Simulation of Disturbances and Recovery in Shortgrass Steppe Plant Communities

Author(s):  
Debra P. C. Peters ◽  
William K. Lauenroth

Simulation modeling is a complementary tool to field observation and experimentation in understanding ecological systems (Lauenroth et a l., 1998). The overall objective of our plant community modeling is to allow us to evaluate the importance of gap dynamics concepts of succession for understanding shortgrass plant community recovery after disturbances. A gap dynamics approach focuses on individual plants, and the interactions between disturbance characteristics and plant life history traits in explaining successional patterns (Watt, 1947). Simulation models have been used extensively to evaluate the importance of gap dynamics processes to short- and long-term vegetation dynamics in temperate and tropical forests (e.g., Botkin et al., 1972; Shugart, 1984). We developed a gap dynamics model for shortgrass steppe plant communities (STEPPE [Coffin and Lauenroth, 1990]) based upon the conceptual and modeling framework provided by forest models, modifying it to represent Great Plains grasslands (Coffin and Lauenroth, 1996; Coffin and Urban, 1993). We used STEPPE in several capacities: (1) to synthesize and integrate existing knowledge to improve our understanding of recovery processes after disturbance, (2) to identify key processes limiting recovery, and (3) to predict long-term recovery dynamics for different climate and disturbance characteristics—in particular, soil texture and disturbance size. Our approach to modeling shortgrass community dynamics was to incorporate only the most important processes needed to address specific research questions. We added processes through time either because the model did not sufficiently represent ecosystem dynamics or because we posed more complicated research questions. STEPPE simulates the recruitment, growth, and mortality of individual plants on a small plot through time at an annual time step (Fig. 7.1) (Coffin and Lauenroth, 1990). Recruitment and mortality both have stochastic elements. Growth is deterministic and is based upon competition for resources among plants. A key difference between STEPPE and the forest models from which it was derived is that belowground resources are the most frequently limiting resources in semiarid grasslands compared with aboveground resources (light) in forests (Lauenroth and Coffin, 1992).

Oikos ◽  
2002 ◽  
Vol 98 (1) ◽  
pp. 53-64 ◽  
Author(s):  
S. Rebollo ◽  
D. G. Milchunas ◽  
I. Noy-Meir ◽  
P. L. Chapman

Author(s):  
Daniel G. Milchunas ◽  
William K. Lauenroth

Although livestock are the most obvious consumers on the shortgrass steppe, they are certainly not the only consumers. However, livestock may influence the other consumers in a number of different ways. They may directly compete for food resources with other aboveground herbivores. There is behavioral interference between livestock and some species of wildlife (Roberts and Becker, 1982), but not others (Austin and Urness, 1986). The removal of biomass by livestock alters canopy structure (physiognomy) and influences microclimate. Bird, small-mammal, and insect species can be variously sensitive to these structural alterations (Brown, 1973; Cody, 1985; MacArthur, 1965; Morris, 1973; Rosenzweig et al., 1975; Wiens, 1969). There are both short- and long-term effects of grazing on plant community species composition, primary production, and plant tissue quality. Belowground consumers can also be affected by the effects of grazing on soil water infiltration, nutrient cycling, carbon allocation patterns of plants, litter accumulation, and soil temperature. The overall effects of livestock on a particular component of the native fauna can be negative or can be positive through facilitative relationships (Gordon, 1988). In this chapter we assess the effects of cattle grazing on other above- and belowground consumers, on the diversity and relative sensitivity of these groups of organisms, and on their trophic structure. We first present some brief background information on plant communities of the shortgrass steppe and on the long-term grazing treatments in which many of the studies reported herein were conducted. Details on the plant communities are presented by Lauenroth in chapter 5 (this volume), grazing effects on plant communities by Milchunas et al. in chapter 16 (this volume); and grazing effects on nutrient distributions and cycling by Burke et al. in chapter 13 (this volume). The physiognomy of the shortgrass steppe is indicated in its name. The dominant grasses (Bouteloua gracilis and Buchloë dactyloides), forb (Sphaeralcea coccinea), and carex (Carex eleocharis) have the majority of their leaf biomass within 10 cm of the ground surface. A number of less abundant midheight grasses and dwarf shrubs are sparsely interspersed among the short vegetation, but usually much of their biomass is within 25 cm of the g round. Basal cover of vegetation typically totals 25% to 35%, and is greater in long-term grazed than in ungrazed grassland. Bare ground (more frequent on grazed sites) and litter-covered ground (more frequent on ungrazed sites) comprise the remainder of the soil surface (Milchunas et al., 1989).


2012 ◽  
Vol 2012 ◽  
pp. 1-9 ◽  
Author(s):  
Randall W. Myster

How best to define and quantify plant communities was investigated using long-term plot data sampled from a recovering pasture in Puerto Rico and abandoned sugarcane and banana plantations in Ecuador. Significant positive associations between pairs of old field species were first computed and then clustered together into larger and larger species groups. I found that (1) no pasture or plantation had more than 5% of the possible significant positive associations, (2) clustering metrics showed groups of species participating in similar clusters among the five pasture/plantations over a gradient of decreasing association strength, and (3) there was evidence for repeatable communities—especially after banana cultivation—suggesting that past crops not only persist after abandonment but also form significant associations with invading plants. I then showed how the clustering hierarchy could be used to decide if any two pasture/plantation plots were in the same community, that is, to define old field communities. Finally, I suggested a similar procedure could be used for any plant community where the mechanisms and tolerances of species form the “cohesion” that produces clustering, making plant communities different than random assemblages of species.


2014 ◽  
Vol 4 (3) ◽  
pp. 178-186 ◽  
Author(s):  
M. G. Merkusheva ◽  
O. A. Anenkhonov ◽  
N. K. Badmaeva ◽  
S. B. Sosorova

2009 ◽  
Vol 73 (12) ◽  
pp. 1136-1143 ◽  
Author(s):  
M.R. Scheintaub ◽  
J.D. Derner ◽  
E.F. Kelly ◽  
A.K. Knapp

Author(s):  
Ning Li ◽  
Yang Liu

As a fundamental part of the urban function, urban green space faced a long-term maintenance requirement. The maintenance of urban green space (i.e., trimming, irrigation, fertilization, pesticide, and plant waste removal) can have environmental impacts, such as energy consumption and greenhouse gas (GHG) emission. This chapter focuses on the adjustment of the plant communities’ combinations in urban green space to reduce the environmental impacts in long-term maintenance. The plant communities in urban green spaces are a combination of four plant layers: woodland, shrubs, herbicides, and grassland. In this chapter, we will start to investigate the environmental impacts in the maintenance of urban green space. Then we introduced the quantitative method life cycle assessment (LCA), to quantify the environmental impacts of the maintenance tasks. We analyzed the maintenance environmental impact (MEI) index of 95 plant community samples (20 m × 20 m) in Zhengzhou (China) through LCA and sorted out the changing curves of the MEI index during the change of the combined amount in each plant layers. Finally, we sorted out the MEI strength of the plant layers and summarized the low MEI plant community model. The low MEI model can save energy consumption and GHG emissions of the maintenance tasks, to contribute to the sustainable development of the urban green space.


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