Institution
University of New Hampshire
Education•Durham, 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.
Topics: Population, Solar wind, Poison control, Magnetosphere, Heliosphere
Papers published on a yearly basis
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California Institute of Technology1, Virginia Institute of Marine Science2, Old Dominion University3, Stanford University4, Tokyo University of Information Sciences5, Centre national de la recherche scientifique6, Duke University7, Oregon State University8, University of Hawaii9, Max Planck Society10, University of New Hampshire11, Sao Paulo State University12, University of Connecticut13, Geophysical Fluid Dynamics Laboratory14, Goddard Space Flight Center15, Plymouth Marine Laboratory16, Nagasaki University17, University of East Anglia18, Lamont–Doherty Earth Observatory19, University of California, Irvine20, Monterey Bay Aquarium Research Institute21, University of Rome Tor Vergata22, National Oceanic and Atmospheric Administration23
TL;DR: The third primary production algorithm round robin (PPARR3) as discussed by the authors compares output from 24 models that estimate depth-integrated primary production from satellite measurements of ocean color, as well as seven general circulation models (GCMs) coupled with ecosystem or biogeochemical models.
Abstract: The third primary production algorithm round robin (PPARR3) compares output from 24 models that estimate depth-integrated primary production from satellite measurements of ocean color, as well as seven general circulation models (GCMs) coupled with ecosystem or biogeochemical models. Here we compare the global primary production fields corresponding to eight months of 1998 and 1999 as estimated from common input fields of photosynthetically-available radiation (PAR), sea-surface temperature (SST), mixed-layer depth, and chlorophyll concentration. We also quantify the sensitivity of the ocean-color-based models to perturbations in their input variables. The pair-wise correlation between ocean-color models was used to cluster them into groups or related output, which reflect the regions and environmental conditions under which they respond differently. The groups do not follow model complexity with regards to wavelength or depth dependence, though they are related to the manner in which temperature is used to parameterize photosynthesis. Global average PP varies by a factor of two between models. The models diverged the most for the Southern Ocean, SST under 10 degrees C, and chlorophyll concentration exceeding 1 mg Chlm(-3). Based on the conditions under which the model results diverge most, we conclude that current ocean-color-based models are challenged by high-nutrient low-chlorophyll conditions, and extreme temperatures or chlorophyll concentrations. The GCM-based models predict comparable primary production to those based on ocean color: they estimate higher values in the Southern Ocean, at low SST, and in the equatorial band, while they estimate lower values in eutrophic regions (probably because the area of high chlorophyll concentrations is smaller in the GCMs). Further progress in primary production modeling requires improved understanding of the effect of temperature on photosynthesis and better parameterization of the maximum photosynthetic rate. (c) 2006 Elsevier Ltd. All rights reserved.
635 citations
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TL;DR: In this article, the authors combine findings from 155 samples of more than 31,000 salespeople to test alternative models of antecedents and consequences of adaptive selling behavior (ASB) and customer orientation (CO).
Abstract: The authors combine findings from 155 samples of more than 31,000 salespeople to test alternative models of antecedents and consequences of adaptive selling behavior (ASB) and customer orientation (CO). A random-effects meta-analysis yields average values for 28 different correlations ranging from −.16 to .35, 19 of which are significant. Controlling for salesperson gender and selling experience, structural equation modeling indicates that ASB increases self-rated, manager-rated, and objective measures of performance, whereas CO increases only self-rated performance. Both ASB and CO increase job satisfaction. Tests of reciprocal relationships indicate that ASB increases CO and job satisfaction increases performance rather than vice versa. Selling experience increases performance but not job satisfaction, and saleswomen rate their performance and satisfaction slightly higher than salesmen do. The magnitudes of the relationships indicate that ASB and selling experience have greater effects than CO ...
633 citations
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University of New Hampshire1, Old Dominion University2, Eduardo Mondlane University3, Universiti Putra Malaysia4, Silliman University5, University of Maryland Center for Environmental Science6, University of the Philippines7, National Institute of Oceanography, India8, University of Chittagong9, University of Western Australia10, National Oceanic and Atmospheric Administration11, Hasanuddin University12, Virginia Institute of Marine Science13, Prince of Songkla University14, National Autonomous University of Mexico15, James Cook University16, University of Virginia17
TL;DR: For the first time, the probability of extinction is determined for the world’s seagrass species under the Categories and Criteria of the International Union for the Conservation of Nature (IUCN) Red List of Threatened Species.
629 citations
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TL;DR: Schimel et al. as discussed by the authors described a blueprint for more comprehensive coordination of various flux measurement and modeling activities into a global terrestrial monitoring network that will have direct relevance to the political decision making of global change.
629 citations
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University of Montana1, Pennsylvania State University2, University of Minnesota3, Oregon State University4, San Diego State University5, Harvard University6, University of California, Berkeley7, United States Forest Service8, University of New Hampshire9, Duke University10, University of Colorado Boulder11, University of Lethbridge12
TL;DR: The results of this study indicate that the current MODIS GPP algorithm shows reasonable spatial patterns and temporal variability across a diverse range of biomes and climate regimes.
Abstract: The Moderate Resolution Spectroradiometer (MODIS) sensor has provided near real-time estimates of gross primary production (GPP) since March 2000. We compare four years (2000 to 2003) of satellite-based calculations of GPP with tower eddy CO2 flux-based estimates across diverse land cover types and climate regimes. We examine the potential error contributions from meteorology, leaf area index (LAI)/fPAR, and land cover. The error between annual GPP computed from NASA's Data Assimilation Office's (DAO) and tower-based meteorology is 28%, indicating that NASA's DAO global meteorology plays an important role in the accuracy of the GPP algorithm. Approximately 62% of MOD15-based estimates of LAI were within the estimates based on field optical measurements, although remaining values overestimated site values. Land cover presented the fewest errors, with most errors within the forest classes, reducing potential error. Tower-based and MODIS estimates of annual GPP compare favorably for most biomes, although MODIS GPP overestimates tower-based calculations by 20%-30%. Seasonally, summer estimates of MODIS GPP are closest to tower data, and spring estimates are the worst, most likely the result of the relatively rapid onset of leaf-out. The results of this study indicate, however, that the current MODIS GPP algorithm shows reasonable spatial patterns and temporal variability across a diverse range of biomes and climate regimes. So, while continued efforts are needed to isolate particular problems in specific biomes, we are optimistic about the general quality of these data, and continuation of the MOD17 GPP product will likely provide a key component of global terrestrial ecosystem analysis, providing continuous weekly measurements of global vegetation production
628 citations
Authors
Showing all 9489 results
Name | H-index | Papers | Citations |
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Derek R. Lovley | 168 | 582 | 95315 |
Peter B. Reich | 159 | 790 | 110377 |
Jerry M. Melillo | 134 | 383 | 68894 |
Katja Klein | 129 | 1499 | 87817 |
David Finkelhor | 117 | 382 | 58094 |
Howard A. Stone | 114 | 1033 | 64855 |
James O. Hill | 113 | 532 | 69636 |
Tadayuki Takahashi | 112 | 932 | 57501 |
Howard Eichenbaum | 108 | 279 | 44172 |
John D. Aber | 107 | 204 | 48500 |
Andrew W. Strong | 99 | 563 | 42475 |
Charles T. Driscoll | 97 | 554 | 37355 |
Andrew D. Richardson | 94 | 282 | 32850 |
Colin A. Chapman | 92 | 491 | 28217 |
Nicholas W. Lukacs | 91 | 367 | 34057 |