*1.1. Urban-Tourist Dynamics from the TALC Model*

The evolution we have been describing can be contextualized within a neighborhood life cycle and interpreted considering the model that Butler called TALC (tourism area life cycle) [8]. This model studies the evolution of tourism from the economic, social, and cultural point of view and analyzes its territorial development through four tourism peripheries: The North Sea and Baltic coasts, Southern Europe, the North African shores, and the tropical oceans [9,10]. The defense of this model turned Butler's work [11] into one of the most cited works on tourism in the world, if not the most cited [12], and soon after its publication arose criticism [13,14], especially that of the undertheorization of tourism [15].

Despite this, four decades after its appearance, its relevance is undoubted and has demonstrated its potential applications in future scenarios [16], given that the TALC remains a clear indicator of the importance of theory in tourism research [17]. Thus, for Oppermann and Agarwal [18], Butler's model is an example of how scientific progress should work, with the ability to adapt to different contexts and to specific situations and circumstances. This has given it great success, based on its apparent universality, its high degree of applicability [19], and, combined with this, the relative absence of alternative models [16,20].

According to TALC, tourist destinations have a dynamic nature, going through different phases of evolution and, as in the biological/product life cycle, decline is often inevitable [12]. Consequently, the last stage foreseen is the rejuvenation or decline of a destination. This interpretation, which has given rise to numerous controversies [21,22], may be useful as a descriptive model to analyze the first phases of transformation of the El Terreno and Santa Catalina-Canteras neighborhoods. However, as many authors have pointed out, the model does not explain and predict the behavior of a specific tourist destination after the phase of stagnation [23], since "depending on the efforts of government and entrepreneurship, rejuvenation, stagnation, or decline are possible outcomes" [24]. This does not prevent the model from interpreting some of the rejuvenation plans and policies of mature destinations [19].

In hindsight, Butler [25] defends a blending of both evolutionary and revolutionary predictions in the case of tourism destinations, an approach that allows for the incorporation of ideas such as chaos theory and chance into the equation of growth, to reflect both the inertia and dynamism that are inherent to tourism. This is a dynamic and predictive model that can incorporate agents, phases, and processes. For example, once the maturity stage is reached, Strapp [26] explains the conversion of conventional tourist destinations from second homes to retirement havens, while Baum [27] says that, alternatively, destinations may choose to leave tourism aside entirely as part of its economic development portfolio. For Benner [28], in the absence of exogenous changes due to policy interventions, or public pressure, in a scenario of overtourism, a destination's tourism sector might contract, downgrade, dislocate, and eventually even disappear.

#### *1.2. Urban-Tourist Dynamics from the Perspective of Gentrification*

In our case study, that of two mature tourist destinations in the most populous cities of the Spanish archipelagos, we argue for the emergence of a new phase of evolution after decline, associated with a process of gentrification. Although there is evidence of the impact of this process in many Western cities, until now, it had only been recognized as affecting urban areas such as historic centers. Mature tourist centers, at least in Spain, had not been analyzed in the light of this new elitization, although the irreversible trend towards their decline had been anticipated, as Knowles and Curtis [29] predicted at the end of the last century. Vera and Rodríguez [30] also pointed out that mass tourism was the final stage in the evolution of these Mediterranean tourist destinations.

However, an analysis from the perspective of tourism gentrification can complement the previous view. As Gotham [31] has pointed out, until the beginning of the 21st century, most analyses of tourism had ignored the impact of tourism on gentrification processes. The studies carried out by this author in the case of New Orleans [32] have given way to extensive literature that has reviewed the links between gentrification in scenarios as diverse as Berlin [33], Venice [34], Memphis [35], Hanoi [36], China [37], or Spain and Latin America [38–40]. Reflection on the relationship between tourism and gentrification includes contributions centered on the theorization of the role of tourists and their practices as producers of tourist space and as generators of medium- and long-term appropriation conflicts, as Hiernaux and González [41] have pointed out.

Tourist gentrification, notes Cócola-Gant [42], involves a deep mutation of the place in which long-term residents can lose the resources and references by which they define their everyday life. The review of conflicts and the emergence of social movements in the tourist city has focused the attention of a powerful line of studies in which the contributions of Colomb and Novy [43] and Opillard [44] stand out. For their part, Gravari-Barbas and Guinand have highlighted the complex and diverse nature of the relationship and point out that tourism more than ever plays an important role in the economy by being generally associated with city rebirth (renaissance and beautification), revitalization, or urban regeneration [45]. Along these lines, this text argues that in El Terreno and Las Canteras a new phase of evolution has been inaugurated, after the stages of maturity and decline, and that this phase is associated with a socio-urban process of gentrification.

#### *1.3. The Differentiated Urban-Tourist Dynamics in El Terreno and Santa Catalina-Canteras*

In general, tourism has gone through waves of expansion and restructuring connected to general techno-economic changes. In the case of Palma and Las Palmas de Gran Canaria, the recognition of tourism and the tourist industry as a complex network, where different business models compete and co-exist in various ways, is important for our understanding of the dynamics behind recent growth in the observed urban tourism transformations [46]. In this sense, we must consider these two territories do not trail a parallel trajectory in a late stage of evolution since, according to the interpretation of destinations as mosaics or assemblages, each can follow a lifecycle that is different from the other, despite their previous common trajectory [47,48]. That is, each of them must be interpreted as a system evolving by responding to external and internal inputs [49]. This fundamental idea lays the necessary foundation of tourism through the lens of the complexity theory, which underlies systems thinking [50].

In summary, in this article we intend to analyze the recent elitist dynamics that are manifested in the mature tourist neighborhoods of El Terreno, in Palma, and Santa Catalina-Canteras, in Las Palmas de Gran Canaria, considering the synergies between TALC and the life cycle of urban areas. In both cases, processes of revaluation and social displacement are recognized, but with differentiated dynamics that reflect, through a comparative analysis, an image of the processes of gentrification in a late phase of capitalism.

#### **2. Materials and Methods**

To characterize the recent socio-urban and tourist dynamics of the mature tourist districts of El Terreno and Santa Catalina-Canteras, we have combined different research sources. First, data from the Continuous Population Register between 2004 and 2019 [51] at a micro spatial level were used. This source is developed based on the exhaustive utilization of the basic variables contained in the Municipal Register on January 1 each year. Among these basic variables, the nationality and place of birth are included for different levels of territorial disaggregation. In our case study, the information is referred to at the lowest possible level of detail, without violating statistical confidentiality, namely the census tracts.

Secondly, information on the socioeconomic level of the population of the neighborhoods studied was considered. In this case, we collected the income data from the Spanish Tax Agency, for the period 2009–19 [52]. The income data are based on the income declared annually by individuals, so it is one of the best possible estimates of the evolution of income at a more detailed scale than at the municipal level, given that it refers to the postal code areas.

Thirdly, data on tourist accommodation was made use of. The National Statistics Institute and the different regional statistics institutes offer information on the hotel and non-hotel tourism offer at the municipal level. The Hotel and Holiday Dwelling Occupancy Survey is a good example of this. Its information allows us to know the evolution of the number of establishments and beds from a time perspective. In this case, as we had to focus the analysis on an infra-municipal scale, we had to resort to the lists of Accommodation Supply of Gran Canaria and Mallorca for 2019, which are produced by the Tourism Boards of the respective islands [53]. These lists show the supply in operation by postal address. The official information was contrasted with the fieldwork and with the data provided by some marketing platforms in relation to holiday homes. Specifically, we consulted the data provided by AIRDNA from platforms such as AirB&B and Vrbo. This portal allowed us to compare the number of dwellings and beds in operation, as well as other data on marketing, using the postal address.

Finally, we also collected information on the evolution of house prices. Official data on housing sales and rental prices in Spain usually only go down to the municipal level and, as we were interested in prices in two specific areas, we resorted to reports from appraisal agencies and electronic agencies. Specifically, we used the data provided by El Idealista.com, which we consider to be the best option for characterizing real estate market trends [54], as they have been provided since 2009, at a district scale.

Therefore, the use of these four main sources allows us to characterize the evolution of the population and residents according to their origin, the income of the resident population, the supply of tourist accommodation, and the evolution of the sale and rental prices of housing. These are the seven indicators that have been used to analyze the residential and tourist dynamics of both neighborhoods and to detect whether there are processes of gentrification that are leading to the displacement of population according to country of birth (see Figure 1).

**Figure 1.** Methodological outline. Own elaboration.

The data provided by these sources have been treated with descriptive statistical procedures, although the greatest difficulty for the selection of information has derived from the different spatial references provided by the different sources at a micro-scale level. Thus, demographic data corresponds to census tracts, tourism data to specific units (real estate), income data to postal districts, and sales and rental prices to districts. To make the analysis possible, we chose to define the boundaries of the neighborhoods according to census sections, which allowed us to work with information from the census. Using a GIS, postcodes and districts were superimposed on the corresponding census sections, selecting the codes and districts with the best territorial fit. Finally, we geo-referenced the tourist accommodation according to postal address, selecting those located within the census sections that had been chosen.

This work procedure allowed us to achieve the following secondary objectives: (i) to characterize the demographic evolution of these neighborhoods, the increase or decrease in population and, especially, the dynamics of immigration according to the geographical origins of their residents; (ii) to analyze the evolution of the housing supply in order to calibrate the weight of tourist establishments and houses for tourist use in the study areas; (iii) to interpret the changes in the socio-economic levels of these neighborhoods; and (iv) to appraise the parallel or non-parallel evolution of housing prices and of the income level of the population. The combination of these objectives let us establish an image of the recent trends in touristification and in the gentrification processes in both neighborhoods, in a late phase of capitalism, which revalues them for new productive uses and consolidates an unequal city: that of investors versus neighbors.

In the following sections, after an in-depth presentation of the study areas and the urban-tourist dynamics that have preceded the recent process of gentrification, the analysis of four of the indicators mentioned in the results section is presented: the dynamics of the regulated and holiday tourism offer and the recent evolution of the population figures and of the contingents according to place of birth. The study of the evolution of property sale and rental prices and per capita income is presented in the discussion section, at the same time as all the results obtained being interpreted in the context of the theories put forward. We conclude with a presentation of the similarities and discrepancies that both destinations seem to have in the interpretative framework indicated.
