Zone II • Versions EN1
Abstract: As a basic component of the Earth’s surface system, soil plays an important role in storing nutrients, maintaining plant growth, conserving water resources, and stabilizing and buffering environmental changes. Standardized surveys and monitoring can be used to delineate the physical, chemical, and biological attributes of soil, which are of great significance for improving regional soil property databases and revealing the spatial distribution of soil. In this study, we conducted standardized field investigations, soil sample collection and tests in nine typical natural forest ecosystems during July and August 2013, including tropical rain forests, subtropical broad-leaved forests, temperate broad-leaved forests, temperate coniferous and broad-leaved mixed forests, and cold temperate coniferous forests in the north-south transect of China. A comprehensive dataset of soil properties was built, covering the main forest types in the northern hemisphere. The dataset contains basic information, including sampling location, climate, vegetation type, biomass, soil type, soil environment (pH, soil temperature, and moisture), soil mechanical composition (sand, clay, silt), soil nutrients (organic matter, total nitrogen, total phosphorus), soil organic carbon components (easy-oxidized organic carbon, microbial carbon, dissolved organic carbon), soil humic carbon components (humic acid carbon, fulvic acid carbon, humin carbon, extractable humus carbon), and soil element content (K, Ca, Na, Mg, Al, Zn, Fe, Cu, Mn). The dataset provides important information for studies investigating the distribution and control mechanisms of forest soils. It also provides data support for optimizing and developing the forest ecosystem process model.
Keywords: north-south transect of eastern China; forest ecosystem; natural forest; soil property
|Title||A dataset of forest soil attribute in the north-south transect of eastern China|
|Data corresponding author||He Nianpeng (firstname.lastname@example.org)|
|Data authors||Xu Li, He Nianpeng|
|Time period||July and August 2013|
|Geographical scope||3700 km from north to south with latitudes ranging from 51.8°N to 18.7°N and longitudes ranging from 108.9°E to 123.0°E; specific areas include: Jianfengling, Dinghu Mountains, Jiulian Mountains, Shennongjia, Taiyue Mountains, Dongling Mountains, Changbai Mountains, Liangshui and Huzhong.|
|Data volume||17.5 KB|
|Data service system||<http://www.cnern.org.cn/data/meta?id=40578>; <http://www.sciencedb.cn/dataSet/handle/602>|
|Sources of funding||Strategic Priority Research Program of the Chinese Academy of Sciences (XDA19020302); National Key Research and Development Program of China (2016YFA0600104); Science and Technology Service Network Initiative of the Chinese Academy of Sciences (KFJ-SW-STS-169)|
|Dataset composition||The dataset consists of one data document, including sampling site, sampling location, climate type, soil type, vegetation type, dominant tree species, vegetation biomass, soil pH, soil temperature, soil moisture, soil texture, soil nutrition content, etc.|
Soil, a basic component of terrestrial ecosystems, plays an important role in storing nutrients, maintaining plant growth, protecting biodiversity, conserving water sources, and purifying the environment.1-3 In the context of global change, comprehensive information on soil attributes helps to improve regional and global soil databases, and to elucidate the response and feedback of soil properties to climate change, thereby providing a reference for regional ecological environment management. Previous studies have conducted on-site investigations on soil properties, which generated basic data for the construction of regional- and global-scale soil attribute databases.4 However, restricted by labor, material and financial resources, earlier regional soil databases largely used common indicators, whereas other monitoring indicators were ignored, which hindered the development of soil science on both regional and global scales.5
As an important component of the forest ecosystem, forest soil plays a vital role in maintaining ecosystem stability and service function.6 Its distributional characteristics and influencing factors on regional scales are helpful to clarify the response and feedback of forest ecosystems to global change. Additionally, a scientific, comprehensive and systematic forest soil attribute dataset we build here can be used to develop and optimize the ecological process model.
Based on the North-South Transect of Eastern China (NSTEC) in the 15 standard bands delineated by the International Geosphere Biosphere Program (IGBP), we selected nine zonal forest ecosystems from the southern rainforests to the northern cold temperate needles, which covered the major forest ecosystem types in the northern hemisphere. We developed a detailed sample survey scheme, and conducted field survey, collection and indoor analysis in accordance with relevant standards and requirements, to form a systematic dataset on China’s typical forest soil properties. The dataset includes information on vegetation type, soil type, climatic environment, soil nutrient, soil texture, soil organic carbon composition, and soil humus carbon composition. This dataset enriches regional and global soil databases and provides data support for the study of soil distribution and control mechanisms. It also provides basic data for model simulation and optimization.
The dataset formation involved steps including field investigation, data processing, data quality control and assessment, data analysis. Detailed procedures are shown in Figure 1.
2.1 Data source
NSTEC is the official fifteenth standard transect of the IGBP. The transect covers about one-third of China’s land area and spans several climatic zones from south to north (e.g., equatorial monsoon climate zone, tropical monsoon climate zone, subtropical monsoon climate zone, warm temperate monsoon climate zone, temperate monsoon climate zone, and cold temperate continental east coast monsoon climate zone) (Table 1 & Figure 2). It is a unique, complete and continuous vegetation belt driven by the world’s heat gradient.7 NSTEC hosts a variety of vegetation types. Distributed successively from south to north are: tropical mountain rain forest, subtropical broad-leaved evergreen forest, temperate broad-leaved deciduous forest, temperate coniferous mixed forest, and cold-temperate coniferous forest are distributed successively, representing the main forest types in the northern hemisphere. Soil physical and chemical properties change significantly as the latitude increases. Red soil with low organic matter content is mostly distributed in low latitude areas, while brown soil with high organic matter content is usually distributed in high latitude areas. This transect provides an ideal natural experimental platform for exploring the structure and function of forest ecosystems, and may help to determine variations in vegetation and soil patterns, as well as control mechanisms for different types of forest ecosystems from regional scales.
|Location||Latitude(N)||Longitude(E)||Vegetation type||Soil type||Human disturbance|
|JF*||18°44'18''||108°51'26''||Tropical monsoon forest||Latosol||No (>100 y)|
|DH||23°10'25''||112°32'14''||Subtropical monsoon evergreen broad-leaved forest||Latosol||No (>80 y)|
|JL||24°35'05''||114°26'28''||Subtropical evergreen broad-leaved forest||Kandiudult||No (>80 y)|
|SN||31°19'15''||110°29'43''||North subtropical deciduous evergreen mixed forest||Dystrochrepts||No (>100 y)|
|TY||36°41'43''||112°04'39''||Warm temperate deciduous broad-leaved forest||Cinnamon soil||No (>100 y)|
|DL||39°57'27''||115°25'24''||Warm temperate deciduous broad-leaved forest||Eutrochrepts||No (>60 y)|
|CB||42°24'16''||128°05'27''||Temperate conifer broad-leaved mixed forest||Cryumbreps||No (>80 y)|
|LS||47°11'06''||128°53'51''||Temperate conifer broad-leaved mixed forest||Cryumbreps||No (>100 y)|
|HZ||51°46'48''||123°01'12''||Cold temperate coniferous forest||Cryorthods||No (>100 y)|
Notes: JF, Jianfengling; DH, Dinghu Mountains; JL, Jiulian Mountains; SN, Shennongjia; TY, Taiyue Mountains; DL, Dongling Mountains; CB, Changbai Mountains; LS, Liangshui; HZ, Huzhong.
The dataset of forest soil properties in the north-south transect of eastern China come from nine typical forest ecosystems on NSTEC (i.e., Jiangfengling [JF], Dinghu Mountains [DH], Jiulian Mountains [JL], Shennongjia [SN], Taiyue Mountains [TY], Dongling Mountains [DL], Changbai Mountains [CB], Liangshui [LS], and Huzhong [HZ]). JF is located in the low latitude tropical monsoon climate region, where the zonal vegetation type is tropical evergreen monsoon forest, and the main soil type is Latosol,8 and Livistona saribus, Prismatomeris tetrandra, and Altingia obovata are the dominant species. DH is located in the humid subtropical monsoon climate region, where the zonal vegetation type is evergreen broad-leaved forest, the main soil type is Latosol,9.and Schima superba, Castanopsis chinensis, and Pinus massoniana are the dominant species. JL is located in the subtropical monsoon climate region, where the zonal vegetation type is evergreen broad-leaved forest, the main soil type is Kandiudult,10 and Castanopsis carlesii, Castanopsis fargesii, Castanopsis fabri, and Schima superba are the dominant species. SN is located in the north subtropical climate region, where the zonal vegetation type is deciduous evergreen mixed forest, the main soil type is Dystrochrepts,11 and Quercus multinervis, Quercus engleriana, and Quercus aliena are the dominant species. TY is located in the warm temperate climate region, where the zonal vegetation type is deciduous broad-leaved forest, the main soil type is Cinnamon,12 where Pinus tabuliformis and Quercus liaotungensis are the dominant species. DL is located in the warm temperate climate region, where the zonal vegetation type is deciduous broad-leaved forest, the main soil type is Eutrochrepts,13 where Quercus wutaishanica and Juglans mandshurica are the dominant species. CB is located in the temperate climate region, where the zonal vegetation type is conifer broad-leaved mixed forest, the main soil type is Cryumbreps,14 where Pinus koraiensis and Tilia amurensis are the dominant species. LS is located in the temperate climate region, where the zonal vegetation type is conifer broad-leaved mixed forest, the main soil type is Cryumbreps,15 and Populus ussuriensis, Pinus koraiensis, and Fraxinus mandshurica are the dominant species. HZ is located in the cold temperate climate region, where the zonal vegetation type is conifer forest, the main soil type is Cryorthods,16 where Larix gmelinii, Betula platyphylla, and Pinus sylvestris are the dominant species.
Field investigations were conducted in the nine typical forests along the NSTEC from July to August 2013. To minimize the effects of land-use change and anthropogenic disturbance, the experimental plots were set in climax forest, using four plots as four independent replicates (30 m × 40 m) for each forest type. We investigated the plant community structure and obtained plant samples before soil sampling. In each plot, soil samples were randomly collected from 30–40 points in the 0–10 cm soil layer using a soil auger, which were then mixed together. The above-ground standing biomass, visible roots, gravel, stone, and litter were removed from the collected samples. Then, they were sieved through a 2 mm mesh and subdivided into two parts. One part was air-dried, and the other part was stored at 4°C. During field sampling, we used a right-angle geothermometer to measure soil temperature. The soil types in each forest were determined based on vegetation types and basic soil characteristics.
2.2 Data processing
After preliminary treatment in the field, soil samples were taken to the laboratory for further analysis. The testing indicators are showed in Figure 3. Soil water content was determined using the drying method. Soil pH and conductivity were measured at a soil-to-water ratio of 1:5. Soil total carbon and soil total nitrogen were determined with an elemental analyzer (Elementar, Vario Max CN, Germany), and soil total phosphorous was determined by the phosphoric acid-molybdenum antimony colorimetric method (Bran Lubbe, AA3, Germany). Soil organic carbon concentration was determined by the potassium dichromate digestion method. Easy-oxidized organic carbon content was determined by the method described by Blair et al.;17 soil microbial carbon was determined by the improved chloroform fumigation method18. An LS 230 laser-diffraction particle-size analyzer was used to determine the soil particle size composition. Soil humus carbon components (humic acid carbon, fulvic acid carbon, and humin carbon) were determined by the method described by Wang et al..19 Soil multi-element content was determined by the inductively coupled plasma atomic emission spectrometry (ICP-AES). Test values for each sample were recorded in time and detail, and all data were input into the computer.
The dataset of forest soil properties in the NSTEC includes: sampling site, sampling location (longitude and latitude), climate (annual average temperature, annual average precipitation, and drought index), soil type, zonal vegetation type, dominant species, vegetation biomass, soil pH, soil temperature (°C), soil water content (%), conductivity, redox potential, soil texture (sand, silt, and clay content; %), soil organic carbon content (SOC, g kg-1), total nitrogen (TN, g kg-1), total phosphorus (TP, g kg-1), easy-oxidized organic carbon content (EOC, g kg-1), soil microbial carbon (MOC, g kg-1), soil dissolved organic carbon (DOC, g kg-1), soil humic acid carbon (HAC, g kg-1), soil fulvic acid carbon (FAC, g kg-1), soil humin carbon (HUC, g kg-1), soil extractable humus carbon (HEC, g kg-1), and multi-element content of the soil (K, Ca, Na, Mg, Al, Zn, Fe, Cu, and Mn).
The dataset was derived from our field investigation and indoor analysis. The dataset quality was controlled through the whole process (including sampling site selection, plot setting, pre-investigation preparation, on-site sampling, and indoor analysis). Moreover, expert verification was used to further ensure the accuracy and reliability of the data.
Dataset quality control before the investigation: we selected nine typical forest ecosystems after carefully analyzing the geographical location, climate and vegetation characteristics of the north-south transect. In addition, we developed a systematic sampling plan to guide the work. To reduce human error, all participants in the survey undertook technical training courses according to the unified specification.
Dataset quality control during the investigation: for plant surveys, a uniform caliper was used to measure and record the diameter at breast height (DBH) of trees and the basal diameter of shrub. Plant names were recorded in consultation with Chinese Flora; species that could not be determined during the field survey were collected and taken back to the laboratory for further identification. According to the soil sampling specifications, the collected soil samples were clearly marked. To correct problematic data, original records were checked immediately after a sample survey was completed, and were supplemented with relevant information where appropriate. Moreover, the field records were digitalized and reviewed, while the original paper records were stored properly.
Dataset quality control after indoor analysis and testing: vegetation and soil samples were pretreated quickly in the laboratory. Then, according to our experiment schedule and the standard analysis method, sample testing was completed on time. The experimental data were entered into the computer in a timely manner and anomalies were checked. The completed dataset was firstly checked by the data organizer before being delivered to the experts for final review and revision to ensure its authenticity and reliability.
A large number of previous field surveys and sampling works have focused on forest ecosystems, some of which have provided basic soil attribute data; however, most of them have a single site focus that provide basic data on soil physical and chemical properties (e.g., SOC, TN, and TP), whereas detailed and systematic data on soil structure and relevant vegetation are lacked. The dataset of forest soil properties in the NSTEC (2013) covers the main forest types in China. Besides basic physical and chemical properties, data on the soil organic carbon component, soil humus carbon component, plant types and biomass are included. This dataset provides important basic data for analyzing the distribution characteristics and regulation mechanisms of different types of forest soils on a regional scale. However, it has some limitations, such as the relatively small number of sampling points and the lack of relevant soil microbial biomass data. To enrich the datasets of soil attributes in China, future studies can build upon our dataset for developing a more detailed sampling plan.
The dataset can be accessed through the Synthesis Research Center of CERN (http://www.cnern.org.cn) or Science Data Bank (http://www.sciencedb.cn/dataSet/handle/602). The former requires users to log in, where a click of “paper data” on the homepage, or of “paper data” in the “data resources” section will direct users to access and download the data. Readers interested in the spatial pattern and control mechanisms of soil attributes can refer to our previous studies.20-22 For other questions or data requests, please contact the corresponding author.
This study is supported by the leaders of CERN. We are very grateful to staff at Jianfengling, Dinghu Mountains, Jiulian Mountains, Shenlongjia, Taiyue Mountains, Dongling Mountains, Changbai Mountains, Huzhong, and Liangshui stations for their support of our field investigation.
Law R. Soil carbon sequestration impacts on global climate change and food security. Science 304(2004): 1623-1627.
Burke I, Yonker C, Parton W, et al. Texture, climate, and cultivation effects on soil organic matter content in US grassland soils. Soil Science Society of America Journal 53(1989): 800-805.
Yang C, Ouyang Z, Yang L, et al. Organic carbon fractions and aggregate stability in an aquatic soil as influenced by agricultural land uses in the Northern China Plain. Acta Ecologica Sinica 26(2006): 4148-4155.
Post W & Kwon K. Soil carbon sequestration and land-use change: processes and potential. Global Change Biology 6(2000): 317-327.
Allen D, Pringle M, Page K, et al. A review of sampling designs for the measurement of soil organic carbon in Australian grazing lands. Rangeland Journal 32(2010): 227-246.
Bonan G. Forest and climate change: forcings, feedbacks, and the climate benefits of forests. Science 320(2008): 1444-1449.
Zhang X & Yang D. Allocation and study on global change transects in China. Quaternary Sciences 1(1995): 43-52.
Chen D, Li Y, Liu H, et al. Biomass and carbon dynamics of a tropical mountain rain forest in China. Science China: Life Sciences 53(2010): 798-810.
Wang C, Yu G, Zhou G, et al. CO2 flux evaluation over the evergreen coniferous and broad-leaved mixed forest in Dinghushan, China. Science in China Series D: Earth Sciences 49 (2006): 127-138.
He J, Zhao X, Fan J, et al. Characteristics of a subtropical evergreen broad-leaved forest community in Jiulianshan. Acta Botanica Boreali-Occidentalia Sinica 30(2010): 2093-2102.
Xiong X, Xiong G, Xie Z, et al. The regeneration of tree species in the mixed evergreen-deciduous broad-leaved forests in the Shennongjia Mountains, Hubei Province. Acta Ecologica Sinica 22(2002): 2001-2005.
Han H, Nan H, Liu H, et al. A study on regeneration diversity in gaps in the typical forest in warm temperate zone of Taiyue Mountain in Shanxi Province. Journal of Beijing Foresty University 27(2005): 116-119.
Li L, Bai F, Liu H, et al. Species composition and community structure of four deciduous broad-leaved secondary forest in Dongling Mountain. Biodiversity Science 19(2011): 243-251.
Shen C, Xiong J, Zhang H, et al. Soil pH drives the spatial distribution of bacterial communities along elevation on Changbai Mountain. Soil Biology & Biochemistry 57(2013): 204-211.
Xu L & Jin G. Species composition and community structure of a typical mixed broad-leaved-Korean pine (Pinus koraiensis) forest plot in Liangshui Nature Reserve, Northeast China. Biodiversity Science 20(2012): 470-481.
Li Y, Hu Y, Chang Y, et al. Forest landscape change and driving forces in Huzhong Forest Bureau of Daxinganling in China. Acta Ecologica Sinica 26(2006): 3347-3357.
Blair G, Lefroy R & Lise L. Soil carbon fractions based on their degree of oxidation, and the development of a carbon management index for agricultural systems. Australian Journal of Agriculture Research 46(1995): 1459-1466.
Baumann A, Schimmack W, Steindl H, et al. Association of fallout radiocesium with soil constituents: effect of sterilization of forest soil by fumigation with chloroform. Radiation and Environmental Biophysics 35(1996): 229-233.
Wang C, He N, Zhang J, et al. Long-term grazing exclusion improves the composition and stability of soil organic matter in Inner Mongolian grasslands. PLOS ONE 2015: pone. 0128837.
Wen D & He N. Spatial patterns and control mechanisms of carbon storage in forest ecosystem: evidence from the north-south transect of eastern China. Ecological Indicators 61(2016): 960-967.
Xu L, Yu G, He N, et al. Carbon storage in China’s terrestrial ecosystems: A synthesis. Scientific Reports 8(2018): srep2806.
1. Xu L & He N. A dataset of forest soil properties in the north-south transect of eastern China. Science Data Bank. DOI: 10.11922/sciencedb.602 (2018).
How to cite this article
Xu L & He N. A dataset of forest soil properties in the north-south transect of eastern China. China Scientific Data 1(2019). DOI: 10.11922/csdata.2018.0027.zh