Diatom species richness in Swiss springs increases with habitat complexity and elevation

Understanding the drivers of species richness gradients is a central challenge of ecological and biodiversity research in freshwater science. Species richness along elevational gradients reveals a great variety of patterns. Here, we investigate elevational changes in species richness and turnover between microhabitats in near-natural spring habitats across Switzerland. Species richness was determined for 175 subsamples from 71 near-natural springs, and Poisson regression was applied between species richness and environmental predictors. Compositional turnover was calculated between the different microhabitats within single springs using the Jaccard index based on observed species and the Chao index based on estimated species numbers. In total, 539 diatom species were identified. Species richness increased monotonically with elevation. Habitat diversity and elevation explaining some of the species richness per site. The Jaccard index for the measured compositional turnover showed a mean similarity of 70% between microhabitats within springs, whereas the Chao index which accounts for sampling artefacts estimated a turnover of only 37%. Thus, the commonly applied method of counting 500 valves led to an undersampling of the rare species and might need to be reconsidered when assessing diatom biodiversity

Global climate-related predictors at kilometer resolution for the past and future

A multitude of physical and biological processes on which ecosystems and human societies depend are governed by the climate, and understanding how these processes are altered by climate change is central to mitigation efforts. We developed a set of climate-related variables at as yet unprecedented spatiotemporal detail as a basis for environmental and ecological analyses. We downscaled time series of near-surface relative humidity (hurs) and cloud area fraction (clt) under the consideration of orography and wind as well as near-surface wind speed (sfcWind) using the delta-change method. Combining these grids with mechanistically downscaled information on temperature, precipitation, and solar radiation, we then calculated vapor pressure deficit (vpd), surface downwelling shortwave radiation (rsds), potential evapotranspiration (pet), the climate moisture index (cmi), and site water balance (swb) at a monthly temporal and 30 arcsec spatial resolution globally from 1980 until 2018 (time-series variables). At the same spatial resolution, we further estimated climatological normals of frost change frequency (fcf), snow cover days (scd), potential net primary productivity (npp), growing degree days (gdd), and growing season characteristics for the periods 1981–2010, 2011–2040, 2041–2070, and 2071–2100, considering three shared socioeconomic pathways (SSP126, SSP370, SSP585) and five Earth system models (projected variables). Time-series variables showed high accuracy when validated against observations from meteorological stations and when compared to alternative products. Projected variables were also highly correlated with observations, although some variables showed notable biases, e.g., snow cover days. Together, the CHELSA-BIOCLIM+ dataset presented here (https://doi.org/10.16904/envidat.332, Brun et al., 2022) allows improvement to our understanding of patterns and processes that are governed by climate, including the impact of recent and future climate changes on the world's ecosystems and the associated services on societies.</p

Functional redundancy of non-volant small mammals increases in human-modified habitats

Aim: Humans are rapidly altering natural habitats across much of the globe. Here we compared 264 globally distributed communities in natural and human-modified habitats to detect changes in community richness and functional diversity with human influence. Location: Global. Taxon: Non-volant small mammals. Methods: We calculated differences in observed to potential species richness (ΔSR) and observed to potential functional diversity (ΔFD) to account for regional pool differences. Then we determined the prevalence of four distinct scenarios of richness and functional diversity differences between human-modified and natural habitats, and evaluated local and geographical variation in these differences. We obtained potential richness by calculating a probabilistic species pool and obtained potential functional diversity through the n-dimensional hypervolume based on pool composition. We tested for differences in average ΔSR and ΔFD between habitats, and determined the most common scenario of ΔSR and ΔFD in human-modified and natural habitats. Results: We found lower ΔSR in human-modified than natural habitats, but no difference in ΔFD. Low ΔSR and high ΔFD predominated in human-modified habitats, and high ΔSR and ΔFD in natural habitats. Low ΔSR and high ΔFD predominated in temperate forests, whereas high ΔSR and ΔFD in tropical forests and grasslands. Scenarios of low ΔSR and high ΔFD, and high ΔSR and low ΔFD, were most common in human-modified and natural habitats of temperate grasslands. Main conclusions: A larger richness in human-modified habitats does not result in larger functional diversity. Rather there seems to be an increase in functional redundancy because species which profit from human modification do not bring new functions into human-modified habitats. While greater richness is found in humanmodified habitats from temperate biomes, this is not the case in extremely biodiverse tropical biomes. Assuming a positive relationship between richness, functional traits and ecosystem function, greater richness in modified habitats may not yield greater function

CHELSA-W5E5: daily 1 km meteorological forcing data for climate impact studies

Current changes in the world's climate increasingly impact a wide variety of sectors globally, from agriculture and ecosystems to water and energy supply or human health. Many impacts of climate on these sectors happen at high spatio-temporal resolutions that are not covered by current global climate datasets. Here we present CHELSA-W5E5 (https://doi.org/10.48364/ISIMIP.836809.3, Karger et al., 2022): a climate forcing dataset at daily temporal resolution and 30 arcsec spatial resolution for air temperatures, precipitation rates, and downwelling shortwave solar radiation. This dataset is a spatially downscaled version of the 0.5∘ W5E5 dataset using the CHELSA V2 topographic downscaling algorithm. We show that the downscaling generally increases the accuracy of climate data by decreasing the bias and increasing the correlation with measurements from meteorological stations. Bias reductions are largest in topographically complex terrain. Limitations arise for minimum near-surface air temperatures in regions that are prone to cold-air pooling or at the upper extreme end of surface downwelling shortwave radiation. We further show that our topographically downscaled climate data compare well with the results of dynamical downscaling using the Weather Research and Forecasting (WRF) regional climate model, as time series from both sources are similarly well correlated to station observations. This is remarkable given the lower computational cost of the CHELSA V2 algorithm compared to WRF and similar models. Overall, we conclude that the downscaling can provide higher-resolution climate data with increased accuracy. Hence, the dataset will be of value for a wide range of climate change impact studies both at global level and for applications that cover more than one region and benefit from using a consistent dataset across these regions

Climatologies at high resolution for the earth's land surface areas

High resolution information on climatic conditions is essential to many applications in environmental and ecological sciences. Here we present the CHELSA Climatologies at high resolution for the earths land surface areas data of downscaled model output temperature and precipitation estimates of the ERA Interim climatic reanalysis to a high resolution of 30 arc seconds. The temperature algorithm is based on statistical downscaling of atmospheric temperatures. The precipitation algorithm incorporates orographic predictors including wind fields, valley exposition, and boundary layer height with a subsequent bias correction. The resulting data consist of a monthly temperature and precipitation climatology for the years 1979 to 2013. We compare the data derived from the CHELSA algorithm with other standard gridded products and station data from the Global Historical Climate Network. We compare the performance of the new climatologies in species distribution modelling and show that we can increase the accuracy of species range predictions. We further show that CHELSA climatological data has a similar accuracy as other products for temperature but that its predictions of precipitation patterns are better

Global patterns and drivers of phylogenetic structure in island floras

Islands are ideal for investigating processes that shape species assemblages because they are isolated &nbsp;and have discrete boundaries. Quantifying phylogenetic assemblage structure allows inferences in-situ speciation. Here, we link phylogenetic assemblage structure to island characteristics across 393 islands worldwide &nbsp;and 37,041 vascular plant species (representing angiosperms overall, palms and ferns). Physical and &nbsp;bioclimatic factors, especially those impeding colonization and promoting speciation, explained &nbsp;more &nbsp;variation &nbsp;in &nbsp;phylogenetic &nbsp;structure &nbsp;of &nbsp;angiosperms &nbsp;overall &nbsp;(49%) &nbsp;and &nbsp;palms &nbsp;(52%) &nbsp;than &nbsp;of &nbsp;ferns consistent with their dispersal- and speciation-related traits and climatic adaptations. Phylogenetic &nbsp;diversity was negatively related to isolation for palms, but unexpectedly it was positively related large-seeded, animal-dispersed palm family whereas colonization from biogeographically distinct in-situ among taxonomic groups on islands, which sheds light on the origin of insular plant diversity.</p

Postglacial species arrival and diversity buildup of northern ecosystems took millennia

What drives ecosystem buildup, diversity, and stability? We assess species arrival and ecosystem changes across 16 millennia by combining regional-scale plant sedimentary ancient DNA from Fennoscandia with near-complete DNA and trait databases. We show that postglacial arrival time varies within and between plant growth forms. Further, arrival times were mainly predicted by adaptation to temperature, disturbance, and light. Major break points in ecological trait diversity were seen between 13.9 and 10.8 calibrated thousand years before the present (cal ka BP), as well as break point in functional diversity at 12.0 cal ka BP, shifting from a state of ecosystem buildup to a state where most habitat types and biotic ecosystem components were in place. Trait and functional diversity stabilized around 8 cal ka BP, after which both remained stable, although changes in climate took place and species inflow continued. Our ecosystem reconstruction indicates a millennial-scale time phase of formation to reach stable and resilient levels of diversity and functioning.publishedVersio