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      Local climate modulates the development of soil nematode communities after glacier retreat

      1 , 2 , 1 , 1 , 3 , 2 , 1 , 1 , 4 , 5 , 1 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 6 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 1 , 21 , 22 , 23 , 24 , 16 , 25 , 26 , 27 , 19 , 6 , 28 , 18 , 29 , 30 , 6 , 31 , 20 , 24 , 1 , 16 , 32 , 33 , 20 , 1 , 20
      Global Change Biology
      Wiley

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          Abstract

          The worldwide retreat of glaciers is causing a faster than ever increase in ice‐free areas that are leading to the emergence of new ecosystems. Understanding the dynamics of these environments is critical to predicting the consequences of climate change on mountains and at high latitudes. Climatic differences between regions of the world could modulate the emergence of biodiversity and functionality after glacier retreat, yet global tests of this hypothesis are lacking. Nematodes are the most abundant soil animals, with keystone roles in ecosystem functioning, but the lack of global‐scale studies limits our understanding of how the taxonomic and functional diversity of nematodes changes during the colonization of proglacial landscapes. We used environmental DNA metabarcoding to characterize nematode communities of 48 glacier forelands from five continents. We assessed how different facets of biodiversity change with the age of deglaciated terrains and tested the hypothesis that colonization patterns are different across forelands with different climatic conditions. Nematodes colonized ice‐free areas almost immediately. Both taxonomic and functional richness quickly increased over time, but the increase in nematode diversity was modulated by climate, so that colonization started earlier in forelands with mild summer temperatures. Colder forelands initially hosted poor communities, but the colonization rate then accelerated, eventually leveling biodiversity differences between climatic regimes in the long term. Immediately after glacier retreat, communities were dominated by colonizer taxa with short generation time and r‐ecological strategy but community composition shifted through time, with increased frequency of more persister taxa with K‐ecological strategy. These changes mostly occurred through the addition of new traits instead of their replacement during succession. The effects of local climate on nematode colonization led to heterogeneous but predictable patterns around the world that likely affect soil communities and overall ecosystem development.

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          brms: An R Package for Bayesian Multilevel Models Using Stan

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            Biodiversity loss and its impact on humanity.

            The most unique feature of Earth is the existence of life, and the most extraordinary feature of life is its diversity. Approximately 9 million types of plants, animals, protists and fungi inhabit the Earth. So, too, do 7 billion people. Two decades ago, at the first Earth Summit, the vast majority of the world's nations declared that human actions were dismantling the Earth's ecosystems, eliminating genes, species and biological traits at an alarming rate. This observation led to the question of how such loss of biological diversity will alter the functioning of ecosystems and their ability to provide society with the goods and services needed to prosper.
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              Simple statistical identification and removal of contaminant sequences in marker-gene and metagenomics data

              Background The accuracy of microbial community surveys based on marker-gene and metagenomic sequencing (MGS) suffers from the presence of contaminants—DNA sequences not truly present in the sample. Contaminants come from various sources, including reagents. Appropriate laboratory practices can reduce contamination, but do not eliminate it. Here we introduce decontam (https://github.com/benjjneb/decontam), an open-source R package that implements a statistical classification procedure that identifies contaminants in MGS data based on two widely reproduced patterns: contaminants appear at higher frequencies in low-concentration samples and are often found in negative controls. Results Decontam classified amplicon sequence variants (ASVs) in a human oral dataset consistently with prior microscopic observations of the microbial taxa inhabiting that environment and previous reports of contaminant taxa. In metagenomics and marker-gene measurements of a dilution series, decontam substantially reduced technical variation arising from different sequencing protocols. The application of decontam to two recently published datasets corroborated and extended their conclusions that little evidence existed for an indigenous placenta microbiome and that some low-frequency taxa seemingly associated with preterm birth were contaminants. Conclusions Decontam improves the quality of metagenomic and marker-gene sequencing by identifying and removing contaminant DNA sequences. Decontam integrates easily with existing MGS workflows and allows researchers to generate more accurate profiles of microbial communities at little to no additional cost. Electronic supplementary material The online version of this article (10.1186/s40168-018-0605-2) contains supplementary material, which is available to authorized users.
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                Author and article information

                Contributors
                Journal
                Global Change Biology
                Global Change Biology
                Wiley
                1354-1013
                1365-2486
                January 2024
                December 08 2023
                January 2024
                : 30
                : 1
                Affiliations
                [1 ] Dipartimento di Scienze e Politiche Ambientali Università degli Studi di Milano Milano Italy
                [2 ] Argaly, Bâtiment CleanSpace Sainte‐Hélène‐du‐Lac France
                [3 ] Institute of Geosciences and Earth Resources, CNR Pisa Italy
                [4 ] Dipartimento di Bioscienze Università degli Studi di Milano Milano Italy
                [5 ] Laboratory AMAP, IRD University of Montpellier, CIRAD, CNRS, INRA Montpellier France
                [6 ] Dipartimento di Scienze della Terra “Ardito Desio” Università degli Studi di Milano Milano Italy
                [7 ] Department of Soil and Physical Sciences Lincoln University Lincoln New Zealand
                [8 ] Departamento de Ciencias Biológicas y Biodiversidad Universidad de Los Lagos Osorno Chile
                [9 ] INRAE, UR RIVERLY Centre de Lyon‐Villeurbanne Villeurbanne France
                [10 ] Instituto de Hidrología Meteorología y Estudios Ambientales IDEAM Bogotá Colombia
                [11 ] Department of Geography, School of Environment and Earth Sciences Central University of Punjab Bathinda Punjab India
                [12 ] Centre for the Study of Regional Development – School of Social Sciences Jawaharlal Nehru University New Delhi India
                [13 ] Department of Earth Sciences Simon Fraser University Burnaby British Columbia Canada
                [14 ] Área de Evaluación de Glaciares y Lfagunas Autoridad Nacional del Agua Huaraz Peru
                [15 ] CEFE, Univ Montpellier CNRS, EPHE, IRD, Univ Paul Valéry Montpellier 3 Montpellier France
                [16 ] Univ. Savoie Mont Blanc Univ. Grenoble Alpes, EDYTEM Chambéry France
                [17 ] Mannaki Whenua – Landcare Research, Soils and Landscapes Lincoln New Zealand
                [18 ] Institute of Water Problems and Hydro‐Energy Kyrgyz National Academy of Sciences Bishkek Kyrgyzstan
                [19 ] Department of Earth and Environmental Sciences (DISAT) University of Milano‐Bicocca Milano Italy
                [20 ] Univ. Grenoble Alpes Univ. Savoie Mont Blanc, CNRS, LECA Grenoble France
                [21 ] Department of Life Sciences and Systems Biology University of Turin Turin Italy
                [22 ] Research and Museum Collections Office, Climate and Ecology Unit MUSE‐Science Museum, Corso del Lavoro e della Scienza Trento Italy
                [23 ] Faculty of Environmental Sciences and Natural Resource Management (INA) Norwegian University of Life Sciences Ås Norway
                [24 ] UiT – The Arctic University of Norway, Tromsø Museum Tromsø Norway
                [25 ] Herbario Nacional de Bolivia: La Paz La Paz Bolivia
                [26 ] Universidad Católica del Norte Antofagasta Chile
                [27 ] Department of Civil and Environmental Engineering University of the Andes Bogotá Colombia
                [28 ] Univ. Grenoble Alpes, CNRS, IRD, Grenoble‐INP Institut des Géosciences de l'Environnement (IGE, UMR 5001) Grenoble France
                [29 ] Institute of Mountain Hazards and Environment Chinese Academy of Sciences Chengdu China
                [30 ] Mountain Societies Research Institute University of Central Asia Bishkek Kyrgyzstan
                [31 ] Department of Geography and the Environment University of Texas at Austin Austin Texas USA
                [32 ] CNR – Water Research Institute Verbania Italy
                [33 ] NBFC – National Biodiversity Future Center Palermo Italy
                Article
                10.1111/gcb.17057
                38273541
                7b331e76-ee2c-4269-90ec-98629dc12bfc
                © 2024

                http://creativecommons.org/licenses/by-nc-nd/4.0/

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