To carry out this study, the three types of spatial units for ecosystem accounting proposed in SEEA EA 2021 were used. The primary spatial units for ecosystem accounting are called ecosystem assets (EA). EAs are contiguous spaces in a specific ecosystem type, characterised by a different set of biotic and abiotic components and their interactions. They play a key role because they are the statistical units for ecosystems accounting, that is, the ecological entities about which information is sought and statistics are finally compiled. This includes information about their extent, condition and the biophysical flows of the provided ES and their monetary value (United Nations 2021).

The second spatial unit type for ecosystems accounting is the area for ecosystems accounting (EAA), which is the geographical territory for which the ecosystems account is compiled. Therefore, the EAA determines which ecosystem assets are included in an ecosystem account (United Nations 2021).

The third type of spatial unit is the basic spatial unit (BSU), which is a geometric construction representing a small spatial area. The purpose of BSUs is to provide a fine-level data framework where data on varied characteristics can be incorporated (United Nations 2021) (Fig. 2).

Figure 2.

Spatial units for ecosystem accounting. Source: United Nations (2021).

Table 1 shows the three types of spatial units used for ecosystems accounting in our study area.

The SEEA EA provides a reference classification for ecosystem types, based on IUCN’s global ecosystem typology, which was proposed by Keith et al. (2020). However, at the national or subnational level, the SEEA EA framework establishes that it may be more appropriate to compile accounts by using an existing ecosystem types of classification and relating it to the SEEA’s reference ecosystems classification for international comparison purposes (United Nations 2021).

Table 2 establishes the correspondence between the two types of coverage/ecosystem (EA) in the CGSM’s Ramsar site, based on the National Legend of Land Cover adapted for Colombia (IDEAM 2010) and the SEEA’s reference ecosystems classification, based on the IUCN’s global ecosystem typology (Keith et al. 2020) (Fig. 3).

Figure 3.

Ecosystem assets (EA) in the Cienaga Grande de Santa Marta Ramsar site according to the IUCN’s global ecosystem typology. Source: Own elaboration, based on Keith et al. (2020).

To carry out this study, environmental and socio-economic data were collected and analysed which were spatially differentiated and available for the study area. These data contain information regarding ecosystem extent, condition and services. Later, with this information, the accounting tables proposed within the SEEA EA framework were elaborated.

Table 3 shows the variables and the data sources employed in this research.

Geographical data for the ecosystem extent account were obtained through a multitemporal analysis of land cover at a CORINE Land Cover scale of 1:100,000 for the years 2012 and 2018 (IDEAM 2021). This geographical information is available online. EA extent data were obtained for these two years and the calculations for gains and losses were carried out. This balance is a necessary input in order to elaborate the first table for ecosystem extent accounting in the CGSM Ramsar site during the 2012-2018 accounting period.

The first step was to homologate the CORINE Land Cover legend for the two geographical layers. Once the data were standardised, the total land cover area for each year of study was generated by calculating the geodesic area with the ArcGIS 10.5 software. Then, the calculations were compiled in Excel tables to facilitate their analysis and visualisation.

Later, with the area database, the transitions were calculated through the intersection geo-processing, which allows comparing the geographical layers of the two time periods in order to compile a matrix of ecosystem type changes. This matrix shows the area of different ecosystem types at the beginning of the accounting period (opening extent), the increases and decreases in this area according to the ecosystem type it was converted from (in the case of increases) or the ecosystem type it was converted to (in the case of decreases) and the area covered by different types of ecosystems at the end of the accounting period (closing extent) (United Nations 2021).

Condition accounts were applied to mangrove forests and coastal lagoons for the 2017-2019 period only, due to data availability. In these ecosystems, the values for the years 2017, 2018 and 2019 were reported for the selected indicators and variables. The information used was taken from the Information System for Mangrove Management in Colombia (SIGMA), the Information System of Marine Environmental Quality (REDCAM), INVEMAR’s Fishing Information System (SIPEIN) and the technical reports of CGSM’s Monitoring of Environmental Conditions and Structural and Functional Changes of the Vegetable Communities and Fishing Resources during CGSM Rehabilitation.

The ES included in this account are the global climate regulation service and the wild fish and other natural aquatic biomass provision service. For their classification, the reference list of ecosystem services proposed by the SEEA EA framework was considered. The global climate regulation services are the ecosystems’ contributions to decrease greenhouse gas (GhG) concentration in the atmosphere through carbon removal (sequestration) from the atmosphere and carbon capture (storage) in ecosystems (United Nations 2021). In this study, accounts were generated for carbon sequestration and storage in CGSM mangroves between 2015 and 2019. The model to estimate reservoirs considers above- and belowground carbon as the two main components that are stored in a mangrove. For estimating aboveground carbon stocks in the CGSM, an approach was employed which was based on the relationships established between the diameter at breast height of mangrove trees and the aboveground biomass. Diameter at breast height data were taken from the mangrove monitoring carried out in the CGSM (INVEMAR 2020).

In this way, the aboveground carbon stock contained in the aerial biomass of the trees in the six mangrove monitoring stations of the CGSM was estimated according to Kauffman and Donato (2012). The procedure described in Yepes et al. (2016) was followed to this effect. Due to the geographical closeness, the allometric equations of Smith and Whelan (2006) were used for estimating the aerial biomass of Rhizophora mangle and Avicennia germinans. On the other hand, the belowground carbon content reports from four CGSM basin mangrove stations were used (Perdomo Trujillo et al. 2020) as the total underground carbon estimates both in basin and fringe/riverine mangroves. These reports have assessed the carbon content at a 1 m depth. The total carbon corresponds to the sum of above- and bellowground carbon.

Carbon sequestration was assessed by relating the annual changes in the carbon content of the aboveground biomass of the monitoring stations in INVEMAR’s mangrove to the time elapsed between year-to-year measurements. Only aboveground carbon sequestration was reported. In the CGSM, recent changes regarding the carbon in the soil have not been assessed, thus allowing us to estimate the belowground carbon sequestration.

In order to estimate the carbon price, the carbon tax rate regulated in Colombia via Article 221 of Law 1819 of 2016 was used. For the year 2017, it was set at USD 5 per tonne of CO₂ generated, with an annual adjustment dependent on national inflation (Congreso de la República de Colombia 2016); this information was obtained from The World Bank (2022).

To quantify the wild fish and other natural aquatic biomass provision, ES, SIPEIN data on the CGSM were used, taking 2015-2019 as the study period. This information allowed estimating the total catch (tonne * year^-1) by group of organisms (fish, crustaceans and molluscs). Data correspond to those collected and estimated by the SIPEIN, selecting 2015-2019 as the study years. The physical and monetary information of the fishing resource was presented, making specifications for four landing places, where information was collected and then distributed to all of the CGSM. In the monetary valuation of the fishing resources, the market-price method was used, as the SIPEIN collects information through surveys on the trading primary prices, that is, the exchange between the fishermen and their customers. The SIPEIN provides information on the income received by group of organisms, including only artisan fishing because it is the only one carried out in the study area.

This study proposes indicators to measure both the ecosystems’ condition and the wild fish provision and global climate regulation ES flows. For these indicators, values for the accounting period 2015-2019 were reported.

According to the ecosystem accounting framework, the ecosystem condition accounts are commonly compiled by ecosystem type, as each ecosystem type has different characteristics. Likewise, the structure of the ecosystem condition accounts depends on the variables selected, data availability, accounts usage and the general application of policies (United Nations 2021).

For our pilot, the set of indicators used to measure the ecosystems’ condition was focused on mangroves and coastal lagoons for the cases of carbon capture and storage in mangrove forests. For the case of fishing resources, estimations of the total catch (tonne * year^-1) were carried out by group of organisms recorded in the CGSM.

To compile the ecosystem condition accounts, the ecosystem condition (SEEA ECT) typology proposed by SEEA EA was used, which is a hierarchical classification consisting of six classes grouped into three main groups, i.e. the abiotic, biotic and landscape characteristics of ecosystems (Czúcz et al. 2021). This typology has three development stages. The first stage consists of defining and selecting the system characteristics and their associated variables. For the mangroves, a total of five variables were selected: basal area (cross sectional area of trees at breast height), seedling and propagule density, interstitial salinity, bird species richness and change in extent of the ecosystems related to water over time (ODS indicator 6.6.1). These variables cover five classes of the ecosystem condition typology (ECT). For the case of coastal lagoons, four variables were selected: dissolved oxygen, total suspended solids, superficial salinity and fish species richness, which cover three ECT classes (Table 4).

The second stage involves deriving the ecosystem indicators from the variables. In the first place, establishing reference levels for specific condition variables is required. Then, the indicators are calculated, rescaling the data of the individual variables and using the reference levels as high or low limits in the variable range. Finally, the information content of indicators is added to calculate the condition indices.

Reference level values used in the ecosystem condition accounts were established from bibliographic reports. For the mangrove condition account, the reference level values used were: Interstitial salinity. Reference intervals to calculate the Mangrove Biological Integrity Indicator (IBIm) for the Cienaga Grande de Santa Marta (INVEMAR 2022). At lower salinity levels, the condition of the mangrove improves. Bird species richness. Bird species reported by Moreno-Bejarano and Álvarez-León (2003). Basal area. Ranges established by Department from bibliographic reports (INVEMAR 2022). Seedlings and propagules density. Reference intervals to calculate the IBIm for the Cienaga Grande de Santa Marta (INVEMAR 2022). Changes in mangrove area (SDG 6.6.1). Indicator of extent of mangrove forests, case Cienaga Grande de Santa Marta - CGSM for the period 1956 - 2019 at scale 1:50000 (INVEMAR 2022).

The reference level values used in the coastal lagoons condition account were: Total suspended solids. Reference values to classify water quality (INVEMAR 2021). At lower concentration of total suspended solids, the condition of the ecosystem improves. Dissolved oxygen. Concentration defined by Colombian regulations for warm fresh waters, estuarine waters and marine waters (4.00 mg O₂ l^-1) (INVEMAR 2021). Surface salinity. Minimum and maximum salinity values recorded in the CGSM between October 2016 and September 2019 (INVEMAR 2018, INVEMAR 2019). At lower salinity levels, the condition of the ecosystem improves. Fish species richness. Commercial fishing species of the CGSM ecoregion (INVEMAR 2021).

The charts for accounting the extent, condition and monetary assets of the ecosystems were elaborated by following the account structure suggested by the SEEA EA accounting framework. Once elaborated, the main information gaps and challenges were identified for implementing ecosystems accounting in a marine-coastal landscape, such as the CGSM Ramsar site. Challenges were identified to attribute ES provision to a specific ecosystem type, in particular for the case of the fishing provision ES. In this study, individual charts for the global climate regulation and the wild fish provision services were presented with data in physical and monetary units.

Suppl. material 1 presents the table for accounting the asset extent of the CGSM Ramsar site ecosystems with the opening and closing stocks for the accounting periods 2012 and 2018.

The ecosystem assets with the highest losses in the 2012-2018 accounting period were pastures, continental wet areas and mangrove forests. The highest gains were recorded in permanent crops, areas with herbaceous and/or shrub vegetation and open areas with little or no vegetation (Fig. 4).

Figure 4.

Gains and losses (ha) of ecosystem assets (EA) for the accounting period 2012 - 2018.

Suppl. material 3 corresponds to the combined version of the accounting table for the mangrove ecosystem condition in the CGSM Ramsar site for the 2017-2019 accounting period.

In the Table, the green cells represent the ecosystem condition variables, which constitute the result of the first stage of the condition accounts compilation. The yellow cells represent the ecosystem condition indicators corresponding to the second stage and the blue cells represent the ecosystem condition aggregate, which is a product of the third stage of the accounting compilation. The results show:

• An increase in the total value of the abiotic indices due to a decrease in interstitial salinity.
• An increase in the biotic indices due to an increase in bird species richness and the presence of seedlings and propagules (however, the basal area showed a decrease during this accounting period).
• An increase in the landscape indices due to an increase in mangrove forest areas in the CGSM Ramsar site during the 2017-2019 period.

Suppl. material 4 presents the combined account of the coastal lagoon ecosystem conditions in the CGSM Ramsar site for the 2017-2019 accounting period.

The results show:

• A decrease in the total values of the abiotic indices due to a decrease in the dissolved oxygen concentration and an increase in the superficial salinity.
• A decrease in the values of biotic indices as a consequence of a decrease in the fish species wealth for the coastal lagoons of the CGSM Ramsar site during the 2017-2019 accounting period.

Table 5 presents the condition indices account, showing a derivation of the aggregate measurements of the mangrove and coastal lagoon ecosystems in the CGSM for the 2017-2019 accounting period.

The results show a net positive change in mangrove conditions, as a consequence of an increase in the values of biotic, abiotic and landscape characteristics. On its part, the coastal lagoons showed a net negative change due to a decrease in the values of the biotic and abiotic characteristics.

Table 6 shows the fishing resources provision ES accounting table for the period 2015-2019.

The total catch has varied between 4617 and 6035 tonne * year^-1, showing a net positive change of 721 tonne * year^-1 for the 2015-2019 accounting period. Fish, followed by crustaceans, recorded the highest catches in the CGSM during this accounting period. SIPEIN did not collect information on mollusc catches during the 2018-2019 period due to logistical issues, which entailed a catch underestimation of these resources for this year (INVEMAR 2019).

Table 7 shows the accounting table for the carbon storage ES provided by the mangrove ecosystem in the CGSM Ramsar site during the 2015-2019 accounting period.

The carbon stock account shows a decrease in the aboveground carbon content during the 2015-2019 period for the different CGSM mangrove types. By 2019, the mangrove carbon content was 16.5% lower than in 2015, evidencing the deterioration suffered by the CGSM mangrove, especially between 2015 and 2017, when the highest decrease took place in the biophysical and monetary stocks. During 2018 and 2019, a positive increase in the biophysical carbon took place, but, in monetary terms, there was a stock decrease, a situation made possible by the Colombian peso’s devaluation against the dollar.

Table 8 shows the accounting table of the carbon sequestration ES provided by the mangrove ecosystem in the CGSM Ramsar site for the 2015-2019 accounting period.

In the carbon sequestration account, due to the deterioration of the mangrove, except for the fringe and riverine mangroves between 2018 and 2019, the different mangrove types generated carbon emissions during the 2015-2019 accounting period. Given that most of the mangrove cover corresponds to basin mangrove, this forest type shows the highest emissions.

Table 9 presents the ecosystem assets account in monetary terms for the CGSM Ramsar site during the 2015-2019 accounting period. In order to provide a valuation of the mangrove assets, the monetary value of the CGSM mangrove carbon stock was included, which was estimated at USD 68,300,000 for 2015 and USD 55,130,561 for 2019. For the mangrove and coastal lagoon ecosystems, the annual supply flow of wild fishing in 2015 and 2019 was used in the valuation of the assets (Table 6), with the net present value method and the following asumptions: an asset lifecycle of 100 years and a social discount rate of 3.5% adopted in Colombia as a parameter in the evaluation of environmental investment projects of the public sector of more than 25 years old in the resolution of the National Planning Department (DNP) No: 1092/22 (Departamento Nacional de Planeacion 2022); the asset value reached USD 105,706,598 in 2015 and USD 97,268,070 in 2019.

Overall, there are considerable losses in the ecosystems’ assets between 2015 and 2019: USD 21,607,967 were lost. There were losses in mangroves of USD 13,169,439 and in Coastal Lagoons & Mangroves of USD 8,438,527. These results show the critical condition of the CGSM’s resources, with an emphasis on the emergence of a type of artisanal fishing in the area, on which families with high poverty levels depend.

SEEA EA ecosystems accounting is based on the acknowledgement that healthy ecosystems and biodiversity are fundamental for supporting and sustaining our welfare, communities and economies (United Nations 2021). Therefore, one of its main objectives is to establish a clear link between the ecosystems’ extent and condition and the ES they provide (La Notte et al. 2022). This is the study case presented in this document, where the CGSM Ramsar site was used as reference and the ecosystems accounting approach was used to provide visibility to the relationships between ecosystem health, human welfare and economy.

The ecosystem extent account shows a decrease in the pasture, continental wet area and mangrove forest area for the period between 2012 and 2018. This may be attributed to changes in soil use, as these ecosystems mainly became permanent crops and heterogeneous agricultural areas. For the specific case of the mangrove, a significant cover loss occurred during the period 2015-2017, as a consequence of the El Niño event, which showed strong and very strong intensities in 2015 and 2016, generating a decrease in the rainfall in the Colombian Caribbean and an increase in the interstitial salinity of the CGSM, which had a negative effect on ecosystem health (INVEMAR 2022).

Nevertheless, since that year (2017), forest recovery has been evidenced, which reflects on the results of the mangrove condition accounts for the period 2017-2019. They show a net positive change in the indicators used to measure this ecosystem’s condition. This change is due to a freshwater input into the lagoon system derived from the dredging works on the main channels coming from Magdalena River, as well as the absence of El Niño-related events. These freshwater inputs generated a decrease in the interstitial salinity and an increase in the seeds and propagules density during this accounting period (INVEMAR 2021, INVEMAR 2022).

As a consequence, a 3,503 ha extension also took place in the period 2017-2019, which corresponds to a 6.87% recovery of the live mangrove, as compared to the initial period in 1956, when 51,150 ha were reported. This increase is a response of the ecosystem to salinity variations and exposes the importance of keeping the freshwater flows coming into the CGSM in optimal conditions.

Regarding bird richness, there was an increase in the number of species. A total of 98 species were recorded in 2019, which corresponds to 50.52% of the reported birds for the Magdalena River delta-estuarine complex (Moreno-Bejarano and Álvarez-León 2003). It is worth highlighting that the registry of species of interest for conservation – such as the northern screamer (Chauna chavaria), the sapphire-bellied hummingbird (Chrysuronia lilliae) and the bronzed cowbird (Molothrus aeneus), in addition to a high number of migratory species – account for the importance of this ecosystem for the birds in the area and their conservation (INVEMAR 2019).

A clear example of the bond between the ecosystem extent and condition and ES provision can be seen in the carbon sequestration ES accounts, whose results show that the cover and/or aerial biomass losses generated carbon emissions during the period 2015-2019 (this record excludes the fringe/riverine mangrove between 2018 and 2019). This is due to the hydric stress undergone by mangroves as a consequence of El Niño event reaching strong to very strong intensities between 2015 and 2016, in addition to other disturbances, such as burnings to obtain charcoal and wetland desiccation. However, the mangrove forest emitted 182,000 less tonnes of carbon than in 2015-2017, reflecting a positive balance with regard to carbon sequestration and mangrove recovery.

The carbon storage account also presented, as it did between 2015 and 2017, the highest decrease in stored carbon for the different mangrove types in these CGSM. From these years on, there was a progressive increase in the carbon stock, as a result of the recovery in ecosystem extent and condition. However, despite the deterioration undergone by the CGSM mangroves, this system shows carbon reservoirs in the order of million tonnes. Likewise, the carbon stocks presented herein are underestimated because mangroves have carbon reservoirs at several metres in depth and the soil carbon measurements used as reference only consider 1 m.

This study’s results regarding coverage and carbon sequestration follow the trend of mangroves in Ramsar sites worldwide (Convención sobre los Humedales 2021). On the one hand, the mangrove extent decreased by an average of 4% between 1997 and 2016, a loss rate estimated at 0.2% a year, which is an order of magnitude lower than the worldwide mean annual loss, estimated at 2% (Convention on Wetlands 2021). Despite that, more than two thirds of the Ramsar sites' mangroves lost surface area, which means that, not only did they lose the capacity to sequester carbon, but also suffered inevitable losses as the carbon stored in soils and biomass were liberated into the atmosphere. Another 20% of the Ramsar sites showed an increase in mangrove area and are, therefore, sequestering more carbon (Convention on Wetlands 2021).

Another link between the ecosystem condition and the provision of services can be seen in the wild fish provision ES account. The analysis performed from the monitoring of INVEMAR fishing resources allows concluding that the changes in resource availability are a response to changes in water salinity, which, in turn, is conditioned by climate variability (INVEMAR 2021). The results of the fishing resources ES account for the period 2015-2019 show that the total catch varied between 4,617 and 6,035 tonne year^-1, highlighting a drastic decrease in 2016, when the highest salinity records of the last two decades were obtained (INVEMAR 2019). Later, between 2017 and 2018, there was a decrease in the salinity values and a recovery of fishery – although another El Niño event took place in 2019 – showing an apparent improvement in the environmental condition of the CGSM, without evidence of a massive fish death toll as in previous years (INVEMAR 2019).

Regarding the annual composition of catch per fish species, the fish monitoring allowed identifying changes in their represention. Due to a salinity increase during El Niño event between 2014 and 2016, fishery was supported by the extraction of estuarine species. Later, in 2017, there was a La Niña event, albeit preceded by El Niño. This climate pattern favoured the estuarine species that showed the greatest appearances, also recording increases in marine species. In 2018, the La Niña event trend of 2017 continued, accordingly reporting a decrease in salinity, a condition that continued even in 2019, despite the occurrence of an El Niño event, with evident improvements in the production of freshwater species (INVEMAR 2019, INVEMAR 2021). These data coincide with the results obtained by Vargas et al. (2022), who, in a study seeking to evaluate the contribution of catch diversity to the stabilisation of fishing income in the CGSM’s biosphere reserve, found that changes in the catch composition during 2012-2018 were related to the seasonal and year-to-year variations of salinity conditions and that catch mean values per effort unit were higher at intermediate salinity levels.

In short, CGSM ecosystems provide a set of services that are fundamental for the human communities inhabiting the area or interacting with the system at other geographical scales (Vilardy and González 2011). However, these ecosystem conditions, as well as their ability to provide services, has been seriously affected by changes in their biotic and abiotic characteristics, especially by the increases in the salinity levels that mainly occurred as a consequence of the alteration of hydric flows and the year-to-year climate variability. In turn, these ecosystems have also responded positively to the interventions orientated towards re-establishing the hydric regime in some CGSM areas.

This pilot study confirms the viability of ecosystems accounting with regard to providing visibility to the contributions of CGSM marine and coastal ecosystems to people and the economy, as well as the usefulness of the accounting framework to providing information for decision-making when integrating information from multiple sources about ecosystem changes and their effects on the provision of ES. Future research should focus on studying and understanding the ecological and management conditions under which the ecosystem services can be sustainably produced. It must aim at identifying management strategies that allow ensuring the continuity of key CGSM ecosystem services, such as food provision, climate regulation and tourism, amongst others. In the SEEA EA accounting context, the ecosystems’ ability to provide ES is defined by their ability to generate them under management conditions and uses at the highest performance or level without affecting its future supply or that of other ES. The evaluation of the capacity of ecosystems to provide ES will depend on the complex interrelationships of multiple indicators to determine the threshold levels that define sustainability (United Nations 2021).

Given the complexity of the marine environment and the difficulty to collect data about it, applying the natural capital approach for the coastal marine environment poses a series of particular challenges that often require modifying methods and strategies (Hooper et al. 2019). To date, the efforts in environmental and economic accounting have focused mainly on the terrestrial domain and have given limited attention to the application of concepts, definitions and classifications to the ocean (Gacutan et al. 2022). Likewise, data and methods to evaluate the provision of marine and coastal ecosystem services are much more limited when compared to terrestrial evaluations (Liquete et al. 2013). Therefore, data availability is a key challenge, especially in the marine environment. To overcome this, a greater effort is required to develop interdisciplinary methodologies that are coherent with policies and applicable in a variety of contexts (Hooper et al. 2019). According to Barbier (2017), the greatest challenge to quantify and value marine ecosystem services is the inadequacy of the available knowledge in order to link changes in the ecosystems’ structure and function to the production of valuable goods and services.

By developing the accounting tables, information gaps were identified which hindered their full elaboration with regard to extent, condition, ecosystem services and monetary assets for the CGSM Ramsar site, as data were not collected at the required spatial or temporal disaggregation level.

For the extent accounts, opening and closing extent data were obtained for all the ecosystems’ assets in the CGSM Ramsar site, thanks to the availability of the land cover layers at a 1:100,000 scale of IDEAM’s CORINE Land Cover for the period 2012-2018. However, difficulties were identified in attributing gains and/or losses in the ecosystem extent to natural events or anthropogenic actions.

The ecosystem condition accounts were limited to mangroves and coastal lagoons because of the data availability for these ecosystems, which stem from the monitoring of water quality, mangrove forest conditions and fishing resources published yearly by INVEMAR. However, information gaps were identified which hindered the reporting of data for all six classes of abiotic, biotic and landscape variables suggested by SEEA EA to measure the ecosystems’ condition.

Regarding the ES flow accounts, difficulties were identified with regard to delimiting the specific contribution of each ecosystem to synergically generated matter and energy flows, for example, estimating the contribution of the coastal marine landscape ecosystems to the commercially important biomass of fish, crustaceans and molluscs. This is because data on fish catch are collected at CGSM landing sites and they are not specifically associated with an ecosystem. In this regard, Barbier (2017) highlights that marine and coastal ecosystems do not exist in isolation, but they are often interconnected through a continuous sea-land or marine landscape (seascape) interface. Therefore, the challenge for future research is to evaluate the benefits that arise in a highly interconnected marine landscape. An emergent and increasingly common approach to evaluating multiple ecosystem services, which is sensitive to the sociological context, is studying them as recurring sets of ecosystem services or ecosystem services bundles (Meacham et al. 2022).

Another important relationship in the way society receives ES corresponds to markets, whose prices were used for valuation in the case of fishing resources. It was evidenced that the biophysical increase in catches is not always directly related to the received monetary income, a situation that may be caused by price elasticity – fishing resources show inelastic supply and elastic demand. It is also necessary considering that fishing income comes from a multi-species basket of offerings with different degrees of replacement depending on consumer preferences. On the other hand, for commercialising CGSM fishing, there are institutional arrangements that influence the income received by fishermen, for instance, fishing pre-sales agreements.

Due to its spatial approach, ecosystem accounting (SEEA EA) allows highlighting and identifying the location of ecosystems and ecosystem services of special interest for those responsible for making policies and decisions orientated towards maintaining the ecosystems’ condition and the continuity of the CGSM’s key ecosystem service flows. Likewise, the construction of ecosystem accounts for several years provides a common baseline that is useful for monitoring the extent, condition and service flow of the ecosystems.

The accounts compiled in this study contribute directly to collecting, organising and integrating spatially referenced data on changes in the ecosystems’ extent and condition, as well as on flows of key ecosystem services, such as fishing resources provision and climate regulation, changes that are associated with the year-to-year climate variation and their effects on the CGSM’s salinity, both in its water bodies and in the soil’s interstitial salinity. Thus, ecosystems accounting evidenced the link between climate variability and the flow of services and benefits for the local communities.

The correspondence between the types of cover/ecosystem (EA) in the CGSM Ramsar site (IDEAM 2010) to the SEEA’s reference ecosystem classification system (Keith et al. 2020) provides a common baseline that can be used for international comparison purposes, which implies an abundance of ecosystem types.

The ecosystem extent account, besides generating information about the gains and losses of ecosystem assets during the period 2012-2018, allowed identifying the nature of these ecosystems’ transitions and spatially locating the critical spots where the gains and losses of natural to transformed cover have concentrated (Fig. 5). This information shows the landscape configuration change during this accounting period and sets the grounds for a complementary analysis on the possible factors that drove these transformations. That is how the decrease in the extent of strategic ecosystems, such as continental wetlands and mangrove forests between 2012 and 2018, exposes the need for monitoring coverages that are growing at the expense of these ecosystems, as well as of continuing with the management measures of channels to maintain the system’s salinity in tolerable conditions in the face future high-intensity El Niño events.

Regarding the climate regulation ES, this study shows that fringe and riverine mangroves are less fluctuating than basin mangroves, which have larger extent and are more susceptible to generating carbon emissions in the face of hydric stress situations under El Niño conditions. Therefore, special management strategies are required such as carrying out channel maintenance at the beginning and during high-intensity El Niño events in order to maintain the mangrove's ability to contribute to climate regulation through carbon sequestration and storage.

Finally, this ecosystems accounting exercise in the CGSM Ramsar site allowed identifying and giving visibility to the magnitude of coastal and marine ecosystems’ contributions to the economy, social welfare and livelihoods at local and global scales, contributions that, in general, have received less attention than those of terrestrial ecosystems. At a local scale, between 3,000 and 3,500 artisan workers obtain their livelihoods through the provision of fishing resources in the CGSM and they obtain much of their food security from fishing (INVEMAR 2021). At a global scale, the climate regulation ES reveals, in the carbon capture and storage accounts, that CGSM mangroves have carbon reservoirs in the order of million tonnes and that the stocks estimated for 2015 and 2019 equate to the annual carbon dioxide emissions of 19.6-25.2 million Colombians – or 2.1-2.7 million US citizens.