Revisiting the dimensionality of biological diversity

Biodiversity can be represented by different dimensions. While many diversity metrics try to capture the variation of these dimensions they also lead to a ‘fragmentation’ of the concept of biodiversity itself. Developing a unified measure that integrates all the dimensions of biodiversity is a theoretical solution for this problem, however, it remains operationally impossible. Alternatively, understanding which dimensions better represent the biodiversity of a set of communities can be a reliable way to integrate the different diversity metrics. Therefore, to achieve a holistic understand of biological diversity, we explore the concept of dimensionality. We define dimensionality of diversity as the number of complementary components of biodiversity, represented by diversity metrics, needed to describe biodiversity in an unambiguously and effective way. We provide a solution that joins two components of dimensionality – correlation and the variation – operationalized through two metrics, respectively: evenness of eigenvalues (EE) and importance values (IV). Through simulation we show that considering EE and IV together can provide information that is neglected when only EE is considered. We demonstrate how to apply this framework by investigating the dimensionality of South American small mammal communities. Our example evidenced that, for some representations of biological diversity, more attention is needed in the choice of diversity metrics necessary to effectively characterize biodiversity. We conclude by highlighting that this integrated framework provides a better understanding of dimensionality than considering only the correlation component.     

ARL4C might serve as a prognostic factor and a novel therapeutic target for gastric cancer: bioinformatics analyses and biological experiments

The ADP-ribosylation factor-like proteins (ARLs) have been proved to regulate the malignant phenotypes of several cancers. However, the exact role of ARLs in gastric cancer (GC) remains elusive. In this study, we systematically investigate the expression status, interactive relations, potential pathways, genetic variations and clinical values of ARLs in GC. We find that ARLs are significantly dysregulated in GC and involved in various cancer-related pathways. Subsequently, machine learning models identify ARL4C as one of the two most significant clinical indicators among ARLs for GC. Furthermore, ARL4C silencing remarkably inhibits the growth and metastasis of GC cells both in vitro and in vivo. Moreover, enrichment analysis indicates that ARL4C is highly correlated with TGF-β1 signalling. Correspondingly, TGF-β1 treatment dramatically increases ARL4C expression and ARL4C knockdown inhibits the phosphorylation level of Smads, downstream factors of TGF-β1. Meanwhile, the coexpression of ARL4C and TGF-β1 worsens the prognosis of GC patients. Our work comprehensively demonstrates the crucial role of ARLs in the carcinogenesis of GC and the specific mechanisms underlying the GC-promoting effects of TGF-β1. More importantly, we uncover the great promise of ARL4C-targeted therapy in improving the efficacy of TGF-β1 inhibitors for GC patients.     

Forest vascular plants as indicators of plant species richness: A data analysis of a flora atlas from northwestern Germany

Abstract

Our study had the objective to examine whether the number of forest vascular plants in a forest-poor region may be indicative of total plant species richness and of the number of threatened plant species. We also related forest plant species richness to geological and soil variables. The analysis was based on a regional flora atlas from the Weser-Elbe region in northwestern Germany including incidence data of species in a total of 1109 grid cells (each ca. 2.8 × 2.8 km²). All taxa were classified either as forest or non-forest species. Total species richness in the grid cells ranged from 65 to 597, with a mean value of 308. The number of forest species varied between 20 and 309 (mean 176). Grid cells with or without particular geological units differed in total and forest species richness, with those containing peatland and marshland being particularly species-poor. Indicator value analysis showed that both total and forest species richness in the grid cells were related to soil acidity and nitrogen in a hump-backed manner, with the highest number of species found at moderately low values for nitrogen and at intermediate values of pH. Forest species richness was highly positively correlated with the number of non-forest species and threatened non-forest species. Indicators for high species richness were primarily those species that are confined to closed semi-natural forests with a varied topography and relatively base- and nutrient-rich soils. Grid cells including historically ancient forest exhibited a higher species richness than grid cells lacking ancient forest, indicating the importance of a long habitat continuity for a high phytodiversity. The “habitat coincidence” of high species richness is best explained by similar responses of forest species and species of other habitats to the main environmental gradients. It is suggested that the regional patterns found for the Weser-Elbe region can be transferred also to other forest-poor regions in Central Europe.     

Strategies for defining traits when calculating economic values for livestock breeding: a review

The objective of the present review was (i) to survey different approaches for choosing the complex of traits for which economic values (EVs) are calculated, (ii) to call attention to the proper definition of traits and (iii) to discuss the manner and extent to which relationships among traits have been considered in the calculation of EVs. For this purpose, papers dealing with the estimation of EVs of traits in livestock were reviewed. The most important reasons for incompatibility of EVs for similar traits estimated in different countries and by different authors were found to be inconsistencies in trait definitions and in assumptions being made about relationships among traits. An important problem identified was how to choose the most appropriate criterion to characterise production or functional ability for a particular class of animals. Accordingly, the review covered the following three topics: (i) which trait(s) would best characterise the growth ability of an animal; (ii) how to define traits expressed repeatedly in subsequent reproductive cycles of breeding females and (iii) how to deal with traits that differ in average value between sexes or among animal groups. Various approaches that have been used to solve these problems were discussed. Furthermore, the manner in which diverse authors chose one or more traits from a group of alternatives for describing a specific biological potential were reviewed and commented on. The consequences of including or excluding relationships among economically important traits when estimating the EV for a specific trait were also examined. An important conclusion of the review is that, for a better comparability and interpretability of estimated EVs in the literature, it is desirable that clear and unique definitions of the traits, complete information on assumptions used in analytical models and details on inter-relationships between traits are documented. Furthermore, the method and the model used for the genetic evaluation of specific traits in a certain breeding organisation are important for the exact definition of traits, for which the economic values will be calculated, and for the inclusion or exclusion of relationships among traits in the calculation of the EVs in livestock breeding.     

Confidence interval of intrinsic optimum temperature estimated using thermodynamic SSI model

The intrinsic optimum temperature for the development of ectotherms is one of the most important factors not only for their physiological processes but also for ecological and evolutional processes. The Sharpe–Schoolfield–Ikemoto (SSI) model succeeded in defining the temperature that can thermodynamically meet the condition that at a particular temperature the probability of an active enzyme reaching its maximum activity is realized. Previously, an algorithm was developed by Ikemoto (Tropical malaria does not mean hot environments. Journal of Medical Entomology, 45, 963–969) to estimate model parameters, but that program was computationally very time consuming. Now, investigators can use the SSI model more easily because a full automatic computer program was designed by Shi et al. (A modified program for estimating the parameters of the SSI model. Environmental Entomology, 40, 462–469). However, the statistical significance of the point estimate of the intrinsic optimum temperature for each ectotherm has not yet been determined. Here, we provided a new method for calculating the confidence interval of the estimated intrinsic optimum temperature by modifying the approximate bootstrap confidence intervals method. For this purpose, it was necessary to develop a new program for a faster estimation of the parameters in the SSI model, which we have also done.     

Genetic differences based on a beef terminal index are reflected in future phenotypic performance differences in commercial beef cattle

The increased demand for animal-derived protein and energy for human consumption will have to be achieved through a combination of improved animal genetic merit and better management strategies. The objective of the present study was to quantify whether differences in genetic merit among animals materialised into phenotypic differences in commercial herds. Carcass phenotypes on 156 864 animals from 7301 finishing herds were used, which included carcass weight (kg), carcass conformation score (scale 1 to 15), carcass fat score (scale 1 to 15) at slaughter as well as carcass price. The price per kilogram and the total carcass value that the producer received for the animal at slaughter was also used. A terminal index, calculated in the national genetic evaluations, was obtained for each animal. The index was based on pedigree index for calving performance, feed intake and carcass traits from the national genetic evaluations. Animals were categorised into four terminal index groups on the basis of genetic merit estimates that were derived before the expression of the phenotypic information by the validation animals. The association between terminal index and phenotypic performance at slaughter was undertaken using mixed models; whether the association differed by gender (i.e. young bulls, steers and heifers) or by early life experiences (animals born in a dairy herd or beef herd) was also investigated. The regression coefficient of phenotypic carcass weight, carcass conformation and carcass fat on their respective estimated breeding values (EBVs) was 0.92 kg, 1.08 units and 0.79 units, respectively, which is close to the expectation of one. Relative to animals in the lowest genetic merit group, animals in the highest genetic merit group had, on average, a 38.7 kg heavier carcass, with 2.21 units greater carcass conformation, and 0.82 units less fat. The superior genetic merit animals were, on average, slaughtered 6 days younger than their inferior genetic merit contemporaries. The superior carcass characteristics of the genetically elite animals materialised in carcasses worth €187 more than those of the lowest genetic merit animals. Although the phenotypic difference in carcass traits of animals divergent in terminal index differed statistically by animal gender and early life experience, the detected interactions were generally biologically small. This study clearly indicates that selection on an appropriate terminal index will produce higher performing animals and this was consistent across all production systems investigated.     

Measurements of peripheral and deep body temperature in cattle – A review

Automation of the measurement of the physiological and behavioural parameters of livestock has become an important goal for both scientists and farmers. Accurate data and knowledge about farmed animals, especially in cattle breeding, are needed. Proper early diagnosis of a cow's health status in real time allows for preventing the development of infection, oestrus detection and leads to reduced environmental stress. Thus, it contributes to more effective herd management. Among the physiological parameters, body temperature and its fluctuations are key indicators of health and well-being in animals. Currently, along with the development of technical solutions and their implementation, increasingly more attention is being paid to the continuously measurement of body core and peripheral temperature in animals. Recently there has been an increased number of publications devoted to this subject. However, there is a need to systematise this knowledge as these studies have had different purposes, have been performed in various environmental conditions, and the measurements were taken using different methods and equipment. As such, the results obtained by the different authors often may not be comparable. For this reason, this paper has two main purposes: to present the most widely used continuous methods of peripheral and body core temperature measurement, and to show its references values which characterise the individual locations of the cattle body in thermoneutral ambient. An analysis of the professional publications regarding measurements of peripheral and deep body temperature led to the conclusion that these methods have high research and diagnostic potential. However, it is necessary to standardised research to enable better and more comparable results, including among others; different cattle groups, animal age, health and environmental conditions.