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Barnes CM, Power AL, Barber DG, Tennant RK, Jones RT, Lee GR, Hatton J, Elliott A, Zaragoza-Castells J, Haley SM, Summers HD, Doan M, Carpenter AE, Rees P, Love J. Deductive automated pollen classification in environmental samples via exploratory deep learning and imaging flow cytometry. THE NEW PHYTOLOGIST 2023; 240:1305-1326. [PMID: 37678361 PMCID: PMC10594409 DOI: 10.1111/nph.19186] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Accepted: 06/30/2023] [Indexed: 09/09/2023]
Abstract
Pollen and tracheophyte spores are ubiquitous environmental indicators at local and global scales. Palynology is typically performed manually by microscopic analysis; a specialised and time-consuming task limited in taxonomical precision and sampling frequency, therefore restricting data quality used to inform climate change and pollen forecasting models. We build on the growing work using AI (artificial intelligence) for automated pollen classification to design a flexible network that can deal with the uncertainty of broad-scale environmental applications. We combined imaging flow cytometry with Guided Deep Learning to identify and accurately categorise pollen in environmental samples; here, pollen grains captured within c. 5500 Cal yr BP old lake sediments. Our network discriminates not only pollen included in training libraries to the species level but, depending on the sample, can classify previously unseen pollen to the likely phylogenetic order, family and even genus. Our approach offers valuable insights into the development of a widely transferable, rapid and accurate exploratory tool for pollen classification in 'real-world' environmental samples with improved accuracy over pure deep learning techniques. This work has the potential to revolutionise many aspects of palynology, allowing a more detailed spatial and temporal understanding of pollen in the environment with improved taxonomical resolution.
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Affiliation(s)
- Claire M. Barnes
- College of Engineering, Swansea University, Bay Campus, Swansea SA1 8EN, UK
| | - Ann L. Power
- Biosciences, Faculty of Life and Health Sciences, University of Exeter, Exeter EX4 4QD, UK
| | - Daniel G. Barber
- Geography, Faculty of Environment, Science and Economics, University of Exeter, Exeter EX4 4RJ, UK
| | - Richard K. Tennant
- Geography, Faculty of Environment, Science and Economics, University of Exeter, Exeter EX4 4RJ, UK
| | | | - G. Rob Lee
- Biosciences, Faculty of Life and Health Sciences, University of Exeter, Exeter EX4 4QD, UK
| | - Jackie Hatton
- Geography, Faculty of Environment, Science and Economics, University of Exeter, Exeter EX4 4RJ, UK
| | - Angela Elliott
- Geography, Faculty of Environment, Science and Economics, University of Exeter, Exeter EX4 4RJ, UK
| | - Joana Zaragoza-Castells
- Geography, Faculty of Environment, Science and Economics, University of Exeter, Exeter EX4 4RJ, UK
| | - Stephen M. Haley
- Geography, Faculty of Environment, Science and Economics, University of Exeter, Exeter EX4 4RJ, UK
| | - Huw D. Summers
- College of Engineering, Swansea University, Bay Campus, Swansea SA1 8EN, UK
| | - Minh Doan
- Bioimaging Analytics, GlaxoSmithKline, Collegeville, Upper Providence, PA 19426, United States
| | - Anne E. Carpenter
- Imaging Platform, Broad Institute of Harvard and MIT, Cambridge, Massachusetts MA 02142, United States
| | - Paul Rees
- College of Engineering, Swansea University, Bay Campus, Swansea SA1 8EN, UK
- Imaging Platform, Broad Institute of Harvard and MIT, Cambridge, Massachusetts MA 02142, United States
| | - John Love
- Biosciences, Faculty of Life and Health Sciences, University of Exeter, Exeter EX4 4QD, UK
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Teng SN, Svenning JC, Xu C. Large mammals and trees in eastern monsoonal China: anthropogenic losses since the Late Pleistocene and restoration prospects in the Anthropocene. Biol Rev Camb Philos Soc 2023; 98:1607-1632. [PMID: 37102332 DOI: 10.1111/brv.12968] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2022] [Revised: 04/16/2023] [Accepted: 04/18/2023] [Indexed: 04/28/2023]
Abstract
Massive human-induced declines of large-sized animals and trees (megabiota) from the Late Pleistocene to the Anthropocene have resulted in downsized ecosystems across the globe, in which components and functions have been greatly simplified. In response, active restoration projects of extant large-sized species or functional substitutes are needed at large scales to promote ecological processes that are important for ecosystem self-regulation and biodiversity maintenance. Despite the desired global scope of such projects, they have received little attention in East Asia. Here, we synthesise the biogeographical and ecological knowledge of megabiota in ancient and modern China, with relevant data mostly located in eastern monsoonal China (EMC), aiming to assess its potential for restoring functionally intact ecosystems modulated by megabiota. We found that during the Late Pleistocene, 12 mammalian megafaunal (carnivores ≥15 kg and herbivores ≥500 kg) species disappeared from EMC: one carnivore Crocuta ultima (East Asian spotted hyena) and 11 herbivores including six megaherbivores (≥1000 kg). The relative importance of climate change and humans in driving these losses remains debated, despite accumulating evidence in favour of the latter. Later massive depletion of megafauna and large-sized (45-500 kg) herbivores has been closely associated with agricultural expansion and societal development, especially during the late Holocene. While forests rich in large timber trees (33 taxa in written records) were common in the region 2000-3000 years ago, millennial-long logging has resulted in considerable range contractions and at least 39 threatened species. The wide distribution of C. ultima, which likely favoured open or semi-open habitats (like extant spotted hyenas), suggests the existence of mosaic open and closed vegetation in the Late Pleistocene across EMC, in line with a few pollen-based vegetation reconstructions and potentially, or at least partially, reflecting herbivory by herbivorous megafauna. The widespread loss of megaherbivores may have strongly compromised seed dispersal for both megafruit (fleshy fruits with widths ≥40 mm) and non-megafruit plant species in EMC, especially in terms of extra-long-distance (>10 km) dispersal, which is critical for plant species that rely on effective biotic agents to track rapid climate change. The former occurrence of large mammals and trees have translated into rich material and non-material heritages passed down across generations. Several reintroduction projects have been implemented or are under consideration, with the case of Elaphurus davidianus a notable success in recovering wild populations in the middle reaches of the Yangtze River, although trophic interactions with native carnivorous megafauna have not yet been restored. Lessons of dealing with human-wildlife conflicts are key to public support for maintaining landscapes shared with megafauna and large herbivores in the human-dominated Anthropocene. Meanwhile, potential human-wildlife conflicts, e.g. public health risks, need to be scientifically informed and effectively reduced. The Chinese government's strong commitment to improved policies of ecological protection and restoration (e.g. ecological redlines and national parks) provides a solid foundation for a scaling-up contribution to the global scope needed for solving the crisis of biotic downsizing and ecosystem degradation.
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Affiliation(s)
- Shuqing N Teng
- School of Life Sciences, Nanjing University, Nanjing, 210023, China
| | - Jens-Christian Svenning
- Center for Ecological Dynamics in a Novel Biosphere (ECONOVO) & Center for Biodiversity Dynamics in a Changing World (BIOCHANGE), Department of Biology, Aarhus University, Aarhus, 8000, Denmark
| | - Chi Xu
- School of Life Sciences, Nanjing University, Nanjing, 210023, China
- Key Laboratory of Restoration and Reconstruction of Degraded Ecosystems in northwestern China of Ministry of Education, Ningxia University, Yinchuan, 750021, China
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Qiu Z, Rao H. Environmental landscape and subsistence strategy of the Shunshanji Culture: A review. FRONTIERS IN PLANT SCIENCE 2022; 13:966635. [PMID: 35937349 PMCID: PMC9355314 DOI: 10.3389/fpls.2022.966635] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/11/2022] [Accepted: 07/04/2022] [Indexed: 06/15/2023]
Abstract
The Shunshanji Culture is the earliest known Neolithic culture in the mid-lower Huai River. In recent years, with new discoveries and deeper studies of the Shunshanji Culture, the concept of the Shunshanji cultural site group has gradually formed. Among them, various types of rice remains have been unearthed in large quantities, which provide key materials for discussing rice farming, rice cultivation and domestication, and related issues in the Huai River Basin. Previous studies have conducted reconstruction of local vegetation landscape and analysis of subsistence strategies on some systematically excavated Shunshanji cultural sites and obtained some new understandings. Integrative research, however, is lacking. In this review, we combine the construction of the local environmental landscape with the settlement landform within the Shunshanji cultural site group and then incorporate it into the regional environmental evolution of the mid-lower Huai River. The consistency and difference in their subsistence were also summarized. In particular, we focus on the relevant clues of the early paddy field cultivation system in the region and perform comparative studies.
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Affiliation(s)
| | - Huiyun Rao
- Key Laboratory of Vertebrate Evolution and Human Origins, Institute of Vertebrate Paleontology and Paleoanthropology, Chinese Academy of Sciences, Beijing, China
- Center for Excellence in Life and Paleoenvironment, Chinese Academy of Sciences, Beijing, China
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