Multiple environmental controls explain global patterns in soil animal communities

Soil animals play important roles in ecosystem functioning and stability, but the environmental controls on their communities are not fully understood. In this study, we compiled a dataset of soil animal communities for which the abundance and body mass of multiple soil animal groups were recorded. The mass–abundance scaling relationships were then used to investigate multiple environmental controls on soil animal community composition. The data reveal latitudinal shifts from high abundances of small soil animals at high latitudes to greater relative abundances of large soil animals at low latitudes. A hierarchical linear mixed effects model was applied to reveal the environmental variables shaping these latitudinal trends. The final hierarchical model identified mean annual temperature, soil pH and soil organic carbon content as key environmental controls explaining global mass–abundance scaling relationships in soil animal communities (R2c = 0.828, Ngroup = 117). Such relationships between soil biota with climate and edaphic conditions have been previously identified for soil microbial, but not soil animal, communities at a global scale. More comprehensive global soil community datasets are needed to better understand the generality of these relationships over a broader range of global ecosystems and soil animal groups

What\u27s In a Mode: Writing Program Administrators\u27 Perception, Value, and Implementation of Multimodality in First-Year Writing

This study focuses on writing program administrators’ (WPAs) views towards the definition and value of multimodality within their first-year writing program curriculum. Furthermore, the study seeks to discover how first-year writing programs go about integrating a multimodal focus, including support structures that are in place, such as training, equipment, technology, and other resources. Multimodality has become a popular topic of discussion for those in Rhetoric/Composition, yet its program-wide implementation remains low. This study updates a 2005 study published in Composition Studies, which provided an overview of what participants labeled as multimodal or new media for their Composition classroom instruction (Anderson, Atkins, Ball, Millar, Selfe, & Selfe) Much of the scholarship on multimodality has centered on defining the concept, proposing practical ways to incorporate multimodality into instruction, and analyzing the pros and cons of its incorporation. So far, not much scholarship has been directly targeted to WPAs. This project explores the theoretical approaches to multimodality through curriculum implementation by presenting an overview of what works for writing programs across institutional contexts, from doctoral granting institutions to associate’s colleges. This research was explored through the theoretical frameworks of antiracism and utilitarianism. Methodology included surveys and semi-structured interviews via Zoom. Data analysis was used to identify themes of student and faculty perception of multimodality, balancing expectations and faculty experiences, and labor conditions. Implications for navigating curriculum changes while balancing structural disadvantages within programs are discussed. Further research is warranted for expanding this research into even more diverse contexts

Optimisation and validation of a PCR for Antigen Receptor Rearrangement (PARR) assay to detect clonality in canine lymphoid malignancies

PCR for antigen receptor gene rearrangements (PARR) analysis is being increasingly used to assist diagnosis of canine lymphoma. In this study, PARR was carried out on consecutive samples received as part of routine diagnostic practice from 271 patients: 195 with lymphoid malignancies, 53 with reactive conditions and 23 with other neoplasms. Initially, published primer sets were used but later minor primer modifications were introduced and primers were rationalised to give a PARR panel that provides a good compromise between sensitivity and cost. Results were compared to diagnoses made by histology or cytology, coupled with immunophenotyping by flow cytometry or immunohistochemistry where possible. After exclusion of 11 poor quality samples, 230/260 (88%) gave a clear result with 162/163 (99%) of samples classified as clonal and 56/67 (84%) classified as polyclonal giving results concordant with the cytological/histological diagnosis. Among 30 samples with equivocal results, 21 had clonal peaks in a polyclonal background and nine showed little amplification. These were from patients with a range of neoplastic and non-neoplastic conditions emphasising the need to interpret such results carefully in concert with other diagnostic tests. The combination of primer sets used in this study resulted in a robust, highly specific and sensitive assay for detecting clonality

Jeans Instability in a Tidally Disrupted Halo Satellite Galaxy

We use a hybrid test particle/N-body simulation to integrate 4 million massless test particle trajectories within a fully self-consistent 10^5 particle N-body simulation. The number of massless particles allows us to resolve fine structure in the spatial distribution and phase space of a dwarf galaxy as it is disrupted in the tidal field of a Milky Way type galaxy. The tidal tails exhibit nearly periodic clumping or a smoke-like appearance. By running simulations with different satellite particle mass, halo particle mass, number of massive and massless particles and with and without a galaxy disk, we have determined that the instabilities are not due to numerical noise, amplification of structure in the halo, or shocking as the satellite passes through the disk of the Galaxy. We measure Jeans wavelengths and growth timescales in the tidal tail and show that the Jeans instability is a viable explanation for the clumps. We find that the instability causes velocity perturbations of order 10 km/s. Clumps in tidal tails present in the Milky Way could be seen in stellar radial velocity surveys as well as number counts. We find that the unstable wavelength growth is sensitive to the simulated mass of dark matter halo particles. A simulation with a smoother halo exhibits colder and thinner tidal tails with more closely spaced clumps than a simulation with more massive dark matter halo particles. Heating by the halo particles increases the Jeans wavelength in the tidal tail affecting substructure development, suggesting an intricate connection between tidal tails and dark matter halo substructure.Comment: 15 pages, 7 figures, submitted to MNRAS, May 25 201

Reaching Underserved Borrower Prospects: A Case Of A Small Rural Bank

Banks want to serve all members of their market, to meet government regulations as well as to follow company policy.  This paper describes a case study of the efforts of a small rural bank to develop a marketing plan to target potential borrowers in underserved groups.  First, market demographic data were used to determine the current population size, income, and race composition of the market.  Second, publicly available competitor data were used to assess peer banks in surrounding market areas.  The third task was to identify underserved socio-economic groups and develop prospect lists.  Fourth, the bank developed outreach efforts to promote bank financial services to target groups.  Fifth, the bank delivered educational programs for target individuals and families.  Sixth, the outreach efforts were evaluated.  Finally, the bank considered options for promoting bank services to underserved residents in the future.  This paper illustrates the difficulty for a small, rural bank to diversify its borrower base, and presents some efforts that a bank can take to pursue its goal of serving all members of its community

Using acoustic indices in ecology : guidance on study design, analyses and interpretation

TBL was supported by Leverhulme Trust, research grant number RPG-2020-160; the Lorentz Centre, Leiden, The Netherlands; and UKAN+. AE and OM were supported by UKAN+.The rise of passive acoustic monitoring and the rapid growth in large audio datasets is driving the development of analysis methods that allow ecological inferences to be drawn from acoustic data. Acoustic indices are currently one of the most widely applied tools in ecoacoustics. These numerical summaries of the sound energy contained in digital audio recordings are relatively straightforward and fast to calculate but can be challenging to interpret. Misapplication and misinterpretation have produced conflicting results and led some to question their value. To encourage better use of acoustic indices, we provide nine points of guidance to support good study design, analysis and interpretation. We offer practical recommendations for the use of acoustic indices in the study of both whole soundscapes and individual taxa and species, and point to emerging trends in ecoacoustic analysis. In particular, we highlight the critical importance of understanding the links between soundscape patterns and acoustic indices. Acoustic indices can offer insights into the state of organisms, populations, and ecosystems, complementing other ecological research techniques. Judicious selection, appropriate application and thorough interpretation of existing indices is vital to bolster robust developments in ecoacoustics for biodiversity monitoring, conservation and future research.Publisher PDFPeer reviewe

Sounding out ecoacoustic metrics: avian species richness is predicted by acoustic indices in temperate but not tropical habitats

Affordable, autonomous recording devices facilitate large scale acoustic monitoring and Rapid Acoustic Survey is emerging as a cost-effective approach to ecological monitoring; the success of the approach rests on the de- velopment of computational methods by which biodiversity metrics can be automatically derived from remotely collected audio data. Dozens of indices have been proposed to date, but systematic validation against classical, in situ diversity measures are lacking. This study conducted the most comprehensive comparative evaluation to date of the relationship between avian species diversity and a suite of acoustic indices. Acoustic surveys were carried out across habitat gradients in temperate and tropical biomes. Baseline avian species richness and subjective multi-taxa biophonic density estimates were established through aural counting by expert ornithol- ogists. 26 acoustic indices were calculated and compared to observed variations in species diversity. Five acoustic diversity indices (Bioacoustic Index, Acoustic Diversity Index, Acoustic Evenness Index, Acoustic Entropy, and the Normalised Difference Sound Index) were assessed as well as three simple acoustic descriptors (Root-mean-square, Spectral centroid and Zero-crossing rate). Highly significant correlations, of up to 65%, between acoustic indices and avian species richness were observed across temperate habitats, supporting the use of automated acoustic indices in biodiversity monitoring where a single vocal taxon dominates. Significant, weaker correlations were observed in neotropical habitats which host multiple non-avian vocalizing species. Multivariate classification analyses demonstrated that each habitat has a very distinct soundscape and that AIs track observed differences in habitat-dependent community composition. Multivariate analyses of the relative predictive power of AIs show that compound indices are more powerful predictors of avian species richness than any single index and simple descriptors are significant contributors to avian diversity prediction in multi-taxa tropical environments. Our results support the use of community level acoustic indices as a proxy for species richness and point to the potential for tracking subtler habitat-dependent changes in community composition. Recommendations for the design of compound indices for multi-taxa community composition appraisal are put forward, with consideration for the requirements of next generation, low power remote monitoring networks

Análisis de introgresión en Apis mellifera iberiensis y Apis mellifera mellifera usando polimorfismos de nucleótidos simples (SNPs)

Diferentes estudios han agrupado las subespecies de A. mellifera en cuatro linajes evolutivos basados sobre marcadores morfométricos, ecológicos, microsatélites y mtDNA: Africano (A), Medio Oriente (O), Este y Centro de Europa (C), Norte y Oeste de Europa (M). El linaje M está representado por las subespecies A. m. iberiensis y A. m. mellifera, cuya distribución es la Península Ibérica para la primera y desde los Pirineos hacia el Norte de Europa para la segunda. Durante las últimas décadas, la introducción masiva de subespecies del linaje C por apicultores ha ocasionado un fuerte flujo génico y más aún al casi completo remplazamiento de A. m. mellifera, como ha sido reportado para Alemania. Por tanto, el análisis de niveles de introgresión en programas de crianza y conservación es de vital importancia para evitar la perdida de diversidad genética y sustitución de especies nativas. Este estudio busca identificar los niveles de introgresión de subespecies del linaje C en las subespecies pertenecientes al linaje M a través de un análisis amplio del genoma usando SNPs. Para 711 individuos correspondiente a A. m. iberiensis y 88 individuos A. m. mellifera fueron genotipados 1536 SNPs. Las subespecies de linaje C A. m. ligustica y A. m. carnica fueron usados como poblaciones de referencia. Los niveles de introgresión fueron evaluados usando un método de agrupamiento Bayesiano implementado en el software STRUCTURE. Nuestros resultados indicaron que la introgresión en A. m .iberiensis no es significante, a diferencia en A. m. mellifera que presentó de 8% a 30% de introgresión. Considerando que muchas de las muestras de A. m. mellifera son provenientes de poblaciones integradas en programas de conservación en el Norte de Europa, este resultado evidencia el profundo contraste entre las dos subespecies del linaje M con respecto a su estado de conservación

Calibration and evaluation of individual-based models using Approximate Bayesian Computation

AbstractThis paper investigates the feasibility of using Approximate Bayesian Computation (ABC) to calibrate and evaluate complex individual-based models (IBMs). As ABC evolves, various versions are emerging, but here we only explore the most accessible version, rejection-ABC. Rejection-ABC involves running models a large number of times, with parameters drawn randomly from their prior distributions, and then retaining the simulations closest to the observations. Although well-established in some fields, whether ABC will work with ecological IBMs is still uncertain.Rejection-ABC was applied to an existing 14-parameter earthworm energy budget IBM for which the available data consist of body mass growth and cocoon production in four experiments. ABC was able to narrow the posterior distributions of seven parameters, estimating credible intervals for each. ABC's accepted values produced slightly better fits than literature values do. The accuracy of the analysis was assessed using cross-validation and coverage, currently the best-available tests. Of the seven unnarrowed parameters, ABC revealed that three were correlated with other parameters, while the remaining four were found to be not estimable given the data available.It is often desirable to compare models to see whether all component modules are necessary. Here, we used ABC model selection to compare the full model with a simplified version which removed the earthworm's movement and much of the energy budget. We are able to show that inclusion of the energy budget is necessary for a good fit to the data. We show how our methodology can inform future modelling cycles, and briefly discuss how more advanced versions of ABC may be applicable to IBMs. We conclude that ABC has the potential to represent uncertainty in model structure, parameters and predictions, and to embed the often complex process of optimising an IBM's structure and parameters within an established statistical framework, thereby making the process more transparent and objective

Reduced SNP panels for genetic identification and introgression analysis in the dark honey bee (Apis mellifera mellifera)

Beekeeping activities, especially queen trading, have shaped the distribution of honey bee (Apis mellifera) subspecies in Europe, and have resulted in extensive introductions of two eastern European C-lineage subspecies (A. m. ligustica and A. m. carnica) into the native range of the M-lineage A. m. mellifera subspecies in Western Europe. As a consequence, replacement and gene flow between native and commercial populations have occurred at varying levels across western European populations. Genetic identification and introgression analysis using molecular markers is an important tool for management and conservation of honey bee subspecies. Previous studies have monitored introgression by using microsatellite, PCR-RFLP markers and most recently, high density assays using single nucleotide polymorphism (SNP) markers. While the latter are almost prohibitively expensive, the information gained to date can be exploited to create a reduced panel containing the most ancestry-informative markers (AIMs) for those purposes with very little loss of information. The objective of this study was to design reduced panels of AIMs to verify the origin of A. m. mellifera individuals and to provide accurate estimates of the level of C-lineage introgression into their genome. The discriminant power of the SNPs using a variety of metrics and approaches including the Weir & Cockerham's FST, an FST-based outlier test, Delta, informativeness (In), and PCA was evaluated. This study shows that reduced AIMs panels assign individuals to the correct origin and calculates the admixture level with a high degree of accuracy. These panels provide an essential tool in Europe for genetic stock identification and estimation of admixture levels which can assist management strategies and monitor honey bee conservation programs