Examinando por Materia "Potential distribution"

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Habitat Suitability Distribution of Genus Gynoxys Cass. (Asteraceae): An Approach to Conservation and Ecological Restoration of the Andean Flora in Peru.
(MDPI, Basel, Switzerland., 2025-03-10) Coronel Castro, Elver; Meza Mori, Gerson; Pariente Mondragon, Eli; Haro, Nixon; Oliva Cruz, Manuel; Barboza , Elgar; Amasifuen Guerra, Carlos A.; Revilla Pantigoso, Italo; Tariq , Aqil; Guzman Valqui, Betty Karina
The study used species distribution models (MaxEnt) to analyze the ecological suitability of the genus Gynoxys in Peru. Bioclimatic, edaphic and topographic variables were integrated to predict areas with high development potential. Potential distribution maps were generated, and model validation showed outstanding performance (AUC > 0.9). The results indicated that variables such as minimum temperature in the warmest season and soil moisture are determinants in the distribution of the Discoide, Gynoxys and Praegynoxys clades. It is concluded that the conservation of the genus requires protection strategies to ensure the sustainability of these montane ecosystems.
Mapping current and future coffee suitability in Peru under climate change: implications for restoration and deforestation-free development
(Frontiers Media S.A, 2026-04-20) Zabaleta Santisteban, Jhon A.; Rojas Briceño, Nilton B.; Silva López, Jhonsy O.; Medina Medina, Angel J.; Tuesta Trauco, Katerin M.; Rivera Fernandez, Abner S.; Silva Melendez, Teodoro B.; Grandez Alberca, Marlen A.; Puscan Rojas, Julio; Salas López, Rolando; Oliva Cruz, Manuel; Cotrina Sanchez, Alexander; Gómez Fernández, Darwin; Barboza, Elgar
Coffee cultivation is central to rural livelihoods and Andean–Amazonian landscapes in Peru; however, it faces increasing pressure from climate change and land-use restrictions. This study aimed to assess the current and future ecological suitability of Coffea arabica at the national scale. A Maximum Entropy (MaxEnt) modeling framework was applied, integrating high-resolution bioclimatic, topographic, and edaphic variables. Model performance was robust (mean AUC = 0.858), and variable importance was evaluated using jackknife tests and contribution metrics. Elevation, precipitation of the driest quarter (bio17), soil nitrogen content, and bulk density were identified as the main determinants of habitat suitability. Under current climatic conditions, highly suitable areas cover 42,322.95 km2 (3.3% of Peru), mainly along the eastern Andean slopes. Spatial exclusion scenarios revealed a pronounced funnel effect in effective land availability, with reductions exceeding 80% when forest-cover constraints were applied. Approximately 39.8% of highly suitable areas overlap with degraded lands, highlighting opportunities for productive restoration through agroforestry systems. Future projections under SSP1–2.6 to SSP5–8.5 scenarios indicate consistent contractions of highly suitable areas (–23% to –42%) and an upslope shift toward higher elevations, while unsuitable areas expand by 4%–5% nationally. These findings provide spatially explicit evidence to support climate-smart territorial planning, restoration prioritization, and sustainable coffee development under accelerating climate change.