Mechanisms of the effects of solar radiation and terrain anisotropy on the vegetation of dark conifer forests in the Pechora-Ilych state biosphere reserve

Shary, P. A.; Смирнов, Н. С.

doi:10.1134/s1067413613010116

Cited by 12 publications

(9 citation statements)

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“…Insolation is utilized to describe the thermal regime of slopes in geobotanical and agricultural research (Shary and Smirnov, 2013;Shary et al, 2016). Catchment and dispersive areas as well as topographic index are widely used in hydrological and related soil, plant and geomorphic studies (Behrens et al, 2010;Beven, 1997;Florinsky et al, 2002;Mitusov et al, 2013Mitusov et al, , 2014Moore et al, 1993;Omelko et al, 2012;Sharaya and Shary, 2011;Shary and Smirnov, 2013). Stream power index is applied in erosion and soil research (Florinsky et al, 2002;Moore et al, 1993;Omelko et al, 2012).…”

Section: Application Of Morphometric Variablesmentioning

confidence: 99%

An illustrated introduction to general geomorphometry

Florinsky

2017

Progress in Physical Geography: Earth and Environment

101

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Geomorphometry is widely used to solve various multiscale geoscientific problems. For the successful application of geomorphometric methods, a researcher should know the basic mathematical concepts of geomorphometry and be aware of the system of morphometric variables, as well as understand their physical, mathematical and geographical meanings. This paper reviews the basic mathematical concepts of general geomorphometry. First, we discuss the notion of the topographic surface and its limitations. Second, we present definitions, formulae and meanings for four main groups of morphometric variables, such as local, non-local, two-field specific and combined topographic attributes, and we review the following 29 fundamental morphometric variables: slope, aspect, northwardness, eastwardness, plan curvature, horizontal curvature, vertical curvature, difference curvature, horizontal excess curvature, vertical excess curvature, accumulation curvature, ring curvature, minimal curvature, maximal curvature, mean curvature, Gaussian curvature, unsphericity curvature, rotor, Laplacian, shape index, curvedness, horizontal curvature deflection, vertical curvature deflection, catchment area, dispersive area, reflectance, insolation, topographic index and stream power index. For illustrations, we use a digital elevation model (DEM) of Mount Ararat, extracted from the Shuttle Radar Topography Mission (SRTM) 1-arc-second DEM. The DEM was treated by a spectral analytical method. Finally, we briefly discuss the main paradox of general geomorphometry associated with the smoothness of the topographic surface and the non-smoothness of the real topography; application of morphometric variables; statistical aspects of geomorphometric modelling, including relationships between morphometric variables and roughness indices; and some pending problems of general geomorphometry (i.e. analysis of inner surfaces of caves, analytical description of non-local attributes and structural lines, as well as modelling on a triaxial ellipsoid). The paper can be used as a reference guide on general geomorphometry.

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Section: Application Of Morphometric Variablesmentioning

confidence: 99%

An illustrated introduction to general geomorphometry

Florinsky

2017

Progress in Physical Geography: Earth and Environment

101

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“…In the present study relief was represented by local geomorphometric characteristics, such as elevation, slope gradient and slope aspect, which strongly affect vegetation structure [ 16 , 22 , 23 ]. Elevation (height of land relative to sea level) and its variation are usually related to local microclimate.…”

Section: Introductionmentioning

confidence: 99%

“…Slope gradient and slope aspect determine the intensity and direction of flows of matter and insolation, respectively, and affect the local water and energy regimes. In addition to these variables, the basic set of characteristics for local land characterization should also include the plan and profile curvatures [ 22 , 24 , 25 , 26 ]. The plan curvature corresponds to the variation among the convex, straight and concave landforms of the terrain and the profile curvature corresponds to the variation among the divergent, neutral and convergent landforms of the terrain [ 27 ].…”

Section: Introductionmentioning

confidence: 99%

“…Several studies have analysed the influence of environmental variability on spatial differentiation of vegetation. However, few have rigorously tested the effects of local geomorphometric variation on the structural characteristics of vegetation [ 22 , 29 , 30 ], such as BA, H and CO, especially when the relief descriptor variables are derived from remote sensing data. The topography can affect the vegetation structure both directly and indirectly.…”

Section: Introductionmentioning

confidence: 99%

“…For example, Webb et al [ 31 ] analysed the direct effects of topography on forest structure in an area of American Samoa and observed higher tree density in ridge forests, with trees of wide diameter and low height at higher altitudes (usually in ridges). In contrast, relief also influences other variables that are important for vegetation, such as humidity, nutrient availability, solar radiation, temperature and soil characteristics, which may have indirect effects on vegetation [ 21 , 22 , 32 , 33 , 34 , 35 ].…”

Section: Introductionmentioning

confidence: 99%

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Predictive Models of Primary Tropical Forest Structure from Geomorphometric Variables Based on SRTM in the Tapajós Region, Brazilian Amazon

Bispo¹,

Santos²,

Valeriano³

et al. 2016

PLoS ONE

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Surveying primary tropical forest over large regions is challenging. Indirect methods of relating terrain information or other external spatial datasets to forest biophysical parameters can provide forest structural maps at large scales but the inherent uncertainties need to be evaluated fully. The goal of the present study was to evaluate relief characteristics, measured through geomorphometric variables, as predictors of forest structural characteristics such as average tree basal area (BA) and height (H) and average percentage canopy openness (CO). Our hypothesis is that geomorphometric variables are good predictors of the structure of primary tropical forest, even in areas, with low altitude variation. The study was performed at the Tapajós National Forest, located in the Western State of Pará, Brazil. Forty-three plots were sampled. Predictive models for BA, H and CO were parameterized based on geomorphometric variables using multiple linear regression. Validation of the models with nine independent sample plots revealed a Root Mean Square Error (RMSE) of 3.73 m2/ha (20%) for BA, 1.70 m (12%) for H, and 1.78% (21%) for CO. The coefficient of determination between observed and predicted values were r2 = 0.32 for CO, r2 = 0.26 for H and r2 = 0.52 for BA. The models obtained were able to adequately estimate BA and CO. In summary, it can be concluded that relief variables are good predictors of vegetation structure and enable the creation of forest structure maps in primary tropical rainforest with an acceptable uncertainty.

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