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.

Both the magnitude and the urgency of the task of assessing global biodiversity require that we make the most of what we know through the use of estimation and extrapolation. Likewise, future biodiversity inventories need to be designed around the use of effective sampling and estimation procedures, especially for 'hyperdiverse' groups of terrestrial organisms, such as arthropods, nematodes, fungi, and microorganisms. The challenge of estimating patterns of species richness from samples can be separated into (i) the problem of estimating local species richness, and (ii) the problem of estimating the distinctness, or complementarity, of species assemblages. These concepts apply on a wide range of spatial, temporal, and functional scales. Local richness can be estimated by extrapolating species accumulation curves, fitting parametric distributions of relative abundance, or using non-parametric techniques based on the distribution of individuals among species or of species among samples. We present several of these methods and examine their effectiveness for an example data set. We present a simple measure of complementarity, with some biogeographic examples, and outline the difficult problem of estimating complementarity from samples. Finally, we discuss the importance of using 'reference' sites (or sub-sites) to assess the true richness and composition of species assemblages, to measure ecologically significant ratios between unrelated taxa, to measure taxon/sub-taxon (hierarchical) ratios, and to 'calibrate' standardized sampling methods. This information can then be applied to the rapid, approximate assessment of species richness and faunal or floral composition at 'comparative' sites.

Estimating Terrestrial Biodiversity through Extrapolation

Gut microbial composition depends on different dietary habits just as health depends on microbial metabolism, but the association of microbiota with different diets in human populations has not yet been shown. In this work, we compared the fecal microbiota of European children (EU) and that of children from a rural African village of Burkina Faso (BF), where the diet, high in fiber content, is similar to that of early human settlements at the time of the birth of agriculture. By using high-throughput 16S rDNA sequencing and biochemical analyses, we found significant differences in gut microbiota between the two groups. BF children showed a significant enrichment in Bacteroidetes and depletion in Firmicutes (P < 0.001), with a unique abundance of bacteria from the genus Prevotella and Xylanibacter, known to contain a set of bacterial genes for cellulose and xylan hydrolysis, completely lacking in the EU children. In addition, we found significantly more short-chain fatty acids (P < 0.001) in BF than in EU children. Also, Enterobacteriaceae (Shigella and Escherichia) were significantly underrepresented in BF than in EU children (P < 0.05). We hypothesize that gut microbiota coevolved with the polysaccharide-rich diet of BF individuals, allowing them to maximize energy intake from fibers while also protecting them from inflammations and noninfectious colonic diseases. This study investigates and compares human intestinal microbiota from children characterized by a modern western diet and a rural diet, indicating the importance of preserving this treasure of microbial diversity from ancient rural communities worldwide.

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Impact of diet in shaping gut microbiota revealed by a comparative study in children from Europe and rural Africa

We have applied “whole-genome shotgun sequencing” to microbial populations collected en masse on tangential flow and impact filters from seawater samples collected from the Sargasso Sea near Bermuda. A total of 1.045 billion base pairs of nonredundant sequence was generated, annotated, and analyzed to elucidate the gene content, diversity, and relative abundance of the organisms within these environmental samples. These data are estimated to derive from at least 1800 genomic species based on sequence relatedness, including 148 previously unknown bacterial phylotypes. We have identified over 1.2 million previously unknown genes represented in these samples, including more than 782 new rhodopsin-like photoreceptors. Variation in species present and stoichiometry suggests substantial oceanic microbial diversity. Microorganisms are responsible for most of the biogeochemical cycles that shape the environment of Earth and its oceans. Yet, these organisms are the least well understood on Earth, as the ability to study and understand the metabolic potential of microorganisms has been hampered by the inability to generate pure cultures. Recent studies have begun to explore environ

/pdf/environmental-genome-shotgun-sequencing-of-the-sargasso-sea-43wxijxylr.pdf

Environmental Genome Shotgun Sequencing of the Sargasso Sea

Using the concept of sample coverage, we derive an approximation of the bias in the Jolly-Seber population size estimators due to heterogeneity of capture probabilities. The resulting bias is expressed as a function of sample coverage, average capture probability, and the coefficient of variation of individual capture probabilities. The effect of unequal catchabilities on the Jolly-Seber survival rate estimators is also briefly discussed. We propose new population size estimators which incorporate the heterogeneity of capture probabilities. A simulation study investigates the performance of the approximation formulas of biases and the proposed estimation procedure. A real data set of male black-kneed capsids discussed in Jolly (Biometrika 52, 225-247, 1965), Seber (The Estimation of Animal Abundance, 1982), and Burnham (In Estimation of Analysis of Insect Populations, pp. 416-435, 1989) illustrates the method.

Quantifying the effects of unequal catchabilities on jolly-seber estimators via sample coverage

In order to understand the effects of intrauterine growth discordancy (15% or more birth weight difference), birth weight, and gestational age on the neonatal adverse events (including 1- or 5-min Apgar scores < 7, neonatal death, ICU admission, respiratory distress, hypoglycemia, hypocalcemia, perinatal infection, blood transfusion, and hyperbilirubinemia) in third trimester twin gestations, 279 consecutive twin pairs delivered from January 1986 to December 1991 were studied. Univariate analyses showed discordant twins were smaller than concordant twins in gestational age by 1.4 weeks (35.74 and 37.14 weeks respectively). When birth weight was compared, that of smaller (one with lower birth weight in a pair) discordant twins (1,951 g) was significantly lower than that of smaller concordant twins (2,423 g), while larger (one with higher birth weight in a pair) discordant twins (2,556 g) and concordant twins (2,594 g) showed no significant difference. Univariate analysis indicated there was a tendency for adverse events to occur in discordant twins, especially in the smaller twin. Through logistic regression analysis, it was found that birth weight and gestational age, but not discordancy, are the predictors of the occurrence of adverse events. A smaller twin weighing no more than 2,000 g has a 10 times greater risk to develop an adverse event as compared to a twin with a birth weight over 2,000 g and a similar gestational age; while a twin with a gestational age of less than 34 weeks has a 5 times greater risk than one 34 weeks or over with a similar birth weight.

Growth discordancy, birth weight, and neonatal adverse events in third trimester twin gestations.

Summary A number of species richness estimators have been developed under the model that individuals (or sampling units) are sampled with replacement. However, if sampling is done without replacement so that no sampled unit can be repeatedly observed, then the traditional estimators for sampling with replacement tend to overestimate richness for relatively high-sampling fractions (ratio of sample size to the total number of sampling units) and do not converge to the true species richness when the sampling fraction approaches one. Based on abundance data or replicated incidence data, we propose a nonparametric lower bound for species richness in a single community and also a lower bound for the number of species shared by multiple communities. Our proposed lower bounds are derived under very general sampling models. They are universally valid for all types of species abundance distributions and species detection probabilities. For abundance data, individuals’ detectabilities are allowed to be heterogeneous among species. For replicated incidence data, the selected sampling units (e.g., quadrats) need not be fully censused and species can be spatially aggregated. All bounds converge correctly to the true parameters when the sampling fraction approaches one. Real data sets are used for illustration. We also test the proposed bounds by using subsamples generated from large real surveys or censuses, and their performance is compared with that of some previous estimators.

/pdf/nonparametric-lower-bounds-for-species-richness-and-shared-5acbtzm2hd.pdf

Nonparametric lower bounds for species richness and shared species richness under sampling without replacement.

The capture-recapture method is applied to estimate the population size of a target population based on ascertainment data in epidemiological applications. We generalize the three-list case of Chao & Tsay (1998) to situations where more than three lists are available. An estimation procedure is presented using the concept of sample coverage, which can be interpreted as a measure of overlap information among multiple list records. When there is enough overlap, an estimator of the total population size is proposed. The bootstrap method is used to construct a variance estimator and confidence interval. If the overlap rate is relatively low, then the population size cannot be precisely estimated and thus only a lower (upper) bound is proposed for positively (negatively) dependent lists. The proposed method is applied to two data sets, one with a high and one with a low overlap rate.

Population size estimation for capture-recapture models with applications to epidemiological data

Summary
Due to sampling limitations, almost every biodiversity survey misses species that are present, but not detected, so that empirical species counts underestimate species richness. A wide range of species richness estimators has been proposed in the literature to reduce undersampling bias. We focus on nonparametric estimators, which make no assumptions about the mathematical form of the underlying species abundance/incidence distributions.
For replicated incidence data, in which only species presence/absence (or detection/non-detection) is recorded in multiple sampling units, most existing nonparametric estimators of the number of undetected species are based on the frequency counts of the uniques (species detected in only one sampling unit) and duplicates (species detected in exactly two sampling units).
Some survey methods, however, record only uniques and super-duplicates (species observed in more than one sampling unit). Using the Good–Turing frequency formula, we developed a method to estimate the number of duplicates for such data, allowing estimation of true species richness, including undetected species.
We test our estimators on several empirical datasets for which doubletons were recorded and on simulated sampling data, then apply them to an extensive, but previously unusable survey of coral reef fishes, for which only uniques and super-duplicates were recorded.
We extend the method to abundance data and discuss other potential applications.

https://besjournals.onlinelibrary.wiley.com/doi/epdf/10.1111/2041-210X.12768

Anne Chao

Papers

Quantifying the effects of unequal catchabilities on jolly-seber estimators via sample coverage

Growth discordancy, birth weight, and neonatal adverse events in third trimester twin gestations.

Nonparametric lower bounds for species richness and shared species richness under sampling without replacement.

Population size estimation for capture-recapture models with applications to epidemiological data

Seen once or more than once: applying Good–Turing theory to estimate species richness using only unique observations and a species list