Christopher M. Perrins

Bio: Christopher M. Perrins is an academic researcher from University of Oxford. The author has contributed to research in topics: Population & Puffinus. The author has an hindex of 46, co-authored 113 publications receiving 18610 citations. Previous affiliations of Christopher M. Perrins include Edward Grey Institute of Field Ornithology.

Birds of the Western Palearctic

Abstract: Handbook of the Birds of Europe, the Middle East and North Africa: The Birds of the Western Palearctic. Vol. 1: Ostrich to Ducks. Edited By S. Cramp, K. E. L. Simmons, I. J. Ferguson-Lees, E. M. Nicholson, M. A. Ogilvie, P. J. S. Olney, K. H. Voous and J. Wattel. Pp. 722. (Oxford University: Oxford, London and New York, 1977.) £25.

The birds of the western Palearctic

Abstract: Volume 1: Non-passerines (Ostriches to Woodpeckers) Volume 2: Passerines (Tyrant Flycatchers to Warblers)

The timing of birds‘ breeding seasons

Abstract: Summary Examination of survival rdtes of nestlings and fledglings of some species show that there is a strong tendency for those young which are hatched earliest in the season to have the greatest chance of surviving to breed. Since natural selection so strongly favours parents who leave many surviving young, the question arises as to why other birds breed later than the date at which they could most successfully raise their young. It is suggested that the food supply for the breeding females immediately prior to the breeding season may limit their ability to form eggs and the females may thus not be able to lay at the time which would result in young being in the nest at the best time for raising them, but as soon after this time as the female is able to produce her eggs. Not all species are likely to be prevented, by food shortage, from breeding at the best time for raising young and the groups of birds most likely to be affected are discussed.

Adaptive Phenotypic Plasticity in Response to Climate Change in a Wild Bird Population

Abstract: Rapid climate change has been implicated as a cause of evolution in poorly adapted populations. However, phenotypic plasticity provides the potential for organisms to respond rapidly and effectively to environmental change. Using a 47-year population study of the great tit (Parus major) in the United Kingdom, we show that individual adjustment of behavior in response to the environment has enabled the population to track a rapidly changing environment very closely. Individuals were markedly invariant in their response to environmental variation, suggesting that the current response may be fixed in this population. Phenotypic plasticity can thus play a central role in tracking environmental change; understanding the limits of plasticity is an important goal for future research.

Selection for the timing of great tit breeding in relation to caterpillar growth and temperature

Abstract: 1. We investigated the relation between the timing of great tit breeding, measured as the mean date of laying the first egg in each clutch, the timing of caterpillar availability, measured as median pupation dates of winter moth, selection for laying dates, measured from the recruitment into the local breeding population in subsequent years, and temperature in the period after egg laying. 2. There was a significant positive correlation between the timing of the great tit's laying and the timing of the caterpillars. 3. In most years there was selection for earlier laying in this great tit population. The selection differentials were usually the same for male and female recruits. 4. The selection differential for laying date was strongly correlated (r = 0.84, n = 21, P <0.0001) with the difference in timing between birds and caterpillars. This difference in timing was in turn strongly correlated with temperatures in the period after egg laying. 5. When the period after the laying date was subdivided, the selection differential was strongly correlated with the mean temperature during the period when most birds were incubating. 6. We discuss six alternative hypotheses explaining a consistent selection differential for earlier laying. One of these is new and is based on the fact that the birds can delay their breeding more succesfully than they can speed it up, once they have started laying. [KEYWORDS: Caterpillar pupation; insectivorous birds;natural selection; timing of breeding; wytham wood Parus-major; clutch size; incubation; heritability;reproduction]

Pattern Recognition and Machine Learning

Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Human biochemical genetics

Abstract: So far in this course we have dealt entirely with the evolution of characters that are controlled by simple Mendelian inheritance at a single locus. There are notes on the course website about gametic disequilibrium and how allele frequencies change at two loci simultaneously, but we didn’t discuss them. In every example we’ve considered we’ve imagined that we could understand something about evolution by examining the evolution of a single gene. That’s the domain of classical population genetics. For the next few weeks we’re going to be exploring a field that’s actually older than classical population genetics, although the approach we’ll be taking to it involves the use of population genetic machinery. If you know a little about the history of evolutionary biology, you may know that after the rediscovery of Mendel’s work in 1900 there was a heated debate between the “biometricians” (e.g., Galton and Pearson) and the “Mendelians” (e.g., de Vries, Correns, Bateson, and Morgan). Biometricians asserted that the really important variation in evolution didn’t follow Mendelian rules. Height, weight, skin color, and similar traits seemed to

A globally coherent fingerprint of climate change impacts across natural systems

Abstract: Causal attribution of recent biological trends to climate change is complicated because non-climatic influences dominate local, short-term biological changes. Any underlying signal from climate change is likely to be revealed by analyses that seek systematic trends across diverse species and geographic regions; however, debates within the Intergovernmental Panel on Climate Change (IPCC) reveal several definitions of a 'systematic trend'. Here, we explore these differences, apply diverse analyses to more than 1,700 species, and show that recent biological trends match climate change predictions. Global meta-analyses documented significant range shifts averaging 6.1 km per decade towards the poles (or metres per decade upward), and significant mean advancement of spring events by 2.3 days per decade. We define a diagnostic fingerprint of temporal and spatial 'sign-switching' responses uniquely predicted by twentieth century climate trends. Among appropriate long-term/large-scale/multi-species data sets, this diagnostic fingerprint was found for 279 species. This suite of analyses generates 'very high confidence' (as laid down by the IPCC) that climate change is already affecting living systems.

Modeling Survival and Testing Biological Hypotheses Using Marked Animals: A Unified Approach with Case Studies

Abstract: The understanding of the dynamics of animal populations and of related ecological and evolutionary issues frequently depends on a direct analysis of life history parameters. For instance, examination of trade-offs between reproduction and survival usually rely on individually marked animals, for which the exact time of death is most often unknown, because marked individuals cannot be followed closely through time. Thus, the quantitative analysis of survival studies and experiments must be based on capture- recapture (or resighting) models which consider, besides the parameters of primary interest, recapture or resighting rates that are nuisance parameters. Capture-recapture models oriented to estimation of survival rates are the result of a recent change in emphasis from earlier approaches in which population size was the most important parameter, survival rates having been first introduced as nuisance parameters. This emphasis on survival rates in capture-recapture models developed rapidly in the 1980s and used as a basic structure the Cormack-Jolly-Seber survival model applied to an homogeneous group of animals, with various kinds of constraints on the model parameters. These approaches are conditional on first captures; hence they do not attempt to model the initial capture of unmarked animals as functions of population abundance in addition to survival and capture probabilities. This paper synthesizes, using a common framework, these recent developments together with new ones, with an emphasis on flexibility in modeling, model selection, and the analysis of multiple data sets. The effects on survival and capture rates of time, age, and categorical variables characterizing the individuals (e.g., sex) can be considered, as well as interactions between such effects. This "analysis of variance" philosophy emphasizes the structure of the survival and capture process rather than the technical characteristics of any particular model. The flexible array of models encompassed in this synthesis uses a common notation. As a result of the great level of flexibility and relevance achieved, the focus is changed from fitting a particular model to model building and model selection. The following procedure is recommended: (1) start from a global model compatible with the biology of the species studied and with the design of the study, and assess its fit; (2) select a more parsimonious model using Akaike's Information Criterion to limit the number of formal tests; (3) test for the most important biological questions by comparing this model with neighboring ones using likelihood ratio tests; and (4) obtain maximum likelihood estimates of model parameters with estimates of precision. Computer software is critical, as few of the models now available have parameter estimators that are in closed form. A comprehensive table of existing computer software is provided. We used RELEASE for data summary and goodness-of-fit tests and SURGE for iterative model fitting and the computation of likelihood ratio tests. Five increasingly complex examples are given to illustrate the theory. The first, using two data sets on the European Dipper (Cinclus cinclus), tests for sex-specific parameters,