Statistics Netherlands

About: Statistics Netherlands is a based out in . It is known for research contribution in the topics: Population & National accounts. The organization has 455 authors who have published 856 publications receiving 28840 citations. The organization is also known as: Centraal Bureau voor de Statistiek & CBS.

Global Biodiversity: Indicators of Recent Declines

Abstract: In 2002, world leaders committed, through the Convention on Biological Diversity, to achieve a significant reduction in the rate of biodiversity loss by 2010. We compiled 31 indicators to report on progress toward this target. Most indicators of the state of biodiversity (covering species' population trends, extinction risk, habitat extent and condition, and community composition) showed declines, with no significant recent reductions in rate, whereas indicators of pressures on biodiversity (including resource consumption, invasive alien species, nitrogen pollution, overexploitation, and climate change impacts) showed increases. Despite some local successes and increasing responses (including extent and biodiversity coverage of protected areas, sustainable forest management, policy responses to invasive alien species, and biodiversity-related aid), the rate of biodiversity loss does not appear to be slowing.

Developing indicators for European birds

Abstract: The global pledge to deliver ‘a significant reduction in the current rate of biodiversity loss by 2010’ is echoed in a number of regional and national level targets. There is broad consensus, however, that in the absence of conservation action, biodiversity will continue to be lost at a rate unprecedented in the recent era. Remarkably, we lack a basic system to measure progress towards these targets and, in particular, we lack standard measures of biodiversity and procedures to construct and assess summary statistics. Here, we develop a simple classification of biodiversity indicators to assist their development and clarify purpose. We use European birds, as example taxa, to show how robust indicators can be constructed and how they can be interpreted. We have developed statistical methods to calculate supranational, multi-species indices using population data from national annual breeding bird surveys in Europe. Skilled volunteers using standardized field methods undertake data collection where methods and survey designs differ slightly across countries. Survey plots tend to be widely distributed at a national level, covering many bird species and habitats with reasonable representation. National species' indices are calculated using log-linear regression, which allows for plot turnover. Supranational species' indices are constructed by combining the national species' indices weighted by national population sizes of each species. Supranational, multi-species indicators are calculated by averaging the resulting indices. We show that common farmland birds in Europe have declined steeply over the last two decades, whereas woodland birds have not. Evidence elsewhere shows that the main driver of farmland bird declines is increased agricultural intensification. We argue that the farmland bird indicator is a useful surrogate for trends in other elements of biodiversity in this habitat.

Selection Bias in Web Surveys

Abstract: Summary At first sight, web surveys seem to be an interesting and attractive means of data collection. They providesimple,cheap,andfastaccesstoalargegroupofpotentialrespondents.However,websurveys are not without methodological problems. Specific groups in the populations are under-represented because they have less access to Internet. Furthermore, recruitment of respondents is often based on self-selection. Both under-coverage and self-selection may lead to biased estimates. This paper describes these methodological problems. It also explores the effect of various correction techniques (adjustment weighting and use of reference surveys). This all leads to the question whether properly design web surveys can be used for data collection. The paper attempts to answer this question. It concludes that under-coverage problems may solve itself in the future, but that self-selection leads to unreliable survey outcomes.