A Guide to identifying priorities and indicators for restoration monitoring
Author | : Food and Agriculture Organization of the United Nations |
Publisher | : Food & Agriculture Org. |
Total Pages | : 78 |
Release | : 2019-09-25 |
ISBN-10 | : 9789251318256 |
ISBN-13 | : 9251318255 |
Rating | : 4/5 (56 Downloads) |
Book excerpt: This guide walks practitioners through seven questions to help them make decisions regarding restoration monitoring. First, practitioners are asked to determine their restoration goals, land use and barriers to sustainability. These choices are filtered by constraints and priorities, so the practitioner will develop the indicators needed to setup their monitoring framework. It provides a framework for identifying indicators. Indicators are value laden measures of development performance designed to measure and calibrate progress. Environmental indicators are used to provide synthesized knowledge on environmental issues, and to highlight the extent of environmental trends. They also help to reduce complexity, provide important links between science and policy, and help decision-makers to provide guidance on environmental governance. An indicator framework can provide a management tool to help countries develop implementation strategies and allocate resources accordingly to reach restoration goals. Tracking progress with indicators can act as a report card to measure progress towards restoration and help ensure the accountability of all stakeholders for achieving the goals. The guide uses country case studies to show how a practitioner could answer the questions, offering a menu of potential indicators for measuring progress that other monitoring practitioners might find useful. Next, it highlights the different types of data that can feed into creating an indicator framework, depending on resource constraints and information needs. Some restoration programs may require fewer, cost-effective indicators that are collected locally. Other programs, may be able to integrate small, locally collected data with big data from satellite imagery and social media.