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EARTH SCIENCE | BIOSPHERE | ECOLOGICAL DYNAMICS

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  • This record contains the R code and bibliographic data used in the publication 'Reciprocal knowledge exchange between climate-driven species redistribution and invasion ecology' (doi:10.21425/F5FBG60804). The aim of this study was to examine the current degree of cross-fertilisation between range shift ecology and invasion ecology, as a first step in determining the level of need for increasing connection between the two fields. To that end, here we examine (1) the structure and degree of similarity of themes explored within range shift and invasion ecology publications, (2) the extent that range shift and invasion publications draw on a common pool of research, and (3) the extent that range shift and invasion publications directly cite publications from the other field of study. This dataset includes: 1) R code used in the litsearchr package to generate a semi-automated search string, 2) publication data used for bibliographic analysis, and 3) R code used with the bibliometrix package for keyword co-occurrence analysis.

  • Snapper and King George whiting occurrence records were aggregated from the Reef Life Survey dataset, IMAS Archives, the Tassie Fish Frame Collection Program, Atlas of Living Australia and Redmap, in addition to pseudoabsences generated through space and time within the study extent, and matched to environmental covariates (sourced from Copernicus Marine) used for species distribution modelling for FRDC project 2018-070

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    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 Spatial Ecosystem And Population Dynamics Model (SEAPODYM) is one such framework that integrates population and general circulation modelling to simulate the spatial dynamics of key organisms. Here, we describe a modification to SEAPODYM, creating a novel model – KRILLPODYM – that generates spatially resolved estimates of krill biomass and demographics. This new model consists of three major components: (1) an age-structured population consisting of five key life stages, each with multiple age classes, which undergo age-dependent growth and mortality, (2) six key habitats that mediate the production of larvae and life stage survival, and (3) spatial dynamics driven by both the underlying circulation of ocean currents and advection of sea-ice. Here we present the first results of KRILLPODYM, using published deterministic functions of population processes and habitat suitability rules. Initialising from a non-informative uniform density across the Southern Ocean our model independently develops a circumpolar population distribution of krill that approximates observations. The model framework lends itself to applied experiments aimed at resolving key population parameters, life-stage specific habitat requirements, and dominant transport regimes, ultimately informing sustainable fishery management. ____ This dataset represents KRILLPODYM modelled estimates of Antarctic krill circumpolar biomass distribution for the final year of a 12-year spin up. Biomass distributions are given for each of the five key life stages outlined above. The accompanying background, model framework and initialisation description can be found in the following reference 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