reporting [22,25] a difference. The rate of energy metabolism in species adapted to life in aquatic environments is relatively high compared to arboreal birds, while nocturnal species have relatively low RMR [21]. Variation in energy metabolism within Aves suggests that adaptations in breathing mechanics may have occurred to meet the oxygen demands of varied lifestyles. The supply of oxygen to gas exchange tissue is critically important for sustaining the metabolic rate of an animal. Numerous studies across a range of phyla have addressed the constraints upon oxygen delivery imposed by body size. For example, an examination of avian respiration by Lasiewski and Calder [26] highlighted the relative efficiency of the unique lung air-sac system. UP are now confirmed to be important respiratory structures in birds involved in inspiration and expiration [10]. Here we disentangle the relationships between uncinate process length (UPL), Mb and RMR in birds adapted to different modes of primary locomotion. An understanding of the relationship between the UPL and metabolic rate will shed further light on the evolution of morphological variation in these processes. Materials and Methods (a) Specimens Measurements of UPL were taken from the left-hand side of skeletons from 112 species using a Mayr digital calliper (16EX 150 mm, Product No: 4102400, Mayr GmbH, Germany). The length of process 4 was used in all statistical analyses. This process occurs in all specimens and has a relatively stable morphology [27]. Following the classification of Tickle et al [12], birds were grouped based upon their primary mode of locomotion and assigned to a single category; (1) walking (n = 13); birds which are flightless or incapable of sustained flight: (2) diving (n = 27); birds which are capable of diving underwater using foot or wing propulsion; and (3) non-specialist (n = 72); all other birds which fly and swim but are not flightless or capable of diving underwater. Body masses were taken from records of intact specimens or literature values [28]. (b) Uncinate process length and body size Reduced major axis (RMA) regression [29] was used to examine the relationship between UPL and Mb. This procedure is appropriate for analysis of morphological characters because the variation in both x and y variables is taken into account [29,30]. The slope and confidence intervals of the regression line were calculated as described by Sokal and Rohlf [29]. RMA equations for log10 transformed data were independently generated in each locomotor category. ANCOVA was used to test for significant differences between regression lines. The potentially confounding effects of the birds having a shared phylogenetic ancestry were controlled by calculating independent contrasts [31]. The phylogeny of Livezey and Zusi [32] was used to generate contrasts for log10 transformed Mb and UPL data, with the CRUNCH facility in the Comparative Analysis of Indepen- dent Contrasts (CAIC) software, version 2.6.9 [33]. A punctua- tional model of evolution was assumed and therefore all branch lengths were set as equal. RMA regression equations were calculated [29] to explore the linear relationship between phylogenetically corrected UPL and Mb. RMA regressions of independent contrasts were performed through the origin [33] for each locomotor mode. (c) Uncinate process length and metabolic rate The relationship between RMR and UPL was studied in a subset of 35 species, taken from the previous dataset. These species Uncinate Scaling were selected because corresponding RMR values are available [21,34]. These species were again assigned to locomotor categories, walking, non-specialist and diving. Body masses and values of RMR (taken from [21,34]) were log10 transformed, and only data corresponding to true RMRs, as defined by them, were used. To ensure that the regression equations describing the relationship between UPL and Mb in the species subset did not differ significantly from those in the larger dataset, RMA analyses were repeated. This procedure is important for validating the assumption that an association between process length and RMR can be extrapolated to the larger dataset. RMA regression was used to investigate the linear relationship between Mb and RMR. Finally, the scaling of RMR with UPL was explored using RMA regression. General linear models (GLM) were used to assess the influence of locomotor mode, UPL and Mb on RMR. By accounting for the variation attributable to Mb and group structure, the GLM provides an estimate of the association between RMR and process length independent of Mb. In the first analysis, locomotor category (diving, non-specialist and walking) was designated as a group factor, while Mb and UPL were the covariates (RMR = locomotor group+UPL+Mb). A second GLM analysis repeated the prior method with the group factor comprising diving and non-specialist species. Lastly, the influence of UPL and Mb on RMR, in the absence of a grouping variable, was examined (RMR = UPL+Mb). A phylogenetically controlled analysis in the form of the GLM (above) was not possible. Therefore, to assess the influence of locomotor mode, UPL and Mb on RMR whilst controlling for phylogeny we employed the following method: first the linear relationship between log10 Mb and log10 UPL was determined (UPL = 0.2137 Mb+0.4336). Residual UPL was then calculated by subtracting the length predicted from the log10 Mb/log10 UPL relationship from actual UPL for each species. The relationship between log10 RMR and residual uncinate process length was then calculated for each of the three locomotor groups using CAIC. RMA regressions were calculated to assess the linear relationship between the independent contrasts generated for RMR and residual UPL within each locomotor mode. GLM analyses were conducted in SPSS (SPSS v.15; SPSS Ltd, Chicago, IL, USA) and ANCOVAs, and RMA regressions in MATLABH 2007b (The MathWorks, Inc., 3 Apple Hill Drive, Natick, MA). Ninety five percent confidence limits are displayed in parentheses immediately after the scaling exponent. Results Uncinate process length and body size Analyses of 112 species indicated that, for all three locomotor modes investigated, uncinate process length scales isometrically with body mass (Figure 1a; Table 1), i.e. in all cases the regression line exponent did not differ significantly from 0.33. The regression line intercept differed between locomotor groups, indicating that processes are longest relative to Mb in diving birds, intermediate in non-specialists and shortest in walking birds (Figure 1a; Table 1) (ANCOVA: group, F2,108 = 14.16, P,0.001; Mb, F1,108 = 169.54, P,0.001). Greater variation around the regression line was evident for the walking category, as indicated by the lower correlation coefficient, r (Figure 1a; Table 1). Scaling of UPL against Mb using independent contrasts suggested that when phylogeny is taken into account the effects were minimal and scaling was isometric (Mb0.33) for all locomotor groups (Figure 1b; Table 1). Similar to the corresponding values estimated using the species level analysis above, variation around the regression line was greatest within the walking category (Table 1). PLoS ONE | www.plosone.org 2 May 2009 | Volume 4 | Issue 5 | e5667