Shifts of trade in Javan ferret badgers Melogale orientalis from wildlife markets to online platforms: implications for conservation policy, human health and monitoring

Wildlife trade is increasingly impeding the conservation of imperilled wildlife and is a potential threat to human health. Ferret badgers are extensively traded in China, although the trends, drivers and health implications of ferret badger trade in other parts of Asia remain poorly known. Here, we focus on the pet trade of a little known endemic small carnivore species, Javan ferret badger Melogale orientalis in Indonesia, over a 10 yr period (2011-2020). The Javan ferret badger is listed as Least Concern on the IUCN Red List of Threatened Species with an unknown population trend. We aimed to gain insight into the magnitude of this trade, its purposes, price trends, distribution records, health risks and shifts to online platforms. We documented 44 ferret badgers in 11 wildlife markets in Java and Bali and 100 ferret badgers for sale on online platforms. We observed a shift in trade from traditional animal markets only, to trade in these markets as well as online. Asking prices, corrected for inflation, declined significantly from ~USD 37 in 2012 to ~USD 22 in 2020, and were related to the purchasing power in cities where trade occurred. Widespread sale of the species highlights that enforcement continues to be overly passive as any trade in the species is illegal. We recommend that the Javan ferret badger be afforded full national protection and prioritised in monitoring efforts to establish its true conservation status. Additionally, concerted efforts are needed to determine if online trade poses a risk to conservation and human health.

Neural bases of automaticity

Automaticity allows us to perform tasks in a fast, efficient, and effortless manner after sufficient practice. Theories of automaticity propose that across practice processing transitions from being controlled by working memory to being controlled by long-term memory retrieval. Recent event-related potential (ERP) studies have sought to test this prediction, however, these experiments did not use the canonical paradigms used to study automaticity. Specifically, automaticity is typically studied using practice regimes with consistent mapping between targets and distractors and spaced practice with individual targets, features that these previous studies lacked. The aim of the present work was to examine whether the practice-induced shift from working memory to long-term memory inferred from subjects' ERPs is observed under the conditions in which automaticity is traditionally studied. We found that to be the case in 3 experiments, firmly supporting the predictions of theories. In addition, we found that the temporal distribution of practice (massed vs. spaced) modulates the shape of learning curves. The ERP data revealed that the switch to long-term memory is slower for spaced than massed practice, suggesting that memory systems are used in a strategic manner. This finding provides new constraints for theories of learning and automaticity. (PsycINFO Database Record

Using alien coins to test whether simple inference is Bayesian

Reasoning and inference are well-studied aspects of basic cognition that have been explained as statistically optimal Bayesian inference. Using a simplified experimental design, we conducted quantitative comparisons between Bayesian inference and human inference at the level of individuals. In 3 experiments, with more than 13,000 participants, we asked people for prior and posterior inferences about the probability that 1 of 2 coins would generate certain outcomes. Most participants' inferences were inconsistent with Bayes' rule. Only in the simplest version of the task did the majority of participants adhere to Bayes' rule, but even in that case, there was a significant proportion that failed to do so. The current results highlight the importance of close quantitative comparisons between Bayesian inference and human data at the individual-subject level when evaluating models of cognition.

A Comparison of Antiserum and Protein A as Secondary Reagents to Assess Toxoplasma gondii Antibody Titers in Cats and Spotted Hyenas

Toxoplasma gondii is a protozoal parasite with worldwide distribution that is able to infect a wide variety of mammals and birds. Our main goal was to screen for T. gondii antibody titers in a previously untested species, the spotted hyena ( Crocuta crocuta); however, this goal first required us to investigate serological procedures that could be suitable for hyenas. Cats are the closest domestic relations of hyenas, so T. gondii antibody titers were first compared in 26 feral cats with specific or nonspecific fluorophore-labeled secondary reagents, i.e., anti-cat IgG or protein A. Substitution of anti-cat IgG with protein A caused a statistically significant drop in titer measurements in cats (P = 0.01) with a reduction of the geometric mean titer equivalent to 1 doubling-dilution. The same procedures were then applied to captive spotted hyenas. Titers measured in 9 of 10 hyenas were identical whether anti-cat IgG or protein A was used as the secondary reagent: 5 had titers <1:16, 2 had titers of 1:16, and 2 had titers of 1:32. One hyena had maximum titers of 1:64 or 1:32 when anti-cat IgG or protein A was used, respectively. The use of protein A as the secondary reagent in serologic assays can be applied to a range of mammalian species and seems unlikely to affect test specificity; however, the use of protein A may reduce test sensitivity, as suggested in the present study using cats. Despite a control program, some exposure to T. gondii had occurred in the Zoo's spotted hyenas.

Brain and behavior in decision-making

Speed-accuracy tradeoff (SAT) is an adaptive process balancing urgency and caution when making decisions. Computational cognitive theories, known as “evidence accumulation models”, have explained SATs via a manipulation of the amount of evidence necessary to trigger response selection. New light has been shed on these processes by single-cell recordings from monkeys who were adjusting their SAT settings. Those data have been interpreted as inconsistent with existing evidence accumulation theories, prompting the addition of new mechanisms to the models. We show that this interpretation was wrong, by demonstrating that the neural spiking data, and the behavioural data are consistent with existing evidence accumulation theories, without positing additional mechanisms. Our approach succeeds by using the neural data to provide constraints on the cognitive model. Open questions remain about the locus of the link between certain elements of the cognitive models and the neurophysiology, and about the relationship between activity in cortical neurons identified with decision-making vs. activity in downstream areas more closely linked with motor effectors.

In everyday life we constantly balance urgency against caution when making decisions – known as the speed-accuracy tradeoff. Traditionally, computational cognitive theories called “evidence accumulation models” have explained the speed accuracy tradeoff as changes in the amount of evidence necessary to trigger the selection of a response. Recent work recording firing rates from the neurons of monkeys while they made decisions revealed an apparent discrepancy between the firing rates and the way evidence accumulation models explain the speed-accuracy tradeoff. This discrepancy was interpreted as showing that traditional parameter settings were wrong, and that the fundamental dynamic structure of the evidence accumulation model required an addition. This result is important because it calls into question nearly half a century of cognitive science. We show instead that only the parameter settings need be adjusted, not the basic model structure, in order to account for the behavioural data and the recorded neural data. Underlying our results was an integrated approach to the neural and behavioral data, allowing both streams to inform the theoretical development.

Avian embryonic development does not change the stable isotope composition of the calcite eggshell

The avian embryo resorbs most of the calcium for bone formation from the calcite eggshell but the exact mechanisms of the resorption are unknown. The present study tested whether this process results in variable fractionation of the oxygen and carbon isotopes in shell calcium carbonate, which could provide a detailed insight into the temporal and spatial use of the eggshell by the developing embryo. Despite the uncertainty regarding changes in stable isotope composition of the eggshell across developmental stages or regions of the shell, eggshells are a popular resource for the analysis of historic and extant trophic relationships. To clarify how the stable isotope composition varies with embryonic development, the δ(13)C and δ(18)O content of the carbonate fraction in shells of black-headed gull (Larus ridibundus) eggs were sampled at four different stages of embryonic development and at five eggshell regions. No consistent relationship between the stable isotope composition of the eggshell and embryonic development, shell region or maculation was observed, although shell thickness decreased with development in all shell regions. By contrast, individual eggs differed significantly in isotope composition. These results establish that eggshells can be used to investigate a species' carbon and oxygen sources, regardless of the egg's developmental stage.

The selenium levels of mothers and their neonates using hair, breast milk, meconium, and maternal and umbilical cord blood in Van Basin

The objective of the present study is to calculate linear regressions between a mother and her child with respect to their selenium concentration (ng/g) in the following traits: maternal blood and umbilical cord blood, maternal and child hair, maternal milk and child umbilical cord blood, maternal milk and meconium, maternal blood plasma, and child meconium. The data were collected at Research Hospital of the University of Yüzüncü Yil from 30 pairs of mothers and their newborn baby. The mean maternal serum Se level in 30 mothers was 68.52 +/- 3.57 ng/g and cord plasma level was 119.90 +/- 18.08 ng/g. The Se concentration in maternal and neonatal hair was 330.84 +/- 39.03 and 1,124.76 +/- 186.84 ng/g, respectively. The Se concentration of maternal milk at day 14 after delivery was determined as 68.63 +/- 7.78 ng/g (n = 13) and the concentration of Se was 418.90 +/- 45.49 ng/g (n = 22) for meconium of neonatal. There was no significant difference between maternal blood and milk Se levels. However, hair Se concentration was significantly higher than milk and maternal blood Se level. For each trait comparison, the average absolute difference in log(10)-transformed Se concentration was calculated between a mother and her child. The observed average absolute difference was compared with a test distribution of 1,000 resampled bootstrap averages where the number of samples was maintained but the relationship between a mother and her child was randomized among samples (alpha = 0.05).