Empirically-identified subgroups of children with autism spectrum disorder and their response to two types of cognitive behavioral therapy

Autism spectrum disorder (ASD) is heterogeneous and likely entails distinct phenotypes with varying etiologies. Identifying these subgroups may contribute to hypotheses about differential treatment responses. The present study aimed to discern subgroups among children with ASD and anxiety in context of the five-factor model of personality (FFM) and evaluate treatment response differences to two cognitive-behavioral therapy treatments. The present study is a secondary data analysis of children with ASD and anxiety (N=202; ages 7–13; 20.8% female) in a cognitive behavioral therapy (CBT) randomized controlled trial (Wood et al., 2020). Subgroups were identified via latent profile analysis of parent-reported FFM data. Treatment groups included standard-of-practice CBT (CC), designed for children with anxiety, and adapted CBT (BIACA), designed for children with ASD and comorbid anxiety. Five subgroups with distinct profiles were extracted. Analysis of covariance revealed CBT response was contingent on subgroup membership. Two subgroups responded better to BIACA on the primary outcome measure and a third responded better to BIACA on a peer-social adaptation measure, while a fourth subgroup responded better to CC on a school-related adaptation measure. These findings suggest that the FFM may be useful in empirically identifying subgroups of children with ASD, which could inform intervention selection decisions for children with ASD and anxiety.

Mitigating future climate change effects on wheat and soybean yields in Central region of Madhya Pradesh by shifting sowing dates

The present work focuses on (1) estimation of future yield of wheat and soybean crop under RCPs scenario 2.6, 4.5 and 8.5 for years 2020, 2050 and 2080 using FAO AquaCrop yield simulating model and (2) assessment of shifting planting date as adaptation measure to mitigate climate change impact for Sehore district, Madhya Pradesh. Statistically downscaled General Circulation Model CanESM2 data was used as input to AquaCrop for generation of future data. The AquaCrop yield model was first checked for its suitability and accuracy in prediction of yield for years 2000–2015, model nash sutcliffe efficiency 0.79, 0.84, RMSE 300.7, 104.4 and coefficient of determination (R2) 0.91, 0.88 were obtained for wheat and soybean crops, respectively. The results depicts that RCP 8.5 shows the highest impact with reduction in wheat and soybean yield for projected year 2080. Under the changed climate, shifting planting date from of wheat from 15th November to 30th November and 1st July to 10th July for soybean resulted in least decline in crop yields and surfaced as a practical adaptation measure for sustaining future yields.

The Comparative Study of Adaptation Measure to Sea Level Rise in Thailand

In the 21st century, global sea level rise associated with climate change will affect beach areas, which provide a number of benefits that include benefits to the recreational sector of the economy. In Thailand, the adoption of structural measures in order to slow down beach erosion and handle the impact of sea level rise is commonly implemented. However, structural measures often bring about negative effects on nearby coastal areas. For this reason, suitable adaptation measures should be determined, in order to protect beach areas and to sustain the tourism carrying capacity of the beach. This study analyzed historical shoreline changes using satellite images, and assessed beach value with the hedonic pricing method. We used a benefit–cost ratio analysis to evaluate the economic valuation assessment of Pattaya beach and Chalatat beach. The results showed that the beach values of Pattaya beach and Chalatat beach were 1,072,250 and 92,092 USD, respectively. The benefit–cost ratio analysis proposed that it is worth implementing beach nourishment for the adaptation measure to address all climate change scenarios. In response to climate change, recommendations could be applied to support beach tourism.

The role of irrigation on potato yields in Northern Germany under climate change

<p>The agricultural sector is particularly vulnerable to changing weather and climate conditions. Climate projections for Germany until the end of this century demonstrate higher temperatures and a substantial net water deficit during the summer months when agriculture is in high demand for water. Additionally, the frequency and length of dry periods increase as a consequence of climate change. Irrigation was introduced in the 1960s in Northeast Lower Saxony (Germany) to become more resilient to changing weather and climate conditions and prevent yield losses. The region involves today the largest irrigated area in Germany. However, during the drought in 2018 water extractions for irrigation by far exceeded the institutional limit. Water using conflicts are likely to strengthen in the future as the irrigation demand will increase. In this study, we explore the importance of irrigation as a climate change adaptation measure in the region. First, we employ a statistical regression model to investigate whether regional climate, hydrological, and irrigation data on a monthly and county level scale are adequate to describe potato yield changes between 1978 and 2018. Soil moisture information originates from the mesoscale hydrologic model (mHM). Irrigation is estimated based on the climatic water balance and crop water demand. These estimations are scaled with irrigation data from local authorities to account for realistic monthly water withdrawals. Second, we use the process-based crop model EPIC to estimate potato crop yields and to validate the performance of the statistical approach. We analyze future yield changes based on climate model projections for the 21st century using the two approaches. We investigate different irrigation scenarios as a potential climate change adaptation measure. By comparing the statistical and process-based approaches we explore whether a rather simplistic statistical approach captures the main processes of the climate change impact on yields.</p>

Climate Change Impacts on Irrigation Requirements of Preserved Forage for Horses under Mediterranean Conditions

Pasture and forage production occupies a large part of the utilized agricultural area in Portugal, a country prone to the effects of climate change. This study aims at evaluating the impacts of climate change on forage irrigation requirements and at defining and assessing different adaptation measures. A second objective focuses on evaluating the impacts on water deficit of rainfed forages. This study was performed in a Lusitano horse stud farm located in Azambuja Municipality, Portugal. The climate change impacts on the crop irrigation requirements and crop water deficit were simulated using the soil water balance model, ISAREG. The reference period considered was 1971–2000 and the climate scenarios were the Representative Concentration Pathways (RCPs) 4.5 and 8.5 (2071–2100). The results show that the adaptation measure aiming at maximum production (several cuts) will increase the irrigation requirements in the different climate change scenarios between 38.4% and 67.1%. The adaptation measure aiming at reducing the water consumption (only one cut) will lead to a reduction in irrigation requirements in the different climate change scenarios, ranging between −31.1% and −64.0%. In rainfed conditions, the water deficit is substantially aggravated in the climate change scenarios.

Insurance Fund as an Adaptation Measure for Increasing Water Security in Basins Under Change

<p>Extreme weather events are increasingly evident and widespread around the world due to climate change. These events are driven by rising temperatures and changes in precipitation patterns, which lead to changes in flood frequency, drought and water availability. To reduce the future impacts of natural disasters, it is crucial to understand the spatiotemporal variability of social, economic and environmental vulnerabilities related to natural disasters. Particularly, developing countries are more vulnerable to climate risks due to their greater economic dependence on climate-sensitive primary activities, infrastructure, finance and other factors that undermine successful adaptation. In this concept, adaptation plays the role of anticipating the adverse effects of climate change and taking appropriate measures to prevent or minimize the damage they may cause. Thus, the insurance fund is a valuable adaptation tool for unexpected losses reimbursement, long-term impacts prevention and encouraging risk mitigation. Although this approach is successful throughout the world and major organizations support insurance as an adaptation measure, the Brazilian insurance fund only provides support for rural landowners. Thus, we will evaluate the implementation of an indexed multi-risk insurance fund integrated with water security parameters, as an instrument for adaptation to climate change. We will use the SWAT+, a hydrosedimentological model, to assess the current conditions and future scenarios (up to 2100) of water security indices considering two International Panel on Climate Change (IPCC) Representative Concentration Pathways (RCP 4.5 and RCP 8.5). Then, we will incorporate those parameters to the Hydrological Risk Transfer Model (MTRH). Our results will provide optimized premium in current and future scenarios for supporting adaptation plans to climate change. Furthermore, to contribute to technical-scientific information addressing possible effects of climate change on the hydrometeorological variables and their spatiotemporal variability.</p>