PREFACE Ecosystems Can Be Predictable, Or They Can Change In
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David Schindler, 5 William H. Schlesinger, 6 Daniel Simberloff, 7
R EPORTS Forecasting Agriculturally Driven Global Environmental Change David Tilman,1* Joseph Fargione,1 Brian Wolff,1 Carla D’Antonio,2 Andrew Dobson,3 Robert Howarth,4 David Schindler,5 William H. Schlesinger,6 Daniel Simberloff,7 Deborah Swackhamer8 During the next 50 years, which is likely to be the final period of rapid agri- cultural expansion, demand for food by a wealthier and 50% larger global population will be a major driver of global environmental change. Should past dependences of the global environmental impacts of agriculture on human population and consumption continue, 109 hectares of natural ecosystems would be converted to agriculture by 2050. This would be accompanied by 2.4- to 2.7-fold increases in nitrogen- and phosphorus-driven eutrophication of terrestrial, freshwater, and near-shore marine ecosystems, and comparable increases in pesticide use. This eutrophication and habitat destruction would cause unprecedented ecosystem simplification, loss of ecosystem services, and species extinctions. Significant scientific advances and regulatory, technolog- ical, and policy changes are needed to control the environmental impacts of agricultural expansion. During the first 35 years of the Green Revolu- ecosystems by the use and release of limiting tion, global grain production doubled, greatly resources that influence ecosystem functioning reducing food shortages, but at high environ- (nitrogen, phosphorus, and water), release of mental cost (1–5). In addition to its effects on pesticides, and conversion of natural ecosys- greenhouse gases (1, 6, 7), agriculture affects tems to agriculture. These sources of global change may rival climate change in environ- 1Department of Ecology, Evolution and Behavior, Uni- mental and societal impacts (2, 8). -
Profile of Stephen R. Carpenter
PROFILE Profile of Stephen R. Carpenter hether you are a fisher- man, a kayaker, or just a lover of the outdoors, the sight—and smell—of a Wscummy, algae-covered lake may not be particularly appealing. For Stephen R. Carpenter, who is all of the above as well as a renowned lake ecologist, the problems associated with this algae buildup, or eutrophication, go far deeper than simple aesthetics. ‘‘Eu- trophication is a significant environmen- tal problem that can impact humans on a recreational, economic, and even pub- lic health level,’’ says Carpenter, ‘‘and it’s likely to intensify in the coming decades due to increases in human pop- ulation, demand for more food, land conversion, and fertilizer use.’’ Carpenter, the S. A. Forbes Professor of Zoology and Halverson Professor of Limnology at the University of Wiscon- sin–Madison (Madison, WI), has studied freshwater ecology for over 30 years. Stephen R. Carpenter and algae on Lake Mendota, WI. His multitude of research interests in- clude eutrophication, aquatic food webs, nutrient cycling, and ecological econom- outdoors at an early age. Carpenter was an aquatic systems ecologist, and ics. Beyond his research and teaching, spent most of his youth in Bethesda, that field really captured my imagination.’’ Carpenter also has, among other activi- MD. ‘‘It was a much smaller place back Carpenter performed undergraduate ties, served on numerous National Sci- then,’’ he says. ‘‘Bethesda was at the research for Fisher, who specialized in ence Foundation (NSF) advisory panels, urban fringe of DC. Everything beyond stream ecology, and Carpenter pub- been President of the Ecological Society that was rural.’’ His father, Richard, was lished his first paper on the primary of America (2001–2002), and served as a chemist, so there was always a lot of production of macrophytes (rooted the Chair of the Beijer Institute of Eco- science discussion in the household. -
Model-Free Forecasting Outperforms the Correct Mechanistic Model for Simulated and Experimental Data
Model-free forecasting outperforms the correct mechanistic model for simulated and experimental data Charles T. Perrettia,1, Stephan B. Munchb, and George Sugiharaa aScripps Institution of Oceanography, University of California at San Diego, La Jolla, CA 92093; and bFisheries Ecology Division, Southwest Fisheries Science Center, Santa Cruz, CA 95060 Edited by Peter J. Bickel, University of California, Berkeley, CA, and approved January 10, 2013 (received for review September 14, 2012) Accurate predictions of species abundance remain one of the most ARMA time series models have been used extensively in ecology; vexing challenges in ecology. This observation is perhaps unsurpris- recent examples include forecasting quasi-extinction risk (10), ing, because population dynamics are often strongly forced and investigating the effects of climate change on fisheries (11), and highly nonlinear. Recently, however, numerous statistical techni- detecting critical thresholds in ecosystem dynamics (12). SSR ques have been proposed for fitting highly parameterized mecha- methods have been less pervasive in ecology (13, 14), although nistic models to complex time series, potentially providing the they are ubiquitous in many other scientific disciplines for de- machinery necessary for generating useful predictions. Alterna- scribing stochastic nonlinear systems (15). tively, there is a wide variety of comparatively simple model-free Here, we pose a rather conservative challenge and ask whether forecasting methods that could be used to predict abundance. Here a correctly specified mechanistic model, fit with commonly used we pose a rather conservative challenge and ask whether a correctly statistical techniques, can provide better forecasts than simple specified mechanistic model, fit with commonly used statistical tech- niques, can provide better forecasts than simple model-free meth- model-free methods for ecological systems with noisy nonlinear ods for ecological systems with noisy nonlinear dynamics. -
Development and Application of a Landscape-Based Lake Typology for the Muskoka River Watershed, Ontario, Canada
Development and application of a landscape-based lake typology for the Muskoka River Watershed, Ontario, Canada by Rachel Anne Plewes A thesis submitted to the Faculty of Graduate and Postdoctoral Affairs in partial fulfillment of the requirements for the degree of Master of Science in Geography Carleton University Ottawa, Ontario © 2015, Rachel Anne Plewes ABSTRACT Lake management typologies have been used successfully in many parts of Europe, but their use in Canada has been limited. In this study, a lake typology was developed for 650 lakes within the Muskoka River Watershed (MRW), Ontario, Canada, to quantify freshwater, terrestrial, and human landscape influences on water quality (Ca, pH, TP and DOC). Five distinct lake types were identified, using a hierarchical system based on three broad physiographic regions within the MRW, and lake and catchment morphometrics derived through digital terrain analysis. The three regions exhibited significantly different DOC concentrations (F=15.85; p<0.001), whereas the lake types had significantly different TP concentrations (F=12.88, p<0.001). Type-specific reference conditions were used to identify lakes affected by human activities that may be in need of restoration due to high TP concentrations. Overall, this thesis demonstrates the applicability of new and emerging landscape modelling tools for lake classification and management in Ontario, Canada. ii ACKNOWLEDGMENTS Firstly, I would like to thank my supervisor Dr. Murray C. Richardson for his guidance and support throughout the past 2 years. Additionally, I appreciate all of Dr. Derek Mueller’s feedback on the drafts of this thesis. I am grateful for the guidance I received from Dr. -
The Nfluence of Land Use and the Catchment Properties
THE INFLUENCE OF LAND USE AND THE CATCHMENT PROPERTIES ON THE TROPHIC STATUS OF SHALLOW LAKES IN TURKEY A THESIS SUBMITTED TO THE GRADUATE SCHOOL OF NATURAL AND APPLIED SCIENCES OF MIDDLE EAST TECHNICAL UNIVERSITY BY SAADET PEREN TUZKAYA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE IN BIOLOGY FEBRUARY 2015 Approval of the thesis: THE INFLUENCE OF LAND USE AND THE CATCHMENT PROPERTIES ON THE TROPHIC STATUS OF SHALLOW LAKES IN TURKEY submitted by SAADET PEREN TUZKAYA in partial fulfillment of the requirements for the degree of Master of Science in Biology Department, Middle East Technical University by, Prof. Dr. Gülbin DURAL ÜNVER ________________ Dean, Graduate School of Natural and Applied Sciences Prof. Dr. Orhan ADALI ________________ Head of Department, Biology Assoc. Prof. Dr. C. Can BİLGİN ________________ Supervisor, Biology Dept., METU Prof. Dr. Meryem Beklioğlu YERLİ ________________ Co-Supervisor, Biology Dept., METU Examining Committee Members: Prof. Dr. Zeki KAYA ________________ Biology Dept., METU Assoc. Prof. Dr. C. Can BİLGİN ________________ Biology Dept., METU Prof. Dr. Zuhal AKYÜREK ________________ Civil Engineering Dept., METU Prof. Dr. Meryem BEKLİOĞLU YERLİ ________________ Biology Dept., METU Prof. Dr. Ayşegül Çetin GÖZEN ________________ Biology Dept., METU Date: 16.02.2015 I hereby declare that all information in this document has been obtained and presented in accordance with academic rules and ethical conduct. I also declare that, as required by these rules and conduct, I have fully cited and referenced all material and results that are not original to this work. Name, Last Name: Saadet Peren Tuzkaya Signature: iv ABSTRACT THE INFLUENCE OF LAND USE AND THE CATCHMENT PROPERTIES ON THE TROPHIC STATUS OF SHALLOW LAKES IN TURKEY Tuzkaya, Saadet Peren M.S., Department of Biology Supervisor: Assoc. -
Noaa's Ecological Forecasting
NOAA’S ECOLOGICAL FORECASTING Ecological forecasts use measurements of the physical and biological environment to predict ecological conditions that can impact natural resources, people, communities, and economies. NOAA aims to deliver accurate, relevant, timely, and reliable ecological forecasts that power the blue economy and build climate resilience. These products and services are made available to coastal resource managers, private industry, and the public. Harmful algal blooms (HABs) Forecasts Hypoxia Forecasts HABs occur in every state and are changing in Hypoxia (low oxygen) has dramatically increased in U.S. frequency, toxicity, and duration. Both toxic and non- coastal systems, with large “dead zones” in Lake Erie, toxic HABs threaten human and marine mammal Chesapeake Bay, and Gulf of Mexico occurring annually. health, drinking water, tourism, commercial and The consequences of such large dead zones include recreational fisheries, and aquaculture. Short-term massive fish kills, loss of fisheries habitat, and economic HAB forecasts predict the intensity, location, and losses in commercially and recreationally valuable fishies. trajectory of blooms, and respiratory health risks of In Lake Erie, hypoxic water reaching the water intake for HABs in some areas. Longer-term forecasts predict cities along the coast can affect water treatment, the severity of HABs for the bloom season in a potentially impacting approximately 2 million residents. particular region. Scenario forecasts are used to test NOAA hypoxia forecasts aim to provide coastal managers the impact of changing environmental conditions, and stakeholders with the information needed to take such as nutrient pollution and climate change, on HAB proactive action to mitigate the impacts of an ongoing occurrence over multi-year time scales. -
Applying Algorithmic Accountability Frameworks with Domain-Specific Codes of Ethics: a Case Study in Ecosystem Forecasting for Shellfish Toxicity in the Gulf of Maine
Applying Algorithmic Accountability Frameworks with Domain-specific Codes of Ethics: A Case Study in Ecosystem Forecasting for Shellfish Toxicity in the Gulf of Maine Isabella Grasso David Russell Abigail Matthews [email protected] [email protected] [email protected] Clarkson University Clarkson University University of Wisconsin-Madison Potsdam, New York Potsdam, New York Madison, Wisconsin Jeanna Matthews Nicholas R. Record [email protected] [email protected] Clarkson University Bigelow Laboratory for Ocean Potsdam, New York Sciences East Boothbay, Maine ABSTRACT CCS CONCEPTS Ecological forecasts are used to inform decisions that can have · Social and professional topics → Codes of ethics; · Applied significant impacts on the lives of individuals and on the health computing → Environmental sciences; · Human-centered com- of ecosystems. These forecasts, or models, embody the ethics of puting → Walkthrough evaluations; their creators as well as many seemingly arbitrary implementation choices made along the way. They can contain implementation KEYWORDS errors as well as reflect patterns of bias learned when ingesting Algorithmic accountability, ethics, ecology, forecasting datasets derived from past biased decision making. Principles and frameworks for algorithmic accountability allow a wide range of ACM Reference Format: stakeholders to place the results of models and software systems Isabella Grasso, David Russell, Abigail Matthews, Jeanna Matthews, and Nicholas into context. We demonstrate how the combination of algorithmic R. Record. 2020. Applying Algorithmic Accountability Frameworks with accountability frameworks and domain-specific codes of ethics help Domain-specific Codes of Ethics: A Case Study in Ecosystem Forecast- answer calls to uphold fairness and human values, specifically in ing for Shellfish Toxicity in the Gulf of Maine. -
Choosing Spatial Units for Landscape-Based Management of the Fisheries Protection Program
Canadian Science Advisory Secretariat (CSAS) Research Document 2017/040 National Capital Region Choosing Spatial Units for Landscape-Based Management of the Fisheries Protection Program D. T. de Kerckhove1, J.A. Freedman2, K.L. Wilson3, M.V. Hoyer4, C. Chu1, and C.K. Minns5 1Ontario Ministry of Natural Resources and Forestry Aquatic Research and Monitoring Section 2140 East Bank Drive Peterborough, ON K9L 1Z8 2University of Florida, School of Forest Resources and Conservation 3University of Calgary, Dept. of Biological Sciences 4University of Florida, Florida LAKEWATCH 5University of Toronto, Dept. of Ecology and Evolutionary Biology July 2017 Foreword This series documents the scientific basis for the evaluation of aquatic resources and ecosystems in Canada. As such, it addresses the issues of the day in the time frames required and the documents it contains are not intended as definitive statements on the subjects addressed but rather as progress reports on ongoing investigations. Research documents are produced in the official language in which they are provided to the Secretariat. Published by: Fisheries and Oceans Canada Canadian Science Advisory Secretariat 200 Kent Street Ottawa ON K1A 0E6 http://www.dfo-mpo.gc.ca/csas-sccs/ [email protected] © Her Majesty the Queen in Right of Canada, 2017 ISSN 1919-5044 Correct citation for this publication: de Kerckhove, D.T., Freedman, J.A., Wilson, K.L., Hoyer, M.V., Chu, C., and Minns, C.K. 2017. Choosing Spatial Units for Landscape-Based Management of the Fisheries Protection Program. DFO Can. Sci. Advis. Sec. Res. Doc. 2017/040. v + 44. TABLE OF CONTENTS ABSTRACT .............................................................................................................................. -
Outstanding Challenges in the Transferability of Ecological Models
UC Davis UC Davis Previously Published Works Title Outstanding Challenges in the Transferability of Ecological Models. Permalink https://escholarship.org/uc/item/4r97d4np Journal Trends in ecology & evolution, 33(10) ISSN 0169-5347 Authors Yates, Katherine L Bouchet, Phil J Caley, M Julian et al. Publication Date 2018-10-01 DOI 10.1016/j.tree.2018.08.001 Peer reviewed eScholarship.org Powered by the California Digital Library University of California TREE 2418 1–13 Review Outstanding Challenges in the Transferability of Ecological Models 1,2, ,y 3,y 4,5 4,5 Katherine L. Yates , * Phil J. Bouchet, M. Julian Caley, Kerrie Mengersen, 6 1 7 8 9 Christophe F. Randin, Stephen Parnell, Alan H. Fielding, Andrew J. Bamford, Stephen Ban, 10 11 12 13 14 A. Márcia Barbosa, Carsten F. Dormann, Jane Elith, Clare B. Embling, Gary N. Ervin, 15 16 17 18,19 20 Rebecca Fisher, Susan Gould, Roland F. Graf, Edward J. Gregr, Patrick N. Halpin, 21 22 23 24 Risto K. Heikkinen, Stefan Heinänen, Alice R. Jones, Periyadan K. Krishnakumar, 25 26 20,27 28,23 Valentina Lauria, Hector Lozano-Montes, Laura Mannocci, Camille Mellin, 29 30 31 32 Mohsen B. Mesgaran, Elena Moreno-Amat, Sophie Mormede, Emilie Novaczek, 33 20 34 35 Steffen Oppel, Guillermo Ortuño Crespo, A. Townsend Peterson, Giovanni Rapacciuolo, 20 13 36 36,37 38 Jason J. Roberts, Rebecca E. Ross, Kylie L. Scales, David Schoeman, Paul Snelgrove, 39 40 41 12 42,43 Göran Sundblad, Wilfried Thuiller, Leigh G. Torres, Heroen Verbruggen, Lifei Wang, 44 45 46 47,48 Seth Wenger, Mark J. -
July 21, 2020 Theory Working Group Call
July 21, 2020 Theory Working Group Call Attendees: Amanda Gallinat, Jody Peters, Anna Sjodin, Christy Rollinson, Mike Dietze, Kathryn Wheeler, Glenda Wardle, John Foster, Michael Stemkovski, Abby Lewis Agenda: 1. Peter Adler needs to step down as the Theory Working Group chair. He will continue to provide input and follow discussions, when possible, but does not have the time to join the calls. Does anyone else want to lead/co-lead the group? a. Glenda, Christy, Abby, Amanda are all potential options b. Jody and Mike to follow up with all 4 about options 2. Update from Anna and Gretchen about their forecasting, prediction, and projection vocab analyses. n=106 respondents to the survey a. Figures b. Conceptual Diagram c. Given the survey data/figures, Anna and Gretchen came up with two ideas for forecast definitions, based on interpretation of the survey data. Anna/Gretchen are happy to have them edited, or a new definition created, by the Theory group. i. A forecast is an estimate, and the associated uncertainty of that estimate, about the future state of a system. ii. A forecast is an estimate about the state of a system in the future, or in a different space, and the uncertainty associated with that estimate. d. What is not considered in these definitions or is there something that didn’t come up in the surveys that would be helpful to ecological forecasting. e. Novel conditions may be a way to combine forecasting to future time/space. Is “novel conditions” too vague? No analog could be another option. Out of sample prediction. -
Pattern and Process Second Edition Monica G. Turner Robert H. Gardner
Monica G. Turner Robert H. Gardner Landscape Ecology in Theory and Practice Pattern and Process Second Edition L ANDSCAPE E COLOGY IN T HEORY AND P RACTICE M ONICA G . T URNER R OBERT H . G ARDNER LANDSCAPE ECOLOGY IN THEORY AND PRACTICE Pattern and Process Second Edition Monica G. Turner University of Wisconsin-Madison Department of Zoology Madison , WI , USA Robert H. Gardner University of Maryland Center for Environmental Science Frostburg, MD , USA ISBN 978-1-4939-2793-7 ISBN 978-1-4939-2794-4 (eBook) DOI 10.1007/978-1-4939-2794-4 Library of Congress Control Number: 2015945952 Springer New York Heidelberg Dordrecht London © Springer-Verlag New York 2015 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifi cally the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfi lms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specifi c statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. -
Ecological Forecasting Initiative 2019 Conference Speaker & Poster
Ecological Forecasting Initiative 2019 Conference Speaker & Poster Abstracts May 13-15, 2019 AAAS Headquarters 1200 New York Ave, NW Washington, DC 20005 @eco4cast #efi2019 The Ecological Forecasting Initiative (EFI) is a broad, interdisciplinary effort aimed at promoting the use of forecasts to understand, manage, and conserve ecosystems and the services they provide. The EFI 2019 meeting is aimed at bringing together scientists, agencies, industry, and stakeholders to build a community of practice and advance research, applications, and collaboration around near-term (subdaily to decadal) ecological forecasts. EFI2019 is sponsored by the Alfred P. Sloan Foundation, the Frederick S. Pardee Center for the Study of the Longer-Range Future at Boston University, and the National Science Foundation’s Office of International Science and Engineering. @ecoforecast #efi2019 Speaker Abstracts Session 1: Theory and Synthesis Monday, May 13 9:00 am S1.1: Keynote Ecological forecasting: the role of observations in models David Schimel1 [email protected] 1NASA JPL [abstract] 2 @ecoforecast #efi2019 Session 1: Theory and Synthesis Monday, May 13 9:00 am S1.2: Lightning Talk Understanding the uncertainties in estimating post-fire recovery of biomass using the Ecosystem Demography (EDv2.2) model Karun Pandit1, Hamid Dashti1, Nancy F. Glenn1, Alejandro N. Flores1, Kaitlin C. Maguire2, Douglas J. Shinneman2, Gerald N. Flerchinger3, Aaron W. Fellows3 [email protected] 1Boise State University; 2U.S. Geological Survey; 3ARS Frequent wildfires in the sagebrush-steppe ecosystems in the Western United States lead to heavy biodiversity loss, and changes in vegetation composition. It is debated in literature whether fires are beneficial or not for maintaining sagebrush ecosystems, it is essential that we understand the impact of these fires in terms of recovery time and potential changes in vegetation composition.