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The biophysical dynamics of giant kelp, Macrocystis pyrifera: seasonal patterns and dispersal mechanisms in the southeast Pacific

Background: Dispersal and connectivity play important roles in shaping the population structure of giant kelp, Macrocystis pyrifera, across the east coast of South America. Its high potential dispersal capacity suggests the existence of metapopulations, where discrete habitat patches or groups of patches form subpopulations that interact at some level. However, the dispersal patterns of giant kelp along the east coast of South America has not been quantified. 

Objective: This study assesses the dispersal and settlement of Macrocystis pyrifera in the Southeast Pacific, specifically focusing on the impact of environmental variables and ocean currents within the Humboldt Current System. 

Methods: Using a combination of hydrodynamic and individual-based models, we analysed kelp fragment movements over 12 years, with a particular emphasis on the effects of the El Niño-Southern Oscillation (ENSO) and seasonal changes. 

Results: Our results highlight a key settlement area in the southern Chilean region, indicating a vital source-sink dynamic for these kelp populations. We found that shorter travel distances of kelp fragments increased settlement success, underscoring the importance of local environmental conditions. ENSO events, especially La Niña, significantly influenced dispersal distances. Seasonal variations, notably in autumn and winter, were observed to favour settlement due to stronger winds. Our study revealed complex northward trajectories of kelp fragments, driven by wind and current patterns. These findings are essential for informing kelp conservation strategies in the context of climate change, emphasizing the necessity of considering local and seasonal environmental factors alongside ENSO impacts.

Data sources acknowledgment: Mora-Soto, A., Palacios, M., Macaya, E. C., Gómez, I., Huovinen, P., Pérez-Matus, A., ... & Macias-Fauria, M. (2020). A high-resolution global map of giant kelp (Macrocystis pyrifera) forests and intertidal green algae (Ulvophyceae) with Sentinel-2 imagery. Remote Sensing, 12(4), 694. https://doi.org/10.3390/rs12040694 

This dataset consist of:

  • One CSV file that contains the coordinates and density of kelp
  • Two files with the output of the biophysical model after being processed (they contain the same information but in different formats)
  • One R file with the code to process the data and run the statistical analysis 
  • README.txt file containing descriptors for the R files.

Software/equipment used to create/collect the data:

  • Google Earth Engine to obtain kelp distribution

Software/equipment used to manipulate/analyse the data:

  • ArcGIS to create the kelp density map
  • Ichthyop to run the biophysical model
  • R to process the Ichthyop output and to run the statistical models
- Start
    Data Record Details
    Data record related to this publication The biophysical dynamics of giant kelp, Macrocystis pyrifera: seasonal patterns and dispersal mechanisms in the southeast Pacific
    Data Publication title The biophysical dynamics of giant kelp, Macrocystis pyrifera: seasonal patterns and dispersal mechanisms in the southeast Pacific
  • Description

    Background: Dispersal and connectivity play important roles in shaping the population structure of giant kelp, Macrocystis pyrifera, across the east coast of South America. Its high potential dispersal capacity suggests the existence of metapopulations, where discrete habitat patches or groups of patches form subpopulations that interact at some level. However, the dispersal patterns of giant kelp along the east coast of South America has not been quantified. 

    Objective: This study assesses the dispersal and settlement of Macrocystis pyrifera in the Southeast Pacific, specifically focusing on the impact of environmental variables and ocean currents within the Humboldt Current System. 

    Methods: Using a combination of hydrodynamic and individual-based models, we analysed kelp fragment movements over 12 years, with a particular emphasis on the effects of the El Niño-Southern Oscillation (ENSO) and seasonal changes. 

    Results: Our results highlight a key settlement area in the southern Chilean region, indicating a vital source-sink dynamic for these kelp populations. We found that shorter travel distances of kelp fragments increased settlement success, underscoring the importance of local environmental conditions. ENSO events, especially La Niña, significantly influenced dispersal distances. Seasonal variations, notably in autumn and winter, were observed to favour settlement due to stronger winds. Our study revealed complex northward trajectories of kelp fragments, driven by wind and current patterns. These findings are essential for informing kelp conservation strategies in the context of climate change, emphasizing the necessity of considering local and seasonal environmental factors alongside ENSO impacts.

    Data sources acknowledgment: Mora-Soto, A., Palacios, M., Macaya, E. C., Gómez, I., Huovinen, P., Pérez-Matus, A., ... & Macias-Fauria, M. (2020). A high-resolution global map of giant kelp (Macrocystis pyrifera) forests and intertidal green algae (Ulvophyceae) with Sentinel-2 imagery. Remote Sensing, 12(4), 694. https://doi.org/10.3390/rs12040694 

    This dataset consist of:

    • One CSV file that contains the coordinates and density of kelp
    • Two files with the output of the biophysical model after being processed (they contain the same information but in different formats)
    • One R file with the code to process the data and run the statistical analysis 
    • README.txt file containing descriptors for the R files.

    Software/equipment used to create/collect the data:

    • Google Earth Engine to obtain kelp distribution

    Software/equipment used to manipulate/analyse the data:

    • ArcGIS to create the kelp density map
    • Ichthyop to run the biophysical model
    • R to process the Ichthyop output and to run the statistical models
    •
  • Other Descriptors
    • Descriptor
      • Descriptor type
    • Data type dataset
  • Keywords
    • Macrocystis pyrifera
    • Humboldt Current System
    • Biophysical Modelling
    • Individual-Based Modelling
    • Kelp
    • El Niño-Southern Oscillation (ENSO)
    • Dispersal
  • Funding source
    • The Australian Research Council Centre of Excellence for Coral Reef Studies
  • Research grant(s)/Scheme name(s)
    • -
    • -
    • Research themes
    Tropical Ecosystems, Conservation and Climate Change
    FoR Codes (*)
    • 370803 - Physical oceanography
    • 410401 - Conservation and biodiversity
    • 410404 - Environmental management
    SEO Codes
- Specify coverage
    Specify spatial or temporal setting of the data
    Temporal (time) coverage
  • Start Date 1997/01/01
  • End Date 2008/12/31
    • Time Period
    Spatial (location) coverage
  • Locations
    • Chile
    • Peru
- Data
    Data Locations

    Type Location Notes
    Attachment Data_BiophysicalDynamicsGiantKelp.zip
    The Data Manager is: Alana Grech
    College or Centre College of Science & Engineering
    Access conditions Open: free access under license
  • Alternative access conditions
    • Data record size .zip file 216MB
- Related resources
  • Related publications
      Name The biophysical dynamics of giant kelp, Macrocystis pyrifera: Seasonal patterns and dispersal mechanisms in the southeast Pacific
    • URL https://doi.org/10.1111/jbi.14980
    • Notes
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  • Related metadata (including standards, codebooks, vocabularies, thesauri, ontologies)
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    • Notes
  • Related data
      Name A High-Resolution Global Map of Giant Kelp (Macrocystis pyrifera) Forests and Intertidal Green Algae (Ulvophyceae) with Sentinel-2 Imagery
    • URL https://doi.org/10.3390/rs12040694
    • Notes The kelp map distribution was obtained from this paper
  • Related services
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    • Notes
- License
- Citation
    Citation Thompson Saud, Gabriela; Grech, Alana (2024): The biophysical dynamics of giant kelp, Macrocystis pyrifera: seasonal patterns and dispersal mechanisms in the southeast Pacific . James Cook University. https://doi.org/10.25903/e8x4-ag45