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The on-going Biodiversity Monitoring in Switzerland Programme (BDM) has monitored vascular-plant species richness since 2001. This long-term programme focuses on two indicators at different spatial scales. First, the local diversity indicator monitors changes of species richness within habitats or types of land use (within-habitat diversity). Second, the landscape diversity indicator is utilized to describe landscape diversity (i.e., within-habitat mosaic diversity). Here we examine if the reproducibility of the BDM methods is sufficiently precise to detect future changes in species richness. We demonstrate that systematic methodical errors are negligible. Random errors that make changes more difficult to detect are also small. We calculate the Minimum Detectable Difference (MDD) for selected BDM strata using the variance of measured values. Then we deduce the MDD values for paired samples using data from grasslands and forests in the Canton Argovia. With 2.4 and 1.6 species they are promisingly precise. We develop a simple scenario for possible changes in species richness and show that they surpass the deduced MDD values by a factor four to six. We conclude that the BDM methods are appropriate for detecting future changes in species richness.

Plattner, M., Birrer, S., & Weber, D. (2004). Data quality in monitoring plant species richness in Switzerland. Community Ecology, 5(1), 135–143. https://doi.org/10.1556/ComEc.5.2004.1.13

Switzerland’s governmental ‘Biodiversity Monitoring’ program is designed to produce factual information on the dynamics of biodiversity within the country for governmental agencies, politicians, and the general public. Monitoring a complex issue like biodiversity in order to give relevant and accurate messages to the general public and politicians within a politically relevant timescale and at moderate cost means focusing on few elements. Because relevant human impacts on biodiversity operate differently at different spatial scales, we need at least three different indicators to observe changes over time in local (‘within-habitat’), landscape (‘habitat-mosaic’), and macro-scale (‘regional’) diversity. To keep things as simple as possible, we use species richness as an indicator for all three levels of diversity, just defining three different spatial scales (10 m² , 1 km² , regions, respectively). Each indicator is based on a number of taxonomic groups which have been selected mainly on the basis of costs and the availability of appropriate methods.

Weber, D., Hintermann, U., & Zangger, A. (2004). Scale and trends in species richness: Considerations for monitoring biological diversity for political purposes: Monitoring biological diversity. Global Ecology and Biogeography, 13(2), 97–104. https://doi.org/10.1111/j.1466-882X.2004.00078.x

As part of the Biodiversity Monitoring Switzerland (BDM), comprehensive records of vascular plant species are made along 2.5 km transects and on 10 m² plots distributed regularly over the entire surface of Switzerland (www.biodiversitymonitoring.ch). Here we analyse data from 2001-2003 for 275 transects and 773 plots (70 287 floristic records). A comparison with the distribution atlas of vascular plants (based on data from 1982-1994) shows that 3 481 records of indigenous taxa from the BDM were new, i.e. species that had not been found in the corresponding mapping unit previously. Alien species (mostly of non-European origin) represented 2.11% of the 2.5-km transect records and 1.01% of the 10-m2 plot records. Red list species (critically endangered, endangered or vulnerable) represented 0.26% of the transect records and 0.06% of the plot records. These percentages are low, given that in 2002, the Swiss flora included 17.5% of alien species and 31.5% of red list species. In accordance with its purpose and methodology, the BDM mainly shows the distribution of widespread species, whereas other monitoring approaches are needed for rare species.

Bäumler, B.; Moser D.M.; Gygagx, A.; Latour, C.; Wyler, N. (2005). Fortschritte in der Floristik der Schweizer Flora (Gefässpflanzen). 69. Folge (Vergleiche des Verbreitungsatlas mit den ersten Daten 2001-2003 des Biodiversitätsmonitoring Schweiz). Botanica Helvetica 115: 83-93.

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