Transpiration data and quantitative skills
Organisation • Plant tissues, organs and systems
Flashcards
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Key concepts
What you'll likely be quizzed about
Definition and cause–effect of transpiration
Transpiration describes the evaporation of water from mesophyll cells into leaf air spaces and diffusion of water vapour through stomata to the atmosphere. Evaporation in the leaf air spaces reduces local water potential, causing water to move from xylem into those cells and maintaining a continuous transpiration stream upward through the plant. Changes in environmental conditions alter driving forces: increased temperature increases evaporation and so increases transpiration; increased wind removes humid air at the leaf surface and so increases transpiration; increased humidity decreases the vapour potential gradient and so reduces transpiration.
Types of data and variables
Quantitative data include continuous measures such as mass loss, time, temperature and area; categorical (qualitative) data include leaf treatments or species. The independent variable is the one deliberately changed and is recorded first in tables; the dependent variable is measured and recorded for each change. Continuous quantitative data suit line graphs; discrete categories suit bar graphs. Proper identification of variables and data types guides graph choice and statistical calculations.
Presenting data in tables
Tables require the independent variable in the first column, column headers with clear titles and SI units, consistent units and consistent decimal places in each column. If repeats occur, list raw repeats and place the mean in the right-most column. Tables that follow these conventions make calculation of change, mean and derived rates straightforward and reduce transcription errors.
Selecting and drawing graphs
Line graphs show how a continuous dependent variable changes with a continuous independent variable (for example, mass loss over time). Scatter graphs explore correlation between two quantitative variables. Bar graphs compare discrete categories. Axes require labelled variables with units, a chosen scale that uses most of the grid, and even intervals; the independent variable goes on the x-axis. Data points are plotted precisely and connected with a line of best fit (straight or curved) where appropriate; anomalies are identified and considered when drawing the trend.
Translating between graphs and numbers
Reading a graph provides numerical values by identifying coordinates and interpolating between grid lines. Converting a table into a graph makes trends visible; converting a graph into a table requires reading values at regular intervals, noting units and recording uncertainty where data are ambiguous. Comparison of numerical summaries (means, rates) with graphical trends supports conclusions and highlights anomalies that may indicate experimental error.
Calculating rates and compound measures
Rate of transpiration commonly appears as change in mass (g) per time (min or s) and often as change per unit leaf area (g cm−2 min−1). Calculation follows the compound measure format: rate = (change in mass) ÷ (time interval), and rate per area = (change in mass) ÷ (time × leaf area). Correct units appear in headers and final answers. Example classroom data use mass changes to calculate water loss per cm2, demonstrating the need for consistent units and clear working.
Key notes
Important points to keep in mind