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The Common Agricultural Policy (CAP) of the European Union (EU) is one of the world's largest agricultural policies and the EU's longest-prevailing one. Originally focused mostly on supporting production and farm income, the CAP has progressively integrated instruments to support the environment. Nonetheless, there is considerable agreement among EU citizens that the CAP still does not do enough to address ongoing environmental degradation and climate change (92% of nonfarmers, 64% of farmers) (1). In May and June 2018, the European Commission (EC) published the financial plan and legislative proposal for the CAP post-2020 (2), prompting numerous proposed amendments that the newly elected European Parliament (EP) will now have to consider. With an eye toward the next and final reform stages, including budget discussions and “trilogue” negotiations between the EC, the Council, and the EP to begin in autumn 2019, we examine whether the proposed post-2020 CAP can address key sustainability issues and meet societal demands for higher environmental performance.

International audience; Obtaining an accurate quantification of population size is often of prime importance in ecology and conservation biology (e.g. population viability analysis, a basic step for assessing species and population status in a given area and guiding effective conservation). When obtaining a reliable quantification of absolute (vs. relative) population size is required, Mark–Release–Recapture (MRR) is a method of choice for many organisms. This is a highly reliable but costly procedure in terms of time and potential impact on species and sites. Consequently, less costly alternatives are highly desirable for conservation and population ecologists.We present here a simplified MRR protocol to mitigate this cost of repeated MRR sampling with little compromise on the quality of the population size estimation. Using one of the largest existing butterfly MRR databases, collected on two fritillary species over a period of 20 years and >20 populations in Belgium, we assessed the possibility to reduce the effort of collecting MRR data while keeping accurate quantification of total population size. By downsampling from the full datasets and calculating a range of demographic census metrics, we specifically investigated whether marking individuals is necessary, and whether the number of sampling sessions can be reduced.We found that counting individuals is not enough: some individual marking, even in a simplistic way to differentiate newly recorded from previously seen individuals, is essential for estimating population size. A simple linear conversion function (number of “missed” individuals for each marked one) can be used to compute population size from the number of individuals marked over a small number of MRR sampling sessions. Parameterizing this function is system specific, because it depends on detectability of individuals, but only requires an initial effort of traditional high‐effort MRR in a few populations encompassing the expected range of population size, combined with previous knowledge on the species about potential factors affecting detectability.Our simplified MRR protocol should allow scientists to obtain absolute population size estimates almost as good as with traditional high‐effort MRR, but at a cost lowered in both the marking procedure and the intensity of field visits.

The rapid expansion of systematic monitoring schemes necessitates robust methods to reliably assess species' status and trends. Insect monitoring poses a challenge where there are strong seasonal patterns, requiring repeated counts to reliably assess abundance. Butterfly monitoring schemes (BMSs) operate in an increasing number of countries with broadly the same methodology, yet they differ in their observation frequency and in the methods used to compute annual abundance indices. Using simulated and observed data, we performed an extensive comparison of two approaches used to derive abundance indices from count data collected via BMS, under a range of sampling frequencies. Linear interpolation is most commonly used to estimate abundance indices from seasonal count series. A second method, hereafter the regional generalized additive model (GAM), fits a GAM to repeated counts within sites across a climatic region. For the two methods, we estimated bias in abundance indices and the statistical power for detecting trends, given different proportions of missing counts. We also compared the accuracy of trend estimates using systematically degraded observed counts of the Gatekeeper Pyronia tithonus (Linnaeus 1767). The regional GAM method generally outperforms the linear interpolation method. When the proportion of missing counts increased beyond 50%, indices derived via the linear interpolation method showed substantially higher estimation error as well as clear biases, in comparison to the regional GAM method. The regional GAM method also showed higher power to detect trends when the proportion of missing counts was substantial.Synthesis and applications. Monitoring offers invaluable data to support conservation policy and management, but requires robust analysis approaches and guidance for new and expanding schemes. Based on our findings, we recommend the regional generalized additive model approach when conducting integrative analyses across schemes, or when analysing scheme data with reduced sampling efforts. This method enables existing schemes to be expanded or new schemes to be developed with reduced within-year sampling frequency, as well as affording options to adapt protocols to more efficiently assess species status and trends across large geographical scales.Monitoring offers invaluable data to support conservation policy and management, but requires robust analysis approaches and guidance for new and expanding schemes. Based on our findings, we recommend the regional generalized additive model approach when conducting integrative analyses across schemes, or when analysing scheme data with reduced sampling efforts. This method enables existing schemes to be expanded or new schemes to be developed with reduced within-year sampling frequency, as well as affording options to adapt protocols to more efficiently assess species status and trends across large geographical scales.

International audience; The Minimum Area Requirements (MAR) of species is a concept that explicitly addresses area and therefore can be highly relevant for conservation planning and policy. This study compiled a comprehensive database of MAR estimates from the literature, covering 216 terrestrial animal species from 80 studies. We obtained estimates from (a) Population Viability Analyses (PVAs) which explored a range of area-related scenarios, (b) PVAs that provided a fixed value – either MAR or the minimum viable population size (MVP) alongside other area-relevant information, and (c) empirical studies of occupancy patterns in islands or isolated habitat patches across area. We assessed the explanatory power of life-history traits (body mass, feeding guild, generation length and offspring size), environmental variables (average precipitation and temperature), research approach and phylogenetic group on MAR estimates. PVAs exploring area showed strong correlation between MAR and body mass. One to two additional variables further improved the predictive power. PVA reporting fixed MAR, and occupancy-based studies, were better explained by the combination of feeding guild, climatic variables and additional life history traits. Phylogeny had a consistent but usually small contribution to the predictive power of models. Our work demonstrates that estimating the MAR across species and taxa is achievable but requires cautious interpretation. We further suggest that occupancy patterns are likely sensitive to transient dynamics and are therefore risky to use for estimating MAR. PVA-based evaluations enable considering time horizon and extinction probability, two aspects that are critical for future implementation of the MAR concept into policy and management.

Movement of organisms is one of the key mechanisms shaping biodiversity, e.g. the distribution of genes, individuals and species in space and time. Recent technological and conceptual advances have improved our ability to assess the causes and consequences of individual movement, and led to the emergence of the new field of ‘movement ecology’. Here, we outline how movement ecology can contribute to the broad field of biodiversity research, i.e. the study of processes and patterns of life among and across different scales, from genes to ecosystems, and we propose a conceptual framework linking these hitherto largely separated fields of research. Our framework builds on the concept of movement ecology for individuals, and demonstrates its importance for linking individual organismal movement with biodiversity. First, organismal movements can provide ‘mobile links’ between habitats or ecosystems, thereby connecting resources, genes, and processes among otherwise separate locations. Understanding these mobile links and their impact on biodiversity will be facilitated by movement ecology, because mobile links can be created by different modes of movement (i.e., foraging, dispersal, migration) that relate to different spatiotemporal scales and have differential effects on biodiversity. Second, organismal movements can also mediate coexistence in communities, through ‘equalizing’ and ‘stabilizing’ mechanisms. This novel integrated framework provides a conceptual starting point for a better understanding of biodiversity dynamics in light of individual movement and space-use behavior across spatiotemporal scales. By illustrating this framework with examples, we argue that the integration of movement ecology and biodiversity research will also enhance our ability to conserve diversity at the genetic, species, and ecosystem levels. peerReviewed