Road density (RD), commonly used to measure the impact of roads on landscapes [1
], is strongly associated with the ecological risks for local ecosystems because road networks run through various landscapes [3
]. Areas with high RD are often characterized by large land areas under construction and those with low forest coverage [4
], leading to a significant decline in landscape structure and ecosystem health [5
]. Linear transportation infrastructure (e.g., roads) and vehicles affect the structure of ecosystems and the dynamics of ecosystem functions. In addition, they have several direct or indirect ecological impacts on ecosystem components, including animal and plant species composition [6
], original habitat fragmentation, changes in the physical-chemical environment and microclimates [1
], invasion of weeds and pest animals, and elevated rates of poaching and wildfires [7
]. During the process of road development in urban regions, the number of original trees decrease and landscape fragmentation increases [1
]. To date, many studies have investigated the impact of road development on various landscape patterns [4
], but research on the impact of road development on forest structural or taxonomic attributes is scarce. In China, road-affected areas were 18.37% of the total terrestrial area [10
] and the government has invested 8.91 billion RMB into road greening practices. The total greening road mileage was over 50 thousand km in 2017 (http://www.ce.cn/xwzx/gnsz/gdxw/201803/12/t20180312_28436372.shtml
). The policy implementation of roadside afforestation has significantly increased the total forest area in China [11
]. These authority regulations on the greening of road networks might strongly interact with forest characteristics; nevertheless, there are very limited well-defined researches on their associations to date.
As an important part of urban green infrastructures, forests and trees have certain effects on the water, heat, carbon, and pollution cycles of a city [12
]. The fractal dimension index, patch numbers, and average patch area of forests may decrease with the development of the road network density [16
]. The most common conclusion regarding the influence of RD on landscape patterns is that RD could reduce the average original vegetation patch area and increase the number and distance between these patches [4
]. Moreover, there is a negative correlation between the plant species richness and the intensity of road construction [17
]. At the city level within the buildup region, a well-designed configuration of roads and urban forests could potentially maximize ecological services, and a basis for such configuration is an exact understanding of their complex associations [18
]. Landscape metrics derived from remote sensing classification results have been used to evaluate temporal and spatial changes of forests as well as management effectiveness [19
]. Together with remote sensing methods and field surveys, urbanization-induced variations of forest structural traits, such as tree height, diameter at breast height, canopy size, and compositional traits, and their association with carbon sequestration have been studied [13
]. Furthermore, it is reported that urban forest landscape metrics (e.g., forest aggregation and patch sizes) are strongly associated with structural-taxonomic attributes, and these metrics are possible indicators of urban forest characteristics [24
]. To date, no study has simultaneously studied road characteristics (both representation at urbanization levels and a specific ecological meaning), landscape metrics of forest, and forest characteristics with regards to species composition and individual sizes. However, the association and decoupling of these metrics will possibly favor urban greenspace management based on road ecological considerations [6
Recent methodological advances dealing with complex associations in the natural environment gave hints for decoupling relationships between road development, urban forest landscapes, and structural-taxonomic attributes. The associations between road development and forest landscape pattern has been explored through correlation analysis and curve fitting [26
], as well as association coefficient and the trend analysis [27
]. Principal component analysis (PCA) could quantitatively analyze the impact of road development on forest landscape patterns [17
]. Redundancy ordination (RDA) and variation partitioning have been used to decouple complex associations among various ecological factors [23
], such as association between glomalin-related soil carbon sequestration and climate and soil physiochemical properties [23
], tree microclimate regulation’s association with background conditions [28
], plant species diversity’s associations with forest community features [29
], and the association between carbon sequestration and forest landscape patterns [31
]. Co-utilization of regression analysis, RDA, and variation partitioning will favor the decoupling of the complex association among road development, forest landscape, and structural-taxonomic attributes.
Using the city of Harbin (the north-most provincial capital city in China, with a population of over 9.6 million in the administrative regions) as an example, in this study, we hypothesized that road development negatively affects forest structural-taxonomic attributes and forest landscape patterns (e.g., road development would reduce forest structural and taxonomic attributes and drive landscape fragmentation) and that the decoupling of their associations may favor urban greenspace management. The main questions addressed in this study are as follows:
(1) What are the changing patterns of urban forest landscape metrics, structural-taxonomic attributes, and road characteristics at different RDs?
(2) How should the associations among RD, landscape metrics, and forest structural-taxonomic attributes be ordinated, and which landscape metrics and road characteristics are indicative of forest structural-taxonomic attributes?
(3) Are there any suggestions for the reasonable planning and management of urban forests that will optimize the ecological service benefits of urban forests?
To verify our hypothesis, we first obtained urban forest field-survey data and extracted and calculated road and landscape metrics data. Then, the road-dependent changes of the forest structural-taxonomic attributes and landscape patterns were studied by heavy, medium, and low road density classification. Finally, the associations and decoupling between road characteristics, forest structural-taxonomic attributes, and landscape patterns were explored by ordination and variation partitioning analysis for possible improvements in road-related landscape planning and management of urban forests.