Mississippi State University

About: Mississippi State University is a education organization based out in Starkville, Mississippi, United States. It is known for research contribution in the topics: Population & Catfish. The organization has 14115 authors who have published 28594 publications receiving 700030 citations. The organization is also known as: The Mississippi State University of Agriculture and Applied Science & Mississippi State University of Agriculture and Applied Science.

The importance of correcting for sampling bias in MaxEnt species distribution models

Abstract: Aim Advancement in ecological methods predicting species distributions is a crucial precondition for deriving sound management actions. Maximum entropy (MaxEnt) models are a popular tool to predict species distributions, as they are considered able to cope well with sparse, irregularly sampled data and minor location errors. Although a fundamental assumption of MaxEnt is that the entire area of interest has been systematically sampled, in practice, MaxEnt models are usually built from occurrence records that are spatially biased towards better-surveyed areas. Two common, yet not compared, strategies to cope with uneven sampling effort are spatial filtering of occurrence data and background manipulation using environmental data with the same spatial bias as occurrence data. We tested these strategies using simulated data and a recently collated dataset on Malay civet Viverra tangalunga in Borneo. Location Borneo, Southeast Asia. Methods We collated 504 occurrence records of Malay civets from Borneo of which 291 records were from 2001 to 2011 and used them in the MaxEnt analysis (baseline scenario) together with 25 environmental input variables. We simulated datasets for two virtual species (similar to a range-restricted highland and a lowland species) using the same number of records for model building. As occurrence records were biased towards north-eastern Borneo, we investigated the efficacy of spatial filtering versus background manipulation to reduce overprediction or underprediction in specific areas. Results Spatial filtering minimized omission errors (false negatives) and commission errors (false positives). We recommend that when sample size is insufficient to allow spatial filtering, manipulation of the background dataset is preferable to not correcting for sampling bias, although predictions were comparatively weak and commission errors increased. Main Conclusions We conclude that a substantial improvement in the quality of model predictions can be achieved if uneven sampling effort is taken into account, thereby improving the efficacy of species conservation planning.

Changes to taxonomy and the International Code of Virus Classification and Nomenclature ratified by the International Committee on Taxonomy of Viruses (2017)

Abstract: This article lists the changes to virus taxonomy approved and ratified by the International Committee on Taxonomy of Viruses (ICTV) in March 2017.

Reducing the Risks of Herbicide Resistance: Best Management Practices and Recommendations

Abstract: Herbicides are the foundation of weed control in commercial crop-production systems. However, herbicide-resistant (HR) weed populations are evolving rapidly as a natural response to selection pressure imposed by modern agricultural management activities. Mitigating the evolution of herbicide resistance depends on reducing selection through diversification of weed control techniques, minimizing the spread of resistance genes and genotypes via pollen or propagule dispersal, and eliminating additions of weed seed to the soil seedbank. Effective deployment of such a multifaceted approach will require shifting from the current concept of basing weed management on single-year economic thresholds.

Encouraging Citizen Adoption of E-Government by Building Trust

Abstract: The growing interest in e-Government raises the question of how governments can increase citizen adoption and usage of their online government services. e-Government becomes especially important given its potential to reduce costs and improve service compared with alternative traditional modes. Citizen trust is proposed to be an important catalyst of e-Government adoption. By investigating online tax services, already available and used extensively in the West, we propose several ways in which governments can increase citizen trust and thus encourage the adoption of this new and potentially significant mode of government service. The proposed e-Government adoption model also takes in account issues of cultural variables, risk, control and technology acceptance.Institution-based trust, such as an independent judicial system with appropriate legal powers, is proposed to be the major tactic to build trust in e-Government. In addition, among new users of online government services, characteristic-based and cognitive-based antecedents should be crucial; general psychological dispositions and knowledge of the process should also engender trust. Among experienced users, on the other hand, it is suggested that the nature of previous interactions with the e-Government system should be the major predictor of trust, and hence of continued use. These propositions are elucidated, as they apply to different cultures and to high-intrusive versus low-intrusive government services. This study has practical implications for the design of mechanisms for the adoption of e-Government.

Abscisic Acid and Abiotic Stress Tolerance in Crop Plants

Abstract: Abiotic stress is a primary threat to fulfill the demand of agricultural production to feed the world in coming decades. Plants reduce growth and development process during stress conditions, which ultimately affect the yield. In stress conditions, plants develop various stress mechanism to face the magnitude of stress challenges, although that is not enough to protect them. Therefore, many strategies have been used to produce abiotic stress tolerance crop plants, among them, ABA (abscisic acid) phytohormone engineering could be one of the methods of choice. ABA is an isoprenoid phytohormone, which regulates various physiological processes ranging from stomatal opening to protein storage and provides adaptation to many stresses like drought, salt, and cold stresses. ABA is also called an important messenger that acts as the signaling mediator for regulating the adaptive response of plants to different environmental stress conditions. In this review, we will discuss the role of ABA in response to abiotic stress at the molecular level and ABA signaling. The review also deals with the effect of ABA in respect to gene expression.