This data set is the survey data of vegetation communities in desert grassland and typical grassland in Inner Mongolia Autonomous Region and Ningxia Hui Autonomous Region. This experiment provides basic data for the study of the causes, processes and mechanisms of natural grassland degradation.
Attribute information includes: species richness, quadrat coverage, aboveground biomass, litter biomass and degradation gradient (0: potential degradation; 1: mild degradation; 2: moderate degradation; 3: severe degradation).
Species richness: Shannon Weiner index
H’=- Σ PilnPi
Where pi = Ni / N, Ni is the number of individuals of species I, and N is the sum of the number of individuals of all species in the community.
Quadrat coverage: the percentage of the area covered by the vertical projection of the aboveground part of the plant in the investigated area.
Aboveground biomass: take the aboveground part of the plant sample and place it in a 65 ℃ constant temperature oven for 24 hours. After taking it out, weigh it with a micrometer electronic balance.
Litter biomass: collect the litter in each quadrat and weigh it with a micrometer balance.
Degradation gradient: different degrees of grassland degradation.
The sampling points of each grassland type are spaced at an interval of about 50 km. The sampling points are randomly selected at open terrain, and the geographic location information of each sampling point is recorded by GPS. Each sample point is set with one 10m × For 10 m large quadrat, five 1 m large quadrats shall be set at each corner and center of the large quadrat × 1 m small quadrat (only 3 small quadrats are set along the diagonal at a few sample points).
Indoor experiment, independent production.
Manually measure the data of plant height, coverage and number of plants, and use a steel ruler with a minimum scale of 1 mm, with an error of less than 1 mm.
| # | number | name | type |
| 1 | 天然草地退化原因、过程与机制 | National key R & D plan |
This work is licensed under a
CC BY 4.0.
CSTR:11738.11.ncdc.Dgrass.db2095.2022
10.12072/ncdc.Dgrass.db2095.2022
