Urban forest landscape patterns in Ma'anshan City, China

Author(s):  
Yuan Wang ◽  
Ze-Min Wu ◽  
Xiang-Rong Wang
2018 ◽  
Vol 10 (12) ◽  
pp. 4397 ◽  
Author(s):  
Yang Li ◽  
Chunyan Xue ◽  
Hua Shao ◽  
Ge Shi ◽  
Nan Jiang

The landscape patterns of urban forests not only reflect the influence of urbanization on urban forests, but also determines its function in urban ecosystem services. In the case of mastering the overall forest landscape pattern of a city, a study of the structure of urban forest landscapes at different scales and in urbanized regions is beneficial to a comprehensive understanding of the forest characteristics of a city. In the present study, an attempt was made to map and monitor the spatio-temporal dynamics of an urban forest in Shanghai from 2004 to 2014 using remote sensing techniques. Methods of landscape ecology analysis are followed to quantify the spatiotemporal patterns of an urban forest landscape by urban and rural gradient regionalization. The results show that the spatial structure of an urban forest landscape is essentially consistent with an urban landscape pattern. Due to strong interference from human activities, the ecological quality of forest landscapes is low. At the landscape level, the urban forest coverage rate increased from 11.43% in 2004 to 16.02% in 2014, however, the number of large patches decreased, there was a high degree of urban forest landscape fragmentation, landscape connectivity was poor, landscape patch boundaries were uniform, and weak links were present between ecological processes. Different urban and rural gradient division methods exhibit obvious gradient characteristics along the urban–rural gradient in Shanghai. The regional differences in the urban forest landscape ecological characteristics have further increased as a result of urban planning and zoning. The total amount of urban forest is located closer to the urban center, which has the smallest total amount of forest; however, in terms of urban forest coverage, the suburbs have more coverage than do the outer suburbs and the central urban areas. The urban forest landscape’s spatial distribution area is evidently different. Urbanization affects the areas closest to urban residential areas, which are markedly disturbed by humans, and the urban forest landscape has a high degree of fragmentation. The forest patches have become divided and unconnected, and the degree of natural connectivity has gradually decreased over the past 10 years. At the landscape class level, broadleaf forests are dominant in Shanghai, and their area exhibits an increasing trend; shrublands and needleleaf forests, however, show a decreasing trend. Compared with other forest types, the spatial distribution of broadleaf forest is concentrated in the suburbs, and the aggregation effect is relatively apparent. From the perspective of urban forest landscape pattern aggregation characteristics in Shanghai, the spatial distribution of urban forest landscape point patterns in the study area exhibit extremely uneven characteristics. The point density of urban forest patches larger than 1 ha in Shanghai increased from 2004 to 2014. However, the total number of patches with areas larger than 5 ha decreased, and this decrease plays an important role in the ecological environment. In the past 10 years, the concentration characteristics of urban forests with large patches has gradually decreased. In 2014, the urban forest landscapes decreased by 5 km compared to the intensity of aggregates in 2004, which also indicates that urban forests in Shanghai tend to be fragmented. The results of this study can be useful to help improve urban residents’ living environments and the sustainable development of the urban ecosystem, and they will also be vital to future management.


PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e5825 ◽  
Author(s):  
Hailiang Lv ◽  
Wenjie Wang ◽  
Xingyuan He ◽  
Chenhui Wei ◽  
Lu Xiao ◽  
...  

Background Urban forests help in mitigating carbon emissions; however, their associations with landscape patterns are unclear. Understanding the associations would help us to evaluate urban forest ecological services and favor urban forest management via landscape regulations. We used Harbin, capital city of the northernmost province in China, as an example and hypothesized that the urban forests had different landscape metrics among different forest types, administrative districts, and urban–rural gradients, and these differences were closely associated with forest carbon sequestration in the biomass and soils. Methods We extracted the urban forest tree coverage area on the basis of 2 GF-1 remote sensing images and object-oriented based classification method. The analysis of forest landscape patterns and estimation of carbon storage were based on tree coverage data and 199 plots. We also examined the relationships between forest landscape metrics and carbon storage on the basis of forest types, administrative districts, ring roads, and history of urban settlements by using statistical methods. Results The small patches covering an area of less than 0.5 ha accounted for 72.6% of all patches (average patch size, 0.31 ha). The mean patch size (AREA_MN) and largest patch index (LPI) were the highest in the landscape and relaxation forest and Songbei District. The landscape shape index (LSI) and number of patches linearly decreased along rural-urban gradients (p < 0.05). The tree biomass carbon storage varied from less than 10 thousand tons in the urban center (first ring road region and 100-year regions) to more than 100 thousand tons in the rural regions (fourth ring road and newly urbanized regions). In the same urban–rural gradients, soil carbon storage varied from less than five thousand tons in the urban centers to 73–103 thousand tons in the rural regions. The association analysis indicated that the total forest area was the key factor that regulates total carbon storage in trees and soils. However, in the case of carbon density (ton ha−1), AREA_MN was strongly associated with tree biomass carbon, and soil carbon density was negatively related to LSI (p < 0.01) and AREA_MN (p < 0.05), but positively related to LPI (p < 0.05). Discussion The urban forests were more fragmented in Harbin than in other provincial cities in Northeastern China, as shown by the smaller patch size, more complex patch shape, and larger patch density. The decrease in LSI along the rural-urban gradients may contribute to the forest carbon sequestrations in downtown regions, particularly underground soil carbon accumulation, and the increasing patch size may benefit tree carbon sequestration. Our findings help us to understand how forest landscape metrics are associated with carbon storage function. These findings related to urban forest design may maximize forest carbon sequestration services and facilitate in precisely estimating the forest carbon sink.


1988 ◽  
Vol 12 (1) ◽  
pp. 83-107 ◽  
Author(s):  
George V Profous ◽  
Rowan A Rowntree ◽  
Robert E Loeb

2014 ◽  
Vol 18 (1) ◽  
pp. 223-238 ◽  
Author(s):  
Sanna Mäkeläinen ◽  
Marko Schrader ◽  
Ilpo K. Hanski

1991 ◽  
Vol 57 (1) ◽  
pp. 73-88 ◽  
Author(s):  
William J. Ripple ◽  
G.A. Bradshaw ◽  
Thomas A. Spies

Forests ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1691
Author(s):  
Jie Zhang ◽  
Zhi Yang ◽  
Zhuo Chen ◽  
Mengyuan Guo ◽  
Peng Guo

Interacting with urban spaces that are green and blue is believed to promote mental well-being and positive emotions. Therefore, there is an incentive to strategically design urban forest landscapes in a given space to evoke more positive emotion. In this study, we conducted a pilot study in Northeast China with 24 parks from 11 cities across 3 provinces. The subjects of the study are the visitors and a total of 1145 photos and selfies were collected from open micro-twitters in Sino Weibo (~50 individuals per park). Facial expressions of happy and sad emotions were recognized and rated as percent scores by FireFACE v1.0. Demographically, male adolescents smiled more than male visitors in other age groups and female teens. Females expressed more positive emotions than males according to their positive response index (PRI; happy-sad). Multivariate linear regression indicated positive contribution of green space to happy scores (estimate of 0.0040) and a stronger negative contribution of blue area to sad scores (estimate of −0.1392). Therefore, an urban forest landscape can be optimized by mapping green- and blue-spaces to predict spatial distributions of positive emotions. Male teens are recommended more as frequent visitors than people in other age ranges.


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