There is now ample evidence of the ecological impacts of recent climate change, from polar terrestrial to tropical marine environments. The responses of both flora and fauna span an array of ecosystems and organizational hierarchies, from the species to the community levels. Despite continued uncertainty as to community and ecosystem trajectories under global change, our review exposes a coherent pattern of ecological change across systems. Although we are only at an early stage in the projected trends of global warming, ecological responses to recent climate change are already clearly visible.

/pdf/ecological-responses-to-recent-climate-change-5dddm9xeiv.pdf

Ecological responses to recent climate change.

Every form of behavior is shaped by trial and error. Such stepwise adaptation can occur through individual learning or through natural selection, the basis of evolution. Since the work of Maynard Smith and others, it has been realized how game theory can model this process. Evolutionary game theory replaces the static solutions of classical game theory by a dynamical approach centered not on the concept of rational players but on the population dynamics of behavioral programs. In this book the authors investigate the nonlinear dynamics of the self-regulation of social and economic behavior, and of the closely related interactions among species in ecological communities. Replicator equations describe how successful strategies spread and thereby create new conditions that can alter the basis of their success, i.e., to enable us to understand the strategic and genetic foundations of the endless chronicle of invasions and extinctions that punctuate evolution. In short, evolutionary game theory describes when to escalate a conflict, how to elicit cooperation, why to expect a balance of the sexes, and how to understand natural selection in mathematical terms.

 Comprehensive treatment of ecological and game theoretic dynamics
 Invasion dynamics and permanence as key concepts
 Explanation in terms of games of things like competition between species

/pdf/evolutionary-games-and-population-dynamics-pax1uk4ywa.pdf

Evolutionary games and population dynamics

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

Birds are difficult to sex. Nestlings rarely show sex-linked morphology and we estimate that adult females appear identical to males in over 50% of the world's bird species. This problem can hinder both evolutionary studies and human-assisted breeding of birds. DNA-based sex identification provides a solution. We describe a test based on two conserved CHD (chromo-helicase-DNA-binding) genes that are located on the avian sex chromosomes of all birds, with the possible exception of the ratites (ostriches, etc.; Struthioniformes). The CHD-W gene is located on the W chromosome; therefore it is unique to females. The other gene, CHD-Z, is found on the Z chromosome and therefore occurs in both sexes (female, ZW; male, ZZ). The test employs PCR with a single set of primers. It amplifies homologous sections of both genes and incorporates introns whose lengths usually differ. When examined on a gel there is a single CHD-Z band in males but females have a second, distinctive CHD-W band.

/pdf/a-dna-test-to-sex-most-birds-4qsdrdaafe.pdf

A DNA test to sex most birds

A DNA test to sex most birds.

-Repeatability is a useful tool for the population geneticist or genetical ecologist, but several papers have carried errors in its calculation We outline the correct calculation of repeatability, point out the common mistake, show how the incorrectly calculated value relates to repeatability, and provide a method for checking published values and calculating approximate repeatability values from the F ratio (mean squares among groups/ mean squares within groups) Received 6 February 1986, accepted 25 August 1986 REPEATABILITY is a measure used in quantitative genetics to describe the proportion of variance in a character that occurs among rather than within individuals Repeatability, r, is given by: r = (VG + VEg)/ VP, (1) where VG is the genotypic variance, VEg the general environmental variance, and Vp the phenotypic variance (Falconer 1960, 1981) In addition to its use in assessing the reliability of multiple measurements on the same individual, repeatability may be used to set an upper limit to the value of heritability (Falconer 1960, 1981) and to separate, for instance, the effects of "self" and "mate" on a character such as clutch size (van Noordwijk et al 1980) Repeatability is therefore a useful statistic for population geneticists and genetical ecologists Recently, we have noticed an increasing number of published papers and unpublished manuscripts in which repeatability was miscalculated Our purpose is fivefold: (1) to outline the correct method of calculating repeatability; (2) to point out a common mistake in calculating repeatability; (3) to show how much this mistake affects values of repeatability; (4) to provide a quick way of checking published estimates, and to calculate an approximate value of repeatability from published F ratios and degrees of freedom; and (5) to make recommendations for authors, referees, editors, and readers to prevent the promulgation and propagation of incorrect repeatability values in the literature CALCULATION OF REPEATABILITY Repeatability is the intraclass correlation coefficient (Sokal and Rohlf 1981), which is based on variance components derived from a one-way analysis of variance (ANOVA) The intraclass correlation coefficient is given by some statistical packages; otherwise it can be calculated from an ANOVA ANOVA is described in most statistics textbooks (eg Sokal and Rohlf 1981; Kirk 1968 gives a detailed treatment of more complex designs of ANOVA), so we will not repeat it here, but give the general form of the results from such an analysis in Table 1 Repeatability, r, is given by r = sA / (S + SA)' (2) where S2A is the among-groups variance component and s2 is the within-group variance component These variance components are calculated from the mean squares in the analysis of variance as:

/pdf/unrepeatable-repeatabilities-a-common-mistake-1cz5svlc6w.pdf

Unrepeatable repeatabilities: a common mistake

Phenological responses to climate change differ across trophic levels, which may lead to birds failing to breed at the time of maximal food abundance. Here we investigate the population consequences of such mistiming in the migratory pied flycatcher, Ficedula hypoleuca. In a comparison of nine Dutch populations, we find that populations have declined by about 90% over the past two decades in areas where the food for provisioning nestlings peaks early in the season and the birds are currently mistimed. In areas with a late food peak, early-breeding birds still breed at the right time, and there is, at most, a weak population decline. If food phenology advances further, we also predict population declines in areas with a late food peak, as in these areas adjustment to an advanced food peak is insufficient. Mistiming as a result of climate change is probably a widespread phenomenon, and here we provide evidence that it can lead to population declines.

/pdf/climate-change-and-population-declines-in-a-long-distance-10ibbxlxk2.pdf

Climate change and population declines in a long-distance migratory bird

In seasonal environments, the main selection pressure on the timing of reproduction (the ultimate factor) is synchrony between offspring requirements and food availability. However, reproduction is initiated much earlier than the time of maximum food requirement of the offspring. Individuals should therefore start reproduction in response to cues (the proximate factors), available in the environment of reproductive decision making, which predict the later environment of selection. With increasing spring temperatures over the past decades, vegetation phenology has advanced, with a concomitant advancement in the reproduction of some species at higher trophic levels. However, a mismatch between food abundance and offspring needs may occur if changes in the environment of decision making do not match those in the environment of selection. Date of egg laying in a great tit (Parus major) population has not advanced over a 23-year period, but selection for early laying has intensified. We believe that this is the first documented case of an adaptive response being hampered because a changing abiotic factor affects the environment in which a reproductive decision is made differently from the environment in which selection occurs.

/pdf/warmer-springs-lead-to-mistimed-reproduction-in-great-tits-5c5d43swph.pdf

Warmer springs lead to mistimed reproduction in great tits (Parus major)

The costs of egg production and incubation may have a crucial effect on avian reproductive decisions, such as clutch size and the timing of reproduction. We carried out a brood-size enlargement experiment on the great tit (Parus major), in which the birds had to lay and incubate extra eggs (full costs), only incubate extra eggs (free eggs) or did not pay any extra cost (free chicks) in obtaining a larger brood. We used female fitness (half the recruits produced plus female survival) as a fitness measure because it is the female which pays the costs of egg production and incubation, and because clutch size is under female control. Female fitness decreased with increasing costs (fitness of free chicks females is higher than that of free eggs females which is higher than that of full costs females). These fitness differences were due to differences in female survival rather than in the number of recruits produced. This is the first time that the costs of egg production and incubation have been estimated using such a complete fitness measure, including, as our measure does, the local survival to the following year of both the female and her offspring. Our results emphasize that reproductive decisions cannot be understood without taking egg production and incubation costs into account.

https://www.uv.mx/personal/tcarmona/files/2010/08/Visser-and-Lessells-2001.pdf

The costs of egg production and incubation in great tits (Parus major)

Modellers of biological, ecological, and environmental systems cannot take for granted the maxim 'simple means general means good'. We argue here that viewing simple models as the main way to achieve generality may be an obstacle to the progress of ecological research. We show how complex models can be both desirable and general, and how simple and complex models can be linked together to produce broad-scale and predictive understanding of biological systems.

/pdf/do-simple-models-lead-to-generality-in-ecology-1n54h1su3u.pdf

C. M. Lessells

Papers

Unrepeatable repeatabilities: a common mistake

Climate change and population declines in a long-distance migratory bird

Warmer springs lead to mistimed reproduction in great tits (Parus major)

The costs of egg production and incubation in great tits (Parus major)

Do simple models lead to generality in ecology