Mega-trees in a fragmented Atlantic Forest landscape: where are they and why are they there?

dos Santos J.G.; Ferreira R.L.C.; Cunha J.S.A.; Fonsêca N.C.; Gorgens E.B.; Lins-e-Silva A.C.B.; Breunig F.M.; Wagner F.H.; Elera-Gonzales D.G.; Finger A.P.; Silva E.A. · Applied Geography (2026) · DOI: 10.1016/j.apgeog.2026.104194

Resumen

Mega-trees play a disproportionate role in forest ecosystems, concentrating large shares of biomass and carbon and sustaining high biodiversity, thereby influencing forest productivity, dynamics and ecosystem services. However, their growth and persistence are constrained by abiotic conditions, particularly in highly fragmented and human-modified landscapes such as the Brazilian Atlantic Forest. This study aimed to map and quantify emergent trees and mega-trees in a fragmented Atlantic Forest landscape in Pernambuco (Northeast Brazil) and to model the habitats that favour their occurrence and long-term survival. We applied machine-learning habitat modelling (MaxEnt) using terrain-derived predictors from a Digital Terrain Model (DTM) at multiple spatial scales (10, 30, 50 and 100 m). Across resolutions, terrain variables were consistently associated with suitable habitats, likely acting as spatial proxies for several non-exclusive processes (water redistribution, nutrient availability, solar exposure, wind shelter, microclimatic buffering and land-use filtering). The Topographic Position Index (TPI) was one of the most influential predictors, suggesting that concave landforms may represent candidate sheltered microsites for mega-tree persistence. Because terrain integrates several co-varying processes, we interpret this as an association rather than evidence of a single causal mechanism. The 10 m model achieved the highest performance (AUC = 0.906), while intermediate resolutions (30 and 50 m; AUC = 0.867 and 0.853) better represented habitat conditions surrounding mega-trees, reducing omission errors seen at 100 m. Overall, terrain-mediated refugia emerge as conservation-relevant targets, providing a spatial framework to support management and restoration planning for mega-trees in fragmented tropical forests. Copyright

Instituciones: Universidad Nacional Autónoma de Chota