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Relevant bibliographies by topics / Biogeochemical cycles

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Academic literature on the topic 'Biogeochemical cycles'

Author: Grafiati

Published: 4 June 2021

Last updated: 29 July 2024

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Journal articles on the topic "Biogeochemical cycles"

1

Akaiwa, Hideo. "Biogeochemical Cycles." TRENDS IN THE SCIENCES 3, no. 4 (1998): 58–59. http://dx.doi.org/10.5363/tits.3.4_58.

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WALKER, J. C. G. "Biogeochemical Cycles." Science 253, no. 5020 (August 9, 1991): 686–87. http://dx.doi.org/10.1126/science.253.5020.686-a.

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Wackett, Lawrence P. "Global biogeochemical cycles." Environmental Microbiology 18, no. 3 (March 2016): 1088–89. http://dx.doi.org/10.1111/1462-2920.13280.

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Rastetter, Edward B. "Modeling coupled biogeochemical cycles." Frontiers in Ecology and the Environment 9, no. 1 (February 2011): 68–73. http://dx.doi.org/10.1890/090223.

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Offre, Pierre, Anja Spang, and Christa Schleper. "Archaea in Biogeochemical Cycles." Annual Review of Microbiology 67, no. 1 (September 8, 2013): 437–57. http://dx.doi.org/10.1146/annurev-micro-092412-155614.

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Van Cappellen, P. "Biomineralization and Global Biogeochemical Cycles." Reviews in Mineralogy and Geochemistry 54, no. 1 (January 1, 2003): 357–81. http://dx.doi.org/10.2113/0540357.

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Schlesinger, William H., Jonathan J. Cole, Adrien C. Finzi, and Elisabeth A. Holland. "Introduction to coupled biogeochemical cycles." Frontiers in Ecology and the Environment 9, no. 1 (February 2011): 5–8. http://dx.doi.org/10.1890/090235.

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TREVORS, J. T., P. KUIKMAN, and B. WATSON. "Transgenic plants and biogeochemical cycles." Molecular Ecology 3, no. 1 (April 14, 2008): 57–64. http://dx.doi.org/10.1111/j.1365-294x.1994.tb00045.x.

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Bush, T., I. B. Butler, A. Free, and R. J. Allen. "Redox regime shifts in microbially-mediated biogeochemical cycles." Biogeosciences Discussions 12, no. 4 (February 17, 2015): 3283–314. http://dx.doi.org/10.5194/bgd-12-3283-2015.

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Abstract. Understanding how the Earth's biogeochemical cycles respond to environmental change is a prerequisite for the prediction and mitigation of the effects of anthropogenic perturbations. Microbial populations mediate key steps in these cycles, yet are often crudely represented in biogeochemical models. Here, we show that microbial population dynamics can qualitatively affect the response of biogeochemical cycles to environmental change. Using simple and generic mathematical models, we find that nutrient limitations on microbial population growth can lead to regime shifts, in which the redox state of a biogeochemical cycle changes dramatically as the availability of a redox-controlling species, such as oxygen or acetate, crosses a threshold (a "tipping point"). These redox regime shifts occur in parameter ranges that are relevant to the sulfur and nitrogen cycles in the present-day natural environment, and may also have relevance to iron cycling in the iron-containing Proterozoic and Archean oceans. We show that redox regime shifts also occur in models with physically realistic modifications, such as additional terms, chemical states, or microbial populations. Our work reveals a possible new mechanism by which regime shifts can occur in nutrient-cycling ecosystems and biogeochemical cycles, and highlights the importance of considering microbial population dynamics in models of biogeochemical cycles.

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Bush, T., I. B. Butler, A. Free, and R. J. Allen. "Redox regime shifts in microbially mediated biogeochemical cycles." Biogeosciences 12, no. 12 (June 17, 2015): 3713–24. http://dx.doi.org/10.5194/bg-12-3713-2015.

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Abstract. Understanding how the Earth's biogeochemical cycles respond to environmental change is a prerequisite for the prediction and mitigation of the effects of anthropogenic perturbations. Microbial populations mediate key steps in these cycles, yet they are often crudely represented in biogeochemical models. Here, we show that microbial population dynamics can qualitatively affect the response of biogeochemical cycles to environmental change. Using simple and generic mathematical models, we find that nutrient limitations on microbial population growth can lead to regime shifts, in which the redox state of a biogeochemical cycle changes dramatically as the availability of a redox-controlling species, such as oxygen or acetate, crosses a threshold (a "tipping point"). These redox regime shifts occur in parameter ranges that are relevant to the present-day sulfur cycle in the natural environment and the present-day nitrogen cycle in eutrophic terrestrial environments. These shifts may also have relevance to iron cycling in the iron-containing Proterozoic and Archean oceans. We show that redox regime shifts also occur in models with physically realistic modifications, such as additional terms, chemical states, or microbial populations. Our work reveals a possible new mechanism by which regime shifts can occur in nutrient-cycling ecosystems and biogeochemical cycles, and highlights the importance of considering microbial population dynamics in models of biogeochemical cycles.

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Dissertations / Theses on the topic "Biogeochemical cycles"

1

Brunner, Benjamin. "The sulfur cycle: from bacterial microenvironment to global biogeochemical cycles /." Zürich : [s.n.], 2003. http://e-collection.ethbib.ethz.ch/show?type=diss&nr=15197.

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Formolo, Michael J. "The biogeochemical cycling of sulfur in two distinct redox regimes /." free to MU campus, to others for purchase, 2004. http://wwwlib.umi.com/cr/mo/fullcit?p3164506.

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Meixner, Thomas. "Alpine biogeochemical modeling case studies, improvements, and parameter estimation /." Diss., The University of Arizona, 1999. http://etd.library.arizona.edu/etd/GetFileServlet?file=file:///data1/pdf/etd/azu_e9791_1999_256_sip1_w.pdf&type=application/pdf.

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Bagnara, Maurizio. "Modelling biogeochemical cycles in forest ecosystems: a Bayesian approach." Doctoral thesis, country:IT, 2015. http://hdl.handle.net/10449/25094.

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Forest models are tools for explaining and predicting the dynamics of forest ecosystems. They simulate forest behavior by integrating information on the underlying processes in trees, soil and atmosphere. Bayesian calibration is the application of probability theory to parameter estimation. It is a method, applicable to all models, that quantifies output uncertainty and identifies key parameters and variables. This study aims at testing the Bayesian procedure for calibration to different types of forest models, to evaluate their performances and the uncertainties associated with them. In particular,we aimed at 1) applying a Bayesian framework to calibrate forest models and test their performances in different biomes and different environmental conditions, 2) identifying and solve structure-related issues in simple models, and 3) identifying the advantages of additional information made available when calibrating forest models with a Bayesian approach. We applied the Bayesian framework to calibrate the Prelued model on eight Italian eddy-covariance sites in Chapter 2. The ability of Prelued to reproduce the estimated Gross Primary Productivity (GPP) was tested over contrasting natural vegetation types that represented a wide range of climatic and environmental conditions. The issues related to Prelued's multiplicative structure were the main topic of Chapter 3: several different MCMC-based procedures were applied within a Bayesian framework to calibrate the model, and their performances were compared. A more complex model was applied in Chapter 4, focusing on the application of the physiology-based model HYDRALL to the forest ecosystem of Lavarone (IT) to evaluate the importance of additional information in the calibration procedure and their impact on model performances, model uncertainties, and parameter estimation. Overall, the Bayesian technique proved to be an excellent and versatile tool to successfully calibrate forest models of different structure and complexity, on different kind and number of variables and with a different number of parameters involved

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Bagnara, Maurizio <1985&gt. "Modelling biogeochemical cycles in forest ecosystems: a Bayesian approach." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2015. http://amsdottorato.unibo.it/7188/1/Bagnara_Maurizio_tesi.pdf.

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Forest models are tools for explaining and predicting the dynamics of forest ecosystems. They simulate forest behavior by integrating information on the underlying processes in trees, soil and atmosphere. Bayesian calibration is the application of probability theory to parameter estimation. It is a method, applicable to all models, that quantifies output uncertainty and identifies key parameters and variables. This study aims at testing the Bayesian procedure for calibration to different types of forest models, to evaluate their performances and the uncertainties associated with them. In particular,we aimed at 1) applying a Bayesian framework to calibrate forest models and test their performances in different biomes and different environmental conditions, 2) identifying and solve structure-related issues in simple models, and 3) identifying the advantages of additional information made available when calibrating forest models with a Bayesian approach. We applied the Bayesian framework to calibrate the Prelued model on eight Italian eddy-covariance sites in Chapter 2. The ability of Prelued to reproduce the estimated Gross Primary Productivity (GPP) was tested over contrasting natural vegetation types that represented a wide range of climatic and environmental conditions. The issues related to Prelued's multiplicative structure were the main topic of Chapter 3: several different MCMC-based procedures were applied within a Bayesian framework to calibrate the model, and their performances were compared. A more complex model was applied in Chapter 4, focusing on the application of the physiology-based model HYDRALL to the forest ecosystem of Lavarone (IT) to evaluate the importance of additional information in the calibration procedure and their impact on model performances, model uncertainties, and parameter estimation. Overall, the Bayesian technique proved to be an excellent and versatile tool to successfully calibrate forest models of different structure and complexity, on different kind and number of variables and with a different number of parameters involved.

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Bagnara, Maurizio <1985&gt. "Modelling biogeochemical cycles in forest ecosystems: a Bayesian approach." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2015. http://amsdottorato.unibo.it/7188/.

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Forest models are tools for explaining and predicting the dynamics of forest ecosystems. They simulate forest behavior by integrating information on the underlying processes in trees, soil and atmosphere. Bayesian calibration is the application of probability theory to parameter estimation. It is a method, applicable to all models, that quantifies output uncertainty and identifies key parameters and variables. This study aims at testing the Bayesian procedure for calibration to different types of forest models, to evaluate their performances and the uncertainties associated with them. In particular,we aimed at 1) applying a Bayesian framework to calibrate forest models and test their performances in different biomes and different environmental conditions, 2) identifying and solve structure-related issues in simple models, and 3) identifying the advantages of additional information made available when calibrating forest models with a Bayesian approach. We applied the Bayesian framework to calibrate the Prelued model on eight Italian eddy-covariance sites in Chapter 2. The ability of Prelued to reproduce the estimated Gross Primary Productivity (GPP) was tested over contrasting natural vegetation types that represented a wide range of climatic and environmental conditions. The issues related to Prelued's multiplicative structure were the main topic of Chapter 3: several different MCMC-based procedures were applied within a Bayesian framework to calibrate the model, and their performances were compared. A more complex model was applied in Chapter 4, focusing on the application of the physiology-based model HYDRALL to the forest ecosystem of Lavarone (IT) to evaluate the importance of additional information in the calibration procedure and their impact on model performances, model uncertainties, and parameter estimation. Overall, the Bayesian technique proved to be an excellent and versatile tool to successfully calibrate forest models of different structure and complexity, on different kind and number of variables and with a different number of parameters involved.

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Stamenkovic, Jelena. "The role of vegetation and soil in the biogeochemical cycling of mercury." abstract and full text PDF (free order & download UNR users only), 2008. http://0-gateway.proquest.com.innopac.library.unr.edu/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3339148.

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McKee, Conor Michael. "Biogeochemical cycles of ammonia and dimethylsulphide in the marine environment." Thesis, University of East Anglia, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.368388.

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Zhang, Rong 1971. "Self sustained thermohaline oscillations and their implications for biogeochemical cycles." Thesis, Massachusetts Institute of Technology, 2001. http://hdl.handle.net/1721.1/8232.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Earth, Atmospheric, and Planetary Sciences, 2001.
Includes bibliographical references (p. 150-156).
An ocean general circulation model (OGCM) configured with a paleo ocean bathymetry such as late Permian shows that different modes of ocean circulation might exist in warm climate: a strong 'thermal mode' induced by cooling at high latitudes and a weak 'haline mode' induced by evaporation at subtropics. The 'haline mode', obtained with enhanced freshwater flux and reduced vertical diffusivity, is inherently unstable, flushed by thermally-driven polar convection every few thousand years. A 3-box model of the thermohaline circulation is developed to study the basic physical mechanism of thermohaline oscillations. By including convective adjustment and a parameterization of the localized nature of convection, the box model shows that haline mode is unstable over a certain freshwater forcing/vertical diffusivity range.
(cont.) Self-sustained oscillatory thermohaline circulations, with periods ranging from centuries to several millennia, are supported. When the amplitude of surface freshwater flux exceeds a certain threshold the haline mode stabilizes. The relationship between oscillation periods and the freshwater flux/vertical diffusivity is also studied. Biogeochemical modeling of the late Permian ocean shows that the strong 'thermal mode' leads to well oxygenated deep ocean, the weak 'haline mode' leads to depletion of deep ocean oxygen. Biogeochemical cycles driven by the thermohaline oscillation found in the 3-box model shows that: the quasi-steady 'haline mode' is correlated with lower biological productivity, depleted deep ocean oxygen, heavier surface 613C due to weak vertical mixing, the transient 'thermal mode' is correlated with higher biological productivity, oxygenated deep ocean and lighter surface 613C due to strong vertical mixing. Those correlations are consistent with rhythmic paleo records. The 613C shift during mode switch is proportional to mean ocean nutrient level.
by Rong Zhang.
Ph.D.

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Singh, Shweta. "Incorporating Biogeochemical Cycles and Utilizing Complexity Theory for Sustainability Analysis." The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1345519020.

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Books on the topic "Biogeochemical cycles"

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Rachael, James, and Open University. Oceanography Course Team., eds. Marine biogeochemical cycles. 2nd ed. Oxford, UK: Elsevier Butterworth Heinemann, 2005.

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Gadd, Geoffrey Michael, ed. Fungi in Biogeochemical Cycles. Cambridge: Cambridge University Press, 2006. http://dx.doi.org/10.1017/cbo9780511550522.

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Astrid, Sigel, Sigel Helmut, and Sigel Roland K. O, eds. Biogeochemical cycles of elements. Boca Raton: Taylor&Francis, 2005.

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M, Gadd Geoffrey, and British Mycological Society, eds. Fungi in biogeochemical cycles. Cambridge: Cambridge University Press, 2006.

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Kasibhatla, Prasad, Martin Heimann, Peter Rayner, Natalie Mahowald, Ronald G. Prinn, and Dana E. Hartley, eds. Inverse Methods in Global Biogeochemical Cycles. Washington, D. C.: American Geophysical Union, 2000. http://dx.doi.org/10.1029/gm114.

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Dury, G. H., Reiner Eiden, James R. Holton, and L. Johnson. The Natural Environment and the Biogeochemical Cycles. Berlin, Heidelberg: Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/978-3-540-39463-1.

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Delmas, Robert J., ed. Ice Core Studies of Global Biogeochemical Cycles. Berlin, Heidelberg: Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/978-3-642-51172-1.

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Bowen, H. J. M., T. Frevert, W. D. Grant, G. Kratz, and P. E. Long. The Natural Environment and the Biogeochemical Cycles. Berlin, Heidelberg: Springer Berlin Heidelberg, 1985. http://dx.doi.org/10.1007/978-3-540-39209-5.

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Fyfe, W. S., Harald Puchelt, and Mieczyslaw Taube. The Natural Environment and the Biogeochemical Cycles. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-540-46995-7.

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1956-, Varotsos Costas, ed. Biogeochemical cycles in globalization and sustainable development. Berlin: Springer, 2008.

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Book chapters on the topic "Biogeochemical cycles"

1

Schneider, Bernd, Olaf Dellwig, Karol Kuliński, Anders Omstedt, Falk Pollehne, Gregor Rehder, and Oleg Savchuk. "Biogeochemical cycles." In Biological Oceanography of the Baltic Sea, 87–122. Dordrecht: Springer Netherlands, 2017. http://dx.doi.org/10.1007/978-94-007-0668-2_3.

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Fernández-Remolar, David C. "Biogeochemical Cycles." In Encyclopedia of Astrobiology, 172–77. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-11274-4_173.

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Bertrand, Jean-Claude, Patricia Bonin, Pierre Caumette, Jean-Pierre Gattuso, Gérald Grégori, Rémy Guyoneaud, Xavier Le Roux, Robert Matheron, and Franck Poly. "Biogeochemical Cycles." In Environmental Microbiology: Fundamentals and Applications, 511–617. Dordrecht: Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-017-9118-2_14.

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Fernández-Remolar, David C. "Biogeochemical Cycles." In Encyclopedia of Astrobiology, 279–84. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-44185-5_173.

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Sibi, G. "Biogeochemical Cycles." In Environmental Biotechnology, 5–33. Boca Raton: CRC Press, 2022. http://dx.doi.org/10.1201/9781003272618-2.

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Reitner, Joachim, and Volker Thiel. "Biogeochemical Cycles." In Encyclopedia of Geobiology, 137. Dordrecht: Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-1-4020-9212-1_28.

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Bache, Bryon W., and Ward Chesworth. "Biogeochemical Cycles." In Encyclopedia of Soil Science, 56–60. Dordrecht: Springer Netherlands, 2008. http://dx.doi.org/10.1007/978-1-4020-3995-9_61.

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Summons, Roger E. "Biogeochemical Cycles." In Topics in Geobiology, 3–21. Boston, MA: Springer US, 1993. http://dx.doi.org/10.1007/978-1-4615-2890-6_1.

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Fernandez-Remolar, David C. "Biogeochemical Cycles." In Encyclopedia of Astrobiology, 1–9. Berlin, Heidelberg: Springer Berlin Heidelberg, 2021. http://dx.doi.org/10.1007/978-3-642-27833-4_173-4.

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Fernández-Remolar, David C. "Biogeochemical Cycles." In Encyclopedia of Astrobiology, 1–6. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-27833-4_173-3.

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Conference papers on the topic "Biogeochemical cycles"

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Müller, Gerrit, Janine Börker, Appy Sluijs, and Jack Middelburg. "River particles in biogeochemical cycles." In Goldschmidt2022. France: European Association of Geochemistry, 2022. http://dx.doi.org/10.46427/gold2022.9778.

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Banfield, Jillian F., Alexander Thomas, Paula Matheus Carnevali, Adi Lavy, Jacob West-Roberts, Alexander Crits-Christoph, Kenneth Hurst-Williams, and Susan Hubbard. "Microbial Mediation of Watershed Biogeochemical Cycles." In Goldschmidt2020. Geochemical Society, 2020. http://dx.doi.org/10.46427/gold2020.124.

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CLEMENTE, J. B., H. A. ADORNA, and J. J. S. VILLAR. "WEAK BISIMULATION BETWEEN TWO BIOGEOCHEMICAL CYCLES." In Third Workshop on Computing: Theory and Practice, WCTP 2013. WORLD SCIENTIFIC, 2014. http://dx.doi.org/10.1142/9789814612883_0004.

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Connock, Gregory T., Jeremy D. Owens, and Xiaolei Liu. "BIOMARKERS AS A TOOL TO CONSTRAIN ANCIENT BIOGEOCHEMICAL CYCLES." In GSA 2020 Connects Online. Geological Society of America, 2020. http://dx.doi.org/10.1130/abs/2020am-352014.

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Cervantes, F. J. "Key roles of humic substances in global biogeochemical cycles." In Fifth International Conference of CIS IHSS on Humic Innovative Technologies «Humic substances and living systems». CLUB PRINT ltd., 2019. http://dx.doi.org/10.36291/hit.2019.cervantes.012.

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Tian, Zheyu, Graham Shields, Ying Zhou, Maoyan Zhu, and Miao Lu. "Reconstructing Biogeochemical Cycles during and after the Ediacaran DOUNCE (Shuram) Excursion." In Goldschmidt2020. Geochemical Society, 2020. http://dx.doi.org/10.46427/gold2020.2598.

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Rahman, Aleksandra, Niko Finke, Kai Blumberg, Rachel L. Simister, Celine Michiels, Alyse Hawley, Sean A. Crowe, and Steven J. Hallam. "NOVEL EPSILONPROTEOBACTERIA FROM SAANICH INLET COUPLES BIOGEOCHEMICAL CYCLES IN ANOXIC MARINE ENVIRONMENTS." In GSA Annual Meeting in Seattle, Washington, USA - 2017. Geological Society of America, 2017. http://dx.doi.org/10.1130/abs/2017am-307626.

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Claustre, Hervé, David Antoine, Lars Boehme, Emmanuel Boss, Fabrizio D'Ortenzio, Odile Fanton D'Andon, Christophe Guinet, et al. "Guidelines Towards an Integrated Ocean Observation System for Ecosystems and Biogeochemical Cycles." In OceanObs'09: Sustained Ocean Observations and Information for Society. European Space Agency, 2010. http://dx.doi.org/10.5270/oceanobs09.pp.14.

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Touche, Jeanne, Marie-Pierre Turpault, Christophe Calvaruso, and Philippe De Donato. "Impacts of drought events on the biogeochemical cycles of a temperate beech forest." In Goldschmidt2022. France: European Association of Geochemistry, 2022. http://dx.doi.org/10.46427/gold2022.11132.

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Boden, Joanne, Eva Stüeken, and Rika Anderson. "Exploring the role of alternative phosphorus species in Precambrian biogeochemical cycles: A genomics approach." In Goldschmidt2023. France: European Association of Geochemistry, 2023. http://dx.doi.org/10.7185/gold2023.14982.

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Reports on the topic "Biogeochemical cycles"

1

Vertenstein, Mariana. Applying computationally efficient schemes for biogeochemical cycles (ACES4BGC). Office of Scientific and Technical Information (OSTI), January 2016. http://dx.doi.org/10.2172/1234244.

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Liu, Xiaohong. Development of Modal Aerosol Module in CAM5 for Biogeochemical Cycles. Office of Scientific and Technical Information (OSTI), November 2017. http://dx.doi.org/10.2172/1409289.

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Galloway, J. N., W. H. Schlesinger, C. M. Clark, N. B. Grimm, R. B. Jackson, B. E. ;. Law, P. E. Thornton, A. R. Townsend, and R. Martin. Ch. 15: Biogeochemical Cycles. Climate Change Impacts in the United States: The Third National Climate Assessment. U.S. Global Change Research Program, 2014. http://dx.doi.org/10.7930/j0x63jt0.

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Reed, Sasha. Final Technical Report: Dryland feedbacks to future climate change: how species mortality and replacement will affect coupled biogeochemical cycles and energy balance. Office of Scientific and Technical Information (OSTI), March 2020. http://dx.doi.org/10.2172/1608533.

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Arnott, James, and Emily Jack-Scott. Interdisciplinary Workshop on the Impacts of Land Use and Land Management on Earth System Evolution, Biogeochemical Cycles, Extremes, and Inter-Sectoral Dynamics. Office of Scientific and Technical Information (OSTI), December 2020. http://dx.doi.org/10.2172/1749946.

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Stanley, Rachel H. R., Thomas Thomas, Yuan Gao, Cassandra Gaston, David Ho, David Kieber, Kate Mackey, et al. US SOLAS Science Report. Woods Hole Oceanographic Institution, December 2021. http://dx.doi.org/10.1575/1912/27821.

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The Surface Ocean – Lower Atmosphere Study (SOLAS) (http://www.solas-int.org/) is an international research initiative focused on understanding the key biogeochemical-physical interactions and feedbacks between the ocean and atmosphere that are critical elements of climate and global biogeochemical cycles. Following the release of the SOLAS Decadal Science Plan (2015-2025) (Brévière et al., 2016), the Ocean-Atmosphere Interaction Committee (OAIC) was formed as a subcommittee of the Ocean Carbon and Biogeochemistry (OCB) Scientific Steering Committee to coordinate US SOLAS efforts and activities, facilitate interactions among atmospheric and ocean scientists, and strengthen US contributions to international SOLAS. In October 2019, with support from OCB, the OAIC convened an open community workshop, Ocean-Atmosphere Interactions: Scoping directions for new research with the goal of fostering new collaborations and identifying knowledge gaps and high-priority science questions to formulate a US SOLAS Science Plan. Based on presentations and discussions at the workshop, the OAIC and workshop participants have developed this US SOLAS Science Plan. The first part of the workshop and this Science Plan were purposefully designed around the five themes of the SOLAS Decadal Science Plan (2015-2025) (Brévière et al., 2016) to provide a common set of research priorities and ensure a more cohesive US contribution to international SOLAS.

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Cooley, S. R., D. J. P. Moore, S. R. Alin, D. Butman, D. W. Clow, N. H. F. French, R. A. Feely, et al. Chapter 17: Biogeochemical Effects of Rising Atmospheric Carbon Dioxide. Second State of the Carbon Cycle Report. Edited by N. Cavallaro, G. Shrestha, R. Birdsey, M. A. Mayes, R. Najjar, S. Reed, P. Romero-Lankao, and Z. Zhu. U.S. Global Change Research Program, 2018. http://dx.doi.org/10.7930/soccr2.2018.ch17.

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Liu, Shuguang, Larry L. Tieszen, Shuqing Zhao, Zhengpeng Li, and Jinxun Liu. Developing a Spatially Distributed Terrestrial Biogeochemical Cycle Modeling System to Support the Management of Fort Benning and its Surrounding Areas. Fort Belvoir, VA: Defense Technical Information Center, December 2010. http://dx.doi.org/10.21236/ada578897.

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Berkowitz, Jacob, Nathan Beane, Kevin Philley, Nia Hurst, and Jacob Jung. An assessment of long-term, multipurpose ecosystem functions and engineering benefits derived from historical dredged sediment beneficial use projects. Engineer Research and Development Center (U.S.), August 2021. http://dx.doi.org/10.21079/11681/41382.

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Abstract:

The beneficial use of dredged materials improves environmental outcomes while maximizing navigation benefits and minimizing costs, in accordance with the principles of the Engineering With Nature® (EWN) initiative. Yet, few studies document the long-term benefits of innovative dredged material management strategies or conduct comprehensive life-cycle analysis because of a combination of (1) short monitoring time frames and (2) the paucity of constructed projects that have reached ecological maturity. In response, we conducted an ecological functional and engineering benefit assessment of six historic (>40 years old) dredged material–supported habitat improvement projects where initial postconstruction beneficial use monitoring data was available. Conditions at natural reference locations were also documented to facilitate a comparison between natural and engineered landscape features. Results indicate the projects examined provide valuable habitat for a variety of species in addition to yielding a number of engineering (for example, shoreline protection) and other (for example, carbon storage) benefits. Our findings also suggest establishment of ecological success criteria should not overemphasize replicating reference conditions but remain focused on achieving specific ecological functions (that is, habitat and biogeochemical cycling) and engineering benefits (that is, storm surge reduction, navigation channel maintenance) achievable through project design and operational management.

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Microbes in Models: Integrating Microbes into Earth System Models for Understanding Climate Change. American Society for Microbiology, June 2023. http://dx.doi.org/10.1128/aamcol.jun.2023.

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Climate change is altering the planet and threatens humanity. Earth system models simulate the planet's physical, chemical, and biological processes to help scientists understand current environmental changes and make projections for Earth's future, which can inform society's responses to combat and mitigate climate change's negative effects. Climate change will fundamentally change life on Earth, including microorganisms. Microbes will also influence climate change by driving biogeochemical cycles through the consumption and production of greenhouse gasses. Thus, explicitly including microbial processes into Earth system models can improve model projections. However, fully understanding the feedbacks between climate change and microbes, and then including those processes into Earth systems models, is a major challenge. This report is based on the deliberations of experts who participated in a virtual colloquium on 6 and 8 December, 2022, organized by the American Academy of Microbiology, which is the honorific leadership group and think tank within the American Society for Microbiology. At the colloquium, these experts from the climate and microbial sciences attempted to clearly articulate current knowledge gaps of the two fields. As a result, the participants compiled a list of top ten challenges to better incorporate microbial processes into Earth system models. Solving these challenges requires new thinking and approaches. Transdisciplinary efforts have the potential to propel science—and society—towards combating climate change.

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