Biogeomorphology relationships among vegetation, soil, and landform elements (Case study of Hablehroud basin)

Document Type : Full length article


1 PhD student of geomorphology, Faculty of Earth Sciences, Department of Physical Geography, Shahid Beheshti University, Iran

2 Faculty of Earth Sciences, Department of Physical Geography, Shahid Beheshti University, Iran


Biogeomorphology, defined as the two-way interaction between geomorphology and ecology in different scales. Every landform is comprised of several micro-scale landform units such as peak, ridge, shoulder, etc. landform units can create various microhabitats and enhance heterogeneity in ecosystems. This information is obtained by extracting patterns from plants, processes, and landforms in the landscape. Differences in landforms are followed by differences in biological factors (type of cover, plenty, pattern, density) and non-biological factors (form, soil, geological, climatic). One of the important factors is the chemical and physical properties of the soil. Because soil not only provides the environment, water, and minerals for the plant but also affects the pattern and distribution, type, and dynamics of the plant. Soil properties in landforms cause changes in pattern, density, and vegetation composition. So, soil properties are influenced by vegetation at smaller spatial scales. Small-scale landform patterns play a major role in determining the plant distribution pattern and are a good tool for evaluating Macro-scale bio geomorphological relationships.
Materials and Methods
The variables examined in this study include the type of landform element, height, chemical and physical properties of soil, and vegetation characteristics (pattern and density). We tested the hypothesis that landform unit features to determine the spatial distribution of vegetation patterns in the case study. This study was aimed to determine the relationship between vegetation properties (vegetation pattern and density) and landform unit type and soil characterize in Hablehroud. Hablehroud basin, that is located between 35°16' 6"- to 35°57' 22" North latitude and 52°15'43" to 53°-8'-53" East longitude (the area about 3200 square km) Between Semnan and Tehran provinces. Our study is based on remote sensing coupled with field observations and laboratory studies.We prepared geomorphic classification of landform unit, vegetation map, and Eco geomorphology map. Using the Geomorphon method of landforms shows the geomorphon-based maps of landforms. Based on geomorphon technique Classification used DEM 12.5 M resolution in SAGA7.5. Geomorphon map includes most common landform elements. In the next step, the vegetation map of the area was prepared using the vegetation index (SAVI). All calculations were performed in ENVI.5.3 software in the next stage after the matching of these two maps; a new Eco geomorphological map was prepared. Where landform-plant units were identified. A field survey was conducted from Jun to July in 2020. We plotted a total of 40 stands within the four micro-landform units in the study basin According to field surveys, and the percentage of vegetation cover four units were identified. Soil samples were collected from a depth of 20cm for all 40 plots (1×1m) some physio-chemical analyses were conducted on them including (PH, EC, wetness, Organic, Texture). According to google earth, field survey, CAD software four types of vegetation patterns includes (spot-dense, gap-dense, spot-scatter, gap-scatter) were identified for each plot. Statistical analyses were calculated using Minitab18 software. We investigate the significance and correlation, principal component analysis, and stepwise regression.
Results and discussion
Geomorphon map includes the 10 most common landform elements: peak, ridge, shoulder, spur, slope, hollow, foot slope, valley, pit, and flat obtained from 498 patterns. In the geomorphon map, a pattern of various landscapes has been created. The vegetation index (SAVI) of the area was prepared using Landsat8 – July 2020. The map of eco- geomorphological units includes four types of geomorphon: Slope, Hollow, Foot slope, Spur which are extracted with dense to scattered vegetation. Field studies of soil sampling have been done to measure the physical and chemical properties of the soil, plot and photograph the plots to extract plant characteristics (pattern and density). Four patterns were extracted: dense point, dense gap, scattered point, and scattered gap for 40 plots. After data collection, type of landform, height, soil properties (chemical and physical) and vegetation (pattern extraction and density) for statistical analysis and analysis of biogeomorphology in Minitab18 including correlation, factor analysis, and multivariate and stepwise regression has been.
Results showed that there is a significant relationship between the type of landform and density and pattern of vegetation. Among four landform unit which includes (hollow, foot slope, slope, spur). Foot slope and Hallow have the highest density and spot-dense pattern. The correlation between pattern and vegetation density with soil moisture and landform unit type is significant with value (p <0.003) and landform type with value (p <0.007). The value of R2 indicates that the predictor variables explain 72.32% of the variance in the vegetation pattern of the sign. The results of regression equations showed that vegetation pattern as a dependent variable is influenced by the four variables, first landform type, and wetness, organic, sand percentage. Regression model 70.50% of the variations in vegetation pattern was related to these four variables. Because landform units have a direct and indirect role in other factors of plant growth and distribution such as moisture absorption, heat, amount of organic matter, erosion, soil texture, and activity of microorganisms. Each of the landform units, according to its shape and characteristics, plays a role in the pattern and density of vegetation. The domain landform generally has four extraction patterns (spot-dense, gap-dense, spot-scatter, gap-scatter) in the study area. The differences in landform-unit area, climate, and topographic features show different patterns of vegetation distribution. The pattern and density of vegetation in the spur are often scattered and in the hollow and the foot slope are spot dense, which is due to the morphometric and topographic features of the units.
The results showed that changes in plant distribution patterns are well related to landform type and soil properties. In this study, four types of landform elements (hollow, foot slope, slope, spur) along with chemical and physical properties of soil about the pattern and density of vegetation were analyzed. So that the type of vegetation pattern has a positive correlation with the amount of sand, PH, EC and has a negative correlation with the rest of the variables. The results of the factor analysis and regression model showed that approximately 69 to 70% of changes in vegetation patterns could be predicted by the variables mentioned in the study. Among the independent variables of landform unit type, Soil moisture, Organic matter, and Height have a significant relationship with the dependent variable and state that different patterns of vegetation in different parts of the Hablehroud basin are related to landform type, height, and different soil characteristics. The effect of landform elements is quite different depending on how much it is affected by soil properties. About vegetation, the most spot-dense pattern at the foot slope, hollow, the slope, and the least occurred in the spur. The spot-scatter pattern had the biggest portion on the slopes, the spur, the hollow, and the foot slope. Gap-scatter pattern, the portion of slopes was higher than other landform elements, and the spot-scatter pattern had the least repetition on the desired landform elements, which is generally observed in the slopes.
Therefore, the effects of geomorphic processes of vegetation characteristics are inevitable.


Main Subjects

احمدی، ح.؛ جوانشیر، ک.؛ قنبریان، غ. و حبیبیان، س. (۱۳۸۱). بررسی ویژگی‏های اکولوژیک جوامع گیاهی با توجه به واحدهای ژئومورفولوژی (مطالعة موردی: منطقة چنار راهدار استان فارس)، مجلة منابع طبیعی ایران، ۵۵(۱).
شکراللهی، ش.؛ مرادی. ح و دیانتی، ق. (۱۳۹۱). بررسی اثر ویژگی‏های خاک و عوامل فیزیوگرافی بر پوشش گیاهی (مطالعة موردی: بخشی از مراتع ییلاقی پلور)، تحقیقات مرتع و بیابان ایران، ۱۹(۴): ۶۶۸-۶۵۵.
قادری، ش.؛ امیریان، ع.؛ کریم‏زاده، آ.؛ دیفرخش، م. و پوررضایی، ح. (۱۳۹۴). بررسی ارتباط پوشش گیاهی با عوامل خاکی با استفاده از آنالیز چندمتغیره (مطالعة موردی: مراتع قشلاقی حوزة چمران استان خوزستان)، تحقیقات مرتع و بیابان ایران، ۲۴(۳): ۴۹۳-۴۷۸.
تایا، ع.؛ کابلی. س.؛ آذرنیون، ح و ناصری، ح (۱۳۹۸). اثر برخی خصوصیات خاک بر الگوی پراکنش گونه‏های گیاهی در حاشیة جنوبی پلایای حاج علیقلی دامغان، مرتع، ۱۳(۴): ۷۰۳-۷۱۴.
علی‏‏نژاد، م.؛ علی‏زاده، م.؛ اونق، م. و محمدیان بهبهانی، ع. (۱۳۹۷). بررسی الگوی پراکنش مکانی نبکا (مطالعة موردی: دشت صوفیکم، استان گلستان)، پژوهشهای جغرافیای طبیعی، ۵۰(۴): 697-712.
جوادی، ا.؛ خان آرمویی، ع و جعفری، م (۱۳۹۵). بررسی ارتباط فاکتورهای پوشش گیاهی و خصوصیات خاک (مطالعة موردی پارک ملی خجیر)، مرتع و آبخیزداری، ۶۹(۲): ۳۵۳-۳۶۶.
جابری، م.؛ شایان، س.؛ یمانی، م.؛ قاسمی، م  و شریفی‏کیا، م (۱۳۹۱). نقش نوزمین‎ ساخت در تحولات ژئومورفولوژیک مرز ساختاری البرز جنوبی- ایران مرکزی (مطالعة موردی: حوضة حبله‏رود)، پژوهش های جغرافیای طبیعی، ۴۴(۴): ۸۱-۸۹.
درویش‏زاده، ر.؛ متکان، ع. و حسینی اصل، ا. (۱۳۹۱). تخمین درصد پوشش گیاهی منطقة خشک ایران مرکزی با استفاده از تصاویر ماهواره‏ای (مطالعة موردی: حوزة شیطور، بافق)، دو فصل‏نامة خشک بوم، ۲۵-37.
زارع، م.؛ قدرتی، ج.؛ نوروزی، غ و دادور، ل. (۱۳۸۵). بررسی رابطة بین پوشش گیاهی با خاک و شکل زمین د‏ر حوزة د‏ق فینو بند‏رعباس، مجلة پژوهش و سازندگی، ۷۶: ۱۴۲-۱۵۰.
فرج‏زاده، منوچهر (‏۱۳۷۸). طرح آمایش استان تهران،‏ مطالعات آب وزارت نیرو.
طرح وزارت جهاد کشاورزی (۱۳۸۹). پروژة حبله‏رود، ج ۵.
سازمان هواشناسی-
Alexander, C.; Deák, B. and Heilmeier, H. (2016). Micro-topography driven vegetation patterns in open mosaic landscapes. Ecological indicators, 60: 906-920.‏
Borgogno, F. et al. (2009). Mathematical models of vegetation pattern formation in ecohydrology. Reviews of Geophysics, 47(1).
Brancaleoni, L. et al. (2003). Relationships between geomorphology and vegetation patterns in subantarctic Andean tundra of Tierra del Fuego. Polar Biology, 26(6): 404-410.
Cannone, N. et al. (2004). Relationships between vegetation patterns and periglacial landforms in northwestern Svalbard. Polar Biology, 27(9): 562-571.
Casalini, A. I.; Bouza, P. J. and Bisigato, A. J. (2019). Geomorphology, soil and vegetation patterns in an arid ecotone. Catena, 174: 353-361.‏
Deák, B.; Kovács, B.; Rádai, Z.; Apostolova, I.; Kelemen, A.; Kiss, R.; ... and Valkó, O. (2021). Linking environmental heterogeneity and plant diversity: the ecological role of small natural features in homogeneous landscapes. Science of The Total Environment, 763: 1-13.‏
Dunkerley, D. L. (2014). Vegetation mosaics of arid Western New South Wales, Australia: Considerations of their origin and persistence. Patterns of Land Degradation in Drylands, Springer: 315-345.
El-Keblawy, A.; Abdelfattah, M. A. and Khedr, A. H. A. (2015). Relationships between landforms, soil characteristics and dominant xerophytes in the hyper-arid northern United Arab Emirates. Journal of Arid Environments, 117: 28-36.‏
Flynn, T.; Rozanov, A.; Ellis, F.; de Clercq, W. and Clarke, C. (2020). Farm-scale soil patterns derived from automated terrain classification. Catena, 185: 104311.‏
Haselberger, S.; Ohler, L. M.; Junker, R. R.; Otto, J. C.; Glade, T. and Kraushaar, S. (2021). Quantification of biogeomorphic interactions between small‐scale sediment transport and primary vegetation succession on proglacial slopes of the Gepatschferner, Austria. Earth Surface Processes and Landforms.‏
Hupp, C. R. and Rinaldi, (2007). Riparian vegetation patterns in relation to fluvial landforms and channel evolution along selected rivers of Tuscany (Central Italy). Annals of the Association of American Geographers, 97(1): 12-30.
Jasiewicz, J, Pawel N, Tomasz F. Stepinski (2013). Landscape similarity, retrieval, and machine mapping of physiographic units, Geomorphology, 221: 104-112
Kim, D. and Kupfer, J. A. (2016). Tri-variate relationships among vegetation, soil, and topography along gradients of fluvial biogeomorphic succession. PloS one, 11(9): e0163223.‏
Li, X. R. et al. (2010). Micro‐geomorphology determines community structure of biological soil crusts at small scales. Earth Surface Processes and Landforms, 35(8): 932-940.
Libohova. Z, Hans, Winzeler.E, Lee.B, Philip J. Schoeneberger, Jyotishka Datta Phillip R. Owens )2016(. Geomorphons- Landform and property predictions in a glacial moraine in Indiana landscapes, Catena, 142; 66-76.
Lukina, N. V.; Orlova, M. A.; Bakhmet, O. N.; Tikhonova, E. V.; Tebenkova, D. N.; Kasakova, A. I. and Knyazeva, S. V. (2019). The influence of vegetation on the forest soil properties in the Republic of Karelia. Eurasian Soil Science, 52(7): 793-807.‏
Marchetti, Z. Y. et al. (2020). Biogeomorphic succession in a fluvial-lacustrine delta of the Middle Paraná River (Argentina): Feedbacks between vegetation and morphodynamics. Science of The Total Environment, 739: 139799.
Masoud, A. A. and Koike, K. (2006). Arid land salinization detected by remotely-sensed landcover changes: A case study in the Siwa region, NW Egypt. Journal of arid environments, 66(1): 151-167.‏
Murray, J. M. et al. (2002). Biogeomorphological implications of microscale interactions between sediment geotechnics and marine benthos: a review. Geomorphology, 47(1): 15-30.
Ngunjiri, M. W.; Libohova, Z.; Owens, P. R. and Schulze, D. G. (2020). Landform pattern recognition and classification for predicting soil types of the Uasin Gishu Plateau, Kenya. Catena, 188: 104390.‏
Nie, X.; Guo, W.; Huang, B.; Zhuo, M.; Li, D.; Li, Z. and Yuan, Z. (2019). Effects of soil properties, topography and landform on the understory biomass of a pine forest in a subtropical hilly region. Catena, 176: 104-111.‏
Paudel, S. and Vetaas, O. R. (2014). Effects of topography and land use on woody plant species composition and beta diversity in an arid Trans-Himalayan landscape, Nepal. Journal of Mountain Science, 11(5): 1112-1122.
Poelking, E. L.; Schaefer, C. E. R.; Fernandes Filho, E. I.; De Andrade, A. M. and Spielmann, A. A. (2015). Soil–landform–plant-community relationships of a periglacial landscape on Potter Peninsula, maritime Antarctica. Solid Earth, 6(2): 583-594.‏
Robaina, S. Trentin, R. Cristo, S. S. V. and Sccoti. A. A. V. (2017). Application of the concept of geomorphons to the landform classification in Tocantins state, Brazil. Raega-O Espaço Geográfico em Análise, 41: 37-48.‏
Rodrigues, P. M. S.; Schaefer, C. E. G. R; de Oliveira Silva, J.; Ferreira Júnior, W. G.; dos Santos, R. M. and Neri, A. V. (2018). The influence of soil on vegetation structure and plant diversity in different tropical savannic and forest habitats. Journal of Plant Ecology, 11(2): 226-236.‏
Stepinski, T. F. and J. Jasiewicz (2011). Geomorphons-a new approach to classification of landforms. Proceedings of geomorphometry, 109-112.
Thompson, D. B.; Walker, L. R.; Landau, F. H. and Stark, L. R. (2005). The influence of elevation, shrub species, and biological soil crust on fertile islands in the Mojave Desert, USA. Journal of Arid Environments, 61(4): 609-629.‏
Valente, C. et al. (2013). Relationships among vegetation, geomorphology and hydrology in the Bananal Island tropical wetlands, Araguaia River basin, Central Brazil. Journal of South American Earth Sciences, 46: 150-160.
Wang, J.; Wang, H.; Cao, Y.; Bai, Z. and Qin, Q. (2016). Effects of soil and topographic factors on vegetation restoration in opencast coal mine dumps located in a loess area Scientific reports, 6(1): 1-11.‏
Yan, G.; Cheng, H.; Teng, L.; Xu, W.; Jiang, Y.; Yang, G. and Zhou, Q. (2020). Analysis of the Use of Geomorphic Elements Mapping to Characterize Subaqueous Bedforms Using Multibeam Bathymetric Data in River System. Applied Sciences, 10(21): 7692.‏
Zhao, Q.; Ding, S.; Liu, Q.; Wang, S.; Jing, Y. and Lu, M. (2020). Vegetation influences soil properties along riparian zones of the Beijiang River in Southern China, 8, e9699.‏
Volume 53, Issue 3
December 2021
Pages 397-413
  • Receive Date: 21 May 2021
  • Revise Date: 17 July 2021
  • Accept Date: 29 August 2021
  • First Publish Date: 06 September 2021