Collaborative Research: Origins of Southeast Asian Rainforests from Paleobotany and Machine Learning

化石叶子是古代植物生命最丰富的记录，博物馆藏品中包含数百万个标本，围绕化石叶子是古代植物生命最丰富的记录，世界各地的博物馆收藏中包含数百万个标本，每年都有更多的发现。然而，目前仅靠叶片化石提供的关于区域和全球植物群落进化的信息有限，因为单一植物物种的单个叶片特征可能差异很大，而且对每个叶片化石的详细、耗时的检查可能仍然无法将其与真正的生物家族联系起来。这个项目通过两种方式解决这个问题。首先是开发虚拟古植物学助手(VPA)，这是一种人工智能工具，将使用机器学习技术快速分析树叶特征，将单个化石分配给植物科和目。VPA与更传统的古植物学方法一起，将被用来解释东南亚现在存在的极其多样化的热带雨林的起源。这些植物群落在重大大陆运动期间进化，并与前超大陆冈瓦那、印度次大陆和欧亚大陆有联系。确定导致这些热带森林聚集的进化和生物地理路径将有助于在区域人口迅速增长的情况下保护这一重要的自然资源。VPA将在互联网和移动平台上免费提供，使世界各地的古植物学家能够做出远远超出该项目的发现。古生物学家和机器学习专家之间的独特合作将为跨学科发展创造极其肥沃的土壤，同时催化新的国际伙伴关系和学生机会。该项目解决了古植物学中最困难的两个挑战，即化石树叶鉴定和东南亚(马来)热带雨林的化石历史。破译叶片化石的生物亲和力对于提高植物进化、生物地理学和古气候的认识具有重要意义。该项目将利用对现存树叶和化石树叶的图像数据库的深入学习来开发第一个应用程序(虚拟古植物学助手，VPA)，用于计算机辅助识别植物科和目的树叶化石。东南亚现存的植物群由令人震惊的复杂植物谱系并列组成，这些植物谱系在来自不同来源后变得多样化，包括冈瓦那(将在巴塔哥尼亚和澳大利亚研究的化石)、印度板块(印度和巴基斯坦)和欧亚大陆(南中国、印度支那、马来群岛)。然而，由于许多来源地区的古植物学数据有限，各种生物地理成分仍然知之甚少。许多被广泛引用的假说从化石中得到了微弱的证实；古植物学和机器视觉将协调起来，揭示植物化石的身份，将它们与地质时间尺度相关联，并重新解释马来西亚的植物区系历史。新的古植物学数据的涌入将检验关于不同来源地区对东南亚雨林植物群的相对贡献的基本假设。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Fossil leaves are the most abundant record of ancient plant life and millions of specimens are contained in museum collections around Fossil leaves are the most abundant record of ancient plant life, and millions of specimens are contained in museum collections around the world, with more discoveries every year. Nevertheless, leaf fossils alone currently provide limited information about the evolution of regional and global plant communities because individual leaf characteristics from a single plant species can vary widely, and detailed, time-consuming examination of each leaf fossil might still not connect it to its true biological family. This project addresses the problem in two ways. First will be the development of the Virtual Paleobotany Assistant (VPA), an artificial intelligence tool that will use machine learning techniques to rapidly analyze leaf characteristics to assign individual fossils to plant families and orders. The VPA, together with more traditional methods of paleobotany, will then be used to interpret the origins of the incredibly diverse tropical rain forests that now exist in Southeast Asia. These plant communities evolved during times of major continental movements and have connections to the former supercontinent of Gondwana, the Indian subcontinent, and Eurasia. Ascertaining the evolutionary and biogeographic pathways that led to the assembly of these tropical forests will help in preserving this important natural resource as the regional human population burgeons. The VPA will be made freely available on the internet and mobile platforms, enabling paleobotanists around the world to make discoveries far beyond this project. The unique collaboration between paleontologists and machine-learning experts will create extremely fertile ground for interdisciplinary advances, while catalyzing new international partnerships and student opportunities. The project addresses two of the most difficult challenges in paleobotany, fossil leaf identification and the fossil history of Southeast Asian (Malesian) rainforests. Decoding the biological affinities of leaf fossils holds central significance for the improved knowledge of plant evolution, biogeography, and paleoclimate. This project will use deep learning on image databases of extant and fossil leaves to develop the first application (the Virtual Paleobotany Assistant, VPA) for computer-assisted identifications of leaf fossils to plant families and orders. The living floras of Southeast Asia are composed of a stunningly complex juxtaposition of plant lineages that diversified after arriving from disparate sources, including Gondwana (fossils to be studied in Patagonia and Australia), the Indian Plate (India and Pakistan), and Eurasia (South China, Indochina, Malay Archipelago). However, the diverse biogeographic components remain poorly understood due to limited paleobotanical data in many of the source areas. Many widely cited hypotheses are weakly corroborated from fossils; paleobotany and machine vision will coordinate to reveal the identities of fossil plants, correlate them to the geologic time scale, and re-interpret Malesia's floristic history. The influx of new paleobotanical data will test fundamental hypotheses about the relative contributions to Southeast Asian rainforest floras from different source areas.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.