Explore the River:

Graphing Data

Changes along the River

Many of the Hudson River's characteristics change along its course. For example, tributaries (streams or smaller rivers that flow into the main portion of the river) increase the volume of the upper (northern) portion of the river, while the lower portion is also an estuary, where freshwater mixes with saltwater from the Atlantic Ocean. Characteristics that change include the river's depth, width, rate of flow, biological communities, and type of bottom (rocky versus soft).

Because these characteristics affect biotic and abiotic variables, it can be helpful to view data collected at one time but across multiple locations. Comparing these variables across space, rather than time, can reveal certain patterns.

Stations along the Hudson River are identified by their distance from the southern tip of Manhattan, which is given a value of RKM 0 (RKM = "river kilometer"). Locations upriver have values that go up, reaching 248 RKM at the Troy Dam north of Albany, New York.

Changes over time

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The river also changes over time. The data you're working with was collected over about 20 years. Instead of focusing on geography, you might choose to consider how the variable(s) you're interested in change as time goes by. If you keep other factors (such as location) constant, you might attribute patterns you see to the passage of time, or variables associated with the passage of time. For example, if you look at a scale of months, you might see seasonal changes. A scale of years could reflect factors such as the introduction of an invasive species like the zebra mussel, and a scale of decades might reflect factors such as long-term changes in the climate.

The Hudson River experiences four distinct seasons. As the months go by, air and water temperature and hours of daylight all change, as do the stages in the life cycles of many organisms. During the longer days of summer, for example, more light is available to producer organisms and temperatures are higher, so more photosynthesis takes place. Food is more abundant during the summer months as well, so consumer populations tend to grow.

Multiple variables

When you're looking at a graph that displays more than one type of data at a time, you may observe patterns that suggest connections between types of data. This can lead to new questions and ideas to investigate.

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This example displays the density of zebra mussels in the Hudson River during the past 20 years. The second variable shows the concentration of chlorophyll (a measure of phytoplankton abundance) at the Kingston, NY sampling station over the same period. The graph shows that zebra mussels first became abundant in the Hudson River in 1992. Beginning that same year, there are no more summer spikes in chlorophyll. This suggests that these two variables might be connected. This may mean that zebra mussels, which feed by filtering suspended particles, are eating the phytoplankton.