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Species richness is the most widely used measure for the diversity of a biological community. Unfortunately, the number of species counted is usually a biased measure, as not all species present may be detected. Use of species counts as a proxy for true species richness requires the assumption of constant (over space and time) species detectability. This index assumption is hardly ever tested and, if violated, comparisons over time, space or other dimensions, for example different habitats, will be distorted. In monitoring programmes one therefore needs to know the proportion of species present that are detected and how this proportion is affected by external factors.

We used capture–recapture techniques to calibrate the Swiss breeding bird survey, where species richness is recorded annually in c. 270 1-km 2 quadrats during two to three visits and interest is focused on annual trends and regional comparisons. Hitherto, analysis has been restricted to species counts, while species detectability and its determinants are not known. We used the interpolated jackknife estimator to compute mean species detectability for 268 quadrats in 2001–03 and tested determinants of detectability related to space, time, observer, survey effort and biology.

Mean species detectability averaged 0·89 (SD 0·06, range 0·72–1·00), with no significant difference among years and significant, but small, regional differences. Observers differed, but surprisingly not in relation to their experience in a quadrat. Detectability was positively related to mean visit duration. Larger communities had a lower mean species detectability. A slight violation of population closure because of staggered arrival of migrants did not introduce any measurable bias into our results.

Synthesis and applications. Species detectability in the Swiss programme was high and varied little in relation to recognized sources of heterogeneity. Nevertheless, increased standardization should be considered for mean visit duration. While these results are pleasing for the Swiss programme and show that using counts as indices of species diversity need not always induce serious bias, conditions in other programmes, and in the future in the Swiss programme, may be quite different. Both in monitoring programmes and in ecological studies, as a way of risk minimization, species richness ought to be rigorously estimated whenever possible to avoid detection of spurious effects because of changes in species detectability.

Kéry, M., & Schmid, H. (2005). Estimating species richness: Calibrating a large avian monitoring programme: Species richness estimation. Journal of Applied Ecology, 43(1), 101–110. https://doi.org/10.1111/j.1365-2664.2005.01111.x

Switzerland carries out measurements of its biological diversity since 2001. In the Swiss Biodiversity Monitoring Programme (BDM) evenly-spread random plots from all over the country are sampled to draw conclusions about Switzerland as a whole. A central coordination office compiles data collection, analysis and publication. Besides biological knowledge professional skills in project management are needed to successfully run such a large monitoring programme. From a conceptional point of view the sampling concept of BDM meets the basic principles of general surveillance proposed for Europe. BDM provides baseline information that can be used to detect unanticipated consequences of the cultivation of GM plants. Depending on the precision the impacts of GM plants are to be addressed, BDM offers different possibilities to serve a general surveillance.

Bühler, C. (2006). Biodiversity Monitoring in Switzerland: What can we learn for general surveillance of GM crops? Journal Für Verbraucherschutz Und Lebensmittelsicherheit, 1(S1), 37–41. https://doi.org/10.1007/s00003-006-0067-5

Mit dieser ersten Folge der Beiträge zur bryofloristischen Erforschung der Schweiz soll eine alte Tradition wieder aufgenommen werden, nämlich die Publikation besonderer Moosfunde. In den Jahren 1892 bis 1929 wurden in den Berichten der Schweizerischen Botanischen Gesellschaft innerhalb der Serie Fortschritte der Schweizerischen Floristik regelmässig Listen mit Moosen publiziert.

Bergamini, A., Hofmann, H., Lüth, M., Müller, N., & Schnyder, N. (2006). Beiträge zur bryologischen Erforschung der Schweiz – Folge 1. Meylania 35: 31-37.

In order to monitor species diversity, surveying indicators in habitats has often been recommended as more cost efficient than assessing species directly. In this study data from the Swiss National Forest Inventory (NFI) and the Biodiversity Monitoring Program (BDM) were used to verify the correlation of species density for vascular plants, mosses, and molluscs with 58 variables of forest structure, site conditions and forest management. The analyses show that site factors, in particular the biogeographic regions, the altitude, slope and the soil acidity, explain 18 to 49% of the observed variance in species density, depending on the species group (taxon). Of all the factors influenced by management, only the availability of light (stand density) was found to play an important role primarily on vascular plants. In addition the density of molluscs is positively correlated to shrub cover. However, none of the regression models tested explains more than 54% of the variance of species density. Therefore, the authors conclude that the species richness of the species groups investigated can be assessed reliably only by direct survey. The analyses confirm that certain data assessed in forest inventories is ecologically very important and relevant for environmental policy.

Brändli, U.-B., Bühler, Ch., & Zangger, A. (2007). Waldindikatoren zur Artenvielfalt: Erkenntnisse aus LFI und BDM. Schweizerische Zeitschrift für das Forstwesen 158: 243-254.