| Description |
1 online resource |
| Series |
Conservation Biology ; 22 |
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Conservation Biology ; 22
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| Contents |
Cover -- Half-title -- Series information -- Title page -- Copyright information -- Dedication -- Table of contents -- List of contributors -- Acknowledgements -- 1 Introduction -- 1.1 The Need For This Book -- 1.2 A Short History of Quantitative Approaches to Biodiversity Conservation -- 1.3 Frameworks For Conservation Decision-Making -- 1.3.1 Decision Theory and Its Application to Conservation... -- 1.3.2 Adaptive Management -- 1.3.3 Management Strategy Evaluation -- 1.4 Overview of the Book -- Part I Approaches to Decision-Making -- 2 Fisheries Science and Participatory Management Strategy Evaluation: Eliciting Objectives, Visions and System Models -- 2.1 Introduction -- 2.2 Case Studies -- 2.2.1 South-East Shark and Scale Fishery -- 2.3 Data-Poor and Minimum Realistic MSEs -- 2.4 Multi-Industry, Multi-Jurisdiction MSEs -- 2.5 What Has Been Learnt -- 2.6 Conclusions -- 3 Rapid Prototyping for Decision Structuring: An Efficient Approach to Conservation Decision Analysis -- 3.1 Introduction -- 3.2 Structured Decision-Making -- 3.3 Rapid Prototyping for Structured Decision-Making -- 3.3.1 What Is Rapid Prototyping? -- 3.3.2 The Diagnostic Phase -- Developing the Decision Structure -- 3.3.3 Refining the Prototype -- 3.3.4 Identifying Participants -- 3.3.5 Subsequent Prototypes and the Stopping Point -- 3.4 A Typology of Outcomes from Rapid Prototyping for SDM -- 3.4.1 Resolving the Decision Challenge -- 3.4.2 Identifying the Need for Specific Subject Matter Expertise or Information -- 3.4.3 Identifying Information Gaps that Require New Research -- 3.4.4 Identifying the Need for Adaptive Management to Resolve Critical Uncertainties -- 3.5 Conclusions -- 4 Understanding Uptake of Decision-Support Models in Conservation and Natural Resource Management -- 4.1 Introduction -- 4.2 Methods and Measurements -- 4.2.1 Recruitment and Participants |
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4.2.2 Measuring Intentions versus Behaviour -- 4.3 Results and Discussion -- 4.3.1 Knowledge -- 4.3.2 Trust -- 4.3.3 When Good Intentions Fail to Translate into Behaviour: Managing Change and External Barriers to Model Uptake -- 4.3.3.1 Our Prior Beliefs -- 4.3.3.2 What We Have Learned -- 4.3.4 Where Does That Leave Us? -- 4.4 Conclusions -- Acknowledgements -- 5 Understanding Human Well-being for Conservation: A Locally Driven, Mixed Methods Approach -- 5.1 Introduction -- 5.2 What Is Human Well-being? -- 5.3 The Significance of Non-Material Well-being to Conservation -- 5.4 Researching Well-being for Conservation: Applying the Framework -- 5.4.1 Developing Indicators Based on Locally Driven Qualitative Understanding -- 5.4.2 Understanding and Measuring Subjective Well-being -- 5.4.3 Understanding the Relational Dimension of Well-being -- 5.5 The Importance of Mixed Methods -- 5.6 Using Well-being Assessments to Inform Decision-Making -- 5.6.1 Defining Objectives and Targets -- 5.6.2 Designing Conservation Strategies and Negotiating Trade-Offs -- 5.6.3 Monitoring, Evaluation and Adaptive Management -- 5.7 Challenges and Future Directions -- 5.8 Conclusions -- Part II Challenges in Implementation -- 6 Implementing Decision Analysis Tools for Invasive Species Management -- 6.1 Introduction -- 6.2 Background -- 6.3 Project Establishment -- 6.4 Preliminary Modelling -- 6.5 Spatial Allocation of Annual Control Effort -- 6.6 Long-Term Strategy: Structured Decision-Making Workshop -- 6.7 Data Collection and Data Management -- 6.7.1 Distribution of Grey Sallow on the Bogong High Plains and in Surrounding Catchments -- 6.7.2 The Effectiveness of Grey Sallow Control -- 6.7.3 Willow Population Processes: Patterns of Establishment after Fire and Age at Maturity -- 6.7.4 Willow Control Effort -- 6.7.5 Data Management -- 6.8 Current Status -- 6.9 Reflections |
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6.9.1 Researcher's Perspective -- Joslin Moore -- 6.9.2 Research Manager's Perspective -- Marie Keatley -- 6.9.3 Environmental Programme Manager's Perspective -- Charlie Pascoe -- 6.9.4 Ranger's Perspective -- Elaine Thomas -- 6.10 Conclusions -- 7 Using Management Strategy Evaluation as a Framework for Improving Conservation... -- 7.1 Introduction -- 7.2 Case Study: The Serengeti -- 7.3 Opportunities and Barriers for Implementing Management Strategy Evaluation -- 7.3.1 Why an MSE for the Serengeti? -- 7.3.2 Our Approach and Some Lessons Learnt -- 7.3.2.1 Harvest and Population Dynamics -- 7.3.2.2 Wildlife Monitoring -- 7.3.2.3 Measuring Illegal Hunting -- 7.3.2.4 Assessment -- 7.3.2.5 Implementation -- 7.3.3 Some Lessons Learnt -- 7.3.3.1 MSE as a Unifying Framework -- 7.3.3.2 MSE as a Diagnostic Tool -- 7.3.3.3 Tool Flexibility -- 7.3.3.4 Limited Feedback between Monitoring and Management Actions -- 7.3.3.5 Challenges in Interdisciplinary Collaborations -- 7.3.3.6 Stakeholder Engagement and Representation -- 7.4 An Ideal Management Strategy Evaluation Approach for the Serengeti -- Step 1: Stakeholder Analysis, Engagement and Representation -- Step 2: Specification and Quantification of Management Objectives -- Step 3: Development and Parameterisation of the MSE Model -- (a) Modelling Hunter Decisions -- (b) Modelling Implementation of Management Advice -- (c) Modelling Monitoring of Hunter Behaviour -- Step 4: Identification, Simulation and Evaluation of Candidate Strategies -- Step 5: Summary of Performance and Selection of the Management Strategy -- 7.5 Conclusions -- Acknowledgements -- 8 The Use of Quantitative Models in the Harvest Management of Wild Ungulates... -- 8.1 Introduction -- 8.2 Contrasting Socio-Ecological Systems Creates Contrasting Trade-offs |
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8.3 Comparing the Use of Models in Ungulate, Carnivore and Small Game Management: Norway as a Case Study -- 8.4 Conclusions -- 9 Linking Biodiversity Indicators with Global Conservation Policy -- 9.1 Introduction -- 9.2 Indicator-Policy Cycle: Linking Target, Policy, Action and Monitoring -- 9.3 How Can Indicator Performance Be Tested? -- 9.4 Are Current Biodiversity Indicators Fit for Purpose? -- 9.4.1 Marine Trophic Index -- 9.4.2 Red List Index -- 9.4.3 Living Planet Index -- 9.5 Conclusions -- 10 Synthesis: Moving Forward Together -- 10.1 The Role of Models in Modern Conservation -- 10.2 Lessons from the Case Studies -- 10.2.1 Participation and People -- 10.2.2 Trade-Offs, Power and Politics -- 10.2.3 Challenges for the Modeller -- 10.2.4 Thinking to the Future -- 10.3 How Far into Conservation Can This Approach Be Taken? -- 10.3.1 Moving into More Complex Situations -- 10.3.2 Supporting Conflict Resolution -- 10.3.3 New Approaches to Predicting Human Behaviour -- 10.4 Decision-Making in a Dynamic World -- 10.4.1 Integration into Adaptive Management -- 10.4.2 Aiming for Optimality? -- 10.5 New Technologies and Expanding Horizons -- 10.6 A Way of Thinking, Not a One-Off Event -- References -- Index |
| Summary |
Making decisions about the management and conservation of nature is necessarily complex, with many competing pressures on natural systems, opportunities and benefits for different groups of people and a varying, uncertain social and ecological environment. An approach which is narrowly focused on either human development or environmental protection cannot deliver sustainable solutions. This volume provides frameworks for improving the integration of natural resource management with conservation and supporting stronger collaboration between researchers and practitioners in developed and developing countries. Novel approaches are required when ecological and social dynamics are highly interdependent. A structured, participatory, model-based approach to decision-making for biodiversity conservation has been proven to produce real-world change. There are surprisingly few successful case studies, however; some of the best are presented here, from fisheries, pest management and conservation. Researchers and practitioners need this interdisciplinary approach, focused on quantitative tools that have been tested and applied, and learning from success |
| Bibliography |
Includes bibliographical references and index |
| Notes |
Print version record |
| Subject |
Nature conservation -- Decision making
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Natural resources -- Management -- Decision making
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Natural resources -- Management.
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Natural resources -- Management -- Decision making
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| Form |
Electronic book
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| ISBN |
9781316135938 |
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1316135934 |
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