Data from: Mass-independent maximal metabolic rate predicts geographic range size of placental mammals

1.Understanding the mechanisms driving geographic range sizes of species is a central issue in ecology, but remarkably few rules link physiology with the distributions of species. Maximal metabolic rate (MMR) during exercise is an important measure of physiological performance. It sets an upper limit to sustained activity and locomotor capacity, so MMR may influence ability to migrate, disperse, and maintain population connectivity. Using both conventional ordinary least squares (OLS) analyses and phylogenetically generalized least squares (PGLS), we tested whether MMR helps explain geographic range size in 51 species of placental mammals.

2.Log body mass alone (OLS r2 = 0.074, p = 0.053; PGLS r2 = 0.016, p = 0.373) and log MMR alone (OLS r2 = 0.140, p = 0.007; PGLS r2 = 0.061, p = 0.081) were weak predictors of log range size.

3.However, multiple regression of log body mass and log MMR accounted for over half of the variation in log range size (OLS R2 = 0.527, p < 0.001). The relationship was also strong after correcting for the phylogenetic non-independence (PGLS R2 = 0.417, p < 0.001).

4.In analyses restricted to rodents (34 species), neither log body mass alone (OLS r2 = 0.004, p = 0.720; PGLS r2 = 0.003, p = 0.77) nor log MMR alone was useful in predicting log geographic range size (OLS r2 = 0.008, p = 0.626; PGLS r2 = 0.046, p = 0.225), but multiple regressions of log body mass and log MMR accounted for roughly a third to a half of the variation in log range size (OLS R2= 0.443, p < 0.001, PGLS r2 = 0.381, p < 0.001).

5.Mass-independent MMR is a strong predictor of mass-independent geographic range size in placental mammals. The ability of body mass and MMR to explain nearly 50% of the variation in the geographic ranges of mammals is surprising and powerful, particularly when neither variable alone is strongly predictive.

6.A better understanding of MMR during exercise may be important to understanding the limits of geographic ranges of mammals, and perhaps other animal groups.

1. 阐明驱动物种地理分布范围大小的机制是生态学领域的核心议题之一，但目前能将生理机能与物种分布联系起来的普适性规律却寥寥无几。运动过程中的最大代谢率（maximal metabolic rate, MMR）是衡量生理性能的重要指标，它为持续活动与运动能力设定了上限，因此可能会影响物种迁徙、扩散以及维持种群连通性的能力。本研究分别采用普通最小二乘法（ordinary least squares, OLS）与系统发育广义最小二乘法（phylogenetically generalized least squares, PGLS）两种分析方法，针对51种胎盘类哺乳动物，检验了最大代谢率是否能够解释其地理分布范围大小。
2. 仅以体质量对数作为自变量时（OLS: r²=0.074, p=0.053；PGLS: r²=0.016, p=0.373），其对分布范围对数的预测能力较弱；仅以最大代谢率对数作为自变量时（OLS: r²=0.140, p=0.007；PGLS: r²=0.061, p=0.081），同样仅能实现较弱的预测效果。
3. 但将体质量对数与最大代谢率对数进行多元回归分析时，其对分布范围对数变异的解释度超过了50%（OLS: R²=0.527, p<0.001）；在校正系统发育非独立性后，该关联依然显著（PGLS: R²=0.417, p<0.001）。
4. 在仅针对啮齿类（共34个物种）的亚组分析中，无论是单独使用体质量对数（OLS: r²=0.004, p=0.720；PGLS: r²=0.003, p=0.77），还是单独使用最大代谢率对数（OLS: r²=0.008, p=0.626；PGLS: r²=0.046, p=0.225），均无法有效预测地理分布范围对数；但将二者结合进行多元回归时，其对分布范围对数变异的解释度约为30%~50%（OLS: R²=0.443, p<0.001；PGLS: r²=0.381, p<0.001）。
5. 质量无关的最大代谢率是胎盘类哺乳动物质量无关地理分布范围大小的强预测因子。体质量与最大代谢率能够解释近50%的哺乳动物地理分布范围变异，这一结果既出人意料又极具说服力，尤其是在单一变量均无显著预测能力的前提下。
6. 若能更深入地理解运动过程中的最大代谢率机制，或有助于阐明哺乳动物乃至其他动物类群的地理分布范围极限。