Article
Biochemistry & Molecular Biology
Cesar A. Fortes-Lima, Romain Laurent, Valentin Thouzeau, Bruno Toupance, Paul Verdu
Summary: Admixture is a fundamental evolutionary process that has influenced genetic patterns in numerous species. Maximum-likelihood approaches have limitations in reconstructing complex admixture histories, leading to the development of an Approximate Bayesian Computation (ABC) framework that integrates machine-learning algorithms to investigate admixture history accurately. The study showed that random forest ABC scenario-choice accurately distinguished complex admixture scenarios, while neural network ABC posterior parameter estimation was accurate and conservative under complex admixture scenarios. This approach provides a promising method for reconstructing detailed admixture histories in populations with multiple admixture pulses.
MOLECULAR ECOLOGY RESOURCES
(2021)
Article
Computer Science, Artificial Intelligence
Jinhee Park, Junseok Kwon
Summary: In this study, novel visual tracking methods based on the Wasserstein approximate Bayesian computation (ABC) are presented. The proposed methods, including Wasserstein ABC (WABC), time-series WABC (TWABC), and Hilbert TWABC (HTWABC), improve the accuracy and efficiency of visual tracking by approximating likelihood distributions and encoding temporal dependencies. Experimental results demonstrate the superiority of the proposed methods, and ablation studies confirm the effectiveness of individual components.
PATTERN RECOGNITION
(2022)
Article
Biochemistry & Molecular Biology
Asher Moshe, Elya Wygoda, Noa Ecker, Gil Loewenthal, Oren Avram, Omer Israeli, Einat Hazkani-Covo, Itsik Pe'er, Tal Pupko
Summary: This study developed a probabilistic approach to infer genome rearrangement rate parameters and used an Approximate Bayesian Computation framework for inference. The method can help elucidate the role of genome rearrangement in evolution and simulate genomes with empirical dynamics.
MOLECULAR BIOLOGY AND EVOLUTION
(2022)
Article
Engineering, Industrial
Manuel Chiachio, Ali Saleh, Susannah Naybour, Juan Chiachio, John Andrews
Summary: This paper presents a probabilistic method for accurately defining the structure and parameters of a reduced Petri net model, enabling accurate modeling of engineering systems and processes. The method allows for numerical measurement and selection of the optimal simplified structure.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2022)
Article
Engineering, Civil
Pinghe Ni, Qiang Han, Xiuli Du, Xiaowei Cheng, Hongyuan Zhou
Summary: This paper presents a data-driven approach for post-earthquake reliability assessments of civil structures. It updates the probability density functions of random variables using measured vibration data, and generates the posterior probability density functions of structural parameters using two approximate Bayesian computation techniques. The updated probability density functions are then used for reliability assessments, and numerical studies verify the accuracy and efficiency of the proposed techniques.
ENGINEERING STRUCTURES
(2022)
Article
Computer Science, Interdisciplinary Applications
Clara Grazian, Luciana Dalla Valle, Brunero Liseo
Summary: Copula models are flexible tools for representing complex dependence structures of multivariate random variables. However, incorporating covariates in these models is challenging due to the lack of unbiased estimators of the conditional copula and the difficulty in selecting the appropriate copula model.
COMPUTATIONAL STATISTICS & DATA ANALYSIS
(2022)
Article
Environmental Sciences
Ludwig Triest, Alieza Del Socorro, Vincent Jay Gado, Analyn M. Mazo, Tim Sierens
Summary: This study focused on the fine-scale spatial genetic structure (FSGS) of Avicennia populations in the Philippines. It found that the proximity to open water and the narrowness of mangrove patches may affect their genetic diversity and structure. Coastal connectivity plays an important role in the long-term persistence of mangrove populations.
FRONTIERS IN MARINE SCIENCE
(2021)
Article
Automation & Control Systems
Yuexi Wang, Tetsuya Kaji, Veronika Rockova
Summary: Approximate Bayesian Computation (ABC) is a method that enables statistical inference in simulator-based models with difficult likelihood calculations but easy simulation. This study constructs a kernel-type approximation of the posterior distribution in ABC by comparing summary statistics of real and simulated data, and uses contrastive learning to directly compare empirical distributions. The research demonstrates the usefulness of this approach in simulated examples and real data analysis in the context of stock volatility estimation.
JOURNAL OF MACHINE LEARNING RESEARCH
(2022)
Article
Plant Sciences
Ichiro Tamaki, Tomohiro Obora, Takafumi Ohsawa, Asako Matsumoto, Yoko Saito, Yuji Ide
Summary: The study showed distinct genetic structures in three oak species but with genetic admixture, especially between QM and QC. The population size of QM remained stable during the last glacial period, while QC and QS expanded. Continuous gene flow between QM and QC was supported, indicating they are in the early stage of speciation, while secondary contact after isolation was supported between QM and QS, and between QC and QS.
JOURNAL OF PLANT RESEARCH
(2021)
Article
Computer Science, Interdisciplinary Applications
Bach Do, Makoto Ohsaki
Summary: This study presents Bayesian optimization-assisted approximate Bayesian computation (BO-assisted ABC) and showcases its application to identifying the approximate posteriors of parameters for known statistical models and of cyclic elastoplastic parameters for structural steels. ABC bypasses likelihood evaluations by generating prior samples that are assigned as samples constituting the posterior if discrepancies between the experimental dataset and the corresponding simulated datasets do not exceed a small, positive threshold. With a modest number of costly simulations, BO facilitates ABC by intelligently constructing a Gaussian process model that approximates the discrepancy mean function.
COMPUTERS & STRUCTURES
(2023)
Article
Ecology
Charlotte Baey, Henrik G. Smith, Maj Rundlof, Ola Olsson, Yann Clough, Ullrika Sahlin
Summary: In this study, alternative strategies for handling high-dimensional data in ABC calibration were investigated. Regression adjustment and machine learning approaches were compared in terms of model estimate coverage and true parameter values. The results showed that random forest-based approaches performed better, and nonlinear regression adjustment outperformed linear ones.
ECOLOGICAL MODELLING
(2023)
Article
Engineering, Mechanical
Joao Pedro Valeriano, Pedro Henrique Cintra, Gustavo Libotte, Igor Reis, Felipe Fontinele, Renato Silva, Sandra Malta
Summary: The long duration of COVID-19 pandemic has led to multiple bursts in infection and death rates, known as epidemic waves. Traditional compartmental models are no longer effective, necessitating more sophisticated mathematical techniques for analyzing epidemic data and making reliable forecasts. In this study, a framework is proposed for analyzing complex dynamical systems by dividing the data into consecutive time-windows for separate analysis. Parameters are estimated for each window using an approximate Bayesian computation (ABC) algorithm, with the posterior distribution from one window serving as the prior distribution for the next. The Bayesian learning approach is tested using COVID-19 case data from various countries, showing improved ABC performance and producing accurate short-term forecasts.
NONLINEAR DYNAMICS
(2023)
Article
Physics, Multidisciplinary
Ilze A. Auzina, Jakub M. Tomczak
Summary: The study aims to address the lack of an optimal Approximate Bayesian Computation method for discrete random variables. The researchers propose an adjusted population-based MCMC ABC method and introduce a novel Markov kernel inspired by differential evolution to redefine ABC parameters as discrete ones. The results indicate the high potential of the proposed framework and the superiority of the new Markov kernel.
Article
Engineering, Civil
Zijie Zeng, Min Gao, Ching Tai Ng, Abdul Hamid Sheikh
Summary: This paper presents a probabilistic framework using ultrasonic guided waves to detect and identify early-state cracks in pipe-like structures. The framework quantifies the values and uncertainties of crack location, crack sizes, and Young's modulus through a Bayesian approach. The proposed framework utilizes an approximate Bayesian computation algorithm to estimate the posterior distributions of unknown parameters. The accuracy and practicability of the framework are validated through numerical and experimental case studies. Evaluation: 9/10
THIN-WALLED STRUCTURES
(2023)
Article
Ecology
Valerie Le Corre, Carole Reibel, Vaya Kati, Stephanie Gibot-Leclerc
Summary: This study aimed to investigate the evolutionary relationships and genetic differentiation among populations of the parasitic weed Phelipanche ramosa infesting different host crops. The study found high genetic differentiation among populations, mainly driven by differentiation among different host crops, with no significant geographic structure. The analysis also identified seven biologically meaningful clusters matched with host crops of origin.
ECOLOGY AND EVOLUTION
(2023)
Article
Marine & Freshwater Biology
Isabella M. Reeves, John A. Totterdell, Andrea Barcelo, Jonathan Sandoval-Castillo, Kimberley C. Batley, Karen A. Stockin, Emma L. Betty, David M. Donnelly, Rebecca Wellard, Luciano B. Beheregaray, Luciana M. Moller
Summary: Population genomics data has been used to assess the population structure of Australasian killer whales, revealing at least three populations: New Zealand, NWA, and SWA. These populations exhibit moderate levels of genetic diversity, small effective population sizes, and low contemporary migration rates. Mitochondrial DNA analysis suggests the existence of matrilineal societies among killer whales in the region.
MARINE MAMMAL SCIENCE
(2022)
Article
Ecology
Catherine R. M. Attard, Jonathan Sandoval-Castillo, Chris J. Brauer, Peter J. Unmack, David Schmarr, Louis Bernatchez, Luciano B. Beheregaray
Summary: This study investigates the persistence of adaptive variation in small populations of desert rainbowfish through population genomic diversity analysis and satellite-derived surface water data integration. The findings suggest that positive selection in refugial subpopulations combined with connectivity during flood periods can enable retention of adaptive diversity, allowing the species to persist in the desert environment.
Article
Biochemistry & Molecular Biology
Eleanor A. L. Pratt, Luciano B. Beheregaray, Kerstin Bilgmann, Nikki Zanardo, Fernando Diaz-Aguirre, Chris Brauer, Jonathan Sandoval-Castillo, Luciana M. Moller
Summary: This study conducted a seascape genomic study on Indo-Pacific bottlenose dolphins and found that heterogeneous seascapes and strong environmental gradients influenced adaptive divergence in these animals. The research revealed that sea surface temperature and salinity gradients played a significant role in their adaptive divergence.
Article
Ecology
Emily J. Booth, Jonathan Sandoval-Castillo, Catherine R. M. Attard, Dean M. Gilligan, Peter J. Unmack, Luciano B. Beheregaray
Summary: This study reveals the role of aridification in driving the divergence of a migratory freshwater species in Australia during the late Pleistocene. The findings are important for informing the conservation management of aquatic organisms under climate change.
JOURNAL OF BIOGEOGRAPHY
(2022)
Article
Ecology
Abbie C. Hay, Jonathan Sandoval-Castillo, Georgina M. Cooke, Ning L. Chao, Luciano B. Beheregaray
Summary: This study examines the role of natural selection in the evolutionary divergence of the Amazonian characin fish. The results suggest that variation in turbidity and pH contribute to adaptive divergence, and genes involved in acid-sensitive ion transport pathways and light-sensitive photoreceptor pathways are associated with this variation.
FRONTIERS IN ECOLOGY AND EVOLUTION
(2022)
Article
Evolutionary Biology
Andrea Bertram, David Fairclough, Jonathan Sandoval-Castillo, Chris Brauer, Anthony Fowler, Maren Wellenreuther, Luciano B. Beheregaray
Summary: The efficacy of fisheries management strategies depends on carrying out stock assessment and management actions at appropriate spatial scales. This study investigated the population genomics of a heavily exploited snapper species along the Australian coastline to understand population structure, connectivity, and the compatibility of current management practices. The results revealed low genetic differentiation and high connectivity across Western Australia, but also identified genetic discontinuities in certain regions, suggesting a need for a review of current spatial management.
EVOLUTIONARY APPLICATIONS
(2022)
Article
Environmental Sciences
Chris J. Brauer, Jonathan Sandoval-Castillo, Katie Gates, Michael P. Hammer, Peter J. Unmack, Louis Bernatchez, Luciano B. Beheregaray
Summary: Under climate change, species without the ability to shift their range rely on genetic variation for adaptation. Genomic vulnerability studies often overlook hybridization as a source of adaptive variation. This study found that hybrid populations of rainbowfish showed reduced vulnerability to climate change compared to pure narrow endemics, highlighting the importance of hybrid populations and adaptive introgression in the evolutionary rescue of species with narrow environmental ranges.
NATURE CLIMATE CHANGE
(2023)
Editorial Material
Geosciences, Multidisciplinary
R. P. Bourman, C. V. Murray-Wallace, C. Wilson, L. Mosley, J. Tibby, D. D. Ryan, E. D. De Carli, A. Tulley, A. P. Belperio, D. Haynes, A. Roberts, C. Westell, E. J. Barnett, S. Dillenburg, L. B. Beheregaray, P. A. Hesp
AUSTRALIAN JOURNAL OF EARTH SCIENCES
(2023)
Article
Ecology
Katie Gates, Jonathan Sandoval-Castillo, Chris J. Brauer, Peter J. Unmack, Martin Laporte, Louis Bernatchez, Luciano B. Beheregaray
Summary: In order to preserve the diversity of ecological and genetic factors in hotspots like tropical rainforests, it is important to understand the forces behind biodiversity. Through studying an Australian rainbowfish, Melanotaenia splendida splendida, across wet tropical regions, we found that environmental gradients and terrain structure strongly influence genetic and morphological variation. While neutral genetic population structure is mostly affected by limited gene flow, ecological variables are equally effective in explaining overall genetic variation and better at explaining body shape variation. The strongest environmental predictors are hydrological and thermal variables, which are correlated with heritable habitat-associated dimorphism in rainbowfish. Climate-associated genetic variation is significantly associated with morphology, supporting the heritability of shape variation. These results highlight the evolved functional differences among localities and emphasize the importance of hydroclimate in early stages of diversification. It is expected that tropical rainforest endemics will need to undergo significant evolutionary responses to mitigate fitness losses caused by climate change.
Article
Fisheries
A. Bertram, J. Bell, C. J. Brauer, A. Fowler, P. Hamer, J. Sandoval-Castillo, J. Stewart, M. Wellenreuther, L. B. Beheregaray
Summary: In southeastern Australia, population genomic differentiation in snapper is concordant with coastal biogeographic boundaries and related to spawning and recruitment dynamics. The current management boundaries align with genetic breaks at bioregional boundaries or local-scale variation. This study highlights the value of population genomic surveys in uncovering stock boundaries and demographic variation related to spawning and recruitment in species with high dispersal potential, and emphasizes the importance of marine biogeography in shaping population structure in commercially important species.
ICES JOURNAL OF MARINE SCIENCE
(2023)
Article
Environmental Sciences
Karl Moy, Jason Schaffer, Michael P. Hammer, Catherine R. M. Attard, Luciano B. Beheregaray, Richard Duncan, Mark Lintermans, Culum Brown, Peter J. Unmack
Summary: The study explores the threat of translocating species on freshwater fish biodiversity and presents a successful case of conserving Running River rainbowfish. By captive-breeding wild fish and translocating them to unoccupied habitats, two populations of Running River rainbowfish were established, but challenges of predation and release timing remain. This provides valuable insights for similar conservation programs involving short-lived fish species.
AQUATIC CONSERVATION-MARINE AND FRESHWATER ECOSYSTEMS
(2023)
Article
Environmental Sciences
Paula M. de Coito, Arsalan Emami-Khoyi, Terry A. Hedderson, Robert J. Toonen, Peter R. Teske, George M. Branch
Summary: Seagrass habitats are declining globally, endangering seagrass-associated animals such as the Critically Endangered limpet Siphonaria compressa. This rare mollusk is found in only two separate lagoons in South Africa and relies on a specific seagrass species for survival. Genetic and morphological analysis revealed that the two populations are distinct subspecies and therefore translocation between them is not recommended as it may worsen the risk of extinction. Conservation measures for each population, such as seagrass bed protection and restoration, should be implemented instead.
AQUATIC CONSERVATION-MARINE AND FRESHWATER ECOSYSTEMS
(2023)
Article
Ecology
Arsalan Emami-Khoyi, Candice M. Jooste, Ryan J. Wasserman, Tatenda Dalu, Morgan J. J. Raath-Kruger, Bettine Jansen van Vuuren, Peter R. Teske
Summary: This study investigated the spatial genetic structure and dispersal history of a calanoid copepod species in temporary wetlands in the Eastern Cape province of South Africa. The wetland populations were highly structured across the landscape and potentially represent cryptic speciation. The dispersal history of these populations was affected by a postulated barrier, which eventually disappeared, allowing the species to spread into coastal regions.
FRESHWATER BIOLOGY
(2023)
Article
Evolutionary Biology
Eleanor A. L. Pratt, Luciano B. Beheregaray, Pedro Fruet, Gabriela Tezanos-Pinto, Kerstin Bilgmann, Nikki Zanardo, Fernando Diaz-Aguirre, Eduardo R. Secchi, Thales R. O. Freitas, Luciana M. Moller
Summary: Climate change has led to major environmental restructuring in the world's oceans, and marine organisms have responded through genomic adaptation. This study investigates the genomic basis of ecotype formation in bottlenose dolphins in the Southern Hemisphere, revealing subspecies-level genomic divergence and lower genomic diversity in inshore lineages. Genomic regions associated with cardiovascular, musculoskeletal, and energy production systems have undergone repeated adaptive evolution in these lineages, suggesting parallel evolution of inshore bottlenose dolphins. Understanding the adaptive capacity of local species and populations is crucial amidst changing marine ecosystems.
GENOME BIOLOGY AND EVOLUTION
(2023)
Article
Ecology
Andrea Barcelo, Jonathan Sandoval-Castillo, Chris J. Brauer, Kerstin Bilgmann, Guido J. Parra, Luciano B. Beheregaray, Luciana M. Moller
Summary: This study conducted a seascape genomics analysis on 214 common dolphins along the southern coast of Australia, and identified five locally-adapted populations with high levels of genomic variation. The study revealed key environmental variables associated with the genomic variation, and suggested that adaptive divergence in common dolphins is related to important metabolic traits.
BMC ECOLOGY AND EVOLUTION
(2022)