Data from: Predicting the cover and richness of intertidal macroalgae in remote areas: a case study in the Antarctic Peninsula ...

1. Antarctica is an iconic region for scientific explorations as it is remote and a critical component of the global climate system. Recent climate change causes dramatic retreat of ice in Antarctica with associated impacts to its coastal ecosystem. These anthropogenic impacts have a potential to in...

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Bibliographic Details
Main Authors: Kotta, Jonne, Valdivia, Nelson, Kutser, Tiit, Toming, Kaire, Rätsep, Merli, Orav-Kotta, Helen
Format: Dataset
Language:English
Published: Dryad 2019
Subjects:
Online Access:https://dx.doi.org/10.5061/dryad.33cd137
https://datadryad.org/stash/dataset/doi:10.5061/dryad.33cd137
Description
Summary:1. Antarctica is an iconic region for scientific explorations as it is remote and a critical component of the global climate system. Recent climate change causes dramatic retreat of ice in Antarctica with associated impacts to its coastal ecosystem. These anthropogenic impacts have a potential to increase habitat availability for Antarctic intertidal assemblages. Assessing the extent and ecological consequences of these changes requires us to develop accurate biotic baselines and quantitative predictive tools. 2. In this study, we demonstrated that satellite based remote sensing, when used jointly with in-situ ground-truthing and machine learning algorithms, provides a powerful tool to predict the cover and richness of intertidal macroalgae. 3. The salient finding was that the Sentinel-based remote sensing described a significant proportion of variability in the cover and richness of Antarctic macroalgae. The highest performing models were for macroalgal richness and the cover of brown and green algae as ... : dataSHEET DATA Cover of substrate types and cover (%) and richness of macroalgal taxonomic groups along with values of the bottom of atmosphere reflectance at different spatial resolution (in metres) at an indicative wavelength. SHEET EXTERNAL VALIDATION DATASET Percent coverage of different macroalgal taxonomic group or macroalgal richness estimated by our BRT modelling together with that estimated during a separate field survey. ...