Differential characteristics and driving forces of the spatial distribution of heritage trees in Luoyang, an ancient capital of China

Abstract

Heritage trees have important historical, landscape, and ecological value. Exploring the spatial distribution pattern of heritage trees is of great importance to the construction of ecological civilization and the connotation of regional history and culture. This paper took 5,216 heritage trees in Luoyang, an ancient capital of China, as the research object and used geospatial analysis methods and a geographically weighted regression model to analyze the differences and driving forces of the spatial distribution of heritage trees. Results show that 1) the heritage trees in Luoyang were primarily Gleditsia sinensis, Sophora japonica, and Platycladus orientalis, and more than half of these trees were under 300 years old; 2) the high-density area formed a distribution pattern of “three cores, one ring, and two belts,” and the distribution of heritage trees had a positive spatial autocorrelation; 3) different driving factors in different regions had complex influences on the spatial distribution of heritage trees, and the order of influence was as follows: area of forest and orchard land > elevation > number of POIs (points of interest) > distance to the nearest river > slope > number of immovable relics. The results could provide a comprehensive understanding of the spatial distribution of heritage trees to protect the ecological function of heritage trees and mine the cultural value of heritage trees.

Protecting Rural Large Old Trees with Multi-Scale Strategies: Integrating Spatial Analysis and the Contingent Valuation Method (CVM) for Socio-Cultural Value Assessment

“…Some 96.99% of the trees resided in the countryside, and the tree density was 0.10 trees/km 2 , which is very close to the nationwide statistical result of 95.15% and 0.13 trees/km 2 , respectively [7,37]. Similar to previous studies [14,20,66], the distribution of scattered large old trees showed an agglomerative pattern, with several clusters in Yi County, Laiyuan, and Quyang. A greater tree number was found in habitats of village fringe (VF), government/community/institutional ground (GC), and scenic resort/historic site (SRHS).…”

“…The nearest neighbor index (R) is defined as the ratio of the actual nearest neighbor distance to the theoretical nearest neighbor distance [14]. Here, it was used to discover the distribution patterns (including random, uniform, or cohesive) of scattered large old trees in Baoding City and Xiongan New Area.…”

“…Here, it was used to discover the distribution patterns (including random, uniform, or cohesive) of scattered large old trees in Baoding City and Xiongan New Area. "Average Nearest Neighbor" in ArcGIS Toolbox 10.2 was used for calculation, and the formula is as follows [14]:…”

“…Another way that trees may be protected is at the community level, by exploring their distribution patterns and driving factors, setting aside large reserves, and paying attention to the dynamic of key influential factors to conduction strategic protection. Such explorations have been made frequently in the literature, at different scales such as worldwide [12], nationwides [7,13], citywide [14,15], within forest parks [16], within ethnic minority settlements [17,18], and within agricultural landscapes [19], which and have provided important information for understanding and conserving of large old trees. For example, it was revealed that the distribution density of scattered large old trees in China was positively correlated with mean annual rainfall and human population density, while the distribution density of clustered large old trees was negatively influenced by human population density [7].…”

“…For example, it was revealed that the distribution density of scattered large old trees in China was positively correlated with mean annual rainfall and human population density, while the distribution density of clustered large old trees was negatively influenced by human population density [7]. A few studies conducted within large-or medium-size cities in China found that the spatial distribution of large old trees showed a state of "scattered and multiple clusters" [14,20], and districts with more scenic resort and historic site (SRHS) and higher gross domestic product (GDP) tend to accommodate more heritage trees [21].…”