The Future is Bright for Evolutionary Morphology and Biomechanics in the Era of Big Data
The Future is Bright for Evolutionary Morphology and Biomechanics in the Era of Big Data
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DOI：
10.1093/icb/icz121
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发表时间：
2019-09-01
影响因子：
2.6
通讯作者：
Price, Samantha A.
中科院分区：
文献类型：
--
作者：
Munoz, Martha M.;Price, Samantha A.
近年来，进化生物力学和形态学领域已经发展成为一门深入的定量和综合科学，从而对结构关系如何塑造宏观进化模式有了更丰富的理解。这个问题突出了概念和实验前沿的新研究，特别关注将大数据方法应用于形式功能进化中的经典问题。正如这个问题所说明的，新技术和分析工具正在促进生物力学，功能形态学和系统发育比较方法的整合，以催化一个新的，更综合的学科。虽然我们正处于生物体生物学大数据生成的风口浪尖，但该领域仍然是数据有限的。这种数据瓶颈主要是由于数字化标本、记录和跟踪生物体运动以及从大量数据集中提取模式的限速步骤。自动化和机器学习方法在帮助数据生成与想法保持同步方面具有很大的潜力。作为最后也是最重要的一点，几乎所有的研究都依赖于博物馆藏品提供的数以万计的样本。如果没有博物馆标本的收集、管理和保护，该领域的未来就不那么光明了。
Synopsis In recent years, the fields of evolutionary biomechanics and morphology have developed into a deeply quantitative and integrative science, resulting in a much richer understanding of how structural relationships shape macroevolutionary patterns. This issue highlights new research at the conceptual and experimental cutting edge, with a special focus on applying big data approaches to classic questions in form-function evolution. As this issue illustrates, new technologies and analytical tools are facilitating the integration of biomechanics, functional morphology, and phylogenetic comparative methods to catalyze a new, more integrative discipline. Although we are at the cusp of the big data generation of organismal biology, the field is nonetheless still data-limited. This data bottleneck is primarily due to the rate-limiting steps of digitizing specimens, recording and tracking organismal movements, and extracting patterns from massive datasets. Automation and machine-learning approaches hold great promise to help data generation keep pace with ideas. As a final and important note, almost all the research presented in this issue relied on specimens-totaling the tens of thousands-provided by museum collections. Without collection, curation, and conservation of museum specimens, the future of the field is much less bright.