Successful validation of a larval dispersal model using genetic parentage data

Bode, Michael, Leis, Jeffrey M., Mason, Luciano B., Williamson, David H., Harrison, Hugo B., Choukroun, Severine, and Jones, Geoffrey P. (2019) Successful validation of a larval dispersal model using genetic parentage data. PLoS Biology, 17 (7). e3000380.

[img]
Preview
PDF (Published Version) - Published Version
Available under License Creative Commons Attribution.

Download (1MB) | Preview
View at Publisher Website: https://doi.org/10.1371/journal.pbio.300...
 
51
954


Abstract

Larval dispersal is a critically important yet enigmatic process in marine ecology, evolution, and conservation. Determining the distance and direction that tiny larvae travel in the open ocean continues to be a challenge. Our current understanding of larval dispersal patterns at management-relevant scales is principally and separately informed by genetic parentage data and biological-oceanographic (biophysical) models. Parentage datasets provide clear evidence of individual larval dispersal events, but their findings are spatially and temporally limited. Biophysical models offer a more complete picture of dispersal patterns at regional scales but are of uncertain accuracy. Here, we develop statistical techniques that integrate these two important sources of information on larval dispersal. We then apply these methods to an extensive genetic parentage dataset to successfully validate a high-resolution biophysical model for the economically important reef fish species Plectropomus maculatus in the southern Great Barrier Reef. Our results demonstrate that biophysical models can provide accurate descriptions of larval dispersal at spatial and temporal scales that are relevant to management. They also show that genetic parentage datasets provide enough statistical power to exclude poor biophysical models. Biophysical models that included species-specific larval behaviour provided markedly better fits to the parentage data than assuming passive behaviour, but incorrect behavioural assumptions led to worse predictions than ignoring behaviour altogether. Our approach capitalises on the complementary strengths of genetic parentage datasets and high-resolution biophysical models to produce an accurate picture of larval dispersal patterns at regional scales. The results provide essential empirical support for the use of accurately parameterised biophysical larval dispersal models in marine spatial planning and management.

Item ID: 61779
Item Type: Article (Research - C1)
ISSN: 1545-7885
Copyright Information: © 2019 Bode et al.
Funders: Australian Research Council (ARC), Australian Research Council (ARC), Australian Research Council (ARC), Australian Research Council Centre of Excellence for Coral Reef Studies, Australian Department of Environment and Energy
Projects and Grants: ARC Linkage grant LP100200561, ARC Future Fellowship FT170100274, ARC DECRA DE160101141
Date Deposited: 12 Apr 2020 21:56
FoR Codes: 41 ENVIRONMENTAL SCIENCES > 4102 Ecological applications > 410203 Ecosystem function @ 20%
31 BIOLOGICAL SCIENCES > 3103 Ecology > 310307 Population ecology @ 40%
31 BIOLOGICAL SCIENCES > 3103 Ecology > 310305 Marine and estuarine ecology (incl. marine ichthyology) @ 40%
SEO Codes: 96 ENVIRONMENT > 9608 Flora, Fauna and Biodiversity > 960808 Marine Flora, Fauna and Biodiversity @ 40%
96 ENVIRONMENT > 9605 Ecosystem Assessment and Management > 960507 Ecosystem Assessment and Management of Marine Environments @ 40%
83 ANIMAL PRODUCTION AND ANIMAL PRIMARY PRODUCTS > 8302 Fisheries - Wild Caught > 830204 Wild Caught Fin Fish (excl. Tuna) @ 20%
Downloads: Total: 954
Last 12 Months: 13
More Statistics

Actions (Repository Staff Only)

Item Control Page Item Control Page