EDITOR'S CHOICE: How much would it cost to monitor farmland biodiversity in Europe?

Abstract

International audienceTo evaluate progress on political biodiversity objectives, biodiversity monitoring provides information on whether intended results are being achieved. Despite scientific proof that monitoring and evaluation increase the (cost) efficiency of policy measures, cost estimates for monitoring schemes are seldom available, hampering their inclusion in policy programme budgets. Empirical data collected from 12 case studies across Europe were used in a power analysis to estimate the number of farms that would need to be sampled per major farm type to detect changes in species richness over time for four taxa (vascular plants, earthworms, spiders and bees). A sampling design was developed to allocate spatially, across Europe, the farms that should be sampled. Cost estimates are provided for nine monitoring scenarios with differing robustness for detecting temporal changes in species numbers. These cost estimates are compared with the Common Agricultural Policy (CAP) budget (2014-2020) to determine the budgetallocation required for the proposed farmland biodiversity monitoring. Results show that the bee indicator requires the highest number of farms to be sampled and the vascular plant indicator the lowest. The costs for the nine farmland biodiversity monitoring scenarios corresponded to 001%-074% of the total CAP budget and to 004%-248% of the CAP budget specifically allocated to environmental targets.Synthesis and applications. The results of the cost scenarios demonstrate that, based on the taxa and methods used in this study, a Europe-wide farmland biodiversity monitoring scheme would require a modest share of the Common Agricultural Policy budget. The monitoring scenarios are flexible and can be adapted or complemented with alternate data collection options (e.g. at national scale or voluntary efforts), data mobilization, data integration or modelling efforts. Editor's Choic

Barcoding the food chain: from Sanger to high-throughput sequencing

“…collection of eDNA samples such as water or soil, which might also facilitate citizen scientist monitoring of species which are not charismatic or easily identifiable (Janzen et al 2005;Adamowicz and Steinke 2015;Ugochukwu et al 2015). Citizen scientist data from morphological identifications is already feeding into policy reports (Geijzendorffer et al 2016), which could usefully reduce the considerable amount of person-hours required for monitoring. Yet researchers have highlighted issues with the use of eDNA, which necessitates knowledge of how eDNA is released from the originating organism.…”

State-of-the-art practices in farmland biodiversity monitoring for North America and Europe

“…(iii) The number of samples must yield the statistical power to detect changes in biodiversity indicators at the required precision and over a predetermined time scale (e.g., X % decrease of the population of species A over Y years; see Legg and Nagy 2006;Franklin et al 2011). Provided that prior knowledge about the variability of the indicator exists, a power analysis can inform on the required sample size (Nielsen et al 2009;Geijzendorffer et al 2016). …”

“…Yet they should be integrated in a global framework that allows for interoperability due to common monitoring protocols and harmonized data structure and standards, making it possible to inform essential biodiversity variables (Schmeller et al 2015). Geijzendorffer et al (2016) show that biodiversity monitoring is ''affordable'' compared to other public expenses that support farming. They argue that the efficiency of agri-environmental schemes and of cross-compliance requirements such as ecological focus areas could be increased if their effects were monitored.…”

Optimising survey effort to monitor environmental variables: A case study using New Zealand kiwifruit orchards

“…see cost function derived by Field et al, 2005). With these points in mind, statistical power analyses can be essential tools for comparing the capacity of different sampling strategies to achieve the purpose for which they are to be applied (for example see Geijzendorffer et al, 2015; GuilleraArroita and Lahoz-Monfort, 2012; Legg and Nagy, 2006; Schalk Power to detect a range of specified trends (0 to À4% pa) in total densities of native bird species over an 11-year period varying the survey frequency (see Table 1) and number of orchards. Points are offset along the x-axis for clarity.…”

“…This is often technically and logistically challenging, especially when treatment impacts vary from site to site (Raudenbush and Liu, 2000) and/or resources are limited (Lindenmayer and Likens, 2010;Magurran et al, 2010). Careful planning and executing of sophisticated analyses of monitoring data are recommended for identifying: cost-effective and robust designs (Field et al, 2007;Geijzendorffer et al, 2015;Johnson et al, 2015); monitoring efforts that have no realistic chance of detecting relevant changes, and options for improving them (Collen and Nicholson, 2014;Field et al, 2007;Legg and Nagy, 2006); and trade-offs between spatial and temporal replication (Rhodes and Jonz en, 2011;Urquhart et al, 1998).…”