Are variations of forest vegetation consistent with trends of meteorological parameters in the northern Zagros region of Iran?

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.

Maroufzade E.; ATTAROD P.

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

Journal Paper

Paper Information

Journal: Iranian journal of Forest Year:2021 | Volume:12 | Issue:4 Page(s): 449-466

Download Full-Text

Persian Verion

View:

450

Download:

Cites:

Information Journal Paper

Title

Are variations of forest vegetation consistent with trends of meteorological parameters in the northern Zagros region of Iran?

Author(s)

Maroufzade E. | ATTAROD P. | Issue Writer Certificate

Keywords

Mann-Kendall testQ1

Pettitt testQ1

step wise regressionQ2

SAVIQ1

NDVIQ1

Abstract

Deterioration of Zagros forests may partly be related to changes in climatic parameters. In the present study, the trends of precipitation and temperature changes in relation to the trend of forest cover changes in Sardasht area, Northern Zagros, was studied using 30 years data (1988-2017) recorded at Sardasht Synoptic Weather Station. Mann-Kendall statistical tests, the Sen’ s slope estimator and Pettitt test were used for trend detecting and finding mutation points of climatic parameters. Trends of forest cover changes in Sardasht were also investigated using NDVI and SAVI vegetation indices. The relationship between the climatic parameters and the vegetation indices was carried out by the simple linear regression analysis and stepwise multivariate regression. Mann-Kendall test showed that the annual, seasonal, and monthly temperatures of January, February, March, May, June, July, August, and September had a significant increasing trend. The trend of changes in NDVI and SAVI indices were not significant, however, these indices pointed out significant relationships with climatic parameter so that temperature of April and SAVI demonstrated the highest simple linear correlation coefficient (0. 499). Stepwise multivariate regression analysis displayed that the SAVI had the highest multivariate correlation (0. 810) with temperature of August, temperature of spring, precipitation of July and temperature of winter. Regarding the impact of climate change on decline of Zagros forests, the regression models presented in this study can be used to make an appropriate decision to protect these forests. Managers should think of the unexpected changes in meteorological parameters owing to global warming.

Cites

No record.

References

No record.

Cite

APA: Copy

Maroufzade, E., & ATTAROD, P.. (2021). Are variations of forest vegetation consistent with trends of meteorological parameters in the northern Zagros region of Iran?. IRANIAN JOURNAL OF FOREST, 12(4 ), 449-466. SID. https://sid.ir/paper/399431/en

Vancouver: Copy

Maroufzade E., ATTAROD P.. Are variations of forest vegetation consistent with trends of meteorological parameters in the northern Zagros region of Iran?. IRANIAN JOURNAL OF FOREST[Internet]. 2021;12(4 ):449-466. Available from: https://sid.ir/paper/399431/en

IEEE: Copy

E. Maroufzade, and P. ATTAROD, “Are variations of forest vegetation consistent with trends of meteorological parameters in the northern Zagros region of Iran?,” IRANIAN JOURNAL OF FOREST, vol. 12, no. 4 , pp. 449–466, 2021, [Online]. Available: https://sid.ir/paper/399431/en

Related Journal Papers