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The Resilient Recurrent Behavior of Mediterranean Semi-Arid Complex Adaptive Landscapes

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  • Irene Petrosillo

    (Landscape Ecology Laboratory, Department of Biological and Environmental Sciences and Technologies, ECOTEKNE, University of Salento, 73100 Lecce, Italy)

  • Donatella Valente

    (Landscape Ecology Laboratory, Department of Biological and Environmental Sciences and Technologies, ECOTEKNE, University of Salento, 73100 Lecce, Italy)

  • Christian Mulder

    (Department of Biological, Geological and Environmental Sciences, University of Catania, 95131 Catania, Italy)

  • Bai-Lian Li

    (Department of Botany and Science & Plant Sciences, University of California, Riverside, CA 92521, USA)

  • K. Bruce Jones

    (Desert Research Institute, Las Vegas, NV 89119, USA)

  • Giovanni Zurlini

    (Landscape Ecology Laboratory, Department of Biological and Environmental Sciences and Technologies, ECOTEKNE, University of Salento, 73100 Lecce, Italy)

Abstract

Growing external pressures from human activities and climate change can exacerbate desertification, compromising the livelihoods of more than 25% of the world’s population. The dryland mosaic is defined by land covers that do not behave similarly, and the identification of their recurring or irregular changes over time is crucial, especially in areas susceptible to become desertified. To this aim, the methodological approach of this research is based on the integration of non-linear data analysis techniques, such as recurrence plots (RPs) and recurrence quantification analysis (RQA), applied to the Enhanced Vegetation Index (EVI), which is a functional ecological proxy of above ground net primary production. The research exploits the recurring change detected in vegetation cover over time to gauge the predictable (resilient) behavior of the EVI as well as its chaoticity in a semi-arid Mediterranean region (Apulia, Italy). Interestingly, the results have shown the spatial rendering of recurrence variables, confirming the well-known hot spots of soil degradation and desertification taking place in the region, which are characterized by greater EVI chaoticity, but they have also identified new potential candidate sites. As a result, the susceptibility to land degradation, as measured by the EVI-RQA approach, can help in measuring land desertification with evident operational benefits for landscape planning. The novelty of the research lies in the spatially explicit identification of resilient and less resilient areas to desertification that can support the definition of more targeted interventions and conservation priorities for better planning and sustainable management of Mediterranean drylands.

Suggested Citation

  • Irene Petrosillo & Donatella Valente & Christian Mulder & Bai-Lian Li & K. Bruce Jones & Giovanni Zurlini, 2021. "The Resilient Recurrent Behavior of Mediterranean Semi-Arid Complex Adaptive Landscapes," Land, MDPI, vol. 10(3), pages 1-18, March.
    • Handle: RePEc:gam:jlands:v:10:y:2021:i:3:p:296-:d:516489
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    References listed on IDEAS

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    1. Christopher Potter & Steven Klooster & Vanessa Genovese, 2012. "Net primary production of terrestrial ecosystems from 2000 to 2009," Climatic Change, Springer, vol. 115(2), pages 365-378, November.
    2. Costanza, Robert & Fisher, Brendan & Mulder, Kenneth & Liu, Shuang & Christopher, Treg, 2007. "Biodiversity and ecosystem services: A multi-scale empirical study of the relationship between species richness and net primary production," Ecological Economics, Elsevier, vol. 61(2-3), pages 478-491, March.
    3. Jorge Belaire-Franch, & Dulce Contreras & Lorena Tordera-Lledo, 2002. "Assessing Non-Linear Structures in Real Exchange Rates Using Recurrence Plot Strategies," Computing in Economics and Finance 2002 239, Society for Computational Economics.
    4. Kevin J. Gaston, 2000. "Global patterns in biodiversity," Nature, Nature, vol. 405(6783), pages 220-227, May.
    5. Benassi, Federico & Cividino, Sirio & Cudlin, Pavel & Alhuseen, Ahmed & Lamonica, Giuseppe Ricciardo & Salvati, Luca, 2020. "Population trends and desertification risk in a Mediterranean region, 1861-2017," Land Use Policy, Elsevier, vol. 95(C).
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    Cited by:

    1. Egidi, Gianluca & Mosconi, Enrico Maria & Turco, Rosario & Salvati, Luca, 2023. "Functions follow structures? The long-term evolution of economic dynamics, social transformations, and landscape morphology in a Mediterranean metropolis," Land Use Policy, Elsevier, vol. 129(C).

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