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Books on the topic 'Ecological estimation'

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1

H, Gardner R., and O'Neill R. V. 1940-, eds. Ecological risk estimation. Lewis Publishers, 1992.

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2

McCallum, Hamish. Population parameters: Estimation for ecological models. Blackwell Science, 2000.

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3

1957-, Ferenc Susan A., and Foran Jeffery Allen 1953-, eds. Multiple stressors in ecological risk and impact assessments: Approaches to risk estimation. Society of Environmental Toxicology and Chemistry, 2000.

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4

Takahashi, Sentaro. Radiation Monitoring and Dose Estimation of the Fukushima Nuclear Accident. Springer Nature, 2014.

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5

Pochvenno-zemelʹnye resursy, ot︠s︡enka, ustoĭchivoe ispolʹzovanie, geoinformat︠s︡ionnoe obespechenie (Conference) (2012 Minsk, Belarus). Pochvenno-zemelʹnye resursy: Ot︠s︡enka, ustoĭchivoe ispolʹzovanie, geoinformat︠s︡ionnoe obespechenie materialy Mezhdunarodnoĭ nauchno-prakticheskoĭ konferent︠s︡ii 6-8 ii︠u︡ni︠a︡ 2012 g., Minsk, Belarusʹ = Soil and land resources : estimation, sustainable use, geoinformational maintenance. Izdatelʹskiĭ t︠s︡entr BGU, 2012.

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6

Hanley, Thomas A. Estimating carrying capacity with simultaneous nutritional constrants. U.S. Dept. of Agriculture, Forest Service, Pacific Northwest Research Station, 1989.

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7

Wong, Carmen. Estimating historical variability of natural disturbances in British Columbia. British Columbia, Forest Science Program, 2003.

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8

Garrett, Mark. Transportation planning on trial: The Clean Air Act and travel forecasting. Sage Publications, 1996.

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9

McCallum, Hamish. Population Parameters: Estimation for Ecological Models. Wiley & Sons, Incorporated, John, 2008.

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10

McCallum, Hamish. Population Parameters: Estimation for Ecological Models. Wiley & Sons, Limited, John, 2008.

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11

McCallum, Hamish. Population Parameters: Estimation for Ecological Models (Methods in Ecology). Blackwell Publishing Limited, 2000.

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12

Takahashi, Sentaro. Radiation Monitoring and Dose Estimation of the Fukushima Nuclear Accident. Springer, 2016.

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13

Takahashi, Sentaro. Radiation Monitoring and Dose Estimation of the Fukushima Nuclear Accident. Springer, 2014.

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14

Jorgensen, Sven E., B. Halling Sorensen, and Henrik Mahler. Handbook of Estimation Methods in Ecotoxicology and Environmental Chemistry (Environmental and Ecological Modeling). CRC, 1997.

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15

(Editor), Susan A. Ferenc, and Jeffery Allen Foran (Editor), eds. Multiple Stressors in Ecological Risk and Impact Assessments: Approaches to Risk Estimation (Setac Special Publications Series). S E T a C Foundation for, 2000.

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16

Hankin, David, Michael S. Mohr, and Kenneth B. Newman. Sampling Theory. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198815792.001.0001.

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We present a rigorous but understandable introduction to the field of sampling theory for ecologists and natural resource scientists. Sampling theory concerns itself with development of procedures for random selection of a subset of units, a sample, from a larger finite population, and with how to best use sample data to make scientifically and statistically sound inferences about the population as a whole. The inferences fall into two broad categories: (a) estimation of simple descriptive population parameters, such as means, totals, or proportions, for variables of interest, and (b) estimati
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17

Tkach, V. P., N. Yu Vysotska, A. S. Torosov, et al. Economic evaluation of ecosystem services of Ukrainian forests. Ukrainian Research Institute of Forestry and Forest Melioration named after G. M. Vysotsky, 2023. http://dx.doi.org/10.33220/2023.978-617-8195-57-1.

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Ecological-economic calculations are presented for assessing the ecosystem services of Ukrainian forests, taking into account international trends. An economic estimation is provided for both wood and non-wood forest products, as well as for the climate-regulating, phytomeliorative, rehabilitation, recreational, and social functions of Ukrainian forests. Additionally, the economic value of the biodiversity of woody plants and forest genetic resources is determined. This scientific publication is intended for forestry professionals, experts of scientific and project organizations, as well as te
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18

Huang, Shongming. Ecologically based individual tree volume tables for aspen (Populus tremuloides Michx.) (Ecologically based individual tree volume estimation for major Alberta tree species report). Alberta Environmental Protection, Land and Forest Services, Forest Management Division, 1994.

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19

Taberlet, Pierre, Aurélie Bonin, Lucie Zinger, and Eric Coissac. The future of eDNA metabarcoding. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198767220.003.0019.

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Environmental DNA-based research is undergoing rapid developments, but its democratization in basic and applied research remains hampered by the biases introduced by molecular approaches, the difficulties in estimating absolute organisms’ abundances, and a lack of general consensus in molecular protocols. Chapter 19 “The future of eDNA metabarcoding” provides an overview of these current challenges and discusses how shotgun sequencing, capture-based methods, inclusion of internal standards, and development of new data repositories could alleviate these limits and facilitate cross-experiments c
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20

Huang, Shongming. Ecologically based individual tree volume tables for balsam poplar (Populus balsamifera L.) (Ecologically based individual tree volume estimation for major Alberta tree species report). Alberta Environmental Protection, Land and Forest Services, Forest Management Division, 1994.

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21

Huang, Shongming. Ecologically based individual tree volume tables for lodgepole pine (Pinus contorta var. latifolia Engelm.) (Ecologically based individual tree volume estimation for major Alberta tree species report). Alberta Environmental Protection, Land and Forest Services, Forest Management Division, 1994.

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22

Walsh, Bruce, and Michael Lynch. Evolution and Selection of Quantitative Traits. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198830870.001.0001.

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Quantitative traits—be they morphological or physiological characters, aspects of behavior, or genome-level features such as the amount of RNA or protein expression for a specific gene—usually show considerable variation within and among populations. Quantitative genetics, also referred to as the genetics of complex traits, is the study of such characters and is based on mathematical models of evolution in which many genes influence the trait and in which non-genetic factors may also be important. Evolution and Selection of Quantitative Traits presents a holistic treatment of the subject, show
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23

Wachs, Martin, and Mark Garrett. Transportation Planning on Trial. SAGE Publications, Incorporated, 1996.

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