Midpoint attractors and species richness: Modelling the interaction between environmental drivers and geometric constraints

We introduce a novel framework for conceptualising, quantifying and unifying discordant patterns of species richness along geographical gradients. While not itself explicitly mechanistic, this approach offers a path towards understanding mechanisms. In this study, we focused on the diverse patterns of species richness on mountainsides. We conjectured that elevational range midpoints of species may be drawn towards a single midpoint attractor – a unimodal gradient of environmental favourability. The midpoint attractor interacts with geometric constraints imposed by sea level and the mountaintop to produce taxon‐specific patterns of species richness. We developed a Bayesian simulation model to estimate the location and strength of the midpoint attractor from species occurrence data sampled along mountainsides. We also constructed midpoint predictor models to test whether environmental variables could directly account for the observed patterns of species range midpoints. We challenged these models with 16 elevational data sets, comprising 4500 species of insects, vertebrates and plants. The midpoint predictor models generally failed to predict the pattern of species midpoints. In contrast, the midpoint attractor model closely reproduced empirical spatial patterns of species richness and range midpoints. Gradients of environmental favourability, subject to geometric constraints, may parsimoniously account for elevational and other patterns of species richness.     

Demographic buffering and compensatory recruitment promotes the persistence of disease in a wildlife population

Demographic buffering allows populations to persist by compensating for fluctuations in vital rates, including disease‐induced mortality. Using long‐term data on a badger (Meles meles Linnaeus, 1758) population naturally infected with Mycobacterium bovis, we built an integrated population model to quantify impacts of disease, density and environmental drivers on survival and recruitment. Badgers exhibit a slow life‐history strategy, having high rates of adult survival with low variance, and low but variable rates of recruitment. Recruitment exhibited strong negative density‐dependence, but was not influenced by disease, while adult survival was density independent but declined with increasing prevalence of diseased individuals. Given that reproductive success is not depressed by disease prevalence, density‐dependent recruitment of cubs is likely to compensate for disease‐induced mortality. This combination of slow life history and compensatory recruitment promotes the persistence of a naturally infected badger population and helps to explain the badger's role as a persistent reservoir of M. bovis.     

Interspecific networks in ground beetle (Coleoptera: Carabidae) assemblages

Although changes to interspecific relationships can significantly alter the composition of insect assemblages, they are often ignored when assessing impacts of environmental change. Long-term ground beetle data were used in this study to analyse ecological networks from three habitats at two sites in Scotland. A Bayesian Network inference algorithm was used to reveal interspecific relationships. The significance and strength of relationships between species (nodes) were estimated along with other network properties. Links were identified as positive relationships if co-occurrences of beetles correlated positively, and as negatives relationships if there was a negative correlation between the occurrences of the species. Most of the species had few links and only 10% of the nodes were connected with several links. Calathus fuscipes, a common carabid in the samples, was the most connected, with nine links to other species. More interspecific relationships were found to be positive than negative, with 48 and 23 links, respectively. The modular structure of the network was assessed and eight separate sub-networks were found. Habitat preferences of the species were clearly represented in the structure of the sets of those five sub-networks containing more than one species and were in line with the findings of the indicator species analysis. In our study, we showed that generated Bayesian networks can model interspecific relationships between carabid species. Due to the relative ease of the collection of field data and the high information content of the results, this method could be incorporated into everyday ecological analysis.     

Home range size of adult Indo‐Pacific bottlenose dolphins (Tursiops aduncus) in a coastal and estuarine system is habitat and sex‐specific

This study examined sex‐specific differences in home range size of adult Indo‐Pacific bottlenose dolphins off Bunbury, Western Australia. We applied a new kernel density estimation approach that accounted for physical barriers to movements. A Bayesian mixture model was developed to estimate a sex effect in home range size with latent group partitioning constrained by association data. A post hoc analysis investigated group partitioning relating to the proportion of time spent in open vs. sheltered waters. From 2007 to 2013, photographic‐identification data were collected along boat‐based systematic transect lines (n = 586). Analyses focused on adult dolphins of known sex (sighted ≥ 30 times; n = 22 males and 34 females). The 95% utilization distributions of males varied between 27 and 187 km² (; 94.8 ± 48.15) and for females between 20 and 133 km² (65.6 ± 30.9). The mixture model indicated a 99% probability that males had larger home ranges than females. Dolphins mostly sighted in open waters had larger home ranges than those in sheltered waters. Home ranges of dolphins sighted in sheltered waters overlapped with areas of highest human activity. We suggest that sex differences in home ranges are driven by male mating strategies, and home range size differences between habitats may be influenced by prey availability and predation risk.     

Circulating serum vitamin D levels and total body bone mineral density: A Mendelian randomization study

Until recently, randomized controlled trials have not demonstrated convincing evidence that vitamin D, or vitamin D in combination with calcium supplementation could improve bone mineral density (BMD), osteoporosis and fracture. It remains unclear whether vitamin D levels are causally associated with total body BMD. Here, we performed a Mendelian randomization study to investigate the association of vitamin D levels with total body BMD using a large‐scale vitamin D genome‐wide association study (GWAS) dataset (including 79 366 individuals) and a large‐scale total body BMD GWAS dataset (including 66,628 individuals). We selected three Mendelian randomization methods including inverse‐variance weighted meta‐analysis (IVW), weighted median regression and MR‐Egger regression. All these three methods did not show statistically significant association of genetically increased vitamin D levels with total body BMD. Importantly, our findings are consistent with recent randomized clinical trials and Mendelian randomization study. In summary, we provide genetic evidence that increased vitamin D levels could not improve BMD in the general population. Hence, vitamin D supplementation alone may not be associated with reduced fracture incidence among community‐dwelling adults without known vitamin D deficiency, osteoporosis, or prior fracture.     

GPA: A Microbial Genetic Polymorphisms Assignments Tool in Metagenomic Analysis by Bayesian Estimation

Identifying antimicrobial resistant(AMR) bacteria in metagenomics samples is essential for public health and food safety. Next-generation sequencing(NGS) technology has provided a powerful tool in identifying the genetic variation and constructing the correlations between genotype and phenotype in humans and other species. However, for complex bacterial samples, there lacks a powerful bioinformatic tool to identify genetic polymorphisms or copy number variations(CNVs) for given genes. Here we provide a Bayesian framework for genotype estimation for mixtures of multiple bacteria, named as Genetic Polymorphisms Assignments(GPA). Simulation results showed that GPA has reduced the false discovery rate(FDR) and mean absolute error(MAE) in CNV and single nucleotide variant(SNV) identification. This framework was validated by whole-genome sequencing and Pool-seq data from Klebsiella pneumoniae with multiple bacteria mixture models, and showed the high accuracy in the allele fraction detections of CNVs and SNVs in AMR genes between two populations. The quantitative study on the changes of AMR genes fraction between two samples showed a good consistency with the AMR pattern observed in the individual strains. Also, the framework together with the genome annotation and population comparison tools has been integrated into an application, which could provide a complete solution for AMR gene identification and quantification in unculturable clinical samples. The GPA package is available at https://github.com/IID-DTH/GPA-package.     

Genetic divergence of Platycerus hongwonpyoi (Coleoptera: Lucanidae) in South Korea

We examined the genetic divergence of Platycerus hongwonpyoi Imura & Choe, 1989 in South Korea using the nuclear wingless (Wg) gene, internal transcribed spacer (ITS) region and mitochondrial cytochrome oxidase subunit I (COI) gene. We found no variation in Wg or ITS. Based on COI, P. hongwonpyoi was split into four well defined and one weakly supported clades, which were inferred to have diverged 2.11–1.33 Ma. The Platycerus hongwonpyoi population size seems to have decreased during the past several tens of thousands of years. The divergence times of major clades of P. hongwonpyoi were comparable with those involved in the speciation of certain Japanese species. Frequent overlapping of different clades at the same sites suggests the occurrence of secondary gene flow following differentiation in South Korea. In conclusion, the genus Platycerus underwent strikingly different divergence patterns in South Korea compared with Japan according to the disparate topographies of these two geographical areas.     

Spatiotemporally explicit demographic modelling supports a joint effect of historical barriers to dispersal and contemporary landscape composition on structuring genomic variation in a red‐listed grasshopper

Inferring the processes underlying spatial patterns of genomic variation is fundamental to understand how organisms interact with landscape heterogeneity and to identify the factors determining species distributional shifts. Here, we use genomic data (restriction site‐associated DNA sequencing) to test biologically informed models representing historical and contemporary demographic scenarios of population connectivity for the Iberian cross‐backed grasshopper Dociostaurus hispanicus, a species with a narrow distribution that currently forms highly fragmented populations. All models incorporated biological aspects of the focal taxon that could hypothetically impact its geographical patterns of genomic variation, including (a) spatial configuration of impassable barriers to dispersal defined by topographic landscapes not occupied by the species; (b) distributional shifts resulting from the interaction between the species bioclimatic envelope and Pleistocene glacial cycles; and (c) contemporary distribution of suitable habitats after extensive land clearing for agriculture. Spatiotemporally explicit simulations under different scenarios considering these aspects and statistical evaluation of competing models within an Approximate Bayesian Computation framework supported spatial configuration of topographic barriers to dispersal and human‐driven habitat fragmentation as the main factors explaining the geographical distribution of genomic variation in the species, with no apparent impact of hypothetical distributional shifts linked to Pleistocene climatic oscillations. Collectively, this study supports that both historical (i.e., topographic barriers) and contemporary (i.e., anthropogenic habitat fragmentation) aspects of landscape composition have shaped major axes of genomic variation in the studied species and emphasizes the potential of model‐based approaches to gain insights into the temporal scale at which different processes impact the demography of natural populations.