Listed are few questions related to the content, process, and structure for each paper explored in this presentation and the questions are meant to facilitate in-class discussions. Discussions were facilitated by Richard Maclean and Jenkins Macedo.

1. Richard Maclean
Jenkins Macedo
Discussion Questions: Drought Assessment and Impacts
November 11, 2013
Zhao & Running, 2010. Drought-Induced Reduction in Global Terrestrial Net Primary
Production from 2000 through 2009. Science, Vol. 329, pg. 940-943.
1. Do you think monitoring global NPP is essential to understand terrestrial climate
change variations?
2. What are some of the complexities associated with remote sensing satellite in
detecting green-ups? What could be some of the potential shortfalls and how could
they be addressed? Considering the global scale of the approaches used in this
project, what could be some of the major challenges and how could these challenges
(if any) be addressed?
3. The authors indicate that satellite data could be used to provide “realistic information”
on vegetation dynamics, which include land cover change, disturbances, regrowth,
which can be used to reduce uncertainties in carbon budget estimates. What do you
think of this statement in relations to what we have learned in previous classes?
4. Given the results in Figure S3, the authors noted that temperature is not a dominant
factor controlling the growing season in vegetated areas in the Southern Hemisphere;
however, they claim that high temperature value can increase both vapor pressure
deficit (VPD) and subsequently increase the rate of Evapotranspiration, which also had
the propensity to lead to a dryer environment and eventually reducing NPP. Given the
result of their analysis indicated in Figure S3, what do you think could be responsible
for this negative correlation between temperature and growing season in contracts to
what is known in the literature involving the association between climate temperature
and growing seasons?
5. What is/are your overall impression of this research? What do you think the authors
did well and why? If you were asked to make a constructive recommendations to
enhance this approach, what would your recommendation be and why?
Asner et al. 2004. Drought Stress and Carbon uptake in an Amazon Forest Measured with
Spaceborn Imaging Spectroscopy. PNAS, Vol. 101, No. 6, pg. 6039-6040.
1. What is your opinion on the efficacy of their ground based sampling? The two field
plots were extensively sampled; do you think this effort was enough to overcome the
point sampling problem in remote sensing? Even with the rigorous sampling, ultimately
their sample size was two. The authors used remote sensing to provide confidence
that the control site represented the larger neighboring forest, are you confident in their
statement that this supports that the dry down site was responding to the treatment
and site specific factors?

2. 2. In their conclusions the authors claim that modeling NPP with NDVI or field estimate
LAI underestimates drought reductions in NPP. This claim is based on their
comparison of several modeled estimates of NPP; do you think they can make this
claim without comparing it to more direct measurements of Aboveground Carbon?
3. The authors test six different scenarios of their formulation of NPPd/c, but they do not
provide a biologically founded weight or reasoning for this technique. Do you feel that
this approach is justified by the novelty of the technique?
4. Do you think the results of this study (particularly Fig. 4) contribute to arguments
supporting continued efforts in hyperspectral image spectroscopy, or, do you think the
results make a more compelling argument towards more targeted multispectral
sensors?
5. Assume that a funding body is deciding to put money behind this technique for
drought monitoring, and they have come to you for your expert opinion. Would you
support their funding? Why or why not, and can you imagine circumstances (particular
advances in the technique, one funding body over another, different area of study,
etc.) that might change your answer?
Mu et al. 2013. A Remotely Sensed Global Terrestrial Drought Severity Index. American
Meteorological Society, pg. 83-96.
1. The authors noted that most drought indices used reanalysis meteorological data that
contains substantial uncertainties. Given their methods, results and recommendation,
do you think the levels of uncertainties were addressed?
2. In the absence of available soil water holding capacity (AWC) data that is not more
than 2.54cm, than AWC is assigned to the topsoil and it is assumed that the bottom
soil layer (below 2.54cm) is zero. What do you think is problematic with this approach
considering our discussions in the last class about the spatial extent of remote sensed
soil moisture content?
3. What are some of the challenges of weather stations data recording processes and
how does that impact your results?
4. What is novel about this approach that would motivate you to recommend this
approach to others interested in assessing and monitoring terrestrial drought severity?
5. What is your general critique of the paper in terms of format, data presentation, and
recommendations for future research?

3. Huang et al. 2010. Regional Aboveground live carbon losses due to drought-induced tree
dieback in pinon-juniper ecosystems. Remote Sensing Environment, Vol. 114, pg. 14711479.
1. Given the long time span of the Landsat data record, do you think the authors could
apply their method to determining long term change in aboveground biomass (AGB)?
Why or why not?
2. The authors point out that their use of ΔPVMAX may confound drought related dieback
with other mortality events. Based on previous work we have read can you think of
methods that could be employed to account for multiple mortality types?
3. In their field work, the authors measure total standing live and dead P-J AGB. They
subsequently use that measure to equal AGB loss by correlating a single year
estimate (field measure AGB) with their differential estimate (ΔPVMAX). Do you think
that is an appropriate comparison? Does their subsequent use of differential remotely
sensed AGB estimate washout any potential problems in the initial correlation?
4. The big picture finding of this study was large magnitude of drought related C loss
compared to wildfire and treatment carbon loss. What implications do you think this
finding may have for land management and policy in the intermountain-west?
5. A side issue related to this work has to do with time scales in carbon accounting.
Huang et al. have generated a remotely sensed estimate of standing dead carbon, and
count it as lost carbon. Do you think this is an appropriate label given the potential
longevity of standing dead carbon as a carbon Pool (especially within their 5 year
timeframe)?