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Spatiotemporal Assessment of Habitat Quality in Sicily, Italy

Author

Listed:
  • Laura Giuffrida

    (Department of Agriculture, Food and Environment, University of Catania, 95123 Catania, Italy)

  • Marika Cerro

    (Department of Agriculture, Food and Environment, University of Catania, 95123 Catania, Italy)

  • Giuseppe Cucuzza

    (Department of Agriculture, Food and Environment, University of Catania, 95123 Catania, Italy)

  • Giovanni Signorello

    (Department of Agriculture, Food and Environment, University of Catania, 95123 Catania, Italy)

  • Maria De Salvo

    (Department of Veterinary Sciences, University of Messina, 98122 Messina, Italy)

Abstract

We measured the spatiotemporal dynamics of habitat quality (HQ) in Sicily in two different reference years, 2018 and 2050, assuming a business-as-usual scenario. To estimate HQ and related vulnerability, we used the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) Habitat Quality model and data on land use/land cover provided by the Esri Land Cover 2050 project. We also implemented a Coarse–Filter approach to validate the reliability of HQ measures and detect biodiversity hotspots that require priority conservation. Further, we used spatial statistic tools for identifying clusters or hotspot/coldspot areas and uncovering spatial autocorrelation in HQ values. Finally, we implemented a geographically weighted regression (GWR) model for explaining local variations in the effects on HQ estimates. The findings reveal that HQ in Sicily varies across space and time. The highest HQ values occur in protected areas and forests. In 2018, the average HQ value was higher than it was in 2050. On average, HQ decreased from 0.29 in 2018 to 0.25 in 2050. This slight decline was mainly due to an increase in crop and urbanized areas at the expense of forests, grasslands, and bare lands. We found the existence of a positive spatial autocorrelation in HQ, demonstrating that areas with higher or lower HQ tend to be clustered, and that clusters come into contact randomly more often in 2050 than in 2018, as the overall spatial autocorrelation moved from 0.28 in 2018 to 1.30 in 2050. The estimated GWR model revealed the sign and the significance effect of population density, compass exposure, average temperature, and patch richness on HQ at a local level, and that such effects vary either in space and time or in significance level. Across all variables, the spatial extent of significant effects intensifies, signaling stronger localized influences in 2050. The overall findings of the study provide useful insights for making informed decisions about conservation and land planning and management in Sicily.

Suggested Citation

  • Laura Giuffrida & Marika Cerro & Giuseppe Cucuzza & Giovanni Signorello & Maria De Salvo, 2025. "Spatiotemporal Assessment of Habitat Quality in Sicily, Italy," Land, MDPI, vol. 14(2), pages 1-28, January.
    • Handle: RePEc:gam:jlands:v:14:y:2025:i:2:p:243-:d:1576258
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    References listed on IDEAS

    as
    1. Li Zhao & Mengwei Su & Xueyan Wang & Xiaoqing Li & Xinhan Chang & Pengtao Zhang, 2023. "Spatial–Temporal Evolution and Prediction of Habitat Quality in Beijing–Tianjin–Hebei Region Based on Land Use Change," Land, MDPI, vol. 12(3), pages 1-16, March.
    2. Hamza K. Kija & Joseph O. Ogutu & Lazaro J. Mangewa & John Bukombe & Francesca Verones & Bente J. Graae & Jafari R. Kideghesho & Mohammed Y. Said & Emmanuel F. Nzunda, 2020. "Spatio-Temporal Changes in Wildlife Habitat Quality in the Greater Serengeti Ecosystem," Sustainability, MDPI, vol. 12(6), pages 1-19, March.
    Full references (including those not matched with items on IDEAS)

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