Huston Michael A
Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831-6335 USA Fax: 423-574-2232; e-mail:
Oecologia. 1997 May;110(4):449-460. doi: 10.1007/s004420050180.
Interactions between biotic and abiotic processes complicate the design and interpretation of ecological experiments. Separating causality from simple correlation requires distinguishing among experimental treatments, experimental responses, and the many processes and properties that are correlated with either the treatments or the responses, or both. When an experimental manipulation has multiple components, but only one of them is identified as the experimental treatment, erroneous conclusions about cause and effect relationships are likely because the actual cause of any observed response may be ignored in the interpretation of the experimental results. This unrecognized cause of an observed response can be considered a "hidden treatment." Three types of hidden treatments are potential problems in biodiversity experiments: (1) abiotic conditions, such as resource levels, or biotic conditions, such as predation, which are intentionally or unintentionally altered in order to create differences in species numbers for "diversity" treatments; (2) non-random selection of species with particular attributes that produce treatment differences that exceed those due to "diversity" alone; and (3) the increased statistical probability of including a species with a dominant negative or positive effect (e.g., dense shade, or nitrogen fixation) in randomly selected groups of species of increasing number or "diversity." In each of these cases, treatment responses that are actually the result of the "hidden treatment" may be inadvertently attributed to variation in species diversity. Case studies re-evaluating three different types of biodiversity experiments demonstrate that the increases found in such ecosystem properties as productivity, nutrient use efficiency, and stability (all of which were attributed to higher levels of species diversity) were actually caused by "hidden treatments" that altered plant biomass and productivity.
生物过程与非生物过程之间的相互作用使得生态实验的设计与解释变得复杂。要将因果关系与简单的相关性区分开来,就需要区分实验处理、实验响应,以及与处理或响应,或两者都相关的许多过程和特性。当一个实验操作有多个组成部分,但只有其中一个被确定为实验处理时,关于因果关系的错误结论很可能会出现,因为在解释实验结果时,任何观察到的响应的实际原因可能会被忽略。这种未被认识到的观察到的响应的原因可以被视为一种“隐藏处理”。在生物多样性实验中,三种类型的隐藏处理是潜在问题:(1)非生物条件,如资源水平,或生物条件,如捕食,它们被有意或无意地改变,以便为“多样性”处理创造物种数量上的差异;(2)对具有特定属性的物种进行非随机选择,这些属性产生的处理差异超过了仅由“多样性”导致的差异;(3)在随机选择的数量不断增加或“多样性”不断增加的物种组中,包含具有显著负面或正面影响(如浓密树荫或固氮)的物种的统计概率增加。在上述每种情况下,实际上是“隐藏处理”结果的处理响应可能会被无意地归因于物种多样性的变化。重新评估三种不同类型生物多样性实验的案例研究表明,在诸如生产力、养分利用效率和稳定性等生态系统属性中发现的增加(所有这些都归因于更高水平的物种多样性)实际上是由改变植物生物量和生产力的“隐藏处理”引起的。