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Forest–to–savanna transitions driven by changes in annual precipitation and dry spell length across the tropics
Forest–to–savanna transitions driven by changes in annual precipitation and dry spell length across the tropics
Ph.D. dissertation – Chapter 1:
I analyze the role of intra-seasonal precipitation variability metrics (e.g., the mean duration of dry and wet spells) in explaining the distribution of forests and savannas across the tropics and examine the potential for ecosystem transitions under projected changes in precipitation variability and mean annual precipitation (Under Review).
Exploring drivers of the current distribution of tropical forest and savanna in Northern South America
Exploring drivers of the current distribution of tropical forest and savanna in Northern South America
We analyzed which factors best explain the transition in northern South America (Llanos ecoregion and northwestern Amazon), where common thresholds based on typical environmental factors (e.g., mean annual precipitation (MAP), wet season precipitation) fail to predict this transition. For instance, savannas in the Llanos occur at MAP levels (> 1500 mm), which are typical of forests in other tropical regions.
Our results highlight the importance of fire frequency and intra-seasonal precipitation in determining forest-savanna transition in northern South America. Furthermore, future studies should consider regional differences in the climatic space of forest and savanna to improve projections of global change impacts on these highly diverse ecosystems. Further details at Valencia et al. (2024).
Which remote sensing product best captures spatio-temporal precipitation variability across Colombia?
Which remote sensing product best captures spatio-temporal precipitation variability across Colombia?
We assessed the performance of nine global precipitation products (GPPs) in Colombia, using 1,334 ground gauges as reference. Overall, CHIRPSv2 outperforms other GPPs throughout the country and its five natural regions for all elevation zones and temporal scales, followed closely by MSWEPv2.8 and IMERG. PERSIANN-CCS and ERA5 products had the lowest performance, mainly over the driest and higher-altitude regions, respectively. Further details at Valencia et al. (2023).
Based on the results of our previous work, we assess the performance of the new CHIRPSv3 product relative to CHIRPSv2 across multiple temporal scales across Colombia and its five natural regions for the period 2001-2023. CHIRPSv3 is expected to overcome reported limitations of CHIRPSv2, specifically its tendency to underestimate precipitation magnitude and variance, as well as its limited capability to accurately distinguish between daily precipitation intensity classes - Manuscript under review).
How well does the SWAT model capture the Leaf Area Index dynamics in tropical Andean ecosystems? What are the implications for land use and land cover change simulations?
How well does the SWAT model capture the Leaf Area Index dynamics in tropical Andean ecosystems? What are the implications for land use and land cover change simulations?
Hydrological models such as the SWAT (Soil and Water Assessment Tool) are widely used tools to project the impacts of LULC (Land Use/Land Cover) change on the water budget. However, their ability to produce reliable predictions depends on how accurately they represent the role of vegetation in the watershed’s water balance. In this study, we analyze how different representations of Leaf Area Index (LAI) affect streamflow responses to LULC change using the original SWAT model, SWAT-T (Alemayehu et al., 2017), and a proposed new variant (SWAT-Tb), which improves LAI bimodal representation for tropical regions. Further details at Valencia et al. (2024). The SWAT-Tb executables are available at https://github.com/Vale nciaSantiago/SWAT-Tb
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