Spatiotemporal Dynamics of Marine Heatwaves and Ocean Acidification Affecting Coral Environments in the Philippines

Abstract

The coral reefs in the Philippines are facing an unprecedented crisis. This study, based on a comprehensive analysis of marine heatwaves (MHWs), degree heating weeks (DHWs), and ocean acidification (OA) indices derived from satellite observations and reanalysis data, reveals how thermal stress and OA have progressively eroded coral ecosystems from 1985 to 2022. This study analyzed 12 critical coral habitats adjacent to the Philippines. The monthly average sea surface temperature (SST) in the study area ranged from 26.6 °C to 29.3 °C. The coast of Lingayen Gulf was identified as the most vulnerable coral reef site in the Philippines, followed by Davao Oriental and Polillo Island. The coast of Lingayen Gulf recorded the highest total MHW days in 2022, amounting to 293 days. The coast of Lingayen Gulf also reached the highest DHW values in July and August 2022, with 8.94 °C weeks, while Davao Oriental experienced the most extended average duration of MHWs in 2020, lasting 90.5 days per event. Large-scale climate features such as the El Niño–Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO) significantly influenced the study area’s SST anomalies and MHW events. High-risk coral bleaching periods, such as 1988–1989, 1998–1999, 2007–2008, and 2009–2010, were characterized by transitions from El Niño and positive PDO phases, to La Niña and negative PDO phases. However, since 2015, global warming has led to high cumulative heat stress without specific climate background patterns. We propose a Coral Marine Environmental Vulnerability Index (CoralVI) to integrate the spatiotemporal dynamics of warming and acidification and their impacts on coral habitats. The data show a rapid increase in the marine environmental vulnerability of coral habitats in the Philippines in recent years, extending to almost the entire coastline, posing significant threats to coral survival.

1. Introduction

Coral reefs face two significant challenges due to climate change: escalating sea surface temperatures (SSTs) and increasing ocean acidity. Both factors impact coral growth, reproduction, and survival [1,2]. Since the Industrial Revolution in the mid-18th century, anthropogenic activities such as burning fossil fuels and deforestation have been the primary sources of continuous carbon dioxide (CO₂) emissions into the atmosphere, significantly contributing to global warming [3]. The oceans absorb about 90% of excess heat from the greenhouse effect, with 52% absorbed by the upper ocean, leading to increased SSTs [4]. Global warming causes oceans to absorb more heat, resulting in higher SSTs and changes in coral reef ecosystems in response to the shifting climate. An increase of approximately 1–2 °C above the long-term average for at least a week can disrupt the symbiotic relationship between the coral host and its algal symbiont, leading to coral bleaching and, in severe cases, coral mortality [5,6,7,8,9,10].

The marine heatwave (MHW) index measures the significant warming of SSTs. It refers to anomalous ocean warming events lasting at least five days, defined based on the 90th percentile of a 30-year baseline period [11]. As anthropogenic climate change persists and ocean warming escalates, global research on MHWs and their drivers becomes increasingly pertinent [4,12]. Understanding and mitigating the potential risks to marine organisms and ecosystems is essential. MHWs are becoming more frequent, enduring longer, and intensifying in strength due to climate change, extending their reach to more expansive geographical areas at an accelerating pace [13,14,15]. Additionally, coral habitats are affected by ocean acidification (OA), where seawater becomes less alkaline due to the absorption of large amounts of anthropogenic CO₂ from the atmosphere. Increasing CO₂ concentrations in ocean waters lowers the pH and influences the surface partial pressure of CO₂ (spCO₂), which indicates the amount of CO₂ present at the ocean’s surface. The atmospheric partial pressure of CO₂ may not necessarily match spCO₂ due to regional internal oceanic processes and biological activity. However, anthropogenic sources can alter CO₂ flux patterns and disrupt the natural chemical equilibrium of the ocean’s carbonate system [16,17]. Coral reefs rely on calcium carbonate precipitation for reef growth, physiological processes, and adaptation. Rising SST and increasing acidity influence calcification rates, chemical and biological dissolution, and the overall structural integrity of reef communities through their calcification and biomineralization processes [1,6]. Ocean warming and OA, driven by increased atmospheric CO₂, pose significant threats to coral reef ecosystems, inducing stress that leads to coral bleaching and severe socioeconomic consequences [18,19,20,21,22].

This study focuses on the waters surrounding the Philippines, spanning 2°N to 24°N and 114°E to 130°E. The Philippines, situated in the Indo-West Pacific, is known for its abundant biodiversity and rich marine life, including coral reefs and diverse marine organisms, covering an area of approximately 25,000 km². Most reefs are fringing reefs, typically found near coastal areas and shorelines. They provide socioeconomic benefits such as habitats for marine organisms, buffers against waves and typhoons, and opportunities for tourism-related activities [23]. The early assessment of coral reefs in the Philippines began in the 1970s, and continuous efforts in reef monitoring have persisted throughout the years. While many past reports and studies focused on more minor scales and were biased toward marine-protected areas, larger-scale assessments of Philippine reefs have emerged [24,25]. Most large-scale research on coral reefs in the Philippines focuses on hard coral cover and coral genetic diversity. In contrast, studies on coral bleaching and acidification are usually conducted on a smaller scale, often targeting selected areas or specific species [26,27]. Research on MHWs in the Philippines and their impacts on coral ecosystems under the influence of climate factors remains limited [28,29], and while emerging studies on MHWs in surrounding areas, such as the South China Sea (SCS), are increasing, they are still insufficient to provide a comprehensive understanding [30,31,32]. Additionally, although research on OA in the Philippines exists, comprehensive large-scale assessments are still lacking [27,33]. Several major ocean currents traverse the Philippines: the SCS Current to its west, the Kuroshio Current (KC) to its north and east, and the Mindanao Current (MC) to its east [34]. Additionally, it is influenced by the Indonesian Throughflow (ITF) to its south [35]. The SCS has a seasonal circulation pattern dominated by the monsoon [36,37,38], with a cyclonic circulation pattern during winter (December to February), an anticyclonic circulation pattern during summer (June to August), and multiple significant eddies [39]. The KC and MC originate from the westward North Equatorial Current (NEC), which bifurcates after reaching the Philippine coasts at 10°N–20°N [40].

Monitoring coral reefs through in situ measurements presents challenges, including high costs, time constraints, and limited geographical coverage. Remote sensing technology provides valuable support due to its spatial and temporal capabilities. However, its accuracy is limited by integrating multiple data sources and methods. Despite each method’s advantages, they can complement each other and yield effective results in coral reef ecosystem monitoring [41]. This study focuses on two phenomena directly impacted by increased atmospheric CO₂ concentrations: ocean warming and OA. It uses information from the MHW index, pH values, spCO₂ values, and the coral bleaching index (Degree Heating Week, DHW) to conduct a large-scale assessment of ocean warming and OA in the Philippine coral reef areas. The aim was to identify high-risk or vulnerable areas prone to coral bleaching. To achieve these objectives, the study set the following critical objectives from a marine sustainability perspective: (1) utilizing satellite and reanalysis data, conduct a large-scale assessment of MHWs, OA, and coral bleaching indices around the waters of the Philippines, mainly focusing on coral reef sites from 1985 to 2022; (2) combine MHW, DHW, and OA parameters to map and identify high-risk trends of potential coral bleaching events and vulnerable coral reef areas; and (3) understand the climatic driving patterns behind these marine environmental geographic characteristics. The results can serve as a basis for marine researchers conducting field monitoring and provide decision-makers with references for coral bleaching mitigation measures.

2. Data and Methods

Coral habitats along the coast of the Philippines are categorized into three groups based on varying marine environmental conditions to explore their thermal and biogeochemical responses. The MHW indices represent states of high-SST anomalies relative to climatic norms in the region, while the DHW indices indicate the potential for coral bleaching due to thermal stress. The OA indices focus on the progressively acidifying marine environment. Combining these three indicators calculates a vulnerability assessment value for the coral environment. Additionally, climate conditions such as El Niño–Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) are utilized to understand the large-scale climate variability characteristics affecting the marine environmental conditions in the study area. The datasets are summarized in

Table 1. Summary of the datasets used in this study.

Dataset Category	Parameter	Source	Temporal Coverage	Spatial Resolution	Purpose of the Study
Ocean Thermal Data	SST	NOAA Coral Reef Watch	1985–2022	5 km	Analyze long-term SST trends
	DHW				Identify thermal stress and bleaching risk
	MHW Indices				Detect extreme thermal events
Ocean Current	Zonal and Meridional Currents	CMEMS, Copernicus	1993–2022	0.25°	Analyze ocean circulation patterns
Biogeochemistry Dataset	spCO2	CMEMS, Copernicus	1993–2022	0.25°	Analyze oceanic carbon dynamics
	pH				Evaluate ocean acidification trends
Climate Patterns	Oceanic Niño Index	NOAA CPC	1985–2022	Monthly	Identify ENSO events
	PDO Index	NOAA NCEI	1985–2022	Monthly	Identify PDO impacts

, with details provided in the corresponding subsections and Figure A1.

2.1. Study Area

Twelve coral reef sites—ten along the coast of the Philippines and two along the coast of Taiwan—were selected for a detailed analysis of potential impacts on coral reefs (Figure 1). The coral reef sites in this study were chosen based on the identified reef sites [19,21,23,42]. These sites were categorized into three groups based on their regions [29] and their areas’ prevalent ocean circulation patterns. Group I (16°N to 24°N and 115°E to 126°E) covers the northern region of the study area, heavily influenced by the KC intrusion into the SCS (Figure 1). This group includes coral reef sites along the coast of Nanwan Bay (Site A; 21.925°N, 120.775°E), Pratas Reef (Site B; 20.725°N, 116.725°E), Batanes (Site C; 19.575°N, 121.925°E), and Cagayan Province (Site D; 18.375°N, 122.375°E). Group II (8°N to 18°N and 114°E to 121°E) is situated on the western side of the study area, particularly the West Philippine Sea (WPS), and is influenced by the circulation patterns of the SCS. It encompasses sites along the coast of Lingayen Gulf (Site E; 16.475°N, 119.875°E), Occidental Mindoro (Site F; 12.725°N, 120.425°E), Busuanga (Site G; 12.325°N, 119.825°E), and El Nido (Site H; 11.275°N, 119.325°E). Group III (5°N to 20°N and 121°E to 130°E) focuses on the eastern region of the study area, where the NEC bifurcates into the KC and MC. This group includes coral reef sites along the coast of Polillo Island (Site I; 15.025°N, 122.075°E), Catanduanes (Site J; 13.625°N, 124.375°E), Siargao (Site K; 10.075°N, 126.075°E), and Davao Oriental (Site L; 6.225°N, 126.175°E).

2.2. Ocean Thermal Data

2.2.1. Sea Surface Temperature

This study utilized the daily global SST product, CoralTemp, provided by the National Oceanic and Atmospheric Administration (NOAA) Coral Reef Watch (CRW). The data span 1 January 1985 to the present, and feature a spatial resolution of 0.05° × 0.05°. This SST product incorporates near-real time and reprocessed data from NOAA’s National Environmental Satellite, Data, and Information Service (NESDIS), as well as reanalysis data from the United Kingdom Met Office’s Operational SST and Sea Ice Analysis (OSTIA) products [9,43].

2.2.2. Degree Heating Weeks and Marine Heatwave Indices

According to the SST dataset mentioned in the previous section, NOAA CRW has calculated the climatological maximum monthly mean (MMM) SST based on the climatological period from 1985 to 2012 [44]. This represents the warmest of the 12 monthly average climatology SST values within each 5 km grid worldwide. Since corals begin to experience stress and initiate bleaching when SST exceeds the MMM by one °C [45], the bleaching threshold (also known as HotSpot, Hs) is defined as the SST at a location exceeding the MMM value by 1 °C. The cumulative thermal stress over the past 12 weeks in a region, measured as the DHW value for a given day i in units of °C-weeks, is then calculated as ${DHW}_i={\sum }_{j=i-83}^i\left({Hs}_j/7\right),\mathrm{where}{Hs}_j\ge 1$.

According to global underwater field observations from professional scientific surveys and informal monitoring reports, NOAA CRW categorizes the DHW values into six risk warning levels associated with potential bleaching and mortality scenarios [9,46,47]: Possible Bleaching (Warning), Reef-Wide Bleaching (Level 1), Reef-Wide Bleaching with Mortality of Heat-Sensitive Corals (Level 2), Multi-Species Mortality (Level 3), Severe Multi-Species Mortality (>50% of corals) (Level 4), and Near-Complete Mortality (>80% of corals) (Level 5). This metric has provided alerts for significant global large-scale coral bleaching events [7,8,10,48]. Therefore, the purpose of the DHW index is not to predict coral bleaching, but to provide a scenario of the potential conditions that the coral ecosystem in the area might experience under the cumulative thermal stress accumulated over the past three months.

In recent years, global warming has increased the frequency and intensity of MHWs, and some studies have begun to indicate that rapid increases in thermal stress over short periods may significantly impact coral bleaching [10,21,49,50,51,52]. MHW indices quantify the state of abnormally high SST in a marine area. An MHW event is the daily NOAA CRW SST value at a particular location exceeding the 90th climatological percentile threshold for at least five consecutive days. Events separated by less than a two-day gap are considered a single event. The climatological threshold was calculated over 30 years, from 1985 to 2014, using an 11-day moving window [11,15,53]. Six MHW indices were defined to characterize MHW events: frequency (F), duration (D), total MHW days (D_TOT), mean intensity (I_MEAN), maximum intensity (I_MAX), and cumulative intensity (I_CUM). The definition and calculation of each index are listed in

Table 2. The definitions, calculations, and units of the six MHW indices. In the formulas, ds and de represent an MHW event’s start and end dates, respectively; SST is the daily SST value, and clim is the climatological value corresponding to the day of the SST value.

MHW Index	Definition	Formula	Unit
F	Total MHW events in a year	$F=N$	Times
D	Number of days from the start to the end of an MHW event	$D=d_e-d_s+1$	Days
${\mathit{D}}_{\mathit{T}\mathit{O}\mathit{T}}$	Total MHW days in a year	$D_{TOT}={\displaystyle \sum _{i=1}^N}{D}_i$	Days
IMEAN	Average SST anomaly in an MHW event	$I_{MEAN}={\displaystyle \frac{{\sum }_{t=ds}^{de}[SST\left(t\right)-clim\left(t\right)]}{d_e-d_s+1}}$	°C
IMAX	Maximum SST anomaly in an MHW event	$I_{MAX}=max\left[SST\left(t\right)-clim\left(t\right)\right]$, where $d_s\le t\le d_e$	°C
ICUM	Sum of the intensity anomalies in an MHW event	$I_{CUM}={\int }_{ds}^{de}[SST\left(t\right)-clim\left(t\right)]dt$	°C days

. These indices were explicitly curated to assess the nature of MHW events in the study area, providing insights into their frequency, duration, and intensity, thus enabling a comprehensive analysis of their characteristics.

2.3. Ocean Current

Ocean current data illustrate the characteristics of regional ocean circulation and the changes influenced by different climate patterns. Monthly global ocean surface current data from 1993 to 2022 were obtained from the Copernicus Marine Environment Monitoring Service (CMEMS), with a spatial resolution of 0.25° × 0.25°. This level 4 dataset (CMEMS Global Total, Ekman, and Geostrophic Currents at the Surface and 15 m) includes reprocessed and near real-time global total velocity fields at the surface and 15 m levels derived from satellite, numerical models, and in situ data. The geostrophic component, comprising daily near-real-time geostrophic current from altimeter data, and Ekman components, including hourly near-real-time 10 m equivalent wind stress data from ERA5 and mixed layer depth data, were integrated to derive the final total velocity fields [54].

2.4. Biogeochemistry Dataset

The monthly ocean biogeochemistry data used in this study, such as surface pH and spCO₂ in seawater, are hindcast data from CMEMS, with a spatial resolution of 0.25° × 0.25°, covering the period from 1993 to 2022. The spCO₂ and pH values determine the OA level and trends in coral habitats. The dataset employs the Pelagic Interactions Scheme for Carbon and Ecosystem Studies (PISCES) biogeochemical model, with atmospheric and oceanic forcing from ECMWF’s ERA-Interim and Mercator-Ocean’s GLORYS2V4-FREE, respectively. This dataset’s spCO₂ and pH values effectively reflect the biogeochemical characteristics of the coral’s adjacent sea area [21]. The pH and spCO₂ values presented in this study are those closest to the coral reef sites used explicitly in this research, given that the biogeochemistry product has a lower spatial resolution than the SST data.

2.5. Coral Marine Environmental Vulnerability

Research indicates that thermal stress and coral bleaching feedback exhibit regional variability [55]. This variability is associated with differences in the thermal tolerances of coral species [56], their adaptation [57,58], and species composition [59] in each habitat. However, due to the challenges of obtaining long-term observational samples and the shortage of researchers, relying solely on in situ survey data is not advisable for validating or generating coral bleaching prediction models. For this reason, we propose a comprehensive marine environmental vulnerability assessment method to help identify and protect high-vulnerability coral reef areas. The Coral Marine Environmental Vulnerability Index (CoralVI) is a simple and rapid indicator for assessing the bleaching risk of coral habitats, utilizing ocean physics and chemical characteristics to evaluate coral bleaching vulnerability [2,60,61,62,63,64,65].

We used a weighted average method to calculate the monthly or yearly CoralVI: $CoralVI=\left(W_{DHW}\times I_{DHW}\right)+\left(W_{MHW}\times I_{MHW}\right)+\left(W_{OA}\times I_{OA}\right),$ where $W$ represents the weight, and $I$ represents the standardized index value. The DHW index directly reflects whether the accumulated thermal stress on corals exceeds the threshold and should be given a higher weight. The MHW index also significantly impacts coral reefs, considering that there may be short-term rapid recovery events; thus, it is given secondary weight. The OA index impacts coral reefs’ calcification process and overall health, but its impact is more indirect and long-term than thermal stress. Therefore, the weights are suggested as follows: $W_{DHW}=0.5$, $W_{MHW}=0.35$, and $W_{OA}=0.15$. $I_{DHW}$ is calculated as the proportion of days in a year/month with DHW $\ge$ 4 ($I_{DHW}={\displaystyle \frac{DaysofDHW\ge 4}{Totaldays}}$); $I_{MHW}$ is calculated as the proportion of days in a year/month with MHW ($I_{MHW}={\displaystyle \frac{MHWdays}{Totaldays}}$); and for $I_{OA}$, considering that lower pH values indicate more severe OA, inverse standardization is used to reflect vulnerability ($I_{OA}={\displaystyle \frac{{pH}_{max}-pH}{{pH}_{max}-{pH}_{min}}}$).

Based on the calculated comprehensive vulnerability index, we classify the corals in the study area into different vulnerability levels as follows: 0.4–1.0: extremely high vulnerability; 0.3–0.4: high vulnerability; 0.2–0.3: moderate vulnerability; and 0.0–0.2: low vulnerability. For example, if a short-term MHW event persists throughout the month, the coral habitat would be classified as a high-vulnerability month. If the month experiences both long-term accumulated DHW values and the impact of a short-term MHW event, it would be classified as extremely high vulnerability. Without significant thermal stress, the coral habitat would be considered moderate or low vulnerability.

2.6. Climate Patterns

The Oceanic Niño Index (ONI) was used to classify the ENSO events in the Niño 3.4 region (5°N–5°S, 120–170°W). The running 3-month mean of SST anomalies in this region were used to define conditions as El Niño (EN), La Niña (LN), or Normal (N). This study assigned the value from the running 3-month mean to the middle month. For example, the mean for December, January, and February (DJF) was classified as the value for January. Additionally, the PDO index from the National Centers for Environmental Information (NCEI) was utilized in this study. The NCEI PDO index represents monthly average SST anomalies across the northern Pacific Ocean region, from 20°N to 70°N. These anomalies are derived from NOAA’s extended reconstructed SST, obtained through leading Empirical Orthogonal Function (EOF) analysis. The resulting EOF patterns were regressed against the PDO index, particularly for the overlapping periods. Monthly global mean SSTs were initially removed to address long-term trends. Subsequently, the SST anomalies were linearly regressed against the time series of the associated principal component to determine the PDO patterns [66].

3. Results

3.1. Spatiotemporal Variation Characteristics of Ocean Currents and SST

The leading mode of EOF analysis of ocean current direction provided insights into the movement of ocean waters from 1993 to 2022 (Figure 2a,c). The leading mode of EOF analysis for ocean current velocity, based on original monthly data from 1993 to 2022, is shown in Figure 2b,d. The flow velocity variability in the KC and MC regions was exceptionally high, indicating that these currents significantly influence the major flow pathways within the study area. In contrast, the flow velocity in the western Philippine Sea was relatively stable. Overall, there is no significant interannual trend in flow speed. The bifurcation of the NEC into the northward KC and the southward MC occurred between 10 and 15°N, with an average position at approximately 12.5°N. The KC intrusion into the Luzon Strait (LS) occurred between 18 and 22°N, with westward flow reaching as far as 114°E. The main KC flowed northward along Taiwan’s eastern coast, while a KC branch invaded the Penghu Channel northward during fall and winter [67]. The southward flow of the MC split into the eastward North Equatorial Countercurrent (NECC) and the westward ITF [68] at around 126°E, with some flow from the ITF curving back into the NECC at around 5°N. More localized circulations can be observed near the coastal areas of the WPS. The SCS region had a seasonal circulation pattern dominated by the monsoon, characterized by a cyclonic circulation pattern during winter, an anticyclonic circulation pattern during summer, and multiple significant eddies [69].

The ocean flow field drived SST’s spatial characteristics, and SST variations were closely intertwined with occurrences of MHWs. Throughout the year, fluctuations in SST significantly influenced the frequency and intensity of MHW events. Understanding these changes is crucial for predicting and mitigating the impacts of thermal stress on coral reefs. The leading mode of EOF analysis on monthly SST values from 1985 to 2022, using both original (Figure 3a,c) and deseasonalized data (Figure 3b,d), illustrated the prevailing SST pattern in the study area. The EOF pattern of the original monthly mean SST showed significant seasonal changes accompanied by an increasing trend in temperature (Figure 3c). The geospatial feature distribution of SST presents the main SST equivalent areas composed of the KC, its branches, the SCS warm current, and the MC (Figure 3a). The removal of seasonality highlighted increased variance in SST variation observed in the 15–21°N region (Figure 3b).

Furthermore, the EOF analysis conducted on monthly SST values from 1985 to 2022 provided more profound insights into the spatiotemporal variations in SST (Figure A2). The principal component for all months showed an increasing trend, signifying continuous warming in the study region. In January, the warmer SSTs were observed at lower latitudes than higher latitudes, with KC intrusion evident in the LS, a pattern that continued until March. By April, there was a poleward shift in the western region, and by May, warming in the WPS, reaching until SCS, became apparent. Warming occurred on both sides in June, especially between 8°N and 16°N. July showed almost consistent warm SSTs across the study area, with the warmer side on the northeastern part at around 12–20°N, 120–125°E. The warmer area shifted to the Pacific area from the WPS around August and September, before reverting to the initial pattern by October and extending until December. Changes in the monthly spatial distribution can be attributed to the seasonal reversal of the western North Pacific monsoon [70,71].

3.2. The Spatiotemporal Characteristics of MHWs Experienced by Coral Habitats

Increased SST over the years and changes in spatial patterns are being observed due to climate change. As defined earlier, extreme temperature events in ocean waters cause MHWs. In Figure 4, the map displays the 38-year average of the MHW indices for the study area. More frequent MHWs were observed near the coastal regions, between the southwest of the Philippines and Borneo, and in the SCS. Among the coral reef sites, Occidental Mindoro (Site F) recorded the highest frequency of events in 2017, with 14 occurrences. Longer average durations were more commonly observed on the eastern side of the study area, especially off the coast of Mindanao. Additionally, Siargao (Site K) experienced the most extended average duration of MHW events in 2020, lasting 90.5 days. The average total MHW days distribution revealed a distinct pattern, with notably longer events observed along the pathway of the KC intrusion in the LS, the surrounding waters of Pratas Reef (Site B), and the Lingayen Gulf (Site E). Furthermore, Site E recorded the most significant total duration of MHW events among the coral reef sites, totaling 293 days in 2022. The spatial characteristics of the average intensity metrics showed similar distributions, with higher latitudes experiencing more intense events. Notably, Site B exhibited significant intensity metrics, achieving the maximum intensity (I_MAX) in 2016 and the highest average cumulative intensity (I_CUM) in 2021, with values of 1.91 °C and 87.13 °C-days/times, respectively. The analysis is divided into three subsections to fully understand the variation in MHWs and their impact on coral reefs in the study area. A closer examination of each group will offer a clearer understanding of the progression of the MHW indices and the coral habitats within them.

3.2.1. Coral Habitats near the Luzon Strait: Group I

The first group focused on the northern part of the study area, specifically the LS and the affected coral habitats. The MHW index time series for this group is shown in Figure 5a–f. The number of occurrences (F), each duration (D), and the annual cumulative number of days (D_TOT) of MHWs all showed an upward trend after 2015, with prominent peaks in several years, such as 1988, 1998, 2015, and 2021. However, the MHW average and maximum intensity did not change as the number of events increased. After 2015, the average annual number of MHW events experienced by the first group of coral habitats was 6.6, with an average duration of 20.3 days each and a total duration of 127.8 days.

The 38-year MHW daily duration shown in Figure 5g indicates that the southwest monsoon period pushes seawater, and the beginning of the summer season causes MHW events to start increasing in June and last until October, with a slight decrease in August, possibly related to the high climatological value of SST. The relatively high MHW at Pratas Reef (Site B) begins in November, caused by the strong intrusion of the warm KC into the LS [69,72], and continues until February. Pratas Reef, Batanes, and Cagayan Province (Sites B, C, and D) are all located on the main path of the KC invading the LS, while Nanwan Bay (Site A) is not on the KC path and has a sub-mesoscale cold eddy generated by topography, maintaining a low number of MHW days [19]. In 2021, the first group reached the peak of average duration (D, 60 days), total duration (D_TOT, 241 days), and cumulative intensity (I_CUM) at Site B. Figure 5h–m shows the MHW index for 2021, revealing the longer duration and higher intensity values observed in the area around Pratas Reef (Site B). Additionally, the path of the KC intrusion into the LS is very evident, especially in the higher MHW index values of frequency, average duration, total duration, and cumulative intensity.

3.2.2. Coral Habitats of the Western Philippines in the WPS: Group II

The second group focuses on the WPS and the coral habitats in this area, as shown in Figure 6a–f, which illustrate the MHW index characteristics of this group. An increasing trend was observed in the mean duration (D), total MHW days (D_TOT), and cumulative intensity (I_CUM) from 2011 onward, indicating that SSTs in the western Philippines are gradually warming, resulting in longer, and more intense MHWs. However, the MHW average and maximum intensity did not change significantly. Peaks in MHW index values were observed in 1988, 1998, 2010, 2017, and from 2020 onward. In particular, the Lingayen Gulf (Site E) has experienced longer and more intense events in recent years, with annual accumulated MHW days exceeding 200 from 2020 to 2022, reaching 293 days in 2022. Occidental Mindoro (Site F) has significantly more peaks in MHW frequency, reaching its highest value in 2017, with 14 events and 157 MHW days. El Nido (Site H) also experienced longer and more intense MHWs, especially in 2010 and 2020, with most MHW indices peaking in 2020. Figure 6g depicts the monthly duration of MHW days of Group II from 1985 to 2022. The average number of MHW days experienced by corals does not differ much from January to April, with Sites E and F having slightly more MHW days than Sites G and H. The number of MHW days began to increase significantly around May, which is related to the southwest monsoon period driving the flow of warm surface water in the WPS [73,74]. It reached a peak in June and July, then continued until October after a slight decrease in August. As the monsoon shifts from southwest to northeast, there was a significant decrease in MHW events in November, with Site E experiencing relatively more MHW days in December and January. This may be due to the intrusion of the KC into the LS in winter, which also affects the SCS circulations, with inflows located at cyclonic eddies (Luzon gyre) at 15–22°N [69,75]. Figure 6h–m shows the spatial distribution of the MHW index in 2020 near Site E, highlighting a higher average duration and cumulative intensity.

3.2.3. Coral Habitats of the Eastern Philippines in the Pacific: Group III

The third group focuses on the eastern side of the study area, specifically the Pacific region and its coral habitats. A clear increasing trend was observed in the average duration (D), total MHW days (D_TOT), and cumulative intensity (I_CUM) of MHW events in Group III (Figure 7a–f). Like the previous two groups, the average intensity (I_MEAN) and maximum intensity (I_MAX) did not change significantly. This group of coral habitats experienced significant MHW impacts in several years, including 1988, 1998, 2007, 2010, 2014, 2017, and 2020. Davao Oriental (Site L) exhibited the highest values in terms of duration, total MHW days, and cumulative intensity, followed by the coast of Polillo Island (Site I). Site L is affected by splitting the MC into the NECC and the Indonesian ITF and the backflow of the MC eddy to the NECC [68,76]. On the other hand, Site I is located at the bifurcation of the NEC and is the origin of the KC and MC [68,77]. In 2020, the average duration and cumulative intensity at Site L reached the highest values, which were 90.5 days and 71.64 °C days, respectively. In the same year, the total number of MHW days at Site I also reached the highest value, with 249 days. The MHW index distribution map for that year (Figure 7h–m) shows that events near Site L in the Pacific region and Davao lasted longer and were more intense, while the area near Site I had more frequent and longer total MHW days. The monthly duration in Group III (Figure 7g) shows the pattern of MHW days for the third group during the study period. The site I had more MHW days in certain months, such as January, April to June, and December, compared to the other three reef sites. A relatively short total duration is observed early in the year, especially in April, and then increased in May and June. The number of MHW days peaked from July to September and gradually decreased until December. The EOF analysis of SST (Figure A2) shows a warming shift from low to high latitudes starting in April due to the southwest monsoon. This may explain the shorter duration of MHW days in the third group during that month. A more consistent warming was observed in the study area around July, continuing into September when the southwest monsoon switched to the northeast monsoon, and the warm SST pattern returned to lower latitudes, coinciding with the peak of the third group.

3.3. Possibility of Coral Bleaching

Figure 8 shows DHW values for 12 coral habitats from 1985 to 2022. Thresholds of DHW of 4 and 8 are key indicators of potential coral bleaching and the severity of reef thermal stress. When DHW values exceed 4, the likelihood of coral bleaching increases; exceeding 8 indicates increased bleaching and expected coral death. Trends in DHW values show seasonal changes in coral bleaching potential at coral sites. Heat stress typically begins to rise in May, with peaks occurring for most coral sites during the summer months, from June to August. Critical heat stress persists into November at some coral sites. This seasonal trend emphasizes the cyclical impact of SST changes on corals, with the highest vulnerability reached during the summer months. Pratas Reef and Cagayan Province (Sites B and D) were observed to be the most vulnerable reef sites, with the potential to experience coral bleaching and death for a total of 12 years. Pratas Reef (Site B) accumulated 877 days, with the highest DHW value recorded in September 2020 at 12.35 °C weeks.

Table 3. Summary of the years for Sites A to L where the DHW values surpassed the DHW = 4 and DHW = 8 thresholds, with the number of days for each year shown in parentheses.

Coral Reef Site	4 ≤ DHW < 8	DHW ≥ 8
A	1998 (72), 2007 (51), 2020 (37), 2022 (48)	2020 (55), 2022 (47)
B	1998 (29), 2006 (18), 2007 (24), 2010 (70), 2015 (10), 2016 (64), 2017 (18), 2018 (22), 2019 (56), 2020 (64), 2021 (73), 2022 (41)	1998 (68), 2007 (69), 2016 (26), 2019 (28), 2020 (81), 2021 (56), 2022 (60)
C	1988 (5), 1998 (56), 2007 (69), 2010 (56), 2014 (60), 2016 (56), 2017 (83), 2019 (68), 2020 (65), 2022 (45)	1998 (28), 2016 (51)
D	1998 (69), 2007 (62), 2012 (17), 2014 (53), 2015 (27), 2016 (68), 2017 (86), 2018 (73), 2019 (65), 2020 (18), 2021 (71), 2022 (41)	2016 (55)
E	1998 (57), 2013 (50), 2016 (69), 2019 (72), 2020 (66), 2022 (46)	2016 (18), 2020 (33)
F	2016 (63), 2020 (63)	---
G	2010 (72), 2014 (75), 2015 (72), 2016 (5), 2022 (75)	---
H	2010 (80), 2020 (78)	---
I	1998 (40), 2007 (50), 2010 (56), 2014 (67), 2015 (65), 2016 (70), 2017 (77), 2019 (60), 2020 (63), 2022 (73)	2016 (17), 2019 (25)
J	1998 (48), 2014 (73)	---
K	1998 (47), 2014 (64), 2017 (43)	---
L	1998 (73), 2010 (98)	---

lists the years and days on which reef sites exceeded the threshold. In 1998, nine coral habitats exceeded the first threshold, except for Sites F, G, and H. Other years with at least half of the sites exceeding the first threshold include 2010, 2014, 2016, 2020, and 2022. Observations also show that coral reef sites north of 15°N (Sites A, B, C, D, E, and I) often suffered from higher thermal stress, frequently exceeding the threshold of 8, compared to sites south of 15°N (Sites F, G, H, J, K, and L), which experienced shorter critical thermal stress durations. The maximum total number of days in coral habitats at low latitudes ranged from 63 days (Occidental Mindoro, Site F) to 98 days (Davao Oriental, Site L), while at high latitude sites, it ranged from 87 days (Coast of Polillo Island, Site I) to 145 days (Pratas Reef, Site B).

These findings align with previous large-scale coral reef assessments, which have identified the Philippines as highly vulnerable to coral reef degradation due to increasing heat stress and low adaptive capacity [78]. Within Philippine waters, high-quality coral reefs (coral cover > 75%) have been steadily declining, while the proportion of degraded reefs (coral cover < 25%) has been increasing [78]. From 1978 to 2019, there were three major coral bleaching events in Philippine coral habitats, including those in 1998 [79], 2010 [78], and 2015–2017 [80]. The large-scale bleaching event in 1998 led to a decline in average coral cover from 39% in 1997 to 32% [78]. Between 2005 and 2010, the proportion of observations with less than 25% of coral cover reached 40% [78]. The survey report from 2015 to 2017 indicated that coral bleaching was observed in 36 out of 66 coastal and island locations (54%). A total of 326 reports were submitted between 2016 and 2017, with 201 documenting coral bleaching. Among the 201 confirmed coral bleaching reports, 79% were recorded in 2016 and 21% in 2017 [80]. One possible reason for the low-to-moderate bleaching incidence is that the average hard coral cover in sampled shallow reef areas less than 5 m deep was 22.8%, with no well-preserved reefs present [25]. Additionally, the previous large-scale bleaching events in 1998 and 2010 may have significantly reduced coral cover in the Philippines, potentially decreasing the cover of coral groups more susceptible to bleaching [80].

3.4. Coral Habitats Experiencing Gradual Ocean Acidification Trends

Understanding OA parameters, such as pH and spCO₂, is crucial for assessing the vulnerability of coral reefs to bleaching. Figure 9 displays the pH and spCO₂ values for each grouping from 1993 to 2022. The pH values at various locations showed significant seasonal fluctuations and long-term trends, fluctuating between 8 and 8.1 with an overall decreasing trend, indicating intensifying ocean acidification. Conversely, the spCO₂ values fluctuated between 300 and 420 μatm, showing an overall increasing trend, reflecting the ocean’s rise in carbon dioxide concentration. These trends suggest that the marine environment is being affected by the rising concentration of atmospheric carbon dioxide, leading to continued ocean acidification. This ongoing acidification weakens coral resilience and increases their susceptibility to environmental stressors. Generally, Group II (Figure 9c,d) exhibited a more acidic environment compared to Group I (Figure 9a,b) and Group III (Figure 9e,f). An annual cyclic pattern can be observed for both parameters. The pH typically reaches its lowest point between June and July, while spCO₂ generally peaks around the same time. Some sites, such as Sites B, H, J, and K, exhibited two peaks, with the larger one occurring in June and a smaller peak observed around October in some years. The lowest pH measurement was recorded at Site H in May 2020, at 7.99, while the highest spCO₂ value of 436.79 μatm was observed at Site B in July 2022. The time series for pH values in 2020 and spCO₂ values for 2022 can be seen in Figure 10. In both years, a relatively more acidic environment was observed from May to September. Group II became more acidic first, followed by Group III and then Group I, indicating a pattern of acidification across the regions.

EOF analysis was performed on the monthly original and deseasonalized pH and spCO₂ values from 1993 to 2022, as depicted in Figure 11, to understand the pattern of acidification in the study area. Figure 11 shows a reverse spatial pattern for both OA parameters, indicating an inverse relationship between pH and spCO₂. From 1993 to 2022, the pH and spCO₂ values in the WPS and the Pacific side exhibited significant spatial and temporal variations. The central and southern regions of the WPS showed lower pH values and higher spCO₂ values, indicating a greater impact of OA in these areas; conversely, the Pacific side had higher pH values and relatively lower spCO₂ values. Both regions displayed clear seasonal fluctuations, with the lowest pH values and highest spCO₂ values in summer and the opposite trend in winter. The long-term trend shows a gradual decrease in pH values and an increase in spCO₂ values, reflecting the intensification of regional OA and the rising concentration of CO₂ in the ocean. After removing the seasonality, Figure 11 illustrates higher variance observed in the WPS region for both parameters, with the pH variability extending even further toward the SCS and northwest Pacific. This suggests that the WPS region experiences more significant changes in terms of acidity in the study area.

EOF analysis was also conducted each month on OA parameters (Figure A3) to illustrate their variations throughout the year. In January, a significant difference in acidity levels was observed between lower and higher latitudes, with the former exhibiting greater acidity, a pattern sustained until March. The spatial distribution started to shift in April, moving poleward from the southwest, with the WPS experiencing increased acidity until June. By July, the acidity had extended into higher latitudes, following a northwest–southeast diagonal pattern. It then began shifting back toward lower latitudes from August until November along the same path before returning to the initial trend around December. The spatial distribution pattern of spCO₂ varied with months due to multiple interacting factors, including seasonal SST changes, ocean circulation, and phytoplankton activity. The monthly spatial distribution characteristics in Figure A3 are significantly correlated with the SST in Figure A2. On the other hand, the spatial distribution of total alkalinity (TA) in seawater also influenced the spatial distribution of spCO₂ [21,81,82]. Therefore, the seasonal SST characteristics and changes in sea surface salinity significantly affected the distribution of alkalinity. Under the same conditions of CO₂ input, high-TA seawater had a stronger buffering capacity, which can more effectively maintain a higher pH value and reduce the concentration of freely dissolved CO₂.

3.5. Identifying Vulnerable Coral Reef Regions

Corals are sensitive to even small changes in temperature, light, and other environmental changes. Warming and acidification can weaken corals and reduce their ability to recover, making them more vulnerable to diseases and eventually leading to mortality [83]. By combining all the information collected in this study with the CoralVI indicator, we can map and identify high-risk and vulnerable coral reef areas in the waters surrounding the Philippines (Figure 12). In addition to the key coral habitats mentioned in this study, many small areas along the Philippine coast also present high vulnerability risks [84,85].

3.5.1. Northern Philippines and LS

A known coral bleaching event occurred at Pratas Reef (Site B) in June 2015, where a 6 °C rise caused bleaching across the entire area and killed around 40 percent of the corals [86]. An MHW event at Site B lasted from 2 June 2015, to 30 June 2015, totaling twenty-nine days, with a maximum anomaly of 1.53 °C above the climatological mean. The pH in June 2015 dropped to 8.01 from 8.03 in May 2015, while the spCO₂ increased from 381.4 µatm to 407.2 µatm. The DHW values reached the first threshold only in August 2015. Although the DHW did not fully account for the bleaching event at Site B, the combined MHW and OA parameters indicate heightened susceptibility to coral bleaching in June 2015. Regarding warming, Group I was vulnerable from June to August due to the monsoon, and around November to January due to the KC intrusion (Figure 4). For the OA parameters, similar patterns were observed, with June to August being the most acidic months based on pH and spCO₂ values (Figure 10) and the EOF analysis of both parameters (Figure A3). The MHW indices (Figure 5a–f) indicate that coral reef sites in Group I were experiencing more frequent, longer, and more intense MHWs, especially at Site B. This vulnerability is supported by the CoralVI values (Figure 12). In Group I, the most vulnerable coral habitat was Site B, which experienced high risk in 1998, 2007, 2010, and from 2016 to the present, especially reaching extremely high vulnerability for three consecutive years from 2020 to 2022. Batanes and Cagayan Province (Sites C and D), on the KC path, were also in a high-vulnerability environment due to the warming of the KC in recent years. Nanwan Bay (Site A) [19] benefits from periodic cold water regulating the sea temperature and relatively reducing the crisis, but unexpectedly, it already reached extremely high vulnerability in 2020 and 2022.

3.5.2. Western Philippines

In 1998, widespread coral bleaching struck various coral reef regions in the Philippines, notably near Lingayen Gulf (Site E), lasting from early June to late November. This event led to a significant decline in live coral cover and extensive bleaching [79]. While El Nido (Site H) experienced the highest number of events, followed by Busuanga (Site G), it was Site E that exhibited the longest average duration and the highest average cumulative intensity. Notably, Sites E to H recorded similar total MHW days for the year 1998. During this time, a prolonged MHW event spanning 26 June to 12 September, lasting 79 days, along with another event from November 13 to 22, covering 10 days, coincided with the reported bleaching episode. Furthermore, DHW values for Site E reached the first threshold around June to August 1998. Although acidity levels for Sites E to H were heightened from April to October 1998, this pattern was anticipated due to the annual cyclic variation. Collectively, the combined effects of MHW, OA, and DHW suggest a high probability of bleaching for Site E. For Group II, vulnerability to warming occurred from April to June and September to October, as indicated by the shift in warm waters in the EOF analysis of SST (Figure A2), attributed to the monsoon. This observation is supported by the MHW days in Figure 6g, showing peaks in June and October. MHW indices (Figure 6a–f) also indicate that Sites E and H experience relatively longer and more intense MHW events compared to Occidental Mindoro (Site F) and Site G, especially in the years 1988, 1998, 2010, 2016, and 2020. The DHW values for Sites E to H (Figure 8) showed heightened thermal stress around June and July, with only Site E surpassing the DHW = 8 °C weeks threshold, indicating expected coral mortality. The OA patterns also indicate that the WPS region was more acidic than Groups I and III (Figure 11). The most acidic environment was observed during June, consistent with the EOF analysis of both pH and spCO₂ (Figure A3), which highlights April to June and September to October as the acidic months for Group II. According to CoralVI, Site E has been in a high-vulnerability environment for four years since 2019, and the results in Figure 12g also show that its adjacent areas have high bleaching risks. Sites F to H began to experience continuous moderate vulnerability conditions from 2020 to 2022, and the entire coast on both sides of Palawan are areas that cannot be ignored for threatening coral health.

3.5.3. Eastern Philippines

There is limited literature available on coral bleaching in the Group III region. While widespread bleaching in the Philippines in 1998 is documented for the western side, information on the eastern side remains scarce. If the months for the coral bleaching event in 1998 also apply to the Group III region, Polillo Island (Site I) had the greatest number of events and total MHW days, while Davao Oriental (Site L) had the highest average duration and cumulative intensity. Site L experienced three MHW events from June to November, with the first event lasting 54 days, from 5 July 1998 to 27 August 1998, with a maximum anomaly of 1.08 °C above the climatological mean. Conversely, Site I experienced five events within the same period, with the first event being the most intense, reaching a maximum anomaly of 1.16 °C above the climatological mean in 29 days from 12 July 1998, to 9 August 1998. Sites I and J also reached the DHW = 4 threshold, indicating potential coral bleaching. The months of vulnerability in ocean acidification coincide with the period of bleaching, possibly exacerbating the situation in the region. Overall, the evidence suggests a probable cause of bleaching in Group III. Group III experiences warming primarily from June to July, when SST patterns remain consistent throughout the study area, and from September to January, during the transition from the southwest to northeast monsoon, leading to the return of warmer waters to lower latitudes (Figure A2), particularly evident at Site L. Similar trends were observed for OA parameters, with the shift to acidic waters occurring from September to January based on EOF analysis (Figure A3). The MHW days (Figure 7g) support this observation, with most MHW events occurring during July and September, and fewer events in April when warm waters move poleward. MHW values for Group III (Figure 7a–f) highlight that Sites I and L experience longer and more intense events, especially in 2010 and 2020. Site J experienced longer average durations and higher average cumulative intensities in 2014. Regarding DHW values, only Site I surpassed the DHW = 8 thresholds, while the rest of the coral reef sites experienced a few years surpassing the DHW = 4 thresholds, with only 1998 being consistent across all sites (Figure 8). CoralVI indicates that Site I in Group III experienced a higher risk of bleaching. It has been in at least a moderate vulnerability environment almost every year since 2015 and even reached extremely high vulnerability in 2020. Sites J to L have been in a moderate-to-high-vulnerability environment for three consecutive years since 2020.

4. Discussion

4.1. Historical Bleaching Event Reports and the Challenge of Severe Data Scarcity

The coral reefs in the East Asia Seas (EAS) region are composed of reefs from Northeast and Southeast Asian countries, spanning a vast geographic area in the Indian and Pacific Oceans. Consequently, in recent years, most sites (82%) have only been surveyed once [87]. Since hard corals form the structural framework of coral reefs, most studies commonly use the percentage of live hard coral cover to indicate reef health [88]. Within the EAS region, trends in hard coral cover vary across different subregions, indicating a degree of heterogeneity in response to disturbances and subsequent recovery [87]. There is significant variation in sample survey numbers across different regions of the Philippines. Coral cover and trends also differ markedly between regions. Since most surveys are conducted within marine-protected areas, the observed increase in coral cover may be related to improvements within these protected areas. On the other hand, the limited availability of information prevents the calculation of standard errors for many sites [78]. Severe underreporting still exists across the Philippines [80], not only due to the country’s extensive coastline, one of the longest in the world, but also because coral bleaching events often coincide with the southwest monsoon from May to October. This seasonal characteristic, marked by heavy rains and typhoon passages, hampers scientific fieldwork and diving activities [80]. Given these challenges, a more efficient approach is to first identify high-risk coral ecosystems before conducting field surveys. To achieve this, an integrated assessment tool is needed to evaluate coral reef vulnerability remotely.

One such tool is the CoralVI index, which provides an early warning system for potential coral bleaching risks rather than direct predictions of bleaching events. Like the DHW index was established years ago, CoralVI incorporates MHW and OA parameters to enhance its applicability and longevity, particularly under accelerated global warming. Although OA has a longer-term impact, it remains an essential risk assessment component [2,60,61]. From a satellite oceanography perspective, OA is closely related to total alkalinity [62], statistically correlating with oceanic physical variables such as SST and salinity [63]. Consequently, trends in OA are highly region-specific. Beyond recognizing the current high vulnerability to coral bleaching, issues regarding the selection of coral restoration sites are already emerging [64], with locations that exhibit long-term, relatively low vulnerability being prioritized for restoration efforts [65]. Therefore, this index can be viewed as a tool for assessing coral ecosystem vulnerability through remote sensing applications within marine geographic information systems. Ecologists and governmental environmental agencies can use this marine physical and chemical index as a foundation, supplemented by the specific characteristics of coral species in the area, to make informed final decisions.

Based on the results of CoralVI, a hindcast analysis was performed to compare high-risk years with major historical bleaching events in the Philippine region, demonstrating strong agreement between predicted risk and past observations (Figure 12). As an early warning tool, CoralVI provides an initial assessment of coral vulnerability, complementing existing monitoring efforts. While its primary function remains as a reference framework for identifying potential high-risk coral ecosystems and supporting conservation strategies, its methodology may require further refinement as more observational data become available. Given the current limitations in sample size and validation, future adjustments to its weighting schemes or parameter selection may enhance its predictive accuracy. Nevertheless, despite these uncertainties, CoralVI remains a valuable tool for guiding conservation efforts through remote sensing applications. In recent years, particularly after 2020, the vulnerability to bleaching risk has become increasingly pronounced, highlighting the urgent need for more manpower and resources to address this issue. The Philippine Coral Bleaching Watch, organized by divers and marine experts and the Department of Environment and Natural Resources Biodiversity Management Bureau, has established an online reporting platform to continue monitoring.

4.2. Trend of MHW Events and the Underlying Large-Scale Climate Patterns

Coral bleaching events resulting in devastating coral loss often coincide with thermal stresses induced by ENSO-related warming [89]. Typically, MHWs in the study area or its vicinity are linked to ENSO [29,30]. However, the influence of ENSO on acidification in the study area remains underexplored. Holbrook et al. [12] discussed the influence of ENSO on MHWs, relating it to ocean conditions and changes in surface wind stress. This study, however, examines not just the influence of ENSO, but also the combined effects of both ENSO and the PDO on SST anomalies and, consequently, on MHW occurrences.

ENSO and PDO significantly influence the waters surrounding the Philippines, shaping temperature patterns and marine phenomena that impact local ecosystems and weather patterns. Six ENSO/PDO combinations were created by integrating three phases from ENSO—El Niño (EN), La Niña (LN), and Normal (N)—with two phases from PDO—Positive (+) and Negative (−), resulting in the following combinations: EN+, EN−, LN+, LN−, N+, and N−. The SST anomaly composite maps, based on Zhao and Wang [90], were updated and generated for each combination by aggregating data from all months with the same combination from 1985 to 2022, as shown in Figure 13. These maps revealed the distinct characteristics of ENSO and PDO for each combination. The El Niño maps showed elevated SST anomalies in the SCS region, whereas the La Niña maps presented influence on anomalies in the Pacific Ocean. Furthermore, the Normal maps exhibited variability depending on the PDO state, indicating a complex interaction between ENSO and PDO dynamics in shaping SST anomalies across the study area. Additionally, positive phases of PDO are associated with cooler anomalies, while negative phases correspond to warmer anomalies. As explained by Newman et al. [66], PDO patterns discussed through negative SSTAs were observed in the western North Pacific when positive SSTAs in the eastern tropical North Pacific were observed, as is the dominant pattern for the positive phase of PDO. Conversely, positive SSTAs observed in the western North Pacific can be seen for the negative phase of PDO, which can be seen in Figure 13d–f.

Figure 14 depicts the stacked time series of ENSO values, PDO values, monthly durations of MHW days for Sites A to L, and MHW categories for Groups I to III from 1985 to 2022 to further understand the effects of ENSO and PDO co-occurrence on MHW. As discussed by Chen et al. [91], the transition from EN to LN often correlates with the occurrence of MHW events due to the western North Pacific subtropical high. In Figure 14, it can be seen that instances of EN+ followed by LN− coincide with frequent and intense MHW events, particularly during periods like 1987–1988, 1997–1998, and 2015–2016. The period from 1987 to 1988 was characterized by strong EN, while 1988–1989 was identified as strong LN. Such transitions proved to produce intense MHW events, especially for Group II, wherein Sites F and H reached extreme categories. A similar case happened around 1998, transitioning from very strong EN to strong LN. All groups experienced a longer total duration of MHW events with varying intensities, mostly moderate and strong. These observations imply that a change from the positive to negative phase of PDO drives intense MHW events. A discernible pattern emerged where a negative PDO, contributing to a warming anomaly in the area, particularly when combined with LN, which also induced warming SST effects, amplified the occurrence and intensity of MHW events. However, the shift from EN to LN was not invariably disruptive; for instance, during 1994–1995 and 2005–2007, when EN− transitioned to LN+, there were still MHW events occurring, but a decrease in both the duration and intensity of MHW events was observed. More consistent MHW occurrences began for Group I around 2005.

Group II and Group III also experienced events, but more began to happen around 2007, becoming consistent starting in 2010. From 2010 onward, continuous LN− conditions persisted until mid-2014. EN− followed by LN− also led to recurrent and severe MHW episodes, evident from 2010 to 2012. Notably, despite EN+ events occurring from 2015 onward, MHW events persisted for the groups. In 2016, the onset of LN− conditions saw a return of intense MHW events, though a slight dip was observed from 2018 to 2019 due to EN conditions, before consistent LN− conditions reemerged in 2020. Knowledge of the combined effects of ENSO and PDO can be used to determine which regions are likely to experience warming anomalies based on specific ENSO-PDO patterns. It is worth noting that longer and more intense events were occurring in recent years, despite the changes in the ENSO-PDO combinations, often comparable to or surpassing the peaks observed in 1988, 1998, and 2010, which can be attributed to increasing SSTs due to global warming and climate change.

5. Conclusions

The impact of MHW and OA on coral reefs and marine ecosystems in the Philippines is of significant concern, particularly regarding coral bleaching. This study conducted a comprehensive evaluation of MHWs, OA, and coral bleaching indices in the surrounding waters of the Philippines, divided into three groups, from 1985 to 2022, using satellite and reanalysis data. This large-scale assessment provided invaluable insights into these stressors’ temporal and spatial dynamics, laying the groundwork for a deeper understanding of their impacts on coral reef ecosystems. The integration of MHW, DHW, and OA parameters yielded valuable insights into the CoralVI index, highlighting the complex interactions between these stressors and their impacts on coral reef ecosystems.

The time series results not only highlight the gradually warming sea surface, but also emphasize the characteristics of high SSTs in the marginal seas of the Northwest Pacific and the SCS during two strong La Niña years (1988–1989 and 1998–1999) and one moderate La Niña year (2020–2021). The analysis further emphasizes the seasonal variations in SST and OA patterns, offering critical insights into the months when coral reef regions are most susceptible to ocean warming and acidification. The summer months, especially June, proved to be the most critical for warming and acidification patterns across all groups. This seasonal warming pattern is closely linked to the onset and progression of the southwest monsoon, which plays a critical role in regulating SST variations across the region. Matsumoto et al. [70] determined that the southwest monsoon typically begins in mid-May, although an earlier onset can be observed in the southern region at around 8°N. This timing aligns with the observed shift in SST distribution starting in April and becoming more pronounced in May. Hu et al. [37] noted that while ENSO has traditionally been considered a factor in regulating the SCS summer monsoon, recent studies suggest that trans-Indian Ocean and SCS weather systems may also influence the early onset of the monsoon in May. The spread of warming across the study region in June can be attributed to the deepening of the southwest monsoon, which continues through August. However, the onset and end of the monsoon are not fixed to an annual cycle; the duration of the SCS monsoon is closely related to SST anomalies in the equatorial Pacific [92]. The southwest monsoon typically dissipates mid-September, initiating the reversal of wind patterns and the onset of the northeast monsoon. Widespread wind shifts from west to east occur mid-October, marking the transition to the dominant northeast monsoon by mid-November, which lasts until April. Over the past 60 years, there has been no significant trend in the intensity of the SCS summer monsoon, but the winter monsoon has shown a clear trend of increasing wind speeds [71].

Group I had additional critical months from October to January due to KC intrusion, and from September to October for Groups II and III due to the seasonal shift in the monsoon. The MHW indices described the effect of warming through temperature anomaly events. With continuous warming of the ocean’s surface, there is a corresponding increase in the frequency, duration, and intensity of MHWs in the study area. Maximum values for frequency, average duration, total MHW days, and cumulative intensity were reached by Occidental Mindoro (Site F, 14 times in 2017), Davao Oriental (Site L, 90.5 days/times in 2020), Lingayen Gulf (Site E, 293 days in 2022), and Pratas Reef (Site B, 87.13 °C-days/times in 2021), respectively. For the DHW, Pratas Reef reached the highest value of 12.35 °C weeks in September 2020. High-risk and vulnerable coral reef regions prone to potential coral bleaching events were also identified in this study. In general, Group I had been experiencing higher thermal stress and MHW metrics, while Group II was more acidic compared to the other groups. Pratas Reef proved to be the most vulnerable to coral bleaching when subjected to both warming and acidification, followed by Lingayen Gulf and Davao Oriental.

This study focused on acquiring information for each parameter independently to pinpoint the regions and times when coral reef ecosystems may be most susceptible to coral bleaching. These findings provide practical guidance for marine researchers conducting in-situ monitoring and for decision-makers tasked with implementing effective coral bleaching mitigation strategies. Additionally, it is important to note that different coral species have varied responses to combined thermal and acidification stresses. Therefore, it is crucial to consider both the species and location when performing or analyzing in situ measurements determined in future work.