PMC:4264897 / 16207-17787 JSONTXT

{"project":"MyTest","denotations":[{"id":"25512844-23637808-26483239","span":{"begin":17,"end":21},"obj":"23637808"},{"id":"25512844-23637808-26483240","span":{"begin":208,"end":212},"obj":"23637808"},{"id":"25512844-23637808-26483241","span":{"begin":506,"end":510},"obj":"23637808"}],"namespaces":[{"prefix":"_base","uri":"https://www.uniprot.org/uniprot/testbase"},{"prefix":"UniProtKB","uri":"https://www.uniprot.org/uniprot/"},{"prefix":"uniprot","uri":"https://www.uniprot.org/uniprotkb/"}],"text":"Kelly and Tawes (2013) calculated condition scores using , but the allometric scaling exponent they used was calculated from that data set (b SMA = 2.319). In this study, we calculated for Kelly and Tawes’ (2013) crickets using the b SMA from the G. texensis reference population (b SMA = 2.642; see above), while the mean pronotum length was the same in both cases (i.e., L 0   =   3.073 mm). As discussed by Peig and Green (2010), using the b SMA from the experimental population (e.g., Kelly and Tawes 2013) might not be ideal because the development of the test animals was manipulated via diet restriction and thus they might not exhibit the “true” scaling relationship. We substituted these values along with individual body mass (M i) and pronotum length (L i) into Eq. (1) to calculate for each cricket. Prior to calculating the common standard major axis regression slope (b SMA) for use in Eq. (1), however, we first tested the assumption that the slopes did not differ between the sexes and diet treatments by adding either sex or diet to the model and inspecting the interaction term (a significant interaction suggests that the slopes are heterogeneous). Similarly, we tested whether the elevations of standard major axis slopes differed within each factor by inspecting their 95% confidence intervals; the hypothesis of different elevations is rejected by overlapping confidence intervals. All variables were log-transformed prior to analysis. We tested the effect of sex and diet on by entering both of these fixed factors as independent variables into an ANOVA."}

{"project":"2_test","denotations":[{"id":"25512844-23637808-26483239","span":{"begin":17,"end":21},"obj":"23637808"},{"id":"25512844-23637808-26483240","span":{"begin":208,"end":212},"obj":"23637808"},{"id":"25512844-23637808-26483241","span":{"begin":506,"end":510},"obj":"23637808"}],"text":"Kelly and Tawes (2013) calculated condition scores using , but the allometric scaling exponent they used was calculated from that data set (b SMA = 2.319). In this study, we calculated for Kelly and Tawes’ (2013) crickets using the b SMA from the G. texensis reference population (b SMA = 2.642; see above), while the mean pronotum length was the same in both cases (i.e., L 0   =   3.073 mm). As discussed by Peig and Green (2010), using the b SMA from the experimental population (e.g., Kelly and Tawes 2013) might not be ideal because the development of the test animals was manipulated via diet restriction and thus they might not exhibit the “true” scaling relationship. We substituted these values along with individual body mass (M i) and pronotum length (L i) into Eq. (1) to calculate for each cricket. Prior to calculating the common standard major axis regression slope (b SMA) for use in Eq. (1), however, we first tested the assumption that the slopes did not differ between the sexes and diet treatments by adding either sex or diet to the model and inspecting the interaction term (a significant interaction suggests that the slopes are heterogeneous). Similarly, we tested whether the elevations of standard major axis slopes differed within each factor by inspecting their 95% confidence intervals; the hypothesis of different elevations is rejected by overlapping confidence intervals. All variables were log-transformed prior to analysis. We tested the effect of sex and diet on by entering both of these fixed factors as independent variables into an ANOVA."}