Climate change is leading to an increase in the frequency and intensity of tropical Atlantic hurricanes. How ecosystems will respond to an increase in intense hurricanes is unclear, but C and nutrient dynamic changes could have broad-scale implications for local, regional, and global biogeochemical cycles. Hurricane Maria, a Category 4 storm, made landfall in southeastern Puerto Rico on Sept. 20, 2017 and passed over the Luquillo Experimental Forest (LEF) with wind speeds of up to 155 miles per hour. The storm led to widespread canopy damage and organic debris deposition on the soil surface. We used existing research plots from the Canopy Trimming Experiment (CTE), a hurricane-simulation experiment in the LEF that has been ongoing since 2002, and a running sensor field measuring belowground variables to test hypotheses surrounding how Hurricane Maria shifted biogeochemical cycling. In these plots, we quantified the amount of litter deposited on the soil surface as a result of Hurricane Maria, conducted monthly soil sampling and recorded soil abiotic conditions. Monthly soil samples (0-10 cm depth; 1 m depth quarterly) were sampled for C, N and P variables, Fe species, and pH. Soil moisture, temperature and oxygen probes tracked belowground abiotic conditions over time (0-15 cm).
Results/Conclusions
Hurricane Maria led to a large deposition of green leaf litter and woody debris: we found that non-woody debris decomposed quickly over the first two months after deposition. There was a large increase in soil temperature after the hurricane (2 +/- 0.3 degrees C change), which we attribute to a decrease in canopy cover and an associated increase of solar radiation reaching the forest floor; this temperature effect resolved ~3 weeks after the hurricane. Soil moisture saw a large initial increase (25% increase +/- 4%) after Hurricane Maria which resolved within a month, while soil oxygen did not see major changes. Changes in soil oxygen and moisture were accompanied by changes to soil Fe species and pH, with monthly monitoring of both for longer-term impacts, along with CNP variables, ongoing. Previous data and modeling results suggest that short-term dynamics are likely to be critical for understanding patterns of long-term change. The presence of research plots with known disturbance history and a wealth of pre-Hurricane Maria in Puerto Rico data provide an unprecedented opportunity to test hypotheses regarding controls on biogeochemical cycling after single and repeated disturbances. This type of work will be critical as climate change and associated disturbances progress.