Steppe Plant Ecology
Research Objectives and Activities
Our research purpose is focused on impact identification of livestock grazing and climate change on ecological dynamics of semi-arid boreal steppe and riparian plant community of Northern Mongolia, but should be applicable to many other areas of East and Central Asia. The research site is located in Lake Hovsgol’s eastern shore six stream valleys that are different level of livestock grazing intensity. Our objectives include:
- Monitor plant communities (species diversity, green biomass, litter accumulation, canopy cover) in the six study valleys. Also monitor soil physical and chemical characteristics that more relate with plant community ecological functions.
- Define differences among watersheds in the context of spatial differences in impacts of livestock grazing on plant communities and soil conditions.
- Perform graphical and statistical analysis of all data and relate to other study results: meteorology, terrestrial insects, small mammals, soil types, and nomad’s land use and livestock grazing practices.
- Our research activities started in 2002 year with the establishment of cross-valley transects in each of the six study valleys with different levels of livestock grazing. We collect samples from the permanent monitoring transects, using a Standard Operating Procedure.
- We have now begun a series of experiments to answer questions resulting from the results of our monitoring studies.
- We cooperate with Academy of Natural Science of Philadelphia, Colorado State University, University of Pennsylvania, USGS Soil Crust Lab at Moab, Biology Faculty of National University of Mongolia (NUM), University of Ulaanbaatar, Geoecology, Geography and Botany Institute of Mongolian Academy of Sciences (MAS).
Study Design and Methods
Monitoring studies continue in the six study valleys (Borsog, Dalbay, Sevsuul, Noyon, Shagnuul and Turag) that have different levels of livestock use. We monitor plant species’ composition, canopy cover, above and belowground biomass, and soil physical and chemical properties. In each valley we established fixed transects across valleys with a 100 meter width. The established transects were divided into four strata in the steppe zone: north facing slope-lower steppe, south facing slope-upper steppe, -lower steppe, and in riparian zone south facing-lower steppe (Figure 1).
Figure 1. Transect and Sampling Design 2.
Summary of Plant Community Monitoring Methods
Plant species diversity, canopy cover and biomass are commonly measured vegetation attributes that refer to the plant species number and weight of plant material within a given area. We collect plant community data from plots (size 0.25m2); using a sample replication number based on the results of a power analyses (= 7 randomly chosen plots in each stratum). Our study is based on a randomized block design. Each quadrate represents a sample unit, and values describing biomass (g/0.25m2) and species number (number/0.25m2) in each quadrate form the data set that is used for statistical analyses.
At first we record all plant species by individual number in each of the plots. After spp. recording, all plants are harvested and placed in paper bags. Plants are separated by species and necromass is collected separately before packaging. After the sampling the aboveground plant biomass, soil cores are collected for estimating belowground plant biomass. Samples of biomass are stored in a dry place during the field research, and later are dried in a laboratory drier (80°C) for 24 hours. We estimate the absolute dry weight of each species using an electronic balance. Figure 1 shows the sampling methods.
Power Analysis for Estimating of Sample Number
Power analysis is used to determine the least number of samples needed to detect statistical differences (p<0.05) among the valleys, based on preliminary pilot study results. We used JMP-4.0 software for the power analyses. Based on this estimate, we concluded that seven plots within each stratum would provide a sufficient estimate of biomass differences. For belowground plant biomass the least plot number is 134 in each valley, or 34 plots in each stratum are required, but this number is impossible because sampling is quite time consuming.
Correlation and Regression
We perform correlation and regression analyses between main parameters of plant community and livestock number and soil condition. The parameters of plant community are the dependent variable in all analyses except relationship between grasshopper number and plant community.
|Independent Variable||Dependent Variable|
|Soil Moisture||Plant Species Composition, Biomass and Canopy Cover|
|Soil Temperature||Plant Species Composition, Biomass and Canopy Cover|
|Soil Total Nitrogen||Plant Species Composition, Biomass and Canopy Cover|
|Soil Total Carbon||Plant Species Composition, Biomass and Canopy Cover|
|Plant Species Number||Plant Species Composition, Biomass and Canopy Cover|
|Livestock Number||Plant Species Composition, Biomass and Canopy Cover|
|Grasshopper Number||Plant Species Composition, Biomass and Canopy Cover|
Nested, or hierarchical designs are very common in environmental effects monitoring studies. The Nested ANOVA is useful when we are constrained from combining all the levels of one factor with all of the levels of a second factor. These designs are most useful when we have what is called a random effects situation. The analysis is more suitable for the study design we chose. In the nested ANOVA, the first level are valleys, which have different levels of livestock use. Second are zones (steppe and Riparian), slopes (north and south facing), strata (upper and lower) and plots (7 plots chosen randomly). The nested design allows us to test two things: (1) difference between the study valleys and (2) the variability of the zones, slopes, strata within valleys. If we find a significant variability among the levels within valleys, then a significant difference between valleys would suggest that there is a livestock impact on plant biomass. The data analyses are made using JMP-4.0, Sigma Plot 2000, and Systat – 9 softwares.
|Valley||Valleys have different livestock numbers|
|Zone||Divide the valleys into forest, steppe and riparian zone|
|Slope||North facing and South Facing Slopes are different for soil moisture, temperature, and solar radiation|
|Stratum||Divide the slopes into strata by soil moisture content. Example; lower steppe, upper steppe|
|Plot||Randomly choose 7 plots in each stratum; the plot number is based on results of power analysis|
We use multivariate analyses such as MDS and cluster analysis.
Lake Hövsgöl and its watershed occupy a north south aligned tectonic basin at the southern end of the Baikal Rift System in northern Mongolia. The region forms the southern boundaries of the Siberian taiga (boreal) forest and of continuous permafrost. In addition, representing the transition zone from taiga forest to steppe, east/west it forms a biogeographic boundary between Central and East Asia.
This ecotone of transitions is undergoing climate change, that is causing a gradual warming and thaw of permafrost and simultaneously is increasing estimated evapotranspiration rates (estimated from SoilWat Model), leading to a substantial yearly loss of soil moisture.
This region has had livestock herding for a long time period, but beginning in the 1980s, the number of livestock has increased, particularly of cashmere goats. This study is focused on the combined impacts of climate change and livestock grazing on steppe plant communities and soil. Intense livestock grazing is leading to a drying condition in the valleys as a result of loss of soil moisture, an increase in soil temperature, and soil compaction (increasing of soil bulk density) and an increasing distribution of xerophyte plants in the heavily grazed areas. The high abundance of xerophyte plants on the heavy grazed valleys is also related to a reduction of the necromass cover. Non-palatable plants are becoming widely distributed in the heavily grazed valleys relative to non or little grazed valleys. The increase of the non-palatable plants appears to be a response to the high livestock grazing pressure. Heavy livestock grazing appears to cause the loss of moss and necromass cover, main insulation blankets for permafrost, in the riparian zone and north facing lower steppe, where are high permafrost distribution. The decreasing of the main insulators due to heavy grazing appears to also be associated with permafrost degradation.
We use SoilWat2.2 model to compare the valleys, which are different livestock grazing level by soil moisture, temperature, transpiration, evaporation , potential and actual evapotranspiration. The U.S. Short Grass Steppe LTER uses this model. We are trying to compare our outputs from the model with the Short Grass Steppe LTER outputs.