1 dataset found
  1. r

    Data from: High-frequency sampling and piecewise models reshape dispersal...

    • researchdata.edu.au
    Updated Aug 22, 2024
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    Connolly Sean; Baird Andrew; Figueiredo Joana; Moneghetti Joanne; Sean Connolly; Andrew Baird (2024). Data from: High-frequency sampling and piecewise models reshape dispersal kernels of a common reef coral [Dataset]. https://researchdata.edu.au/data-from-high-reef-coral/3381477
    Explore at:
    Dataset updated
    Aug 22, 2024
    Dataset provided by
    James Cook University
    Authors
    Connolly Sean; Baird Andrew; Figueiredo Joana; Moneghetti Joanne; Sean Connolly; Andrew Baird
    Description

    Abstract [Related Publication]:

    Models of dispersal potential are required to predict connectivity between populations of sessile organisms. However, to date, such models do not allow for time‐varying rates of acquisition and loss of competence to settle and metamorphose, and permit only a limited range of possible survivorship curves. We collect high‐resolution observations of coral larval survival and metamorphosis, and apply a piecewise modeling approach that incorporates a broad range of temporally‐varying rates of mortality and loss of competence. Our analysis identified marked changes in competence loss and mortality rates, whose timing implicates developmental failure and depletion of energy reserves. Asymmetric demographic rates suggest more intermediate‐range dispersal, less local retention, and less long‐distance dispersal than predicted by previously‐employed non‐piecewise models. Because vital rates are likely temporally asymmetric, at least for non‐feeding broadcast‐spawned larvae, piecewise analysis of demographic rates will likely yield more reliable predictions of dispersal potential.

    Usage Notes [Dryad]:

    TenuisGBR2012longtermsurvival.csv
    Empirical long term survival data for A. Tenuis larvae. "temp" is the temperature that the larvae were raised at, "rep" is the replicate number, "day" is the date the observation was taken, "age (h)" is the larval age (h) at the time of the observation, "age (d)" is the larval age (d) at the time of the observation, "larvae" is the number of larvae at the beginning of the experiment, "surv" is the number of larvae alive at the time of the observation.

    A.tenuisGBR2012metamorphosis.csv
    Empirical metamorphosis data for A. Tenuis larvae. "temp" is the temperature that the larvae were raised at, "date" is the date the observation was taken, "hour" is the hour of the day that the observation was taken, "age (h)" is the larval age (h) at the time of the observation, "age (d)" is the larval age (d) at the time of the observation, "rep" is the replicate number, "larvae" is the number of larvae at the beginning of the experiment, "meta" is the number of larvae that had metamorphosed by the time of the observation, "swimming" is the number of larvae swimming at the time of the observation.

    Survival model fit R code
    This code fits the best-fitting survival model to the data.
    (survival model code.R)

    Competence model fit R code
    This code fits the best-fitting competence model to the data.
    (competence model code.R)

    The dataset also includes 2 README files (MS Word format) for the R codes.

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Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Connolly Sean; Baird Andrew; Figueiredo Joana; Moneghetti Joanne; Sean Connolly; Andrew Baird (2024). Data from: High-frequency sampling and piecewise models reshape dispersal kernels of a common reef coral [Dataset]. https://researchdata.edu.au/data-from-high-reef-coral/3381477

Data from: High-frequency sampling and piecewise models reshape dispersal kernels of a common reef coral

Related Article
Explore at:
Dataset updated
Aug 22, 2024
Dataset provided by
James Cook University
Authors
Connolly Sean; Baird Andrew; Figueiredo Joana; Moneghetti Joanne; Sean Connolly; Andrew Baird
Description

Abstract [Related Publication]:

Models of dispersal potential are required to predict connectivity between populations of sessile organisms. However, to date, such models do not allow for time‐varying rates of acquisition and loss of competence to settle and metamorphose, and permit only a limited range of possible survivorship curves. We collect high‐resolution observations of coral larval survival and metamorphosis, and apply a piecewise modeling approach that incorporates a broad range of temporally‐varying rates of mortality and loss of competence. Our analysis identified marked changes in competence loss and mortality rates, whose timing implicates developmental failure and depletion of energy reserves. Asymmetric demographic rates suggest more intermediate‐range dispersal, less local retention, and less long‐distance dispersal than predicted by previously‐employed non‐piecewise models. Because vital rates are likely temporally asymmetric, at least for non‐feeding broadcast‐spawned larvae, piecewise analysis of demographic rates will likely yield more reliable predictions of dispersal potential.

Usage Notes [Dryad]:

TenuisGBR2012longtermsurvival.csv
Empirical long term survival data for A. Tenuis larvae. "temp" is the temperature that the larvae were raised at, "rep" is the replicate number, "day" is the date the observation was taken, "age (h)" is the larval age (h) at the time of the observation, "age (d)" is the larval age (d) at the time of the observation, "larvae" is the number of larvae at the beginning of the experiment, "surv" is the number of larvae alive at the time of the observation.

A.tenuisGBR2012metamorphosis.csv
Empirical metamorphosis data for A. Tenuis larvae. "temp" is the temperature that the larvae were raised at, "date" is the date the observation was taken, "hour" is the hour of the day that the observation was taken, "age (h)" is the larval age (h) at the time of the observation, "age (d)" is the larval age (d) at the time of the observation, "rep" is the replicate number, "larvae" is the number of larvae at the beginning of the experiment, "meta" is the number of larvae that had metamorphosed by the time of the observation, "swimming" is the number of larvae swimming at the time of the observation.

Survival model fit R code
This code fits the best-fitting survival model to the data.
(survival model code.R)

Competence model fit R code
This code fits the best-fitting competence model to the data.
(competence model code.R)

The dataset also includes 2 README files (MS Word format) for the R codes.

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