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Natural disasters have been demonstrated to cause devastating effects on economic and social development in China, but little is known about the relationship between natural disasters and income at the household level. This study explores the impact of natural disasters on household income, expenditure, and inequality in China as the first study of this nature for the country. The empirical analysis is conducted based on a unique panel dataset that contains six waves of the Chinese Household Income Project (CHIP) survey data over the 1988–2018 period, data on natural disasters, and other social and economic status of households. By employing the fixed effects models, we find that disasters increase contemporaneous levels of income inequality, and disasters that occurred in the previous year significantly increase expenditure inequality. Natural disasters increase operating income inequality but decrease transfer income inequality. Poor households are found to be more vulnerable to disasters and suffer significant income losses. However, there is no evidence to suggest that natural disasters significantly reduce the income of upper- and middle-income groups. These findings have important implications for policies aimed at poverty alleviation and revenue recycling, as they can help improve economic justice and enhance resilience to natural disasters.

Agricultural activities can result in the contamination of surface runoff with pathogens, pesticides, and nutrients. These pollutants can enter surface water bodies in two ways: by direct discharge into surface waters or by infiltration and recharge into groundwater, followed by release to surface waters. Lack of financial resources makes risk assessment through analysis of drinking water pollutants challenging for drinking water suppliers. Inability to identify agricultural lands with a high-risk level and implement action measures might lead to public health issues. As a result, it is essential to identify hazards and conduct risk assessments even with limited data. This study proposes a risk assessment model for agricultural activities based on available data and integrating various types of knowledge, including expert and literature knowledge, to estimate the levels of hazard and risk that different agricultural activities could pose to the quality of withdrawal waters. To accomplish this, we built a Bayesian network with continuous and discrete inputs capturing raw water quality and land use upstream of drinking water intakes (DWIs). This probabilistic model integrates the DWI vulnerability, threat exposure, and threats from agricultural activities, including animal and crop production inventoried in drainage basins. The probabilistic dependencies between model nodes are established through a novel adaptation of a mixed aggregation method. The mixed aggregation method, a traditional approach used in ecological assessments following a deterministic framework, involves using fixed assumptions and parameters to estimate ecological outcomes in a specific case without considering inherent randomness and uncertainty within the system. After validation, this probabilistic model was used for four water intakes in a heavily urbanized watershed with agricultural activities in the south of Quebec, Canada. The findings imply that this methodology can assist stakeholders direct their efforts and investments on at-risk locations by identifying agricultural areas that can potentially pose a risk to DWIs.

This study aimed at evaluating the efficacy of an online CBT intervention with limited therapist contact targeting a range of posttraumatic symptoms among evacuees from the 2016 Fort McMurray wildfires. One hundred and thirty-six residents of Fort McMurray who reported either moderate PTSD symptoms (PCL-5 ≥ 23) or mild PTSD symptoms (PCL-5 ≥ 10) with moderate depression (PHQ-9 ≥ 10) or subthreshold insomnia symptoms (ISI ≥ 8) were randomized either to a treatment (n = 69) or a waitlist condition (n = 67). Participants were on average 45 years old, and mostly identified as White (82%) and as women (76%). Primary outcomes were PTSD, depression, and insomnia symptoms. Secondary outcomes were anxiety symptoms and disability. Significant Assessment Time × Treatment Condition interactions were observed on all outcomes, indicating that access to the treatment led to a decrease in posttraumatic stress (F[1,117.04] = 12.128, p = .001; d = .519, 95% CI = .142–.895), depression (F[1,118.29] = 9.978, p = .002; d = .519, 95% CI = .141–.898) insomnia (F[1,117.60] = 4.574, p = .035; d = .512, 95% CI = .132–.892), and anxiety (F[1,119.64] = 5.465, p = .021; d = .421, 95% CI = .044–.797) symptom severity and disability (F[1,111.55] = 7.015, p = .009; d = .582, 95% CI = .200–.963). Larger effect sizes (d = 0.823–1.075) were observed in participants who completed at least half of the treatment. The RESILIENT online treatment platform was successful to provide access to specialized evidence-based mental health care after a disaster.

Studies show associations between prenatal maternal stress (PNMS) and child autism, with little attention paid to PNMS and autism in young adulthood. The broad autism phenotype (BAP), encompassing sub-clinical levels of autism, includes aloof personality, pragmatic language impairment and rigid personality. It remains unclear whether different aspects of PNMS explain variance in different BAP domains in young adult offspring. We recruited women who were pregnant during, or within 3 months of, the 1998 Quebec ice storm crisis, and assessed three aspects of their stress (i.e., objective hardship, subjective distress and cognitive appraisal). At age 19, the young adult offspring (n = 33, 22F / 11M) completed a BAP self-report. Linear and logistic regressions were implemented to examine associations between PNMS and BAP traits. Up to 21.4% of the variance in BAP total score and in BAP three domains tended to be explained by at least one aspect of maternal stress, For example, 16.8% of the variance in aloof personality tended to be explained by maternal objective hardship; 15.1% of the variance in pragmatic language impairment tended to be explained by maternal subjective distress; 20.0% of the variance in rigid personality tended to be explained by maternal objective hardship and 14.3% by maternal cognitive appraisal. Given the small sample size, the results should be interpreted with caution. In conclusion, this small prospective study suggests that different aspects of maternal stress could have differential effects on different components of BAP traits in young adults.

Abstract Studies have shown that prenatal maternal stress (PNMS) affects brain structure and function in childhood. However, less research has examined whether PNMS effects on brain structure and function extend to young adulthood. We recruited women who were pregnant during or within 3 months following the 1998 Quebec ice storm, assessed their PNMS, and prospectively followed‐up their children. T1‐weighted magnetic resonance imaging (MRI) and resting‐state functional MRI were obtained from 19‐year‐old young adults with ( n  = 39) and without ( n  = 65) prenatal exposure to the ice storm. We examined between‐group differences in gray matter volume (GMV), surface area (SA), and cortical thickness (CT). We used the brain regions showing between‐group GMV differences as seeds to compare between‐group functional connectivity. Within the Ice Storm group, we examined (1) associations between PNMS and the atypical GMV, SA, CT, and functional connectivity, and (2) moderation by timing of exposure. Primarily, we found that, compared to Controls, the Ice Storm youth had larger GMV and higher functional connectivity of the anterior cingulate cortex, the precuneus, the left occipital pole, and the right hippocampus; they also had larger CT, but not SA, of the left occipital pole. Within the Ice Storm group, maternal subjective distress during preconception and mid‐to‐late pregnancy was associated with atypical left occipital pole CT. These results suggest the long‐lasting impact of disaster‐related PNMS on child brain structure and functional connectivity. Our study also indicates timing‐specific effects of the subjective aspect of PNMS on occipital thickness.

The climate crisis not only has significant impacts on biodiversity and the physical health of humans, but its ramifications are also affecting people’s mental health. Eco-anxiety, or the emotions that emerge with the awareness of climate change and the apprehension of its detrimental effects, has been investigated in adults and adolescents, but much less attention has been given to the impacts on children’s mental health and well-being. Initial evidence confirms that youth are significantly concerned about climate change, but few studies have investigated the resulting emotional responses of children and the role of their parents in tempering these, especially using qualitative methodologies. The present study used a descriptive qualitative design with a convenience sample of parents and child dyads, assessed separately. Children’s ( n = 15, ages 8–12 years) experiences were explored using semi-structured interviews and their parents’ ( n = 12) perceptions were captured using a survey with closed and open-ended questions. A reflexive thematic analysis was used to analyze the interview data, and content analysis was used to investigate parent-child experiences. Three themes emerged from the thematic analysis: 1. children’s understanding of climate change, 2. their emotional reaction to climate change, and 3. their coping mechanisms to deal with these emotions. The comparative content analysis revealed that parents who were aware that their children had concerns about climate change, had children who used more adaptive coping mechanisms. The results of this qualitative study contribute to a better understanding of children’s emotional experience of the awareness of climate change in Canada and how they cope with these emotions. Furthermore, the results provide insight into the role parents might play in helping their children cope with their feelings.

Abstract Climatic disaster impacts, such as loss of human life as its most severe consequence, have been rising globally. Several studies argue that population growth is responsible for the rise, and the role of climate change is not evident. While disaster mortality is highest in low-income countries, existing studies focus mostly on developed countries. Here we address this impact attribution question in the context of the Global South using disaster-specific mixed-effects regression models. We show that the rise in landslide and flood mortality in a low-income country such as Nepal between 1992-2021 is primarily attributable to increased precipitation extremes. An increase in one standardized unit in maximum one-day precipitation increases flood mortality by 33%, and heavy rain days increase landslide mortality by 45%. Similarly, a one-unit increase in per capita income decreases landslide and flood mortality by 30% and 45%, respectively. Population density does not show significant effects.

Abstract Surface conditions are known to mediate the impacts of climate warming on permafrost. This calls for a better understanding of the environmental conditions that control the thermal regime and the depth of the active layer, especially within heterogeneous tundra landscapes. This study analyzed the spatial relationships between thaw depths, ground surface temperature (GST), and environmental conditions in a High Arctic tundra environment at Bylot Island, Nunavut, Canada. Measurements were distributed within the two dominant landforms, namely earth hummocks and low‐center polygons, and across a topographic gradient. Our results revealed that GST and thaw depth were highly heterogeneous, varying by up to 3.7°C and by more than 20 cm over short distances (<1 m) within periglacial landforms. This microscale variability sometimes surpassed the variability at the hillslope scale, especially in summer. Late‐winter snowpack thickness was found to be the prime control on the spatial variability in winter soil temperatures due to the highly heterogeneous snow cover induced by blowing snow, and this thermal effect carried over into summer. However, microtopography was the predominant driver of the spatial variability in summer GST, followed by altitude and moss thickness. In contrast, the spatial variability in thaw depth was influenced predominantly by variations in moss thickness. Hence, summer microclimate conditions dominated active layer development, but a thicker snowpack favored soil cooling in the following summer, due to the later disappearance of snow cover. These results enhance our understanding of High Arctic tundra environments and highlight the complexity of considering surface feedback effects in future projections of permafrost states within heterogeneous tundra landscapes.

Abstract. Accurate knowledge of snow depth distributions in forested regions is crucial for applications in hydrology and ecology. In such a context, understanding and assessing the effect of vegetation and topographic conditions on snow depth variability is required. In this study, the spatial distribution of snow depth in two agro-forested sites and one coniferous site in eastern Canada was analyzed for topographic and vegetation effects on snow accumulation. Spatially distributed snow depths were derived by unmanned aerial vehicle light detection and ranging (UAV lidar) surveys conducted in 2019 and 2020. Distinct patterns of snow accumulation and erosion in open areas (fields) versus adjacent forested areas were observed in lidar-derived snow depth maps at all sites. Omnidirectional semi-variogram analysis of snow depths showed the existence of a scale break distance of less than 10 m in the forested area at all three sites, whereas open areas showed comparatively larger scale break distances (i.e., 11–14 m). The effect of vegetation and topographic variables on the spatial variability in snow depths at each site was investigated with random forest models. Results show that the underlying topography and the wind redistribution of snow along forest edges govern the snow depth variability at agro-forested sites, while forest structure variability dominates snow depth variability in the coniferous environment. These results highlight the importance of including and better representing these processes in physically based models for accurate estimates of snowpack dynamics.

What role can a speculative political ecology play in (re)imaging urban futures of climate extremes? In recent years, narratives of dystopian futures of climate extremes have proliferated in geosciences, and across the media and creative arts. These anxiety-fueled narratives often generate a sense of resignation and unavoidability, which contributes to foreclosing the possibility of radically different political projects. In this article, we argue that these narratives conceal the coproduction of nature and society and treat nature as the problem, thereby locking futures into dystopic configurations. Political ecology scholarship can contribute to generate a politics of possibility by reconceptualizing the relations that constitute urban futures under climate extremes as socionatural. This, we argue, calls for a more experimental political ecology and new forms of theorizing. To this aim, we develop a speculative political ecological approach grounded on a numerical model that examines the potential of transformative change in the aftermath of extreme flood events in a capitalist city. Analytically, this opens a unique possibility of exploring urban futures beyond current trajectories, and how these alternative futures might transform vulnerability and inequality across urban spaces. From a policy perspective, we lay the foundations for a new generation of models that apprehend the role of power and agency in shaping uneven urban futures of climate extremes.

Wetlands and reservoirs are important water flow and storage regulators in a river basin; therefore, they can play a crucial role in mitigating flood and hydrological drought risks. Despite the advancement of river basin theory and modeling, our knowledge is still limited about the extent to which these two regulators could perform such a role, especially under future climate extremes. To improve our understanding, we first coupled wetlands and reservoir operations into a semi-spatially explicit hydrological model and then applied it in a case study involving a large river basin in northeast China. The projection of future floods and hydrological droughts was performed using the hydrological model during different periods (near future: 2026–2050, middle century: 2051–2075, and end century: 2076–2100) under five future climate change scenarios. We found that the risk of future floods and hydrological droughts can vary across different periods – in particular, it will experience relatively large increases and slight decreases. This large river basin will experience flood events of longer duration, with larger peak flows and volume, and of enhanced flashiness compared to the historical period. Simultaneously, the hydrological droughts will be much more frequent, with longer durations and more serious deficits. Therefore, the risk of floods and droughts will, overall, increase further under future climate change even under the combined influence of reservoirs and wetlands. These findings highlight the hydrological regulation function of wetlands and reservoirs and attest that the combining of wetlands with reservoir operation cannot fully eliminate the increasing future flood and drought risks. To improve a river basin's resilience to the risks of future climate change, we argue that the implementation of wetland restoration and the development of accurate forecasting systems for effective reservoir operation are of great importance. Furthermore, this study demonstrated a wetland–reservoir integrated modeling and assessment framework that is conducive to risk assessment of floods and hydrological droughts and that can be used for other river basins in the world.