A generalizable monitoring model to implement policies to promote forest restoration – A case study in São Paulo - Brazil

Ribeiro Nobre, Silvana and Guilherme Borges, José and Díaz Balteiro, Luis Augusto and Estraviz Rodríguez, Luis Carlos and Carrascosa von Glenn, Helena and Zakia, María José (2019). A generalizable monitoring model to implement policies to promote forest restoration – A case study in São Paulo - Brazil. "Forest Policy And Economics", v. 103 ; pp. 123-135. ISSN 1389-9341. https://doi.org/10.1016/j.forpol.2018.03.001.

Description

Title: A generalizable monitoring model to implement policies to promote forest restoration – A case study in São Paulo - Brazil
Author/s:
  • Ribeiro Nobre, Silvana
  • Guilherme Borges, José
  • Díaz Balteiro, Luis Augusto
  • Estraviz Rodríguez, Luis Carlos
  • Carrascosa von Glenn, Helena
  • Zakia, María José
Item Type: Article
Título de Revista/Publicación: Forest Policy And Economics
Date: June 2019
ISSN: 1389-9341
Volume: 103
Subjects:
Freetext Keywords: Adaptive management; Forest management decision support system; Forest restoration; Integrated forest planning
Faculty: E.T.S.I. Montes, Forestal y del Medio Natural (UPM)
Department: Ingeniería y Gestión Forestal y Ambiental
Creative Commons Licenses: Recognition - No derivative works - Non commercial

Full text

[img]
Preview
PDF - Requires a PDF viewer, such as GSview, Xpdf or Adobe Acrobat Reader
Download (1MB) | Preview

Abstract

Examples of large-scale restoration programs to recover ecosystem services are now common in many countries, and governments are assuming ambitious forest restoration targets. Given the increasing investment of time, effort, and money in restoration, there is an urgent need to develop monitoring programs to assess restoration effectiveness. Some countries are already conducting monitoring programs, but the effectiveness of the restoration programs remains mostly unknown. Restoration evaluation often entails significant difficulties, such as the lack of harmonized monitoring data and imprecise information available about project goals and implementation. With the intent of contributing to the development of effective and accountable restoration projects, the objective of our work is to create a conceptual model that provides the building blocks of a planning and monitoring system to support forest restoration programs. The aim is to develop a conceptual model that represents forest restoration monitoring processes that effectively attain and measure the desirable outcomes. The São Paulo Forest Restoration Program is the case study that provides variables and processes to illustrate the development of the conceptual model. This paper presents the conceptual model, emphasizing generalizable principles that extend its applicability to similar monitoring programs. Based on action learning principles and recommendations from a comprehensive literature review, the resulting Forest Management Decisions Support System (FMDSS) embeds adaptive management strategies and the existence of an auto-updatable knowledge base. The result is a conceptual model that can be generalizable and applicable beyond the realms of the FMDSS. The restoration of degraded areas in a case with > 40,000 rural properties serves as the case study. Although the planning and the monitoring of the restoration programs differ, the generalizable principles used to develop the conceptual model presented in this paper result in continuous intelligent monitoring processes that transform the systems so that they are adaptable to apparently different situations. Additionally, conceptual models that integrate adaptive planning and monitoring processes, supported by an auto-updatable knowledge base, mitigate the risk of failures, mainly when the comprehensive gathering of well-established references for the initial knowledge base has been conducted well at the outset.

Funding Projects

TypeCodeAcronymLeaderTitle
Horizon 2020691149SuFoRunUnspecifiedModels and decision SUpport tools for integrated FOrest policy development under global change and associated Risk and UNcertainty

More information

Item ID: 55377
DC Identifier: http://oa.upm.es/55377/
OAI Identifier: oai:oa.upm.es:55377
DOI: 10.1016/j.forpol.2018.03.001
Deposited by: Memoria Investigacion
Deposited on: 12 Jun 2019 10:48
Last Modified: 12 Jun 2019 10:48
  • Logo InvestigaM (UPM)
  • Logo GEOUP4
  • Logo Open Access
  • Open Access
  • Logo Sherpa/Romeo
    Check whether the anglo-saxon journal in which you have published an article allows you to also publish it under open access.
  • Logo Dulcinea
    Check whether the spanish journal in which you have published an article allows you to also publish it under open access.
  • Logo de Recolecta
  • Logo del Observatorio I+D+i UPM
  • Logo de OpenCourseWare UPM