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Book
volumes : illustrations (some color), maps (some color) ; 24 cm
  • 1 OVERVIEW OF THIS BOOK 1 1.1 VOLUMES I AND II 1 1.1.1 Volume I 1 1.1.2 Volume II 1 1.2 WHAT TYPE OF SPATIAL DATA DO WE ANALYSE IN THIS BOOK? 1 1.2.1 Areal and lattice data 1 1.2.2 Geostatistical data 2 1.2.3 Spatial point pattern data 3 1.3 OUTLINE OF THIS BOOK 3 1.4 PREREQUISITES 4 1.5 AVAILABILITY OF R CODE AND DATA 4 2 RECOGNISING STATISTICAL DEPENDENCY 5 2.1 PSEUDOREPLICATION 5 2.2 LINEAR REGRESSION APPLIED TO SPATIAL DATA 7 2.2.1 Irish pH data 7 2.2.2 Protocol from Zuur et al. (2016) 8 2.2.3 Visualisation of the experimental design 9 2.2.4 Data exploration 9 2.2.5 Dependency 12 2.2.6 Statistical model 15 2.2.7 Fit the model 16 2.2.8 Model validation 17 2.3 GAM APPLIED TO TEMPORAL DATA 21 2.3.1 Subnivium temperature data 21 2.3.2 Sources of dependency 22 2.3.3 The model 23 2.3.4 Model validation 24 2.4 GLMM APPLIED ON HIERARCHICAL AND SPATIAL DATA 26 2.5 TECHNICALITIES 28 2.5.1 Matrix notation 28 2.5.2 How is dependency causing problems? 31 2.6 DISCUSSION 32 3 TIME SERIES AND GLS 33 3.1 OSPREYS 33 3.2 COVARIANCE AND CORRELATION COEFFICIENTS 33 3.3 LINEAR REGRESSION MODEL 35 3.4 FOCUSSING ON THE RESIDUAL COVARIANCE MATRIX 35 3.5 DEPENDENCY AND THE COVARIANCE MATRIX 36 3.6 GLS: DEALING WITH TEMPORAL DEPENDENCY 39 3.6.1 Adelie penguins 39 3.6.2 Do we have dependency? 40 3.6.3 Formulation of the linear regression model 40 3.6.4 Application of the linear regression model 41 3.6.5 R code for acf and variogram 45 3.6.6 Formulation of the GLS model 46 3.6.7 Implementation using the gls function 50 3.7 MULTIPLE TIME SERIES 51 3.8 DISCUSSION 53 4 SPATIAL DATA AND GLS 55 4.1 VARIOGRAM MODELS FOR SPATIAL DEPENDENCY 55 4.2 APPLICATION ON THE IRISH PH DATA 57 4.3 MATERN CORRELATION FUNCTION 59 5 LINEAR MIXED EFFECTS MODELS AND DEPENDENCY 61 5.1 WHITE STORKS 61 5.2 CONSIDERING THE DATA (WRONGLY) AS ONE-WAY NESTED 62 5.3 FITTING THE ONE-WAY NESTED MODEL USING LMER 65 5.4 MODEL VALIDATION 67 5.5 SKETCHING THE FITTED VALUES 68 5.6 CONSIDERING THE DATA (CORRECTLY) AS TWO-WAY NESTED 69 5.7 APPLICATIONS TO SPATIAL AND TEMPORAL DATA 72 5.8 DIFFERENCE WITH THE AR1 PROCESS APPROACH 72 6 MODELLING SPACE EXPLICITLY 73 6.1 MODEL FORMULATION 73 6.2 COVARIANCE MATRIX OF THE SPATIAL RANDOM EFFECT 75 6.3 SPATIAL-TEMPORAL CORRELATION* 79 7 INTRODUCTION TO BAYESIAN STATISTICS 83 7.1 WHY GO BAYESIAN? 83 7.2 GENERAL PROBABILITY RULES 84 7.3 THE MEAN OF A DISTRIBUTION* 85 7.4 BAYES' THEOREM AGAIN 87 7.5 CONJUGATE PRIORS 88 7.6 MARKOV CHAIN MONTE CARLO SIMULATION 93 7.6.1 Underlying idea 93 7.6.2 Installing JAGS and R2jags 94 7.6.3 Flowchart for running a model in JAGS 94 7.6.4 Preparing the data for JAGS 95 7.6.5 JAGS code 96 7.6.6 Initial values and parameters to save 98 7.6.7 Running JAGS 99 7.6.8 Accessing numerical output from JAGS 100 7.6.9 Assess mixing 100 7.6.10 Posterior information 101 7.7 INTEGRATED NESTED LAPLACE APPROXIMATION* 103 7.7.1 Joint posterior distribution 103 7.7.2 Marginal distributions 105 7.7.3 Back to high school 107 7.7.4 INLA 109 7.8 EXAMPLE USING R-INLA 110 7.9 DISCUSSION 114 8 MULTIPLE LINEAR REGRESSION IN R-INLA 115 8.1 INTRODUCTION 115 8.2 DATA EXPLORATION 116 8.3 MODEL FORMULATION 117 8.4 LINEAR REGRESSION RESULTS 117 8.4.1 Executing the model in R-INLA 117 8.4.2 Output for the betas 117 8.4.3 Output for the hyper-parameters 119 8.4.4 Fitted model 123 8.5 MODEL VALIDATION 123 8.6 MODEL SELECTION 126 8.6.1 Should we do it? 126 8.6.2 Using the DIC 126 8.6.3 Out of sample prediction 131 8.6.4 Posterior predictive check 133 8.7 VISUALISING THE MODEL 135 9 MIXED EFFECTS MODELLING IN R-INLA TO ANALYSE OTOLITH DATA 139 9.1 OTOLITHS IN PLAICE 139 9.2 MODEL FORMULATION 140 9.3 DEPENDENCY 140 9.4 DATA EXPLORATION 141 9.5 RUNNING THE MODEL IN R-INLA 143 9.6 MODEL VALIDATION 146 9.7 MODEL SELECTION 149 9.8 MODEL INTERPRETATION 149 9.8.1 Option 1 for prediction: Adding extra data 150 9.8.2 Option 2 for prediction: Using the inla.make.lincombs 153 9.8.3 Adding extra data or inla.make.lincombs? 155 9.9 MULTIPLE RANDOM EFFECTS 155 9.10 CHANGING PRIORS OF FIXED PARAMETERS 156 9.11 CHANGING PRIORS OF HYPERPARAMETERS 158 9.12 SHOULD WE CHANGE PRIORS? 164 10 POISSON, NEGATIVE BINOMIAL, BINOMIAL AND GAMMA GLMS IN R-INLA 165 10.1 POISSON AND NEGATIVE BINOMIAL GLMS IN R-INLA 165 10.1.1 Introduction 165 10.1.2 Poisson GLM in R-INLA 166 10.1.3 Negative binomial GLM in R-INLA 172 10.1.4 Model selection for the NB GLM 175 10.1.5 Visualisation of the NB GLM 177 10.2 BERNOULLI AND BINOMIAL GLM 180 10.2.1 Bernoulli GLM 181 10.2.2 Model selection with the marginal likelihood 184 10.2.3 Binomial GLM 185 10.3 GAMMA GLM 187 11 MATERN CORRELATION AND SPDE 191 11.1 CONTINUOUS GAUSSIAN FIELD 191 11.2 MODELS THAT WE HAVE IN MIND 191 11.3 MATERN CORRELATION 192 11.4 SPDE APPROACH 197 12 LINEAR REGRESSION MODEL WITH SPATIAL DEPENDENCY FOR THE IRISH PH DATA 205 12.1 INTRODUCTION 205 12.2 MODEL FORMULATION 205 12.3 LINEAR REGRESSION RESULTS 206 12.4 MODEL VALIDATION 207 12.5 ADDING SPATIAL CORRELATION TO THE MODEL 208 12.6 DEFINING THE MESH FOR THE IRISH PH DATA 212 12.7 DEFINE THE WEIGHT FACTORS AIK 216 12.8 DEFINE THE SPDE 218 12.9 DEFINE THE SPATIAL FIELD 218 12.10 DEFINE THE STACK 218 12.11 DEFINE THE FORMULA FOR THE SPATIAL MODEL 221 12.12 EXECUTE THE SPATIAL MODEL IN R 221 12.13 RESULTS 222 12.14 MODEL SELECTION 227 12.15 MODEL VALIDATION 228 12.16 MODEL INTERPRETATION 228 12.17 DETAILED INFORMATION ABOUT THE STACK* 232 12.17.1 Stack for the fitted model again 232 12.17.2 Stack for the new covariate values 234 12.17.3 Combine the two stacks 236 12.17.4 Run the model 236 13 SPATIAL POISSON MODELS APPLIED TO PLANT DIVERSITY 239 13.1 INTRODUCTION 239 13.2 DATA EXPLORATION 239 13.2.1 Sampling locations 239 13.2.2 Outliers 241 13.2.3 Collinearity 242 13.2.4 Relationships 243 13.2.5 Numbers of zeros 244 13.2.6 Conclusions data exploration 244 13.3 MODEL FORMULATION 244 13.4 GLM RESULTS 245 13.5 ADDING SPATIAL CORRELATION TO THE MODEL 248 13.5.1 Model formulation 248 13.5.2 Mesh 248 13.5.3 Projector matrix 253 13.5.4 SPDE 254 13.5.5 Spatial field 254 13.5.6 Stack 254 13.5.7 Formula 255 13.5.8 Run R-INLA 255 13.5.9 Inspect results 256 13.6 SIMULATING FROM THE MODEL 262 13.7 WHAT TO WRITE IN A PAPER 265 14 TIME-SERIES ANALYSIS IN R-INLA 267 14.1 SIMULATION STUDY 267 14.2 TRENDS IN MIGRATION DATES OF SOCKEYE SALMON 269 14.2.1 Applying a random walk trend model 269 14.2.2 Posterior distribution of the sigmas 272 14.2.3 Covariates and trends 273 14.2.4 Making the trend smoother 274 14.3 TRENDS IN POLAR BEAR MOVEMENTS 280 14.4 TRENDS IN WHALE STRANDINGS 283 14.5 MULTIVARIATE TIME SERIES FOR HAWAIIAN BIRDS 285 14.5.1 Importing and preparing the data 285 14.5.2 Data exploration 286 14.5.3 Model formulation 287 14.5.4 Executing the models 288 14.5.5 Mixing Poisson and negative binomial distributions 295 14.6 AR1 TRENDS 297 14.6.1 AR1 trend for regularly spaced time-series data 297 14.6.2 AR1 trend for irregularly spaced time-series data 299 15 SPATIAL-TEMPORAL MODELS FOR ORANGE-CROWNED WARBLERS COUNT DATA 307 15.1 INTRODUCTION 307 15.2 POISSON GLM 308 15.3 MODEL WITH SPATIAL CORRELATION 312 15.4 SPATIAL-TEMPORAL CORRELATION: AR1 318 15.4.1 Why do it? 318 15.4.2 Explanation of the model 318 15.4.4 Simulating a spatial-temporal AR random field 320 15.4.5 Implementation of AR1 model in R-INLA 323 15.4.6 More detailed information on the code 326 15.5 SPATIAL-TEMPORAL CORRELATION: EXCHANGEABLE 328 15.6 SPATIAL-TEMPORAL CORRELATION: REPLICATED 329 15.7 SIMULATION STUDY 330 15.8 DISCUSSION 333 16 SPATIAL-TEMPORAL BERNOULLI MODELS FOR CORAL DISEASE DATA 335 16.1 INTRODUCTION 335 16.2 BERNOULLI MODEL IN R-INLA 336 16.3 SPATIAL CORRELATED BERNOULLI MODEL 338 16.4 SPATIAL-TEMPORAL CORRELATED BERNOULLI MODEL 342 REFERENCES 347 INDEX 353 OTHER BOOKS 357.
  • (source: Nielsen Book Data)9780957174191 20170814
In Chapter 2 we discuss an important topic: dependency. Ignoring this means that we have pseudoreplication. We present a series of examples and discuss how dependency can manifest itself. We briefly discuss frequentist tools that are available for the analysis of temporal and spatial data in Chapters 3 and 4, and we will conclude that their application is rather limited, especially if non-Gaussian distributions are required. We will therefore consider alternative models, but these require Bayesian techniques. In Chapter 5 we discuss linear mixed-effects models to analyse hierarchical (i.e. clustered or nested) data, and in Chapter 6 we outline how we add spatial and spatial-temporal dependency to regression models via spatial (and/or temporal) correlated random effects. In Chapter 7 we introduce Bayesian analysis, Markov chain Monte Carlo techniques (MCMC), and Integrated Nested Laplace Approximation (INLA). INLA allows us to apply models to spatial, temporal, or spatial-temporal data. In Chapters 8 through 16 we present a series of INLA examples. We start by applying linear regression and mixed-effects models in INLA (Chapters 8 and 9), followed by GLM examples in Chapter 10. In Chapters 11 through 13 we show how to apply GLM models on spatial data. In Chapter 14 we discuss time-series techniques and how to implement them in INLA. Finally, in Chapters 15 and 16 we analyse spatial-temporal models in INLA.
(source: Nielsen Book Data)9780957174191 20170814
Marine Biology Library (Miller), Science Library (Li and Ma)
Book
xx, 572 pages ; 26 cm
Marine Biology Library (Miller), Science Library (Li and Ma)
Book
428 pages, 16 unnumbered pages of plates : illustrations (some color), map ; 25 cm
  • Darwin's really dangerous idea
  • Beauty happens
  • Manakin dances
  • Aesthetic innovation and decadence
  • Make way for duck sex
  • Beauty from the beast
  • Bromance before romance
  • Human beauty happens too
  • Pleasure happens
  • The Lysistrata effect
  • The queering of Homo sapiens
  • This aesthetic view of life.
What can explain the incredible diversity of beauty in nature? Richard O. Prum, an award-winning ornithologist, discusses Charles Darwin's second and long-neglected theory--aesthetic mate choice--and what it means for our understanding of evolution. In addition, Prum connects those same evolutionary dynamics to the origins and diversity of human sexuality, offering riveting new thinking about the evolution of human beauty and the role of mate choice, thereby transforming our ancestors from typical infanticidal primates into socially intelligent, pair-bonding caregivers. Prum's book is an exhilarating tour de force that begins in the trees and ends by fundamentally challenging how we understand human evolution and ourselves. -- adapted from book jacket.
Marine Biology Library (Miller), Science Library (Li and Ma)
Book
260 pages : illustrations ; 23 cm
  • What is group selection?
  • Group selection in the 1970s
  • Career beginnings and science after the thesis
  • Experimental studies of population heritability
  • Population ecology and population heritability
  • The evolution of sociality
  • Calibrating the laboratory to nature
  • Experimental studies of Wright's shifting balance theory
  • Beyond the shifting balancing theory.
All organisms live in clusters, but such fractured local populations, or demes, nonetheless maintain connectivity with one another by some amount of gene flow between them. Most such metapopulations occur naturally, like clusters of amphibians in vernal ponds or baboon troops spread across the African veldt. Others have been created as human activities fragment natural landscapes, as in stands of trees separated by roads. As landscape change has accelerated, understanding how these metapopulations function and specifically how they adapt has become crucial to ecology and to our very understanding of evolution itself. With "Adaptation in Metapopulations, " Michael J. Wade explores a key component of this new understanding of evolution: interaction. Synthesizing decades of work in the lab and in the field in a book both empirically grounded and underpinned by a strong conceptual framework, Wade looks at the role of interaction across scales from gene selection to selection at the level of individuals, kin, and groups. In so doing, he integrates molecular and organismal biology to reveal the true complexities of evolutionary dynamics from genes to metapopulations.".
(source: Nielsen Book Data)9780226129730 20160704
Marine Biology Library (Miller), Science Library (Li and Ma)
Book
xvi, 414 pages : illustrations ; 24 cm
  • 1. Introduction
  • 2. Essential distributions for zero-inflated models
  • 3. Introducing zero-inflated Poisson models
  • 4. Zero-inflated models applied to orange-crowned warblers
  • 5. Zero-inflated models applied to shark abundance data
  • 6. Hurdle models for riparian spider counts
  • 7. Models for zero-inflated continuous data applied to Chinese tallow trees
  • 8. Linear mixed effects models
  • 9. Zero-altered models with two-way nested and crossed random effects
  • 10. Introduction to Bayesian statistics
  • 11. Bayesian analysis for Poisson, NB, ZIP and Bernoulli models
  • 12. Bayesian analysis for linear mixed effects models
  • Beaver and Lilies
  • 13. The zero trick to fit any distribution in a Bayesian analysis
  • 14. Bayesian model selection techniques
  • 15. Bayesian model selection applied to zero-inflated butterfly data
  • 16. Zero-inflated seagrass coverage data
  • 17. Other distributions
  • 18. Multivariate GLMM.
This book provides the statistical tools to aid analysis of datasets. It deals with two main difficulties faced with large datasets, lots of zeros and dependency.
Marine Biology Library (Miller), Science Library (Li and Ma)
Book
xiv, 205 pages : illustrations ; 23 cm
  • Chapter 1: Data Defined Climbing the pyramid A brief history of the data world Data file formats Chapter 2: Clues for uncovering data Why agencies collect, analyze, publish data Clues from data entry Clues from reports Tricks to uncover forms and reports On your own Chapter 3: Online databases Destination: data portals Statistical stockpiles Agency sites Non-governmental resources Data search tricks Don't forget the road map On your own Chapter 4: Identifying and requesting offline data Other clues for offline data Find the data nerd Requesting the data Writing the data request FOIA in action Negotiating through obstacles Getting help On your own Chapter 5: Data dirt is everywhere All data are dirty Detecting dirt in agricultural data Changed rules = changed data On your own Chapter 6: Data integrity checks Big-picture checks Detailed checks On your own Chapter 7: Getting your data in shape Column carving Concatenate to paste Date tricks Power scrubbing with OpenRefine Extracting data from PDFs On your own Chapter 8: Number summaries and comparisons Simple summary statistics Compared to what? Benchmarking On your own Chapter 9: Calculating summary statistics and number comparisons Sum crimes by year Minimum and maximum numbers Amount change Stepping up to percent change Running rates Running ratios Percent of total More summarizing On your own Chapter 10: Spreadsheets as database managers Sorting Filtering records Grouping and summarizing On your own Chapter 11: Visualizing your data Data visualization defined Some best practices Chapter 12: Charting choices Visualizing data with charts On your own Chapter 13: Charting in Excel Pie chart Horizontal bar charts Column and line charts Scatterplot Stock chart Sparklines On your own Chapter 14: Charting with Web tools Online visualization options Evaluating web visualization platforms Creating Fusion Table charts On your own Chapter 15: Taking analysis to the next level Database managers Statistical programs.
  • (source: Nielsen Book Data)9781483333465 20160618
We are swimming in a world of data, and this handy guide will keep students afloat while they learn to make sense of it all. David Herzog, a journalist with more than 15 years of experience using data analysis to transform information into captivating storytelling, introduces readers to the fundamentals of data literacy. Assuming the reader has no advanced knowledge of data analysis or statistics, the book shows how to create insight from publicly-available data. Extensively illustrated, step-by-step instructions within a concise, yet comprehensive, reference will help readers to master: * What data is and what it isn't, * How to develop a "database set of mind, " * How to gather data, How to evaluate data, * How to clean up "dirty data, " * How to visualize data, and * How to use tools for data analysis and visualization.
(source: Nielsen Book Data)9781483333465 20160618
Marine Biology Library (Miller), Science Library (Li and Ma)
Book
1 volume (various pagings) : illustrations (chiefly color) ; 29 cm
  • Patterns and Processes of Becoming: A Framework for Understanding Animal Development 1. Making New Bodies: Mechanisms of Developmental Organization 2. Specifying Identity: Mechanisms of Developmental Patterning 3. Differential Gene Expression: Mechanisms of Cell Differentiation 4. Cell-Cell Communication: Mechanisms of Morphogenesis 5. Stem Cells and Their Niches: Cell Generation and Regeneration Gametogenesis and Fertilization: The Circle of Sex 6. Sex Determination and Gametogenesis 7. Fertilization: Beginning a New Organism Early Development: Cleavage, Gastrulation, and Axis Formation 8. Rapid Specification in Snails and Nematodes 9. The Genetics of Axis Specification in Drosophila 10. Sea Urchins and Tunicates: Deuterostome Invertebrates 11. Amphibians and Fish 12. Birds and Mammals Building with Ectoderm: The Vertebrate Nervous System and Epidermis 13. Neural Tube Formation and Patterning 14. Brain Growth 15. Axons and Neural Crest Cells 16. Epidermis and Ectodermal Placodes Building with Mesoderm and Endoderm: Organogenesis 17. Paraxial Mesoderm: Segmentation and Somite Differentiation 18. Intermediate and Lateral Plate Mesoderm: Blood, Heart, and Kidneys 19. The Tetrapod Limb 20. Endoderm: Tubes and Organs for Digestion and Respiration Postembryonic Development 21. Metamorphosis 22. Regeneration 23. Aging Development in Wider Contexts 24. Development in Health and Disease: Birth Defects, Endocrine Disruptors, and Cancer 25. Development and the Environment: Biotic, Abiotic, and Symbiotic Regulation of Development 26. Development and Evolution: Developmental Mechanisms of Evolutionary Change.
  • (source: Nielsen Book Data)9781605354705 20160912
Scott Gilbert's Developmental Biology has metamorphosed into the Gilbert and Barresi Developmental Biology.
(source: Nielsen Book Data)9781605354705 20160912
Marine Biology Library (Miller), Science Library (Li and Ma)
Book
xx, 984 pages : illustrations, maps ; 29 cm
  • Contributors Preface and Acknowledgments Marine and Terrestrial Maps of California 1. Introduction (Erika Zavaleta and Harold Mooney) DRIVERS 2. Climate (Sam F. Iacobellis, Daniel R. Cayan, John T. Abatzoglou, and Harold Mooney) 3. Fire as an Ecosystem Process (Jon E. Keeley and Hugh D. Safford) 4. Geomorphology and Soils (Robert C. Graham and Toby A. O'Geen) 5. Population and Land Use (Peter S. Alagona, Tim Paulson, Andrew B. Esch, and Jessica Marter-Kenyon) 6. Oceanography (Steven J. Bograd, Andrew Leising, and Elliott L. Hazen) 7. Atmospheric Chemistry (Andrzej Bytnerowicz, Mark Fenn, Edith B. Allen, and Ricardo Cisneros) HISTORY 8. Ecosystems Past: Vegetation Prehistory (Constance I. Millar and Wallace B. Woolfenden) 9. Paleovertebrate Communities (Elizabeth A. Hadly and Robert S. Feranec) 10. Indigenous California (Terry L. Jones and Kacey Hadick) BIOTA 11. Biodiversity (Bernie Tershy, Susan Harrison, Abraham Borker, Barry Sinervo, Tara Cornelisse, Cheng Li, Dena Spatz, Donald Croll, and Erika Zavaleta) 12. Vegetation (Christopher R. Dolanc, Todd Keeler-Wolf, and Michael G. Barbour) 13. Biological Invasions (Erika Zavaleta, Elissa Olimpi, Amelia A. Wolf, Bronwen Stanford, Jae Pasari, Sarah Skikne, Paulo Quadri, Katherine Ennis, and Flavia Oliveira) 14. Climate Change Impacts (Christopher B. Field, Nona R. Chiariello, and Noah S. Diffenbaugh) 15. Introduction to Concepts of Biodiversity, Ecosystem Functioning, Ecosystem Services, and Natural Capital (Rebecca Chaplin-Kramer, Lisa Mandle, Elizabeth Rauer, and Suzanne Langridge) ECOSYSTEMS 16. The Offshore Ecosystem (Steven J. Bograd, Elliott L. Hazen, Sara M. Maxwell, Andrew W. Leising, Helen Bailey, and Richard D. Brodeur) 17. Shallow Rocky Reefs and Kelp Forests (Mark H. Carr and Daniel C. Reed) 18. Intertidal (Carol A. Blanchette, Mark W. Denny, John M. Engle, Brian Helmuth, Luke P. Miller, Karina J. Nielsen, and Jayson Smith) 19. Estuaries: Life on the Edge (James E. Cloern, Patrick Barnard, Erin Beller, John Callaway, J. Letitia Grenier, Edwin D. Grosholz, Robin Grossinger, Kathy Hieb , James T. Holligaugh, Noah Knowles, Martha Sutula, Samuel Veloz, Kerstin Wasson, and Alison Whipple) 20. Sandy Beaches (Jenifer E. Dugan and David M. Hubbard) 21. Coastal Dunes (Peter Alpert) 22. Coastal Sage Scrub (Elsa E. Cleland, Jennifer Funk, and Edith B. Allen) 23. Grasslands (Valerie T. Eviner) 24. Chaparral (V. Thomas Parker, R. Brandon Pratt, and Jon E. Keeley) 25. Oak Woodlands (Frank W. Davis, Dennis D. Baldocchi, and Claudia M. Tyler) 26. Coast Redwood Forests (Harold Mooney and Todd E. Dawson) 27. Montane Forests (Malcolm North, Brandon Collins, Hugh Safford, and Nathan L. Stephenson) 28. Subalpine Forests (Constance I. Millar and Philip W. Rundel) 29. Alpine Ecosystems (Philip W. Rundel and Constance I. Millar) 30. Deserts (Jayne Belnap, Robert H. Webb , Todd C. Esque, Matthew L. Brooks, Lesley A. DeFalco, and James A. MacMahon) 31. Wetlands (Walter G. Duffy, Philip Garone, Brenda J. Grewell, Sharon Kahara, Joseph Fleskes, Brent Helm, Peter Moyle, Rosemary Records, and Joseph Silveira) 32. Lakes (John Melack and S. Geoffrey Schladow) 33. Rivers (Mary E. Power, Sarah J. Kupferberg, Scott D. Cooper, and Michael L. Deas) Managed Systems 34. Managed Island Ecosystems (Kathryn McEachern, Tanya Atwater, Paul W. Collins, Kate Faulkner, and Daniel V. Richards) 35. Marine Fisheries (Eric P. Bjorkstedt, John C. Field, Milton Love, Laura Rogers-Bennett, and Rick Starr) 36. Forestry (William Stewart, Benktesh Sharma, Rob York, Lowell Diller, Nadia Hamey, Roger Powell, and Robert Swiers) 37. Range Ecosystems (Sheri Spiegal, Lynn Huntsinger, Peter Hopkinson, and James Bartolome) 38. Agriculture (Alex McCalla and Richard Howitt) 39. Urban Ecosystems (Diane E. Pataki, G. Darrel Jenerette, Stephanie Pincetl, Tara L. E. Trammell, and La'Shaye Ervin) POLICY AND STEWARDSHIP 40. Land Use Regulation for Resource Conservation (Stephanie Pincetl, Terry Watt, and Maria Santos) 41. Stewardship, Conservation, and Restoration in the Context of Environmental Change (Adina M. Merenlender, David D. Ackerly, Katherine Suding, M. Rebecca Shaw, and Erika Zavaleta) INDEX.
  • (source: Nielsen Book Data)9780520278806 20160619
This long-anticipated reference and source book for California's remarkable ecological abundance provides an integrated assessment of each major ecosystem type - its distribution, structure, function, and management. With a comprehensive synthesis of our knowledge about this biologically diverse state, Ecosystems of California covers the state from oceans to mountaintops using multiple lenses: past and present, flora and fauna, aquatic and terrestrial, natural and managed. Each chapter evaluates natural processes for a specific ecosystem, describes drivers of change, and discusses how that ecosystem may be altered in the future. This book also explores the drivers of California's ecological patterns and the history of the state's various ecosystems, outlining how the challenges of climate change and invasive species and opportunities for regulation and stewardship could potentially affect the state's ecosystems. The text explicitly incorporates both human impacts and conservation and restoration efforts and shows how ecosystems support human well-being. Edited by two esteemed ecosystem ecologists and with overviews by leading experts on each ecosystem, this definitive work will be indispensable for natural resource management and conservation professionals as well as for undergraduate or graduate students of California's environment and curious naturalists.
(source: Nielsen Book Data)9780520278806 20160619
Engineering Library (Terman), Marine Biology Library (Miller), Science Library (Li and Ma)

9. Invertebrates [2016]

Book
xix, 1104 pages : illustrations (some color) ; 29 cm
  • Introduction Classification, Systematics, Phylogeny The Protists: Kingdom Protista Introduction to Metazoa: Animal Architecture Introduction to Metazoa: Animal Development, Life Histories, and Origins Introduction to the Animal Kingdom Two Basal Metazoan Phyla: Porifera and Placozoa Phylum Cnidaria: Anemones, Corals, Jellyfish, and Their Kin Phylum Ctenophora: The Comb Jellies Introduction to the Bilateria, and the Phylum Xenacoelomorpha: Triploblasty and Bilateral Symmetry Provide New Avenues for Animal Radiation Phylum Platyhelminthes: Flatworms and Their Kin Four Enigmatic Protostome Phyla: Rhombozoa, Orthonectida, Chaetognatha, Gastrotricha Phylum Nemertea: The Ribbon Worms Phylum Mollusca: Snails, Clams, Cephalopods, and Their Kin Phylum Annelida: The Segmented (and Some Unsegmented) Worms Two Enigmatic Spiralian Phyla: Entoprocta and Cycliophora The Gnathifera: Phyla Gnathostomulida, Rotifera (including Acanthocephala), and Micrognathozoa The Lophophorates: Phyla Phoronida, Bryozoa, and Brachiopoda The Nematoida: Phyla Nematoda and Nematomorpha The Scalidophora: Phyla Kinorhyncha, Priapula, and Loricifera The Emergence of the Arthropods: Onychophora, Tardigrada, Trilobites, and the Arthropod Body Plan Phylum Arthropoda: The Crustacea Phylum Arthropoda The Hexapoda: Insects and Their Kin Phylum Arthropoda The Myriapods: Centipedes, Millipedes, and Their Kin Phylum Arthropoda: The Chelicerata Introduction to Deuterostomes, and the Phylum Echinodermata Phylum Hemichordata: Acorn Worms and Pterobranchs Phylum Chordata: Urochordata and Cephalochordata Perspectives on Invertebrate Phylogeny.
  • (source: Nielsen Book Data)9781605353753 20160619
Invertebrates presents a modern survey of the 34 animal phyla (plus the Protista) and serves as both a college course text and a reference on invertebrate biology.
(source: Nielsen Book Data)9781605353753 20160619
Marine Biology Library (Miller), Science Library (Li and Ma)
Book
xiii, 285 pages : illustrations ; 24 cm.
This novel, interdisciplinary text achieves an integration of empirical data and theory with the aid of mathematical models and statistical methods. The emphasis throughout is on spatial ecology and evolution, especially on the interplay between environmental heterogeneity and biological processes. The book provides a coherent theme by interlinking the modelling approaches used for different subfields of spatial ecology: movement ecology, population ecology, community ecology, and genetics and evolutionary ecology (each being represented by a separate chapter). Each chapter starts by describing the concept of each modelling approach in its biological context, goes on to present the relevant mathematical models and statistical methods, and ends with a discussion of the benefits and limitations of each approach. The concepts and techniques discussed throughout the book are illustrated throughout with the help of empirical examples. This is an advanced text suitable for any biologist interested in the integration of empirical data and theory in spatial ecology/evolution through the use of quantitative/statistical methods and mathematical models. The book will also be of relevance and use as a textbook for graduate-level courses in spatial ecology, ecological modelling, theoretical ecology, and statistical ecology.
(source: Nielsen Book Data)9780198714873 20160912
Marine Biology Library (Miller), Science Library (Li and Ma)
Book
xi, 275 pages : illustrations, maps ; 24 cm.
  • In the beginning
  • Understanding nature
  • The Aleutian archipelago
  • Sea otters and kelp forests
  • A toe in the arctic ocean
  • Return to Attu
  • Generality and variation
  • A serpentine food web
  • Sea otters and the red queen hypothesis: plant/herbivore coevolution
  • Sea otters and killer whales
  • Megafaunal collapse
  • Whale wars
  • Foxes and seabirds
  • A global perspective
  • Retrospection
  • Looking to the future.
To newly minted biologist James Estes, the sea otters he was studying in the leafy kelp forests off the coast of Alaska appeared to have an unbalanced relationship with their greater environment. Gorging themselves on the sea urchins that grazed among the kelp, these small charismatic mammals seemed to give little back in return. But as Estes dug deeper, he unearthed a far more complex relationship between the otter and its underwater environment, discovering that otters play a critical role in driving positive ecosystem dynamics. While teasing out the connective threads, he began to question our assumptions about ecological relationships. These questions would ultimately inspire a lifelong quest to better understand the surprising complexity of our natural world and the unexpected ways we discover it. Serendipity tells the story of James Estes' life as a naturalist and the concepts that have driven his interest in researching the ecological role of top-level predators. Using the relationships between sea otters, kelp, and sea urchins as a touchstone, Estes retraces his investigations of numerous other species, ecosystems, and ecological processes in an attempt to discover why ecologists can learn so many details about the systems in which they work and yet understand so little about the broader processes that influence these systems. Part memoir, part natural history, and deeply inquisitive, Serendipity will entertain and inform readers as it raises thoughtful questions about our relationship with the natural world.
(source: Nielsen Book Data)9780520285033 20160704
Marine Biology Library (Miller), Science Library (Li and Ma)
Book
xvii, 469 pages : illustrations (some color) ; 27 cm.
  • The Golem of Prague Statistical golems Statistical rethinking Three tools for golem engineering Summary Small Worlds and Large Worlds The garden of forking data Building a model Components of the model Making the model go Summary Practice Sampling the Imaginary Sampling from a grid-approximate posterior Sampling to summarize Sampling to simulate prediction Summary Practice Linear Models Why normal distributions are normal A language for describing models A Gaussian model of height Adding a predictor Polynomial regression Summary Practice Multivariate Linear Models Spurious association Masked relationship When adding variables hurts Categorical variables Ordinary least squares and lm Summary Practice Overfitting, Regularization, and Information Criteria The problem with parameters Information theory and model performance Regularization Information criteria Using information criteria Summary Practice Interactions Building an interaction Symmetry of the linear interaction Continuous interactions Interactions in design formulas Summary Practice Markov Chain Monte Carlo Good King Markov and His island kingdom Markov chain Monte Carlo Easy HMC: map2stan Care and feeding of your Markov chain Summary Practice Big Entropy and the Generalized Linear Model Maximum entropy Generalized linear models Maximum entropy priors Summary Counting and Classification Binomial regression Poisson regression Other count regressions Summary Practice Monsters and Mixtures Ordered categorical outcomes Zero-inflated outcomes Over-dispersed outcomes Summary Practice Multilevel Models Example: Multilevel tadpoles Varying effects and the underfitting/overfitting trade-off More than one type of cluster Multilevel posterior predictions Summary Practice Adventures in Covariance Varying slopes by construction Example: Admission decisions and gender Example: Cross-classified chimpanzees with varying slopes Continuous categories and the Gaussian process Summary Practice Missing Data and Other Opportunities Measurement error Missing data Summary Practice Horoscopes.
  • (source: Nielsen Book Data)9781482253443 20170130
Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds readers' knowledge of and confidence in statistical modeling. Reflecting the need for even minor programming in today's model-based statistics, the book pushes readers to perform step-by-step calculations that are usually automated. This unique computational approach ensures that readers understand enough of the details to make reasonable choices and interpretations in their own modeling work. The text presents generalized linear multilevel models from a Bayesian perspective, relying on a simple logical interpretation of Bayesian probability and maximum entropy. It covers from the basics of regression to multilevel models. The author also discusses measurement error, missing data, and Gaussian process models for spatial and network autocorrelation. By using complete R code examples throughout, this book provides a practical foundation for performing statistical inference. Designed for both PhD students and seasoned professionals in the natural and social sciences, it prepares them for more advanced or specialized statistical modeling. Web Resource The book is accompanied by an R package (rethinking) that is available on the author's website and GitHub. The two core functions (map and map2stan) of this package allow a variety of statistical models to be constructed from standard model formulas.
(source: Nielsen Book Data)9781482253443 20170130
Marine Biology Library (Miller), Science Library (Li and Ma)
Book
ix, 229 pages : illustrations ; 24 cm.
  • Acknowledgments vii 1. Introduction 1 PART I APPROACHES, IDEAS, AND THEORIES IN COMMUNITY ECOLOGY 2. How Ecologists Study Communities 9 3. A Brief History of Ideas in Community Ecology 20 PART II THE THEORY OF ECOLOGICAL COMMUNITIES 4. The Pursuit of Generality in Ecology and Evolutionary Biology 39 5. High-Level Processes in Ecological Communities 49 6. Simulating Dynamics in Ecological Communities 69 PART III EMPIRICAL EVIDENCE 7. The Nature of Empirical Evidence 93 8. Empirical Evidence: Selection 107 9. Empirical Evidence: Ecological Drift and Dispersal 138 10. Empirical Evidence: Speciation and Species Pools 158 PART IV CONCLUSIONS, REFLECTIONS, AND FUTURE DIRECTIONS 11. From Process to Pattern and Back Again 175 12. The Future of Community Ecology 182 References 193 Index 225.
  • (source: Nielsen Book Data)9780691164847 20160919
A plethora of different theories, models, and concepts make up the field of community ecology. Amid this vast body of work, is it possible to build one general theory of ecological communities? What other scientific areas might serve as a guiding framework? As it turns out, the core focus of community ecology--understanding patterns of diversity and composition of biological variants across space and time--is shared by evolutionary biology and its very coherent conceptual framework, population genetics theory. The Theory of Ecological Communities takes this as a starting point to pull together community ecology's various perspectives into a more unified whole. Mark Vellend builds a theory of ecological communities based on four overarching processes: selection among species, drift, dispersal, and speciation. These are analogues of the four central processes in population genetics theory--selection within species, drift, gene flow, and mutation--and together they subsume almost all of the many dozens of more specific models built to describe the dynamics of communities of interacting species. The result is a theory that allows the effects of many low-level processes, such as competition, facilitation, predation, disturbance, stress, succession, colonization, and local extinction to be understood as the underpinnings of high-level processes with widely applicable consequences for ecological communities. Reframing the numerous existing ideas in community ecology, The Theory of Ecological Communities provides a new way for thinking about biological composition and diversity.
(source: Nielsen Book Data)9780691164847 20160919
ebrary Access limited to one user.
Marine Biology Library (Miller), Science Library (Li and Ma)
Book
viii, 288 pages, 8 unnumbered pages of plates : color illustrations ; 22 cm
  • Part I. The misunderstood fish
  • Part II. What a fish perceives
  • What a fish sees
  • What a fish hears, smells, and tastes
  • Navigation, touch, and beyond
  • Part III. What a fish feels
  • Pain, consciousness, and awarenes
  • From stress to joy
  • Part IV. What a fish thinks
  • Fins, scales, and intelligence
  • Tools, plans, and monkey minds
  • Part V. Who a fish knows
  • Suspended together
  • Social contracts
  • Cooperation, democracy, and peacekeeping
  • Part VI. How a fish breeds
  • Sex lives
  • Parenting styles
  • Part VII. Fish out of water.
"The author of Second Nature challenges popular misconceptions to explore the complex lives of the planet's diverse fish species, drawing on the latest understandings in animal behavior and biology to reveal their self-awareness, elaborate courtship rituals and cooperative intelligence, "--NoveList.
Marine Biology Library (Miller), Science Library (Li and Ma)
Book
191 pages.
  • Starting out. Do not think about why you are applying ; Ignore the market ; Stay at the same university ; Follow the money blindly ; Do an unfunded PhD ; Do an interdisciplinary PhD ; Believe advertised completion times ; Ignore the information the university provides you ; Expect the money to take care of itself
  • Supervisors . Go it alone and stay quiet ; Choose the coolest supervisor ; Have co-supervisors ; Do not clarify the supervisor's (or your own) expectations ; Avoid your supervisor and committee ; Stay in a bad relationship ; Expect people to hold your hand
  • Managing your program. Concentrate only on your thesis ; Expect to write the perfect comprehensive exam ; Select a topic for entirely strategic reasons ; Do not teach, or teach a ton of courses ; Do not seek teaching instruction ; Move away from the university before finishing your degree ; Postpone those tedious approval processes ; Organize everything only in your head ; Do not attend conferences, or attend droves of conferences
  • Your work and social life. Concentrate solely on school ; Expect friends and family to understand ; Socialize only with your clique ; Get a job!
  • Writing. Write only your PhD thesis ; Postpone publishing ; Cover everything ; Do not position yourself ; Write only to deadlines ; Abuse your audience
  • Your attitude and actions. Expect to be judged only on your work ; Have a thin skin ; Be inconsiderate ; Become "that" student ; Never compromise ; Gossip ; Say whatever pops into your head on social media
  • Delicate matters. Assume that the university is more inclusive than other institutions ; Insist on your rights ; Get romantically involved with faculty ; Cheat and plagiarize
  • Am I done yet?: on finishing. Skip job talks ; Expect to land a job in a specific university ; Expect people to hire you to teach your thesis ; Turn down opportunities to participate in job searches ; Neglect other people's theses ; Get an unknown external examiner ; Do not understand the endgame ; Be blase about your defense ; Do not plan for your job interview ; Persevere at all costs ; Consider a non-academic career a form of failure ; Final thoughts.
Don't think about why you're applying. Select a topic for entirely strategic reasons. Choose the coolest supervisor. Write only to deadlines. Expect people to hold your hand. Become "that" student. When it comes to a masters or PhD program, most graduate students don't deliberately set out to fail. Yet, of the nearly 500,000 people who start a graduate program each year, up to half will never complete their degree. Books abound on acing the admissions process, but there is little on what to do once the acceptance letter arrives. Veteran graduate directors Kevin D. Haggerty and Aaron Doyle have set out to demystify the world of advanced education. Taking a wry, frank approach, they explain the common mistakes that can trip up a new graduate student and lay out practical advice about how to avoid the pitfalls. Along the way they relate stories from their decades of mentorship and even share some slip-ups from their own grad experiences. The litany of foul-ups is organized by theme and covers the grad school experience from beginning to end: selecting the university and program, interacting with advisors and fellow students, balancing personal and scholarly lives, navigating a thesis, and creating a life after academia. Although the tone is engagingly tongue-in-cheek, the lessons are crucial to anyone attending or contemplating grad school. 57 Ways to Screw Up in Grad School allows you to learn from others' mistakes rather than making them yourself.
(source: Nielsen Book Data)9780226280905 20160618
Marine Biology Library (Miller), Science Library (Li and Ma)
Book
xxxi, 1192 pages : illustrations ; 26 cm
  • 1. Foundations-- 2. Bipolar transistors-- 3. Field effect transistors-- 4. Operational amplifiers-- 5. Precision circuits-- 6. Filters-- 7. Oscillators and timers-- 8. Low noise techniques and transimpedance-- 9. Power regulation-- 10. Digital electronics-- 11. Programmable logic devices-- 12. Logical interfacing-- 13. Digital meets analog-- 14. Computers, controllers, and data links-- 15. Microcontrollers.
  • (source: Nielsen Book Data)9780521809269 20160618
At long last, here is the thoroughly revised and updated third edition of the hugely successful The Art of Electronics. It is widely accepted as the best single authoritative book on electronic circuit design. In addition to new or enhanced coverage of many topics, the third edition includes 90 oscilloscope screenshots illustrating the behavior of working circuits, dozens of graphs giving highly useful measured data of the sort that is often buried or omitted in datasheets but which you need when designing circuits, and 80 tables (listing some 1650 active components), enabling intelligent choice of circuit components by listing essential characteristics (both specified and measured) of available parts. The new Art of Electronics retains the feeling of informality and easy access that helped make the earlier editions so successful and popular. It is an indispensable reference and the gold standard for anyone, student or researcher, professional or amateur, who works with electronic circuits.
(source: Nielsen Book Data)9780521809269 20160618
Engineering Library (Terman), Marine Biology Library (Miller), Science Library (Li and Ma)
PHYSICS-105-01
Book
vii, 264 pages, 8 unnumbered pages of plates : illustrations ; 25 cm
Over the course of two decades, John Hargrove worked with 20 different whales on two continents and at two of SeaWorld's U.S. facilities. For Hargrove, becoming an orca trainer fulfilled a childhood dream. However, as his experience with the whales deepened, Hargrove came to doubt that their needs could ever be met in captivity. When two fellow trainers were killed by orcas in marine parks, Hargrove decided that SeaWorld's wildly popular programs were both detrimental to the whales and ultimately unsafe for trainers. After leaving SeaWorld, Hargrove became one of the stars of the controversial documentary Blackfish. The outcry over the treatment of SeaWorld's orca has now expanded beyond the outlines sketched by the award-winning documentary, with Hargrove contributing his expertise to an advocacy movement that is convincing both federal and state governments to act. In Beneath the Surface, Hargrove paints a compelling portrait of these highly intelligent and social creatures, including his favourite whales Takara and her mother Kasatka, two of the most dominant orcas in SeaWorld. And he includes vibrant descriptions of the lives of orcas in the wild, contrasting their freedom in the ocean with their lives in SeaWorld. Hargrove's journey is one that humanity has just begun to take-toward the realization that the relationship between the human and animal worlds must be radically rethought.
(source: Nielsen Book Data)9781137280107 20160618
Marine Biology Library (Miller), Science Library (Li and Ma)
Book
xvi, 395 pages : illustrations, maps ; 27 cm
  • Preface Acknowledgments Introduction PART I. THE BIOLOGY OF GIANT KELP 1. Introduction to Giant Kelp Forests Worldwide 2. The Structure, Function, and Abiotic Requirements of 3. The Abiotic Environment 4. Demography, Dispersal, and Connectivity of Populations PART II. THE GIANT KELP ECOSYSTEM 5. Giant Kelp Communities 6. Detached Giant Kelp Communities, Production, and Food / Control Webs 7. Facilitative and Competitive Interactions in Giant Kelp Forests 8. Grazing in Kelp Communities 9. Predation and Trophic Cascades in Kelp Communities PART III. HUMAN USAGE, MANAGEMENT, AND CONSERVATION 10. Anthropogenic Effects on Kelp Forests 11. Human Usage of Giant Kelp and Kelp Forest Organisms 12. Marine Protected Areas and Fisheries Effects PART IV. GLOBAL CHANGE AND THE FUTURE 13. Global Change 14. Giant Kelp Forests: Conclusions and Final Thought Afterword References Index.
  • (source: Nielsen Book Data)9780520278868 20160618
This is the largest seaweed, giant kelp (Macrocystis) is the fastest growing and most prolific of all plants found on earth. Growing from the seafloor and extending along the ocean surface in lush canopies, giant kelp provides an extensive vertical habitat in a largely two-dimensional seascape. It is the foundation for one of the most species-rich, productive, and widely distributed ecological communities in the world. Schiel and Foster's scholarly review and synthesis take the reader from Darwin's early observations to contemporary research, providing a historical perspective for the modern understanding of giant kelp evolution, biogeography, biology, and physiology. The authors furnish a comprehensive discussion of kelp species and forest ecology worldwide, with considerations of human uses and abuses, management and conservation, and the current and likely future impacts of global change. This volume promises to be the definitive treatise and reference on giant kelp and its forests for many years, and it will appeal to marine scientists and others who want a better appreciation and understanding of these wondrous forests of the sea.
(source: Nielsen Book Data)9780520278868 20160618
Marine Biology Library (Miller), Science Library (Li and Ma)
Book
vi, 224 pages : illustrations ; 24 cm
  • 1. Introduction / Richard Sever and Kaaren Janssen
  • 2. A career at a small liberal arts college / Jennifer Punt
  • 3. Core facility management / Claire M. Brown
  • 4. Academic administration / Lydia Villa-Komaroff
  • 5. Careers in science and grant administration: view from the National Institutes of Health / Marion Zatz and Sherry Dupere
  • 6. At the crossroads of science and society: careers in science policy / Amy P. Patterson, Mary E. Groesch, Allan C. Shipp, and Christopher J. Viggiani
  • 7. Working for a scientific society / Martin Frank
  • 8. Leaving the bench and finding your foundation / John E. Spiro
  • 9. Patent law: at the cutting edge of science, but not at the bench / Salim Mamajiwalla
  • 1-. Biotech start-ups and entrepreneurships / Susan Froshauer
  • 11. A career for life scientists in management consulting / Rodney W. Zemmel
  • 12. Medical communications: the "write" career path for you? / Yfke Hager
  • 13. Science journalism and writing / Helen Pearson
  • 14. Career in science publishing / John R.
Marine Biology Library (Miller), Science Library (Li and Ma)
Book
x, 191 pages : illustrations ; 24 cm.
A comprehensive guide to everything scientists need to know about data management, this book is essential for researchers who need to learn how to organize, document and take care of their own data. Researchers in all disciplines are faced with the challenge of managing the growing amounts of digital data that are the foundation of their research. Kristin Briney offers practical advice and clearly explains policies and principles, in an accessible and in-depth text that will allow researchers to understand and achieve the goal of better research data management. Data Management for Researchers includes sections on: * The data problem - an introduction to the growing importance and challenges of using digital data in research. Covers both the inherent problems with managing digital information, as well as how the research landscape is changing to give more value to research datasets and code. * The data lifecycle - a framework for data's place within the research process and how data's role is changing. Greater emphasis on data sharing and data reuse will not only change the way we conduct research but also how we manage research data. * Planning for data management - covers the many aspects of data management and how to put them together in a data management plan. This section also includes sample data management plans. * Documenting your data - an often overlooked part of the data management process, but one that is critical to good management; data without documentation are frequently unusable. * Organizing your data - explains how to keep your data in order using organizational systems and file naming conventions. This section also covers using a database to organize and analyze content. * Improving data analysis - covers managing information through the analysis process. This section starts by comparing the management of raw and analyzed data and then describes ways to make analysis easier, such as spreadsheet best practices. It also examines practices for research code, including version control systems. * Managing secure and private data - many researchers are dealing with data that require extra security. This section outlines what data falls into this category and some of the policies that apply, before addressing the best practices for keeping data secure. * Short-term storage - deals with the practical matters of storage and backup and covers the many options available. This section also goes through the best practices to insure that data are not lost. * Preserving and archiving your data - digital data can have a long life if properly cared for. This section covers managing data in the long term including choosing good file formats and media, as well as determining who will manage the data after the end of the project. * Sharing/publishing your data - addresses how to make data sharing across research groups easier, as well as how and why to publicly share data. This section covers intellectual property and licenses for datasets, before ending with the altmetrics that measure the impact of publicly shared data. * Reusing data - as more data are shared, it becomes possible to use outside data in your research. This chapter discusses strategies for finding datasets and lays out how to cite data once you have found it. This book is designed for active scientific researchers but it is useful for anyone who wants to get more from their data: academics, educators, professionals or anyone who teaches data management, sharing and preservation. "An excellent practical treatise on the art and practice of data management, this book is essential to any researcher, regardless of subject or discipline." -Robert Buntrock, Chemical Information Bulletin.
(source: Nielsen Book Data)9781784270124 20160619
Marine Biology Library (Miller), Science Library (Li and Ma)