DOCSLIB.ORG

Trophic State Index

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Trophic State Index Trophic state index From Wikipedia, the free encyclopedia Jump to: navigation, search The quantities of nitrogen, phosphorus, and other biologically useful nutrients are the primary determinants of a lake's trophic state index (TSI). Nutrients such as nitrogen and phosphorus tend to be limiting resources in standing water bodies, so increased concentrations tend to result in increased plant growth, followed by corollary increases in subsequent trophic levels. [1] Consequently, a lake's trophic index may sometimes be used to make a rough estimate of its biological condition.[2] Although the term "trophic index" is commonly applied to lakes, any surface water body may be indexed. Carlson's Trophic State Index Carlson's index is one of the more commonly used trophic indices, and is the trophic index used by the United States Environmental Protection Agency.[2] The trophic state is defined as the total weight of biomass in a given water body at the time of measurement. Because they are of public concern, the Carlson index uses the algal biomass as an objective classifier of a lake or other water body's trophic status.[3] According to the US EPA, the Carlson Index should only be used with lakes that have relatively few rooted plants and non-algal turbidity sources. [2] Index Variables Because they tend to correlate, three independent variables can be used to calculate the Carlson Index: chlorophyll pigments, total phosphorus and Secchi depth. Of these three, chlorophyll will probably yield the most accurate measures, as it is the most accurate predictor of biomass. Phosphorus may be a more accurate of a water body's summer trophic status than chlorophyll if the measurements are made during the winter. Finally, the Secchi depth is probably the least accurate measure, but also the most affordable and expedient one. Consequently, citizen monitoring programs and other volunteer or large- scale surveys will often use the Secchi depth. By translating the Secchi transparency values to a log base 2 scale, each successive doubling of biomass is represented as a whole integer index number.[4] The Secchi depth, which measures water transparency, indicates the concentration of dissolved and particulate material in the water, which in turn can be used to derive the biomass. This relationship is expressed in the following equation: where z = the depth at which the disk disappears, I0 is the intensity of light striking the water's surface, Iz is about 10% of I0 and is considered a constant, kw is a coefficient for the attenuation of light by water and dissolved substances, α is treated as a constant with the units of square meters per milligram and C is the concentration of particulate matter in units for milligrams per cubic meter.[3] Trophic Classifications A lake is usually classified as being in one of three possible classes: oligotrophic, mesotrophic or eutrophic. Lakes with extreme trophic indices may also be considered hyperoligotrophic or hypereutrophic. The table below demonstrates how the index values translate into trophic classes. Relationships between Trophic Index (TI), chlorphyll (Chl), phosphorus (P, both micrograms per litre), Secchi depth (SD, metres), and Trophic Class (after Carlson 1996[4]) TI Chl P SD Trophic Class <30—40 0—2.6 0—12 >8—4 Oligotrophic 40—50 2.6—7.3 12—24 4—2 Mesotrophic 50—70 7.3—56 24—96 2—0.5 Eutrophic 70—100+ 56—155+ 96—384+ 0.5—<0.25 Hypereutrophic Oligotrophic lakes generally host very little or no aquatic vegetation and are relatively clear, while eutrophic lakes tend to host large quantities of organisms, including algal blooms. Each trophic class supports different types of fish and other organisms, as well. If the algal biomass in a lake or other water body reaches too high a concentration (say <80 TI), massive fish die-offs may occur as decomposing biomass deoxygenates the water. Oligotrophic Kurtkowiec Lake, an oligotrophic lake in the Tatra Mountains of southern Poland An oligotrophic lake is a lake with low primary productivity, the result of low nutrient content. These lakes have low algal production, and consequently, often have very clear waters, with high drinking-water quality. The bottom waters of such lakes typically have ample oxygen; thus, such lakes often support many fish species, like lake trout, which require cold, well-oxygenated waters. The oxygen content is likely to be higher in deep lakes, owing to their larger hypolimnetic volume. Ecologists use the term oligotrophic to distinguish unproductive lakes, characterised by nutrient deficiency, from productive, eutrophic lakes, with an ample or excessive nutrient supply. Oligotrophic lakes are most common in cold regions underlain by resistant igneous rocks (especially granitic bedrock). Mesotrophic Mesotrophic lakes are lakes with an intermediate level of productivity, greater than oligotrophic lakes, but less than eutrophic lakes. These lakes are commonly clear water lakes and ponds with beds of submerged aquatic plants and medium levels of nutrients. Lake Pohjalampi is an example of a mesotrophic lake The term mesotrophic is also applied to terrestrial habitats. Mesotrophic soils have moderate nutrient levels. Eutrophic Algal bloom in a village river in the mountains near Chengdu, Sichuan, China. A eutrophic body of water, commonly a lake or pond has high primary productivity due to excessive nutrients and is subject to algal blooms resulting in poor water quality. The bottom waters of such bodies are commonly deficient in oxygen, ranging from hypoxic to anoxic. Eutrophic waters commonly lack fish species like trout which require cold, well- oxygenated waters. This oxygen deficiency is most apparent in shallow lakes, owing to the smaller hypolimnetic volume. The process of eutrophication may occur naturally or be the result of anthropogenic influences. [5] Eutrophic comes from the Greek eutrophos meaning well-nourished, from eu meaning good and trephein meaning to nourish[6] Hypereutrophic Hypereutrophic lakes are very nutrient-rich lakes characterized by frequent and severe nuisance algal blooms and low transparency. Hypereutrophic lakes are the most biologically productive lakes, and support large amounts of plants, fish and other animals. Hypereutrophic lakes have a visibility depth of less than 3 feet, they have greater than 40 micrograms/litre total chlorophyll and greater than 100 micrograms/liter phosphorus. The excessive algal blooms can also significantly reduce oxygen levels and prevent life from functioning at lower depths creating dead zones beneath the surface. Trophic Index Drivers Both natural and anthropogenic factors can influence a lake or other water body's Trophic Index. A water body situated in a nutrient-rich region with high Net Primary Productivity may be naturally eutrophic. Nutrients carried into water bodies from Non-point sources such as agricultural runoff, residential fertilisers, and sewage will all increase the algal biomass, and can easily cause an oligotrophic lake to become hypereutrophic. Management Targets Often, the desired Trophic Index differs between stakeholders. Water-fowl enthusiasts (e.g. duck hunters) may want a lake to be eutrophic so that it will support a large population of waterfowl. Residents, on the other hand, may want the same lake to be oligotrophic, as this is more pleasant for swimming and boating. Natural Resource agencies are generally responsible for reconciling these conflicting uses and determining what a water body's trophic index should be. See also Biomass (ecology) Eutrophication Nonpoint source pollution Secchi disk Surface runoff Trophic level Trophic level index, a similar measure used in New Zealand Water quality References 1. Note that this use of trophic levels refers to feeding dynamics, and has a much different meaning than a lake's trophic index. 2. United States Environmental Protection Agency (2007) Carlson's Trophic State Index. Aquatic Biodiversity. http://www.epa.gov/bioindicators/aquatic/carlson.html accessed 17 February, 2008. 3. Carlson, R.E. (1977) A trophic state index for lakes. Limnology and Oceanography. 22:2 361--369. 4. Carlson R.E. and J. Simpson (1996) A Coordinator's Guide to Volunteer Lake Monitoring Methods. North American Lake Management Society. 96 pp. 5. Campbell, Neil A.; Reece, Jane B. (2005). Biology. Benjamin Cummings. p. 1230 p. ISBN 0-8053-7146-X. 6. Definition of eutrophic at dictionary.com. .
Load more

Recommended publications
  • Freshwater Ecosystems and Biodiversity
    Network of Conservation Educators & Practitioners Freshwater Ecosystems and Biodiversity Author(s): Nathaniel P. Hitt, Lisa K. Bonneau, Kunjuraman V. Jayachandran, and Michael P. Marchetti Source: Lessons in Conservation, Vol. 5, pp. 5-16 Published by: Network of Conservation Educators and Practitioners, Center for Biodiversity and Conservation, American Museum of Natural History Stable URL: ncep.amnh.org/linc/ This article is featured in Lessons in Conservation, the official journal of the Network of Conservation Educators and Practitioners (NCEP). NCEP is a collaborative project of the American Museum of Natural History’s Center for Biodiversity and Conservation (CBC) and a number of institutions and individuals around the world. Lessons in Conservation is designed to introduce NCEP teaching and learning resources (or “modules”) to a broad audience. NCEP modules are designed for undergraduate and professional level education. These modules—and many more on a variety of conservation topics—are available for free download at our website, ncep.amnh.org. To learn more about NCEP, visit our website: ncep.amnh.org. All reproduction or distribution must provide full citation of the original work and provide a copyright notice as follows: “Copyright 2015, by the authors of the material and the Center for Biodiversity and Conservation of the American Museum of Natural History. All rights reserved.” Illustrations obtained from the American Museum of Natural History’s library: images.library.amnh.org/digital/ SYNTHESIS 5 Freshwater Ecosystems and Biodiversity Nathaniel P. Hitt1, Lisa K. Bonneau2, Kunjuraman V. Jayachandran3, and Michael P. Marchetti4 1U.S. Geological Survey, Leetown Science Center, USA, 2Metropolitan Community College-Blue River, USA, 3Kerala Agricultural University, India, 4School of Science, St.
    [Show full text]
  • 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).
    [Show full text]
  • 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.
    [Show full text]
  • 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.
    [Show full text]
  • 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.
    [Show full text]
  • Microbial Loop' in Stratified Systems
    MARINE ECOLOGY PROGRESS SERIES Vol. 59: 1-17, 1990 Published January 11 Mar. Ecol. Prog. Ser. 1 A steady-state analysis of the 'microbial loop' in stratified systems Arnold H. Taylor, Ian Joint Plymouth Marine Laboratory, Prospect Place, West Hoe, Plymouth PLl 3DH, United Kingdom ABSTRACT. Steady state solutions are presented for a simple model of the surface mixed layer, which contains the components of the 'microbial loop', namely phytoplankton, picophytoplankton, bacterio- plankton, microzooplankton, dissolved organic carbon, detritus, nitrate and ammonia. This system is assumed to be in equilibrium with the larger grazers present at any time, which are represented as an external mortality function. The model also allows for dissolved organic nitrogen consumption by bacteria, and self-grazing and mixotrophy of the microzooplankton. The model steady states are always stable. The solution shows a number of general properties; for example, biomass of each individual component depends only on total nitrogen concentration below the mixed layer, not whether the nitrogen is in the form of nitrate or ammonia. Standing stocks and production rates from the model are compared with summer observations from the Celtic Sea and Porcupine Sea Bight. The agreement is good and suggests that the system is often not far from equilibrium. A sensitivity analysis of the model is included. The effect of varying the mixing across the pycnocline is investigated; more intense mixing results in the large phytoplankton population increasing at the expense of picophytoplankton, micro- zooplankton and DOC. The change from phytoplankton to picophytoplankton dominance at low mixing occurs even though the same physiological parameters are used for both size fractions.
    [Show full text]
  • Trophic Control Changes with Season and Nutrient Loading in Lakes
    UC Irvine UC Irvine Previously Published Works Title Trophic control changes with season and nutrient loading in lakes. Permalink https://escholarship.org/uc/item/90c25815 Journal Ecology letters, 23(8) ISSN 1461-023X Authors Rogers, Tanya L Munch, Stephan B Stewart, Simon D et al. Publication Date 2020-08-01 DOI 10.1111/ele.13532 Peer reviewed eScholarship.org Powered by the California Digital Library University of California Ecology Letters, (2020) 23: 1287–1297 doi: 10.1111/ele.13532 LETTER Trophic control changes with season and nutrient loading in lakes Abstract Tanya L. Rogers,1 Experiments have revealed much about top-down and bottom-up control in ecosystems, but Stephan B. Munch,1 manipulative experiments are limited in spatial and temporal scale. To obtain a more nuanced Simon D. Stewart,2 understanding of trophic control over large scales, we explored long-term time-series data from 13 Eric P. Palkovacs,3 globally distributed lakes and used empirical dynamic modelling to quantify interaction strengths Alfredo Giron-Nava,4 between zooplankton and phytoplankton over time within and across lakes. Across all lakes, top- Shin-ichiro S. Matsuzaki5 and down effects were associated with nutrients, switching from negative in mesotrophic lakes to posi- 3,6 tive in oligotrophic lakes. This result suggests that zooplankton nutrient recycling exceeds grazing Celia C. Symons * pressure in nutrient-limited systems. Within individual lakes, results were consistent with a ‘sea- The peer review history for this arti- sonal reset’ hypothesis in which top-down and bottom-up interactions varied seasonally and were cle is available at https://publons.c both strongest at the beginning of the growing season.
    [Show full text]
  • Assessing the Water Quality of Lake Hawassa Ethiopia—Trophic State and Suitability for Anthropogenic Uses—Applying Common Water Quality Indices
    International Journal of Environmental Research and Public Health Article Assessing the Water Quality of Lake Hawassa Ethiopia—Trophic State and Suitability for Anthropogenic Uses—Applying Common Water Quality Indices Semaria Moga Lencha 1,2,* , Jens Tränckner 1 and Mihret Dananto 2 1 Faculty of Agriculture and Environmental Sciences, University of Rostock, 18051 Rostock, Germany; [email protected] 2 Faculty of Biosystems and Water Resource Engineering, Institute of Technology, Hawassa University, Hawassa P.O. Box 05, Ethiopia; [email protected] * Correspondence: [email protected]; Tel.: +491-521-121-2094 Abstract: The rapid growth of urbanization, industrialization and poor wastewater management practices have led to an intense water quality impediment in Lake Hawassa Watershed. This study has intended to engage the different water quality indices to categorize the suitability of the water quality of Lake Hawassa Watershed for anthropogenic uses and identify the trophic state of Lake Hawassa. Analysis of physicochemical water quality parameters at selected sites and periods was conducted throughout May 2020 to January 2021 to assess the present status of the Lake Watershed. In total, 19 monitoring sites and 21 physicochemical parameters were selected and analyzed in a laboratory. The Canadian council of ministries of the environment (CCME WQI) and weighted Citation: Lencha, S.M.; Tränckner, J.; arithmetic (WA WQI) water quality indices have been used to cluster the water quality of Lake Dananto, M. Assessing the Water Hawassa Watershed and the Carlson trophic state index (TSI) has been employed to identify the Quality of Lake Hawassa Ethiopia— trophic state of Lake Hawassa. The water quality is generally categorized as unsuitable for drinking, Trophic State and Suitability for aquatic life and recreational purposes and it is excellent to unsuitable for irrigation depending on Anthropogenic Uses—Applying the sampling location and the applied indices.
    [Show full text]
  • 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.
    [Show full text]
  • 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.
    [Show full text]
  • 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.
    [Show full text]
  • Supplement A: Assumptions and Equations in Ecopath with Ecosim Governing Equations
    Transactions of the American Fisheries Society 145:136–162, 2016 © American Fisheries Society 2016 DOI: 10.1080/00028487.2015.1069211 Supplement A: Assumptions and Equations in Ecopath with Ecosim Governing Equations The Ecopath module of EwE is a static, mass-balance ecosystem model that uses two governing equations for each species and age group (Christensen and Walters 2004). The first governing equation describes each species group’s production for a time period, i.e., production (P) is the sum of fishery catch (F), predation (M2), net migration (immigration, I, and emigration, E), biomass accumulation (BA), and mortality from other sources (‘other mortality’, M0): P = F + M2 + (I - E) + BA - M0 The second governing equation is based on the principle of conservation of matter within a group, and is designed to balance the energy flows of a biomass pool, i.e., consumption (C) equals the sum of production (P), respiration (R), and unassimilated food (U): C = P + R + U At a minimum, Ecopath requires inputs of diet composition (DCi,j, where i is predator and j is prey), fishery catch (Yi), and three of the following four parameters for each model group (i): biomass (Bi), production-to-biomass ratio (Pi/Bi), consumption-to-biomass ratio (Qi/Bi), and the ecotrophic efficiency (EEi, the fraction of the production that is used in the system and does not move directly to the detritus pool). Mass-balance principles are then used to estimate the fourth parameter. P/B is the annual production rate of the population in Ecopath. Under equilibrium conditions, the P/B ratio of fish is equivalent to its total annual instantaneous mortality (Z) (Allen 1971).
    [Show full text]