Remote sensing of seasonal changes and disturbances in mangrove forest: a case study from South Florida

Abstract

Knowledge of the spatial and temporal changes caused by episodic disturbances and seasonal variability is essential for understanding the dynamics of mangrove forests at the landscape scale, and for building a baseline that allows detection of the effects of future environmental change. In combination with LiDAR data, we calculated four vegetation indices from 150 Landsat TM images from 1985 to 2011 in order to detect seasonal changes and distinguish them from disturbances due to hurricanes and chilling events in a mangrove‐dominated coastal landscape. We found that normalized difference moisture index (NDMI) performed best in identifying both seasonal and event‐driven episodic changes. Mangrove responses to chilling and hurricane events exhibited distinct spatial patterns. Severe damage from intense chilling events was concentrated in the interior dwarf and transition mangrove forests with tree heights less than 4 m, while severe damage from intense hurricanes was limited to the mangrove forest near the coast, where tree heights were more than 4 m. It took 4–7 months for damage from intense chilling events and hurricanes to reach their full extent, and took 2–6 yr for the mangrove forest to recover from these disturbances. There was no significant trend in the vegetation changes represented by NDMI over the 27‐yr period, but seasonal signals from both dwarf and fringe mangrove forests were discernible. Only severe damage from hurricanes and intense chilling events could be detected in Landsat images, while damage from weak chilling events could not be separated from the background seasonal change.

Temperature thresholds for black mangrove (Avicennia germinans) freeze damage, mortality and recovery in North America: Refining tipping points for range expansion in a warming climate

“…For example, chilling temperatures (i.e. 0–3°C) in South Florida were sufficient to cause damage to L. racemosa and R. mangle individuals (Ross et al, ; Zhang, Thapa, Ross, & Gann, ).…”

Investigating Sub-tropical Community Resistance and Resilience to Climate Disturbance

“…And, as climate disturbance regimes change in the future, their role in influencing communities will change with it. Changes to communities from climate disturbance can have important consequences for services provided by natural systems, such as the provisioning of fish and wildlife (Stevens et al 2016), agriculture (Downton & Miller 1993), coastal storm protection (Zhang et al 2016), and many others. These studies improve our mechanistic understandings of how two types of climate disturbances can affect sub-tropical communities, and provides a framework of research to build on, especially related to those indirect consequences of these community changes, such as changes to predator prey interactions that could be studied in the future.…”

“…In mangrove forest patches in subtropical China, Liu et al (2012) came to a similar conclusion: mangroves located on the leeward sides of hills suffered minimal damage following the 2008 cold spell relative to those on the windward side. In a similar fashion, subtle changes in elevation that may trap cool air in addition to distance to oceans that can act as a heat source and alter mangrove cross-patch forest resistance in both sub-tropical China and the U.S. (Liu et al 2014;Zhang et al 2016;Chen et al 2010Chen et al , 2016.…”

“…I first used a long-term, albeit coarse spatial resolution approach, to capture temperature variation across the three zones during every cold disturbance that affected the region from 2003-2012 (window based off of data availability, # of cold disturbances =22). Second, I examined temperature changes at higher spatial resolutions (3-7 sensors per zone, 19 sensors total), during the extreme 2010 spell, one moderate event (January 2008) and another moderate spell (December 2010) that resulted in negative effects on tropical species Zhang et al 2016).…”

“…Thus, as a supplement to our longer-term analysis, and to potentially account for finer scale spatial patterns in temperatures, I conducted a higher spatial resolution analysis of water temperatures. These disturbances occurred in January of 2008, January 2010 (ECE), and December 2010, and all resulted in some negative impact to tropical species Blewett and Stevens 2014;Zhang et al 2016). Though these events incurred ecological change, they differed in both their intensity (degree of coldness) and duration (number of days temperatures remained at stressful levels for tropical species).…”