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To 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 budget allocation 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 0·01%-0·74% of the total CAP budget and to 0·04%-2·48% 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. [ABSTRACT FROM AUTHOR]

1. In temperate farmed landscapes conservation policies increasingly emphasize large-scale reductions in land-use intensity. Yet despite a managed reversion to more favourable abiotic conditions, depleted regional species pools may prevent the re-assembly of target communities. 2. Using national-scale survey data recorded across Great Britain in 1998, we investigated the extent to which grassland indicator plant species persisted on potential refuge habitats across a spatial gradient of intensive land cover in lowland 1-km squares. These habitats comprised road verges, field boundaries, watercourse banks and small biotope fragments. Intensive land cover comprised built land, arable and improved grassland. 3. The rate of reduction in indicator species richness across the intensive land cover gradient was significantly lower in all potential refuge features than in surrounding fields and larger areas of habitat. 4. The best refuge locations were watercourse banks and small biotopes. In both cases, indicator species richness was higher than adjacent fields at the lowest intensive land cover and stayed higher as intensive land cover increased. 5. However, as intensive land cover increased, plant traits associated with higher nutrient availability were more prominently represented among indicator species. 6. Although richer assemblages of indicator species persisted on refuge features, population sizes are likely to be small, because of species–area effects, and also vulnerable to nutrient surpluses and reduced or inappropriate disturbance. 7. Synthesis and applications. Across the British lowlands, linear landscape features and small habitat fragments can provide limited safe havens for unimproved grassland plant species. However, the identity of refuge features and their species richness and composition are likely to vary with local conditions. Three activities are therefore paramount in assessing their role in larger scale extensification schemes: (i) development of rapid ways of assessing the plant diversity and distribution of refuge features in local areas; (ii) quantification of the risks posed to the viability of residual source populations through implementation of different options for incorporating them into extensification schemes; (iii) maximization of scheme performance by targeting landscapes with sufficient residual diversity to enable increases in population size of the target species in the medium term. [ABSTRACT FROM AUTHOR]

Summary: 1. Ellenberg’s indicator values scale the flora of a region along gradients reflecting light, temperature, continentality, moisture, soil pH, fertility and salinity. They can be used to monitor environmental change. 2. Ellenberg values can be extended from central Europe, for which they were defined, to nearby parts of Europe. Given a database of quadrat samples, they can be repredicted by a simple algorithm consisting of two-way weighted averaging, followed by local regression. 3. A database of British samples was assembled from two large surveys. Ellenberg values were repredicted. 4. Except for the indicator of continentality, the correlation of repredicted and original values was in the range 0·72 (light) to 0·91 (moisture). The continentality indicator could not be adequately repredicted by the algorithm, and is unusable in Britain. 5. Discrepancies between original and repredicted values can be attributed to various causes, including wrong original values, differing ecological requirements in Britain and central Europe, biased sampling of the British range of habitats, and the occurrence of small plants in shaded or basic microhabitats within well illuminated or predominantly acid quadrats. 6. The repredicted values were generally reliable, but a small proportion was clearly wrong. Wrong values were due to either inadequate sampling of species’ realized niches in Britain or sampling with quadrats that were too large and included species that were not close associates. [ABSTRACT FROM AUTHOR]