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Acta Geographica Sinica >

2024 , Vol. 79 >Issue 1: 206 - 217

DOI: https://doi.org/10.11821/dlxb202401013

Bio-Geography

Changes of forest topsoil carbon fractions across urban-rural transects in Beijing

  • TIAN Yuehan , 1, 2 ,
  • GUO Hongbo 1, 2 ,
  • GAO Xiaofei 1, 2 ,
  • XIA Nan 1, 2 ,
  • DU Enzai , 1, 2
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  • 1. Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
  • 2. State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China

Received date: 2023-07-10

  Revised date: 2023-12-22

  Online published: 2024-01-29

Supported by

Fundamental Research Funds for the Central Universities(2233200006)

Project of State Key Laboratory of Earth Surface Processes and Resource Ecology(2021-TS-02)

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Abstract

Rapid urbanization has profoundly altered soil carbon cycling and thereby reshaped the spatial pattern of soil carbon content and fractions across the urban-rural gradients. In this study, we measured the contents of total carbon and its different fractions in the topsoil (surface layer 0-10 cm and subsurface layer 10-20 cm) of twenty parks across four urban-rural transects in Beijing, China. We analyzed the spatial variations of different soil carbon fractions and their potential driving factors across the urban-rural gradients. The results showed that topsoil total carbon (topsoil: 21.0±1.6 g/kg; subsurface soil: 18.0±1.3 g/kg) was dominated by organic carbon (topsoil: 64.6%±4.5%; subsurface soil: 54.9%±4.5%). Topsoil contents of organic carbon showed a nonlinear trend from the urban core to the rural area, while the topsoil inorganic carbon content decreased significantly. Topsoil organic carbon (topsoil: 13.8±1.5 g/kg; subsurface soil: 10.0±1.2 g/kg) was dominated by particulate organic carbon (topsoil: 71.3%±2.4%; subsurface soil: 70.5%±2.9%). The contents of both particulate organic carbon and mineral associated organic carbon showed nonlinear changes across the urban-rural forest transects. The proportion of particulate organic carbon was relatively low in urban areas, while that of mineral associated organic carbon showed an opposite trend. Soil texture, soil pH, and park age were important drivers to shape the spatial variation of topsoil carbon components across the urban-rural transects, while the urban-rural climate gradient and species diversity were found to have an unimportant role. Our findings improve the understanding of how urbanization reshapes soil carbon fractions and have useful implications for soil management in urban forests.

Key words： urban forest; urbanization; soil organic carbon; particulate organic carbon; mineral associated organic carbon; spatial pattern

Cite this article

TIAN Yuehan , GUO Hongbo , GAO Xiaofei , XIA Nan , DU Enzai . Changes of forest topsoil carbon fractions across urban-rural transects in Beijing[J]. Acta Geographica Sinica, 2024 , 79(1) : 206 -217 . DOI: 10.11821/dlxb202401013

1 引言

土壤为人类提供了众多关键的生态系统服务[1]，尤其在调节植物生长、缓解气候变化等方面起着重要作用。然而，快速的城市化强烈改变了土壤的结构和功能[2-3]，导致诸多土壤属性在城市和郊区间呈现明显的梯度变化（即城郊梯度变化）[4-5]。已有研究表明，城市森林土壤与近郊森林土壤相比具有更高的碳含量[6-7]。土壤碳由具有不同周转率的碳组分组成[8]，周转较快的碳组分对环境变化和人为干扰更为敏感[9]，因此不同碳组分对气候变化与人为干扰的响应可能存在明显差异[10-11]。然而，以往的研究多聚焦于城市化对森林土壤总碳或总有机碳的影响[12-13]，关于城市化对森林土壤碳组分的影响尚缺乏深入认识。
土壤碳库可划分为有机碳（SOC）及无机碳（SIC）[14]，通常有机碳占比最高且活性更强[15]。越来越多的研究将有机碳分为颗粒态有机碳（POC）和矿物结合态有机碳（MAOC），以更好地认识土壤碳的积累、持久性及其对环境变化的响应[16]。颗粒态有机碳主要来源于半分解的植物残体，是相对不稳定的有机碳组分，而矿物结合态有机碳主要由难分解的微生物代谢物和残体形成，周转缓慢且更为稳定[17]。因此，森林土壤不同碳组分在城郊梯度上的空间变化规律及其驱动因素可能存在明显的差异。
城市森林土壤碳组分的空间格局可能受到多种因素的影响。首先，城市热岛促进了微生物呼吸作用[18]，使易分解的活性碳组分发生损失。例如，在美国纽约及巴尔的摩开展的城郊梯度样带研究发现，与郊区相比，城区森林土壤活性有机碳组分减少但惰性有机碳组分增加[2,8]。其次，土壤属性的变化也会导致不同碳组分的变化。例如，由于碱性混凝土的输入[19-20]，市区土壤的pH普遍比郊区高[21]，而且无机碳的占比增加。因此，人为管理措施可能会通过改变土壤质地进而影响土壤通气性及矿物含量[22]，最终影响土壤有机碳及其组分的固存。此外，年龄更老的城市森林由于土壤碳积累时间更久而具有更高的土壤有机碳含量[23-24]。城市森林植被覆盖率也可能通过改变枯落物输入量以及土壤温度和湿度等微环境因子，造成土壤碳组分的变化[25]。除上述因素外，城市森林不同树种组成也可能通过影响凋落物的分解[26]、土壤酶活性[27]、土壤理化性质[28]等，导致土壤碳组分发生变化。然而，目前很少有研究定量揭示上述多种因素对城郊梯度上森林土壤不同碳组分的影响及其相对重要性。
作为中国首都和世界上最大的城市之一，北京在过去40年内经历了快速的城市化进程[29]，形成了典型的城郊梯度森林景观[30-31]，为研究城郊梯度上森林土壤碳组分的变化提供了良好平台。本文拟通过对北京4条城郊样带上20个城市公园中森林斑块进行调查采样，分析其表土（表层0~10 cm和亚表层10~20 cm）总碳及不同碳组分在城郊梯度上的空间变化特征和影响因素。

2 材料与方法

2.1 研究区域及采样设计

北京（39.43°N~41.05°N, 115.42°E~117.50°E）属于温带大陆性季风气候，年均温约为11~13 ℃，年均降水约为500~600 mm。自然地带性植被类型以温带落叶阔叶林及针阔叶混交林为主[32]。本文从市中心（故宫博物院）到郊区设置4条不同走向（东北、西北、西南和正南）的城郊梯度样带[33]，随机选取20个独立的城市森林公园进行采样（图1）。采样公园到市中心的距离在3~79 km之间。从市中心到郊区，主要土地覆盖类型由建设用地转变为农田，再过渡为次生植被。在城郊梯度上，年均温呈下降趋势，年降水无变化规律；土壤pH呈下降趋势，土壤粘粉粒含量呈先降低后增加的趋势；公园年龄在0~40 km范围内随距离增加而下降，超过40 km后则随距离增加而增加；公园植被覆盖度无显著变化。
图1 北京城郊样带及公园采样点分布

Fig. 1 Urban-rural transects and locations of sampling parks

2.2 样品采集与分析

样带调查与采样于2019年6月下旬至7月初进行[31,33]。在每个公园随机选择3块典型森林斑块，去除土壤表层的凋落物，用土钻采集表层（0~10 cm）和亚表层（10~20 cm）土壤样品，每个公园内同层土样分别均匀混合成一个样品。采集土壤样品的同时，记录森林斑块的树种数。土壤样品经自然风干后过2 mm筛，去除石砾、死根及其他植物残体，用于土壤理化性质和土壤碳组分分析。通过pH计法（PB-10, Sartorius, Germany）测定土壤pH；通过全自动激光粒度仪法（Malvern Mastersizer 2000, Worcestershire, UK）测定土壤粘粉粒含量。将土壤样品研磨并过100目筛，用碳氮元素分析仪（CN802, Velp, Italy）测定土壤总碳含量。
土壤有机碳含量通过酸水解法测定。称取土样5.0 g用10%的稀盐酸彻底去除无机碳，之后多次用去离子水洗酸至溶液呈中性，置于65 ℃烘箱内烘干至恒重。随后研磨过100目筛，用碳氮元素分析仪（CN802, Velp, Italy）测定土壤有机碳含量。土壤中无机碳含量通过土壤总碳含量减去有机碳含量的差值计算得出。采用湿筛和粒径分组法将土壤有机质分离为颗粒态有机质（POM，粒径> 53 μm）和矿物结合态有机质（MAOM，粒径< 53 μm）[16,34]，分别得到颗粒态和矿物结合态有机质悬浊液，经过沉淀、去除上清液、烘干、称重后，计算其质量回收率。将筛分得到的两类组分样品分别研磨并过100目筛，通过添加稀盐酸去除无机碳后，用碳氮元素分析仪（CN802, Velp, Italy）分别测定其土壤有机碳含量。根据质量守恒定律，结合公式（1）~（3）分别计算得到颗粒态有机碳和矿物结合态有机碳含量[35]：
M a s s R e c = M a s s P O M + M a s s M A O M M a s s B u i k s o i l × 100 %
P O C = M a s s P O M × O C P O M M a s s B u i k s o i l × M a s s R e c
M A O C = M a s s M A O M × O C M A O M M a s s B u i k s o i l × M a s s R e c
式中：MassRec为土壤质量回收率；MassBulk soil为土壤样品质量；MassPOM和MassMAOM分别为分离所得颗粒态有机质与矿物结合态有机质的质量；OCPOM和OCMAOM分别为颗粒态有机质与矿物结合态有机质中测得的有机碳含量；POC和MAOC分别为土壤样品中颗粒态有机碳与矿物结合态有机碳的含量。经计算，筛分后的土壤平均质量回收率为97.3%，物理分组效果较好。

2.3 潜在影响因素数据获取

为分析影响不同土壤碳组分含量空间变异的潜在因素，本文收集了与土壤碳输入及输出过程直接相关的3类影响因素数据，包括气候因素（年均温和年降水）、土壤因素（土壤质地和土壤pH）、植被因素（公园植被覆盖度、公园年龄和树种多样性）。其中，气象数据来自中国气象局（http://data.cma.cn/），土壤理化性质（pH和质地）数据来自实验测试，公园植被覆盖度通过地理国情监测云平台（http://www.dsac.cn/）的卫星遥感图像（空间分辨率为2.5 m）估算得出，公园年龄来自北京市园林绿化管理局网站（http://yllhj.beijing.gov.cn/），树种多样性以采样时所记录的树种数为指标。除上述因素外，人为管理措施（如施肥、灌溉等）也会影响城市森林土壤属性[30]，但受限于这类数据的可获得性，本文未能将其纳入影响因素分析。

2.4 统计分析

通过Shapiro-Wilk test对不同土壤碳组分含量数据进行正态性检验，对不符合正态分布的数据进行正态转换。通过线性或非线性回归分析检验城郊梯度上森林表土不同碳组分含量及各类环境因素的空间变化趋势。基于相关分析检验表土不同碳组分含量随气候、土壤和植被因素的变化。使用“rdacca.hp”程序包[36]进行基于层次分割原理的方差分解（VPA），量化各影响因素的综合作用及相对重要性。本文统计分析均基于R软件（version 4.0.5）完成[37]，统计分析样本量均为20个，统计显著性水平为P < 0.05。

3 结果

3.1 表土总有机碳和无机碳含量的城郊梯度变化

北京城郊梯度上森林表土总碳（表层21.0±1.6 g/kg；亚表层18.0±1.3 g/kg）以有机碳为主导（表层土壤占比64.6%±4.5%；亚表层土壤占比54.9%±4.5%）。在城郊梯度上，森林表土总有机碳与无机碳含量的空间变化规律存在明显差异（图2）。从市区到郊区，有机碳含量呈先下降后升高的非线性趋势（图2a、2e），有机碳在总碳中的占比（SOC∶STC）总体呈增加趋势（图2b、2f）。无机碳含量在城郊梯度上呈现显著下降趋势（图2c、2g），无机碳在总碳中的占比（SIC∶STC）总体呈下降趋势（图2d、2h）。
图2 北京森林表土有机碳和无机碳含量城郊梯度及其在总碳中占比的变化

Fig. 2 Changes of topsoil organic carbon and inorganic carbon contents and their contributions to total carbon across urban-rural forest transects in Beijing

3.2 表土颗粒态有机碳和矿物结合态有机碳含量的城郊梯度变化

城郊梯度森林表土有机碳（表层13.8±1.5 g/kg；亚表层10.0±1.2 g/kg）以颗粒态有机碳为主导（表层土壤占比71.3%±2.4%；亚表层土壤占比70.5%±2.8%）。从市中心到郊区，矿物结合态有机碳和颗粒态有机碳含量均呈先下降后升高的非线性趋势（图3a、3e）。在城郊梯度上，两种有机碳组分在总有机碳中的占比表现出相反的变化，颗粒态有机碳的占比（POC∶SOC）在市区相对较低，在城郊梯度上呈显著非线性增加趋势（图3b、3f）；矿物结合态有机碳的占比（MAOC∶SOC）在市区相对较高，呈显著非线性下降趋势（图3d、3h）。
图3 北京森林表土颗粒态有机碳和矿物结合态有机碳含量城郊梯度及其在总有机碳中占比变化

Fig. 3 Changes of topsoil particulate organic carbon and mineral associated organic carbon content and their contributions to total organic carbon across urban-rural forest transects in Beijing region

3.3 土壤碳组分含量与环境因素的关系以及各影响因素的相对重要性

基于相关分析发现，表层和亚表层土壤有机碳含量均与土壤pH呈显著负相关（表层P < 0.001；亚表层P < 0.01），且与公园年龄呈显著正相关（P < 0.01）（图4a、4c、4d、4f），有机碳含量仅在表层土壤中与粘粉粒含量呈显著正相关（图4b）。无机碳含量仅在表层土壤中与土壤pH呈显著正相关（图4a），亚表层土壤的无机碳含量同各影响因素均无显著相关性（图4d~4f）。
图4 北京森林表土碳组分与土壤pH、土壤粘粉粒含量及公园年龄之间的相关关系

Fig. 4 Correlations between topsoil carbon fractions and soil pH, soil clay and silt content and park age across urban-rural forest transects in Beijing

表层和亚表层土壤的颗粒态有机碳含量均与土壤pH呈显著负相关，且与公园年龄呈显著正相关（图4g、4i、4j、4l）。表层土壤的矿物结合态有机碳含量与土壤pH呈显著负相关，与公园年龄呈显著正相关（图4g、4i）。亚表层土壤的矿物结合态有机碳含量则仅与公园年龄呈显著正相关（图4l）。此外，表层土壤颗粒态有机碳和矿物结合态有机碳含量均与土壤粘粉粒含量呈显著正相关（图4h）。
方差分解（VPA）结果表明，各影响因素总共解释了表层土壤颗粒态有机碳、矿物结合态有机碳及无机碳含量空间变异总方差的71.4%、65.4%和45.5%（图5a~5c）。其中，土壤pH对颗粒态有机碳、矿物结合态有机碳及无机碳含量变异的单独解释率均最大，分别为29.9%、29.6%和15.7%。各影响因素总共解释了亚表层土壤颗粒态有机碳、矿物结合态有机碳及无机碳含量空间变异总方差的63.4%、45.3%和51.8%（图5d~5f）。其中土壤pH对颗粒态有机碳含量变异的单独解释率最高，为29.5%（图5d）。相比之下，公园年龄对于矿物结合态有机碳及无机碳含量变异的单独解释率最高，分别为16.1%和19.9%（图5e~5f）。
图5 不同因素对北京森林表土碳组分城郊梯度空间变异影响的相对重要性

Fig. 5 Relative importance of different drivers in shaping the spatial variation of topsoil carbon fractionsacross urban-rural forest transects in Beijing

4 讨论

4.1 城郊梯度上不同表土碳组分的空间变化规律

本文发现森林表土无机碳含量城郊梯度上表现为线性降低趋势，且无机碳在总碳中的占比也在城区相对更高。前人在北京[38]、上海[39]及美国菲尼克斯[40]等城市的研究也有类似的结论。城市森林表土无机碳含量与土壤pH显著正相关，而且土壤pH对表土无机碳空间变异的方差解释率最高，这可能是因为城区人类活动更密集，产生的城市建筑垃圾（尤其是水泥和混凝土）通常由富含钙和镁元素的碱性物质构成[41]，易与土壤溶解的CO2反应生成碳酸盐，从而导致无机碳积累[42]。然而，城郊梯度上表土总有机碳、颗粒态有机碳和矿物结合态有机碳含量均呈先降低后增加的趋势，不同于以往研究发现的土壤总有机碳含量在城郊梯度上的单调递减趋势[38]。这可能是由于本文设置的城郊梯度样带覆盖范围更广，而以往研究主要集中在城区与近郊区的对比（图6）。
图6 森林表土碳组分城郊梯度变化及其影响因素空间变异概念图

Fig. 6 Conceptual diagram of spatial variation of topsoil carbon fractions and potential drivers across urban-rural gradients

在城郊梯度上，城市森林表土有机碳、颗粒态有机碳和矿物结合态有机碳含量的空间变化主要受土壤pH、粘粉粒含量及公园年龄影响。城市森林公园在城郊梯度上建成时间及管理强度的不同影响了上述3种因素在城郊梯度上的变化，进而导致了表土有机碳组分含量的非线性格局（图6）。公园年龄一方面可以直接反映土壤有机碳的积累时间[7,43]，另一方面也侧面反映了人类活动干扰的程度[38]。市中心建成时间较长的森林公园管理措施趋于稳定，促进了有机碳的稳定积累，近郊区新建的城市森林公园由于土壤回填及人为踩踏等干扰更为频繁，土壤保持水分与养分的能力较差[23]，不利于有机碳的持续积累。相比之下，虽然远郊森林公园很少受到密集的人为管理，但地表丰富的凋落物能够输入丰富的有机质及养分[44]，因此有机碳及其组分含量同样较高。此外，表土质地在市中心及远郊相对较细，粒径较小的土壤粘粉粒通常比表面积更大，能够形成更多的有机碳—矿物化学键从而促进有机碳及其组分的固定[45]。市区偏碱性的土壤中钙含量较高，土壤中的Ca2+桥键是土壤有机碳稳定的重要机制[46]，能增加对有机碳的固定能力[47]。

4.2 颗粒态有机碳对城市森林表土总有机碳的主导性贡献

本文发现城郊梯度上森林表土有机碳组分始终以颗粒态有机碳为主，这可能与城市土壤发育时间较短有关。一般认为颗粒态有机碳主要来源于新鲜的植物残体，而随着土壤的发育，微生物过程主导的矿物结合态有机碳则会逐渐积累[16,48]。然而，本文也发现，与郊区相比，颗粒态有机碳对总有机碳的贡献在城区更小，而矿物结合态有机碳对有机碳的贡献在城区更大，这可能是由于城区土壤有较长的碳累积时间，增加了颗粒态有机碳向矿物结合态有机碳的转化，同时频繁的凋落物移除措施也会减少植物残体向土壤有机碳库的归还[49]，从而降低了颗粒态有机碳组分的比例。虽然市中心由于热岛效应（图6）导致大气及土壤温度相对更高[50]，可能加速不稳定的颗粒态有机碳组分的分解速率，同时高温会促进土壤微生物活性有利于矿物结合态有机碳的积累。然而，本文并未发现年均温和颗粒态有机碳及矿物结合态有机碳含量存在相关性，这表明在局地小尺度下，温度对土壤有机碳动态的单独效应可能并不明显。

4.3 城郊梯度上不同表土碳组分空间变异的主导因素

本文发现土壤pH和公园年龄是解释表土碳组分含量在城郊梯度上空间变异的最重要因素。以往的研究多强调气候因素（年均温和年降水）[51⇓-53]和植被类型[54-55]对自然土壤碳组分空间格局的决定作用，但这些研究通常是在区域尺度或全球上进行的，涵盖了多样的水热条件和土壤植被类型。相比之下，北京市城郊梯度上的温度和降水变化较小，并且土壤与植被类型也基本一致（图6）。有研究表明城市化较高的地区存在非常明显的城郊经济水平差异[53,56]，城区与郊区在森林养护、人群踩踏和垃圾处理等方面的差异会使土壤受干扰时间及土壤属性存在很大差别[57-58]。例如，城区园林管理倾向于增加植被覆盖度，通常进行施肥和灌溉措施，有利于树木生长和土壤净碳固存[59]；郊区公园的集约开发则往往会破坏土壤结构并加速土壤养分流失，减弱土壤物理化学保护机制对有机碳的固定作用[43]。总之，我们的研究结果表明，在局地尺度上，人为因素导致的土壤与植被变化相比气候因素对土壤碳组分的空间变异影响更为强烈。

4.4 不确定性与未来研究展望

本文对城市森林表土碳组分空间变异潜在影响因素的分析存在一定不确定性。例如，城市森林通常会受到频繁的园艺管理（如施肥、灌溉和修剪），尤其是在人为活动密集的城市核心区[60]。由于缺乏相应的数据，本文无法量化城市森林管理措施的影响。此外，较高浓度的大气CO2可以刺激城市树木生长[61]，增加植物的土壤碳输入；大气氮沉降“城市热点现象”会增加土壤中氮的有效性，影响植物的生长以及微生物群落特征[30]，从而影响土壤碳组分的变化。遗憾的是，本文未能测定城市公园样点尺度的大气CO2浓度和大气氮沉降速率，无法进行相关量化分析。因此，在未来的研究中应综合考虑上述多种因素的影响，从而深化对城市森林土壤碳循环过程调控机制的认识。同时，城市公园需要通过更科学的管理措施增强土壤碳的稳定性，从而更好地维持城市森林土壤的功能。

5 结论

本文基于样带调查手段分析了北京森林表土碳组分城郊梯度空间变化特征及其影响因素。结果表明，从市中心到郊区，表土无机碳含量表现为线性下降趋势，总有机碳、颗粒态有机碳和矿物结合态有机碳含量均呈先降低后增加的趋势。城郊梯度上总有机碳组分始终以颗粒态有机碳为主，颗粒态有机碳对总有机碳的贡献在城区更小，而矿物结合态有机碳对总有机碳的贡献在城区更大。土壤质地、pH和公园年龄是解释表土碳组分在城郊梯度上空间变异的主要因素，而气候因素的影响相对较小，表明在局地尺度上人为活动导致的土壤与植被属性变化对城市森林土壤碳组分的影响更为重要。未来研究应更多关注人为影响和气候变化背景下，城市森林土壤碳组分的动态变化及其响应机制。

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