Publications by authors named "H CASTELLANOS"

We describe the geographical variation in tree species composition across Amazonian forests and show how environmental conditions are associated with species turnover. Our analyses are based on 2023 forest inventory plots (1 ha) that provide abundance data for a total of 5188 tree species. Within-plot species composition reflected both local environmental conditions (especially soil nutrients and hydrology) and geographical regions.

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Article Synopsis
  • Amazonia's floodplain system is the largest and most biodiverse, but our understanding of its forest species and their unique roles is still limited, especially as changing flood patterns impact these communities.
  • About one-sixth of the tree diversity in Amazonia is specifically adapted to live in floodplain environments, indicating a significant ecological specialization within these forests.
  • The study emphasizes that the unique composition of floodplain forests is influenced by regional flooding patterns, highlighting the necessity of maintaining overall hydrological health to ensure the survival of Amazon's tree diversity and its essential ecosystem functions.
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Trees structure the Earth's most biodiverse ecosystem, tropical forests. The vast number of tree species presents a formidable challenge to understanding these forests, including their response to environmental change, as very little is known about most tropical tree species. A focus on the common species may circumvent this challenge.

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Hybrid nanofluids offer higher stability, synergistic effects, and better heat transfer compared to simple nanofluids. Their higher thermal conductivity, lower viscosity, and interaction with magnetic fields make them ideal for various applications, including materials science, transportation, medical technology, energy, and fundamental physics. The governing partial differential equations are numerically solved by employing a finite volume approach, and the effects of various parameters on the nanofluid flow and thermal characteristics are systematically examined from the simulations based on a self-developed MATLAB code.

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