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Soil degradation can have an impact on the soil microbiota, but its specific effects on soil fungal communities are poorly understood. In this work, we studied the impact of soil degradation on the richness and diversity of communities of soil fungi, including three different degrees of degradation in Germany and Panama. Soil fungi were isolated monthly using the soil-sprinkling method for 8 months in Germany and 3 months in Panama, and characterized by morphological and molecular data. Soil physico-chemical properties were measured and correlated with the observed values of fungal diversity. We isolated a total of 71 fungal species, 47 from Germany, and 32 from Panama. Soil properties were not associated with fungal richness, diversity, or composition in soils, with the exception of soil compaction in Germany. The geographic location was a strong determinant of the soil fungal species composition although in both countries there was dominance by members of the orders Eurotiales and Hypocreales. In conclusion, the results of this work do not show any evident influence of soil degradation on communities of soil fungi in Germany or Panama.
Aim: Predicting future changes in species richness in response to climate change is one of the key challenges in biogeography and conservation ecology. Stacked species distribution models (S‐SDMs) are a commonly used tool to predict current and future species richness. Macroecological models (MEMs), regression models with species richness as response variable, are a less computationally intensive alternative to S‐SDMs. Here, we aim to compare the results of two model types (S‐SDMS and MEMs), for the first time for more than 14,000 species across multiple taxa globally, and to trace the uncertainty in future predictions back to the input data and modelling approach used.
Location: Global land, excluding Antarctica.
Taxon: Amphibians, birds and mammals.
Methods: We fitted S‐SDMs and MEMs using a consistent set of bioclimatic variables and model algorithms and conducted species richness predictions under current and future conditions. For the latter, we used four general circulation models (GCMs) under two representative concentration pathways (RCP2.6 and RCP6.0). Predicted species richness was compared between S‐SDMs and MEMs and for current conditions also to extent‐of‐occurrence (EOO) species richness patterns. For future predictions, we quantified the variance in predicted species richness patterns explained by the choice of model type, model algorithm and GCM using hierarchical cluster analysis and variance partitioning.
Results: Under current conditions, species richness predictions from MEMs and S‐SDMs were strongly correlated with EOO‐based species richness. However, both model types over‐predicted areas with low and under‐predicted areas with high species richness. Outputs from MEMs and S‐SDMs were also highly correlated among each other under current and future conditions. The variance between future predictions was mostly explained by model type.
Main conclusions: Both model types were able to reproduce EOO‐based patterns in global terrestrial vertebrate richness, but produce less collinear predictions of future species richness. Model type by far contributes to most of the variation in the different future species richness predictions, indicating that the two model types should not be used interchangeably. Nevertheless, both model types have their justification, as MEMs can also include species with a restricted range, whereas S‐SDMs are useful for looking at potential species‐specific responses.
Aim: To provide distribution information and preliminary conservation assessments for all species of the pineapple family (Bromeliaceae), one of the most diverse and ecologically important plant groups of the American tropics—a global biodiversity hotspot. Furthermore, we aim to analyse patterns of diversity, endemism and the conservation status of the Bromeliaceae on the continental level in the light of their evolutionary history.
Location: The Americas.
Methods: We compiled a dataset of occurrence records for 3,272 bromeliad species (93.4% of the family) and modelled their geographic distribution using either climate‐based species distribution models, convex hulls or geographic buffers dependent on the number of occurrences available. We then combined this data with information on taxonomy and used the ConR software for a preliminary assessment of the conservation status of all species following Criterion B of the International Union for the Conservation of Nature (IUCN).
Results: Our results stress the Atlantic Forest in eastern Brazil, the Andean slopes, Central America and the Guiana Highlands as centres of bromeliad diversity and endemism. Phylogenetically ancient subfamilies of bromeliads are centred in the Guiana highlands whereas the large radiations of the group spread across different habitats and large geographic area. A total of 81% of the evaluated bromeliad species are Possibly Threatened with extinction. We provide range polygons for 3,272 species, as well as newly georeferenced point localities for 911 species in the novel “bromeliad” r package, together with functions to generate diversity maps for individual taxonomic or functional groups.
Main conclusions: Diversity centres of the Bromeliaceae agreed with macroecological patterns of other plant and animal groups, but show some particular patterns related to the evolutionary origin of the family, especially ancient dispersal corridors. A staggering 2/3rds of Bromeliaceae species might be threatened with extinction, especially so in tropical rain forests, raising concerns about the conservation of the family and bromeliad‐dependent animal species.