hb2015 johnston and harrison-sapflow
TRANSCRIPT
Mariann JohnstonSophie Harrison
Sap flow 2014: Does CaSiO3 enhance water use?
Background• Hubbard Brook whole-watershed transpiration
response to 1999 wollastonite (CaSiO3) addition
(Green et al. 2013)
Background• 2011 - A CaSiO3 treatment was added to a
subset of MELNHE sites (Green et al.) A 5th plot was added with a one-time CaSiO3
treatment i(1.2 metric tonnes ac-1) Included ‘old cohort’ sites: Bartlett C8, Hubbard
Brook (old), and Jeffers Brook (old)
• 2013 –Transpiration measurements attempted on Control and CaSiO3 plots at all three ‘old cohort’ sites concurrently, growing season But . . .
About measuring transpiration . . .• Granier method: reference probe 10 cm below a heated
probe, measures temperature difference (ΔT) (Granier, 1987)
• Measurements collected by data logger every 30 seconds, average recorded every 15 minutes
• ΔT converted to sapflux (Js, g x m2 x s-1) using BaseLiner software (Oren and Parashkevov, 2012)
Back to the Background• 2013 efforts suggested increased transpiration
in CaSiO3 treatment at HB-old (Zahor 2013 w/ M.Pruyn)• This despite technical difficulties that impeded more
comprehensive analysis -• 2014 effort redesigned to focus on one site at a
time, full battery power, frequent monitoring– We instrumented Control and CaSiO3 plots – Selected 3 trees each of 3 species (sugar maple,
American beech, yellow birch) totaling 9 per plot• Sophie Harrison presented some preliminary
results at last year’s meeting
Research Questions: What impacts transpiration rate?• Does CaSiO3 addition increase transpiration?
– Expect that it does, possibly due to increased xylem and fine root growth
– These data are now 3 years post-application• Does transpiration rate vary between tree
species?
Field Methods 2014• A total of 47 trees were
measured across the three sites
• Measurements collected for ~5 days per stand
Statistical Methods• Data analyzed as diurnal curves
from 5:00 am to 10:00 pm• Mixed model approach to repeated
measures analysis • Can handle missing values and
unbalanced design• Covariates were vapor pressure
deficit, wind speed, and radiation (Hubbard Brook Weather Station 1)
• Predictors were treatment, species• Block effect for site/date
Photos from www.hubbardbrook.org, watershed-6-tour
Results - Species
Results - Treatment
Also of interest-• Atmospheric covariates (radiation, vapor
pressure deficit, wind speed) were all significant, and explained 22% of the residual variation in the data.
• Covariates were added to the model before examining for predictor effects.
Results- Summary• Species (p=0.0165) and Species * Time (p=0.0174)
were significant.– Species varied in mean transpiration rate and in
transpiration pattern over the course of a day– Explained 18% of between-tree variance
• Treatment effect of CaSiO3 was significant (p=0.0219)– Treatment effect is still apparent (higher) in the 3rd
season after application– Explained 11.5% of between-tree variance
References & Acknowledgements• Granier, A. (1987). Evaluation of transpiration in a Douglas-fir stand by means of sap
flow measurements. Tree Physiology 3: 309-320.• Green, M.B., et al. (2013). Decreased water flowing from a forest amended with
calcium silicate. Proceedings of the National Academy of Sciences 110(15):5999-6003.
• Oren, Parashkevov, & Duke University. (2012). BaseLiner (Version 2.4.2) http://ch2oecology.env.duke.edu/orenlab/sofware.html
• Michele Pruyn!!!!!• Adam Wild• Mark Green
• NSRC • Sophie Harrison• Ruth Yanai• Matt Vadaboncoeur• 2014 Shoestring Crew
Thank You To . . .