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Garzón, Marta Benito; Sánchez de Dios, Rut; Sainz Ollero, Helios
Holocene (Sevenoaks), 08/2008, Letnik: 18, Številka: 5Journal Article
We model the past and future distribution of Pinus sylvestris in the Iberian Peninsula using the random forest algorithm, a machine learning technique that implements an automatic combination of tree predictors. In order to model the past, we chose two of the most climatically significant events recognized affecting the species distribution: the last glacial maximum (LGM, 21 000 cal. BP), and the mid Holocene (6000 cal. BP). In order to model the distributions, we based the future scenarios of climate change upon the four storylines projected by the Intergovernmental Panel on Climate Change (A1, A2, B1 and B2). The results obtained for the past show a contraction in the distribution area during the LGM and a subsequent expansion, coinciding with an improvement in climate in the mid Holocene. The presence of isolated populations of Pinus sylvestris at low altitudes could support the existence of refuges for Northern European taxa. The results obtained for the future, even in the least aggressive scenario, show a rapid decrease in this species' distribution and a vertical migration as a response to climate change. Pinus sylvestris populations would be restricted in the future to the higher altitudes of the mountains in the north of the Iberian Peninsula (mainly the Pyrenees), and the species would disappear from the central and southern mountain ranges. These results identify a risk to high-mountain forest species in the Iberian Peninsula from the effects of global warming.
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Leto | Faktor vpliva | Izdaja | Kategorija | Razvrstitev | ||||
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JCR | SNIP | JCR | SNIP | JCR | SNIP | JCR | SNIP |
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in: SICRIS
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