Soil respiration （SR） is commonly modeled by a Q10 （an indicator of temperature sensitivity） function in ecosystem models. Q10 is usually treated as a constant of 2 in these models, although Q10 value of SR often ...Soil respiration （SR） is commonly modeled by a Q10 （an indicator of temperature sensitivity） function in ecosystem models. Q10 is usually treated as a constant of 2 in these models, although Q10 value of SR often decreases with increasing temperatures. It remains unclear whether a general temperature- dependent Q10 model of SR exists at biome and global scale. In this paper, we have compiled the long-term Q10 data of 38 SR studies ranging from the Boreal, Temperate, to Tropical/Sublropical biome on four continents. Our analysis indicated that the general temperature-dependent biome Q10 models of SR existed, especially in the Boreal and Temperate biomes. A single-exponential model was better than a simple linear model in fitting the average Q10 values at the biome scale. Average soil temperature is a better predictor of Q10 value than average air temperature in these models, especially in the Boreal biome. Soil temperature alone could explain about 50% of the Q10 variations in both the Boreal and Temperate biome single-exponential Q10 model. Q10 value of SR decreased with increasing soil temperature but at quite different rates among the three biome Q10 models. The k values （Q10 decay rate constants） were 0.09, 0.07, and 0.02/℃ in the Boreal, Temperate, and Tropical/Subtropical biome, respectively, suggesting that Q10 value is the most sensitive to soil temperature change in the Boreal biome, the second in the Temperate biome, and the least sensitive in the Tropical/ Subtropical biome. This also indirectly confirms that acclimation of SR in many soil warming experiments probably occurs. The k value in the ＂global＂ single-exponential Q10 model which combined both the Boreal and Temperate biome data set was 0.08/℃. However, the global general temperature-dependent Q10 model developed using the data sets of the three biomes is not adequate for predicting Q10 values of SR globally. The existence of the general temperature-dependent Q10 models of SR in the Boreal and Temperate biome has important implications for modeling SR, especially in the Boreal biome. More detail model runs are needed to exactly evaluate the impact of using a fixed Q10 vs a temperature-dependent Q10 on SR estimate in ecosystem models （e.g., TEM, Biome-BGC, and PnET）.展开更多
物种分布模型(species distribution models,SDMs)已成为宏观生态学和生物地理学研究不可或缺的工具,广泛应用于预测物种分布、评估外来物种的入侵风险和气候变化对物种分布的影响等,从而指导入侵物种防控和生物多样性保护规划。然而,...物种分布模型(species distribution models,SDMs)已成为宏观生态学和生物地理学研究不可或缺的工具,广泛应用于预测物种分布、评估外来物种的入侵风险和气候变化对物种分布的影响等,从而指导入侵物种防控和生物多样性保护规划。然而,该领域的快速发展也伴随着理论与实践的脱节,尤其体现在对“生态位”概念的混淆上。本文系统梳理了生态学中3个核心的生态位概念:格林内尔生态位(Grinnellian niche),关注环境条件与物种分布的宏观关系;埃尔顿生态位(Eltonian niche),强调物种在群落中的功能角色和生物互作;以及哈钦森生态位(Hutchinsonian niche),提供了“n维超体积(n-dimensional hypervolume)”的数学框架,并区分了基础生态位与实际生态位。本文进一步探讨了与各生态位概念相对应的建模方法,包括标准的物种分布模型、联合物种分布模型(joint species distribution models,JSDMs)和n维超体积分析。通过分析当前研究中存在的概念混淆(如将基于存在记录的物种分布模型等同于基础生态位模型)、模型误用(如忽视非平衡状态和采样偏差)等常见问题,本文强调了明确研究的理论基础、匹配建模方法与研究问题、审慎解读模型结果的重要性。最后,本文提出,未来的研究应致力于概念的清晰化、方法的整合化以及理论与应用的深度融合,从而更科学、规范地应用物种分布模型,推动生态学理论的发展。展开更多
文摘Soil respiration （SR） is commonly modeled by a Q10 （an indicator of temperature sensitivity） function in ecosystem models. Q10 is usually treated as a constant of 2 in these models, although Q10 value of SR often decreases with increasing temperatures. It remains unclear whether a general temperature- dependent Q10 model of SR exists at biome and global scale. In this paper, we have compiled the long-term Q10 data of 38 SR studies ranging from the Boreal, Temperate, to Tropical/Sublropical biome on four continents. Our analysis indicated that the general temperature-dependent biome Q10 models of SR existed, especially in the Boreal and Temperate biomes. A single-exponential model was better than a simple linear model in fitting the average Q10 values at the biome scale. Average soil temperature is a better predictor of Q10 value than average air temperature in these models, especially in the Boreal biome. Soil temperature alone could explain about 50% of the Q10 variations in both the Boreal and Temperate biome single-exponential Q10 model. Q10 value of SR decreased with increasing soil temperature but at quite different rates among the three biome Q10 models. The k values （Q10 decay rate constants） were 0.09, 0.07, and 0.02/℃ in the Boreal, Temperate, and Tropical/Subtropical biome, respectively, suggesting that Q10 value is the most sensitive to soil temperature change in the Boreal biome, the second in the Temperate biome, and the least sensitive in the Tropical/ Subtropical biome. This also indirectly confirms that acclimation of SR in many soil warming experiments probably occurs. The k value in the ＂global＂ single-exponential Q10 model which combined both the Boreal and Temperate biome data set was 0.08/℃. However, the global general temperature-dependent Q10 model developed using the data sets of the three biomes is not adequate for predicting Q10 values of SR globally. The existence of the general temperature-dependent Q10 models of SR in the Boreal and Temperate biome has important implications for modeling SR, especially in the Boreal biome. More detail model runs are needed to exactly evaluate the impact of using a fixed Q10 vs a temperature-dependent Q10 on SR estimate in ecosystem models （e.g., TEM, Biome-BGC, and PnET）.
文摘物种分布模型(species distribution models,SDMs)已成为宏观生态学和生物地理学研究不可或缺的工具,广泛应用于预测物种分布、评估外来物种的入侵风险和气候变化对物种分布的影响等,从而指导入侵物种防控和生物多样性保护规划。然而,该领域的快速发展也伴随着理论与实践的脱节,尤其体现在对“生态位”概念的混淆上。本文系统梳理了生态学中3个核心的生态位概念:格林内尔生态位(Grinnellian niche),关注环境条件与物种分布的宏观关系;埃尔顿生态位(Eltonian niche),强调物种在群落中的功能角色和生物互作;以及哈钦森生态位(Hutchinsonian niche),提供了“n维超体积(n-dimensional hypervolume)”的数学框架,并区分了基础生态位与实际生态位。本文进一步探讨了与各生态位概念相对应的建模方法,包括标准的物种分布模型、联合物种分布模型(joint species distribution models,JSDMs)和n维超体积分析。通过分析当前研究中存在的概念混淆(如将基于存在记录的物种分布模型等同于基础生态位模型)、模型误用(如忽视非平衡状态和采样偏差)等常见问题,本文强调了明确研究的理论基础、匹配建模方法与研究问题、审慎解读模型结果的重要性。最后,本文提出,未来的研究应致力于概念的清晰化、方法的整合化以及理论与应用的深度融合,从而更科学、规范地应用物种分布模型,推动生态学理论的发展。
