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GEOGRAPHICAL RESEARCH >

2017 , Vol. 36 >Issue 3: 495 - 505

DOI: https://doi.org/10.11821/dlyj201703008

Articles

Relationship between landscape patterns and soil salinity based on canonical correspondence analysis in coastal reclamation area

  • XIE Xuefeng , 1 ,
  • PU Lijie , 1, 2 ,
  • ZHU Ming 1 ,
  • XU Yan 1 ,
  • WANG Xiaohan 1 ,
  • XU Caiyao 1 ,
  • CHEN Xinjian 1
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  • 1. School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210023, China
  • 2. Key Laboratory of the Coastal Zone Exploitation and Protection, Ministry ofLand and Resources, Nanjing 210023, China

Received date: 2016-07-25

  Request revised date: 2016-12-06

  Online published: 2017-03-20

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《地理研究》编辑部
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Abstract

Coastal zone is an important land reserve resources. Its improvement and development has become a hot topic in many countries. Rudong coastal reclamation area was selected as the study area in this study. The canonical correspondence analysis was applied to analyze the relationship between soil salinization and landscape pattern at different scales, and to determine the contribution of the landscape index to the degree of soil salinization. The results showed that the patch density (PD), edge density (ED), landscape shape index (LSI), aggregation index (AI) and interspersion and juxtaposition index (IJI) of the study area were higher and varied in land use types that indicated the higher level of landscape fragmentation and more complex of landscape structure; The landscape structure was dominantly affected by anthropogenic activities. Soil Na+ and Cl- was the main component of soil salinity, accounting for 87.4% and 90.1% of the total cations and anions, respectively. The coefficient of variation of soil salinization index varied from 53.49% to 129.03%, which reflected the non-homogeneous distribution of soil salinity caused by anthropogenic activities. The result of canonical correspondence analysis showed that, landscape pattern variables in 100 m and 200 m buffer zones could explain 66.6% and 80.1% variations of soil salinization, respectively. The positive relationship was observed among the ratio of agricultural construction land, irrigated land and the level of soil salinity, while that of dry land was negatively correlated with the level of soil salinity. Soil salinization had a positive correlation with largest patch index (LPI) and contagion index (CONTAG), while as it had a negative correlation with PD, ED, LSI and Shannon's diversity index (SHDI) on landscape level. On patch class level, LPI, ED and LSI were the Colinear indicators affecting the soil salinization. Finally, the study on the relationship between landscape patterns and soil salinization may be of great significance to optimize the land use pattern and to reduce the degree of soil salinization.

Key words： landscape pattern; soil salinization; canonical correspondence analysis; coastal reclamation area

Cite this article

XIE Xuefeng , PU Lijie , ZHU Ming , XU Yan , WANG Xiaohan , XU Caiyao , CHEN Xinjian . Relationship between landscape patterns and soil salinity based on canonical correspondence analysis in coastal reclamation area[J]. GEOGRAPHICAL RESEARCH, 2017 , 36(3) : 495 -505 . DOI: 10.11821/dlyj201703008

1 引言

土壤盐渍化作为土地退化的形式之一,受气候、地貌、水文地质等自然因素和耕作、灌溉、田间管理等人类活动共同影响,广泛分布于内陆干旱半干旱地区和滨海滩涂盐沼地区[1,2]。滨海盐渍化土壤中含有大量的可溶性盐,容易引起植物的生理水分不足,抑制营养物质的吸收,导致植物发育不良,产量降低[3,4]。苏北地区滩涂资源丰富,滩涂面积达0.76万km2,占全国滩涂总面积的1/4以上,是非常重要的后备土地资源,而盐渍土的广泛分布严重制约着围垦区农业的发展[5-7]。传统地学统计中,野外采集土壤耗时长、工作量大、破坏性强、代表性差,而将遥感技术与地学分析相结合可以很好的克服传统检测方法的不足[8,9]。土地利用类型和覆被状况及其景观格局的差异显著地改变了土壤的物理化学性质和土壤酶活性,深刻地影响着表层土壤的盐渍化程度;同时合理的优化土地利用格局,可以有效地降低土壤盐分。因此,使用与盐渍化程度显著相关的景观格局指数作为景观环境指标,可以直接反映土壤盐分变化的原因,对于盐分监测、区域土地管理等都具有重要的意义。王玉刚等野外调查和室内分析研究了不同土地利用下天山北麓土壤盐渍化特征及影响因素[10];孙倩等探讨了土地利用/覆被变化对盐渍化的效应分析[11];曹雷等探讨了土壤盐度对—库绿洲不同尺度景观格局的影响[12]。在分析方法上,以往的研究多采用传统的统计分析如相关分析、方差分析、因子分析和多元线性回归分析,当变量数据较多时,线性相关等分析则受到限制;数量生态学中的典范对应分析（canonical correspondence analysis,CCA）分析方法能够直观地给出多变量间的相互作用关系,可以反映滩涂围垦区的土壤盐化特征和碱化特征与景观格局的数量关系,对研究多尺度景观格局与土壤盐渍化之间的关系是一个很好的补充。
本文以如东滨海滩涂围垦区为研究对象,采用CCA分析对样点缓冲区景观格局指数与土壤盐渍化指标之间的关系进行分析,探讨不同尺度的景观格局对土壤盐渍化程度的影响,为优化滩涂围垦区土地利用格局,降低滩涂围垦区土壤盐渍化程度提供参考。

2 数据来源与研究方法

2.1 研究区概况

研究区位于江苏省东南部的如东县,地处长江三角洲北翼,东面濒临黄海,位于120°42′E~121°22′E,32°12′N~32°36′N（图1）。研究区属北亚热带季风性湿润气候,光照充足,雨热同期,年平均温度15.0 °C,年平均降水量1028.6 mm。如东县被誉为黄金海岸,拥有海岸线长度106 km,滩涂面积约693 km2。作为典型的滩涂围垦区,如东县在1949年后,已围垦面积达到了241 km2。受土壤盐渍化影响,围垦区农作物的产量仍然较低,因此探讨围垦区景观格局与土壤盐渍化程度之间的关系对于提高农作物产量,促进农业发展具有重要意义。本文选择如东县老北坎垦区、新北坎垦区、东凌垦区和豫东垦区为研究区,分别围垦于1951年、1974年、1982年和2007年,总面积约70.15 km2。
Fig. 1 Location of the study area

图1 研究区域位置

2.2 数据来源

研究区土地利用数据来自于南通市国土局2013年土地利用普查数据,土壤样品于2012年9月13-14日在研究区选取不同土地利用类型进行采集,并用GPS精确定位,依据样点选择的典型性、代表性和一致性原则,共选取30个样点,每个样点3次重复,并在0~20 cm深度土层取样,共取得土壤样品90个。将土壤样品带回实验室自然风干后除去植物根系、贝壳等杂质,磨碎过2 mm筛后备用,所有土壤样品均使用蒸馏水制备1 ∶ 5土水质量比溶液,静置过滤后得到浸提液,测定离子组成含量。其中,HCO3-、CO32-用标准硫酸滴定法测定,Cl-用标准硝酸银滴定法测定,Mg2+、Ca2+、SO42-用EDTA络合滴定法测定,Na+、K+用火焰光度法测定,土壤全盐量（total salt,St）为8种离子重量之和;钠吸附比（sodium adsorption ratio,SAR）的计算公式为：
SAR = C N a + 1 2 ( C C a 2 + + C M g 2 + ) （1）
式中： C N a + 、 C C a 2 + 、 C M g 2 + 分别表示溶液中Na+、Ca2+、Mg2+的浓度。

2.3 景观格局指数选取

景观指数是对景观格局特征的定量表征,包括类型组成与空间格局两方面[13,14]。本文参考全国土地利用分类标准[15],结合研究区土地利用现状,将研究区的景观类型划分为旱地、水田、居民点、农建地（包含农村道路、设施农用地）、水浇地、林草地、养殖坑塘、河流沟渠、滩涂盐沼9种类型。结合已有研究,利用Spearman秩相关分析方法,筛选出相互独立、不存在显著相关关系的格局指标（P>0.05）[16]。在类型水平上选择斑块密度（patch density,PD）、最大斑块指数（largest patch index,LPI）、边缘密度指数（edge density,ED）、景观形状指数（landscape similarity index,LSI）、周长—面积分维数（perimeter area fractal dimension,PAFRAC）、聚集度指数（aggregation index,AI）和散布与并列指数（interspersion juxtaposition index,IJI）,并在景观水平上增选蔓延度指数（contagion index,CONTAG）和香农多样性指数（Shannon's diversity index,SHDI）（表1）,所选景观指数包括破碎度、景观形状、蔓延度和景观多样性四类,均在Fragstats 3.3软件中计算得到,各景观指数的表达式及生态学意义参见李明涛等的研究[17]。
Tab. 1 Landscape pattern index of reclamation area in Rudong county

表1 如东垦区景观格局指数

土地利用类型 景观格局指数
CA(km2) PLAND(%) PD LPI(%) ED LSI PAFRAC IJI AI CONTAG SHDI
旱地 14.87 21.20 30.22 0.58 134.15 61.16 1.31 77.89 95.32 - -
水田 1.90 2.70 5.35 0.15 16.37 20.88 1.12 79.60 95.66 - -
居民点 4.64 6.62 32.34 0.28 65.48 53.62 1.26 77.52 92.26 - -
农建地 6.26 8.93 10.11 4.01 91.18 65.49 1.51 86.03 94.66 - -
水浇地 16.63 23.71 21.47 0.28 118.46 51.52 1.21 72.47 96.28 - -
林草地 1.97 2.81 2.15 0.80 10.86 13.79 1.29 77.47 97.26 - -
养殖坑塘 12.48 17.79 19.80 0.53 92.07 45.97 1.20 81.20 96.18 - -
河流沟渠 10.86 15.48 5.45 5.76 170.17 90.99 1.50 78.64 91.80 - -
滩涂盐沼 0.54 0.77 2.10 0.19 3.58 11.45 1.21 53.32 95.71 - -
总计 70.15 100.00 128.98 5.76 351.15 75.05 1.26 79.00 94.77 50.25 1.89

2.4 缓冲区分析

综合考虑土壤盐渍化的空间变异性和边界附近采样点对研究结果可能存在的干扰,根据欧氏距离原理,利用ArcGIS 10.2软件中的Buffer工具,以采样点为中心,分别以100 m和200 m为缓冲半径建立的圆形缓冲区作为分析单元[18],并通过Fragstats 3.3软件计算不同尺度缓冲区景观水平和类型水平的景观格局指数。

2.5 统计分析

描述性统计分析用于土壤盐渍化特征的分析,包括最小值、最大值、平均值、标准差、变异系数、偏度和峰度。CCA分析方法用于滨海滩涂围垦区景观格局与土壤盐渍化之间的关系。CCA分析是在非线性对应分析的基础上,与多元回归分析结合发展而来的一种排序分析方法,其基本原理是通过样方的空间排列和排序轴的生态梯度,解释样方分布与环境因子间的关系,即将每次迭代过程中的样方排序坐标结果与环境因子进行多元线性回归来反映环境因子对排序结果的影响[19-21]。描述性统计分析在SPSS 19.0统计软件中实现,CCA排序分析在Canoco for Windows 4.5分析软件中实现。本文以如东滩涂围垦区的30个采样点为研究样本,以各采样点的St和SAR为物种变量,来描述各样本的盐渍化过程特征,其中St和SAR分别是表征土壤的盐化程度和碱化程度的重要指标;环境因子分别采用100 m缓冲区尺度和200 m缓冲区尺度的景观水平和斑块类型水平上的景观格局指数,通过CCA排序分析探讨景观格局与土壤盐渍化过程之间的关系。

3 结果分析

3.1 景观格局特征分析

由表1和图2可知,垦区内水浇地、旱地、养殖坑塘和河流沟渠的面积较广,分别为16.63 km2、14.87 km2、12.48 km2和10.86 km2,分别占研究区总面积的23.71%、21.20%、17.79%和15.48%;而水田、林草地和滩涂盐沼的面积较小,分别为1.90 km2、1.97 km2和0.54 km2,分别占研究区总面积的2.70%、2.81%和0.77%。居民点和旱地的PD最高,分别达到了32.34和30.22,说明这两种斑块类型的破碎化程度较高;其他依次为水浇地、养殖坑塘、农建地、河流沟渠、水田、林草地和滩涂盐沼。从LPI来看,河流沟渠的LPI指数最大,达5.76%,农建地次之,为4.01%,说明河流沟渠和农建地相对呈连续分布;其他景观类型的LPI 指数均不足1%,说明所有斑块的面积均较小,分布较为零碎。ED和LSI的分布较为相似,都为河流最高,说明其斑块类型最为复杂;而水田、林草地和滩涂盐沼较低,说明斑块类型较为简单;其余地类均较高且差异不大。PAFRAC指数的分布范围为1.12~1.51,表明各类斑块受人为干扰的程度均较大。IJI指数排序为农建地>养殖坑塘>水田>河流沟渠>旱地>居民点>林草地>水浇地>滩涂盐沼,说明农建地、坑塘养殖的分布聚集度高,彼此邻近;而水浇地和盐沼分布较有规律,IJI值较小。研究区所有土地利用/覆被类型的AI指数均在90以上,说明研究区各种地类的聚集程度都很高;其中林草地的AI指数最高,河流沟渠和居民点最低,说明在研究区内林草地的分布最为集中而居民点和河流沟渠的分布相对较为散乱。研究区的CONTAG、SHDI指数分别为50.25和1.89,说明研究区内同一斑块的连通性一般,区域范围内存在着多种类型、不同面积的斑块。
Fig. 2 classification of land use types in Rudongcoastal reclamation area

图2 如东滩涂围垦区土地利用分类

3.2 土壤盐分特征分析

研究区表层土壤盐分描述性统计结果表明（表2）,各盐分离子含量的差异巨大,Ca2+、Mg2+、Na+、K+、HCO3-、SO42-、Cl-的平均含量分别为0.31cmol ⋅ kg-1、1.08cmol ⋅ kg-1、11.83cmol ⋅ kg-1、0.32cmol ⋅ kg-1、0.43cmol ⋅ kg-1、0.83cmol ⋅ kg-1、11.45 cmol ⋅ kg-1;Na+和Cl-分别占阳离子总量和阴离子总量的87.4%和90.1%,此前研究表明,滨海盐渍土中,可溶性氯化物盐所占比例最大,硫酸盐次之,重碳酸盐最小[22]。此外,St和SAR的范围分别为0.41~27.96 g/kg和0.15~28.15,平均值分别为8.35 g/kg和11.71,参考王遵亲等所著《中国盐渍土》中关于土壤盐碱化分级,研究区土壤盐渍化程度达到了重度盐渍化水平[23]。土壤盐渍化指标的变异系数差异巨大,从HCO3-的53.49%到Ca2+的129.03%,反映了人为活动造成的土壤盐分的非均匀分布。偏度和峰度的结果表明,Mg2+、Na+、K+、SAR、St呈正态分布,Ca2+、HCO3-、SO42-、Cl-则呈非正态分布。
Tab. 2 Descriptive statistical values of soil salinity indicator in surface soil (0~20 cm)

表2 表层土壤（0~20 cm）盐分指标描述性统计值

指标 最小值 最大值 平均值 标准差 变异系数 偏度 峰度
Ca2+(cmol/kg) 0.03 2.13 0.31 0.40 129.03 3.43 14.41
Mg2+(cmol/kg) 0.06 3.54 1.08 1.21 112.04 0.99 -0.58
Na+(cmol/kg) 0.06 39.13 11.83 12.79 108.11 0.72 -1.02
K+(cmol/kg) 0.01 0.87 0.32 0.29 90.63 0.52 -1.25
HCO3-(cmol/kg) 0.20 1.55 0.43 0.23 53.49 4.29 21.21
SO42-(cmol/kg) 0.05 2.92 0.83 0.81 97.59 1.08 0.13
Cl-(cmol/kg) 0.02 43.65 11.45 14.28 124.72 1.03 -0.46
St (g/kg) 0.41 27.96 8.35 8.94 107.07 0.93 -0.57
SAR 0.15 28.15 11.71 9.53 81.38 0.20 -1.53

3.3 景观水平格局与土壤盐渍化关系

表3和图3分别为不同缓冲区尺度景观水平CCA排序的特征值及累积解释量和不同缓冲区尺度景观水平格局与St和SAR的梯度排序结果。
Tab. 3 Eigenvalues, and cumulative variances of CCA ordination on the landscape level

表3 景观水平CCA排序的特征值及累积解释量

缓冲距离 排序轴 特征值 景观格局与过程特征相关性 过程特征累积解释量(%) 格局—过程关系累积解释量(%)
100 m AX 1 0.108 0.836 59.6 89.5
AX 2 0.013 0.690 66.6 100.0
AX 3 0.047 0.000 92.4 0.0
AX 4 0.014 0.000 100.0 0.0
200 m AX 1 0.136 0.939 75.1 93.7
AX 2 0.009 0.582 80.1 100.0
AX 3 0.024 0.000 93.4 0.0
AX 4 0.012 0.000 100.0 0.0
从表3来看,CCA排序分析的特征值总和为0.181,其中100 m缓冲区和200 m缓冲区的第1主轴的特征值分别为0.108和0.136,占总特征值的59.6%和75.1%。从格局与过程特征的相关性来看,100 m和200 m缓冲区的第1排序轴上景观格局特征与土壤盐渍化程度的相关系数分别为0.836和0.939,第2排序轴的相关系数分别为0.690和0.582,表明景观格局与土壤盐渍化过程的关系密切。从格局与过程关系的解释量来看,两种不同尺度上,前两个排序轴都可解释土壤盐渍化变化的100%,其中第1排序轴能够累积解释负荷变化的89.5%和93.7,表明第1排序轴能够反映景观格局指标与土壤盐渍化关系的绝大部分信息。
从景观组成与土壤盐渍化的关系来看（图3）,100 m缓冲区尺度和200 m缓冲区尺度的排序结果基本一致,只是个别指标的影响程度存在差别。农建地面积比例与St呈正相关,与SAR相关关系不显著;水浇地面积比例与St和SAR均呈正相关;旱地面积比例与St呈负相关关系,与SAR相关关系不显著;而河流沟渠面积比例与St呈弱负相关关系,与SAR呈显著负相关关系。这说明不同土地利用/覆被类型由于蒸发蒸腾、土壤容重、土壤养分和酶活性等都有所差异,所以对土壤盐渍化程度的影响也不相同。Wu等的研究结果表明水田和旱地的土壤盐分显著低于种植碱蓬和田菁的水浇地[24,25];Sun等的研究认为小麦、玉米和水稻的种植可以在一定程度上降低土壤盐分[26,27];这都与本文结果的结果基本一致。
Fig. 3 CCA ordination of soil salinization and landscape pattern on landscape level

图3 景观水平景观格局与土壤盐渍化CCA排序

从景观格局指数与土壤盐渍化的关系来看（图3）,不同尺度的景观格局与土壤盐渍化的关系差异不大。在100 m缓冲区尺度上,LPI、CONTAG、AI与St呈正相关关系,PD、ED、LSI、SHDI与St呈负相关关系,IJI对St的预测能力较弱;LPI、CONTAG与SAR呈正相关关系,ED、SHDI、LSI、IJI与SAR呈负相关关系,AI、PD、PAFRAC对SAR的预测能力较弱。在200 m缓冲区尺度上,LPI、CONTAG、PAFRAC与St呈正相关关系,ED、LSI、IJI、SHDI与St呈负相关关系,PD、AI对St的预测能力则相对较弱;SAR与各景观格局指数之间的关系与St类似。这表明了在滨海滩涂围垦区景观格局与土壤盐渍化之间的关系密切,景观格局受人类干扰越小,聚集程度越高,土壤的盐渍化程度越高;景观的破碎化程度越高,景观结构越复杂,景观多样性越丰富,土壤的盐渍化程度越低。

3.4 类型水平格局与土壤盐渍化关系

由于土地利用方式和人类活动强度的差异,不同土地利用类型上土壤盐渍化程度有所不同,利用空间分析与CCA 排序法,选择在研究区分布面积较广、与土壤盐渍化程度较为密切的农建地、水浇地、旱地3种景观,分析类型水平上不同尺度景观格局指数与土壤盐渍化之间的关系,结果如图4~图6所示。
Fig. 4 CCA ordination of soil salinization and landscape pattern on class level in agricultural construction land

图4 农建地类型水平景观格局与土壤盐渍化CCA排序

Fig. 5 CCA ordination of soil salinization and landscape pattern on class level in irrigated land

图5 水浇地类型水平景观格局与土壤盐渍化CCA排序

Fig. 6 CCA ordination of soil salinization and landscape pattern on class level in dry land

图6 旱地类型水平景观格局与土壤盐渍化CCA排序

从图4可以看出,农建地不同尺度的景观格局指数中,LPI与St呈正相关关系,PD、ED、LSI、AI与St呈负相关关系;PD与SAR呈正相关关系,ED、LSI、AI与SAR呈负相关关系,LPI与SAR相关关系较弱;IJI在100 m缓冲区尺度上与St和SAR呈正相关,而在200 m缓冲区尺度上刚好相反。对水浇地而言（图5）,不同尺度的各景观格局指标均与St和SAR呈正相关,其中LPI与St的相关性最为显著,说明水浇地的大面积分布使得土壤盐渍化程度维持在较高水平。旱地不同尺度的景观格局与土壤盐渍化之间的关系大致与农建地和水浇地相反（图6）,St与IJI呈正相关,与其余景观指标均呈负相关;SAR与ED、PD、PAFRAC的相关关系不明显,与其余景观指数均呈负相关。

4 讨论

4.1 围垦时间与土壤盐渍化关系

研究中不同垦区也存在着围垦时间上差异,而围垦区土壤盐分的含量与滩涂围垦时间关系密切。图7表明不同围垦年限间,土壤盐渍化程度差异显著,2007年垦区和滩涂盐沼的平均St和SAR分别达到了16.00 g/kg、18.88 g/kg和21.29、22.56,显著高于1954年、1974年和1982年垦区;其中1954年垦区的平均盐分已经降至0.54 g/kg和0.33,基本属于非盐渍化土。这可能是因为随着人类改良活动强度的增加和活动时间的增长,土地利用类型发生显著改变,土壤质量不断提升,土壤盐渍化程度不断降低。
Fig. 7 Statistical value of soil salt content (St) and SAR at 0-20 cm at different reclamation times

图7 不同围垦年限下0~20 cm土壤St和SAR的统计值

4.2 景观格局与盐渍化效应

由于不同土地利用方式下人类活动强度的差异,不同类型景观上土壤盐渍化程度有所不同[28]。本文中,土壤盐渍化程度与农建地面积百分比和水浇地面积百分比呈正相关,与旱地面积呈负相关。农建地多为农村道路、晾晒场等硬地表面,土壤蒸发作用旺盛,导致土壤盐分向表层集聚,导致表层土壤盐分含量较高。水浇地覆被类型主要是碱蓬、芦苇和盐蒿等盐生植被,由于缺少耕作、灌溉和施肥等田间管理措施,土壤容重较大,土壤可溶性盐分的淋溶作用较弱,加之土壤有机质含量较低,抑盐能力差,使得表层土壤的盐分较高。旱地的主要作物为小麦、棉花和玉米等,由于植被的覆盖使得地表蒸发作用减弱,深耕、施肥和灌溉等措施使得土壤容重降低,孔隙增大,土壤肥力增加,表层盐分向下部淋洗,导致表层盐渍化程度降低。
景观格局与土壤盐渍化程度的关系与空间尺度存在着一定的关联。从景观水平来看,最大斑块指数（LPI）、蔓延度指数（CONTAG）和聚集度指数（AI）与土壤盐渍化程度呈正相关关系,说明垦区受人类活动干扰越小,斑块越聚集,优势斑块作用越突出,越有利于盐分的集聚;斑块密度（PD）、边缘密度（ED）、景观形状指数（LSI）和香农多样性指数（SHDI）与土壤盐渍化程度呈负相关关系,说明景观的破碎化程度越高,景观结构越复杂,研究区内不同类型的景观斑块数量越多,越有利于土壤的盐渍化程度的降低。曹雷等的研究同样认为土壤盐分与缓冲区内斑块密度（PD）、景观形状指数（LSI）呈负相关,而与聚合度（AI）和蔓延度（CONTAG）呈正相关[12]。从斑块类型水平来看,农建地和水浇地的大面积团聚分布具有一定的积盐效应,而景观的破碎化和形状的复杂化则可以有效降低土壤的盐渍化程;旱地景观的单个斑块面积越大,几何形状越复杂,斑块聚集程度越高,越有利于土壤的盐渍化程度的降低。

4.3 滨海盐渍土改良治理对策

结合滨海滩涂围垦区的环境特征和土壤盐渍化特征以及空间分异趋势,针对性提出滨海盐渍土改良治理对策。① 合理规划土地利用方式,优化土地利用格局,分散布局水浇地、农建地等用地类型,增加斑块密度,提升景观的破碎化程度和景观结构的复杂性。② 实施生态快速改良,加快促进水浇地向水田、旱地等用地类型转变。综合物理（客土改良、秸秆覆盖和水旱轮作等）、化学（结构改良剂和化学改良剂等）、生物（耐盐植被）和工程（土地平整、灌排系统和暗管排盐等）改良措施,加快重度盐渍化地区排盐排碱。

5 结论

本文以景观生态学理论为基础,通过建立实际采样点不同梯度缓冲区,将采样点缓冲区内的景观格局与土壤盐渍化程度指标进行了典范对应分析,结论如下：
（1）研究区景观组成以水浇地和旱地为主,景观破碎化程度居民点最高,其次为旱地;河流沟渠和农建地相对呈连续分布;河流沟渠的景观结构最为复杂,而林草地和滩涂盐沼则较为简单;各种地类聚集程度均较高,但同一斑块的连通性一般,区域范围内存在着多种类型、不同面积的斑块,景观分布受人为干扰的程度较大。
（2）研究区表层土壤盐渍化程度差异较大,以可溶性氯化物盐为主,硫酸盐次之,重碳酸盐最小。研究区土壤St和SAR的平均含量分别为8.35 g/kg和11.71,属重度盐渍化土。土壤盐渍化指标的变异系数差异巨大,从HCO3-的53.49%到Cl-/SO42-的180.13%,说明人为的改良活动是造成土壤盐渍化非均匀分布的主要原因。
（3）研究区土壤盐渍化程度与景观组成存在密切的关系,其中农建地和水浇地面积比例与土壤盐渍化程度呈正相关关系,旱地面积比例则与盐渍化程度呈负相关关系。在景观水平上,土壤的盐渍化程度受景观的破碎化、多样性和蔓延度的影响较大,景观越破碎、结构越复杂、类型越丰富,斑块分布越零散,土壤的盐渍化程度越低。在斑块类型水平上,影响土壤盐渍化程度的景观格局指数因景观类型和景观格局尺度不同而异,其中,最大斑块面积指数（LPI）、边缘密度（ED）、景观形状指数（LSI）是影响研究区土壤盐渍化程度的共性指标。

The authors have declared that no competing interests exist.

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[10]
王玉刚, 李彦, 肖笃宁. 土地利用对天山北麓土壤盐渍化的影响. 水土保持学报, 2009, 23(5): 179-183.通过野外调查和室内分析,研究了新疆三工河流域平原绿洲耕地、人工林地、草地、灌木林地和盐碱地0-20 cm表层土壤盐渍化特征。结果表明：整个农业绿洲土壤盐分含量均值为9.33 g/kg,其中耕地平均值为6.9g/kg,超过75%耕地样点集中分布在低于2 g/kg的区间,而其它土地利用类型均高于10 g/kg,并且样点分散分布于各盐分等级中,自然和人为活动对不同土地利用类型盐分聚积均有显著作用;随地貌单元,自南向北盐分均值含量增加,在冲洪积扇中上部和地下水溢出带,盐分均值低于3.8 g/kg,而在冲洪积平原区,则高于10 g/kg;由于区域水资源的南北分布格局与利用差异,使得土壤盐分具有中等或强的空间变异性。

DOI

[Wang Yugang, Li Yan, Xiao Duning.Effects of land use type on soil salinization atnorthern slope of Tianshan Mountain. Journal of Soil and Water Conservation, 2009, 23(5): 179-183.]

[11]
孙倩, 塔西甫拉提·特依拜, 张飞, 等. 干河—库车河三角洲绿洲土地利用/覆被时空变化遥感研究. 生态学报, 2012, 32(10): 3252-3265.土地利用/覆被变化( LUCC) 是全球变化研究的重要核心问题之一，选择干旱区典型绿洲新疆干河—库车河三角洲绿洲为研究靶区，利用1989 年、2001 年、2006 年和2010 年的同期遥感影像数据，借助RS 和GIS 技术，对绿洲土地覆盖变化信息进行定量提取和分析。结果表明: ①1989—2001 年，各类地物面积呈现五增二减的趋势: 耕地、林地、中度盐渍地、水体和其他均有所增加; 而轻度盐渍地和重度盐渍地有所减少; 2001—2006 年，呈现四增三减的趋势: 耕地，轻度盐渍地，中度盐渍地和重盐渍地均有所增加; 林地、水体和其他均有所减少; 2006—2010 年，呈现四增三减的趋势: 中度盐渍地，重度盐渍地、水体和其他均有所增加; 耕地、林地、轻度盐渍地均有所减少。②随着时间的推移，各类地物的重心均有所偏移。其中水体的重心于1989—2001 年间向北迁移的距离最远，为23． 12 km; 同期重度盐渍地重心迁移距离次之，为22． 04 km。林地的重心于1989—2001 年间逐年向西南方向迁移，并且迁移的距离逐年增大，中度盐渍地重心总体向西北方向偏移。③21 年间，Shannon 多样性指数、Shannon 均匀度指数均呈稳步增加的趋势，景观的异质性程度呈现上升趋势; 聚集度差异不大，集中在78 到85 之间，说明斑块类型连接程度较高。1989—2006 年，分维数增加，研究区的土地利用景观格局愈来愈复杂，人类干扰程度在不断增强;2006—2010 年，分维数略有所下降，景观格局略有所改善。总之， 21 年间-库地区各类型土地利用情况变化显著，不仅各土地覆盖类型间面积转换频繁，而且土地利用景观格局发生了很大的变化。该研究确定了土地利用/土地覆被的时空变化规律，分析驱动因子，提出改良建议，研究结果对西部干旱区绿洲的环境演变和可持续发展研究具有现实意义，也是对全球变化研究的重要补充。

DOI

[Sun Qian, Tashpolat Tiyip, Zhang Fei, et al.Dynamics of land use/cover changes in the Weigan and Kuqa Rivers Delta oasis based on remote sensing. Acta Ecologica Sinica, 2012, 32(10): 3252-3265.]

[12]
曹雷, 丁建丽, 于海洋. -库绿洲多尺度景观格局与盐度关系. 农业工程学报, 2016, 32(3): 101-110.中国盐渍化土壤面积大，分布广，对区域农业发展构成了严重的威胁。探索土壤景观格局与盐度的关系将有助于盐渍化监测和评估。该研究选择-库绿洲GF-1影像为数据源，结合研究区同期38个样点不同剖面土壤盐度数据，对样点缓冲区景观格局与土壤盐度做Pearson相关分析和逐步回归分析，揭示土壤盐度空间分布格局，探讨景观格局与盐度的定量关系。结果表明：1）水平方向上，土壤盐分高值区主要集中分布在绿洲东部荒漠地带和绿洲西部农牧交错区；垂直方向上，-库绿洲表层土壤盐渍化现象最为严重，其他各层土壤盐渍化情况相对较轻，盐渍化程度随着深度下降呈降低趋势；2）绿洲区域易受人类活动影响，景观破碎化程度高，而同一区域不同梯度下，随着缓冲距离的增加，区域景观类型增多、均质性降低、多样性增强；3）耕地利用数量指标能较好指示土壤盐度状况，而水体面积、盐渍地面积、其他用地面积、最大斑块指数（largest patch index，LPI）、蔓延度（contagion index，CONTAG）和分维数（perimeter-area fractal dimension，PAFRAC）对盐度影响相对较弱；4）除0～10 cm层外，自＞10～20 cm至＞80～100 cm层逐步回归方程的自变量中，耕地面积、水体面积和最大斑块指数LPI为负效应，而盐渍地面积、其他用地面积、CONTAG和PAFRAC为正效应，最优回归方程决定系数为0.537。该研究确定了-库绿洲土壤盐度的分异规律，以及不同盐度对绿洲景观格局的影响程度。研究结果可为西北干旱区绿洲土壤盐度预警提供理论依据，同时为干旱区景观格局研究提供一定的参考价值。

DOI

[Cao Lei, Ding Jianli, Yu Haiyang.Relationship between multi-scale landscape pattern and salinity in Weigan and Kuqa rivers delta oasis. Transactions of the CSAE, 2016, 32(3): 101-110.]

[13]
傅伯杰, 陈利顶, 马克明, 等. 景观生态学原理及应用. 北京: 科学出版社, 2011.

[Fu Bojie, Chen Liding, Ma Keming, et al.Principle and Application of Landscape Ecology. Beijing: Science Press, 2011.]

[14]
邬建国. 景观生态学: 格局、过程、尺度与等级. 北京: 高等教育出版社, 2007.

[Wu Jianguo.Landscape Ecology: Pattern, Process, Scale and Hierarchy. Beijing: Higher Education Press, 2007.]

[15]
国土资源部. GB-T21010-2007. 土地利用现状分类标准. 北京: 中国标准出版社, 2007.

[Ministry of Land and Resources of the People's Republic of China. Current Land Use Classification (GB-T21010-2007). Beijing: Standards Press of China, 2007.]

[16]
耿润哲, 李明涛, 王晓燕, 等. 基于SWAT模型的流域土地利用格局变化对面源污染的影响. 农业工程学报, 2015, 31(16): 241-250.近年来随着流域经济社会的快速发展，密云水库流域的土地利用格局也发生了明显的改变，作为影响流域非点源污染输出的主要因素，探讨土地利用格局的演变对非点源污染的影响对有效控制非点源污染具有重要的意义。该文以密云水库上游流域为研究区，从土地利用变化与污染过程相互作用的角度出发，开展流域非点源污染过程对土地利用变化的响应研究。基于流域1995年、2000年、2005年3期的土地利用数据，基于SWAT（soil and water assessment tool）模型，模拟评价流域非点源污染负荷分布特征，并应用景观格局指数、典范对应分析（canonical correspondence analysis, CCA）和通径分析等方法，从全流域和三级保护区等多空间尺度，量化分析流域土地利用及其格局时空变化对非点源污染负荷的影响。研究结果表明流域的非点源负荷与土地利用格局间存在着密切的联系。格局指数能累积解释流域非点源污染负荷变化的56.3%。污染负荷受土地利用格局的破碎度和形状的影响较大。通径分析的结果表明，耕地、林地面积比例、形状指数和斑块密度是影响研究区非点源污染负荷输出的主要因子，其中形状指数和耕地面积比例对 TN、TP 负荷的解释能力要明显高于其他指标。从空间尺度上看，各格局因子与非点源污染负荷的关系具有尺度效应，随着空间尺度的递增，格局对负荷的解释程度降低，在较小的尺度范围内，尤其是一级保护区的解释能力最高，达到62.9%，表明离水库越近的区域应是非点源防治高度重视的区域。

DOI

[Geng Runzhe, Li Mingtao, Wang Xiaoyan, et al.Effect of land use/landscape changes on diffuse pollution load from watershed based on SWAT model. Transactions of the CSAE, 2015, 31(16): 241-250.]

[17]
李明涛, 王晓燕, 刘文竹. 潮河流域景观格局与非点源污染负荷关系研究. 环境科学学报, 2013, 33(8): 2296-2306.以密云水库上游潮河流域为研究 区,在HSPF模型模拟的基础上,利用CCA排序和路径分析等多种统计分析方法,分析不同水平景观格局与非点源污染过程的相关关系,确定各景观指数对非点 源污染的影响和贡献程度.结果表明:潮河流域景观格局与非点源污染过程的关系密切,二者的关系与空间尺度也有着紧密的关联.景观格局指数能累积解释55% 的流域非点源污染负荷变化,土地利用面积比例的影响要大于景观格局指数,耕地是污染负荷的主要贡献源,而林地和草地较能有效控制污染物的输出.污染负荷受 景观的破碎化、多样性和蔓延度的影响较大,流域内的景观越破碎、类型越丰富,斑块分布越零散,污染物的输出也就越多.斑块类型水平上,影响污染物负荷的指 标因景观类型不同而异,其中,斑块密度(PD)和边缘密度(ED)是影响流域非点源污染负荷的共性指标.路径分析的结果表明,边缘密度(ED)、香农多样 性指数(SHDI)、聚集度指数(AI)和蔓延度指数(CONTAG)是影响流域非点源污染负荷输出的主要景观格局变量,其中,香农多样性指数对TN、 TP负荷的解释能力最大.较少的人类活动干扰和斑块类型的团聚分布能减少污染物输出的风险.

[Li Mingtao, Wang Xiaoyan, Liu Wenzhu.Relationship between landscape pattern and non-point source pollution loads in the Chaohe River Watershed. Acta Scientiae Circumstantiae, 2013, 33(8): 2296-2306.]

[18]
李铖, 李芳柏, 吴志峰, 等. 景观格局对农业表层土壤重金属污染的影响. 应用生态学报, 2015, 26(4): 1137-1144.景观格局是决定诸多生态过程的重要因素，但其对农业土壤重金属污染的影响尚未明确.鉴于此，本研究基于珠江三角洲2005年的300个表层土壤as、pb、cd、ni样点数据和土地利用/覆盖图，使用地统计分析、景观格局分析、单因子污染指数和pearson相关分析，揭示4种农业表层土壤重金属的污染特征及空间分布格局，探讨样点缓冲区内景观格局与农业表层土壤重金属污染的定量关系.结果显示：1)235个农业表层土壤样品中，as、pb、cd和ni超过国家土壤质量二级标准的比例分别为3.8%、0.4%、17.0%和9.4%，高污染区主要位于广州、佛山和中山；2)耕地表层土壤样品中重金属的平均污染水平大于林地和果园，但除了cd，其他3种重金属污染水平在不同农用地类型上的差异并不显著；3)缓冲区内水体的比例、平均斑块规模、破碎化程度、景观形状复杂度和聚集度/连接度与4种表层土壤重金属污染水平呈显著正相关；缓冲区内城市用地的部分景观格局与土壤pb和cd污染水平呈现类似的显著正相关.相反，缓冲区内林地的比例、平均斑块规模和聚集度越大，土壤pb和ni污染水平越低(呈显著负相关， p <0.05)；4)距离工业用地越近，农业表层土壤pb、cd和ni污染水平越高.景观多样性仅与土壤cd污染呈显著正相关.研究结果可为珠江三角洲农业土壤重金属污染防治提供理论依据.？

[Li Cheng, Li Fangbai, Wu Zhifeng, et al.Impacts of landscape patterns on heavy metal contamination of agricultural top soils in the Pearl River Delta, South China. Chinese Journal of Applied Ecology, 2015, 26(4): 1137-1144.]

[19]
哈凯, 丁庆龙, 门明新, 等. 山地丘陵区土地利用分布及其与地形因子关系: 以河北省怀来县为例. 地理研究, 2015, 34(5): 909-921.为探究山地丘陵地区不同地形因子对土地利用空间格局的影响,以河北省怀来县为例,研究了各土地利用类型在不同地形上的分布特征。同时,定性和定量分析了土地利用景观格局与地形环境的相关性。研究表明土地利用景观格局分布存在明显的地形梯度特征,较高地形级别主要分布着林地和草地,其分布指数在较高地形级别占据优势位;而受人类活动干扰影响较大的城乡建设用地、采矿用地、耕地、园地和水域的优势位分布在较低地形级别上。移动窗口法得到的景观格局指数的分布定性显示出土地利用景观格局随地形变化的梯度特征,典范对应分析结果定量显示出典范对应分析排序的前4个轴的累计土地利用景观指数—地形解释变量为96.98%,地形因子第1排序轴与土地利用变化景观格局指数特征第一排序轴的相关系数达到0.671,其土地利用景观格局指数与地形因子存在显著的相关性。由此可见,高程、坡度和地形起伏度这三类地形因子对山地丘陵区的土地利用类型的结构和空间分布起着重要的影响作用。

DOI

[Ha Kai, Ding Qinglong, Men Mingxin, et al.Spatial distribution of land use and its relationship with terrain factors in hilly area. Geographical Research, 2015, 34(5): 909-921.]

[20]
沙迪, 翟清明, 张雪萍, 等. 甲氨基阿维菌素苯甲酸盐对黑土区农田土壤动物群落的影响. 地理研究, 2015, 34(5): 872-882.甲维盐属高效半合成抗生素杀虫剂。在哈尔滨市典型黑土农田区,研究不同浓度甲维盐处理对土壤动物群落结构的影响。结果表明:甲维盐处理显著降低了土壤动物群落的个体密度和类群数量,且这种趋势随着甲维盐浓度的增加而增强;显著改变了群落的垂直分布格局,表聚性特征被削弱,使动物较多地聚集于5~15 cm土层;改变了群落多样性特征,其中螨类和跳虫对多样性的贡献相对较大;显著改变了表层土壤化学性质,但不同动物类群对土壤环境变化的响应规律不同,螨类和跳虫对甲维盐干扰具有较强的适应能力。甲维盐处理可以显著改变黑土区农田土壤动物群落结构,浓度是影响该过程的重要因素,施用杀虫剂时需慎重评价其生态后果。

DOI

[Sha Di, Zhai Qingming, Zhang Xueping, et al.Effects of emamectin benzoate on soil animal community in a black soil farmland. Geographical Research, 2015, 34(5): 872-882.]

[21]
张金屯. 数量生态学. 北京: 科学出版社, 2004.

[Zhang Jintun. Quantitative Ecology.Beijing: Science Press, 2004.]

[22]
Li J G, Pu L J, Zhu M, et al.Evolution of soil properties following reclamation in coastal areas: A review. Geoderma, 2014, 226: 130-139.Reclamation in coastal zones is effective for relieving population pressure and ensuring food safety. Since the 1950s, the development of coastal zones has entered a peak period. At present, the reclamation of coastal zones mainly occurs in developing countries. The coastal reclaimed lands are mainly used for agricultural production, urban and industrial development, and port construction. The scale and scope of reclamation in coastal lands are larger than in interior lands, and pose substantial environmental risks. This review summarizes the trends in soil physicochemical property evolution following reclamation in salt marshes from around the world. The following important conclusions were obtained: physicochemical properties of coastal saline soils (CSSs) significantly improved over the long term following reclamation in Eastern Asia. Long term fertilization and cultivation resulted in modified soil structure [an increase in the proportion of macroaggregates (>250m) and silt (0.002-0.05mm)], enhancing the capacity for preserving fertility and C sequestration. Reclamation significantly increased soil organic matter (SOM), phosphorus (P), and nitrogen (N) concentrations, and soil properties approached a relatively stable level nearly 30years after reclamation, especially in Eastern Asia. However, in Europe and North America, SOM in coastal reclaimed soils (CRSs) decreased rapidly after reclamation, and soil acidification was also a severe problem during reclamation. Coastal reclamation could significantly increase soil GHG (CO 2 , CH 4 , and N 2 O) emissions, further affecting global C cycle. Microbial biomass and activity as well as activities of related enzymes increased gradually in CRS in Eastern Asia, in particular the activities of urease and phosphatase involved in nutrient cycling. In general, physicochemical properties of CRS in Eastern Asia tend to modify, but deteriorate in Europe and North America. Nevertheless, offshore eutrophication, soil heavy metal and organic pollutant concentrations, and salt marsh ecosystem degradation were the most serious environmental risks posed by coastal reclamation. Some strategies to alleviate these risks are put forward. In this review, we also identified priority areas of future research on CRS.

DOI

[23]
王遵亲, 祝寿泉, 俞仁培, 等. 中国盐渍土. 北京: 科学出版社, 2004.

[Wang Zunqing, Zhu Shouquan, Yu Rrenpei, et al.Saline Soil in China. Beijing: Science Press, 1994.]

[24]
Wu Y, Liu R, Zhao Y, et al.Spatial and seasonal variation of salt ions under the influence of halophytes, in a coastal flat in eastern China. Environmental Geology, 2009, 57(7): 1501-1508.The high salinity of coastal saline field is a key factor limiting the reclamation. Halophytes have been utilized in the reclamation of saline land. The study area is in Yancheng, China. An analysis of the concentrations of Rb, Cs, Sr, and Ba, the ratio of Rb/Cs, and Sr/Ba in soils in autumn shows that the soil of this study area has great homogeneity. Artemisia halodendron, Gossypium hirsutum,...

DOI

[25]
Xu Y, Pu L J, Zhu M, et al.Spatial variation of soil salinity in the coastal reclamation area, Eastern China. Journal of Coastal Research, 2014, 30(2): 411-417.Reclamation of coastal saline tidal flats has become a common practice for coastal countries faced with a decrease in cultivated land and an increase in population. Because the variability of soil salinity is considerable, understanding the spatial distribution of this salinity and its components is essential for land use planning. This study was conducted in a coastal area in eastern China that has been reclaimed under various land use types at different times. The objective of the work was to assess the effect of the reclamation time and land use types on soil salinity and spatial variation of soil salinity by using conventional statistics and geostatistical techniques. The results indicate that reclamation times and land use types significantly influence soil salinity in coastal areas. Cropland and aquaculture pond have same effect on soil desalinization. Soil desalinization reached a balance after 30 years. According to the average soil salinity at the depth of 0-40 cm and soil salinity spatial stability of soil profile, the study area is divided into eight management zones, which is useful for soil sampling investigation and making decisions on the kind of crops that can be cultivated at the different fields of the study area.

DOI

[26]
Yu J, Li Y, Han G, et al.The spatial distribution characteristics of soil salinity in coastal zone of the Yellow River Delta. Environmental Earth Sciences, 2014, 72(2): 589-599.In coastal area, salinization is a common and serious problem for crop cultivation and ecological restoration of degraded wetlands. Therefore, the soil salinity has attracted increasing attention from farmers, government and environmental scientists. The factors controlling the soil salinity distribution have become a hot point in saline soil studies. In this study, statistics and geostatistics were used to explore the distribution of soil salinity in the Yellow River Delta (YRD) based on 150 soil samples that were collected in June 2010. Besides the experimental work, a geographical information system technique was adopted in this study. The results showed that the soil salinity ranged from 0.11 to 10.50dSm 1 and the salinity in topsoil was higher than that in subsoil in the YRD, indicating that the salt in subsoil moved up and accumulated in topsoil as a function of evaporation. There was a significant difference among soil salinity spatial variances from different soil depths in the YRD. Generally, soil salinity of the topsoil was higher than that of the subsoil. Meanwhile, there were significant positive correlations in soil salinity between different soil depths. In addition, landforms, land uses, soil types and soil texture were important factors affecting soil salinity. The current distribution of soil salinity resulted from the comprehensive effects of anthropogenic activities and natural processes. The present study results suggest that the impacts of human activities were critical factors for salt redistribution in the coastal wetlands, which should be valuable for agricultural management and ecological restoration in the YRD.

DOI

[27]
Sun Y, Chen X, Zhang Z, et al.The spatial variation of apparent soil electrical conductivity on the root area of cotton fields in coastal saline soil. Chinese Journal of Soil Science, 2014, 45(3): 585-589.Soil salinization and secondary salinization were the key obstruction factors which restricted the agricultural sustainable development of the Yellow River delta. Understanding and evaluating the spatial-temporal dynamics of farmland soil salinity was the premise to use and improve it scientifically. The cotton filed in the coastal saline-alkali land of the Yellow River delta was selected as research object in this paper. EM38- MK2 earth conductivity meter was used to measure the apparent conductivity of soil root layers(0 ~ 0.375 m and 0 ~ 0.75 m) at the two key growth periods before and after the precipitation concentrated months, meanwhile the spatial distribution characteristics and influence factors of apparent conductivity in the cotton root zone soil were analyzed. The results showed that: 1) before and after the precipitation, the spatial variation of coastal soil salinity at Yellow River delta was up to or over medium level; 2) after correcting earth conductivity and eliminating interference factors for reading, the earth conductivity of the two key soil layers(0 ~ 0.375 m and 0 ~ 0.75 m) could be rapidly determined, which could be effectively used to monitor and evaluate the soil salinization in coastal cotton field; 3) Based on the region survey of landform and crop growth condition in the Yellow River delta region, we suggested that it should be optimized land use pattern and strengthened the infrastructure of irrigation and water conservancy at the regional scale. For the field scale, strengthening land consolidation and setting up a complete set of irrigation and drainage measure were the basis for management and improvement of coastal saline soil.

[28]
Yu J B, Li Y Z, Han G X, et al.The spatial distribution characteristics of soil salinity in coastal zone of the Yellow River Delta. Environmental Earth Sciences, 2014, 72(2): 589-599.In coastal area, salinization is a common and serious problem for crop cultivation and ecological restoration of degraded wetlands. Therefore, the soil salinity has attracted increasing attention from farmers, government and environmental scientists. The factors controlling the soil salinity distribution have become a hot point in saline soil studies. In this study, statistics and geostatistics were used to explore the distribution of soil salinity in the Yellow River Delta (YRD) based on 150 soil samples that were collected in June 2010. Besides the experimental work, a geographical information system technique was adopted in this study. The results showed that the soil salinity ranged from 0.11 to 10.50dSm 1 and the salinity in topsoil was higher than that in subsoil in the YRD, indicating that the salt in subsoil moved up and accumulated in topsoil as a function of evaporation. There was a significant difference among soil salinity spatial variances from different soil depths in the YRD. Generally, soil salinity of the topsoil was higher than that of the subsoil. Meanwhile, there were significant positive correlations in soil salinity between different soil depths. In addition, landforms, land uses, soil types and soil texture were important factors affecting soil salinity. The current distribution of soil salinity resulted from the comprehensive effects of anthropogenic activities and natural processes. The present study results suggest that the impacts of human activities were critical factors for salt redistribution in the coastal wetlands, which should be valuable for agricultural management and ecological restoration in the YRD.

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