| Popis: |
Tropical vegetation influences local, regional, and global climates, largely through its relationship with the atmosphere, including seasonal patterns of photosynthesis and transpiration. Removal and replacement of natural vegetation can alter both of these processes. In the Amazon, land use/land cover change (LULCC; e.g. deforestation) started decades ago and is expected to continue, with potentially strong effects on climate. However, long-term data on tropical photosynthetic activity and transpiration are scarce, limiting our ability to estimate large-scale effects of LULCC. Here, we use remote sensing data to analyze the impact of LULCC on seasonal patterns of photosynthetic activity and transpiration in the southern Amazon. This region, naturally dominated by forest and Cerrado, has seen high rates of LULCC. Within each of these two ecosystems, we compare estimates of photosynthetic activity (from GOME-2 and GOSIF solar induced fluorescence, SIF) and transpiration (from the Global Land Evaporation Amsterdam Model, GLEAM) in paired sites with high and low rates of LULCC. In forest-dominated regions, deforestation has reduced photosynthetic activity and transpiration, particularly during the dry season, and replaced dry season greening with dry season browning. The SIF datasets disagree on wet season responses; SIF increases with deforestation according to GOME-2, but decreases according to GOSIF. In Cerrado-dominated areas, LULCC has increased photosynthetic activity during the wet season. In both ecosystems, LULCC has resulted in a higher seasonal or annual range of photosynthetic activity levels. The observed effects are often stronger in regions with more extensive LULCC. We found large differences between the two SIF products in both forest- and Cerrado-dominated pixels, with GOME-2 consistently providing higher maximum SIF values. These discrepancies merit further consideration. This analysis broadly characterizes the effects of LULCC on photosynthetic activity and transpiration in this region, and can be used to validate model representations of these effects. |
