Numerical ragweed pollen forecasts using different source maps: a comparison for France.

One of the key input parameters for numerical pollen forecasts is the distribution of pollen sources. Generally, three different methodologies exist to assemble such distribution maps: (1) plant inventories, (2) land use data in combination with annual pollen counts, and (3) ecological modeling. We have used six exemplary maps for all of these methodologies to study their applicability and usefulness in numerical pollen forecasts. The ragweed pollen season of 2012 in France has been simulated with the numerical weather prediction model COSMO-ART using each of the distribution maps in turn. The simulated pollen concentrations were statistically compared to measured values to derive a ranking of the maps with respect to their performance. Overall, approach (2) resulted in the best correspondence between observed and simulated pollen concentrations for the year 2012. It is shown that maps resulting from ecological modeling that does not include a sophisticated estimation of the plant density have a very low predictive skill. For inventory maps and the maps based on land use data and pollen counts, the results depend very much on the observational site. The use of pollen counts to calibrate the map enhances the performance of the model considerably

B1 Was the Ancestor B Chromosome Variant in the Western Mediterranean Area in the Grasshopper Eyprepocnemis plorans.

We analyzed the distribution of 2 repetitive DNAs, i.e. ribosomal DNA (rDNA) and a satellite DNA (satDNA), on the B chromosomes found in 17 natural populations of the grasshopper Eyprepocnemis plorans plorans sampled around the western Mediterranean region, including the Iberian Peninsula, Balearic Islands, Sicily, and Tunisia. Based on the amount of these repetitive DNAs, 4 types of B variants were found: B 1 , showing an equal or higher amount of rDNA than satDNA, and 3 other variants, B 2 , B 24 and B 5 , bearing a higher amount of satDNA than rDNA. The variants B 1 and B 2 varied in size among populations: B 1 was about half the size of the X chromosome in Balearic Islands, but two-thirds of the X in Iberian populations at Alicante, Murcia and Albacete provinces. Likewise, B 2 was about one-third the size of the X chromosome in populations from the Granada province but half the size of the X in the populations collected at Málaga province. The widespread geographical distribution of the B 1 variant makes it the best candidate for being the ancestor B chromosome in the whole western Mediterranean region

Comparison of the Electronic Structures and Energetics of Ferroelectric LiNbO3 and LiTaO3

This paper explains the origin of the ferroelectric instability in LiNbO3 and LiTaO3 and compares the electronic structures and energetics of the two materials.Comment: 31 pages, 11 Postscript figure

Too many candidates: Embedded covariate selection procedure for species distribution modelling with the covsel R package

1. Selecting the best subset of covariates out of a panel of many candidates is a key and highly influential stage of the species distribution modelling process. Yet, there is currently no commonly accepted and widely adopted standard approach by which to perform this selection. 2. We introduce a two-step “embedded” covariate selection procedure aimed at optimizing the predictive ability and parsimony of species distribution models fitted in a context of high-dimensional candidate covariate space. The procedure combines a collinearity-filtering algorithm (Step A) with three model-specific embedded regularization techniques (Step B), including generalized linear model with elastic net regularization, generalized additive model with null-space penalization, and guided regularized random forest. 3. We evaluated the embedded covariate selection procedure through an example application aimed at modelling the habitat suitability of 50 species in Switzerland from a suite of 123 candidate covariates. We demonstrated the ability of the embedded covariate selection procedure to provide significantly more accurate species distribution models as compared to models obtained with alternative procedures. Model performance was independent of the characteristics of the species data, such as the number of occurrence records or their spatial distribution across the study area. 4. We implemented and streamlined our embedded covariate selection procedure in the covsel R package, paving the way for a ready-to-use, automated, covariate selection tool that was missing in the field of species distribution modelling. All the information required for installing and running the covsel R package is openly available on the GitHub repository https://github.com/N-SDM/covsel

Projecting Untruncated Climate Change Effects on Species' Climate Suitability: Insights From an Alpine Country

Climate projections for continental Europe indicate drier summers, increased annual precipitation, and less snowy winters, which are expected to cause shifts in species' distributions. Yet, most regions/countries currently lack comprehensive climate‐driven biodiversity projections across taxonomic groups, challenging effective conservation efforts. To address this gap, our study evaluated the potential effects of climate change on the biodiversity of an alpine country of Europe, Switzerland. We used a state‐of‐the art species distribution modeling approach and species occurrence data that covered the climatic conditions encountered across the full species' ranges to help limiting niche truncation. We quantified the relationship between baseline climate and the spatial distribution of 7291 species from 12 main taxonomic groups and projected future climate suitability for three 30‐year periods and two greenhouse gas concentration scenarios (RCP4.5 and 8.5). Our results indicated important effects of projected climate changes on species' climate suitability, with responses varying by the taxonomic and conservation status group. The percentage of species facing major changes in climate suitability was higher under RCP8.5 (68%) compared to RCP4.5 (66%). By the end of the century, decreases in climate suitability were projected for 3000 species under RCP8.5 and 1758 species under RCP4.5. The most affected groups under RCP8.5 were molluscs, algae, and amphibians, while it was molluscs, birds, and vascular plants under RCP4.5. Spatially, by 2070–2099, we projected an overall decrease in climate suitability for 39% of the cells in the study area under RCP8.5 and 10% under RCP4.5, while projecting an increase for 50% of the cells under RCP8.5 and 73% under RCP4.5. The most consistent geographical shifts were upward, southward, and eastward. We found that the coverage of high climate suitability cells by protected areas was expected to increase. Our models and maps provide guidance for spatial conservation planning by pointing out future climate‐suitable areas for biodiversity

N‐SDM: a high‐performance computing pipeline for Nested Species Distribution Modelling

Predicting contemporary and future species distributions is relevant for science and decision making, yet the development of high-resolution spatial predictions for numerous taxonomic groups and regions is limited by the scalability of available modelling tools. Uniting species distribution modelling (SDM) techniques into one high-performance computing (HPC) pipeline, we developed N-SDM, an SDM platform aimed at delivering reproducible outputs for standard biodiversity assessments. N-SDM was built around a spatially-nested framework, intended at facilitating the combined use of species occurrence data retrieved from multiple sources and at various spatial scales. N-SDM allows combining two models fitted with species and covariate data retrieved from global to regional scales, which is useful for addressing the issue of spatial niche truncation. The set of state-of-the-art SDM features embodied in N-SDM includes a newly devised covariate selection procedure, five modelling algorithms, an algorithm-specific hyperparameter grid search, and the ensemble of small-models approach. N-SDM is designed to be run on HPC environments, allowing the parallel processing of thousands of species at the same time. All the information required for installing and running N-SDM is openly available on the GitHub repository https://github.com/N-SDM/N-SDM

N‐SDM: a high‐performance computing pipeline for Nested Species Distribution Modelling

Predicting contemporary and future species distributions is relevant for science and decision making, yet the development of high‐resolution spatial predictions for numerous taxonomic groups and regions is limited by the scalability of available modelling tools. Uniting species distribution modelling (SDM) techniques into one high‐performance computing (HPC) pipeline, we developedN‐SDM, an SDM platform aimed at delivering reproducible outputs for standard biodiversity assessments.N‐SDMwas built around a spatially‐nested framework, intended at facilitating the combined use of species occurrence data retrieved from multiple sources and at various spatial scales.N‐SDMallows combining two models fitted with species and covariate data retrieved from global to regional scales, which is useful for addressing the issue of spatial niche truncation. The set of state‐of‐the‐art SDM features embodied inN‐SDMincludes a newly devised covariate selection procedure, five modelling algorithms, an algorithm‐specific hyperparameter grid search, and the ensemble of small‐models approach.N‐SDMis designed to be run on HPC environments, allowing the parallel processing of thousands of species at the same time. All the information required for installing and runningN‐SDMis openly available on the GitHub repositoryhttps://github.com/N‐SDM/N‐SDM

High content of constitutive heterochromatin in two species of Pseudonannolene

Due to the fact that a considerable amount of constitutive heterochromatin has been commonly found in millipedes, this paper presents the characterization of the chromosomal complement, through C-banding technique, of two species of millipedes belonging to the genus Pseudonannolene. The species Pseudonannolene tocaiensis shows 2n=20, with five chromosomal pairs almost completely heterochromatic and the remaining pairs with pericentromeric C+ blocks. P. silvestris shows 2n=16, with a large heterochromatic portion in the first two pairs of autosomes, which presented the long arms totally C+.Depto. de Biologia, I.B. UNESP Câmpus de Rio Claro, Av 24 A- n. 1515, CEP 13 506 900, Rio Claro, Sao PauloDepto. de Biologia, I.B. UNESP Câmpus de Rio Claro, Av 24 A- n. 1515, CEP 13 506 900, Rio Claro, Sao Paul

Cytogenetic analysis of Astylus antis (Perty, 1830) (Coleoptera, Melyridae): Karyotype, heterochromatin and location of ribosomal genes

Cytogenetic analysis of Astylus antis using mitotic and meiotic cells was performed to characterize the haploid and diploid numbers, sex determination system, chromosome morphology, constitutive heterochromatin distribution pattern and chromosomes carrying nucleolus organizer regions (NORs). Analysis of spermatogonial metaphase cells revealed the diploid number 2n = 18, with mostly metacentric chromosomes. Metaphase I cells exhibited 2n = 8II+Xyp and a parachute configuration of the sex chromosomes. Spermatogonial metaphase cells submitted to C-banding showed the presence of small dots of constitutive heterochromatin in the centromeric regions of nearly all the autosomes and on the short arm of the X chromosome (Xp), as well as an additional band on one of the arms of pair 1. Mitotic cells submitted to double staining with base-specific fluorochromes (DAPI-CMA3 ) revealed no regions rich in A+T or G+C sequences. Analysis of spermatogonial mitotic cells after sequential Giemsa/AgNO 3 staining did not reveal any specific mark on the chromosomes. Meiotic metaphase I cells stained with silver nitrate revealed a strong impregnation associated to the sex chromosomes, and in situ hybridization with an 18S rDNA probe showed ribosomal cistrons in an autosomal bivalent