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-Mart ́ınez 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.

Bioclimate map of Sardinia (Italy)

ROSATI, LEONARDO;
2015-01-01

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-Mart ́ınez 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.
2015
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11563/112210
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