Equipe Géomicrobiologie, Université de Paris, Institut de Physique du Globe de Paris, CNRS, Paris, France.
Laboratorio de Estudios Cristalográficos, Instituto Andaluz de Ciencias de la Tierra, Consejo Superior de Investígacìones Cientificas-Universidad de Granada, Granada, Spain.
Geobiology. 2020 May;18(3):282-305. doi: 10.1111/gbi.12377. Epub 2019 Dec 26.
The identification of cellular life in the rock record is problematic, since microbial life forms, and particularly bacteria, lack sufficient morphologic complexity to be effectively distinguished from certain abiogenic features in rocks. Examples include organic pore-fillings, hydrocarbon-containing fluid inclusions, organic coatings on exfoliated crystals and biomimetic mineral aggregates (biomorphs). This has led to the interpretation and re-interpretation of individual microstructures in the rock record. The morphologic description of entire populations of microstructures, however, may provide support for distinguishing between preserved micro-organisms and abiogenic objects. Here, we present a statistical approach based on quantitative morphological description of populations of microstructures. Images of modern microbial populations were compared to images of two relevant types of abiogenic microstructures: interstitial spaces and silica-carbonate biomorphs. For the populations of these three systems, the size, circularity, and solidity of individual particles were calculated. Subsequently, the mean/SD, skewness, and kurtosis of the statistical distributions of these parameters were established. This allowed the qualitative and quantitative comparison of distributions in these three systems. In addition, the fractal dimension and lacunarity of the populations were determined. In total, 11 parameters, independent of absolute size or shape, were used to characterize each population of microstructures. Using discriminant analysis with parameter subsets, it was found that size and shape distributions are typically sufficient to discriminate populations of biologic and abiogenic microstructures. Analysis of ancient, yet unambiguously biologic, samples (1.0 Ga Angmaat Formation, Baffin Island, Canada) suggests that taphonomic effects can alter morphometric characteristics and complicate image analysis; therefore, a wider range of microfossil assemblages should be studied in the future before automated analyses can be developed. In general, however, it is clear from our results that there is great potential for morphometric descriptions of populations in the context of life recognition in rocks, either on Earth or on extraterrestrial bodies.
在岩石记录中识别细胞生命是有问题的，因为微生物生命形式，特别是细菌，缺乏足够的形态复杂性，无法有效地与岩石中的某些非生物特征区分开来。这些特征包括有机孔隙填充物、含碳氢化合物的流体包裹体、剥落晶体上的有机涂层和仿生矿物聚集体（生物形态）。这导致了对岩石记录中单个微观结构的解释和重新解释。然而，对整个微观结构种群的形态描述可能有助于区分保存的微生物和非生物物体。在这里，我们提出了一种基于微观结构种群定量形态描述的统计方法。现代微生物种群的图像与两种相关类型的非生物微观结构的图像进行了比较：间隙空间和硅碳酸盐生物形态。对于这三个系统的种群，计算了单个颗粒的大小、圆形度和密实度。随后，建立了这些参数统计分布的均值/标准差、偏度和峰度。这使得可以对这三个系统的分布进行定性和定量比较。此外，还确定了种群的分形维数和空穴度。总共使用了 11 个独立于绝对大小或形状的参数来描述每个微观结构种群。使用带有参数子集的判别分析发现，大小和形状分布通常足以区分生物和非生物微观结构的种群。对古代但明确是生物的样品（加拿大巴芬岛 10 亿年的 Angmaat 组）的分析表明，埋藏效应会改变形态特征并使图像分析复杂化；因此，在开发自动化分析之前，应该在未来研究更广泛的微化石组合。然而，总的来说，从我们的结果中可以清楚地看出，在岩石中识别生命的背景下，对种群进行形态描述具有很大的潜力，无论是在地球上还是在地球以外的天体上。
