Abstract

Environmental temperature is a widely used variable to describe weather and climate conditions. The use of temperature anomalies to identify variations in climate and weather systems makes temperature a key variable to evaluate not only climate variability but also shifts in ecosystem structural and functional properties. In contrast to terrestrial ecosystems, the assessment of regional temperature anomalies in coastal wetlands is more complex since the local temperature is modulated by hydrology and weather. Thus, it is unknown how the regional free-air temperature (TFree) is coupled to local temperature anomalies, which can vary across interfaces among vegetation canopy, water, and soil that modify the wetland microclimate regime. Here, we investigated the temperature differences (offsets) at those three interfaces in mangrove-saltmarsh ecotones in coastal Louisiana and South Florida in the northern Gulf of Mexico (2017–2019). We found that the canopy offset (range: 0.2–1.6°C) between TFree and below-canopy temperature (TCanopy) was caused by the canopy buffering effect. The similar offset values in both Louisiana and Florida underscore the role of vegetation in regulating near-ground energy fluxes. Overall, the inundation depth did not influence soil temperature (TSoil). The interaction between frequency and duration of inundation, however, significantly modulated TSoil given the presence of water on the wetland soil surface, thus attenuating any short- or long-term changes in the TCanopy and TFree. Extreme weather events—including cold fronts and tropical cyclones—induced high defoliation and weakened canopy buffering, resulting in long-term changes in canopy or soil offsets. These results highlight the need to measure simultaneously the interaction between ecological and climatic processes to reduce uncertainty when modeling macro- and microclimate in coastal areas under a changing climate, especially given the current local temperature anomalies data scarcity. This work advances the coupling of Earth system models to climate models to forecast regional and global climate change and variability along coastal areas.

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