A method for the analysis of piosphere data applicable to range assessment.

1978 ◽  
Vol 1 (2) ◽  
pp. 126 ◽  
Author(s):  
RD Graetz ◽  
JA Ludwig
Keyword(s):  
Growth Curve ◽  
Population Biology ◽  
Assessment Method ◽  
Logistic Growth ◽  
Curve Equation ◽  
Potential Use

The logistic growth curve equation of population biology is shown to satisfactorily describe the responses of some vegetation and soil measures as a function of distance out from a watering point. Two of the three parameters of this equation can be readily related to parameters of the herbivore - rangeland ecosystem. The potential use of this equation is explored for the development of a simple, quantitative range assessment method. -

Relationship Between Two Stock–Recruitment Curves

1977 ◽  
Vol 34 (3) ◽  
pp. 425-428 ◽  
Author(s):  
L. L. Eberhardt
Keyword(s):  
Difference Equation ◽  
Population Growth ◽  
Population Size ◽  
Growth Curve ◽  
Population Biology ◽  
Population Regulation ◽  
Growth Curves ◽  
Equation Model ◽  
Logistic Growth ◽  
Stock Recruitment

The Beverton and Holt and Ricker stock–recruitment curves can be used to generate population growth curves. The Beverton and Holt curve is then identical to a difference equation model for the logistic growth curve, and may be derived in terms of equations for linearly density-dependent population regulation. The same equations lead to the Ricker curve if the density-regulating effect is assumed to depend only on population size at the beginning of the interval between generations. At low rates of population growth, the Ricker curve approaches that of Beverton and Holt. The two curves appear to represent certain concepts known in population biology as "r and K selection."

Responses of Subterranean Clover Communities to Temperature. I. Dry Matter Production and Plant Morphogenesis

1976 ◽  
Vol 3 (4) ◽  
pp. 527 ◽  
Author(s):  
S Fukai ◽  
JH Silsbury
Keyword(s):  
Leaf Area ◽  
Growth Curve ◽  
Dry Matter ◽  
Subterranean Clover ◽  
Experimental Period ◽  
Main Stem ◽  
Logistic Growth ◽  
Similar Time ◽  
Plant Parts ◽  
Leaf Appearance

Subterranean clover communities were grown in temperature-controlled naturally lit glasshouses at 15, 20, 25 and 30�C. Dry matter yield, leaf area and the distribution of dry matter between plant parts were determined at about 14-day intervals for up to 130 days from planting. Leaf appearance, leaf death, leaf number and growth of laterals were observed for individual plants in the community over a similar time period. A logistic growth curve was found for each temperature and crop growth rate calculated from the equation fitted for each growth curve. The optimum temperature for growth was relatively high (20-25°C) when plants were young, but decreased during growth so that after 100 days total dry matter was inversely related to temperature over the range 15-30°C. Both the rate of leaf appearance and the rate of leaf death on the main stem were constant at each temperature during the experimental period and were directly related to temperature. The number of leaves per unit ground area was determined mainly by the rates of leaf appearance and leaf death on the main stem, since the contribution of laterals was small. The proportion of stem and petiole to total dry matter increased, and that of green leaf lamina decreased, with increase in total dry matter. Neither was markedly affected by temperature. An inverse relationship between specific leaf area and temperature resulted in a lower ratio of leaf area to total dry matter at 15°C compared with that at 20, 25 or 30°C.

Atmospheric Quality Assessment Model Based on Immune Clonal Selection Algorithm

2011 ◽  
Vol 255-260 ◽  
pp. 3013-3017
Author(s):  
Li Min Wang ◽  
Xu Ming Han ◽  
Ming Li ◽  
Chi Jun Zhang ◽  
Yan Ting Zhang
Keyword(s):  
Quality Assessment ◽  
Growth Curve ◽  
Clonal Selection ◽  
Assessment Method ◽  
Experimental Results ◽  
Assessment Model ◽  
Clonal Selection Algorithm ◽  
Selection Algorithm ◽  
Intelligence Theory ◽  
Curve Index

The immune clonal selection algorithm is used to optimize the parameters in the formula of S growth curve index in the paper, thus we can obtain an assessment model for atmospheric comprehensive pollution that is suitable to the cases of multi-pollutants. Moreover the proposed assessment model is applied in the field of atmosphere assessment. Experimental results show that the assessment method proposed for atmosphere quality has many advantages such as pellucid principle, physical explication and correct assessment results etc. It is a new effective approach for intelligence theory and technology applied in the field of environment. Therefore it has great potential in the field of assessment the atmospheric quality.

Fitting a growth curve equation to field data

1980 ◽  
Vol 22 (1) ◽  
pp. 1-9 ◽  
Author(s):  
G.F. Byrne ◽  
J.E. Drummond
Keyword(s):  
Growth Curve ◽  
Field Data ◽  
Curve Equation

Determinants of diversity in higher taxonomic categories

Paleobiology ◽  
1980 ◽  
Vol 6 (4) ◽  
pp. 444-450 ◽  
Author(s):  
James W. Valentine
Keyword(s):  
Species Richness ◽  
New Species ◽  
Growth Curve ◽  
High Frequency ◽  
Maximum Level ◽  
Logistic Growth ◽  
Higher Taxa ◽  
Equilibrium Level ◽  
Higher Categories ◽  
Taxonomic Categories

It is often assumed that, if a few species are introduced into a relatively empty environment, the subsequent diversification will take the form of a logistic growth curve, rising to an equilibrium level of species richness. The diversifications of taxa in higher categories commonly resemble logistic curves, although there are no well-defined theoretical bases for such a resemblance.A model of diversification of taxa in higher categories is based on the notion that many taxa originate rapidly. Relatively small changes leading to new species occur at a high frequency, while larger changes leading to progressively higher taxa occur with progressive rarity. During diversification in an empty environment, few large changes will occur before the environment is filled. The rate of filling, relative to the rate of production of higher taxa, determines the richness of taxa in higher categories and gives the diversification curves a logistic appearance although the maximum level achieved is not an equilibrium. Subsequently, opportunities for diversification will generally lead only to the appearance of taxa in progressively lower categories.

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