Supporting effect of landscape characteristics of urban green ecotone on
avian community: A case study of Huangshan City Center
Abstract
Urban green ecotone plays an increasingly important role in supporting
avian communities. Research on ecotone primarily focuses on large scale
and mesoscale effects, leaving small-scale relationships between
interface mutations and avian communities poorly understood. This study
focused on small-scale urban green spaces and examined 29 sample plots
from four urban green spaces in downtown Huangshan, observing bird
species and numbers as indicators of avian communities. Landscape
patterns such as patch area, density, diversity index, and vegetation
characteristics such as vertical forest structure, coverage, evergreen,
deciduous, flowering, and fruits plants were selected as factors
affecting bird diversity in urban green ecotones. The results showed
that 1) ecotone area exhibited a rich composition of avian communities,
including greater species diversity and numbers than that in the pure
forest area. 2) Ecotone zones showed distinct characteristics—higher
patch density and diversity index—indicating rich land-use types and
spatial heterogeneity, supporting bird species diversity. While tree and
deciduous species appeared similar between the ecotone zone and pure
forest area, significant differences were notable in forest facies,
cover, shrubs, evergreen, flowering and fruit plants. The coverage value
of the ecotone sample was lower than that of the pure forest sample but
higher than that of the pure forest sample in terms of forest facies,
shrubs, evergreens, and fruit plants. 3) Bird species observed in the
ecotone area showed significant correlation with shrubs (r=0.284,
p<0.01), leaf litter (r=0.261, p<0.01), patch
density (r=0.326, p<0.01), and patch index (r=0.361,
p<0.01). A negative correlation was noticed with coverage
(r=-0.262, p<0.01), though it did not significantly affect
bird species. These findings will hopefully help refine the spatial
layout patterns of urban green spaces and optimize plant allocation for
enhanced environmental impact.