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Książki na temat „Yield predictions”

Autor: Grafiati

Data publikacji: 9 maja 2025

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1

J, Zarnoch Stanley, i Southern Forest Experiment Station (New Orleans, La.), red. Growth and yield predictions for thinned and unthinned slash pine plantations on cutover sites in the west Gulf Region. New Orleans, La: U.S. Dept. of Agriculture, Forest Service, Southern Forest Experiment Station, 1992.

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2

International, Symposium on Stocks Assessment and Yield Prediction (1985 Quetico Centre Ontario). International Symposium on Stocks Assessment and Yield Prediction. Ottawa: Department of Fisheries and Oceans, 1987.

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3

B, Yang, Outcalt Kenneth W i United States. Forest Service. Southern Research Station, red. Stand-yield prediction for managed Ocala sand pine. [Asheville, NC]: U.S. Dept. of Agriculture, Forest Service, Southern Research Station, 1997.

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4

Dennington, Roger W. New loblolly pine growth and yield prediction system. Atlanta, Ga: U.S. Dept. of Agriculture, Forest Service, Cooperative Forestry, 1988.

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5

B, Yang, Outcalt Kenneth W i United States. Forest Service. Southern Research Station, red. Stand-yield prediction for managed Ocala sand pine. [Asheville, NC]: U.S. Dept. of Agriculture, Forest Service, Southern Research Station, 1997.

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6

B, Yang, Outcalt Kenneth W i United States. Forest Service. Southern Research Station., red. Stand-yield prediction for managed Ocala sand pine. [Asheville, NC]: U.S. Dept. of Agriculture, Forest Service, Southern Research Station, 1997.

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7

Rockwood, D. L. Stand-yield prediction for managed Ocala sand pine. Ashville, NC: U.S. Dept. of Agriculture, Forest Service, Southern Research Station, 1997.

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8

Rockwood, D. L. Stand-yield prediction for managed Ocala sand pine. Ashville, NC: U.S. Dept. of Agriculture, Forest Service, Southern Research Station, 1997.

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9

International Symposium on Stocks Assessment and Yield Prediction (1985 Quetico Centre, Ont.). International Symposium on Stocks Assessment and Yield Prediction [proceedings]. Ottawa: Fisheries and Oceans, Information and Publications Branch, 1987.

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10

José de Jesús Pineda de Gyvez. IC defect-sensitivity: Theory and computational models for yield prediction. [s.l.]: [s.n.], 1991.

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11

Hoff, Kristen G. Limitations of lumber-yield nomograms for predicting lumber requirements. Newton Square, PA: U.S. Dept. of Agriculture, Forest Service, Northeastern Research Station, 2000.

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12

Hoff, Kristen G. Limitations of lumber-yield nomograms for predicting lumber requirements. Newton Square, PA: U.S. Dept. of Agriculture, Forest Service, Northeastern Research Station, 2000.

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13

Hoff, Kristen G. Limitations of lumber-yield nomograms for predicting lumber requirements. Newton Square, PA: U.S. Dept. of Agriculture, Forest Service, Northeastern Research Station, 2000.

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14

United States. Forest Service. Northeastern Research Station, red. Limitations of lumber-yield nomograms for predicting lumber requirements. Newtown Square, PA: U.S. Dept. of Agriculture, Forest Service, Northeastern Research Station, 2000.

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15

United States. Forest Service. Northeastern Research Station, red. Limitations of lumber-yield nomograms for predicting lumber requirements. Newtown Square, PA: U.S. Dept. of Agriculture, Forest Service, Northeastern Research Station, 2000.

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16

Veale, Stuart R. Bond yield analysis: A guide to predicting bond returns. New York, NY: New York Institute of Finance, 1988.

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17

Baldwin, V. C. Loblolly pine growth and yield prediction for managed west Gulf plantations. New Orleans, La: U.S. Dept. of Agriculture, Forest Service, Southern Forest Experiment Station, 1987.

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18

Logan, R. L. Prediction of sediment yield from tributary basins along Huelsdonk ridge, Hoh River, Washington. [Olumpia, Wash.]: Washington State Dept. of Natural Resources, 1991.

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19

Brantley, Steven R. The Alaska Volcano Observatory: Expanded monitoring of volcanoes yields results. [Reston, Va.]: U.S. Dept. of the Interior, U.S. Geological Survey, 2004.

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20

Karvonen, Tuomo. A model for predicting the effect of drainage on soil moisture, soil temperature and crop yield. Otaniemi, Finland: Helsinki University of Technology, Laboratory of Hydrology and Water Resources Engineering, 1988.

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21

Blaszczynski, Jacek S. Watershed soil erosion, runoff, and sediment yield prediction using geographic information systems: A manual of GIS procedures. Denver, Colo: U.S. Dept. of the Interior, Bureau of Land Management, BLM Service Center, 1994.

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22

P, Dagnall S., Harwell Laboratory (Oxfordshire, England). Energy Technology Support Unit. i Macaulay Land Use Research Institute., red. Predicting yield of short rotation coppice: Proceedings of a workshop : 27 February 1997, ETSU, Harwell, UK. [Harwell?]: ETSU, 1997.

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23

B, Ward Keith, Baldwin V. C i Southern Forest Experiment Station (New Orleans, La.), red. COMPUTEM̲ERCHLOB: A growth and yield prediction system with a merchandising optimizer for planted loblolly pine in the West Gulf region. New Orleans, La: U.S. Dept. of Agriculture, Forest Service, Southern Forest Experiment Station, 1990.

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24

B, Ward Keith, Baldwin V. C i Southern Forest Experiment Station (New Orleans, La.), red. COMPUTEunderMERCHLOB: A growth and yield prediction system with a merchandising optimizer for planted loblolly pine in the West Gulf region. New Orleans, La: U.S. Dept. of Agriculture, Forest Service, Southern Forest Experiment Station, 1990.

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25

Shrimp Yield Prediction Workshop (1983 Galveston, Tex.). Proceedings of the Shrimp Yield Prediction Workshop: November 16-17, 1983, Texas A&M University at Galveston, Mitchell Campus, Galveston, Texas. College Station, Tex: Texas A&M Sea Grant College Program, 1986.

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B, Ward Keith, Baldwin V. C i Southern Forest Experiment Station (New Orleans, La.), red. COMPUTE MERCHLOB: A growth and yield prediction system with a merchandising optimizer for planted loblolly pine in the West Gulf region. New Orleans, La: U.S. Dept. of Agriculture, Forest Service, Southern Forest Experiment Station, 1990.

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27

1936-, Chang S. J., red. VB merch-lob: A growth-and-yield prediction system with a merchandising optimizer for planted loblolly pine in the West Gulf region. Asheville, N.C: United States Dept. of Agriculture, Forest Service, Southern Research Station, 2005.

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28

1936-, Chang S. J., red. VB merch-slash: A growth-and-yield prediction system with a merchandising optimizer for planted slash pine in the West Gulf region. Asheville, N.C: United States Dept. of Agriculture, Forest Service, Southern Research Station, 2005.

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29

Nixon, Chappell Henry, Maguire Douglas A i University of Washington. College of Forest Resources., red. Predicting forest growth and yield: Current issues, future prospects : papers presented at a seminar series and workshop held at the University of Washington, January-March 1987. Seattle, Wash: College of Forest Resources, University of Washington, 1987.

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30

Singh, Teja. Forest yield predictions: Risk modeling and simulation : Final report. Forestry Canada, Northern Forestry Centre, 1990.

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31

Birch, Jonathan. The Rule under Attack. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198733058.003.0003.

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HRG has been criticized for being an ‘empty statement’ or tautology, for failing to yield predictions, and for failing to yield causal explanations of change. There is some justification for these charges, yet they do not undermine the value of HRG as an organizing framework. In response to the ‘tautology’ complaint, we should admit that HRG is tautology-like, in that it avoids detailed dynamical assumptions. But this is an advantage in an organizing framework, because it ensures its compatibility with a wide range of more detailed models. In response to the ‘prediction’ complaint, we should concede that HRG is not very useful for prediction, but the role of an organizing framework is not predictive. In response to the ‘causal explanation’ complaint, this chapter argues that HRG, by organizing our thinking about ultimate causes, generates understanding of those causes. It also compares favourably to other possible organizing frameworks.

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32

Baker, Victor R. Interdisciplinarity and the Earth Sciences. Redaktor Robert Frodeman. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780198733522.013.8.

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The inherent interdisciplinary of the Earth sciences derives from combining aspects of other disciplines when studying the Earth. Though most commonly viewed as providing science-as-knowledge, the Earth sciences can yield greater societal benefit through their nature-directed transdisciplinarity. As an example, paleoflood hydrology involves a relating to the complexities of natural world that overcomes limitations imposed when simplifying reality in order to make predictions. Paleoflood hydrology discovers the natural recordings of ancient (but very real) cataclysmic processes that have the documented ability to cause harm. The commonsense recognition that what has actually happened can indeed happen again provides much more incentive to generate engaged and wise public action than does an abstract prediction of the so-called hundred-year flood. This kind of science differs from that of its constituent disciplines, and it has great potential for making progress on many issues of current societal concern through public education, communication, and guided policy.

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33

Stand-yield prediction for managed Ocala sand pine. [Asheville, NC]: U.S. Dept. of Agriculture, Forest Service, Southern Research Station, 1997.

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34

Pernet, Bruno, red. Larval Feeding: Mechanisms, Rates, and Performance in Nature. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198786962.003.0007.

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Larvae of many marine invertebrates must capture and ingest particulate food in order to develop to metamorphosis. These larvae use only a few physical processes to capture particles, but implement these processes using diverse morphologies and behaviors. Detailed understanding of larval feeding mechanism permits investigators to make predictions about feeding performance, including the size spectrum of particles larvae can capture and the rates at which they can capture them. In nature, larvae are immersed in complex mixtures of edible particles of varying size, density, flavor, and nutritional quality, as well as many particles that are too large to ingest. Concentrations of all of these components vary on fine temporal and spatial scales. Mechanistic models linking larval feeding mechanism to performance can be combined with data on food availability in nature and integrated into broader bioenergetics models to yield increased understanding of the biology of larvae in complex natural habitats.

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35

Yan, Veronica X., i Daphna Oyserman. The world as we see it. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198789710.003.0011.

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Cultural knowledge allows people to engage the world seemingly effortlessly—their implicit expectations for how everyday experiences will unfold seem to match their observations, triggering a sense that all is right with the world and oneself. However, culture-based expectations are sometimes violated; yielding an experience of cultural disfluency that triggers increased systematic reasoning, reduces experienced inherence, and increases uncertainty about the world and one’s present and future self. This chapter synthesizes these culture-based processes with identity-based motivation theory to yield predictions. Identity-based motivation theory predicts that people prefer to act (action-readiness) and make sense of their experiences (procedural-readiness) in ways that fit who they are but that who they are is dynamically constructed in context. Procedural-readiness entails go-to interpretation of metacognitive experiences of ease and difficulty and go-to mental procedures—focusing on a main point, on connections, or on ranking—that align with individualistic, collectivistic, and honor mindsets.

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36

Kautish, Sandeep, Vishal Goyal, N. Pradeep, Sonia Abdellatif i C. R. Nirmala. Modern Techniques for Agricultural Disease Management and Crop Yield Prediction. IGI Global, 2019.

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37

Kautish, Sandeep, Vishal Goyal, N. Pradeep, Sonia Abdellatif i C. R. Nirmala. Modern Techniques for Agricultural Disease Management and Crop Yield Prediction. IGI Global, 2019.

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38

Kautish, Sandeep, Vishal Goyal, N. Pradeep, Sonia Abdellatif i C. R. Nirmala. Modern Techniques for Agricultural Disease Management and Crop Yield Prediction. IGI Global, 2019.

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Pradeep, N. Modern Techniques for Agricultural Disease Management and Crop Yield Prediction. IGI Global, 2019.

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Kautish, Sandeep, Vishal Goyal, N. Pradeep, Sonia Abdellatif i C. R. Nirmala. Modern Techniques for Agricultural Disease Management and Crop Yield Prediction. IGI Global, 2019.

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41

Limitations of lumber-yield nomograms for predicting lumber requirements. Newtown Square, PA: U.S. Dept. of Agriculture, Forest Service, Northeastern Research Station, 2000.

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42

National Aeronautics and Space Administration (NASA) Staff. Strip-Yield Model for Predicting the Growth of Part-Through Cracks under Cyclic Loading. Independently Published, 2018.

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43

Boken, Vijendra K., Arthur P. Cracknell i Ronald L. Heathcote. Monitoring and Predicting Agricultural Drought. Oxford University Press, 2005. http://dx.doi.org/10.1093/oso/9780195162349.001.0001.

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Agricultural droughts affect whole societies, leading to higher food costs, threatened economies, and even famine. In order to mitigate such effects, researchers must first be able to monitor them, and then predict them; however no book currently focuses on accurate monitoring or prediction of these devastating kinds of droughts. To fill this void, the editors of Monitoring and Predicting Agricultural Drought have assembled a team of expert contributors from all continents to make a global study, describing biometeorological models and monitoring methods for agricultural droughts. These models and methods note the relationships between precipitation, soil moisture, and crop yields, using data gathered from conventional and remote sensing techniques. The coverage of the book includes probabilistic models and techniques used in America, Europe and the former USSR, Africa, Asia, and Australia, and it concludes with coverage of climate change and resultant shifts in agricultural productivity, drought early warning systems, and famine mitigation. This will be an essential collection for those who must advise governments or international organizations on the current scope, likelihood, and impact of agricultural droughts. Sponsored by the World Meterological Organization

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44

Kagan, Jerome. Five Constraints on Predicting Behavior. The MIT Press, 2018. http://dx.doi.org/10.7551/mitpress/9780262036528.001.0001.

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Scientists were unable to study the relation of brain to mind until the invention of technologies that measured the brain activity accompanying psychological processes. Yet even with these new tools, conclusions are tentative or simply wrong. This book describes five conditions that place serious constraints on the ability to predict mental or behavioral outcomes based on brain data: the setting in which evidence is gathered, the expectations of the subject, the source of the evidence that supports the conclusion, the absence of studies that examine patterns of causes with patterns of measures, and the habit of borrowing terms from psychology. The book describes the importance of context, and how the experimental setting—including the room, the procedure, and the species, age, and sex of both subject and examiner—can influence the conclusions. It explains how subject expectations affect all brain measures; considers why brain and psychological data often yield different conclusions; argues for relations between patterns of causes and outcomes rather than correlating single variables; and criticizes the borrowing of psychological terms to describe brain evidence. Brain sites cannot be in a state of “fear.” A deeper understanding of the brain's contributions to behavior, the book argues, requires investigators to acknowledge these five constraints in the design or interpretation of an experiment.

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45

Jappelli, Tullio, i Luigi Pistaferri. The Age Profile of Consumption and Wealth. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780199383146.003.0002.

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The life-cycle model yields a number of important empirical predictions about consumption and saving behavior. First, the growth rate of consumption depends on the difference between the expected real interest rate and the rate of time preference and varies with the elasticity of intertemporal substitution. Second, individuals seek to smooth the marginal utility of consumption over time. Third, young consumers should be accumulating resources for retirement, and hence have an adequate level of wealth at retirement. Finally, the elderly should be decumulating resources. To test these predictions, one can draw on a vast array of data on interest rates, consumption, income, and wealth. Some come from time series and national accounts, others from cross-sectional or longitudinal surveys of households. This chapter introduces stylized facts that emerge from a first examination of such data, pointing out the merits but also the drawbacks of the available sources.

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46

Krupenye, Christopher, Evan L. MacLean i Brian Hare. Does the bonobo have a (chimpanzee-like) theory of mind? Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198728511.003.0006.

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Theory of mind—the ability to reason about the thoughts and emotions of others—is central to what makes us human. Chimpanzees too appear to understand some psychological states. While less is known about bonobos, several lines of evidence suggest that the social-cognitive abilities of the two sister taxa may differ in key respects. This chapter outlines a framework to guide future research on bonobo social cognition based on the predictions of two potentially complementary hypotheses. The self-domestication hypothesis suggests that selection against aggression and for prosociality in bonobos may have impacted the ontogeny of their social-cognitive skills relative to chimpanzees. The empathizing–systemizing hypothesis links degree of prenatal brain masculinization, a potential result of self-domestication, to adult cognition. Specifically, relative feminization may yield more flexible theory of mind skills in bonobos than chimpanzees. Finally, directions for future study, including development of new paradigms that maximize ecological validity for bonobos, are discussed. La théorie de l’esprit—le pouvoir de raisonner les pensées et émotions des autres—est centrale à notre nature humaine. Il parait que les chimpanzés peuvent comprendre quelques états psychologiques. Tandis que nous savons moins des bonobos, plusieurs témoignages suggèrent que les capacités socio-cognitives des deux taxons soeur peuvent différer dans des aspects clefs. Nous traçons un cadre pour guider les prochaines recherches sur la cognition sociale des bonobos, basé sur les prédictions de deux hypothèses potentiellement complémentaires. L’hypothèse d’auto-domestication suggère que l’anti-agression et la prosocialité des bonobos a influé leur ontogenèse et leur capacités socio-cognitives relativement aux chimpanzés. L’hypothèse d’empathie systématique (Empathizing–Systemizing) forme un lien entre le degré de masculinisation prénatale du cerveau, le résultat potentiel d’auto-domestication, et la cognition adulte. Spécifiquement, la féminisation relative génère des théories de l’esprit plus flexibles chez les bonobos que chez les chimpanzés. Enfin, nous discutons le directions pour les prochaines études, inclut le développement de nouveaux paradigmes qui maximisent la validité écologique des bonobos.

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47

Marshall, Brian E. Predicting Ecology and Fish Yields in African Reservoirs from Preimpoundment Physico-Chemical (C I F a Technical Paper). Food & Agriculture Org, 1985.

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Ferraro, Paul J. Are payments for ecosystem services benefiting ecosystems and people? Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198808978.003.0025.

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This chapter examines the evidence surrounding whether payments for ecosystem services (PES) have delivered the anticipated benefits for people and nature. Proponents claim PES are scalable and clearly link conservation investments to conservation objectives. PES also materially reward rural households, thereby potentially alleviating poverty and reducing conflict between conservation and rural communities. The reality is not so simple. Theory yields ambiguous predictions, even implying that the more participants gain from PES, the less the environment gains, and offering no reason to expect win-wins to automatically arise. The empirical evidence is scant, with very few examples of even modest environmental and social impacts. Nevertheless, alternative conservation approaches have no better evidence of transformative impacts (and often much worse evidence). Given that solutions exist for making PES more likely to achieve their purported environmental benefits, scholars and practitioners would be ill-advised to abandon PES programs, but well advised to design better assessments.

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49

Wittman, David M. General Relativity and the Schwarzschild Metric. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780199658633.003.0018.

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Previously, we saw that variations in the time part of the spacetime metric cause free particles to accelerate, thus unifying gravity and relativity; and that orbits trace those accelerations, which follow the inverse‐square law around spherical source masses. But a metric that empirically models orbits is not enough; we want to understand how any arrangement of mass determines the metric in the surrounding spacetime. This chapter describes thinking tools, especially the frame‐independent idea of spacetime curvature, that helped Einstein develop general relativity. We describe the Einstein equation, which determines the metric given a source or set of sources. Solving that equation for the case of a static spherical mass (such as the Sun) yields the Schwarzschild metric. We compare Schwarzschild and Newtonian predictions for precession, the deflection of light, and time delay of light; and we contrast the effects of variations in the time and space parts of the metric.

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50

Clarke, Andrew. The Metabolic Theory of Ecology. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780199551668.003.0012.

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The model of West, Brown & Enquist (WBE) is built on the assumption that the metabolic rate of cells is determined by the architecture of the vascular network that supplies them with oxygen and nutrients. For a fractal-like network, and assuming that evolution has minimised cardiovascular costs, the WBE model predicts that s=metabolism should scale with mass with an exponent, b, of 0.75 at infinite size, and ~ 0.8 at realistic larger sizes. Scaling exponents ~ 0.75 for standard or resting metabolic rate are observed widely, but far from universally, including in some invertebrates with cardiovascular systems very different from that assumed in the WBE model. Data for field metabolic rate in vertebrates typically exhibit b ~ 0.8, which matches the WBE prediction. Addition of a simple Boltzmann factor to capture the effects of body temperature on metabolic rate yields the central equation of the Metabolic Theory of Ecology (MTE). The MTE has become an important strand in ecology, and the WBE model is the most widely accepted physical explanation for the scaling of metabolic rate with body mass. Capturing the effect of temperature through a Boltzmann factor is a useful statistical description but too simple to qualify as a complete physical theory of thermal ecology.

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