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Institution

University of New Hampshire

EducationDurham, New Hampshire, United States
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.


Papers
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Journal ArticleDOI
TL;DR: The results reveal both important differences and similarities between universities.
Abstract: This article presents rates of violence against dating partners by students at 31 universities in 16 countries (5 in Asia and the Middle East, 2 in Australia-New Zealand, 6 in Europe, 2 in Latin America, 16 in North America). Assault and injury rates are presented for males and females at each of the 31 universities. At the median university, 29% of the students physically assaulted a dating partner in the previous 12 months (range = 17% to 45%) and 7% had physically injured a partner (range = 2% to 20%). The results reveal both important differences and similarities between universities. Perhaps the most important similarity is the high rate of assault perpetrated by both male and female students in all the countries.

541 citations

Journal ArticleDOI
TL;DR: The scientific objectives targeted by the SPP/FIELDS instrument, the instrument design itself, and the instrument concept of operations and planned data products are described.
Abstract: NASA’s Solar Probe Plus (SPP) mission will make the first in situ measurements of the solar corona and the birthplace of the solar wind. The FIELDS instrument suite on SPP will make direct measurements of electric and magnetic fields, the properties of in situ plasma waves, electron density and temperature profiles, and interplanetary radio emissions, amongst other things. Here, we describe the scientific objectives targeted by the SPP/FIELDS instrument, the instrument design itself, and the instrument concept of operations and planned data products.

540 citations

Journal ArticleDOI
TL;DR: It is found that stream denitrification produces N2O at rates that increase with stream water nitrate (NO3−) concentrations, but that <1% of denitrified N is converted to N1O, and it is suggested that increased stream NO3− loading stimulatesDenitrification and concomitant N2o production, but does not increase the N2 O yield.
Abstract: Nitrous oxide (N2O) is a potent greenhouse gas that contributes to climate change and stratospheric ozone destruction. Anthropogenic nitrogen (N) loading to river networks is a potentially important source of N2O via microbial denitrification that converts N to N2O and dinitrogen (N2). The fraction of denitrified N that escapes as N2O rather than N2 (i.e., the N2O yield) is an important determinant of how much N2O is produced by river networks, but little is known about the N2O yield in flowing waters. Here, we present the results of whole-stream 15N-tracer additions conducted in 72 headwater streams draining multiple land-use types across the United States. We found that stream denitrification produces N2O at rates that increase with stream water nitrate (NO3−) concentrations, but that <1% of denitrified N is converted to N2O. Unlike some previous studies, we found no relationship between the N2O yield and stream water NO3−. We suggest that increased stream NO3− loading stimulates denitrification and concomitant N2O production, but does not increase the N2O yield. In our study, most streams were sources of N2O to the atmosphere and the highest emission rates were observed in streams draining urban basins. Using a global river network model, we estimate that microbial N transformations (e.g., denitrification and nitrification) convert at least 0.68 Tg·y−1 of anthropogenic N inputs to N2O in river networks, equivalent to 10% of the global anthropogenic N2O emission rate. This estimate of stream and river N2O emissions is three times greater than estimated by the Intergovernmental Panel on Climate Change.

536 citations

Journal ArticleDOI
TL;DR: A new compilation of Greenland bed topography that assimilates seafloor bathymetry and ice thickness data through a mass conservation approach is presented, yielding major improvements over previous data sets, particularly in the marine‐terminating sectors of northwest and southeast Greenland.
Abstract: Greenland's bed topography is a primary control on ice flow, grounding line migration, calving dynamics, and subglacial drainage. Moreover, fjord bathymetry regulates the penetration of warm Atlantic water (AW) that rapidly melts and undercuts Greenland's marine-terminating glaciers. Here we present a new compilation of Greenland bed topography that assimilates seafloor bathymetry and ice thickness data through a mass conservation approach. A new 150 m horizontal resolution bed topography/bathymetric map of Greenland is constructed with seamless transitions at the ice/ocean interface, yielding major improvements over previous data sets, particularly in the marine-terminating sectors of northwest and southeast Greenland. Our map reveals that the total sea level potential of the Greenland ice sheet is 7.42 ± 0.05 m, which is 7 cm greater than previous estimates. Furthermore, it explains recent calving front response of numerous outlet glaciers and reveals new pathways by which AW can access glaciers with marine-based basins, thereby highlighting sectors of Greenland that are most vulnerable to future oceanic forcing.

535 citations

Journal ArticleDOI
TL;DR: In this paper, the lognormal distribution is presented as a useful model for bio-optical variability at a variety of spatial and temporal scales, and a parametric statistical framework is presented for using the LDA model to assess the effects of heterogeneity and scale on closure.
Abstract: The lognormal distribution is presented as a useful model for bio-optical variability at a variety of spatial and temporal scales. A parametric statistical framework is presented for using the lognormal model to assess the effects of heterogeneity and scale on closure. Variability at small scales affects but is unresolved by large-scale measurements. An assumed lognormal distribution allows one to integrate over small-scale variability to predict large-scale measurements. Examples are presented to demonstrate how knowledge of the variance can be incorporated into models to relate measurements made at different scales.

534 citations


Authors

Showing all 9489 results

NameH-indexPapersCitations
Derek R. Lovley16858295315
Peter B. Reich159790110377
Jerry M. Melillo13438368894
Katja Klein129149987817
David Finkelhor11738258094
Howard A. Stone114103364855
James O. Hill11353269636
Tadayuki Takahashi11293257501
Howard Eichenbaum10827944172
John D. Aber10720448500
Andrew W. Strong9956342475
Charles T. Driscoll9755437355
Andrew D. Richardson9428232850
Colin A. Chapman9249128217
Nicholas W. Lukacs9136734057
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202351
2022183
20211,148
20201,128
20191,140
20181,089