Date of Award
1-1-2017
Document Type
Dissertation
Degree Name
Ph.D.
Organizational Unit
Geography and the Environment
First Advisor
Matthew J. Taylor, Ph.D.
Second Advisor
Michael Keables
Third Advisor
Michael Daniels
Fourth Advisor
Kevin Anchukaitis
Keywords
Climate change, Coffee, Dendrochronology, Guatemala, Hydroclimatic reconstruction, Paleoclimatology
Abstract
This dissertation makes use of a physical geography perspective to examine the relationship between agriculture and climate in Guatemala using dendrochronology. I examined the potential of high-resolution climate proxy data from dendrochronology to help fill in the gaps of past climate information to better understand the natural and anthropogenic variability of precipitation which, in turn, can inform Guatemala’s agriculture sector. This research has demonstrated successful cross-dating and climate sensitivity of Abies guatemalensis in the Pacific slope of Guatemala. Based on this, I have produced a 124-year record of mean precipitation from June-July-August. The mean precipitation from June-July-August at this site seems to receive an important influence from the sea surface temperature (SST) in the Pacific Ocean in the form of El Niño Southern Oscillation (ENSO) in the region 3.4. The analysis on the frequency of the precipitation records suggests that single year droughts dominate the record yet, periods of 9 years below-average rainfall can persist. Likewise, single year pluvial events also dominate the evaluated period. The long-term reconstruction of precipitation allowed to describe past relationships between coffee plantations and pests. For instance, the frequency analysis suggests that 4 or more consecutive periods of above-average precipitation are associated with several coffee pests and subsequently great economical losses due to crop failures, including the last coffee leaf rust crisis.
This study also presents a streamflow reconstruction of the Upper Samalá River watershed using a tree ring-width chronology derived from the Guatemalan fir (Abies guatemalensis) to reconstruct mean August-September-October streamflow volumes for the period 1889-2013. Our analysis shows that strong statistical correlations are present between tree-ring width measurements and monthly natural streamflow series. The mean August-September-October streamflow variability is dominated by single year events for both above and below the long-term mean. This reconstruction reveals important teleconnections with the ENSO 3.4 region and it is to our knowledge, the only streamflow reconstruction in Guatemala using tree-ring measurements. This new long-term record will be useful to recalculate historical discharge peaks and floods that affect agricultural areas in the mid and lower basin but also the hydroelectric production.
Our analysis suggests that records from the GIMMS 3g v.0 Normalized Difference Vegetation Index (NDVI), are inversely correlated to precipitation in the Upper Samalá River watershed at the location of the A. guatemalensis forest stand Kanchej. This suggest that the net solar radiation income during the cloud-free timing throughout the mid-summer drought could be partially responsible for promoting cloudiness by heating the SST and hence, promoting precipitation during the second peak of precipitation during September and October. The independent analyses of precipitation and NDVI sensitivity of A. guatemalensis and the correlation between precipitation and NDVI suggest that precipitation is a modulator of radial growth of A. guatemalensis in this location of Guatemala. These findings can be used to refine the knowledge on the climatic controls on A. guatemalensis radial growth.
Publication Statement
Copyright is held by the author. User is responsible for all copyright compliance.
Rights Holder
Diego Pons
Provenance
Received from ProQuest
File Format
application/pdf
Language
en
File Size
157 p.
Recommended Citation
Pons, Diego, "Exploring Historical Coffee and Climate Relations in Southern Guatemala: An Integration of Tree Ring Analysis and Remote Sensing Data" (2017). Electronic Theses and Dissertations. 1356.
https://digitalcommons.du.edu/etd/1356
Copyright date
2017
Discipline
Physical Geography, Remote Sensing, Paleoclimate Science