Current and future distribution of Shihuahuaco (Dipteryx spp.) under climate change scenarios in the Central-Eastern Amazon of Peru

• Autores: Cárdenas Rengifo, Gloria Patricia, Bravo Morales, Nino Frank, Barboza Castillo, Elgar, Salazar Coronal, Wilian, Ocaña Reyes, Jimmy Alcides, Vásquez Macedo, Miguel, Lobato Gálvez, Roiser Honorio, Injante Silva, Pedro Hugo, Arbizu Berrocal, Carlos Irvin
• Formato: artículo
• Fecha de Publicación: 2023
• Institución: Instituto Nacional de Innovación Agraria
• Repositorio: INIA-Institucional
• Lenguaje: inglés
• OAI Identifier: oai:null:20.500.12955/2187
• Enlace del recurso: https://hdl.handle.net/20.500.12955/2187; https://doi.org/10.3390/su15107789
• Nivel de acceso: acceso abierto
• Materia: Maximum entropy; Ecological niche; Biodiversity conservation; Models of species; Distribution; Climate change; Sustainability of shihuahuaco; https://purl.org/pe-repo/ocde/ford#4.01.02; Entropía; Conservación de la diversidad biológica; Cambio climático; Entropy

The consequences of climate change influence the distribution of species, which plays a key role in ecosystems. In this work, the modeling of the current and potential future distribution was carried out under different climate change scenarios of a tree species of high economic and commercial value, Dipteryx spp. This is a hardwood species that plays an important role in carbon sequestration, providing food and nesting for wildlife species, reaching more than 40 m in height with an average diameter of 70 to 150 cm. This species is currently threatened by overexploitation. Thirty-six bioclimatic, topographic and edaphic variables with ~1 km2 spatial resolution obtained from the WorldClim, SoilGrids and SRTM databases where used. Highly correlated variables were identified with the MaxEnt software for forecasting how the species distribution will be affected until the year 2100, according to the climate scenarios SPP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5, representing the periods 2021–2040, 2041–2060, 2061–2080 and 2081–2100, respectively. The AUC accuracy value of 0.88 to 0.89 was found for the distribution models and the highest contributing variables used were Bio 5, precipitation, Bio 2, and Bio 14. In the climate scenario SPP1-2.6 (Bio 5, precipitation and Bio 2) in 2061–2080, suitable and very suitable habitats represented 30.69% of the study area (2616 ha and 586.97 ha, respectively) and those increased by 1.75% under current climate conditions, and the suitable and unsuitable habitats represented 69.31% of the total area. The results of this research provide valuable information on the current and future distribution of the species and identify zones that can be used as the basis for the creation of conservation areas, formulation of restoration projects, reforestation and sustainable management to avoid the extinction of the species in the face of the effects of climate change.