Measuring, Reporting, and Verification of Forest Restoration
Restoring ecosystems can increase biodiversity, safeguard the ecosystem services on which people and nature depend, and contribute to climate change mitigation. Ambitions such as the European Green Deal (2019), the EU Biodiversity Strategy for 2030 (2020), the EU Nature Restoration Plan (2019), and the UN Decade on Ecosystem Restoration (2021–2030), present a fantastic opportunity to scale up ecosystem restoration and bring about transformational change. This document describes the framework used by the Horizon Europe project SUPERB to prepare effective monitoring plans in support of forest restoration projects.
Introduction
There is a wealth of information about the best practice principles to apply in design restoration projects (e.g. Evans et al. 2016; Stanturf et al 2017; Blume et al. 2019; Gann et al. 2019; Nelson et al 2024), and common to all is an emphasis on the importance of periodic monitoring to feedback into project management and demonstrate an activity or policies are effective. Many stakeholders interested in large scale ecosystem restoration will already be aware of the UN-REDD+ programme, which seeks to sequester and store carbon in forests. Participants of REDD+ commit to a process of Measurement, Reporting, and Verification (MRV) to update and publish their projected impact. As biodiversity and ecosystem properties other that emissions reduction are expected to play an increasingly significant role in restoration funding, a similarly transparent and rigorous mechanism for assessment is required. Consequently this guide describes how users could deliver their an adaptive MRV reporting strategy and to address fundamental questions about their project:
- Has the restoration project achieving the maximum potential for that ecosystem, and does this match the original desired objectives?
Could alternative restoration methods and techniques have been used to improve recovery of the ecosystem?
What adjustments to design, implementation and monitoring could improve cost-efficiency?
Effective monitoring design (Section 1) will identify how successfully projects lead to the recovery of ecosystems based relevant benchmarks of progress and forecast objectives. Appropriate indicators will be closely linked to restoration objectives and reflect an understanding of the spatial and temporal scales of ecosystem recovery (Section 2). Sharing of data and results is not only a critical component of an adaptive management approach, but making this accessible will also help to reduce costs of restoration projects collectively (Section 3). It is imperative that as nations and communities, we act swiftly to stem environmental degradation, but there are gaps in our knowledge on the optimal strategy to adopt. We highlight three issues (progress reporting at early phases, forecasting site potential and monitoring efficiency), that stakeholders interested in developing projects will need to be aware of (Section 4).
2. Indicators of Forest Restoration
We developed multi‐scale ecological reference models for the SUPERB restoration project by monitoring a diverse set of ecosystem attributes—from invasive species presence and soil health to structural diversity (via forest inventories, drone imagery and lidar) and ecosystem functions like nutrient cycling and carbon storage. These standardized, long‐term surveys integrate species composition, physical conditions and landscape connectivity to provide benchmarks against which future restoration success can be measured.
1. Planning and Design
Quantifying restoration success entails setting explicit, measurable, time‑bound objectives and using baseline surveys alongside counterfactual and reference‑ecosystem models to assess “additionality” and convergence toward desired states. By comparing multiple ecological indicators across restoration trajectories—some of which may respond quickly and others more slowly—projects can robustly determine when outcomes exceed business‑as‑usual and match reference conditions.
3. Reporting and Data Management
The SUPERB MRV‑BES framework adapts the UN‑REDD+ MRV approach to forest restoration by combining SMART baseline surveys with a suite of indicators (vegetation, soil carbon, microbial eDNA, bioacoustics, LiDAR/multispectral) and reference‑stand trajectories to efficiently detect ecological change. All data—from professional and citizen‑science sampling to satellite imagery—are processed via open‑source tools under rigorous QA/QC and stored in a centralized Darwin‑Core/INSPIRE‑compliant database with persistent identifiers and Creative Commons licensing for transparency and reuse.