Elsevier

Urban Forestry & Urban Greening

Volume 38, February 2019, Pages 33-41
Urban Forestry & Urban Greening

Most suitable landscape patterns to preserve indigenous plant diversity affected by increasing urbanization: A case study of Shunyi District of Beijing, China

https://doi.org/10.1016/j.ufug.2018.11.004Get rights and content

Abstract

The effects of urbanization on plant diversity have been increasingly investigated around the world, but our knowledge of the performances of urbanized landscape is still inadequate for suitable urban landscape planning and management. We asked: 1) what are the effects of urbanized landscape pattern on indigenous plant diversity, and 2) do these effects exhibit scale dependence? A total of 105 plots, distributed throughout the study area were chosen. Each plot was 10 m × 10 m. Alpha-diversity, and beta-diversity of species taxonomic composition across plots was calculated. Four groups of landscape metrics (complexity, fragmentation, diversity, and urbanization intensity) were measured for each plot. Ten scales, ranging from 100 m to 1000 m and with increasing steps of 100 m, were used as spatial scales. Pearson’s correlation analyses were used to detect relationships between the indigenous plant diversity along the urbanization gradient and the ten landscape metrics. Shannon’s Diversity Index (SDI), Shannon’s Evenness Index (SEI), Edge Density (ED), and Landscape Shape Index (LSI) were highly and positively correlated with alpha and beta plant diversity, whereas Largest Patch Index (LPI) were negatively correlated with plant diversity. Such correlations became stronger at higher spatial scales, and the highest at 600–700 m. The intensity of urbanization increased the values of ED and LPI in urbanized landscape and negatively influenced plant diversity. The correlations were influenced by the spatial extent. The study offers some guidelines on landscape pattern, including patch size, shape, and its configuration, in managing urban areas optimally to support plant diversity and wildlife. Landscape unit with diverse land uses with a radius of 600–700 m for Beijing, and other specific radius for other cities in the world are proposed as the most suitable landscape pattern for preserving indigenous plant diversity.

Introduction

Urbanization, which is often marked by changes in land use and fragmentation, is being increasingly recognized as the cause of many ecological problems such as loss of biodiversity and the urban heat island effect (Romero et al., 2012; Liu et al., 2015). These adverse effects have become a hot topic in Europe, North America, and Australia in the recent past (Sukopp, 2004; Crane and Kinzig, 2005; McKinney, 2006), also begin to be noticed in the developing countries (Wang et al., 2012; Yan and Yang, 2017). The negative effect of urbanization on native plant species has been extensively investigated (Chocholouskova and Pysek, 2003; McKinney, 2006), although a positive effect is also on record (Moffatt et al., 2004). The species richness in the former studies encompassed only native plant species, whilst the later included both native and alien plant species (Knapp et al., 2008; Muratet et al., 2008; Rija et al., 2014).

One analysis of 11,525 sites across the world showed that species richness and total abundance of plants were slightly lower in the more intensively urban sites, and species richness also tended to be lower nearby roads and in 122 more accessible sites (Moffatt et al., 2004). The estimated richness was 76.5% lower in intensively urban sites than that in countryside (Newbold et al., 2015). In urban environments, the density of plant species (the number of species per square kilometre) has declined substantially, and only 25% of the native plant species remain (Aronson et al., 2014b). In Paris, France, the presence of non-building zones (notably rivers and ponds and, to a lesser extent, forests, open urban and rural areas, and vacant urban areas) had a positive impact on plant diversity. In contrast, all kinds of building zones, and especially collective dwelling sites, had a significant negative influence on plant diversity (Muratet et al., 2008). One study in Beijing originate a downbeat correlation between the remoteness from the city centre and both species richness and density of shrubs and trees, and nearly half of the total urban plant species were found to be aliens (Wang et al., 2012). Plant diversity increased with increasing distance from the city centre but was also negatively affected by the proportion of built-up areas, as was reported in several other studies (Vakhlamova et al., 2014). However, as mentioned earlier, some studies have also reported the opposite results, namely that urbanization enhances plant diversity (Honnay et al., 2003; Muratet et al., 2008; Knapp et al., 2008), since alien plant species were also encompassed in the study. For example, a case study in Tanzania reported the proportion of exotic species in the urban area was significantly higher (75.6%) than that of native species (Rija et al., 2014).

With the advance of study, the effects of the urban landscape pattern, i.e. the composition and configuration of urban patches on plant diversity have been the topic of recent studies. The landscape structure, formed by different land uses, habitats, and their configuration can significantly shape and regulate the composition and diversity of plant communities (Walz, 2015). Computer simulations indicate that plant diversity is sensitive to the effects of habitat loss and speciation rate caused by landscape metrics (Campos et al., 2013). In one case study, landscape metrics explained 25%–28% of the variation in plant diversity (Monteiro et al., 2013). Landscape metrics are good indicators of overall species richness, especially of woody plants. Among the different landscape metrics, those that describe patch shape, proximity, texture, and landscape diversity are often better indicators than those that describe patch area, similarity, and edge contrast (Schindler et al., 2013), and the spatial scale affects such correlations between landscape metrics and plant diversity (Higgins et al., 2012; Schindler et al., 2013). Landscape metrics indicate three aspects: complexity (patch shape and its complexity), disturbance (by human beings), and fragmentation (distances and the degree of isolation among inhabited patches) (Amici et al., 2015). Disturbance (distance to human settlements, distance from the road) contributed the most to explaining the variance of total species richness, and fragmentation contributed the most to explaining the variance of forest species richness, whereas complexity contributed very low (Amici et al., 2015). In north-eastern Greece, landscape metrics, especially fragmentation, were good indicators of the species richness of woody plants, orchids, and birds (Schindler et al., 2013). Landscape complexity proved to be a particularly sensitive indicator of plant richness (Moser et al., 2002). Landscape pattern of urban areas also demonstrated a close relationship with plant richness (Lososova et al., 2011; Bourne and Conway, 2014; Malkinson et al., 2018). Sizes and proportions of various land uses within urban landscape demonstrated different relations with plant richness (Melliger et al., 2017). The relationships between urban properties and species richness patterns have been disentangled by the patch-matrix approach (Malkinson et al., 2018). The effects of urban landscape complexity, fragmentation and diversity on plant species diversity are still unknown.

Beijing is the fastest urbanizing location in the world: its urban area and population almost doubled within 15 years. Beijing is therefore a particularly suitable site for examining the changes in native plant species as move from its centre to its suburbs and beyond to find out which the landscape metrics of an urbanizing area impact the diversity of indigenous plants species. Thus, the aims of this study are: 1) to explore the effects of urbanized landscape on plant diversity and the most suitable metrics for preserving plant diversity, and 2) to explore the effects of spatial scale on the correlations between landscape and plant diversity and discern the optional scales

Section snippets

Study area

The study area (40°00ʹ–40°18ʹ N and 116°28ʹ–116°56ʹ E) is the part of Shunyi district of Beijing City (Fig. 1) and is spread over 1021 km², of which 95.7% consists of a plain. The area is divided into six communities, 19 towns, and 426 villages. Twenty rivers flow through the study area, and the slope of the area is about 0.06%. The highest elevation is 637 m, at one edge of the study area, whereas the average elevation is 35 m. The climate is of the semi-humid continental monsoon type, the

Relationship between landscape metrics and the Shannon–Wiener index

For the Shannon–Wiener index of indigenous plant diversity, the landscape metrics showed a significant influence, the dominant among them being edge density (ED), landscape shape index (LSI), Largest patch index (LPI), and PSCoV (Tables 2A–2C): ED and LSI showed the highest and positive correlations (0.131–0.244) with the Shannon–Wiener index, followed, in that order, by Shannon’s Diversity Index (SDI) (0.110–0.192), Shannon’s Evenness Index (SEI) (0.100–0.201), and patch richness density (PRD)

Complexity of the urban landscape and plant diversity

Landscape complexity indicates the complexity of patch shape and the characteristics of the edges that define the shape and has proved to be a sensitive indicator of plant richness, especially in agricultural landscapes (Moser et al., 2002). In the urban environment of the current study, landscape complexity contributes 2–22% to plant diversity, higher than landscape diversity and less than fragmentation. ED and LSI showed approximately the same affirmative correlations with the Shannon–Weiner

Conclusion and recommendation

Shannon’s Diversity Index, SEI, ED, and LSI were robustly and positively correlated to alpha and beta plant diversity at all the spatial scales among the four groups of landscape metrics (complexity, fragmentation, diversity, and urbanization intensity). PSCoV and LPI were negatively correlated to plant diversity, the correlations becoming stronger with increasing spatial scales. Urbanization intensity increased the values of ED and LPI, and negatively influenced plant diversity. Landscape

Conflict of interest

The authors declare no competing financial interests.

Acknowledgments

The study was financially supported by the Top Discipline and First-class University Construction Project (ydzxxk201818) of Minzu University of China; The study project from the Collaborative Innovation Centre for Ethnic Minority Development in China; the Undergraduate Research and Training Program (URTP2017110024) of Minzu University of China. Thanks to Dr. Nabi for his improvement in English expression of the manuscript.

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