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. 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?

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. 1471-

1479.

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)?