Spatial prediction of species’ distributions from occurrence-only records: combining point pattern analysis, ENFA and regression-kriging

A computational framework to map species’ distributions (realized density) using occurrence-only data and environmental predictors is presented and illustrated using a textbook example and two case studies: distribution of root vole (Microtes oeconomus) in the Netherlands, and distribution of white-tailed eagle nests (Haliaeetus albicilla) in Croatia. The framework combines strengths of point pattern analysis (kernel smoothing), Ecological Niche Factor Analysis (ENFA) and geostatistics (logistic regression-kriging), as implemented in the spatstat, adehabitat and gstat packages of the R environment for statistical computing. A procedure to generate pseudo-absences is proposed. It uses Habitat Suitability Index (HSI, derived through ENFA) and distance from observations as weight maps to allocate pseudo-absence points. This design ensures that the simulated pseudo-absences fall further away from the occurrence points in both feature and geographical spaces. The simulated pseudo-absences can then be combined with occurrence locations and used to build regression-kriging prediction models. The output of prediction are either probabilitiesy of species’ occurrence or density measures. Addition of the pseudo-absence locations has proven effective — the adjusted R-square increased from 0.71 to 0.80 for root vole (562 records), and from 0.69 to 0.83 for white-tailed eagle (135 records) respectively; pseudo-absences improve spreading of the points in feature space and ensure consistent mapping over the whole area of interest. Results of cross validation (leave-one-out method) for these two species showed that the model explains 98% of the total variability in the density values for the root vole, and 94% of the total variability for the white-tailed eagle. The framework could be further extended to Generalized multivariate Linear Geostatistical Models and spatial prediction of multiple species. A copy of the R script and step-by-step instructions to run such analysis are available via contact author’s website

Characterization of S-layer proteins of potential probiotic starter culture Lactobacillus brevis SF9B isolated from sauerkraut

Abstract S-layers represent the simplest biological membranes developed during the evolution and are one of the most abundant biopolymers on Earth. Current fundamental and applied research aim to reveal the chemical structure, morphogenesis and function of S-layer proteins (Slps). This is the first paper that describes the Slps of certain Lactobacillus brevis strain isolated from sauerkraut. The whole genome sequence (WGS) analysis of the L. brevis SF9B strain uncovered three genes encoding the putative Slps, but merely one, identified as similar to the SlpB of L. brevis ATCC 14869, was expressed. Slp-expressing SF9B cells exhibited increased survival in simulated gastrointestinal (GI) conditions and during freeze-drying. Their survival in stress conditions was additionally enhanced by microencapsulation, especially when using alginate with gelatine as a matrix. Thus prepared cells were subjected to simulated GI conditions and their mortality was only 0.28 ± 0.45 log CFU/mL. Furthermore, a correlation between the high surface hydrophobicity and the remarkable aggregative capacity of SF9B strain was established. The results indicate a prominent role of Slps in adhesion to mucin, extracellular matrix (ECM) proteins, and particularly to Caco-2 cells, where the removal of Slps utterly abolished the adhesiveness of SF9B cells for 7.78 ± 0.25 log CFU/mL.Peer reviewe

From Data to Software to Science with the Rubin Observatory LSST

The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) dataset will dramatically alter our understanding of the Universe, from the origins of the Solar System to the nature of dark matter and dark energy. Much of this research will depend on the existence of robust, tested, and scalable algorithms, software, and services. Identifying and developing such tools ahead of time has the potential to significantly accelerate the delivery of early science from LSST. Developing these collaboratively, and making them broadly available, can enable more inclusive and equitable collaboration on LSST science. To facilitate such opportunities, a community workshop entitled "From Data to Software to Science with the Rubin Observatory LSST" was organized by the LSST Interdisciplinary Network for Collaboration and Computing (LINCC) and partners, and held at the Flatiron Institute in New York, March 28-30th 2022. The workshop included over 50 in-person attendees invited from over 300 applications. It identified seven key software areas of need: (i) scalable cross-matching and distributed joining of catalogs, (ii) robust photometric redshift determination, (iii) software for determination of selection functions, (iv) frameworks for scalable time-series analyses, (v) services for image access and reprocessing at scale, (vi) object image access (cutouts) and analysis at scale, and (vii) scalable job execution systems. This white paper summarizes the discussions of this workshop. It considers the motivating science use cases, identified cross-cutting algorithms, software, and services, their high-level technical specifications, and the principles of inclusive collaborations needed to develop them. We provide it as a useful roadmap of needs, as well as to spur action and collaboration between groups and individuals looking to develop reusable software for early LSST science.Comment: White paper from "From Data to Software to Science with the Rubin Observatory LSST" worksho

From Data to Software to Science with the Rubin Observatory LSST

editorial reviewedThe Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) dataset will dramatically alter our understanding of the Universe, from the origins of the Solar System to the nature of dark matter and dark energy. Much of this research will depend on the existence of robust, tested, and scalable algorithms, software, and services. Identifying and developing such tools ahead of time has the potential to significantly accelerate the delivery of early science from LSST. Developing these collaboratively, and making them broadly available, can enable more inclusive and equitable collaboration on LSST science. To facilitate such opportunities, a community workshop entitled "From Data to Software to Science with the Rubin Observatory LSST" was organized by the LSST Interdisciplinary Network for Collaboration and Computing (LINCC) and partners, and held at the Flatiron Institute in New York, March 28-30th 2022. The workshop included over 50 in-person attendees invited from over 300 applications. It identified seven key software areas of need: (i) scalable cross-matching and distributed joining of catalogs, (ii) robust photometric redshift determination, (iii) software for determination of selection functions, (iv) frameworks for scalable time-series analyses, (v) services for image access and reprocessing at scale, (vi) object image access (cutouts) and analysis at scale, and (vii) scalable job execution systems. This white paper summarizes the discussions of this workshop. It considers the motivating science use cases, identified cross-cutting algorithms, software, and services, their high-level technical specifications, and the principles of inclusive collaborations needed to develop them. We provide it as a useful roadmap of needs, as well as to spur action and collaboration between groups and individuals looking to develop reusable software for early LSST science

Diet composition of the golden jackal (Canis aureus L.) on the Pelješac Peninsula, Dalmatia, Croatia

Background and Purpose: No previous field investigations have been conducted on the biology and ecology of the native population of golden jackals (Canis aureus L.) from Dalmatia. The object of this study was to determine the feeding habits of this poorly studied population. Materials and Methods: The diet composition of golden jackals from Dalmatia was examined by scat analysis. From winter 1995 to spring 1997, field visits were made every season to the golden jackal habitat on the Pelješac Peninsula in Dalmatia, Croatia and scats of golden jackals were collected (n=130). Scats were washed out, dried and sorted. Classification of components was made under appropriate magnification. Conclusions: Both animal and plant components were found. Scat included from one to four components. The highest frequency was found for mammals (50.3%) followed by fruit seeds and vegetables (34.1%), insects (29.5%), birds (including eggs; 24.8%), artificial materials (24%) and branches, leaves and grass (24%). In scats containing mammal remains, the highest incidence was for large mammals (unidentified large mammals of the order Artiodactyla and Lagomorpha). Small mammals were found but in a negligible frequency. The most important fruits for jackals are Ficus carica L. (14%), Vitis vinifera L. (14%) and Juniperus oxicedrus L. (4.6%). The most important orders of insects are Orthoptera (16%), Coleoptera (12%) and Dyctioptera (3%), and for birds order Charadriiformes (6%). The negligible amount of small mammals found in scats differed from the majority of investigations carried out elsewhere. Results: The results show the close relation of the population with human settlements and regional agricultural habits

Impact of biased sampling effort and spatial uncertainty of locations on models of plant invasion patterns in Croatia

Very frequently biological databases are used for analysing distribution of different taxa. These databases are usually the result of variable sampling effort and location uncertainty. The aim of this study was to test the influence of geographically biased sampling effort and spatial uncertainty of locations on models of species richness. For this purpose, we assessed the pattern of invasive alien plants in Croatia using the Flora Croatica Database. The procedure applied in testing of the sensitivity of models consisted of sample area sectioning into coherent ecological classes (hereinafter Gower classes). The quadrants were then ranked based on sampling effort per class. This resulted in creation of models using varying numbers of quadrants whose performance was tested with independent validation points. From this the best fitting model was determined, as well as a threshold of sampling effort. The data from quadrants with sampling effort below the threshold were considered too unreliable for modelling. Further, spatial uncertainty was simulated by adding a random term to each location and re-running the models using the simulated locations. Biased sampling effort and spatial uncertainty of locations had similar effects on model performance in terms of the magnitude of the affected area, as in both cases 7% of the quadrants showed statistically significant deviations in alien plant species richness. The model using only on the quandrants with the highest 35% quantile sampling effort best balanced the sampling effort per quadrant and overall geographical coverage. It predicted a mean number of 3.2 invasive alien plant species per quadrant for the Alpine region, 5.2 for the Continental, 6.1 for the Mediterranean and 5.3 for the Pannonian region of Croatia. Thus, the observational databases can be considered as a reliable source for species richness models and, most likely, for other types of species distribution models, given that their limitations are accounted for in the data selection process. In order to obtain precise estimates of species richness it is required to sample the whole range of ecological conditions of the study area

An Extremely Rare Case of Cementless Third Generation Corail Stem Neck Fracture With Fractographic Analysis

The cementless Corail stem is one of the most frequently implanted stems and has undergone several design changes. Currently in use is the third generation, named Corail AMT. Until now, only one third-generation Corail stem neck fracture has been described in 2020. In our paper, we present an almost identical complication with an additional analysis of the fracture using a scanning electron microscope. The revision surgery consisted of changing the broken implant with a Corail revision stem, along with replacing the polyethylene liner and the femoral head with new one, after which the patient achieved a full recovery. According to the available literature, this is the second case of this extremely rare complication