Plant Physiology

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.

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 cm²is 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
Acer platanoides � Norway maple
Acer rubrum � Red maple
Acer saccharum � Sugar maple
Acer saccharinum � Silver maple
Acer negundo � Box elder
Rhus glabra � Smooth sumac
Rhus typhina � Staghorn sumac
Ilex verticillata � Winterberry
Berberis thunbergii � Japanese barberry
Berberis vulgaris � Common or European barberry
Alnus incana � Speckled alder
B. alleghaniensis (=B. lutea) � Yellow birch
Betula papyrifera � White or paper birch
Betula nigra � River birch
Carpinus caroliniana � Blue beech
Corylus americana � American hazelnut
Corylus cornuta � Beaked hazelnut
Ostrya virginiana � Ironwood, Hophornbeam
Catalpa speciosa � Common catalpa
Diervilla lonicera � Bush honeysuckle
Lonicera tartarica � Honeysuckle
Sambucus canadensis � Common elderberry
Sambucus pubens � Red elder
Symphoricarpos albus - Snowberry
Symphoricarpos occidentalis � Wolfberry
Viburnum lentago � Nannyberry
Viburnum rafinesquianum - Arrowwood
Viburnum trilobum � High-bush cranberry
Celastrus scandens � Bittersweet
Euonymus alatus � Winged euonymus
Cornus alternifolia � Pagoda dogwood
Cornus foemina � Gray dogwood
Cornus rugosa � Round-leaved dogwood
Cornus stolonifera � Red osier dogwood
Eleagnus angustifolia � Russian olive
Amorpha canescens � Lead plant
Gleditsia triacanthos � Honey locust
Gymnocladus dioica � Kentucky coffee tree
Quercus alba � White oak
Quercus bicolor � Swamp white oak
Quercus macrocarpa � Bur oak
Quercus rubra (= Q. borealis) � Northern red oak
Quercus ellipsoidalis � Northern pin oak
Ribes cynobasti � Prickly gooseberry
Aesculus glabra � Buckeye
Juglans nigra � Black walnut
Juglans cinerea � Butternut
Ribes lacustre � Swamp currant
Syringa reticulata � Japanese tree lilac
Syringa vulgaris � Common lilac
Fraxinus americana � White ash
Fraxinus pennsylvanica � Green ash
Fraxinus nigra � Black ash
Rhamnus cathartica � European Buckthorn
Amalanchier canadensis � Serviceberry
Aronia melanocarpa � Black chokeberry
Crataegus sp. � Hawthorne
Pyrus malus � Apple
Physocarpus opulifolius � Ninebark
Potentilla fruticosa � Cinquefoil
Prunus americana � Wild plum
Prunus pensylvanica � Pin cherry
Prunus serotina � Black cherry
Prunus virginiana � Chokecherry
Sorbaria sorbifolia � False spiraea
Sorbus aucuparia � Mountain ash
Spiraea alba � Meadowsweet
Phellodendron amurense � Amur cork tree, Cork tree
Zanthoxylum americanum � Prickly ash
Salix discolor � Pussy willow
Salix exigua � Sandbar willow
Salix nigra � Black willow
Populus alba � White or silver poplar
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;
Tilia americana � Basswood, Linden
Celtis occidentalis � Hackberry
Ulmus americana � American elm
Ulmus pumila � Chinese elm
Ulmus rubra � Slippery elm

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:

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

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

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