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

Statistical method for testing the neutral mutation hypothesis by DNA polymorphism.

Collinearity refers to the non independence of predictor variables, usually in a regression-type analysis. It is a common feature of any descriptive ecological data set and can be a problem for parameter estimation because it inflates the variance of regression parameters and hence potentially leads to the wrong identification of relevant predictors in a statistical model. Collinearity is a severe problem when a model is trained on data from one region or time, and predicted to another with a different or unknown structure of collinearity. To demonstrate the reach of the problem of collinearity in ecology, we show how relationships among predictors differ between biomes, change over spatial scales and through time. Across disciplines, different approaches to addressing collinearity problems have been developed, ranging from clustering of predictors, threshold-based pre-selection, through latent variable methods, to shrinkage and regularisation. Using simulated data with five predictor-response relationships of increasing complexity and eight levels of collinearity we compared ways to address collinearity with standard multiple regression and machine-learning approaches. We assessed the performance of each approach by testing its impact on prediction to new data. In the extreme, we tested whether the methods were able to identify the true underlying relationship in a training dataset with strong collinearity by evaluating its performance on a test dataset without any collinearity. We found that methods specifically designed for collinearity, such as latent variable methods and tree based models, did not outperform the traditional GLM and threshold-based pre-selection. Our results highlight the value of GLM in combination with penalised methods (particularly ridge) and threshold-based pre-selection when omitted variables are considered in the final interpretation. However, all approaches tested yielded degraded predictions under change in collinearity structure and the ‘folk lore’-thresholds of correlation coefficients between predictor variables of |r| >0.7 was an appropriate indicator for when collinearity begins to severely distort model estimation and subsequent prediction. The use of ecological understanding of the system in pre-analysis variable selection and the choice of the least sensitive statistical approaches reduce the problems of collinearity, but cannot ultimately solve them.

https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1600-0587.2012.07348.x

Collinearity: a review of methods to deal with it and a simulation study evaluating their performance

Summary 1. While teaching statistics to ecologists, the lead authors of this paper have noticed common statistical problems. If a random sample of their work (including scientific papers) produced before doing these courses were selected, half would probably contain violations of the underlying assumptions of the statistical techniques employed. 2. Some violations have little impact on the results or ecological conclusions; yet others increase type I or type II errors, potentially resulting in wrong ecological conclusions. Most of these violations can be avoided by applying better data exploration. These problems are especially troublesome in applied ecology, where management and policy decisions are often at stake. 3. Here, we provide a protocol for data exploration; discuss current tools to detect outliers, heterogeneity of variance, collinearity, dependence of observations, problems with interactions, double zeros in multivariate analysis, zero inflation in generalized linear modelling, and the correct type of relationships between dependent and independent variables; and provide advice on how to address these problems when they arise. We also address misconceptions about normality, and provide advice on data transformations. 4. Data exploration avoids type I and type II errors, among other problems, thereby reducing the chance of making wrong ecological conclusions and poor recommendations. It is therefore essential for good quality management and policy based on statistical analyses.

https://besjournals.onlinelibrary.wiley.com/doi/epdf/10.1111/j.2041-210X.2009.00001.x

A protocol for data exploration to avoid common statistical problems

A DNA test to sex most birds.

Evaluating the potential for anthropogenic habitats to act as surrogates for the natural habitats they replace is a key issue in conservation biology. In California, flooded rice fields are used by numerous aquatic birds during winter. If this habitat functions similarly to more natural wetlands, increased flooding may help replace the extensive wetlands that occurred in the region prior to agricultural development. I tested whether food abundance, perceived predation threat, foraging performance, and the way in which birds allocate their time to different behaviors differed between flooded rice fields and seminatural wetlands for several species of aquatic bird. When appropriate, I also compared flooded and unflooded fields. Invertebrate densities did not differ among habitats. Seminatural wetlands had less rice grain but more seeds from other plants than the two rice habitats. The frequency with which predators passed over a feeding area was lower in flooded fields than in unflooded fields or seminatural wetlands. Most differences in feeding performance and time allocation among habitats were small and statistically insignificant. For some species, feeding efficiency was greater in seminatural wetlands than in flooded fields. Increasing attack rates and the amount of time spent feeding when in flooded fields, however, may allow birds to compensate for reduced efficiency. Multivariate analyses showed that group size, predation threat, time of day, date, and water depth often were associated with behaviors, but that these variables rarely accounted for habitat differences. Flooded fields apparently provide equivalent foraging habitat to seminatural wetlands and, because of reduced predation threat, may be a safer habitat for waterbirds. Thus, if managed appropriately, one of the world's dominant forms of agriculture can provide valuable waterbird habitat.




Resumen: La evaluacion del potencial en habitats antropogenicos para actuar como substitutos de los habitats naturales que remplazaron es un tema clave en la biologia de la conservacion. En California, tierras inundadas para cultivo de arroz son utilizadas por numerosas aves acuaticas durante el invierno. Si estos habitats funcionan en forma similar a humedales mas naturales, el incremento de inundaciones podria ayudar a reemplazar los extensos humedales que existieron en la region antes del desarrollo agricultural. Analize si la abundancia de alimento, la percepcion del peligro de depredacion, el rendimiento en forrajeo y la forma en que las aves distribuyen su tiempo hacia diferentes conductas difieren entre arrozales inundados y humedales seminaturales para diferentes especies de aves acuaticas. Cuando fue posible, tambien compare arrozales inundados contra no inundados. Las densidades de invertebrados no difirieron entre habitats. Los humedales seminaturales tuvieron menos grano de arroz, pero mas semillas de otras plantas que los dos tipos de habitats de arrozal. La frecuencia con la que los depredadores pasaron sobre un area de alimentacion fue menor en los campos inundados que en los campos no inundados o los humedales seminaturales. La mayoria de las diferencias en el rendimiento alimenticio y el tiempo dedicado entre habitats fue pequeno y estadisticamente insignificante. Para algunas especies, la eficiencia alimenticia fue mayor en humedales seminaturales que en los campos inundados. Sin embargo, el incremento en las tasas de ataque y las cantidades de tiempo utilizado para alimentacion cuando los campos estaban inundados podria permitir a las aves compensar por esta reducida eficiencia. Un analisis multivariado mostro que el tamano de grupo, el peligro de depredacion, hora del dia, fecha y profundidad del agua estuvieron frecuentemente asociados con conductas, pero estas variables raramente aportaron elementos para encontrar diferencias entre habitats. Los arrozales inundados aparentemente proveen un habitat de forrajeo equivalente a los humedales seminaturales y debido a la reducida amenaza de depredacion, podrian ser un habitat seguro para aves acuaticas. Por lo tanto, si son manejados adecuadamente, una de las formas mas dominantes de agricultura a nivel mundial puede proporcionar habitat valioso para las aves acuaticas.

https://www.jstor.org/stable/pdfplus/2641917.pdf

Functional Equivalency between Rice Fields and Seminatural Wetland Habitats

1  Recent legislation designed to reduce air pollution has restricted Californian rice-farmers from burning rice stubble after harvest Intentional flooding of fields during winter to speed straw decomposition is becoming increasingly common as growers seek alternatives to burning residual straw The potential for flooded fields to act as a surrogate for destroyed wetland habitat may be an additional benefit in a region that hosts a large proportion of North America’s wintering waterbirds We investigated the degree to which waterbirds use flooded fields and whether the method of flooding affects their use Specifically, we tested whether waterbird use (a) was greater in intentionally flooded fields than in unflooded fields, (b) differed among flooded fields receiving different straw manipulations and (c) varied with water depth



2  Intentionally flooded rice fields received significantly greater use by 24 of 31 species studied Only great blue herons Ardea herodias and sandhill cranes Grus canadensis were significantly more common in unflooded fields Geese densities did not differ between flooded and unflooded fields



3  We found no differences in the densities of most species in flooded fields that received different straw manipulations to improve decomposition rates Exceptions included several small shorebirds which occurred at highest densities in fields where straw was incorporated into the soil



4  Species differed in their use of different water depths For 14 species we tested whether preferred depths, suggested in the literature, received disproportionately higher use Most of these species were more likely to be encountered within the suggested depth ranges Depth, however, was a poor predictor of bird density Depths of 15–20 cm resulted in frequent use by the greatest number of species



5  We conclude that flooding rice fields increased suitable habitat for most, but not all, species studied Different straw manipulation methods had little effect on most species Water depth, however, was important in determining species occurrence During the first half of the winter, water depths were greater than the median depths used by most species

https://www.jstor.org/stable/pdfplus/2405191.pdf

Winter management of Californian rice fields for waterbirds

Summary 1. Methods papers play a crucial role in advancing applied ecology. Counting organisms, in particular, has a rich history of methods development with many key advances both in field sampling and the treatment of resulting data. 2. Most counts, however, have associated errors due to portions of the population of interest being unavailable for detection (e.g. target population not fully sampled; individuals present but not detectable), detection mistakes (e.g. detectable individuals missed; non-existent individuals recorded), or erroneous counts (e.g. large groups miscounted; individuals misidentified). 3. Developments in field methods focus on reducing biases in the actual counts. Simultaneously, statisticians have developed many methods for improving inference by quantifying and correcting for biases retrospectively. Prominent examples of methods used to account for detection errors include distance sampling and multiple-observer methods. 4. Simulations, in which population characteristics are set by the investigator, provide an efficient means of testing methods. With good estimates of sampling biases, computer simulations can be used to evaluate how much a given counting problem affects estimates of parameters such as population size and decline, thereby allowing applied ecologists to test the efficacy of sampling designs. Combined with cost estimates for each field method, such models would allow the cost-effectiveness of alternative protocols to be assessed. 5. Synthesis and applications. Major advances are likely to come from research that looks for systematic patterns, across studies, in the effects of different types of bias and assumption violation on the ecological conclusions drawn. Specifically, determining how often, and under what circum stances, errors contribute to poor management and policy would greatly enhance future application of ecological knowledge.

https://www.cals.ncsu.edu/course/zo501/Readings/How%20You%20Count%20JAE.pdf

How you count counts: the importance of methods research in applied ecology

/pdf/conservation-implications-of-flooding-rice-fields-on-winter-4uliqkp8qa.pdf

Chris S. Elphick

Papers

A protocol for data exploration to avoid common statistical problems

Functional Equivalency between Rice Fields and Seminatural Wetland Habitats

Winter management of Californian rice fields for waterbirds

How you count counts: the importance of methods research in applied ecology

Conservation implications of flooding rice fields on winter waterbird communities