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Conservation of Wildlife Populations : Demography, Genetics, and Management | WorldCat.org

Intro

Title page

Copyright page

Contents

List of boxes

Preface to second edition

Preface to first edition

List of symbols

Acknowledgments for second edition

Acknowledgments for first edition

PART I: Background to Applied Population Biology

CHAPTER 1: The big picture: human population dynamics meet applied population biology

Introduction

Population Ecology of Humans

Human population growth

Human impacts on wildlife through effects other than population size

Extinction Rates of Other Species

Number of species on Earth: described and not yet described

Historic versus current rates of extinction

Humans and Sustainable Harvest

The Big Picture

Further Reading

CHAPTER 2: Designing studies and interpreting population biology data: how do we know what we know?

Introduction

Obtaining Reliable Facts Through Sampling

Replication and randomization

Controls

Accuracy, error, and variation

Linking Observed Facts to Ideasmind Leads to Understanding

The hypothetico-deductive (HD) approach

Three ways to test hypotheses

Model selection based on information-theoreticmethods

Bayesian statistics: updating knowledge withnew information

Ethics and the Wildlife Population Biologist

Summary

Further Reading

CHAPTER 3: Genetic concepts and tools to support wildlife population biology

Introduction

What Is Genetic Variation?

Genetic Markers Used in Wildlife Population Biology

Fragment analysis

Microsatellite DNA

Single nucleotide polymorphisms (SNPs)

Genes that affect fitness: functional genomics, adaptive variation, and transcriptomics

Insights into Wildlife Population Biology Using Genetic Tools

Taxonomy and hybridization

Determining species identity and distribution

Determining gender and individual identity

Summary. All Vital Rates are not Created Equal: Analytical Sensitivities and Elasticities

Stochasticity in Age and Stage-Structured Populations

Sensitivity Analysis in the Broad Sense to Help Evaluate Management Actions

Sensitivity analysis method 1: manual perturbation

Sensitivity analysis method 2: analytical sensitivity and elasticity analysis

Sensitivity analysis method 3: life-stage simulation analysis

Fitness is Lambda, Selection is Management

Case Studies Using Matrix Models to Guide Conservation Decision-Making

Case study 1: what are the best management actions to recover an endangered species?

Case study 2: prioritizing recovery actions in Sierra Nevada bighorn sheep using asymptotic and nonasymptotic sensitivity analysis

Case study 3: what are the most efficient management actions to reduce a pest population?

Case study 4: how should a harvested species be managed?

Summary

Further Reading

CHAPTER 7: Density-dependent population change

Introduction

Negative Density Dependence

The Logistic: One Simple Model of Negative Density-Dependent Population Growth

Some Counterintuitive Dynamics: Limit Cycles and Chaos

Positive Density Dependence

Negative and Positive Density Dependence Operate Together

Component Versus Demographic Outcomes of Density Dependence

Summary

Further Reading

CHAPTER 8: Predation and wildlife populations

Introduction

Does Predation Affect Prey Numbers?

Factor 1. Determining How Predation Affects Prey Numbers: Predation Rate

Numerical responses of predators

Functional responses of predators

Total predation rate

Factor 2. Determining How Predation Affects Prey Numbers: Compensation

Factor 3. Determining How Predation Affects Prey Numbers: Who Gets Killed

Summary

Further Reading. CHAPTER 9: Genetic variation and fitness in wildlife populations

Introduction

Long-Term Benefits of Genetic Variation

Genetic variation allows long-term adaptation

Genetic variation provides ecosystem services

What Determines Levels of Genetic Variation in Populations?

The big four: mutation, gene flow, natural selection, and genetic drift

The genetic effective population size

Genetic changes due to population fragmentation

Quantifying the Loss of Heterozygosity: The Inbreeding Coefficient

Defining inbreeding

Estimating the inbreeding coefficient in wildlife populations

When Does Inbreeding Due to Genetic Drift Lead to Inbreeding Depression?

Inbreeding depression in wildlife populations

Can wild populations adapt to inbreeding through purging?

Another genetic mechanism that could reduce vital rates: mutations in mtDNA

Inbreeding depression meets other concerns in fragmented populations

Outbreeding Depression and the Loss of Local Adaptation

Genetic Rescue, Genetic Restoration, and Long-Term Population Recovery

Appropriate Levels of Genetic Connectivity

Case Studies Where Genetic Rescue Meets the Real World

Greater prairie chicken

Rocky Mountain bighorn sheep

Adder

Wolves of several types: Scandinavian, Mexican, and US

Florida panther

Summary

Further Reading

CHAPTER 10: Dynamics of multiple populations

Introduction

What Is Connectivity?

Consequences of Connectivity for Wildlife Populations

Persistence and fluctuations of populations

Colonization and recolonization of empty sites

Abundance of populations providing dispersers

Taxonomic designation

Measuring Connectivity among Wildlife Populations

Radiotelemetry and mark-recapture

Genetic approaches

Multiple Populations are Not All Equal

Multiple isolated populations

Metapopulations. Further Reading

CHAPTER 4: Estimating population vital rates

Introduction

Estimating Abundance and Density

Background: censusing, estimating, and indexing abundance

Transect methods for estimating abundance

Sightability or observation probability models

Capture-mark-recapture (CMR) methods for estimating abundance

Robust design

Density estimation in capture-mark-recapture studies

Survival Estimation

Known-fate models

CMR using the Cormack-Jolly-Seber method

Band-return approaches

Other approaches

Estimation of Reproduction

Sex Ratio

Sex ratios in the wild

Summary

Further Reading

PART II: Population processes: the basis for management

CHAPTER 5: The simplest way to describe and project population growth: exponential or geometric change

Introduction

Fundamentals of Geometric or Exponential Growth

Discrete (geometric) growth

Continuous (exponential) growth

Overview of λ and r

Doubling time

Causes and Consequences of Variation in Population Growth

Factors that cause population growth to fluctuate

Implications of variation in population growth

Quantifying Exponential Population Growth in a Stochastic Environment

Exponential growth with observation error only (EGOE)

Exponential growth with process noise only (EGPN)

Process noise and observation error occurring simultaneously (EGSS)

Summary

Further Reading

CHAPTER 6: All stage classes are not equal in their effects on population growth: structured population-projection models

Introduction

Anatomy of a Population-Projection Matrix

How Timing of Sampling Affects the Matrix

Projecting a Matrix Through Time Leads to Transient and Asymptotic Dynamics

How to project the matrix

Stable stage distribution, transient dynamics, and reproductive value