More stories

  • in

    Climate, caribou and human needs linked by analysis of Indigenous and scientific knowledge

    Forbes, B. C. & Kumpula, T. The ecological role and geography of reindeer (Rangifer tarandus) in Northern Eurasia. Geogr. Compass 3, 1356–1380 (2009).Article 

    Google Scholar 
    Post, E. & Pedersen, C. Opposing plant community responses to warming with and without herbivores. Proc. Natl Acad. Sci. USA 105, 12353–12358 (2008).Article 
    CAS 

    Google Scholar 
    Berkes, F., Colding, J. & Folke, C. Navigating Social-Ecological Systems: Building Resilience for Complexity and Change (Cambridge Univ. Press, 2003).Tremblay, R., Landry-Cuerrier, M. & Humphries, M. M. Culture and the social-ecology of local food use by Indigenous communities in northern North America. Ecol. Soc. 25, 8 (2020).Kenny, T.-A., Fillion, M., Simpkin, S., Wesche, S. & Chan, L. Caribou (Rangifer tarandus) and Inuit nutrition security in Canada. Ecohealth 15, 590–607 (2018).Article 

    Google Scholar 
    Benson, K. Gwich’in Knowledge of Porcupine Caribou: State of Current Knowledge and Gaps Assessment (Department of Cultural Heritage, Gwich’in Tribal Council, 2019); https://thelastgreatherd.com/wp-content/uploads/2020/06/GTC-current-knowledge-and-gaps-assessment.pdfParlee, B. & Caine, K. When the Caribou Do Not Come: Indigenous Knowledge and Adaptive Management in the Western Arctic (UBC Press, 2018).Herds: Status of Herds (CircumArctic Rangifer Monitoring and Assessment Network, accessed 3 November 2021); https://carma.caff.is/herdsFesta-Bianchet, M., Ray, J. C., Boutin, S., Côté, S. D. & Gunn, A. Conservation of caribou (Rangifer tarandus) in Canada: an uncertain future. Can. J. Zool. 89, 419–434 (2011).Article 

    Google Scholar 
    Gunn, A. Voles, lemmings and caribou: population cycles revisited? Rangifer 23, 105–111 (2003).Article 

    Google Scholar 
    Ferguson, M. A. D., Williamson, R. G. & Messier, F. Inuit knowledge of long-term changes in a population of Arctic tundra caribou. Arctic 51, 201–219 (1998).Article 

    Google Scholar 
    Beaulieu, D. Dene traditional knowledge about caribou cycles in the Northwest Territories. Rangifer 32, 59–67 (2012).Article 

    Google Scholar 
    Mallory, C. D. & Boyce, M. S. Observed and predicted effects of climate change on Arctic caribou and reindeer. Environ. Rev. 26, 13–25 (2018).Article 

    Google Scholar 
    Uboni, A. et al. Long-term trends and role of climate in the population dynamics of Eurasian reindeer. PLoS ONE 11, e0158359 (2016).Article 

    Google Scholar 
    Chapin, F. S. III et al. Directional changes in ecological communities and social-ecological systems: a framework for prediction based on Alaskan examples. Am. Nat. 168, S36–S49 (2006).Article 

    Google Scholar 
    Tengö, M. et al. Weaving knowledge systems in IPBES, CBD and beyond – lessons learned for sustainability. Curr. Opin. Environ. Sustain. 26, 17–25 (2017).Article 

    Google Scholar 
    Berkes, F. Sacred Ecology 4th edn (Routledge, 2018).Stuart Chapin, F. III et al. Earth stewardship: science for action to sustain the human-earth system. Ecosphere 2, 89 (2011).Parlee, B. L., Sandlos, J. & Natcher, D. C. Undermining subsistence: barren-ground caribou in a ‘tragedy of open access’. Sci. Adv. 4, e1701611 (2018).Article 

    Google Scholar 
    Johnson, J. T. et al. Weaving Indigenous and sustainability sciences to diversify our methods. Sustain. Sci. 11, 1–11 (2016).Article 
    CAS 

    Google Scholar 
    Reid, A. J. et al. ‘Two-eyed seeing’: an Indigenous framework to transform fisheries research and management. Fish Fish. 22, 243–261 (2021).Article 

    Google Scholar 
    Tengö, M., Brondizio, E. S., Elmqvist, T., Malmer, P. & Spierenburg, M. Connecting diverse knowledge systems for enhanced ecosystem governance: the multiple evidence base approach. AMBIO 43, 579–591 (2014).Article 

    Google Scholar 
    Aminpour, P. et al. The diversity bonus in pooling local knowledge about complex problems. Proc. Natl Acad. Sci. USA 118, e2016887118 (2021).Article 
    CAS 

    Google Scholar 
    Henri, D. A. et al. Weaving Indigenous knowledge systems and Western sciences in terrestrial research, monitoring and management in Canada: a protocol for a systematic map. Ecol. Solut. Evid. 2, e12057 (2021).Article 

    Google Scholar 
    Ljubicic, G. J., Mearns, R., Okpakok, S. & Robertson, S. Nunami iliharniq (learning from the land): reflecting on relational accountability in land-based learning and cross-cultural research in Uqšuqtuuq (Gjoa Haven, Nunavut). Arct. Sci. 8, 252–291 (2022).Article 

    Google Scholar 
    Stern, E. R. & Humphries, M. M. Interweaving local, expert, and Indigenous knowledge into quantitative wildlife analyses: a systematic review. Biol. Conserv. 266, 109444 (2022).Article 

    Google Scholar 
    Bourgeon, L., Burke, A. & Higham, T. Earliest human presence in North America dated to the last glacial maximum: new radiocarbon dates from Bluefish Caves, Canada. PLoS ONE 12, e0169486 (2017).Article 

    Google Scholar 
    Kuhnlein, H. V., McDonald, M., Spigelski, D., Vittrekwa, E. & Erasmus, B. in Indigenous Peoples’ Food Systems: the Many Dimensions of Culture, Diversity and Environment for Nutrition and Health (eds Kuhnlein, H. V. et al.) Ch. 3 (FAO, Centre for Indigenous Peoples’ Nutrition and Environment, 2009).Porcupine Caribou Technical Committee. Porcupine Caribou Annual Summary Report 2018–2019 (Porcupine Caribou Management Board, Whitehorse, Yukon, 2019); https://pcmb.ca/wp-content/uploads/2020/06/PCH_annual_summ_report_Nov29_2019_FINAL.pdfIPCC. Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) (Cambridge Univ. Press, 2013).Zhang, X. et al. in Canada’s Changing Climate Report (eds Bush, E. & Lemmen, D. S.) Ch. 4 (Government of Canada, 2019).Griffith, B. et al. in Arctic Refuge Coastal Plain Terrestrial Wildlife Research Summaries Biological Science Report USGS/BRD BSR-2002-0001 (eds Douglas, D. C. et al.) 8–37 (US Geological Survey, 2002).Russell, D. & Gunn, A. Vulnerability Analysis of the Porcupine Caribou Herd to Potential Development of the 1002 lands in the Arctic National Wildlife Refuge, Alaska (Environment Yukon, Canadian Wildlife Service and GNWT Department of Environment and Natural Resources, 2019); https://pcmb.ca/wp-content/uploads/2021/10/Russell-and-Gunn-PCH-vulnerability-analysis-2019.pdfKruse, J. A. et al. Modeling sustainability of Arctic communities: an interdisciplinary collaboration of researchers and local knowledge holders. Ecosystems 7, 815–828 (2004).Berman, M., Nicolson, C., Fofinas, G., Tetlichi, J. & Martin, S. Adaptation and sustainability in a small Arctic community: results of an agent-based simulation model. Arctic 57, 401–414 (2004).Article 

    Google Scholar 
    Kofinas, G., Aklavik, Arctic Village, Old Crow & Fort McPherson. in The Earth is Faster Now: Indigenous Observations of Arctic Environmental Change (eds Krupnik, I. & Jolly, D.) 55–91 (Arctic Research Consortium of the United States, 2002).Eamer, J. in Bridging Scales and Knowledge Systems: Concepts and Applications in Ecosystem Assessment (eds Reid, W. V. et al.) 185–206 (Island Press, 2006).Shipley, B. Cause and Correlation in Biology: a User’s Guide to Path Analysis, Structural Equations and Causal Inference with R 2nd edn (Cambridge Univ. Press, 2016).Parlee, B. & Furgal, C. Well-being and environmental change in the Arctic: a synthesis of selected research from Canada’s International Polar Year program. Clim. Change 115, 13–34 (2012).Article 

    Google Scholar 
    Kofinas, G. P. The Costs of Power Sharing: Community Involvment in Canadian Porcuine Caribou Co-management. PhD thesis, Univ. of British Columbia (1998).Ford, J. D. et al. Including indigenous knowledge and experience in IPCC assessment reports. Nat. Clim. Change 6, 349–353 (2016).Article 

    Google Scholar 
    Brinkman, T. J. et al. Arctic communities perceive climate impacts on access as a critical challenge to availability of subsistence resources. Clim. Change 139, 413–427 (2016).Article 

    Google Scholar 
    McNeil, P., Russell, D. E., Griffith, B., Gunn, A. & Kofinas, G. Where the wild things are: seasonal variation in caribou distribution in relation to climate change. Rangifer 25, 51–63 (2005).Berman, M. & Kofinas, G. Hunting for models: grounded and rational choice approaches to analyzing climate effects on subsistence hunting in an Arctic community. Ecol. Econ. 49, 31–46 (2004).Article 

    Google Scholar 
    Hansen, B. B. et al. Climate events synchronize the dynamics of a resident vertebrate community in the High Arctic. Science 339, 313–315 (2013).Article 
    CAS 

    Google Scholar 
    Collings, P., Marten, M. G., Pearce, T. & Young, A. G. Country food sharing networks, household structure, and implications for understanding food insecurity in Arctic Canada. Ecol. Food Nutr. 55, 30–49 (2016).Article 

    Google Scholar 
    BurnSilver, S., Magdanz, J., Stotts, R., Berman, M. & Kofinas, G. Are mixed economies persistent or transitional? Evidence using social networks from Arctic Alaska. Am. Anthropol. 118, 121–129 (2016).Article 

    Google Scholar 
    Baggio, J. A. et al. Multiplex social ecological network analysis reveals how social changes affect community robustness more than resource depletion. Proc. Natl Acad. Sci. USA 113, 13708–13713 (2016).Article 
    CAS 

    Google Scholar 
    Gagnon, C. A. et al. Merging Indigenous and scientific knowledge links climate with the growth of a large migratory caribou population. J. Appl. Ecol. 57, 1644–1655 (2020).Article 

    Google Scholar 
    Houde, N. The six faces of traditional ecological knowledge: challenges and opportunities for Canadian co-management arrangements. Ecol. Soc. 12, 34 (2007).Article 

    Google Scholar 
    Fancy, S. G., Pank, L. F., Whitten, K. R. & Regelin, W. L. Seasonal movements of caribou in Arctic Alaska as determined by satellite. Can. J. Zool. 67, 644–650 (1989).Article 

    Google Scholar 
    Porcupine Caribou Technical Committee. Porcupine Caribou Annual Summary Report 2014 (Porcupine Caribou Management Board, Whitehorse, Yukon, 2014); https://pcmb.ca/wp-content/uploads/2021/07/PCH_annual_summ_report_2014_2015_NOV19_FINAL.pdfEastland, W. G. Influence of Weather on Movements and Migrations of Caribou. PhD thesis, Univ. of Alaska (1991).Tyler, N. J. C. Climate, snow, ice, crashes, and declines in populations of reindeer and caribou (Rangifer tarandus L.). Ecol. Monogr. 80, 197–219 (2010).Article 

    Google Scholar 
    Hansen, B. B., Aanes, R. & Saether, B. E. Feeding-crater selection by high-arctic reindeer facing ice-blocked pastures. Can. J. Zool. 88, 170–177 (2010).Article 

    Google Scholar 
    Solberg, E. J. et al. Effects of density-dependence and climate on the dynamics of a Svalbard reindeer population. Ecography 24, 441–451 (2001).Article 

    Google Scholar 
    Hansen, B. B., Aanes, R., Herfindal, I., Kohler, J. & Sæther, B.-E. Climate, icing, and wild arctic reindeer: past relationships and future prospects. Ecology 92, 1917–1923 (2011).Article 

    Google Scholar 
    Langlois, A. et al. Detection of rain-on-snow (ROS) events and ice layer formation using passive microwave radiometry: a context for Peary caribou habitat in the Canadian Arctic. Remote Sens. Environ. 189, 84–95 (2017).Article 

    Google Scholar 
    Russell, D. E., Gunn, A. & White, R. G. CircumArctic collaboration to monitor caribou and wild reindeer. Arctic 68, 6–10 (2015).Article 

    Google Scholar 
    Russell, D. E. et al. CARMA’s MERRA-based caribou range climate database. Rangifer 33, 145–152 (2013).Article 

    Google Scholar 
    ArcGIS version 10 (Environmental Systems Resource Institute, 2010).Cai, J., Russell, D. & Whitfield, P. Methodology and Algorithms for Constructing CARMA Bio-climate Tables (Simon Fraser Univ., 2011).Stenseth, N. C. & Mysterud, A. Weather packages: finding the right scale and composition of climate in ecology. J. Anim. Ecol. 74, 1195–1198 (2005).Article 

    Google Scholar 
    Pebesma, E. J. & Bivand, R. S. Classes and methods for spatial data in R. R News 5, 9–13 (2005).Bivand, R. S., Pebesma, E. J. & Gomez-Rubio, V. Applied Spatial Data Analysis with R 2nd edn (Springer, 2013).Bivand, R. S., Keitt, T. & Rowlingson, B. Rgdal: Bindings for the Geospatial Data Abstraction Library. R package version 0.8-16 (R Foundation for Statistical Computing, 2014); https://cran.r-project.org/web/packages/rgdal/index.htmlBivand, R. S. & Rundel, C. Rgeos: Interface to Geometry Engine – Open Source (GEOS). R package version 0.3-4 (R Foundation for Statistical Computing, 2014); https://cran.r-project.org/web/packages/rgeos/index.htmlLefcheck, J. S. piecewise SEM: piecewise structural equation modelling in R for ecology, evolution and systematics. Methods Ecol. Evol. 7, 573–579 (2016).Article 

    Google Scholar 
    Shipley, B. Confirmatory path analysis in a generalized multilevel context. Ecology 90, 363–368 (2009).Article 

    Google Scholar 
    Thomas, D. W. et al. Common paths link food abundance and ectoparasite loads to physiological performance and recruitment in nestling blue tits. Funct. Ecol. 21, 947–955 (2007).Article 

    Google Scholar 
    Shipley, B. The AIC model selection method applied to path analytic models compared using a d-separation test. Ecology 94, 560–564 (2013).Article 

    Google Scholar 
    Burnham, K. P. & Anderson, D. R. Model Selection and Multimodel Inference: a Practical Information-Theoretic Approach (Springer, 2002).Schielzeth, H. Simple means to improve the interpretability of regression coefficients. Methods Ecol. Evol. 593, 103–113 (2010).Article 

    Google Scholar  More

  • in

    No impact of nitrogen fertilization on carbon sequestration in a temperate Pinus densiflora forest

    SettingThis study was conducted in approximately 40-year-old naturally regenerated P. densiflora stands in Wola National Experimental Forest in Gyeongnam province in South Korea (35°12′ N, 128°10′ E; Table 1). The productivity of this forest is low, with a dominant tree height of 10 m at 20 years of age. Over the last 10 years, the mean annual precipitation was 1490 mm, of which one third fell during summer (July–August), and the mean temperature was 13.1 °C. The vegetation growing season generally lasts for approximately 200 days, extending from early April to October. The soil texture is a silt loam originating from sandstone and shale (clay 13.0 ± 0.8%, silt 44.1 ± 1.3%, sand 42.9 ± 1.6%; n = 18). The given texture results in volumetric water contents at 13.4 ± 0.7% (m3 m−3) at permanent wilting point (1500 kPa) and 40.7 ± 1.2% at field capacity (10 kPa)55. The understory is covered with Lespedeza spp., Quercus variabilis, Q. serrata, Smilax china, and Lindera glauca.In 2010, we selected two adjacent P. densiflora stands approximately 100 m apart from each other (180 m and 195 m above sea level, on slopes of 15° and 33°, both stands face south). Following a completely randomized design, we established nine plots (10 × 10 m2 with a 5 m untreated buffer) within each stand, of which three were randomly assigned to annual NPK fertilization, three to PK fertilization, and the rest to a control treatment without fertilization. The fertilizer, composed of urea, fused superphosphate and potassium chloride (N3P4K1) or P4K1 was added manually by deposition on the forest floor for 3 years in April 2011, April 2012, and March 2013. Over these 3 years, the NPK plots received 33.9 g N, 45 g P, and 11.1 g K m−2, while the PK plots received 45 g P and 11.1 g K m−2.Tree and stand measurementsThe standing biomass of trees was estimated using a combination of site-specific allometric equations based on destructive harvesting56 and repeated measurements of the dimensions of all trees in each plot (5–18 trees plot−1). The stem diameter at 1.2 m (D) was measured for all trees in each plot for which D was ≥ 6 cm. Selecting a representative tree in size for each plot within the 4 × 4 m2 center of the plot, we measured the tree height (H) and crown base for the representative trees. Measurements were performed in April and September 2011, September 2012–2014, and October 2021. We observed no effect of fertilization on the relationship between D and H or between D and crown base, so we assumed no effect on the allometric functions for foliage or branch biomass. A dendrometer band (Series 5 Manual Band, Forestry Suppliers Inc., Jackson, MS, USA) was installed on 18 representative trees (one per plot) to monitor radial growth monthly.Three 0.25 m2 circular litter traps were installed 60 cm above the forest floor in each plot in April 2011. Litter was collected at 3-month intervals between June 2011 and March 2015. The litter from each trap was transported to the laboratory and then oven-dried at 65 °C for 48 h. All dried samples were separated into needles, bark, cones, branches, and miscellaneous components, and weighed separately.In September 2014, we estimated the biomass of understory vegetation, separately for woody plants and herbaceous plants. All woody plants  More

  • in

    Ecological divergence of syntopic marine bacterial species is shaped by gene content and expression

    Cohan FM. Bacterial species and speciation. Syst Biol. 2001;50:513–24.Article 
    CAS 
    PubMed 

    Google Scholar 
    Delmont TO, Kiefl E, Kilinc O, Esen OC, Uysal I, Rappe MS, et al. Single-amino acid variants reveal evolutionary processes that shape the biogeography of a global SAR11 subclade. eLife 2019;8:e46497.Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Hunt DE, David LA, Gevers D, Preheim SP, Alm EJ, Polz MF. Resource partitioning and sympatric differentiation among closely related bacterioplankton. Science 2008;320:1081–5.Article 
    CAS 
    PubMed 

    Google Scholar 
    Moore LR, Rocap G, Chisholm SW. Physiology and molecular phylogeny of coexisting Prochlorococcus ecotypes. Nature 1998;393:464–7.Article 
    CAS 
    PubMed 

    Google Scholar 
    Rivas LR. A reinterpretation of the concepts “sympatric” and “allopatric” with proposal for the additional terms “syntopic” and “allotopic”. Syst Zool. 1964;13:42–3.Article 

    Google Scholar 
    Friedman J, Alm EJ, Shapiro BJ. Sympatric speciation: when is it possible in bacteria? PLoS One. 2013;8:e53539.Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Kiene RP, Nowinski B, Esson K, Preston C, Marin R III, Birch J, et al. Unprecedented DMSP concentrations in a massive dinoflagellate bloom in Monterey Bay. Ca Geophys Res Lett. 2019;46:12279–88.Article 

    Google Scholar 
    Scholin CA, Birch J, Jensen S, Marin R, Massion E, Pargett D, et al. The quest to develop ecogenomic sensors a 25-year history of the environmental sample processor (ESP) as a case study. Oceanography. 2017;30:100–13.Article 

    Google Scholar 
    Nowinski B, Smith CB, Thomas CM, Esson K, Marin R, Preston CM, et al. Microbial metagenomes and metatranscriptomes during a coastal phytoplankton bloom. Sci Data. 2019;6:1–7.Article 
    CAS 

    Google Scholar 
    Luo H, Löytynoja A, Moran MA. Genome content of uncultivated marine Roseobacters in the surface ocean. Environ Microbiol. 2012;14:41–51.Article 
    CAS 
    PubMed 

    Google Scholar 
    Connon SA, Giovannoni SJ. High-throughput methods for culturing microorganisms in very-low-nutrient media yield diverse new marine isolates. Appl Environ Microbiol. 2002;68:3878–85.Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Feng X, Chu X, Qian Y, Henson MW, Lanclos VC, Qin F, et al. Mechanisms driving genome reduction of a novel Roseobacter lineage. ISME J. 2021;15:3576–86.Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Moran MA, Belas R, Schell M, González J, Sun F, Sun S, et al. Ecological genomics of marine roseobacters. Appl Environ Microbiol. 2007;73:4559–69.Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Newton RJ, Griffin LE, Bowles KM, Meile C, Gifford S, Givens CE, et al. Genome characteristics of a generalist marine bacterial lineage. ISME J. 2010;4:784–98.Article 
    CAS 
    PubMed 

    Google Scholar 
    Suzuki MT, Preston CM, Béjà O, De La Torre J, Steward G, DeLong EF. Phylogenetic screening of ribosomal RNA gene-containing clones in bacterial artificial chromosome (BAC) libraries from different depths in Monterey Bay. Micro Ecol. 2004;48:473–88.Article 
    CAS 

    Google Scholar 
    Buchan A, González JM, Moran MA. Overview of the marine Roseobacter lineage. Appl Environ Microbiol. 2005;71:5665–77.Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Giebel H-A, Kalhoefer D, Lemke A, Thole S, Gahl-Janssen R, Simon M, et al. Distribution of Roseobacter RCA and SAR11 lineages in the North Sea and characteristics of an abundant RCA isolate. ISME J. 2011;5:8–19.Article 
    PubMed 

    Google Scholar 
    Ottesen EA, Marin R, Preston CM, Young CR, Ryan JP, Scholin CA, et al. Metatranscriptomic analysis of autonomously collected and preserved marine bacterioplankton. ISME J. 2011;5:1881–95.Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Zhang Y, Sun Y, Jiao N, Stepanauskas R, Luo H. Ecological genomics of the uncultivated marine Roseobacter lineage CHAB-I-5. Appl Environ Microbiol. 2016;82:2100–11.Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Aylward FO, Eppley JM, Smith JM, Chavez FP, Scholin CA, DeLong EF. Microbial community transcriptional networks are conserved in three domains at ocean basin scales. Proc Nat Acad Sci. 2015;112:5443–8.Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Ottesen EA, Young CR, Eppley JM, Ryan JP, Chavez FP, Scholin CA, et al. Pattern and synchrony of gene expression among sympatric marine microbial populations. Proc Nat Acad Sci. 2013;110:E488–E97.Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Nowinski B, Motard‐Côté J, Landa M, Preston CM, Scholin CA, Birch JM, et al. Microdiversity and temporal dynamics of marine bacterial dimethylsulfoniopropionate genes. Environ Microbiol. 2019;21:1687–701.Article 
    CAS 
    PubMed 

    Google Scholar 
    Mukherjee S, Stamatis D, Bertsch J, Ovchinnikova G, Sundaramurthi JC, Lee J, et al. Genomes OnLine Database (GOLD) v. 8: overview and updates. Nucleic Acids Res. 2021;49:D723–D33.Article 
    CAS 
    PubMed 

    Google Scholar 
    Chen I-MA, Chu K, Palaniappan K, Pillay M, Ratner A, Huang J, et al. IMG/M v. 5.0: an integrated data management and comparative analysis system for microbial genomes and microbiomes. Nucleic Acids Res. 2019;47:D666–D77.Article 
    CAS 
    PubMed 

    Google Scholar 
    Satinsky BM, Gifford SM, Crump BC, Moran MA. Use of internal standards for quantitative metatranscriptome and metagenome analysis. In: DeLong EF, editor. Methods in Enzymology 531: Elsevier; 2013. p. 237–50.Satinsky BM, Gifford SM, Crump BC, Smith C.Moran MA, Internal genomic DNA standard for quantitative metagenome analysis V3. protocols io 2017; https://doi.org/10.17504/protocols.io.jxdcpi6p.Satinsky BM, Gifford SM, Crump BC, Smith C.Moran MA, Preparation of custom synthesized RNAtranscript standard V3. protocols io. 2017; https://doi.org/10.17504/protocols.io.jxccpiwp.Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods. 2012;9:357.Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Kang DD, Froula J, Egan R, Wang Z. MetaBAT, an efficient tool for accurately reconstructing single genomes from complex microbial communities. PeerJ 2015;3:e1165.Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Olm MR, Brown CT, Brooks B, Banfield JF. dRep: a tool for fast and accurate genomic comparisons that enables improved genome recovery from metagenomes through de-replication. ISME J. 2017;11:2864–8.Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Parks DH, Imelfort M, Skennerton CT, Hugenholtz P, Tyson GW. CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Res. 2015;25:1043–55.Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Rodriguez-R LM, Konstantinidis KT. The enveomics collection: a toolbox for specialized analyses of microbial genomes and metagenomes. PeerJ Prepr. 2016. Report No.: 2167–9843Lee K, Choo Y-J, Giovannoni SJ, Cho J-C. Maritimibacter alkaliphilus gen. nov., sp. nov., a genome-sequenced marine bacterium of the Roseobacter clade in the order Rhodobacterales. Int J Syst Evol Microbiol. 2007;57:1653–8.Article 
    PubMed 

    Google Scholar 
    Eren AM, Esen ÖC, Quince C, Vineis JH, Morrison HG, Sogin ML, et al. Anvi’o: an advanced analysis and visualization platform for ‘omics data. PeerJ 2015;3:e1319.Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Tatusov RL, Galperin MY, Natale DA, Koonin EV. The COG database: a tool for genome-scale analysis of protein functions and evolution. Nucleic Acids Res. 2000;28:33–6.Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Huerta-Cepas J, Forslund K, Coelho LP, Szklarczyk D, Jensen LJ, Von Mering C, et al. Fast genome-wide functional annotation through orthology assignment by eggNOG-mapper. Mol Biol Evol. 2017;34:2115–22.Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Aramaki T, Blanc-Mathieu R, Endo H, Ohkubo K, Kanehisa M, Goto S, et al. KofamKOALA: KEGG ortholog assignment based on profile HMM and adaptive score threshold. Bioinformatics 2020;36:2251–2.Article 
    CAS 
    PubMed 

    Google Scholar 
    Bushnell B. BBMap: a fast, accurate, splice-aware aligner. No. LBNL-7065E. Lawrence Berkeley National Laboratory, Berkeley, CA (United States); 2014.Markowitz VM, Chen I-MA, Palaniappan K, Chu K, Szeto E, Grechkin Y, et al. The integrated microbial genomes system: an expanding comparative analysis resource. Nucleic Acids Res. 2010;38:D382–D90.Article 
    CAS 
    PubMed 

    Google Scholar 
    Sun Y, Luo H. Homologous recombination in core genomes facilitates marine bacterial adaptation. Appl Environ Microbiol. 2018;84:e02545–17.Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Pfaffel O. ClustImpute: An R package for K-means clustering with build-in missing data imputation. https://www.researchgate.net/publication/341881683.Moran MA, Satinsky B, Gifford SM, Luo H, Rivers A, Chan L-K, et al. Sizing up metatranscriptomics. ISME J 2013;7:237–43.Article 
    CAS 
    PubMed 

    Google Scholar 
    Sunagawa S, Coelho LP, Chaffron S, Kultima JR, Labadie K, Salazar G, et al. Structure and function of the global ocean microbiome. Science. 2015;348:1261359.Article 
    PubMed 

    Google Scholar 
    Gifford SM, Zhao L, Stemple B, DeLong K, Medeiros PM, Seim H, et al. Microbial niche diversification in the Galápagos Archipelago and its response to El Niño. Front Microbiol. 2020;11:575194.Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Rich VI, Pham VD, Eppley J, Shi Y, DeLong EF. Time‐series analyses of Monterey Bay coastal microbial picoplankton using a ‘genome proxy’microarray. Environ Microbiol. 2011;13:116–34.Article 
    CAS 
    PubMed 

    Google Scholar 
    Riedel T, Tomasch J, Buchholz I, Jacobs J, Kollenberg M, Gerdts G, et al. Constitutive expression of the proteorhodopsin gene by a flavobacterium strain representative of the proteorhodopsin-producing microbial community in the North Sea. Appl Environ Microbiol. 2010;76:3187–97.Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Iverson V, Morris RM, Frazar CD, Berthiaume CT, Morales RL, Armbrust EV. Untangling genomes from metagenomes: revealing an uncultured class of marine Euryarchaeota. Science 2012;335:587–90.Article 
    CAS 
    PubMed 

    Google Scholar 
    Yooseph S, Nealson KH, Rusch DB, McCrow JP, Dupont CL, Kim M, et al. Genomic and functional adaptation in surface ocean planktonic prokaryotes. Nature 2010;468:60–6.Article 
    CAS 
    PubMed 

    Google Scholar 
    Wagner-Döbler I, Biebl H. Environmental biology of the marine Roseobacter lineage. Annu Rev Microbiol. 2006;60:255–80.Article 
    PubMed 

    Google Scholar 
    West NJ, Obernosterer I, Zemb O, Lebaron P. Major differences of bacterial diversity and activity inside and outside of a natural iron‐fertilized phytoplankton bloom in the Southern Ocean. Environ Microbiol. 2008;10:738–56.Article 
    CAS 
    PubMed 

    Google Scholar 
    Luo H, Moran MA. Evolutionary ecology of the marine Roseobacter clade. Microbiol Mol Biol Rev. 2014;78:573–87.Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Simon M, Scheuner C, Meier-Kolthoff JP, Brinkhoff T, Wagner-Döbler I, Ulbrich M, et al. Phylogenomics of Rhodobacteraceae reveals evolutionary adaptation to marine and non-marine habitats. ISME J 2017;11:1483–99.Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Jain C, Rodriguez-R LM, Phillippy AM, Konstantinidis KT, Aluru S. High throughput ANI analysis of 90K prokaryotic genomes reveals clear species boundaries. Nat Comm. 2018;9:1–8.Article 

    Google Scholar 
    Caro‐Quintero A, Konstantinidis KT. Bacterial species may exist, metagenomics reveal. Environ Microbiol. 2012;14:347–55.Article 
    PubMed 

    Google Scholar 
    Tindall BJ, Rosselló-Móra R, Busse H-J, Ludwig W, Kämpfer P. Notes on the characterization of prokaryote strains for taxonomic purposes. Int J Syst Evol Microbiol. 2010;60:249–66.Article 
    CAS 
    PubMed 

    Google Scholar 
    Cohan FM. What are bacterial species? Ann Rev Microbiol. 2002;56:457–87.Article 
    CAS 

    Google Scholar 
    Mende DR, Sunagawa S, Zeller G, Bork P. Accurate and universal delineation of prokaryotic species. Nat Meth. 2013;10:881–4.Article 
    CAS 

    Google Scholar 
    Olm MR, Crits-Christoph A, Diamond S, Lavy A, Matheus Carnevali PB, Banfield JF. Consistent metagenome-derived metrics verify and delineate bacterial species boundaries. mSystems 2020;5:e00731–19.Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Konstantinidis KT, Tiedje JM. Prokaryotic taxonomy and phylogeny in the genomic era: advancements and challenges ahead. Curr Opin Microbiol. 2007;10:504–9.Article 
    CAS 
    PubMed 

    Google Scholar 
    Delmont TO, Eren EM. Linking pangenomes and metagenomes: The Prochlorococcus metapangenome. PeerJ 2018;2018:e4320–e.Article 

    Google Scholar 
    Neidhardt F, Umbarger H Chemical composition of Escherichia coli. In: FC N, Curtiss R III, JL I, ECC L, KB L, B M, et al., editors. Escherichia coli and Salmonella typhimurium: Cellular and Molecular Biology. Washington DC: ASM Press; 1996. p. 13-6.Taniguchi Y, Choi PJ, Li G-W, Chen H, Babu M, Hearn J, et al. Quantifying E. coli proteome and transcriptome with single-molecule sensitivity in single cells. Science. 2010;329:533–8.Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Rodríguez-Gijón A, Nuy JK, Mehrshad M, Buck M, Schulz F, Woyke T, et al. A genomic perspective across Earth’s microbiomes reveals that genome size in Archaea and Bacteria is linked to ecosystem type and trophic strategy. Front Microbiol. 2022;12:761869.Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Ryu K-S, Kim C, Kim I, Yoo S, Choi B-S, Park C. NMR application probes a novel and ubiquitous family of enzymes that alter monosaccharide configuration. J Biol Chem. 2004;279:25544–8.Article 
    CAS 
    PubMed 

    Google Scholar 
    Giachino A, Waldron KJ. Copper tolerance in bacteria requires the activation of multiple accessory pathways. Mol Microbiol. 2020;114:377–90.Article 
    CAS 
    PubMed 

    Google Scholar 
    Wang X, Zhang Y, Ren M, Xia T, Chu X, Liu C, et al. Cryptic speciation of a pelagic Roseobacter population varying at a few thousand nucleotide sites. ISME J. 2020;14:3106–19.Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Uchimiya M, Schroer W, Olofsson M, Edison AS, Moran MA. Diel investments in metabolite production and consumption in a model microbial system. ISME J. 2022;16:1306–17.Article 
    CAS 
    PubMed 

    Google Scholar 
    Cordero OX, Wildschutte H, Kirkup B, Proehl S, Ngo L, Hussain F, et al. Ecological populations of bacteria act as socially cohesive units of antibiotic production and resistance. Science 2012;337:1228–31.Article 
    CAS 
    PubMed 

    Google Scholar 
    Morris JJ, Lenski RE, Zinser ER. The Black Queen Hypothesis: evolution of dependencies through adaptive gene loss. mBio 2012;3:e00036–12.Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Environmental data from CTD during the Fall 2016 ESP deployment in Monterey Bay, CA. Biological and Chemical Oceanography Data Management Office (BCO-DMO). 2019. Available from: https://doi.org/10.1575/1912/bco-dmo.756376.1.Environmental data from Niskin bottle sampling during the Fall 2016 ESP deployment in Monterey Bay. Biological and Chemical Oceanography Data Management Office (BCO-DMO). 2019. Available from: https://doi.org/10.1575/1912/bco-dmo.756413.1. More

  • in

    Organic carbon accumulation and aggregate formation in soils under organic and inorganic fertilizer management practices in a rice–wheat cropping system

    Zhe, W. et al. Probing the nature of soil organic matter. Crit. Rev. Environ. Sci. Technol. 52, 4072–4093 (2022).Article 

    Google Scholar 
    Blanco-Canqui, H. & Lal, R. Mechanisms of carbon sequestration in soil aggregates. Crit. Rev. Plant Sci. 23, 481–504 (2004).Article 
    CAS 

    Google Scholar 
    Six, J., Paustian, K., Elliott, E. T. & Combrink, C. Soil structure and organic matter: I. Distribution of aggregate–size classes and aggregate–associated carbon. Soil Sci. Soc. Am. J. 64, 681–689 (2000).Article 
    ADS 
    CAS 

    Google Scholar 
    Lehmann, J. & Kleber, M. The contentious nature of soil organic matter. Nature 528, 60–68 (2015).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Six, J., Bossuyt, H., Degryze, S. & Denef, K. A history of research on the link between (micro)aggregates, soil biota, and soil organic matter dynamics. Soil Tillage Res. 79, 7–31 (2004).Article 

    Google Scholar 
    Tisdall, J. M. & Oades, J. M. Organic matter and water-stable aggregates in soils. Eur. J. Soil Sci. 33, 141–163 (1982).Article 
    CAS 

    Google Scholar 
    Luo, Y. et al. Rice rhizodeposition promotes the build-up of organic carbon in soil via fungal necromass. Soil Biol. Biochem. 160, 108345 (2021).Article 
    CAS 

    Google Scholar 
    Wang, X. et al. Organic amendments drive shifts in microbial community structure and keystone taxa which increase C mineralization across aggregate size classes. Soil Biol. Biochem. 153, 108062 (2021).Article 
    CAS 

    Google Scholar 
    Duan, Y. et al. Long–term fertilisation reveals close associations between soil organic carbon composition and microbial traits at aggregate scales. Agric. Ecosyst. Environ. 306, 107169 (2021).Article 
    CAS 

    Google Scholar 
    Christensen, B. T. Physical fractionation of soil and structural and functional complexity in organic matter turnover. Eur. J. Soil Sci. 52, 345–353 (2001).Article 
    CAS 

    Google Scholar 
    Olk, D. C. & Gregorich, E. G. Overview of the symposium proceedings, “meaningful pools in determining soil carbon and nitrogen dynamics”. Soil Sci. Soc. Am. J. 70, 967–974 (2006).Article 
    ADS 
    CAS 

    Google Scholar 
    Courtier-Murias, D. et al. Unraveling the long–term stabilization mechanisms of organic materials in soils by physical fractionation and NMR spectroscopy. Agric. Ecosyst. Environ. 171, 9–18 (2013).Article 
    CAS 

    Google Scholar 
    Rodrigues, L. A. T. et al. Short– and long–term effects of animal manures and mineral fertilizer on carbon stocks in subtropical soil under no–tillage. Geoderma 386, 114913 (2021).Article 
    ADS 
    CAS 

    Google Scholar 
    Mao, J., Dan, C. O., Fang, X., He, Z. & Schmidt-Rohr, K. Influence of animal manure application on the chemical structures of soil organic matter as investigated by advanced solid–state NMR and FT–IR spectroscopy. Geoderma 146, 353–362 (2008).Article 
    ADS 
    CAS 

    Google Scholar 
    Simonetti, G. et al. Characterization of humic carbon in soil aggregates in a long–term experiment with manure and mineral fertilization. Soil Sci. Soc. Am. J. 25, 880–890 (2012).Article 

    Google Scholar 
    Cambardella, C. A. & Elliott, E. T. Particulate soil organic-matter changes across a grassland cultivation sequence. Soil Sci. Soc. Am. J. 56, 777–783 (1992).Article 
    ADS 

    Google Scholar 
    Conant, R. T., Six, J. & Paustian, K. Land use effects on soil carbon fractions in the southeastern United States. I. Management-intensive versus extensive grazing. Biol. Fertil. Soils 38, 386–392 (2003).Article 
    CAS 

    Google Scholar 
    Blanco-Moure, N., Gracia, R., Bielsa, A. C. & López, M. V. Soil organic matter fractions as affected by tillage and soil texture under semiarid Mediterranean conditions. Soil Tillage Res. 155, 381–389 (2016).Article 

    Google Scholar 
    Yu, H. et al. Accumulation of organic C components in soil and aggregates. Sci. Rep. 5, 13804 (2015).Article 
    ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Schöning, I., Morgenroth, G. & Kögel-Knabner, I. O/N–alkyl and alkyl C are stabilised in fine particle size fractions of forest soils. Biogeochemistry 73, 475–497 (2005).Article 

    Google Scholar 
    Solomon, D., Lehmann, J., Kinyangi, J., Liang, B. & Schäfer, T. Carbon K-edge NEXAFS and FTIR–ATR spectroscopic investigation of organic carbon speciation in soils. Soil Sci. Soc. Am. J. 13, 107–119 (2005).Article 

    Google Scholar 
    Yan, H., Chen, C., Xu, Z., Williams, D. & Xu, J. Assessing management impacts on soil organic matter quality in subtropical Australian forests using physical and chemical fractionation as well as 13C NMR spectroscopy. Soil Biol. Biochem. 41, 640–650 (2009).Article 

    Google Scholar 
    Masoom, H. et al. Soil organic matter in its native state: Unravelling the most complex biomaterial on earth. Environ. Sci. Technol. 50, 1670–1680 (2016).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Vogel, C. et al. Clay mineral composition modifies decomposition and sequestration of organic carbon and nitrogen in fine soil fractions. Biol. Fertil. Soils 51, 427–442 (2015).Article 
    CAS 

    Google Scholar 
    Sharma, S., Singh, P., Angmo, P. & Satpute, S. Total and labile pools of organic carbon in relation to soil biological properties under contrasting land-use systems in a dry mountainous region. Carbon Manage. 13, 352–371 (2022).Article 
    CAS 

    Google Scholar 
    Six, J., Elliott, E., Paustian, K. & Doran, J. Aggregation and soil organic matter accumulation in cultivated and native grassland soils. Soil Sci. Soc. Am. J. 62, 1367–1377 (1998).Article 
    ADS 
    CAS 

    Google Scholar 
    Elliott, E. T. Aggregate structure and carbon, nitrogen, and phosphorus in native and cultivated soils. Soil Sci. Soc. Am. J. 50, 627–633 (1986).Article 
    ADS 

    Google Scholar 
    Yu, H., Ding, W., Luo, J., Geng, R. & Cai, Z. Long-term application of organic manure and mineral fertilizers on aggregation and aggregate-associated carbon in a sandy loam soil. Soil Tillage Res. 124, 170–177 (2012).Article 

    Google Scholar 
    Carter, M. R. & Gregorich, E. G. (eds) Soil Sampling and Methods of Analysis 2nd edn, 230–233 (Taylor & Francis Group, CRC, 2007).
    Google Scholar 
    Lu, R. (ed.) Soil and Agro-chemistry Analytical Methods 146–149 (China Agricultural Science and Technology Press, 1999).
    Google Scholar 
    Wu, J., Joergensen, R. G., Pommerening, B., Chaussod, R. & Brookes, P. C. Measurement of soil microbial biomass C by fumigation extraction: An automated procedure. Soil Biol. Biochem. 22, 1167–1169 (1990).Article 
    CAS 

    Google Scholar 
    Zhang, X., Zhu, A., Yang, W. & Zhang, J. Accumulation of organic components and its association with macroaggregation in a sandy loam soil following conservation tillage. Plant Soil. 416, 1–15 (2017).Article 
    CAS 

    Google Scholar 
    Skjemstad, J. O., Clarke, P., Taylor, J. A., Oades, J. M. & Newman, R. H. The removal of magnetic materials from surface soils—a solid state 13C CP/MAS NMR study. Soil Res. 32, 1215–1229 (1994).Article 
    CAS 

    Google Scholar 
    Ringle, C. M., Wende, S. & Becker, J. M. SmartPLS 3.” Boenningstedt: SmartPLS GmbH. Preprint at http://www.smartpls.com (2015).Jerbi, M., Labidi, S., Lounès-Hadj Sahraoui, A., Chaar, H. & Ben Jeddi, F. Higher temperatures and lower annual rainfall do not restrict, directly or indirectly, the mycorrhizal colonization of barley (Hordeum vulgare L.) under rainfed conditions. PLoS ONE 15, e0241794 (2020).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Cohen, J. Statistical power analysis for the behavioral sciences 2nd edn, 407–530 (Erlbaum Associates, Berlin, 1988).MATH 

    Google Scholar 
    Singh, P. & Benbi, D. K. Physical and chemical stabilization of soil organic matter in cropland ecosystems under rice–wheat, maize–wheat and cotton–wheat cropping systems in northwestern India. Carbon Manag. 12, 603–621 (2021).Article 
    CAS 

    Google Scholar 
    Kiem, R. & Kögel-Knabner, I. Contribution of lignin and polysaccharides to the refractory carbon pool in C–depleted arable soils. Soil Biol. Biochem. 35, 101–118 (2003).Article 
    CAS 

    Google Scholar 
    Lutzow, M. V. et al. Stabilization of organic matter in temperate soils: mechanisms and their relevance under different soil conditions: a review. Eur. J. Soil Sci. 57, 426–445 (2006).Article 

    Google Scholar 
    Yudina, A. V., Klyueva, V. V., Romanenko, K. A. & Fomin, D. S. Micro- within macro: How micro-aggregation shapes the soil pore space and water-stability. Geoderma 415, 115771 (2022).Article 
    ADS 
    CAS 

    Google Scholar 
    Tisdall, J. M., Smith, S. E. & Rengasamy, P. Aggregation of soil by fungal hyphae. Soil Res. 35, 55–60 (1997).Article 

    Google Scholar 
    Li, T. et al. Contrasting impacts of manure and inorganic fertilizer applications for nine years on soil organic carbon and its labile fractions in bulk soil and soil aggregates. CATENA 194, 104739 (2020).Article 
    CAS 

    Google Scholar 
    Liang, Y. et al. Effect of chemical fertilizer and straw-derived organic amendments on continuous maize yield, soil carbon sequestration and soil quality in a Chinese Mollisol. Agric. Ecosyst. Environ. 314, 107403 (2021).Article 
    CAS 

    Google Scholar 
    Liang, C., Kästner, M. & Joergensen, R. G. Microbial necromass on the rise: The growing focus on its role in soil organic matter development. Soil Biol. Biochem. 150, 108000 (2020).Article 
    CAS 

    Google Scholar 
    Sharma, S., Singh, P. & Kumar, S. Responses of soil carbon pools, enzymatic activity, and crop yields to nitrogen and straw incorporation in a rice-wheat cropping system in North-Western India. Front. Sustain. Food Syst. 4, 532704 (2020).Article 

    Google Scholar 
    Puget, P., Chenu, C. & Balesdent, J. Dynamics of soil organic matter associated with particle–size fractions of water–stable aggregates. Eur. J. Soil Sci. 51, 595–605 (2000).Article 

    Google Scholar  More

  • in

    Surface-layer protein is a public-good matrix exopolymer for microbial community organisation in environmental anammox biofilms

    Jayathilake PG, Jana S, Rushton S, Swailes D, Bridgens B, Curtis T, et al. Extracellular polymeric substance production and aggregated bacteria colonization influence the competition of microbes in biofilms. Front Microbiol. 2017;8:1865.Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Flemming H-C, Neu TR, Wingender J (eds). The Perfect Slime: Microbial Extracellular Polymeric Substances (EPS). IWA Publishing, London, 2016.Morales-García AL, Bailey RG, Jana S, Burgess JG. The role of polymers in cross-kingdom bioadhesion. Philos Trans R Soc Lond B Biol Sci. 2019;374:20190192.Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Davey ME, O’Toole GA. Microbial biofilms: From ecology to molecular genetics. Microbiol Mol. 2000;64:847–67.Article 
    CAS 

    Google Scholar 
    Peters BM, Jabra-Rizk MA, O’May GA, Costerton JW, Shirtliff ME. Polymicrobial interactions: Impact on pathogenesis and human disease. Clin Microbiol Rev. 2012;25:193–213.Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Karygianni L, Ren Z, Koo H, Thurnheer T. Biofilm matrixome: Extracellular components in structured microbial communities. Trends Microbiol. 2020;28:668–81.Article 
    CAS 
    PubMed 

    Google Scholar 
    Morris BEL, Henneberger R, Huber H, Moissl-Eichinger C. Microbial syntrophy: Interaction for the common good. FEMS Microbiol Rev. 2013;37:384–406.Article 
    CAS 
    PubMed 

    Google Scholar 
    Decho AW, Gutierrez T. Microbial extracellular polymeric substances (EPSs) in ocean systems. Front Microbiol. 2017;8:922.Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Boleij M, Seviour T, Wong LL, van Loosdrecht MCM, Lin Y. Solubilization and characterization of extracellular proteins from anammox granular sludge. Water Res. 2019;164:114952.Article 
    CAS 
    PubMed 

    Google Scholar 
    Kim D, Barraza JP, Arthur RA, Hara A, Lewis K, Liu Y, et al. Spatial mapping of polymicrobial communities reveals a precise biogeography associated with human dental caries. Proc Natl Acad Sci USA. 2020;117:12375–86.Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Sadiq FA, Burmølle M, Heyndrickx M, Flint S, Lu W, Chen W, et al. Community-wide changes reflecting bacterial interspecific interactions in multispecies biofilms. Crit Rev Microbiol. 2021;47:338–58.Article 
    PubMed 

    Google Scholar 
    Liu W, Jacquiod S, Brejnrod A, Russel J, Burmølle M, Sørensen SJ. Deciphering links between bacterial interactions and spatial organization in multispecies biofilms. ISME J. 2019;13:3054–66.Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Bridier A, Le Coq D, Dubois-Brissonnet F, Thomas V, Aymerich S, Briandet R. The spatial architecture of Bacillus subtilis biofilms deciphered using a surface-associated model and in situ imaging. PLOS One. 2011;6:e16177.Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Lee KWK, Periasamy S, Mukherjee M, Xie C, Kjelleberg S, Rice SA. Biofilm development and enhanced stress resistance of a model, mixed-species community biofilm. ISME J. 2014;8:894–907.Article 
    CAS 
    PubMed 

    Google Scholar 
    Myszka K, Czaczyk K. Characterization of adhesive exopolysaccharide (EPS) produced by Pseudomonas aeruginosa under starvation conditions. Curr Microbiol. 2009;58:541–6.Article 
    CAS 
    PubMed 

    Google Scholar 
    Harimawan A, Ting YP. Investigation of extracellular polymeric substances (EPS) properties of P. aeruginosa and B. subtilis and their role in bacterial adhesion. Colloids Surf B. 2016;146:459–67.Article 
    CAS 

    Google Scholar 
    Yang X-R, Li H, Nie S-A, Su J-Q, Weng B-S, Zhu G-B, et al. Potential contribution of anammox to nitrogen loss from paddy soils in Southern China. Appl Environ Microbiol. 2015;81:938–47.Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Kartal B, van Niftrik L, Keltjens JT, Op den Camp HJM, Jetten MSM Chapter 3 – Anammox—Growth physiology, cell biology, and metabolism. In: Poole RK, editor. Adv Microb Physiol. 60: Academic Press; 2012. p. 211–62.Lu Y, Natarajan G, Nguyen TQN, Thi SS, Arumugam K, Seviour TW, et al. Species level enrichment of AnAOB and associated growth morphology under the effect of key metabolites. bioRxiv. 2020. 2020.02.04.934877Gonzalez-Gil G, Sougrat R, Behzad AR, Lens PN, Saikaly PE. Microbial community composition and ultrastructure of granules from a full-scale anammox reactor. Micro Ecol. 2015;70:118–31.Article 
    CAS 

    Google Scholar 
    Kindaichi T, Yuri S, Ozaki N, Ohashi A. Ecophysiological role and function of uncultured Chloroflexi in an anammox reactor. Water Sci Technol. 2012;66:2556–61.Article 
    CAS 
    PubMed 

    Google Scholar 
    Qin Y, Han B, Cao Y, Wang T. Impact of substrate concentration on anammox-UBF reactors start-up. Bioresour Technol. 2017;239:422–9.Article 
    CAS 
    PubMed 

    Google Scholar 
    Chen Z, Meng Y, Sheng B, Zhou Z, Jin C, Meng F. Linking exoproteome function and structure to anammox biofilm development. Environ Sci Technol. 2019;53:1490–500.Article 
    CAS 
    PubMed 

    Google Scholar 
    Ali M, Shaw DR, Albertsen M, Saikaly PE. Comparative genome-centric analysis of freshwater and marine ANAMMOX cultures suggests functional redundancy in nitrogen removal processes. Front Microbiol. 2020;11:1637.Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Jia F, Yang Q, Liu X, Li X, Li B, Zhang L, et al. Stratification of extracellular polymeric substances (EPS) for aggregated anammox microorganisms. Environ Sci Technol. 2017;51:3260–8.Article 
    CAS 
    PubMed 

    Google Scholar 
    Hou X, Liu S, Zhang Z. Role of extracellular polymeric substance in determining the high aggregation ability of anammox sludge. Water Res. 2015;75:51–62.Article 
    CAS 
    PubMed 

    Google Scholar 
    Feng C, Lotti T, Lin Y, Malpei F. Extracellular polymeric substances extraction and recovery from anammox granules: Evaluation of methods and protocol development. Chem Eng J. 2019;374:112–22.Article 
    CAS 

    Google Scholar 
    Lotti T, Carretti E, Berti D, Montis C, Del Buffa S, Lubello C, et al. Hydrogels formed by anammox extracellular polymeric substances: Structural and mechanical insights. Sci Rep. 2019;9:11633.Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Jakubovics NS, Goodman SD, Mashburn-Warren L, Stafford GP, Cieplik F. The dental plaque biofilm matrix. Periodontology 2000. 2021;86:32–56.Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Ðapa T, Leuzzi R, Ng YK, Baban ST, Adamo R, Kuehne SA, et al. Multiple factors modulate biofilm formation by the anaerobic pathogen Clostridium difficile. J Bacteriol. 2013;195:545–55.Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Honma K, Inagaki S, Okuda K, Kuramitsu HK, Sharma A. Role of a Tannerella forsythia exopolysaccharide synthesis operon in biofilm development. Micro Pathog. 2007;42:156–66.Article 
    CAS 

    Google Scholar 
    Li X-R, Du B, Fu H-X, Wang R-F, Shi J-H, Wang Y, et al. The bacterial diversity in an anaerobic ammonium-oxidizing (anammox) reactor community. Syst Appl Microbiol. 2009;32:278–89.Article 
    CAS 
    PubMed 

    Google Scholar 
    Cho S, Takahashi Y, Fujii N, Yamada Y, Satoh H, Okabe S. Nitrogen removal performance and microbial community analysis of an anaerobic up-flow granular bed anammox reactor. Chemosphere 2010;78:1129–35.Article 
    CAS 
    PubMed 

    Google Scholar 
    Morgenroth E, Sherden T, Van Loosdrecht MCM, Heijnen JJ, Wilderer PA. Aerobic granular sludge in a sequencing batch reactor. Water Res. 1997;31:3191–4.Article 
    CAS 

    Google Scholar 
    Wong LL, Natarajan G, Boleij M, Thi SS, Winnerdy FR, Mugunthan S, et al. Extracellular protein isolation from the matrix of anammox biofilm using ionic liquid extraction. Appl Microbiol Biotechnol. 2020;104:3643–54.Article 
    CAS 
    PubMed 

    Google Scholar 
    Law Y, Kirkegaard RH, Cokro AA, Liu X, Arumugam K, Xie C, et al. Integrative microbial community analysis reveals full-scale enhanced biological phosphorus removal under tropical conditions. Sci Rep. 2016;6:25719.Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Ondov BD, Bergman NH, Phillippy AM. Interactive metagenomic visualization in a Web browser. BMC Bioinform. 2011;12:385.Article 

    Google Scholar 
    Liu X, Arumugam K, Natarajan G, Seviour TW, Drautz-Moses DI, Wuertz S, et al. Draft genome sequence of a Candidatus brocadia bacterium enriched from activated sludge collected in a tropical climate. Genome Announc. 2018;6:e00406–18.Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Price MN, Dehal PS, Arkin AP. FastTree 2-approximately maximum-likelihood trees for large alignments. PloS One. 2010;5:e9490–e.Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Arkin AP, Cottingham RW, Henry CS, Harris NL, Stevens RL, Maslov S, et al. KBase: The United States Department of Energy Systems Biology Knowledgebase. Nat Biotechnol. 2018;36:566–9.Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Parks DH, Imelfort M, Skennerton CT, Hugenholtz P, Tyson GW. CheckM: Assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Res. 2015;25:1043–55.Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Buchfink B, Reuter K, Drost H-G. Sensitive protein alignments at tree-of-life scale using DIAMOND. Nat Methods. 2021;18:366–8.Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Buchfink B, Xie C, Huson DH. Fast and sensitive protein alignment using DIAMOND. Nat Methods. 2015;12:59–60.Article 
    CAS 
    PubMed 

    Google Scholar 
    Daims H, Nielsen JL, Nielsen PH, Schleifer K-H, Wagner M. In situ characterization of Nitrospira-like nitrite-oxidizing bacteria active in wastewater treatment plants. Appl Environ Microbiol. 2001;67:5273–84.Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Seviour T, Wong LL, Lu Y, Mugunthan S, Yang Q, Shankari UDOCS, et al. Phase transitions by an abundant protein in the anammox extracellular matrix mediate cell-to-cell aggregation and biofilm formation. mBio 2020;11:e02052–20.Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Protter DSW, Rao BS, Van Treeck B, Lin Y, Mizoue L, Rosen MK, et al. Intrinsically disordered regions can contribute promiscuous interactions to RNP granule assembly. Cell Rep. 2018;22:1401–12.Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Fulton KM, Smith JC, Twine SM. Clinical applications of bacterial glycoproteins. Expert Rev Proteom. 2016;13:345–53.Article 
    CAS 

    Google Scholar 
    Upreti RK, Kumar M, Shankar V. Bacterial glycoproteins: Functions, biosynthesis and applications. Proteomics 2003;3:363–79.Article 
    CAS 
    PubMed 

    Google Scholar 
    van Teeseling MCF, Maresch D, Rath CB, Figl R, Altmann F, Jetten MSM, et al. The S-layer protein of the anammox bacterium Kuenenia stuttgartiensiss is heavily O-glycosylated. Front Microbiol. 2016;7:1721.PubMed 
    PubMed Central 

    Google Scholar 
    McGonigle JM, Lang SQ, Brazelton WJ, Parales RE. Genomic evidence for formate metabolism by Chloroflexi as the key to unlocking deep carbon in lost city microbial ecosystems. Appl Environ Microbiol. 2020;86:e02583–19.Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Vuillemin A, Kerrigan Z, D’Hondt S, Orsi WD. Exploring the abundance, metabolic potential and gene expression of subseafloor Chloroflexi in million-year-old oxic and anoxic abyssal clay. FEMS Microbiol Ecol. 2020;96:fiaa223.Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Kartal B, de Almeida NM, Maalcke WJ, Op den Camp HJ, Jetten MS, Keltjens JT. How to make a living from anaerobic ammonium oxidation. FEMS Microbiol Rev. 2013;37:428–61.Article 
    CAS 
    PubMed 

    Google Scholar 
    Loera-Muro A, Guerrero-Barrera A, Tremblay DNY, Hathroubi S, Angulo C. Bacterial biofilm-derived antigens: A new strategy for vaccine development against infectious diseases. Expert Rev Vaccines. 2021;20:385–96.Article 
    CAS 
    PubMed 

    Google Scholar 
    Hobley L, Harkins C, MacPhee CE, Stanley-Wall NR. Giving structure to the biofilm matrix: An overview of individual strategies and emerging common themes. FEMS Microbiol Rev. 2015;39:649–69.Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Elias S, Banin E. Multi-species biofilms: Living with friendly neighbors. FEMS Microbiol Rev. 2012;36:990–1004.Article 
    CAS 
    PubMed 

    Google Scholar 
    Teeseling MCFV, Almeida NMD, Klingl A, Speth DR, Camp HJMOD, Rachel R, et al. A new addition to the cell plan of anammox bacteria: Candidatus Kuenenia stuttgartiensis has a protein surface layer as the outermost layer of the cell. J Bacteriol. 2014;196:80–9.Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Paula AJ, Hwang G, Koo H. Dynamics of bacterial population growth in biofilms resemble spatial and structural aspects of urbanization. Nat Commun. 2020;11:1354.Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Kragelund C, Caterina L, Borger A, Thelen K, Eikelboom D, Tandoi V, et al. Identity, abundance and ecophysiology of filamentous Chloroflexi species present in activated sludge treatment plants. FEMS Microbiol Ecol. 2007;59:671–82.Article 
    CAS 
    PubMed 

    Google Scholar 
    Nierychlo M, Miłobędzka A, Petriglieri F, McIlroy B, Nielsen PH, McIlroy SJ. The morphology and metabolic potential of the Chloroflexi in full-scale activated sludge wastewater treatment plants. FEMS Microbiol Ecol. 2018;95.Kragelund C, Thomsen TR, Mielczarek AT, Nielsen PH. Eikelboom’s morphotype 0803 in activated sludge belongs to the genus Caldilinea in the phylum Chloroflexi. FEMS Microbiol Ecol. 2011;76:451–62.Article 
    CAS 
    PubMed 

    Google Scholar 
    Zhang J, Miao Y, Zhang Q, Sun Y, Wu L, Peng Y. Mechanism of stable sewage nitrogen removal in a partial nitrification-anammox biofilm system at low temperatures: Microbial community and EPS analysis. Bioresour Technol. 2020;297:122459.Article 
    CAS 
    PubMed 

    Google Scholar 
    Björnsson L, Hugenholtz P, Tyson GW, Blackall LL. Filamentous Chloroflexi (green non-sulfur bacteria) are abundant in wastewater treatment processes with biological nutrient removal. Microbiology 2002;148:2309–18.Article 
    PubMed 

    Google Scholar 
    Boleij M, Pabst M, Neu TR, van Loosdrecht MCM, Lin Y. Identification of glycoproteins isolated from extracellular polymeric substances of full-scale anammox granular sludge. Environ Sci Technol. 2018;52:13127–35.Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Pabst M, Grouzdev DS, Lawson CE, Kleikamp HBC, de Ram C, Louwen R, et al. A general approach to explore prokaryotic protein glycosylation reveals the unique surface layer modulation of an anammox bacterium. ISME J. 2022;16:346–57.Article 
    CAS 
    PubMed 

    Google Scholar 
    Berlanga M, Guerrero R. Living together in biofilms: The microbial cell factory and its biotechnological implications. Micro Cell Fact. 2016;15:165.Article 

    Google Scholar 
    Liu T, Tian R, Li Q, Wu N, Quan X. Strengthened attachment of anammox bacteria on iron-based modified carrier and its effects on anammox performance in integrated floating-film activated sludge (IFFAS) process. Sci Total Environ. 2021;787:147679.Article 
    CAS 
    PubMed 

    Google Scholar  More

  • in

    Denser forests across the USA experience more damage from insects and pathogens

    Teale, S. A. & Castello, J. D. The past as key to the future: a new perspective on forest health. In Forest Health: An Integrated Perspective (eds Castello, J. D. & Teale, S. A.) 3–16 (Cambridge University Press, 2011). https://doi.org/10.1017/CBO9780511974977.002.Chapter 

    Google Scholar 
    Jactel, H., Koricheva, J. & Castagneyrol, B. Responses of forest insect pests to climate change: Not so simple. Curr. Opin. Insect Sci. 35, 103–108 (2019).Article 
    PubMed 

    Google Scholar 
    Trumbore, S., Brando, P. & Hartmann, H. Forest health and global change. Science 349, 814–818 (2015).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    North, M. P. et al. Operational resilience in western US frequent-fire forests. For. Ecol. Manag. 507, 120004 (2022).Article 

    Google Scholar 
    Raffa, K. F. et al. A literal use of “forest health” safeguards against misuse and misapplication. J. For. 107, 276–277 (2009).
    Google Scholar 
    Kolb, T. E., Wagner, M. R. & Covington, W. W. Concepts of forest health: Utilitarian and ecosystem perspectives. J. For. 92, 10–15 (1994).
    Google Scholar 
    Cale, J. A. et al. A quantitative index of forest structural sustainability. Forests 5, 1618–1634 (2014).Article 

    Google Scholar 
    Lintz, H. E. et al. Quantifying density-independent mortality of temperate tree species. Ecol. Indic. 66, 1–9 (2016).Article 

    Google Scholar 
    Stanke, H., Finley, A. O., Domke, G. M., Weed, A. S. & MacFarlane, D. W. Over half of western United States’ most abundant tree species in decline. Nat. Commun. 12, 451 (2021).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Bettinger, P., Boston, K., Siry, J. P. & Grebner, D. L. Chapter 2—Valuing and Characterizing Forest Conditions. In Forest Management and Planning (eds Bettinger, P. et al.) 21–63 (Academic Press, 2017). https://doi.org/10.1016/B978-0-12-809476-1.00002-3.Chapter 

    Google Scholar 
    Crowther, T. W. et al. Mapping tree density at a global scale. Nature 525, 201–205 (2015).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Fettig, C. J. et al. The effectiveness of vegetation management practices for prevention and control of bark beetle infestations in coniferous forests of the western and southern United States. For. Ecol. Manag. 238, 24–53 (2007).Article 

    Google Scholar 
    Morin, R. S. & Liebhold, A. M. Invasions by two non-native insects alter regional forest species composition and successional trajectories. For. Ecol. Manag. 341, 67–74 (2015).Article 

    Google Scholar 
    Nowak, J. T., Meeker, J. R., Coyle, D. R., Steiner, C. A. & Brownie, C. Southern pine beetle infestations in relation to forest stand conditions, previous thinning, and prescribed burning: Evaluation of the southern pine beetle prevention program. J. For. 113, 454–462 (2015).
    Google Scholar 
    Asaro, C. & Chamberlin, L. A. Outbreak history (1953–2014) of spring defoliators impacting oak-dominated forests in Virginia, with emphasis on gypsy moth (Lymantria dispar L.) and fall cankerworm (Alsophila pometaria Harris). Am. Entomol. 61, 174–185 (2015).Article 

    Google Scholar 
    Negrón, J. F. Probability of infestation and extent of mortality associated with the Douglas-fir beetle in the Colorado Front Range. For. Ecol. Manag. 107, 71–85 (1998).Article 

    Google Scholar 
    Negrón, J. F. & Popp, J. B. Probability of ponderosa pine infestation by mountain pine beetle in the Colorado Front Range. For. Ecol. Manag. 191, 17–27 (2004).Article 

    Google Scholar 
    Schmid, J. M. & Frye, R. H. Spruce Beetle in the Rockies. Gen. Tech. Rep. RM-49 (US Department of Agriculture, Forest Service, Rocky Mountain Forest and Range Experiment Station, 1977).
    Google Scholar 
    Krivak-Tetley, F. E. et al. Aggressive tree killer or natural thinning agent? Assessing the impacts of a globally important forest insect. For. Ecol. Manag. 483, 118728 (2021).Article 

    Google Scholar 
    Bradford, J. B. et al. Tree mortality response to drought-density interactions suggests opportunities to enhance drought resistance. J. Appl. Ecol. 59, 549–559 (2022).Article 

    Google Scholar 
    Young, D. J. N. et al. Long-term climate and competition explain forest mortality patterns under extreme drought. Ecol. Lett. 20, 78–86 (2017).Article 
    PubMed 

    Google Scholar 
    Furniss, T. J., Das, A. J., van Mantgem, P. J., Stephenson, N. L. & Lutz, J. A. Crowding, climate, and the case for social distancing among trees. Ecol. Appl. 32, e2507 (2022).Article 
    PubMed 

    Google Scholar 
    Woodall, C. W. & Weiskittel, A. R. Relative density of United States forests has shifted to higher levels over last two decades with important implications for future dynamics. Sci. Rep. 11, 1–12 (2021).Article 

    Google Scholar 
    Gandhi, K. J. K., Campbell, F. & Abrams, J. Current status of forest health policy in the United States. Insects 10, 1–14 (2019).Article 

    Google Scholar 
    Ciesla, W. M. The role of human activities on forest insect outbreaks worldwide. Int. For. Rev. 17, 269–281 (2015).
    Google Scholar 
    Jactel, H. & Brockerhoff, E. G. Tree diversity reduces herbivory by forest insects. Ecol. Lett. 10, 835–848 (2007).Article 
    PubMed 

    Google Scholar 
    Marini, L., Ayres, M. P. & Jactel, H. Impact of stand and landscape management on forest pest damage. Annu. Rev. Entomol. 67, 181–199 (2022).Article 
    PubMed 

    Google Scholar 
    Guyot, V., Castagneyrol, B., Vialatte, A., Deconchat, M. & Jactel, H. Tree diversity reduces pest damage in mature forests across Europe. Biol. Lett. 12, 20151037 (2016).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Kneeshaw, D. D. et al. The vision of managing for pest-resistant landscapes: Realistic or utopic? Curr. For. Rep. 7, 97–113 (2021).PubMed 
    PubMed Central 

    Google Scholar 
    Chisholm, P. J., Stevens-Rumann, C. S. & Davis, T. S. Interactions between climate and stand conditions predict pine mortality during a bark beetle outbreak. Forests 12, 360 (2021).Article 

    Google Scholar 
    Ferrell, G. T., Otrosina, W. J. & Demars, C. J. Predicting susceptibility of white fir during a drought-associated outbreak of the fir engraver, Scolytus ventralis in California. Can. J. For. Res. 24, 302–305 (1994).Article 

    Google Scholar 
    Asaro, C., Nowak, J. T. & Elledge, A. Why have southern pine beetle outbreaks declined in the southeastern U.S. with the expansion of intensive pine silviculture? A brief review of hypotheses. For. Ecol. Manag. 391, 338–348 (2017).Article 

    Google Scholar 
    Nowak, J. T., Klepzig, K. D., Coyle, D. R., Carothers, W. A. & Gandhi, K. J. K. Southern pine beetles in central hardwood forests: Frequency, spatial extent, and changes to forest structure. In Managing Forest Ecosystems Volume 32: Natural Disturbances and Historic Range of Variation (eds Greenberg, C. H. & Collins, B. S.) 73–88 (Springer International Publishing, 2016). https://doi.org/10.1007/978-3-319-21527-3_4.Chapter 

    Google Scholar 
    Crocker, S. J., Liknes, G. C., McKee, F. R., Albers, J. S. & Aukema, B. H. Stand-level factors associated with resurging mortality from eastern larch beetle (Dendroctonus simplex LeConte). For. Ecol. Manag. 375, 27–34 (2016).Article 

    Google Scholar 
    Mattson, W. J. & Addy, N. D. Phytophagous insects as regulators of forest primary production. Science 190, 515–522 (1975).Article 
    ADS 

    Google Scholar 
    Thom, D. & Seidl, R. Natural disturbance impacts on ecosystem services and biodiversity in temperate and boreal forests. Biol. Rev. 91, 760–781 (2016).Article 
    PubMed 

    Google Scholar 
    Grégoire, J. C., Raffa, K. F. & Lindgren, B. S. Economics and politics of bark beetles. In Bark Beetles: Biology and Ecology of Native and Invasive Species (eds Vega, F. E. & Hofstetter, R. W.) 585–613 (Academic Press, 2015). https://doi.org/10.1016/B978-0-12-417156-5.00015-0.Chapter 

    Google Scholar 
    Kolb, T. E. et al. Observed and anticipated impacts of drought on forest insects and diseases in the United States. For. Ecol. Manag. 380, 321–334 (2016).Article 

    Google Scholar 
    Fettig, C. J. et al. Changing climates, changing forests: A western North American perspective. J. For. 111, 214–228 (2013).
    Google Scholar 
    Liebhold, A. M. et al. A highly aggregated geographical distribution of forest pest invasions in the USA. Divers. Distrib. 19, 1208–1216 (2013).Article 

    Google Scholar 
    Siegert, N. W., Mccullough, D. G., Liebhold, A. M. & Telewski, F. W. Dendrochronological reconstruction of the epicentre and early spread of emerald ash borer in North America. Divers. Distrib. 20, 847–858 (2014).Article 

    Google Scholar 
    Smith, A., Herms, D. A., Long, R. P. & Gandhi, K. J. K. Community composition and structure had no effect on forest susceptibility to invasion by the emerald ash borer (Coleoptera: Buprestidae). Can. Entomol. 147, 318–328 (2015).Article 

    Google Scholar 
    Aukema, J. E. et al. Historical accumulation of nonindigenous forest pests in the continental United States. Bioscience 60, 886–897 (2010).Article 

    Google Scholar 
    Hicke, J. A. et al. Effects of biotic disturbances on forest carbon cycling in the United States and Canada. Glob. Chang. Biol. 18, 7–34 (2012).Article 
    ADS 

    Google Scholar 
    Feeny, P. Seasonal changes in oak leaf tannins and nutrients as a cause of spring feeding by winter moth caterpillars. Ecology 51, 565–581 (1970).Article 

    Google Scholar 
    Schowalter, T. D., Hargrove, W. W. & Crossley, D. A. Herbivory in forested ecosystems. Annu. Rev. Entomol. 31, 177–196 (1986).Article 

    Google Scholar 
    Seidl, R. et al. Forest disturbances under climate change. Nat. Clim. Chang. 7, 395–402 (2017).Article 
    ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Colautti, R. I., Ricciardi, A., Grigorovich, I. A. & MacIsaac, H. J. Is invasion success explained by the enemy release hypothesis? Ecol. Lett. 7, 721–733 (2004).Article 

    Google Scholar 
    Catford, J. A., Jansson, R. & Nilsson, C. Reducing redundancy in invasion ecology by integrating hypotheses into a single theoretical framework. Divers. Distrib. 15, 22–40 (2009).Article 

    Google Scholar 
    Guyot, V. et al. Tree diversity limits the impact of an invasive forest pest. PLoS One 10, 1–16 (2015).Article 

    Google Scholar 
    Root, R. B. Organization of a plant-arthropod association in simple and diverse habitats: The fauna of collards (Brassica oleracea). Ecol. Monogr. 43, 95–124 (1973).Article 

    Google Scholar 
    Acker, S. A., Boetsch, J. R., Fallon, B. & Denn, M. Stable background tree mortality in mature and old-growth forests in western Washington (NW USA). For. Ecol. Manag. 532, 120817 (2023).Article 

    Google Scholar 
    Shive, K. L. et al. Ancient trees and modern wildfires: Declining resilience to wildfire in the highly fire-adapted giant sequoia. For. Ecol. Manag. 511, 120110 (2022).Article 

    Google Scholar 
    Searle, E. B., Chen, H. Y. H. & Paquette, A. Higher tree diversity is linked to higher tree mortality. Proc. Natl. Acad. Sci. U.S.A. 119, 1–7 (2022).Article 

    Google Scholar 
    Hart, S. J., Veblen, T. T., Eisenhart, K. S., Jarvis, D. & Kulakowski, D. Drought induces spruce beetle (Dendroctonus rufipennis) outbreaks across northwestern Colorado. Ecology 95, 930–939 (2014).Article 
    PubMed 

    Google Scholar 
    Hart, S. J., Veblen, T. T. & Kulakowski, D. Do tree and stand-level attributes determine susceptibility of spruce-fir forests to spruce beetle outbreaks in the early 21st century? For. Ecol. Manag. 318, 44–53 (2014).Article 

    Google Scholar 
    Temperli, C. et al. Are density reduction treatments effective at managing for resistance or resilience to spruce beetle disturbance in the southern Rocky Mountains? For. Ecol. Manag. 334, 53–63 (2014).Article 

    Google Scholar 
    Six, D. L., Biber, E. & Long, E. Management for mountain pine beetle outbreak suppression: Does relevant science support current policy? Forests 5, 103–133 (2014).Article 

    Google Scholar 
    Black, S. H., Kulakowski, D., Noon, B. R. & Dellasala, D. A. Do bark beetle outbreaks increase wildfire risks in the central U.S. rocky mountains? Implications from recent research. Nat. Areas J. 33, 59–65 (2013).Article 

    Google Scholar 
    Oswalt, S. N., Smith, W. B., Miles, P. D. & Pugh, S. A. Forest Resources of the United States, 2017: A Technical Document Supporting the Forest Service 2020 RPA Assessment. Gen. Tech. Rep. WO-97 (US Department of Agriculture, Forest Service, 2019). https://doi.org/10.2737/WO-GTR-97.Book 

    Google Scholar 
    Cleland, D. et al. Terrestrial condition assessment for national forests of the USDA Forest Service in the continental US. Sustainability 9, 1–19 (2017).Article 

    Google Scholar 
    USDA Forest Service Forest Health Protection. Insect and Disease Detection Survey (IDS) data downloads. https://www.fs.usda.gov/foresthealth/applied-sciences/mapping-reporting/detection-surveys.shtml (2021). Accessed on 9 October 2021.Spruce, J. P. et al. Assessment of MODIS NDVI time series data products for detecting forest defoliation by gypsy moth outbreaks. Remote Sens. Environ. 115, 427–437 (2011).Article 
    ADS 

    Google Scholar 
    Gomez, D. F., Ritger, H. M. W., Pearce, C., Eickwort, J. & Hulcr, J. Ability of remote sensing systems to detect bark beetle spots in the southeastern US. Forests 11, 1–10 (2020).Article 

    Google Scholar 
    Hanavan, R. P. et al. Supplementing the forest health national aerial survey program with remote sensing during the COVID-19 pandemic: Lessons learned from a collaborative approach. J. For. 120, 125–132 (2021).
    Google Scholar 
    Johnson, E. W. & Wittwer, D. Aerial detection surveys in the United States. Aust. For. 71, 212–215 (2008).Article 

    Google Scholar 
    Bright, B. C. et al. Using satellite imagery to evaluate bark beetle-caused tree mortality reported in aerial surveys in a mixed conifer forest in Northern Idaho, USA. Forests 11, 1–19 (2020).Article 

    Google Scholar 
    Coleman, T. W. et al. Accuracy of aerial detection surveys for mapping insect and disease disturbances in the United States. For. Ecol. Manag. 430, 321–336 (2018).Article 

    Google Scholar 
    Hicke, J. A., Xu, B., Meddens, A. J. H. & Egan, J. M. Characterizing recent bark beetle-caused tree mortality in the western United States from aerial surveys. For. Ecol. Manag. 475, 118402 (2020).Article 

    Google Scholar 
    Kosiba, A. M. et al. Spatiotemporal patterns of forest damage and disturbance in the northeastern United States: 2000–2016. For. Ecol. Manag. 430, 94–104 (2018).Article 

    Google Scholar 
    Meigs, G. W., Kennedy, R. E., Gray, A. N. & Gregory, M. J. Spatiotemporal dynamics of recent mountain pine beetle and western spruce budworm outbreaks across the Pacific Northwest Region USA. For. Ecol. Manag. 339, 71–86 (2015).Article 

    Google Scholar 
    Bechtold, W. A. & Patterson, P. L. The Enhanced Forest Inventory and Analysis Program—National Sampling Design and Estimation Procedures. Gen. Tech. Rep. SRS-80 (US Department of Agriculture, Forest Service, Southern Research Station, 2005). https://doi.org/10.2737/SRS-GTR-80.Book 

    Google Scholar 
    Randolph, K. D. C. et al. Past and present individual-tree damage assessments of the US national forest inventory. Environ. Monit. Assess. 193, 116 (2021).Article 
    PubMed 

    Google Scholar 
    Kromroy, K. W., Juzwik, J., Castillo, P. & Hansen, M. H. Using forest service forest inventory and analysis data to estimate regional oak decline and oak mortality. North. J. Appl. For. 25, 17–24 (2008).Article 

    Google Scholar 
    Coulston, J. W., Edgar, C. B., Westfall, J. A. & Taylor, M. E. Estimation of forest disturbance from retrospective observations in a broad-scale inventory. Forests 11, 1298 (2020).Article 

    Google Scholar 
    Wilson, B. T., Lister, A. J. & Riemann, R. I. A nearest-neighbor imputation approach to mapping tree species over large areas using forest inventory plots and moderate resolution raster data. For. Ecol. Manag. 271, 182–198 (2012).Article 

    Google Scholar 
    Blackard, J. A. et al. Mapping U.S. forest biomass using nationwide forest inventory data and moderate resolution information. Remote Sens. Environ. 112, 1658–1677 (2008).Article 
    ADS 

    Google Scholar 
    Brosofske, K. D., Froese, R. E., Falkowski, M. J. & Banskota, A. A review of methods for mapping and prediction of inventory attributes for operational forest management. For. Sci. 60, 733–756 (2014).Article 

    Google Scholar 
    Lister, A. J. et al. Use of remote sensing data to improve the efficiency of national forest inventories: A case study from the United States national forest inventory. Forests 11, 1–41 (2020).Article 

    Google Scholar 
    USDA Forest Service Forest Health Protection. Individual Tree Species Parameter (ITSP) maps – GIS data downloads. https://www.fs.usda.gov/foresthealth/applied-sciences/mapping-reporting/indiv-tree-parameter-maps.shtml (2021). Accessed on 9 October 2021.Ellenwood, J. R., Krist, F. J. & Romero, S. A. National Individual Tree Species Atlas. FHTET-15-01 (US Department of Agriculture, Forest Service, Forest Health Technology Enterprise Team, 2015).
    Google Scholar 
    Krist, F. J. et al. National Insect and Disease Forest Risk Assessment. FHTET-14-01 (US Department of Agriculture, Forest Service, Forest Health Technology Enterprise Team, 2014).
    Google Scholar 
    Rulequest Inc. Cubist, release 2.07. https://www.rulequest.com/cubist-info.html (2011). Accessed on 15 July 2022.R Core Team. R: A language and environment for statistical computing. https://www.r-project.org (2021). Accessed on 4 March 2022.Esri Inc. ArcGIS Pro 2.8.0. https://www.esri.com/en-us/arcgis/products/arcgis-pro/overview (2021). Accessed on 4 March 2022. More

  • in

    Direct competition and potential displacement involving managed Trogoderma stored product pests

    Finkelman, S., Navarro, S., Rindner, M. & Dias, R. Effect of low pressure on the survival of Trogoderma granarium Everts, Lasioderma serricorne (F.) and Oryzaephilus surinamensis (L.) at 30°C. J. Stored. Prod. Res. 42, 23–30 (2006).Article 

    Google Scholar 
    Hosseininaveh, V. A., Bandani, A. P., Azmayeshfard, P. S., Hosseinkhani, S. & Kazzazi, M. Digestive proteolytic and amylolytic activities in Trogoderma granarium Everts (Dermestidae: Coleoptera). J. Stored. Prod. Res. 43, 515–522 (2007).Article 
    CAS 

    Google Scholar 
    Burges, H. D. Development of the khapra beetle, Trogoderma granarium, in the lower part of its temperature range. J. Stored. Prod. Res. 44, 32–35 (2008).Article 

    Google Scholar 
    Hagstrum D. W & Subramanyam, B. Stored-Product Insect Resource (AACC International, 2009).Beal, R. S. Synopsis of the economic species of Trogoderma occurring in the United States with description of a new species (Coleoptera: Dermestidae). Ann. Entomol. Soc. Am. 49, 559–566 (1956).Article 

    Google Scholar 
    Kerr, J. A. Khapra beetle returns. Pest Control 49(12), 24–25 (1984).
    Google Scholar 
    Sinha, R. N. & Utida, S. Climatic areas potentially vulnerable to stored product insects in Japan. Appl. Entomol. Zool. 2, 124–132 (1967).Article 

    Google Scholar 
    Banks, H. J. Distribution and establishment of Trogoderma granarium Everts (Coleoptera: Dermestidae): Climatic and other influences. J. Stored. Prod. Res. 13, 183–202 (1977).Article 

    Google Scholar 
    Kavallieratos, N. G., Athanassiou, C. G., Guedes, R. N. C., Drempela, J. D. & Boukouvala, M. C. Invader competition with local competitors: Displacement or coexistence among the invasive khapra beetle, Trogoderma granarium Everts (Coleoptera: Dermestidae), and two other major stored-grain beetles?. Front. Plant. Sci. 8, 1837 (2017).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Lampiri, E., Baliota, G. V., Morrison, W. M., Domingue, M. J. & Athanassiou, C. Comparative population growth of the khapra beetle (Coleoptera: Dermestidae) and the warehouse beetle (Coleoptera: Dermestidae) on wheat and rice. J. Econ. Entomol. 115, 344–352 (2021).Article 

    Google Scholar 
    Athanassiou, C. G., Phillips, T. W. & Wakil, W. Biology and control of the khapra beetle, Trogoderma granarium, a major quarantine threat to global food security. Ann. Rev. Entomol. 64, 131–148 (2019).Article 
    CAS 

    Google Scholar 
    Stibick, J. New pest response guidelines: khapra beetle. APHIS– PPQ–Emergency and Domestic Programs. (U.S Department of Agriculture, 2009).Myers, S. W. & Hagstrum, D. W. Quarantine, In Stored stored product protection, (ed. Hagstrum D.W. Phillips T.W. & Cuperus G.) 297–304 (Kansas State University, 2012).Day, C. & White, B. Khapra beetle, Trogoderma granarium interceptions and eradications in Australia and around the world. In SARE working papers 1609. (Crawley: School of Agricul. Res. Econ. 2016).Burges, H. D. Diapause, pest status and control of the Khapra beetle. Trogoderma Granar. Everts Ann. Appl. Biol. 50, 614–617 (1962).Article 

    Google Scholar 
    Nair, K. & Desai, A. The termination of diapause in Trogoderma granarium Everts (Coleoptera, Dermestidae). J. Stored. Prod. Res. 8, 275–290 (1973).Article 

    Google Scholar 
    Burges, H. D. Studies on the Dermestid beetle Trogoderma granarium Everts—IV. Feeding, growth, and respiration with particular reference to diapause larvae. J. Insect. Physiol. 5, 317–334 (1960).Article 
    CAS 

    Google Scholar 
    Wilches, D., Laird, R. A., Floate, K. & Fields, P. G. A review of diapause and tolerance to extreme temperatures in dermestids (Coleoptera). J. Stored Prod. Res. 68, 50–62 (2016).Article 

    Google Scholar 
    Vick, K. W., Drummond, P. C. & Coffelt, J. A. Trogoderma inclusum and T. glabrum: Effects of time of day on production of female pheromone, male responsiveness and mating. Ann. Entomol. Soc. Am. 66, 1001–1004 (1973).Article 

    Google Scholar 
    Partida, G. J. & Strong, R. G. Distribution and relative abundance of Trogoderma spp. in relation to climate zones of California. J. Econ. Entomol. 63, 1553–1560 (1970).Article 

    Google Scholar 
    Hagstrum, D. W. Seasonal variation of stored wheat environment and insect populations. J. Econ. Entomol. 16, 77–83 (1987).
    Google Scholar 
    Mullen, M. A. & Arbogast, R. T. Insect succession in a stored-corn ecosystem in southeast Georgia. J. Econ. Entomol. 81, 899–912 (1988).
    Google Scholar 
    Partida, G. J. & Strong, R. G. Comparative studies on the biologies of six species of Trogoderma: T. inclusum. Ann. Entomol. Soc. Am. 68, 91–103 (1975).Article 

    Google Scholar 
    Beal, R. S. Biology and taxonomy of the nearctic species of Trogoderma. Univ. Calif. Misc. Publ. Entomol. 10, 35–102 (1954).
    Google Scholar 
    Castañé, C., Agustí, N., del Estal, P. & Riudavets, J. Survey of Trogoderma spp in Spanish mills and warehouses. J. Stored. Prod. Res. 88, 1061 (2020).Article 

    Google Scholar 
    Levinson, H. Z. & Mori, K. The pheromone activity of chiral isomers of trogodermal for male khapra beetles. Naturwissenschaften 67, 148–149 (1980).Article 
    CAS 

    Google Scholar 
    Silverstein, R. M. et al. Perception by Trogoderma species of chirality and methyl branching at a site far removed from a functional group in a pheromone component. J. Chem. Ecol. 6, 911–917 (1980).Article 
    CAS 

    Google Scholar 
    Vick, K. W. Effects of interspecific matings of Trogoderma glabrum and T. inclusum on oviposition and re-mating. Ann. Entomol. Soc. Am. 66, 237–239 (1973).Article 
    MathSciNet 

    Google Scholar 
    Drijfhout, S. et al. Catalogue of abrupt shifts in intergovernmental panel on climate change climate models. Proc. Natl. Acad. Sci. USA 112, E5777–E5786 (2015).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Phillips, T. W., Pfannenstiel, L. & Hagstrum, D. Survey of Trogoderma species (Coleoptera: Dermestidae) associated with international trade of dried distiller’s grains and solubles in the USA. Julius-Kühn-Archiv 1, 233–238 (2018).
    Google Scholar 
    Hadaway, A. The biology of the beetles, Trogoderma granarium Everts and Trogoderma versicolor (Creutz). Bull. Entomol. Res. 46, 781–796 (1956).Article 
    CAS 

    Google Scholar 
    Gorham, J. R. Insect and Mite Pests in Food: An Illustrated Key. Vols. 1 and 2, (U.S Department of Agriculture, 1991).Furui, S., Miyanoshita, A., Imamura, T., Minegishi, Y. & Kokutani, R. Qualitative real-time PCR identification of the khapra beetle, Trogoderma granarium (Coleoptera: Dermestidae). Appl. Entomol. Zool. 54, 101–107 (2019).Article 
    CAS 

    Google Scholar 
    Olson, R. L., Farris, R. E., Barr, N. B. & Cognato, A. I. Molecular identification of Trogoderma granarium (Coleoptera: Dermestidae) using the 16s gene. J Pest Sci 87, 701–710 (2014).Article 

    Google Scholar 
    Wu, Y. et al. Development of an array of molecular tools for the identification of khapra beetle (Trogoderma granarium), a destructive beetle of stored food products. Sci. Rep. 13, 3327 (2023).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Lampiri, E., Athanassiou, C. & Arthur, F. H. Population growth and development of the khapra beetle (Coleoptera: Dermestidae), on different sorghum fractions. J. Econ. Entomol. 114, 424–429 (2021).Article 
    CAS 
    PubMed 

    Google Scholar 
    Athanassiou, C. G., Kavallieratos, N. G. & Boukouvala, M. C. Population growth of the khapra beetle, Trogoderma granarium Everts (Coleoptera: Dermestidae) on different commodities. J. Stored. Prod. Res. 69, 72–77 (2016).Article 

    Google Scholar 
    Karnavar, G. K. Mating behaviour and fecundity in Trogoderma granarium (Coleoptera: Dermestidae). J. Stored. Prod. Res. 8, 65–69 (1972).Article 

    Google Scholar 
    Pray, L. A. & Goodnight, C. J. Genetic variation in inbreeding depression in the red flour beetle Tribolium castaneum. Evolution 49, 176–188 (1995).Article 
    PubMed 

    Google Scholar 
    Barzin, S., Naseri, B., Fathi, S. A. A., Razmjou, J. & Aeinehchi, P. Feeding efficiency and digestive physiology of Trogoderma granarium Everts (Coleoptera: Dermestidae) on different rice cultivars. J. Stored. Prod. Res. 84, 101511 (2019).Article 

    Google Scholar 
    Naseri, B., Aeinehchi, P. & Ashjerdi, A. R. Nutritional responses and digestive enzymatic profile of Trogoderma granarium Everts (Coleoptera: Dermestidae) on 10 commercial rice cultivars. J. Stored. Prod. Res. 87, 101591 (2020).Article 

    Google Scholar 
    Sarwar, M. & Sattar, M. Varietals assessment of different wheat varieties for their resistance response to Khapra beetle Trogoderma granarium. Pak. J. Seed. Technol. 1(10), 1–7 (2007).
    Google Scholar 
    Wilches, D., Laird, R., Floate, K. & Fields, P. Effects of acclimation and diapause on the cold tolerance of Trogoderma granarium. Entomol. Exp. Appl. 165, 169–178 (2017).Article 
    CAS 

    Google Scholar 
    Paini, D. R. & Yemshanov, D. Modelling the arrival of invasive organisms via the international marine shipping network: a Khapra beetle study. PLoS ONE 7(9), e44589 (2012).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Morrison, W. R., Grosdidier, R. F., Arthur, F. H., Myers, S. W. & Domingue, M. J. Attraction, arrestment, and preference by immature Trogoderma variabile and Trogoderma granarium to food and pheromonal stimuli. J. Pest Sci. 93, 135–147 (2020).Article 

    Google Scholar 
    Arthur, F. H. & Morrison, W. M. Methodology for assessing progeny production and grain damage on commodities treated with insecticides. Agronomy 10(6), 804 (2020).Article 
    CAS 

    Google Scholar  More

  • in

    Local environment drives rapid shifts in composition and phylogenetic clustering of seagrass microbiomes

    McFall-Ngai, M. et al. Animals in a bacterial world, a new imperative for the life sciences. Proc. Natl. Acad. Sci. U.S.A. 110, 3229–3236 (2013).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Hammer, T. J., Sanders, J. G. & Fierer, N. Not all animals need a microbiome. FEMS Microbiol. Lett. 366, fnz117 (2019).Article 
    CAS 
    PubMed 

    Google Scholar 
    Griffiths, S. M. et al. Host genetics and geography influence microbiome composition in the sponge Ircinia campana. J. Anim. Ecol. 88, 1684–1695 (2019).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Coleman-Derr, D. et al. Plant compartment and biogeography affect microbiome composition in cultivated and native Agave species. New Phytol. 209, 798–811 (2016).Article 
    CAS 
    PubMed 

    Google Scholar 
    Marzinelli, E. M. et al. Continental-scale variation in seaweed host-associated bacterial communities is a function of host condition, not geography. Environ. Microbiol. 17, 4078–4088 (2015).Article 
    PubMed 

    Google Scholar 
    Wang, L., English, M. K., Tomas, F. & Mueller, R. S. Recovery and community succession of the Zostera marina Rhizobiome after transplantation. bioRxiv https://doi.org/10.1101/2020.04.20.052357 (2020).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Copeland, J. K., Yuan, L., Layeghifard, M., Wang, P. W. & Guttman, D. S. Seasonal community succession of the phyllosphere microbiome. Mol. Plant. Microbe. Interact. 28, 274–285 (2015).Article 
    CAS 
    PubMed 

    Google Scholar 
    Shi, S. et al. Successional trajectories of rhizosphere bacterial communities over consecutive seasons. MBio 6, e00746 (2015).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Shade, A., McManus, P. S. & Handelsman, J. Unexpected diversity during community succession in the apple flower microbiome. MBio 4, e00602 (2013).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Avena, C. V. et al. Deconstructing the bat skin microbiome: Influences of the host and the environment. Front. Microbiol. 7, 1753 (2016).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Rothschild, D. et al. Environment dominates over host genetics in shaping human gut microbiota. Nature 555, 210–215 (2018).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Glasl, B., Smith, C. E., Bourne, D. G. & Webster, N. S. Disentangling the effect of host-genotype and environment on the microbiome of the coral Acropora tenuis. PeerJ 7, e6377 (2019).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Weigel, B. L. & Erwin, P. M. Effects of reciprocal transplantation on the microbiome and putative nitrogen cycling functions of the intertidal sponge, Hymeniacidon heliophila. Sci. Rep. 7, 43247 (2017).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Fuhrman, J. A., Cram, J. A. & Needham, D. M. Marine microbial community dynamics and their ecological interpretation. Nat. Rev. Microbiol. 13, 133–146 (2015).Article 
    CAS 
    PubMed 

    Google Scholar 
    Ziegler, M. et al. Coral bacterial community structure responds to environmental change in a host-specific manner. Nat. Commun. 10, 3092 (2019).Article 
    ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Wagner, M. R. et al. Host genotype and age shape the leaf and root microbiomes of a wild perennial plant. Nat. Commun. 7, 12151 (2016).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Kraft, N. J. B. et al. Community assembly, coexistence and the environmental filtering metaphor. Funct. Ecol. 29, 592–599 (2015).Article 

    Google Scholar 
    Weiher, E. & Keddy, P. A. The assembly of experimental wetland plant communities. Oikos 73, 323–335 (1995).Article 

    Google Scholar 
    Cavender-Bares, J., Kitajima, K. & Bazzaz, F. A. Multiple trait associations in relation to habitat differentiation among 17 Floridian oak species. Ecol. Monogr. 74, 635–662 (2004).Article 

    Google Scholar 
    Cavender-Bares, J., Ackerly, D. D., Baum, D. A. & Bazzaz, F. A. Phylogenetic overdispersion in Floridian oak communities. Am. Nat. 163, 823–843 (2004).Article 
    CAS 
    PubMed 

    Google Scholar 
    Webb, C. O. Exploring the Phylogenetic structure of ecological communities: An example for rain forest trees. Am. Nat. 156, 145–155 (2000).Article 
    PubMed 

    Google Scholar 
    Webb, C. O., Ackerly, D. D., McPeek, M. A. & Donoghue, M. J. Phylogenies and community ecology. Annu. Rev. Ecol. Syst. 33, 475–505 (2002).Article 

    Google Scholar 
    Kembel, S. W. et al. Relationships between phyllosphere bacterial communities and plant functional traits in a neotropical forest. Proc. Natl. Acad. Sci. U.S.A. 111, 13715–13720 (2014).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Burke, C., Steinberg, P., Rusch, D., Kjelleberg, S. & Thomas, T. Bacterial community assembly based on functional genes rather than species. Proc. Natl. Acad. Sci. U.S.A. 108, 14288–14293 (2011).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Martiny, J. B. H., Jones, S. E., Lennon, J. T. & Martiny, A. C. Microbiomes in light of traits: A phylogenetic perspective. Science https://doi.org/10.1126/science.aac9323 (2015).Article 
    PubMed 

    Google Scholar 
    Goberna, M. & Verdú, M. Predicting microbial traits with phylogenies. ISME J. 10, 959–967 (2016).Article 
    PubMed 

    Google Scholar 
    Duarte, C. M. The future of seagrass meadows. Environ. Conserv. 29, 192–206 (2002).Article 

    Google Scholar 
    Fonseca, M. S., Fisher, J. S., Zieman, J. C. & Thayer, G. W. Influence of the seagrass, Zostera marina L., on current flow. Estuar. Coast. Shelf Sci. 15, 351–364 (1982).Article 
    ADS 

    Google Scholar 
    Fonseca, M. S., Kenworthy, W. J. & Thayer, G. W. A low cost transplanting procedure for sediment stabilization and habitat development using eelgrass (Zostera marina). Wetlands 2, 138–151 (1982).Article 

    Google Scholar 
    Moore, K. A. & Short, F. T. Zostera: Biology, ecology, and management. In Seagrasses: Biology, ecology and conservation (eds Larkum, A. W. D. et al.) 361–386 (Springer, 2006).
    Google Scholar 
    Fahimipour, A. K. et al. Global-scale structure of the eelgrass microbiome. Appl. Environ. Microbiol. 83, e03391-16 (2017).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Bengtsson, M. M. et al. Eelgrass leaf surface microbiomes are locally variable and highly correlated with epibiotic eukaryotes. Front. Microbiol. 8, 1312 (2017).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Cúcio, C., Engelen, A. H., Costa, R. & Muyzer, G. Rhizosphere microbiomes of European + seagrasses are selected by the plant, but are not species specific. Front. Microbiol. 7, 440 (2016).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Schenck, F. R., DuBois, K., Kardish, M. R., Stachowicz, J. J. & Hughes, A. R. The effect of warming on seagrass wasting disease depends on host genotypic identity and diversity. Ecology e3959 (2022).Beatty, D. S. et al. Predictable changes in eelgrass microbiomes with increasing wasting disease prevalence across 23° latitude in the Northeastern Pacific. mSystems 7, e0022422 (2022).Article 
    PubMed 

    Google Scholar 
    Hughes, A. R., Stachowicz, J. J. & Williams, S. L. Morphological and physiological variation among seagrass (Zostera marina) genotypes. Oecologia 159, 725–733 (2009).Article 
    ADS 
    PubMed 

    Google Scholar 
    Randall Hughes, A. & Stachowicz, J. J. Seagrass genotypic diversity increases disturbance response via complementarity and dominance. J. Ecol. 99, 445–453 (2010).
    Google Scholar 
    Kamel, S. J., Hughes, A. R., Grosberg, R. K. & Stachowicz, J. J. Fine-scale genetic structure and relatedness in the eelgrass Zostera marina. Mar. Ecol. Prog. Ser. 447, 127–137 (2012).Article 
    ADS 

    Google Scholar 
    Abbott, J. M., DuBois, K., Grosberg, R. K., Williams, S. L. & Stachowicz, J. J. Genetic distance predicts trait differentiation at the subpopulation but not the individual level in eelgrass Zostera marina. Ecol. Evol. 8, 7476–7489 (2018).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Sand-Jensen, K. Biomass, net production and growth dynamics in an eelgrass (Zostera marina L.) population in Vellerup Vig, Denmark. Ophelia 14, 185–201 (1975).Article 

    Google Scholar 
    Vacher, C. et al. The phyllosphere: Microbial jungle at the plant-climate interface. Annu. Rev. Ecol. Evol. Syst. 47, 1–24 (2016).Article 

    Google Scholar 
    Miazaki, A. S., Gastauer, M. & Meira-Neto, J. A. A. Environmental severity promotes phylogenetic clustering in campo rupestre vegetation. Acta Bot. Brasilica 29, 561–566 (2015).Article 

    Google Scholar 
    DuBois, K., Williams, S. L. & Stachowicz, J. J. Previous exposure mediates the response of eelgrass to future warming via clonal transgenerational plasticity. Ecology 101, e03169 (2020).Article 
    PubMed 

    Google Scholar 
    Rüger, L. et al. Assembly patterns of the rhizosphere microbiome along the longitudinal root axis of maize (Zea mays L.). Front. Microbiol. 12, 614501 (2021).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Fitzpatrick, C. R. et al. Assembly and ecological function of the root microbiome across angiosperm plant species. Proc. Natl. Acad. Sci. U.S.A. 115, E1157–E1165 (2018).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Fitzgerald, D. B., Winemiller, K. O., Sabaj Pérez, M. H. & Sousa, L. M. Seasonal changes in the assembly mechanisms structuring tropical fish communities. Ecology 98, 21–31 (2017).Article 
    PubMed 

    Google Scholar 
    Campbell, A. H., Marzinelli, E. M., Gelber, J. & Steinberg, P. D. Spatial variability of microbial assemblages associated with a dominant habitat-forming seaweed. Front. Microbiol. 6, 230 (2015).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Eriander, L., Infantes, E., Olofsson, M., Olsen, J. L. & Moksnes, P.-O. Assessing methods for restoration of eelgrass (Zostera marina L.) in a cold temperate region. J. Exp. Mar. Bio. Ecol. 479, 76–88 (2016).Article 

    Google Scholar 
    Zhou, Y. et al. Restoring eelgrass (Zostera marina L.) habitats using a simple and effective transplanting technique. PLoS ONE 9, e92982 (2014).Article 
    ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Galushko, A. & Kuever, J. Desulfocapsaceae. Bergey’s Manual of Systematics of Archaea and Bacteria 1–6 Preprint at https://doi.org/10.1002/9781118960608.fbm00332 (2021).Waite, D. W. et al. Proposal to reclassify the proteobacterial classes Deltaproteobacteria and Oligoflexia, and the phylum Thermodesulfobacteria into four phyla reflecting major functional capabilities. Int. J. Syst. Evol. Microbiol. 70, 5972–6016 (2020).Article 
    CAS 
    PubMed 

    Google Scholar 
    Knoblauch, C., Sahm, K. & Jørgensen, B. B. Psychrophilic sulfate-reducing bacteria isolated from permanently cold arctic marine sediments: description of Desulfofrigus oceanense gen. nov., sp. nov., Desulfofrigus fragile sp. nov., Desulfofaba gelida gen. nov., sp. nov., Desulfotalea psychrophila gen. nov., sp. nov. and Desulfotalea arctica sp. nov.. Int. J. Syst. Bacteriol. 49 Pt 4, 1631–1643 (1999).Article 
    CAS 
    PubMed 

    Google Scholar 
    Isaksen, M. F. & Teske, A. Desulforhopalus vacuolatus gen. nov., sp. nov., a new moderately psychrophilic sulfate-reducing bacterium with gas vacuoles isolated from a temperate estuary. Arch. Microbiol. 166, 160–168 (1996).Article 
    CAS 

    Google Scholar 
    Song, J., Hwang, J., Kang, I. & Cho, J.-C. A sulfate-reducing bacterial genus, Desulfosediminicola gen. nov., comprising two novel species cultivated from tidal-flat sediments. Sci. Rep. 11, 19978 (2021).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Trevelline, B. K., Fontaine, S. S., Hartup, B. K. & Kohl, K. D. Conservation biology needs a microbial renaissance: a call for the consideration of host-associated microbiota in wildlife management practices. Proc. Biol. Sci. 286, 20182448 (2019).PubMed 
    PubMed Central 

    Google Scholar 
    Christian, N., Whitaker, B. K. & Clay, K. Microbiomes: Unifying animal and plant systems through the lens of community ecology theory. Front. Microbiol. 6, 869 (2015).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Zieman, J. C. Productivity in seagrasses: Methods and rates. In Handbook of Seagrass Biology: An ecosystem perspective (eds Phillips, R. C. & McRoy, C. P.) 87–116 (Garland STPM Press, 1980).
    Google Scholar 
    Dennison, W. C. Leaf production. Seagrass research methods, UNESCO, Paris 77–79 (1990).Walters, W. et al. Improved bacterial 16S rRNA gene (V4 and V4–5) and fungal internal transcribed spacer marker gene primers for microbial community surveys. mSystems 1, e00009-15 (2016).Article 
    PubMed 

    Google Scholar 
    Comeau, A. M., Douglas, G. M. & Langille, M. G. I. Microbiome Helper: A custom and streamlined workflow for microbiome research. mSystems 2, e00127-16 (2017).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Callahan, B. J. et al. DADA2: High-resolution sample inference from Illumina amplicon data. Nat. Methods 13, 581–583 (2016).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Quast, C. et al. The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools. Nucleic Acids Res. 41, D590–D596 (2013).Article 
    CAS 
    PubMed 

    Google Scholar 
    Wright, E. S. DECIPHER: Harnessing local sequence context to improve protein multiple sequence alignment. BMC Bioinform. 16, 322 (2015).Article 

    Google Scholar 
    Price, M. N., Dehal, P. S. & Arkin, A. P. FastTree 2-approximately maximum-likelihood trees for large alignments. PLoS ONE 5, e9490 (2010).Article 
    ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Britton, T., Anderson, C. L., Jacquet, D., Lundqvist, S. & Bremer, K. Estimating divergence times in large phylogenetic trees. Syst. Biol. 56, 741–752 (2007).Article 
    PubMed 

    Google Scholar 
    McMurdie, P. J. & Holmes, S. phyloseq: An R package for reproducible interactive analysis and graphics of microbiome census data. PLoS ONE 8, e61217 (2013).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Paradis, E. & Schliep, K. ape 50: An environment for modern phylogenetics and evolutionary analyses in R. Bioinformatics 35, 526–528 (2019).Article 
    CAS 
    PubMed 

    Google Scholar 
    Silverman, J. D., Washburne, A. D., Mukherjee, S. & David, L. A. A phylogenetic transform enhances analysis of compositional microbiota data. Elife 6, 1–20 (2017).Article 

    Google Scholar 
    McMurdie, P. J. & Holmes, S. Waste not, want not: Why rarefying microbiome data is inadmissible. PLoS Comput. Biol. 10, e1003531 (2014).Article 
    ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Webb, C. O., Ackerly, D. D. & Kembel, S. W. Phylocom: Software for the analysis of phylogenetic community structure and trait evolution. Bioinformatics 24, 2098–2100 (2008).Article 
    CAS 
    PubMed 

    Google Scholar 
    Russel, J. Russel88/MicEco: v0.9.15. (2021). 10.5281/zenodo.4733747.Kembel, S. W. et al. Picante: R tools for integrating phylogenies and ecology. Bioinformatics 26, 1463–1464 (2010).Article 
    CAS 
    PubMed 

    Google Scholar 
    Friedman, J., Hastie, T. & Tibshirani, R. Regularization paths for generalized linear models via coordinate descent. J. Stat. Softw. 33, 1–22 (2010).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Kahle, D. & Wickham, H. Ggmap: Spatial visualization with ggplot2. R J. 5, 144 (2013).Article 

    Google Scholar  More