Reju Sam John

University of Auckland

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David T. S. Hayman

Massey University

Renata L. Muylaert

Massey University

Jonathan C. Marshall

Massey University

Wantida Horpiencharoen

Massey University

Tigga Kingston

Texas Tech University

Surajit Paul

Manipal Academy of Higher Education

Maria Cristina Rulli

Politecnico di Milano

Nikolas Galli

Politecnico di Milano

Prateek Gupta

Savitribai Phule Pune University

David A. Wilkinson

Inserm

Cooperative Institutions

Massey University

King Mongkut's University of Technology Thonburi

University of California, Berkeley

Pondicherry University

Centre National de la Recherche Scientifique

International Union for Conservation of Nature (Bangladesh)

University of Würzburg

University of Oxford

Savitribai Phule Pune University

Universidade de São Paulo

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Mapping threatened Thai bovids provides opportunities for improved conservation outcomes in Asia

Royal Society Open Science (2024)

Wantida Horpiencharoen Renata L. Muylaert Jonathan C. Marshall Reju Sam John Antony J. Lynam

Wild bovids provide important ecosystem functions as seed dispersers and vegetation modifiers. Five wild bovids remain in Thailand: gaur ( Bos gaurus ), banteng ( Bos javanicus ), wild water buffalo ( Bubalus arnee ), mainland serow ( Capricornis sumatraensis ) and Chinese goral ( Naemorhedus griseus ). Their populations and habitats have declined substantially and become fragmented by land-use change. We use ecological niche models to quantify how much potential suitable habitat for these species remains within protected areas in Asia and then specifically Thailand. We combined species occurrence data from several sources (e.g. mainly camera traps and direct observation) with environmental variables and species-specific and single, large accessible areas in ensemble models to generate suitability maps, using out-of-sample predictions to validate model performance against new independent data. Gaur, banteng and buffalo models showed reasonable model accuracy throughout the entire distribution (greater than or equal to 62%) and in Thailand (greater than or equal to 80%), whereas serow and goral models performed poorly for the entire distribution and in Thailand, though 5 km movement buffers markedly improved the performance for serow. Large suitable areas were identified in Thailand and India for gaur, Cambodia and Thailand for banteng and India for buffalo. Over 50% of suitable habitat is located outside protected areas, highlighting the need for habitat management and conflict mitigation outside protected areas.

10.1098/rsos.240574

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High connectivity and human movement limits the impact of travel time on infectious disease transmission

medRxiv (Cold Spring Harbor Laboratory) (2023)

Reju Sam John Joel C. Miller Renata L. Muylaert David T. S. Hayman

The speed of spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) during the coronavirus disease 2019 (COVID-19) pandemic highlights the importance of understanding how infections are transmitted in a highly connected world. Prior to vaccination, changes in human mobility patterns were used as non-pharmaceutical interventions to eliminate or suppress viral transmission. The rapid spread of respiratory viruses, various intervention approaches, and the global dissemination of SARS-CoV-2 underscore the necessity for epidemiological models that incorporate mobility to comprehend the spread of the virus. Here, we introduce a metapopulation susceptible–exposed–infectious–recovered (SEIR) model parameterised with human movement data from 340 cities in China. Our model replicates the early case trajectory in the COVID-19 pandemic. We then use machine learning algorithms to determine which network properties best predict spread between cities and find travel time to be most important, followed by the human movement Weighted Personalised PageRank. However, we show that travel time is most influential locally, after which the high connectivity between cities reduces the impact of travel time between individual cities on transmission speed. Additionally, we demonstrate that only significantly reduced movement substantially impacts infection spread times throughout the network.

Pandemic

Metapopulation

10.1101/2023.07.26.23293210

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Impact of infectious diseases on wild bovidae populations in Thailand: insights from population modelling and disease dynamics

Journal of The Royal Society Interface (2024)

Wantida Horpiencharoen Jonathan C. Marshall Renata L. Muylaert Reju Sam John David T. S. Hayman

The wildlife and livestock interface is vital for wildlife conservation and habitat management. Infectious diseases maintained by domestic species may impact threatened species such as Asian bovids, as they share natural resources and habitats. To predict the population impact of infectious diseases with different traits, we used stochastic mathematical models to simulate the population dynamics over 100 years for 100 times in a model gaur (

Bovidae

Wildlife disease

10.1098/rsif.2024.0278

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Present and future distribution of bat hosts of sarbecoviruses: implications for conservation and public health

bioRxiv (Cold Spring Harbor Laboratory) (2021)

Renata L. Muylaert Tigga Kingston Jinhong Luo Maurício Humberto Vancine Nikolas Galli

Abstract Global changes in response to human encroachment into natural habitats and carbon emissions are driving the biodiversity extinction crisis and increasing disease emergence risk. Host distributions are one critical component to identify areas at risk of spillover, and bats act as reservoirs of diverse viruses. We developed a reproducible ecological niche modelling pipeline for bat hosts of SARS-like viruses (subgenus Sarbecovirus ), given that since SARS-CoV-2 emergence several closely-related viruses have been discovered and sarbecovirus-host interactions have gained attention. We assess sampling biases and model bats’ current distributions based on climate and landscape relationships and project future scenarios. The most important predictors of species distribution were temperature seasonality and cave availability. We identified concentrated host hotspots in Myanmar and projected range contractions for most species by 2100. Our projections indicate hotspots will shift east in Southeast Asia in >2 °C hotter locations in a fossil-fueled development future. Hotspot shifts have implications for conservation and public health, as loss of population connectivity can lead to local extinctions, and remaining hotspots may concentrate near human populations.

Biodiversity hotspot

Extinction (optical mineralogy)

10.1101/2021.12.09.471691

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Citations (1)