283 research outputs found

    Land Ecosystems and Hydrology

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    The terrestrial biosphere is an integral component of the Earth Observing System (EOS) science objectives concerning climate change, hydrologic cycle change, and changes in terrestrial productivity. The fluxes o f CO2 and other greenhouse gases from the land surface influence the global circulation models directly, and changes in land cover change the land surface biophysical properties o f energy and mass exchange. Hydrologic cycle perturbations result from terrestrially-induced climate changes, and more directly from changes in land cover acting on surface hydrologic balances. Finally, both climate and hydrology jointly control biospheric productivity, the source o f food, fuel, and fiber for humankind. The role of the land system in each of these three topics is somewhat different, so this chapter is organized into the subtopics of Land-Climate, Land-Hydrology, and Land-Vegetation interactions (Figures 5.1, 5.2, and 5.3)

    The problem of scale in the prediction and management of pathogen spillover

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    Disease emergence events, epidemics and pandemics all underscore the need to predict zoonotic pathogen spillover. Because cross-species transmission is inherently hierarchical, involving processes that occur at varying levels of biological organization, such predictive efforts can be complicated by the many scales and vastness of data potentially required for forecasting. A wide range of approaches are currently used to forecast spillover risk (e.g. macroecology, pathogen discovery, surveillance of human populations, among others), each of which is bound within particular phylogenetic, spatial and temporal scales of prediction. Here, we contextualize these diverse approaches within their forecasting goals and resulting scales of prediction to illustrate critical areas of conceptual and pragmatic overlap. Specifically, we focus on an ecological perspective to envision a research pipeline that connects these different scales of data and predictions from the aims of discovery to intervention. Pathogen discovery and predictions focused at the phylogenetic scale can first provide coarse and pattern-based guidance for which reservoirs, vectors and pathogens are likely to be involved in spillover, thereby narrowing surveillance targets and where such efforts should be conducted. Next, these predictions can be followed with ecologically driven spatio-temporal studies of reservoirs and vectors to quantify spatio-temporal fluctuations in infection and to mechanistically understand how pathogens circulate and are transmitted to humans. This approach can also help identify general regions and periods for which spillover is most likely. We illustrate this point by highlighting several case studies where long-term, ecologically focused studies (e.g. Lyme disease in the northeast USA, Hendra virus in eastern Australia, Plasmodium knowlesi in Southeast Asia) have facilitated predicting spillover in space and time and facilitated the design of possible intervention strategies. Such studies can in turn help narrow human surveillance efforts and help refine and improve future large-scale, phylogenetic predictions. We conclude by discussing how greater integration and exchange between data and predictions generated across these varying scales could ultimately help generate more actionable forecasts and interventions

    Estimating viral prevalence with data fusion for adaptive two-phase pooled sampling.

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    The COVID-19 pandemic has highlighted the importance of efficient sampling strategies and statistical methods for monitoring infection prevalence, both in humans and in reservoir hosts. Pooled testing can be an efficient tool for learning pathogen prevalence in a population. Typically, pooled testing requires a second-phase retesting procedure to identify infected individuals, but when the goal is solely to learn prevalence in a population, such as a reservoir host, there are more efficient methods for allocating the second-phase samples.To estimate pathogen prevalence in a population, this manuscript presents an approach for data fusion with two-phased testing of pooled samples that allows more efficient estimation of prevalence with less samples than traditional methods. The first phase uses pooled samples to estimate the population prevalence and inform efficient strategies for the second phase. To combine information from both phases, we introduce a Bayesian data fusion procedure that combines pooled samples with individual samples for joint inferences about the population prevalence.Data fusion procedures result in more efficient estimation of prevalence than traditional procedures that only use individual samples or a single phase of pooled sampling.The manuscript presents guidance on implementing the first-phase and second-phase sampling plans using data fusion. Such methods can be used to assess the risk of pathogen spillover from reservoir hosts to humans, or to track pathogens such as SARS-CoV-2 in populations

    Localization of a 64-kDa phosphoprotein in the lumen between the outer and inner envelopes of pea chloroplasts

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    The identification and localization of a marker protein for the intermembrane space between the outer and inner chloroplast envelopes is described. This 64-kDa protein is very rapidly labeled by [Îł-32P]ATP at very low (30 nM) ATP concentrations and the phosphoryl group exhibits a high turnover rate. It was possible to establish the presence of the 64-kDa protein in this plastid compartment by using different chloroplast envelope separation and isolation techniques. In addition comparison of labeling kinetics by intact and hypotonically lysed pea chloroplasts support the localization of the 64-kDa protein in the intermembrane space. The 64-kDa protein was present and could be labeled in mixed envelope membranes isolated from hypotonically lysed plastids. Mixed envelope membranes incorporated high amounts of 32P from [Îł-32P]ATP into the 64-kDa protein, whereas separated outer and inner envelope membranes did not show significant phosphorylation of this protein. Water/Triton X-114 phase partitioning demonstrated that the 64-kDa protein is a hydrophilic polypeptide. These findings suggest that the 64-kDa protein is a soluble protein trapped in the space between the inner and outer envelope membranes. After sonication of mixed envelope membranes, the 64-kDa protein was no longer present in the membrane fraction, but could be found in the supernatant after a 110000 Ă— g centrifugation

    Taxonomic patterns in the zoonotic potential of mammalian viruses

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    Predicting and simplifying which pathogens may spill over from animals to humans is a major priority in infectious disease biology. Many efforts to determine which viruses are at risk of spillover use a subset of viral traits to find trait-based associations with spillover. We adapt a new method—phylofactorization—to identify not traits but lineages of viruses at risk of spilling over. Phylofactorization is used to partition the International Committee on Taxonomy of Viruses viral taxonomy based on non-human host range of viruses and whether there exists evidence the viruses have infected humans. We identify clades on a range of taxonomic levels with high or low propensities to spillover, thereby simplifying the classification of zoonotic potential of mammalian viruses. Phylofactorization by whether a virus is zoonotic yields many disjoint clades of viruses containing few to no representatives that have spilled over to humans. Phylofactorization by non-human host breadth yields several clades with significantly higher host breadth. We connect the phylogenetic factors above with life-histories of clades, revisit trait-based analyses, and illustrate how cladistic coarse-graining of zoonotic potential can refine trait-based analyses by illuminating clade-specific determinants of spillover risk

    Ecological and evolutionary drivers of hemoplasma infection and bacterial genotype sharing in a Neotropical bat community

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    Most emerging pathogens can infect multiple species, underlining the importance of understanding the ecological and evolutionary factors that allow some hosts to harbour greater infection prevalence and share pathogens with other species. However, our understanding of pathogen jumps is based primarily around viruses, despite bacteria accounting for the greatest proportion of zoonoses. Because bacterial pathogens in bats (order Chiroptera) can have conservation and human health consequences, studies that examine the ecological and evolutionary drivers of bacterial prevalence and barriers to pathogen sharing are crucially needed. Here were studied haemotropic Mycoplasma spp. (i.e., haemoplasmas) across a speciesâ€rich bat community in Belize over two years. Across 469 bats spanning 33 species, half of individuals and twoâ€thirds of species were haemoplasma positive. Infection prevalence was higher for males and for species with larger body mass and colony sizes. Haemoplasmas displayed high genetic diversity (21 novel genotypes) and strong host specificity. Evolutionary patterns supported codivergence of bats and bacterial genotypes alongside phylogenetically constrained host shifts. Bat species centrality to the network of shared haemoplasma genotypes was phylogenetically clustered and unrelated to prevalence, further suggesting rare—but detectable—bacterial sharing between species. Our study highlights the importance of using fine phylogenetic scales when assessing host specificity and suggests phylogenetic similarity may play a key role in host shifts not only for viruses but also for bacteria. Such work more broadly contributes to increasing efforts to understand crossâ€species transmission and the epidemiological consequences of bacterial pathogens
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