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Article

Decision Support System for the Assessment and Enhancement of Agrobiodiversity Performance

1
C-MAST—Centre for Mechanical and Aerospace Science and Technologies, Department of Electromechanical Engineering, University of Beira Interior, 6201-001 Covilhã, Portugal
2
NECE—Research Unit in Business Sciences, Department of Management and Economics, University of Beira Interior, 6201-001 Covilhã, Portugal
3
LEAF—Linking Landscape, Environment, Agriculture and Food, School of Agriculture Research Center, University of Lisbon, 1649-004 Lisboa, Portugal
4
TERRA—Sustainable Land Use and Ecosystem Services, School of Agriculture, University of Lisbon, 1649-004 Lisboa, Portugal
5
CEF—Forest Research Centre, School of Agriculture, University of Lisbon, 1649-004 Lisboa, Portugal
*
Author to whom correspondence should be addressed.
Sustainability 2024, 16(15), 6519; https://doi.org/10.3390/su16156519 (registering DOI)
Submission received: 26 June 2024 / Revised: 22 July 2024 / Accepted: 28 July 2024 / Published: 30 July 2024
(This article belongs to the Section Sustainable Agriculture)

Abstract

The industrialisation of agriculture and changes in production systems have contributed to a biodiversity decline worldwide. Developing accurate and adequate assessment methods can encourage farmers to support more sustainable agricultural management. This study presents a decision support system to promote agrobiodiversity that incorporates not only a quantitative assessment of relevant indicators of agrobiodiversity performance but also provides enhancement practice recommendations and associated benefits, presenting an action plan in order of priority. Additionally, the decision support system allows a visual comparison between biodiversity composite indicators and indicators representing pest control and crop yield. Since grape cultivation is considered one of the most intensive agricultural systems, thus significantly impacting biodiversity, the elaborated decision support system was tested on a viticultural agroecosystem in the demarcated Douro region in Portugal. The results demonstrated the decision support system functioning according to the selected methodology and allowed the identification of future lines for investigation. During the analysed period, the following were verified: an increase of 2% in the biodiversity indicator, 130% in harvest yield, and 2077% in the enemy-to-pest ratio. It is expected that the elaborated DSS will offer a significant contribution by bridging communication gaps on alternative management options to improve biodiversity performance in agricultural systems.
Keywords: agrobiodiversity; assessment; decision support system; agriculture; viticulture agrobiodiversity; assessment; decision support system; agriculture; viticulture

Share and Cite

MDPI and ACS Style

Marcelino, S.M.; Gaspar, P.D.; Paço, A.; Lima, T.M.; Monteiro, A.; Franco, J.C.; Santos, E.S.; Campos, R.; Lopes, C.M. Decision Support System for the Assessment and Enhancement of Agrobiodiversity Performance. Sustainability 2024, 16, 6519. https://doi.org/10.3390/su16156519

AMA Style

Marcelino SM, Gaspar PD, Paço A, Lima TM, Monteiro A, Franco JC, Santos ES, Campos R, Lopes CM. Decision Support System for the Assessment and Enhancement of Agrobiodiversity Performance. Sustainability. 2024; 16(15):6519. https://doi.org/10.3390/su16156519

Chicago/Turabian Style

Marcelino, Sara Morgado, Pedro Dinis Gaspar, Arminda Paço, Tânia M. Lima, Ana Monteiro, José Carlos Franco, Erika S. Santos, Rebeca Campos, and Carlos M. Lopes. 2024. "Decision Support System for the Assessment and Enhancement of Agrobiodiversity Performance" Sustainability 16, no. 15: 6519. https://doi.org/10.3390/su16156519

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