Summary 1.How body mass and body temperature influence metabolic rate has been of interest for decades. Today that interest can be seen in the form of debates over the proper scaling coefficients, and the mechanistic underpinnings of allometric models for metabolic rate in relation to body mass and body temperature. We tested explicit assumptions built into what we term the Arrhenius fractal supply (AFS) model of these relationships. This model, and its assumptions, is foundational to the controversial Metabolic Theory of Ecology. 2. In addition to predicting that the scaling exponent for body mass is 3/4, the AFS model originally predicted that metabolic responses to body temperature, measured as activation energies, should fall between 0·2 and 1·2 eV. More recently, the latter range was narrowed to 0·6 and 0·7 eV. 3. To test the AFS's predictions, we used multiple regression of ln(metabolic rate) as a function of ln(body mass) and 1/(body temperature) to fit the best scaling exponent for body mass to nine data sets of many diverse species. 4. For the majority of the data sets, in addition to not supporting a scaling exponent of 3/4, the analyses indicated that effects of body temperature sometimes fell outside the range of 0·6-0·7 eV, indicating that the predictions of the AFS model do not hold universally. 5. Effects of body temperature, however, did fall within the range of 0·2-1·2 eV. To aid interpretation of these results, we transformed activation energies into Q 10 s. At ecologically realistic temperatures, the values of Q 10 that approximate activation energies of 0·2-1·2 eV ranged from c. 1·4 to 6·1 (where 6·1 is clearly unreasonably high). Hence, any model that predicts activation energies between 0·2 and 1·2 eV does not appear to be an informative scaling model at the organismal level. 6. The AFS model is foundational for the Metabolic Theory of Ecology. While we commend the attempt to incorporate scaling of metabolism into ecological theory, and the research it has inspired, we caution against using untested, and likely incorrect, assumptions as a foundation to a general theory of ecology. We recommend that scientists allow the data to determine the best model for incorporating energetics into ecological theory.

A rising prevalence of head lice among school children and rising sales of insecticides with anecdotal evidence of their treatment failure, led us to examine whether head lice in Bristol and Bath were resistant to the insecticides available for treating head lice. Ten schools in Bristol and Bath were visited to collect field samples of head lice. A comparison was made of the survival rates of fully sensitive laboratory reared body lice and field samples of head lice on insecticide exposure. To confirm the in vitro relevance of these tests we performed supervised treatments of affected subjects with malathion or permethrin. There were significant differences (P < 10-6 Fishers exact test) between head and body lice survival for malathion and permethrin exposure, but not for carbaryl. There was an 87% failure rate for permethrin and a 64% failure rate for malathion with the topical treatment of a selected number of infested school children. We conclude that there is a high resistance to permethrin and malathion, but head lice remain fully sensitive to carbaryl. This is the first report of doubly resistant head lice. As permethrin, phenothrin (a very similar synthetic pyrethroid) or malathion are the active ingredients in all the over-the-counter head lice treatments in the U.K., then it is likely that head lice prevalence will continue to increase. The resistance against permethrin employed by the head louse is probably the kdr (knockdown resistance) mechanism, and an enzyme-mediated malathion-specific esterase is the likely mechanism against malathion.

Ecoimmunology utilizes techniques from traditionally laboratory-based disciplines--for example, immunology, genomics, proteomics, neuroendocrinology, and cell biology--to reveal how the immune systems of wild organisms both shape and respond to ecological and evolutionary pressures. Immunological phenotypes are embedded within a mechanistic pathway leading from genotype through physiology to shape higher-order biological phenomena. As such, "mechanisms" in ecoimmunology can refer to both the within-host processes that shape immunological phenotypes, or it can refer the ways in which different immunological phenotypes alter between-organism processes at ecological and evolutionary scales. The mechanistic questions ecoimmunologists can ask, both within-organisms and between-organisms, however, often have been limited by techniques that do not easily transfer to wild, non-model systems. Thus, a major focus in ecoimmunology has been developing and refining the available toolkit. Recently, this toolkit has been expanding at an unprecedented rate, bringing new challenges to choosing techniques and standardizing protocols across studies. By confronting these challenges, we will be able to enhance ecoimmunological inquiries into the physiological basis of life-history trade-offs; the development of low-cost biomarkers for susceptibility to disease; and the investigation of the ecophysiological underpinnings of disease ecology, behavior, and the coevolution of host-parasite systems. The technical advances in, and crossover technologies from, disciplines associated with ecoimmunology and how these advances can help us understand the mechanistic basis of immunological variability in wild species were the focus of the symposium, Methods and Mechanisms in Ecoimmunology.

Metabolic rates are correlated with many aspects of ecology, but how selection on different aspects of metabolic rates affects their mutual evolution is poorly understood. Using laboratory mice, we artificially selected for high maximal mass-independent metabolic rate (MMR) without direct selection on mass-independent basal metabolic rate (BMR). Then we tested for responses to selection in MMR and correlated responses to selection in BMR. In other lines, we antagonistically selected for mice with a combination of high mass-independent MMR and low mass-independent BMR. All selection protocols and data analyses included body mass as a covariate, so effects of selection on the metabolic rates are mass adjusted (that is, independent of effects of body mass). The selection lasted eight generations. Compared with controls, MMR was significantly higher (11.2%) in lines selected for increased MMR, and BMR was slightly, but not significantly, higher (2.5%). Compared with controls, MMR was significantly higher (5.3%) in antagonistically selected lines, and BMR was slightly, but not significantly, lower (4.2%). Analysis of breeding values revealed no positive genetic trend for elevated BMR in high-MMR lines. A weak positive genetic correlation was detected between MMR and BMR. That weak positive genetic correlation supports the aerobic capacity model for the evolution of endothermy in the sense that it fails to falsify a key model assumption. Overall, the results suggest that at least in these mice there is significant capacity for independent evolution of metabolic traits. Whether that is true in the ancestral animals that evolved endothermy remains an important but unanswered question. INTRODUCTIONEnergy metabolism is one of the most fundamental aspects of biology, and it is key to understanding life histories of living organisms. Its central importance is reflected in the thousands of studies published on energy metabolism (Houston et al., 1993;Hayes and O'Connor, 1999;Speakman, 2008; Burton et al., 2011, Konarzewski andKsiążek, 2013;White and Kearney, 2013). Despite these studies, many questions about metabolic rates and energy metabolism remain unanswered. For example, is there a universal metabolic scaling law, why is resting metabolism correlated with daily energy use in mammals but not birds, how did the diverse resting and maximal metabolic rates of animals evolve and is there a necessary correlation between resting and maximal aerobic metabolism in vertebrates (Ricklefs et al., 1996;Clavijo-Baque and Bozinovic, 2012)? Some of these questions are very difficult to answer but ecological and evolutionary physiologists have recently made increasing use of artificial selection experiments to test hypotheses about the phenotypic and genetic integration of energy metabolism (Swallow et al