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Data from: Combined mechanistic modelling predicts changes in species distribution and increased co-occurrence of a tropical urchin herbivore and a habitat-forming temperate kelp

Citation

Castro, Louise et al. (2021), Data from: Combined mechanistic modelling predicts changes in species distribution and increased co-occurrence of a tropical urchin herbivore and a habitat-forming temperate kelp, Dryad, Dataset, https://doi.org/10.5061/dryad.n5tb2rbsh

Abstract

This dataset aims to identify climate change impacts on spawning and settlement of a tropical herbivore, the sea-urchin, Tripneustes gratilla, along eastern Australia and into the Tasman Sea including Lord Howe Island. The dataset contains the trajectories of particles that represent T. gratilla larvae and their dispersal by ocean currents for each day of both a contemporary (2006-2015) and future ‘business as usual’ RCP 8.5 climate change scenario (2090-2100). T. gratilla larval dispersal under both climate scenarios is simulated using the Connectivity Modelling System (CMS). Particles are advected in CMS by 3D velocity fields produced with a state-of-the-art configuration of the Ocean Forecasting Model version 3 (OFAM3) that simulates the contemporary oceanic environment and projects it under an RCP8.5 climate change scenario. Spawning and settlement of particles within CMS are based on known biological traits of T. gratilla.

Methods

This dataset contains the trajectories of particles that represent the dispersal of Tripneustes gratilla larvae by ocean currents. The trajectories are given by the position (longitude, latitude, and depth) of the larvae over time (every day). The Connectivity Modelling System version 1.0 (CMS) (Paris et al., 2013) was the Lagrangian particle tracking system used to simulate the dispersal of virtual T. gratilla sea urchin larvae. The oceanographic data used to forecast the impact of climate change on the dispersal of T. gratilla came from the Ocean Forecasting Australian Model version 3 (OFAM3, (Oke et al., 2013) configured to downscale and project future climate as detailed in Zhang et al. (2016) and Feng, Zhang, Sloyan, and Chamberlain (2017). The future climate scenario projected by OFAM3 was the Representative Concentration Pathway 8.5 (RCP 8.5), which is a 'business as usual' emissions scenario (van Vurren et al., 2011). T. gratilla larvae were advected both horizontally and vertically in CMS with 3-dimensional velocity fields produced by OFAM3; that is with ocean current vectors defined by north-south, east-west, and up-down components. Additionally, diffusion is implemented following the method described in Cetina-Heredia et al. 2015, 2019. Particle releases in CMS were based on known biological spawning behaviours of adult T. gratilla, and advection was simulated over a time period that corresponds to T. gratilla's pelagic larval duration (PLD). This dataset includes the trajectories of the sea urchin larvae for each year of a contemporary (2006-2015) and future (2090-2100) RCP 8.5 carbon emissions scenario. Trajectories are stored as Matlab files.

Usage Notes

Each yearly Matlab trajectory file contains the following information:

dep - the daily depth recorded for each particle released during its trajectory.

distance - how far the particle has travelled (km) since it's release during its trajectory

exitcode - the CMS exit code allocated to each particle at the end of it's trajectory. Exit codes are explained in the CMS manual. https://github.com/beatrixparis/connectivity-modeling-system/blob/master/User-Guide-v2.pdf

ind_nan - the length of the particle's trajectory

lat - the daily latitude recorded for each particle during its trajectory

location - the number of each particle released

lon - the daily longitude recorded for each particle during its trajectory

p_dt_ref - release date for each particle recorded as a Matlab number

release_date - release date for each particle recorded as a Gregorian number

temp - the daily temperature recorded for each particle during its trajectory

The above variables are either recorded as a one-dimensional array or two-dimensional matrix. The one-dimensional array's length = number of partices released in a year. The two-dimensional matrix includes both the number of particles released in a year and the number of days the particle travelled.

Funding

Australian Research Council, Award: LP 150100064

Australian Research Council, Award: LP16100162

Australian Research Council, Award: DP170100023

Australian Research Council, Award: DP190102030

NSW Environmental Trust