Using Stable Isotopes to Estimate Trophic Position: Models, Methods, and Assumptions
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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). -
Lesson Overview from There Depends on Who Eats Whom! 3.3 Energy Flow in Ecosystems
THINK ABOUT IT What happens to energy stored in body tissues when one organism eats another? Energy moves from the “eaten” to the “eater.” Where it goes Lesson Overview from there depends on who eats whom! 3.3 Energy Flow in Ecosystems Food Chains A food chain is a series of steps in which organisms transfer energy by eating and being eaten. Food chains can vary in length. An example from the Everglades is shown. Food Chains Food Chains In some aquatic food chains, such as the example shown, Larger fishes, like the largemouth bass, eat the small fishes. primary producers are a mixture of floating algae called The bass are preyed upon by large wading birds, such as the phytoplankton and attached algae. These producers are anhinga, which may ultimately be eaten by an alligator. eaten by small fishes, such as flagfish. Food Chains Food Webs There are four steps in this food chain. In most ecosystems, feeding relationships are much more The top carnivore is four steps removed from the primary complicated than the relationships described in a single, simple producer. chain because many animals eat more than one kind of food. Ecologists call this network of feeding interactions a food web. An example of a food web in the Everglades is shown. Food Chains Within Food Webs Decomposers & Detritivores in Food Webs Each path through a food web is a food chain. Most producers die without being eaten. In the detritus A food web, like the one shown, links all of the food chains in an pathway, decomposers convert that dead material to detritus, ecosystem together. -
Trophic Levels
Trophic Levels Douglas Wilkin, Ph.D. Jean Brainard, Ph.D. Say Thanks to the Authors Click http://www.ck12.org/saythanks (No sign in required) AUTHORS Douglas Wilkin, Ph.D. To access a customizable version of this book, as well as other Jean Brainard, Ph.D. interactive content, visit www.ck12.org CK-12 Foundation is a non-profit organization with a mission to reduce the cost of textbook materials for the K-12 market both in the U.S. and worldwide. Using an open-content, web-based collaborative model termed the FlexBook®, CK-12 intends to pioneer the generation and distribution of high-quality educational content that will serve both as core text as well as provide an adaptive environment for learning, powered through the FlexBook Platform®. Copyright © 2015 CK-12 Foundation, www.ck12.org The names “CK-12” and “CK12” and associated logos and the terms “FlexBook®” and “FlexBook Platform®” (collectively “CK-12 Marks”) are trademarks and service marks of CK-12 Foundation and are protected by federal, state, and international laws. Any form of reproduction of this book in any format or medium, in whole or in sections must include the referral attribution link http://www.ck12.org/saythanks (placed in a visible location) in addition to the following terms. Except as otherwise noted, all CK-12 Content (including CK-12 Curriculum Material) is made available to Users in accordance with the Creative Commons Attribution-Non-Commercial 3.0 Unported (CC BY-NC 3.0) License (http://creativecommons.org/ licenses/by-nc/3.0/), as amended and updated by Creative Com- mons from time to time (the “CC License”), which is incorporated herein by this reference. -
Progress and Challenges in Using Stable Isotopes to Trace Plant Carbon and Water Relations Across Scales
Biogeosciences, 9, 3083–3111, 2012 www.biogeosciences.net/9/3083/2012/ Biogeosciences doi:10.5194/bg-9-3083-2012 © Author(s) 2012. CC Attribution 3.0 License. Progress and challenges in using stable isotopes to trace plant carbon and water relations across scales C. Werner1,19, H. Schnyder2, M. Cuntz3, C. Keitel4, M. J. Zeeman5, T. E. Dawson6, F.-W. Badeck7, E. Brugnoli8, J. Ghashghaie9, T. E. E. Grams10, Z. E. Kayler11, M. Lakatos12, X. Lee13, C. Maguas´ 14, J. Ogee´ 15, K. G. Rascher1, R. T. W. Siegwolf16, S. Unger1, J. Welker17, L. Wingate18, and A. Gessler11 1Experimental and Systems Ecology, University Bielefeld, 33615 Bielefeld, Germany 2Lehrstuhl fur¨ Grunlandlehre,¨ Technische Universitat¨ Munchen,¨ 85350 Freising-Weihenstephan, Germany 3UFZ – Helmholtz Centre for Environmental Research, Permoserstr. 15, 04318 Leipzig, Germany 4University of Sydney, Faculty of Agriculture, Food and Natural Resources, 1 Central Avenue, Eveleigh, NSW 2015, Australia 5College of Oceanic and Atmospheric Sciences, Oregon State University, 104 COAS Admin Bldg, Corvallis (OR), USA 6Center for Isotope Biogeochemistry, Department of Integrative Biology, University of California, Berkeley, CA 94720, USA 7Potsdam Institute for Climate Impact Research (PIK) PF 60 12 03, 14412 Potsdam, Germany 8CNR – National Research Council of Italy – Institute of Agro-environmental and Forest Biology, via Marconi 2, 05010 Porano (TR), Italy 9Laboratoire d’Ecologie, Systematique´ et Evolution (ESE), CNRS AgroParisTech – UMR8079, Batimentˆ 362, Universite´ de Paris-Sud (XI), 91405 Orsay Cedex, France 10Ecophysiology of Plants, Department of Ecology and Ecosystem Management, Technische Universitat¨ Munchen,¨ Von-Carlowitz-Platz 2, 85354 Freising, Germany 11Institute for Landscape Biogeochemistry Leibniz-Zentrum fur¨ Agrarlandschaftsforschung (ZALF) e.V., Eberswalderstr. -
Structure of Tropical River Food Webs Revealed by Stable Isotope Ratios
OIKOS 96: 46–55, 2002 Structure of tropical river food webs revealed by stable isotope ratios David B. Jepsen and Kirk O. Winemiller Jepsen, D. B. and Winemiller, K. O. 2002. Structure of tropical river food webs revealed by stable isotope ratios. – Oikos 96: 46–55. Fish assemblages in tropical river food webs are characterized by high taxonomic diversity, diverse foraging modes, omnivory, and an abundance of detritivores. Feeding links are complex and modified by hydrologic seasonality and system productivity. These properties make it difficult to generalize about feeding relation- ships and to identify dominant linkages of energy flow. We analyzed the stable carbon and nitrogen isotope ratios of 276 fishes and other food web components living in four Venezuelan rivers that differed in basal food resources to determine 1) whether fish trophic guilds integrated food resources in a predictable fashion, thereby providing similar trophic resolution as individual species, 2) whether food chain length differed with system productivity, and 3) how omnivory and detritivory influenced trophic structure within these food webs. Fishes were grouped into four trophic guilds (herbivores, detritivores/algivores, omnivores, piscivores) based on literature reports and external morphological characteristics. Results of discriminant function analyses showed that isotope data were effective at reclassifying individual fish into their pre-identified trophic category. Nutrient-poor, black-water rivers showed greater compartmentalization in isotope values than more productive rivers, leading to greater reclassification success. In three out of four food webs, omnivores were more often misclassified than other trophic groups, reflecting the diverse food sources they assimilated. When fish d15N values were used to estimate species position in the trophic hierarchy, top piscivores in nutrient-poor rivers had higher trophic positions than those in more productive rivers. -
Stable Isotope Methods in Biological and Ecological Studies of Arthropods
eea_572.fm Page 3 Tuesday, June 12, 2007 4:17 PM DOI: 10.1111/j.1570-7458.2007.00572.x Blackwell Publishing Ltd MINI REVIEW Stable isotope methods in biological and ecological studies of arthropods CORE Rebecca Hood-Nowotny1* & Bart G. J. Knols1,2 Metadata, citation and similar papers at core.ac.uk Provided by Wageningen University & Research Publications 1International Atomic Energy Agency (IAEA), Agency’s Laboratories Seibersdorf, A-2444 Seibersdorf, Austria, 2Laboratory of Entomology, Wageningen University and Research Centre, P.O. Box 8031, 6700 EH Wageningen, The Netherlands Accepted: 13 February 2007 Key words: marking, labelling, enrichment, natural abundance, resource turnover, 13-carbon, 15-nitrogen, 18-oxygen, deuterium, mass spectrometry Abstract This is an eclectic review and analysis of contemporary and promising stable isotope methodologies to study the biology and ecology of arthropods. It is augmented with literature from other disciplines, indicative of the potential for knowledge transfer. It is demonstrated that stable isotopes can be used to understand fundamental processes in the biology and ecology of arthropods, which range from nutrition and resource allocation to dispersal, food-web structure, predation, etc. It is concluded that falling costs and reduced complexity of isotope analysis, besides the emergence of new analytical methods, are likely to improve access to isotope technology for arthropod studies still further. Stable isotopes pose no environmental threat and do not change the chemistry or biology of the target organism or system. These therefore represent ideal tracers for field and ecophysiological studies, thereby avoiding reductionist experimentation and encouraging more holistic approaches. Con- sidering (i) the ease with which insects and other arthropods can be marked, (ii) minimal impact of the label on their behaviour, physiology, and ecology, and (iii) environmental safety, we advocate more widespread application of stable isotope technology in arthropod studies and present a variety of potential uses. -
Ecology (Pyramids, Biomagnification, & Succession
ENERGY PYRAMIDS & Freshmen Biology FOOD CHAINS/FOOD WEBS May 4 – May 8 Lecture ENERGY FLOW •Energy → powers life’s processes •Energy = ATP! •Flow of energy determines the system’s ability to sustain life FEEDING RELATIONSHIPS • Energy flows through an ecosystem in one direction • Sun → autotrophs (producers) → heterotrophs (consumers) FOOD CHAIN VS. FOOD WEB FOOD CHAINS • Energy stored by producers → passed through an ecosystem by a food chain • Food chain = series of steps in which organisms transfer energy by eating and being eaten FOOD WEBS •Feeding relationships are more complex than can be shown in a food chain •Food Web = network of complex interactions •Food webs link all the food chains in an ecosystem together ECOLOGICAL PYRAMIDS • Used to show the relationships in Ecosystems • There are different types: • Energy Pyramid • Biomass Pyramid • Pyramid of numbers ENERGY PYRAMID • Only part of the energy that is stored in one trophic level can be passed on to the next level • Much of the energy that is consumed is used for the basic functions of life (breathing, moving, reproducing) • Only 10% is used to produce more biomass (10 % moves on) • This is what can be obtained from the next trophic level • All of the other energy is lost 10% RULE • Only 10% of energy (from organisms) at one trophic level → the next level • EX: only 10% of energy/calories from grasses is available to cows • WHY? • Energy used for bodily processes (growth/development and repair) • Energy given off as heat • Energy used for daily functioning/movement • Only 10% of energy you take in should be going to your actual biomass/weight which another organism could eat BIOMASS PYRAMID • Total amount of living tissue within a given trophic level = biomass • Represents the amount of potential food available for each trophic level in an ecosystem PYRAMID OF NUMBERS •Based on the number of individuals at each trophic level. -
Oxygen Isotopic Signature of CO2 from Combustion Processes
Atmos. Chem. Phys., 11, 1473–1490, 2011 www.atmos-chem-phys.net/11/1473/2011/ Atmospheric doi:10.5194/acp-11-1473-2011 Chemistry © Author(s) 2011. CC Attribution 3.0 License. and Physics Oxygen isotopic signature of CO2 from combustion processes M. Schumacher1,2,3, R. A. Werner3, H. A. J. Meijer1, H. G. Jansen1, W. A. Brand2, H. Geilmann2, and R. E. M. Neubert1 1Centre for Isotope Research, University of Groningen, Nijenborgh 4, 9747 AG Groningen, The Netherlands 2Max-Planck-Institute for Biogeochemistry, Hans-Knoell-Straße 10, 07745, Jena, Germany 3Institute of Plant Sciences, Swiss Federal Institute of Technology Zurich,¨ Universitatsstraße¨ 2, 8092 Zurich,¨ Switzerland Received: 21 July 2008 – Published in Atmos. Chem. Phys. Discuss.: 5 November 2008 Revised: 2 February 2011 – Accepted: 5 February 2011 – Published: 16 February 2011 Abstract. For a comprehensive understanding of the global (diffusive) transport of oxygen to the reaction zone as the carbon cycle precise knowledge of all processes is neces- cause of the isotope fractionation. The original total 18O sig- sary. Stable isotope (13C and 18O) abundances provide in- nature of the material appeared to have little influence, how- formation for the qualification and the quantification of the ever, a contribution of specific bio-chemical compounds to diverse source and sink processes. This study focuses on the individual combustion products released from the involved 18 δ O signature of CO2 from combustion processes, which material became obvious. are widely present both naturally (wild fires), and human in- duced (fossil fuel combustion, biomass burning) in the car- bon cycle. All these combustion processes use atmospheric 1 Introduction oxygen, of which the isotopic signature is assumed to be con- stant with time throughout the whole atmosphere. -
Investigations of Nuclear Forensic Signatures in Uranium Bearing Materials a Dissertation Submitted to the Graduate School of the University of Cincinnati
Investigations of Nuclear Forensic Signatures in Uranium Bearing Materials A dissertation submitted to the Graduate School of the University of Cincinnati in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Ph.D) In the Department of Chemistry Of the McMicken College of Arts and Sciences By Lisa Ann Meyers B.S. Ohio Northern University 2009 August 2013 Committee Chairs: Thomas Beck, Ph.D. Apryll Stalcup, Ph.D. i Abstract Nuclear forensics is a multidisciplinary science that uses a variety of analytical methods and tools to investigate the physical, chemical, elemental, and isotopic characteristics of nuclear and radiological material. A collection of these characteristics is called signatures that aids in determining how, where and when the material was manufactured. Radiological chronometry (i.e., age dating) is an important tool in nuclear forensics that uses several methods to determine the length of time that has elapsed since a material was last purified. For example, the “age” of a uranium-bearing material is determined by measuring the ingrowth of 230Th from its parent, 234U. A piece of scrap uranium metal bar buried in the dirt floor of an old, abandoned metal rolling mill was analyzed using multi-collector inductively coupled plasma mass spectroscopy (MC-ICP- MS). The mill rolled uranium rods in the 1940s and 1950s. The age of the metal bar was determined to be 61 years at the time of analysis using the 230Th/234U chronometer, which corresponds to a purification date of July 1950 ± 1.5 years. Radiochronometry was determined for three different types of uranium metal samples. -
Determination of Trophic Relationships Within a High Arctic Marine Food Web Using 613C and 615~ Analysis *
MARINE ECOLOGY PROGRESS SERIES Published July 23 Mar. Ecol. Prog. Ser. Determination of trophic relationships within a high Arctic marine food web using 613c and 615~ analysis * Keith A. ~obson'.2, Harold E. welch2 ' Department of Biology. University of Saskatchewan, Saskatoon, Saskatchewan. Canada S7N OWO Department of Fisheries and Oceans, Freshwater Institute, 501 University Crescent, Winnipeg, Manitoba, Canada R3T 2N6 ABSTRACT: We measured stable-carbon (13C/12~)and/or nitrogen (l5N/l4N)isotope ratios in 322 tissue samples (minus lipids) representing 43 species from primary producers through polar bears Ursus maritimus in the Barrow Strait-Lancaster Sound marine food web during July-August, 1988 to 1990. 613C ranged from -21.6 f 0.3%0for particulate organic matter (POM) to -15.0 f 0.7%0for the predatory amphipod Stegocephalus inflatus. 615~was least enriched for POM (5.4 +. O.8%0), most enriched for polar bears (21.1 f 0.6%0), and showed a step-wise enrichment with trophic level of +3.8%0.We used this enrichment value to construct a simple isotopic food-web model to establish trophic relationships within thls marine ecosystem. This model confirms a food web consisting primanly of 5 trophic levels. b13C showed no discernible pattern of enrichment after the first 2 trophic levels, an effect that could not be attributed to differential lipid concentrations in food-web components. Although Arctic cod Boreogadus saida is an important link between primary producers and higher trophic-level vertebrates during late summer, our isotopic model generally predicts closer links between lower trophic-level invertebrates and several species of seabirds and marine mammals than previously established. -
Can Algal Photosynthetic Inorganic Carbon Isotope Fractionation Be Predicted in Lakes Using Existing Models?
Aquat. Sci. 68 (2006) 142–153 1015-1621/06/020142-12 DOI 10.1007/s00027-006-0818-5 Aquatic Sciences © Eawag, Dübendorf, 2006 Research Article Can algal photosynthetic inorganic carbon isotope fractionation be predicted in lakes using existing models? Darren L. Bade1,3,*, Michael L. Pace2, Jonathan J. Cole2 and Stephen R. Carpenter1 1 Center for Limnology, University of Wisconsin-Madison, USA 2 Institute of Ecosystem Studies, Millbrook, NY, USA 3 Present address: Institute of Ecosystem Studies, PO Box AB (65 Sharon Turnpike), Millbrook, NY 12545, USA Received: 30 June 2005; revised manuscript accepted: 7 December 2005 Abstract. Differential fractionation of inorganic carbon stable isotopes for studies ranging from food webs to stable isotopes during photosynthesis is an important paleolimnology. In our largest comparative study, values cause of variability in algal carbon isotope signatures. of δ13C-POC ranged from –35.1 ‰ to –21.3 ‰. Using Several physiological models have been proposed to ex- several methods to obtain an algal isotopic signature, we ε plain algal photosynthetic fractionation factors ( p). These found high variability in fractionation among lakes. There ε models generally consider CO2 concentration, growth was no relationship between p and one of the most im- rate, or cell morphometry and have been supported by portant predictors in existing models, pCO2. A whole-lake empirical evidence from laboratory cultures. Here, we inorganic 13C addition was used to create distinct algal ε explore the applicability of these models to a broad range isotope signatures to aid in examining p. Measurements of lakes with mixed phytoplankton communities. Under- and a statistical model from the isotope addition revealed standing this fractionation is necessary for using carbon that algal fractionation was often low (0 – 15 ‰). -
Measurement of the Isotopic Composition of Dissolved Iron in the Open Ocean F
Measurement of the isotopic composition of dissolved iron in the open ocean F. Lacan, Amandine Radic, Catherine Jeandel, Franck Poitrasson, Géraldine Sarthou, Catherine Pradoux, Remi Freydier To cite this version: F. Lacan, Amandine Radic, Catherine Jeandel, Franck Poitrasson, Géraldine Sarthou, et al.. Measure- ment of the isotopic composition of dissolved iron in the open ocean. Geophysical Research Letters, American Geophysical Union, 2008, pp.L24610. 10.1029/2008GL035841. hal-00399111 HAL Id: hal-00399111 https://hal.archives-ouvertes.fr/hal-00399111 Submitted on 15 Jul 2009 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 Measurement of the Isotopic Composition of dissolved Iron in the Open Ocean 2 3 Lacan1 F., Radic1 A., Jeandel1 C., Poitrasson2 F., Sarthou3 G., Pradoux1 C., Freydier2 R. 4 5 1: CNRS, LEGOS, UMR5566, CNRS-CNES-IRD-UPS, Observatoire Midi-Pyrénées, 18, Av. 6 E. Belin, 31400 Toulouse, France. 7 2: LMTG, CNRS-UPS-IRD, 14-16, avenue Edouard Belin, 31400 Toulouse, France. 8 3: LEMAR, UMR CNRS 6539, IUEM, Technopole Brest Iroise, Place Nicolas Copernic, 9 29280 Plouzané, France. 10 11 Paper published in Geophysical Research Letters (2008) L24610. 12 We acknowledge Geophysical Research Letters and the American Geophysical Union copyright 13 14 This work demonstrates for the first time the feasibility of the measurement of the isotopic 15 composition of dissolved iron in seawater for a typical open ocean Fe concentration range 16 (0.1-1nM).