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. 2021 Aug 5;11(17):12204-12219.
doi: 10.1002/ece3.7985. eCollection 2021 Sep.

Positive relationships among aboveground biomass, tree species diversity, and urban greening management in tropical coastal city of Haikou

Affiliations

Positive relationships among aboveground biomass, tree species diversity, and urban greening management in tropical coastal city of Haikou

Mir Muhammad Nizamani et al. Ecol Evol. .

Abstract

Within urban green spaces, tree species diversity is believed to correlate with aboveground biomass, though there is some disagreement within the literature on the strength and directionality of the relationship. Therefore, we assessed the relationship between the biodiversity of woody species and the aboveground biomass of woody plant species in the tropical, coastal city of Haikou in southern China. To accomplish this, we obtained comprehensive tree and site data through field sampling of 190 urban functional units (UFUs, or work units) corresponding to six types of land uses governmental-institutional, industrial-commercial, park-recreational, residential, transport infrastructure, and undeveloped area. Based on our field data, we investigated the relationship between tree species diversity and aboveground biomass using multiple regression, which revealed significant relationships across all five types of land uses. Aboveground biomass in green spaces was also correlated with anthropogenic factors, especially time since urban development, or site age, annual maintenance frequency by human caretakers, and human population density. Among these factors, maintenance is the strongest predictor of aboveground biomass in urban green space. Therefore, this study highlights the critical role of maintenance of urban green space in promoting both aboveground biomass and woody biodiversity in urban ecosystems and, consequently, on urban ecosystem services. Our findings contribute to a deeper understanding of the ecosystem services provided by communities of woody plant species in urban areas.

Keywords: Simpson diversity index (D); ecosystem services; functional traits; multiple regression.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

FIGURE 1
FIGURE 1
Field sampling plot showing the urban forest of Haikou. (a) Terminalia catappa (Gaertn.) Eichler in the residential area of Haikou, the top of their trunk was lost in the typhoon. (b) Pandanus utilis Bory. (c) Phoenix dactylifera L. (d) Roystonea regia L.H. Bailey. (e) Caryota mitis Lour. (f) Ceiba speciosa (A. St.‐Hil.) Ravenna. (g) Ficus benghalensis L. (h) Casuarina cunninghamiana Miq. (i) Washingtonia robusta H. Wendl
FIGURE 2
FIGURE 2
Workflow for establishing urban sampling plots used in this study is shown using a cartoon diagram. (a) We established a grid over the full geographic extent of the study area. Within each grid cell (highlighted in yellow), we identified associated aggregates of infrastructure, or work units, and assigned these to one of four types of land use. In this cartoon, the types of land use comprise Red, Green, Blue, and Purple, and each aggregate (outlined in black) may extend into multiple grid cells. (b) Within each grid cell, such as the one highlighted in yellow, we identified (i) work units occupying the most land area within the cell and (ii) any culturally significant work units, such as parts, historical sites, and so on. (c) Within work units covering the most land area (i.e., Purple) and in culturally significant sites if any (i.e., Blue), we performed fieldwork to visually identify areas suitable for establishing sampling plots (i.e., they contained vegetation, not roads or buildings as indicated by white areas), and we sought to find the most diverse areas for plots (i.e., represented by increasingly dark colors) to best determine the full extent of species diversity within the sampled work unit. Within the sampling plots, we counted all woody species that we observed
FIGURE 3
FIGURE 3
Images showing the locations of the study. (a) Map of China yellow highlighted is Hainan and blue highlighted is Haikou. (b) Map of Haikou. (c) SPOT‐7 satellite image of Haikou city showing the vegetation cover in relation to impermeable area cover and the sample area
FIGURE 4
FIGURE 4
Four pictures of the undeveloped types of land use
FIGURE 5
FIGURE 5
UPGMA tree of dissimilarity using a Euclidean distance matrix of the z‐transformed all variables to detect covariance. Species diversity (S), Simpson diversity index (D), Shannon diversity index (He), Pielou evenness index (Je), site age, annual maintenance frequency, and population density
FIGURE 6
FIGURE 6
Aboveground biomass per unit area of five urban types of land use

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