Robust joint modeling of longitudinal measurements and time to event data using normal/independent distributions: A Bayesian approach

Joint modeling of longitudinal data and survival data has been used widely for analyzing AIDS clinical trials, where a biological marker such as CD4 count measurement can be an important predictor of survival. In most of these studies, a normal distribution is used for modeling longitudinal responses, which leads to vulnerable inference in the presence of outliers in longitudinal measurements. Powerful distributions for robust analysis are normal/independent distributions, which include univariate and multivariate versions of the Student's t, the slash and the contaminated normal distributions in addition to the normal. In this paper, a linear‐mixed effects model with normal/independent distribution for both random effects and residuals and Cox's model for survival time are used. For estimation, a Bayesian approach using Markov Chain Monte Carlo is adopted. Some simulation studies are performed for illustration of the proposed method. Also, the method is illustrated on a real AIDS data set and the best model is selected using some criteria.     

Integrating the Rabinowitz rarity framework with a National Plant Inventory in South Korea

Increasingly large presence‐only survey datasets are becoming available for use in conservation assessments. Potentially, these records could be used to determine spatial patterns of plant species rarity and endemism. We test the integration of a large South Korean species record database with Rabinowitz rarity classes. Rabinowitz proposed seven classes of species rarity using three variables: geographic range, habitat specificity, and local population size. We estimated the range size and local abundance of 2,215 plant species from species occurrence records and habitat specificity as the number of landcover types each species’ records were found in. We classified each species into a rarity class or as common, compared species composition by class to national lists, and mapped the spatial pattern of species richness for each rarity class. Species were classed to narrow or wide geographic ranges using 315 km, the average from a range size index of all species (D_max), based on maximum distance between observations. There were four classes each within the narrow and wide range groups, sorted using cutoffs of local abundance and habitat specificity. Nationally listed endangered species only appeared in the narrow‐range classes, while nationally listed endemic species appeared in almost all classes. Species richness in most rarity classes was high in northeastern South Korea especially for species with narrow ranges. Policy implications. Large presence‐only surveys may be able to estimate some classes of rarity better than others, but modification to include estimates of local abundance and habitat types, could greatly increase their utility. Application of the Rabinowitz rarity framework to such surveys can extend their utility beyond species distribution models and can identify areas that need further surveys and for conservation priority. Future studies should be aware of the subjectivity of the rarity classification and that regional scale implementations of the framework may differ.     

From Scilla to Charybdis – is our voyage safer now?

The genus Charybdis Speta (previously Urginea maritima agg.) was investigated karyologically and genetically throughout its geographic range in the Mediterranean. The different ploidy levels show a strong geographic pattern. Diploid populations are mainly found along the northern coast of Africa with C. pancration extending northwards from Tunisia to southern Italy. Tetraploid populations are most densely distributed in the eastern Mediterranean but are also found in North Africa, on the Balearic and Canary Islands. Hexaploid populations are restricted to the Iberian Peninsula and adjacent Morocco and Algeria. Chloroplast microsatellite data suggest that determination of ploidy levels alone is insufficient to adequately describe the existing populations. Especially the tetraploid and hexaploid populations exhibit additional genetic differentiation and geographic structuring. AFLP data indicate that tetraploid populations from southern Italy are of hybrid origin. Phylogenetic analysis further revealed that the genera Urginea Steinh. and Charybdis are not directly related to each other but have strong ties to genera from southern Africa. A possible colonization scenario of the Mediterranean via NW Africa and Iberia is discussed.     

A Multiple‐Absorbent Markov Process in Survival Studies: Application to Breast Cancer

A Markov process with several absorbent states is applied for analyzing a breast cancer dataset. The study examines the evolution of patients until death, and shows that two well‐differentiated ways can be considered in the evolution of patients towards the death state: those who relapse and those who not. The risk groups we have considered are determined by the application of treatments radiotherapy and chemotherapy, which are introduced as covariates. Four states are distinguished: no relapse, relapse, death after metastasis, and death without metastasis, the last two absorbent. We apply a methodology that uses algorithmic procedures, avoiding differential equations. The transition probability functions and the likelihood function in the model are calculated. For the dataset, the survival functions and the mean times in states for the different group of risks are determined. We show that the metastasis is the main cause of death in this cohort, but the number of deaths by relapse is not negligible.     

Factors affecting the fruiting of bilberries: an analysis of categorical data set

The present study is an application of categorical data analysis in ecological research. The approach is based on logistic regression following an exploratory graphical analysis. The material was collected in an extensive forest inventory in which a set of observations was made by eye in a stratified random sample of 262 mature upland forest stands in South Finland. The problem was to interpret the variation in the fertility of the tillers of bilberry (Vaccinium myrtillus). In the field, the fertility was recorded as a three-class ordinal variable. The information available for the interpretation included the visually estimated density of the tree crowns, the soil fertility class determined using Cajander's forest site types and the percent cover of V. myrtillus.The GLM framework was employed in successive stages of the data analysis in order to find a model to fit the data. For this, the three-class ordinal response variable was reduced to two classes: stands characterized by (a) sterile and (b) fertile bilberry tillers. Successful prediction of the distribution of these two types of forest stands was achieved with a logistic-regression model by using canopy coverage and soil fertility classes as predictor variables. The generalized linear modelling framework is suitable for studying many ecological problems even when only rough categorical estimates of environmental scalars are available.     

Receptor analysis: An arithmetic correction improves precision and accuracy

Data of receptor analysis by ligand binding experiments should be processed using the formula DCORR = (B1 - B2.F1/F2)/VS.DCORR is an estimate of the concentration of receptor-bound radioligand; B1 and F1 are estimates of bound and free radioligand in assay 1; B2 and F2 are the corresponding values obtained from the parallel assay 2, which contains an additional excess of nonlabeled ligand; VS is the volume of assays 1 and 2 that was submitted to separation. DCORR will be superior to the conventional formula, D = (B1 - B2)/VS, if the radiolabeled receptor-ligand complexes are incompletely separated from nonspecifically bound and free radioligands. DCORR corrects for the systematic underestimation of the specifically bound radioligand implicated in D as well as for random errors due to imprecise pipetting during preparation of the parallel assays. The superiority of DCORR over D is verified by processing the data of androgen receptor analyses using agar gel electrophoresis for separation of bound and free radioligand.     

Abundance and degree of dispersion of genomic d(GA) n ·d(TC) n sequences

Summary The abundance of d(GA) _n ·d(TC) _n tracts was determined in genomes of rodents and primates. Dot blot hybridization assays revealed that such tracts constitute 0.40%, 0.30%, and 0.40%, respectively, of the rat, hamster, and mouse genomes, but only 0.07% and 0.05% of the human and monkey genomes. A plaque hybridization assay of rat and human genomic libraries showed that 37% and 16%, respectively, of the recombinant phages in these libraries contain d(GA) _n ·d(TC) _n tracts. A survey of sequences stored in the GenBank data bank showed that a significant fraction of the stored rodent genes (about 2.0%) contain long d(GA) _n ·d(TC) _n tracts (n> 30) with <10% mismatching. The primate genes contain only shorter tracts (n<15) with <10% mismatching. In addition, the rodent and the primate genes contain tracts with larger degrees of mismatching. The chicken, which represents an entirely different branch of the evolutionary tree, was found to be as low in d(GA) _n ·d(TC) _n tracts as the primates. It is suggested that a common ancestor of the rodents has acquired the ability to amplify d(GA) _n ·d(TC) _n tracts.     

Feeding habits of larval Mirogrex terraesanctae (Steinitz, 1952) in Lake Kinneret (Israel) I. Field study

Analysis of the food composition, distribution, lengths and dry weights of larval bleak, Mirogrex terraesanctae (Steinitz, 1952) in Lake Kinneret, Israel was conducted. Indices of electivity of ingested prey organisms were also determined. Larvae were surveyed throughout the 1989–90 reproductive seasons (Dec–Mar). Small larvae (<10.28 mm SL) preferentially select prey items smaller than 180 µ. Dominant zooplankters in the larval guts included: Bosmina longirostris, Ceriodaphnia reticulata and C. rigaudi, Asplanchna priodonita, Synchaeta oblonga, S. pectinata and juvenile cyclopoid copepods. Diaphanosoma brachiurum was rarely found (instars only) and no adult copepods were observed in larval guts. Some larvae specimens were found with up to 500 undigested (intact) accidentally ingested cells of Peridinium spp. per gut.     

Feeding habits of larval Mirogrex terraesanctae (Steinitz, 1952) in Lake Kinneret (Israel) II. Experimental study

Interactions between the larvae of Mirogrex terraesanctae (Steinitz, 1952) in Lake Kinneret, Israel, and their zooplankton prey were studied experimentally. Prey species preference and size selectivities were measured. Larvae were hatched in the lab from eggs collected in the field, and fed different food items in various concentrations. The food items included lake zooplankton, algae, and commercial pellets. It was shown that small, first feeding larvae (7–8.5 mm SL) prefer small bodied zooplankters (< 180 µ). The effect of these food sources on larval growth was measured. It was found that larval Mirogrex grew at a higher rate when fed zooplankton prey sized from 63 µ–250 µ. Food items smaller than 63 µ, larger than 250 µ and Scenedesmus sp., produced less than optimal growth rates. The importance of Mirogrex feeding habits and their potential influence on the Kinneret ecosystem is considered.     

Nullius in Verba1: Advancing Data Transparency in Industrial Ecology

With the growth of the field of industrial ecology (IE), research and results have increased significantly leading to a desire for better utilization of the accumulated data in more sophisticated analyses. This implies the need for greater transparency, accessibility, and reusability of IE data, paralleling the considerable momentum throughout the sciences. The Data Transparency Task Force (DTTF) was convened by the governing council of the International Society for Industrial Ecology in late 2016 to propose best‐practice guidelines and incentives for sharing data. In this article, the members of the DTTF present an overview of developments toward transparent and accessible data within the IE community and more broadly. We argue that increased transparency, accessibility, and reusability of IE data will enhance IE research by enabling more detailed and reproducible research, and also facilitate meta‐analyses. These benefits will make the results of IE work more timely. They will enable independent verification of results, thus increasing their credibility and quality. They will also make the uptake of IE research results easier within IE and in other fields as well as by decision makers and sustainability practitioners, thus increasing the overall relevance and impact of the field. Here, we present two initial actions intended to advance these goals: (1) a minimum publication requirement for IE research to be adopted by the Journal of Industrial Ecology; and (2) a system of optional data openness badges rewarding journal articles that contain transparent and accessible data. These actions will help the IE community to move toward data transparency and accessibility. We close with a discussion of potential future initiatives that could build on the minimum requirements and the data openness badge system.