Quo vadis, smallholder forest landscape? An introduction to the LPB-RAP model

Sonja Holler; Daniel Kübler; Olaf Conrad; Oliver Schmitz; Carmelo Bonannella; Tomislav Hengl; Jürgen Böhner; Sven Günter; Melvin Lippe

doi:10.1371/journal.pone.0297439

Quo vadis, smallholder forest landscape? An introduction to the LPB-RAP model

PLoS One. 2024 Feb 2;19(2):e0297439. doi: 10.1371/journal.pone.0297439. eCollection 2024.

Authors

Sonja Holler^{1

2}, Daniel Kübler¹, Olaf Conrad², Oliver Schmitz³, Carmelo Bonannella^{4

5}, Tomislav Hengl⁴, Jürgen Böhner², Sven Günter¹, Melvin Lippe¹

Affiliations

¹ Thünen Institute of Forestry, Hamburg, Germany.
² Center for Earth System Research and Sustainability (CEN), Hamburg University, Hamburg, Germany.
³ Department of Physical Geography, Faculty of Geosciences, Utrecht University, Utrecht, The Netherlands.
⁴ OpenGeoHub, Wageningen, The Netherlands.
⁵ Laboratory of Geo-Information Science and Remote Sensing, Wageningen University & Research, Wageningen, The Netherlands.

Abstract

The impacts of the Anthropocene on climate and biodiversity pose societal and ecological problems that may only be solved by ecosystem restoration. Local to regional actions are required, which need to consider the prevailing present and future conditions of a certain landscape extent. Modeling approaches can be of help to support management efforts and to provide advice to policy making. We present stage one of the LaForeT-PLUC-BE model (Landscape Forestry in the Tropics-PCRaster Land Use Change-Biogeographic & Economic model; in short: LPB) and its thematic expansion module RAP (Restoration Areas Potentials). LPB-RAP is a high-resolution pixel-based scenario tool that relies on a range of explicit land use types (LUTs) to describe various forest types and the environment. It simulates and analyzes future landscape configurations under consideration of climate, population and land use change long-term. Simulated Land Use Land Cover Change (LULCC) builds on dynamic, probabilistic modeling incorporating climatic and anthropogenic determinants as well as restriction parameters to depict a sub-national regional smallholder-dominated forest landscape. The model delivers results for contrasting scenario settings by simulating without and with potential Forest and Landscape Restoration (FLR) measures. FLR potentials are depicted by up to five RAP-LUTs. The model builds on user-defined scenario inputs, such as the Shared Socioeconomic Pathways (SSP) and Representative Concentration Pathways (RCP). Model application is here exemplified for the SSP2-RCP4.5 scenario in the time frame 2018-2100 on the hectare scale in annual resolution using Esmeraldas province, Ecuador, as a case study area. The LPB-RAP model is a novel, heuristic Spatial Decision Support System (SDSS) tool for smallholder-dominated forest landscapes, supporting near-time top-down planning measures with long-term bottom-up modeling. Its application should be followed up by FLR on-site investigations and stakeholder participation across all involved scales.

Copyright: © 2024 Holler et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

MeSH terms

Biodiversity
Conservation of Natural Resources* / methods
Ecosystem*
Forestry / methods
Forests

Grants and funding

The research of Thünen affiliated authors was funded by the Thünen Institute (and conducted by the Thünen Institute of Forestry, Hamburg, Germany), and the German Federal Ministry of Food and Agriculture (Project Landscape Forestry in the Tropics (LaForeT); Project Phase 1: LaForeT - User and Scales; Project Phase 2: LaForeT R2 - Restoration & REDD+), based on a decision of the German Federal Parliament. We are further grateful for the funding provided by the German Federal Office for Agriculture and Food (BLE) under Project Number 281-006-01 (LaForeT Policies). The maps of Potential Natural Vegetation provided by OpenGeoHub were developed in the context of the Open-Earth-Monitor Cyberinfrastructure project. The Open-Earth-Monitor Cyberinfrastructure project has received funding from the European Union’s Horizon Europe research, an innovation program under grant agreement No. 101059548. The funders did not participate in any way in study design, data collection and analysis, decision to publish, or preparation of the manuscript.