| Resumo: | Background and Aims: Some Magnolia species have a highly restricted distribution, making them highly vulnerable to extinction, considering the current degradation caused by human activities. Little is known about the effect of environmental variables and land use on their natural populations. Therefore, this study analyzes the distribution of two endangered Magnolia species, Magnolia jardinensis and M. yarumalensis, and their relationship with environmental variables and land cover.
Methods: Field trips were carried out in the northwestern Andes of Colombia, where individuals of both species were georeferenced. In addition, herbarium records and global biodiversity databases (GBIF) were used to obtain additional information on location. topographic, vegetation cover, and climate data (WorldClim) were employed, including maximum temperature of the warmest month (Tmax), minimum temperature of the coldest month (Tmin), annual precipitation (PPT), precipitation of the wettest quarter (PTH), and precipitation of the driest quarter (PTS).
Key results: The results indicate that the geographical distribution of these Magnolia species is restricted and with variations in altitudinal ranges (M. jardinensis: 1995.46-2667.49 m a.s.l.; M. yarumalensis: 1648.05-2759.59 m a.s.l.). Although both species are associated with humid and very humid environments, significant differences were observed between the precipitation of the sites where the two species grow (M. jardinensis: 2363.94 mm/year, 752.33 mm PTH, 384.73 mm PTS; M. yarumalensis: 2464.88 mm/year, 814.21 mm PTH, 356.25 mm PTS). Furthermore, it was evident that most trees grow in areas affected by human activities, such as secondary vegetation, clean pastures, and forest plantations.
Conclusions: Restriction in distribution ranges and disturbance conditions where these species occur increase their risk of extinction, especially concerning increasing temperatures in the context of current climate change. Both magnolias could be considered species with extremely small populations.
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