The use of opportunistic data for IUCN Red List assessments

IUCN Red Lists are recognized worldwide as powerful instruments for the conservation of species. Quantitative criteria to standardize approaches for estimating population trends, geographic ranges and population sizes have been developed at global and sub-global levels. Little attention has been given to the data needed to estimate species trends and range sizes for IUCN Red List assessments. Few regions collect monitoring data in a structured way and usually only for a limited number of taxa. Therefore, opportunistic data are increasingly used for estimating trends and geographic range sizes. Trend calculations use a range of proxies: (i) monitoring sentinel populations, (ii) estimating changes in available habitat, or (iii) statistical models of change based on opportunistic records. Geographic ranges have been determined using: (i) marginal occurrences, (ii) habitat distributions, (iii) range-wide occurrences, (iv) species distribution modelling (including site-occupancy models), and (v) process-based modelling. Red List assessments differ strongly among regions (Europe, Britain and Flanders, north Belgium). Across different taxonomic groups, in European Red Lists IUCN criteria B and D resulted in the highest level of threat. In Britain, this was the case for criterion D and criterion A, while in Flanders criterion B and criterion A resulted in the highest threat level. Among taxonomic groups, however, large differences in the use of IUCN criteria were revealed. We give examples from Europe, Britain and Flemish Red List assessments using opportunistic data and give recommendations for a more uniform use of IUCN criteria among regions and among taxonomic groups

Statistics for citizen science: extracting signals of change from noisy ecological data

1. Policy-makers increasingly demand robust measures of biodiversity change over short time periods. Long-term monitoring schemes provide high-quality data, often on an annual basis, but are taxonomically and geographically restricted. By contrast, opportunistic biological records are relatively unstructured but vast in quantity. Recently, these data have been applied to increasingly elaborate science and policy questions, using a range of methods. At present we lack a firm understanding of which methods, if any, are capable of delivering unbiased trend estimates on policy-relevant timescales. 2. We identified a set of candidate methods that employ data filtering criteria and/or correction factors to deal with variation in recorder activity. We designed a computer simulation to compare the statistical properties of these methods under a suite of realistic data collection scenarios. We measured the Type I error rates of each method-scenario combination, as well as the power to detect genuine trends. 3. We found that simple methods produce biased trend estimates, and/or had low power. Most methods are robust to variation in sampling effort, but biases in spatial coverage, sampling effort per visit, and detectability, as well as turnover in community composition all induced some methods to fail. No method was wholly unaffected by all forms of variation in recorder activity, although some performed well enough to be useful. 4. We warn against the use of simple methods. Sophisticated methods that model the data collection process offer the greatest potential to estimate timely trends, notably Frescalo and Occupancy-Detection models. 5. The potential of these methods and the value of opportunistic data would be further enhanced by assessing the validity of model assumptions and by capturing small amounts of information about sampling intensity at the point of data collection

A regionally informed abundance index for supporting integrative analyses across butterfly monitoring schemes

1. 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. 2. 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). 3. 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. 4. 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

Habitatrichtlijnrapportage 2019: Annex D Habitattypen : Achtergronddocument

This document describes the concepts, data and methods used in the 2019 report (under Article 17 of the Habitats Directive) on the conservation status of habitat types for the parameters range, area, structure and functions, and future prospects. The ranges of nearly all habitat types have not changed. No reliable, updated data on area were available for most habitat types. The methodology for assessing structure and functions has been thoroughly revised to accommodate long-term monitoring data and meet the new reporting formats. The European Commission has also introduced a new method for assessing future prospects. The report presents the results and indicates where the methods and data can be improved

Tracking Progress Toward EU Biodiversity Strategy Targets : EU Policy Effects in Preserving its Common Farmland Birds

Maximizing the area under biodiversity-related conservation measures is a main target of the European Union (EU) Biodiversity Strategy to 2020. We analyzed whether agrienvironmental schemes (AES) within EU common agricultural policy, special protected areas for birds (SPAs), and Annex I designation within EU Birds Directive had an effect on bird population changes using monitoring data from 39 farmland bird species from 1981 to 2012 at EU scale. Populations of resident and short-distance migrants were larger with increasing SPAs and AES coverage, while Annex I species had higher population growth rates with increasing SPAs, indicating that SPAs may contribute to the protection of mainly target species and species spending most of their life cycle in the EU. Because farmland birds are in decline and the negative relationship of agricultural intensification with their population growth rates was evident during the implementation of AES and SPAs, EU policies seem to generally attenuate the declines of farmland bird populations, but not to reverse them.Peer reviewe

The European Butterfly Indicator for grassland species: 1990-2013

This report presents the fifth version of the European Grassland Butterfly Indicator, one of the EU biodiversity indicators of the European Environment Agency

Long-term and large-scale multispecies dataset tracking population changes of common European breeding birds

Around fifteen thousand fieldworkers annually count breeding birds using standardized protocols in 28 European countries. The observations are collected by using country-specific and standardized protocols, validated, summarized and finally used for the production of continent-wide annual and long-term indices of population size changes of 170 species. Here, we present the database and provide a detailed summary of the methodology used for fieldwork and calculation of the relative population size change estimates. We also provide a brief overview of how the data are used in research, conservation and policy. We believe this unique database, based on decades of bird monitoring alongside the comprehensive summary of its methodology, will facilitate and encourage further use of the Pan-European Common Bird Monitoring Scheme results.publishedVersio

Over a century of data reveal more than 80% decline in butterflies in the Netherlands

Opportunistic butterfly records from 1890 to 2017 were analysed to quantitatively estimate the overall long-term change in occurrence of butterfly species in the Netherlands. For 71 species, we assessed trends in the number of occupied 5 km × 5 km sites by applying a modified List Length method, which takes into account changes in observation effort. We summarised the species trends in a Multi-Species Indicator (MSI) by taking the geometric mean of the species indices. Between 1890–1930 and 1981–1990, the MSI decreased by 67%; downward trends were detected for 42 species, many of which have disappeared completely from the Netherlands. Monitoring count data available from 1992 showed a further 50% decline in MSI. Combined, this yields an estimated decline of 84% in 1890–2017. We argue that in reality the loss is likely even higher. We also assessed separate MSIs for three major butterfly habitat types in the Netherlands: grassland, woodland and heathland. Butterflies strongly declined in all three habitats alike. The trend has stabilised over recent decades in grassland and woodland, but the decline continues in heathland