ISSN 10674136, Russian Journal of Ecology, 2013, Vol. 44, No. 5, pp. 381–386. © Pleiades Publishing, Ltd., 2013.
In the area with the same climate, topography is
one of the most important factors that affect the vege
tation pattern (Hara et al., 1996a). Topography con
trols the redistribution of spatial resources, e.g., light,
heat, water and soil nutrients by the geomorphy
change (Kikuchi, 2001), thus affecting the plant distri
bution pattern. The relationship between the vegeta
tion and topography has recently been explored in sev
eral studies: such as slope position on the influence of
vegetation pattern (Noki, 2003), vegetation pattern on
some process response (D’Odorico et al., 2005), and
so on. Moreover, Swansond et. al (1988) analyzed the
effects of topography on ecosystem patterns, which
could indirectly control the vegetation patterns at dif
ferent scales (Inoue et al., 2008).However, the cyclical
phenomenon of the vegetation pattern fluctuating
with the topography is rarely researched. Generally, in
arid and semiarid mountain, we will find rolling hills,
with treescovered and barren slopes extending alter
nately, forming a regular change, which is topography
and vegetation fluctuations showed correspond.
In order to take into account the influences of topog
raphy in different scales on the vegetation patterns, scal
ing was often used in ecological researches. Wavelet anal
ysis is a good tool to research on multiscale phenomena.
Wavelet analysis can emphasized variability, even within
The article is published in the original.
cyclic phenomena, and suggested hierarchical structure
in the patterns (Sari C. Saunders al. 2005). Ecology is
often used mexh and morl, the Mexican Hat provides
better detection and localization of patch and gap events
over the Morlet (Mi, 2005), whereas morl may indicate
the vegetation pattern at multiscales. Because the peri
ods of these two wavelets are largely different, they can
not be directly used to study the same phenomenon.
Therefore, utilization of the ecologically using wavelet
with the same period can distinguish the cycle character
istics of vegetation pattern at multiscales, and is signifi
cant to understand the maintenance mechanisms of
scaledependent vegetation pattern.
is a perennial small tree or shrub
like plant distributed and grown on shifting or half
shifting sand dunes. In this work, taking Gurbantung
gut Desert dominant tree species as an example, the
ecologically using Mexh and Morl wavelet with unan
imous period (torrence and compo, 1998b) is selected
to research a given phenomenon. The objectives of this
study are: (1) to discuss the cyclic phenomena of in
limited distance in the Gurbantunggut desert, China,
and the maintenance mechanisms of cycle phenome
non at a given scale; (2) to forecast tendency of
distribution patters at given scale.
The areas included in this study were located at Jinghe
E), Kuitun (44
The Cycle Characteristics of
and Topography at Multiscales in Gurbantunggut Desert, China
Yuyang Song, Yuanyuan Li, and Mingyan Li
Department of Forestry, Agricultural College, Xinjiang Shihezi University, Shihezi, Xinjiang 832003, China
Received October 10, 2012
—We employed ecologically using Mexh and Mori wavelet methods to analyze the cycle phenomena
and their maintaining mechanisms of the
distribution in complex longitudinal
sand ridges (CLSRS). The results showed that ecologically using wavelet can distinguish
distributed in parallelshaped, latticeshaped and forkshaped dunes with a dominant cycle of 165–180 m,
100–110 m and 70–80 m, respectively. Besides the dominant cycle, ecologically using Mori wavelet also
showed 2–3 minor small peaks on different scales. The mechanisms to maintain the cycles at multiscales of
relies on the seed spread, interference intensity in different topography and soil properties.
The formations, configurations and presences of the three types of dunes should have some direct relations
with the wind fields of the areas where the patterns are located, and also with the ground surface conditions.
If the distribution pattern is periodic, meanwhile the abrupt change points are significant; we can predict the
distribution pattern in a certain area.
, Ecologically using wavelet, Cycle phenomena, Topography, Prediction