96 research outputs found

    Quantifying Tropical Plant Diversity Requires an Integrated Technological Approach

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    Tropical biomes are the most diverse plant communities on Earth, and quantifying this diversity at large spatial scales is vital for many purposes. As macroecological approaches proliferate, the taxonomic uncertainties in species occurrence data are easily neglected and can lead to spurious findings in downstream analyses. Here, we argue that technological approaches offer potential solutions, but there is no single silver bullet to resolve uncertainty in plant biodiversity quantification. Instead, we propose the use of artificial intelligence (AI) approaches to build a data-driven framework that integrates several data sources – including spectroscopy, DNA sequences, image recognition, and morphological data. Such a framework would provide a foundation for improving species identification in macroecological analyses while simultaneously improving the taxonomic process of species delimitation

    An empirical approach towards the efficient and optimal production of influenza-neutralizing ovine polyclonal antibodies demonstrates that the novel adjuvant CoVaccine HT(TM) is functionally superior to Freund's adjuvant

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    Passive immunotherapies utilising polyclonal antibodies could have a valuable role in preventing and treating infectious diseases such as influenza, particularly in pandemic situations but also in immunocompromised populations such as the elderly, the chronically immunosuppressed, pregnant women, infants and those with chronic diseases. The aim of this study was to optimise current methods used to generate ovine polyclonal antibodies. Polyclonal antibodies to baculovirus-expressed recombinant influenza haemagglutinin from A/Puerto Rico/8/1934 H1N1 (PR8) were elicited in sheep using various immunisation regimens designed to investigate the priming immunisation route, adjuvant formulation, sheep age, and antigen dose, and to empirically ascertain which combination maximised antibody output. The novel adjuvant CoVaccine HT™ was compared to Freund’s adjuvant which is currently the adjuvant of choice for commercial production of ovine polyclonal Fab therapies. CoVaccine HT™ induced significantly higher titres of functional ovine anti-haemagglutinin IgG than Freund’s adjuvant but with fewer side effects, including reduced site reactions. Polyclonal hyperimmune sheep sera effectively neutralised influenza virus in vitro and, when given before or after influenza virus challenge, prevented the death of infected mice. Neither the age of the sheep nor the route of antigen administration appeared to influence antibody titre. Moreover, reducing the administrated dose of haemagglutinin antigen minimally affected antibody titre. Together, these results suggest a cost effective way of producing high and sustained yields of functional ovine polyclonal antibodies specifically for the prevention and treatment of globally significant diseases.Natalie E. Stevens, Cara K. Fraser, Mohammed Alsharifi, Michael P. Brown, Kerrilyn R. Diener, John D. Haybal

    Understanding different dominance patterns in western Amazonian forests

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    Dominance of neotropical tree communities by a few species is widely documented, but dominant trees show a variety of distributional patterns still poorly understood. Here, we used 503 forest inventory plots (93,719 individuals ≥2.5 cm diameter, 2609 species) to explore the relationships between local abundance, regional frequency and spatial aggregation of dominant species in four main habitat types in western Amazonia. Although the abundance-occupancy relationship is positive for the full dataset, we found that among dominant Amazonian tree species, there is a strong negative relationship between local abundance and regional frequency and/or spatial aggregation across habitat types. Our findings suggest an ecological trade-off whereby dominant species can be locally abundant (local dominants) or regionally widespread (widespread dominants), but rarely both (oligarchs). Given the importance of dominant species as drivers of diversity and ecosystem functioning, unravelling different dominance patterns is a research priority to direct conservation efforts in Amazonian forests

    Greenhouse gas emissions resulting from conversion of peat swamp forest to oil palm plantation.

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    Conversion of tropical peat swamp forest to drainage-based agriculture alters greenhouse gas (GHG) production, but the magnitude of these changes remains highly uncertain. Current emissions factors for oil palm grown on drained peat do not account for temporal variation over the plantation cycle and only consider CO2 emissions. Here, we present direct measurements of GHGs emitted during the conversion from peat swamp forest to oil palm plantation, accounting for CH4 and N2O as well as CO2. Our results demonstrate that emissions factors for converted peat swamp forest is in the range 70-117 t CO2 eq ha-1 yr-1 (95% confidence interval, CI), with CO2 and N2O responsible for ca. 60 and ca. 40% of this value, respectively. These GHG emissions suggest that conversion of Southeast Asian peat swamp forest is contributing between 16.6 and 27.9% (95% CI) of combined total national GHG emissions from Malaysia and Indonesia or 0.44 and 0.74% (95% CI) of annual global emissions

    Imaging spectroscopy predicts variable distance decay across contrasting Amazonian tree communities

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    1. The forests of Amazonia are among the most biodiverse on Earth, yet accurately quantifying how species composition varies through space (i.e., beta‐diversity) remains a significant challenge. Here, we use high‐fidelity airborne imaging spectroscopy from the Carnegie Airborne Observatory to quantify a key component of beta‐diversity, the distance decay in species similarity through space, across three landscapes in Northern Peru. We then compared our derived distance decay relationships to theoretical expectations obtained from a Poisson Cluster Process, known to match well with empirical distance decay relationships at local scales. 2. We used an unsupervised machine learning approach to estimate spatial turnover in species composition from the imaging spectroscopy data. We first validated this approach across two landscapes using an independent dataset of forest composition in 49 forest census plots (0.1–1.5 ha). We then applied our approach to three landscapes, which together represented terra firme clay forest, seasonally flooded forest and white‐sand forest. We finally used our approach to quantify landscape‐scale distance decay relationships and compared these with theoretical distance decay relationships derived from a Poisson Cluster Process. 3. We found a significant correlation of similarity metrics between spectral data and forest plot data, suggesting that beta‐diversity within and among forest types can be accurately estimated from airborne spectroscopic data using our unsupervised approach. We also found that estimated distance decay in species similarity varied among forest types, with seasonally flooded forests showing stronger distance decay than white‐sand and terra firme forests. Finally, we demonstrated that distance decay relationships derived from the theoretical Poisson Cluster Process compare poorly with our empirical relationships. 4. Synthesis. Our results demonstrate the efficacy of using high‐fidelity imaging spectroscopy to estimate beta‐diversity and continuous distance decay in lowland tropical forests. Furthermore, our findings suggest that distance decay relationships vary substantially among forest types, which has important implications for conserving these valuable ecosystems. Finally, we demonstrate that a theoretical Poisson Cluster Process poorly predicts distance decay in species similarity as conspecific aggregation occurs across a range of nested scales within larger landscapes

    Age, extent and carbon storage of the central Congo Basin peatland complex

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    Peatlands are carbon-rich ecosystems that cover just three per cent of Earth's land surface, but store one-third of soil carbon. Peat soils are formed by the build-up of partially decomposed organic matter under waterlogged anoxic conditions. Most peat is found in cool climatic regions where unimpeded decomposition is slower, but deposits are also found under some tropical swamp forests. Here we present field measurements from one of the world's most extensive regions of swamp forest, the Cuvette Centrale depression in the central Congo Basin. We find extensive peat deposits beneath the swamp forest vegetation (peat defined as material with an organic matter content of at least 65 per cent to a depth of at least 0.3 metres). Radiocarbon dates indicate that peat began accumulating from about 10,600 years ago, coincident with the onset of more humid conditions in central Africa at the beginning of the Holocene. The peatlands occupy large interfluvial basins, and seem to be largely rain-fed and ombrotrophic-like (of low nutrient status) systems. Although the peat layer is relatively shallow (with a maximum depth of 5.9 metres and a median depth of 2.0 metres), by combining in situ and remotely sensed data, we estimate the area of peat to be approximately 145,500 square kilometres (95 per cent confidence interval of 131,900-156,400 square kilometres), making the Cuvette Centrale the most extensive peatland complex in the tropics. This area is more than five times the maximum possible area reported for the Congo Basin in a recent synthesis of pantropical peat extent. We estimate that the peatlands store approximately 30.6 petagrams (30.6 × 10(15) grams) of carbon belowground (95 per cent confidence interval of 6.3-46.8 petagrams of carbon)-a quantity that is similar to the above-ground carbon stocks of the tropical forests of the entire Congo Basin. Our result for the Cuvette Centrale increases the best estimate of global tropical peatland carbon stocks by 36 per cent, to 104.7 petagrams of carbon (minimum estimate of 69.6 petagrams of carbon; maximum estimate of 129.8 petagrams of carbon). This stored carbon is vulnerable to land-use change and any future reduction in precipitation

    Early Onset Prion Disease from Octarepeat Expansion Correlates with Copper Binding Properties

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    Insertional mutations leading to expansion of the octarepeat domain of the prion protein (PrP) are directly linked to prion disease. While normal PrP has four PHGGGWGQ octapeptide segments in its flexible N-terminal domain, expanded forms may have up to nine additional octapeptide inserts. The type of prion disease segregates with the degree of expansion. With up to four extra octarepeats, the average onset age is above 60 years, whereas five to nine extra octarepeats results in an average onset age between 30 and 40 years, a difference of almost three decades. In wild-type PrP, the octarepeat domain takes up copper (Cu2+) and is considered essential for in vivo function. Work from our lab demonstrates that the copper coordination mode depends on the precise ratio of Cu2+ to protein. At low Cu2+ levels, coordination involves histidine side chains from adjacent octarepeats, whereas at high levels each repeat takes up a single copper ion through interactions with the histidine side chain and neighboring backbone amides. Here we use both octarepeat constructs and recombinant PrP to examine how copper coordination modes are influenced by octarepeat expansion. We find that there is little change in affinity or coordination mode populations for octarepeat domains with up to seven segments (three inserts). However, domains with eight or nine total repeats (four or five inserts) become energetically arrested in the multi-histidine coordination mode, as dictated by higher copper uptake capacity and also by increased binding affinity. We next pooled all published cases of human prion disease resulting from octarepeat expansion and find remarkable agreement between the sudden length-dependent change in copper coordination and onset age. Together, these findings suggest that either loss of PrP copper-dependent function or loss of copper-mediated protection against PrP polymerization makes a significant contribution to early onset prion disease

    Sustainable palm fruit harvesting as a pathway to conserve Amazon peatland forests

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    Sustainable management of intact tropical peatlands is crucial for climate change mitigation, for biodiversity conservation and to support the livelihoods of local communities. Here, we explore whether sustainable fruit harvesting from Mauritia flexuosa palms could support these linked goals by increasing fruit production and incomes across the 2.8 million hectares of the most carbon-dense ecosystem in Amazonia: the lowland peatlands of northeastern Peru. M. flexuosa is dioecious, and fruits are typically harvested by felling female palms; the proportion of female palms therefore provides a good indicator of the health of a stand. Across 93 widely distributed sites, we found that the proportion of female palms increases with travel time to the urban market, and overall, fruit harvesting has halved the current potential production and income from this resource. However, significantly more female palms are found where fruit are harvested by climbing. We estimate that region-wide uptake of climbing could eventually increase potential fruit production by 51% and increase its gross value to US$62 ± 28.2 million yr–1. These findings demonstrate the high cost of unsustainable resource extraction in Neotropical forests and outline a practical path to conserve and sustainably exploit one of the most carbon-rich landscapes on the planet

    A Coarse-Grained Biophysical Model of E. coli and Its Application to Perturbation of the rRNA Operon Copy Number

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    We propose a biophysical model of Escherichia coli that predicts growth rate and an effective cellular composition from an effective, coarse-grained representation of its genome. We assume that E. coli is in a state of balanced exponential steadystate growth, growing in a temporally and spatially constant environment, rich in resources. We apply this model to a series of past measurements, where the growth rate and rRNA-to-protein ratio have been measured for seven E. coli strains with an rRNA operon copy number ranging from one to seven (the wild-type copy number). These experiments show that growth rate markedly decreases for strains with fewer than six copies. Using the model, we were able to reproduce these measurements. We show that the model that best fits these data suggests that the volume fraction of macromolecules inside E. coli is not fixed when the rRNA operon copy number is varied. Moreover, the model predicts that increasing the copy number beyond seven results in a cytoplasm densely packed with ribosomes and proteins. Assuming that under such overcrowded conditions prolonged diffusion times tend to weaken binding affinities, the model predicts that growth rate will not increase substantially beyond the wild-type growth rate, as indicated by other experiments. Our model therefore suggests that changing the rRNA operon copy number of wild-type E. coli cells growing in a constant rich environment does not substantially increase their growth rate. Other observations regarding strains with an altered rRNA operon copy number, such as nucleoid compaction and the rRNA operon feedback response, appear to be qualitatively consistent with this model. In addition, we discuss possible design principles suggested by the model and propose further experiments to test its validity
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