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University of Alberta (2020)

The response of Tropical Dry Forests to meteorological drought and El Niño Southern Oscillation

Lidong, Zou

Titre : The response of Tropical Dry Forests to meteorological drought and El Niño Southern Oscillation

Auteur : Lidong, Zou

Université de soutenance : University of Alberta

Grade : Doctor of Philosophy (PhD) 2020

Résumé partiel
As a result of economic pressures from agricultural development, timber extraction, tourism and the expansion of cattle ranching, Tropical Dry Forests (TDFs) are considered one of the most threatened and least protected ecosystems in the neotropics. Interacting with these human-induced effects, natural disturbances resulting from climate change are also affecting their capacity to provide key ecosystem services. One of the most recurrent effects associated to climate change is the increase in the frequency, and intensity of meteorological droughts driven by the El Niño-Southern Oscillation (ENSO). The former in turn leads to changes in the structure and function of these tropical ecosystems. Despite the importance that drought plays on the provision of ecosystem services, the response of TDFs to meteorological droughts is not fully understood. In this context, the utility of remote-sensing drought indices in the context of the ENSO was evaluated in this doctoral dissertation via four chapters. Chapter 1 conducts a review of droughts in the context of the ENSO. Chapter 2 evaluates the utility of three remote-sensing drought indices : the Vegetation Condition Index (VCI), the Temperature Condition Index (TCI), and the Vegetation Health Index (VHI), in a TDF located at the Santa Rosa National Park Environmental Monitoring Super site (SRNP-EMSS), Guanacaste, Costa Rica. This evaluation was done at multiple temporal scales (year, month and season). Chapter 2 findings suggests that the TCI performed best over the VCI and the VHI. Chapter 3 assesses the response of Gross Primary Productivity of the SRNP-EMSS to meteorological droughts. The former is done using a temporal correlation analysis of the Normalized Difference Vegetation Index (NDVI), Land Surface Temperature (LST), and the Standard Precipitation Index (SPI) at monthly and seasonal scales. Results indicate that the NDVI and LST are largely influenced by seasonality as well as the magnitude, duration, and timing of precipitation.

Mots clés : TDFs Meteorological drought MODIS Drought ENSO

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Page publiée le 10 mai 2021