Assessing uncertainties in climate change adaptation and land management

The entire cascade of scenario generation, global and regional climate modeling, as well as concrete measures towards climate adaptation are subject to uncertainties. An exact prediction of how the climate will change in the coming years, and how it will affect land use, is not possible. There is thus a perceived need to identify ways via which uncertainties can be addressed. Based on the need to address the research gap in this area, this paper reports the findings of a study on uncertainty in a climate change adaptation context, and how it is perceived. It consists of a multi-stakeholder survey among climate change professionals, including academic staff at universities, representatives from international agencies, members of NGOs, policymakers, and representatives of industry from 50 countries, including a balanced representation of industrialized and developing nations. The results obtained suggest that uncertainties are often a hindrance to engagement in climate change adaptation efforts, and to land management. Furthermore, there is a range of tools to reduce climate change adaptation uncertainties, whose deployment may help to address them. The paper concludes by providing a list of lessons learned and suggestions as to how uncertainty can be better communicated, and by doing so, how a reduction in the levels of climate change vulnerability may be achieved, and how land management may be fostered

Resistance Mechanism of <i>Plutella xylostella</i> (L.) Associated with Amino Acid Substitutions in Acetylcholinesterase-1: Insights from Homology Modeling, Docking and Molecular Dynamic Simulation

Plutella xylostella, a destructive crucifer pest, can rapidly develop resistance to most classes of pesticides. This study investigated the molecular resistance mechanisms to chlorpyrifos, an organophosphate pesticide. Two P. xylostella genes, ace1 and ace2, were described. The nucleotide sequence results revealed no variation in ace2, while the resistant strain (Kar-R) had four amino acid alterations in ace1, two of which (A298S and G324A) were previously shown to confer organophosphate resistance in P. xylostella. In the present study, the 3D model structures of both the wild-type (Gu-S) and mutant (Kar-R) of P. xylostella ace1 strains were studied through molecular dynamics (MDs) simulations and molecular docking. Molecular dynamics simulations of RMSD revealed less structural deviation in the ace1 mutant than in its wild-type counterpart. Higher flexibility in the 425–440 amino acid region in the mutant active site (Glu422 and Acyl pocket) increased the active site’s entropy, reducing the enzyme’s affinity for the inhibitors. Gene expression analysis revealed that the relative transcription levels of ace1 were significantly different in the Kar-R strain compared with the Gu-S strain. This study enhances the understanding of the mechanisms governing ace1′s resistance to insecticide and provides essential insights for new insecticides as well as valuable insights into environmentally conscious pest management techniques

Barriers, Challenges, and Requirements for ICT Usage among Sub-Assistant Agricultural Officers in Bangladesh: Toward Sustainability in Agriculture

The present work is the first detailed study of sub-assistant agricultural officers (SAAOs), who are key players in delivering agriculture extension services in Bangladesh. We determined the status of information and communication technology (ICT) usage, knowledge gaps, approaches and tools for information delivery, barriers and obstacles to ICT usage, requirements for adoption, and possible solutions for efficient agriculture extension advisory services. We surveyed key respondents (SAAOs, n = 117) from nine sub-districts under the six administrative districts of Bangladesh with a semi-structured questionnaire. We found that 73.2% of all extension officers had basic knowledge of ICT. We observed that the most effective tool for information dissemination was field visits (90.90%, Moulvibazar district) and the most frequent extension approach was training and workshops (77.31%, Dhaka district). The best sources for information collection were broadcast media and social media. While delivering information, difficulty was found due to technical obstacles in Gazipur district, Rajshahi district, Sylhet district, and Dhaka district among 60% to 70% of SAAOs. However, farmers&rsquo; ignorance was reported in both Feni district and Moulvibazar district (36.36%). A shortage of computers in Gazipur district (56.25%) was an essential barrier to ICT usage for extension services. A major challenge in using ICT applications in Dhaka district was inadequate training support (64.51%). Mobile devices, internet connectivity, updated ICT applications, and a farmers&rsquo; database were the most important supports needed for the SAAO&rsquo;s skilled advisory activities. In conclusion, our results and recommendations will help to redesign policies to improve infrastructure and allocate funding for capacity and skill development and ICT-based innovations in this sector to achieve sustainable extension and advisory services and attain food security in Bangladesh

Genetic mapping of folate QTLs using a segregated population in maize.

As essential B vitamin for humans, folates accumulation in edible parts of crops, such as maize kernels, is of great importance for human health. But its breeding is always limited by the prohibitive cost of folate profiling. The molecular breeding is a more executable and efficient way for folate fortification, but is limited by the molecular knowledge of folate regulation. Here we report the genetic mapping of folate quantitative trait loci (QTLs) using a segregated population crossed by two maize lines, one high in folate (GEMS31) and the other low in folate (DAN3130). Two folate QTLs on chromosome 5 were obtained by the combination of F2 whole-exome sequencing and F3 kernel-folate profiling. These two QTLs had been confirmed by bulk segregant analysis using F6 pooled DNA and F7 kernel-folate profiling, and were overlapped with QTLs identified by another segregated population. These two QTLs contributed 41.6% of phenotypic variation of 5-formyltetrahydrofolate, the most abundant storage form among folate derivatives in dry maize grains, in the GEMS31×DAN3130 population. Their fine mapping and functional analysis will reveal details of folate metabolism, and provide a basis for marker-assisted breeding aimed at the enrichment of folates in maize kernels

Genetic mapping of folate QTLs using a segregated population in maize

peer reviewedAs essential B vitamin for humans, folates accumulation in edible parts of crops, such as maize kernels, is of great importance for human health. But its breeding is always limited by the prohibitive cost of folate profiling. The molecular breeding is a more executable and efficient way for folate fortification, but is limited by the molecular knowledge of folate regulation. Here we report the genetic mapping of folate quantitative trait loci (QTLs) using a segregated population crossed by two maize lines, one high in folate (GEMS31) and the other low in folate (DAN3130). Two folate QTLs on chromosome 5 were obtained by the combination of F2 whole-exome sequencing and F3 kernel-folate profiling. These two QTLs had been confirmed by bulk segregant analysis using F6 pooled DNA and F7 kernel-folate profiling, and were overlapped with QTLs identified by another segregated population. These two QTLs contributed 41.6% of phenotypic variation of 5-formyltetrahydrofolate, the most abundant storage form among folate derivatives in dry maize grains, in the GEMS31×DAN3130 population. Their fine mapping and functional analysis will reveal details of folate metabolism, and provide a basis for marker-assisted breeding aimed at the enrichment of folates in maize kernels

Toward food waste reduction at universities

PeerReviewe

Assessing Uncertainties in Climate Change Adaptation and Land Management

The entire cascade of scenario generation, global and regional climate modeling, as well as concrete measures towards climate adaptation are subject to uncertainties. An exact prediction of how the climate will change in the coming years, and how it will affect land use, is not possible. There is thus a perceived need to identify ways via which uncertainties can be addressed. Based on the need to address the research gap in this area, this paper reports the findings of a study on uncertainty in a climate change adaptation context, and how it is perceived. It consists of a multi-stakeholder survey among climate change professionals, including academic staff at universities, representatives from international agencies, members of NGOs, policymakers, and representatives of industry from 50 countries, including a balanced representation of industrialized and developing nations. The results obtained suggest that uncertainties are often a hindrance to engagement in climate change adaptation efforts, and to land management. Furthermore, there is a range of tools to reduce climate change adaptation uncertainties, whose deployment may help to address them. The paper concludes by providing a list of lessons learned and suggestions as to how uncertainty can be better communicated, and by doing so, how a reduction in the levels of climate change vulnerability may be achieved, and how land management may be fostered

Deploying artificial intelligence for climate change adaptation

Artificial Intelligence (AI) is believed to have a significant potential use in tackling climate change. This paper explores the connections between AI and climate change research as a whole and its usefulness in climate change adaptation efforts in particular. Using a systematic review of the literature on applications of AI for climate change adaptation and a questionnaire survey of a multinational and interdisciplinary team of climate change researchers, this paper shows the various means via which AI can support research on climate change in diverse regions, and contribute to efforts towards climate change adaptation. The surveyed articles are classified under nine areas, e.g., Global/Earth Related; Water-related Issues and agriculture, 95% of which are related to adaptation. The areas that have attracted the most studies about AI applications are water-related management issues (38%). In terms of the survey results, the most robust agreements were noted concerning the capacity of digitisation and AI to strengthen governance practices and afford policy coherence in climate change. Evidence gathered in the study suggests that, provided that due care is taken, the use of AI can provide a welcome support to global efforts to better understand and handle the many challenges associated with a changing climate