Plant Physiology (Biology 327) - Dr. Stephen G. Saupe; College of St. Benedict/ St. John's University; Biology Department; Collegeville, MN 56321; (320) 363 - 2782; (320) 363 - 3202, fax; ssaupe@csbsju.edu |
Leaf Margin Analysis, Or, Are Leaves Good Predictors of Climate?
Objectives: The purpose of this lab is to:
Introduction:
Since plants are stationary they must respond
developmentally, and ultimately evolutionarily, to their environment. As a
result, it's not surprising that leaf morphology (shape) has been shown to be
related to climate. For example, some the following correlations have been
reported (Wiemann et
al, 1998): (a) leaf length is directly related to the mean annual
temperature (MAT); (b) leaf area is directly correlated to both mean annual precipitation (MAP) and
MAT; and (c) leaf width is directly correlated with MAP. Thus, leaves are longer
and larger in climates with warmer
temperatures and higher rainfall.
Another interesting observation that was first reported about 100 year ago is that woody deciduous plants having leaves with toothed margins (termed serrate) predominate in temperate climates while species with smooth (termed entire) leaf margins predominate in frigid (arctic, montane), dry (or saline), and tropical climates. This relationship has been used to derive a mathematical model for predicting climate from leaf margins. One application of this model is to determine MAT in the geological past by analyzing the leaf margins of fossil plants.
It is not clear why there should be such a strong correlation between leaf margin and temperature. A recent analysis suggests that serrated margins provide regions of quicker photosynthesis in cooler conditions (Royer & Wilf, 2006).
Wiemann et al. (1998) and Wilf (1997) report that the following equations have been derived to predict MAT (in degrees C) or MAP (in cm) from leaf margin structure (% is expressed as a whole number, not a decimal fraction):
The purpose of today's lab is to test the accuracy of these models for our area.
Pre-Lab Study:
Print, read, and bring to class a copy of this
exercise.
Complete Table 1 by locating the data for our area for mean annual temperature (MAT) and mean annual precipitation (MAP). These data can be obtained from a variety of web-based sources such as the Midwest Regional Climate Center (click on: Climate of the Midwest/Climate Summaries). If you need to convert unit, there are many web sites that will help.
Table 1. Climate Data for Central Minnesota | ||
MAT | deg C | deg F |
MAP | inches | cm |
source: | ||
if web site, date accessed: |
Table 2. Predicted % of woody species in central Minnesota with serrate leaf margins | |
Model | Predicted % with serrate leaves |
Equation 1 | |
Equation 2 | |
Equation 3 | |
Equation 4 | |
Equation 5 | |
mean |
Table 3. Predicted % of woody species in central Minnesota with large leaves Model Predicted % with large leaves Equation 6
Before lab begins, send to me an email that
includes Table 1, 2 & 3. In addition, be sure to record these data on
the
lab handout and bring them to
lab:
For each of your assigned species, bring to class: (a) an image (8.5 x 11) of the plant clearly showing the leaf margins; (b) write on the image whether the plant is native to Minnesota or not; and (c) write on the image the length and width of a typical leaf (in cm) or mark the scale on your diagram so that we can calculate the length/width from the image. Most of this information can be obtained from sources such as the USDA Plants Database, Flora of North America project site, or books of images such as the Illustrated Guide to Accompany Gleason & Cronquist's Manual of Plants of NE United States and Canada. Images are available in this site or found through a Google "Image" search or other.
Methods:
Once in lab, examine the herbarium specimens provided and/or
images & data obtained by your lab mates and complete Table 4. For a leaf
to be considered serrate, the tooth must be an extension of
a vein (vascular extension). In other words, veins should run into the
teeth. Do not count "spines," as in holly, as teeth. By definition (Wiemann et
al., 1998), a leaf that has an area greater than 33 cm2 is
considered "large." A quick method to approximate the area of a leaf is to multiply
leaf length x leaf width x 2/3 (Manual of Leaf Architecture).
Alternately, compare an "average" leaf of each species to a model that you cut
out of paper that is 33 cm2 (or 5.8 x 5.8 cm). Once you
have collected your data, complete the summary data tables (5, 6 & 7).
Table 4. Characteristics of leaves of deciduous woody plants in Central Minnesota | ||||||
Species | Native (N) or non-native (X) | Entire (E) or Serrate (S) | Leaf Length (cm) | Leaf Width (cm) | ca. Leaf Area (cm2) | Leaf Size (L = large > 33 cm2; S = small, < 33 cm2) |
Acer ginnala � Amur maple |
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Acer platanoides � Norway maple |
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Acer rubrum � Red maple | ||||||
Acer saccharum � Sugar maple | ||||||
Acer saccharinum � Silver maple |
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Acer negundo � Box elder | ||||||
Rhus glabra � Smooth sumac | ||||||
Rhus typhina � Staghorn sumac | ||||||
Ilex verticillata � Winterberry | ||||||
Berberis thunbergii � Japanese barberry |
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Berberis vulgaris � Common or European barberry | ||||||
Alnus incana � Speckled alder | ||||||
B. alleghaniensis (=B. lutea) � Yellow birch |
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Betula papyrifera � White or paper birch | ||||||
Betula nigra � River birch | ||||||
Carpinus caroliniana � Blue beech | ||||||
Corylus americana � American hazelnut |
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Corylus cornuta � Beaked hazelnut | ||||||
Ostrya virginiana � Ironwood, Hophornbeam |
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Catalpa speciosa � Common catalpa | ||||||
Diervilla lonicera � Bush honeysuckle | ||||||
Lonicera tartarica � Honeysuckle |
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Sambucus canadensis � Common elderberry | ||||||
Sambucus pubens � Red elder | ||||||
Symphoricarpos albus - Snowberry |
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Symphoricarpos occidentalis � Wolfberry | ||||||
Viburnum lentago � Nannyberry | ||||||
Viburnum rafinesquianum - Arrowwood |
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Viburnum trilobum � High-bush cranberry | ||||||
Celastrus scandens � Bittersweet | ||||||
Euonymus alatus � Winged euonymus |
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Cornus alternifolia � Pagoda dogwood | ||||||
Cornus foemina � Gray dogwood | ||||||
Cornus rugosa � Round-leaved dogwood |
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Cornus stolonifera � Red osier dogwood | ||||||
Eleagnus angustifolia � Russian olive | ||||||
Amorpha canescens � Lead plant |
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Gleditsia triacanthos � Honey locust | ||||||
Gymnocladus dioica � Kentucky coffee tree | ||||||
Quercus alba � White oak |
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Quercus bicolor � Swamp white oak | ||||||
Quercus macrocarpa � Bur oak | ||||||
Quercus rubra (= Q. borealis) � Northern red oak |
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Quercus ellipsoidalis � Northern pin oak | ||||||
Ribes cynobasti � Prickly gooseberry | ||||||
Aesculus glabra � Buckeye |
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Juglans nigra � Black walnut | ||||||
Juglans cinerea � Butternut | ||||||
Ribes lacustre � Swamp currant |
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Syringa reticulata � Japanese tree lilac | ||||||
Syringa vulgaris � Common lilac | ||||||
Fraxinus americana � White ash |
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Fraxinus pennsylvanica � Green ash | ||||||
Fraxinus nigra � Black ash | ||||||
Rhamnus cathartica � European Buckthorn |
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Amalanchier canadensis � Serviceberry | ||||||
Aronia melanocarpa � Black chokeberry | ||||||
Crataegus sp. � Hawthorne |
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Pyrus malus � Apple | ||||||
Physocarpus opulifolius � Ninebark | ||||||
Potentilla fruticosa � Cinquefoil |
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Prunus americana � Wild plum | ||||||
Prunus pensylvanica � Pin cherry | ||||||
Prunus serotina � Black cherry |
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Prunus virginiana � Chokecherry | ||||||
Sorbaria sorbifolia � False spiraea | ||||||
Sorbus aucuparia � Mountain ash |
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Spiraea alba � Meadowsweet | ||||||
Phellodendron amurense � Amur cork tree, Cork tree | ||||||
Zanthoxylum americanum � Prickly ash | ||||||
Salix discolor � Pussy willow |
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Salix exigua � Sandbar willow | ||||||
Salix nigra � Black willow | ||||||
Populus alba � White or silver poplar |
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Populus deltoides � Cottonwood | ||||||
Populus grandidentata � Large toothed aspen | ||||||
Populus nigra cv. italica � Lombardy poplar |
||||||
Populus tremuloides � Quaking aspen | ||||||
Populus balsamifera � Balsam popular | ||||||
Dirca palustris � Leatherwood; |
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Tilia americana � Basswood, Linden | ||||||
Celtis occidentalis � Hackberry | ||||||
Ulmus americana � American elm |
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Ulmus pumila � Chinese elm | ||||||
Ulmus rubra � Slippery elm |
Table 5. Data Summary | |||
Native | Introduced | Total | |
Species number | |||
Percent of total species | |||
Number of species with serrate leaves | |||
Number of species with entire leaves | |||
Percent species with serrate leaves | |||
Percent species with entire leaves | |||
Number of species with large leaves | |||
Percent of native species with large leaves |
Table 6. Predicted MAT for central Minnesota based on leaf morphology of all woody species, native woody species and non-native species | |||
Model | MAT (◦C) - data from all species | MAT (◦C) - native species data | MAT (◦C) - introduced species data |
Equation 1 | |||
Equation 2 | |||
Equation 3 | |||
Equation 4 | |||
Equation 5 | |||
Mean |
Table 7. Predicted MAP for central Minnesota based on leaf morphology of all woody species, native woody species and non-native species | |||
Model | MAP (cm) - data from all species | MAT (cm) - native species data | MAT (cm) - introduced species data |
Equation 6 |
Data & Analysis: Once you have collected your data:
Complete the summary data tables (5, 6 & 7).
Table 8. Chi square goodness-of-fit test comparing native species with serrate and entire margins |
|
null hypothesis: |
|
Observed values: | serrate: entire: |
Expected values: | serrate: entire: |
p value = | |
Conclusion: | The null hypothesis should be: rejected accepted |
Table 9. Chi square 2 x 2 contingency table, comparing leaf margins on native and non-native species | ||
native species | non-native species | |
serrate | ||
entire |
Table 10. Results of chi square 2 x 2 contingency table, comparing leaf margins on native and non-native species |
|
null hypothesis: | |
p value = | |
Conclusion: | The null hypothesis should be: rejected accepted |
Post-Lab Assignment: Write an abstract of this lab. Append to your abstract completed copies of tables 5 - 10. In you abstract address questions such as:
References:
Bailey, IW, EW Sinnott (1916) The climatic distribution of certain types of angiosperm leaves. American Journal of Botany 3: 24 - 39.
Leaf Architecture Working Group (1999) Manual of Leaf Architecture. Yale University.
Royer, DL & P Wilf (2006) Why do toothed leaves correlate with cold climates? Gas exchange at leaf margins provides new insights into a classic paleotemperature proxy. Int. J. Plant Sci. 167: 11 - 18.
Sinnott, EW, IW Bailey (1915) Investigations on the phylogeny of the angiosperms. 5. Foliar evidence as to the ancestry and early climatic environment of the angiosperms. American Journal of Botany 2: 1 - 22.
Wiemann, MC, SR Manchester, DL Dilcher, LF Hinojosa, EA Wheeler (1998) Estimation of temperature and precipitation from morphological characters of dicotyledonous leaves. American Journal of Botany 85: 1796 - 1802.
Wilf, P (1997) When are leaves good thermometers? A new case for leaf margin analysis. Paleobiology 23: 373 - 390.
Web Sites:
Checklist of Trees & Shrubs of the College of St. Benedict & St. John's University - SG Saupe
Common Trees & Shrubs of St. John's - SG Saupe
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Last updated:
01/07/2009 � Copyright by SG
Saupe