Temporal variability of satellite chlorophyll-a as an ecological resilience indicator in the central region of the Gulf of California

Multiple publications over the past decades argue that the Gulf of California is a region with high biological diversity and productivity. However, ecosystem resilience to climate disturbances and anthropogenic stressors in the Gulf of California remains poorly explored. One method to assess ecosystem resilience based on ecological indicators is the analysis of continuous records of critical environmental variables. Here we analyze satellite time-series of sea surface chlorophyll-a concentration (Chl-a) over the past two decades (1997–2020) and hydrographic data obtained from the central Gulf of California (2005–2019) to detect abrupt transitions (tipping points) and shifts in the temporal trends and their association with the most prominent modes of climate variability in the northeastern Pacific. In addition, based on the critical “slow-down theory”, we estimated the autocorrelation time (AcT) and standard deviation (SD) of satellite sea surface Chl-a, as a resilience indicator (RI), to monitor whether early-warning signals anticipate any impacts of climate change. We observed a clear negative trend in SST in the pre-2012 period, related to decadal and multiannual modes of variability of the Pacific decadal Oscillation (PDO), El Niño Modoki (EMI), and Pacific Meridional Mode (PMM_SST). In contrast, a positive SST trend in the period post-2012 to 2017 was associated with the multiannual warming event in the northeastern Pacific that peaked during the intense 2015–2016 El Niño. These trends differentially regulate the Chl-a response during the cold (November to April) and warm (June to October) seasons, in line with the shift of regime in 2012. The critical transition early-warning signal depicted better consistency in the use of increasing SD in Chl-a_Sat time series, but still, AcT provides an effective predictor of a slowdown in most cases. GAM results showed that the main mode of climate variability that affects Chl-a was PMM_SST. EMI, NPGO, and PDO modes had a less significant influence on Chl-a than PMM_SST. The monitoring of high-frequency satellite records in the Gulf of California central region provided insight into temporal trends and their association with modes of climate variability. It represents an indicator of the effectiveness of the application of RIs for resilience monitoring that can be used to inform resource management decisions.