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. Preprints2021, 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
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. Preprints2021, 2021020571
APA Style
De Simone, W., Allegrezza, M., Frattaroli, A.R., Montecchiari, S., Tesei, G., Zuccarello, V., & Michele, D.M. (2021). Integrating Remote Sensing and Ecological Modelling to Assess the Potential Impact of <em>Brachypodium genuense</em> on Grasslands Habitat Conservation. Preprints. https://doi.org/
Chicago/Turabian Style
De Simone, W., Vincenzo Zuccarello and Di Musciano Michele. 2021 "Integrating Remote Sensing and Ecological Modelling to Assess the Potential Impact of <em>Brachypodium genuense</em> on Grasslands Habitat Conservation" Preprints. https://doi.org/
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.
Keywords
Habitat grasslands monitoring; Brachypodium genuense; vegetation dynamics; Campo Imperatore plateau; Sentinel-2; Machine learning; Multispectral classification; Topographic niche models; Natura 2000.
Subject
Environmental and Earth Sciences, Atmospheric Science and Meteorology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
