Larger areas support more species. To test the application of this biogeographic principle to ponds, we consider the relationship between size and diversity for 80 ponds in Switzerland, using richness (number of species) and conservation value (score for all species present, according to their degree of rarity) of aquatic plants, molluscs (Gastropoda, Sphaeriidae), Coleoptera, Odonata (adults) and Amphibia. Pond size was found to be important only for Odonata and explained 31% of the variability of their species richness. Pond size showed only a feeble relationship with the species richness of all other groups, particularly the Coleoptera and Amphibia. The weakness of this relationship was also indicated by the low z-values obtained (< 0.13). The SLOSS analyses showed that a set of ponds of small size has more species and has a higher conservation value than a single large pond of the same total area. But we also show that large ponds harbour species missing in the smaller ponds. Finally, we conclude that in a global con- servation policy (protection, restoration, management), all size ranges of ponds should be promoted

ABSTRACT1. As ponds are now recognized as freshwater habitats clearly distinct from lakes and running waters, there is a need for standardized tools for assessing their ecological integrity and status, and particularly their biodiversity.2. A standardized method was developed for sampling and assessing the species richness of ponds. Experiences accumulated in previous studies, together with data gathered from 80 Swiss ponds, provided the basis of the proposed method.3. Five taxonomic groups were chosen as complementary representatives of pond inhabitants: aquatic plants, aquatic Gastropoda, aquatic Coleoptera, adult Odonata and Amphibia.4. To sample aquatic flora, quadrats are located along transects perpendicular to the longest axis of the pond. The number of quadrats is calculated from a relationship with pond area. A nonparametric estimator (Jackknife-1) is used to estimate the true species richness from the observed richness.5. Aquatic invertebrates (Gastropoda, Coleoptera) are collected with a hand net. Sampling is stratified within the dominant habitats. The number of samples is calculated from a relationship with pond area. As with the vegetation, the Jackknife-1 estimator is used to estimate the true species richness.6. The species richness of adult Odonata is assessed using a standardized field survey method combining observations from early and late summer. The species richness is corrected with an abundance-based estimator (Chao1). The species richness of Amphibia is obtained from an exhaustive inventory.7. For the assessment of biodiversity, species richness values derived from measurements are compared to values predicted for conditions that enable a high species richness. Generalized Additive Models are used to predict species richness from environmental predictors characterizing the pond. The ratio of measured richness to predicted richness allows the allocation of a quality status to each pond. Results are divided into five biological quality classes, as recommended in the EC Water Framework Directive (WFD).

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ABSTRACT1. The aim of this study was to identify the environmental variables correlated with biodiversity in alpine ponds.2. Twenty alpine ponds in Switzerland were chosen to examine the relationship between the species (or family) richness of five biological groups and a selection of eight environmental variables.3. Altitude, pH, conductivity, macrophyte presence, fish presence and trophic state, showed significant relationships with the diversity of at least one biological group. On the other hand, pond area and depth demonstrated no significant correlations with biodiversity.4. Most highlighted relationships between biodiversity and environmental variables were different from those seen in lowland ponds, reflecting the distinctive nature of alpine water bodies. The results of the study suggest that there is a need to establish specific biodiversity evaluation tools for alpine ponds, which differ from those already used for lowland ponds.

ABSTRACT1. Ponds are particularly rich habitats and play an essential role in the conservation of aquatic biodiversity. Therefore it is necessary to develop a specific method for evaluating their biological integrity, and particularly their water quality. Metrics have proved to be efficient for studies on running waters. Such an approach would be particularly useful for ponds and therefore needs to be tested.2. Eight metrics based on the richness of invertebrates and amphibians and 73 others derived from the biological/ecological trait categories linked to Coleoptera, Odonata and Gastropoda were tested for their potential as indicators of the trophic state of 94 ponds in Switzerland. The relationships between these metrics and the state of water eutrophication were explored.3. Four metrics based on richness responded to excessive nutrient levels in the colline vegetation belt. These were: aquatic Coleoptera species richness; the pooled species richness of aquatic Coleoptera, aquatic Gastropoda, adult Odonata and Amphibia (COGA); the family-level richness of macroinvertebrates and the family-level richness of the combined Megaloptera and Odonata groups (MO). At altitudes above 800 m (i.e. montane-subalpine and alpine vegetation belts), two to four other metrics were identified as pond water-quality indicators.4. Furthermore, many trait categories were sensitive to excessive nutrient levels. In the colline belt, 13 out of the 33 metrics derived from the biological/ecological traits responded to an increase in the trophic state (i.e. at least one metric for each of the three invertebrate groups tested). However, the patterns of the relationships are unclear and further investigations are required to identify and select the relevant metrics for an assessment of water quality.5. In conclusion, for the future assessment of pond quality, four metrics derived from richness could be taken into consideration. Nevertheless, further investigations are required to identify the biological/ecological traits that could be combined with these richness metrics.