To construct the SES, a group of researchers first conducted biological monitoring of gray whales and analyzed trends over time. Between 2016 and 2023, a group of researchers and volunteers conducted vessel censuses in the study area, supervised by the Marine Mammal Research Program (PRIMMA) of the Autonomous University of Baja California Sur (UABCS) (sanignaciograywhales.org). During these annual censuses, whose reports have been published in the International Whaling Commission (Urbán et al., 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023), we performed systematic counts along predetermined routes for each lagoon. For each lagoon, we conducted at least three annual censuses, at least one per month from the second week of January to the second week of March, culminating in a total of 29 censuses per lagoon, except for Bahía Magdalena, which had 30 censuses (88 censuses in total) ( Figure 2 ). These censuses estimate the minimum number of gray whales within the main winter breeding and nursing lagoons along the Pacific coast of the Baja California peninsula. In each census, we used a portable Global Positioning System (GPS) device to follow a predetermined transect in each lagoon. For the lagoons of the BMAC, we followed the pre-designed routes by authors such as Fleischer et al. (1995), Gardner and Chavez-Rosales (2000), and Perez-Cortez et al. (2004) ( Figure 1 ). This duplication of census effort allows us to compare whale counts within the year along the same census transect of each lagoon, and to compare with historical counts from previous years (Jones and Swartz, 1984; Urbán et al., 2003b).

For these censuses, we used the methodology proposed by Jones and Swartz (1984), which consists of navigating small outboard motorboats of 7 to 8 meters in length, following pre-designed routes at a speed of 11 km/h during the whale count. This speed is used to minimize the probability of whales outpacing the vessel, giving observers enough time to detect whales surfacing along the tracking route. Whales were recorded by two pairs of observers, one on the port side and another on the starboard side. Whales were counted only when they were at a right angle to the observers, and a fifth person recorded the sighting in a logbook, noting the time of the sighting, the number of whales, their swimming direction, and whether a calf accompanied them or if they were single whales. Additionally, we recorded some environmental conditions such as the Beaufort Sea state, wind direction, cloud cover, sea surface temperature, and depth. Censuses were not conducted or were aborted if in progress wind and sea state conditions exceeded Beaufort Sea state 3 (winds over 18 km/h with consistent whitecaps). By convention, “mother-calf pairs” (i.e., female whales with calves of the year) are counted as a single unit. “Single whales” refer to females without calves, adult males, and immature or juvenile animals.

Using the annual census data, we created temporal models for each lagoon and whale group (number of mother-calf pairs and single whales). We implemented Bayesian mixed-effects temporal models with an integrated nested Laplace approximation (INLA) approach (Rue et al., 2009), which has proven to be a great alternative for modeling time series, providing results in terms of posterior probability distributions instead of fixed values, and incorporating various types of random effects of temporal nature (Blangiardo et al., 2013; Zuur and Leno, 2018). We used years 2016 to 2023 as covariates to show long-term trends and the weekly scale from week 1 to week 16 of the year to cover the weeks of the first three months of each year, covering the census period to show temporal trends. We tested various model structures with combinations of the covariates. We used the best model results to show the long-term and seasonal temporal trends of the estimated number of gray whales over the eight years of systematic censuses.

During the biological monitoring, researchers identified some practices during whale watching that could affect the whales’ well-being. As a result, we designed and evaluated compliance with the guidelines of the official Mexican regulations, specifically the Mexican Official Standard NOM-131-SEMARNAT-2010 (DOF, 2011). We assessed compliance with guidelines such as the maximum observation time (30 minutes), the maximum allowed navigation speed (9 km/h in the observation area, decreasing to 4 km/h when starting the observation activity), the observation distance between the vessel and the whales (60 meters), the trajectory of the vessel’s approach to the whale (in a diagonal line from the rear side of the whale), and the maximum number of vessels observing the same whale or group of whales (four vessels). For the in situ evaluation of violations of the official regulations, we used a survey and registration method adapted from Quintana-Martín Montalvo et al. (2021) (the modified survey is available in Supplementary Table 1 ). This involved data collection by a group of researchers from a smaller vessel (45 feet or 13.7 meters long), positioned approximately 300 meters from a group of whales being observed by tourists. Sampling was conducted for a minimum of 6 minutes (2 scans to check for compliance or violation) and a maximum of 45 minutes (15 scans) as soon as visual contact with the group was lost or the whale-watching activity ended by a vessel or group of vessels. The size and composition of the group (adults and calves) were estimated visually. We then conducted a Principal Component Analysis (PCA) to identify the main violations of the official standard in each community and group of whales (mother-calf pairs, single whales, and groups of more than three whales) (Greenacre et al., 2023) to reduce the dimensionality of the multiple violations assessed and observe only the primary relationships between communities and violations (Chan and Shi, 1997; Greenacre et al., 2023). We used the scores of the projection of each locality in the principal components space to represent the position of the original observations in the principal components space, which helped to understand the influence of each principal component on the observations. We also performed a Pearson correlation analysis between the principal components and the violations to analyze and visualize how each community is associated with the principal components and the violations (Greenacre et al., 2023). To understand the dynamics of whale-watching tourism and its economic impact in the study area, we analyzed available data from the Mexican government’s Secretariat of Environment and Natural Resources (SEMARNAT). SEMARNAT collects information reported annually by tourism operators regarding the number of permits, trips, income, and jobs generated by whale-watching in Mexico (SEMARNAT, 2024).

Analyzing the trends of the last eight years of whale counts, the lack of compliance with official regulations by tourism operators, and the economic importance of whale watching in the localities, we approached the communities to begin participatory work involving key stakeholders according to the nature of the activity, including tour operators conducting gray whale watching, tourists, and government representatives. In early winter 2022, we conducted 18 interviews with representatives of service operators. These interviews aimed to delve deeply into their experiences in tourism, tourists’ perceptions, their understanding and views on official regulations, as well as their knowledge and perceptions of climate change and its impact on gray whales and whale-watching activities (the interview questions for tour operators are available in the Supplementary Table 2 ). We conducted the interviews in the three communities of the BMAC ( Figure 1 ) and one additional interview with a representative of the Director of the Biosphere Reserve of the Pacific Islands in the Baja California Peninsula of the National Commission of Natural Protected Areas (CONANP).

Our research was a collaborative effort, with a wealth of information obtained from interviews. At the end of the winters of 2022 and 2023, we conducted 12 participatory workshops using mixed methodologies in focus groups. These workshops were aimed at people from communities near the observation area, with a primary focus on tour operators. The workshops, distributed among the three localities, were a platform for sharing and gathering insights. The first round of workshops in each locality focused on understanding the community’s perception of climate change, its effects on gray whales and tourism, and sharing the results of the whale count censuses. The second part involved providing updated information on the status of the gray whale population, the observed effects of climate change on migration routes and breeding lagoons, and their interest in regulations and whale welfare. The third part provided detailed information on current regulations and their importance for whale conservation and tourist safety.

Between the third and fourth rounds of workshops, we conducted semi-structured surveys among 235 tourists to gather information on their level of interest in gray whale watching, overall satisfaction with the activity, satisfaction with the information provided during the tour, compliance with regulations, and the number of vessels encountered during the tour. For each of these sections, we asked participants to indicate their level of agreement on a Likert scale (1 - strongly disagree to 5 - strongly agree) (Pett, 2015). Additionally, we collected data on socio-demographic aspects, travel expenditures, and asked about scenarios in which they would be willing to return about the amount of information received during the WW trip, the number of vessels watching whales at the same time (crowding), and the number of whales (especially mother-calf pairs) (the survey questions for tourists are available in the Supplementary Table 3 ). The intention to return has been widely addressed in the theory of planned behavior, which states that tourists’ intention to return depends on attitudes, subjective norms, and perceived behavioral control (Ajzen, 1991). Perceived crowding reveals a subjective perception of the number of vessels encountered affecting tourist satisfaction (Vaske and Donnelly, 2002).

We performed descriptive statistical analyses to understand the factors related to tourist satisfaction and to assess whether communities exhibited tendencies to commit specific types of normative violations. Through a correlation tree, we identified the segmentation of tourists based on their overall satisfaction with gray whale watching. Correlation trees reveal complex and non-linear relationships between predictive variables and the response variable (satisfaction level) (Breiman et al., 2017).

Finally, we conducted the fourth round of workshops where researchers shared our interpretation of the interviews, the results of the tourist surveys, the evaluation of compliance with regulations, and the relationship with the results of the whale censuses. In this final round, we conducted a feedback process where, through brainstorming sessions, we identified the essential variables of the SES and their interactions, discussed important adaptation actions for the system to be resilient to the effects of climate change, emphasizing that these actions are crucial for the future of gray whale watching and tourism. We validated the mental model of the SES via focal groups. To qualitatively understand the behavior of the system elements and the flows indicating how the variables interact, we represented the polarities of the links connecting these variables to show cause-effect relationships (Loucks and Van Beek, 2017). We represented these polarities with a plus (+) or minus (−) sign to show the direction of the relationship between the two interconnected variables (Maani and Cavana, 2007).

We obtained six models, selecting one for each locality with a different grouping of whales (mother-calf pairs and single whales). For all competing models, the negative binomial probability better represented the response variable than the Poisson distribution. Model selection was carried out using the Watanabe-Akaike Information Criterion (WAIC) ( Table 1 ).

In the case of single whales, the best model was the same for each locality, including the number of continuous weeks (CW) from January 2016 to March 2023 (long-term scale), and the week of the year (WY) from January to March (seasonal scale) with second-order polynomials. Mother-calf pairs had different models for each locality; the most complex model was for BA with CW with third-order polynomials and WY with second-order polynomials, followed by SDC with second-order polynomials in both covariates. The simplest model for mother-calf pairs was for BM with CW plus WY with second-order polynomials ( Table 1 ). There is a differentiated segregation of whales in the bays. The northernmost region (SDC) hosts the highest number of mother-calf pairs, while BM and BA have more single whales. On the other hand, the number of single whales has been higher in BA, with the annual average number of whales in this area being between three and seven times higher than in BM and between five and fourteen times higher than in SDC over the past four years ( Figure 2 ).

The data reveals a trend of decreasing mother-calf pairs over the years. The highest counts were observed in 2016 and 2017 in SDC, with maximum counts of 46 and 44 pairs, respectively. However, the following year (2018), only about one-third of that number was counted. This trend is consistent across all lagoons, with the most drastic changes observed in SDC, followed by BA. Between 2017 and 2022, there was a 95% decrease in the maximum number of mother-calf pairs counted in SDC, a 94% decrease in BA, and a 75% decrease in PSC. While 2023 saw a slightly higher increase than the average trend estimated in the long-term model, the overall trend is a cause for concern ( Figure 2 ).

The trend in the number of single whales has been increasing in BM and BA, although it is more pronounced in the southernmost area. Following the lowest counts of single whales in 2016 in BM, there was a drop in 2020, with slightly higher maximum counts in 2021 and 2022, but even in these years, the maximum whale count was 41% less than in 2017. However, by 2023, there was a historic increase with a maximum count of 97 single whales, 131% more than in 2022 and 40% more than in 2017. In the case of BA, the maximum count of single whales increased consistently until 2021, with three times more whales in 2019 than the previous year. Between 2020 and 2022, there were no clear differences, but there was a 10% decrease between 2021 and 2022. However, in 2023, there was a considerable increase with a maximum count of 295 single whales (70% more whales than in 2022). SDC is the only lagoon showing a long-term decreasing trend in single whales. In 2022, SDC had a maximum count of single whales almost 50% lower than in 2021 and 60% lower than in 2019, and in 2023 was the only lagoon with fewer single whales than the previous year, with a 64% decrease ( Figure 2 ).

The number of whales in the breeding lagoons, mainly the mother-calf pairs, and their declining trend over time are the primary state factors of the SES, as without whales, the system simply would not exist. Going from a maximum of 44 mother-calf pairs to two implies a change in the main factor of the SES, raising other questions related to how the system can remain resilient to these changes: Will the number of whales observed be important to tourists? Have tour operators noticed these changes in the whales? Is tourism conducted in the same way? Are there implications if tourism remains the same or grows?, among others.

After examining the temporal trend of gray whales visiting the Bahía Magdalena area over time, we compared the three localities within the BMAC. We evaluated how this tourist activity aligned with the official Mexican regulations. By assessing compliance with the Mexican Official Standard NOM-131-SEMARNAT-2010 using principal component analysis, we observed that violations of exceeded observation time (Time), improper approach trajectory to the whales (Trajectory), and high navigation speed (Speed) are distributed differently in the principal components ( Figure 3 ). Trajectory and Speed are strongly correlated with the first principal component (Comp.1), with correlations of r = 0.90 and r = 0.77, respectively ( Table 2 ). This suggests that Comp.1 represents a variability axis where long trajectories and high-speed violations predominate. On the other hand, Time shows a high correlation with the second principal component (Comp.2, r = 0.92), while Speed has a negative correlation with Comp.2 (r = -0.53) ( Table 2 ). This indicates that Comp.2 represents a variability axis where long violation times oppose high-speed violations. By examining the scores of the communities in these components, we observed that when operators from the community of PSC observe single whales (PSC.single), they have high scores in both components ( Table 2 ), suggesting that this community has improper approaches to the whales and prolonged violation times ( Figure 3 ). Operators from PCH have a high score in Comp.1 and a negative score in Comp.2 when observing single whales, indicating that this community tends to have improper approach trajectories to the whales, navigate at high speeds, but usually respect the maximum observation time. In contrast, in the presence of mother-calf pairs, all localities have low scores in both components, indicating better approach trajectories, slow navigation, and no exceeding the maximum observation times ( Figure 3 ).

Currently, we do not have evaluations from different years with varying numbers of whales, but we have the experience of being constantly present during the winter season, conducting whale monitoring, and evaluating compliance with regulations on different days of the week and at various times, some with higher tourism intensity than others. Therefore, we observed an increase in poor practices during times of higher influx of tourist vessels in the observation areas, mainly the mouths of the lagoons to the open sea.

Subsequently, our objective was to understand the importance of whale watching as an economic activity. By examining the available data in the SEMARNAT database (SEMARNAT, 2024), we observed that despite the geographical proximity of the localities within the same lagoon complex, there are significant variations in the number of tourists visiting these areas and their economic contributions. Interestingly, we observed a notable increase in economic income in PALM, where there has been a clearer decrease in gray whales, particularly mother-calf pairs ( Figure 4 ). The differences in income between PALM and PSC are evident, with the former consistently being a higher income generator and conducting a greater number of trips since 2009 ( Figure 4 ). However, there are cases where PSC’s earnings could be proportionally higher, such as in 2015, when it generated $228,280 dollars in 655 trips, just $1,780 dollars less than PALM, despite conducting only one-third of the trips. However, there are no available records in the SEMARNAT databases for the southernmost site (PCH) despite its official inclusion as a whale watching area in 2013 (DOF, 2012).

Specifically for PALM, starting in 2013, there was a significant increase in income, exceeding $200,000, much higher than in previous years ( Figure 4 ). Since 2013, revenues in this community have ranged from $230,000 to $940,000 in 2022, followed by a notable decrease in 2020 and 2021, marking the lowest historical incomes from whale watching in PALM ($10,300 and $1,930, respectively). The difference between the second-highest income year and the highest is notable; in 2022, revenues were 85% higher than in 2019. Similar to PALM, PSC experienced its highest income year in 2022 ($444,300), followed by 2015 ($228,930), and then 2014 ($162,000). In 2020, revenues slightly exceeded those of 2012, which was the worst year, and in 2022, revenues were 94% higher than in 2015, the second-highest income year ( Figure 4 ).

The number of trips appears to have remained relatively stable in PALM, fluctuating between 2,400 and 2,900 trips per year since 2013. A similar pattern is observed in PSC from 2009 to 2015, but a steady decline in the number of trips has been recorded until 2020. In 2020, the historical minimum of trips was recorded, with only 112, only surpassed by 2010 when only 55 trips were reported ( Figure 4 ). The growth pattern in the number of trips is less noticeable compared to the economic income, particularly for PALM, where a historical record of earnings was achieved in 2019, before the onset of the SARS-CoV-2 Coronavirus pandemic, which was then greatly surpassed in 2022 ( Figure 4 ). Despite some years with declines in tourist activity, the increase in recent years is clear, especially the upturn in 2022, which underscores the importance of a growing activity, contrary to the decline in gray whales. The low values in 2012 for both economic income and the number of trips should be taken with caution, as we did not find an explanation for these values, and even service operators mentioned that they do not reflect the tourist dynamics of that year. It also appears that the record of travel information for 2017 by SEMARNAT is missing.

The next step was to understand in depth the perceptions, knowledge, and needs identified by whale-watching operators. We conducted a total of 18 interviews with whale-watching operators from the three communities in the BMAC. In PALM, eight whale-watching operators were interviewed, including the leaders of the two cooperatives and two individuals registered for whale watching. Unlike the other two communities, whale-watching operators in PALM stand out for their high level of organization, maintaining constant communication and making decisions related to whale watching through democratic processes. They also associate with foreign companies arriving on yachts or cruises, facilitating information exchange, and raising awareness about recent events, such as the unusual mortality of gray whales. Additionally, alternative nature tourism activities were identified in PALM due to its diverse environments, including dunes, mangroves, and wildlife. The operators expressed their understanding of the need for training and close communication with whale researchers in the area.

In PSC, six whale-watching operators were interviewed, perceiving high competition among operators who often adjust prices to attract tourists. There is discontent with fishing activities during the whale-watching season, with limited knowledge of the recent UME among the operators. Some operators wanted local guides to be trained to join boat operators and share information to improve onboard safety.

In the southernmost community, PCH, three whale-watching operators were interviewed. They demonstrated great interest in learning about gray whale ecology and sharing information with tourists. Despite being relatively new to tourism, PCH is optimistic due to its proximity to the state capital city and perceived competitive advantages over other communities. The operators expressed interest in the presence of surveillance authorities to ensure compliance with regulations and prevent unauthorized tourist activities.

To gain a more comprehensive view of the current situation of whale watching, we also interviewed the current representative of the Biosphere Reserve of the Pacific Islands of the Baja California Peninsula, belonging to the federal government agency called the National Commission of Natural Protected Areas (CONANP). During the interview, differences were highlighted between fishing and tourism groups in the level of organization among the communities and disparities and complaints among certain communities. There is a perception that the number of permits for whale-watching activities is excessive, underscoring the need to regulate tourism to ensure its sustainability. Additionally, there is a call for developing alternative nature-based tourism activities to alleviate pressure on whale watching. Furthermore, there is an emphasis on the need for closer engagement from researchers and government authorities with the communities, particularly with whale-watching operators, due to growing dissatisfaction related to the decline in whales in recent seasons.

Through in-depth interviews, we identified that in all three localities there is a recognition of the decline in whales, especially mother-calf pairs. Although there are varying levels of knowledge related to the effects of climate change, everyone expressed a strong interest in learning more. We began to identify input variables to the SES related to its resilience, such as interest in diversifying tourist activities, training to learn more about the biology and ecology of whales, and we found that not everyone was fully aware of the official regulations and their importance.

In order to directly share the requested information, such as general aspects of the biology and ecology of the gray whale, the results of the biological monitoring conducted by PRIMMA, and to learn more about the recent UME of gray whales, we organized 12 participatory workshops (4 per site). In the first three rounds of workshops, we shared this information and discussed sustainable and resilient tourism, the importance and benefits of applying NOM-131-SEMARNAT-2010, and discussed some improvement and adaptation strategies to climate change, which were later taken up and established in the fourth round of workshops. Additionally, we identified an interest in understanding tourists’ perceptions and satisfaction with the activity. Tourists often came with the idea of touching whales, generated by social media, which was reflected in an insistence by tourists to get too close to increase their chance of touching a whale, which could lead to several operators harassing the whales.

To understand the tourist typology and the factors associated with their satisfaction, we administered 235 semi-structured surveys to tourists immediately after their gray whale watching trips between 2022 and 2023. Sixty-four percent of these surveys were collected in PALM, 22% in PCH, and 14% in PSC. The age range of the surveyed tourists varied between 13 to 80 years old, with most being between 27 and 51 years old in all sites. Tourists mentioned their main motivations for visiting the area and watching whales, where 62% of the tourists stated that their primary motivation was simply to see the whales, with a particular interest in seeing calves. Only 25% reported having an interest in seeing the entire natural environment. Thirteen percent said they were visiting the area only because it was part of a tour package. In all localities, most tourists reported having completed university studies, followed by high school and postgraduate education. The most frequent occupation in all localities was professional work (34% of the total), followed by employee (20%). Of the total tourists, 34% spent less than $250 dollars, 23.8% spent between $250 - $500 dollars, and 15.3%, a similar percentage of tourists, spent between $500-1000 and $1000-1500 dollars. In PAL and PCH, the majority spent less than $250 dollars (34.4% and 45.1%, respectively); however, in PSC a high percentage of tourists preferred not to mention how much they had spent (45.5%) ( Figure 5 ).

Half of the respondents were national tourists, one-third were locals, and 17% were foreigners. PSC had the highest proportion of national tourists (55%), followed by PCH (25%) and PALM (20%) ( Figure 5 ). When analyzing the proportion of tourists according to their origin (international, national, or local), we observed that international tourists (tourists from another country) had the highest proportion of university (41%) and postgraduate (28%) studies. The majority of national tourists (Mexicans who do not live in B.C.S.) had university studies (22%), followed by high school (12%) and postgraduate (11%) studies. Among local tourists (residents of B.C.S.), university and pre-university (high school) studies predominated (27% each), followed by secondary education (13%) ( Figure 5A ). Fifty-one percent of international tourists mentioned having a professional job, followed by retired tourists (23%). Most national tourists had professional jobs (34%), followed by employees (20%), and only 10% were retired tourists ( Figure 5B ).

After providing a general overview of the guidelines for proper whale watching according to NOM-131-SEMARNAT-2010, we sought to measure tourists’ perceptions of compliance with these guidelines. Among tourists visiting PALM, 51% rated compliance as excellent, 8% considered it moderate, and only 4% rated it as poor. In comparison, a smaller proportion of visitors to PCH and PSC rated compliance as excellent, with 35% and 39%, respectively. However, 12% of respondents rated compliance as deficient in both PCH and PSC. Additionally, 11% of all tourists refused to rate the compliance of their tour ( Figure 5D ). Interestingly, there were no clear differences in the compliance rating according to the tourists’ origin. Among international tourists, 56% rated compliance as excellent, followed by 43% of locals and 42% of nationals. Conversely, no foreigners rated compliance as deficient, while only 6% of locals and 9% of nationals perceived compliance as deficient. These findings suggest a generally positive perception of compliance with whale-watching guidelines among tourists, regardless of their origin ( Figure 5D ).

Tourists were willing to return for whale watching under certain circumstances, with no clear differences observed between communities or tourist origins. Sixty-four percent mentioned that they would consider returning if provided with more information during the whale-watching tour. In comparison, 23% said they would do so with the same information ( Figure 6A ). Interestingly, none of the respondents mentioned returning with less information than they received. Similarly, when asked about their willingness to return if they saw the same number of mother whales with calves, only 12% responded that the number of whales does not affect their decision to return. However, most tourists expressed that they would be more likely to return if the number of whale-watching vessels in the observation area was lower (30%) or at least the same as they observed during their tour (43%). Another 24% mentioned that a change in the number of vessels does not affect their decision ( Figure 6A ). Additionally, 40% of respondents expressed interest in engaging in more tourist activities in the area besides whale watching, even if it meant incurring higher expenses. About 33% said they neither agreed nor disagreed with this idea, while 21% chose not to answer. These responses indicate a potential to diversify tourist activities to enhance visitor experiences and support local economies.

According to the correlation tree analysis, tourist satisfaction was primarily associated with the level of satisfaction with the information provided during the tour ( Figure 6B ). This factor served as the main determinant of satisfaction, indicating that tourists who felt adequately informed during the whale-watching tour were more likely to report higher levels of satisfaction. According to the conditions shown by the correlation tree, the highest degree of tourist satisfaction (4.9 out of a scale of 5) was obtained when there was medium to high satisfaction with the information received (>= 3.5, right branch of the tree) and subsequently, if tourists considered themselves moderately to highly in agreement with having learned new information during the tour (>= 3.5 out of a scale of 5). This suggests that tourists who felt they gained new insights or knowledge during the experience had higher satisfaction ( Figure 6B ). The next level of satisfaction was related to the tourists’ educational level. Tourists with university or postgraduate education who had satisfaction with the information received equal to or greater than the average (>= 2.5 out of 5) reported being moderately to highly satisfied with the activity (4.3 out of 5). Another important factor is whether the respondents were local or foreign tourists (national or international). Interestingly, it was found that Mexicans from outside Baja California Sur (BCS) were less satisfied with the information received than local tourists. This distinction highlights the importance of considering cultural or regional differences in tourists’ expectations and experiences during whale-watching tours. It is worth noting that factors related to information and learning something new are found in three of the five nodes of the tree, including the main node, highlighting the importance of these factors in tourists’ overall satisfaction with the WW activity.

Once the data from the ecological and socioeconomic subsystems were analyzed, the results were presented in the fourth participatory workshop, following feedback from each section, through brainstorming sessions and focus groups. Among the participants, whom tour operators mostly represented, some civil associations, and representatives of CONANP, we consolidated the mental model of the social-ecological system of whale watching on a medium or meso scale that includes the three localities of the Bahía Magdalena–Bahía Almejas Complex, integrating various ecological and socioeconomic components to understand their interactions and responses to changes over time ( Figure 7 ).

We found that resilience in this SES is defined by the system’s ability to sustain economic activity over time while facing its main stressor: the effect of climate change on gray whales. Climatic variables such as ice levels in the feeding area and sea surface temperature in the breeding areas influence the number and condition of whales visiting the bays, serving as input variables and identified as external stressors to the system over which we have no control. The state of the biological component, represented by the number of whales, is related to actions that can make the SES resilient.

Tourist satisfaction emerges as a central variable within the SES, influencing and being influenced by most of the other variables. Satisfaction is a variable that balances the two indicators of the resilience of the activity: the number of whales and the economic income of tour operators. Satisfaction is strongly linked to the information provided by tour operators, with increased quantity and quality of information increasing satisfaction and potentially fostering greater environmental awareness among tourists. Additionally, improving the information used in marketing campaigns to promote the activity can lead to better compliance with regulations and reduce the pressure on tour operators to get closer to the whales. We did not lose sight of the fact that satisfaction is also influenced by the educational level of tourists; the higher the education, the greater their demand, and it is also higher among non-local tourists (non-residents of B.C.S.) ( Figure 7 ).

Tourist preferences support efforts to control the increase in the number of vessels in the whale-watching area, which could improve satisfaction. Additionally, diversifying tourist activities in each locality could reduce the number of vessels dedicated exclusively to whale watching, allowing for better organization and compliance with regulations even with fewer whales ( Figure 7 ).

Two main causal relationships were identified between elements, defined as feedback loops in the SES mental model. These elements are connected in such a way that if we follow the causality starting from any element in the loop, we can eventually return to the first element. The first feedback loop (F1) is defined by the relationship between the increase in tourists and economic income and whether this generates a higher number of vessels watching whales simultaneously, which would negatively affect tourist satisfaction. The second feedback loop (F2) is defined by the effect on satisfaction from poor practices that lead to non-compliance with official regulations due to increased tourism ( Figure 7 ). Overall, the mental model provides information on the complex interactions within the SES of whale watching in a simple and easily understandable way, and helps to emphasize the importance of adaptive management strategies to ensure the resilience of both the economic activity and the whale populations in the area.