Verlässliche Daten über unsere Lebensgrundlage
Species richness is the most widely used biodiversity index, but can be hard to measure. Many species remain undetected, hence raw species counts will often underestimate true species richness. In contrast, capture–recapture methods estimate true species richness and correct for imperfect and varying detectability.
Detectability is a crucial quantity that provides the link between a species count and true species richness. For insects, it has hardly ever been estimated, although this is required for the interpretation of species counts.
In the Swiss butterfly monitoring programme about 100 transect routes are surveyed seven times a year using a highly standardised protocol. In July 2003, control observers made two additional surveys on 38 transects. Data from these 38 quadrats were analysed to see whether currently available capture–recapture models can provide quadrat-specific estimates of species richness, and to estimate species detectability in relation to transect, observer, survey, region, and abundance.
Species richness over the entire season cannot be estimated using current capture–recapture methods. The species pool was open, preventing use of closed population models, and detectability varied by species, preventing use of current open population models. Assuming a closed species pool during two mid-season (July) surveys, a Jackknife capture–recapture method was used that accounts for heterogeneity to estimate mean detectability and species richness.
In every case, more species were present than were counted. Mean species detectability was 0.61 (SE 0.01) with significant differences between observers (range 0.37–0.83). Species-specific detection at time t + 1 was then modelled for those species seen at t for three mid-season surveys. Detectability averaged 0.50 (range 0.17–0.81) for individual species and 0.65, 0.44, and 0.42 for surveys. Abundant species were detected more easily, although this relationship explained only 5% of variation in species detectability.
These are important, although not entirely unexpected, results for species richness estimation of short-lived animals. Raw counts of species may be misleading species richness indicators unless many surveys are conducted. Monitoring programmes should be calibrated, i.e. the assumption of constant detectability over dimensions of interest needs to be tested. The development of capture–recapture or similar models that can cope with both open populations and heterogeneous species detectability to estimate species richness should be a research priority.
Kéry, M., & Plattner, M. (2007). Species richness estimation and determinants of species detectability in butterfly monitoring programmes. Ecological Entomology, 32(1), 53–61. https://doi.org/10.1111/j.1365-2311.2006.00841.x
Identification of spatial patterns of species diversity is a central problem in conservation biology, with the patterns having implications for the design of biodiversity monitoring programs. Nonetheless, there are few field data with which to examine whether variation in species richness represents consistent correlations among taxa in the richness of rare or common species, or the relative importance of common and rare species in establishing trends in species richness within taxa. We used field data on three higher taxa (birds, butterflies, vascular plants) to examine the correlation of species richness among taxa and the contribution of rare and common species to these correlations. We used graphical analysis to compare the contributions to spatial variation in species richness by widely-distributed (‘common’) and sparsely-distributed (‘rare’) species. The data came from the Swiss Biodiversity Monitoring Program, which is national in scope and based on a randomly located, regular sampling grid of 1 km2 cells, a scale relevant to real-world monitoring and management. We found that the correlation of species richness between groups of rare and common species varies among higher taxa, with butterflies exhibiting the highest levels of correlation. Species richness of common species is consistently positively correlated among these three taxa, but in no case exceeded 0.69. Spatial patterns of species richness are determined mainly by common species, in agreement with coarse resolution studies, but the contribution of rare species to variation in species richness varies within the study area in accordance with elevation. Our analyses suggest that spatial patterns in species richness can be described by sampling widely distributed species alone. Butterflies differ from the other two taxa in that the richness of red-listed species and other rare species is correlated with overall butterfly species richness. Monitoring of butterfly species richness may provide information on rare butterflies and on species richness of other taxa as well.
Pearman, P. B., & Weber, D. (2007). Common species determine richness patterns in biodiversity indicator taxa. Biological Conservation, 138(1–2), 109–119. https://doi.org/10.1016/j.biocon.2007.04.005
The use of surrogates to identify protected areas is a common practice in conservation biology. The use of top predators as surrogates has been criticized but recently a strong positive relationship was found between the presence of top predators and species diversity of several taxa. As mentioned by the authors, these striking results need to be assessed on a larger scale.
We used data from the Swiss Biodiversity Monitoring Programme and the Swiss breeding bird survey to analyse the use of raptor species as a surrogate for plant, butterfly and bird species richness. For each raptor species, we compared species richness in sites where a raptor species was recorded and compared these sites with the remaining sites in which the raptor species was not recorded. For comparison we conducted the same analyses using tits Parus spp. Tits are common prey species of some raptor species and were the most species-rich generalist genus in our data.
We found little justification for a focus on top predators when identifying conservation areas. For bird and plant species richness, raptors were reasonable surrogates for high species richness but no raptor species predicted sites with above-average butterfly species richness.
The presence of tit species performed equally as well as the presence of raptor species to predict sites with high species richness of birds and plants, and performed even better for predicting high butterfly species richness.
Synthesis and applications. Conservation planners using indicator species should be aware that relationships among higher taxa are complex and depend on the species group and the scale of analysis. As shown with the case of raptors, the usefulness of a biodiversity indicator can vary between adjacent areas even if the same species groups are analysed. We recommend the use of more than one indicator species from different taxonomic groups when identifying areas of high biodiversity.
Roth, T., & Weber, D. (2007). Top predators as indicators for species richness? Prey species are just as useful: Predators and biodiversity. Journal of Applied Ecology, 45(3), 987–991. https://doi.org/10.1111/j.1365-2664.2007.01435.x
We present a method that permits the retrospective assessment of frequency changes in species, based on the evaluation of specimens in biological collections. The method assumes that the increase and decrease in the frequency of a species is reflected in the number of collected specimens. A comparison of the specimen numbers from different time periods allows for an evaluation of the frequency changes of a particular species, provided that the specimen numbers are corrected for the general collecting activity of each time period. We used a reference data set consisting of 10 521 specimens of 85 species to reflect general collecting activity. For 42 species of bryophytes in Switzerland, we calculated the 'relative collecting activity', i.e. the number of specimens of an individual species as a percentage of the number of specimens from the reference data set. We examined changes in the relative collecting activity between the periods 1850-1939 and 1940-1999, using a permutation test. The calculated results were further assessed, taking all background information on each single species into account. In seven cases, the resulting assessments differed from the test results. According to the assessments, 16 species showed a decline and four had increased. The frequency of seven species was considered stable. For the remaining 15, mainly rare species, reliable assessments depend on further study of their former and actual frequencies. When species analysed were arranged into three classes of rare, medium and high frequency, the results showed that the rare and medium frequency species underwent significant decline, whereas the common species were stable. The fact that 12 species of medium or high frequency have most probably declined is of particular interest.
Hofmann, H., Urmi, E., Bisang, I., Müller, N., Küchler, M., & Schubiger, C. (2007). Retrospective assessment of frequency changes in Swiss bryophytes over the last two centuries. Lindbergia, 32, 18–32.
In der 69. Folge der Forschritte (Bäumler et al. 2005) wurden die ersten Daten 2001-2003 des Biodiversitäts-Monitoring Schweiz (BDM) mit dem Verbreitungsatlas der Schweizer Flora verglichen (Welten und Sutter 1982, Nachträge 1984, 1994). Die Erfassung der gesamten Schweiz (vgl. Messnetze in Abb. 1) ist beim BDM auf 5 Jahre angesetzt. Im vorliegenden Beitrag werden nun die mit dem vollständigen Datensatz 2001-2005 aktualisierten Resultate und Grafiken der Folge 69 erneut publiziert.
Latour, C., & Bäumler, B. (2007). Fortschritte in der Floristik der Schweizer Flora (Gefässpflanzen). 74. Folge: Aktualisierte Resultate (Daten 2001-2005) zum Vergleich des Verbreitungsatlas mit den ersten Daten 2001-2003 des Biodiversitäts-Monitoring Schweiz (69. Folge). Botanica Helvetica.
- How do local habitat management and landscape structure at different spatial scales affect fritillary butterfly distribution on fragmented wetlands?
- Modelling vascular plant diversity at the landscape scale using systematic samples.
- Spectral rarefaction: Linking ecological variability and plant species diversity.
- Hierarchical Bayes estimation of species richness and occupancy in spatially replicated surveys.
Sonderheft Hotspot
Das Hotspot Sonderheft zu 20 Jahren BDM zeigt, wer hinter den Daten steckt und beleuchtet aktuelle Entwicklungen der Biodiversität.
Publikationen
Sammlung aller veröffentlichten wissenschaftlichen Publikationen mit Daten des BDM: