Working Paper Article Version 1 This version is not peer-reviewed

Integrating Remote Sensing and Ecological Modelling to Assess the Potential Impact of Brachypodium genuense on Grasslands Habitat Conservation

Version 1 : Received: 23 February 2021 / Approved: 25 February 2021 / Online: 25 February 2021 (10:06:59 CET)

How to cite: De Simone, W.; Allegrezza, M.; Frattaroli, A.R.; Montecchiari, S.; Tesei, G.; Zuccarello, V.; Michele, D.M. Integrating Remote Sensing and Ecological Modelling to Assess the Potential Impact of Brachypodium genuense on Grasslands Habitat Conservation. Preprints 2021, 2021020571 De Simone, W.; Allegrezza, M.; Frattaroli, A.R.; Montecchiari, S.; Tesei, G.; Zuccarello, V.; Michele, D.M. Integrating Remote Sensing and Ecological Modelling to Assess the Potential Impact of Brachypodium genuense on Grasslands Habitat Conservation. Preprints 2021, 2021020571

Abstract

Remote sensing (RS) has been widely adopted as a tool to investigate several biotic and abiotic factors, directly and indirectly, related to biodiversity conservation. European grasslands are one of the most biodiverse habitats in Europe. Most of these habitats are subject to priority conservation measure, and they are threatened by several human induced process. The broad expansions of few dominant species are widely reported as drivers of biodiversity loss. In this context, using Sentinel-2 (S2) images, we investigate the distribution of one of the most spreading species: <i>Brachypodium genuense</i>. We performed a binary Random Forest (RF) classification of <i>B. genuense</i> using a RS image and field sampled presence/absence points. Then, we integrate the occurrences obtained from RS classification into niche models to identify the topographic drivers of <i>B. genuense</i> distribution. Lastly, the impact of <i>B. genuense</i> distribution in the N2k habitats was assessed by overlay analysis. The RF classification process detected <i>B. genuense</i>'s cover with an overall accuracy of 91.18%. The integration of RS and topographic niche models shows that the most relevant topographic variables that influence the distribution of <i>B. genuense</i> are slope, elevation, solar radiation and Topographic Wet Index (TWI) in order of importance. The overlay analysis shows that 74.04% of the <i>B. genuense</i> identified in the study area falls on the semi-natural dry grasslands. The study highlights the importance of the RS classification and the topographic niche models as an integrated approach for mapping a broad-expansion species such as <i>B. genuense</i>. The coupled techniques presented in this work should be applicable to other plant communities with remotely recognizable characteristics for more effective management of N2k habitats.

Subject Areas

Habitat grasslands monitoring; Brachypodium genuense; vegetation dynamics; Campo Imperatore plateau; Sentinel-2; Machine learning; Multispectral classification; Topographic niche models; Natura 2000.

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our diversity statement.

Leave a public comment
Send a private comment to the author(s)
Views 0
Downloads 0
Comments 0
Metrics 0


×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.
We use cookies on our website to ensure you get the best experience.
Read more about our cookies here.