White / Garrott Analysis of Wildlife Radio-Tracking Data

1. Auflage 2012
ISBN: 978-0-08-092657-5
Verlag: Elsevier Science & Techn.
Format: EPUB
Kopierschutz: 6 - ePub Watermark

E-Book, Englisch, 383 Seiten

With the substantial advances in the miniaturization of electronic components, wildlife biologists now routinely monitor the movements of free-ranging animals with radio-tracking devices. This book explicates the many analytical techniques and computer programs available to extract biological information from the radio tracking data. - Presentation of software programs for solving specific problems - Design of radio-tracking studies - Mechanics of data collection - Estimation of position by triangulation - Graphic presentation of animal migration, dispersal, fidelity, and association - Home range estimation, habitat utilization, and estimation of survival rates and population size

Zielgruppe

Academic/professional/technical: Undergraduate. Academic/professional/technical: Postgraduate. Academic/professional/technical: Research and professional

Autoren/Hrsg.

White, Gary C.

Garrott, Robert A.

Inhaltsverzeichnis

1;Front Cover;1
2;Analysis of Wildlife Radio-Tracking Data;4
3;Copyright Page;5
4;Table of Contents;6
5;Preface;12
6;Chapter 1. Preliminaries;16
6.1;Map Coordinate Systems;17
6.2;Entry of Data for Computer Processing;21
6.3;Summary;25
6.4;References;25
7;Chapter 2. Design of Radio-Tracking Studies;28
7.1;Radio-Tracking Studies and the Scientific Method;28
7.2;Treatments, Controls, and Replicates;32
7.3;Sampling and Statistical Considerations;34
7.4;Field Considerations;36
7.5;Final Thoughts;37
7.6;Summary;38
7.7;References;38
8;Chapter 3. Effects of Tagging on the Animal;42
8.1;Design of Experiments to Detect Effects of Transmitters on Animals;43
8.2;Effects of Transmitters on Animals;50
8.3;Summary;53
8.4;References;53
9;Chapter 4. Estimating Animal Locations;56
9.1;Nontriangulation Location Techniques;57
9.2;Triangulation Location Techniques;62
9.3;Performance of Lenth's Estimators;84
9.4;Data Quality Control and Censoring;87
9.5;Summary;89
9.6;References;90
10;Chapter 5. Designing and Testing Triangulation Systems;94
10.1;Measuring Accuracy of Directional Bearings;95
10.2;Special Considerations for Mobile Triangulation Systems;105
10.3;Designing the Triangulation System;109
10.4;Summary;125
10.5;References;126
11;Chapter 6. Simple Movements;128
11.1;Identifying and Correcting Data Errors;128
11.2;Still Graphics;130
11.3;Animated Graphics;134
11.4;Migration and Dispersal;136
11.5;Measuring Fidelity;148
11.6;Animal Association;152
11.7;Sample Size;155
11.8;Summary;156
11.9;References;156
12;Chapter 7. Home Range Estimation;160
12.1;Independence of Observations;162
12.2;Minimum Convex Polygon;163
12.3;Bivariate Normal Models;170
12.4;Nonparametric Approaches;181
12.5;Computer Programs for Home Range Calculation;188
12.6;Extension of Home Range Estimators;189
12.7;Evaluating Home Range Estimators;189
12.8;Similarity of Home Ranges;190
12.9;Preferred Home Range Estimator;193
12.10;Usefulness of the Home Range Concept;193
12.11;Summary;194
12.12;References;195
13;Chapter 8. Habitat Analysis;198
13.1;Availability;198
13.2;Utilization;200
13.3;Preference;201
13.4;Critical Habitat;213
13.5;Accuracy of Radio-Tracking Locations;215
13.6;Home Range Approach;216
13.7;Sample Size;217
13.8;Summary;218
13.9;References;219
14;Chapter 9. Survival Rate Estimation;222
14.1;Binomial Distribution;223
14.2;Parameter Estimation by Numerical Methods;228
14.3;Program SURVIV;230
14.4;Methods Incorporating Time Until Death;241
14.5;Medical Survival Analysis;257
14.6;Summary;266
14.7;References;267
15;Chapter 10. Population Estimation;270
15.1;Capture—Recapture Estimation;270
15.2;Line Transects;284
15.3;Aerial Surveys;284
15.4;Summary;284
15.5;References;285
16;Chapter 11. Data Analysis System;286
16.1;Need for Analysis System for Radio-Tracking Data;286
16.2;Data Analysis System Design;288
16.3;Current Directions;289
16.4;Summary;290
16.5;References;290
17;Appendix 1. Introduction;292
18;Appendix 2. FIELDS: Radio-Tracking Data Preprocessor;308
19;Appendix 3. BIOCHECK: Radio-Tracking Data Checking;310
20;Appendix 4. BIOPLOT: Radio-Tracking Data Plotting and Editing;314
21;Appendix 5. HOMER: Home Range Estimation;316
22;Appendix 6 PC SURVIV User's Manual Version 1.4;322
23;Appendix 7. SAS Home Range Estimation Procedures;358
24;Appendix 8. Survival Estimation Computer Listings;376
25;Appendix 9. SAS Monte Carlo Simulation of Capture-Recapture;382
26;Index;388

Leseproben

Chapter 2 Design of Radio-Tracking Studies
Radio-tracking provides a useful technique for studying the mechanics of wildlife populations. Movements (Chapter 6) provide information on how animals use the environment, migration patterns, dispersal, and activity patterns. Home range estimates (Chapter 7) quantify the area used by an animal. Habitat use studies provide information on habitat preference and, if properly defined, can provide information on the need for various habitat types (Chapter 8). Survival studies provide estimates of mortality rates (Chapter 9), and population estimation (Chapter 10) studies estimate the number of animals in the population. However, whether radio-tracking should be used in a study depends on the objectives of the study, the type of data to be collected, and the constraints put on the investigator regarding funding, field conditions, equipment limitations, and the species under study. The purpose of this chapter is to discuss the design of wildlife radio-tracking studies, with particular emphasis on conducting experiments to demonstrate cause-and-effect relationships. Radio-Tracking Studies and the Scientific Method
A key step in the implementation of any radio-tracking study is careful design. Although this may seem obvious to most readers, it is an extremely important point which is occasionally overlooked or ignored by telemetry users. Sargeant (1980:58) stated, “It is likely that more money and effort have been wasted on ill-conceived radio-tracking studies than on the use of any other field technique.” It appears that the reason for these “ill-conceived” studies is the general attitude of some investigators that, by placing transmitters on a handful of animals and “tracking” them, one is guaranteed to obtain good biological data. This fact could not be further from the truth. Radio-tracking is nothing more than a specialized technique available to the investigator along with hundreds of other techniques for collecting information. A similar opinion has been expressed by Lance and Watson (1979:113): … the purely descriptive study based on no apparent hypothesis and in which the objective is merely general information. Such a use of radio-tracking might be legitimate for exploring a wholly unknown subject, but these are few in ecology nowadays, and miscellaneous data-gathering is a poor reflection of the technique’s true potential. To avoid this pitfall when planning a radio-tracking study we suggest applying the five steps of the basic scientific method. The first step is defining the scope of the problem to be addressed. Some studies may have very specific objectives and, hence, a detailed definition of the problem can be formulated at the very outset of the planning process. Often, however, the scope of a study is quite broad, leading to a very general definition. The second step is to study existing information that pertains to the defined problem. This can be a tedious and time-consuming process if a large body of literature has been published in the field of interest, but the time is well spent. Reviewing the results of previous studies allows one to become familiar with the current “state of knowledge” and aids in the formulation of specific hypotheses, the third step in the scientific method. This is an important step in the planning process, as explicitly defining each hypothesis to be tested before the study begins allows the investigator to design data collection procedures and statistical tests that will optimize one’s chance of obtaining conclusive results. Once methodology and sample size decisions have been made, the fourth step, data collection, is initiated. The final step in the scientific method is careful analysis of the data, allowing the investigator to draw conclusions about rejecting the hypotheses tested. Wildlife radio-tracking studies can be divided into three basic conceptual designs: descriptive, correlational, and manipulative. The procedures outlined in the scientific method can be applied in all three designs, but are routinely used only in manipulative studies. Descriptive studies use radio-tracking to observe natural behavioral processes, usually with no attempt at hypothesis formulation or testing before the data are collected. Such studies are very common among telemetry users and include general investigations of home range size and shape and seasonal and daily movements. These studies are useful in learning more about the natural history of a species, but are limited to learning what an animal does, not why the animal is doing it (Sanderson 1966). To illustrate this point, consider a study of habitat utilization. A group of instrumented ungulates is located at random times throughout the day to determine the habitats used. Thus, the primary result of this descriptive study is the proportion of time an individual animal spends in each habitat type. The investigator now knows the animal’s location, but not why the animal used a particular habitat type or what it was doing while in that habitat. A more informative approach would be to formulate one or more hypotheses and design a correlational study to determine whether the behavior of the monitored animals supports this hypothesis. For example, the instrumented animals have available three habitat types, a grass–forb community, a low shrub community, and a closed-canopy forest community. One possible hypothesis is that as the ambient air temperature increases, the ungulates select habitats with a vegetative structure that provides thermal cover (i.e., reduced temperatures). To test this hypothesis, the investigator monitors the microclimate temperatures in each of the habitat communities while simultaneously tracking the ungulates. Results of the study may support the hypothesis, in that the temperatures within the forest community were consistently lower than the temperatures in the grassland and shrub communities. In addition, as the temperatures rose in the nonforested communities, the animals tended to avoid these habitats and occupy the forested community. In this example, a correlation is developed between elevated air temperatures and use of the forest habitat type, providing the investigator with more information than a descriptive study. However, the investigator must be aware that in a correlational study, a relationship between two or more variables does not imply cause and effect. In other words, the data do not indicate that higher air temperatures caused the animals to move from the grassland and shrub communities to the forest community, although a correlation is present. Other factors not monitored during the study may have been responsible for the observed response. In our temperature–ungulate example, lack of harassment from parasitic insects, rather than air temperature, may cause the animal to use the forest habitat. Similarly, evidence that a habitat was selectively used (i.e., occupied in higher proportion than its availability) does not imply that the habitat is “critical” to the animal’s well-being. Manipulative studies require that the system be perturbated. In order to conclusively demonstrate that a particular habitat type is needed to insure the welfare of a population, that habitat must be made unavailable to the population and the decline in the individual’s health and/or the fitness of the population demonstrated. Thus, the study design requires an experimental approach, with appropriate manipulations (treatments), controls, and replicates. One experimental approach to the ungulate habitat example would be to monitor microclimate temperature in each of the three habitats on four study areas while simultaneously tracking instrumented animals. After the preliminary data are collected, showing a correlation between increased air temperatures and use of the forest habitat, two of the study areas are randomly selected for treatment. Ideally, the treatment should only involve altering the variable of interest, in this case, artificially increasing the air temperature within the forest habitat. A more practical treatment, however, may be removal of the forest canopy. Data on air temperature and habitat use would again be collected on all four areas and results compared between times for each study area and between the treatment and control areas. If the data from the controls were similar between monitoring periods, there were no effects due to time, and any changes in the treatments could be attributed to the perturbation. The above example is an over-simplification, but it illustrates the importance of manipulative studies. While descriptive and correlational studies may provide insights into why animals behave in a particular manner, manipulative experiments, including both time and geographic controls, are needed to obtain conclusive results about why animals behave as they do. Consider another, even simpler, example of the importance of experimental manipulations as opposed to correlational studies. You are watching television, when the screen begins to scroll. Two possible explanations (hypotheses) are: (1) your television failed or (2) the broadcasting station failed. How do you decide which of these hypotheses is incorrect? Without hesitating, you switch channels, performing the manipulative experiment to distinguish between the two possible hypotheses. Without the manipulation of changing channels, you have no information to decide between the two explanations. Even in everyday life, we use experimental manipulations to collect...