Identification, Monitoring, Indicators and Assessments Identification, Monitoring, Indicators and Assessments About Introduction Background Programme COP Decisions Implementation Pilot Assessments Database of Scientific AssessmentsNational-Level Indicators Principles Key questionsTested Indicators Global IndicatorsGBO 2GBO 3 Related Information Meetings and Documents Other Relevant DocumentsNotifications Identification & Monitoring // Principles Monday // 4.30.2007 Principles for selecting indicators Indicators should be: Policy relevant and meaningful Indicators should send a clear message and provide information at a level appropriate for policy and management decision making by assessing changes in the status of biodiversity (or pressures, responses, use or capacity), related to baselines and agreed policy targets if possible.Biodiversity relevant Indicators should address key properties of biodiversity or related issues as state, pressures, responses, use or capacity.Scientifically sound Indicators must be based on clearly defined, verifiable and scientifically acceptable data, which are collected using standard methods with known accuracy and precision, or based on traditional knowledge that has been validated in an appropriate way.Broadly accepted The power of an indicator depends on its broad acceptance. Involvement of the policy makers, and major stakeholders and experts in the development of an indicator is crucial.Based on affordable monitoring Indicators should be measurable in an accurate and affordable way and part of a sustainable monitoring system, using determinable baselines and targets for the assessment of improvements and declines.Based on affordable modelling Information on cause-effect relationships should be achievable and quantifiable, in order to link pressures, state and response indicators. These relation models enable scenario analyses and are the basis of the ecosystem approach.Sensitive Indicators should be sensitive to show trends and, where possible, permit distinction between human-induced and natural changes. Indicators should thus be able to detect changes in systems in time frames and on the scales that are relevant to the decisions, but also be robust so that measuring errors do not affect the interpretation. It is important to detect changes before it is too late to correct the problems being detected.
Identification & Monitoring // Principles Monday // 4.30.2007 Principles for selecting indicators Indicators should be: Policy relevant and meaningful Indicators should send a clear message and provide information at a level appropriate for policy and management decision making by assessing changes in the status of biodiversity (or pressures, responses, use or capacity), related to baselines and agreed policy targets if possible.Biodiversity relevant Indicators should address key properties of biodiversity or related issues as state, pressures, responses, use or capacity.Scientifically sound Indicators must be based on clearly defined, verifiable and scientifically acceptable data, which are collected using standard methods with known accuracy and precision, or based on traditional knowledge that has been validated in an appropriate way.Broadly accepted The power of an indicator depends on its broad acceptance. Involvement of the policy makers, and major stakeholders and experts in the development of an indicator is crucial.Based on affordable monitoring Indicators should be measurable in an accurate and affordable way and part of a sustainable monitoring system, using determinable baselines and targets for the assessment of improvements and declines.Based on affordable modelling Information on cause-effect relationships should be achievable and quantifiable, in order to link pressures, state and response indicators. These relation models enable scenario analyses and are the basis of the ecosystem approach.Sensitive Indicators should be sensitive to show trends and, where possible, permit distinction between human-induced and natural changes. Indicators should thus be able to detect changes in systems in time frames and on the scales that are relevant to the decisions, but also be robust so that measuring errors do not affect the interpretation. It is important to detect changes before it is too late to correct the problems being detected.
