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Updated: Jul 5, 2026

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM

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Published on: October 11, 2016

Microphytobenthos spatio-temporal dynamics across an intertidal gradient using Random Forest classification and

S Haro¹, B Jesus², S Oiry²

¹Department of Biology, Faculty of Marine and Environmental Sciences, University of Cadiz, 11510 Puerto Real, Cadiz, Spain.

The Science of the Total Environment

|September 13, 2021

Summary

Microphytobenthos (MPB) biomass peaks in winter in Cadiz Bay, with growth in autumn/winter and loss in spring/summer. High-resolution satellite data accurately maps these intertidal communities.

Keywords:

Benthic microalgae Biomass Intertidal gradient Machine learning Remote sensing Seagrass

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Area of Science:

Marine ecology
Remote sensing
Benthic ecology

Background:

Microphytobenthos (MPB) are crucial primary producers in coastal ecosystems.
Understanding MPB dynamics is vital for ecosystem health but challenging due to environmental variability.

Purpose of the Study:

To investigate the seasonal and interannual dynamics of intertidal MPB biomass, cover, and growth rates.
To assess the utility of Sentinel-2 satellite imagery and Random Forest algorithms for mapping MPB and other benthic communities.

Main Methods:

Utilized Sentinel-2 satellite imagery to calculate NDVI over a four-year period in Cadiz Bay.
Employed a Random Forest machine learning algorithm for high-resolution (10m) classification of benthic communities.
Analyzed MPB biomass, cover, and net growth rates based on NDVI changes.

Main Results:

MPB dominated the intertidal zone, with peak biomass in winter and highest cover in the mid-intertidal zone.
Net MPB growth rates were highest from autumn to winter, while loss rates peaked in spring and summer.
Random Forest classification accurately mapped MPB and other benthic communities at high spatio-temporal resolution.

Conclusions:

High-resolution remote sensing effectively monitors intertidal MPB dynamics.
MPB exhibit distinct seasonal patterns in biomass and growth, influenced by factors like sea level.
Further research is needed to understand the ecological regulation of MPB in temperate intertidal flats.