date: 2026-09-25T08:58:35Z pdf:PDFVersion: 1.7 pdf:docinfo:title: AI-driven forest restoration: A governance framework for people and nature xmp:CreatorTool: Elsevier access_permission:can_print_degraded: true subject: Environmental Science and Policy, 183 (2026) 104463. doi:10.1016/j.envsci.2026.104463 language: English dc:format: application/pdf; version=1.7 pdf:docinfo:custom:robots: noindex pdf:docinfo:creator_tool: Elsevier access_permission:fill_in_form: true pdf:docinfo:custom:CreationDate--Text: 3rd September 2026 pdf:encrypted: false dc:title: AI-driven forest restoration: A governance framework for people and nature modified: 2026-09-25T08:58:35Z cp:subject: Environmental Science and Policy, 183 (2026) 104463. doi:10.1016/j.envsci.2026.104463 pdf:docinfo:custom:CrossMarkDomains[1]: sciencedirect.com robots: noindex pdf:docinfo:subject: Environmental Science and Policy, 183 (2026) 104463. doi:10.1016/j.envsci.2026.104463 pdf:docinfo:creator: Fernando Morales-Rueda meta:author: Maganizo Kruger Nyasulu pdf:docinfo:custom:CrossmarkMajorVersionDate: 2010-04-23 access_permission:extract_for_accessibility: true pdf:docinfo:custom:CrossMarkDomains[2]: elsevier.com ElsevierWebPDFSpecifications: 7.0.1 pdf:docinfo:custom:doi: 10.1016/j.envsci.2026.104463 pdf:docinfo:custom:CrossmarkDomainExclusive: true Author: Maganizo Kruger Nyasulu producer: Acrobat Distiller 8.1.0 (Windows) CrossmarkDomainExclusive: true pdf:docinfo:producer: Acrobat Distiller 8.1.0 (Windows) CreationDate--Text: 3rd September 2026 doi: 10.1016/j.envsci.2026.104463 pdf:unmappedUnicodeCharsPerPage: 0 dc:description: Environmental Science and Policy, 183 (2026) 104463. doi:10.1016/j.envsci.2026.104463 Keywords: Artificial Intelligence,Socio-ecological restoration,Environmental governance,Participation,Policy Alignment,Polycentrism access_permission:modify_annotations: true dc:creator: Maganizo Kruger Nyasulu description: Environmental Science and Policy, 183 (2026) 104463. doi:10.1016/j.envsci.2026.104463 Last-Modified: 2026-09-25T08:58:35Z dcterms:modified: 2026-09-25T08:58:35Z title: AI-driven forest restoration: A governance framework for people and nature xmpMM:DocumentID: uuid:1b499bed-4ce8-4c0c-b682-0d58baae1cbe Last-Save-Date: 2026-09-25T08:58:35Z CrossMarkDomains[1]: sciencedirect.com pdf:docinfo:keywords: Artificial Intelligence,Socio-ecological restoration,Environmental governance,Participation,Policy Alignment,Polycentrism pdf:docinfo:modified: 2026-09-25T08:58:35Z meta:save-date: 2026-09-25T08:58:35Z Content-Type: application/pdf X-Parsed-By: org.apache.tika.parser.DefaultParser creator: Maganizo Kruger Nyasulu dc:language: English dc:subject: Artificial Intelligence,Socio-ecological restoration,Environmental governance,Participation,Policy Alignment,Polycentrism pdf:docinfo:custom:ElsevierWebPDFSpecifications: 7.0.1 access_permission:assemble_document: true xmpTPg:NPages: 10 pdf:charsPerPage: 4432 access_permission:extract_content: true access_permission:can_print: true CrossMarkDomains[2]: elsevier.com meta:keyword: Artificial Intelligence,Socio-ecological restoration,Environmental governance,Participation,Policy Alignment,Polycentrism access_permission:can_modify: true CrossmarkMajorVersionDate: 2010-04-23