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Agroforestry system as a model of conservation and production to assist forest restoration initiatives

Grant number: 21/00815-0
Support type:Scholarships in Brazil - Master
Effective date (Start): December 01, 2021
Effective date (End): December 31, 2022
Field of knowledge:Agronomical Sciences - Forestry Resources and Forestry Engineering
Principal researcher:Edson José Vidal da Silva
Grantee:Vitoria Duarte Derisso
Home Institution: Escola Superior de Agricultura Luiz de Queiroz (ESALQ). Universidade de São Paulo (USP). Piracicaba , SP, Brazil
Associated research grant:18/18416-2 - Understanding restored forests for benefiting people and nature - NewFor, AP.BTA.TEM

Abstract

The search for alternative models of forest restoration has been increasing and the use of restoration methods that integrate conservationist and productivist goals, such as Agroforestry Systems (AFS) is seen as a potential. However, more studies are needed that seek to show the effect of management intensity on ecological indicators and the provision of ecosystem services, in addition to investigating whether the norms and criteria established in bills for SAFs are coherent. Thus, the present study aims to validate the reference values of AFS monitoring indicators in areas protected by SMA Resolution 189/2018 and to assess the relationship established between management intensity in AFS and ecological indicators and ecosystem service provision (diversity of products generated and coffee yields) for the Pontal do Paranapanema region. Abundance and species richness will be compared for arboreal and regenerating individuals, Shannon (H') and Jaccard indices, aboveground biomass between 5.6-year-old AFS, 10-year-old AFS and reference forest. The management intensity, diversity of products generated and coffee productivity will be evaluated for the AFS areas and, based on the data obtained, a regression analysis will be performed to establish a relationship between all ecological indicators and ecosystem services evaluated (response variables) and each management intensity (predictive variable). To validate the reference values, we will separate the study areas into two groups (indicators that satisfy the legislation and those that do not) and compare by means of the ANOVA, followed by the Tukey test for comparison of means (± = 0.05) , only if the data have a normal distribution. Otherwise, variances will be calculated using Kruskal-Wallis followed by the Wilcoxon test for comparison of means (± = 0.05). All analyzes will be generated in the R 4.0.3 software. (AU)

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