High biodiversity silvopastoral system as an alternative to improve the thermal environment in the dairy farms

Int J Biometeorol. 2019 Jan;63(1):83-92. doi: 10.1007/s00484-018-1638-8. Epub 2018 Nov 19.

Abstract

The aim of this work was to evaluate the influence of high biodiversity silvopastoral system (SPSnuclei) on microclimate and thermal comfort index thru a parallel with treeless pasture (TLP) during the four seasons of the year. Three conditions were determined for this study: shadowing area in SPSnuclei, sunny area in SPSnuclei, and sunny area in TLP. During two consecutive days in each season, the following microclimatic variables were collected: air temperature (°C), relative humidity (%), illuminance (lux), wind speed (m/s), and soil surface temperature (°C). The temperature and humidity index (THI) was calculated for each condition as indicative of thermal comfort. An influence analysis was carried out by generalized linear models to evaluate the system effects on the microclimatic variables. A confirmatory analysis was done with Wilcoxon-Mann-Whitney. Systems (SPSnuclei x TLP) influenced the microclimatic variables and THI (p < 0.05). The lowest means of air temperature, illuminance, wind speed, and soil surface temperature were found in SPSnuclei. As expected, autumn and winter presented a comfortable environment even on treeless pastureland. Only the SPSnuclei showed a comfortable environment for dairy production during spring. During summer, the TLP had a microclimate and thermal comfort index not suitable for dairy production already in the first hours of the day (THI between 79 and 85). We concluded that SPSnuclei provided better environment for pasture-based dairy production when compared to TLP. The high THI measured in TLP during summer could be a limiting factor on animal production.

Keywords: Ambience; Microclimate; Native trees; Shading; Thermal comfort; Tree nuclei.

MeSH terms

  • Animals
  • Biodiversity*
  • Brazil
  • Cattle
  • Dairying*
  • Farms*
  • Humidity
  • Microclimate*
  • Seasons
  • Temperature*
  • Thermosensing
  • Wind