Altered albedo dominates the radiative forcing changes in a subtropical forest following an extreme snow event.

Subtropical forests are important ecosystems globally due to their extensive role in carbon sequestration. Extreme climate events are known to introduce disturbances in the ecosystem that cause long-term changes in carbon balance and radiation reflectance. However, how these ecosystem function changes contribute to global warming in terms of radiative forcing (RF), especially in the years following a disturbance, still needs to be investigated. We studied an extreme snow event that occurred in a subtropical evergreen broadleaved forest in south-western China in 2015 and used 9 years (2011-2019) of net ecosystem CO2 exchange (NEE) and surface albedo (α) data to investigate the effect of the event on the ecosystem RF changes. In the year of the disturbance, leaf area index (LAI) declined by 40% and α by 32%. The annual NEE was -718 ±â€…128 g C m-2 as a sink in the pre-disturbance years (2011-2014), but after the event, the sink strength dropped significantly by 76% (2015). Both the vegetation, indicated by LAI, and α recovered to pre-disturbance levels in the fourth post-disturbance year (2018). However, the NEE recovery lagged and occurred a year later in 2019, suggesting a more severe and lasting impact on the ecosystem carbon balance. Overall, the extreme event caused a positive (warming effect) net RF which was predominantly caused by changes in α (90%-93%) rather than those in NEE. This result suggests that, compared to the climate effect caused by forest carbon sequestration changes, the climate effect of α alterations can be more sensitive to vegetation damage induced by natural disturbances. Moreover, this study demonstrates the important role of vegetation recovery in driving canopy reflectance and ecosystem carbon balance during the post-disturbance period, which determines the ecosystem feedbacks to the climate change.

Assessment of metal contaminants along the Bay of Bengal - Multivariate pollution indices.

The spatial concentration of heavy metals (Mn, Ni, Cu, Co, Zn, Cd, and Pb) was studied in coastal areas (n = 9) including water (n = 27) and sediment (n = 27) in the Palk Bay, India to understand the metal pollution due to prevailing natural and anthropogenic activities. Pollution indices like metal index (MI), geoaccumulation index (Igeo), contamination factor (CF), pollution load index (PLI) and potential ecological risk (PER) were calculated based on the background/reference value. The values of MI index indicated that water was free of metals, whereas Igeo, CF, PLI and PER indicated moderate contamination of sediment in monsoon. Cadmium concentrations were the highest irrespective of the indices (Igeo: 0.04-1.42, Cf: 0.36-0.74, PLI: 0.36-0.74, and PER: 76.89-143.36) indicating moderate pollution. The Principal Component Analysis (PCA) affirmed that Cd was positively correlated with stations indicating anthropogenic sources of Cd contamination.