ISP lab exam study guide PDF

Title ISP lab exam study guide
Course Water And The Environment Lab
Institution Michigan State University
Pages 4
File Size 85 KB
File Type PDF
Total Downloads 72
Total Views 130

Summary

lab write up ...


Description

Lab #1: how much does temperature vary in large and small aquatic environments?  Specific heat of water- high specific heat, takes a relatively large amount of energy to raise the temperature of water  Specific heat- amount of heat required to change the temperature of 1 gram of the substance by 1 degC  Heat capacity- amount of heat required to change the temperature of the system by 1 degC  Heat capacity equation= specific heat x mass  Climate moderation- ocean/lakes locally moderate air temperatures compared to areas further inland of similar elevation and latitude  Weather generation- oceans/lakes can create weather by altering temperature and moisture conditions  Scientific method- a methodical, empirical process by which a scientist seeks knowledge about the natural world  Steps to the scientific method- ask question, develop hypothesis, conduct a study, analyze data, draw conclusion  Describing numbers in a meaningful way- be quantitative (use of numbers, amounts, quantities, measurements)  Components of a good graph- title, x and y axis labeled, legend, include degrees, grams, etc., show trendline,  Independent- x axis, explanatory manipulated variable  Dependent- y axis, response variable  Measurements of location- mean (average), the expected value, or norm of a data set  Measurement of variation/dispersion- standard deviation, the spread, the average amount the data points differ (vary or deviate) from the mean Lab #2: what determines the water clarity of lakes, rivers, and oceans?  Importance of water clarity- helps photosynthesis, healthy fisheries, tourist attractions  What affects clarity? Phytoplankton, zooplankton, dissolved and suspended materials (all block sunlight)  What happens to light in water? It is transmitted, scattered, and absorbed  Attenuate- to reduce in intensity or weaken, attenuated light= lower intensity  Light attenuation coefficient (k)- a measure of how effectively light passes through water  High k (high light attenuation)- turbid water, rapid decrease in light with depth  Low k (low light attenuation)- clear water, slow decrease in light with depth  Euphotic zone- the depth at which light intensity is 1% of the intensity at the surface  Continuous variables- can take on any value between its minimum and maximum value, i.e. line graphs, scatter plots  Categorical variables- variable that can take on one of a limited, and usually fixed, number of possible values, thus assigning each individual to a particular group or “category,” i.e. bar graph

   

Trendline- depicts the average trend R^2- the ability of your independent variable (x) to predict (explain) your dependent variable (y) is quantified with this Line graphs- frequently show a trend in a continuous dependent variable through time Scatter plots- show relationships between two continuous variables

Lab #3: where does the phosphorus go?  Eutrophication- process where water bodies receive excess nutrients that stimulate excessive algae growth  Forms of phosphorus- phosphate ion, algae, daphnia  In a closed system, elements like phosphorus are not created or destroyed, they are recycled and reused through chemical transformations  In the aquatic food chain, phosphorus is transformed by aquatic plants and herbivores  Dissolved phosphorus- dissolved in water, inorganic, only form algae can use, not a form animals can use  Suspended phosphorus- contained within organisms, organic, cell structures and biological molecules  Transformed through uptake, excretion, and recycling  Elements of a good experiment - replication to increase accuracy and precision, yields more representative results and eliminates biases  How is it too much of a good thing? Can result in toxic and harmful algae blooms  Error bars- illustrate extent of the variation (error), adds +-1 standard deviation to the graph  Observational studies- more subjective, biased, can get more variation in results  Experiments- quantitative, make results more reliable and trustworthy Lab #4: how does human activity in watersheds affect the quality of lakes and rivers?  The water chemistry of lakes and rivers is largely determined by the characteristics of the watershed from which the water originates (i.e. the surrounding terrestrial landscape  Water chemistry in turn affects water quality and lake productivity, as well as sensitivity to acidification  Watershed- area of land that drains into a specific water body  Human activity on land affecting water quality - agriculture and urban areas affect quality of watershed, increased run off, point source and nonpoint source categories of water pollution  How do we quantify water quality? Total phosphorus (nutrients), chlorophyll (greenness), secchi depth transparency (water clarity)  Sample size- want large and representative samples, this increases the strength of the results and allow them to be generalized Lab #5: are the great lakes being influenced by the global greenhouse effect?

         

Weather- day to day conditions, specific weather events (sunny, rainy, snowy) Climate- long term conditions, trends in weather events (temperate, tropical, etc) Global climate change- any significant change in global “average” climate patterns lasting an extended period of time Potential effects of climate change- rise in global average temperature, more frequent and extreme weather ocean acidification, rising sea levels Human role- burning fossil fuels, loss of carbon “sinks,” deforestation reduces the ability of photosynthesis to sequester carbon dioxide Why do you need a lot of data? Climate conditions can naturally vary dramatically from year to year, need lots to distinguish changes (trends) from this huge amount of background, year to year variation Significance F, p-value- the probability the null hypothesis is true given the observed data, probability is quantitative and objective Most climate models make predictions about changes in average temperature for the entire earth, or average temperature and precipitation for large regions of the planet The lower the significance value, the more sure we can be our results weren’t due to chance Predicted long term consequences in the great lakes region- increase in temperatures

Lab #6: how are flow, turbidity, and precipitation related for the red cedar river?  Discharge- flow, volume of water passing a point in the river in a period of time (i.e. a rate)  Importance of measuring them= Precipitation and discharge- predicting where, when and how often floods will occur, regulating flows for power generation, water supply  Discharge= area x velocity  Velocity - distance/time  Turbidity- concentration of particles that are suspended in water, grams per liter, grams per liter  Load- mass of particles passing a point in the river in a period of time, grams per second  Turbidity= mass of used filter-mass of clean filter/water volume filtered  Murkiness is caused by particles, probably fine soil particles (clay) washed in from the surrounding landscape  Turbidity measurements can tell us something about a river’s watershed, the quality of a river as a habitat for various fish species, and the amount of sediment being transported by a river  A high particle load means that a lot of particles (suspended soil particles in most cases) are being transported downstream by the river  Being able to accurately predict the flow of rivers is crucial to what? To prevent loss of life and minimize social disruption during floods  Particle load- mass of particles passing a point in the river in a unit period of

  

time, using estimates of turbidity and discharge, high particle load means that a lot of particles are being transported downstream by river Turbulence- strong mixing of air or water Correlation coefficient r- measures the strength and direction of a linear relationship between two variables Measurement error- difference between a measured value of quantity and its true value...


Similar Free PDFs