Hidden Markov analysis describes dive patterns in semiaquatic animals

Existing methods of dive analysis, developed for fully aquatic animals, tend to focus on frequency of behaviors rather than transitions between them. They, therefore, do not account for the variability of behavior of semiaquatic animals, and the switching between terrestrial and aquatic environments. This is the first study to use hidden Markov models (HMM) to divide dives of a semiaquatic animal into clusters and thus identify the environmental predictors of transition between behavioral modes. We used 18 existing data sets of the dives of 14 American mink (Neovison vison) fitted with time-depth recorders in lowland England. Using HMM, we identified 3 behavioral states (1, temporal cluster of dives; 2, more loosely aggregated diving within aquatic activity; and 3, terminal dive of a cluster or a single, isolated dive). Based on the higher than expected proportion of dives in State 1, we conclude that mink tend to dive in clusters. We found no relationship between temperature and the proportion of dives in each state or between temperature and the rate of transition between states, meaning that in our study area, mink are apparently not adopting different diving strategies at different temperatures. Transition analysis between states has shown that there is no correlation between ambient temperature and the likelihood of mink switching from one state to another, that is, changing foraging modes. The variables provided good discrimination and grouped into consistent states well, indicating promise for further application of HMM and other state transition analyses in studies of semiaquatic animals.

Population ecology of the Asian house rat (Rattus tanezumi) in complex lowland agroecosystems in the Philippines

Context. Rattus tanezumi (the Asian house rat) is the principal rodent pest of rice and coconut crops in the Philippines. Little is known about the population and breeding ecology of R. tanezumi in complex agroecosystems; thus, current methods of rodent control may be inappropriate or poorly implemented. Aims. To investigate the habitat use, population dynamics and breeding biology of R. tanezumi in complex lowland agroecosystems of the Sierra Madre Biodiversity Corridor, Luzon, and to develop ecologically based rodent management (EBRM) strategies that will target specific habitats at specific times to improve cost-efficiency and minimise non-target risks. Methods. An 18-month trapping study was conducted in rice monoculture, rice adjacent to coconut, coconut groves, coconut-based agroforest and forest habitats. Trapped animals were measured, marked and assessed for breeding condition. Key results. Five species of rodent were captured across all habitats with R. tanezumi the major pest species in both the rice and coconut crops. The stage of the rice crop was a major factor influencing the habitat use and breeding biology of R. tanezumi. In rice fields, R. tanezumi abundance was highest during the tillering to ripening stages of the rice crop and lowest during the seedling stage, whereas in coconut groves abundance was highest from the seedling to tillering stage of nearby rice crops. Peaks in breeding activity occurred from the booting stage of the rice crop until just after harvest, but >10% of females were in breeding condition at each month of the year. Conclusions. In contrast with the practices applied by rice farmers in the study region, the most effective time for lethal management based on the breeding ecology of R. tanezumi is likely to be during the early stages of the rice crop, before the booting stage. Farmers generally apply control actions as individuals. We recommend coordinated community action. Continuous breeding throughout the year may necessitate two community campaigns per rice cropping season. To limit population growth, the most effective time to reduce nesting habitat is from the booting stage until harvest. Implications. By adopting EBRM strategies, we expect a reduction in costs associated with rodent control, as well as improved yield and reduced risk to non-target species.

Predicting how many animals will be where: how to build, calibrate and evaluate individual-based models

Individual-based models (IBMs) can simulate the actions of individual animals as they interact with one another and the landscape in which they live. When used in spatially-explicit landscapes IBMs can show how populations change over time in response to management actions. For instance, IBMs are being used to design strategies of conservation and of the exploitation of fisheries, and for assessing the effects on populations of major construction projects and of novel agricultural chemicals. In such real world contexts, it becomes especially important to build IBMs in a principled fashion, and to approach calibration and evaluation systematically. We argue that insights from physiological and behavioural ecology offer a recipe for building realistic models, and that Approximate Bayesian Computation (ABC) is a promising technique for the calibration and evaluation of IBMs. IBMs are constructed primarily from knowledge about individuals. In ecological applications the relevant knowledge is found in physiological and behavioural ecology, and we approach these from an evolutionary perspective by taking into account how physiological and behavioural processes contribute to life histories, and how those life histories evolve. Evolutionary life history theory shows that, other things being equal, organisms should grow to sexual maturity as fast as possible, and then reproduce as fast as possible, while minimising per capita death rate. Physiological and behavioural ecology are largely built on these principles together with the laws of conservation of matter and energy. To complete construction of an IBM information is also needed on the effects of competitors, conspecifics and food scarcity; the maximum rates of ingestion, growth and reproduction, and life-history parameters. Using this knowledge about physiological and behavioural processes provides a principled way to build IBMs, but model parameters vary between species and are often difficult to measure. A common solution is to manually compare model outputs with observations from real landscapes and so to obtain parameters which produce acceptable fits of model to data. However, this procedure can be convoluted and lead to over-calibrated and thus inflexible models. Many formal statistical techniques are unsuitable for use with IBMs, but we argue that ABC offers a potential way forward. It can be used to calibrate and compare complex stochastic models and to assess the uncertainty in their predictions. We describe methods used to implement ABC in an accessible way and illustrate them with examples and discussion of recent studies. Although much progress has been made, theoretical issues remain, and some of these are outlined and discussed.

Functional identity and diversity of animals predict ecosystem functioning better than species-based indices

Drastic biodiversity declines have raised concerns about the deterioration of ecosystem functions and have motivated much recent research on the relationship between species diversity and ecosystem functioning. A functional trait framework has been proposed to improve the mechanistic understanding of this relationship, but this has rarely been tested for organisms other than plants. We analysed eight datasets, including five animal groups, to examine how well a trait-based approach, compared with a more traditional taxonomic approach, predicts seven ecosystem functions below- and above-ground. Trait-based indices consistently provided greater explanatory power than species richness or abundance. The frequency distributions of single or multiple traits in the community were the best predictors of ecosystem functioning. This implies that the ecosystem functions we investigated were underpinned by the combination of trait identities (i.e. single-trait indices) and trait complementarity (i.e. multi-trait indices) in the communities. Our study provides new insights into the general mechanisms that link biodiversity to ecosystem functioning in natural animal communities and suggests that the observed responses were due to the identity and dominance patterns of the trait composition rather than the number or abundance of species per se.

Diversity of STs, plasmids and ESBL genes among Escherichia coli from humans, animals and food in Germany, the Netherlands and the UK

This study aimed to compare ESBL-producing Escherichia coli causing infections in humans with infecting or commensal isolates from animals and isolates from food of animal origin in terms of the strain types, the ESBL gene present and the plasmids that carry the respective ESBL genes. A collection of 353 ESBL-positive E. coli isolates from the UK, the Netherlands and Germany were studied by MLST and ESBL genes were identified. Characterization of ESBL gene-carrying plasmids was performed using PCR-based replicon typing. Moreover, IncI1-Iγ and IncN plasmids were characterized by plasmid MLST. The ESBL-producing E. coli represented 158 different STs with ST131, ST10 and ST88 being the most common. Overall, blaCTX-M-1 was the most frequently detected ESBL gene, followed by blaCTX-M-15, which was the most common ESBL gene in the human isolates. The most common plasmid replicon type overall was IncI1-Iγ followed by multiple IncF replicons. ESBL genes were present in a wide variety of E. coli STs. IncI1-Iγ plasmids that carried the blaCTX-M-1 gene were widely disseminated amongst STs in isolates from animals and humans, whereas other plasmids and STs appeared to be more restricted to isolates from specific hosts.

Maternal weaning modulates emotional behavior and regulates the gut-brain axis

Evidence shows that nutritional and environmental stress stimuli during postnatal period influence brain development and interactions between gut and brain. In this study we show that in rats, prevention of weaning from maternal milk results in depressive-like behavior, which is accompanied by changes in the gut bacteria and host metabolism. Depressive-like behavior was studied using the forced-swim test on postnatal day (PND) 25 in rats either weaned on PND 21, or left with their mother until PND 25 (non-weaned). Non-weaned rats showed an increased immobility time consistent with a depressive phenotype. Fluorescence in situ hybridization showed non-weaned rats to harbor significantly lowered Clostridium histolyticum bacterial groups but exhibit marked stress-induced increases. Metabonomic analysis of urine from these animals revealed significant differences in the metabolic profiles, with biochemical phenotypes indicative of depression in the non-weaned animals. In addition, non-weaned rats showed resistance to stress-induced modulation of oxytocin receptors in amygdala nuclei, which is indicative of passive stress-coping mechanism. We conclude that delaying weaning results in alterations to the gut microbiota and global metabolic profiles which may contribute to a depressive phenotype and raise the issue that mood disorders at early developmental ages may reflect interplay between mammalian host and resident bacteria.