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Dataset Abstract

This research is designed to collect data on diversity in subtropical forest ecosystems and relate it to ecosystem services such as primary productivity, carbon storage, prevention of soil erosion, and invasion resistance to exotic plants. This data describes the Comparative Study Sites (CSPs), used to compare the planted diversity experiment with naturally grown forests. The plots have a size of 30x30m and are situated in the Gutianshan Nature reserve, Zhejiang Province, China. Data were collected in 2008. They comprise geographical locations, elevation, inclination, exposition of the plots, an estimated age of the plot, height and cover of two tree layers, the shrub layer and the herb layer, and cover of bare soil. This data set includes environmental measures on the CSPs that are of interest for all researchers.

Dataset Design

The utilization of the forest until the 1990ies allowed us to employ a stratified sampling for establishing observational plots (in the following called Comparative Study Plots, CSPs) according to successional stages. Although most of the forest are belongs to intermediate or late successional stages, young stands are located in the peripheral buffer zone of the Gutianshan NNR, where logging has been performed until the present. Plots were assigned to five strata according to the average age of tree layer individuals (1: < 20 yrs, 2: < 40 yrs, 3: < 60 yrs, 4: < 80 yrs, 5:  80 yrs). CSP locations within strata were selected randomly; however, due to inaccessibility and excessive slopes (> 50°) of many locations, parts to the NNR had to be excluded from sampling, thus, resulting in an uneven distribution of some of the plots (Fig. 1). In total, 27 CSPs were established between May and July 2008. Species recording was performed between May and October 2008 with several visits per plot. Each CSP has a size of 30 m by 30 m, which approximates to the plot size (1 mu plot) in the BEF-Experiment at Xingangshan (Jiangxi, Fig. 1). The corners of every CSP were permanently marked with magnets and subareas of each CSP were set apart for measuring various ecosystem functioning variables, among them basic soil properties. Soil moisture was assessed on soil samples taken from five different layers of the mineral soil in 10 cm-intervals on three dates (summer and autumn 2008, spring 2009). We used mean values by averaging the soil water contents over all layers and all dates. Topsoil samples (0-5 cm) were taken in summer 2009 from four locations in each plot, pooled in a bulk sample per CSP, air-dried and then used to determine pH, both measured in H2O and 1 M KCl. A complete inventory of woody species and bamboo (Pleioblastus amarus) (> 1 m height) was carried out on the whole plot. All herbaceous species and tree recruits (i.e. seedlings and saplings ≤ 1 m height) were recorded in a central subplot of 10 m x 10 m. All individuals were identified to the species level, making use of herbarium samples and comparisons with correctly identified individuals, and counted per species. The proportion of unidentifiable individuals in a CSP ranged between 0 % and 2.3 %. These individuals were not included in the subsequent data analysis.

Spatial Extent

The Gutianshan National Nature Reserve (NNR) is located in the western part of Zhejiang Province (29º8'18" – 29º17'29" N, 118º2'14" – 118º11'12" E, Fig. 1). The Gutianshan NNR has an area of approximately 81 km2 and was initially established as a National Forest Reserve in 1975 and became a National Nature Reserve in 2001. The NNR comprises a large portion of broad-leaved forests of advanced successional stages (Hu & Yu 2008), which have not been managed since the beginning of the 1990ies, as well as young successional stages and conifer plantations, mainly of Cunninghamia lanceolata and Pinus massoniana. --- The vegetation is composed of different types of subtropical evergreen and mixed broad-leaved forests (Yu et al. 2001). Most of the stands are secondary forests, evidenced by maximum tree ages of 180 years, by agricultural terraces in almost all plots and by the presence of charcoal in almost all soil profiles. Around the Gutianshan NRR extensive deforestation has occurred during the Great Leap Forward in the 1950s, as in most parts of Southeast China. However, due to prevailing steep slopes, the Gutianshan area was only marginally usable for agricultural activities, and thus an exceptionally intact forest cover has been preserved. --- The climate at Gutianshan NNR is warm and temperate with a short dry season in November and December and with warm summers (Fig. 2). The climatic conditions are characteristic for the subtropics with an annual average temperature of 15.1°C, January minimum temperatures of -6.8°C, July maximum temperatures of 38.1°C and an accumulated temperature sum (≥ 5°C) of 5221.5 degree days.

Published

Ecology monograph paper, doi: 10.1890/09-2172.1

Temporal Extent

Most of the data were collected in 2008, while some additional data were also collected in 2009.

Taxonomic Extent

The forest is representative for Chinese mixed broad-leaved forests (Wu 1980, Hu & Yu 2008, Legendre et al. 2009), with evergreen species dominating the forest in number of individuals (Yu et al. 2001) but with approximately similar proportions of deciduous species in terms of species number (Lou and Jin 2000). A total of 1426 seed plant species of 648 genera and of 149 families has been recorded as occurring naturally in the NNR. About 258 of the species are woody (Lou and Jin 2000).

Data Analysis

Data can be used as covariates in other data sets. Successional age (Age of the 5th largest tree) and diersity of tree species are the main explanatory variables (species number)

Data columns available in the raw data part of this dataset

date
year of samplingDate time information
Data group: Date time information
Keywords: date
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* Böhnke, M. also contributed to this column.
plot
CSP nameBEF research plot nameReasearch plots of the Biodiversity - Ecosystem functioning experiment (BEF-China). There are three main sites for research plots in the BEF Experiment: Comparative Study Plots (CSP) in the Gutianshan Nature Reserve, having a size of 30x30m^2, measured on the ground. Main Experiment plots have a size of 1 mu, which is about 25x25m^2 in horizontal projection. Pilot Study Plots have a size of 1x1 m^2.Research plots on the main experiment have a "p" in front of their IDs and then a 6 digit code: Plots in the main sites A and B are named according to their position in the original spreadsheet, in which they were designed. They consist of 6 digits: _1st digit_: Site (1:A, 2:B), _digit 2and3_: southwards row: as in spreadsheets the rows are named from the top to the bottom; _digit 4 and 5_: westward column: as in the original spreadsheet, but the letters are converted to numbers (A=01, B=02); _6th digit_: indicator, if the plot has been shifted a quarter mu. Example: "p205260": "p" means that this is a plot that is specified. "2" means, that we are at site B. Now the coordinates of the south - west corner: "0526". Since "e" is the fifth letter of the alphabet, this is Plot E26. The last digit "0" means that this plot was not moved by a quarter of a Mu, as some sites in Site A. The 6th digit can also indicate the subplot within the plot. "5", "6", "7", "8" indicate the northwest, northeast, southeast, and southwest quarter plot respectively.; Datagroup description: Reasearch plots of the Biodiversity - Ecosystem functioning experiment (BEF-China). There are three main sites for research plots in the BEF Experiment: Comparative Study Plots (CSP) in the Gutianshan Nature Reserve, having a size of 30x30m^2, measured on the ground. Main Experiment plots have a size of 1 mu, which is about 25x25m^2 in horizontal projection. Pilot Study Plots have a size of 1x1 m^2.Research plots on the main experiment have a "p" in front of their IDs and then a 6 digit code: Plots in the main sites A and B are named according to their position in the original spreadsheet, in which they were designed. They consist of 6 digits: _1st digit_: Site (1:A, 2:B), _digit 2and3_: southwards row: as in spreadsheets the rows are named from the top to the bottom; _digit 4 and 5_: westward column: as in the original spreadsheet, but the letters are converted to numbers (A=01, B=02); _6th digit_: indicator, if the plot has been shifted a quarter mu. Example: "p205260": "p" means that this is a plot that is specified. "2" means, that we are at site B. Now the coordinates of the south - west corner: "0526". Since "e" is the fifth letter of the alphabet, this is Plot E26. The last digit "0" means that this plot was not moved by a quarter of a Mu, as some sites in Site A. The 6th digit can also indicate the subplot within the plot. "5", "6", "7", "8" indicate the northwest, northeast, southeast, and southwest quarter plot respectively.; Datagroup description: Reasearch plots of the Biodiversity - Ecosystem functioning experiment (BEF-China). There are three main sites for research plots in the BEF Experiment: Comparative Study Plots (CSP) in the Gutianshan Nature Reserve, having a size of 30x30m^2, measured on the ground. Main Experiment plots have a size of 1 mu, which is about 25x25m^2 in horizontal projection. Pilot Study Plots have a size of 1x1 m^2. Research plots on the main experiment have a "p" in front of their IDs and then a 6 digit code: Plots in the main sites A and B are named according to their position in the original spreadsheet, in which they were designed. They consist of 6 digits: _1st digit_: Site (1:A, 2:B), _digit 2and3_: southwards row: as in spreadsheets the rows are named from the top to the bottom; _digit 4 and 5_: westward column: as in the original spreadsheet, but the letters are converted to numbers (A=01, B=02); _6th digit_: indicator, if the plot has been shifted a quarter mu. Example: "p205260": "p" means that this is a plot that is specified. "2" means, that we are at site B. Now the coordinates of the south - west corner: "0526". Since "e" is the fifth letter of the alphabet, this is Plot E26. The last digit "0" means that this plot was not moved by a quarter of a Mu, as some sites in Site A. The 6th digit can also indicate the subplot within the plot. "5", "6", "7", "8" indicate the northwest, northeast, southeast, and southwest quarter plot respectively.
Data group: BEF research plot name
Keywords: CSP, location
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* Böhnke, M. also contributed to this column.
Elevation
Elevation of the sampled plot, measured with geko201 GPS; Elevation;; ; GIS, Hypsometer, Interpolation from map (derived from datagroup); Instrumentation: GIS, Hypsometer, Interpolation from map (derived from datagroup)
Unit: m asl
Data group: Elevation
Keywords: elevation, co-variable
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aspect
aspect of the sampled plot. Measured with compass. Mind that there have been ambiguous values related to aspect by different researchers. Measured with compass.Aspect
Unit: degree
Data group: Aspect
Keywords: co-variable
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* Böhnke, M. also contributed to this column.
aspect_ValueComment
comment to measured values in the column aspectHelper
Data group: Helper
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Coordinates_N
latitude, measured with geko 201, mind that some of the coordinates were not helpful in finding the plot. It is not clear, if they all refer to the south-west corner of the plot.Latitude
Unit: WGS 84, Dezimalgrad: hddd.ddddd degree
Data group: Latitude
Keywords: latitude, location
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Coordinates_E
longitude, measured with geko 201, mind that some of the coordinates were not helpful in finding the plot. It is not clear, if they all refer to the south-west corner of the plot.Longitude
Unit: WGS 84, Dezimalgrad: hddd.ddddd degree
Data group: Longitude
Keywords: longitude, location
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Coordinates_ValueComment
comment to measured values in the columns coordinatesHelper
Data group: Helper
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Inclination
InclinationInclination
Unit: degree
Data group: Inclination
Keywords: inclination, co-variable
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successional_stage
successional age of the CSP, updated by Helge Bruelheide, Goddert v Oheimb, Karin NadrowskiSuccessional age of a forest plot
Data group: Successional age of a forest plot
Keywords: successional age, explanatory
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tree_age_max5
plot age as estimated by the age of the 5th largest treeSuccessional age of a forest plot
Data group: Successional age of a forest plot
Keywords: successional age, explanatory
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T1_height
height of highest tree layer. Height of vegetation layers was estimated as mean value from four different spots within the CSP, with simultaneous estimates by four different researchers.Vegetation layer height
Unit: meter
Data group: Vegetation layer height
Keywords: tree layer, height, co-variable
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T1_cover
cover of highest tree layer, cover of vegetation layers was estimated as a mean of four different spots within the CSP, with simultaneous estimates by four different researchers. Note that climbers were excluded from estimation.; Datagroup description: Estimated cover when looking from above. Cover can be estimated in percent, but there are also ordinal classifications of cover, such as Londo or Braun Blanquet.; Datagroup description: Estimated cover when looking from above. Cover can be estimated in percent, but there are also ordinal classifications of cover, such as Londo or Braun Blanquet. Cumulated vegetation cover ist calculated as: To combine T1 and T2 (both in %) you simply use the formula T_total = T1 + T2 * (100-T1)/100 For example: T1 = 50% and T2 = 50% give T_total = 75%.
Unit: percent
Data group: Vegetation layer cover
Keywords: tree layer, cover, co-variable
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T2_height
height of intermediate tree layer. Height of vegetation layers was estimated as mean value from four different spots within the CSP, with simultaneous estimates by four different researchers.Vegetation layer height
Unit: meter
Data group: Vegetation layer height
Keywords: tree layer, height, co-variable
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T2_cover
cover of intermediate tree layer, cover of vegetation layers was estimated as a mean of four different spots within the CSP, with simultaneous estimates by four different researchers. Note that climbers were excluded from estimation.; Datagroup description: Estimated cover when looking from above. Cover can be estimated in percent, but there are also ordinal classifications of cover, such as Londo or Braun Blanquet.; Datagroup description: Estimated cover when looking from above. Cover can be estimated in percent, but there are also ordinal classifications of cover, such as Londo or Braun Blanquet. Cumulated vegetation cover ist calculated as: To combine T1 and T2 (both in %) you simply use the formula T_total = T1 + T2 * (100-T1)/100 For example: T1 = 50% and T2 = 50% give T_total = 75%.
Unit: percent
Data group: Vegetation layer cover
Keywords: tree layer, cover, co-variable
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SL_height
height of shrub layerVegetation layer height
Unit: meter
Data group: Vegetation layer height
Keywords: height, shrub layer, co-variable
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SL_cover
cover of shrub layer; Datagroup description: Estimated cover when looking from above. Cover can be estimated in percent, but there are also ordinal classifications of cover, such as Londo or Braun Blanquet.; Datagroup description: Estimated cover when looking from above. Cover can be estimated in percent, but there are also ordinal classifications of cover, such as Londo or Braun Blanquet. Cumulated vegetation cover ist calculated as: To combine T1 and T2 (both in %) you simply use the formula T_total = T1 + T2 * (100-T1)/100 For example: T1 = 50% and T2 = 50% give T_total = 75%.
Unit: percent
Data group: Vegetation layer cover
Keywords: cover, shrub layer, co-variable
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HL_height
height of herb layer. The her layer was defined to be 1 m and was not measured.Vegetation layer height
Unit: meter
Data group: Vegetation layer height
Keywords: herb layer
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HL_cover
cover of herb layer. Cover of the herb layer was estimated by Sabine Both in the central plot of the CSP.; Datagroup description: Estimated cover when looking from above. Cover can be estimated in percent, but there are also ordinal classifications of cover, such as Londo or Braun Blanquet.; Datagroup description: Estimated cover when looking from above. Cover can be estimated in percent, but there are also ordinal classifications of cover, such as Londo or Braun Blanquet. Cumulated vegetation cover ist calculated as: To combine T1 and T2 (both in %) you simply use the formula T_total = T1 + T2 * (100-T1)/100 For example: T1 = 50% and T2 = 50% give T_total = 75%.
Unit: percent
Data group: Vegetation layer cover
Keywords: herb layer, cover, co-variable
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Open_soil
soil cover. Estimated in the central plot of the CSP.; Datagroup description: Estimated cover when looking from above. Cover can be estimated in percent, but there are also ordinal classifications of cover, such as Londo or Braun Blanquet.; Datagroup description: Estimated cover when looking from above. Cover can be estimated in percent, but there are also ordinal classifications of cover, such as Londo or Braun Blanquet. Cumulated vegetation cover ist calculated as: To combine T1 and T2 (both in %) you simply use the formula T_total = T1 + T2 * (100-T1)/100 For example: T1 = 50% and T2 = 50% give T_total = 75%.
Unit: percent
Data group: Vegetation layer cover
Keywords: soil, cover, co-variable
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fallen_wood
fallen wood cover estimation. Estimated in the central plot of the CSP.; Datagroup description: Estimated cover when looking from above. Cover can be estimated in percent, but there are also ordinal classifications of cover, such as Londo or Braun Blanquet.; Datagroup description: Estimated cover when looking from above. Cover can be estimated in percent, but there are also ordinal classifications of cover, such as Londo or Braun Blanquet. Cumulated vegetation cover ist calculated as: To combine T1 and T2 (both in %) you simply use the formula T_total = T1 + T2 * (100-T1)/100 For example: T1 = 50% and T2 = 50% give T_total = 75%.
Unit: percent
Data group: Vegetation layer cover
Keywords: cover, woody debris, co-variable
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* Böhnke, M. also contributed to this column.
N_individuals
Number of tree and shrub individualsOrganism count
Unit: count
Data group: Organism count
Keywords: density, explanatory
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N_adult_species
Number of tree and shrub species. Trees were counted when they exceeded 1m height. This data is aggregated from the raw data provided by Martin Böhnke.Biodiversity; Taxon diversity can be given as species richness, or other diversity indices. We also use rarefied species richness, shannon diversity index, and phylogenetic diversity indices.;; Source: Oksanen, J.; Kindt, R.; Legendre, P.; O'Hara, B.; Simpson, G. L.; Solymos, P.; Stevens, M. H. H. & Wagner, H. vegan: Community Ecology Package 2008, Ricotta, C. A semantic taxonomy for diversity measures Acta Biotheoretica, 2007, 55, 23-33 ., "Dray, S. an (derived from datagroup)
Unit: count
Data group: Taxonomic biodiversity
Keywords: tree layer, explanatory
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N_herb_species
Number of herb species, excluding woody species and climbers. Herbs were considered those plants that are less then 1 m high. This data is aggregated data from Sabine Both.Biodiversity; Taxon diversity can be given as species richness, or other diversity indices. We also use rarefied species richness, shannon diversity index, and phylogenetic diversity indices.;; Source: Oksanen, J.; Kindt, R.; Legendre, P.; O'Hara, B.; Simpson, G. L.; Solymos, P.; Stevens, M. H. H. & Wagner, H. vegan: Community Ecology Package 2008, Ricotta, C. A semantic taxonomy for diversity measures Acta Biotheoretica, 2007, 55, 23-33 ., "Dray, S. an (derived from datagroup)
Unit: count
Data group: Taxonomic biodiversity
Keywords: herb layer, biodiversity, explanatory
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rarefy_100
estimate of species number by randomly drawing 100 individuals (rarefaction) Rarefaction curves show the increase in species number with an increase of sampled individuals. R uses rarefy() from the package vegan to estimated species number for a given number of individuals. To compare different plots, the number of individuals should be smaller than the minimum number of individuals.; ; Oksanen, J.; Kindt, R.; Legendre, P.; O'Hara, B.; Simpson, G. L.; Solymos, P.; Stevens, M. H. H. & Wagner, H. vegan: Community Ecology Package 2008, Ricotta, C. A semantic taxonomy for diversity measures Acta Biotheoretica, 2007, 55, 23-33 ., "Dray, S. an (derived from datagroup); Source: Oksanen, J.; Kindt, R.; Legendre, P.; O'Hara, B.; Simpson, G. L.; Solymos, P.; Stevens, M. H. H. & Wagner, H. vegan: Community Ecology Package 2008, Ricotta, C. A semantic taxonomy for diversity measures Acta Biotheoretica, 2007, 55, 23-33 ., "Dray, S. an (derived from datagroup)
Unit: count
Data group: Taxonomic biodiversity
Keywords: biodiversity, rarefied diversity, explanatory
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Fdleaf
functional diversity of tree traits; The Functional Diversity (FD) was measured for each CSP by calculating Rao’s Quadratic Entropy Rao. The index takes the relative abundances of species and the pairwise functional differences between species into account. Based on leaf traits only.Functional biodiversity
Data group: Functional biodiversity
Keywords: functional biodiversity, explanatory
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FD_Qall_traits
Functional diversity all tree traitsFunctional biodiversity
Data group: Functional biodiversity
Keywords: functional biodiversity, explanatory
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t_cover
cumulative tree layer cover; Datagroup description: Vegetation layer cover; Datagroup description: Estimated cover when looking from above. Cover can be estimated in percent, but there are also ordinal classifications of cover, such as Londo or Braun Blanquet. Cumulated vegetation cover ist calculated as: To combine T1 and T2 (both in %) you simply use the formula T_total = T1 + T2 * (100-T1)/100 For example: T1 = 50% and T2 = 50% give T_total = 75%.
Data group: Vegetation layer cover
Keywords: cover, co-variable, trees
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sum_cover
cumulative tree and shrub layer cover; Datagroup description: Vegetation layer cover; Datagroup description: Estimated cover when looking from above. Cover can be estimated in percent, but there are also ordinal classifications of cover, such as Londo or Braun Blanquet. Cumulated vegetation cover ist calculated as: To combine T1 and T2 (both in %) you simply use the formula T_total = T1 + T2 * (100-T1)/100 For example: T1 = 50% and T2 = 50% give T_total = 75%.
Data group: Vegetation layer cover
Keywords: cover, shrubs, co-variable, trees
Alert Sample values are not displayed because this column hasn't been approved yet.