From ridge to reef. Land use dynamics and ecosystem services in the Yuna River basin: insights for policymaking.

From ridge to reef. 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Land use dynamics and ecosystem services in the Yuna River basin: insights for policymaking. Víctor Gómez Valenzuela, Solhanlle Bonilla-Duarte, Katerin Ramírez, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4663717/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This paper aims to analyze the land use land change dynamics in the Yuna River basin in the northeast region of the Dominican Republic (DR), considering their implications for ecosystem services. The Yuna basin is one of the most critical watersheds in the Caribbean, connecting the northeastern hills of the Cordillera Central to the Atlantic Ocean in the Samaná Bay. The basin is also connected to the global value chains of agricultural and mining commodities, such as organic cocoa exports and gold, from several mining concessions in its territory. The Basin faces socioeconomic pressures expressed in the timeless analysis of land-use dynamics, which can jeopardize the basin's ability to provide ecosystem services in the medium and long term. It suggests developing an approach based on the adaptive management of ecosystems and deploying a payment for environmental services scheme for watershed restoration. Yuna river basin land use change dynamics ecosystem services natural resources management Dominican Republic Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 1. Introduction This paper aims to characterize the land use land change dynamics in the Yuna basin in the northeast region of the Dominican Republic (DR), considering the relevance of ecosystem services in a complex landscape mosaic that connects the Northeastern hills of the Cordillera Central of the DR with the Atlantic Ocean in the Samaná Bay. A river basin is a territory delimited by a hydrographic system that drains into a central waterway, to which aquifers such as streams, lakes, estuaries, and wetlands are connected to the marine area [ 1 ]. The Yuna basin drains its waters along a mosaic of productive landscapes that includes the country's leading rice and cocoa production areas for export, as well as one of the leading cattle regions, the central mining basin, and one of the axes of the interconnected hydroelectric system critical for the country's renewable energy supply [ 2 , 3 ]. Thus, the ecosystems in the basin are crucial for food security and developing agricultural, mining, and energy-productive capacities [ 4 ]. Still, these ecosystems respond non-linearly to external and internal pressures such as climate change and socioeconomic pressures through land use dynamics [ 5 – 7 ]. In turn, Samaná Bay is one of the country's most critical tourism development poles, with an infrastructure exceeding five thousand hotel rooms in an environment where ecosystem services are crucial for natural-based tourism and the development of communities around marine mammal tourism [ 8 , 9 ]. The estimated area of the Yuna basin is about 526,527 hectares (5,265.26 km 2 ), equivalent to just over 10% of the country's surface area, and with a total population in 2021 of 1,645,697 inhabitants, which may reach 2 million in its immediate area of influence, for a density of 312.5 inhabitants/km 2 [ 10 , 11 ] (see Fig. 1 ). ( Fig. 1 . Yuna river basin and sub-basins in the Dominican Republic) River basins are one of the spaces where the interactions between the environment, natural resources, economy, and society acquire a sense of urgency in the face of global challenges arising from climate change, such as adaptation processes and socio-technical transitions towards sustainability [ 12 ]. They are sensitive spaces to climatic pressure and the depletion of natural resources derived from social and economic pressures, so the study of their response as complex systems in local contexts is of enormous importance to understanding the social challenges in terms of sustainability [ 13 ]. Basins are concrete, tangible spaces, and knowing their dynamics, responses, and interactions with social and economic life puts us in a better position to address the societal challenges that arise from the global challenges we face regarding sustainability. By analyzing the ecosystem services provided in the watersheds, it is possible to study the interaction of ecosystems, social challenges, and adaptation processes as in a few other socio-environmental spaces [ 14 ]. The Yuna basin is critical in the DR due to its connection with the global value chains of agricultural and mining commodities such as organic cocoa exports and gold from several mining concessions [ 2 ]. In the DR, the Yuna basin is undoubtedly one of the most important due to its regional and national contribution to development [ 15 ]. Unfortunately, there is a lack of disaggregated economic data at the territorial level to compare the relative weight of the different hydrographic basins and their territories. However, by simple inspection, it is possible to verify the economic importance of the Yuna basin due to its strategic weight in agricultural production and mining activity. The Yuna basin is home to one of the world's most extensive open-pit gold mining operations at the Pueblo Viejo deposit, operated by the Canadian company Barrick Gold [ 2 , 16 ]. In 2021, the Dominican Republic's gold exports amounted to US $ 1,780 million, the country's main export product, placing the Dominican Republic among the 50 most important nations in mineral export [ 17 ]. It indicates the connection of the basin with global value chains through commodities derived from agricultural activity (cocoa for export) and mining products (gold, silver, and nickel), which come out of its bowels. As can be seen, the Yuna basin's ecosystems are pivotal in several economic activities, particularly in agriculture and its productivity, due to their contribution to the country's food security. This is primarily due to their ecosystem services, such as water provision for various uses [ 15 ]. Agricultural production is critical to food security, given the weight of the basin in the production of items such as rice (mainly in the lower sub-basin) and cocoa (mainly in the middle sub-basin). Other critical agricultural items include tobacco, coffee, fruit tree cultivation, and livestock (cattle and especially pig farming), representing between 50% and two-thirds of all national agricultural activity, which in 2022 represented 5.7% of GDP [ 18 ]. The DR is the world's eighth largest exporter of cocoa beans, with an estimated export value of over US $ 206 million in 2021, with the Netherlands, Belgium, and Luxembourg as its main export destinations [ 3 ]. The mining activity that occurs mainly in the middle sub-basin is the most important in the country (Monseñor Nouel and María Trinidad Sánchez provinces), contributing 1.4% of the Dominican GDP in 2022 [ 19 ]. Thus, the Yuna basin is of strategic importance for the development of the Dominican Republic as a source of wealth and well-being that connects the ecosystems of the central mountain range where the Yuna River and its main tributaries are born, with the coastal marine ecosystems of the Samaná Bay and its surroundings, which is why the adaptive management of its ecosystems along the altitudinal gradient of the basin [ 20 , 21 ], as well as the services they provide, is vital for the continuity of the economic and social contribution that the basin makes to the population of the two administrative regions that make it up and to the rest of the Dominican Republic. Thus, this paper departs from the following research questions: What is the current situation of critical ecosystems in the Yuna basin from a land use perspective? What is the relative economic importance of the ecosystems and their implications for decision-making? A land use land change (LULC) analysis of the Yuna River basin combined with available secondary data on ecosystem services was conducted to answer the above questions. Finally, understanding the dynamics of the basin's ecosystems and their landscape gradient is crucial for making informed decisions about their adaptive management [ 21 – 23 ]. It is essential to promote multifunctional landscapes for sustainability [ 24 , 25 ]. Therefore, this article is situated at an intersection where political concerns about agroecology (ecosystem services related to agriculture), renewable energies (the basin's role in producing hydro-energy), and the conservation of natural resources converge to promote sustainable livelihoods [ 26 , 27 ]. Accordingly, this article contributes to the achievement of the Sustainable Development Goals (SDGs) 14 (coastal marine ecosystems) and 15 (terrestrial ecosystems) in a broader context of the ridge-to-reef (R2R) analytical framework [ 28 ], critical for Small Development Island States (SIDS), such as the DR [ 29 , 30 ]. 2. Material and methods 2.1 The study area The Yuna River basin is a complex exoreic hydrographic system that drains its waters into the Atlantic Ocean. It connects the mountain ecosystems of the northwest of the DR with the marine area in the Samaná Bay. The system comprises two main subsystems or sub-basins, the Camú River and the Yuna River. The Camú River has an extension of 144.35 km. It rises in the Ébano Verde Scientific Reserve in the Municipality of Constanza and tributes its waters to the Yuna riverbed at the height of the municipality of Pimentel. The Yuna River, with an extension of 197.2 km, rises in the Loma de la Humeadora National Park in the Municipality of Villa Altagracia, converting all the northeast part of the country and flowing into the Mangroves of Bajo Yuna National Park in the Samaná Bay [ 31 ]. About 18 protected areas are directly related to the basin, including scenic routes, natural monuments, scientific reserves, national parks, and wildlife refuges, representing around 13% of the total surface of the basin, equivalent to about 68,661.93 hectares. Figure 2 consists of a digital elevation model of the basin that shows its elevations, the tributary rivers of the Camú and Yuna sub-basis, and its estuary in Samaná Bay, connecting the basin with the Atlantic Ocean. ( Fig. 2 . Digital Elevation Model of the Yuna Basin) The different rivers and streams that connect to each of the subsystems of the basin are highlighted, highlighting some of the structural characteristics of the landscape, such as its rugged relief in the middle and upper areas of the basin and the flood zones in the lower basin in the vicinity of the mouth of the Yuna. The structural features of the basin's landscape highlight the inherent complexity of exoreic systems such as the Yuna Basin in the Dominican Republic, emphasizing the interconnections between natural and socio-productive systems, connecting mountains to coastal and marine habitats [ 32 ]. In terms of surface water availability, it is one of the most important basins of the DR since once the flows of the Camú and Yuna rivers are integrated, it develops an average flow of around 90 m 3 /second, significantly higher than the average flows of the Yaque del Norte (40 m 3 /sec) and the Yaque del Sur (45 m 3 /sec), with an average rainfall along the basin of between 2,500 and 3,000 millimeters of rain per year [ 33 , 34 ]. It is also one of the most intervened basins in terms of hydraulic infrastructures, given that it is home to five reservoirs, including the Hatillo, Rincón, and Blanco dams, with storage capacities of 441, 75.5 and 0.73 million cubic meters of water, respectively [ 33 ]. The combined potential of its reservoirs for hydropower generation amounts to 262 gigawatt hours/year [ 34 ]. From the point of view of the altitudinal gradient, the Yuna basin has been segmented into three levels: the upper, middle, and lower sub-basins. The above segmentation is somewhat arbitrary and was carried out considering a) the contour lines of the topographic sheets at scales of 1:50 thousand, indicating essential changes in the landscape, especially in the transition from the lower to the middle sub-basin, and b) the spatial distribution of the main economic activities of the basin—mainly rice cultivation and mining. Table 1 presents the altitudinal range and surface area data for the sub-basins indicated. Table 1 The altitudinal gradient of the Yuna Basin Gradient Altitude (meters above sea level) Estimated area % Upper sub-basin 200 m.a.s.l.-2,600 m.a.s.l. 152,653.57 ha (1,526.54 km 2 ) 29 Middle sub-basin 20 m.a.s.l.-2,600 m.a.s.l. 289,366.81 ha (2,893.67 km 2 ) 55 Lower sub-basin 0–20 m.a.s.l. 84,506.96 ha (845.07 km 2 ) 16 Source: Own elaboration Table 1 . The altitudinal gradient of the Yuna Basin According to the data in Table 1 , the lower sub-basin has the smallest surface area and constitutes a flood zone comprising a rich hydrography in which the upper and middle basins converge. These characteristics of the lower sub-basin and the existing irrigation infrastructures have allowed intensive use for agricultural activities such as rice cultivation. The lower sub-basin also receives the waters of the industrial and urban activities in the middle basin, mainly mining, draining its waters into the Bajo Yuna Mangrove National Park, a rich coastal-marine estuary located in the Samaná Bay. During the boreal winter, Samaná Bay receives a population of around 1000 humpback whales from the North Atlantic in an ecosystem made up of about 239 species of birds (native, migratory, and endemic) and related protected areas such as the Los Haitises National Park or the Marine Mammal Sanctuary north of the Samaná Bay [ 8 , 35 ]. As far as the middle sub-basin is concerned, it has the largest relative area with just over 289 thousand hectares and highly intensive productive use of the soils, including mining and crops such as cocoa. The upper sub-basin is the second largest surface area, with just over 152,000 hectares, where extractive activities such as mining coexist with land uses for conservation (protected areas) and crops such as coffee. 2.2 The LULC analysis The LULC analysis for the Yuna basin was carried out for the decade between 2012 and 2022 to approximate the relationship between landscape and ecosystem services [ 1 , 20 , 21 , 36 , 37 ]. In this way, the basin can be understood as a complex system defined by a set of multi-scale and multi-level interactions of environmental, climatic, and socioeconomic factors, as well as defined by the positive and negative synergies of ecosystem services about the economic activities with which they are directly related [ 6 , 38 ]. For the Yuna basin, a LULC was carried out, based, first, on two verified layers of geospatial information on land use and land cover, corresponding to the years 2012 and 2022, which made it possible to analyze the temporal behavior of anthropogenic activities and their impact on the conservation of ecosystems in the basin. For the preparation of the classified satellite images, several geospatial software were used for the estimation of the changes in use both in units of area and in percentage changes, and with the Terrset software through the Land Change Modeler module, the change from forest land to agricultural areas and pastures was analyzed) we worked within Terrset with Machine Learning to generate potential transitions at the geospatial level [ 39 ]. Based on the preparation of images described above, to predict land use change in the basin, the year 2030 was chosen as the time horizon, and the Markov Chains technique combined with Cellular Automata was used to generate potential transitions at the geospatial level (see appendix 1 for methodological details). A Markov chain is more than a matrix of transition probabilities from one state to another that then allows us to predict land uses for a future time based on the transition probability maps generated through the classification process described above [ 40 , 41 ]. The essential mathematical expression of transition probability is: $${\sum }_{I=1}^{m}Pij=1 i=\text{1,2}\dots \dots m$$ Where: Pij = the probability of transition within a range of 0–1 from one land use to another and m = the type of land use defined for the study area [ 41 ], so that the matrix of transition probabilities in a Markov chain would be given as follows: $$P=\left(Pij\right)=\begin{array}{ccc}P11& P12\dots & P1m\\ P21& P12& P2m\\ Pm1& Pn2& Pmm\end{array}$$ The independent variables selected for the prediction were the slope of the terrain in the study area, the primary and secondary pathways of the study area, and the third-order transitions generated within Terrsset [ 42 ]. The Markov chain model, together with the analysis based on cellular automata developed within the framework of this product, has allowed the simulation of the evolution of the Yuna basin within the defined time horizon (2030) so that each pixel of geospatial data configured based on Table 3 is affected by a transition function that takes as an argument the average values of the neighboring pixels as a function of the period time Analyzed [ 36 , 41 ]. 2.3 Approach to Ecosystem Services Valuation Concerning the estimation of the relative importance of the ecosystem services of the Yuna basin, an analysis based on available secondary data on proxy markets related to the values of direct and indirect use of ecosystem services was carried out. It considered the consumptive and non-consumptive uses of water for the provision of services and a transfer of benefits perspective for the values of indirect use values for some regulating ecosystem services, in this case, carbon sequestration and fixation [ 43 – 45 ]. The transfer of benefits for the indicated regulation services was carried out using the I-Tree-Canopy software using the social carbon prices for the Dominican Republic with a value of US $ 31.00 per ton for the capture service and US $ 17.0 for the fixed carbon [ 46 , 47 ] (see appendix 2 for more details). In addition, the following assumptions were made: Around 13% of the basing surface is covered by protected areas, which represent around 68,661.94 hectares. Thus, the protected areas interacting directly with the basin were taken about green infrastructures, such as the Valle Nuevo or Los Haitises National Parks, with the Ébano or Loma Quita Espuela scientific reserves, among others. Five hundred points were used throughout the basin. The results related to removing pollutants were estimated based on valid data for Puerto Rico due to its proximity to the Dominican Republic. However, we recommend that they be discarded for now and are looked at with the greatest caution given the most significant cost differences that may be involved in using air pollutant removal technologies in the country. The above assumptions are based on a functional ecosystem perspective highlighting direct and indirect linkages between ecosystems and their components [ 48 ], i.e., as a complex system. The estimation of the non-use values of the basin using declared preference methods was not possible in the framework of this research, which resulted in a partial estimation of the Total Economic Value (VET) of ecosystem services, which considers both the use and non-use values of ecosystems [ 49 , 50 ]. 3. Results 3.1 LULC analysis. Figure 3 shows the land uses for the year 2022 on a general scale of the entire basin, indicating a level of intensive land use and a highly anthropic landscape that has functional effects on ecosystems and their capacity to provide services [ 51 ]. ( Fig. 3 . Land Use in the Yuna River Basin 2022) A complex mosaic in which intensive use of the land prevails, including the ecosystem services related to agriculture and intensive livestock, represented by rice (52,055.28 ha), cocoa (58,388.80 ha), and pasture plantations (168,046.69 ha). These agricultural uses together represent 52.9% of the surface area of the basin, thus determining the configuration of its general landscape [ 52 ]. Table 2 summarizes the primary land uses of the Yuna River basin. Table 2 Land Use in the Yuna Basin 2022 Land use Hectares % Coniferous forest 17,430.45 3.31 Broadleaf forest 122,086.52 23.19 Dry Forest 277.93 0.05 Mangrove forest 251.29 0.05 Rice crops 52,055.28 9.89 Cocoa crops 58,388.80 11.09 African palm (Oil palm) 29.97 0.01 Musaceae 19,307.59 3.67 Fruit crops (pineapple, orange, coconut, others) 2,229.23 0.42 Subsistence agriculture (dispersed crops) 2,649.46 0.50 Coffee crops 5,225.66 0.99 Pastures 168,046.69 31.92 Bodies of water 5,114.87 0.97 Built-up land 11,900.04 2.26 Mining 1,825.29 0.35 Bushes 59,708.27 11.34 Total 526,527.34 100.0 Source: Own elaboration Table 2 . Land use statistics in the Yuna Basin 2022 Rice and cocoa crops (52,055.28 and 58,388.80 hectares, respectively) demand ecosystem services such as intensive water use for the former or soil quality, pollination, or the benefits derived from biodiversity and climate regulation for the latter [ 53 ]. Concerning pastures (168,046.69 ha), it is necessary to assert that livestock farming interacts with the heterogeneity of the landscape in a multi-scale process related to the biodiversity of the grasslands, thus contributing to ecosystem services such as soil fertility and erosion control, which this economic activity is related to regulatory services and cultural services such as scenic beauty and its contribution to the Functional diversity of the landscape [ 54 ]. Considering the findings in Table 2 , about 62% of the land use is anthropogenic (about 326 thousand ha), which includes activities such as agriculture, livestock (pastures), urbanized soils, artificial water bodies, and mining, among other uses. Conservation-oriented uses represent about 26.6% of the basin's surface area (about 140,000 ha), including coniferous forests, broadleaf forests, dry forests, and mangroves in coastal areas. In the same way, land uses related to the agroecosystems of the basin, in this case, giving priority to cocoa and coffee [ 53 , 55 ], represent some 63,614 hectares, which would mean that the area of the basin intended for the development of an eventual PES program would be about 203,660 hectares, which represents 38.6% of its total area of the basin. When taken together, anthropogenic uses account for just over two-thirds of the basin's surface, which is an indicator of an economically intensive watershed that depends on ecosystem services such as water supply, soil conservation, erosion control, nutrient recycling, pest control or pollination, the latter a key element to the yield of crops such as fruit trees, cocoa or coffee, which predominate in the basin [ 5 ]. Regarding the LULC analysis comparing 2012 and 2022, Fig. 4 and Table 3 show the significant changes experienced throughout the decade. The intertemporal analysis of land use can approximate an answer to the question related to the situation of the basin's critical ecosystems. (Fig. 4 . Land Use Change 2012–2022 ) Table 3 Inter-temporal Land Use Dynamics 2012–2022 Land use 2012 2022 Change % of variation Direction Hectares % Hectares % Coniferous forest 28,155.83 5.35 17,430.45 3.31 -10,725.38 -38.09% ↓ Broadleaf forest 129,184.27 24.54 122,086.52 23.19 -7,097.75 -5.49% ↓ Dry Forest 823.29 0.16 277.93 0.05 -545.36 -66.24% ↓ Mangrove forest 3,324.36 0.63 251.29 0.05 -3,073.07 -92.44% ↓ Rice crops 52,302.86 9.93 52,055.28 9.89 -247.58 -0.47% ↓ Cocoa crops 56,049.21 10.65 58,388.80 11.09 2,339.59 4.17% ↑ African palm (Oil palm) 0.00 0.00 29.97 0.01 29.97 100.00% ↑ Musaceae 26,220.73 4.98 19,307.59 3.67 -6,913.14 -26.37% ↓ Fruit trees (pineapple, orange, coconut, others) 4,507.89 0.86 2,229.23 0.42 -2,278.66 -50.55% ↓ Coffee crops 3,733.49 0.71 5,225.66 0.99 1,492.17 39.97% ↑ Subsistence agriculture 4,079.98 0.77 2,649.46 0.50 -1,430.52 -35.06% ↓ Pastures 192,345.16 36.53 168,046.69 31.92 -24,298.47 -12.63% ↓ Body of waters 3,364.90 0.64 5,114.87 0.97 1,749.97 52.01% ↑ Built-up land 13,264.55 2.52 11,900.04 2.26 -1,364.51 -10.29% ↓ Mining 561.92 0.11 1,825.29 0.35 1,263.37 224.83% ↑ Bushes 8,608.90 1.64 59,708.27 11.34 51,099.37 593.56% ↑ Total 526,527.34 100.00 526,527.34 100.00 Source: Own Elaboration Table 3 . Inter-temporal Land Use Dynamics 2012–2022 Figure 5 summarizes the findings of Table 3 , indicating a trend of land use change in which decreased ecosystems such as coniferous forests or traditional agriculture have led to a dramatic increase in shrubland. This indicates a possible trend towards landscape deterioration. ( Fig. 5 . Land Use Statistics 2012–2022) The coniferous forest in the upper sub-basin shrank by 38% in the analyzed period, the broadleaf forest shrank by 5.4%, and the already meager dry forest lost 66% of cover. In the case of mangroves in the lower sub-basin, the impact over the decade reduced it by 92%. The most affected ecosystems have been the ones indicated, but when we look at the land uses with a vocation for conservation, the affected ecosystems went from covering an area of just over 161 thousand hectares in 2012 to 140 thousand hectares for an overall reduction equivalent to 13% of the area covered (coniferous forest, broadleaf forest, dry forest, and mangrove). Regarding intensive agriculture, the area cultivated with rice was almost unchanged (just a decrease of 0.47% between 2012 and 2022). On the other hand, the areas dedicated to cocoa and coffee cultivation experienced an increase of 4.17% and 39.97%, respectively. Fruit crops (pineapple, orange, and others.) fell by around 50% between 2012 and 2022. The area dedicated to pasture was reduced by 12.6%, as well as subsistence agriculture in the basin, which experienced a reduction of 35% from 2012 to 2022, possibly related to the diversification of productive activities in the basin and the process of demographic decline that has been experienced for several decades in the Dominican countryside. Over the decade, urban land use fell by 10%, while water bodies (dams, dams, reservoirs) increased by 52% along with mining, which expanded by more than 200%. The most striking change can be seen in the increase in shrubland, whose cover has grown by nearly 600%. In a very preliminary way and without data to confirm it, the possibility can be raised that this change may indicate a landscape degradation process as a response to the pressure of socioeconomic factors and environmental stress in the basin that affects ecosystems and the services they provide [ 51 ]. Suppose it adds up the losses of coniferous, broadleaf, grasslands (pastures), and other essential losses. In that case, the total resembles the increase in shrubland in the basin, which could indicate a trend toward deforestation. For now, there is a lack of firmer evidence to support this idea, and more research needs to be done on the matter. As indicated, it has been possible to estimate the dynamics of land use change to 2030 by using Markov chains and cellular automata, as shown in Fig. 6 . (Fig. 6 . Markov chain-based simulation 2022–2030 ). The Markov-based prediction model has limitations and should be taken as an indication of the change in the trend of land use in 2030. Table 4 summarizes the results of the Markov-chain simulation: Table 4 Land use change statistics 2022–2030 Land use Hectares Win/losses % of variation Direction 2022 2030 Coniferous forest 17,391.00 13,605.00 -3,786.00 -22% ↓ Broadleaf forest 118,195.00 119,857.00 1,662.00 1% ↑ Dry forest 309.00 308.00 -1.00 0% n/a Mangrove forest 157.00 99.00 -58.00 -37% ↓ Rice crops 51,365.00 51,363.00 -2.00 0% n/a Cocoa crops 56,339.00 56,333.00 -6.00 0% n/a Fruit crops (pineapple, orange, coconut, Musaceae, oil palm, others) 21,496.00 21,496.00 0.00 0% n/a Subsistence agriculture 2,645.00 2,642.00 -3.00 0% n/a Pastures 161,879.00 152,599.00 -9,280.00 -6% ↓ Body of waters 5,077.00 5,077.00 0.00 0% n/a Built-up land 11,687.00 11,683.00 -4.00 0% n/a Mining 1,761.00 1,721.00 -40.00 -2% ↓ Bushes 71,347.00 82,695.00 11,348.00 16% ↑ Source: Own elaboration Table 4 . Land use change statistics 2022–2030 The findings in Table 4 are consistent with the land use change between 2012 and 2022. By 2030, the trend continues, significantly affecting coniferous forests in the upper sub-basin (projected decrease of 22% of the area) and mangrove forests in the lower sub-basin (projected reduction of 37%). Despite their limitations, these scenarios clearly show the urgency of an intervention that ensures the capacities of the identified critical ecosystems to provide services. Figure 7 gives a more unambiguous indication of the projected dynamics for 2030. ( Fig. 7 . Land Use Statistics for 2030) As shown in Fig. 7 , the big losers in the coming years are land uses related to the conservation of ecosystems. The coniferous forest in the upper basin, essential for the water supply service for consumptive and non-consumptive uses, will be reduced by more than 20% compared to 2022, having already experienced a loss of 38% compared to 2012. This situation will undoubtedly put much more stress on the basin and its ability to meet the demand for surface water for the coming decades, considering that by 2040, the market is expected to reach 2,540.22 million cubic meters per year, not to mention the adverse effects on support and regulation services that the trend of landscape degradation marked by the simulation would have Performed. The trend of the mangrove in the lower basin is just as dramatic, so it is very likely that if the simulated scenario continues, the mangrove will tend to disappear from the areas in which it was found in 2022. The efforts of organizations such as CEBSE will likely contribute to reversing this trend in the lower Yuna basin. The trend of change and possible landscape deterioration continues with the increase in shrublands by more than 15% compared to 2022, having already experienced an increase of more than 500% compared to 2012. The impact of reducing the area occupied by these ecosystems can be varied. In the case of the ecosystems of the upper basin, it can be translated, on the one hand, into the decrease of the water balance of the basin, specifically in the amount of water stored in its aquifers, and on the other hand, in the increase in the rates of soil erosion and sediment entrainment to hydroelectric reservoirs will decrease its lifespan and reducing its efficiency. Without counting, ecosystem services regulation would no longer capture carbon [ 56 ]. In the case of mangrove ecosystems, their reduction has several implications from the point of view of the provision of a wide vector of ecosystem services, ranging from a decrease in net biomass productivity to an increase in the risk of flooding as a result of increased exposure to the eventual tropical storms that regularly hit the Caribbean [ 57 ]. The dramatic reduction of the mangrove forest already experienced between 2012 and 2022 is a powerful wake-up call as the income generated by fishing is affected, and protection is diminished, among other services [ 57 ]. It is worth saying that mangroves are one of the most productive and dynamic ecosystems for decomposing and recycling nutrients and carbon sequestration [ 58 ], contributing to waste assimilation. However, it is also an ecosystem that serves as a refuge for around 239 species of birds (native, migratory, and endemic) in the surroundings of the Samaná Bay at the mouth of the Yuna River [ 8 ]. How does the destruction of the mangrove affect Samaná Bay's ability to receive a population of around 1000 humpback whales from the North Atlantic during the boreal winter? We cannot answer this question in the context of this report. However, a PES intervention is undoubtedly required to protect and restore a critically threatened ecosystem in the lower Yuna sub-basin. Therefore, the landscape along the altitudinal gradient over the next decade is proposed to be managed from a multifunctional landscape perspective [ 59 ]. 3.2 The relative economic importance of ecosystem services Given the available data and paper purpose, let’s focus only on provisioning (water supply) and regulatory (CO 2 sequestration) ecosystem services [ 12 , 14 ]. Supporting and cultural ecosystem services can be considered as assumed and should be estimated further on [ 14 ]. An example of the economic and social importance of the Yuna basin can be seen in the water supply service for consumptive (agricultural, industrial, and residential) and non-consumptive (hydroelectricity, recreation, and tourism) uses. The first thing to consider is that the Yuna basin produces about 15% of the available surface water in the DR, equivalent to about 3,600 million cubic meters per year (MCM/year) [ 60 , 61 ]. Table 5 shows the participation of the Yuna basin in the generation of surface water supply. Table 5 Surface water availability by hydrographic regions Hydrographic regions Millions of cubic meters % Yaque del Norte river basin 2,945.46 12.33 Atlantic region 4,634.73 19.67 Yuna river basin 3,600.96 15.28 East Region 3,195.95 13.56 Ozama-Nizao region 4,459.08 18.92 Yaque del Sur river basin 4,771.51 20.25 Total 23,567.69 100.00 Source: Own elaboration Table 5 . Surface water availability by hydrographic regions Combining different sources of information from public organizations, the basin's water demand for consumptive and non-consumptive uses could be estimated at 2,510.42 million MCM/year by 2020, of which 51.69% corresponds to consumptive uses (1,297.66 MCM/year) and 48.21% to non-consumptive uses (1,212.76) [ 4 , 61 – 63 ]. The above demand is equivalent to 69.7% of the entire surface water supply of the basin estimated in the National Hydrological Plan [ 61 ]. The estimate of the projected demand for 2020 is slightly higher than that made in the framework of the INDRHI Trends and Scenarios Report [ 62 ], given that the estimated demand for turbine water for hydroelectricity generation in the Yuna basin has been added for more clarity [ 4 , 63 ]. Based on the previous estimate, of the consumptive uses (1,297.66 MCM/year), 66.63% were dedicated to agriculture, 18.24% to livestock (combined agriculture represents 84.87% of consumptive uses), human consumption represented about 9.27%, and industry and mining 5.86%. Figure 8 shows the distribution of the consumptive uses and the number of millions of cubic meters per year of each activity. ( Fig. 8 . Consumptive uses of water in the Yuna basin) As indicated in Fig. 8 , the demand for water for non-consumptive uses, especially for hydroelectricity generation, stood at around 1,212.76 MCM/year. The amount of water turbines used for hydroelectricity generation is equivalent to 48.21% of the surface water availability. Figure 9 shows the water demand and availability estimated by INDRHI [ 62 ]. ( Fig. 9 . Water supply and demand in the Yuna Basin) Figure 9 shows that the basin is not a linear system. As can be seen, in the years 2001, 2002, 2003, 2007, 2009, 2010, 2016, 2018, 2019, and 2020, water availability was below demand, that is, for ten years of the series. The situation described in the graph is likely related to climate variability and the effects of droughts caused by events such as the Southern Oscillation, better known as El Niño, whose effects have been documented for the insular Caribbean [ 62 , 64 ], shown, in this case, the environmental climate vulnerability of the basin, regardless of any projection scenario on demand and availability of its water balance. Assuming a conservative range of variability of around 10% between estimates of different future scenarios defined by INDRHI [ 62 ] and the projected demand for water for the basin made in this report (2,510.42 MCM/year), for the years 2040 and 2060 would be in ranges between 2,478.19 and 2,726.00 MCM/year and between 2,666.38 and 2,933.02 MCM/year, respectively. In other words, at the upper limits of the projected demand for the years 2040 and 2060, between 75.42% and 81.47% of the entire capacity of the surface water supply of the basin would be reached without adding these estimates, the ecological flow projected for 2040 and 2060 at 991.39 MCM/year [ 62 ]. Therefore, it can be said that the ecosystem services of the Yuna basin, such as the provision of water for consumptive and non-consumptive uses, not only for the present but also for the future, are under significant anthropic pressure that may jeopardize the ability of the basin's ecosystems to provide them sustainably in the medium-long term. Based on the hydrological relevance of the Yuna River basin for the Dominican Republic, the approach followed for the monetary estimation of the ecosystem services of the basin has been that of proximate markets [ 43 ]. For the values of water demand for consumptive and non-consumptive uses, the total volume of water used for consumptive purposes was considered to make it available for other uses. According to the data in this report, the demand for water for different uses (consumptive and non-consumptive) as of 2020 is 2,889.76 MCM/year per year, of which 37% corresponds to consumptive uses, that is, 1,069,211.2 and 1,820, 548 MCM/year for consumptive and no-consumptive uses, respectively. An average cost of US $ 0.60/m 3 was assumed for effluent treatment (data provided by Barrick Gold) so that, directly, the value of water for consumptive purposes would be around US $ 641.5 million a year. The best proxy in the Yuna basin for non-consumptive water use is the production of hydroelectricity. Table 6 summarizes the available information on the average generation of hydroelectric plants in GW/year in 2020 of the basin and the volume of turbine water in MCM, i.e., the volume of water used to produce electricity [ 63 ]. Table 6 Hydroelectric production and turbine water Hydroelectric Production GW/year Turbine water in MMC Hatillo complex 82.32 740,560,426 Pinalito complex 93.5 62,523,227 Rincón complex 21.23 241,329,669 Rio Blanco complex 113.5 168,347,503 Total 310.6 1,212,760,825 Source: Own elaboration Table 6 . Hydroelectric production and turbine water The opportunity cost for hydroelectricity production for the wholesale market has been estimated at $ DOP 0.82/m3, equivalent to US $ 0.014/m3 [ 4 ], so that the value of non-consumptive water use in the basin considering not only turbine water but the overall potential of water for available non-consumptive use (63% of the surface water supply indicated above), the value of water for non-consumptive use would be US $ 25.4 million/year. Based on the above estimates, the water supply service's value for consumptive use (US $ 641.5 million) and non-consumptive use (US $ 25 million) is around US $ 667.0 million/year . The value of the water supply service is about 3.2 times greater than that of cocoa exports and is only surpassed by the export of gold and silver in the basin. Regarding regulating ecosystem services (capturing and fixing CO2) [ 65 – 67 ], our findings indicate that the Yuna River captures about 3.17 million t/CO2/year, and the fixed carbon in trees is around 41.4 million t/CO 2 . The estimated social prices for CO 2 in the DR range from US $ 31.00/tCO for carbon sequestration to US $ 17/tCO 2 for fixed CO 2 [ 46 ]. Thus, the value of regulating ecosystem services only considering CO 2 sequestration is about US $ 98.2 million/year . In conclusion, the Yuna River basin provides ecosystem services for around US $ 765.2 million/year (see Table 7 ). Table 7 Selected ecosystem services in Yuna river basin Ecosystem services Value US $ (mm) % Provisioning services Consumptive use of water 641.5 83.8 Non-consumptive use of water 25.4 3.3 Regulating services Annual Carbon Sequestration 98.2 12.8 Estimated Total Annual Value 765.2 100.0 Source: Own elaboration It should be noted that coniferous ecosystems have suffered a significant loss in 2022 (38% compared to 2012), and mangrove ecosystems in the lower basin, which were reduced by 92%, or the already meager dry forest whose surface area was reduced by 66% compared to 2012. It points out a critical situation for ecosystem services in the coastal zone, especially considering the relevance of blue carbon sequestration for coastal ecosystem management [ 65 , 66 ]. The possible trend of landscape degradation caused by a complex dynamic of land use change over a decade reduces the capacity of ecosystems to provide services and fulfill their ecological functions, and this translates directly into the reduction of the capacity of ecosystems to provide ecosystem services of regulation or support. Table 7 . Use values of the basin's ecosystem As seen in Table 7 , the weight of the use values of the basin's ecosystems falls on the water supply service for consumptive uses (83.8%). The most productive ecosystems in the basin, and at the same time the most threatened, are found in the upper basin in terms of water supply and regulation services (coniferous forest in the upper sub-basin, essential for water supply services and carbon sequestration and mangrove in the lower sub-basin). 4. Discussion: insights for policymaking A vital issue for the future of systems with the complexity of the Yuna basin is to consider how to maintain the capacity of its ecosystems to provide services given its regional and national importance, as well as the growing trend of its economic and productive activities that imply an increase in the demand for provision services such as water for consumptive and non-consumptive uses and other services. For the coming years, in the face of a scenario of deterioration of the landscape and the functions and services of its ecosystems. Based on the results discussed above, this section proposes some general elements to be considered in decision-making on conservation and sustainable development in the context of the Yuna basin, which can be comparable to contexts of similar complexity that face similar challenges. 4.1 An R2R approach The exoreic nature of the Yuna Basin is critical to developing an R2R approach for the adaptive management of the Yuna Basin ecosystems and the services they provide along its entire altitudinal gradient. An R2R consists of an integrated approach to the ecosystem services that connect mountain systems with coastal-marine systems through watersheds. It considers the effects of landscape on water and emphasizes the interconnections between natural and socio-productive systems, connecting mountains with coastal and marine habitats [ 32 ]. The interconnections between the ecosystems of the Yuna basin along its altitudinal gradient and the economic activities carried out in it indicate the need for a comprehensive approach to managing local ecosystems due to the effects such interactions have on the landscape, especially when considering their relationship with ecosystem services [ 52 ]. The most obvious indicators of these effects can be seen in the marked decrease in land uses for conservation in the basin between 2012 and 2022, especially the impact on the coniferous forest (-38.09%) and the riparian mangrove forest (-92.44%), as well as in the trend of general deterioration of the landscape by 2030. In the context of tropical marine ecosystems from riparian mangrove forests, coral reefs, and seagrass meadows, global factors such as climate change and local factors such as increased land runoff, erosion of mountain soils, upstream land-use change due to inappropriate production practices, Infrastructure development, and water pollution act together as environmental stressors, affecting the provision and chains of ecosystem services in coastal-marine zones [ 67 ]. The result of these complex dynamics includes the impact on ecosystem services related to social, cultural, and biological values and the economic activities on which the communities that interact along the watersheds that connect mountains with coastal marine areas depend [ 1 , 68 ]. At the level of coastal-marine ecosystems, factors such as soil erosion and sediment dragging from upstream can negatively impact marine biodiversity, affecting economic activities such as tourism or fishing [ 68 ]. 4.2 Promoting Multifunctional Landscapes The multifunctional landscape approach would represent a paradigm shift in the integrated management of ecosystems that are part of the country's watersheds. Planning under a land-use scheme that recognizes the benefits of ecosystem services and their economic importance can generate multifunctionality with a more diverse supply of goods (market and non-market), leading to more significant environmental, social, and economic benefits [ 25 ]. Therefore, in the case of the Yuna basin, it is necessary to increase the multifunctional use of the landscape under a sustainability governance scheme, which improves its functional diversity and the resilience of ecosystems along the altitudinal gradient of the basin [ 7 ]. For example, the broadleaf forest plays a connectivity role along the basin's altitudinal gradient, and combined with the cocoa and coffee agroecosystems, it contributes substantially to the ecosystem services generated in the basin. A clear issue is that the development of a PES program in the basin must go hand in hand with straightforward and focused initiatives for the restoration of ecosystems along the altitudinal gradient, as well as with economic tools and instruments that promote a change in behavior in social and economic agents that allow them to take advantage of the ecosystem services provided by a basin with a sense of social and intergenerational equity—regional and national importance, such as that of the Yuna. 4.3 The development of PES schemes Considering the problem of natural resource management that affects the mountain ecosystems of the DR [ 69 – 71 ], especially in the Yuna basin, where two main subsystems originate in mountain-protected areas, as well as the complex mosaic of landscape-scale land use, the Payment for Environmental Services (PES) approach can be helpful to promote more integrated ecosystem management as well as multifunctional landscapes that contribute to the sustainability of the basin, that is, with the capacity of the system to provide services following the challenges and demands of local and national development, given the importance of the Yuna basin for the Dominican economy. Following Wunder's definition [ 72 ], a PES is a " (1) voluntary transaction in which (2) a well-defined environmental service (or corresponding land use) is (3) "purchased" by a (minimum one) purchaser of environmental services (4) from a (minimum) environmental service provider (5) if and only if its provision is guaranteed (conditionality) ." This definition emphasizes three significant aspects of a PES scheme: PES's transactional and voluntary nature indicates its potential as an economic instrument. Agents (seller and buyer) who transact a good (environmental service or land use) Conditionality for payment or compensation to be made, i.e., that the good or service can be provided under the conditions agreed upon and verified under the same terms. Therefore, the central idea behind a PES is, on the one hand, the practical application of Coase's theorem in the sense that, given the required institutional conditions, economic actors can agree among themselves rights and obligations (which can take the form of financial transactions in cash or in-kind), to improve their welfare and resolve the negative externalities that their economic activities cause on each other as long as the costs of transaction remain very low [ 45 ]. Therefore, considering the sustainability challenges faced by the Yuna basin, and based on the analysis of the land-use dynamics of the basin's landscape, as well as the general estimate of the economic importance of specific ecosystem services provided by its ecosystems, it is suggested that the actions of an eventual PES program focus on: Management of water supply services for different uses Ecosystem restoration (specifically with a climate regulation approach), especially around protected areas. Sustainable production and use of the land (specifically the conversion of forest to shrubland), as well as the rational use of water. Biodiversity conservation and management of the protected areas of the Lower Basin Capacity building for sustainability. In practical terms, the idea is that certain land uses in the Yuna basin, either for conservation-restoration purposes (reforestation) or for productive purposes (good land use practices such as the use of barriers, terraced cultivation, or fallow), benefit rights holders (landowners) as well as downstream users (higher water quality and quantity, lower treatment costs, among others). It is expected that the deployment of a PES program in the Yuna basin will provoke a change in the behavior of its stakeholders that translates into an improvement in the health indicators of its ecosystems and in adaptive management of them and the services they provide, with a sense of inclusion and intergenerational equity. An important additionality of the PES approach for the Yuna Basin is that it allows for the consideration of trade-offs between services provided for various plausible future land-use scenarios based on priorities that watershed users and stakeholders can identify. Thus, ecosystem services can serve as a tool for watershed planning by incorporating actors into a management scheme consistent with policy objectives and based on learning [ 73 ]. It implies that systems focused on the management of ecosystem services (e.g., payment systems) operate as means and instruments of public policy, so from an institutional point of view, they can improve the capacity for the implementation of initiatives for the conservation and sustainable management of ecosystem services, supporting the implementation of sustainable practices, promoting participation, and improving coordination among institutional actors to facilitate the management of natural capital [ 74 , 75 ]. 5. Concluding remarks, limitations, and further research. The challenges the Yuna River basin experiences regarding sustainability in achieving SDG 14 and 15 are significant and serve as an example of the difficulties confronting hydrographic basins in SIDS that are highly impacted by anthropogenic activities. In this sense, this article has presented the preliminary results of the analysis of the situation of the critical ecosystems of the basin and the economic importance of the ecosystem services provided not only for the northeastern region of the DR but for the entire Caribbean country. However, these results are partial, and the analysis of the state and health of the basin's ecosystems must be expanded. In terms of the analysis of the health of local ecosystems, primary information is needed on the ecological functions and energy flows of critical ecosystems such as pine forests and mangroves. Thus, more attention and research focus are necessary to support the adaptive management of protected areas in the basin, as well as knowing in more detail their biodiversity or the responses of ecosystems to the pressures of variability and climate change. The absence and dispersion of primary data is a problem for making adaptive decisions, and creating a research program for the main hydrographic basins of the country is recommended. In terms of economic analysis, progress must be made towards a total economic value approach that incorporates the non-use values of ecosystems through stated preference approaches. It is necessary to better understand social preferences regarding conservation and local sustainable development as part of a broader feasibility exercise on alternatives and medium and long-term intervention strategies in the basin. From the point of view of the implementation of economic instruments regarding PES that stakeholders can adopt, it is necessary to deepen the analysis of Dominican environmental legislation so that progress can be made in defining a policy mix for the adaptive management of the basin's natural resources. A methodological alternative may be using discrete selection experiments to evaluate some of the available economic instruments and determine their probability of adoption by the identified stakeholders. The mapping of social actors in the different sub-basins is another element to consider for the design of a more integrated strategy in terms of sustainable development at the local level, which includes the design of broader mechanisms and instruments, such as the creation of a Water Fund for the Yuna basin through which different experiences and mechanisms of PES and local development can be implemented, such as the development of decentralized PES markets through the use of technologies such as blockchain and the implementation of solutions based on the scale nature of small and medium producers located along the altitudinal gradient of the basin, especially in the upper and lower sub-basins. Finally, in the medium and long term, the Yuna basin will experience significant pressure on certain ecosystem services, such as providing water for consumptive and non-consumptive uses. Thus, the basin's response capacity will depend on the health of its ecosystems and how they respond to complex dynamics, such as the effects of climate variability and climate change. The above represents a considerable challenge in terms of sustainability, which requires the participation not only of public authorities but also the involvement of multinational and national private interests with a presence in the basin that depends on the exploitation of the natural resources of the territory bathed by the Yuna River. Declarations Author Contribution VGV: Conceptualization, Methodology, Writing-Original draft preparation, Supervision, Funding acquisition; SBD: validation and draft preparation; KR: validation and draft preparation; CBG: Data management, GIS analysis, field support; APE: Data management, field support. Acknowledgement The authors thank the Interamerican Development Bank (IDB) for their partial support in preparing this work connected to their initiative on ecological restoration and management of the Yuna River basin from Ridge to Reef, particularly to Jean Marie Benoit Lefevre and Elia Mariel Martínez Moises, from the IDB National office in Santo Domingo. References Comeros-Raynal MT, et al. Applying a ridge-to-reef framework to support watershed, water quality, and community-based fisheries management in American Samoa. Coral Reefs. 2019;38(3):505–20. Gómez-Valenzuela V, et al. Mining conflict in the Dominican Republic: The case of Loma Miranda. Resour Policy. 2020;66:101614. OEC. Granos de Cacao en República Dominicana. 2023 [cited 2023 30-08-2023]; https://oec.world/es/profile/bilateral-product/cocoa-beans/reporter/dom#:~:text=2021%20)%20%24206M-,En%202021%2C%20República%20Dominicana%20exportó%20%24206M%20en%20Granos%20de,Suiza%20(%2412%2C7M ). Martínez Sosa J. 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La Biodiversidad en la República Dominicana. 1 ed. Santo Domingo, D. N.: Ministerio de Medioambiente y Recursos Naturales (MARENA); 2020. p. 608. MARENA, Inventario Nacional Forestal de la República Dominicana . 2021, Ministerio de Medio Ambiente y Recursos Naturales (MARENA): Santo Domingo, D. N. p. 288. Martinez-Batlle JR. Fire and forest loss in the Dominican Republic during the 21st Century. bioRxiv, 2022: p. 2021.06.15.448604. Wunder S. Payments for environmental services and the poor: concepts and preliminary evidence. Environ Dev Econ. 2008;13(3):279–97. Terrado M, et al. Integrating ecosystem services in river basin management plans. J Appl Ecol. 2016;53(3):865–75. Engel S, Pagiola S, Wunder S. Designing payments for environmental services in theory and practice: An overview of the issues. Ecol Econ. 2008;65(4):663–74. Costanza R. Valuing natural capital and ecosystem services toward the goals of efficiency, fairness, and sustainability. Ecosyst Serv. 2020;43:101096. Additional Declarations No competing interests reported. Supplementary Files Appendix1.docx Appendix2.pdf Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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Valenzuela","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/0lEQVRIiWNgGAWjYDACZmTOBwMog4eBgbEBtxaEHOMMAwYJwlqQ5ZiBKglrMTjO/PzBxz0Mdv1ihw9/tim4U8fPfoDxwds2Btl+XFoOsxk2znjGkDxzdlqCcY7BMwnJngRmw7ltDMYzcVgj2czD2MxzgCHZ4HaOQXKOwWEJgxsMbNK8bQyJGw4Q1JL/4bAFUIv9DQb23/i08DNDtNgBbWFsZgDZIsHAxoxfC5vhzBkHJBIkZ6cZM/YYHJaccSaxWXLOOQmcfmHjP/zgw4cDNvb80smPP/z4c5ifv/3wwQ9vymxwhhgUSCQiGQmOEQn8GoDAnqCKUTAKRsEoGLkAAFrjVXYfUlN0AAAAAElFTkSuQmCC","orcid":"","institution":"Instituto Tecnológico de Santo Domingo","correspondingAuthor":true,"prefix":"","firstName":"Víctor","middleName":"Gómez","lastName":"Valenzuela","suffix":""},{"id":331561455,"identity":"8fca9ebf-e58a-4d3a-822a-b48541c23fbb","order_by":1,"name":"Solhanlle Bonilla-Duarte","email":"","orcid":"","institution":"Instituto Tecnológico de Santo Domingo","correspondingAuthor":false,"prefix":"","firstName":"Solhanlle","middleName":"","lastName":"Bonilla-Duarte","suffix":""},{"id":331561456,"identity":"402e63d0-f89d-438c-ab38-f2be5573601e","order_by":2,"name":"Katerin Ramírez","email":"","orcid":"","institution":"Instituto Tecnológico de Santo Domingo","correspondingAuthor":false,"prefix":"","firstName":"Katerin","middleName":"","lastName":"Ramírez","suffix":""},{"id":331561457,"identity":"28feb7a1-d53e-4e14-bdff-be34f8b1246d","order_by":3,"name":"Claudia Caballero Gonzalez","email":"","orcid":"","institution":"Instituto Tecnológico de Santo Domingo","correspondingAuthor":false,"prefix":"","firstName":"Claudia","middleName":"Caballero","lastName":"Gonzalez","suffix":""},{"id":331561458,"identity":"bd715f0c-6799-46d5-a3b5-c2e08892e6fb","order_by":4,"name":"Ana Pou Espina","email":"","orcid":"","institution":"Instituto Tecnológico de Santo Domingo","correspondingAuthor":false,"prefix":"","firstName":"Ana","middleName":"Pou","lastName":"Espina","suffix":""}],"badges":[],"createdAt":"2024-06-30 17:03:47","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4663717/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4663717/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":61314064,"identity":"fc235f50-5756-4a77-9ae1-4f8d278d6e20","added_by":"auto","created_at":"2024-07-29 11:40:01","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":705722,"visible":true,"origin":"","legend":"\u003cp\u003eLocation of the Yuna river basin in the Dominican Republic\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-4663717/v1/c04cc67ebf431d88870ac513.png"},{"id":61314692,"identity":"374d5e26-4c6c-489a-b6d9-d6f3100e465a","added_by":"auto","created_at":"2024-07-29 11:48:01","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1144052,"visible":true,"origin":"","legend":"\u003cp\u003eDigital elevation model of the Yuna river basin\u003c/p\u003e\n\u003cp\u003eSource: Own elaboration\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-4663717/v1/65a1198c17c490115d8ca5af.png"},{"id":61314072,"identity":"d967c2eb-c346-4a31-a283-4d198451c82f","added_by":"auto","created_at":"2024-07-29 11:40:01","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":761474,"visible":true,"origin":"","legend":"\u003cp\u003eLand use in the Yuna river basin in 2022\u003c/p\u003e","description":"","filename":"image3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4663717/v1/c0d1d17bc37ecded9f76feb0.jpeg"},{"id":61314066,"identity":"12fe80f9-bf87-4c7b-b3f8-1d3641d11280","added_by":"auto","created_at":"2024-07-29 11:40:01","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1270247,"visible":true,"origin":"","legend":"\u003cp\u003eLand use change 2012-2022\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-4663717/v1/2a7ce6d983e34e2e6bd8687f.png"},{"id":61314067,"identity":"0cd4e509-27a3-4b94-afaf-c23d2c7d2c07","added_by":"auto","created_at":"2024-07-29 11:40:01","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":63562,"visible":true,"origin":"","legend":"\u003cp\u003eLand use change statistics 2012-2022\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-4663717/v1/77fc1c719b2cde3e7cf490ce.png"},{"id":61314069,"identity":"567de138-ef56-4ff9-82d8-383f737da7a3","added_by":"auto","created_at":"2024-07-29 11:40:01","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":351627,"visible":true,"origin":"","legend":"\u003cp\u003eMarkov chain-based simulation 2022-2030\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-4663717/v1/519ff414fec5cf93642bc669.png"},{"id":61314065,"identity":"2b21170a-816d-46d0-bd5b-f1ba56fc1b9e","added_by":"auto","created_at":"2024-07-29 11:40:01","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":49298,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eLand Use statistics for 2030\u003c/em\u003e\u003c/p\u003e","description":"","filename":"image7.png","url":"https://assets-eu.researchsquare.com/files/rs-4663717/v1/48938835c798edbfce2e25cc.png"},{"id":61314693,"identity":"a156b249-7dfb-4ad1-a23d-de1771a61639","added_by":"auto","created_at":"2024-07-29 11:48:01","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":41720,"visible":true,"origin":"","legend":"\u003cp\u003eConsumptive uses of wáter in the Yuna river basin\u003c/p\u003e\n\u003cp\u003eSource: Own elaboration\u003c/p\u003e","description":"","filename":"image8.png","url":"https://assets-eu.researchsquare.com/files/rs-4663717/v1/e74106ea813a01acdf292003.png"},{"id":61314071,"identity":"bc027559-dcab-4041-9f9d-ebe296baaefa","added_by":"auto","created_at":"2024-07-29 11:40:01","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":117050,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eWater supply and demand in the Yuna Basin\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eSource: Own elaboration with data from INDRHI\u003c/p\u003e","description":"","filename":"image9.png","url":"https://assets-eu.researchsquare.com/files/rs-4663717/v1/c545f6e5cc233123f7cbd0da.png"},{"id":76721241,"identity":"e11b5b53-7b14-43c0-bb72-d5d71175f3d6","added_by":"auto","created_at":"2025-02-20 04:38:53","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5923936,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4663717/v1/85e572dc-79b4-4944-8f2c-632b43a881ca.pdf"},{"id":61314073,"identity":"3e8edee6-3c86-4109-bcbd-0d5da4561686","added_by":"auto","created_at":"2024-07-29 11:40:01","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":3482948,"visible":true,"origin":"","legend":"","description":"","filename":"Appendix1.docx","url":"https://assets-eu.researchsquare.com/files/rs-4663717/v1/971a1babdc912e10dc494a32.docx"},{"id":61314074,"identity":"55b09400-655c-4d8f-bed3-1d64ccb43f53","added_by":"auto","created_at":"2024-07-29 11:40:02","extension":"pdf","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":445427,"visible":true,"origin":"","legend":"","description":"","filename":"Appendix2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4663717/v1/59b53e5f4d3ef6483ab8a669.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"From ridge to reef. Land use dynamics and ecosystem services in the Yuna River basin: insights for policymaking.","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThis paper aims to characterize the land use land change dynamics in the Yuna basin in the northeast region of the Dominican Republic (DR), considering the relevance of ecosystem services in a complex landscape mosaic that connects the Northeastern hills of the Cordillera Central of the DR with the Atlantic Ocean in the Saman\u0026aacute; Bay. A river basin is a territory delimited by a hydrographic system that drains into a central waterway, to which aquifers such as streams, lakes, estuaries, and wetlands are connected to the marine area [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe Yuna basin drains its waters along a mosaic of productive landscapes that includes the country's leading rice and cocoa production areas for export, as well as one of the leading cattle regions, the central mining basin, and one of the axes of the interconnected hydroelectric system critical for the country's renewable energy supply [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Thus, the ecosystems in the basin are crucial for food security and developing agricultural, mining, and energy-productive capacities [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Still, these ecosystems respond non-linearly to external and internal pressures such as climate change and socioeconomic pressures through land use dynamics [\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. In turn, Saman\u0026aacute; Bay is one of the country's most critical tourism development poles, with an infrastructure exceeding five thousand hotel rooms in an environment where ecosystem services are crucial for natural-based tourism and the development of communities around marine mammal tourism [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The estimated area of the Yuna basin is about 526,527 hectares (5,265.26 km\u003csup\u003e2\u003c/sup\u003e), equivalent to just over 10% of the country's surface area, and with a total population in 2021 of 1,645,697 inhabitants, which may reach 2\u0026nbsp;million in its immediate area of influence, for a density of 312.5 inhabitants/km\u003csup\u003e2\u003c/sup\u003e [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] (see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003e(\u003c/em\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. \u003cem\u003eYuna river basin and sub-basins in the Dominican Republic)\u003c/em\u003e\u003c/p\u003e \u003cp\u003eRiver basins are one of the spaces where the interactions between the environment, natural resources, economy, and society acquire a sense of urgency in the face of global challenges arising from climate change, such as adaptation processes and socio-technical transitions towards sustainability [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. They are sensitive spaces to climatic pressure and the depletion of natural resources derived from social and economic pressures, so the study of their response as complex systems in local contexts is of enormous importance to understanding the social challenges in terms of sustainability [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Basins are concrete, tangible spaces, and knowing their dynamics, responses, and interactions with social and economic life puts us in a better position to address the societal challenges that arise from the global challenges we face regarding sustainability. By analyzing the ecosystem services provided in the watersheds, it is possible to study the interaction of ecosystems, social challenges, and adaptation processes as in a few other socio-environmental spaces [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe Yuna basin is critical in the DR due to its connection with the global value chains of agricultural and mining commodities such as organic cocoa exports and gold from several mining concessions [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In the DR, the Yuna basin is undoubtedly one of the most important due to its regional and national contribution to development [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Unfortunately, there is a lack of disaggregated economic data at the territorial level to compare the relative weight of the different hydrographic basins and their territories. However, by simple inspection, it is possible to verify the economic importance of the Yuna basin due to its strategic weight in agricultural production and mining activity. The Yuna basin is home to one of the world's most extensive open-pit gold mining operations at the Pueblo Viejo deposit, operated by the Canadian company Barrick Gold [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. In 2021, the Dominican Republic's gold exports amounted to US\u003cspan\u003e$\u003c/span\u003e1,780\u0026nbsp;million, the country's main export product, placing the Dominican Republic among the 50 most important nations in mineral export [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. It indicates the connection of the basin with global value chains through commodities derived from agricultural activity (cocoa for export) and mining products (gold, silver, and nickel), which come out of its bowels.\u003c/p\u003e \u003cp\u003e As can be seen, the Yuna basin's ecosystems are pivotal in several economic activities, particularly in agriculture and its productivity, due to their contribution to the country's food security. This is primarily due to their ecosystem services, such as water provision for various uses [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Agricultural production is critical to food security, given the weight of the basin in the production of items such as rice (mainly in the lower sub-basin) and cocoa (mainly in the middle sub-basin). Other critical agricultural items include tobacco, coffee, fruit tree cultivation, and livestock (cattle and especially pig farming), representing between 50% and two-thirds of all national agricultural activity, which in 2022 represented 5.7% of GDP [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The DR is the world's eighth largest exporter of cocoa beans, with an estimated export value of over US\u003cspan\u003e$\u003c/span\u003e206\u0026nbsp;million in 2021, with the Netherlands, Belgium, and Luxembourg as its main export destinations [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The mining activity that occurs mainly in the middle sub-basin is the most important in the country (Monse\u0026ntilde;or Nouel and Mar\u0026iacute;a Trinidad S\u0026aacute;nchez provinces), contributing 1.4% of the Dominican GDP in 2022 [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThus, the Yuna basin is of strategic importance for the development of the Dominican Republic as a source of wealth and well-being that connects the ecosystems of the central mountain range where the Yuna River and its main tributaries are born, with the coastal marine ecosystems of the Saman\u0026aacute; Bay and its surroundings, which is why the adaptive management of its ecosystems along the altitudinal gradient of the basin [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], as well as the services they provide, is vital for the continuity of the economic and social contribution that the basin makes to the population of the two administrative regions that make it up and to the rest of the Dominican Republic. Thus, this paper departs from the following research questions: What is the current situation of critical ecosystems in the Yuna basin from a land use perspective? What is the relative economic importance of the ecosystems and their implications for decision-making? A land use land change (LULC) analysis of the Yuna River basin combined with available secondary data on ecosystem services was conducted to answer the above questions.\u003c/p\u003e \u003cp\u003eFinally, understanding the dynamics of the basin's ecosystems and their landscape gradient is crucial for making informed decisions about their adaptive management [\u003cspan additionalcitationids=\"CR22\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. It is essential to promote multifunctional landscapes for sustainability [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Therefore, this article is situated at an intersection where political concerns about agroecology (ecosystem services related to agriculture), renewable energies (the basin's role in producing hydro-energy), and the conservation of natural resources converge to promote sustainable livelihoods [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Accordingly, this article contributes to the achievement of the Sustainable Development Goals (SDGs) 14 (coastal marine ecosystems) and 15 (terrestrial ecosystems) in a broader context of the ridge-to-reef (R2R) analytical framework [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], critical for Small Development Island States (SIDS), such as the DR [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e"},{"header":"2. Material and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 The study area\u003c/h2\u003e \u003cp\u003eThe Yuna River basin is a complex exoreic hydrographic system that drains its waters into the Atlantic Ocean. It connects the mountain ecosystems of the northwest of the DR with the marine area in the Saman\u0026aacute; Bay. The system comprises two main subsystems or sub-basins, the Cam\u0026uacute; River and the Yuna River. The Cam\u0026uacute; River has an extension of 144.35 km. It rises in the \u0026Eacute;bano Verde Scientific Reserve in the Municipality of Constanza and tributes its waters to the Yuna riverbed at the height of the municipality of Pimentel. The Yuna River, with an extension of 197.2 km, rises in the Loma de la Humeadora National Park in the Municipality of Villa Altagracia, converting all the northeast part of the country and flowing into the Mangroves of Bajo Yuna National Park in the Saman\u0026aacute; Bay [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. About 18 protected areas are directly related to the basin, including scenic routes, natural monuments, scientific reserves, national parks, and wildlife refuges, representing around 13% of the total surface of the basin, equivalent to about 68,661.93 hectares. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e consists of a digital elevation model of the basin that shows its elevations, the tributary rivers of the Cam\u0026uacute; and Yuna sub-basis, and its estuary in Saman\u0026aacute; Bay, connecting the basin with the Atlantic Ocean.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003e(\u003c/em\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. \u003cem\u003eDigital Elevation Model of the Yuna Basin)\u003c/em\u003e\u003c/p\u003e \u003cp\u003eThe different rivers and streams that connect to each of the subsystems of the basin are highlighted, highlighting some of the structural characteristics of the landscape, such as its rugged relief in the middle and upper areas of the basin and the flood zones in the lower basin in the vicinity of the mouth of the Yuna. The structural features of the basin's landscape highlight the inherent complexity of exoreic systems such as the Yuna Basin in the Dominican Republic, emphasizing the interconnections between natural and socio-productive systems, connecting mountains to coastal and marine habitats [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn terms of surface water availability, it is one of the most important basins of the DR since once the flows of the Cam\u0026uacute; and Yuna rivers are integrated, it develops an average flow of around 90 m\u003csup\u003e3\u003c/sup\u003e/second, significantly higher than the average flows of the Yaque del Norte (40 m\u003csup\u003e3\u003c/sup\u003e/sec) and the Yaque del Sur (45 m\u003csup\u003e3\u003c/sup\u003e/sec), with an average rainfall along the basin of between 2,500 and 3,000 millimeters of rain per year [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. It is also one of the most intervened basins in terms of hydraulic infrastructures, given that it is home to five reservoirs, including the Hatillo, Rinc\u0026oacute;n, and Blanco dams, with storage capacities of 441, 75.5 and 0.73\u0026nbsp;million cubic meters of water, respectively [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. The combined potential of its reservoirs for hydropower generation amounts to 262 gigawatt hours/year [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFrom the point of view of the altitudinal gradient, the Yuna basin has been segmented into three levels: the upper, middle, and lower sub-basins. The above segmentation is somewhat arbitrary and was carried out considering a) the contour lines of the topographic sheets at scales of 1:50 thousand, indicating essential changes in the landscape, especially in the transition from the lower to the middle sub-basin, and b) the spatial distribution of the main economic activities of the basin\u0026mdash;mainly rice cultivation and mining. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the altitudinal range and surface area data for the sub-basins indicated.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe altitudinal gradient of the Yuna Basin\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGradient\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAltitude (meters above sea level)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEstimated area\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUpper sub-basin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e200 m.a.s.l.-2,600 m.a.s.l.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e152,653.57 ha (1,526.54 km\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle sub-basin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 m.a.s.l.-2,600 m.a.s.l.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e289,366.81 ha (2,893.67 km\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLower sub-basin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u0026ndash;20 m.a.s.l.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e84,506.96 ha (845.07 km\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eSource: Own elaboration\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. \u003cem\u003eThe altitudinal gradient of the Yuna Basin\u003c/em\u003e\u003c/p\u003e \u003cp\u003eAccording to the data in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, the lower sub-basin has the smallest surface area and constitutes a flood zone comprising a rich hydrography in which the upper and middle basins converge. These characteristics of the lower sub-basin and the existing irrigation infrastructures have allowed intensive use for agricultural activities such as rice cultivation. The lower sub-basin also receives the waters of the industrial and urban activities in the middle basin, mainly mining, draining its waters into the Bajo Yuna Mangrove National Park, a rich coastal-marine estuary located in the Saman\u0026aacute; Bay. During the boreal winter, Saman\u0026aacute; Bay receives a population of around 1000 humpback whales from the North Atlantic in an ecosystem made up of about 239 species of birds (native, migratory, and endemic) and related protected areas such as the Los Haitises National Park or the Marine Mammal Sanctuary north of the Saman\u0026aacute; Bay [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAs far as the middle sub-basin is concerned, it has the largest relative area with just over 289 thousand hectares and highly intensive productive use of the soils, including mining and crops such as cocoa. The upper sub-basin is the second largest surface area, with just over 152,000 hectares, where extractive activities such as mining coexist with land uses for conservation (protected areas) and crops such as coffee.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 The LULC analysis\u003c/h2\u003e \u003cp\u003eThe LULC analysis for the Yuna basin was carried out for the decade between 2012 and 2022 to approximate the relationship between landscape and ecosystem services [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. In this way, the basin can be understood as a complex system defined by a set of multi-scale and multi-level interactions of environmental, climatic, and socioeconomic factors, as well as defined by the positive and negative synergies of ecosystem services about the economic activities with which they are directly related [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. For the Yuna basin, a LULC was carried out, based, first, on two verified layers of geospatial information on land use and land cover, corresponding to the years 2012 and 2022, which made it possible to analyze the temporal behavior of anthropogenic activities and their impact on the conservation of ecosystems in the basin.\u003c/p\u003e \u003cp\u003eFor the preparation of the classified satellite images, several geospatial software were used for the estimation of the changes in use both in units of area and in percentage changes, and with the Terrset software through the Land Change Modeler module, the change from forest land to agricultural areas and pastures was analyzed) we worked within Terrset with Machine Learning to generate potential transitions at the geospatial level [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Based on the preparation of images described above, to predict land use change in the basin, the year 2030 was chosen as the time horizon, and the Markov Chains technique combined with Cellular Automata was used to generate potential transitions at the geospatial level (see \u003cb\u003eappendix 1\u003c/b\u003e for methodological details). A Markov chain is more than a matrix of transition probabilities from one state to another that then allows us to predict land uses for a future time based on the transition probability maps generated through the classification process described above [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. The essential mathematical expression of transition probability is:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$${\\sum }_{I=1}^{m}Pij=1 i=\\text{1,2}\\dots \\dots m$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere: Pij\u0026thinsp;=\u0026thinsp;the probability of transition within a range of 0\u0026ndash;1 from one land use to another and m\u0026thinsp;=\u0026thinsp;the type of land use defined for the study area [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e], so that the matrix of transition probabilities in a Markov chain would be given as follows:\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$P=\\left(Pij\\right)=\\begin{array}{ccc}P11\u0026amp; P12\\dots \u0026amp; P1m\\\\ P21\u0026amp; P12\u0026amp; P2m\\\\ Pm1\u0026amp; Pn2\u0026amp; Pmm\\end{array}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThe independent variables selected for the prediction were the slope of the terrain in the study area, the primary and secondary pathways of the study area, and the third-order transitions generated within Terrsset [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. The Markov chain model, together with the analysis based on cellular automata developed within the framework of this product, has allowed the simulation of the evolution of the Yuna basin within the defined time horizon (2030) so that each pixel of geospatial data configured based on Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e3\u003c/span\u003e is affected by a transition function that takes as an argument the average values of the neighboring pixels as a function of the period time Analyzed [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Approach to Ecosystem Services Valuation\u003c/h2\u003e \u003cp\u003eConcerning the estimation of the relative importance of the ecosystem services of the Yuna basin, an analysis based on available secondary data on proxy markets related to the values of direct and indirect use of ecosystem services was carried out. It considered the consumptive and non-consumptive uses of water for the provision of services and a transfer of benefits perspective for the values of indirect use values for some regulating ecosystem services, in this case, carbon sequestration and fixation [\u003cspan additionalcitationids=\"CR44\" citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. The transfer of benefits for the indicated regulation services was carried out using the I-Tree-Canopy software using the social carbon prices for the Dominican Republic with a value of US\u003cspan\u003e$\u003c/span\u003e31.00 per ton for the capture service and US\u003cspan\u003e$\u003c/span\u003e17.0 for the fixed carbon [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e] (see \u003cb\u003eappendix 2\u003c/b\u003e for more details). In addition, the following assumptions were made:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eAround 13% of the basing surface is covered by protected areas, which represent around 68,661.94 hectares. Thus, the protected areas interacting directly with the basin were taken about green infrastructures, such as the Valle Nuevo or Los Haitises National Parks, with the \u0026Eacute;bano or Loma Quita Espuela scientific reserves, among others.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eFive hundred points were used throughout the basin. The results related to removing pollutants were estimated based on valid data for Puerto Rico due to its proximity to the Dominican Republic. However, we recommend that they be discarded for now and are looked at with the greatest caution given the most significant cost differences that may be involved in using air pollutant removal technologies in the country.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eThe above assumptions are based on a functional ecosystem perspective highlighting direct and indirect linkages between ecosystems and their components [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e], i.e., as a complex system. The estimation of the non-use values of the basin using declared preference methods was not possible in the framework of this research, which resulted in a partial estimation of the Total Economic Value (VET) of ecosystem services, which considers both the use and non-use values of ecosystems [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.1 LULC analysis.\u003c/h2\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the land uses for the year 2022 on a general scale of the entire basin, indicating a level of intensive land use and a highly anthropic landscape that has functional effects on ecosystems and their capacity to provide services [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003e(\u003c/em\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. \u003cem\u003eLand Use in the Yuna River Basin 2022)\u003c/em\u003e\u003c/p\u003e \u003cp\u003eA complex mosaic in which intensive use of the land prevails, including the ecosystem services related to agriculture and intensive livestock, represented by rice (52,055.28 ha), cocoa (58,388.80 ha), and pasture plantations (168,046.69 ha). These agricultural uses together represent 52.9% of the surface area of the basin, thus determining the configuration of its general landscape [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e2\u003c/span\u003e summarizes the primary land uses of the Yuna River basin.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLand Use in the Yuna Basin 2022\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLand use\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHectares\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConiferous forest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17,430.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBroadleaf forest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e122,086.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDry Forest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e277.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMangrove forest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e251.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRice crops\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e52,055.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCocoa crops\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58,388.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAfrican palm (Oil palm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e29.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMusaceae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19,307.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFruit crops (pineapple, orange, coconut, others)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,229.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSubsistence agriculture (dispersed crops)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,649.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoffee crops\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5,225.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePastures\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e168,046.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e31.92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBodies of water\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5,114.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBuilt-up land\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11,900.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMining\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,825.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBushes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e59,708.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e526,527.34\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e100.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eSource: Own elaboration\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e2\u003c/span\u003e. \u003cem\u003eLand use statistics in the Yuna Basin 2022\u003c/em\u003e\u003c/p\u003e \u003cp\u003eRice and cocoa crops (52,055.28 and 58,388.80 hectares, respectively) demand ecosystem services such as intensive water use for the former or soil quality, pollination, or the benefits derived from biodiversity and climate regulation for the latter [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. Concerning pastures (168,046.69 ha), it is necessary to assert that livestock farming interacts with the heterogeneity of the landscape in a multi-scale process related to the biodiversity of the grasslands, thus contributing to ecosystem services such as soil fertility and erosion control, which this economic activity is related to regulatory services and cultural services such as scenic beauty and its contribution to the Functional diversity of the landscape [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eConsidering the findings in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e2\u003c/span\u003e, about 62% of the land use is anthropogenic (about 326 thousand ha), which includes activities such as agriculture, livestock (pastures), urbanized soils, artificial water bodies, and mining, among other uses. Conservation-oriented uses represent about 26.6% of the basin's surface area (about 140,000 ha), including coniferous forests, broadleaf forests, dry forests, and mangroves in coastal areas. In the same way, land uses related to the agroecosystems of the basin, in this case, giving priority to cocoa and coffee [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e], represent some 63,614 hectares, which would mean that the area of the basin intended for the development of an eventual PES program would be about 203,660 hectares, which represents 38.6% of its total area of the basin. When taken together, anthropogenic uses account for just over two-thirds of the basin's surface, which is an indicator of an economically intensive watershed that depends on ecosystem services such as water supply, soil conservation, erosion control, nutrient recycling, pest control or pollination, the latter a key element to the yield of crops such as fruit trees, cocoa or coffee, which predominate in the basin [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eRegarding the LULC analysis comparing 2012 and 2022, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e3\u003c/span\u003e show the significant changes experienced throughout the decade. The intertemporal analysis of land use can approximate an answer to the question related to the situation of the basin's critical ecosystems.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e(Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. \u003cem\u003eLand Use Change 2012\u0026ndash;2022\u003c/em\u003e)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eInter-temporal Land Use Dynamics 2012\u0026ndash;2022\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLand use\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e2012\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eChange\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e% of variation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDirection\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHectares\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHectares\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConiferous forest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28,155.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17,430.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-10,725.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-38.09%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026darr;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBroadleaf forest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e129,184.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e122,086.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-7,097.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-5.49%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026darr;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDry Forest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e823.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e277.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-545.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-66.24%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026darr;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMangrove forest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,324.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e251.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-3,073.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-92.44%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026darr;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRice crops\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52,302.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52,055.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-247.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.47%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026darr;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCocoa crops\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56,049.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e58,388.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2,339.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.17%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026uarr;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAfrican palm (Oil palm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e29.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e100.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026uarr;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMusaceae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26,220.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19,307.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-6,913.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-26.37%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026darr;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFruit trees (pineapple, orange, coconut, others)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,507.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,229.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2,278.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-50.55%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026darr;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoffee crops\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,733.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5,225.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,492.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e39.97%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026uarr;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSubsistence agriculture\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,079.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,649.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1,430.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-35.06%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026darr;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePastures\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e192,345.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e168,046.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e31.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-24,298.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-12.63%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026darr;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody of waters\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,364.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5,114.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,749.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e52.01%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026uarr;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBuilt-up land\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13,264.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11,900.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1,364.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-10.29%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026darr;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMining\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e561.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,825.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,263.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e224.83%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026uarr;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBushes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8,608.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e59,708.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e51,099.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e593.56%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026uarr;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e526,527.34\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e100.00\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e526,527.34\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e100.00\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eSource: Own Elaboration\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Inter-temporal Land Use Dynamics 2012\u0026ndash;2022\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e summarizes the findings of Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e3\u003c/span\u003e, indicating a trend of land use change in which decreased ecosystems such as coniferous forests or traditional agriculture have led to a dramatic increase in shrubland. This indicates a possible trend towards landscape deterioration.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003e(\u003c/em\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. \u003cem\u003eLand Use Statistics 2012\u0026ndash;2022)\u003c/em\u003e\u003c/p\u003e \u003cp\u003eThe coniferous forest in the upper sub-basin shrank by 38% in the analyzed period, the broadleaf forest shrank by 5.4%, and the already meager dry forest lost 66% of cover. In the case of mangroves in the lower sub-basin, the impact over the decade reduced it by 92%. The most affected ecosystems have been the ones indicated, but when we look at the land uses with a vocation for conservation, the affected ecosystems went from covering an area of just over 161 thousand hectares in 2012 to 140 thousand hectares for an overall reduction equivalent to 13% of the area covered (coniferous forest, broadleaf forest, dry forest, and mangrove).\u003c/p\u003e \u003cp\u003eRegarding intensive agriculture, the area cultivated with rice was almost unchanged (just a decrease of 0.47% between 2012 and 2022). On the other hand, the areas dedicated to cocoa and coffee cultivation experienced an increase of 4.17% and 39.97%, respectively. Fruit crops (pineapple, orange, and others.) fell by around 50% between 2012 and 2022. The area dedicated to pasture was reduced by 12.6%, as well as subsistence agriculture in the basin, which experienced a reduction of 35% from 2012 to 2022, possibly related to the diversification of productive activities in the basin and the process of demographic decline that has been experienced for several decades in the Dominican countryside. Over the decade, urban land use fell by 10%, while water bodies (dams, dams, reservoirs) increased by 52% along with mining, which expanded by more than 200%. The most striking change can be seen in the increase in shrubland, whose cover has grown by nearly 600%.\u003c/p\u003e \u003cp\u003eIn a very preliminary way and without data to confirm it, the possibility can be raised that this change may indicate a landscape degradation process as a response to the pressure of socioeconomic factors and environmental stress in the basin that affects ecosystems and the services they provide [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Suppose it adds up the losses of coniferous, broadleaf, grasslands (pastures), and other essential losses. In that case, the total resembles the increase in shrubland in the basin, which could indicate a trend toward deforestation. For now, there is a lack of firmer evidence to support this idea, and more research needs to be done on the matter. As indicated, it has been possible to estimate the dynamics of land use change to 2030 by using Markov chains and cellular automata, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e(Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. \u003cem\u003eMarkov chain-based simulation 2022\u0026ndash;2030\u003c/em\u003e).\u003c/p\u003e \u003cp\u003eThe Markov-based prediction model has limitations and should be taken as an indication of the change in the trend of land use in 2030. Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e summarizes the results of the Markov-chain simulation:\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLand use change statistics 2022\u0026ndash;2030\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLand use\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eHectares\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eWin/losses\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e% of variation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDirection\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2030\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConiferous forest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17,391.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13,605.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-3,786.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-22%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026darr;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBroadleaf forest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e118,195.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e119,857.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,662.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026uarr;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDry forest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e309.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e308.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMangrove forest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e157.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e99.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-58.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-37%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026darr;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRice crops\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51,365.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51,363.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCocoa crops\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56,339.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56,333.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-6.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFruit crops (pineapple, orange, coconut, Musaceae, oil palm, others)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21,496.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21,496.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSubsistence agriculture\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,645.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,642.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-3.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePastures\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e161,879.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e152,599.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-9,280.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026darr;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody of waters\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5,077.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5,077.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBuilt-up land\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11,687.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11,683.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-4.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003en/a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMining\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,761.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,721.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-40.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026darr;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBushes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71,347.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e82,695.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11,348.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026uarr;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eSource: Own elaboration\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. \u003cem\u003eLand use change statistics 2022\u0026ndash;2030\u003c/em\u003e\u003c/p\u003e \u003cp\u003eThe findings in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e are consistent with the land use change between 2012 and 2022. By 2030, the trend continues, significantly affecting coniferous forests in the upper sub-basin (projected decrease of 22% of the area) and mangrove forests in the lower sub-basin (projected reduction of 37%). Despite their limitations, these scenarios clearly show the urgency of an intervention that ensures the capacities of the identified critical ecosystems to provide services. Figure\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e gives a more unambiguous indication of the projected dynamics for 2030.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003e(\u003c/em\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e. \u003cem\u003eLand Use Statistics for 2030)\u003c/em\u003e\u003c/p\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e, the big losers in the coming years are land uses related to the conservation of ecosystems. The coniferous forest in the upper basin, essential for the water supply service for consumptive and non-consumptive uses, will be reduced by more than 20% compared to 2022, having already experienced a loss of 38% compared to 2012. This situation will undoubtedly put much more stress on the basin and its ability to meet the demand for surface water for the coming decades, considering that by 2040, the market is expected to reach 2,540.22\u0026nbsp;million cubic meters per year, not to mention the adverse effects on support and regulation services that the trend of landscape degradation marked by the simulation would have Performed. The trend of the mangrove in the lower basin is just as dramatic, so it is very likely that if the simulated scenario continues, the mangrove will tend to disappear from the areas in which it was found in 2022. The efforts of organizations such as CEBSE will likely contribute to reversing this trend in the lower Yuna basin. The trend of change and possible landscape deterioration continues with the increase in shrublands by more than 15% compared to 2022, having already experienced an increase of more than 500% compared to 2012. The impact of reducing the area occupied by these ecosystems can be varied. In the case of the ecosystems of the upper basin, it can be translated, on the one hand, into the decrease of the water balance of the basin, specifically in the amount of water stored in its aquifers, and on the other hand, in the increase in the rates of soil erosion and sediment entrainment to hydroelectric reservoirs will decrease its lifespan and reducing its efficiency. Without counting, ecosystem services regulation would no longer capture carbon [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the case of mangrove ecosystems, their reduction has several implications from the point of view of the provision of a wide vector of ecosystem services, ranging from a decrease in net biomass productivity to an increase in the risk of flooding as a result of increased exposure to the eventual tropical storms that regularly hit the Caribbean [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. The dramatic reduction of the mangrove forest already experienced between 2012 and 2022 is a powerful wake-up call as the income generated by fishing is affected, and protection is diminished, among other services [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. It is worth saying that mangroves are one of the most productive and dynamic ecosystems for decomposing and recycling nutrients and carbon sequestration [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e], contributing to waste assimilation. However, it is also an ecosystem that serves as a refuge for around 239 species of birds (native, migratory, and endemic) in the surroundings of the Saman\u0026aacute; Bay at the mouth of the Yuna River [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. How does the destruction of the mangrove affect Saman\u0026aacute; Bay's ability to receive a population of around 1000 humpback whales from the North Atlantic during the boreal winter? We cannot answer this question in the context of this report. However, a PES intervention is undoubtedly required to protect and restore a critically threatened ecosystem in the lower Yuna sub-basin. Therefore, the landscape along the altitudinal gradient over the next decade is proposed to be managed from a multifunctional landscape perspective [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.2 The relative economic importance of ecosystem services\u003c/h2\u003e \u003cp\u003eGiven the available data and paper purpose, let\u0026rsquo;s focus only on provisioning (water supply) and regulatory (CO\u003csub\u003e2\u003c/sub\u003e sequestration) ecosystem services [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Supporting and cultural ecosystem services can be considered as assumed and should be estimated further on [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. An example of the economic and social importance of the Yuna basin can be seen in the water supply service for consumptive (agricultural, industrial, and residential) and non-consumptive (hydroelectricity, recreation, and tourism) uses. The first thing to consider is that the Yuna basin produces about 15% of the available surface water in the DR, equivalent to about 3,600\u0026nbsp;million cubic meters per year (MCM/year) [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e shows the participation of the Yuna basin in the generation of surface water supply.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSurface water availability by hydrographic regions\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHydrographic regions\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMillions of cubic meters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYaque del Norte river basin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,945.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAtlantic region\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,634.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYuna river basin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,600.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEast Region\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,195.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOzama-Nizao region\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,459.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYaque del Sur river basin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,771.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e23,567.69\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e100.00\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eSource: Own elaboration\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. Surface water availability by hydrographic regions\u003c/p\u003e \u003cp\u003eCombining different sources of information from public organizations, the basin's water demand for consumptive and non-consumptive uses could be estimated at 2,510.42\u0026nbsp;million MCM/year by 2020, of which 51.69% corresponds to consumptive uses (1,297.66 MCM/year) and 48.21% to non-consumptive uses (1,212.76) [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan additionalcitationids=\"CR62\" citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. The above demand is equivalent to 69.7% of the entire surface water supply of the basin estimated in the National Hydrological Plan [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. The estimate of the projected demand for 2020 is slightly higher than that made in the framework of the INDRHI Trends and Scenarios Report [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e], given that the estimated demand for turbine water for hydroelectricity generation in the Yuna basin has been added for more clarity [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. Based on the previous estimate, of the consumptive uses (1,297.66 MCM/year), 66.63% were dedicated to agriculture, 18.24% to livestock (combined agriculture represents 84.87% of consumptive uses), human consumption represented about 9.27%, and industry and mining 5.86%. Figure\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e shows the distribution of the consumptive uses and the number of millions of cubic meters per year of each activity.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003e(\u003c/em\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e. \u003cem\u003eConsumptive uses of water in the Yuna basin)\u003c/em\u003e\u003c/p\u003e \u003cp\u003eAs indicated in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e, the demand for water for non-consumptive uses, especially for hydroelectricity generation, stood at around 1,212.76 MCM/year. The amount of water turbines used for hydroelectricity generation is equivalent to 48.21% of the surface water availability. Figure\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e shows the water demand and availability estimated by INDRHI [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003e(\u003c/em\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e. \u003cem\u003eWater supply and demand in the Yuna Basin)\u003c/em\u003e\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e shows that the basin is not a linear system. As can be seen, in the years 2001, 2002, 2003, 2007, 2009, 2010, 2016, 2018, 2019, and 2020, water availability was below demand, that is, for ten years of the series. The situation described in the graph is likely related to climate variability and the effects of droughts caused by events such as the Southern Oscillation, better known as El Ni\u0026ntilde;o, whose effects have been documented for the insular Caribbean [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e], shown, in this case, the environmental climate vulnerability of the basin, regardless of any projection scenario on demand and availability of its water balance. Assuming a conservative range of variability of around 10% between estimates of different future scenarios defined by INDRHI [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e] and the projected demand for water for the basin made in this report (2,510.42 MCM/year), for the years 2040 and 2060 would be in ranges between 2,478.19 and 2,726.00 MCM/year and between 2,666.38 and 2,933.02 MCM/year, respectively. In other words, at the upper limits of the projected demand for the years 2040 and 2060, between 75.42% and 81.47% of the entire capacity of the surface water supply of the basin would be reached without adding these estimates, the ecological flow projected for 2040 and 2060 at 991.39 MCM/year [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. Therefore, it can be said that the ecosystem services of the Yuna basin, such as the provision of water for consumptive and non-consumptive uses, not only for the present but also for the future, are under significant anthropic pressure that may jeopardize the ability of the basin's ecosystems to provide them sustainably in the medium-long term.\u003c/p\u003e \u003cp\u003eBased on the hydrological relevance of the Yuna River basin for the Dominican Republic, the approach followed for the monetary estimation of the ecosystem services of the basin has been that of proximate markets [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. For the values of water demand for consumptive and non-consumptive uses, the total volume of water used for consumptive purposes was considered to make it available for other uses. According to the data in this report, the demand for water for different uses (consumptive and non-consumptive) as of 2020 is 2,889.76 MCM/year per year, of which 37% corresponds to consumptive uses, that is, 1,069,211.2 and 1,820, 548 MCM/year for consumptive and no-consumptive uses, respectively. An average cost of US\u003cspan\u003e$\u003c/span\u003e0.60/m\u003csup\u003e3\u003c/sup\u003e was assumed for effluent treatment (data provided by Barrick Gold) so that, directly, the value of water for consumptive purposes would be around \u003cb\u003eUS\u003cspan\u003e$\u003c/span\u003e 641.5\u0026nbsp;million\u003c/b\u003e a year. The best proxy in the Yuna basin for non-consumptive water use is the production of hydroelectricity. Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e summarizes the available information on the average generation of hydroelectric plants in GW/year in 2020 of the basin and the volume of turbine water in MCM, i.e., the volume of water used to produce electricity [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHydroelectric production and turbine water\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHydroelectric\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProduction GW/year\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTurbine water in MMC\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHatillo complex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e82.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e740,560,426\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePinalito complex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e93.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62,523,227\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRinc\u0026oacute;n complex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e241,329,669\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRio Blanco complex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e113.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e168,347,503\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e310.6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1,212,760,825\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eSource: Own elaboration\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. \u003cem\u003eHydroelectric production and turbine water\u003c/em\u003e\u003c/p\u003e \u003cp\u003eThe opportunity cost for hydroelectricity production for the wholesale market has been estimated at \u003cspan\u003e$\u003c/span\u003eDOP 0.82/m3, equivalent to US\u003cspan\u003e$\u003c/span\u003e0.014/m3 [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], so that the value of non-consumptive water use in the basin considering not only turbine water but the overall potential of water for available non-consumptive use (63% of the surface water supply indicated above), the value of water for non-consumptive use would be US\u003cspan\u003e$\u003c/span\u003e25.4\u0026nbsp;million/year. Based on the above estimates, the water supply service's value for consumptive use (US\u003cspan\u003e$\u003c/span\u003e 641.5\u0026nbsp;million) and non-consumptive use (US\u003cspan\u003e$\u003c/span\u003e25\u0026nbsp;million) is around \u003cb\u003eUS\u003cspan\u003e$\u003c/span\u003e667.0\u0026nbsp;million/year\u003c/b\u003e. The value of the water supply service is about 3.2 times greater than that of cocoa exports and is only surpassed by the export of gold and silver in the basin. Regarding regulating ecosystem services (capturing and fixing CO2) [\u003cspan additionalcitationids=\"CR66\" citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e], our findings indicate that the Yuna River captures about 3.17\u0026nbsp;million t/CO2/year, and the fixed carbon in trees is around 41.4\u0026nbsp;million t/CO\u003csub\u003e2\u003c/sub\u003e. The estimated social prices for CO\u003csub\u003e2\u003c/sub\u003e in the DR range from US\u003cspan\u003e$\u003c/span\u003e31.00/tCO for carbon sequestration to US\u003cspan\u003e$\u003c/span\u003e17/tCO\u003csub\u003e2\u003c/sub\u003e for fixed CO\u003csub\u003e2\u003c/sub\u003e [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Thus, the value of regulating ecosystem services only considering CO\u003csub\u003e2\u003c/sub\u003e sequestration is about \u003cb\u003eUS\u003cspan\u003e$\u003c/span\u003e98.2\u0026nbsp;million/year\u003c/b\u003e. In conclusion, the Yuna River basin provides ecosystem services for around US\u003cspan\u003e$\u003c/span\u003e765.2\u0026nbsp;million/year (see Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSelected ecosystem services in Yuna river basin\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEcosystem services\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eValue US\u003cspan\u003e$\u003c/span\u003e (mm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eProvisioning services\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConsumptive use of water\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e641.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e83.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-consumptive use of water\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRegulating services\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnnual Carbon Sequestration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e98.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEstimated Total Annual Value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e765.2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e100.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eSource: Own elaboration\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIt should be noted that coniferous ecosystems have suffered a significant loss in 2022 (38% compared to 2012), and mangrove ecosystems in the lower basin, which were reduced by 92%, or the already meager dry forest whose surface area was reduced by 66% compared to 2012. It points out a critical situation for ecosystem services in the coastal zone, especially considering the relevance of blue carbon sequestration for coastal ecosystem management [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e]. The possible trend of landscape degradation caused by a complex dynamic of land use change over a decade reduces the capacity of ecosystems to provide services and fulfill their ecological functions, and this translates directly into the reduction of the capacity of ecosystems to provide ecosystem services of regulation or support.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e. Use values of the basin's ecosystem\u003c/p\u003e \u003cp\u003eAs seen in Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e, the weight of the use values of the basin's ecosystems falls on the water supply service for consumptive uses (83.8%). The most productive ecosystems in the basin, and at the same time the most threatened, are found in the upper basin in terms of water supply and regulation services (coniferous forest in the upper sub-basin, essential for water supply services and carbon sequestration and mangrove in the lower sub-basin).\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion: insights for policymaking","content":"\u003cp\u003eA vital issue for the future of systems with the complexity of the Yuna basin is to consider how to maintain the capacity of its ecosystems to provide services given its regional and national importance, as well as the growing trend of its economic and productive activities that imply an increase in the demand for provision services such as water for consumptive and non-consumptive uses and other services. For the coming years, in the face of a scenario of deterioration of the landscape and the functions and services of its ecosystems. Based on the results discussed above, this section proposes some general elements to be considered in decision-making on conservation and sustainable development in the context of the Yuna basin, which can be comparable to contexts of similar complexity that face similar challenges.\u003c/p\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e4.1 An R2R approach\u003c/h2\u003e \u003cp\u003eThe exoreic nature of the Yuna Basin is critical to developing an R2R approach for the adaptive management of the Yuna Basin ecosystems and the services they provide along its entire altitudinal gradient. An R2R consists of an integrated approach to the ecosystem services that connect mountain systems with coastal-marine systems through watersheds. It considers the effects of landscape on water and emphasizes the interconnections between natural and socio-productive systems, connecting mountains with coastal and marine habitats [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe interconnections between the ecosystems of the Yuna basin along its altitudinal gradient and the economic activities carried out in it indicate the need for a comprehensive approach to managing local ecosystems due to the effects such interactions have on the landscape, especially when considering their relationship with ecosystem services [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. The most obvious indicators of these effects can be seen in the marked decrease in land uses for conservation in the basin between 2012 and 2022, especially the impact on the coniferous forest (-38.09%) and the riparian mangrove forest (-92.44%), as well as in the trend of general deterioration of the landscape by 2030.\u003c/p\u003e \u003cp\u003eIn the context of tropical marine ecosystems from riparian mangrove forests, coral reefs, and seagrass meadows, global factors such as climate change and local factors such as increased land runoff, erosion of mountain soils, upstream land-use change due to inappropriate production practices, Infrastructure development, and water pollution act together as environmental stressors, affecting the provision and chains of ecosystem services in coastal-marine zones [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe result of these complex dynamics includes the impact on ecosystem services related to social, cultural, and biological values and the economic activities on which the communities that interact along the watersheds that connect mountains with coastal marine areas depend [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e]. At the level of coastal-marine ecosystems, factors such as soil erosion and sediment dragging from upstream can negatively impact marine biodiversity, affecting economic activities such as tourism or fishing [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Promoting Multifunctional Landscapes\u003c/h2\u003e \u003cp\u003eThe multifunctional landscape approach would represent a paradigm shift in the integrated management of ecosystems that are part of the country's watersheds. Planning under a land-use scheme that recognizes the benefits of ecosystem services and their economic importance can generate multifunctionality with a more diverse supply of goods (market and non-market), leading to more significant environmental, social, and economic benefits [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Therefore, in the case of the Yuna basin, it is necessary to increase the multifunctional use of the landscape under a sustainability governance scheme, which improves its functional diversity and the resilience of ecosystems along the altitudinal gradient of the basin [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFor example, the broadleaf forest plays a connectivity role along the basin's altitudinal gradient, and combined with the cocoa and coffee agroecosystems, it contributes substantially to the ecosystem services generated in the basin. A clear issue is that the development of a PES program in the basin must go hand in hand with straightforward and focused initiatives for the restoration of ecosystems along the altitudinal gradient, as well as with economic tools and instruments that promote a change in behavior in social and economic agents that allow them to take advantage of the ecosystem services provided by a basin with a sense of social and intergenerational equity\u0026mdash;regional and national importance, such as that of the Yuna.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e4.3 The development of PES schemes\u003c/h2\u003e \u003cp\u003eConsidering the problem of natural resource management that affects the mountain ecosystems of the DR [\u003cspan additionalcitationids=\"CR70\" citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e], especially in the Yuna basin, where two main subsystems originate in mountain-protected areas, as well as the complex mosaic of landscape-scale land use, the Payment for Environmental Services (PES) approach can be helpful to promote more integrated ecosystem management as well as multifunctional landscapes that contribute to the sustainability of the basin, that is, with the capacity of the system to provide services following the challenges and demands of local and national development, given the importance of the Yuna basin for the Dominican economy. Following Wunder's definition [\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e], a PES is a \" \u003cem\u003e(1) voluntary transaction in which (2) a well-defined environmental service (or corresponding land use) is (3) \"purchased\" by a (minimum one) purchaser of environmental services (4) from a (minimum) environmental service provider (5) if and only if its provision is guaranteed (conditionality)\u003c/em\u003e.\" This definition emphasizes three significant aspects of a PES scheme:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003ePES's transactional and voluntary nature indicates its potential as an economic instrument.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eAgents (seller and buyer) who transact a good (environmental service or land use)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eConditionality for payment or compensation to be made, i.e., that the good or service can be provided under the conditions agreed upon and verified under the same terms.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eTherefore, the central idea behind a PES is, on the one hand, the practical application of Coase's theorem in the sense that, given the required institutional conditions, economic actors can agree among themselves rights and obligations (which can take the form of financial transactions in cash or in-kind), to improve their welfare and resolve the negative externalities that their economic activities cause on each other as long as the costs of transaction remain very low [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Therefore, considering the sustainability challenges faced by the Yuna basin, and based on the analysis of the land-use dynamics of the basin's landscape, as well as the general estimate of the economic importance of specific ecosystem services provided by its ecosystems, it is suggested that the actions of an eventual PES program focus on:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eManagement of water supply services for different uses\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eEcosystem restoration (specifically with a climate regulation approach), especially around protected areas.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eSustainable production and use of the land (specifically the conversion of forest to shrubland), as well as the rational use of water.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eBiodiversity conservation and management of the protected areas of the Lower Basin\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eCapacity building for sustainability.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eIn practical terms, the idea is that certain land uses in the Yuna basin, either for conservation-restoration purposes (reforestation) or for productive purposes (good land use practices such as the use of barriers, terraced cultivation, or fallow), benefit rights holders (landowners) as well as downstream users (higher water quality and quantity, lower treatment costs, among others). It is expected that the deployment of a PES program in the Yuna basin will provoke a change in the behavior of its stakeholders that translates into an improvement in the health indicators of its ecosystems and in adaptive management of them and the services they provide, with a sense of inclusion and intergenerational equity.\u003c/p\u003e \u003cp\u003eAn important additionality of the PES approach for the Yuna Basin is that it allows for the consideration of trade-offs between services provided for various plausible future land-use scenarios based on priorities that watershed users and stakeholders can identify. Thus, ecosystem services can serve as a tool for watershed planning by incorporating actors into a management scheme consistent with policy objectives and based on learning [\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e]. It implies that systems focused on the management of ecosystem services (e.g., payment systems) operate as means and instruments of public policy, so from an institutional point of view, they can improve the capacity for the implementation of initiatives for the conservation and sustainable management of ecosystem services, supporting the implementation of sustainable practices, promoting participation, and improving coordination among institutional actors to facilitate the management of natural capital [\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Concluding remarks, limitations, and further research.","content":"\u003cp\u003eThe challenges the Yuna River basin experiences regarding sustainability in achieving SDG 14 and 15 are significant and serve as an example of the difficulties confronting hydrographic basins in SIDS that are highly impacted by anthropogenic activities. In this sense, this article has presented the preliminary results of the analysis of the situation of the critical ecosystems of the basin and the economic importance of the ecosystem services provided not only for the northeastern region of the DR but for the entire Caribbean country. However, these results are partial, and the analysis of the state and health of the basin's ecosystems must be expanded.\u003c/p\u003e \u003cp\u003eIn terms of the analysis of the health of local ecosystems, primary information is needed on the ecological functions and energy flows of critical ecosystems such as pine forests and mangroves. Thus, more attention and research focus are necessary to support the adaptive management of protected areas in the basin, as well as knowing in more detail their biodiversity or the responses of ecosystems to the pressures of variability and climate change. The absence and dispersion of primary data is a problem for making adaptive decisions, and creating a research program for the main hydrographic basins of the country is recommended. In terms of economic analysis, progress must be made towards a total economic value approach that incorporates the non-use values of ecosystems through stated preference approaches. It is necessary to better understand social preferences regarding conservation and local sustainable development as part of a broader feasibility exercise on alternatives and medium and long-term intervention strategies in the basin.\u003c/p\u003e \u003cp\u003eFrom the point of view of the implementation of economic instruments regarding PES that stakeholders can adopt, it is necessary to deepen the analysis of Dominican environmental legislation so that progress can be made in defining a policy mix for the adaptive management of the basin's natural resources. A methodological alternative may be using discrete selection experiments to evaluate some of the available economic instruments and determine their probability of adoption by the identified stakeholders. The mapping of social actors in the different sub-basins is another element to consider for the design of a more integrated strategy in terms of sustainable development at the local level, which includes the design of broader mechanisms and instruments, such as the creation of a Water Fund for the Yuna basin through which different experiences and mechanisms of PES and local development can be implemented, such as the development of decentralized PES markets through the use of technologies such as blockchain and the implementation of solutions based on the scale nature of small and medium producers located along the altitudinal gradient of the basin, especially in the upper and lower sub-basins.\u003c/p\u003e \u003cp\u003eFinally, in the medium and long term, the Yuna basin will experience significant pressure on certain ecosystem services, such as providing water for consumptive and non-consumptive uses. Thus, the basin's response capacity will depend on the health of its ecosystems and how they respond to complex dynamics, such as the effects of climate variability and climate change. The above represents a considerable challenge in terms of sustainability, which requires the participation not only of public authorities but also the involvement of multinational and national private interests with a presence in the basin that depends on the exploitation of the natural resources of the territory bathed by the Yuna River.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eVGV: Conceptualization, Methodology, Writing-Original draft preparation, Supervision, Funding acquisition; SBD: validation and draft preparation; KR: validation and draft preparation; CBG: Data management, GIS analysis, field support; APE: Data management, field support.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors thank the Interamerican Development Bank (IDB) for their partial support in preparing this work connected to their initiative on ecological restoration and management of the Yuna River basin from Ridge to Reef, particularly to Jean Marie Benoit Lefevre and Elia Mariel Mart\u0026iacute;nez Moises, from the IDB National office in Santo Domingo.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eComeros-Raynal MT, et al. 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Ecosyst Serv. 2020;43:101096.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Yuna river basin, land use change dynamics, ecosystem services, natural resources management, Dominican Republic","lastPublishedDoi":"10.21203/rs.3.rs-4663717/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4663717/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis paper aims to analyze the land use land change dynamics in the Yuna River basin in the northeast region of the Dominican Republic (DR), considering their implications for ecosystem services. The Yuna basin is one of the most critical watersheds in the Caribbean, connecting the northeastern hills of the Cordillera Central to the Atlantic Ocean in the Saman\u0026aacute; Bay. The basin is also connected to the global value chains of agricultural and mining commodities, such as organic cocoa exports and gold, from several mining concessions in its territory. The Basin faces socioeconomic pressures expressed in the timeless analysis of land-use dynamics, which can jeopardize the basin's ability to provide ecosystem services in the medium and long term. It suggests developing an approach based on the adaptive management of ecosystems and deploying a payment for environmental services scheme for watershed restoration.\u003c/p\u003e","manuscriptTitle":"From ridge to reef. Land use dynamics and ecosystem services in the Yuna River basin: insights for policymaking.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-29 11:39:56","doi":"10.21203/rs.3.rs-4663717/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"65484a1a-fad9-45cf-84a9-311757e46cca","owner":[],"postedDate":"July 29th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-02-20T04:38:12+00:00","versionOfRecord":[],"versionCreatedAt":"2024-07-29 11:39:56","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4663717","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4663717","identity":"rs-4663717","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}