Author: Latest Results

Malaria transmission risk is projected to increase in the highlands of Western and Northern Rwanda

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Abstract

Malaria is one of the major health threats in Africa, and the risk of transmission is projected to be exacerbated by global warming. Rwanda experienced an 11-fold increase in malaria incidence from 2011 to 2015 despite extensive funding and implementation of control measures. Here, we focus on Rwanda as a case study and simulate monthly malaria incidence between 2010 and 2015, employing an ensemble learning method. Next, we project future malaria prevalence using shared socio-economic pathways (SSP2-4.5 and SSP5-8.5). We find that the projected increases in temperature and precipitation may shift malaria transmission risk to the highlands of western and northern Rwanda. These two regions that currently experience low malaria transmission. The seasonal effects of malaria incidence may be less apparent from January to June, and the peak season for malaria transmission in the highlands could occur one month earlier. Our findings highlight the impacts of climate change on malaria epidemics in Rwanda, which have implications for other world regions.

The impact of COVID-19 on the debate on open science: a qualitative analysis of published materials from the period of the pandemic

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Abstract

This study is an analysis of the international debate on open science that took place during the pandemic. It addresses the question, how did the COVID-19 pandemic impact the debate on open science? The study takes the form of a qualitative analysis of a large corpus of key articles, editorials, blogs and thought pieces about the impact of COVID on open science, published during the pandemic in English, German, Portuguese, and Spanish. The findings show that many authors believed that it was clear that the experience of the pandemic had illustrated or strengthened the case for open science, with language such as a “stress test”, “catalyst”, “revolution” or “tipping point” frequently used. It was commonly believed that open science had played a positive role in the response to the pandemic, creating a clear ‘line of sight’ between open science and societal benefits. Whilst the arguments about open science deployed in the debate were not substantially new, the focuses of debate changed in some key respects. There was much less attention given to business models for open access and critical perspectives on open science, but open data sharing, preprinting, information quality and misinformation became most prominent in debates. There were also moves to reframe open science conceptually, particularly in connecting science with society and addressing broader questions of equity.

What’s the Future for Science in the New Zealand Curriculum?

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Abstract

This commentary article considers the current contentious debates over the national school science curriculum in Aoteaora New Zealand. The co-authors of this commentary are members of a group of science teacher educators and science education researchers who met recently to discuss concerns over aspects of these debates in the context of a wider political contest over the control and direction of education policy.

The challenging concept of eradication: A core concept guiding and frustrating public health

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Abstract

The celebrated 1980 announcement that smallpox had been eradicated was made using the following definition of eradication: “Permanent reduction to zero of the worldwide incidence of infection caused by a specific agent as a result of deliberate efforts: intervention measures are no longer needed.” Public health around the world works with this definition of “eradication,” setting it as a goal for other infectious disease control programs. The definition is simple. Its application, however, has produced long-running and complex public health campaigns that threaten the commitment of funders, health care providers, and governments. In this paper, the authors demonstrate the disease-specific challenges of eradication through the example of the Global Polio Eradication Initiative (GPEI). While many deem eradication worth its high costs because it is the end of morbidity and mortality from a disease, it does not mean the end of disease control efforts. Public health must be prepared for the possibility of disease reoccurrence in the form of undetected natural reservoirs of disease, lab leaks from stored samples, bioterror attacks using stolen samples, and the synthetic recreation of microbes. This paper clarifies the role of reoccurrence prevention in eradication, calling for its addition in the definition of eradication.

Climate Change and Hydrological Extremes

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Abstract

Purpose of Review

Climate change has profoundly impacted the Earth's atmospheric system and altered the terrestrial water cycle, reshaping the spatiotemporal patterns of hydrological extremes, including floods and droughts. This review aims to summarize recent advancements in understanding the response of hydrological extremes to climate change in both past and future.

Recent Findings

Historical floods driven by heavy rainfall are increasing, while those dominated by snow processes are decreasing, resulting in non-significant changes on a global average. Previously overestimated droughts, due to inaccuracies in hydrological modules within offline diagnostic metrics, have been corrected by advanced modeling results, also revealing minimal historical changes on a global scale. Earth system simulations project concurrent increases in both floods and droughts under future climate change scenarios.

Summary

Climate change influences hydrological extremes across various scales, with diverse spatial distributions and underlying mechanisms. Decision-makers should integrate multi-source information to enhance the monitoring and adaptation of hydrological extremes, particularly focusing on abrupt drought-flood alternations.

Climate Change and Hydrological Extremes

Latest Results

Abstract

Purpose of Review

Climate change has profoundly impacted the Earth's atmospheric system and altered the terrestrial water cycle, reshaping the spatiotemporal patterns of hydrological extremes, including floods and droughts. This review aims to summarize recent advancements in understanding the response of hydrological extremes to climate change in both past and future.

Recent Findings

Historical floods driven by heavy rainfall are increasing, while those dominated by snow processes are decreasing, resulting in non-significant changes on a global average. Previously overestimated droughts, due to inaccuracies in hydrological modules within offline diagnostic metrics, have been corrected by advanced modeling results, also revealing minimal historical changes on a global scale. Earth system simulations project concurrent increases in both floods and droughts under future climate change scenarios.

Summary

Climate change influences hydrological extremes across various scales, with diverse spatial distributions and underlying mechanisms. Decision-makers should integrate multi-source information to enhance the monitoring and adaptation of hydrological extremes, particularly focusing on abrupt drought-flood alternations.

Antarctic sea ice surface temperature bias in atmospheric reanalyses induced by the combined effects of sea ice and clouds

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Abstract

Sea-ice surface temperature from atmospheric reanalysis has been used as an indicator of ice melt and climate change. However, its performance in atmospheric reanalyses is not fully understood in Antarctica. Here, we quantified biases in six widely-used reanalyses using satellite observations, and found strong and persistent warm biases in most reanalyses examined. Further analysis of the biases revealed two main culprits: incorrect cloud properties, and inappropriate sea-ice representation in the reanalysis products. We found that overestimated cloud simulation can contribute more than 4 K warm bias, with ERA5 exhibiting the largest warm bias. Even in reanalysis with smaller biases, this accuracy is achieved through a compensatory relationship between relatively lower cloud fraction bias and overestimated sea ice insulation effect. A dynamic downscaling simulation shows that differences in sea-ice representation can contribute a 2.3 K warm bias. The representation of ice concentration is the primary driver of the spatial distribution of biases by modulating the coupling between sea ice and clouds, as well as surface heat conduction. The lack of a snow layer in all reanalyses examined also has an impact on biases.

Antarctic sea ice surface temperature bias in atmospheric reanalyses induced by the combined effects of sea ice and clouds

Latest Results

Abstract

Sea-ice surface temperature from atmospheric reanalysis has been used as an indicator of ice melt and climate change. However, its performance in atmospheric reanalyses is not fully understood in Antarctica. Here, we quantified biases in six widely-used reanalyses using satellite observations, and found strong and persistent warm biases in most reanalyses examined. Further analysis of the biases revealed two main culprits: incorrect cloud properties, and inappropriate sea-ice representation in the reanalysis products. We found that overestimated cloud simulation can contribute more than 4 K warm bias, with ERA5 exhibiting the largest warm bias. Even in reanalysis with smaller biases, this accuracy is achieved through a compensatory relationship between relatively lower cloud fraction bias and overestimated sea ice insulation effect. A dynamic downscaling simulation shows that differences in sea-ice representation can contribute a 2.3 K warm bias. The representation of ice concentration is the primary driver of the spatial distribution of biases by modulating the coupling between sea ice and clouds, as well as surface heat conduction. The lack of a snow layer in all reanalyses examined also has an impact on biases.

Elevation-dependent dynamics of soil properties in a hilly watershed: a landform-based approach

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Abstract

Understanding the variation of soil physical properties in relation to land use and elevation is essential for modeling soil-landscape relationships and sustainable land management. Hence, this study investigates the spatio-temporal variability of soil physical properties in a lower Himalayan watershed, where agriculture, forest, and grasslands are dominant. Samples from 104 sites in a 422 km2 watershed were collected using a gridded sampling scheme (2 km × 2 km resolution) over 57 weeks. Spatial patterns were analyzed using the Kriging technique, and Spearman rank correlation was employed to identify landform-dependent correlations between soil properties and elevation. The interdependence of the properties was detected using principal component analysis (PCA), while the random forest (RF) approach explored the factors influencing electrical conductivity (EC), organic content (OC), soil temperature (ST), and soil moisture (SM). The results revealed that forest landforms have higher coarser fractions (40%) compared to other landforms, while grasslands have higher soil fines (66%). A positive correlation was observed for elevation with sand content (0.15*), organic content (0.42*), and specific gravity (0.03), while a negative correlation was observed for silt (0.10), clay (0.21*), bulk density (0.52*), electrical conductivity (0.41*), soil moisture (0.28*), and temperature (0.31*). Elevation, soil texture, and specific gravity were identified as critical controls for EC, OC, ST, and SM, emphasizing the importance of soil properties, especially elevation and texture, in shaping spatial distributions. These findings contribute to creating a high-resolution regional inventory for effective land use management, adaptation to climate change, and improved livelihood, specifically for mountain people.

Elevation-dependent dynamics of soil properties in a hilly watershed: a landform-based approach

Latest Results

Abstract

Understanding the variation of soil physical properties in relation to land use and elevation is essential for modeling soil-landscape relationships and sustainable land management. Hence, this study investigates the spatio-temporal variability of soil physical properties in a lower Himalayan watershed, where agriculture, forest, and grasslands are dominant. Samples from 104 sites in a 422 km2 watershed were collected using a gridded sampling scheme (2 km × 2 km resolution) over 57 weeks. Spatial patterns were analyzed using the Kriging technique, and Spearman rank correlation was employed to identify landform-dependent correlations between soil properties and elevation. The interdependence of the properties was detected using principal component analysis (PCA), while the random forest (RF) approach explored the factors influencing electrical conductivity (EC), organic content (OC), soil temperature (ST), and soil moisture (SM). The results revealed that forest landforms have higher coarser fractions (40%) compared to other landforms, while grasslands have higher soil fines (66%). A positive correlation was observed for elevation with sand content (0.15*), organic content (0.42*), and specific gravity (0.03), while a negative correlation was observed for silt (0.10), clay (0.21*), bulk density (0.52*), electrical conductivity (0.41*), soil moisture (0.28*), and temperature (0.31*). Elevation, soil texture, and specific gravity were identified as critical controls for EC, OC, ST, and SM, emphasizing the importance of soil properties, especially elevation and texture, in shaping spatial distributions. These findings contribute to creating a high-resolution regional inventory for effective land use management, adaptation to climate change, and improved livelihood, specifically for mountain people.