Steller sea lion spatial‐use patterns derived from a Bayesian model of opportunistic observations

Despite acquisition of a substantial catalog of telemetry data from Steller sea lions (Eumetopias jubatus) over the past two decades, scientists still lack comprehensive regionally explicit knowledge about Steller sea lion habitat use. The Platforms of Opportunity data contain records of Steller sea lion sightings throughout the species’ entire range and have potential to fill gaps in knowledge about their spatial use; however, the data have not previously been used because effort (e.g., time spent surveying or area sampled) was not recorded when sightings were obtained. For this study a novel approach was used to overcome the lack of effort data through development of an effort index and a Bayesian negative binomial model. The model quantified Steller sea lion encounter rates and associated uncertainty within 15 × 15 km² grid cells across the species’ entire range. Year‐round, as well as breeding and nonbreeding season encounter rates were estimated. The results of this analysis identify several previously undocumented areas of high use by Steller sea lions, indicate that only 37% of Steller sea lion high‐use areas fall within designated critical habitat, and demonstrate that use of depth and distance from shore as indicators of Steller sea lion habitat is contraindicated.     

Efficient algorithms for optimal designs with correlated observations in pharmacokinetics and dose-finding studies

Random effects models are widely used in population pharmacokinetics and dose-finding studies. However, when more than one observation is taken per patient, the presence of correlated observations (due to shared random effects and possibly residual serial correlation) usually makes the explicit determination of optimal designs difficult. In this article, we introduce a class of multiplicative algorithms to be able to handle correlated data and thus allow numerical calculation of optimal experimental designs in such situations. In particular, we demonstrate its application in a concrete example of a crossover dose-finding trial, as well as in a typical population pharmacokinetics example. Additionally, we derive a lower bound for the efficiency of any given design in this context, which allows us on the one hand to monitor the progress of the algorithm, and on the other hand to investigate the efficiency of a given design without knowing the optimal one. Finally, we extend the methodology such that it can be used to determine optimal designs if there exist some requirements regarding the minimal number of treatments for several (in some cases all) experimental conditions.     

Estimating mixtures of leaf functional types using continental-scale satellite and climatic data

Aim Recent research has shown that much of the variability in leaf gas exchange and leaf longevity can be related to variations in the surface : volume ratio of leaves. The aim of this paper was to develop a theoretical framework and a practical method to extend that result to the vegetation at the continental scale. Location The study was conducted in Australia. Methods We propose that vegetation is composed of a mixture of three basic leaf types, ‘turgor’ (T), ‘mesic’ (M) and ‘sclerophyll’ (S) leaves. Changes in the relative proportions of T, M and S leaves within a vegetation type are visualized using a ternary diagram and differences in vegetation structure are shown to be easily mapped onto the ternary diagram. We estimate the proportions of T, M and S leaves using readily available data. The total amount of PAR absorbed by the vegetation (fPAR) is estimated using continental‐scale satellite observations. The total fPAR is then decomposed into that absorbed by T, M and S leaves. The relative absorption of PAR by T leaves is estimated from the temporal dynamics in the satellite signal, while the relative proportions of M and S leaves are estimated using climatic (solar radiation, rainfall) data. Results When the availability of light, nutrients and water were near‐optimal, the vegetation was composed of predominantly M leaves. In low nutrient environments S leaves predominated. T leaves were dominant in disturbed environments. Conclusions The theoretical framework is used to predict that elevated atmospheric CO₂ would tend to increase the proportion of M and S leaves in an ecosystem and the resulting change means that the proportion of T leaves would decrease. In terms of the TMS scheme, this implies that elevated CO₂ has the same net effect on the vegetation as a decrease in disturbance.     

A Growth Curve Analysis for Bulls Tested at Station

Data on 2712 bulls tested at station were analysed to study the effect of certain external variables on growth traits of bulls. Most of the animals were Ayrshires (2136). Otherwise Finncattle bulls and Frisian bulls were involved. The testing covers the interval 60–365 days of age, although in part of the data the period is 30–365. Bulls were weighted every 30th day (between 1965 and 1970), or at the ages of 60 and 180 days, and thereafter every 30 days up to the age of 365 days (between 1971 and 1977). Also birth weight was available for 1250 calves. Feeding and general treatment of bulls at station was as uniform as possible for all animals. Conseqúently it can be assumed that effects of non-genetic factors on the growth traits of bulls are minimized. One of the objectives of this study was to compare the growth curves for the three breeds. In our data measurements at certain time-points have dropped out during the course of data collection. Therefore we study the influence of deleting measurements. We also consider the problem of influential measurements at both the design level and the inference level. Several types of growth curves are fitted to the data in order to find the most appropriate model.     

On the Estimation of the Mean with Random Number Of Observations. (Comments on a Paper by M. Singh and V. K. Gupta)

In this paper we study the problem of estimating the mean when the number of observations taken on each unit is a random variable. The estimator proposed by M. Singh and V. K. Gupta (1980) is discussed and modified. It is argued, however, that the arithmetic mean is a more appropriate choice of estimator.     

A modification of the redistribution to the right algorithm using disease markers

Disease markers are time-dependent covariates which describeprogression towards development of disease. Traditional methodsin survival analysis do not make use of available data on thesemarkers to recover additional information from censored individuals.Using a heuristic modification of the redistribution to theright algorithm (Efron, 1967), a new approach for recoveringinformation for censored individuals using disease markers isproposed. Additionally, the statistical properties of the proposedmethod are examined. There are two possible advantages to thismodification: (i) bias reduction when censoring is informative,and (ii) an increase in efficiency in the case of truly noninformativecensoring.     

Estimates of a Treatment Effect Based on Censored Data Rank Tests

Linear rank test statistics are applied to the problem of estimating a treatment effect if two sets of censored failure time data are compared and the distributions of the log-failure times of the two samples are assumed to differ only in location. Rank tests for this accelerated failure time model are reviewed and Hodges-Lehmann type estimates for the shift parameter are proposed. Properties of these estimates are investigated, computational aspects are discussed and an example is presented.     

The use of digital video recorders in pollination biology

1. Digital video recording (DVR) devices, such as the GoPro Hero, have the potential to greatly benefit pollination ecology, but the advantages of digitally recording pollinator activity over direct human observation have not been formally assessed. 2. Two plant taxa, Lavandula angustifolia and Canna ‘sp.’, with differing floral morphology, were used to compare the value of DVR and direct observations in estimating honeybee (Apis mellifera) visitation, flower density and number of flowers visited per foraging bout. 3. The two methods yielded identical results when observing the structurally simple L. angustifolia at both high (10.54 ± 0.52 per plant) and low honeybee density (2.24 ± 0.20 per plant). However, DVR underestimated the number of flowers scored in the field of view (28.7 ± 1.8 direct vs. 22.7 ± 0.9 DVR), the number of honeybees observed (5.3 ± 0.8 direct vs. 3.7 ± 0.7 DVR) and the number of flowers visited during foraging bouts (8.3 ± 1.2 direct vs. 5.5 ± 1.0 DVR) on the more complex Canna ‘sp.’ 4. It is concluded that portable weatherproof DVR devices such as the GoPro Hero are valuable tools for pollination biologists, allowing a single researcher to make simultaneous observations of multiple plants in one or more sites, whilst also allowing the footage to be reviewed. However, DVR devices are limited by their depth and field of view when target plants are large or structurally complex.     

Citizen science and wildlife biology: Synergies and challenges

Citizen science (CS) has evolved over the past decades as a working method involving interested citizens in scientific research, for example by reporting observations, taking measurements or analysing data. In the past, research on animal behaviour has been benefitting from contributions of citizen scientists mainly in the field of ornithology but the full potential of CS in ecological and behavioural sciences is surely still untapped. Here, we present case studies that successfully applied CS to research projects in wildlife biology and discuss potentials and challenges experienced. Our case studies cover a broad range of opportunities: large‐scale CS projects with interactive online tools on bird song dialects, engagement of stakeholders as citizen scientists to reduce human–wildlife conflicts, involvement of students of primary and secondary schools in CS projects as well as collaboration with the media leading to successful recruitment of citizen scientists. Each case study provides a short overview of the scientific questions and how they were approached to showcase the potentials and challenges of CS in wildlife biology. Based on the experience of the case studies, we highlight how CS may support research in wildlife biology and emphasise the value of fostering communication in CS to improve recruitment of participants and to facilitate learning and mutual trust among different groups of interest (e.g., researchers, stakeholders, students). We further show how specific training for the participants may be needed to obtain reliable data. We consider CS as a suitable tool to enhance research in wildlife biology through the application of open science procedures (i.e., open access to articles and the data on publicly available repositories) to support transparency and sharing experiences.     

Phenological stages of the pomegranate tree (Punka granatum L.)

As in other temperate species, the pomegranate tree shows different phenological characteristics through its vegetative cycle in response to changing temperature. This phenology has been studied as a basis for comparisons of the successive stages of growth and reproduction in different geographical areas and conditions. The variety Mollar de Elche was studied, since it is grown on more than 95% of the total area devoted to this crop in Spain. Thirteen phenological-stages were identified during the annual cycle, starting at bud in dormancy and finishing a year later with leaf fall. These stages are denoted using the BBCH General Scale which uses numerical codes to represent particular stages. The code uses a two-digit number to describe the different phenological states and makes it possible to distinguish between principal and secondary stages of development. The duration of stages was measured in days and as accumulated degree-day.