KRILLPODYM modelled estimates of Antarctic krill circumpolar distribution

Maintenance and Update Frequency: asNeeded Statement: A full description of the model background, framework, and implementation can be found in the following paper: Green, D. B., Titaud, O., Bestley, S., Corney, S. P., Hindell, M. A., Trebilco, R., Conchon, A. and Lehodey, P. in review. KRILLPODYM:...

Full description

Bibliographic Details
Other Authors: AODN Data Manager (distributor), Data Officer (distributor), Green, David (pointOfContact), Green, David (author), IMAS Data Manager (hasAssociationWith), Institute for Marine and Antarctic Studies (IMAS) (resourceProvider), Institute for Marine and Antarctic Studies (IMAS), University of Tasmania (UTAS) (hasAssociationWith)
Format: Dataset
Language:unknown
Published: Australian Ocean Data Network
Subjects:
Online Access:https://doi.org/10.25959/895K-K978
https://researchdata.edu.au/krillpodym-modelled-estimates-circumpolar-distribution/2760279
Description
Summary:Maintenance and Update Frequency: asNeeded Statement: A full description of the model background, framework, and implementation can be found in the following paper: Green, D. B., Titaud, O., Bestley, S., Corney, S. P., Hindell, M. A., Trebilco, R., Conchon, A. and Lehodey, P. in review. KRILLPODYM: a mechanistic, spatially resolved model of Antarctic krill distribution and abundance. - Frontiers in Marine Science Credit This research was supported by the Australian Research Council Special Research Initiative, Australian Centre for Excellence in Antarctic Science (Project Number SR200100008). DG received funding through a Tasmania Graduate Research Scholarship. SB was supported by the Australian Research Council under DECRA award DE180100828. Further funding was provided through the European H2020 International Cooperation project Mesopelagic Southern Ocean Prey and Predators No 692173. Robust prediction of population responses to changing environments requires the integration of factors controlling population dynamics with processes affecting distribution. This is true everywhere but especially in polar pelagic environments. Biological cycles for many polar species are synchronised to extreme seasonality, while their distributions may be influenced by both the prevailing oceanic circulation and sea-ice distribution. Antarctic krill (krill, Euphausia superba) is one such species exhibiting a complex life history that is finely tuned to the extreme seasonality of the Southern Ocean. Dependencies on the timing of optimal seasonal conditions has led to concerns over the effects of future climate on krill’s population status, particularly given the species’ important role within Southern Ocean ecosystems. Under a changing climate, established correlations between environment and species may breakdown. Developing the capacity for predicting krill responses to climate change therefore requires methods that can explicitly consider the interplay between life history, biological conditions, and transport. The ...