Functional organization of human sensorimotor cortex for speech articulation.

Speaking is one of the most complex actions that we perform, but nearly all of us learn to do it effortlessly. Production of fluent speech requires the precise, coordinated movement of multiple articulators (for example, the lips, jaw, tongue and larynx) over rapid time scales. Here we used high-resolution, multi-electrode cortical recordings during the production of consonant-vowel syllables to determine the organization of speech sensorimotor cortex in humans. We found speech-articulator representations that are arranged somatotopically on ventral pre- and post-central gyri, and that partially overlap at individual electrodes. These representations were coordinated temporally as sequences during syllable production. Spatial patterns of cortical activity showed an emergent, population-level representation, which was organized by phonetic features. Over tens of milliseconds, the spatial patterns transitioned between distinct representations for different consonants and vowels. These results reveal the dynamic organization of speech sensorimotor cortex during the generation of multi-articulator movements that underlies our ability to speak

Ames life science telescience testbed evaluation

Eight surrogate spaceflight mission specialists participated in a real-time evaluation of remote coaching using the Ames Life Science Telescience Testbed facility. This facility consisted of three remotely located nodes: (1) a prototype Space Station glovebox; (2) a ground control station; and (3) a principal investigator's (PI) work area. The major objective of this project was to evaluate the effectiveness of telescience techniques and hardware to support three realistic remote coaching science procedures: plant seed germinator charging, plant sample acquisition and preservation, and remote plant observation with ground coaching. Each scenario was performed by a subject acting as flight mission specialist, interacting with a payload operations manager and a principal investigator expert. All three groups were physically isolated from each other yet linked by duplex audio and color video communication channels and networked computer workstations. Workload ratings were made by the flight and ground crewpersons immediately after completing their assigned tasks. Time to complete each scientific procedural step was recorded automatically. Two expert observers also made performance ratings and various error assessments. The results are presented and discussed

Spatiotemporal studies of black spruce forest soils and implications for the fate of C

Post-fire storage of carbon (C) in organic-soil horizons was measured in one Canadian and three Alaskan chronosequences in black spruce forests, together spanning stand ages of nearly 200 yrs. We used a simple mass balance model to derive estimates of inputs, losses, and accumulation rates of C on timescales of years to centuries. The model performed well for the surface and total organic soil layers and presented questions for resolving the dynamics of deeper organic soils. C accumulation in all study areas is on the order of 20–40 gC/m2/yr for stand ages up to ∼200 yrs. Much larger fluxes, both positive and negative, are detected using incremental changes in soil C stocks and by other studies using eddy covariance methods for CO2. This difference suggests that over the course of stand replacement, about 80% of all net primary production (NPP) is returned to the atmosphere within a fire cycle, while about 20% of NPP enters the organic soil layers and becomes available for stabilization or loss via decomposition, leaching, or combustion. Shifts toward more frequent and more severe burning and degradation of deep organic horizons would likely result in an acceleration of the carbon cycle, with greater CO2 emissions from these systems overall

Integrating forest inventory and analysis data into a LIDAR-based carbon monitoring system

Forest Inventory and Analysis (FIA) data may be a valuable component of a LIDAR-based carbon monitoring system, but integration of the two observation systems is not without challenges. To explore integration methods, two wall-to-wall LIDAR-derived biomass maps were compared to FIA data at both the plot and county levels in Anne Arundel and Howard Counties in Maryland. Allometric model-related errors were also considered. In areas of medium to dense biomass, the FIA data were valuable for evaluating map accuracy by comparing plot biomass to pixel values. However, at plots that were defined as “nonforest”, FIA plots had limited value because tree data was not collected even though trees may be present. When the FIA data were combined with a previous inventory that included sampling of nonforest plots, 21 to 27% of the total biomass of all trees was accounted for in nonforest conditions, resulting in a more accurate benchmark for comparing to total biomass derived from the LIDAR maps. Allometric model error was relatively small, but there was as much as 31% difference in mean biomass based on local diameter-based equations compared to regional volume-based equations, suggesting that the choice of allometric model is important. To be successfully integrated with LIDAR, FIA sampling would need to be enhanced to include measurements of all trees in a landscape, not just those on land defined as “forest”. Improved GPS accuracy of plot locations, intensifying data collection in small areas with few FIA plots, and other enhancements are also recommended.https://doi.org/10.1186/1750-0680-9-

Local discrepancies in continental scale biomass maps: a case study over forested and non-forested landscapes in Maryland, USA

Continental-scale aboveground biomass maps are increasingly available, but their estimates vary widely, particularly at high resolution. A comprehensive understanding of map discrepancies is required to improve their effectiveness in carbon accounting and local decision-making. To this end, we compare four continental-scale maps with a recent high-resolution lidar-derived biomass map over Maryland, USA. We conduct detailed comparisons at pixel-, county-, and state-level. Spatial patterns of biomass are broadly consistent in all maps, but there are large differences at fine scales (RMSD 48.5–92.7 Mg ha−1). Discrepancies reduce with aggregation and the agreement among products improves at the county level. However, continental scale maps exhibit residual negative biases in mean (33.0–54.6 Mg ha−1) and total biomass (3.5–5.8 Tg) when compared to the high-resolution lidar biomass map. Three of the four continental scale maps reach near-perfect agreement at ~4 km and onward but do not converge with the high-resolution biomass map even at county scale. At the State level, these maps underestimate biomass by 30–80 Tg in forested and 40–50 Tg in non-forested areas. Local discrepancies in continental scale biomass maps are caused by factors including data inputs, modeling approaches, forest/non-forest definitions and time lags. There is a net underestimation over high biomass forests and non-forested areas that could impact carbon accounting at all levels. Local, high-resolution lidar-derived biomass maps provide a valuable bottom-up reference to improve the analysis and interpretation of large-scale maps produced in carbon monitoring systems.https://doi.org/10.1186/s13021-015-0030-

The Earth BioGenome Project 2020: Starting the clock

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The Earth BioGenome Project 2020: Starting the clock.

© The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Lewin, H. A., Richards, S., Lieberman Aiden, E., Allende, M. L., Archibald, J. M., Bálint, M., Barker, K. B., Baumgartner, B., Belov, K., Bertorelle, G., Blaxter, Mark L., Cai, J., Caperello, N. D., Carlson, K., Castilla-Rubio, J. C., Chaw, S-M., Chen, L., Childers, A. K., Coddington, J. A., Conde, D. A., Corominas, M., Crandall, K. A., Crawford, A. J., DiPalma, F., Durbin, R., Ebenezer, T. E., Edwards, S. V., Fedrigo, O., Flicek, P., Formenti, G., Gibbs, R. A., Gilbert, M. Thomas P., Goldstein, M. M., Graves, J. M., Greely, H. T., Grigoriev, I. V., Hackett, K. J., Hall, N., Haussler, D., Helgen, K. M., Hogg, C. J., Isobe, S., Jakobsen, K. S., Janke, A., Jarvis, E. D., Johnson, W. E., Jones, S. J. M., Karlsson, E. K., Kersey, P. J., Kim, J-H., Kress, W. J., Kuraku, S., Lawniczak, M. K. N., Leebens-Mack, J. H., Li, X., Lindblad-Toh, K., Liu, X., Lopez, J. V., Marques-Bonet, T., Mazard, S., Mazet, J. A. K., Mazzoni, C. J., Myers, E. W., O’Neill, R. J., Paez, S., Park, H., Robinson, G. E., Roquet, C., Ryder, O. A., Sabir, J. S. M., Shaffer, H. B., Shank, T. M., Sherkow, J. S., Soltis, P. S., Tang, B., Tedersoo, L., Uliano-Silva, M., Wang, K., Wei, X., Wetzer, R., Wilson, J. L., Xu, X., Yang, H., Yoder, A. D., Zhang, G. The Earth BioGenome Project 2020: starting the clock. Proceedings of the National Academy of Sciences of the United States of America, 119(4), (2022): e2115635118, https://doi.org/10.1073/pnas.2115635118.November 2020 marked 2 y since the launch of the Earth BioGenome Project (EBP), which aims to sequence all known eukaryotic species in a 10-y timeframe. Since then, significant progress has been made across all aspects of the EBP roadmap, as outlined in the 2018 article describing the project’s goals, strategies, and challenges (1). The launch phase has ended and the clock has started on reaching the EBP’s major milestones. This Special Feature explores the many facets of the EBP, including a review of progress, a description of major scientific goals, exemplar projects, ethical legal and social issues, and applications of biodiversity genomics. In this Introduction, we summarize the current status of the EBP, held virtually October 5 to 9, 2020, including recent updates through February 2021. References to the nine Perspective articles included in this Special Feature are cited to guide the reader toward deeper understanding of the goals and challenges facing the EBP

Taxonomy based on science is necessary for global conservation

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