AN INVESTIGATION ON REGRESSION MODELS TO PREDICT RANGE PLANT PRODUCTION

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

TAHMASEBI P.; EBRAHIMI A.; FAAL M.

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: Journal of Rangeland Year:2011 | Volume:5 | Issue:2 Page(s): 137-146

Download Full-Text

Persian Verion

View:

1,116

Download:

Cites:

Information Journal Paper

Title

AN INVESTIGATION ON REGRESSION MODELS TO PREDICT RANGE PLANT PRODUCTION

Author(s)

TAHMASEBI P. | EBRAHIMI A. | FAAL M. | Issue Writer Certificate

Keywords

ESTIMATION OF PLANT PRODUCTIONQ2

MORPHOLOGICAL CHARACTERISTICSQ2

VALIDATIONQ1

REGRESSION MODELSQ2

LIFE FORMQ2

ROSETTEQ2

Abstract

Knowledge in range plant production provides appropriate information in rangelands function and health for ecosystem managers. Estimation of range plant production using MORPHOLOGICAL CHARACTERISTICS increases efficiency of sampling and required time. This study carried out in order to investigate the relationships between plant production and some MORPHOLOGICAL CHARACTERISTICS (canopy diameter, plant mean diameter, plant height, canopy cover basal area and primeter) of six plant species Stipa henckeriana, Bromus tomentellu s, Astragalus effeusus, Astragalus caragana, Astragalus cyclophylusand Onobrychis gaoba considering numerous statistical models which executed in two levels of the plant species and LIFE FORM. To do so, 30 individuals were randomly chosen in a steppic rangeland in the neighborhood of Zayanderood dam and then above characteristics were measured for each plant species separately. Three groups of statistical models including using only one characteristic (one dimensional model), those using several characteristics (two dimensional models) and multiple regressions were employed. Then selected significant models were validated in order to find best models. The results showed that there were significant relationships between plant production and each characteristic. Basal diameter, basal perimeter and mean canopy cover predicted more appropriately plant production and, conversely, the height as an independent variable did not have significant relationship with production. Furthermore, using two or more MORPHOLOGICAL CHARACTERISTICS in REGRESSION MODELS increased plant production predictions ability compared to those models with one morphological characteristic. The results confirmed that 1) considering two or more characteristics as independent variables may enhance estimation efficiency of plant production 2) ESTIMATION OF PLANT PRODUCTION in the normal morphological form is more accurate than in ROSETTE plant such as A. effusus.

Cites

No record.

References

No record.

Cite

APA: Copy

TAHMASEBI, P., EBRAHIMI, A., & FAAL, M.. (2011). AN INVESTIGATION ON REGRESSION MODELS TO PREDICT RANGE PLANT PRODUCTION. RANGELAND, 5(2), 137-146. SID. https://sid.ir/paper/136220/en

Vancouver: Copy

TAHMASEBI P., EBRAHIMI A., FAAL M.. AN INVESTIGATION ON REGRESSION MODELS TO PREDICT RANGE PLANT PRODUCTION. RANGELAND[Internet]. 2011;5(2):137-146. Available from: https://sid.ir/paper/136220/en

IEEE: Copy

P. TAHMASEBI, A. EBRAHIMI, and M. FAAL, “AN INVESTIGATION ON REGRESSION MODELS TO PREDICT RANGE PLANT PRODUCTION,” RANGELAND, vol. 5, no. 2, pp. 137–146, 2011, [Online]. Available: https://sid.ir/paper/136220/en

Related Journal Papers