2008
DOI: 10.3170/2008-7-18568
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Forecasting the pattern and pace of Fagus forest expansion in Majella National Park, Italy

Abstract: Question: Can the pattern and pace of spontaneous Fagus forest expansion from 1975 to 2003 be accurately detected with mid‐resolution satellite imagery? Can the historical Fagus expansion be modelled on the basis of environmental predictors? If so, where are the highest probabilities for future Fagus expansion? What are the implications for park management? Location: Majella National Park, Italy, > 1000 m a.s.l.; municipalities of S. Eufemia and Pacentro. Methods: Fagus cover change was detected by overlayi… Show more

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Cited by 36 publications
(13 citation statements)
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“…; Piermattei et al ), also the sub‐alpine and alpine belts of the Majella massif during the last 50 yr have been influenced by colonization of previously abandoned areas, which has led to an expansion of mountain pine dwarf shrubland (van Gils et al. ; Palombo et al. ).…”
Section: Discussionmentioning
confidence: 99%
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“…; Piermattei et al ), also the sub‐alpine and alpine belts of the Majella massif during the last 50 yr have been influenced by colonization of previously abandoned areas, which has led to an expansion of mountain pine dwarf shrubland (van Gils et al. ; Palombo et al. ).…”
Section: Discussionmentioning
confidence: 99%
“…Morrone, Rotella, Pizzalto and Porrarra and the calcareous Majella massif (van Gils et al. , ). This last reaches 2793 m a.s.l.…”
Section: Methodsmentioning
confidence: 99%
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“…Forest distribution and change at a bottom line is often influenced by both climate change and human activities (e.g., grazing, wood harvesting, and agricultural expansion), and is sensitive to external interruption. 1,2 Conversely, forest distribution at the top line is, relative to the bottom line, less influenced by human activities, thus forest cover change at top lines can be largely attributed to climate change. Therefore, research on tree line change in mountainous regions has become an important research topic related to global climate change, biodiversity, and forest ecosystems.…”
Section: Introductionmentioning
confidence: 96%
“…We controlled for collinearity between predictor variables in two ways. A priori, the Pearson correlation coefficient between these predictors was calculated (Van Gils, Batsukh, David, Munthali, & Liberatoscioli, 2008). A posteriori, the least contributing predictors with a high standard deviation (SD), was removed by stepwise backward elimination (Duque-Lazo, Navarro-Cerrillo, van Gils, & Groen, 2018;Fekede et al, 2019;van Gils, Westinga, Carafa, Antonucci, & Ciaschetti, 2014).…”
Section: The Wild Boar Density Along the Least Cost Path Is High Enough For Transmissionmentioning
confidence: 99%