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Biodiversity is the number of various species of organisms in a given place. Biodiversity ensures that every organism within an ecosystem has a niche in which it can thrive. Generally, the more biodiversity an area has, the more sustainable it is and the more it is able to recover from disaster. With more variation and numbers, an illness for example could infect one species but it would not severely hurt the ecosystem it is in. Lawns have become pervasive with their growing significance in human experiences. Biodiversity is also a feature that accompanies the presence of lawns because various species of flora and fauna exist in these miniature habitats. Plant diversity on lawns is impacted significantly by human disturbances like mowing and use of herbicides which are characteristic of common maintenance practices. These effects have been studied extensively in urban areas but not so much in small towns like Amherst, Massachusetts. In this study, we will investigate the role of these human disturbances here at the University of Massachusetts Amherst and around. We will start by obtaining relevant data about maintenance practices and carrying out sampling experiments in 6 selected lawns. Analysis and comparison of the obtained data will reveal if, in fact, lawn maintenance practices negatively affect plant species diversity. This will provide a framework and resources for future decision-making in terms of biodiversity conservation.

Biodiversity is the number of various species of organisms in a given place. Biodiversity ensures that every organism within an ecosystem has a niche in which it can thrive. Generally, the more biodiversity an area has, the more sustainable it is and the more it is able to recover from disaster. With more variation and numbers, an illness for example could infect one species but it would not severely hurt the ecosystem it is in. Lawns have become pervasive with their growing significance in human experiences. Biodiversity is also a feature that accompanies the presence of lawns because various species of flora and fauna exist in these miniature habitats. Plant diversity on lawns is impacted significantly by human disturbances like mowing and use of herbicides which are characteristic of common maintenance practices. These effects have been studied extensively in urban areas but not so much in small towns like Amherst, Massachusetts. In this study, we will investigate the role of these human disturbances here at the University of Massachusetts Amherst and around. We will start by obtaining relevant data about maintenance practices and carrying out sampling experiments in 6 selected lawns. Analysis and comparison of the obtained data will reveal if, in fact, lawn maintenance practices negatively affect plant species diversity. This will provide a framework and resources for future decision-making in terms of biodiversity conservation.

Although most animals in temperate forests survive the winter months by either migrating or hibernating this species does neither, like its relative the Mephitis mephitis (skunk). They remain inactive during the winter months and survive by using the fat that is stored within their bodies, they leave their dens during the summer and only leave in the winter when temperatures are above freezing. The Mephitis scandere has brown pelage that covers its body, the perfect color to help it camouflage in its environment. They have a thin white stripe on their forehead that goes down to its snout and the thin white line also runs along its dorsum.

Sieve Cells are called this because the tubes act as one continuous cell. Sieve tubes are a collection of sieve tube elements that tend to look empty, have very prominent joints, and are very long. They don’t have a nucleus (like xylem, but are living cells), don’t have a cytoskeleton, have very few organelles  (no Golgi, plastids or lignin; some ER, few mitochondria, have plasma membrane). There are companion cells next to sieve cell-ordinary cell that feeds sieve cell/keeps it alive. A ‘Sieve plate’ is the wall in between each cell. Sieve plates are almost like slime/goo and are very prominent-these are phloem clots (like a blood clot in a plant) stops the flow of nutrients. This is how plants keep nutrients from being lost if it is damaged/cut. They contains special clotting proteins and polysaccharides.

Covariates are continuous and natural, a block is discrete. Blocks need one of each treatment and must be decided before experiment is started. Blocking affects how replicates are assigned to treatments. Thus, once a decision has been made, it cannot later be decided to remove ‘block’ as a term in the analysis (some people would today if it does not explain significant variation). The decision to measure covariates can be made at any point. Many potential covariates can be measured. If the analysis shows that they do not explain significant variation in your response, they can be dropped from the model.

 A split-plot design is defined as one factor assigned at the level of main plots (water or none), which are then subdivided into subplots that are the level of replication for a second factor (corn type). A nested design is defined as a research design in which levels of one factor are hierarchically subsumed under levels of another factor. As a result, assessing the complete combination of A and B levels is not possible. Like a split plot design, replication differs for different factors within the same experiment. However, in a nested design each level of one factor is NOT crossed with all levels of the other factor. An example we could use to understand this is to compare differences between 6 cities, 3 on the west and 3 on the east. We can’t analyze the interaction between city and coast because Boston is only on the east coast, Seattle is only on the west.

          The Socioecological Model is a method of categorizing female social relationships through agonism. This is further examined along three social dimensions. The first dimension seeks to establish whether or not a dominance hierarchy is present in the given group being analyzed. A group which lacks a strict hierarchy is defined as egalitarian, in which there are undetectable or poorly defined dominance relationships, or in which the dominance hierarchy is not clear or nonlinear. In these groups, food is often dispersed in a way such that patches cannot be defended, resulting in scramble competition in which the first female to arrive at a food resource may get a larger share of the food simply because she got there first. This means there is nothing to gain from contesting the resource, and thus typically produces weak social relationships in females, with no need for post conflict resolution like grooming. In contrast, a group which exhibits a strict hierarchy is known as despotic, in which there are clearly established, formalized dominance relationships that are usually linear. When there is competition over essential resources, aggressive interactions maintain dominance hierarchy and contest competition is high. High rank can provide priority of access to resources, and potentially higher reproductive success, and may may also result in alliances or affiliative behaviors like grooming. The second dimension aims, once a hierarchy has been observed, to further classify the type of hierarchy present. There may be a nepotistic hierarchy, in which female relatives rank close together due to coalitions and often don’t disperse, or individualistic hierarchies, in which the rank of female relatives are independent of each other, and females do disperse. The third and final dimension seeks to assign the degree of tolerance within the group structure, and generally assumes that as tolerance increases, the severity of aggression decreases while threats toward dominant individuals increases.

A Type I Error is a false positive where a true null hypothesis is rejected, and a Type II Error is a false negative where a false null hypothesis is accepted. In this case, a Type II Error would conclude this pesticide does not increase cancer rates when it does, a Type I Error would conclude this pesticide does increase cancer rates when it doesn’t. We would want to minimize our risk of Type II Error because this sort of error could mislead people into thinking the pesticide is safe when it is not, and the continued use of it would increase cancer rates. A Type I Error is less important because in this case, cancer rates would not rise since the pesticide would be deemed unsafe. It may cause farmers to lose millions of dollars, but that is less expensive than the lives of people and the compounded medical costs of cancer of the country.

The randomization procedure to choose the territories may give us more large territories than small or vice versa. It could also generate coordinates that are close to one territory, both decreasing the randomization. A better randomization procedure would be to assign a number to each possible territory, (1-10 for the large territories, 11-20 for the small territories, for example) that could be used and use a random number generator, then generate 5 numbers for larger territories and 5 for smaller ones. This way, there is an even amount of territory sizes and each territory experimented on is randomized. 

The factors that determine power are Replicants, Experimental noise (random variation) Experimental design (the various aspects, but a simpler design has more power), P-Value cutoff (usually P = 0.05), and How strong the treatment effect is (how big the difference is between treatment and control mean; stronger effect = more power). The power of our experiment is 84.2% (842 successful/1000 total). The probability that we get valid results is 0.842. The probability that we don’t get these results is 1 minus the power of design; 1-0.842=0.158, a 15.8% chance that water temperature doesn’t affect mating behavior. This would be a Type II error because a Type II error is the probability of falsely concluding there is no effect of treatments, when there really is a treatment effect. The probability that we would incorrectly conclude that water treatment did have an effect would be 0.05, since this is the cutoff for a significant alpha value. Since we would be rejecting a true null hypothesis, this would be a Type I error.