Montane cloud forests are incredibly biodiverse regions that exist globally at narrow elevation bands and are frequently under the presence of low-level clouds and fog. Increasing temperatures and rising cloud base heights threaten these ecosystems, and may reduce the duration of time that plants are exposed to fog. Some cloud forest species have adapted to cloud immersion and enhanced photosynthesis rates have been observed under such conditions. This manuscript tests a simple model for simulating stomatal conductance for vegetation under cloud immersion based on Jarvis's empirical formulation. The light-available energy function within the model is modified to reflect variability observed in Abies fraseri under sun, low cloud, and cloud immersed sky conditions in the Southern Appalachian Mountains. Results demonstrate that this approach captures differences amongst stomatal opening during sun, low cloud and immersed conditions for similar ranges of temperature, light, diffusivity, and xylem water potential. Simulated average stomatal conductance during cloud immersion exceeded estimates during sun and low cloud conditions by 3 and 1.5 times, respectively. The magnitude of the estimated stomatal conductance for immersed and low cloud conditions falls below experimental data under all potential environmental states. Similarly, transpiration rates estimated from modeled stomatal conductance were also lower than observed values. The larger discrepancy for cloud immersed periods highlights the need to account for plant adaptation strategies like reduced transpiration and foliar uptake that occur during cloud immersion. Simulating adaptation processes for cloud forests in modeling studies is critical in order to evaluate fully the resilience of montane cloud forest vegetation under disturbance regimes.
The Upper Zambezi River Basin (UZRB) delineates a complex region of topographic, soil and rainfall gradients between the Congo rainforest and the Kalahari Desert. Satellite imagery shows permanent wetlands in low-lying convergence zones where surface–groundwater interactions are vigorous. A dynamic wetland classification based on MODIS Nadir BRDF-Adjusted Reflectance is developed to capture the inter-annual and seasonal changes in areal extent due to groundwater redistribution and rainfall variability. Simulations of the coupled water–carbon cycles of seasonal wetlands show nearly double rates of carbon uptake as compared to dry areas, at increasingly lower water-use efficiencies as the dry season progresses. Thus, wetland extent and persistence into the dry season is key to the UZRB’s carbon sink and water budget. Whereas groundwater recharge governs the expansion of wetlands in the rainy season under large-scale forcing, wetland persistence in April–June (wet–dry transition months) is tied to daily morning fog and clouds, and by afternoon land–atmosphere interactions (isolated convection). Rainfall suppression in July–September results from colder temperatures, weaker regional circulations, and reduced instability in the lower troposphere, shutting off moisture recycling in the dry season despite high evapotranspiration rates. The co-organization of precipitation and wetlands reflects land–atmosphere interactions that determine wetland seasonal persistence, and the coupled water and carbon cycles.
