Assessment of farm households’ perception, beliefs and attitude toward climatic risks: A case study of rural Vietnam

Vietnam is one the most vulnerable region to climate change and extreme climatic events, such as flash floods and droughts. This present research aims to explore the farm households’ beliefs, risk perception, adaptive attitude and climate change adaptation measures that they currently utilize in their farms to cope with climatic risks. Further, this study analyzed effect of climate change belief, awareness and adaptive attitudes on farmers’ adaptive behavior. By using structured questionnaire, the data from 816 respondents were collected from seven provinces of Vietnam. We used ordinary least squares regression and logistic regression approach to analyze farmers’ belief, perception of climatic change, and risk attitude towards climatic hazards. Results revealed that farmers in the study area are using the most common climatic risk management strategies including applying new technologies, adjustment of the seasonal calendar, and diversification. Findings further revealed that that farm households were mostly concerned about the risk in soil erosion and washout, followed by the stress of prolonging dry season and droughts. The study participants also reported a decrease in precipitation and increase in temperature and frequency and incidence of other extreme climatic events. A positive significant relationship was found between farm management practices and ecological communities. Risk perceptions and attitude toward climate change are essential factors among farm households of northern mountains of Vietnam. Thus, the climate strain linked with the institutional stress and socio-economic has serious insinuations for farm households’ livelihood bases, a universal climate change adaptation scheme is required to endure farmers’ livelihood.

Simulating impact of climatic variability and extreme climatic events on crop production

Wide range of inter-annual climatic variability and frequent occurrence of extreme climatic events in Indian context is a great concern. There is a need to assess the impact of these events on agriculture production as well suggest the agri-management options for sustenance. The appropriate region specific agro-advisory needs to be established for the farmers and other stake holders. Crop simulation models are effective tools for assessing the crops’ response to these climate related events and for suggesting suitable adaptation procedures for ensuring higher agricultural production. Remote sensing and GIS are effective tools in this regard to prepare the regional based agro-advisories, by linking with the crop simulation models and relational database layers of bio-physical and socio-economic aspects. For effective agro-advisory services, there is a need to link the other biotic and abiotic stresses for accurate estimates and generating window of suitable agri-management options. Crop simulation models can effectively integrate these stresses for crop and soil processes understanding and ultimate yield formation. In this review article, we have discussed about the inter-annual/ seasonal climatic variability and occurrence of extreme climatic events in India and demonstrated the potential of crop models viz., INFOCROP, WTGROWS, DSSAT to assess the impact of these events (also including climate change) on growth and yield of crops and cropping systems and thereby suggesting appropriate adaptation strategies for sustenance. The potential of remote sensing for crop condition assessment and regional/national yield forecast has been demonstrated. Crop simulation tools coupled with remote sensing inputs through GIS can play an important role in evolving this unique operational platform of designing weather based agro-advisory services for India.

Misinformation and instant access: inconsistent reporting during extreme climatic events, reflecting on Tropical Cyclone Idai

In an era of globalisation, the spread of misinformation is becoming increasingly problematic. The dissemination of inaccurate and conflicting news on events such as tropical cyclones, can result in people being placed at increased risk and negatively influence the amount of aid received by the region. This study scrutinises media articles, and with the use of comparative analysis, uncovers the potential cause of misinformation in disaster journalism. The results of the study found that 59% (n=80) of the articles reported on wind speed values while 80% (n=80) of the articles reported on the number of fatalities. Results indicate that 44% (n=80) of the articles used official sources, uncovering that the potential source of misinformation is not only what is provided to journalists from official sources, but how the various sources used lead to contradicting news articles. The variations in news reports can be attributed to factors such as, the influx of different reports and the changing conditions during a disaster, all of which make consistent reporting on a disaster a challenging process.

Sandtank-ML: An Educational Tool at the Interface of Hydrology and Machine Learning

Hydrologists and water managers increasingly face challenges associated with extreme climatic events. At the same time, historic datasets for modeling contemporary and future hydrologic conditions are increasingly inadequate. Machine learning is one promising technological tool for navigating the challenges of understanding and managing contemporary hydrological systems. However, in addition to the technical challenges associated with effectively leveraging ML for understanding subsurface hydrological processes, practitioner skepticism and hesitancy surrounding ML presents a significant barrier to adoption of ML technologies among practitioners. In this paper, we discuss an educational application we have developed—Sandtank-ML—to be used as a training and educational tool aimed at building user confidence and supporting adoption of ML technologies among water managers. We argue that supporting the adoption of ML methods and technologies for subsurface hydrological investigations and management requires not only the development of robust technologic tools and approaches, but educational strategies and tools capable of building confidence among diverse users.

The Importance of Monitoring River Water Discharge

River discharge time series, originally recorded to anticipate floods and water scarcity, later became indispensable to design hydroelectric dams. Presently, discharge monitoring aids in detecting climatic and environmental change, because the discharge and quality of river water are functions of many climatic, biological, geological, and topographic variables coexisting in the basin. Climate change is altering the atmospheric precipitation distribution pattern-both, in time and space-as well as the occurrence of extreme climatic events. It is important the global upgrading of river gauging networks to unveil hydrological trends and changing atmospheric patterns. In so doing, discharge monitoring stations–and the resulting time series-may be, as well, invaluable in revealing the role played by significant environmental variables.

Tree Mortality Risks Under Climate Change in Europe: Assessment of Silviculture Practices and Genetic Conservation Networks

General Context: Climate change can positively or negatively affect abiotic and biotic drivers of tree mortality. Process-based models integrating these climatic effects are only seldom used at species distribution scale.Objective: The main objective of this study was to investigate the multi-causal mortality risk of five major European forest tree species across their distribution range from an ecophysiological perspective, to quantify the impact of forest management practices on this risk and to identify threats on the genetic conservation network.Methods: We used the process-based ecophysiological model CASTANEA to simulate the mortality risk of Fagus sylvatica, Quercus petraea, Pinus sylvestris, Pinus pinaster, and Picea abies under current and future climate conditions, while considering local silviculture practices. The mortality risk was assessed by a composite risk index (CRIM) integrating the risks of carbon starvation, hydraulic failure and frost damage. We took into account extreme climatic events with the CRIMmax, computed as the maximum annual value of the CRIM.Results: The physiological processes' contributions to CRIM differed among species: it was mainly driven by hydraulic failure for P. sylvestris and Q. petraea, by frost damage for P. abies, by carbon starvation for P. pinaster, and by a combination of hydraulic failure and frost damage for F. sylvatica. Under future climate, projections showed an increase of CRIM for P. pinaster but a decrease for P. abies, Q. petraea, and F. sylvatica, and little variation for P. sylvestris. Under the harshest future climatic scenario, forest management decreased the mean CRIM of P. sylvestris, increased it for P. abies and P. pinaster and had no major impact for the two broadleaved species. By the year 2100, 38–90% of the European network of gene conservation units are at extinction risk (CRIMmax=1), depending on the species.Conclusions: Using a process-based ecophysiological model allowed us to disentangle the multiple drivers of tree mortality under current and future climates. Taking into account the positive effect of increased CO2 on fertilization and water use efficiency, average mortality risk may increase or decrease in the future depending on species and sites. However, under extreme climatic events, our process-based projections are as pessimistic as those obtained using bioclimatic niche models.

Contrasting climate influences on Nothofagus pumilio establishment along elevational gradients

Predicted warmer temperatures and more frequent extreme climatic events in the southern Andes will affect the dynamics of the Patagonian forests. These environmental changes may differentially alter the probability of Nothofagus pumilio establishment across its altitudinal range of distribution. We monitored fruit rain, seedling emergence and survival at the lower and upper elevation boundaries of N. pumilio forests in Santa Cruz (49° 22'S − 72º 56' W), Argentina. From 2012 to 2018, recruitment and mortality were evaluated biannually in the field. Seedling establishment was tested in relation to drought, based on the SPEI (Standardized Precipitation Evapotranspiration Index), and changes in elevation. Fruit rain was consistently higher at low elevation and the abundance of fruits was not affected by drought intensity. Seedling emergence was ~ 11 to 19 times larger at the upper forest boundary, in particular during years characterized by warm-dry climatic conditions in spring-early summer. In contrast, seedling abundance was ~ 3 times larger at low elevations during relatively cold-wet growing seasons. Over the period 2012 to 2018, dominated by dry-warm spring and summers, survival probability curves for seedlings and juvenile trees were higher at upper than lower elevations. Our results show contrasting effects of climate on tree establishment at the elevation limits, with positive and negative drought effects at high and low elevations, respectively. Predicted increase of extreme drought events during the XXI century could be detrimental for N. pumilio establishment at dry, low-elevation forests.