1. Presenter: Reuben Hilliard
Faculty Advisors: Dr. Paula Jackson & Dr. Brad Barney
Undergraduate Research Assistants: Chelsea Harris, Josh Hashemi & Gage Allred
Introduction
Surviving Climate Change
Comparing drought & fungicide response in two riparian tree species for use in ecological restoration
Riparian zones fulfill many ecosystem functions and occur at all elevations near
rivers, streams, and in floodplains. They function as a natural buffer against
erosion in river and stream banks, filter downstream pollution, and provide
increased habitat complexity (Wildlife, 2006). Due to development, logging, and
expanding agriculture, many riparian zones have been destroyed or depleted. This
has a profound ecological effect that leads to increased sedimentation and
pollution in natural water systems (Hernandez-Santana, 2011). These zones often
undergo rehabilitation to restore health back into the surrounding environment.
Salix nigra (Black Willow) and Platanus occidentalis (American Sycamore) are
two common riparian species of trees (Conger, 1996). Of these, Salix nigra is
frequently used to restore these areas, however not much information exists on the
ability to use Platanus occidentalis for this purpose. This research is part of a
larger study looking at the ecology and physiology of both of these species, with
the overarching aim of comparing the behavior of Platanus occidentalis to the
more widely studied Salix nigra, and determining the feasibility of using Platanus
occidentalis in restoration processes. Of additional importance is the fungal biota
which inhabit the soil beneath these trees. Mycorrhizal fungi have been reported to
improve plant growth in many crops through enhanced root growth and function
(Westphat et al, 2008). It also improves early plant establishment and increased the
most valuable early fruit yield under some environmental stress conditions. This is
of ecological importance and will be incorporated in this study.
Objectives
1) Determine whether there is a different response in Salix nigra and Platanus
occidentalis to drought.
2) Determine if the fungal biota, Mycorrhizae, modified the drought response
among species.
One cause for data errors in greenhouse experiments can be due to microclimate
differences, such as light, airflow and heat among saplings, within different
planters. As stated by Brien et al. (2003), sound statistical design and analysis is
better than rearranging the position of plants during the experiment itself. In our
experiment, Platanus occidentalis and Salix nigra saplings were planted using a
Randomized Complete Block Design, as seen in Table I. It involved a complete
experimental treatment within each planter series, allowing for homogenous
growing conditions within a single tray, regardless of differences among planters
themselves. To account for variability in sapling size, each tray had a similar
distribution of size classes. All the saplings were tagged with unique identifiers,
such as PO-01 or SN-02. 15-17 individuals of each species were subjected to a
control, inundation, or drought condition; and drought with and without the
addition of mycorrhizal spores, a fungal biota, which was controlled with the
addition of a fungicide, Benomyl. In total, 31 Platanus and 34 Salix cuttings
received sufficient nutrients in the form of a slow-release fertilizer and after taking
baseline measurements, were allowed to grow in planters through the spring of
2015. From May 18th until August 23rd, a team of myself and 3 undergraduate
research assistants, took anatomical and physiological measurements.
For the anatomical measures, an indicator of growth rate, both the circumference
and the height were taken for each plant on a weekly basis. For the physiological
data, a LICOR LI-6400 Infrared Gas Analyzer (IRGA) was used to measure
photosynthetic rate from leaves repeatedly over the period of weeks, systematically
moving through the plants, selecting a predefined leaf from a randomly selected
plant from each treatment and block. This was a tedious process, with each leaf
taking up to 16min for a full measurement run. The results were used to build light
response curves. Net Photosynthetic rate, or CO2 assimilation (µmol CO2 m-2 leaf
area s-1) from several trials were plotted against light intensity, or Absorbed
Photosynthetically Active Radiation (αPAR, µmol photons m-2 leaf area s-1). The
slope of the linear phase of the response curve is a measure of "photosynthetic
efficiency" of the plant, or how efficiently solar energy is converted into chemical
energy. Different plants show differences in the shape of their light response
curves, which reveals characteristics of the underlying photosynthesis processes,
including the efficiency at which light is utilized by photosynthesis and the rate of
O2 uptake.
In this longitudinal study, both the anatomical and the physiological data were
analyzed using SAS 9.4 with the MIXED Procedure, which models mixed effects
over time.
Oregon Department of Fish and Wildlife. 2006. Oregon Conservation Strategy. Oregon Department
of Fish and Wildlife, Salem, Oregon.
Hernandez-Santana, V., Asbjornsen, H., Sauer, T., Isenhart, T., Schilling, K., & Schultz, R. 2011.
Enhanced transpiration by riparian buffer trees in response to advection in a humid temperate agricultural
landscape. Forest Ecology and Management, 261(8), 1415-1427.
Conger, RM. 1996. Black willow (Salix nigra ) use in phytoremediation techniques to remove the
herbicide bentazon from shallow groundwater. Master’s thesis, Louisiana State University
Brien, C. J., Berger, B., Rabie, H., & Tester, M. 2013. Accounting for variation in designing
greenhouse experiments with special reference to greenhouses containing plants on conveyor systems. Plant
Methods, 9(5), 1746-4811
Westphal, A., Snyder, N., Xing, L. 2008. Effects of Inoculations with Mycorrhizal Fungi of Soilless
Potting Mixes During Transplant Production on Watermelon Growth and Early Fruit Yield. HortScience,
43(2), 354-360
References
(Image:
bioimages.vanderbilt.edu/baskauf/
15370.htm)
Table I: A Randomized Complete Block Design
(Image:
bioimages.vanderbilt.edu/baskau
f/23004.htm)
(Image:
bioimages.vanderbilt.edu/baskau
f/29666.htm)
(Image:
http://bioimages.vanderbilt.edu/
baskauf/13574.htm)
Salix nigra and Platanus occidentalis saplings planted and set up in greenhouse.
Salix nigra leaves
(left) and
Salix nigra tree
(right)
Platanus
occidentalis leaves
(left) and
Platanus
occidentalis tree
(right)
Height measurements for Salix nigra sapling and mature plant (above) and LICOR
LI-6400 IRGA (below).
Block 1 Block 2
A B B A
D C C D
ConclusionsMethods Results
Anatomical Results:
Linear Rate of Growth among Species & Drought Conditions
Physiological Results:
Photosynthetic Light Response Curve & Mean Maxima Bar Chart
** p < .0001
Statistical Models
Randomized Complete Block Design
yij = µ + αi + bj + εij
Autoregressive Heterogeneous Covariance Matrix
Unstructured Covariance Matrix
Mixed Effects Model
y = Xβ + Zu + ε
Relevant Code
Graphs and Bar Chart designed in Tableau 9.2
*Coding the explanatory variables;
DATA research.anatomical_data;
SET together;
daysc = date - mdy(5,18,2015);
dayscat = daysc;
tag = species;
species = substr(tag,1,2);
fungicide = scan(treatment,1,"/");
drought = substr(scan(treatment,2,"/"),1,1);
tmt=1;
if species="PO" then tmt=tmt+4;
if drought="D" then tmt=tmt+2;
if fungicide="Fungicide" then tmt=tmt+1; RUN;
*Optimal Anatomical model. Unstructured Cov Matrix;
PROC MIXED data = research.anatomical_data;
CLASS species drought fungicide tag blocknum dayscat;
MODEL height = species drought species|daysc drought|daysc
/solution ddfm = kr;
REPEATED dayscat/ subject = tag(blocknum) type = un R RCORR ; RUN;
*Optimal Physiological model, stratified by species. Autoregressive Heterogeneous Cov Matrix;
PROC SORT data = research.master_photo; BY Species Tag PAR; run;
PROC MIXED data = research.master_photo;
BY Species;
CLASS tag treatment blocknum PAR;
MODEL photo = treatment PAR ;
RANDOM blocknum;
REPEATED PAR /subject = tag type = arh(1) ;
LSMEANS treatment /pdiff tdiff ; RUN;
*Data output for Mean Maxima Photosynthetic Rate and Std Errors;
ODS GRAPHICS ON;
PROC MIXED data = research.master_photo;
WHERE PAR = 800;
CLASS Tag blocknum fungicide drought species PAR period;
MODEL photo = species*fungicide*drought
/ noint solution ddfm=kr;
RANDOM blocknum;
RANDOM int / subject=tag; RUN; ODS GRAPHICS OFF;
The results indicate that Salix nigra and Platanus occidentalis do respond
differently to drought conditions. In fact, the interaction of the days count and
the drought condition was highly significant (p < .0001). This meant that as the
experiment proceeded the drought condition became more pronounced. As seen
in the anatomical results, for the drought condition, Platanus was able to
outperform Salix in the linear rate of growth (corrected for errors), 0.86cm/Day
and 0.74cm/Day, respectively. The fungicide treatment did not have a significant
effect in either species.
The physiological results indicated that the PAR level, or light intensity given to
the leaf, was significant (p < 0.05). This analysis had to be stratified by species,
as none of the other factors were significant initially. When this was done,
Platanus was right on the cusp of being significant in the drought condition
during period 2 (last 5 weeks of the experiment). Even though Salix didn’t
respond to the drought or fungicide treatments, this information is still of
biological interest to researchers, as it indicates that Salix can be stressed and
still perform unhindered, with minimal interruptions.
Of particular note is how well Platanus performed in the ‘No Fungicide/Drought’
treatment, which can be observed in both the light curve and the mean maxima
photosynthetic output figures (left). This could indicate that the fungal biota
which remained in the soil, had a beneficial effect on the outcome of
Platanus growth, as well as its solar energy conversion efficiency. This will
require future research to isolate these outcomes.
These results were quite positive and allow future research to focus specifically
on Platanus as a species to use in restoration of Georgia’s riparian ecosystems.