Spatial Modeling of Douglas‐Fir Plantations in Italy After 120 Years of Experimentation
ABSTRACT This study aims to identify the ecological factors that drive the survival of Douglas‐fir (Pseudotsuga menziesii [Mirb.] Franco) in Italy, using data from old‐growth experimental stands. A record of 124 Douglas‐fir plantations was compiled from a literature review and ground survey, includi...
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Wiley
2025-08-01
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| Series: | Ecology and Evolution |
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| Online Access: | https://doi.org/10.1002/ece3.71943 |
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| author | Maurizio Marchi Martina Cocozza Gabriele Bucci Paolo Iovieno |
| author_facet | Maurizio Marchi Martina Cocozza Gabriele Bucci Paolo Iovieno |
| author_sort | Maurizio Marchi |
| collection | DOAJ |
| description | ABSTRACT This study aims to identify the ecological factors that drive the survival of Douglas‐fir (Pseudotsuga menziesii [Mirb.] Franco) in Italy, using data from old‐growth experimental stands. A record of 124 Douglas‐fir plantations was compiled from a literature review and ground survey, including 98 Douglas‐fir stands established in the early 20th century. The probability of survival of the species at the surveyed sites was modeled using Species Distribution Models (SDM) with soil and climatic variables as predictors. Pseudo‐absences were also used to balance the proportion of presences and absences in the modeling steps. The best‐fitting models were used to predict the probability of survival of Douglas‐fir stands across the entire country and in the native range of the species to assess the model's goodness of fit. Fitted models performed well with a mean True Skill Statistics (TSS) score of 0.91, suggesting that temperature‐related factors primarily influence the survival of Douglas‐fir stands in Italy. The two most relevant predictors were GDD5 (growing degree‐days above 5°C) and AHM (Annual Heat Moisture), indicating the importance of temperatures and water availability also in the Mediterranean area. A large portion of Italy was predicted to be potentially suitable for Douglas‐fir afforestation or reforestation, mainly across the Apennine Mountains of central Italy. Model projections for the species' native area largely overlap with the range of the coastal variety of Douglas‐fir (P. menziesii var. viridis), supporting the hypothesis that most Douglas‐fir stands in Italy were established using propagation material from this region. |
| format | Article |
| id | doaj-art-34bd6b677e854d1497d4c434804db654 |
| institution | Kabale University |
| issn | 2045-7758 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Wiley |
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| series | Ecology and Evolution |
| spelling | doaj-art-34bd6b677e854d1497d4c434804db6542025-08-25T08:37:30ZengWileyEcology and Evolution2045-77582025-08-01158n/an/a10.1002/ece3.71943Spatial Modeling of Douglas‐Fir Plantations in Italy After 120 Years of ExperimentationMaurizio Marchi0Martina Cocozza1Gabriele Bucci2Paolo Iovieno3CNR‐Institute of Biosciences and BioResources, Florence Research Area Sesto Fiorentino ItalyCNR‐Institute of Biosciences and BioResources, Florence Research Area Sesto Fiorentino ItalyCNR‐Institute of Biosciences and BioResources, Florence Research Area Sesto Fiorentino ItalyCNR‐Institute of Biosciences and BioResources, Florence Research Area Sesto Fiorentino ItalyABSTRACT This study aims to identify the ecological factors that drive the survival of Douglas‐fir (Pseudotsuga menziesii [Mirb.] Franco) in Italy, using data from old‐growth experimental stands. A record of 124 Douglas‐fir plantations was compiled from a literature review and ground survey, including 98 Douglas‐fir stands established in the early 20th century. The probability of survival of the species at the surveyed sites was modeled using Species Distribution Models (SDM) with soil and climatic variables as predictors. Pseudo‐absences were also used to balance the proportion of presences and absences in the modeling steps. The best‐fitting models were used to predict the probability of survival of Douglas‐fir stands across the entire country and in the native range of the species to assess the model's goodness of fit. Fitted models performed well with a mean True Skill Statistics (TSS) score of 0.91, suggesting that temperature‐related factors primarily influence the survival of Douglas‐fir stands in Italy. The two most relevant predictors were GDD5 (growing degree‐days above 5°C) and AHM (Annual Heat Moisture), indicating the importance of temperatures and water availability also in the Mediterranean area. A large portion of Italy was predicted to be potentially suitable for Douglas‐fir afforestation or reforestation, mainly across the Apennine Mountains of central Italy. Model projections for the species' native area largely overlap with the range of the coastal variety of Douglas‐fir (P. menziesii var. viridis), supporting the hypothesis that most Douglas‐fir stands in Italy were established using propagation material from this region.https://doi.org/10.1002/ece3.71943climateecological modelingexotic tree speciesforest tree provenanceshabitat suitability |
| spellingShingle | Maurizio Marchi Martina Cocozza Gabriele Bucci Paolo Iovieno Spatial Modeling of Douglas‐Fir Plantations in Italy After 120 Years of Experimentation Ecology and Evolution climate ecological modeling exotic tree species forest tree provenances habitat suitability |
| title | Spatial Modeling of Douglas‐Fir Plantations in Italy After 120 Years of Experimentation |
| title_full | Spatial Modeling of Douglas‐Fir Plantations in Italy After 120 Years of Experimentation |
| title_fullStr | Spatial Modeling of Douglas‐Fir Plantations in Italy After 120 Years of Experimentation |
| title_full_unstemmed | Spatial Modeling of Douglas‐Fir Plantations in Italy After 120 Years of Experimentation |
| title_short | Spatial Modeling of Douglas‐Fir Plantations in Italy After 120 Years of Experimentation |
| title_sort | spatial modeling of douglas fir plantations in italy after 120 years of experimentation |
| topic | climate ecological modeling exotic tree species forest tree provenances habitat suitability |
| url | https://doi.org/10.1002/ece3.71943 |
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