Background: Dengue is an endemic vector-borne disease influenced by environmental factors such as landscape and climate. Previous studies separately assessed the effects of landscape and climate factors on mosquito occurrence and dengue incidence. However, both factors concurrently coexist in time and space and can interact, affecting mosquito development and dengue disease transmission. For example, eggs laid in a suitable environment can hatch after being submerged in rain water. It has been difficult for conventional statistical modeling approaches to demonstrate these combined influences due to mathematical constraints.
Objectives: To investigate the combined influences of landscape and climate factors on mosquito occurrence and dengue incidence.
Methods: Entomological, epidemiological, and landscape data from the rainy season (July-December) were obtained from respective government agencies in Metropolitan Manila, Philippines, from 2012 to 2014. Temperature, precipitation and vegetation data were obtained through remote sensing. A random forest algorithm was used to select the landscape and climate variables. Afterward, using the identified key variables, a model-based (MOB) recursive partitioning was implemented to test the combined influences of landscape and climate factors on ovitrap index (vector mosquito occurrence) and dengue incidence.
Results: The MOB recursive partitioning for ovitrap index indicated a high sensitivity of vector mosquito occurrence on environmental conditions generated by a combination of high residential density areas with low precipitation. Moreover, the MOB recursive partitioning indicated high sensitivity of dengue incidence to the effects of precipitation in areas with high proportions of residential density and commercial areas.
Conclusions: Dengue dynamics are not solely influenced by individual effects of either climate or landscape, but rather by their synergistic or combined effects. The presented findings have the potential to target vector surveillance in areas identified as suitable for mosquito occurrence under specific climatic conditions and may be relevant as part of urban planning strategies to control dengue.
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http://dx.doi.org/10.1016/j.scitotenv.2021.148406 | DOI Listing |
Mol Ecol
January 2025
Department of Biology, Colorado State University, Fort Collins, Colorado, USA.
Identifying populations at highest risk from climate change is a critical component of conservation efforts. However, vulnerability assessments are usually applied at the species level, even though intraspecific variation in exposure, sensitivity and adaptive capacity play a crucial role in determining vulnerability. Genomic data can inform intraspecific vulnerability by identifying signatures of local adaptation that reflect population-level variation in sensitivity and adaptive capacity.
View Article and Find Full Text PDFSci Data
January 2025
University of Bern, Wyss Academy for Nature, Bern, 3011, Switzerland.
Throughout the last centuries, European climate changed substantially, which affected the potential to plant and grow crops. These changes happened not just over time but also had a spatial dimension. Yet, despite large climatic fluctuations, quantitative historical studies typically rely on static measures for agricultural suitability due to the non-availability of time-varying indices.
View Article and Find Full Text PDFEcol Lett
January 2025
Department of Biological Sciences, Texas Tech University, Lubbock, Texas, USA.
Accurately representing the relationships between nitrogen supply and photosynthesis is crucial for reliably predicting carbon-nitrogen cycle coupling in Earth System Models (ESMs). Most ESMs assume positive correlations amongst soil nitrogen supply, leaf nitrogen content, and photosynthetic capacity. However, leaf photosynthetic nitrogen demand may influence the leaf nitrogen response to soil nitrogen supply; thus, responses to nitrogen supply are expected to be the largest in environments where demand is the greatest.
View Article and Find Full Text PDFSci Total Environ
January 2025
Guangzhou Huadu district drainage management center, Guangzhou 510800, China.
Rapid urbanization has significantly altered surface landscape configurations, leading to complex urban climates. While much attention has been focused on impervious surfaces' impact on extreme precipitation, a critical gap remains in understanding how various 2D urban landscape components influence extreme precipitation across different durations. Through an analysis of the non-stationarity and spatiotemporal variations in extreme precipitation across the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) from 1990 to 2020, we constructed the non-stationary Generalized Additive Models for Location Scale and Shape (GAMLSS) model by introducing six urban landscape structural metrics as explanatory variables for each of the 27 meteorological stations in the GBA.
View Article and Find Full Text PDFJ Environ Manage
January 2025
School of Landscape Architecture, Beijing Forestry University, Beijing, 100083, China. Electronic address:
As climate change and urbanization progress, the urban heat island issue will affect more people. Urban blue-green spaces can effectively mitigate the urban heat island effect, and their structure and morphology significantly impact the degree of mitigation. To identify the most effective blue-green space distribution for mitigating the heat island effect across different urban function zones (UFZ), we selected 14 landscape metrics of blue-green spaces in the main urban area of Nanjing.
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