[Home ] [Archive]   [ فارسی ]  
:: Main :: About :: Current Issue :: Archive :: Search :: Submit :: Contact ::
:: Volume 10, Issue 20 (9-2022) ::
PEC 2022, 10(20): 275-286 Back to browse issues page
Modeling of species richness by macro ecological methods (MEM) and Stacked Species Distribution Models (S-SDM) in Rangelands
Mandana Mohammadi1, Zeinab Jafarian *, Reza Tamartash1, Mansoureh Kargar1
1- Sari Agricultural Sciences and Natural Resources University
Sari Agricultural Sciences and Natural Resources University, Sari Agricultural Sciences and Natural Resources University , z.jafarian@sanru.ac.ir
Abstract:   (114 Views)
Species richness is a simple and interpretable indicator of biodiversity and is one of the most important and and practical measurements in the rangeland ecosystems. Experimental models of richness are used to determine the points of richness of suitable and unsuitable species, and the factors affecting it. The aim of this study is to compare two methods of modeling species richness S-SDM and MEM in the Sorkh-Griveh rangelands in Mazandaran province. For sampling of vegetation and soil, random-systematic stratification method was used. In each sampling unit, 10 plots of 1m2 and a total of 260 plots of one square meter were located. Species list, presence and absence of species were recorded in each plot. Also, three soil samples were taken in each sampling unit from a depth of 0-30 cm. Data related to a number of soil physical and chemical factors were collected in the measurement laboratory, topographic variables were determined with the help of GIS software and 15-year climatic data were collected from meteorological stations in nearby areas. Plant species richness was predicted by amplified regression tree (BRT) model with macroecological methods (MEM) and aggregated distribution model (S-SDM). Data analysis was performed using R software version 3.1.1. The results showed that the species richness observed with the richness predicted by both methods and the richness predicted by MEM method had a significant correlation with the richness predicted by the combination of MEM and S-SDM methods. The results obtained from Spearman's correlation between different methods of predicting the richness of plant species indicated that the S-SDM method with a value of -0.184 and then the MEM method with a value of 0.177 were more consistent with the observed species richness. The results show that by modeling species richness, information about plant community composition, species identification and their prediction in space and time can be used to investigate biodiversity changes.
Keywords: Ecological Modeling, Environmental Factors, Boosted Regression Tree Model, Sorkh-Griveh rangeland.
Full-Text [PDF 895 kb]   (41 Downloads)    
Type of Study: Applicable | Subject: Special
Received: 2022/02/6 | Accepted: 2022/08/25 | Published: 2022/09/22
References
1. Austin, M. 2007. Species distribution models and ecological theory: a critical assessment and some possible new approaches. Ecological modelling, 200(1-2): 1-19.
2. Calabrese, J.M., Certain, G., Kraan, C. Dormann, C. F. 2014. Stacking species distribution models and adjusting bias by linking them to Macroecological Models. Global Ecology and Biogeography. 23(1):99-112.
3. D'Amen, M., Dubuis, A., Fernandes, R.F., Pottier, J., Pellissier, L. and Guisan, A. 2015. Using species richness and functional traits predictions to constrain assemblage predictions from stacked species distribution models. Journal of Biogeography. 42(7): 1255-1266.
4. Deak, B., Kovacs, B., Radai, Z., Apostovala, I., Kelemen, A., Kiss, R., Lukaes, K., Palpurina, P., Sopotlivea, D., Bathori, F. Valko, O. 2021. Linking environmental heterogeneity and plantdiversity: The ecological role of small natural feature in homogeneous landscape. Science of the total environment.763: 144199.
5. Dubuis, A., Pottier, J., Rion, V., Pellissier, L., Theurillat, J.P. Guisan, A. 2011. Predicting spatial patterns of plant species richness: a comparison of direct macroecological and species stacking modelling approaches. Diversity and Distributions. 17(6): 1122-1131.
6. Dubuis, A., Giovanettina, S., Pellissier, L., Pottier, J., Vittoz, P. Guisan, A. 2013. Improving the prediction of plant species distribution and community composition by adding edaphic to topo-climatic variables. Journal of Vegetation Science. 24(4):593-606.
7. Ferrier, S. Guisan, A. 2006. Spatial modelling of biodiversity at the community level. Journal of Applied Ecology. 43(3): 393-404.
8. Haines-Young, R, 2009. Land use and biodiversity relationships. Land use policy. 26: 178-S186.
9. Jafarian, Z., Kargar, M., Tamartash R. Alavi S. J. 2019 a. Spatial distribution modelling of plant functional diversity in the mountain rangeland, north of Iran, Ecological Indicator. 97: 231-238.
10. Jafarian, Z., Kargar M., Bahreini, Z. 2019 b. Which spatial distribution model best predicts the occurrence of dominant species in semi-arid rangeland of northern Iran? Ecological informatic. 50:33-42.
11. Kargar, M., Jafarian, Z., Tamartash, R. Alavi, S.J. 2018. Prediction of spatial distribution of plant species richness in‎ the Valdarreh Rangelands, Mazandaran by Macroecological‎ Modelling and Stacked Species Distribution Models. Ecopersia. 6(2): 139-145.
12. Liang, J., Ding, ZH., Lie, G., Zhou, ZH., BikramSingh, P., Zhang, ZH., Hu, H. 2020. Species richness patterns of vascular plants and their drivers along an elevational gradient in the central Himalayas, Global Ecology and Conservation. 24: e01279.
13. McKee, J.K., Sciulli, P.W., Fooce, C.D. Waite, T.A. 2004. Forecasting global biodiversity threats associated with human population growth. Biological Conservation, 115(1): 161-164.
14. Medinski, T.V., Mills, A.J., Esler, K.J., Schmiedel, U. Jürgens, N. 2010. Do soil properties constrain species richness? Insights from boundary line analysis across several biomes in south western Africa. Journal of Arid Environments.74(9):1052-1060.
15. Mills, A., Fey, M., Donaldson, J., Todd, S. Theron, L. 2009. Soil infiltrability as a driver of plant cover and species richness in the semi-arid Karoo, South Africa. Plant and Soil. 320(1-2): 321-332.
16. Peet, R.K. 1974. The measurement of species diversity. Annual Review of Ecology and Systematics, 5(1): 285-307.
17. Vockenhuber, E.A., Scherber, C., Langenbruch, C., Meißner, M., Seidel, D. Tscharntke, T. 2011. Tree diversity and environmental context predict herb species richness and cover in Germany's largest connected deciduous forest. Perspectives in Plant Ecology, Evolution and Systematics. 13(2): 111-119.
18. Xu, Y., Chen, Y., Li, W., Fu, A., Ma, X., Gui, D. Chen, Y. 2010. Distribution pattern and environmental interpretation of plant species diversity in the mountainous region of Ili River Valley, Xinjiang, China. Journal of Plant Ecology (Chinese Version). 34(10): 1142-1154.
Send email to the article author

Add your comments about this article
Your username or Email:

CAPTCHA


XML   Persian Abstract   Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

mohammadi M, jafarian Z, tamartash R, kargar M. Modeling of species richness by macro ecological methods (MEM) and Stacked Species Distribution Models (S-SDM) in Rangelands. PEC 2022; 10 (20) :275-286
URL: http://pec.gonbad.ac.ir/article-1-840-en.html


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 10, Issue 20 (9-2022) Back to browse issues page
مجله حفاظت زیست بوم گیاهان Journal of Plant Ecosystem Conservation
Persian site map - English site map - Created in 0.04 seconds with 30 queries by YEKTAWEB 4505