GEOMATIC Techniques to Study the Ecological Processes of Field Data

Authors

  • Imteaz Husain

geometic techniques, spatial pattern analysis, canonical correspondence analysis

Abstract

Geometic techniques are widely applied in landscape ecology to quantify the spatial patterns exhibited within species and its associated root fungi. Several analyses have been developed and modified to improve the ability to detect and characterize the patterns by the growth of species and population in various scale. Analysis of spatial pattern for disease and pathogen are of interest for the understanding and management plan to control the increase or spread within plant populations due to the numerous shared channels. Mathematical approaches encounter and give quantitative information of infections caused by many soilborne plant pathogens which are generally found in clusters of patches. Reliable approach for the use of spatial data can be established either by the research objective or by the measurement types and sampling designs procedures. We applied several mathematical tools to quantify the quantitative nature of Meloidogyne javanica and its associated soil fungi and soil characteristics in the development of nematode populations in the tomato grown field.

Downloads

How to Cite

GEOMATIC Techniques to Study the Ecological Processes of Field Data. (2014). Global Journal of Science Frontier Research, 14(F4), 35-43. https://journalofscience.org/index.php/GJSFR/article/view/1260

References

J Sasser, D Freckman (1987) A world prospective on nematology: the role of the society. 7-14.

G Agrios (1997) Plant Pathology.

R Mankau (1980) Biocontrol: fungi as nematode control agents. 12, 244-252.

Deborah Neher, Richard Olson (1999) Nematode communities in soils of four farm cropping management systems. 43(5), 430-438.

Gerard Korthals, Tom Bongers, Jan Kammenga, Alexey Alexiev, Theo Lexmond (1996) Long-term effects of copper and ph on the nematode community in an agroecosystem. 15(6), 979-985.

D Neher, C Campbell (1994) Nematode communities and microbial biomass in soils with annual and perennial crops. 1, 17-28.

M Beare (1997) Fungal and Bacterial Pathways of Organic Matter Decomposition and Nitrogen Mineralization in Arable Soils. 37-70.

C Ettema, T Bongers (1993) Characterization of nematode colonization and succession in disturbed soil using the Maturity Index. 16, 79-85.

P Goodell, H Ferris (1980) Plant parasitic nematode distributions in an alfalfa field. 12, 136-141.

J Singh, H Gaur (1996) Seasonal variation in the horizontal spatial pattern of the root-knot nematode Meloidogyne incognita and application of the negative binomial and Taylor's power law models in developing sampling schemes. 26, 226-236.

L Taylor (1984) Assessing and Interpreting the Spatial Distributions of Insect Populations. 29, 321-357.

B Boag, P Topham (1984) Aggregation of Plant Parasitic Nematodes and Taylor's Power Law. 30(3), 348-357.

L Duncan, J Ferguson, R Dunn, J Noling (1989) Application of Taylor's power law to sample statistics to Tylenchulus semipenetrains in Florida citrus. 21, 707-711.

Howard Ferris, Ingrid Benavides (1990) Opinions and Suggestions on Nematode Faunal Analysis. 56(1), 183-189.

Francis Pierce, Peter Nowak (1999) Aspects of Precision Agriculture. 67, 1-85.

C Campbell, L Madden (1990) Introduction to plant disease epidemiology. 348.

S Shaukat, A Khan (1993) Spatial pattern analysis of three nematode populations associated with chilli. 16, 473-478.

Cajo Ter Braak (1986) Canonical Correspondence Analysis: A New Eigenvector Technique for Multivariate Direct Gradient Analysis. 67(5), 1167-1179.

D Fiscus (1997) Development and evaluation of an indicator of soil health based on nematode communities.

Judith Myers (1978) Selecting a Measure of Dispersion. 7(5), 619-621.

M Lloyd (1967) Mean crowding. 36, 1-30.

M Morisita (1964) Application of I δ index to sampling techniques. 12, 149-164.

P Greig-Smith (1983) Quantitative Plant Ecology, 3 rd Edition.

P Moran (1950) Notes on continuous stochastic phenomena. 37, 17-37.

Robert Sokal, Neal Oden (1978) Spatial autocorrelation in biology: 1. Methodology. 10(2), 199-228.

C Ter Braak, I Prentice (1988) A theory of gradient analysis. 18, 271-317.

Ter Braak, C Šmilauer, P (2002) Canoco Reference Manual and CanoDraw for Windows User's Guide: Software for Canonical Community Ordination (version 4.5).

R De Goede (1993) Graphical presentation and interpretation of nematode community structure: C-P triangles.

Deborah Neher, Steven Peck, John Rawlings, C Campbell (1995) Measures of nematode community structure and sources of variability among and within agricultural fields. 170(1), 167-181.

GEOMATIC Techniques to Study the Ecological Processes of Field Data

Published

2014-09-04

How to Cite

GEOMATIC Techniques to Study the Ecological Processes of Field Data. (2014). Global Journal of Science Frontier Research, 14(F4), 35-43. https://journalofscience.org/index.php/GJSFR/article/view/1260