Despite the importance of network analysis in biological practice, dominant models of scientific explanation do not account satisfactorily for how this family of explanations gain their explanatory power in every specific application. This insufficiency is particularly salient in the study of the ecology of the microbiome. Drawing on Coyte et al. (2015) study of the ecology of the microbiome, Deulofeu et al. (2021) argue that these explanations are neither mechanistic, nor purely mathematical, yet they are substantially empirical. Building on their criticisms, in the present work we make a step further elucidating this kind of explanations with a general analytical framework according to which scientific explanations are ampliative, specialized embeddings (ASE), which has recently been successfully applied to other biological subfields. We use ASE to reconstruct in detail the Coyte et al.’s case study and on its basis, we claim that network explanations of the ecology of the microbiome, and other similar explanations in ecology, gain their epistemological force in virtue of their capacity to embed biological phenomena in non-accidental generalizations that are simultaneously ampliative and specialized.

尽管网络分析在生物学实践中很重要，但科学解释的主导模型并不能令人满意地解释这一系列解释如何在每个特定应用中获得解释力。这种不足在微生物组生态学研究中尤为突出。借鉴 Coyte 等人的经验。 (2015) 微生物生态学研究，Deulofeu 等人。 （2021）认为这些解释既不是机械的，也不是纯粹数学的，但它们基本上是经验性的。基于他们的批评，在目前的工作中，我们用一个通用的分析框架进一步阐明了这种解释，根据该框架，科学解释是放大的、专门的嵌入（ASE），最近已成功应用于其他生物学子领域。我们使用 ASE 详细重建了 Coyte 等人的案例研究，并在此基础上，我们声称微生物组生态学的网络解释以及生态学中的其他类似解释凭借其以下能力获得了认识论力量：将生物现象嵌入非偶然的概括中，这些概括同时具有放大性和专门性。