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Non-forest ecosystems, dominated by shrubs, grasses and herbaceous plants, provide ecosystem services including carbon sequestration and forage for grazing, and are highly sensitive to climatic changes. Yet these ecosystems are poorly represented in remotely sensed biomass products and are undersampled by in situ monitoring. Current global change threats emphasize the need for new tools to capture biomass change in non-forest ecosystems at appropriate scales. Here we developed and deployed a new protocol for photogrammetric height using unoccupied aerial vehicle (UAV) images to test its capability for delivering standardized measurements of biomass across a globally distributed field experiment. We assessed whether canopy height inferred from UAV photogrammetry allows the prediction of aboveground biomass (AGB) across low-stature plant species by conducting 38 photogrammetric surveys over 741 harvested plots to sample 50 species. We found mean canopy height was strongly predictive of AGB across species, with a median adjusted R2 of 0.87 (ranging from 0.46 to 0.99) and median prediction error from leave-one-out cross-validation of 3.9%. Biomass per-unit-of-height was similar within but different among, plant functional types. We found that photogrammetric reconstructions of canopy height were sensitive to wind speed but not sun elevation during surveys. We demonstrated that our photogrammetric approach produced generalizable measurements across growth forms and environmental settings and yielded accuracies as good as those obtained from in situ approaches. We demonstrate that using a standardized approach for UAV photogrammetry can deliver accurate AGB estimates across a wide range of dynamic and heterogeneous ecosystems. Many academic and land management institutions have the technical capacity to deploy these approaches over extents of 1–10 ha−1. Photogrammetric approaches could provide much-needed information required to calibrate and validate the vegetation models and satellite-derived biomass products that are essential to understand vulnerable and understudied non-forested ecosystems around the globe.
The fauna of Curculionoidea (exclusive of the subfamilies Scolytinae and Platypodinae of the Curculionidae) is surveyed for Dade and Monroe Counties in southern Florida. Numbers of genera and species represented are as follows: Anthribidae (12 genera, 22 species), Belidae (1 genus, 2 species), Attelabidae (3 genera, 3 species), Brentidae (6 genera, 14 species) and Curculionidae (115 genera, 249 species). No Nemonychidae are recorded from southern Florida. Included in the totals are 26 species considered as introduced to the region and 5 species likely not established in the region. Twenty apparently undescribed species are recorded. Fifteen are assignable to genera as follows; Ormiscus (2) (Anthribidae), and Podapion (1) (Brentidae), and Prosaldius (1), Acalles (6), Calles (1), Zascelis (1), Notolomus (1), Lixus (1), and Conotmchelus (1) (Curculionidae). The generic placement of 5 undescribed species of Curculionidae is uncertain and descriptions of new genera may be required. New generic records for the United States of America are Homocloeus Jordan (Anthribidae), and Stenotrupis Wollaston (Curculionidae; Cossoninae) and Heilus Kuschel (Curculionidae; Curculioninae). New species records for the United States are Homocloeus distentm Frieser and Homochw sexverrucatm (Suffrian) (Anthribidae) and Stenotrupis acicula Wollaston, Caulophilus rufotestuceus (Champion), Minominus minimus (Boheman) (Curculionidae; Cossoninae), and Anthonomus rubricosus Boheman and Heilus bioculatus (Boheman) (Curculionidae; Curculioninae). Particularly well-represented in terms of species diversity is the anthribid genus Ormiscus (6), the brentid genus Apion (9) and the curculionid genera Listronotus (21), Anthonomus (14), Acalles (13), Conotrachelus (11), Tyloderma (10) and Sphenophorus (10).
Unique features of a global human ectoparasite identified through sequencing of the bed bug genome
(2016)
The bed bug, Cimex lectularius, has re-established itself as a ubiquitous human ectoparasite throughout much of the world during the past two decades. This global resurgence is likely linked to increased international travel and commerce in addition to widespread insecticide resistance. Analyses of the C. lectularius sequenced genome (650 Mb) and 14,220 predicted protein-coding genes provide a comprehensive representation of genes that are linked to traumatic insemination, a reduced chemosensory repertoire of genes related to obligate hematophagy, host–symbiont interactions, and several mechanisms of insecticide resistance. In addition, we document the presence of multiple putative lateral gene transfer events. Genome sequencing and annotation establish a solid foundation for future research on mechanisms of insecticide resistance, human–bed bug and symbiont–bed bug associations, and unique features of bed bug biology that contribute to the unprecedented success of C. lectularius as a human ectoparasite.
Erebaces woodruffi Anderson, new species (Curculionidae: Molytinae: Cryptorhynchini), from Palawan (Philippines) is described and illustrated. This is the second species of the genus Erebaces Pascoe described from the Philippines. It can be separated from Erebaces kidapawanus Pancini by the pair of divergent dorsal pale-scaled lines on the pronotum extended onto the elytra and by the form of the elytral tubercles.
Background: Intracerebral haemorrhage growth is associated with poor clinical outcome and is a therapeutic target for improving outcome. We aimed to determine the absolute risk and predictors of intracerebral haemorrhage growth, develop and validate prediction models, and evaluate the added value of CT angiography.
Methods: In a systematic review of OVID MEDLINE—with additional hand-searching of relevant studies' bibliographies— from Jan 1, 1970, to Dec 31, 2015, we identified observational cohorts and randomised trials with repeat scanning protocols that included at least ten patients with acute intracerebral haemorrhage. We sought individual patient-level data from corresponding authors for patients aged 18 years or older with data available from brain imaging initially done 0·5–24 h and repeated fewer than 6 days after symptom onset, who had baseline intracerebral haemorrhage volume of less than 150 mL, and did not undergo acute treatment that might reduce intracerebral haemorrhage volume. We estimated the absolute risk and predictors of the primary outcome of intracerebral haemorrhage growth (defined as >6 mL increase in intracerebral haemorrhage volume on repeat imaging) using multivariable logistic regression models in development and validation cohorts in four subgroups of patients, using a hierarchical approach: patients not taking anticoagulant therapy at intracerebral haemorrhage onset (who constituted the largest subgroup), patients taking anticoagulant therapy at intracerebral haemorrhage onset, patients from cohorts that included at least some patients taking anticoagulant therapy at intracerebral haemorrhage onset, and patients for whom both information about anticoagulant therapy at intracerebral haemorrhage onset and spot sign on acute CT angiography were known.
Findings: Of 4191 studies identified, 77 were eligible for inclusion. Overall, 36 (47%) cohorts provided data on 5435 eligible patients. 5076 of these patients were not taking anticoagulant therapy at symptom onset (median age 67 years, IQR 56–76), of whom 1009 (20%) had intracerebral haemorrhage growth. Multivariable models of patients with data on antiplatelet therapy use, data on anticoagulant therapy use, and assessment of CT angiography spot sign at symptom onset showed that time from symptom onset to baseline imaging (odds ratio 0·50, 95% CI 0·36–0·70; p<0·0001), intracerebral haemorrhage volume on baseline imaging (7·18, 4·46–11·60; p<0·0001), antiplatelet use (1·68, 1·06–2·66; p=0·026), and anticoagulant use (3·48, 1·96–6·16; p<0·0001) were independent predictors of intracerebral haemorrhage growth (C-index 0·78, 95% CI 0·75–0·82). Addition of CT angiography spot sign (odds ratio 4·46, 95% CI 2·95–6·75; p<0·0001) to the model increased the C-index by 0·05 (95% CI 0·03–0·07).
Interpretation: In this large patient-level meta-analysis, models using four or five predictors had acceptable to good discrimination. These models could inform the location and frequency of observations on patients in clinical practice, explain treatment effects in prior randomised trials, and guide the design of future trials.
Funding: UK Medical Research Council and British Heart Foundation.
A new global synthesis and biomization of long (> 40 kyr) pollen-data records is presented, and used with simulations from the HadCM3 and FAMOUS climate models to analyse the dynamics of the global terrestrial biosphere and carbon storage over the last glacial–interglacial cycle. Global modelled (BIOME4) biome distributions over time generally agree well with those inferred from pollen data. The two climate models show good agreement in global net primary productivity (NPP). NPP is strongly influenced by atmospheric carbon dioxide (CO2) concentrations through CO2 fertilization. The combined effects of modelled changes in vegetation and (via a simple model) soil carbon result in a global terrestrial carbon storage at the Last Glacial Maximum that is 210–470 Pg C less than in pre-industrial time. Without the contribution from exposed glacial continental shelves the reduction would be larger, 330–960 Pg C. Other intervals of low terrestrial carbon storage include stadial intervals at 108 and 85 kaBP, and between 60 and 65 kaBP during Marine Isotope Stage 4. Terrestrial carbon storage, determined by the balance of global NPP and decomposition, influences the stable carbon isotope composition (δ 13C) of seawater because terrestrial organic carbon is depleted in 13C. Using a simple carbon-isotope mass balance equation we find agreement in trends between modelled ocean δ 13C based on modelled land carbon storage, and palaeo-archives of ocean δ 13C, confirming that terrestrial carbon storage variations may be important drivers of ocean δ 13 C changes.
A new global synthesis and biomization of long (> 40 kyr) pollen-data records is presented and used with simulations from the HadCM3 and FAMOUS climate models and the BIOME4 vegetation model to analyse the dynamics of the global terrestrial biosphere and carbon storage over the last glacial–interglacial cycle. Simulated biome distributions using BIOME4 driven by HadCM3 and FAMOUS at the global scale over time generally agree well with those inferred from pollen data. Global average areas of grassland and dry shrubland, desert, and tundra biomes show large-scale increases during the Last Glacial Maximum, between ca. 64 and 74 ka BP and cool substages of Marine Isotope Stage 5, at the expense of the tropical forest, warm-temperate forest, and temperate forest biomes. These changes are reflected in BIOME4 simulations of global net primary productivity, showing good agreement between the two models. Such changes are likely to affect terrestrial carbon storage, which in turn influences the stable carbon isotopic composition of seawater as terrestrial carbon is depleted in 13C.
Investigators in the cognitive neurosciences have turned to Big Data to address persistent replication and reliability issues by increasing sample sizes, statistical power, and representativeness of data. While there is tremendous potential to advance science through open data sharing, these efforts unveil a host of new questions about how to integrate data arising from distinct sources and instruments. We focus on the most frequently assessed area of cognition - memory testing - and demonstrate a process for reliable data harmonization across three common measures. We aggregated raw data from 53 studies from around the world which measured at least one of three distinct verbal learning tasks, totaling N = 10,505 healthy and brain-injured individuals. A mega analysis was conducted using empirical bayes harmonization to isolate and remove site effects, followed by linear models which adjusted for common covariates. After corrections, a continuous item response theory (IRT) model estimated each individual subject’s latent verbal learning ability while accounting for item difficulties. Harmonization significantly reduced inter-site variance by 37% while preserving covariate effects. The effects of age, sex, and education on scores were found to be highly consistent across memory tests. IRT methods for equating scores across AVLTs agreed with held-out data of dually-administered tests, and these tools are made available for free online. This work demonstrates that large-scale data sharing and harmonization initiatives can offer opportunities to address reproducibility and integration challenges across the behavioral sciences.