The distribution, fate, and effects of human and veterinary antibiotics in the environment have been the subject of intense investigation for nearly two decades. Studies show that the structure and function of microbial communities in soil and sediment are modified by antibiotic exposure but the resulting impact on biogeochemical processes is poorly understood. This review summarizes the most recent data on the present use and physicochemical properties of human and veterinary antibiotics and provides an overview of their occurrence in soil and sediment. This is followed by an examination of the potential effects of antibiotics on microbial nitrogen turnover and methodological approaches to measuring the effects of antibiotics on nitrification and denitrification. Recent studies identified six major classes of antibiotics in soil and sediment, occurring at concentrations between ng·kg⁻¹ and mg·kg⁻¹. Among these, tetracycline and fluorquinolone antibiotics are the most resistant to degradation and leaching and may accumulate to high concentrations (mg·kg⁻¹) in terrestrial environments. Less persistent compounds such as the sulfonamides are often detected at lower concentrations (ng·kg⁻¹ to μg·kg⁻¹) but their occurrence is also reported more frequently. Only 26 studies were found that investigated the effects of antibiotics on microbial nitrogen cycling. Some antibiotics had no observable effect on nitrogen redox activity in soil and sediment while others appeared to increase or decrease rates of reaction. This lack of consensus could be attributed to a number of different variables including antibiotic dose, method of antibiotic application, variations in the microbial community structure, or method of quantification. We conclude by recommending that future studies adopt a more comprehensive approach to report on changes of the microbial community structure and function as well as the short- and long-term impacts of antibiotics on the accumulation and loss of nitrogen pollutants.

Exposure to sub-inhibitory concentrations of antibiotics has been shown to alter the metabolic activity of micro-organisms, but the impact on soil denitrification and N₂O production has rarely been reported. In this study, incubation and column transport experiments were conducted on soils exposed to as many as four antibiotics in the ng·kg⁻¹ range (several orders of magnitude below typical exposure rates) to evaluate the impact of ultralow dose exposure on net nitrate losses and soil N₂O flux over time. Under anaerobic incubation conditions, three antibiotics produced statistically significant dose response curves in which denitrification was stimulated at some doses and inhibited at others. Sulfamethoxazole in particular had a stimulatory effect at ultralow doses, an effect also evidenced by a near 17% increase in nitrate removal during column transport. Narasin also showed evidence of stimulating denitrification in anaerobic soils within 3 days of exposure, which is concurrent to a statistically significant increase in N₂O flux measured over moist soils exposed to similar doses. The observation that even ultralow levels of residual antibiotics may significantly alter the biogeochemical cycle of nitrogen in soil raises a number of concerns pertaining to agriculture, management of nitrogen pollution and climate change and warrants additional investigations.

Coral reefs are among the most biologically diverse ecosystems on Earth. In the last few decades, a combination of stressors has produced significant declines in reef expanse, with declining reef health attributed largely to thermal stresses. We investigated the correspondence between time-series satellite remote sensing-based sea surface temperature (SST) datasets and ocean temperature monitored in situ at depth in coral reefs near La Parguera, Puerto Rico. In situ temperature data were collected for Cayo Enrique and Cayo Mario, San Cristobal, and Margarita Reef. The three satellite-based SST datasets evaluated were NOAA’s Coral Reef Watch (CoralTemp), the UK Meteorological Office’s Operational SST and Sea Ice Analysis (OSTIA), and NASA’s Jet Propulsion Laboratory (G1SST). All three satellite-based SST datasets assessed displayed a strong positive correlation (>0.91) with the in situ temperature measurements. However, all SST datasets underestimated the temperature, compared with the in situ measurements. A linear regression model using the SST datasets as the predictor for the in situ measurements produced an overall offset of ~1 °C for all three SST datasets. These results support the use of all three SST datasets, after offset correction, to represent the temperature regime at the depth of the corals in La Parguera, Puerto Rico.