Coral-Reef-Derived Dimethyl Sulfide and the Climatic Impact of the Loss Of

Total Page:16

File Type:pdf, Size:1020Kb

Coral-Reef-Derived Dimethyl Sulfide and the Climatic Impact of the Loss Of Atmos. Chem. Phys., 21, 5883–5903, 2021 https://doi.org/10.5194/acp-21-5883-2021 © Author(s) 2021. This work is distributed under the Creative Commons Attribution 4.0 License. Coral-reef-derived dimethyl sulfide and the climatic impact of the loss of coral reefs Sonya L. Fiddes1,2,3,a, Matthew T. Woodhouse3, Todd P. Lane4, and Robyn Schofield4 1Australian-German Climate and Energy College, University of Melbourne, Parkville, Australia 2ARC Centre of Excellence for Climate System Science, School of Earth Sciences, University of Melbourne, Parkville, Australia 3Climate Science Centre, Oceans and Atmosphere, Commonwealth Scientific and Industrial Research Organisation, Aspendale, Australia 4ARC Centre of Excellence for Climate Extremes, School of Earth Sciences, University of Melbourne, Parkville, Australia anow at: Australian Antarctic Program Partnership, Institute of Marine and Antarctic Studies, University of Tasmania, Hobart, Australia Correspondence: Sonya L. Fiddes (sonya.fi[email protected]) Received: 9 October 2020 – Discussion started: 27 October 2020 Revised: 3 March 2021 – Accepted: 17 March 2021 – Published: 20 April 2021 Abstract. Dimethyl sulfide (DMS) is a naturally occurring sponses are found to have no robust effect on regional climate aerosol precursor gas which plays an important role in the via direct and indirect aerosol effects. This work emphasises global sulfur budget, aerosol formation and climate. While the complexities of the aerosol–climate system, and the limi- DMS is produced predominantly by phytoplankton, recent tations of current modelling capabilities are highlighted, in observational literature has suggested that corals and their particular surrounding convective responses to changes in symbionts produce a comparable amount of DMS, which aerosol. In conclusion, we find no robust evidence that coral- is unaccounted for in models. It has further been hypothe- reef-derived DMS influences global and regional climate. sised that the coral reef source of DMS may modulate re- gional climate. This hypothesis presents a particular concern given the current threat to coral reefs under anthropogenic climate change. In this paper, a global climate model with 1 Introduction online chemistry and aerosol is used to explore the influence of coral-reef-derived DMS on atmospheric composition and Marine organisms (phytoplankton, algae) are known to pro- climate. A simple representation of coral-reef-derived DMS duce the chemical dimethyl sulfoniopropionate (DMSP). In is developed and added to a common DMS surface water cli- the ocean, DMSP experiences enzymatic cleavage, forming matology, resulting in an additional flux of 0.3 Tg yr−1 S, or dimethyl sulfide (DMS; Yoch, 2002; see Fig.1, point 1), 1.7 % of the global sulfur flux from DMS. By comparing the which can then be released into the atmosphere (2). At- differences between both nudged and free-running ensem- mospheric DMS (DMSa) can undergo a series of chemical ble simulations with and without coral-reef-derived DMS, reactions to become a sulfate aerosol (3). When in suffi- the influence of coral-reef-derived DMS on regional climate ciently large abundance (4), these sulfate aerosols can im- is quantified. In the Maritime Continent–Australian region, pact aerosol loading and cloud properties, altering the ra- where the highest density of coral reefs exists, a small de- diation budget directly (5) and indirectly (6) and having a crease in nucleation- and Aitken-mode aerosol number con- cooling effect (7). This effect has been hypothesised to form centration and mass is found when coral reef DMS emis- a short-term bioregulatory negative feedback system, known sions are removed from the system. However, these small re- as the CLAW (Charlson, Lovelock, Andreae and Warren) hy- pothesis (Charlson et al., 1987), whereby marine organisms Published by Copernicus Publications on behalf of the European Geosciences Union. 5884 S. L. Fiddes et al.: Influence of coral reefs on climate can alter their environment when stressed. This hypothesis (Swan et al., 2012; Fischer and Jones, 2012; Hopkins et al., remains unproven, and arguments against it cite the com- 2016; Swan et al., 2017). Of interest to this study are the plexity and non-linearity of the DMS–climate system (Quinn findings from Hopkins et al.(2016), where the effect of tidal and Bates, 2011; Green and Hatton, 2014). Nevertheless, at exposure on three Indo-Pacific coral species was studied in longer timescales, global modelling studies have shown that laboratory experiments. From their results, Hopkins et al. −2 −1 marine-derived DMS plays an important role in maintaining (2016) extrapolate a fluxDMS of 9–35 µmol m d over the current large-scale climate (Thomas et al., 2010; Wood- coral reefs from Acropora cf. horrida, while an additional 5 house et al., 2010; Gabric et al., 2013; Mahajan et al., 2015), and 8 µmol m−2 d−1 can be estimated from two other species providing global cooling via direct and indirect aerosol ef- in their experiments (P. cylindrica and S. hystrix.). These es- fects of up to 0.45 ◦C(Fiddes et al., 2018) when compared timates are equivalent to a total of 709–1548 µg m−2 d−1 of to a world in which no marine DMS exists. Our previous sulfur (if all species are present) and in this work is further paper (Fiddes et al., 2018) describes these studies, DMS sur- extrapolated to global coral reef coverage (approximately face water climatologies and flux parameterisations in more 284 300 km2), giving 0.074–0.16 Tg yr−1 of sulfur. Whilst detail. these extrapolations are highly speculative in terms of arti- Many global DMS–climate modelling studies have also ficial laboratory experiments, estimated exposure time and considered DMS under future scenarios (Bopp et al., 2004; coverage of coral reefs, and they account for just three Indo- Gabric et al., 2004; Kloster et al., 2007; Cameron-Smith Pacific species of coral and only DMS produced during tidal et al., 2011; Six et al., 2013; Grandey and Wang, 2015; stress, the Hopkins et al.(2016) estimations were the first to Schwinger et al., 2017). However, considering our under- attempt to quantify the large-scale flux of coral-reef-derived standing of DMS in the current climate remains uncertain, DMS. the aforementioned studies do not provide a clear consen- Following these observed results, numerous studies have sus on how DMS production may respond to a warming cli- made links to coral DMS, aerosol formation, cloud cover mate. With this in mind, better knowledge of current sources and/or sea surface temperatures (SSTs) (Modini et al., 2009; of DMS is important to further our understanding of DMS– Deschaseaux et al., 2012; Leahy et al., 2013; Swan et al., climate interaction now and into the future. 2017; Jones et al., 2017; Cropp et al., 2018; Jackson et al., One such source of DMS that is currently unaccounted 2018, 2020b). Jones(2013), Jones et al.(2017) and Cropp for in climate modelling is coral reefs. Recent studies have et al.(2018) further suggest that coral reefs participate in shown that corals, coral symbionts, and coral by-products bioregulatory feedback as suggested by the CLAW hypothe- (e.g. mucus) produce large amounts of DMSP (Broad- ses. Most of these studies do not explicitly account for the bent et al., 2002; Broadbent and Jones, 2004; Jones and complexity of the DMS–climate system and its significant Trevena, 2005; Jones et al., 2007; Burdett et al., 2015; non-linearities (see Thomas et al., 2011; Quinn and Bates, Jackson et al., 2020a). Of note for this work, Jones et al. 2011; Green and Hatton, 2014; Fiddes et al., 2018). In addi- (2018) have summarised reports of fluxDMS values of 0– tion, deducing a climatic impact of one aerosol species using 4906 µg m−2 d−1 and a mean of 205 µg m−2 d−1 in summer observations alone is fraught with co-varying and confound- and 0.6–481 µg m−2 d−1 with a mean of 77 µg m−2 d−1 over ing influences from other aerosol species. These complexities winter over the Great Barrier Reef (GBR). Jones et al.(2018) can only be addressed through modelling studies; however also suggest that total emissions from the GBR are equivalent no modelling study has included coral-reef-derived DMS as to 0.02 Tg yr−1 of sulfur, noting that total global sulfur flux a source of sulfur to date. from DMS is estimated to be between 9–35 Tg yr−1 (Belviso To add urgency to this problem, coral reef ecosystems et al., 2004; Elliott, 2009; Woodhouse et al., 2010; Tesdal globally are facing dire risk due to anthropogenic climate et al., 2016; Fiddes et al., 2018) and that DMS makes up change (Hughes et al., 2017, 2018). The IPCC special re- approximately one-fifth of the global sulfur budget (Sheng port on climate change (IPCC, 2018) states that under 1.5 ◦C et al., 2015). The Jones et al.(2018) coral reef flux estimation warming, 70 %–90 % of coral reefs will be extinct. The risk has been made from measurements both over coral reefs and to coral reefs is twofold; increasing sea surface tempera- in the GBR lagoon and also includes an estimate of the addi- tures are causing more frequent mass coral bleaching events tional flux from tropical cyclones. The tropical cyclone emis- (Hughes et al., 2017; King et al., 2017), whilst increas- sion has been calculated (not observed) using the Liss and ing ocean acidification is causing reduced calcification and Merlivat(1986) flux parameterisation, taking into account growth of coral species (Hoegh-Guldberg et al., 2017; Mag- average wind speeds of tropical cyclones and accounting for nan et al., 2016). Whilst the death of global coral reefs due approximately five cyclone days per year in the region.
Recommended publications
  • A Quick Guide to Southeast Florida's Coral Reefs
    A Quick Guide to Southeast Florida’s Coral Reefs DAVID GILLIAM NATIONAL CORAL REEF INSTITUTE NOVA SOUTHEASTERN UNIVERSITY Spring 2013 Prepared by the Land-based Sources of Pollution Technical Advisory Committee (TAC) of the Southeast Florida Coral Reef Initiative (SEFCRI) BRIAN WALKER NATIONAL CORAL REEF INSTITUTE, NOVA SOUTHEASTERN Southeast Florida’s coral-rich communities are more valuable than UNIVERSITY the Spanish treasures that sank nearby. Like the lost treasures, these amazing reefs lie just a few hundred yards off the shores of Martin, Palm Beach, Broward and Miami-Dade Counties where more than one-third of Florida’s 19 million residents live. Fishing, diving, and boating help attract millions of visitors to southeast Florida each year (30 million in 2008/2009). Reef-related expen- ditures generate $5.7 billion annually in income and sales, and support more than 61,000 local jobs. Such immense recreational activity, coupled with the pressures of coastal development, inland agriculture, and robust cruise and commercial shipping industries, threaten the very survival of our reefs. With your help, reefs will be protected from local stresses and future generations will be able to enjoy their beauty and economic benefits. Coral reefs are highly diverse and productive, yet surprisingly fragile, ecosystems. They are built by living creatures that require clean, clear seawater to settle, mature and reproduce. Reefs provide safe havens for spectacular forms of marine life. Unfortunately, reefs are vulnerable to impacts on scales ranging from local and regional to global. Global threats to reefs have increased along with expanding ART SEITZ human populations and industrialization. Now, warming seawater temperatures and changing ocean chemistry from carbon dioxide emitted by the burning of fossil fuels and deforestation are also starting to imperil corals.
    [Show full text]
  • Effects of Eutrophication on Stream Ecosystems
    EFFECTS OF EUTROPHICATION ON STREAM ECOSYSTEMS Lei Zheng, PhD and Michael J. Paul, PhD Tetra Tech, Inc. Abstract This paper describes the effects of nutrient enrichment on the structure and function of stream ecosystems. It starts with the currently well documented direct effects of nutrient enrichment on algal biomass and the resulting impacts on stream chemistry. The paper continues with an explanation of the less well documented indirect ecological effects of nutrient enrichment on stream structure and function, including effects of excess growth on physical habitat, and alterations to aquatic life community structure from the microbial assemblage to fish and mammals. The paper also dicusses effects on the ecosystem level including changes to productivity, respiration, decomposition, carbon and other geochemical cycles. The paper ends by discussing the significance of these direct and indirect effects of nutrient enrichment on designated uses - especially recreational, aquatic life, and drinking water. 2 1. Introduction 1.1 Stream processes Streams are all flowing natural waters, regardless of size. To understand the processes that influence the pattern and character of streams and reduce natural variation of different streams, several stream classification systems (including ecoregional, fluvial geomorphological, and stream order classification) have been adopted by state and national programs. Ecoregional classification is based on geology, soils, geomorphology, dominant land uses, and natural vegetation (Omernik 1987). Fluvial geomorphological classification explains stream and slope processes through the application of physical principles. Rosgen (1994) classified stream channels in the United States into seven major stream types based on morphological characteristics, including entrenchment, gradient, width/depth ratio, and sinuosity in various land forms.
    [Show full text]
  • Verifiable Semantic Difference Languages
    Verifiable Semantic Difference Languages Thibaut Girka David Mentré Yann Régis-Gianas Mitsubishi Electric R&D Centre Mitsubishi Electric R&D Centre Univ Paris Diderot, Sorbonne Paris Europe Europe Cité, IRIF/PPS, UMR 8243 CNRS, PiR2, Rennes, France Rennes, France INRIA Paris-Rocquencourt Paris, France ABSTRACT 1 INTRODUCTION Program differences are usually represented as textual differences Let x be a strictly positive natural number. Consider the following on source code with no regard to its syntax or its semantics. In two (almost identical) imperative programs: this paper, we introduce semantic-aware difference languages. A difference denotes a relation between program reduction traces. A s = 0 ; 1 s = 0 ; 1 difference language for the toy imperative programming language d = x ; 2 d = x − 1 ; 2 while (d>0) { 3 while (d>0) { 3 Imp is given as an illustration. i f (x%d== 0) 4 i f (x%d== 0) 4 To certify software evolutions, we want to mechanically verify s = s + d ; 5 s = s + d ; 5 − − that a difference correctly relates two given programs. Product pro- d = d 1 ; 6 d = d 1 ; 6 } 7 } 7 grams and correlating programs are effective proof techniques for s = s − x 8 8 relational reasoning. A product program simulates, in the same programming language as the compared programs, a well-chosen The program P1 (on the left) stores in s the sum of the proper interleaving of their executions to highlight a specific relation be- divisors of the integer x. To that end, it iterates over the integers tween their reduction traces. While this approach enables the use from x to 1 using the variable d and accumulates in the variable s of readily-available static analysis tools on the product program, it the values of d that divide x.
    [Show full text]
  • Microscale Ecology Regulates Particulate Organic Matter Turnover in Model Marine Microbial Communities
    ARTICLE DOI: 10.1038/s41467-018-05159-8 OPEN Microscale ecology regulates particulate organic matter turnover in model marine microbial communities Tim N. Enke1,2, Gabriel E. Leventhal 1, Matthew Metzger1, José T. Saavedra1 & Otto X. Cordero1 The degradation of particulate organic matter in the ocean is a central process in the global carbon cycle, the mode and tempo of which is determined by the bacterial communities that 1234567890():,; assemble on particle surfaces. Here, we find that the capacity of communities to degrade particles is highly dependent on community composition using a collection of marine bacteria cultured from different stages of succession on chitin microparticles. Different particle degrading taxa display characteristic particle half-lives that differ by ~170 h, comparable to the residence time of particles in the ocean’s mixed layer. Particle half-lives are in general longer in multispecies communities, where the growth of obligate cross-feeders hinders the ability of degraders to colonize and consume particles in a dose dependent manner. Our results suggest that the microscale community ecology of bacteria on particle surfaces can impact the rates of carbon turnover in the ocean. 1 Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA. 2 Department of Environmental Systems Science, ETH Zurich, Zürich 8092, Switzerland. Correspondence and requests for materials should be addressed to O.X.C. (email: [email protected]) NATURE COMMUNICATIONS | (2018) 9:2743 | DOI: 10.1038/s41467-018-05159-8 | www.nature.com/naturecommunications 1 ARTICLE NATURE COMMUNICATIONS | DOI: 10.1038/s41467-018-05159-8 earning how the composition of ecological communities the North Pacific gyre20.
    [Show full text]
  • Plankton Community Composition, Organic Carbon and Thorium-234 Particle Size Distributions, and Particle Export in the Sargasso Sea
    Journal of Marine Research, 67, 845–868, 2009 Plankton community composition, organic carbon and thorium-234 particle size distributions, and particle export in the Sargasso Sea by H. S. Brew1, S. B. Moran1,2, M. W. Lomas3 and A. B. Burd4 ABSTRACT Measurements of plankton community composition (eight planktonic groups), particle size- fractionated (10, 20, 53, 70, and 100-␮m Nitex screens) distributions of organic carbon (OC) and 234Th, and particle export of OC and 234Th are reported over a seasonal cycle (2006–2007) from the Bermuda Atlantic Time-Series (BATS) site. Results indicate a convergence of the particle size distributions of OC and 234Th during the winter-spring bloom period (January–March, 2007). The observed convergence of these particle size distributions is directly correlated to the depth-integrated abundance of autotrophic pico-eukaryotes (r ϭ 0.97, P Ͻ 0.05) and, to a lesser extent, Synechococcus (r ϭ 0.85, P ϭ 0.14). In addition, there are positive correlations between the sediment trap flux of OC and 234Th at 150 m and the depth-integrated abundance of pico-eukaryotes (r ϭ 0.94, P ϭ 0.06 for OC, and r ϭ 0.98, P Ͻ 0.05 for 234Th) and Synechococcus (r ϭ 0.95, P ϭ 0.05 for OC, and r ϭ 0.94, P ϭ 0.06 for 234Th). An implication of these observations and recent modeling studies (Richardson and Jackson, 2007) is that, although small in size, pico-plankton may influence large particle export from the surface waters of the subtropical Atlantic.
    [Show full text]
  • An Introduction to Programming in Simula
    An Introduction to Programming in Simula Rob Pooley This document, including all parts below hyperlinked directly to it, is copyright Rob Pooley ([email protected]). You are free to use it for your own non-commercial purposes, but may not copy it or reproduce all or part of it without including this paragraph. If you wish to use it for gain in any manner, you should contact Rob Pooley for terms appropriate to that use. Teachers in publicly funded schools, universities and colleges are free to use it in their normal teaching. Anyone, including vendors of commercial products, may include links to it in any documentation they distribute, so long as the link is to this page, not any sub-part. This is an .pdf version of the book originally published by Blackwell Scientific Publications. The copyright of that book also belongs to Rob Pooley. REMARK: This document is reassembled from the HTML version found on the web: https://web.archive.org/web/20040919031218/http://www.macs.hw.ac.uk/~rjp/bookhtml/ Oslo 20. March 2018 Øystein Myhre Andersen Table of Contents Chapter 1 - Begin at the beginning Basics Chapter 2 - And end at the end Syntax and semantics of basic elements Chapter 3 - Type cast actors Basic arithmetic and other simple types Chapter 4 - If only Conditional statements Chapter 5 - Would you mind repeating that? Texts and while loops Chapter 6 - Correct Procedures Building blocks Chapter 7 - File FOR future reference Simple input and output using InFile, OutFile and PrintFile Chapter 8 - Item by Item Item oriented reading and writing and for loops Chapter 9 - Classes as Records Chapter 10 - Make me a list Lists 1 - Arrays and simple linked lists Reference comparison Chapter 11 - Like parent like child Sub-classes and complex Boolean expressions Chapter 12 - A Language with Character Character handling, switches and jumps Chapter 13 - Let Us See what We Can See Inspection and Remote Accessing Chapter 14 - Side by Side Coroutines Chapter 15 - File For Immediate Use Direct and Byte Files Chapter 16 - With All My Worldly Goods..
    [Show full text]
  • A View of Physical Mechanisms for Transporting Harmful Algal Blooms to T Massachusetts Bay ⁎ Yu Zhanga, , Changsheng Chenb, Pengfei Xueb,1, Robert C
    Marine Pollution Bulletin 154 (2020) 111048 Contents lists available at ScienceDirect Marine Pollution Bulletin journal homepage: www.elsevier.com/locate/marpolbul A view of physical mechanisms for transporting harmful algal blooms to T Massachusetts Bay ⁎ Yu Zhanga, , Changsheng Chenb, Pengfei Xueb,1, Robert C. Beardsleyc, Peter J.S. Franksd a College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, PR China b School for Marine Science and Technology, University of Massachusetts-Dartmouth, New Bedford, MA 02744, USA c Department of Physical Oceanography, Woods Hole Oceanographic Institution, Woods Hole, MA 02543, USA d Integrative Oceanography Division, Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA 92093, USA ARTICLE INFO ABSTRACT Keywords: Physical dynamics of Harmful Algal Blooms in Massachusetts Bay in May 2005 and 2008 were examined by the Harmful algal bloom simulated results. Reverse particle-tracking experiments suggest that the toxic phytoplankton mainly originated Massachusetts Bay from the Bay of Fundy in 2005 and the western Maine coastal region and its local rivers in 2008. Mechanism Ocean modeling studies suggest that the phytoplankton were advected by the Gulf of Maine Coastal Current (GMCC). In 2005, Lagrangian flow Nor'easters increased the cross-shelf surface elevation gradient over the northwestern shelf. This intensified the Eastern and Western MCC to form a strong along-shelf current from the Bay of Fundy to Massachusetts Bay. In 2008, both Eastern and Western MCC were established with a partial separation around Penobscot Bay before the outbreak of the bloom. The northeastward winds were too weak to cancel or reverse the cross-shelf sea surface gradient, so that the Western MCC carried the algae along the slope into Massachusetts Bay.
    [Show full text]
  • Open Ocean Dead-Zones in the Tropical J I Northeast Atlantic
    Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Biogeosciences Discuss., 11, 17391–17411, 2014 www.biogeosciences-discuss.net/11/17391/2014/ doi:10.5194/bgd-11-17391-2014 BGD © Author(s) 2014. CC Attribution 3.0 License. 11, 17391–17411, 2014 This discussion paper is/has been under review for the journal Biogeosciences (BG). Open ocean Please refer to the corresponding final paper in BG if available. dead-zones Open ocean dead-zone in the tropical J. Karstensen et al. North Atlantic Ocean Title Page 1 1 1 1 1 2 J. Karstensen , B. Fiedler , F. Schütte , P. Brandt , A. Körtzinger , G. Fischer , Abstract Introduction R. Zantopp1, J. Hahn1, M. Visbeck1, and D. Wallace3 Conclusions References 1GEOMAR Helmholtz Centre for Ocean Research Kiel, Kiel, Germany Tables Figures 2Faculty of Geosciences and MARUM, University of Bremen, Bremen, Germany 3Halifax Marine Research Institute (HMRI), Halifax, Canada J I Received: 3 November 2014 – Accepted: 13 November 2014 – Published: 12 December 2014 J I Correspondence to: J. Karstensen ([email protected]) Back Close Published by Copernicus Publications on behalf of the European Geosciences Union. Full Screen / Esc Printer-friendly Version Interactive Discussion 17391 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Abstract BGD The intermittent appearances of low oxygen environments are a particular thread for marine ecosystems. Here we present first observations of unexpected low (< 11, 17391–17411, 2014 2 µmolkg−1) oxygen environments in the open waters of the eastern tropical North −1 5 Atlantic, a region where typically oxygen concentration does not fall below 40 µmolkg . Open ocean The low oxygen zones are created just below the mixed-layer, in the euphotic zone of dead-zones high productive cyclonic and anticyclonic-modewater eddies.
    [Show full text]
  • RML Algol 60 Compiler Accepts the Full ASCII Character Set Described in the Manual
    I I I · lL' I I 1UU, Alsol 60 CP/M 5yst.. I I , I I '/ I I , ALGOL 60 VERSION 4.8C REI.!AS!- NOTE I I I I CP/M Vers1on·2 I I When used with CP/M version 2 the Algol Ifste. will accept disk drive Dames extending from A: to P: I I I ASSEMBLY CODE ROUTINES I I .'n1~ program CODE.ALG and CODE.ASe 1s an aid to users who wish ·to add I their own code routines to the runtime system. The program' produc:es an I output file which contains a reconstruction of the INPUT, OUTPUT, IOC and I ERROR tables described in the manual. 1111s file forms the basis of an I assembly code program to which users may edit in their routines... Pat:ts I not required may be removed as desired. The resulting program should I then be assembled and overlaid onto the runtime system" using DDT, the I resulti;lg code being SAVEd as a new runtime system. It 1s important that. I the CODE program be run using the version of the runtimesY$tem to. which I the code routines are to be linked else the tables produced DUly, be·\, I incompatible. - I I I I Another example program supplied. 1. QSORT. the sortiDI pro~edure~, I described in the manual. I I I I I I I I I I , I I I -. I I 'It I I I I I I I I I I I ttKL Aleol 60 C'/M Systea I LONG INTEGER ALGOL Arun-L 1s a version of the RML zao Algol system 1nwh1c:h real variables are represented, DOt in the normal mantissalexponent form but rather as 32 .bit 2 s complement integers.
    [Show full text]
  • Workplace Learning Connection Annual Report 2019-20
    2019 – 2020 ANNUAL REPORT SERVING SCHOOLS, STUDENTS, EMPLOYERS, AND COMMUNITIES IN BENTON, CEDAR, IOWA, JOHNSON, JONES, LINN, AND WASHINGTON COUNTIES Connecting today’s students to tomorrow’s careers LINN COUNTY JONES COUNTY IOWA COUNTY CENTER REGIONAL CENTER REGIONAL CENTER 200 West St. 1770 Boyson Rd. 220 Welter Dr. Williamsburg, Iowa 52361 Hiawatha, Iowa 52233 Monticello, Iowa 52310 866-424-5669 319-398-1040 855-467-3800 KIRKWOOD REGIONAL CENTER WASHINGTON COUNTY AT THE UNIVERSITY OF IOWA REGIONAL CENTER 2301 Oakdale Blvd. 2192 Lexington Blvd. Coralville, Iowa 52241 Washington, Iowa 52353 319-887-3970 855-467-3900 BENTON COUNTY CENTER CEDAR COUNTY CENTER 111 W. 3rd St. 100 Alexander Dr., Suite 2 WORKPLACE LEARNING Vinton, Iowa 52349 Tipton, Iowa 52772 CONNECTION 866-424-5669 855-467-3900 2019 – 2020 AT A GLANCE Thank you to all our contributors, supporters, and volunteers! Workplace Learning Connection uses a diverse funding model that allows all partners to sustain their participation in an equitable manner. Whether a partners’ interest are student career development, future workforce development, or regional economic development, all funds provide age-appropriate career awareness and exploration services matching the mission of WLC and our partners. Funding the Connections… 2019 – 2020 Revenue Sources Kirkwood Community College (General Fund) $50,000 7% State and Federal Grants (Kirkwood: Perkins, WTED, IIG) $401,324 54% Grant Wood Area Education Agency $40,000 5% K through 12 School Districts Fees for Services $169,142 23% Contributions,
    [Show full text]
  • Think Complexity: Exploring Complexity Science in Python
    Think Complexity Version 2.6.2 Think Complexity Version 2.6.2 Allen B. Downey Green Tea Press Needham, Massachusetts Copyright © 2016 Allen B. Downey. Green Tea Press 9 Washburn Ave Needham MA 02492 Permission is granted to copy, distribute, transmit and adapt this work under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License: https://thinkcomplex.com/license. If you are interested in distributing a commercial version of this work, please contact the author. The LATEX source for this book is available from https://github.com/AllenDowney/ThinkComplexity2 iv Contents Preface xi 0.1 Who is this book for?...................... xii 0.2 Changes from the first edition................. xiii 0.3 Using the code.......................... xiii 1 Complexity Science1 1.1 The changing criteria of science................3 1.2 The axes of scientific models..................4 1.3 Different models for different purposes............6 1.4 Complexity engineering.....................7 1.5 Complexity thinking......................8 2 Graphs 11 2.1 What is a graph?........................ 11 2.2 NetworkX............................ 13 2.3 Random graphs......................... 16 2.4 Generating graphs........................ 17 2.5 Connected graphs........................ 18 2.6 Generating ER graphs..................... 20 2.7 Probability of connectivity................... 22 vi CONTENTS 2.8 Analysis of graph algorithms.................. 24 2.9 Exercises............................. 25 3 Small World Graphs 27 3.1 Stanley Milgram......................... 27 3.2 Watts and Strogatz....................... 28 3.3 Ring lattice........................... 30 3.4 WS graphs............................ 32 3.5 Clustering............................ 33 3.6 Shortest path lengths...................... 35 3.7 The WS experiment....................... 36 3.8 What kind of explanation is that?............... 38 3.9 Breadth-First Search.....................
    [Show full text]
  • Coral 66 Language Reference Makrjal
    CORAL 66 LANGUAGE REFERENCE MAKRJAL The Centre for Computing History Nl www.CompuUngHistofy.ofg.uk \/ k > MICRO FOCUS CORAL 66 LANGUAGE REFERENCE MANUAL Version 3 Micro Focus Ltd. Issue 2 March 1982 Not to be copied without the consent of Micro Focus Ltd. This language definition reproduces material from the British Standard BS5905 which is hereby acknowledged as a source. / \ / N Micro Focus Ltd. 58,Acacia Rood, St. Johns Wbod, MICRO FOCUS London NW8 6AG Telephones: 017228843/4/5/6/7 Telex: 28536 MICROFG CX)PYRI(fflT 1981, 1982 by Micro Focus Ltd. ii CORAL 66 LANGUAGE REFERENCE MANUAL AMENDMENT RECORD AMENDMENT DATED INSERTED BY SIGNATURE DATE NUMBER iii PREFACE This manual defines the programming language CORAL 66 as implemented in Version 3 of the CORAL compilers known as RCC80 and RCC86. Now that British Standard BS5905 has become the main source for CORAL implementation its structure and style have been adopted. Con5)ared to previous version's of the RCC compilers. Version 3 incorporates 'TABLE' and 'OVERLAY', and allows additional forms of Real numbers in line with the British Standard. Coiiq}iler error reporting has been .modified slightly - in particular all error messages now have identifying numbers and are listed in appendices to the operating manuals. Micro Focus has now assumed direct responsibility for production of all RCC CORAL manuals and believes that this will offer users a better service than has been possible in the past. iv AUDIENCE This manual is intended as a description of CORAL 66 for reference and assumes familiarity with use of the language.
    [Show full text]