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Institution

Oregon State University

EducationCorvallis, Oregon, United States
About: Oregon State University is a education organization based out in Corvallis, Oregon, United States. It is known for research contribution in the topics: Population & Climate change. The organization has 28192 authors who have published 64044 publications receiving 2634108 citations. The organization is also known as: Oregon Agricultural College & OSU.


Papers
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Journal ArticleDOI
TL;DR: In this article, a food-web model was proposed to estimate the production of sinking zooplankton feces and algal aggregates comprising the sinking particle flux at the base of the euphotic zone.
Abstract: The export of organic carbon from the surface ocean by sinking particles is an important, yet highly uncertain, component of the global carbon cycle. Here we introduce a mechanistic assessment of the global ocean carbon export using satellite observations, including determinations of net primary production and the slope of the particle size spectrum, to drive a food-web model that estimates the production of sinking zooplankton feces and algal aggregates comprising the sinking particle flux at the base of the euphotic zone. The synthesis of observations and models reveals fundamentally different and ecologically consistent regional-scale patterns in export and export efficiency not found in previous global carbon export assessments. The model reproduces regional-scale particle export field observations and predicts a climatological mean global carbon export from the euphotic zone of ~6 Pg C yr−1. Global export estimates show small variation (typically < 10%) to factor of 2 changes in model parameter values. The model is also robust to the choices of the satellite data products used and enables interannual changes to be quantified. The present synthesis of observations and models provides a path for quantifying the ocean's biological pump.

358 citations

Journal ArticleDOI
TL;DR: Of high importance is the identification of a widely applicable set of transferability metrics, with appropriate tools to quantify the sources and impacts of prediction uncertainty under novel conditions.
Abstract: Predictive models are central to many scientific disciplines and vital for informing management in a rapidly changing world However, limited understanding of the accuracy and precision of models transferred to novel conditions (their ‘transferability’) undermines confidence in their predictions Here, 50 experts identified priority knowledge gaps which, if filled, will most improve model transfers These are summarized into six technical and six fundamental challenges, which underlie the combined need to intensify research on the determinants of ecological predictability, including species traits and data quality, and develop best practices for transferring models Of high importance is the identification of a widely applicable set of transferability metrics, with appropriate tools to quantify the sources and impacts of prediction uncertainty under novel conditions

358 citations

Journal ArticleDOI
TL;DR: In this article, the authors propose a framework that unifies the central aims of conservation and fishery management, while meeting other human needs such as the provision of ecosystem services (e.g., maintenance of coastal water quality, shoreline protection, and recreational opportunities).
Abstract: Marine reserves are being established worldwide in response to a growing recognition of the conservation crisis that is building in the oceans. However, designation of reserves has been largely opportunistic, or protective measures have been implemented (often overlapping and sometimes in conflict) by different entities seeking to achieve dif- ferent ends. This has created confusion among both users and enforcers, and the proliferation of different measures provides a false sense of protection where little is offered. This paper sets out a procedure grounded in current understanding of ecological processes, that allows the evaluation and selection of reserve sites in order to develop functional, interconnected networks of fully protected reserves that will fulfill multiple objectives. By fully protected we mean permanently closed to fishing and other resource extraction. We provide a frame- work that unifies the central aims of conservation and fishery management, while also meeting other human needs such as the provision of ecosystem services (e.g., maintenance of coastal water quality, shoreline protection, and recreational opportunities). In our scheme, candidate sites for reserves are evaluated against 12 criteria focused toward sustaining the biological integrity and productivity of marine systems at both local and regional scales. While a limited number of sites will be indispensable in a network, many will be of similar value as reserves, allowing the design of numerous alternative, biologically adequate net- works. Devising multiple network designs will help ensure that ecological functionality is preserved throughout the socioeconomic evaluation process. Too often, socioeconomic cri- teria have dominated the process of reserve selection, potentially undermining their efficacy. We argue that application of biological criteria must precede and inform socioeconomic evaluation, since maintenance of ecosystem functioning is essential for meeting all of the goals for reserves. It is critical that stakeholders are fully involved throughout this process. Application of the proposed criteria will lead to networks whose multifunctionality will help unite the objectives of different management entities, so accelerating progress toward improved stewardship of the oceans.

358 citations

Journal ArticleDOI
TL;DR: In this paper, an Oregon andic soil was sequentially density fractionated at 1.65, 1.85, 2.28, and 2.55 cm −3 and analyzed the six fractions for measures of organic matter and mineral phase properties.
Abstract: In mineral soil, organic matter (OM) accumulates mainly on and around surfaces of silt- and clay-size particles. When fractionated according to particle density, C and N concentration (per g fraction) and C/N of these soil organo-mineral particles decrease with increasing particle density across soils of widely divergent texture, mineralogy, location, and management. The variation in particle density is explained potentially by two factors: (1) a decrease in the mass ratio of organic to mineral phase of these particles, and (2) variations in density of the mineral phase. The first explanation implies that the thickness of the organic accumulations decreases with increasing particle density. The decrease in C/N can be explained at least partially by especially stable sorption of nitrogenous N-containing compounds (amine, amide, and pyrrole) directly to mineral surfaces, a phenomenon well documented both empirically and theoretically. These peptidic compounds, along with ligand-exchanged carboxylic compounds, could then form a stable inner organic layer onto which other organics could sorb more readily than onto the unconditioned mineral surfaces (“onion” layering model). To explore mechanisms underlying this trend in C concentration and C/N with particle density, we sequentially density fractionated an Oregon andic soil at 1.65, 1.85, 2.00, 2.28, and 2.55 g cm −3 and analyzed the six fractions for measures of organic matter and mineral phase properties. All measures of OM composition showed either: (1) a monotonic change with density, or (2) a monotonic change across the lightest fractions, then little change over the heaviest fractions. Total C, N, and lignin phenol concentration all decreased monotonically with increasing density, and 14 C mean residence time (MRT) increased with particle density from ca. 150 years to >980 years in the four organo-mineral fractions. In contrast, C/N, 13 C and 15 N concentration all showed the second pattern. All these data are consistent with a general pattern of an increase in extent of microbial processing with increasing organo-mineral particle density, and also with an “onion” layering model. X-ray diffraction before and after separation of magnetic materials showed that the sequential density fractionation (SDF) isolated pools of differing mineralogy, with layer-silicate clays dominating in two of the intermediate fractions and primary minerals in the heaviest two fractions. There was no indication that these differences in mineralogy controlled the differences in density of the organo-mineral particles in this soil. Thus, our data are consistent with the hypothesis that variation in particle density reflects variation in thickness of the organic accumulations and with an “onion” layering model for organic matter accumulation on mineral surfaces. However, the mineralogy differences among fractions made it difficult to test either the layer-thickness or “onion” layering models with this soil. Although SDF isolated pools of distinct mineralogy and organic-matter composition, more work will be needed to understand mechanisms relating the two factors.

358 citations

Journal ArticleDOI
TL;DR: In this article, the exact relationship between the mean wind speed and the mean of the cube of the wind speed is discussed, and it is concluded that the mean and standard deviation of wind speed are the minimum statistics necessary for wind power estimates, and that the existing wind power studies based solely on the total mean wind power density omit much valuable information about the wind power.
Abstract: Some of the problems of wind power statistics are examined. The exact relationship between the mean wind speed and the mean of the cube of the wind speed is discussed. The Weibull probability density function, a good model for wind speed distributions, leads to a Weibull model for the distribution of the cube of the wind speed. This model facilitates the computation of the mean and the standard deviation of the total wind power density, the usable wind power density, and the wind power density during the hours when an aerogenerator is operating. The Weibull model is applied to data from three Oregon wind power sites located in rugged terrain. It is concluded that the mean and standard deviation of the wind speed are the minimum statistics necessary for wind power estimates, that the Weibull model for the wind power density has many computational advantages, and that the existing wind power studies based solely on the total mean wind power density omit much valuable information about the wind powe...

358 citations


Authors

Showing all 28447 results

NameH-indexPapersCitations
Robert Stone1601756167901
Menachem Elimelech15754795285
Thomas J. Smith1401775113919
Harold A. Mooney135450100404
Jerry M. Melillo13438368894
John F. Thompson132142095894
Thomas N. Williams132114595109
Peter M. Vitousek12735296184
Steven W. Running12635576265
Vincenzo Di Marzo12665960240
J. D. Hansen12297576198
Peter Molnar11844653480
Michael R. Hoffmann10950063474
David Pollard10843839550
David J. Hill107136457746
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023105
2022375
20213,156
20203,109
20193,017
20182,987