Eco‐efficiency as a strategy for optimizing the sustainability of pest management

Agricultural industrialization and the subsequent reliance on pesticides has resulted in numerous unintended consequences, such as impacts upon the environment and by extension human health. Eco‐efficiency is a strategy for sustainably increasing production, while simultaneously decreasing these externalities on ecological systems. Eco‐efficiency is defined as the ratio of production to environmental impacts. It has been widely adopted to improve chemical production, but we investigate the challenges of applying eco‐efficiency to pesticide use. Eco‐efficiency strategies include technological innovation, investment in research and development, improvement of business processes, and accounting for market forces. These components are often part of integrated pest management (IPM) systems that include alternatives to pesticides, but its implementation is often thwarted by commercial realities and technical challenges. We propose the creation and adoption of an eco‐efficiency index for pesticide use so that the broad benefits of eco‐efficient strategies such as IPM can be more readily quantified. We propose an index based upon the ratio of crop yield to a risk quotient (RQ) calculated from pesticide toxicity. Eco‐efficiency is an operational basis for optimizing pest management for sustainability. It naturally favors adoption of IPM and should be considered by regulators, researchers, and practitioners involved in pest management. © 2019 Society of Chemical Industry     

Identification and validation of cold responsive microRNAs of <Emphasis Type="Italic">Hevea brasiliensis</Emphasis> using high throughput sequencing

Cold stress is one of the major abiotic factors that influence the productivity and geographical distribution of many agriculturally important crops like Hevea brasiliensis. Cultivation of H. brasiliensis in India is being extended to northeastern regions, where low temperature during winter adversely affects its survival, growth, and productivity. Developing cold-tolerant genotypes is a primary requisite to maximize the productivity under such challenging environmental conditions. However, lack of methods for early evaluation of cold tolerance in the newly developed clones and the extensive time required for assessing their tolerance in the field are major constraints for clonal selection. The present study was initiated with an objective to identify and characterize cold stress responsive miRNAs from H. brasiliensis that show stronger association with cold tolerance. Next generation sequencing using Illumina HiSeq method revealed the expression of 21 and 29 conserved miRNA (from clone RRIM 600) families in cold-stressed and control samples, respectively. Forty-two novel miRNAs were identified from this study. Upon differential expression analysis, eight conserved miRNAs were found commonly expressed in both the samples. When expression analyses were performed subsequently with six selected miRNAs in two Hevea clones (viz. RRII 105 and RRIM 600), miR169 showed a strong association with cold tolerance. miRNAs such as miR482 and miR159 also exhibited association with cold tolerance. This study suggests the possibility of employing these miRNAs as markers for cold tolerance after validation in more number of genotypes with varying levels of cold tolerance.     

Marine Anticancer Agents: An Overview with a Particular Focus on Their Chemical Classes

The marine environment is a rich source of biologically active molecules for the treatment of human diseases, especially cancer. The adaptation to unique environmental conditions led marine organisms to evolve different pathways than their terrestrial counterparts, thus producing unique chemicals with a broad diversity and complexity. So far, more than 36,000 compounds have been isolated from marine micro- and macro-organisms including but not limited to fungi, bacteria, microalgae, macroalgae, sponges, corals, mollusks and tunicates, with hundreds of new marine natural products (MNPs) being discovered every year. Marine-based pharmaceuticals have started to impact modern pharmacology and different anti-cancer drugs derived from marine compounds have been approved for clinical use, such as: cytarabine, vidarabine, nelarabine (prodrug of ara-G), fludarabine phosphate (pro-drug of ara-A), trabectedin, eribulin mesylate, brentuximab vedotin, polatuzumab vedotin, enfortumab vedotin, belantamab mafodotin, plitidepsin, and lurbinectedin. This review focuses on the bioactive molecules derived from the marine environment with anticancer activity, discussing their families, origin, structural features and therapeutic use.     

Evidence for genetic distinction among sympatric ecotypes of Arctic char (Salvelinus alpinus) in south‐western Alaskan lakes

Resource polymorphism may play an important role in the process of speciation. The Arctic char (Salvelinus alpinus) exhibits great phenotypic and genetic diversity across its range, making it an ideal species for studies of resource polymorphism and divergence. Here, we investigated genetic variation at 11 microsatellite loci among 287 Arctic char from five isolated yet proximate postglacial lakes in south‐western Alaska that were previously examined for resource polymorphism. Significant differences in pairwise F_ST were detected among all lakes (range from 0.05 to 0.28, all P < 0.02). In one lake (Lower Tazimina Lake), we found evidence for two genetic groups of char and for significant differences in the distribution of microsatellite variability among at least two of the three previously described body size morphotypes (‘large’‐, ‘medium’‐, and ‘small’‐bodied char; maximum F_ST = 0.09; differences in admixture proportions). We also found a significant association between genetic admixture proportions and gill raker counts among body size morphs (r = ?0.73, P < 0.001). Our data represent the first record of genetically distinct sympatric morphs of Arctic char in Alaska and provide further evidence that differences in morphology associated with feeding (gill rakers) and growth trajectories reflect niche diversification and promote genetic divergence in Holarctic populations of Arctic char.     

The delay of flowering time in almond: a review of the combined effect of adaptation,mutation and breeding

Regulation of flowering time in almond, as in other Prunus species, is a complex process involving both chill and heat requirements. Following exposure to appropriate consecutive periods of cold and warm temperatures, the buds break dormancy and sprout or flower depending on bud type. To maximize flowering and subsequent vegetative growth and fruit set, chilling and ensuing warm temperature requirements have to be fully satisfied. Because of its potential for very early flowering, flowering time in almond is a major determinant of its adaptation to new environments. In colder regions, Late-flowering is often necessary to avoid frost damage during and just after flowering. Consequently, the selection of delayed flowering times remains an important objective in almond improvement programs. Flowering time is considered a quantitative though highly heritable trait. In addition, a dominant gene (Late flowering, Lb), originally identified in a spontaneous mutation of the Californian almond cultivar ‘Nonpareil’, was also described. The objective of this review is a comparative analysis of the effects of regional adaptation, breeding and mutation on the delay of flowering time in new almond cultivars. Findings indicate that the adaptation of almonds from the Mediterranean basin to colder regions in Northern Europe and America has been mainly achieved through delayed flowering. These adapted late-flowering cultivars have usually been developed by selecting desired quantitative genes within each regional germplasm. Additional progress thus appears achievable with a more comprehensive understanding of the quantitative and qualitative genetics controlling this trait. The use of molecular markers for the early selection of genes conferring late flowering, including both spontaneous mutations as well as unique regional germplasm, should allow development of even later cultivars including ultra-late cultivars flowering as into April.     

A multi-method approach to delineate and validate migratory corridors

Context

Managers are faced with numerous methods for delineating wildlife movement corridors, and often must make decisions with limited data. Delineated corridors should be robust to different data and models.

Objectives

We present a multi-method approach for delineating and validating wildlife corridors using multiple data sources, which can be used conserve landscape connectivity. We used this approach to delineate and validate migration corridors for wildebeest (Connochaetes taurinus) in the Tarangire Ecosystem of northern Tanzania.

Methods

We used two types of locational data (distance sampling detections and GPS collar locations), and three modeling methods (negative binomial regression, logistic regression, and Maxent), to generate resource selection functions (RSFs) and define resistance surfaces. We compared two corridor detection algorithms (cost-distance and circuit theory), to delineate corridors. We validated corridors by comparing random and wildebeest locations that fell within corridors, and cross-validated by data type.

Results

Both data types produced similar RSFs. Wildebeest consistently selected migration habitat in flatter terrain farther from human settlements. Validation indicated three of the combinations of data type, modeling, and corridor detection algorithms (detection data with Maxent modeling, GPS collar data with logistic regression modeling, and GPS collar data with Maxent modeling, all using cost-distance) far outperformed the other seven. We merged the predictive corridors from these three data-method combinations to reveal habitat with highest probability of use.

Conclusions

The use of multiple methods ensures that planning is able to prioritize conservation of migration corridors based on all available information.