Ecological Indicators (Jan 2024)

A new quality index based on soil-vegetation networks to determine the recovery of functionality in abandoned agrosystems

  • Juan Pedro Martín-Sanz,
  • Inmaculada Valverde-Asenjo,
  • Miguel Ángel Casermeiro,
  • José Antonio Molina,
  • José Ramón Quintana

Journal volume & issue
Vol. 158
p. 111466

Abstract

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The development of indices of ecosystem quality makes it possible to obtain robust information with less human and material effort. These indices are especially useful for assessing the quality of ecosystems disturbed by anthropogenic impact since they can inform management decisions designed to recover their functionality. The abandonment of agricultural activity is a major environmental challenge, and it is important to understand its consequences on ecosystem functioning. The main objective of this work was to develop a robust quality index of abandoned agrosystems based on detailed information on soil properties and structure and the composition of the vegetation. A chronosequence was built of abandoned vineyards over the last 60 years. Seventeen soil physical-chemical properties and ten enzymatic activities related to the cycles of C, N, P and S were determined in 21 plots along the chronosequence. Total vegetation cover, cover of cryptograms and phanerogams and cover of plant functional groups was also recorded. The main factors involved in the quality of the ecosystem were detected by means of network analyses based on these variables. Models were then developed to calculate ecosystem quality indices. Our results showed how the evolution of soil properties occurred simultaneously with variations in the composition and structure of the vegetation. The major factors that determined the functionality of abandoned agrosystems were the quantity and quality of soil organic matter (high TOC and WHN) and the lesser abundance of sulphur accumulator plants. The ecosystem quality index model found to be the most robust was the index with integration by weights and non-linear scores, which followed a sigmoid pattern throughout the chronosequence. Our results highlight the importance of developing robust quality indices based on an interdisciplinary approach.

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