The influence of diet on the distribution of nitrogen isotopes in animals was investigated by analyzing animals grown in the laboratory on diets of constant nitrogen isotopic composition. 
The isotopic composition of the nitrogen in an animal reflects the nitrogen isotopic composition of its diet. The δ^(15)N values of the whole bodies of animals are usually more positive than those of their diets. Different individuals of a species raised on the same diet can have significantly different δ^(15)N values. The variability of the relationship between the δ^(15)N values of animals and their diets is greater for different species raised on the same diet than for the same species raised on different diets. Different tissues of mice are also enriched in ^(15)N relative to the diet, with the difference between the δ^(15)N values of a tissue and the diet depending on both the kind of tissue and the diet involved. The δ^(15)N values of collagen and chitin, biochemical components that are often preserved in fossil animal remains, are also related to the δ^(15)N value of the diet. 
The dependence of the δ^(15)N values of whole animals and their tissues and biochemical components on the δ^(15)N value of diet indicates that the isotopic composition of animal nitrogen can be used to obtain information about an animal's diet if its potential food sources had different δ^(15)N values. The nitrogen isotopic method of dietary analysis probably can be used to estimate the relative use of legumes vs non-legumes or of aquatic vs terrestrial organisms as food sources for extant and fossil animals. However, the method probably will not be applicable in those modern ecosystems in which the use of chemical fertilizers has influenced the distribution of nitrogen isotopes in food sources. 
The isotopic method of dietary analysis was used to reconstruct changes in the diet of the human population that occupied the Tehuacan Valley of Mexico over a 7000 yr span. Variations in the δ^(15)C and δ^(15)N values of bone collagen suggest that C_4 and/or CAM plants (presumably mostly corn) and legumes (presumably mostly beans) were introduced into the diet much earlier than suggested by conventional archaeological analysis.

Influence of Diet On the Distribtion of Nitrogen Isotopes in Animals

Beginning with Emlen (1966) and MacArthur and Pianka (1966) and extending through the last ten years, several authors have sought to predict the foraging behavior of animals by means of mathematical models. These models are very similar,in that they all assume that the fitness of a foraging animal is a function of the efficiency of foraging measured in terms of some "currency" (Schoener, 1971) -usually energy- and that natural selection has resulted in animals that forage so as to maximize this fitness. As a result of these similarities, the models have become known as "optimal foraging models"; and the theory that embodies them, "optimal foraging theory." The situations to which optimal foraging theory has been applied, with the exception of a few recent studies, can be divided into the following four categories: (1) choice by an animal of which food types to eat (i.e., optimal diet); (2) choice of which patch type to feed in (i.e., optimal patch choice); (3) optimal allocation of time to different patches; and (4) optimal patterns and speed of movements. In this review we discuss each of these categories separately, dealing with both the theoretical developments and the data that permit tests of the predictions. The review is selective in the sense that we emphasize studies that either develop testable predictions or that attempt to test predictions in a precise quantitative manner. We also discuss what we see to be some of the future developments in the area of optimal foraging theory and how this theory can be related to other areas of biology. Our general conclusion is that the simple models so far formulated are supported are supported reasonably well by available data and that we are optimistic about the value both now and in the future of optimal foraging theory. We argue, however, that these simple models will requre much modification, espicially to deal with situations that either cannot easily be put into one or another of the above four categories or entail currencies more complicated that just energy.

Citation classic - optimal foraging - a selective review of theory and tests

https://bio.uib.no/te/papers/Grimm_2010_The_ODD_protocol_.pdf

The ODD protocol: A review and first update

We present a high-quality genome sequence of a Neanderthal woman from Siberia. We show that her parents were related at the level of half-siblings and that mating among close relatives was common among her recent ancestors. We also sequenced the genome of a Neanderthal from the Caucasus to low coverage. An analysis of the relationships and population history of available archaic genomes and 25 present-day human genomes shows that several gene flow events occurred among Neanderthals, Denisovans and early modern humans, possibly including gene flow into Denisovans from an unknown archaic group. Thus, interbreeding, albeit of low magnitude, occurred among many hominin groups in the Late Pleistocene. In addition, the high-quality Neanderthal genome allows us to establish a definitive list of substitutions that became fixed in modern humans after their separation from the ancestors of Neanderthals and Denisovans.

http://dash.harvard.edu/bitstream/handle/1/12717373/4031459.pdf?sequence=1

The complete genome sequence of a Neanderthal from the Altai Mountains

The complete title of this book runs ‘Analyzing Linguistic Data: A Practical Introduction to Statistics using R’ and as such it very well reflects the purpose and spirit of the book. The author guides the reader in about 350 pages from descriptive and basic statistical methods over classification and clustering to (generalised) linear and mixed models. Each of the methods is introduced in the context of concrete linguistic problems and demonstrated on exciting datasets from current research in the language sciences. In line with its practical orientation, the book focuses primarily on using the methods and interpreting the results. This implies that the mathematical treatment of the techniques is held at a minimum if not absent from the book. In return, the reader is provided with very detailed explanations on how to conduct the analyses using R [1]. The first chapter sets the tone being a 20-page introduction to R. For this and all subsequent chapters, the R code is intertwined with the chapter text and the datasets and functions used are conveniently packaged in the languageR package that is available on the Comprehensive R Archive Network (CRAN). With this approach, the author has done an excellent job in enabling researchers and students alike to reproduce the analyses and learn by doing. Another quality as a textbook is the fact that every chapter ends with Workbook sections where the user is invited to exercise his or her analysis skills on supplemental datasets. Full solutions including code, results and comments are given in Appendix A (30 pages). Instructors are therefore very well served by this text, although they might want to balance the book with some more mathematical treatment depending on the target audience. After the introductory chapter on R, the book opens on graphical data exploration. Chapter 3 treats probability distributions and common sampling distributions. Under basic statistical methods (Chapter 4), distribution tests and tests on means and variances are covered. Chapter 5 deals with clustering and classification. Strangely enough, the clustering section has material on PCA, factor analysis, correspondence analysis and includes only one subsection on clustering, devoted notably to hierarchical partitioning methods. The classification part deals with decision trees, discriminant analysis and support vector machines. The regression chapter (Chapter 6) treats linear models, generalised linear models, piecewise linear models and a substantial section on models for lexical richness. The final chapter on mixed models is particularly interesting as it is one of the few text book accounts that introduce the reader to using the (innovative) lme4 package of Douglas Bates which implements linear mixed-effects models. Moreover, the case studies included in this

Analyzing linguistic data: a practical introduction to statistics using R

Over the past few decades, socioecological models have been developed to explain the relationships between the ecological conditions, social systems, and reproductive success of primates. Feeding competition, predation pressures, and risk of infanticide are predicted to influence how female reproductive success (FRS) depends upon their dominance rank, group size, and mate choices. This paper examines how those factors affected the reproductive success of female mountain gorillas (Gorilla beringei beringei) of the Virunga Volcanoes, Rwanda from 1967–2004. Reproductive success was measured through analyses of interbirth intervals, infant survival, and surviving infant birth rates using data from 214 infants born to 67 females. Mountain gorillas were predicted to have “within-group scramble” feeding competition, but we found no evidence of lower FRS in larger groups, even as those groups became two to five times larger than the population average. The gorillas are considered to have negligible “within-group contest” competition, yet higher ranked mothers had shorter interbirth intervals. Infant survival was higher in multimale groups, which was expected because infanticide occurs when the male dies in a one-male group. The combination of those results led to higher surviving birth rates for higher ranking females in multimale groups. Overall, however, the socioecological factors accounted for a relatively small portion of the variance in FRS, as expected for a species that feeds on abundant, evenly distributed foliage.

Socioecological influences on the reproductive success of female mountain gorillas ( Gorilla beringei beringei )

Variation in the social system of mountain gorillas: The male perspective

Gorillas: Diversity in ecology and behavior

Variation in male dispersal and behavior patterns are components of intraspecific differences in social systems. A comparison of male behavior in different social settings can be useful for determining which behavioral mechanisms contribute to variability in social systems. Two heterosexual multimale groups and one all-male group of mountain gorillas (Gorilla gorilla beringei) were observed for over 1100 h at the Karisoke Research Centre, Rwanda. Data on proximity patterns, dominance relationships, aggression, agonistic interventions, affiliation, and homosexual behavior were compared among the males in these groups to examine the influence of female presence, sex ratio, group size, and kinship on male—male interactions. Males in the all-male group stayed closer together, affiliated more, exhibited more homosexual behavior, and were more aggressive toward each other than males in heterosexual groups. However, the males in heterosexual groups showed more wounding and more consistent dominance relationships. Kinship did not influence male-male relationships in the all-male group. The males in the heterosexual groups rarely interacted with one another; they may actively avoid close proximity to reduce aggression. Results suggest that the variable social system of mountain gorillas may be more strongly influenced by demographic factors, male-female social relationships, and male-male competition for mates than by any benefits of male-male relationships.

Male‐male Interactions in Heterosexual and All‐male Wild Mountain Gorilla Groups

Investigating sexual dimorphism is important for our understanding of its influence on reproductive strategies including male-male competition, mate choice, and sexual conflict. Measuring physical traits in wild animals can be logistically challenging and disruptive for the animals. Therefore body size and ornament variation in wild primates have rarely been quantified. Gorillas are amongst the most sexually dimorphic and dichromatic primates. Adult males (silverbacks) possess a prominent sagittal crest, a pad of fibrous and fatty tissue on top of the head, have red crest coloration, their saddle appears silver, and they possess a silverline along their stomach. Here we measure levels of sexual dimorphism and within-male variation of body length, head size, and sexual dichromatism in a population of wild western gorillas using photogrammetry. Digital photogrammetry is a useful and precise method to measure sexual dimorphism in physical traits yielding sexual dimorphism indices (ISD), similar to those derived from traditional measurements of skeletal remains. Silverbacks were on an average 1.23 times longer in body length than adult females. Sexual dimorphism of head size was highest in measures of crest size (max ISD: 60.4) compared with measures of facial height (max ISD: 24.7). The most sexually dimorphic head size measures also showed the highest within-sex variation. We found no clear sex differences in crest coloration but there was large sexual dichromatism with high within-male variation in saddle coloration and silverline size. Further studies should examine if these sexually dimorphic traits are honest signals of competitive ability and confer an advantage in reproductive success.

/pdf/using-photogrammetry-and-color-scoring-to-assess-sexual-1xex07yolw.pdf

Martha M. Robbins

Papers

Socioecological influences on the reproductive success of female mountain gorillas ( Gorilla beringei beringei )

Variation in the social system of mountain gorillas: The male perspective

Gorillas: Diversity in ecology and behavior

Male‐male Interactions in Heterosexual and All‐male Wild Mountain Gorilla Groups

Using photogrammetry and color scoring to assess sexual dimorphism in wild western gorillas (Gorilla gorilla).