Effects of Urban Forest Types and Traits on Soil Organic Carbon Stock in Beijing
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Article Effects of Urban Forest Types and Traits on Soil Organic Carbon Stock in Beijing Xinhui Xu 1,2, Zhenkai Sun 1,2,*, Zezhou Hao 1,2, Qi Bian 1,2, Kaiyue Wei 1,2 and Cheng Wang 1,2 1 Research Institute of Forestry, Chinese Academy of Forestry, Beijing 100091, China; [email protected] (X.X.); [email protected] (Z.H.); [email protected] (Q.B.); [email protected] (K.W.); [email protected] (C.W.) 2 Key Laboratory of Tree Breeding and Cultivation and Urban Forest Research Centre, National Forestry and Grassland Administration, Beijing 100091, China * Correspondence: [email protected] Abstract: Forests can affect soil organic carbon (SOC) quality and distribution through forest types and traits. However, much less is known about the influence of urban forests on SOC, especially in the effects of different forest types, such as coniferous and broadleaved forests. Our objectives were to assess the effects of urban forest types on the variability of SOC content (SOC concentration (SOCC) and SOC density (SOCD)) and determine the key forest traits influencing SOC. Data from 168 urban forest plots of coniferous or broadleaved forests located in the Beijing urban area were used to predict the effects of forest types and traits on SOC in three different soil layers, 0–10 cm, 10–20 cm, and 20–30 cm. The analysis of variance and multiple comparisons were used to test the differences in SOC between forest types or layers. Partial least squares regression (PLSR) was used to explain the influence of forest traits on SOC and select the significant predictors. Our results showed that in urban forests, the SOCC and SOCD values of the coniferous forest group were both significantly higher than those of the broadleaved group. The SOCC of the surface soil was significantly higher Citation: Xu, X.; Sun, Z.; Hao, Z.; than those of the following two deep layers. In PLSR models, 42.07% of the SOCC variance and Bian, Q.; Wei, K.; Wang, C. Effects of 35.83% of the SOCD variance were explained by forest traits. Diameter at breast height was selected Urban Forest Types and Traits on Soil as the best predictor variable by comparing variable importance in projection (VIP) scores in the Organic Carbon Stock in Beijing. models. The results suggest that forest types and traits could be used as an optional approach to Forests 2021, 12, 394. https:// assess the organic carbon stock in urban forest soils. This study found substantial effects of urban doi.org/10.3390/f12040394 forest types and traits on soil organic carbon sequestration, which provides important data support for urban forest planning and management. Academic Editor: Cate Macinnis-Ng Keywords: forest types; forest traits; partial least squares regression; soil organic carbon; urban forest Received: 13 February 2021 Accepted: 24 March 2021 Published: 26 March 2021 1. Introduction Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in Urban green spaces, including urban forests, play a pivotal role as substitutes for published maps and institutional affil- the lost natural environment in the city’s original location [1]. Urban forests provide a iations. large number of ecosystem services [2], such as enhancing amenity values [3], maintaining biodiversity [4], and increasing carbon sequestration [5]. The increase and decrease of soil organic carbon (SOC) may affect climate change greatly [6,7]. Moreover, SOC storage impacts the other ecological functions of soil as well, such as biomass production, nutrient and water-holding capacity, infiltration capacity and resistance to erosion, and providing Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. habitats for biological activity [8,9]. Studies of forest groups and species characteristics This article is an open access article affecting soil fertility parameters have been widely carried out in the non-urban envi- distributed under the terms and ronment [10], but less so in an urban context [11]. An in-depth understanding of the conditions of the Creative Commons relationship between urban forest and SOC is key to maintain and enhance the quality of Attribution (CC BY) license (https:// urban ecosystem services. creativecommons.org/licenses/by/ There is growing recognition of the top-down and bottom-up regulation between 4.0/). plants and soil organisms [12]. Studies of the effects of aboveground forest types and Forests 2021, 12, 394. https://doi.org/10.3390/f12040394 https://www.mdpi.com/journal/forests Forests 2021, 12, 394 2 of 16 traits on SOC distribution are also underway. Jobbagy and Jackson (2000) found that different forest types significantly affected the vertical distribution of SOC [13]. There is generally high variability in urban SOC, and Canedoli et al. (2019) showed that the SOC concentration (SOCC) of urban parks was higher than that of non-parks, defined as green squares, private gardens, tree lines, or street greens [14]. In an urban context, soils are not only under the disturbance of an artificial environment but are also affected by vegetation [15]. Urban trees can affect the soil’s biological, physical, and chemical properties through their root systems and the quantity and quality of fallen leaves [16]. Understanding the impact of urban trees on soil properties is critical [17]. However, the effect of urban forests on SOC and to what extent urban forests can increase SOC reserves remain unclear. It has been long recognized that forest types differ greatly in forest traits [18] and thereby can affect ecosystem properties, including soil organic matter [5]. The previous studies of forest traits in relation to soil carbon stocks have focused on some key factors, such as tree canopy [19], diameter at breast height [20,21], litterfall [22–24], fine root biomass [25], and herbaceous vegetation [26]. These forest traits affect SOC and other soil properties through direct or indirect pathways. The direct pathway of trees interacting with soil includes both leaf litter input and root release. The litterfall from woody plants is the main source of soil organic matter [27–31]. Tree species vary significantly in their litter quality, as well as in their litter decomposition rates [32]. In the urban environment, the litter disposal methods of different forest types may influence soil organic carbon differently. The low crown and needle leaves of coniferous species mean that their fallen leaves are cleaned up less often [33,34], whereas the fallen leaves of deciduous broad-leaved forests are often cleaned up. Experiments have demonstrated that tree roots release substantial quantities of carbon into soil [35,36]. An indirect pathway by which forests interact with SOC—whereby forests or a single tree may affect soil respiration—is providing a microenvironment and microclimate for the soil. Thereby, urban forest types and tree species may impact soil organization and related process through the microenvironment, litterfall, and tree roots, thereby leading to differences in urban forest SOC. So far, Beijing has implemented two rounds of the Million-Mu (667 m2) Plain Afforesta- tion Project. In recent years, Beijing’s urban forest afforestation area is constantly increasing, which provided good conditions for the development of this study [37,38]. Currently, the connections between urban forest and soil organic carbon stock are still under-explored. To help address these knowledge gaps, we studied 107 urban parks in Beijing. Based on SOC stock and urban forest types and traits, we hypothesized that: (1) urban forest soil organic carbon is different between coniferous and broadleaved forests, (2) urban forest traits have a significant influence on soil organic carbon, and (3) soil organic carbon in different layers has a different relationship with urban forest traits. In this study, we aimed to elucidate the relationship between urban forest and soil organic carbon so as to provide data support for urban forest planning and management in the future. 2. Study Area and Methods 2.1. Study Area Beijing, the capital city of China, has a history of over 3000 years. Over the past decades, Beijing has been undergoing rapid development, and a series of ring roads were constructed as the city expanded outward from its historic center. This urbanization occurred in all four directions, started from the central area inside the 2nd ring road, then sequentially toward the surrounding areas [39]. The study area was all within the sixth ring road, which covers the central and suburban areas of Beijing (Figure1). Forests 2021, 12, 394 3 of 15 Forests 2021, 12, 394 3 of 16 FigureFigure 1. The 1. The layout layout of soil of soil sampling sampling parks parks (A) ( Aand) and the the ring ring road road location location (B ().B ). Based on maps and reachable park directories on the Baidu Map, we located over Based on maps and reachable park directories on the Baidu Map, we located over 200 200 parks on the map. With the map gridded by 5 km × 5 km, we randomly selected one parks on the map. With the map gridded by 5 km × 5 km, we randomly selected one park park in each grid. We discarded parks that were built on former factories to ensure that they in each grid. We discarded parks that were built on former factories to ensure that they were only affected by the typical urban forest environment. After this, we manually added were only affected by the typical urban forest environment. After this, we manually added some parks more than 50 years old to make the age of parks more even. Then, 107 parks some parks more than 50 years old to make the age of parks more even. Then, 107 parks were selected in total. We tried to sample both coniferous and broadleaved forests in each were selected in total. We tried to sample both coniferous and broadleaved forests in each park to compare the SOC content between forest types.