Preface to the Princeton Landmarks in Biology Edition vii Preface xi Symbols Used xiii 1. The Importance of Islands 3 2. Area and Number of Speicies 8 3. Further Explanations of the Area-Diversity Pattern 19 4. The Strategy of Colonization 68 5. Invasibility and the Variable Niche 94 6. Stepping Stones and Biotic Exchange 123 7. Evolutionary Changes Following Colonization 145 8. Prospect 181 Glossary 185 References 193 Index 201

The Theory of Island Biogeography

Information theoretic approaches and model averaging are increasing in popularity, but this approach can be difficult to apply to the realistic, complex models that typify many ecological and evolutionary analyses. This is especially true for those researchers without a formal background in information theory. Here, we highlight a number of practical obstacles to model averaging complex models. Although not meant to be an exhaustive review, we identify several important issues with tentative solutions where they exist (e.g. dealing with collinearity amongst predictors; how to compute model-averaged parameters) and highlight areas for future research where solutions are not clear (e.g. when to use random intercepts or slopes; which information criteria to use when random factors are involved). We also provide a worked example of a mixed model analysis of inbreeding depression in a wild population. By providing an overview of these issues, we hope that this approach will become more accessible to those investigating any process where multiple variables impact an evolutionary or ecological response.

https://www.otago.ac.nz/threatenedbirdgroup/Publications_files/Grueber_et%20al%20JEB_2011_incl%20Corrigendum.pdf

Multimodel inference in ecology and evolution: challenges and solutions

Rates of hybridization and introgression are increasing dramatically worldwide because of translocations of organisms and habitat modifications by humans. Hybridization has contributed to the extinction of many species through direct and indirect means. However, recent studies have found that natural hybridization has played an important role in the evolution of many plant and animal taxa. Determining whether hybridization is natural or anthropogenic is crucial for conservation, but is often difficult to achieve. Controversy has surrounded the setting of appropriate conservation policies to deal with hybridization and introgression. Any policy that deals with hybrids must be flexible and must recognize that nearly every situation involving hybridization is different enough that general rules are not likely to be effective. We provide a categorization of hybridization to help guide management decisions

https://www.cell.com/trends/ecology-evolution/pdf/S0169-5347(01)02290-X.pdf

The problems with hybrids: setting conservation guidelines

The purpose of this review is to clarify the concepts of bias, precision and accuracy as they are commonly defined in the biostatistical literature, with our focus on the use of these concepts in quantitatively testing the performance of point estimators (specifically species richness estimators). We first describe the general concepts underlying bias, precision and accuracy, and then describe a number of commonly used unscaled and scaled performance measures of bias, precision and accuracy (e.g. mean error, variance, standard deviation, mean square error, root mean square error, mean absolute error, and all their scaled counterparts) which may be used to evaluate estimator performance. We also provide mathematical formulas and a worked example for most performance measures. Since every measure of estimator performance should be viewed as suggestive, not prescriptive, we also mention several other performance measures that have been used by biostatisticians or ecologists. We then outline several guidelines of how to test the performance of species richness estimators: the detailed description of data simulation models and resampling schemes, the use of real and simulated data sets on as many different estimators as possible, mathematical expressions for all estimators and performance measures, and the presentation of results for each scaled performance measure in numerical tables with increasing levels of sampling effort. We finish with a literature review of promising new research related to species richness estimation, and summarize the results of 14 studies that compared estimator performance, which confirm that with most data sets, non-parametric estimators (mostly the Chao and jackknife estimators) perform better than other estimators, e.g. curve models or fitting species-abundance distributions.

http://viceroy.eeb.uconn.edu/estimates/EstimateSPages/EstSUsersGuide/References/WaltherAndMoore2005.pdf

The concepts of bias, precision and accuracy, and their use in testing the performance of species richness estimators, with a literature review of estimator performance

James G. Wiener, David P. Krabbenhoft, Gary H. Heinz, and Anton M. ScheuhammerCONTENTS16.1 Introduction 409
16.2 Evolution of the Environmental Mercury Problem 410
16.3 Global-Scale Environmental Cycling and Fate 413
16.4 Mercury Speciation and Environmental Concentrations 415

Ecotoxicology of Mercury

Temporal variation of demographic characteristics for animal populations is of interest to both ecologists and biological modelers. The standard deviation of a series of estimated parameter values (e.g., estimated population size) or some function thereof (e.g., log of the estimated parameters) is commonly used as a measure of temporal variability. These measures of temporal variation overestimate the true temporal variation by not accounting for sampling variability inherent to the estimation of unknown population parameters. Using a variance-components approach to partitioning the total variability of an estimated parameter, we demonstrate the ease with which sampling variation can be removed from the observed total variation of parameter estimates. Estimates of temporal variability of survival are given after removal of sampling variation for three bird species: the federally listed Roseate Tern (Sterna dougallii), Black-capped Chickadees (Parus atricapillus), and Mallard ducks (Anas platyrhynchos). Sampling variation accounted for the majority of the total variation in the survival estimates for nearly all of the populations studied. Substantial differences in observed significance levels were observed when testing for demographic differences in temporal variation using temporal variance estimates adjusted and unadjusted for sampling variance.

Estimation of temporal variability of survival in animal populations

Summary

1
Stephens et al. (2005) argue for ‘pluralism’ in statistical analysis, combining null hypothesis testing and information-theoretic (I-T) methods. We show that I-T methods are more informative even in single variable problems and we provide an ecological example.

2
I-T methods allow inferences to be made from multiple models simultaneously. We believe multimodel inference is the future of data analysis, which cannot be achieved with null hypothesis-testing approaches.

3
We argue for a stronger emphasis on critical thinking in science in general and less reliance on exploratory data analysis and data dredging. Deriving alternative hypotheses is central to science; deriving a single interesting science hypothesis and then comparing it to a default null hypothesis (e.g. ‘no difference’) is not an efficient strategy for gaining knowledge. We think this single-hypothesis strategy has been relied upon too often in the past.

4
We clarify misconceptions presented by Stephens et al. (2005).

5
We think inference should be made about models, directly linked to scientific hypotheses, and their parameters conditioned on data, Prob(Hj | data). I-T methods provide a basis for this inference. Null hypothesis testing merely provides a probability statement about the data conditioned on a null model, Prob(data | H0).

6
Synthesis and applications. I-T methods provide a more informative approach to inference. I-T methods provide a direct measure of evidence for or against hypotheses and a means to consider simultaneously multiple hypotheses as a basis for rigorous inference. Progress in our science can be accelerated if modern methods can be used intelligently; this includes various I-T and Bayesian methods.

Concerns regarding a call for pluralism of information theory and hypothesis testing

Combinations of water velocity and passage length in highway culverts were evaluated to determine conditions that enabled or prevented the passage of nonanadromous rainbow trout Oncorhynchus mykiss, brown trout Salmo trutta, cutthroat trout O. clarki, and brook trout Salvelinus fontinalis. Fish passage through six culverts 45–93 m long was determined by trapping and electrofishing. Water velocities were measured 5 cm above the bottom (bottom velocity) and at 0.6 ofthe water depth at intervals between rest sites throughout the lengths of the culverts. Nonlinear regression lines specific to species and state of sexual maturity were fit to the combinations of mean bottom velocity and passage length representing the most strenuous conditions that allowed the upstream passage of trout. Because of the similarity of the strenuous passage relations among species, the spawning rainbow trout relation could be used as the general criterion for passage of the trout studied. This relation indicated that fish ...

An Evaluation of Trout Passage through Six Highway Culverts in Montana

The relative ease with which linear regression models are understood explains the popularity of such techniques in estimating population size with catch-effort data. However, the development and us...

Catch-effort maximum likelihood estimation of important population parameters

Monitoring of natural resources is crucial to ecosys- tem conservation, and yet it can pose many challenges. Annual surveys for amphibian breeding occupancy were conducted in Yellowstone and Grand Teton National Parks over a 4-year period (2006-2009) at two scales: catchments (portions of watersheds) and individual wetland sites. Catchments were selected in a stratified random sample with habitat quality and ease of access serving as strata. All known wetland sites with suitable habitat were surveyed within selected catchments. Changes in breeding occurrence of tiger salamanders, boreal chorus frogs, and Columbia-spotted frogs were assessed using multi-season occupancy estimation. Numerous a priori models were considered within an information theoretic framework including those with catchment and site-level covariates. Hab- itat quality was the most important predictor of occupancy. Boreal chorus frogs demonstrated the greatest increase in breeding occupancy at the catchment level. Larger changes for all 3 species were detected at the finer site-level scale. Connectivity of sites explained occupancy rates more than other covariates, and may improve understanding of the dy- namic processes occurring among wetlands within this ecosys- tem. Our results suggest monitoring occupancy at two spatial scales within large study areas is feasible and informative.

https://www.fs.fed.us/rm/pubs_other/rmrs_2012_gould_w001.pdf

William R. Gould

Papers

Estimation of temporal variability of survival in animal populations

Concerns regarding a call for pluralism of information theory and hypothesis testing

An Evaluation of Trout Passage through Six Highway Culverts in Montana

Catch-effort maximum likelihood estimation of important population parameters

Estimating Occupancy in Large Landscapes: Evaluation of Amphibian Monitoring in the Greater Yellowstone Ecosystem