Population genomics identifies genetic structure and admixture in the endangered Beale’s Eyed Turtle (Sacalia bealei), and implications for aquatic ecology and ex situ breeding - Wing-Him Lee; Yik-Hei Sung; Bi Wei Low; Jonathan J. Fong (Marine Life Science & Technology, 2026)
Freshwater turtles are one of the most threatened animal groups in the world, especially in Asia. The Beale’s Eyed Turtle ( Sacalia bealei ) is a highly endangered Chinese species at risk of extinction due to overexploitation for the food and pet trades. Nonetheless, Hong Kong still houses a handful of relatively healthy populations of this species, providing an increasingly rare opportunity to study the population genetics of wild populations and, in turn, guide conservation action. In this study, we used genome-wide double-digest restriction-site associated DNA sequencing (ddRADseq) markers to examine the population structure of S. bealei from all known wild individuals with samples suitable for DNA sequencing, representing a subset of its distribution in Hong Kong (two localities: HK1, HK2) and Fujian Province. Although genetic diversity is relatively low, we recovered four genetic clusters, with three corresponding to each of the three known localities (HK1, HK2, Fujian), and admixture between the clusters. Captive-breeding colony individuals showed mixed geographic origins, with approximately half clustering with Fujian populations and half with Hong Kong populations. These data were used to evaluate the genetic diversity and infer the geographic origin of an ex situ breeding colony with individuals of unknown provenance. These results provide important baseline information on the population structure of wild S. bealei and the potential geographic origins of captive turtles, which directly contribute to in situ and ex situ conservation efforts of the species.

Social dimensions of Managed Aquifer Recharge: A scoping review - Laura Castro-Diaz; Margaret V. du Bray; Melissa Beresford; Cara Jacob; Jelena Jankovic-Rankovic; Jonathan Hallemeier; Aubrey Harris; Glen Low; Daniel Siegel; John Sabo; Amber Wutich (Journal of Environmental Management, 2026)

Linking gut, heart and metabolic health through cholesterol conversion by Akkermansia muciniphila - Negin Kazemian; Ramin Karimianghadim; S. Amirhossein Golzan; Nitin; Jackline D.W. Irungu; Geoff B. Coombs; Jonathan Low; Jonathan P. Little; Wesley F. Zandberg; Frank Halperin; Kirk Bergstrom; Avirup Guha; et al. (Chemical Engineering Journal, 2025)

Opportunities to better integrate inland fish and fisheries in multilateral environmental agreements - Abigail J. Lynch; Devin Bartley; T. Douglas Beard, Jr.; Gabriel Borba; Steven J. Cooke; Ian G. Cowx; Vittoria Elliott; Holly Embke; Edith Gondwe; Zeb Hogan; Jonathan G. Low; Jamie C. Madden; et al. (Environmental Science & Policy, 2025)

Influence assessment by index decomposition analysis, prioritizing design variable for ecodesign - Amos Wei Lun Lee; Yee Shee Tan; Fu Weijia; Wen Feng Lu; Jonathan Sze Choong Low (Sustainable Production and Consumption, 2025)

Ex vivo metabolism kinetics of primary to secondary bile acids via a physiologically relevant human faecal microbiota model - Daniel Zhi Wei Ng; Adrian Low; Amanda Jia Hui Tan; Jia Hui Ong; Wit Thun Kwa; Jonathan Wei Jie Lee; Eric Chun Yong Chan (Chemico-Biological Interactions, 2024)

UM3-LCE3-ISN: a methodology for multi-level life cycle environmental and economic evaluation of industrial symbiosis networks - Piya Kerdlap; Jonathan Sze Choong Low; Daren Zong Loong Tan; Zhiquan Yeo; Seeram Ramakrishna (The International Journal of Life Cycle Assessment, 2024)

How can Transformers and large language models like ChatGPT help LCA practitioners? - Simone Cornago; Seeram Ramakrishna; Jonathan Sze Choong Low (Resources, Conservation and Recycling, 2023)

Cross-modal generative models for multi-modal plastic sorting - Edward R.K. Neo; Jonathan S.C. Low; Vannessa Goodship; Stuart R. Coles; Kurt Debattista (Journal of Cleaner Production, 2023)

Life cycle cost analysis of distributed versus centralized plastic sorting and recycling - Piya Kerdlap; Aloisius Rabata Purnama; Jonathan Sze Choong Low; Daren Zong Loong Tan; Claire Y. Barlow; Seeram Ramakrishna (Journal of Industrial Ecology, 2023)

Deep learning for chemometric analysis of plastic spectral data from infrared and Raman databases - Edward Ren Kai Neo; Jonathan Sze Choong Low; Vannessa Goodship; Kurt Debattista (Resources, Conservation and Recycling, 2023)

Comparing the environmental performance of distributed versus centralized plastic recycling systems: Applying hybrid simulation modeling to life cycle assessment - Piya Kerdlap; Aloisius Rabata Purnama; Jonathan Sze Choong Low; Daren Zong Loong Tan; Claire Y. Barlow; Seeram Ramakrishna (Journal of Industrial Ecology, 2022)

Life cycle environmental and economic assessment of industrial symbiosis networks: a review of the past decade of models and computational methods through a multi-level analysis lens - Piya Kerdlap; Jonathan Sze Choong Low; Seeram Ramakrishna (The International Journal of Life Cycle Assessment, 2020)

Tools for promoting industrial symbiosis: A systematic review - Zhiquan Yeo; Donato Masi; Jonathan Sze Choong Low; Yen Ting Ng; Puay Siew Tan; Stuart Barnes (Journal of Industrial Ecology, 2019)
Industrial symbiosis (IS) employs a cross‐organizational perspective to seek synergistic pairings of one company's waste output to another company's input, enabled by interfirm cooperation through resource and information sharing. Orchestrating IS relationships among companies, however, remains a complex process. In the literature, a wide range of qualitative and quantitative tools have emerged, tackling issues ranging from identifying IS creation opportunities to performance evaluation. Thus far, the available literature has focused on separate aspects and perspective of IS creation. Each individual work contributes, in part, to the overall process of IS creation. The disparate perspectives provided by the literature reflect the fragmented nature of available tools supporting IS, which operate in isolation of each other. An encompassing view of tools supporting the process of IS creation is missing to date. Therefore, to fill this gap, this study aims to develop a more comprehensive description of the landscape of IS tools by analyzing the associated approaches, roles, and contribution of existing tools. Through this understanding, the insights gained can be used to aid future development and advancement of tools for IS practitioners.

Late season pharmaceutical fate in wetland mesocosms with and without phosphorous addition - Pascal Cardinal; Julie C. Anderson; Jules C. Carlson; Jennifer E. Low; Jonathan K. Challis; Charles S. Wong; Mark L. Hanson (Environmental Science and Pollution Research, 2016)

Stakeholders’ perspectives on opportunities and challenges for climate technology facilitation in developing countries: informing the operation of the Climate Technology Centre and Network - Patrick Nussbaumer; Manfredi Caltagirone; Jonathan Duwyn; Heinz Leuenberger; Victor Low; Zitouni Ould-Dada; Mark Radka; Bettina Schreck; Jukka Uosukainen; Rene Van Berkel (Climate and Development, 2016)

Mutant strains of Pichia pastoris with enhanced secretion of recombinant proteins - Sasha Larsen; Jun Weaver; Katherine de Sa Campos; Rhobe Bulahan; Jackson Nguyen; Heather Grove; Amy Huang; Lauren Low; Namphuong Tran; Seth Gomez; Jennifer Yau; Thomas Ilustrisimo; et al. (Biotechnology Letters, 2013)

Life cycle emissions and energy study of biodiesel derived from waste cooking oil and diesel in Singapore - Celia Bee Hong Chua; Hui Mien Lee; Jonathan Sze Choong Low (The International Journal of Life Cycle Assessment, 2010)

Zero tolerance ecology: improving ecological inference by modelling the source of zero observations - Tara G. Martin; Brendan A. Wintle; Jonathan R. Rhodes; Petra M. Kuhnert; Scott A. Field; Samantha J. Low‐Choy; Andrew J. Tyre; Hugh P. Possingham (Ecology Letters, 2005)
A common feature of ecological data sets is their tendency to contain many zero values. Statistical inference based on such data are likely to be inefficient or wrong unless careful thought is given to how these zeros arose and how best to model them. In this paper, we propose a framework for understanding how zero‐inflated data sets originate and deciding how best to model them. We define and classify the different kinds of zeros that occur in ecological data and describe how they arise: either from ‘true zero’ or ‘false zero’ observations. After reviewing recent developments in modelling zero‐inflated data sets, we use practical examples to demonstrate how failing to account for the source of zero inflation can reduce our ability to detect relationships in ecological data and at worst lead to incorrect inference. The adoption of methods that explicitly model the sources of zero observations will sharpen insights and improve the robustness of ecological analyses.

Rhizoeconomics: Carbon costs of phosphorus acquisition - Jonathan P. Lynch; Melissa D. Ho; Low phosphorus (Plant and Soil, 2005)

Cocaine-induced locomotor activity and cocaine discrimination in dopamine D 4 receptor mutant mice - Jonathan L. Katz; Allison L. Chausmer; Gregory I. Elmer; Marcelo Rubinstein; Malcolm J. Low; David K. Grandy (Psychopharmacology, 2003)

Cocaine-induced locomotor activity and cocaine discrimination in dopamine D2 receptor mutant mice - Allison L. Chausmer; Gregory I. Elmer; Marcelo Rubinstein; Malcolm J. Low; David K. Grandy; Jonathan L. Katz (Psychopharmacology, 2002)

Phylogenetic signals from point mutations and polymorphic Alu - Daniel S. York; Vincent M. Blum; Jonathan A. Low; Diane J. Rowold; Valery Puzyrev; Victor Saliukov; Olga Odinokova; Rene J. Herrera (Genetica, 1999)