Population Structure and Spatial Distribution Pattern of Populus euphratica Riparian Forest Under Environmental Heterogeneity Along the Tarim River, Northwest China

Abstract

Populus euphratica Oliv. (Euphrates poplar), as the dominant tree species of desert riparian forests along the Central Asian inland rivers, plays a critical role in protecting arid land ecosystems. In recent decades, climate change and excessive water resources utilization activities have led to the environmental degradation of desert riparian forests along the Tarim River in northwest China. Understanding the forest stand structure and spatial distribution pattern provide important guidance for monitoring forest dynamics in support of sustainable management. However, few studies have examined how riparian forests stand attributes differ in response to environmental heterogeneity. In this study, terrestrial laser scanning (TLS) was applied to acquire a total of 1648 individual P. euphratica tree’s 3D structure attributes within 18 plots along the upper, middle, and lower reaches of the Tarim River, which included tree height (TH), diameter at breast height (DBH), crown diameter (CD), crown projection area (CPA), stand density index (SDI), age structure ratios, and spatial pattern. The results showed that the average tree segmentation and structure determination accuracies of TLS were 93.2 and 94.6%. From the upper to the lower reaches, the average TH and CD decreased by 3.8 and 0.3 m, while the DBH increased by 4.2 cm. The SDI and CPA exhibited the following order: upper reaches (454 n ha–1, 82.3%) > middle reaches (382 n ha–1, 67.3%) > lower reaches (263 n ha–1, 39.1%), the differences were significant at 0.05 level. The population age structure changed from growing population in the upper reaches to stable population in the middle and a temporarily stable population in the lower reaches. The pair correlation g(r) function determined random distribution pattern in the upper reaches [g(r) = 1.2], an aggregated pattern in the middle [g(r) = 3.1], and lower reaches [g(r) = 9.7]. The decline in groundwater depth and soil moisture increased aggregated distribution pattern (R = 0.67 and 0.56, P < 0.05) of the P. euphratica along the mainstream of Tarim River. The results enrich our understanding of the current development stage of P. euphratica, which is important for optimizing management strategies and realizing the sustainability of floodplain ecosystems.

The Effect of Elevation on the Population Structure, Spatial Patterning and Intraspecific Interactions of Picea schrenkiana in the Eastern Tianshan Mountains: A Test of the Stress Gradient Hypothesis

“…In highly heterogeneous environments, adults may aggregate in plots with better soil nutrients. For instance, there is a clear pattern of aggregated distribution of adult Populus euphratica in fragmented habitats [7]. In the case of P. schrenkiana, the spatial clustering of adults is observed relatively infrequently, indicating that density-dependent self-thinning is the primary reason for the even distribution of adults.…”

“…Age structure, which refers to the distribution of different age groups within a population, serves as a crucial indicator for characterizing future population trends [5]. A population's spatial distribution ultimately Forests 2023, 14, 2092 2 of 14 results from the interactions of its individuals with their immediate environment [6][7][8]. Due to competition among nearby plants for light, soil nutrients, and water resources, plants respond immediately to their close neighbors [8,9].…”

Improving the Estimation of Structural Parameters of a Mixed Conifer–Broadleaf Forest Using Structural, Textural, and Spectral Metrics Derived from Unmanned Aerial Vehicle Red Green Blue (RGB) Imagery

“…However, different UAV metrics and highresolution imagery offer relatively higher estimation accuracy, particularly with RGB imagery. In this study, we extracted structural, textural, and spectral metrics from high spatial resolution RGB imagery to predict forest structural parameters [33]. The classification accuracy of land use improves with high spatial resolution remote sensing images (>1.65 m/pixel) in heterogeneous forests using spectral and textural features [37,40].…”

“…Previous studies have estimated forest structural parameters using area-based approaches (plot, stand, or landscape level) [18,19,31], an individual-based approach [7,10,13,15,20,21], or both [14,17]. In this study, forest structural parameters were estimated using an area-based approach suitable for explaining forest complexity and spatial distribution patterns [32,33].…”

Population Structure, Distribution, and Spatial Characteristics of Alsophila spinulosa in Chishui, China

“…In contrast, the correlations between age classes significantly differed at larger scales and tended to plateau. This may result from a combination of clustering [30], density constraints [31], dispersal limitation [32], and habitat heterogeneity [33]. Clustering can increase individual survival as a means of defense against external threats.…”