Keywords:
Water quality biological assessment.
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Electronic books.
Description / Table of Contents:
Monitoring Ecological Impacts provides the tools needed to design assessment programs that can reliably monitor, detect and allow management of human impacts on the natural environment. The procedures described are well grounded in inferential logic. Step-by-step guidelines and flow diagrams provide clear and useable protocols, which are applicable to real situations.
Type of Medium:
Online Resource
Pages:
1 online resource (448 pages)
Edition:
1st ed.
ISBN:
9780511155703
URL:
https://ebookcentral.proquest.com/lib/geomar/detail.action?docID=201667
DDC:
577.640287
Language:
English
Note:
Cover -- Half-title -- Title -- Copyright -- Dedication -- Contents -- Preface and Acknowledgements -- Part I Introduction to the nature of monitoring problems and to rivers -- 1 Why we need well-designed monitoring programs -- 1.1 HUMAN PRESSURES ON FLOWING WATERS -- 1.2 THE NEED FOR THIS BOOK -- 1.3 THE SCOPE, APPROACH AND INTENDED AUDIENCES OF THIS BOOK -- 1.4 THE STRUCTURE OF THE BOOK AND THE PURPOSE OF EACH OF THE CHAPTERS -- 1.5 IMPORTANT ISSUE -- 2 The ecological nature of flowing waters -- 2.1 RIVERS AND THEIR CATCHMENTS -- 2.2 THE BIOTA OF RIVERS AND STREAMS -- 2.3 CONCEPTS OF RIVER STRUCTURE AND FUNCTIONING -- 2.4 ISSUES OF SCALE AND PATCHINESS IN FLOWING WATERS -- 2.5 IMPORTANT ISSUES -- 3 Assessment of perturbation -- 3.1 TYPES OF DISTURBANCE -- 3.2 THE PURPOSES OF MONITORING -- 3.2.1 To assess the ecological state of ecosystems -- 3.2.2 To assess whether regulated performance criteria have been exceeded -- 3.2.3 To detect and assess the impacts of human-generated disturbance(s) -- 3.2.4 To assess the responses to restoration efforts -- 3.3 IMPORTANT ISSUES -- Part II Principles of inference and design -- 4 Inferential issues for monitoring -- 4.1 SAMPLING -- 4.2 UNCERTAINTY AND PROBABILITY -- 4.3 VARIABLES -- 4.4 ESTIMATION -- 4.5 STATISTICAL MODELS -- 4.5.1 Regression models -- 4.5.2 Analysis of variance (ANOVA) models -- 4.5.3 Fitting models -- 4.5.4 Comparing models -- 4.6 ANALYSES OF VARIANCE (ANOVA) -- 4.6.1 Type of factors -- 4.6.2 Partitioning the variance -- 4.7 HYPOTHESIS-TESTING: CLASSICAL APPROACH -- 4.8 HYPOTHESIS-TESTING: THE BAYESIAN APPROACH -- 4.9 ASSUMPTIONS OF STATISTICAL ANALYSES OF MONITORING PROGRAMS -- 4.10 UNIVARIATE AND MULTIVARIATE ANALYSIS -- 4.11 IMPORTANT ISSUES -- 5 The logical bases of monitoring design -- 5.1 CLASSES OF MONITORING -- 5.2 MONITORING TO DETECT HUMAN IMPACTS ON THE ENVIRONMENT.
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5.2.1 Detecting change -- 5.2.2 Discriminating impacts from natural changes -- 5.3 BACI DESIGNS -- 5.3.1 Natural dynamics and the duration of monitoring -- 5.3.2 Spatial variation and multiple locations -- 5.3.3 Asymmetry in impact assessment monitoring -- 5.4 SCALES OF IMPACT AND MONITORING -- 5.4.1 Sampling within locations - impacts on status -- 5.4.2 Sampling within locations - impacts on variation -- 5.4.3 Sampling within periods - duration and fluctuations in impact -- 5.4.4 Collecting the samples -- 5.4.5 Other considerations -- 5.5 CAREFUL DESIGN IS THE MOST IMPORTANT STEP -- 5.6 IMPORTANT ISSUES -- 6 Problems in applying designs -- 6.1 A BRIEF HISTORICAL SKETCH -- 6.2 PROBLEMS INHERENT IN THE NATURE OF RIVERS -- 6.2.1 Interdependence between locations -- 6.2.2 Variation in time -- 6.2.3 Logistic and technical issues -- 6.3 PROBLEMS ARISING FROM THE TYPES OF VARIABLES USED -- 6.3.1 Variation and imprecision -- 6.3.2 Physicochemical variables as surrogates for biological variables -- 6.3.3 Univariate biological variables -- 6.3.4 Multivariate response variables -- 6.4 SOCIAL, INSTITUTIONAL AND POLITICAL ISSUES -- 6.4.1 Difficulties caused by different backgrounds -- 6.4.2 Insufficient lead time for pre-impact monitoring -- 6.5 IMPORTANT ISSUES -- 7 Alternative models for impact assessment -- 7.1 BACKGROUND OF APPROACHES -- 7.1.1 BACI -- BACIP -- Intervention Analysis -- 7.1.2 MBACI -- 7.1.3 Beyond-BACI -- 7.2 THESE APPROACHES ARE DIFFERENT! -- 7.2.1 Why it matters -- 7.3 FORMAL SAMPLING AND ANALYTICAL FRAMEWORK -- 7.3.1 The sampling program -- BACIP -- MBACI -- Beyond-BACI -- 7.3.2 The analytical models and formal hypotheses -- BACIP -- MBACI -- A special case: MBACI with a single Before and single After sample -- Beyond-BACI -- 7.3.3 Tests for Impact -- BACI and BACIP -- MBACI -- Beyond-BACI -- 7.4 POWER CONSIDERATIONS -- 7.4.1 BACI and BACIP.
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7.4.2 MBACI -- 7.4.3 Beyond-BACI -- 7.5 DETECTING MORE SUBTLE EFFECTS -- 7.6 EXTENT OF IMPACTS -- 7.7 FLEXIBLE ANALYSIS/INFLEXIBLE HYPOTHESIS -- 7.8 IMPORTANT ISSUES -- Part III Applying principles of inference and design -- 8 Applying monitoring designs to flowing waters -- 8.1 SPATIAL VARIATION AND THE LOCATION OF CONTROLS -- 8.1.1 The nature of controls -- 8.1.2 Spatial extent and nature of impact -- 8.1.3 Finding control locations -- Criteria for controls -- The dilemma of the trade-off in similarity and number of controls -- Statistical independence and location of controls -- Ensuring control locations are free of the human impact -- Spatial confounding, environmental differences and location of controls -- The relative significance of problems with controls -- How many control locations are necessary? -- 8.1.4 Subsampling of locations -- 8.1.5 Examples of decision trees for finding and choosing controls -- 8.2 TEMPORAL VARIATION, AND BEFORE AND AFTER SAMPLING -- 8.2.1 Temporal extent and nature of impact -- 8.2.2 Frequency of sampling within Periods -- 8.2.3 Subsamples within Times -- 8.2.4 Statistical independence and sampling through time -- 8.3 DOING THE SAMPLING -- 8.4 A WORKED EXAMPLE - EFFECTS OF LIMING TO DECREASE ACIDITY -- 8.4.1 Background to the problem and preliminary data -- 8.4.2 Selection of control and impact locations -- 8.4.3 Predictions and data collection -- 8.4.4 Results and analysis -- 8.5 IMPORTANT ISSUES -- 9 Inferential uncertainty and multiple lines of evidence -- 9.1 A BRIEF REVISIT OF INFERENTIAL UNCERTAINTY AND PROBABILITY -- 9.2 A LEVELS-OF-EVIDENCE APPROACH -- 9.3 A SUGGESTED STEP-BY-STEP GUIDE TO USING A LEVELS-OF-EVIDENCE APPROACH -- 9.3.1 Defining and quantifying causal criteria -- Strength of association -- Consistency of association -- Specificity of association -- Temporality.
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Biological or ecological gradient -- Biological or ecological plausibility -- Experimental evidence -- Analogy -- 9.3.2 Building a 'levels-of-evidence' case for changes associated with the human impact -- 1. Set down the characteristics of the human activity -- 2. Set down the characteristics of the impact location -- 3. Clarify the question(s) -- 4. Decide how an effect will be considered to have been 'detected' -- 5. Decide upon the qualities of studies to be included in the review -- 6. Carry out a broad-ranging review, extracting relevant data -- 9.3.3 Collating common sources of natural variance in the response variables -- 9.3.4 Cataloguing effects -- 9.3.5 Predictions and ways of ruling out alternative explanations -- After impact with data from the impact location only -- 9.3.6 Assessing the predictions -- 9.4 SOME FINAL COMMENTS ON THE PROCESS -- 9.5 IMPORTANT ISSUES -- 10 Variables that are used for monitoring in flowing waters -- 10.1 CONSIDERATIONS FOR CHOOSING VARIABLES -- 10.1.1 Questions addressed by the monitoring program -- 10.1.2 Causality, mechanisms, inference -- 10.1.3 Ecological and socioeconomic significance of change -- 10.1.4 Efficiency -- 10.2 RELATIVE WEIGHTING OF ATTRIBUTES -- 10.3 IMPORTANT ISSUES -- 11 Defining important changes -- 11.1 WHY DO WE NEED TO DEFINE CHANGES IN TERMS OF 'EFFECT SIZES'? -- 11.2 KINDS OF CHANGE, RISKS AND CONSEQUENCES -- 11.3 PRACTICAL STEPS, AND SOME DIFFICULTIES, IN SETTING AN EFFECT SIZE -- 11.3.1 A caricature of how this seems to work for drinking water -- 11.3.2 Quantifying the relationship between the response variable and the potential impact -- 11.3.3 Negotiating about values, risks and consequences -- 11.4 IMPORTANT ISSUES -- 12 Decisions and trade-offs -- 12.1 MAKING STATISTICAL DECISIONS -- 12.2 BALANCING TYPE I AND TYPE II ERRORS -- 12.2.1 Fixed Alpha, adjust n.
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12.2.2 Fixed Beta, adjust n and Alpha -- 12.2.3 Scalable decision criteria -- 12.3 COST-BENEFIT ANALYSIS AND DESIGN -- 12.4 FURTHER VARIATIONS ON BALANCED DECISION-MAKING -- 12.5 IMPORTANT ISSUES -- 13 Optimization -- 13.1 WHAT WE MEAN BY OPTIMIZATION -- 13.2 BY NOW YOU SHOULD HAVE… -- 13.3 YOU WILL NEED AN ESTIMATE OF VARIANCE -- 13.3.1 Sources of variance estimates -- 13.4 DEVELOPING AN IDEALIZED SAMPLING SCHEME… -- 13.4.1 Form of output -- 13.5 TRADING OFF -- 13.5.1 Spend more -- 13.5.2 Live with increased risk -- 13.5.3 Maintaining the risk, reducing the cost -- Eliminating variables -- Sampling more cheaply -- 13.5.4 Accepting larger effect sizes -- 13.6 UNCERTAINTY IN OPTIMIZATION -- 13.6.1 Origins of uncertainty -- 13.6.2 Incorporating capacity for readjusting the sampling program -- 13.7 POST-MONITORING 'OPTIMIZATION': IMPLICATIONS FOR DECISION CRITERIA -- 13.8 A WORKED EXAMPLE - LIMING TO DECREASE ACIDITY OF STREAMS -- 13.8.1 Nomination of an important effect size -- 13.8.2 Deciding the relative costs of Type I and II errors -- 13.8.3 Deciding the actual probability of errors -- 13.8.4 Use of pilot data and power analysis to examine the number of locations needed in the monitoring program -- 13.8.5 Trading off costs and risks -- Spend more money? -- Live with increased risks? -- Reduce the cost of sampling? -- 13.8.6 Implications from this example -- 13.9 IMPORTANT ISSUES -- 14 The special case of monitoring attempts at restoration -- 14.1 ISSUES CONCERNING THE STUDY OF ECOLOGICAL RESTORATION -- 14.2 CAN BACI DESIGNS BE APPLIED TO ECOLOGICAL RESTORATION? -- 14.2.1 The real way that restoration differs -- 14.3 ANALYTICAL TECHNIQUES APPLICABLE TO RESTORATION MONITORING -- 14.3.1 The logic of specifying an effect size for recovery -- 14.4 HOW LONG SHOULD WE MONITOR ATTEMPTS AT RESTORATION?.
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14.5 THE NEED FOR CLARITY IN DECLARING THE GOALS OF RESTORATION.
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