The global contribution of soil mosses to ecosystem services

Soil mosses are among the most widely distributed organisms on land. Experiments and observations suggest that they contribute to terrestrial soil biodiversity and function, yet their ecological contribution to soil has never been assessed globally under natural conditions. Here we conducted the most comprehensive global standardized field study to quantify how soil mosses influence 8 ecosystem services associated with 24 soil biodiversity and functional attributes across wide environmental gradients from all continents. We found that soil mosses are associated with greater carbon sequestration, pool sizes for key nutrients and organic matter decomposition rates but a lower proportion of soil-borne plant pathogens than unvegetated soils. Mosses are especially important for supporting multiple ecosystem services where vascular-plant cover is low. Globally, soil mosses potentially support 6.43 Gt more carbon in the soil layer than do bare soils. The amount of soil carbon associated with mosses is up to six times the annual global carbon emissions from any altered land use globally. The largest positive contribution of mosses to soils occurs under a high cover of mat and turf mosses, in less-productive ecosystems and on sandy and salty soils. Our results highlight the contribution of mosses to soil life and functions and the need to conserve these important organisms to support healthy soils.The study work associated with this paper was funded by a Large Research Grant from the British Ecological Society (no. LRB17\1019; MUSGONET). D.J.E. is supported by the Hermon Slade Foundation. M.D.-B. was supported by a Ramón y Cajal grant from the Spanish Ministry of Science and Innovation (RYC2018-025483-I), a project from the Spanish Ministry of Science and Innovation for the I + D + i (PID2020-115813RA-I00 funded by MCIN/AEI/10.13039/501100011033a) and a project PAIDI 2020 from the Junta de Andalucía (P20_00879). E.G. is supported by the European Research Council grant agreement 647038 (BIODESERT). M.B. is supported by a Ramón y Cajal grant from Spanish Ministry of Science (RYC2021-031797-I). A.d.l.R is supported by the AEI project PID2019-105469RB-C22. L.W. and Jianyong Wang are supported by the Program for Introducing Talents to Universities (B16011) and the Ministry of Education Innovation Team Development Plan (2013-373). The contributions of T.G. and T.U.N. were supported by the Research Program in Forest Biology, Ecology and Technology (P4-0107) and the research projects J4-3098 and J4-4547 of the Slovenian Research Agency. The contribution of P.B.R. was supported by the NSF Biological Integration Institutes grant DBI-2021898. J. Durán and A. Rodríguez acknowledge support from the FCT (2020.03670.CEECIND and SFRH/BDP/108913/2015, respectively), as well as from the MCTES, FSE, UE and the CFE (UIDB/04004/2021) research unit financed by FCT/MCTES through national funds (PIDDAC)

Global hotspots for soil nature conservation

19 páginas.- 5 figuras.- 98 referencias.- Supplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41586-022-05292-xSoils are the foundation of all terrestrial ecosystems1. However, unlike for plants and animals, a global assessment of hotspots for soil nature conservation is still lacking2. This hampers our ability to establish nature conservation priorities for the multiple dimensions that support the soil system: from soil biodiversity to ecosystem services. Here, to identify global hotspots for soil nature conservation, we performed a global field survey that includes observations of biodiversity (archaea, bacteria, fungi, protists and invertebrates) and functions (critical for six ecosystem services) in 615 composite samples of topsoil from a standardized survey in all continents. We found that each of the different ecological dimensions of soils—that is, species richness (alpha diversity, measured as amplicon sequence variants), community dissimilarity and ecosystem services—peaked in contrasting regions of the planet, and were associated with different environmental factors. Temperate ecosystems showed the highest species richness, whereas community dissimilarity peaked in the tropics, and colder high-latitudinal ecosystems were identified as hotspots of ecosystem services. These findings highlight the complexities that are involved in simultaneously protecting multiple ecological dimensions of soil. We further show that most of these hotspots are not adequately covered by protected areas (more than 70%), and are vulnerable in the context of several scenarios of global change. Our global estimation of priorities for soil nature conservation highlights the importance of accounting for the multidimensionality of soil biodiversity and ecosystem services to conserve soils for future generations.This project received funding from the British Ecological Society (agreement LRA17\1193; MUSGONET). C.A.G. and N.E. were funded by DFG–FZT 118, 202548816; C.A.G. was supported by FCT-PTDC/BIA-CBI/2340/2020; M.D.-B. was supported by RYC2018-025483-I, PID2020-115813RA-I00\MCIN/AEI/10.13039/501100011033 and P20_00879. M.A.M.-M. and S.A. were funded by FONDECYT 1181034 and ANID-PIA-Anillo INACH ACT192057. J.D. and A.R. acknowledge support from IF/00950/2014, 2020.03670.CEECIND, SFRH/BDP/108913/2015 and UIDB/04004/2020. Y.-R.L. was supported by 2662019PY010 from the FRFCU. L.T. was supported by the ESF grant PRG632. F.B. and J.L.M. were supported by i-LINK+2018 (LINKA20069) funded by CSIC. C.T.-D. was supported by the Grupo de Biodibersidad & Cambio Global UBB–GI 170509/EF. C.P. was supported by the EU H2020 grant agreement 101000224. H.C. was supported by NSFC32101335, FRFCU2412021QD014 and CPSF2021M690589. J.P.V. was supported by DST (DST/INT/SL/P-31/2021) SERB (EEQ/2021/001083) and BHU-IoE (6031).Peer reviewe

Energetic Assessment of the Nonexercise Activities under Free-Living Conditions

Nonexercise activities (NAs) are common types of physical activity in daily life and critical component in energy expenditure. However, energetic assessment of NA, particularly in free-living subjects, is a technical challenge. In this study, mechanical modeling and portable device were used to evaluate five common types of NA in daily life: sit to stand, lie to sit, bowing while standing, squat, and right leg over left. A human indirect calorimeter was used to measure the activity energy expenditure of NA. Mechanical work and mechanical efficiency of NA were calculated for mechanical modeling. Thirty-two male subjects were recruited for the study (20 subjects for the development of models and 12 subjects for evaluation of models). The average (mean ± SD) mechanical work of 5 NAs was 2.31 ± 0.50, 2.88 ± 0.57, 1.75 ± 0.55, 3.96 ± 1.25, and 1.25 ± 0.51 J/kg·m, respectively. The mean mechanical efficiencies of those activities were 22.0 ± 3.3%, 26.5 ± 5.1%, 19.8 ± 3.7%, 24.0 ± 5.5%, and 26.3 ± 5.5%. The activity energy expenditure estimated by the models was not significantly different from the measurements by the calorimeter (p>0.05) with accuracies of 102.2 ± 20.7%, 103.7 ± 25.8%, 105.6 ± 14.6%, 101.1 ± 28.0%, and 95.8 ± 20.7%, respectively, for those activities. These findings suggest that the mechanical models combined with a portable device can provide an alternative method for the energetic analysis of nonexercise activities under free-living condition

Clinical Application of Artificial Intelligence Recognition Technology in the Diagnosis of Stage T1 Lung Cancer

Background and objective Lung cancer is the cancer with the highest morbidity and mortality at home and abroad at present. Using computed tomography (CT) to screen lung cancer nodules is a huge workload. To test the effect of artificial intelligence in automatic identification of lung cancer by using artificial intelligence to find the lung cancer nodules automatically in the chest CT of 1 mm and 5 mm thick. Methods 5,000 cases of T1 stage lung cancer patients with 1 mm and 5 mm layer thickness were respectively labeled and learned by computer neural network, the algorithm of forming pulmonary nodules was carried out. 500 cases of chest CT in T1 stage lung cancer patients with 1 mm and 5 mm thickness were tested by artificial intelligence formation, and the sensitivity and specificity were compared with artificial reading. Results Using artificial intelligence to read chest CT 500 in 5 mm, the sensitivity was 95.20%, the specificity was 93.20%, and the Kappa value of two times repeated read was 0.926,1. For 1 mm chest CT 500 cases, the sensitivity is 96.40%, the specificity is 95.60%, and the Kappa reads two times is 0.938,6. Compared with 5 doctors, the same CT sets with 1 mm thickness were read. The detection rates of artificial intelligence and artificial reading were similar to those of lung cancer nodules and negative control read films, and there was no significant difference between them. In the comparison of the same CT slices with 5 mm thickness, the number of detection of lung cancer nodules by artificial intelligence is better than that of artificial reading, and the sensitivity is higher, but the number of false messages is increased and the specificity is slightly worse. Conclusion The automatic learning of early lung cancer chest CT images by artificial intelligence can achieve high sensitivity and specificity of early lung cancer identification, and assist doctors in the diagnosis of lung cancer

Mitotic phosphorylation of PRC1 at Thr470 is required for PRC1 oligomerization and proper central spindle organization

During cell division, chromosome segregation is orchestrated by the interaction of spindle microtubules with the centromere. A dramatic remodeling of interpolar microtubules into an organized central spindle between the separating chromatids is required for the initiation and execution of cytokinesis. Central spindle organization requires mitotic kinesins, the chromosomal passenger protein complex, and microtubule bundling protein PRC1. PRC1 is phosphorylated by Cdc2 at Thr470 and Thr481 during mitosis. However, the functional relevance of PRC1 phosphorylation at Thr470 has remained elusive. Here we show that expression of the non-phosphorylatable mutant PRC1 T470A but not the phospho-mimicking mutant PRC1 T470E causes aberrant organization of the central spindle. Immunoprecipitation experiment indicates that both PRC1 T470A and PRC1 T470E mutant proteins associate with wild-type PRC1, suggesting that phosphorylation of Thr470 does not alter PRC1 self-association. In addition, in vitro co-sedimentation experiment showed that PRC1 binds to microtubule independent of the phosphorylation state of Thr470. Gel-filtration experiment suggested that phosphorylation of Thr470 promotes oligomerization of PRC1. Given the fact that prevention of the Thr470 phosphorylation inhibits PRC1 oligomerization in vitro and causes an aberrant organization of central spindle in vivo, we propose that this phosphorylation-dependent PRC1 oligomerization ensures that central spindle assembly occurs at the appropriate time in the cell cycle. © 2007 IBCB, SIBS, CAS All rights reserved.link_to_subscribed_fulltex