As human population size increases and cities become denser, several urban-related selection pressures increasingly affect species composition in both terrestrial and aquatic habitats. Yet, it is not well known whether and how urbanization influences other facets of biodiversity, such as the functional and evolutionary composition of communities, and at what spatial scale urbanization acts. Here we used a hierarchical sampling design in which urbanization levels were quantified at seven spatial scales (ranging from 50 to 3200 m radii). We found that urbanization gradients are associated with a strong shift in cladoceran zooplankton species traits, which in turn affected phylogenetic composition of the entire metacommunity, but only when considering urbanization at the smallest spatial scale (50 m radius). Specifically, small cladoceran species dominated in more urbanized ponds whereas large-bodied, strong competitors prevailed in less urbanized systems. We also show that trait and phylogenetic metrics strongly increase the amount of variation in b-diversity that can be explained by degree of urbanization, environmental and spatial factors. This suggests that the mechanisms shaping b-diversity in our study system are mediated by traits and phylogenetic relatedness rather than species identities. Our study indicates that accounting for traits and phylogeny in metacommunity analyses helps to explain seemingly idiosyncratic patterns of variation in zooplankton species composition along urbanization gradients. The fact that urbanization acts only at the smallest spatial scale suggests that correctly managing environmental conditions locally has the power to counteract the effects of urbanization on biodiversity patterns. The multidimensional approach we applied here can be applied to other systems and organism groups and seems to be key in understanding how overall biodiversity changes in response to anthropogenic pressures and how this scales up to affect ecosystem functioning.

A resampling of 38 small farmland ponds in Belgium after 10 years revealed a high temporal species turnover for both phytoplankton and zooplankton communities, associated with substantial changes in abiotic factors, especially a reduction in total phosphorus concentration. Across ponds, phytoplankton biomass decreased while evenness and richness increased between the samplings in 2003 and 2013. By contrast, the zooplankton assemblage was characterised by lower biomass, richness and evenness in 2013. Ponds experiencing larger environmental change showed stronger changes in phytoplankton richness and evenness. Resource use efficiency (RUE) of zooplankton increased with greater environmental change and zooplankton evenness, which points to a switch towards species with higher RUE or greater variety in food sources in higher trophic levels. As ponds are important habitats for freshwater biodiversity and ecosystems services, the strong but predictable species turnover and the opposing effects of environmental change on different trophic levels need to be embedded in conservation and management plans.

Hatching rates and the timing of diapause termination are traits of high relevance in ecology and evolution of diapausing organisms. The analysis of hatching from dormant stages of planktonic organisms is an active area of research, which has been extensively studied in the context of phenology adjustment over latitude. Research on populations from temporary ponds has revealed temporal hatching profiles consisting of various hatching peaks, which is considered a risk‐spreading strategy. Studies on outstanding scientific questions such as the evolution of risk‐spreading strategies, the importance of genetic variation in hatching in an eco‐evolutionary context, and the genomic underpinning of hatching phenotypes all require very large sample sizes. We therefore developed a high throughput approach for the assessment of hatching rates and temporal hatching profiles of resting stages from crustacean zooplankton. Our method consists in the photographic monitoring of resting stages hatching assays and the detection of hatchlings using free software for the automation of biological image analysis. We compared the performance of our new method with data obtained by traditional visual assessment of hatching. Our results indicate that our approach is highly accurate (>95%) and raises efficiency by a factor of 10 compared to non‐automated visual assessment. Our new high throughput approach therefore allows to upscale the analysis of temporal hatching profiles and hatching success to sample sizes that will enable large‐scale genomic studies or massive phenotyping and monitoring of these highly relevant traits in the future.

No abstract

No abstract