Sesser; Kristin B Byrd; Sam Veloz; Matthew E Reiter
Journal:  Ecol Appl       Date:  2022-04-24       Impact factor: 6.105

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