Biogeographic Distribution of Cedrela spp. Genus in Peru Using MaxEnt Modeling: A Conservation and Restoration Approach

Abstract

The increasing demand for tropical timber from natural forests has reduced the population sizes of native species such as Cedrela spp. because of their high economic value. To prevent the decline of population sizes of the species, all Cedrela species have been incorporated into Appendix II of the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES). The study presents information about the modeled distribution of the genus Cedrela in Peru that aims to identify potential habitat distribution of the genus, its availability in areas protected by national service of protected areas, and highlighted some areas because of their conservation relevance and the potential need for restoration. We modeled the distribution of the genus Cedrela in Peru using 947 occurrence records that included 10 species (C. odorata, C. montana, C. fissilis, C. longipetiolulata, C. angustifolia, C. nebulosa, C. kuelapensis, C. saltensis, C. weberbaueri, and C. molinensis). We aim to identify areas environmentally suitable for the occurrence of Cedrela that are legally protected by the National Service of Protected Areas (PAs) and those that are ideal for research and restoration projects. We used various environmental variables (19 bioclimatic variables, 3 topographic factors, 9 edaphic factors, solar radiation, and relative humidity) and the maximum entropy model (MaxEnt) to predict the probability of occurrence. We observed that 6.7% (86,916.2 km2) of Peru presents a high distribution probability of occurrence of Cedrela, distributed in 17 departments, with 4.4% (10,171.03 km2) of the area protected by PAs mainly under the category of protection forests. Another 11.65% (21,345.16 km2) of distribution covers areas highly prone to degradation, distributed mainly in the departments Ucayali, Loreto, and Madre de Dios, and needs immediate attention for its protection and restoration. We believe that the study will contribute significantly to conserve Cedrela and other endangered species, as well as to promote the sustainable use and management of timber species as a whole.

Zoogeographic regionalisation of terrestrial vertebrates of Mozambique

“…To deal with collinearity and improve the interpretability of our analysis, we followed a two‐step approach. We first identified clusters for all 20 variables using the function “removecollinearity” from the “virtualspecies” R package (Cotrina‐Sánchez et al., 2021; Leroy et al., 2016). The variables were clustered according to a Pearson correlation coefficient of r = 0.65.…”

An image is worth a thousand species: mapping plant biodiversity with citizen science, remote sensing, and deep learning

“…While downscaling and interpolation techniques (24, 25) exist that allow one to scale these bioclimatic variables to 250-100 meter resolution – a similar resolution to our methods – these downscaling and interpolation methods are inherently limited in the amount of novel information they can provide, and introduce a new source of potential bias (26). Furthermore, there has been evidence that SDMs trained using coarser-grained climate data overestimate some montane species’ tolerance to changing climate compared to meters-resolution local scale information (27).…”

“…By modeling each individual species of a community, we can begin to detect not just individual species, but phenomena of the entire community as well. While traditional SDMs have been used to model entire genera simultaneously, or single species SDMs have been aggregated across thousands of species to create continent-wide metrics (2, 24), and while CNNs have been used to detect vegetation categories and Ellenberg’s indicator values (65, 66) using a single SDM to detect community-level patterns from individual species distribution data has not been attempted to date. Here, we explore how both individual species-level phenomena are learned by deepbiosphere and how community ecological level phenomena and change are also well-captured by deepbiosphere .…”

A New Species of Cedrela (Meliaceae) from a Colombian Dry Forest and an Updated Key for the Species of the Genus

“…To prevent the decline of population sizes, all Cedrela taxa have been incorporated into Appendix II of the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES, 2021; https://cites.org/esp/node/57207). Cedrela is subject to overexploitation and excessive logging for domestic and international trade, habitat loss, genetic erosion, and significant illicit cutting and illegal trade (Llerena et al, 2018; Araujo-Murakami et al, 2020; Cotrina-Sánchez et al, 2021).…”

“…org/esp/node/57207). Cedrela is subject to overexploitation and excessive logging for domestic and international trade, habitat loss, genetic erosion, and significant illicit cutting and illegal trade (Llerena et al, 2018;Araujo-Murakami et al, 2020;Cotrina-Sánchez et al, 2021).…”