Scoping the use of predictive models to address priority questions concerning terrestrial biodiversity

Rapid environmental change caused by anthropogenic activities has a major influence on the state of natural ecosystems, impacting the biodiversity and human societies that depend on them. Determining the likely future impacts of environmental changes, and how to manage them, can be greatly enhanced using modelling approaches able to predict future ecosystem states and biodiversity patterns. This report scopes the priorities and potential for informative predictive analyses of terrestrial biodiversity patterns. Specifically, the report describes 12 research priorities and broadly summarises the data requirements needed for addressing them using predictive modelling. The report concludes with some more detailed case studies of research questions and how they could be addressed

In vitro neuroprotective activities of two distinct probiotic consortia

Neurodegeneration has been linked to changes in the gut microbiota and this study compares the neuroprotective capability of two bacterial consortia, known as Lab4 and Lab4b, using the established SH-SY5Y neuronal cell model. Firstly, varying total antioxidant capacities (TAC) were identified in the intact cells from each consortia and their secreted metabolites, referred to as conditioned media (CM). 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) and Crystal Violet (CV) assays of cell viability revealed that Lab4 CM and Lab4b CM could induce similar levels of proliferation in SH-SY5Y cells and, despite divergent TAC, possessed a comparable ability to protect undifferentiated and retinoic acid-differentiated cells from the cytotoxic actions of rotenone and undifferentiated cells from the cytotoxic actions of 1-methyl-4-phenylpyridinium iodide (MPP+). Lab4 CM and Lab4b CM also had the ability to attenuate rotenone-induced apoptosis and necrosis with Lab4b inducing the greater effect. Both consortia showed an analogous ability to attenuate intracellular reactive oxygen species accumulation in SH-SY5Y cells although the differential upregulation of genes encoding glutathione reductase and superoxide dismutase by Lab4 CM and Lab4b CM, respectively, implicates the involvement of consortia-specific antioxidative mechanisms of action. This study implicates Lab4 and Lab4b as potential neuroprotective agents and justifies their inclusion in further in vivo studies

Using GIS-linked Bayesian Belief Networks as a tool for modelling urban biodiversity

The ability to predict spatial variation in biodiversity is a long-standing but elusive objective of landscape ecology. It depends on a detailed understanding of relationships between landscape and patch structure and taxonomic richness, and accurate spatial modelling. Complex heterogeneous environments such as cities pose particular challenges, as well as heightened relevance, given the increasing rate of urbanisation globally. Here we use a GIS-linked Bayesian Belief Network approach to test whether landscape and patch structural characteristics (including vegetation height, green-space patch size and their connectivity) drive measured taxonomic richness of numerous invertebrate, plant, and avian groups. We find that modelled richness is typically higher in larger and better-connected green-spaces with taller vegetation, indicative of more complex vegetation structure and consistent with the principle of ‘bigger, better, and more joined up’. Assessing the relative importance of these variables indicates that vegetation height is the most influential in determining richness for a majority of taxa. There is variation, however, between taxonomic groups in the relationships between richness and landscape structural characteristics, and the sensitivity of these relationships to particular predictors. Consequently, despite some broad commonalities, there will be trade-offs between different taxonomic groups when designing urban landscapes to maximise biodiversity. This research demonstrates the feasibility of using a GIS-coupled Bayesian Belief Network approach to model biodiversity at fine spatial scales in complex landscapes where current data and appropriate modelling approaches are lacking, and our findings have important implications for ecologists, conservationists and planners

A conserved fungal glycosyltransferase facilitates pathogenesis of plants by enabling hyphal growth on solid surfaces

Article Authors Metrics Comments Related Content Abstract Author summary Introduction Results and discussion Conclusions Methods Supporting information Acknowledgments References Reader Comments (0) Media Coverage (0) Figures Abstract Pathogenic fungi must extend filamentous hyphae across solid surfaces to cause diseases of plants. However, the full inventory of genes which support this is incomplete and many may be currently concealed due to their essentiality for the hyphal growth form. During a random T-DNA mutagenesis screen performed on the pleomorphic wheat (Triticum aestivum) pathogen Zymoseptoria tritici, we acquired a mutant unable to extend hyphae specifically when on solid surfaces. In contrast “yeast-like” growth, and all other growth forms, were unaffected. The inability to extend surface hyphae resulted in a complete loss of virulence on plants. The affected gene encoded a predicted type 2 glycosyltransferase (ZtGT2). Analysis of >800 genomes from taxonomically diverse fungi highlighted a generally widespread, but discontinuous, distribution of ZtGT2 orthologues, and a complete absence of any similar proteins in non-filamentous ascomycete yeasts. Deletion mutants of the ZtGT2 orthologue in the taxonomically un-related fungus Fusarium graminearum were also severely impaired in hyphal growth and non-pathogenic on wheat ears. ZtGT2 expression increased during filamentous growth and electron microscopy on deletion mutants (ΔZtGT2) suggested the protein functions to maintain the outermost surface of the fungal cell wall. Despite this, adhesion to leaf surfaces was unaffected in ΔZtGT2 mutants and global RNAseq-based gene expression profiling highlighted that surface-sensing and protein secretion was also largely unaffected. However, ΔZtGT2 mutants constitutively overexpressed several transmembrane and secreted proteins, including an important LysM-domain chitin-binding virulence effector, Zt3LysM. ZtGT2 likely functions in the synthesis of a currently unknown, potentially minor but widespread, extracellular or outer cell wall polysaccharide which plays a key role in facilitating many interactions between plants and fungi by enabling hyphal growth on solid matrices

A model-based approach to climate reconstruction using tree-ring data

Quantifying long-term historical climate is fundamental to understanding recent climate change. Most instrumentally recorded climate data are only available for the past 200 years, s o proxy observations from natural archives are often considered. We describe a model-based approach to reconstructing climate defined in terms of raw tree-ring measurement data that simultaneously accounts for non-climatic and climatic variability. In this approach we specify a joint model for the tree-ring data and climate variable that we fit using Bayesian inference. We consider a range of prior densities and compare the modeling approach to current methodology using an example case of Scots pine from Torneträsk, Sweden to reconstruct growing season temperature. We describe how current approaches translate into particular model assumptions. We explore how changes to various components in the model-based approach affect the resulting reconstruction. We show that minor changes in model specification can have little effect on model fit but lead to large changes in the predictions. In particular, the periods of relatively warmer and cooler temperatures are robust between models, but the magnitude of the resulting temperatures are highly model dependent. Such sensitivity may not be apparent with traditional approaches because the underlying statistical model is often hidden or poorly described