A triple increase in global river basins with water scarcity due to future pollution.

Water security is at stake today. While climate changes influence water availability, urbanization and agricultural activities have led to increasing water demand as well as pollution, limiting safe water use. We conducted a global assessment of future clean-water scarcity for 2050s by adding the water pollution aspect to the classical water quantity-induced scarcity assessments.

Diameter, height and species of 42 million trees in three European landscapes generated from field data and airborne laser scanning data.

Ecology and forestry sciences are using an increasing amount of data to address a wide variety of technical and research questions at the local, continental and global scales. However, one type of data remains rare: fine-grain descriptions of large landscapes. Yet, this type of data could help address the scaling issues in ecology and could prove useful for testing forest management strategies and accurately predicting the dynamics of ecosystem services.

Resilience of transportation infrastructure networks to road failures.

Anthropogenic climate change drives extreme weather events, leading to significant consequences for both society and the environment. This includes damage to road infrastructure, causing disruptions in transportation, obstructing access to emergency services, and hindering humanitarian organizations after natural disasters. In this study, we develop a novel method for analyzing the impacts of natural hazards on transportation networks rooted in the gravity model of travel, offering a fresh perspective to assess the repercussions of natural hazards on transportation network stability.

High-resolution climate projection dataset based on CMIP6 for Peru and Ecuador: BASD-CMIP6-PE.

Here, we present BASD-CMIP6-PE, a high-resolution (1d, 10 km) climate dataset for Peru and Ecuador based on the bias-adjusted and statistically downscaled CMIP6 climate projections of 10 GCMs. This dataset includes both historical simulations (1850-2014) and future projections (2015-2100) for precipitation and minimum, mean, and maximum temperature under three Shared Socioeconomic Pathways (SSP1-2.6, SSP3-7.

Network percolation provides early warnings of abrupt changes in coupled oscillatory systems: An explanatory analysis.

Functional networks are powerful tools to study statistical interdependency structures in spatially extended or multivariable systems. They have been used to get insights into the dynamics of complex systems in various areas of science. In particular, percolation properties of correlation networks have been employed to identify early warning signals of critical transitions.

Bursting multistability induced by double-Hopf bifurcation.

We study the slow-fast dynamics of a system with a double-Hopf bifurcation and a slowly varying parameter. The model consists of coupled Bonhöffer-van der Pol oscillators excited by a periodic slow-varying AC source. We consider two cases where the slowly varying parameter passes by or crosses the double-Hopf bifurcation, respectively.

Diagnosing norms and norm change in rural Bangladesh: an exploration of gendered social norms and women's empowerment.

Background: Gender-transformative public health programs often aim to address power inequities between men and women and promote women's empowerment. However, to achieve transformative change, it is necessary to first identify the underlying norms that perpetuate these power imbalances. The objective of our study was to use Bicchieri's theory of social norms and model of norm change to identify gendered norms and evidence of norm change amongst participants of the Food and Agricultural Approaches to Reducing Malnutrition (FAARM) trial in rural Sylhet Division, Bangladesh.

Effect of a behaviour change intervention on household food hygiene practices in rural Bangladesh: A cluster-randomised controlled trial.

Introduction: Behavioural interventions could improve caregivers' food hygiene practices in low-resource settings. So far, evidence is limited to small-scale and short-term studies, and few have evaluated the long-term maintenance of promoted behaviours. We evaluated the effect of a relatively large-scale behaviour change intervention on medium and long-term maintenance of household food hygiene practices in Bangladesh.

Interpolation and sampling effects on recurrence quantification measures.

The recurrence plot and the recurrence quantification analysis (RQA) are well-established methods for the analysis of data from complex systems. They provide important insights into the nature of the dynamics, periodicity, regime changes, and many more. These methods are used in different fields of research, such as finance, engineering, life, and earth science.

Adaptive resonance and control of chaos in a new memristive generalized FitzHugh-Nagumo bursting model.

In a new memristive generalized FitzHugh-Nagumo bursting model, adaptive resonance (AR), in which the neuron system's response to a varied stimulus can be improved by the ideal intensity of adaptation currents, is examined. We discovered that, in the absence of electromagnetic induction, there is signal detection at the greatest resonance peak of AR using the harmonic balance approach. For electromagnetic induction's minor impacts, this peak of the AR is optimized, whereas for its larger effects, it disappears.

Earth beyond six of nine planetary boundaries.

This planetary boundaries framework update finds that six of the nine boundaries are transgressed, suggesting that Earth is now well outside of the safe operating space for humanity. Ocean acidification is close to being breached, while aerosol loading regionally exceeds the boundary. Stratospheric ozone levels have slightly recovered.

Effect of a Homestead Food Production Program on the Prevalence of Diarrhea and Acute Respiratory Infection in Children in Sylhet, Bangladesh: A Cluster-Randomized Controlled Trial.

Diarrhea and respiratory illness are leading causes of mortality and morbidity among young children. We assessed the impact of a homestead food production intervention on diarrhea and acute respiratory infection (ARI) in children in Bangladesh, secondary outcomes of the Food and Agricultural Approaches to Reducing Malnutrition (FAARM) cluster-randomized trial. The trial enrolled 2,705 married women and their children 3 years or younger in 96 rural settlements (geographic clusters) in Sylhet Division, Bangladesh.

Thalassemia and hemoglobinopathy prevalence in a community-based sample in Sylhet, Bangladesh.

Background: Inherited blood disorders affect 7% of the population worldwide, with higher prevalences in countries in the "thalassemia belt," which includes Bangladesh. Clinical management options for severely affected individuals are expensive; thus, targeted government policies are needed to support prevention and treatment programs. In Bangladesh, there is a lack of data, in particular community-based estimates, to determine population prevalence.

Direct and indirect simulating and projecting hydrological drought using a supervised machine learning method.

There is a trend in using Artificial Intelligence methods as simulation tools in different aspects of hydrology, including river discharge simulations, drought predictions, and crop yield simulations. The motivation of this work was to assess two various concepts in applying these methods in simulations and projections of hydrological drought. In this study, Standardized Runoff Index (SRI) was simulated and projected using Artificial Neural Networks (ANNs).

Wild foods contribute to women's higher dietary diversity in India.

Wild foods, from forests and common lands, can contribute to food and nutrition security. Most previous studies have established correlations between wild food consumption and children's dietary diversity in Africa, but other groups and geographic contexts remain understudied. Here a rigorous quasi-experimental method was combined with monthly interval data to assess the contribution of wild foods to women's diets.

Quantification of urban mitigation potentials - coping with data heterogeneity.

Cities are at the forefront of European and international climate action. However, in many cities, the ever-growing urban population is putting pressure on settlement and infrastructure development, increasing attention to urban planning, infrastructure and buildings. This paper introduces a set of quantification approaches, capturing impacts of urban planning measures in three fields of action: sustainable building, transport and redensification.

Population, land use and economic exposure estimates for Europe at 100 m resolution from 1870 to 2020.

Understanding the influence of climate change on past extreme weather impacts is a vital research task. However, the effects of climate change are obscured in the observed impact data series due to the rapid evolution of the social and economic circumstances in which the events occurred. The HANZE v2.

Uncertainty in non-CO greenhouse gas mitigation contributes to ambiguity in global climate policy feasibility.

Despite its projected crucial role in stringent, future global climate policy, non-CO greenhouse gas (NCGG) mitigation remains a large uncertain factor in climate research. A revision of the estimated mitigation potential has implications for the feasibility of global climate policy to reach the Paris Agreement climate goals. Here, we provide a systematic bottom-up estimate of the total uncertainty in NCGG mitigation, by developing 'optimistic', 'default' and 'pessimistic' long-term NCGG marginal abatement cost (MAC) curves, based on a comprehensive literature review of mitigation options.

A threefold approach to rescue the 2030 Agenda from failing.

Rescuing the 2030 Agenda for Sustainable Development from failing requires prioritizing Sustainable Development Goals (SDGs), understanding the impacts of underachieving SDGs, and building a post-2030 Agenda based on scientific evidence.

Safe and just Earth system boundaries.

The stability and resilience of the Earth system and human well-being are inseparably linked, yet their interdependencies are generally under-recognized; consequently, they are often treated independently. Here, we use modelling and literature assessment to quantify safe and just Earth system boundaries (ESBs) for climate, the biosphere, water and nutrient cycles, and aerosols at global and subglobal scales. We propose ESBs for maintaining the resilience and stability of the Earth system (safe ESBs) and minimizing exposure to significant harm to humans from Earth system change (a necessary but not sufficient condition for justice).

Power spectral estimate for discrete data.

The identification of cycles in periodic signals is a ubiquitous problem in time series analysis. Many real-world datasets only record a signal as a series of discrete events or symbols. In some cases, only a sequence of (non-equidistant) times can be assessed.

Projected landscape-scale repercussions of global action for climate and biodiversity protection.

Land conservation and increased carbon uptake on land are fundamental to achieving the ambitious targets of the climate and biodiversity conventions. Yet, it remains largely unknown how such ambitions, along with an increasing demand for agricultural products, could drive landscape-scale changes and affect other key regulating nature's contributions to people (NCP) that sustain land productivity outside conservation priority areas. By using an integrated, globally consistent modelling approach, we show that ambitious carbon-focused land restoration action and the enlargement of protected areas alone may be insufficient to reverse negative trends in landscape heterogeneity, pollination supply, and soil loss.

China can be self-sufficient in maize production by 2030 with optimal crop management.

Population growth and economic development in China has increased the demand for food and animal feed, raising questions regarding China's future maize production self-sufficiency. Here, we address this challenge by combining data-driven projections with a machine learning method on data from 402 stations, with data from 87 field experiments across China. Current maize yield would be roughly doubled with the implementation of optimal planting density and management.