Measuring and modelling microclimatic air temperature in a historically degraded tropical forest.
Int J Biometeorol
; 66(6): 1283-1295, 2022 Jun.
Article
em En
| MEDLINE
| ID: mdl-35357567
Climate change is predicted to cause widespread disruptions to global biodiversity. Most climate models are at the macroscale, operating at a ~ 1 km resolution and predicting future temperatures at 1.5-2 m above ground level, making them unable to predict microclimates at the scale that many organisms experience temperature. We studied the effects of forest structure and vertical position on microclimatic air temperature within forest canopy in a historically degraded tropical forest in Sikundur, Northern Sumatra, Indonesia. We collected temperature measurements in fifteen plots over 20 months, alongside vegetation structure data from the same fifteen 25 × 25 m plots. We also performed airborne surveys using an unmanned aerial vehicle (UAV) to record canopy structure remotely, both over the plot locations and a wider area. We hypothesised that old-growth forest structure would moderate microclimatic air temperature. Our data showed that Sikundur is a thermally dynamic environment, with simultaneously recorded temperatures at different locations within the canopy varying by up to ~ 15 °C. Our models (R2 = 0.90 to 0.95) showed that temperature differences between data loggers at different sites were largely determined by variation in recording height and the amount of solar radiation reaching the topmost part of the canopy, although strong interactions between these abiotic factors and canopy structure shaped microclimate air temperature variation. The impacts of forest degradation have smaller relative influence on models of microclimatic air temperature than abiotic factors, but the loss of canopy density increases temperature. This may render areas of degraded tropical forests unsuitable for some forest-dwelling species with the advent of future climate change.
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Base de dados:
MEDLINE
Assunto principal:
Florestas
/
Microclima
Tipo de estudo:
Prognostic_studies
Idioma:
En
Ano de publicação:
2022
Tipo de documento:
Article