Introduction A series of sampling techniques were used in the field in order to estimate the amount of biomass that an area contained. The experiments were conducted at the Bisley Park on a Saturday. Two different methods were employed, namely quadrat-based methods and the disc-pasture metre method. The results gained from these samples were used to create an estimate of the biomass in the area. Materials and Methods There are two techniques used in the quadrat-based methods, namely the Comparative Yield Method and the Dry Weight Rank Method for Botanical Composition. The first experiment used was that of the Comparative Yield Method. This method requires two sets of data to be collected in order to get relevant inferences about the area. The grass biomasses are classed according to a three-class system. The classes are based on the biomass of the grasses in a given quadrat. The quadrat with a high biomass is a rank 3, whereas a quadrat with a low biomass has a rank of 1. In between these two is obviously a rank 2. If a quadrat has an intermittent value, then a rank of 1.5 or 2.5 can be given. The first set of data collected is to calibrate the classes, so three samples of each rank are cut and dried to be weighed later. This is done to get an idea of how much biomass is present per rank. The second set of data collected is done by taking a random transect of about 25 metres and noting the ranks at each meter interval. These points are recorded used to make inferences on the available biomass in the area. The second technique for the quadrat-based method is that of the Dry Weight Rank Method for Botanical Composition. This also involves walking a random 25 meter transect. The difference, instead, is that the q... ... middle of paper ... ...r. It could be due to different grass types that were being used. Our equation is specific to this area and can't be applied to another area, and vice versa. The other equation is specific to that area and vegetation type. Conclusion All these experiments have different ways of obtaining a biomass value for any specific area. Thus it is fair that they have varying end values. They also all have certain bias' that affect the end value. I think that the Comparative Yield Method is the most precise due to the cuttings that are taken before in order to make a representative curve. The Disc-Pasture method is, however, a much easier and less time consuming practise, but has a certain set backs as far as the end result is concerned. Our results showed that there is a possibility for erratic values to occur. It could be put to experimental error or poor field-work.
... got very different results, however they had carried out the experiment in slightly different ways, making it difficult to compare results.
(Kumar et al., 2008a). Globally, 1.3 1010 metric tons of wood is produced by terrestrial
Once the gray wolf population had declined in the National Park, many ecological impacts were observed. Without a sustainable wolf population in the park, the elk population began to take over and increase in size. Due to this increase in elk, many of the deciduous woody species began to become overgrazed. With the e...
How does the vegetation surface type affect the amount of runoff? Speculate why this happens.
In this experiment, there were several objectives. First, this lab was designed to determine the difference, if any, between the densities of Coke and Diet Coke. It was designed to evaluate the accuracy and precision of several lab equipment measurements. This lab was also designed to be an introduction to the LabQuest Data and the Logger Pro data analysis database. Random, systematic, and gross errors are errors made during experiments that can have significant effects to the results. Random errors do not really have a specific cause, but still causes a few of the measurements to either be a little high or a little low. Systematic errors occur when there are limitations or mistakes on lab equipment or lab procedures. These kinds of errors cause measurements to be either be always high or always low. The last kind of error is gross errors. Gross errors occur when machines or equipment fail completely. However, gross errors usually occur due to a personal mistake. For this experiment, the number of significant figures is very important and depends on the equipment being used. When using the volumetric pipette and burette, the measurements are rounded to the hundredth place while in a graduated cylinder, it is rounded to the tenth place.
Comparing the Growth of Pea Plants Grown in the Light and in the Dark Aim: To compare the vertical growth and weight gain of pea plants grown in the light and in the dark. Background Knowledge: Photosynthesis forms the basis for this experiment. This is the process by which a plant makes food for itself from the raw materials around it. The energy needed for photosynthesis comes from sunlight, which is the variable for this experiment.
Two members of the group were instructed to visit the laboratory each day of the experiment to water and measure the plants (Handout 1). The measurements that were preformed were to be precise and accurate by the group by organizing a standardized way to measure the plants. The plants were measured from the level of the soil, which was flat throughout all the cups, to the tip of the apical meristems. The leaves were not considered. The watering of the plants took place nearly everyday, except for the times the lab was closed. Respective of cup label, the appropriate drop of solution was added to the plant, at the very tip of the apical meristems.
The question that was proposed for investigation was: Can the theoretical, actual, and percent yields be determined accurately (Lab Guide pg. 83)?
Janick. J. (2011). Center for New Crops & Plant Products - Department of Horticulture and
We used wheatgrass were 40 wheatgrass seeds, two empty pots, soil, and water. We first added soil for both pots and 20 wheatgrass seeds in each pot. My partner and I decided that we label pot one experiment which is “sugar and water” and pot two control which is “water” only. The experiment was for almost four weeks we had to make sure both get the same room temperature and water, so we can see the results after this amount of time. Both pots had same room temperature so both can have the same amount of sunlight also, the same amount of water which is a glass of water from the sink once a week. In the experiment pot we added a glass of water with one teaspoon of sugar and the control pot glass of water. Every week we used to see both pots grow almost the same. At the end of the experiment, my partner and I measured the length for both plants and we recorded the average for each plant, so we can know the rate of growth
Perry, D. A. (1998). The Scientific Basis of Forestry, Annual Review of Ecology and System Thematic 29:435-466, Retrieved July 9, 2005 from: http://www.panda.org/about_wwf/what_we_do/policy/policy_and_events/index.cfm
...dity variation, largely because RH is not a variable expressed in the Arrhenius equation. It is likely that the Copan researchers, like the experimental parameters of Michels and colleagues (1983) might consider the RH of tropical soils to be always 100 percent. For contexts deeper than 50 cm, this may be a reasonable assumption. However, it should be borne in mind that the majority of the variability in hydration rates occurs between RH values of 90 and 100 percent, and a 1 percent change in RH translates to approximately a 3 percent change in hydration rate (Tremaine 1989). So if blades from Copan were recovered from contexts with 90 percent RH, their OHD dates would be in error by approximately 30 percent, excluding all other sources of error.
There is also the potential of human error within this experiment for example finding the meniscus is important to get an accurate amount using the graduated pipettes and burettes. There is a possibility that at one point in the experiment a chemical was measured inaccurately affecting the results. To resolve this, the experiment should have been repeated three times.
"Home | American Society of Agronomy." Home | American Society of Agronomy. N.p., n.d. Web. 25 Mar. 2014. .
The diagram below shows that grass doesn’t have a steady growth curve throughout the year, there’s a peak in May with surplus grass. The grazing method chosen helps to make the most efficient use of grass at all times of the grazing cycle.