Pedro J. Leitão

Supplementary Information: High spatial resolution mapping identifies habitat characteristics of the invasive vine Antigonon leptopus on St. Eustatius (Lesser Antilles)

Supplementary information for Coralita mapping (Report) publication (BioNews Article).  

Supplementary Text In the Material and Methods section of the main text, we provide an overview of the classification procedure using a Support Vector Machine (SVM). In this Supplementary text, we provide further details regarding the following components of the procedure: i) the radiometric and atmospheric correction of the WorldView-2 image (part of Step 0 in the main text); ii) the selection of the 10 independent, most-explaining variables to be considered within the SVM classification (part of Step 2 in the main text); iii) Cross-validation to evaluate SVM model performance iv) the post-processing steps that were performed after obtaining a Coralita distribution map from the SVM procedure (also part of Step 2 in the main text).

 

Related Resources:

1. Topographic Wetness Index raster layer for Statia developed for use in the Coralita mapping publication (https://www.dcbd.nl/document/topographic-wetness-index-raster-layer-statia). 

2. Raster layers: High spatial resolution mapping identifies habitat characteristics of the invasive vine Antigonon leptopus on St. Eustatius (Lesser Antilles) (Raster Layers).

Date
2021
Data type
Research report
Theme
Research and monitoring
Geographic location
St. Eustatius

High spatial resolution mapping identifies habitat characteristics of the invasive vine Antigonon leptopus on St. Eustatius (Lesser Antilles)

On the Caribbean island of St. Eustatius, Coralita (Antigonon leptopus) is an aggressive invasive vine posing major biodiversity conservation concerns. The generation of distribution maps can address these conservation concerns by helping to elucidate the drivers of invasion. We test the use of support vector machines to map the distribution of Coralita on St. Eustatius at high spatial resolution and use this map to identify potential landscape and geomorphological factors associated with Coralita presence. This latter step was performed by comparing the actual distribution of Coralita patches to a random distribution of patches. To train the support vector machine algorithm, we used three vegetation indices and seven texture metrics derived from a 2014 WorldView-2 image. The resulting map shows that Coralita covered 3.18% of the island in 2014, corresponding to an area of 64 ha. The mapped distribution was highly accurate, with 93.2% overall accuracy (Coralita class producer's accuracy: 76.4%, user's accuracy: 86.2%). Using this classification map, we found that Coralita is not randomly distributed across the landscape, occurring significantly closer to roads and drainage channels, in areas with higher accumulated moisture, and on flatter slopes. Coralita was found more often than expected in grasslands, disturbed forest, and urban areas but was relatively rare in natural forest. These results highlight the ability of high spatial resolution data from sensors such as WorldView-2 to produce accurate invasive species, providing valuable information for predicting current and future spread risks and for early detection and removal plans.

 

Referenced in BioNews publication (BioNews Article). 

 

Related Resources:

1. Supplementary Infromation (Report)

2. Topographic Wetness Index raster layer for Statia developed for use in the Coralita mapping publication (Raster Layers). 

3. Raster layers: High spatial resolution mapping identifies habitat characteristics of the invasive vine Antigonon leptopus on St. Eustatius (Lesser Antilles) (Raster Layers).

Date
2021
Data type
Scientific article
Theme
Research and monitoring
Journal
Geographic location
St. Eustatius