Tree functional diversity affects litter decomposition and arthropod community composition in a tropical forest

Disturbance can alter tree species and functional diversity in tropical forests, which in turn could affect carbon and nutrient cycling via the decomposition of plant litter. However, the influence of tropical tree diversity on forest floor organisms and the processes they mediate are far from clear. We investigated the influence of different litter mixtures on arthropod communities and decomposition processes in a 60‐year‐old lowland tropical forest in Panama, Central America. We used litter mixtures representing pioneer and old growth tree species in experimental mesocosms to assess the links between litter types, decomposition rates, and litter arthropod communities. Overall, pioneer species litter decomposed most rapidly and old growth species litter decomposed the slowest but there were clear non‐additive effects of litter mixtures containing both functional groups. We observed distinct arthropod communities in different litter mixtures at 6 mo, with greater arthropod diversity and abundance in litter from old growth forest species. By comparing the decay of different litter mixtures in mesocosms and conventional litterbags, we demonstrated that our mesocosms represent an effective approach to link studies of litter decomposition and arthropod communities. Our results indicate that changes in the functional diversity of litter could have wider implications for arthropod communities and ecosystem functioning in tropical forests.     

Combining disease models to test for gene-environment interaction in nuclear families

It is useful to have robust gene-environment interaction tests that can utilize a variety of family structures in an efficient way. This article focuses on tests for gene-environment interaction in the presence of main genetic and environmental effects. The objective is to develop powerful tests that can combine trio data with parental genotypes and discordant sibships when parents' genotypes are missing. We first make a modest improvement on a method for discordant sibs (discordant on phenotype), but the approach does not allow one to use families when all offspring are affected, e.g., trios. We then make a modest improvement on a Mendelian transmission-based approach that is inefficient when discordant sibs are available, but can be applied to any nuclear family. Finally, we propose a hybrid approach that utilizes the most efficient method for a specific family type, then combines over families. We utilize this hybrid approach to analyze a chronic obstructive pulmonary disorder dataset to test for gene-environment interaction in the Serpine2 gene with smoking. The methods are freely available in the R package fbati.     

Identification of a novel neuropathogenic Theiler's murine encephalomyelitis virus

Theiler's murine encephalitis viruses (TMEV) are divided into two subgroups based on their neurovirulence. Persistent strains resemble Theiler's original viruses (referred to as the TO subgroup), which largely induce a subclinical polioencephalomyelitis during the acute phase of the disease and can persist in the spinal cord of susceptible animals, inducing a chronic demyelinating disease. In contrast, members of the neurovirulent subgroup cause an acute encephalitis characterized by the rapid onset of paralysis and death within days following intracranial inoculation. We report herein the characterization of a novel neurovirulent strain of TMEV, identified using pyrosequencing technology and referred to as NIHE. Complete coverage of the NIHE viral genome was obtained, and it shares <90% nucleotide sequence identity to known TMEV strains irrespective of subgroup, with the greatest sequence variability being observed in genes encoding the leader and capsid proteins. The histopathological analysis of infected brain and spinal cord demonstrate inflammatory lesions and neuronal necrosis during acute infection with no evidence of viral persistence or chronic disease. Intriguingly, genetic analysis indicates the putative expression of the L protein, considered a hallmark of strains within the persistent subgroup. Thus, the identification and characterization of a novel neurovirulent TMEV strain sharing features previously associated with both subgroups will lead to a deeper understanding of the evolution of TMEV strains and new insights into the determinants of neurovirulence.     

Assessing the Bioavailability and Risk from Metal-Contaminated Soils and Dusts

Exposure to contaminated soil and dust is an important pathway in human health risk assessment. Physical and chemical characteristics and biological factors determine the bioaccessibility/bioavailability of soil and dust contaminants. Within a single sample, contamination may arise from multiple sources of toxic elements that may exist as different species that impact bioavailability. In turn, the bioaccessibility/bioavailability of soil and dust contaminants directly impacts human health risk. Research efforts focusing on development and application of in vitro and in vivo methods to measure the bioaccessibility/bioavailability of metal-contaminated soils have advanced in recent years. The objective of this workshop was to focus on developments in assessing the bioaccessibility/bioavailability of arsenic-contaminated soils, metals’ contamination in urban Canadian residences and potential children's exposures to toxic elements in house dust, an urban community-based study (i.e., West Oakland Residential Lead Assessment), bioavailability studies of soil cadmium, chromium, nickel, and mercury and human exposures to contaminated Brownfield soils. These presentations covered issues related to human health and bioavailability along with the most recent studies on community participation in assessing metals’ contamination, studies of exposures to residential contamination, and in vitro and in vivo methods development for assessing the bioaccessibility/bioavailability of metals in soils and dusts.     

Interior-Point Methods for Estimating Seasonal Parameters in Discrete-Time Infectious Disease Models

Infectious diseases remain a significant health concern around the world. Mathematical modeling of these diseases can help us understand their dynamics and develop more effective control strategies. In this work, we show the capabilities of interior-point methods and nonlinear programming (NLP) formulations to efficiently estimate parameters in multiple discrete-time disease models using measles case count data from three cities. These models include multiplicative measurement noise and incorporate seasonality into multiple model parameters. Our results show that nearly identical patterns are estimated even when assuming seasonality in different model parameters, and that these patterns show strong correlation to school term holidays across very different social settings and holiday schedules. We show that interior-point methods provide a fast and flexible approach to parameterizing models that can be an alternative to more computationally intensive methods.     

Taking a big bite: Working together to better understand the evolution of feeding in primates

The study of adaptation requires the integration of an array of different types of data. A single individual can find such integration daunting, if not impossible. In an effort to clarify the role of diet in the evolution of the primate craniofacial and dental apparatus, we assembled a team of researchers that have various types and degrees of expertise. This interaction has provided a range of insights for all contributors, and this has helped to refine questions, clarify the possibilities and limitations that laboratory and field settings offer, and further explore the ways in which laboratory and field data can be suitably integrated. A complete and accurate picture of dietary adaptation cannot be gained in isolation. Collaboration provides the bridge to a more holistic view of primate biology and evolution.