SciELO - Scientific Electronic Library Online

 
vol.27 número3Ecuación dinámica para estimar el crecimiento en diámetro de Pinus montezumae Lamb. en Puebla, MéxicoCambios en la cubierta terrestre a través de los mapas ESA-CCI-LC (2000-2015), Ixtacamaxtitlán, Puebla índice de autoresíndice de materiabúsqueda de artículos
Home Pagelista alfabética de revistas  

Servicios Personalizados

Revista

Articulo

Indicadores

Links relacionados

  • No hay artículos similaresSimilares en SciELO

Compartir


Madera y bosques

versión On-line ISSN 2448-7597versión impresa ISSN 1405-0471

Resumen

CORREA-DIAZ, Arian; GOMEZ-GUERRERO, Armando  y  VELASCO-BAUTISTA, Efraín. A close up of daily temperature and moisture in two Mexican high-elevation forests. Madera bosques [online]. 2021, vol.27, n.3, e2732206.  Epub 28-Mar-2022. ISSN 2448-7597.  https://doi.org/10.21829/myb.2021.2732206.

The scarcity of meteorological stations and the strong need for climatic information in alpine forests require the use of large-scale climatic algorithms but the lack of in situ information produces high uncertainty on their suitability. In this study, we used linear mixed models to study the topographic effect (elevation and aspect) and time variations (from hourly to monthly) on temperature (T) and relative humidity (RH) with a 5-year instrumental database. Furthermore, we compared climatic information from a geographical algorithm and our in-situ data. Our data covered two mountains (Tláloc-TLA and Jocotitlán-JOC, State of México), four elevation belts (from 3500 m to 3900 m a.s.l.), and two aspects (Northwest and Southwest). We found differences for average temperature (TLA = 7.56 °C ± 0.03 °C and JOC = 6.98 °C ± 0.02 °C), and relative humidity between mountains (TLA = 69.3% ± 0.12% and JOC = 72.5% ± 0.13%,). The most significant variables explaining T were the elevation (Δ= -0.36 °C by 100 m) and aspect, while the aspect was relevant for RH. May was the warmest month (9.50 °C ± 0.10 °C for average temperature) while September the wettest for both mountains (85.1% ± 0.30% and 87.4% ± 0.25 % RH, respectively). Despite the higher correlations between climatic sources (up to r = 0.83), the geographical algorithm overestimates T and underestimates RH. We propose that when climatic information from geographical algorithms is used in alpine forests, calibrations are needed whenever possible with in situ information.

Palabras llave : Pinus hartwegii; relative humidity; temperature.

        · resumen en Español     · texto en Inglés