Journal Articles

Permanent URI for this collectionhttps://mro.massey.ac.nz/handle/10179/7915

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Author: search.filters.author.Muylaert RLSubject: search.filters.subject.Biodiversity

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    Upscaling effects on infectious disease emergence risk emphasize the need for local planning in primary prevention within biodiversity hotspots
    (Springer Nature Limited, 2025-10-27) Muylaert RL; Wilkinson DA; Dwiyanti EI; Hayman DTS
    Zoonotic risk assessments are increasingly vital in the wake of recent epidemics. The microbial diversity of parasitic organisms correlates with host species richness, with regions of high biodiversity facing elevated risks of emerging zoonotic infections. While habitat loss and fragmentation reduce species diversity, anthropogenic encroachment, particularly in forested areas, amplifies human exposure to novel pathogens. This study integrates host habitat, biodiversity, human encroachment, and population at risk to estimate novel disease emergence and epidemic risk at multiple spatial scales. Using Java, Indonesia, as a case study, we demonstrate that degrading spatial resolution leads to information loss, with optimal resolutions typically below 2000 m, ideally around 500 m when native-resolution processing is unfeasible. Gravity models of epidemic spread highlight Jakarta and West Java as high-risk areas, with varying contributions from surrounding regions. Our spatial analysis underscores the influence of population centers on forest management and agroforestry practices. These findings offer valuable insights for guiding pandemic prevention research and improving pathogen- and driver-based risk monitoring strategies.
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    Malaria Risk Drivers in the Brazilian Amazon: Land Use-Land Cover Interactions and Biological Diversity.
    (MDPI (Basel, Switzerland), 2023-08-01) Gonzalez Daza W; Muylaert RL; Sobral-Souza T; Lemes Landeiro V; Oren E; Blanco G
    Malaria is a prevalent disease in several tropical and subtropical regions, including Brazil, where it remains a significant public health concern. Even though there have been substantial efforts to decrease the number of cases, the reoccurrence of epidemics in regions that have been free of cases for many years presents a significant challenge. Due to the multifaceted factors that influence the spread of malaria, influencing malaria risk factors were analyzed through regional outbreak cluster analysis and spatio-temporal models in the Brazilian Amazon, incorporating climate, land use/cover interactions, species richness, and number of endemic birds and amphibians. Results showed that high amphibian and bird richness and endemism correlated with a reduction in malaria risk. The presence of forest had a risk-increasing effect, but it depended on its juxtaposition with anthropic land uses. Biodiversity and landscape composition, rather than forest formation presence alone, modulated malaria risk in the period. Areas with low endemic species diversity and high human activity, predominantly anthropogenic landscapes, posed high malaria risk. This study underscores the importance of considering the broader ecological context in malaria control efforts.
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    DarkCideS 1.0, a global database for bats in karsts and caves
    (Springer Nature Limited, 2022-04-05) Tanalgo KC; Tabora JAG; de Oliveira HFM; Haelewaters D; Beranek CT; Otálora-Ardila A; Bernard E; Gonçalves F; Eriksson A; Donnelly M; González JM; Ramos HF; Rivas AC; Webala PW; Deleva S; Dalhoumi R; Maula J; Lizarro D; Aguirre LF; Bouillard N; Quibod MNRM; Barros J; Turcios-Casco MA; Martínez M; Ordoñez-Mazier DI; Orellana JAS; Ordoñez-Trejo EJ; Ordoñez D; Chornelia A; Lu JM; Xing C; Baniya S; Muylaert RL; Dias-Silva LH; Ruadreo N; Hughes AC
    Understanding biodiversity patterns as well as drivers of population declines, and range losses provides crucial baselines for monitoring and conservation. However, the information needed to evaluate such trends remains unstandardised and sparsely available for many taxonomic groups and habitats, including the cave-dwelling bats and cave ecosystems. We developed the DarkCideS 1.0 (https://darkcides.org/), a global database of bat caves and species synthesised from publicly available information and datasets. The DarkCideS 1.0 is by far the largest database for cave-dwelling bats, which contains information for geographical location, ecological status, species traits, and parasites and hyperparasites for 679 bat species are known to occur in caves or use caves in part of their life histories. The database currently contains 6746 georeferenced occurrences for 402 cave-dwelling bat species from 2002 cave sites in 46 countries and 12 terrestrial biomes. The database has been developed to be collaborative and open-access, allowing continuous data-sharing among the community of bat researchers and conservation biologists to advance bat research and comparative monitoring and prioritisation for conservation.