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  Analysis of Olive Grove Destruction by Xylella fastidiosa Bacterium on the Land Surface Temperature in Salento Detected Using Satellite Images

Semeraro, T., Buccolieri, R., Vergine, M., De Bellis, L., Luvisi, A., Emmanuel, R., Marwan, N. (2021): Analysis of Olive Grove Destruction by Xylella fastidiosa Bacterium on the Land Surface Temperature in Salento Detected Using Satellite Images. - Forests, 12, 9, 1266.
https://doi.org/10.3390/f12091266

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 Creators:
Semeraro, Teodoro1, Author
Buccolieri, Riccardo1, Author
Vergine, Marzia1, Author
De Bellis, Luigi1, Author
Luvisi, Andrea1, Author
Emmanuel, Rohinton1, Author
Marwan, Norbert2, Author              
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, Potsdam, ou_persistent13              

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Free keywords: social‐ecological  system;  agricultural;  Xylella  fastidiosa;  panarchy;  ecosystem  services;  land surfaces temperature; microclimate regulation; recurrence analysis; landscape regeneration
 Abstract: Agricultural activity replaces natural vegetation with cultivated land and it is a major cause of local and global climate change. Highly specialized agricultural production leads to exten‐sive monoculture farming with a low biodiversity that may cause low landscape resilience. This is the case on the Salento peninsula, in the Apulia Region of Italy, where the Xylella fastidiosa bacterium has caused the mass destruction of olive trees, many of them in monumental groves. The historical land cover that characterized the landscape is currently in a transition phase and can strongly affect climate conditions. This study aims to analyze how the destruction of olive groves by X. fastidiosa affects local climate change. Land surface temperature (LST) data detected by Landsat 8 and MODIS satellites are used as a proxies for microclimate mitigation ecosystem services linked to the evolu‐tion of the land cover. Moreover, recurrence quantification analysis was applied to the study of LST evolution. The results showed that olive groves are the least capable forest type for mitigating LST, but they are more capable than farmland, above all in the summer when the air temperature is the highest. The differences in the average LST from 2014 to 2020 between olive groves and farmland ranges from 2.8 °C to 0.8 °C. Furthermore, the recurrence analysis showed that X. fastidiosa was rapidly changing the LST of the olive groves into values to those of farmland, with a difference in LST reduced to less than a third from the time when the bacterium was identified in Apulia six years ago. The change generated by X. fastidiosa started in 2009 and showed more or less constant behavior after 2010 without substantial variation; therefore, this can serve as the index of a static situation, which can indicate non‐recovery or non‐transformation of the dying olive groves. Failure to restore the initial environmental conditions can be connected with the slow progress of the up‐rooting and replacing infected plants, probably due to attempts to save the historic aspect of the landscape by looking for solutions that avoid uprooting the diseased plants. This suggests that so‐cial‐ecological systems have to be more responsive to phytosanitary epidemics and adapt to ecolog‐ical processes, which cannot always be easily controlled, to produce more resilient landscapes and avoid unwanted transformations.

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 Dates: 2021-09-012021-09-162021-09-16
 Publication Status: Finally published
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.3390/f12091266
PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: RD4 - Complexity Science
Research topic keyword: Climate impacts
Research topic keyword: Ecosystems
Research topic keyword: Forest
Research topic keyword: Land use
Regional keyword: Europe
Model / method: Nonlinear Data Analysis
Model / method: Quantitative Methods
MDB-ID: No data to archive
OATYPE: Gold Open Access
 Degree: -

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Title: Forests
Source Genre: Journal, SCI, Scopus, p3, oa
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Pages: - Volume / Issue: 12 (9) Sequence Number: 1266 Start / End Page: - Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/161012
Publisher: MDPI