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Vollert SA, Drovandi C, Adams MP. Unlocking ensemble ecosystem modelling for large and complex networks. PLoS Comput Biol 2024; 20:e1011976. [PMID: 38483981 DOI: 10.1371/journal.pcbi.1011976] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 03/26/2024] [Accepted: 03/07/2024] [Indexed: 03/27/2024] Open
Abstract
The potential effects of conservation actions on threatened species can be predicted using ensemble ecosystem models by forecasting populations with and without intervention. These model ensembles commonly assume stable coexistence of species in the absence of available data. However, existing ensemble-generation methods become computationally inefficient as the size of the ecosystem network increases, preventing larger networks from being studied. We present a novel sequential Monte Carlo sampling approach for ensemble generation that is orders of magnitude faster than existing approaches. We demonstrate that the methods produce equivalent parameter inferences, model predictions, and tightly constrained parameter combinations using a novel sensitivity analysis method. For one case study, we demonstrate a speed-up from 108 days to 6 hours, while maintaining equivalent ensembles. Additionally, we demonstrate how to identify the parameter combinations that strongly drive feasibility and stability, drawing ecological insight from the ensembles. Now, for the first time, larger and more realistic networks can be practically simulated and analysed.
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Affiliation(s)
- Sarah A Vollert
- Centre for Data Science, Queensland University of Technology, Brisbane, Queensland, Australia
- School of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Christopher Drovandi
- Centre for Data Science, Queensland University of Technology, Brisbane, Queensland, Australia
- School of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Matthew P Adams
- Centre for Data Science, Queensland University of Technology, Brisbane, Queensland, Australia
- School of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia
- School of Chemical Engineering, The University of Queensland, St Lucia, Australia
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2
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A Taxonomy-Agnostic Approach to Targeted Microbiome Therapeutics-Leveraging Principles of Systems Biology. Pathogens 2023; 12:pathogens12020238. [PMID: 36839510 PMCID: PMC9959781 DOI: 10.3390/pathogens12020238] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Revised: 01/18/2023] [Accepted: 01/31/2023] [Indexed: 02/05/2023] Open
Abstract
The study of human microbiomes has yielded insights into basic science, and applied therapeutics are emerging. However, conflicting definitions of what microbiomes are and how they affect the health of the "host" are less understood. A major impediment towards systematic design, discovery, and implementation of targeted microbiome therapeutics is the continued reliance on taxonomic indicators to define microbiomes in health and disease. Such reliance often confounds analyses, potentially suggesting associations where there are none, and conversely failing to identify significant, causal relationships. This review article discusses recent discoveries pointing towards a molecular understanding of microbiome "dysbiosis" and away from a purely taxonomic approach. We highlight the growing role of systems biological principles in the complex interrelationships between the gut microbiome and host cells, and review current approaches commonly used in targeted microbiome therapeutics, including fecal microbial transplant, bacteriophage therapies, and the use of metabolic toxins to selectively eliminate specific taxa from dysbiotic microbiomes. These approaches, however, remain wholly or partially dependent on the bacterial taxa involved in dysbiosis, and therefore may not capitalize fully on many therapeutic opportunities presented at the bioactive molecular level. New technologies capable of addressing microbiome-associated diseases as molecular problems, if solved, will open possibilities of new classes and categories of targeted microbiome therapeutics aimed, in principle, at all dysbiosis-driven disorders.
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Nilson SM, Gandolfi B, Grahn RA, Kurushima JD, Lipinski MJ, Randi E, Waly NE, Driscoll C, Murua Escobar H, Schuster RK, Maruyama S, Labarthe N, Chomel BB, Ghosh SK, Ozpinar H, Rah HC, Millán J, Mendes-de-Almeida F, Levy JK, Heitz E, Scherk MA, Alves PC, Decker JE, Lyons LA. Genetics of randomly bred cats support the cradle of cat domestication being in the Near East. Heredity (Edinb) 2022; 129:346-355. [PMID: 36319737 PMCID: PMC9708682 DOI: 10.1038/s41437-022-00568-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Revised: 09/29/2022] [Accepted: 09/30/2022] [Indexed: 11/04/2022] Open
Abstract
Cat domestication likely initiated as a symbiotic relationship between wildcats (Felis silvestris subspecies) and the peoples of developing agrarian societies in the Fertile Crescent. As humans transitioned from hunter-gatherers to farmers ~12,000 years ago, bold wildcats likely capitalized on increased prey density (i.e., rodents). Humans benefited from the cats' predation on these vermin. To refine the site(s) of cat domestication, over 1000 random-bred cats of primarily Eurasian descent were genotyped for single-nucleotide variants and short tandem repeats. The overall cat population structure suggested a single worldwide population with significant isolation by the distance of peripheral subpopulations. The cat population heterozygosity decreased as genetic distance from the proposed cat progenitor's (F.s. lybica) natural habitat increased. Domestic cat origins are focused in the eastern Mediterranean Basin, spreading to nearby islands, and southernly via the Levantine coast into the Nile Valley. Cat population diversity supports the migration patterns of humans and other symbiotic species.
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Affiliation(s)
- Sara M Nilson
- Division of Animal Sciences, University of Missouri, Columbia, MO, 65211, USA
| | - Barbara Gandolfi
- Department of Population Health and Reproduction, School of Veterinary Medicine, University of California, Davis, CA, 95616, USA
| | - Robert A Grahn
- Department of Population Health and Reproduction, School of Veterinary Medicine, University of California, Davis, CA, 95616, USA
| | - Jennifer D Kurushima
- Department of Population Health and Reproduction, School of Veterinary Medicine, University of California, Davis, CA, 95616, USA
| | - Monika J Lipinski
- Department of Population Health and Reproduction, School of Veterinary Medicine, University of California, Davis, CA, 95616, USA
| | - Ettore Randi
- Department of Chemistry and Bioscience, Aalborg University, Fredrik Bajers Vej 7H, 9220, Aalborg Øst, Denmark
| | - Nashwa E Waly
- Department of Animal Medicine, Faculty of Veterinary Medicine, Assuit University, 71526, Assiut, Egypt
| | | | - Hugo Murua Escobar
- Clinic for Hematology, Oncology and Palliative Care, University Medical Center Rostock, 18055, Rostock, Germany
| | - Rolf K Schuster
- Central Veterinary Research Laboratory, Dubai, United Arab Emirates
| | - Soichi Maruyama
- Laboratory of Veterinary Public Health, Nihon University, 1866 Kameino, Fujisawa, Kanagawa, 252-0880, Japan
| | - Norma Labarthe
- Programa de Bioética, Ética Aplicada e Saúde Coletiva, Fundação Oswaldo Cruz, Rio de Janeiro, RJ, 21040-360, Brazil
- Programa de Pós-Graduação em Medicina Veterinária - Clínica e Reprodução Animal, Faculdade de Veterinária, Universidade Federal Fluminense, Rua Vital Brazil Filho 64, Niterói, RJ, 24230-340, Brazil
| | - Bruno B Chomel
- Department of Population Health and Reproduction, School of Veterinary Medicine, University of California, Davis, CA, 95616, USA
| | | | - Haydar Ozpinar
- Graduate School of Health Sciences, Istanbul Gedik University, 34876, İstanbul, Turkey
| | - Hyung-Chul Rah
- Research Institute of Veterinary Medicine, College of Veterinary Medicine, Chungbuk National University, Cheongju, 28644, South Korea
| | - Javier Millán
- Instituto Agroalimentario de Aragón-IA2 (Universidad de Zaragoza-CITA), Miguel Servet 177, 50013, Zaragoza, Spain
- Fundación ARAID, Avda. de Ranillas, 50018, Zaragoza, Spain
- Facultad de Ciencias de la Vida, Universidad Andres Bello, Santiago, Chile
| | - Flavya Mendes-de-Almeida
- Programa de Pós-Graduação em Medicina Veterinária - Clínica e Reprodução Animal, Faculdade de Veterinária, Universidade Federal Fluminense, Rua Vital Brazil Filho 64, Niterói, RJ, 24230-340, Brazil
| | - Julie K Levy
- Maddie's Shelter Medicine Program, College of Veterinary Medicine, University of Florida, Gainesville, FL, 32608, USA
| | | | | | - Paulo C Alves
- CIBIO/InBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos/InBIO Associate Lab & Faculdade de Ciências, Universidade do Porto, Campus e Vairão, 4485-661, Vila do Conde, Portugal
- Wildlife Biology Program, University of Montana, Missoula, MT, 59812, USA
| | - Jared E Decker
- Division of Animal Sciences, University of Missouri, Columbia, MO, 65211, USA.
- Institute for Data Science and Informatics, University of Missouri, Columbia, MO, 65211, USA.
| | - Leslie A Lyons
- Department of Population Health and Reproduction, School of Veterinary Medicine, University of California, Davis, CA, 95616, USA.
- Department of Veterinary Medicine & Surgery, College of Veterinary Medicine, University of Missouri, Columbia, MO, 65211, USA.
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Clark‐Wolf TJ, Hahn PG, Brelsford E, Francois J, Hayes N, Larkin B, Ramsey P, Pearson DE. Preventing a series of unfortunate events: using qualitative models to improve conservation. J Appl Ecol 2022. [DOI: 10.1111/1365-2664.14231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Affiliation(s)
- T. J. Clark‐Wolf
- Wildlife Biology Program, Department of Ecosystem and Conservation Sciences, W.A. Franke College of Forestry and Conservation University of Montana Missoula, MT 59812 USA
- Current Address: Center for Ecosystem Sentinels, Department of Biology University of Washington Seattle, WA 98195 USA
| | - Philip G. Hahn
- Department of Entomology and Nematology University of Florida Gainesville, FL 32608 USA
| | - Eric Brelsford
- Stamen, 2017 Mission St Suite 300 San Francisco, CA 94110 USA
| | - Jaleen Francois
- Stamen, 2017 Mission St Suite 300 San Francisco, CA 94110 USA
| | - Nicolette Hayes
- Stamen, 2017 Mission St Suite 300 San Francisco, CA 94110 USA
| | - Beau Larkin
- MPG Ranch, 19400 Lower Woodchuck Road Florence, MT 59833 USA
| | - Philip Ramsey
- MPG Ranch, 19400 Lower Woodchuck Road Florence, MT 59833 USA
| | - Dean E. Pearson
- Rocky Mountain Research Station, U.S. Department of Agriculture Forest Service Missoula, MT 59801 USA
- Division of Biological Sciences University of Montana Missoula, MT 59812 USA
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Plein M, O'Brien KR, Holden MH, Adams MP, Baker CM, Bean NG, Sisson SA, Bode M, Mengersen KL, McDonald‐Madden E. Modeling total predation to avoid perverse outcomes from cat control in a data-poor island ecosystem. CONSERVATION BIOLOGY : THE JOURNAL OF THE SOCIETY FOR CONSERVATION BIOLOGY 2022; 36:e13916. [PMID: 35352431 PMCID: PMC9804458 DOI: 10.1111/cobi.13916] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Revised: 12/22/2021] [Accepted: 03/21/2022] [Indexed: 06/14/2023]
Abstract
Data hungry, complex ecosystem models are often used to predict the consequences of threatened species management, including perverse outcomes. Unfortunately, this approach is impractical in many systems, which have insufficient data to parameterize ecosystem interactions or reliably calibrate or validate such models. Here we demonstrate a different approach, using a minimum realistic model to guide decisions in data- and resource-scarce systems. We illustrate our approach with a case-study in an invaded ecosystem from Christmas Island, Australia, where there are concerns that cat eradication to protect native species, including the red-tailed tropicbird, could release meso-predation by invasive rats. We use biophysical constraints (metabolic demand) and observable parameters (e.g. prey preferences) to assess the combined cat and rat abundances which would threaten the tropicbird population. We find that the population of tropicbirds cannot be sustained if predated by 1607 rats (95% credible interval (CI) [103, 5910]) in the absence of cats, or 21 cats (95% CI [2, 82]) in the absence of rats. For every cat removed from the island, the bird's net population growth rate improves, provided that the rats do not increase by more than 77 individuals (95% CI [30, 174]). Thus, in this context, one cat is equivalent to 30-174 rats. Our methods are especially useful for on-the-ground predator control in the absence of knowledge of predator-predator interactions, to assess whether 1) the current abundance of predators threatens the prey population of interest, 2) managing one predator species alone is sufficient to protect the prey species given potential release of another predator, and 3) control of multiple predator species is needed to meet the conservation goal. Our approach demonstrates how to use limited information for maximum value in data-poor systems, by shifting the focus from predicting future trajectories, to identifying conditions which threaten the conservation goal. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Michaela Plein
- School of Earth and Environmental ScienceUniversity of QueenslandSt LuciaQueenslandAustralia
- Centre for Biodiversity and Conservation ScienceUniversity of QueenslandSt LuciaQueenslandAustralia
- Administration de la nature et des forêtsDiekirchLuxembourg
| | - Katherine R. O'Brien
- School of Chemical EngineeringUniversity of QueenslandSt LuciaQueenslandAustralia
| | - Matthew H. Holden
- Centre for Biodiversity and Conservation ScienceUniversity of QueenslandSt LuciaQueenslandAustralia
- School of Biological SciencesUniversity of QueenslandBrisbaneQueenslandAustralia
- School of Mathematics and PhysicsUniversity of QueenslandBrisbaneQueenslandAustralia
| | - Matthew P. Adams
- School of Earth and Environmental ScienceUniversity of QueenslandSt LuciaQueenslandAustralia
- Centre for Biodiversity and Conservation ScienceUniversity of QueenslandSt LuciaQueenslandAustralia
- School of Chemical EngineeringUniversity of QueenslandSt LuciaQueenslandAustralia
- School of Mathematical SciencesQueensland University of TechnologyBrisbaneQueenslandAustralia
- ARC Centre of Excellence for Mathematical and Statistical FrontiersQueensland University of, TechnologyBrisbaneQueenslandAustralia
| | - Christopher M. Baker
- School of Mathematics and StatisticsThe University of MelbourneParkvilleVictoriaAustralia
- Melbourne Centre for Data ScienceThe University of MelbourneParkvilleVictoriaAustralia
- Centre of Excellence for Biosecurity Risk AnalysisThe University of MelbourneMelbourneVictoriaAustralia
| | - Nigel G. Bean
- School of Mathematical SciencesUniversity of AdelaideAdelaideSouth AustraliaAustralia
- Australian Research Council Centre of Excellence for Mathematical and Statistical FrontiersUniversity of AdelaideAdelaideSouth AustraliaAustralia
| | - Scott A. Sisson
- School of Mathematics and StatisticsUniversity of New South WalesSydneyNew South WalesAustralia
- UNSW Data Science HubUniversity of New SouthWales, SydneyNew South WalesAustralia
| | - Michael Bode
- School of Mathematical SciencesQueensland University of TechnologyBrisbaneQueenslandAustralia
| | - Kerrie L. Mengersen
- School of Mathematical SciencesQueensland University of TechnologyBrisbaneQueenslandAustralia
- ARC Centre of Excellence for Mathematical and Statistical FrontiersQueensland University of, TechnologyBrisbaneQueenslandAustralia
| | - Eve McDonald‐Madden
- School of Earth and Environmental ScienceUniversity of QueenslandSt LuciaQueenslandAustralia
- Centre for Biodiversity and Conservation ScienceUniversity of QueenslandSt LuciaQueenslandAustralia
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Hurley KF, Levy JK. Rethinking the Animal Shelter's Role in Free-Roaming Cat Management. Front Vet Sci 2022; 9:847081. [PMID: 35372561 PMCID: PMC8964341 DOI: 10.3389/fvets.2022.847081] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2022] [Accepted: 02/04/2022] [Indexed: 01/11/2023] Open
Abstract
Substantial societal investment is made in the management of free-roaming cats by various methods, with goals of such programs commonly including wildlife conservation, public health protection, nuisance abatement, and/or promotion of cat health and welfare. While there has been a degree of controversy over some of the tactics employed, there is widespread agreement that any method must be scientifically based and sufficiently focused, intensive and sustained in order to succeed. The vast majority of free-roaming cat management in communities takes place through local animal shelters. Throughout the 20th century and into the 21st, this consisted primarily of ad hoc admission of cats captured by members of the public, with euthanasia being the most common outcome. In North America alone, hundreds of millions of cats have been impounded and euthanized and billions of dollars invested in such programs. Given the reliance on this model to achieve important societal goals, it is surprising that there has been an almost complete lack of published research evaluating its success. Wildlife conservation and public health protection will be better served when debate about the merits and pitfalls of methods such as Trap-Neuter-Return is grounded in the context of realistically achievable alternatives. Where no perfect answer exists, an understanding of the potential strengths and shortcomings of each available strategy will support the greatest possible mitigation of harm—the best, if still imperfect, solution. Animal shelter function will also benefit by discontinuing investment in methods that are ineffective as well as potentially ethically problematic. This will allow the redirection of resources to more promising strategies for management of cats as well as investment in other important animal shelter functions. To this end, this article reviews evidence regarding the potential effectiveness of the three possible shelter-based strategies for free-roaming cat management: the traditional approach of ad hoc removal by admission to the shelter; admission to the shelter followed by sterilization and return to the location found; and leaving cats in place with or without referral to mitigation strategies or services provided by other agencies.
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Affiliation(s)
- Kate F. Hurley
- Koret Shelter Medicine Program, School of Veterinary Medicine, University of California – Davis, Davis, CA, United States
- *Correspondence: Kate F. Hurley
| | - Julie K. Levy
- Maddie's Shelter Medicine Program, College of Veterinary Medicine, University of Florida, Gainesville, FL, United States
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