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Bioclimate map of Sardinia (Italy)

Author

Listed:
  • Simona Canu
  • Leonardo Rosati
  • Michele Fiori
  • Andrea Motroni
  • Rossella Filigheddu
  • Emmanuele Farris

Abstract

Bioclimatology deals with the interrelation between climate and living organisms, in particular, plants and plant communities, considering the main climate variables that are relevant for species distribution. In this context spatial interpolation of monthly temperature and precipitation data using 203 rain gauges and 68 temperature gauges for Sardinia (Italy) was undertaken. As interpolation technique, we used regression kriging which combines multiple linear regression (MLR) with ordinary kriging of the residuals. MLR procedures include as independent variables: altitude, latitude, longitude, coast distance and a topographic factor of relative elevation. Elevation data were obtained from digital elevation model at 40 m resolution. Following the approach of the Worldwide Bioclimatic Classification System, a bioclimatic diagnosis of the entire territory was derived using map algebra calculations of the bioclimatic indices proposed by Rivas-Martínez et al. [(2011). Worldwide Bioclimatic classification system. Global Geobotany , 1 , 1-638]. Two macrobioclimates (Mediterranean pluviseasonal oceanic and Temperate oceanic), one macrobioclimatic variant (Submediterranean), and four classes of continentality (from weak semihyperoceanic to weak semicontinental), eight thermotypic horizons (from lower thermomediterranean to upper supratemperate) and seven ombrotypic horizons (from lower dry to lower hyperhumid) were identified, resulting in a combination of 43 isobioclimates. The resulting map represents a useful environmental stratum, for regional planning, ecological modeling and biodiversity conservation.

Suggested Citation

  • Simona Canu & Leonardo Rosati & Michele Fiori & Andrea Motroni & Rossella Filigheddu & Emmanuele Farris, 2015. "Bioclimate map of Sardinia (Italy)," Journal of Maps, Taylor & Francis Journals, vol. 11(5), pages 711-718, October.
  • Handle: RePEc:taf:tjomxx:v:11:y:2015:i:5:p:711-718
    DOI: 10.1080/17445647.2014.988187
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    References listed on IDEAS

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    1. D. Smiraglia & G. Capotorti & D. Guida & B. Mollo & V. Siervo & C. Blasi, 2013. "Land units map of Italy," Journal of Maps, Taylor & Francis Journals, vol. 9(2), pages 239-244, June.
    2. Bajocco, S. & Rosati, L. & Ricotta, C., 2010. "Knowing fire incidence through fuel phenology: A remotely sensed approach," Ecological Modelling, Elsevier, vol. 221(1), pages 59-66.
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    Cited by:

    1. Federica Isola & Sabrina Lai & Federica Leone & Corrado Zoppi, 2023. "Land Take and Landslide Hazard: Spatial Assessment and Policy Implications from a Study Concerning Sardinia," Land, MDPI, vol. 12(2), pages 1-23, January.
    2. Michele Salis & Liliana Del Giudice & Roghayeh Jahdi & Fermin Alcasena-Urdiroz & Carla Scarpa & Grazia Pellizzaro & Valentina Bacciu & Matilde Schirru & Andrea Ventura & Marcello Casula & Fabrizio Ped, 2022. "Spatial Patterns and Intensity of Land Abandonment Drive Wildfire Hazard and Likelihood in Mediterranean Agropastoral Areas," Land, MDPI, vol. 11(11), pages 1-22, October.
    3. Tim Drissen & Christopher Faust & Julia T. Treitler & Robin Stadtmann & Stefan Zerbe & Jasmin Mantilla-Contreras, 2022. "National Park or Cultural Landscape Preservation? What the Soil Seed Bank Reveals for Plant Diversity Conservation," Sustainability, MDPI, vol. 14(21), pages 1-24, October.
    4. Sabrina Lai & Federica Leone & Corrado Zoppi, 2020. "Spatial Distribution of Surface Temperature and Land Cover: A Study Concerning Sardinia, Italy," Sustainability, MDPI, vol. 12(8), pages 1-20, April.
    5. Bazzato, Erika & Rosati, Leonardo & Canu, Simona & Fiori, Michele & Farris, Emmanuele & Marignani, Michela, 2021. "High spatial resolution bioclimatic variables to support ecological modelling in a Mediterranean biodiversity hotspot," Ecological Modelling, Elsevier, vol. 441(C).
    6. Xavier Barber & David Conesa & Antonio López-Quílez & Javier Morales, 2019. "Multivariate Bioclimatic Indices Modelling: A Coregionalised Approach," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 24(2), pages 225-244, June.
    7. Maria Luisa Lopez Fernandez & Dauren Zhumabayev & Ricardo Marco Garcia & Kanat Baigarin & Maria Soledad Lopez Fernandez & Saken Baisholanov, 2020. "Assessment of bioclimatic change in Kazakhstan, end 20th—middle 21st centuries, according to the PRECIS prediction," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-37, October.

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