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Contains fulltext : 216802.pdf (publisher's version ) (Closed access), The European Union's Natura 2000 (N2000), is one of the largest international networks of protected areas. One of its aims is to secure the status of a pre-determined set of (targeted) bird and butterfly species. However, also non-target species may benefit from N2000. We evaluated how the terrestrial component of this network relates to the abundance of non-targeted, more common bird and butterfly species using data from long-term volunteer-based monitoring programs in 9,602 sites for birds and 2,001 sites for butterflies. In almost half of the 155 bird species assessed, and particularly among woodland specialists, abundance increased with the proportion of N2000 sites in the landscape. The corresponding positive relationship was found for 27 of the 104 butterfly species, although most of these species were generalists. These positive relationships disappeared for most of the species when land-cover covariates were taken into account, hinting that land-cover is a primary factor defining the positive effects of the N2000 network. The increase in abundance with N2000 was correlated with the specialization index for bird species, but not for butterfly species. Although the N2000 network supports higher abundance of a large spectrum of species, the low number of specialist butterfly species showing a positive association stresses the need to implement management plan improving the quality of habitats of N2000 areas potentially harboring openland butterfly specialists. For a better understanding of the processes involved, we advocate for a standardized collection of data on N2000 sites. Article impact statement: Across Europe the abundance of a majority of nontarget birds and a quarter of nontarget butterflies increased with Natura 2000 coverage. This article is protected by copyright. All rights reserved

The European Union's Natura 2000 (N2000) is among the largest international networks of protected areas. One of its aims is to secure the status of a predetermined set of (targeted) bird and butterfly species. However, nontarget species may also benefit from N2000. We evaluated how the terrestrial component of this network affects the abundance of nontargeted, more common bird and butterfly species based on data from long‐term volunteer‐based monitoring programs in 9602 sites for birds and 2001 sites for butterflies. In almost half of the 155 bird species assessed, and particularly among woodland specialists, abundance increased (slope estimates ranged from 0.101 [SD 0.042] to 3.51 [SD 1.30]) as the proportion of landscape covered by N2000 sites increased. This positive relationship existed for 27 of the 104 butterfly species (estimates ranged from 0.382 [SD 0.163] to 4.28 [SD 0.768]), although most butterflies were generalists. For most species, when land‐cover covariates were accounted for these positive relationships were not evident, meaning land cover may be a determinant of positive effects of the N2000 network. The increase in abundance as N2000 coverage increased correlated with the specialization index for birds, but not for butterflies. Although the N2000 network supports high abundance of a large spectrum of species, the low number of specialist butterflies with a positive association with the N2000 network shows the need to improve the habitat quality of N2000 sites that could harbor open‐land butterfly specialists. For a better understanding of the processes involved, we advocate for standardized collection of data at N2000 sites.

Biodiversity is being lost at an unprecedented rate, and monitoring is crucial for understanding the causal drivers and assessing solutions. Most biodiversity monitoring data are collected by volunteers throughcitizen science projects, and often crucial information is lacking to account for the inevitable biases that observers introduce during data collection. We contend that citizen science projects intended to supportbiodiversity monitoring must gather information about the observationprocess as well as species occurrence. We illustrate this using eBird, a global citizen science project that collects information on bird occurrences as well as vital contextual information on the observation process while maintaining broad participation. Our fundamental argument is that regardless of what species are being monitored, when citizen science projects collect a small set of basic information about how participants make their observations, the scientific value of the data collected will be dramatically improved.

Monitoring the status and trends of species is critical to their conservation and management. However, the current state of biodiversity monitoring is insufficient to detect such for most species and habitats, other than in a few localised areas. One of the biggest obstacles to adequate monitoring is the lack of local capacity to carry out such programs. Thus, building the capacity to do such monitoring is imperative. We here highlight different biodiversity monitoring efforts to illustrate how capacity building efforts are being conducted at different geographic scales and under a range of resource, literacy, and training constraints. Accordingly, we include examples of monitoring efforts from within countries (Kenya, France, and China), within regions (Central America and the Arctic) and larger capacity building programs including EDGE (Evolutionarily Distinct and Globally Endangered) of Existence and the National Red List Alliance.

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 GAM, fits a generalized additive model 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 s

The Convention on Biological Diversity's strategic plan lays out five goals: “(A) address the underlying causes of biodiversity loss by mainstreaming biodiversity across government and society; (B) reduce the direct pressures on biodiversity and promote sustainable use; (C) improve the status of biodiversity by safeguarding ecosystems, species and genetic diversity; (D) enhance the benefits to all from biodiversity and ecosystem services; (E) enhance implementation through participatory planning, knowledge management and capacity building.” To meet and inform on the progress towards these goals, a globally coordinated approach is needed for biodiversity monitoring that is linked to environmental data and covers all biogeographic regions. During a series of workshops and expert discussions, we identified nine requirements that we believe are necessary for developing and implementing such a global terrestrial species monitoring program. The program needs to design and implement an integrated information chain from monitoring to policy reporting, to create and implement minimal data standards and common monitoring protocols to be able to inform Essential Biodiversity Variables (EBVs), and to develop and optimize semantics and ontologies for data interoperability and modelling. In order to achieve this, the program needs to coordinate diverse but complementary local nodes and partnerships. In addition, capacities need to be built for technical tasks, and new monitoring technologies need to be integrated. Finally, a global monitoring program needs to facilitate and secure funding for the collection of long-term data and to detect and fill gaps in under-observed regions and taxa. The accomplishment of these nine requirements is essential in order to ensure data is comprehensive, to develop robust models, and to monitor biodiversity trends over large scales. A global terrestrial species monitoring program will enable researchers and policymakers to better understand the st

This report presents the European Grassland Butterfly Indicator, based on national Butterfly Monitoring Schemes (BMS) in 19 countries across Europe, most of them in the European Union. The indicator shows that since 1990 till 2011 butterfly populations have declined by almost 50 %, indicating a dramatic loss of grassland biodiversity. This also means the situation has not improved since the first version of the indicator published in 2005. Of the 17 species, 8 have declined in Europe, 2 have remained stable and 1 increased. For six species the trend is uncertain. The main driver behind the decline of grassland butterflies is the change in rural land use: agricultural intensification where the land is relatively flat and easy to cultivate, and abandonment in mountains and wet areas, mainly in eastern and southern Europe. Agricultural intensification leads to uniform, almost sterile grasslands for biodiversity. Grassland butterflies thus mainly survive in traditionally farmed low-input systems (High Nature Value (HNV) Farmland) as well as nature reserves, and on marginal land such as road verges and amenity areas. Abandonment is caused by socio-economic factors. When farming on low-productivity land brings only small incomes and there is little or no support from the Common Agricultural Policy (CAP), farmers give up their enterprises and the land is left unmanaged. The grassland quickly becomes tall and rank and is soon replaced by scrub and woodland.The EU Biodiversity Strategy recognises the poor conservation status of grasslands and of their characteristic butterflies. The actions set out in this Strategy need urgent implementation. Appropriate management is vital both for grasslands designated as Natura 2000 areas and on HNV farmland outside these areas. Financial support for biodiversity-friendly actions and programmes should also be further enhanced through the Common Agricultural Policy measures.Butterflies offer the possibility to be used as a structural headl

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This Editorial presents the focus, scope and policies of the inaugural issue of Nature Conservation, a new open access, peer-reviewed journal bridging natural sciences, social sciences and hands-on applications in conservation management. The journal covers all aspects of nature conservation and aims particularly at facilitating better interaction between scientists and practitioners. The journal will impose no restrictions on manuscript size or the use of colour. We will use an XML-based editorial workflow and several cutting-edge innovations in publishing and information dissemination. These include semantic mark-up of, and enhancements to published text, data, and extensive cross-linking within the journal and to external sources. We believe the journal will make an important contribution to better linking science and practice, offers rapid, peer-reviewed and flexible publication for authors and unrestricted access to content.

Without robust and unbiased systems for monitoring, changes in natural systems will remain enigmatic for policy makers, leaving them without a clear idea of the consequences of any environmental policies they might adopt. Generally, biodiversity-monitoring activities are not integrated or evaluated across any large geographic region. The EuMon project conducted the first large-scale evaluation of monitoring practices in Europe through an on-line questionnaire and is reporting on the results of this survey. In September 2007 the EuMon project had documented 395 monitoring schemes for species, which represents a total annual cost of about 4 million, involving more than 46,000 persons devoting over 148,000 person-days/year to biodiversity-monitoring activities. Here we focused on the analysis of variations of monitoring practices across a set of taxonomic groups (birds, amphibians and reptiles, mammals, butterflies, plants, and other insects) and across 5 European countries (France, Germany, Hungary, Lithuania, and Poland). Our results suggest that the overall sampling effort of a scheme is linked with the proportion of volunteers involved in that scheme. Because precision is a function of the number of monitored sites and the number of sites is maximized by volunteer involvement, our results do not support the common belief that volunteer-based schemes are too noisy to be informative. Just the opposite, we believe volunteer-based schemes provide relatively reliable data, with state-of-the-art survey designs or data-analysis methods, and consequently can yield unbiased results. Quality of data collected by volunteers is more likely determined by survey design, analytical methodology, and communication skills within the schemes rather than by volunteer involvement per se.

Citizen science, defined as participation of the general public in scientific research, could significantly help scientists to address biodiversity issues, through (i) monitoring the state of biodiversity, (ii) framing indicators which synthesise and communicate information on the state of biodiversity, (iii) building scenarios to evaluate the plausible consequences of different policies. A key asset of citizen science is that participating citizens disseminate the information they gain, thereby increasing the profile of issues being researched. We review further benefits associated with biodiversity monitoring, indicators and policy scenarios, envisioned as collaborative tools between scientists and citizens. Such collaboration promotes both the scientific adequacy and social legitimacy of these tools, so that they can meaningfully inform debates and decisions on public policy.

Halting the loss of biodiversity comes along with the need to quantify biodiversity composition and dynamics at large spatial and temporal scales. Highly standardized, international monitoring networks would be ideal, but they do not exist yet. If we are to assess changes in biodiversity now, combining output available from ongoing monitoring initiatives is the only option. However, integration of biodiversity information across schemes is still very poorly developed. In this paper, we outline practical issues to be considered when planning to combine existing monitoring information. First, we provide an overview of avenues for integration along the four dimensions that characterize a monitoring design: sample size, biological coverage, spatial coverage and temporal coverage. We also emphasize that complementarity in monitoring targets across schemes enables to describe complex processes of biodiversity dynamics, e.g. through relating species traits to the impacts of environmental changes. Second, we review some methods to overcome differences in designs among monitoring schemes, such as site selection, post-stratification and measurement error. Finally, we point out some commonly used statistical methods that are at hand for combining data or parameter estimates. We especially emphasize the possible levels of data integration (raw data, parameter estimates, or effect size estimates), and the largely under-exploited potential of meta-analysis methods and weighted analyses. This contribution aims to bolster the practice and use of integration of ongoing monitoring initiatives for biodiversity assessment.