2020
DOI: 10.3390/land10010001
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The Relict Ecosystem of Maytenus senegalensis subsp. europaea in an Agricultural Landscape: Past, Present and Future Scenarios

Abstract: Maytenus senegalensis subsp. europaea is a shrub belonging to the Celastraceae family, whose only European populations are distributed discontinuously along the south-eastern coast of the Iberian Peninsula, forming plant communities with great ecological value, unique in Europe. As it is an endangered species that makes up plant communities with great palaeoecological significance, the development of species distribution models is of major interest under different climatic scenarios, past, present and future, … Show more

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Cited by 11 publications
(5 citation statements)
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References 75 publications
(95 reference statements)
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“…Our models showed potential impacts of climate change on the series Fissa species in the Iberian Peninsula, a result that is consistent with previous climate change analyses conducted with mountain species (Lenoir et al 2008;Engler et al 2011) and threatened taxa (Mendoza-Fernández et al 2021). Studies about the effects of climate change on biodiversity have predicted range contractions for many species, but range expansion has also been documented (see e.g.…”
Section: Discussionsupporting
confidence: 90%
“…Our models showed potential impacts of climate change on the series Fissa species in the Iberian Peninsula, a result that is consistent with previous climate change analyses conducted with mountain species (Lenoir et al 2008;Engler et al 2011) and threatened taxa (Mendoza-Fernández et al 2021). Studies about the effects of climate change on biodiversity have predicted range contractions for many species, but range expansion has also been documented (see e.g.…”
Section: Discussionsupporting
confidence: 90%
“…Variables with a correlation coefficient greater than 0.75 were considered highly correlated, and only those with high importance and interpretability were retained for species distribution modeling. The method of evaluating and selecting variables based on their importance using ensemble models allows for a more comprehensive consideration of each variable’s contribution to model predictions compared to other approaches for addressing multicollinearity [ 50 , 51 ]. Consequently, this method facilitates the selection of important variables, thereby enhancing the interpretability of the model.…”
Section: Methodsmentioning
confidence: 99%
“…43% of its distribution area is nowadays occupied by greenhouses. As a result, the landscape is highly fragmented and only a few poorly conserved patches of native vegetation remain in the area [15,83,84].…”
Section: Habitat Managementmentioning
confidence: 99%