Investigating the response of leaf area index to droughts in southern African vegetation using observations and model simulations

Abstract

Abstract. In many regions of the world, frequent and continual dry spells are exacerbating drought conditions, which have severe impacts on vegetation biomes. Vegetation in southern Africa is among the most affected by drought. Here, we assessed the spatiotemporal characteristics of meteorological drought in southern Africa using the standardized precipitation evapotranspiration index (SPEI) over a 30-year period (1982–2011). The severity and the effects of droughts on vegetation productiveness were examined at different drought timescales (1- to 24-month timescales). In this study, we characterized vegetation using the leaf area index (LAI) after evaluating its relationship with the normalized difference vegetation index (NDVI). Correlating the LAI with the SPEI, we found that the LAI responds strongly (r=0.6) to drought over the central and southeastern parts of the region, with weaker impacts (r<0.4) over parts of Madagascar, Angola, and the western parts of South Africa. Furthermore, the latitudinal distribution of LAI responses to drought indicates a similar temporal pattern but different magnitudes across timescales. The results of the study also showed that the seasonal response across different southern African biomes varies in magnitude and occurs mostly at shorter to intermediate timescales. The semi-desert biome strongly correlates (r=0.95) to drought as characterized by the SPEI at a 6-month timescale in the MAM (March–May; summer) season, while the tropical forest biome shows the weakest response (r=0.35) at a 6-month timescale in the DJF (December–February; hot and rainy) season. In addition, we found that the spatial pattern of change of LAI and SPEI are mostly similar during extremely dry and wet years, with the highest anomaly observed in the dry year of 1991, and we found different temporal variability in global and regional responses across different biomes. We also examined how well an ensemble of state-of-the-art dynamic global vegetation models (DGVMs) simulate the LAI and its response to drought. The spatial and seasonal response of the LAI to drought is mostly overestimated in the DGVM multimodel ensemble compared to the response calculated for the observation-based data. The correlation coefficient values for the multimodel ensemble are as high as 0.76 (annual) over South Africa and 0.98 in the MAM season over the temperate grassland biome. Furthermore, the DGVM model ensemble shows positive biases (3 months or longer) in the simulation of spatial distribution of drought timescales and overestimates the seasonal distribution timescales. The results of this study highlight the areas to target for further development of DGVMs and can be used to improve the models' capability in simulating the drought–vegetation relationship.

The essentiality of Essential Biodiversity Variables: implementation in nature conservation policies

“…However, the work of shows that LAI can be effectively used as an indicator for various habitat types (including forests) for assessing drought and drought risk. Similar results have been found by Lawal et al (2022), where LAI responds strongly to drought over central and southeastern parts of South Africa. Salinity is a water condition problem not similar to but related to drought.…”

“…Agricultural lands that surround the national park, industries, and drinking water subtraction usurp groundwater, which leads to a lowering of the groundwater table. Preventing and restoring the groundwater table and mitigating drought is a management priority (Lawal et al, 2022). For forest habitat types, drought is less of a problem and forests can even be a cause of drought, as the development of forests lowers the groundwater table, as well as causes less rain to penetrate the ground (Gelderland, 2017).…”

Future drought propagation through the water-energy-food-ecosystem nexus – A Nordic perspective

“…However, one of its key limitations is that it is a meteorological drought index and does not necessarily reflect vegetative stress. Other indices, such as streamflow normalized by environmental flow for freshwater ecosystems (Tharme, 2003) or the leaf area index for terrestrial ecosystems (Lawal et al, 2022), might be more suitable to represent ecosystem health and should be tested in future WEFE nexus studies.…”

Increased impact of the El Niño–Southern Oscillation on global vegetation under future warming environment

“…In addition, the models may have biases in simulating different phases (e.g., onset and length) of the growing season 49 , 50 and the magnitude of LAI growth 51 . However, outputs from Earth system models are still helpful to investigate the variations of global vegetation cover 44 , 52 , 53 .…”