Data summarizing monitoring and evaluation for three European environmental policies in 9 cases across Europe

The data presented in this DiB article provide an overview of Monitoring and Evaluation (M&E) carried out for 3 European environmental policies (the Water Framework Directive, the Natura 2000 network of protected areas, and Agri-Environment Schemes implemented under the Common Agricultural Policy), as implemented in 9 cases (Catalonia (Spain), Estonia, Finland, Flanders (Belgium), Hungary, Romania, Slovakia, Scotland (UK), Sweden). These data are derived from reports and documents about monitoring programs that were publicly-available online in 2017. The literature on M&E to support adaptive management structured the issues that have been extracted and summarized. The data is related to the research article entitled “Policy-driven monitoring and evaluation: does it support adaptive management of socio-ecological systems?” [Stem et al., 2005]. The information provides a first overview of monitoring and evaluation that has been implemented in response to key European environmental policies. It provides a structured overview that permits a comparison of cases and policies and can assist other scholars and practitioners working on monitoring and evaluation.

A practical approach to improve the statistical performance of surface water monitoring networks

The representativeness of aquatic ecosystem monitoring and the precision of the assessment results are of high importance when implementing the EU's Water Framework Directive that aims to secure a good status of waterbodies in Europe. However, adapting monitoring designs to answer the objectives and allocating the sampling resources effectively are seldom practiced. Here, we present a practical solution how the sampling effort could be re-allocated without decreasing the precision and confidence of status class assignment. For demonstrating this, we used a large data set of 272 intensively monitored Finnish lake, coastal, and river waterbodies utilizing an existing framework for quantifying the uncertainties in the status class estimation. We estimated the temporal and spatial variance components, as well as the effect of sampling allocation to the precision and confidence of chlorophyll-a and total phosphorus. Our results suggest that almost 70% of the lake and coastal waterbodies, and 27% of the river waterbodies, were classified without sufficient confidence in these variables. On the other hand, many of the waterbodies produced unnecessary precise metric means. Thus, reallocation of sampling effort is needed. Our results show that, even though the studied variables are among the most monitored status metrics, the unexplained variation is still high. Combining multiple data sets and using fixed covariates would improve the modeling performance. Our study highlights that ongoing monitoring programs should be evaluated more systematically, and the information from the statistical uncertainty analysis should be brought concretely to the decision-making process.

Policy-driven monitoring and evaluation: Does it support adaptive management of socio-ecological systems?

Inadequate Monitoring and Evaluation (M&E) is often thought to hinder adaptive management of socio-ecological systems. A key influence on environmental management practices are environmental policies: however, their consequences for M&E practices have not been well-examined. We examine three policy areas - the Water Framework Directive, the Natura 2000 Directives, and the Agri-Environment Schemes of the Common Agricultural Policy - whose statutory requirements influence how the environment is managed and monitored across Europe. We use a comparative approach to examine what is monitored, how monitoring is carried out, and how results are used to update management, based on publicly available documentation across nine regional and national cases. The requirements and guidelines of these policies have provided significant impetus for monitoring: however, we find this policy-driven M&E usually does not match the ideals of what is needed to inform adaptive management. There is a tendency to focus on understanding state and trends rather than tracking the effect of interventions; a focus on specific biotic and abiotic indicators at the expense of understanding system functions and processes, especially social components; and limited attention to how context affects systems, though this is sometimes considered via secondary data. The resulting data are sometimes publicly-accessible, but it is rarely clear if and how these influence decisions at any level, whether this be in the original policy itself or at the level of measures such as site management plans. Adjustments to policy-driven M&E could better enable learning for adaptive management, by reconsidering what supports a balanced understanding of socio-ecological systems and decision-making. Useful strategies include making more use of secondary data, and more transparency in data-sharing and decision-making. Several countries and policy areas already offer useful examples. Such changes are essential given the influence of policy, and the urgency of enabling adaptive management to safeguard socio-ecological systems.