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Introduction
Studies indicate that land use/land cover changes (LULCC) are driven directly or indirectly by human activities, resulting in environmental changes at various scales (Rasool et al., 2020). In certain countries, population growth, rapid economic expansion, and market growth lead to extensive and intensive land use for productive purposes, causing severe ecological issues, ecosystem degradation, biodiversity loss, and depletion of ecosystem services (Nóbrega et al., 2018). These issues are worsened by the rising demand for food and the lack of land-use planning to control urban growth, leading to significant conversion of forest lands into agricultural lands (Lopes et al., 2015). Thus, LULCC serves as a direct ecological indicator of human interaction with ecosystems (Arowolo et al., 2018).
Since land use and ecosystem services interact and constrain each other, it is crucial to economically evaluate the impact of LULCC on ecosystem services and to study the ecological and environmental effects of these changes on human well-being. This aims to provide a scientific basis for achieving sustainable development goals (Qiu et al., 2021).
Globally, the relationship between LULCC and the ecosystem services value (ESV) has been studied in various contexts and for different environmental policy objectives. Examples include the design of LULCC monitoring and control strategies (Morshed et al., 2021), optimization of land use allocation (Zheng et al., 2019), improvements in the economic performance of metropolitan areas (Akhtar et al., 2020) and the effects of urbanization (Tianhong et al., 2010). In natural ecosystems, LULCC and ESV studies have been used to analyze ecosystem conservation trends (Arowolo et al., 2018) and advance sustainable development goals (Qiu et al., 2021). In Mexico, studies linking LULCC with ecosystem services are rare, but two notable studies have focused on assessing the effects of forestry activities in the state of Veracruz (Martínez et al., 2009) and urban growth in the Gulf of Mexico region(Mendoza-González et al., 2012).
Monetary estimates of ecosystem services based on LULCC play a crucial role in raising environmental awareness and assessing the importance of ecosystems. They also help understand the relationship between ecosystems and other factors that contribute to sustainable human well-being (Su et al., 2020).
Research becomes relevant within a regional context where significant changes have occurred in the territory over the last two decades. Mexico ranks as the third-largest country in the Americas by population, boasting around 126 million inhabitants (Instituto Nacional de Estadística y Geografía [INEGI], 2020); 46 % live in states bordering the coast, including Oaxaca. These areas have experienced increased anthropization due to population growth, industrial ports, industries, and the expansion of human settlements along the coastline (Godwyn-Paulson et al., 2021). In the Costa region of Oaxaca, anthropogenic processes have been identified as altering ecosystems, including land use changes towards agriculture, livestock, tourism, and urban development (Cruz et al., 2019; Maass et al., 2009).
Therefore, this research aimed to achieve three main objectives: firstly, to classify land use/land cover (LULC) in the Copalita River watershed in the state of Oaxaca, Mexico, from 2000 to 2020; secondly, to analyze variations in each type of land cover over this period; and thirdly, to estimate the economic value of ecosystem services.
Materials and Methods
Study area
The Copalita River watershed covers approximately 152 945 hectares (Blancas-Díaz et al., 2022) and belongs to the Hydrological Region 21, which falls under Administrative Zone V, South Pacific Region, in the southern part of the state of Oaxaca, Mexico (Figure 1). The watershed comprises four sub-basins and includes 19 municipalities (seven from the Costa region and 12 from the Sierra Sur region). With a maximum altitude of 3 500 meters, it encompasses 26 of the 34 vegetation types found in the country (Mansourian et al., 2020). In the Zimatán watershed, adjacent to Copalita, 1 384 botanical species and 70 infra-species have been identified, spanning 668 genera and 144 families, underscoring the region's importance due to its plant diversity and the presence of endangered and unidentified species (Salas-Morales et al., 2003).
Analysis of changes in land use and land cover
LULC of the watershed were analyzed using Landsat 7 satellite images for the year 2000 and Landsat 8 for 2020 (https://earthexplorer.usgs.gov/). The satellite images were captured during the spring of their respective years because during this season, the spectral signatures of land cover categories can be distinguished (Fahad et al., 2021) and seasonal effects are minimized (Morshed et al., 2021). These images, with a resolution of 30 meters, were analyzed using the semi-automatic classification plugin (SCP) in the QGIS software (Belenok et al., 2021). SCP performed supervised classification based on training samples generated for each land cover type (Congedo, 2021).
Overall accuracy and kappa coefficient were considered as validation mechanisms for the LULC maps for the years 2000 and 2020. The kappa coefficient is widely used in LULCC analysis to measure accuracy and evaluate classification by comparing observed (actual) data with classified (simulated) data (Rwanga & Ndambuki, 2017). More information about these validation tools can be found in Saputra and Lee (2019).
Subsequently, using the tools available in QGIS, the transition matrix was obtained, which encapsulates the changes in land cover during the period (Feng et al., 2020). The matrix's diagonal elements denote persistence, while off-diagonal positions signify conversions from one category to another (Anley et al., 2022).
The analysis of change intensity in land use and land cover
Based on the conversion matrix, the variation in cover transitions within the watershed over a 20-year interval was analyzed to determine if they deviate from a seemingly uniform process (Aldwaik & Pontius, 2012). This analysis is conducted across three levels: interval, category, and transition. Observed changes at each level are compared with hypothetical uniform changes using quantitative measures (Akinyemi & Mashame, 2018).
At the interval level, the intensity analysis examines the size and speed of change in the watershed area. At the category level, the change in each type of land cover and land use is analyzed to determine if the observed variation is primarily quantitative or related to spatial relocation. At the transition level, the area and intensity of losses and gains between LULC categories are studied. At this level, when the value exceeds the uniform intensity line, it indicates that the category exhibits a directed transition, while falling below the line suggests an avoided transition. A directed transition implies that the LULC category experiences a loss or gain of area that is more pronounced than expected if the change had been uniform across all categories. This transition may indicate specific processes driving the LULCC in the area. An avoided transition experiences a loss or gain of area that is less pronounced than expected if the change had been uniform across all categories. This transition may indicate factors that mitigate or limit land cover change in the category in question. Detailed descriptions of intensity analysis can be found in Huang et al. (2012) and Aldwaik and Pontius (2012).
Calculation of the economic value of ecosystem services
The identified LULC types were grouped and defined based on field surveys in the watershed, the study of Salas-Morales et al. (2007) and information from the Comisión Nacional para el Conocimiento y Uso de la Biodiversidad (CONABIO, 2023). In this study, the ESV coefficients from Costanza et al. (2014) were utilized, which provide estimates for 16 major biomes and 17 ecosystem service functions. From these, the researchers selected those deemed most similar to those identified in the study area (Table 1).
Table 1 Land cover and land use in the Copalita River watershed in Oaxaca.
| Local-scale watershed coverage | Description | Global-scale biome coverage (Costanza et al., 2014) |
|---|---|---|
| Forest | Gallery3: heterogeneous. It is located in thin strips alongside rivers. Trees reach up to 12 m in height. Mesophilic2: several layers with abundance of ferns and epiphytes. Trees lose 50 % of foliage at some time of the year. Frequent rainfall and high humidity throughout the year. Conifers, mixed forests, and oak2: tall trees in temperate to cold mountainous areas. | Temperate forest |
| Rainforest | Low deciduous3: canopy height ranges from 6 to 8 m, although some species reach up to 16 m. The shrub layer reaches up to 5 m in height, and thin herbs and vines are abundant. Low thorny deciduous3: trees with heights between 4 and 5 m, some reaching up to 6 m, and are thorny. Low and medium semi-deciduous3: develops in ravines where relative humidity is higher. Dominant species reach heights of up to 15 m. Evergreen2: species with heights of up to 30 m or more, with year-round foliage. Lianas, epiphytes, and palms abound in warm and humid climates. Complex ecosystems with high species variation. | Tropical Forest |
| Wetland and mangrove 2 | Mangrove: Woody, dense, arboreal or shrubby vegetation formation up to 30 m in height. Coastal wetlands with great biological diversity. | Wetlands |
| Low coverage lands 1 | Agriculture, livestock, and deforested areas | Cropland |
| Water bodies | Rivers and streams. | Lakes/rivers |
| Construction | Urban2: dense human communities and infrastructure development that displace pre-existing communities and ecosystems. Extraction1: areas of construction material extraction. | Urban |
1Identified coverage, grouped, and named by the authors. 2Definitions from CONABIO (2023). 3Definitions from Salas-Morales et al. (2007).
The economic value coefficients of the selected biomes were adopted and assigned as the approximate economic value of ecosystem services for the most similar land cover or land use within the watershed. Table 2 shows the substitution of the monetary value coefficients from Costanza et al. (2014) with the land cover and land use types of the watershed. It can be observed that wetlands have the highest monetary value per hectare per year, while forests and rainforests have the lowest values.
Table 2 Economic value (USD·ha-1·yr-1) of ecosystem services and functions provided by land use/land cover in the Copalita River watershed.
| Service | Ecosystem function | Water bodies |
Low coverage lands |
Construction | Forest | Rainforest | Wetlands |
|---|---|---|---|---|---|---|---|
| Provisioning | Food | 106.00 | 2 323.00 | 0.00 | 270.00 | 200.00 | 952.00 |
| Raw materials | 0.00 | 219.00 | 0.00 | 152.00 | 84.00 | 416.00 | |
| Regulation | Gases | 0.00 | 0.00 | 0.00 | 4.00 | 12.00 | 0.00 |
| Climate | 0.00 | 411.00 | 905.00 | 711.00 | 2 044.00 | 200.00 | |
| Disasters | 0.00 | 0.00 | 0.00 | 19.00 | 66.00 | 4 596.00 | |
| Water | 7 514.00 | 0.00 | 16.00 | 3.00 | 8.00 | 1 789.00 | |
| Water supply | 1 808.00 | 400.00 | 0.00 | 143.00 | 27.00 | 959.00 | |
| Waste treatment | 918.00 | 397.00 | 0.00 | 120.00 | 120.00 | 111 345.00 | |
| Supporting | Erosion control | 0.00 | 107.00 | 0.00 | 100.00 | 337.00 | 3 507.00 |
| Soil formation | 0.00 | 532.00 | 0.00 | 14.00 | 14.00 | 0.00 | |
| Nutrient cycling | 0.00 | 0.00 | 0.00 | 66.00 | 3.00 | 577.00 | |
| Pollination | 0.00 | 22.00 | 0.00 | 9.00 | 30.00 | 0.00 | |
| Biological control | 0.00 | 33.00 | 0.00 | 169.00 | 11.00 | 303.00 | |
| Habitat/refuge | 0.00 | 0.00 | 0.00 | 619.00 | 39.00 | 12 452.00 | |
| Genetic resources | 0.00 | 1 042.00 | 0.00 | 448.00 | 1 517.00 | 243.00 | |
| Cultural | Recreation | 2 166.00 | 82.00 | 5 740.00 | 953.00 | 867.00 | 2 199.00 |
| Culture | 0.00 | 0.00 | 0.00 | 1.00 | 2.00 | 636.00 | |
| Total ecosystem value (USD·ha-1·yr-1) |
12 512.00 | 5 568.00 | 6 661.00 | 3 801.00 | 5 381.00 | 140 174.00 |
Finally, the evaluation model by Costanza et al. (1997), was applied, using the benefit transfer method (BTM) to estimate the ESV. This method has been utilized in recent studies (Akhtar et al., 2020; Arowolo et al., 2018; Morshed et al., 2021) and its application has increased due to the availability of technological tools and information on ecosystem values (Acharya et al., 2019; Khan et al., 2019). Despite criticisms for not considering local variations in ecosystems (Schmidt et al., 2016), the BTM allows for a quick assessment and provides useful information for natural resource management (Tolessa et al., 2021).
ESV of the six LULC types in the watershed for the years 2000 and 2020 was calculated using the following equation:
where,
ESVt = estimation of the total ESV at time t
Akt = area (ha) of a land use or land cover type k at time t
Vck = Coefficient of ecosystem service value (USD·ha-1·yr-1) of a land use or land cover type k.
The change in ESV over the period was calculated as the growth rate using the following equation:
where,
ESVcr = Rate of change of ESV during the analyzed time interval, from period t 1 to period t 2
Calculation of the economic value of ecosystem service functions
The ESV of each of the ecosystem service functions in 2000 and 2020 was estimated with the following equation:
where,
ESVft = ESV estimate of a function f at time t
Akt = area (ha) of a land use or land cover type k at time t
VCfk = coefficient of ecosystem service value of function f (USD·ha-1·yr-1) for each land use or land cover k .
Results
Land use and land cover changes in the Copalita river watershed
Figure 2 shows the classification results for the LULCC analysis using the SCP in QGIS. An overall accuracy of 88.24 % (2000) and 86.06 % (2020) and a kappa coefficient of 0.76 (2000) and 0.70 (2020) were reported. The spatial distribution of LULC categories in the watershed exhibited remarkable variations over the period studied. In 2000, forests dominated the northern, northwestern, northeastern and central zones, and rainforest cover predominated in the southern zone (Figure 2a). Two wetlands of the watershed are located at the mouth to the sea. In 2020, the areas of low coverage lands and construction (north, northeast and south) show an increasing trend, in contrast to the rainforest in the southern zone of the watershed (Figure 2b).
Figure 2 Spatial distribution of land cover and land use changes in the Copalita River Basin, Oaxaca, in the years 2000 (a) and 2020 (b).
According to Table 3, in 2000 forests covered approximately 62.61 % of the total area of the watershed, while rainforest and low coverage lands accounted for 35.20 % and 1.69 %, respectively. For the period 2000-2020, the average annual rate of forests increased by 0.62 %, rainforest decreased by 3.22 %, and low coverage lands increased by 9.32 %. Construction expanded at an average annual rate of 2.85 %.
Table 3 Conversion matrix of land use/land cover (ha) in the Copalita River watershed, Oaxaca, for the period 2000-2020.
| 2000 | 2020 | |||||||
|---|---|---|---|---|---|---|---|---|
| Water bodies | Low coverage lands | Construction | Forest | Rainforest | Wetlands | Initial total (ha) | Area (%) | |
| Water bodies | 233.28 | 148.59 | 124.56 | 156.6 | 81.99 | 10.44 | 755.46 | 0.49 |
| Land with low coverage | 124.92 | 1 069.11 | 215.82 | 580.23 | 604.17 | 7.47 | 2 601.72 | 1.69 |
| Construction | 47.97 | 122.94 | 204.03 | 145.35 | 153.72 | 1.08 | 675.09 | 0.44 |
| Forest | 27.45 | 2 389.23 | 179.55 | 89 201.07 | 4 071.87 | 2.43 | 95 871.60 | 62.61 |
| Rainforest | 71.19 | 11 732.94 | 458.64 | 18 472.77 | 23 100.57 | 19.08 | 53 855.19 | 35.20 |
| Wetlands | 3.51 | 2.16 | 1.17 | 2.16 | 4.41 | 57.24 | 70.65 | 0.04 |
| Final total (ha) | 508.32 | 15 464.97 | 1 183.77 | 108 558.18 | 28 016.73 | 97.74 | 153 829.71 | |
| Area (%) | 0.33 | 10.05 | 0.77 | 70.57 | 18.21 | 0.06 | ||
| Average annual change (%) | -1.96 | 9.32 | 2.85 | 0.62 | -3.22 | 1.64 | -0.11 | |
Analysis of land use/land cover change intensity
Interval level
The intensity analysis at the interval level revealed an observed change of 25.98 % of the watershed's territory during the period; in other words, an annual change of approximately 1.30 % in land cover and land use. Since only one interval was analyzed, at this level of analysis, the value of the uniform intensity (dashed horizontal line in Figure 3) is equal to the annual percentage change.
Category level
Figure 3 illustrates annual changes in land use categories using pairs of bars representing gross gains and losses. The dashed horizontal line indicates the average intensity of change over 20 years. Bars that exceed this line reflect activity in land cover change, while those below show inactivity. Low coverage lands, construction, and water bodies experienced active changes. Rainforest cover showed gross losses, wetlands only had gross gains and forests showed inactivity in both components.
Transition level
Rainforest and water bodies coverage decrased in the watershed’s total area. At the transition level, it was evaluated how these categories transformed towards areas more related to human activity: low coverage lands and construction, respectively.
In Figure 4a, when the category of low coverage lands gained extension, the gross annual transition mainly came from rainforest (586.65 ha) and forest (119.46 ha). In terms of percentage, Figure 4b shows that when low coverage lands gain extension, they do so intensively from the categories of rainforest (1.09 %), water bodies (0.98 %), and construction (0.91 %), while an intensive transition from forest and wetlands is avoided.
Figures 4c and 4d show the transition outcomes of the rainforest category towards other categories. In Figure 4c, when rainforest loses extension, the transition is mainly towards forest (923.63 ha) and low coverage lands (586.64 ha). Figure 4d indicates that the loss of rainforest exhibited a directed transition towards low coverage lands (3.79 %) and construction (1.94 %). Towards the rest of the categories, rainforest shows an avoided transition.
Figure 4 Intensity analysis of land use and land cover change at the transition level in the Copalita River watershed for the period 2000-2020. a) Gross annual transition area (ha) of each category towards low coverage lands; b) Annual transition intensity (%) of each category towards low coverage lands; c) Gross annual transition area (ha) of rainforest towards other categories; d) Annual transition intensity (%) of rainforest towards other categories. DT: Directed Transition and AT: Avoided Transition
Construction primarily expanded at the expense of rainforest (22.93 ha), low coverage lands (10.79 ha), and forest (8.98 ha) (Figure 5a). Water bodies (0.82 %), low coverage lands (0.41 %), wetlands (0.08 %), and rainforest (0.04 %) exhibit a directed transition towards construction, while forest (0.01 %) shows an avoided transition (Figure 5b).
Water bodies lost extension primarily to forest (7.83 ha), low coverage lands (7.43 ha), and construction (6.23 ha) (Figure 5c). Water bodies show a directed transition towards construction (0.53 %) and wetlands (0.53 %) and an avoided transition towards forest (0.01 %) and rainforest (0.01 %) (Figure 5d).
Figure 5 Intensity analysis of land use and land cover change at the transition level in the Copalita River watershed for the period 2000-2020. a) Gross annual transition area (ha) of each category towards construction; b) Annual transition intensity (%) of each category towards construction; c) Gross annual transition area (ha) of water bodies towards the rest of the categories; d) Annual transition intensity (%) of water bodies towards the other categories. DT: Directed Transition and AT: Avoided Transition.
Economic value of ecosystem services
Table 4 indicates that, in the Copalita River watershed, the ESV provided by LULC decreased by 2.21 % between 2000 and 2020, falling from 692 775 885.42 USD to 677 442 417.84 USD. Forests and rainforest were the land covers that contributed the most to the ESV in both years, jointly representing 94.46 % (2000) and 83.16 % (2020). For the same period, the value of forests increased by 13.23 %, while rainforest and water bodies decreased by 48.02 % and 32.7 %, respectively. Low coverage lands and construction, categories more related to anthropogenic activity, increased their value by 494.41 % and 75.35 %, with average annual growth rates of 9.32 % and 2.84 %, respectively
Table 4 Ecosystem service values of land cover and land use in the Copalita River Basin, Oaxaca, in the Period 2000-2020.
| Economic value | Water bodies | Low coverage lands | Construction | Forest | Rainforest | Wetlands | Total |
|---|---|---|---|---|---|---|---|
| 2000 (MUSD·yr-1) | 9.45 | 14.48 | 4.49 | 364.40 | 290.03 | 9.90 | 692.77 |
| 2000 (%) | 1.36 | 2.09 | 0.64 | 52.60 | 41.86 | 1.43 | 100.00 |
| 2020 (MUSD·yr-1) | 6.36 | 86.10 | 7.88 | 412.62 | 150.75 | 13.70 | 677.44 |
| 2020 (%) | 0.93 | 12.71 | 1.16 | 60.91 | 22.25 | 2.02 | 100.00 |
| Δ 2000-2020 (MUSD·yr-1) | -3.09 | 71.62 | 3.39 | 48.22 | -139.27 | 3.79 | -15.33 |
| Δ 2000-2020 (%) | -32.71 | 494.41 | 75.35 | 13.23 | -48.02 | 38.34 | -2.21 |
| Δ Annual average (%) | -1.96 | 9.32 | 2.84 | 0.62 | -3.21 | 1.63 | -0.11 |
MUSD: million US dollars.
Economic Value of Ecosystem Service Functions
According to Table 5, the ecosystem services of regulation and support contributed the most to the total economic value of the Copalita watershed over a 20-year period. In 2000 and 2020, these two services represented 65.95 % and 70.16 % of the total value, respectively, although their relative contribution decreased over time. In contrast, the provisioning ecosystem services had a lower contribution to the total value but experienced a 49.1% increase in their relative contribution in 2020.
The regulation and support functions of ecosystem services, specifically climate regulation and genetic resources, contribute the most to the total value of the watershed. However, the economic value of this watershed shows a decreasing trend. Nine ecosystem service functions decreased in economic value, while eight functions experienced an increase.
Table 5 Economic value of ecosystem service functions in the Copalita River watershed, Oaxaca, for the period 2000-2020.
| Ecosystem Services |
Functions | 2000 (MUSD·yr-1) |
Relative contribution (%) |
2020 (MUSD·yr-1) |
Relative contribution (%) |
Rate of change | |
|---|---|---|---|---|---|---|---|
| (MUSD·yr-1) | (%) | ||||||
| Provisioning | Food production | 42.86 | 6.19 | 70.99 | 10.48 | 28.13 | 65.64 |
| Raw material | 19.70 | 2.84 | 22.28 | 3.29 | 2.58 | 13.11 | |
| Total provisioning | 62.56 | 9.03 | 93.27 | 13.77 | 30.71 | 49.10 | |
| Regulation | Gas regulation | 1.03 | 0.15 | 0.77 | 0.11 | -0.26 | -25.22 |
| Climate regulation | 180.03 | 25.99 | 141.90 | 20.95 | -38.13 | -21.18 | |
| Disturbance regulation | 5.70 | 0.82 | 4.36 | 0.64 | -1.34 | -23.54 | |
| Water regulation | 6.53 | 0.94 | 4.56 | 0.67 | -1.97 | -30.15 | |
| Water supply | 17.64 | 2.55 | 23.48 | 3.47 | 5.84 | 33.11 | |
| Waste treatment | 27.57 | 3.98 | 33.88 | 5.00 | 6.31 | 22.90 | |
| Total regulation | 238.50 | 34.43 | 208.95 | 30.84 | -29.55 | -12.39 | |
| Supporting | Erosion control | 28.28 | 4.08 | 22.29 | 3.29 | -5.98 | -21.16 |
| Soil formation | 3.48 | 0.50 | 10.14 | 1.50 | 6.66 | 191.29 | |
| Nutrient cycling | 6.53 | 0.94 | 7.31 | 1.08 | 0.78 | 11.87 | |
| Pollination | 2.54 | 0.37 | 2.16 | 0.32 | -0.38 | -14.95 | |
| Biological control | 16.90 | 2.44 | 19.19 | 2.83 | 2.29 | 13.56 | |
| Habitat/refuge | 62.33 | 9.00 | 69.51 | 10.26 | 7.18 | 11.52 | |
| Genetic resources | 127.44 | 18.40 | 107.27 | 15.84 | -20.17 | -15.83 | |
| Total support | 247.50 | 35.73 | 237.87 | 35.11 | -9.62 | -3.89 | |
| Cultural | Recreation | 143.98 | 20.78 | 137.13 | 20.24 | -6.85 | -4.76 |
| Cultural | 0.25 | 0.04 | 0.23 | 0.03 | -0.02 | -8.79 | |
| Total cultural | 144.22 | 20.82 | 137.35 | 20.28 | -6.87 | -4.77 | |
| Total | 692.78 | 100.00 | 677.44 | 100.00 | -15.33 | -2.21 | |
MUSD: million US dollars.
Discussion
Land Use and Land Cover Changes and Intensity
From 2000 to 2020, the extent of forests, low coverage lands, and construction in the Copalita River watershed increased at an annual rate of 0.62 %, 9.32 %, and 2.85 %, respectively, challenging the trends of forest reduction documented in other studies. For instance, in the upper watershed of the Blue Nile in Ethiopia, Anley et al. (2022) reported that, over the past two decades, forests decreased from representing 6.8 % to 3.5 % of the territory, and cultivated land (included in the low coverage lands category in this study) increased from 63.7 % to 78.2 %. In that study, the trend of forest transition was opposite to the results of the present study, although the proportion of forests in the Blue Nile watershed is lower, while the trend of cultivated lands aligns with our findings. This land cover already occupied the largest proportion of the territory in the Copalita watershed in 2000, which may explain why the increase is not as significant in comparison. On the other hand, Qiu et al. (2021) analyzed the Guangxi region in China and found that the general trend of LULCC from 1990 to 2020 was a decrease in wetlands, forests, and grasslands, and an increase in drylands and construction areas, while bare land remained essentially unchanged. Among these, forests and drylands experienced the greatest change, with a net change of -6 573.578 km2 and 5 883.295 km2, respectively. Over time, the area of buildable land continued to grow, increasing by 2 309.883 km2at a rate of 1.84 % over the past 30 years. Similarly, in the Andassa basin, Ethiopia, Gashaw et al. (2018) revealed a continuous expansion of cultivated lands and buildable land, and a loss of forests, shrubs, and grasslands for the period 1985-2015, a trend expected to continue over the next three decades. The study by Gao et al. (2021) indicated an increase in the area of grassland, bare lands, water bodies, and urban areas, and a decrease in croplands, forests, and wetlands, primarily caused by the growth of urban areas. The study by Ziaul-Hoque et al. (2022) on the coast of Bangladesh noted a decrease in agricultural areas and bare land and an increase in urbanized areas, mangrove forests, water bodies, and saline/aquaculture areas. These results contrast with the increasing expansion of low coverage lands in Copalita.
In the case of Copalita, the increase in forests is attributed to local reforestation and coffee cultivation under shade (García Alvarado et al., 2017). The increase in low coverage lands and construction is due to constant intervention by human activities such as continuous land use change towards agriculture, livestock, tourism, and urbanization (Maass et al., 2009).
In contrast, rainforest experienced the greatest decrease (-48.02 %) in the Copalita watershed, consistent with studies conducted in watersheds such as Rib (Anley et al., 2022) and Andassa (Gashaw et al., 2018). The analysis of these watersheds could be useful to understand the loss of rainforest in Copalita; however, some studies report less pronounced reductions over similar periods, such as in Lake Taihu, China (-4.76 %; Gao et al., 2021) and in Pakistan and Nigeria (Aziz, 2021). Exploring the context of these losses may clarify the causes of accelerated decreases in certain watersheds.
The ecosystem services value
A decrease of 2.21% in the ESV in the watershed is estimated during the period, with an average annual rate of 0.11 %. This agrees with research on LULCC, which also shows a tendency towards a decrease in ESV over similar periods, with reductions of 13.5 % (Anley et al., 2022), 4.01 % (Ziaul Hoque et al., 2022), 23.1 % (Aziz, 2021), 3.8 % (Liu et al., 2020), 6.99 % (Gashaw et al., 2018) and 21.41 % (Gao et al., 2021).
The decrease in the economic value of the watershed is related to the transition from natural coverages such as rainforest and water bodies to land uses intensely altered by human activity such as construction and low coverage lands. This may be due to the increase in stone extraction for construction in the tourist area of Santa Cruz Huatulco and the expansion of lands for livestock and cultivation. Population growth and unplanned urbanization also contribute to this loss of economic value as indicated by Hasan et al. (2017) and Morshed et al. (2021).
In the case of wetlands, an increase in ESV is observed, supporting their conservation in coastal areas, as mentioned by Ziaul Hoque et al. (2022). However, the decrease in coverage and economic value of water bodies coincides with research indicating that urbanization, agriculture, and deforestation negatively impact the water cycle (Fahad et al., 2021; Liverman & Cuesta, 2008; Loveland & Mahmood, 2014).
To improve the accuracy of ESV estimates, it is suggested to conduct local valuation studies involving various stakeholders to avoid biases. Additionally, it could be complemented with a more detailed analysis of vegetation types in the basin through field research with vegetation specialists to better understand the ecological importance and level of degradation of each type of coverage.
The value of ecosystem service functions
The results highlight the predominance of ecosystem services of regulation and support in contributing to the total value of the watershed, despite their relative contribution decreasing during the study period. This contrasts with the study by Qiu et al. (2021), where the main components were climate and water regulation. Sannigrahi et al. (2020), in an approach without the benefit transfer method, found that the most valuable function was habitat (30 780.00 USD·yr-1), followed by nutrient cycling (12 626.00 USD·yr-1) and gas regulation (7 228.81 USD·yr-1).
The results are comparable to the decrease in the value of functions such as food production, raw materials, and biological control in Ziaul Hoque et al. (2022). In the study of Akhtar et al. (2020) climate regulation, water regulation, and food production also decreased; however, unlike that study, the value of waste treatment, soil formation, and biological control functions in the Copalita watershed increased. Nine ecosystem service functions decreased in economic value, while eight functions experienced an increase. This overall result leads to a decreasing trend in the general balance of changes in VES in the watershed.
An ecological protection priority approach tends to increase regulation and supporting services, while a focus on economic development drastically decreases them (Liu et al., 2020). The decrease in the value of regulation and supporting functions (from 65 % to 70 %), along with the increase in provisioning services (49 %), highlights the growing demand from the watershed's inhabitants, driven by activities such as tourism; therefore, planning for these needs is crucial to avoid long-term environmental impacts. Analyzing trends in the economic value of ecosystem services and functions and their spatial location over the long term becomes a valuable indicator for such planning and approaches.
Study limitations
Further research is needed to understand the underlying mechanism of LULCC and its economic impact. It is important to note that economic values do not accurately represent the value of ecosystems but function as composite indicators to understand alterations in them. In this regard, analysis in smaller intervals would improve precision in interpreting the behavior of ecosystem services; furthermore, valuing these services and their functions would require simulations of future scenarios.
Similarly, more detailed analyses at the local level would be beneficial, especially in regions with geographical and cultural similarities such as the southern-southeastern zone of Mexico and Central America; however, it is important to consider that this research may require significant resources. Nevertheless, the studies would provide more specific information and facilitate decision-making in public policy regarding ecosystem sustainability.
Conclusions
The expansion of low coverage lands and construction, along with the decrease in rainforest, reflects negative effects of anthropogenic activity in this watershed. The intensive loss of rainforest and water bodies negatively impacts the provision of ecosystem services, especially in regulation and support. The reduction in the economic value of these services highlights the importance of conserving natural coverage to sustain environmental and economic benefits. The dynamics of land cover and land use change indicate an increase in provisioning services, but with a decrease in services of higher economic value. Therefore, sustainable management strategies are required to reverse trends in land cover and land use change and to protect the ecosystem services of the watershed.
