Net Primary Production in the Ocean Cross-Chapter Box
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Methane Cold Seeps As Biological Oases in the High‐
LIMNOLOGY and Limnol. Oceanogr. 00, 2017, 00–00 VC 2017 The Authors Limnology and Oceanography published by Wiley Periodicals, Inc. OCEANOGRAPHY on behalf of Association for the Sciences of Limnology and Oceanography doi: 10.1002/lno.10732 Methane cold seeps as biological oases in the high-Arctic deep sea Emmelie K. L. A˚ strom€ ,1* Michael L. Carroll,1,2 William G. Ambrose, Jr.,1,2,3,4 Arunima Sen,1 Anna Silyakova,1 JoLynn Carroll1,2 1CAGE - Centre for Arctic Gas Hydrate, Environment and Climate, Department of Geosciences, UiT The Arctic University of Norway, Tromsø, Norway 2Akvaplan-niva, FRAM – High North Research Centre for Climate and the Environment, Tromsø, Norway 3Division of Polar Programs, National Science Foundation, Arlington, Virginia 4Department of Biology, Bates College, Lewiston, Maine Abstract Cold seeps can support unique faunal communities via chemosynthetic interactions fueled by seabed emissions of hydrocarbons. Additionally, cold seeps can enhance habitat complexity at the deep seafloor through the accretion of methane derived authigenic carbonates (MDAC). We examined infaunal and mega- faunal community structure at high-Arctic cold seeps through analyses of benthic samples and seafloor pho- tographs from pockmarks exhibiting highly elevated methane concentrations in sediments and the water column at Vestnesa Ridge (VR), Svalbard (798 N). Infaunal biomass and abundance were five times higher, species richness was 2.5 times higher and diversity was 1.5 times higher at methane-rich Vestnesa compared to a nearby control region. Seabed photos reveal different faunal associations inside, at the edge, and outside Vestnesa pockmarks. Brittle stars were the most common megafauna occurring on the soft bottom plains out- side pockmarks. -
A Comparison of Global Estimates of Marine Primary Production from Ocean Color
ARTICLE IN PRESS Deep-Sea Research II 53 (2006) 741–770 www.elsevier.com/locate/dsr2 A comparison of global estimates of marine primary production from ocean color Mary-Elena Carra,Ã, Marjorie A.M. Friedrichsb,bb, Marjorie Schmeltza, Maki Noguchi Aitac, David Antoined, Kevin R. Arrigoe, Ichio Asanumaf, Olivier Aumontg, Richard Barberh, Michael Behrenfeldi, Robert Bidigarej, Erik T. Buitenhuisk, Janet Campbelll, Aurea Ciottim, Heidi Dierssenn, Mark Dowello, John Dunnep, Wayne Esaiasq, Bernard Gentilid, Watson Greggq, Steve Groomr, Nicolas Hoepffnero, Joji Ishizakas, Takahiko Kamedat, Corinne Le Que´re´k,u, Steven Lohrenzv, John Marraw, Fre´de´ric Me´lino, Keith Moorex, Andre´Moreld, Tasha E. Reddye, John Ryany, Michele Scardiz, Tim Smythr, Kevin Turpieq, Gavin Tilstoner, Kirk Watersaa, Yasuhiro Yamanakac aJet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Dr, Pasadena, CA 91101-8099, USA bCenter for Coastal Physical Oceanography, Old Dominion University, Crittenton Hall, 768 West 52nd Street, Norfolk, VA 23529, USA cEcosystem Change Research Program, Frontier Research Center for Global Change, 3173-25,Showa-machi, Yokohama 236-0001, Japan dLaboratoire d’Oce´anographie de Villefranche, 06238, Villefranche sur Mer, France eDepartment of Geophysics, Stanford University, Stanford, CA 94305-2215, USA fTokyo University of Information Sciences 1200-1, Yato, Wakaba, Chiba 265-8501, Japan gLaboratoire d’Oce´anographie Dynamique et de Climatologie, Univ Paris 06, MNHN, IRD,CNRS, Paris F-75252 05, France hDuke University -
A New Type of Plankton Food Web Functioning in Coastal Waters Revealed by Coupling Monte Carlo Markov Chain Linear Inverse Metho
A new type of plankton food web functioning in coastal waters revealed by coupling Monte Carlo Markov Chain Linear Inverse method and Ecological Network Analysis Marouan Meddeb, Nathalie Niquil, Boutheina Grami, Kaouther Mejri, Matilda Haraldsson, Aurélie Chaalali, Olivier Pringault, Asma Sakka Hlaili To cite this version: Marouan Meddeb, Nathalie Niquil, Boutheina Grami, Kaouther Mejri, Matilda Haraldsson, et al.. A new type of plankton food web functioning in coastal waters revealed by coupling Monte Carlo Markov Chain Linear Inverse method and Ecological Network Analysis. Ecological Indicators, Elsevier, 2019, 104, pp.67-85. 10.1016/j.ecolind.2019.04.077. hal-02146355 HAL Id: hal-02146355 https://hal.archives-ouvertes.fr/hal-02146355 Submitted on 3 Jun 2019 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. 1 A new type of plankton food web functioning in coastal waters revealed by coupling 2 Monte Carlo Markov Chain Linear Inverse method and Ecological Network Analysis 3 4 5 Marouan Meddeba,b*, Nathalie Niquilc, Boutheïna Gramia,d, Kaouther Mejria,b, Matilda 6 Haraldssonc, Aurélie Chaalalic,e,f, Olivier Pringaultg, Asma Sakka Hlailia,b 7 8 aUniversité de Carthage, Faculté des Sciences de Bizerte, Laboratoire de phytoplanctonologie 9 7021 Zarzouna, Bizerte, Tunisie. -
Host-Secreted Antimicrobial Peptide Enforces Symbiotic Selectivity in Medicago Truncatula
Host-secreted antimicrobial peptide enforces symbiotic selectivity in Medicago truncatula Qi Wanga, Shengming Yanga, Jinge Liua, Kata Terecskeib, Edit Ábrahámb, Anikó Gombárc, Ágota Domonkosc, Attila Szucs} b, Péter Körmöczib, Ting Wangb, Lili Fodorc, Linyong Maod,e, Zhangjun Feid,e, Éva Kondorosib,1, Péter Kalóc, Attila Keresztb, and Hongyan Zhua,1 aDepartment of Plant and Soil Sciences, University of Kentucky, Lexington, KY 40546; bInstitute of Biochemistry, Biological Research Center, Szeged 6726, Hungary; cNational Agricultural Research and Innovation Centre, Agricultural Biotechnology Institute, Gödöllo} 2100, Hungary; dBoyce Thompson Institute for Plant Research, Cornell University, Ithaca, NY 14853; and eU.S. Department of Agriculture–Agricultural Research Service Robert W. Holley Center for Agriculture and Health, Cornell University, Ithaca, NY 14853 Contributed by Éva Kondorosi, February 14, 2017 (sent for review January 17, 2017; reviewed by Rebecca Dickstein and Julia Frugoli) Legumes engage in root nodule symbioses with nitrogen-fixing effectors or microbe-associated molecular patterns (MAMPs) soil bacteria known as rhizobia. In nodule cells, bacteria are enclosed such as surface polysaccharides to facilitate their invasion of the in membrane-bound vesicles called symbiosomes and differentiate host (7, 8). Therefore, effector- or MAMP-triggered plant im- into bacteroids that are capable of converting atmospheric nitrogen munity mediated by intracellular nucleotide binding/leucine-rich into ammonia. Bacteroid differentiation -
7.014 Handout PRODUCTIVITY: the “METABOLISM” of ECOSYSTEMS
7.014 Handout PRODUCTIVITY: THE “METABOLISM” OF ECOSYSTEMS Ecologists use the term “productivity” to refer to the process through which an assemblage of organisms (e.g. a trophic level or ecosystem assimilates carbon. Primary producers (autotrophs) do this through photosynthesis; Secondary producers (heterotrophs) do it through the assimilation of the organic carbon in their food. Remember that all organic carbon in the food web is ultimately derived from primary production. DEFINITIONS Primary Productivity: Rate of conversion of CO2 to organic carbon (photosynthesis) per unit surface area of the earth, expressed either in terns of weight of carbon, or the equivalent calories e.g., g C m-2 year-1 Kcal m-2 year-1 Primary Production: Same as primary productivity, but usually expressed for a whole ecosystem e.g., tons year-1 for a lake, cornfield, forest, etc. NET vs. GROSS: For plants: Some of the organic carbon generated in plants through photosynthesis (using solar energy) is oxidized back to CO2 (releasing energy) through the respiration of the plants – RA. Gross Primary Production: (GPP) = Total amount of CO2 reduced to organic carbon by the plants per unit time Autotrophic Respiration: (RA) = Total amount of organic carbon that is respired (oxidized to CO2) by plants per unit time Net Primary Production (NPP) = GPP – RA The amount of organic carbon produced by plants that is not consumed by their own respiration. It is the increase in the plant biomass in the absence of herbivores. For an entire ecosystem: Some of the NPP of the plants is consumed (and respired) by herbivores and decomposers and oxidized back to CO2 (RH). -
Euphotic Zone Depth: Its Derivation and Implication to Ocean-Color Remote Sensing" (2007)
University of South Florida Scholar Commons Marine Science Faculty Publications College of Marine Science 3-16-2007 Euphotic Zone Depth: Its Derivation and Implication to Ocean- Color Remote Sensing ZhongPing Lee Stennis Space Center Alan Weidemann Stennis Space Center John Kindle Stennis Space Center Robert Arnone Stennis Space Center Kendall L. Carder University of South Florida, [email protected] See next page for additional authors Follow this and additional works at: https://scholarcommons.usf.edu/msc_facpub Part of the Marine Biology Commons Scholar Commons Citation Lee, ZhongPing; Weidemann, Alan; Kindle, John; Arnone, Robert; Carder, Kendall L.; and Davis, Curtiss, "Euphotic Zone Depth: Its Derivation and Implication to Ocean-Color Remote Sensing" (2007). Marine Science Faculty Publications. 11. https://scholarcommons.usf.edu/msc_facpub/11 This Article is brought to you for free and open access by the College of Marine Science at Scholar Commons. It has been accepted for inclusion in Marine Science Faculty Publications by an authorized administrator of Scholar Commons. For more information, please contact [email protected]. Authors ZhongPing Lee, Alan Weidemann, John Kindle, Robert Arnone, Kendall L. Carder, and Curtiss Davis This article is available at Scholar Commons: https://scholarcommons.usf.edu/msc_facpub/11 JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 112, C03009, doi:10.1029/2006JC003802, 2007 Euphotic zone depth: Its derivation and implication to ocean-color remote sensing ZhongPing Lee,1 Alan Weidemann,1 John Kindle,1 Robert Arnone,1 Kendall L. Carder,2 and Curtiss Davis3 Received 6 July 2006; revised 12 October 2006; accepted 1 November 2006; published 16 March 2007. [1] Euphotic zone depth, z1%, reflects the depth where photosynthetic available radiation (PAR) is 1% of its surface value. -
Bacterial Production and Respiration
Organic matter production % 0 Dissolved Particulate 5 > Organic Organic Matter Matter Heterotrophic Bacterial Grazing Growth ~1-10% of net organic DOM does not matter What happens to the 90-99% of sink, but can be production is physically exported to organic matter production that does deep sea not get exported as particles? transported Export •Labile DOC turnover over time scales of hours to days. •Semi-labile DOC turnover on time scales of weeks to months. •Refractory DOC cycles over on time scales ranging from decadal to multi- decadal…perhaps longer •So what consumes labile and semi-labile DOC? How much carbon passes through the microbial loop? Phytoplankton Heterotrophic bacteria ?? Dissolved organic Herbivores ?? matter Higher trophic levels Protozoa (zooplankton, fish, etc.) ?? • Very difficult to directly measure the flux of carbon from primary producers into the microbial loop. – The microbial loop is mostly run on labile (recently produced organic matter) - - very low concentrations (nM) turning over rapidly against a high background pool (µM). – Unclear exactly which types of organic compounds support bacterial growth. Bacterial Production •Step 1: Determine how much carbon is consumed by bacteria for production of new biomass. •Bacterial production (BP) is the rate that bacterial biomass is created. It represents the amount of Heterotrophic material that is transformed from a nonliving pool bacteria (DOC) to a living pool (bacterial biomass). •Mathematically P = µB ?? µ = specific growth rate (time-1) B = bacterial biomass (mg C L-1) P= bacterial production (mg C L-1 d-1) Dissolved organic •Note that µ = P/B matter •Thus, P has units of mg C L-1 d-1 Bacterial production provides one measurement of carbon flow into the microbial loop How doe we measure bacterial production? Production (∆ biomass/time) (mg C L-1 d-1) • 3H-thymidine • 3H or 14C-leucine Note: these are NOT direct measures of biomass production (i.e. -
GLOBAL PRIMARY PRODUCTION and EVAPOTRANSPIRATION by Steven W
15 GLOBAL PRIMARY PRODUCTION AND EVAPOTRANSPIRATION by Steven W. Running and Maosheng Zhao DATA PRODUCTS Moderate Resolution Imaging Spectroradiometer Terrestrial primary production provides the energy to (MODIS) sensor, these variables are calculated maintain the structure and functions of ecosystems, every eight days in near real time at 1 km resolution. and supplies goods (e.g. food, fuel, wood and fi bre) MODIS GPP, NPP and ET data are available at the for human society. Gross primary production (GPP) EOS data gateway (see link below). is the amount of carbon fi xed by photosynthesis, To correct for contamination in the global and net primary production (NPP) is the amount of refl ectance data due to severe cloudiness or aerosols carbon converted into biomass after subtracting in the near real time products, these datasets are the cost of plant respiration. The water loss through reprocessed at the end of each year to build more exchange of trace gas CO2 by leaf stomata during stable, permanent datasets. These end-of-year photosynthesis plus evaporation from soil and versions of MODIS GPP, NPP and ET are available at plants is evapotranspiration (ET). ET computes the NTSG, University of Montana (see link below). water lost by a land surface, so it is consequently a component of the water balance in a region, and RESULTS FOR 2000–2006 is therefore relevant for drought monitoring and Figure 1 shows the seven-year average MODIS water management, providing an assessment of NPP for vegetated land on earth at 1 km spatial the water potentially available for human society. -
Coastal and Marine Ecological Classification Standard (2012)
FGDC-STD-018-2012 Coastal and Marine Ecological Classification Standard Marine and Coastal Spatial Data Subcommittee Federal Geographic Data Committee June, 2012 Federal Geographic Data Committee FGDC-STD-018-2012 Coastal and Marine Ecological Classification Standard, June 2012 ______________________________________________________________________________________ CONTENTS PAGE 1. Introduction ..................................................................................................................... 1 1.1 Objectives ................................................................................................................ 1 1.2 Need ......................................................................................................................... 2 1.3 Scope ........................................................................................................................ 2 1.4 Application ............................................................................................................... 3 1.5 Relationship to Previous FGDC Standards .............................................................. 4 1.6 Development Procedures ......................................................................................... 5 1.7 Guiding Principles ................................................................................................... 7 1.7.1 Build a Scientifically Sound Ecological Classification .................................... 7 1.7.2 Meet the Needs of a Wide Range of Users ...................................................... -
Grade 3 Unit 2 Overview Open Ocean Habitats Introduction
G3 U2 OVR GRADE 3 UNIT 2 OVERVIEW Open Ocean Habitats Introduction The open ocean has always played a vital role in the culture, subsistence, and economic well-being of Hawai‘i’s inhabitants. The Hawaiian Islands lie in the Pacifi c Ocean, a body of water covering more than one-third of the Earth’s surface. In the following four lessons, students learn about open ocean habitats, from the ocean’s lighter surface to the darker bottom fl oor thousands of feet below the surface. Although organisms are scarce in the deep sea, there is a large diversity of organisms in addition to bottom fi sh such as polycheate worms, crustaceans, and bivalve mollusks. They come to realize that few things in the open ocean have adapted to cope with the increased pressure from the weight of the water column at that depth, in complete darkness and frigid temperatures. Students fi nd out, through instruction, presentations, and website research, that the vast open ocean is divided into zones. The pelagic zone consists of the open ocean habitat that begins at the edge of the continental shelf and extends from the surface to the ocean bottom. This zone is further sub-divided into the photic (sunlight) and disphotic (twilight) zones where most ocean organisms live. Below these two sub-zones is the aphotic (darkness) zone. In this unit, students learn about each of the ocean zones, and identify and note animals living in each zone. They also research and keep records of the evolutionary physical features and functions that animals they study have acquired to survive in harsh open ocean habitats. -
Phytoplankton As Key Mediators of the Biological Carbon Pump: Their Responses to a Changing Climate
sustainability Review Phytoplankton as Key Mediators of the Biological Carbon Pump: Their Responses to a Changing Climate Samarpita Basu * ID and Katherine R. M. Mackey Earth System Science, University of California Irvine, Irvine, CA 92697, USA; [email protected] * Correspondence: [email protected] Received: 7 January 2018; Accepted: 12 March 2018; Published: 19 March 2018 Abstract: The world’s oceans are a major sink for atmospheric carbon dioxide (CO2). The biological carbon pump plays a vital role in the net transfer of CO2 from the atmosphere to the oceans and then to the sediments, subsequently maintaining atmospheric CO2 at significantly lower levels than would be the case if it did not exist. The efficiency of the biological pump is a function of phytoplankton physiology and community structure, which are in turn governed by the physical and chemical conditions of the ocean. However, only a few studies have focused on the importance of phytoplankton community structure to the biological pump. Because global change is expected to influence carbon and nutrient availability, temperature and light (via stratification), an improved understanding of how phytoplankton community size structure will respond in the future is required to gain insight into the biological pump and the ability of the ocean to act as a long-term sink for atmospheric CO2. This review article aims to explore the potential impacts of predicted changes in global temperature and the carbonate system on phytoplankton cell size, species and elemental composition, so as to shed light on the ability of the biological pump to sequester carbon in the future ocean. -
Moe Pond Limnology and Fisii Population Biology: an Ecosystem Approach
MOE POND LIMNOLOGY AND FISII POPULATION BIOLOGY: AN ECOSYSTEM APPROACH C. Mead McCoy, C. P.Madenjian, J. V. Adall1s, W. N. I-Iannan, D. M. Warner, M. F. Albright, and L. P. Sohacki BIOLOGICAL FIELD STArrION COOPERSTOWN, NEW YORK Occasional Paper No. 33 January 2000 STATE UNIVERSITY COLLEGE AT ONEONTA ACKNOWLEDGMENTS I wish to express my gratitude to the members of my graduate committee: Willard Harman, Leonard Sohacki and Bruce Dayton for their comments in the preparation of this manuscript; and for the patience and understanding they exhibited w~lile I was their student. ·1 want to also thank Matthew Albright for his skills in quantitative analyses of total phosphorous and nitrite/nitrate-N conducted on water samples collected from Moe Pond during this study. I thank David Ramsey for his friendship and assistance in discussing chlorophyll a methodology. To all the SUNY Oneonta BFS interns who lent-a-hand during the Moe Pond field work of 1994 and 1995, I thank you for your efforts and trust that the spine wounds suffered were not in vain. To all those at USGS Great Lakes Science Center who supported my efforts through encouragement and facilities - Jerrine Nichols, Douglas Wilcox, Bruce Manny, James Hickey and Nancy Milton, I thank all of you. Also to Donald Schloesser, with whom I share an office, I would like to thank you for your many helpful suggestions concerning the estimation of primary production in aquatic systems. In particular, I wish to express my appreciation to Charles Madenjian and Jean Adams for their combined quantitative prowess, insight and direction in data analyses and their friendship.