Chytridiomycosis, due to the fungus Batrachochytrium dendrobatidis (Bd), has been associated with the alarming decline and extinction crisis of amphibians worldwide. Because conservation programs are implemented locally, it is essential to understand how the complex interactions among host species, climate and human activities contribute to Bd occurrence at regional scales. Using weighted phylogenetic regressions and model selection, we investigated geographic patterns of Bd occurrence along a latitudinal gradient of 1500 km within a biodiversity hot spot in Chile (1845 individuals sampled from 253 sites and representing 24 species), and its association with climatic, socio-demographic and economic variables. Analyses show that Bd prevalence decreases with latitude although it has increased by almost 10% between 2008 and 2013, possibly reflecting an ongoing spread of Bd following the introduction of Xenopus laevis. Occurrence of Bd was higher in regions with high gross domestic product (particularly near developed centers) and with a high variability in rainfall regimes, whereas models including other bioclimatic or geographic variables, including temperature, exhibited substantially lower fit and virtually no support based on Akaike weights. In addition, Bd prevalence exhibited a strong phylogenetic signal, with five species having high numbers of infected individuals and higher prevalence than the average of 13.3% across all species. Taken together, our results highlight that Bd in Chile might still be spreading south, facilitated by a subset of species that seem to play an important epidemiological role maintaining this pathogen in the communities, in combination with climatic and human factors affecting the availability and quality of amphibian breeding sites. This information may be employed to design conservation strategies and mitigate the impacts of Bd in the biodiversity hot spot of southern Chile, and similar studies may prove useful to disentangle the role of different factors contributing to the emergence and spread of this catastrophic disease.
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Chemosphere
January 2025
Department of Agricultural Machinery Engineering, University of Tehran, Iran.
Soil oil pollution is a major environmental issue, especially in oil-producing nations, as it threatens the health of plants, animals, and humans. While bioremediation has been extensively utilized as a cost-effective method for restoring oil-contaminated soil, its environmental impact has garnered relatively little attention. Researchers often concentrate on reducing pollutant concentrations below permissible limits to restore soil quality.
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January 2025
Forestry and Forest Products Research Institute, Matsunosato 1, Tsukuba, Ibaraki, 305-8687, Japan.
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Uniwersytet Medyczny w Poznaniu.
In 2024, we observe the fortieth anniversary of the publication, where, for the first time, the term of Seasonal Affective Disorder (SAD) was used. Presently, SAD is regarded as a special category of mood disorder. In the American Diagnostic and Statistical Manual of Mental Disorders, fifth edition (DSM-V), the seasonality makes a specifier, "with seasonal pattern", both for recurrent depression or Major Depressive Disorder (MDD), and for Bipolar Disorder (BD).
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January 2025
Asian Development Bank Institute, Research, Tokyo, 100-6008, Japan.
Global food production predominantly depends on a limited number of cereal crops; however, numerous other crops have the potential to support the nutrition and economy of many local communities in developing countries. The different crop species characterized as having relatively low perceived economic importance or agricultural significance are known as underutilized crops. Millet is one of the underutilized crops with significant potential to address nutrient and hunger-related challenges in many developing countries like Nepal due to its versatility and climate resilience.
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January 2025
RTI International, 3040 Cornwallis Rd., P.O. Box 12194, Research Triangle Park, NC, 27709, USA.
Geospatially explicit and statistically accurate person and household data allow researchers to study community-and neighborhood-level effects and design and test hypotheses that would otherwise not be possible without the generation of synthetic data. In this article, we demonstrate the workflow for generating spatially explicit household- and individual-level synthetic populations for the United States representing the year 2019. We use publicly available U.
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