University of New Hampshire

About: University of New Hampshire is a education organization based out in Durham, New Hampshire, United States. It is known for research contribution in the topics: Population & Solar wind. The organization has 9379 authors who have published 24025 publications receiving 1020112 citations. The organization is also known as: UNH.

Structure and evolution of teleost mitochondrial control regions

Abstract: We amplified and sequenced the mitochondrial control region from 23 species representing six families of teleost fish. The length of this segment is highly variable among even closely related species due to the presence of tandemly repeated sequences and large insertions. The position of the repetitive sequences suggests that they arise during replication both near the origin of replication and at the site of termination of the D-loop strand. Many of the conserved sequence blocks (CSBs) observed in mammals are also found among fish. In particular, the mammalian CSB-D is present in all of the fish species studied. Study of potential secondary structures of RNAs from the conserved regions provides little insight into the functional constraints on these regions. The variable structure of these control regions suggests that particular care should be taken to identify the most appropriate segment for studies of intraspecific variation.

Type-A Arabidopsis response regulators are partially redundant negative regulators of cytokinin signaling.

Abstract: Type-A Arabidopsis (Arabidopsis thaliana) response regulators (ARRs) are a family of 10 genes that are rapidly induced by cytokinin and are highly similar to bacterial two-component response regulators. We have isolated T-DNA insertions in six of the type-A ARRs and constructed multiple insertional mutants, including the arr3,4,5,6,8,9 hextuple mutant. Single arr mutants were indistinguishable from the wild type in various cytokinin assays; double and higher order arr mutants showed progressively increasing sensitivity to cytokinin, indicating functional overlap among type-A ARRs and that these genes act as negative regulators of cytokinin responses. The induction of cytokinin primary response genes was amplified in arr mutants, indicating that the primary response to cytokinin is affected. Spatial patterns of ARR gene expression were consistent with partially redundant function of these genes in cytokinin signaling. The arr mutants show altered red light sensitivity, suggesting a general involvement of type-A ARRs in light signal transduction. Further, morphological phenotypes of some arr mutants suggest complex regulatory interactions and gene-specific functions among family members.

Rapid local acceleration of relativistic radiation-belt electrons by magnetospheric chorus

Abstract: Recent analysis of satellite data obtained during the 9 October 2012 geomagnetic storm identified the development of peaks in electron phase space density, which are compelling evidence for local electron acceleration in the heart of the outer radiation belt, but are inconsistent with acceleration by inward radial diffusive transport. However, the precise physical mechanism responsible for the acceleration on 9 October was not identified. Previous modelling has indicated that a magnetospheric electromagnetic emission known as chorus could be a potential candidate for local electron acceleration, but a definitive resolution of the importance of chorus for radiation-belt acceleration was not possible because of limitations in the energy range and resolution of previous electron observations and the lack of a dynamic global wave model. Here we report high-resolution electron observations obtained during the 9 October storm and demonstrate, using a two-dimensional simulation performed with a recently developed time-varying data-driven model, that chorus scattering explains the temporal evolution of both the energy and angular distribution of the observed relativistic electron flux increase. Our detailed modelling demonstrates the remarkable efficiency of wave acceleration in the Earth's outer radiation belt, and the results presented have potential application to Jupiter, Saturn and other magnetized astrophysical objects.

A method for scaling vegetation dynamics: the ecosystem demography model (ed)

Abstract: The problem of scale has been a critical impediment to incorporating im- portant fine-scale processes into global ecosystem models. Our knowledge of fine-scale physiological and ecological processes comes from a variety of measurements, ranging from forest plot inventories to remote sensing, made at spatial resolutions considerably smaller than the large scale at which global ecosystem models are defined. In this paper, we describe a new individual-based, terrestrial biosphere model, which we label the eco- system demography model (ED). We then introduce a general method for scaling stochastic individual-based models of ecosystem dynamics (gap models) such as ED to large scales. The method accounts for the fine-scale spatial heterogeneity within an ecosystem caused by stochastic disturbance events, operating at scales down to individual canopy-tree-sized gaps. By conditioning appropriately on the occurrence of these events, we derive a size- and age-structured (SAS) approximation for the first moment of the stochastic ecosystem model. With this approximation, it is possible to make predictions about the large scales of interest from a description of the fine-scale physiological and population-dynamic pro- cesses without simulating the fate of every plant individually. We use the SAS approxi- mation to implement our individual-based biosphere model over South America from 15 8 Nt o1 5 8S, showing that the SAS equations are accurate across a range of environmental conditions and resulting ecosystem types. We then compare the predictions of the biosphere model to regional data and to intensive data at specific sites. Analysis of the model at these sites illustrates the importance of fine-scale heterogeneity in governing large-scale eco- system function, showing how population and community-level processes influence eco- system composition and structure, patterns of aboveground carbon accumulation, and net ecosystem production.