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.

过去几十年的多份出版物认为，加利福尼亚湾是一个生物多样性和生产力高的地区。然而，加利福尼亚湾的生态系统对气候干扰和人为压力源的复原力仍然缺乏探索。基于生态指标评估生态系统恢复力的一种方法是分析关键环境变量的连续记录。在这里，我们分析了海面叶绿素a浓度的卫星时间序列（Chl- a) 过去二十年（1997-2020 年）和从加利福尼亚湾中部（2005-2019 年）获得的水文数据，以检测突然转变（临界点）和时间趋势的变化及其与最突出的气候模式的关联太平洋东北部的变化。此外，基于关键的“减速理论”，我们估计了卫星海面Chla-a的自相关时间（AcT）和标准差（SD），作为弹性指标（RI），用于监测预警是否信号预测气候变化的任何影响。我们观察到 2012 年之前 SST 出现明显的负趋势，这与太平洋年代际振荡 (PDO)、厄尔尼诺莫多基 (EMI) 和太平洋经向模式 (PMM _{SST ) 的年代际和多年变化模式有关}）。相比之下，2012 年后至 2017 年期间的正 SST 趋势与东北太平洋的多年变暖事件有关，该事件在 2015-2016 年强烈的厄尔尼诺现象期间达到顶峰。这些趋势对寒冷（11 月至 4 月）和温暖（6 月至 10 月）季节的叶绿素-a 反应进行了不同的调节，与 2012 年的政权转变一致。关键的过渡预警信号描绘了在使用在 Chl- a _Sat时间序列中增加 SD ，但在大多数情况下，AcT 仍然提供了放缓的有效预测指标。GAM 结果表明，影响 Chla- a的主要气候变率模式是 PMM _SST。EMI、NPGO 和 PDO 模式对 Chl- 的影响较小a比 PMM _SST。对加利福尼亚湾中部地区高频卫星记录的监测提供了对时间趋势及其与气候变率模式的关联的洞察。它代表了将 RI 应用于弹性监控的有效性的指标，可用于为资源管理决策提供信息。