Evaluation of Pasture Productivity and Quality in the Montado Ecosystem Using Proximal Sensors

Abstract

Montado is a silvo-pastoral system characterized by open canopy woodlands of mainly Quercus suber and Quercus rotundifolia, mingled in some areas with other Mediterranean tree species, with natural or cultivated grassland in the undercover and grazing animals. A decline of these ecosystems has been reported since the end of the nineteenth century in southern Portugal. In order to ensure a sustainable management, there is an urgent need to produce knowledge on the resilience thresholds of these systems. Monitoring of indicators for a timely evaluation of pasture variability in Montado is particularly complex and an important challenge due to the existence of different strata (soil, pasture, trees and animals). The conventional methods for determining key components of pasture productivity and quality are time consuming and expensive, hence the interest in evaluating faster and cost effective tools. Monitoring pasture productivity and quality over time is critical for defining the nutritional value of pastures and designing balanced diets for grazing animals. The aims of this study were to evaluate two proximal sensors with potential to monitor relevant variables in the Montado ecosystem and demonstrate their application in a case study: a capacitance probe and an active optical sensor (AOS). This work uses data from a dryland biodiverse Mediterranean pasture, collected during spring of 2016 and 2017. The significant and strong correlations between capacitance and pasture biomass and between normalized difference vegetation index (NDVI) measured by AOS and pasture crude protein (CP) and pasture fibre (NDF, neutral detergent fibre) can make an important contribution to determination of key components of pasture productivity and quality and to support decisions in the implementation of site-specific pasture and grazing management. This correlation can be used for the management