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Article

Assessment of the Trophic Status and Trend Using the Transitional Water Eutrophication Assessment Method: A Case Study from Venice Lagoon

by
Emanuele Ponis
1,*,
Federica Cacciatore
1,
Valentina Bernarello
1,
Rossella Boscolo Brusà
1,
Marta Novello
2,
Adriano Sfriso
3,
Fabio Strazzabosco
2,
Michele Cornello
1 and
Andrea Bonometto
1
1
ISPRA, Italian National Institute for Environmental Protection and Research, Brondolo 5, 30015 Chioggia, Italy
2
Environmental Prevention and Protection Agency of Veneto Region (ARPAV), Via Ospedale Civile 24, 35121 Padua, Italy
3
Department of Environmental Sciences, Informatics & Statistics (DAIS), University Ca’ Foscari Venice, Via Torino 155, 30170 Mestre, Italy
*
Author to whom correspondence should be addressed.
Environments 2024, 11(11), 251; https://doi.org/10.3390/environments11110251
Submission received: 28 August 2024 / Revised: 14 October 2024 / Accepted: 31 October 2024 / Published: 12 November 2024
Browse Figures
Figure 1
<p>Map of the stations sampled in the Venice Lagoon during the period 2011–2022. Natural water bodies, according to WFD, are also indicated.</p> "> Figure 2
<p>Distribution (%) of the TWEAM trophic classes for each triennial monitoring cycle (MC). (<b>A</b>): data grouped per water body (WB); (<b>B</b>): data grouped per station (ST).</p> "> Figure 3
<p>Eutrophic status assessment using the TWEAM in Venice Lagoon WBs (background color) and stations (dot color) during the first (<b>A</b>: 2011–2013) and last (<b>B</b>: 2020–2022) MC. Green = non-eutrophic; beige = mesotrophic; red = eutrophic.</p> "> Figure 4
<p>Box plots of the scores of TWEAM metrics resulted at the 28 stations in the Venice Lagoon: (<b>A</b>) Dissolved Inorganic Nitrogen (DIN) (μM); (<b>B</b>) Orthophosphate (P-PO<sub>4</sub>) (μM); (<b>C</b>) MaQI index; (<b>D</b>) TWQI index. Data are grouped per monitoring cycle (MC). Dotted lines indicate the boundaries among ecological quality classes: H = high; G = good; M = moderate; P = poor; B = bad.</p> "> Figure 5
<p>PCA biplot of the two main components for the whole dataset, including the TWEAM metrics as variables and TWEAM scores as supplementary quantitative variables. The data of the four cycles are grouped per TWEAM class. For each group, the centroids and the confidence ellipses (95% of samples) are shown.</p> ">
Versions Notes

Abstract

:
The Transitional Water Eutrophication Assessment Method (TWEAM) is a multi-index set up for assessing the eutrophication risk and trend in transitional waters. It includes a selection of environmental variables, an ecological status indicator (i.e., Macrophyte Quality Index, MaQI) and the Transitional Water Quality Index (TWQI). Possible outcomes of the TWEAM include three trophic classes in terms of eutrophication risk: (i) eutrophic; (ii) non-eutrophic; (iii) mesotrophic. The method was applied on data collected at 28 stations in the Venice Lagoon over four triennial monitoring cycles (MC I-IV) in the period 2011–2022. The spatial variability and medium-term trend of eutrophication risk were investigated, highlighting a general improvement in trophic conditions over time, with a decrease in mesotrophic stations (representing 46% of total in MC-I and 25% in MC-IV) in favor of non-eutrophic stations (46% of total in MC-I and 73% in MC-IV). The main driver of observed positive changes is related to the colonization of sensitive macroalgae and aquatic angiosperms, resulting in an increase in the percentage of stations with MaQI in good/high ecological status from 25% in MC-I to 54% in MC-IV. Eutrophic sites showed a non-linear trend, particularly in choked areas of the central lagoon, with anthropogenic disturbances and low water renewal.

1. Introduction

The eutrophication assessment of transitional water bodies represents a complex issue, considering their naturally high productivity and the confounding influences from naturally (i.e., natural decomposition of organic matter, freshwater inputs of water naturally rich in organic matter, nutrient imbalance caused by natural nitrification, low water renewal) and anthropogenically (i.e., agricultural runoff, wastewater discharges, aquaculture) induced processes [1,2].
Finding a reliable method to correctly evaluate the trophic status of these environments has great strategic relevance in the implementation of protection and restoration strategies, with strong consequences on either environmental planning or management [3,4,5]. An inaccurate evaluation of the trophic status may, in fact, hinder a correct evaluation of the effectiveness of measures implemented over time to reduce eutrophication, as well as negatively affect the effectiveness of the new measures planning to be undertaken.
The trophic status assessment of shallow coastal lagoons is strongly affected by the high temporal variability of biotic and abiotic variables, which significantly fluctuate depending on tidal and seasonal factors, such as freshwater inputs, the seasonal succession of primary producers, and the seawater renewal rate [6,7].
The eutrophication assessment of superficial water bodies has historically been quantified through the measurement of variables such as, for instance, water transparency, primary production, nutrients, and oxygen demand [8,9]. Several studies, starting from the pivotal works in [10] on coastal waters and [11] on lakes, demonstrated the effectiveness of multi-metric indices on providing more reliable and comprehensive estimates of the trophic status compared to single metrics or parameters that provide only partial and not robust information on the trophic status. The added value of using a multi-metric index instead of single metrics is particularly pronounced in the case of estuarine environments, usually with conditions of high spatial and temporal fluctuations [8,12].
The assessment of medium- to long-term trends is essential for understanding the ongoing dynamics, encompassing both natural changes and those arising from restoration efforts or, conversely, anthropogenic pressures. Most studies evaluating trends over the medium to long term analyzed different parameters individually, e.g., [13,14,15], while there are few examples in the literature of trend studies based on multi-metric indices, e.g., [16,17], likely due to the challenge of having homogeneous long-term data required for their application to past periods.
Since the second half of the 20th century, the Venice Lagoon ecosystem was particularly exposed to eutrophication threats, due to different anthropogenic drivers that led to the nutrient enrichment of waters and sediments. Starting from the first decade of 2000, a progressive improvement in the trophic status of the Venice lagoon has been observed, even if it still remains a sensible area at risk of eutrophication and particularly vulnerable to climate change [18] (and references therein) and [19].
Despite being recently developed [20], the Transitional Water Eutrophication Assessment method (TWEAM) was designed as a smart index calculated from commonly collected data in institutional monitoring programs, such as those related to the Water Framework Directive (WFD, 2000/60/EC), and it is thus easily applicable to past periods. Moreover, the TWEAM is officially accepted as an Italian methodology for the evaluation of eutrophication in transitional Water Bodies (WBs) and complies with both the WFD and Nitrate (ND, 91/676/EEC) Directives.
In this study, we present the first application of the TWEAM for an integrated analysis of the medium-term trend (2011–2022), based on WFD triennial monitoring cycle data, of eutrophication risk in a lagoon environment, such as the Venice Lagoon, that is one of the most relevant transitional systems of the Mediterranean Sea.

2. Materials and Methods

2.1. Study Area

The Venice Lagoon is a large coastal microtidal lagoon (approx. 550 km2), mostly characterized by shallow waters (average depth close to 1 m) and canals connected to the sea by 3 large (600–900 m) and deep (10–15, up over 50 m) inlets. The lagoon includes a complex mosaic of aquatic, intertidal, and terrestrial habitats of ecological relevance and hosts a large list of flora and fauna species of conservation and community interest. Further details can be found in the European Nature Information System webpage (EUNIS) dedicated to the Venice Lagoon and its NATURA 2000 habitats [21]. According to the WFD, the Venice Lagoon is divided into 11 natural WBs (belonging to 4 different types according to salinity (polyaline (P) = salinity range 20–30; euhaline (E) = salinity ≥ 30) and to confinement degree (C = confined; NC = non-confined)) and 3 heavily modified WBs.

2.2. Data Collection and Analyses

The dataset analyzed during this work includes 28 stations, representative of the 11 natural WBs of the Venice Lagoon (Figure 1), selected among those routinely monitored by the Environmental Prevention and Protection Agency of Veneto Region (ARPAV) within the institutional WFD monitoring activities for the classification of the ecological quality status of each WB. In particular, the dataset includes four triennial monitoring cycles (MCs) of WFD operational monitoring: I cycle (2011–2013); II cycle (2014–2016); III cycle (2017–2019); IV cycle (2020–2022). Among the data collected in this context, this study has considered physico-chemical parameters and macrophyte data. In particular, physico-chemical parameters (i.e., dissolved inorganic nitrogen (DIN = NO3− + NO2− + NH4+), orthophosphates (P-PO4), Chlorophyll-a (Chl-a), dissolved oxygen (DO)), were collected seasonally (four times a year) every year from all MCs, while macrophyte data were collected twice a year (spring and autumn) in only one year for each MC, according to the WFD operational monitoring program transposed into national law (Italian Legislative Decree, D.Lgs. 156/2006 and its subsequent amendments and additions).
For the whole considered period, sampling and laboratory analyses were performed according to the national protocols described in [22,23].
Macrophyte cover and species identification were assessed according to Sfriso et al., 2019 [24]. The ecological classification status of macrophytes (sensu WFD) was assessed using the Macrophyte Quality Index (MaQI) [25], officially adopted by Italian legislation.

2.3. The TWEAM Index

An exhaustive description of the TWEAM index is reported in [20].
Briefly, the multi-metric index is based on a step procedure. Phase 1 considers a preliminary screening based on MaQI and DIN, P-PO4 concentrations, averaged over each cycle and assessed with the thresholds set by Italian legislation (Italian Environmental Ministry Decree 260/2010). This phase may allow for the direct classification of trophic status (E1 = eutrophic, N1 = non-eutrophic) while, in case of mismatches between nutrients, or among nutrients and MaQI, a further step is required (Phase 2).
Phase 2 integrates results by the application of the Transitional Water Quality Index (TWQI), a multi-metric index set up for assessing the trophic status in shallow transitional water ecosystems [26]. The TWQI combines main causal factors of eutrophication (N and P concentrations), key biological elements (Chl-a, aquatic angiosperm and macroalgal cover), and an indicator of eutrophication effects (DO). The TWQI score was calculated using data collected over one year for each cycle, by averaging the values of water quality data (nutrients, Chl-a, and DO), sampled quarterly, and the percentage of aquatic angiosperm and macroalgae cover, sampled twice (spring and autumn), using the boundary classification inferred by Christia et al., 2014 [27].
The classes identified in this phase are as follows:
  • E2 = eutrophic, based on integrated analysis;
  • N2 = non-eutrophic, based on integrated analysis;
  • M = mesotrophic, at risk of eutrophication in the case of the current trend indicating a worsening.
Considering that N1 and N2 both refer to the same non-eutrophic status, and as a similar consideration, both E1 and E2 refer to the same eutrophic status, the final outcomes of the TWEAM application can be resumed in three classes: eutrophic (E), mesotrophic (M), and non-eutrophic (N).

2.4. Statistical Analysis

Statistical analyses were performed using R software (version R.4.3.2) [28], with the packages lawstat (version 3.6), kendall (version 2.2.1), Rcmdr (version 2.9-5), RcmdrFactoMineR (version 2.11), factorextra (version 1.07), and rColorBrewer (version 1.1-3). The ANOSIM (analysis of similarity) test was applied using Primer v.6.
Pairwise comparisons were performed using Tukey and Kramer (Nemenyi) tests with Tukey–Dist approximation for independent samples, when the Kruskal–Wallis rank test was significant (p < 0.05).
Trend analysis was performed using the Mann–Kendall test.
The principal component factor analysis (PCA) technique was applied to investigate the factors that mainly affect the variance of each TWEAM class. One-way ANOSIM and related pairwise comparisons (number of permutations 999) were applied to test the differences among groups of stations highlighted by PCA biplot results. The level of significance was p < 0.1%.

3. Results

All input data and results are reported in the Supplementary Materials in Table S1 (TWQI data input and results) and Table S2 (TWEAM data input and results).

3.1. Eutrophic Risk Assessment by TWEAM

Over the four triennial cycles of monitoring, significant heterogeneity of trophic conditions was found (Table 1, Figure 2), with a dominance of non-eutrophic and mesotrophic WBs in MC I (46% each) and II (46% and 36%, respectively) and of non-eutrophic WBs in MC III and IV (64% and 73%, respectively). Comparing the first and the last monitoring cycles, three WBs improved their status from M to N, whilst in both cycles, PC4 was the only WB classified under the eutrophic condition. Similar temporal patterns were observed at a station scale (Table 1, Figure 2). During the period 2011–2022, the number of stations classified under non-eutrophic conditions increased from 11 in MC I to 18 in MC IV, whilst the mesotrophic stations decreased from 15 to 7. The number of eutrophic stations increased from two in MC I to six in MC II and III, due to the worsening of the trophic conditions of stations in the central lagoon at WBs PNC1 (PNC1_1, PNC1-7B) and PNC2 (PNC2_1, PNC2_2). Thereafter, except for PNC1, these stations returned to their initial mesotrophic status.
At a geographical scale (Figure 3), stations classified under non-eutrophic status were widely distributed throughout the lagoon, except for the three WBs, located in the inner areas of the southern and central basins (PC3, PC4) and between the city of Venice, the industrial area of Porto Marghera, and the settlement of Mestre (PNC1), that always maintained a mesotrophic or eutrophic status. The comparison between the first and the last monitoring cycles showed an improvement in the non-eutrophic status of stations, particularly in the southern basin. Differently, in the central and northern basin, most stations belonging to polyhaline WBs maintained their mesotrophic condition.

3.2. Analysis of TWEAM Metrics

The box plots of the single TWEAM metrics are resumed in Figure 4.

3.2.1. Metric 1: DIN

DIN concentrations constantly decreased over time (Figure 4A), with a mean value (average of all stations for each MC) ranging from 26.9 μM in cycle I to 12.2 μM in cycle IV. The thresholds set by Italian legislation for good ecological status (GES, sensu WFD) in water bodies with salinity <30 (DIN < 30 μM) and >30 (DIN < 18 μM) were exceeded for 50.0% of the stations in cycle I, for 14.3% of stations in cycle II, for 10.7% of stations in cycle III, and at only one station (3.6%) in cycle IV.
The Mann–Kendall test did not indicate a significant trend (p > 0.05, tau negative). However, significant differences were found among monitoring cycles (Kruskal–Wallis = 27.314, df = 3, p < 0.001), with DIN values statistically higher in cycle I than in other cycles (p < 0.01).

3.2.2. Metric 2: P-PO4

A decrease over time was observed also for P-PO4 (Figure 4B), with mean values ranging from 0.27 μM in cycle I to 0.10 μM in cycle IV. No station exceeded the threshold of 0.48 μM defined by Italian legislation for the GES of euhaline WBs.
The Mann–Kendall test, as in the case of DIN, did not show a statistically significant trend (p > 0.05, tau negative).
Significant differences were found among monitoring cycles (Kruskal–Wallis = 39.215, df = 3, p < 0.001) with only the P-PO4 concentrations of cycle I statistically higher than those of cycle IV (p < 0.01).

3.2.3. Metric 3: MaQI

During the four cycles, the MaQI scores exhibited a constant increase, from a mean value corresponding to a classification of moderate ecological status in MC I and II to a good ecological status in MC III and IV (Figure 4C). These changes are consequences of a decrease over MCs in the number of stations in poor ecological status (from 50.0% in cycle I to 35.7% in cycle IV) and an increase in stations in good ecological status (from 17.9% in cycle I to 46.4% in cycle IV).
The Mann–Kendall test showed no significant trend (p > 0.05, tau positive). No significant differences were also found among cycles (Kruskal–Wallis = 6.244, df = 3, p > 0.05).

3.2.4. Metric 4: TWQI

The TWQI mean values were quite stable among the different cycles, varying between 59.9 and 63.3, leading to an overall classification of good status, except for MC II (moderate) (Figure 4D). These values were close to the moderate/good boundary of 60. The most frequent classes were good in the I and III MCs (42.9% and 46.3%, respectively) and moderate in the II and IV MCs (46.4% and 39.3%, respectively). Considering the single metrics composing the TWQI index, most of variations among cycles are consequences of changes in macroalgal coverage (range of MCs’ means: 32.7%–58.3%) and aquatic angiosperm coverage (range of MCs’ means: 16.8%–29.1%).
The Mann–Kendall test resulted not statistically significant (p > 0.05, tau negative). No significant differences were found among cycles (Kruskal–Wallis = 1.410, df = 3, p > 0.05).
Figure 5 depicts PCA results, showing that the first (Dim 1) and second (Dim 2) components together explained 83.9% of the total variance. Non-eutrophic stations differed from eutrophic ones for Dim1, with the first group mostly associated with positive MaQI and TWQI scores (factor scores of 0.884 and 0.815, respectively) and the latter associated with negative P-PO4 and DIN scores (factor scores of −0.672 and −0.810, respectively). Dim 2 is mostly associated with a positive P-PO4 score (factor score of 0.640). Non-eutrophic stations were well separated from the other groups, while eutrophic and mesotrophic stations largely overlapped. ANOSIM confirmed significant differences among all groups (Global R = 0.44, p < 0.1%), and pairwise tests showed significant differences between N vs. E (R = 0.697, p = 0.1%) and N vs. M (R = 0.399, p = 0.1%). Overlap between M and E, shown in biplot Figure 5, was also confirmed (R = 0.11, p = 4.2%).

4. Discussion

Many European policies consider eutrophication assessment as a priority issue of interest in water protection. For this purpose, pluriannual monitoring cycles are carried out by national and regional environmental agencies, collecting a multitude of physico-chemical and biological data [4,9,29]. The interpretation of these data is often difficult and uncertain, especially if the different monitored parameters provide conflicting indications. The application of the TWEAM in this work showed a strong ability to integrate all main eutrophication metrics and indicators for a comprehensive assessment of the eutrophic conditions in a lagoon over a period of four monitoring cycles from 2011 to 2022. Although we only processed data from the Venice Lagoon, they cover a wide range of environmental conditions, which differ for anthropogenic pressures, hydraulic and morphological features, and trophic status [30,31,32,33]. Moreover, the Venice Lagoon has exhibited changes in trophic conditions in recent decades [18,24], making it an ideal study site to test the capability of the TWEAM to capture temporal variations. The reliability of this method for determining eutrophication risks was previously tested over 100 Italian lagoon sites in [20].
During the first two monitoring cycles in the Venice Lagoon, the most frequent classes were non-eutrophic and mesotrophic, while eutrophic cases were less present. In the last two cycles (2017–2019 and 2020–2022), there was an increase in non-eutrophic cases, reaching up to 72.7% for WBs and 64.3% for STs in the last cycle. Conversely, during all four cycles, a sharp decrease in mesotrophic cases was recorded, dropping from 45.5% to 18.2% of WBs and from 53.6% to 25.0% of STs.
At the lagoon scale, non-eutrophic conditions were found in a large part of the lagoon, except for inner areas, which are more influenced by anthropogenic disturbances and by freshwater inputs, increasing eutrophic conditions. These findings agree with those of [24], whose authors described the Venice Lagoon as oligo-mesotrophic in a great part of its surface.
In the present study, mesotrophic stations, mostly identified in MC I, shared a similar geographical localization with eutrophic stations. The multivariate analysis highlighted the strong proximity of the centroids between the stations classified by the TWEAM as in the eutrophic and mesotrophic classes.
The long-term analysis carried out in [24] with data collected since the mid-20th century highlighted a significant increase in eutrophication from the post-World War II industrial development until the end of the 1980s. This increase triggered macroalgal blooms and favored hyper-dystrophic conditions. In the following years, different environmental scenarios have occurred, with progressive trophic improvement in the last two decades [24], mainly due to climatic changes [34], a decrease in nutrient loads [13], and natural recovery and restoration projects [35,36].
These signals of improvement were confirmed in the central area of the Lagoon of Venice in [18] for a similar timeframe. For the period 1998–2007, they highlighted a significant decrease in nitrates and ammonium, as a probable consequence of a reduction in agricultural runoff and of an improvement in wastewater treatment. The trend is less clear during the following years (2007–2017), as the stabilization of low concentrations of ammonium and interannual hydrologically driven variability for nitrates were observed.
The medium-term pattern observed in our work in the period 2011–2022 seems to confirm the above-mentioned improvement in trophic status even in presence of a not-linear temporal pattern, observed especially in eutrophic stations. The application of the TWEAM in upcoming MCs (monitoring activities are still ongoing in the area, as a part of national institutional WFD activities) will allow us to verify the significance of the changes in trophic state in a longer time series.
The average annual concentrations of nutrients showed a slight decrease for both DIN and P-PO4, with values that remained low during all four monitoring cycles (except for four stations in cycle I for DIN), sustaining non-eutrophic conditions. MaQI results indicated a constant increase in the ecological quality status, confirming changes in macroalgal and aquatic angiosperm assemblages observed in previous works that highlighted the shift from opportunistic macroalgae to species with higher ecological values, as well as the recolonization of aquatic angiosperms [36,37]. TWQI values resulted quite stable, with no significant trend over the four cycles, since the increase in aquatic angiosperm coverage, which enhances the index value, was generally negatively compensated for by the increase in macroalgae coverage without considering their ecological value. In addition, the use of macroalgae cover, as a proxy of macroalgae abundance in TWQI metrics, could lead to the underestimation of trophic status in case of a high percentage of cover but low biomass.
The general improvement of trophic conditions over time is the result of a progressive shift of most mesotrophic stations toward non-eutrophic conditions. Eutrophic stations showed a non-linear trend, especially in choked areas of the central lagoon, with an inter-cycle fluctuation between eutrophic and mesotrophic conditions. These findings suggest the instability of mesotrophic status in the Venice Lagoon, which may represent an intermediate stage of transition. The number of mesotrophic stations decreased from 15 in the MC I to 8 in MC II and 4 in MC III; thereafter, a partial increase in mesotrophic stations was observed in MC IV (7 STs), which may represent an intermediate stage of transition.
This circumstance does not find clear references in the literature, despite a multitude of works that analyzed trends in trophic status. Therefore, more than being an intrinsic characteristic of mesotrophic conditions, the observed instability could stem from the concurrent and opposite effect of (i) the implementation of measures aimed at reducing the risk of eutrophication and, more generally, at improving the ecological quality of transitional environments, as well as (ii) the intrinsic vulnerability of transitional environments that are exposed to eutrophication risk.
In recent decades, indeed, several measures have been implemented to reduce sources of pressure and to increase overall purification capacity and to limit the input of nutrients into the lagoon, such as an increase in sewage treatments and a reduction in detergent phosphorus [13], best practices in agriculture, and nature-based solutions at the river basin scale, e.g., [38]. In addition, in recent years, large-scale ecological restoration measures have also been carried out to enhance the recovery of the conservation status of lagoon water bodies [39,40]. The overall effect of this strategy has favored a gradual improvement in trophic status over the long term, which is still observable nowadays in some areas of the lagoon. Nevertheless, trajectories of recovery require a long time [41] and follow a pathway that is not linear and easily predictable [42,43,44].
A study carried out in [45] reported an improvement in the ecological status of the water column in the shallow coastal lagoons of South France since the first decade of the 21st century.
Mesotrophic status has different ecological and economic implications according to the trophic trajectories of water bodies over time. Mesotrophic status might be a natural, stable, healthy, and sustainable state of lagoon water bodies, in which a moderate natural level of nutrients supports a balanced ecosystem, high biodiversity, and associated ecosystem services of different typologies, such as fishing and extensive aquaculture. If there are clear signs of a worsening trend in certain parameters (e.g., an increase in water nutrients, changes in primary producers’ structure toward macroalgae and phytoplankton communities), a precautionary approach should be considered, and the WB should be followed over time. In this work, the shift observed from a mesotrophic to a non-eutrophic status can be, therefore, the result of a slow and non-linear restoration process that started over 20 years ago, and it seems to be particularly related to the improvement of macrophytes. The mean MaQI values in stations that changed their trophic status from mesotrophic to non-eutrophic in the period 2011–2022 increased from 0.28 (poor) to 0.63 (good). The improvement in MaQI values was associated with the increased presence of sensitive macroalgae and the colonization of aquatic angiosperms, also triggered in the northern lagoon by the implementation of ecological restoration projects [39]. In addition, some transplants carried out by fishermen between the salt marshes of the southern lagoon, as well as in some shallow areas of the central lagoon, have also contributed to boosting the spread of aquatic angiosperms and high-quality macroalgal species in the other two lagoon basins. This improvement was also favored by the reduction in nutrient concentrations and, above all, by a decrease in the Manila clam (Ruditapes philippinarum Adams & Reeve, 1850) harvesting effort [24,39]. In the choked areas where clam harvesting still remains active, this activity might contribute to maintaining the MaQI in poor–bad ecological status.
On the other hand, lagoons are particularly vulnerable and intrinsically at risk of eutrophication [1], also depending on annual climatic and hydrological conditions, which exhibit high interannual variability. For instance, MC II and MC III were rainier compared to other triennial cycles [46]. This could partially explain the observed fluctuations between meso- and eutrophic conditions throughout the four MCs in the inner stations, which are more sensitive to watershed inputs and more vulnerable to eutrophication. Indeed, these areas are characterized by low bathymetry and high water renewal times [47], making them more exposed to high nutrient concentrations and eutrophication phenomena. Additionally, the sediments of these areas can act as both a sink and a source of nutrients. This internal nutrient recycling dynamic could lead to periodic peaks in inorganic nitrogen and sustain high productivity and eutrophic conditions [48]. Furthermore, these areas are more susceptible to hydrological changes, such as variations in precipitation patterns and temperature. Under climate change, they may also be impacted by extreme rainfall events, drought–flood cycles, and water heating, resulting in localized massive nutrient events and an increase in eutrophication [49,50].
Due to these internal cycling processes, these sites could require a longer time to recover [41]. Here, the interannual variability of macroalgae coverage and DIN concentrations seems to be the major driver of TWQI fluctuations around the moderate/poor boundary and, consequently, between meso- and eutrophic TWEAM status.
The mesotrophic status, therefore, appears to be a short blanket, which is pulled from one side by natural recovery and restoration measures, which follow non-linear and delayed trajectories, and, from the other side, by the intrinsic vulnerability of lagoon environments to eutrophication, including the inertia to trophic status changes due to internal nutrient recycling and the interannual variability of hydrological and climatic conditions. Future monitoring cycles will confirm if non-eutrophic stations have achieved a stable condition and assess whether recovery processes are also ongoing in inner areas, where a longer time may be necessary. Alternatively, the findings may indicate if further ecological restoration measures are needed to achieve environmental objectives in these areas.
Future investigations may offer a deeper understanding of the hypothesis regarding potential mesotrophic status instability. In the future, the concurrent and overlapping effects of ongoing anthropogenic pressures, longstanding mitigation measures, ecological restoration interventions, and interannual and long-term hydrological variations attributed to climate change, could arise the instability of trophic status.

5. Conclusions

The TWEAM application to the Venice Lagoon as a case study provided an integrated analysis and resulted in being a simple and efficient tool for conducting comprehensive trophic status assessments. Indeed, individual metrics or parameters might provide only incomplete and occasionally contradictory signals, making assessments difficult to standardize. The integration of drivers, status, and impact indicators of eutrophication into a single assessment method, such as the TWEAM, enabled an objective and replicable evaluation across stations, water bodies, and monitoring cycles, ensuring the robust identification of ongoing temporal and spatial changes in the trophic status of a coastal lagoon.
The observed changes indicate a general improvement in trophic conditions over time, resulting from the shift of most mesotrophic stations toward non-eutrophic conditions and suggesting the instability of mesotrophic status in the Venice Lagoon. The trajectory of recovery showed a non-linear trend, especially in choked areas that presented inter-cycle fluctuation between eutrophic and mesotrophic conditions. This pattern was put in relation to different concurrent and sometimes conflicting factors, such as the implementation of restoration measures, the natural vulnerability of transitional environments to eutrophication, and the potential intrinsic instability of mesotrophic status.
Finally, in its application in the Venice lagoon as a case study, the TWEAM provided valuable information for water managers and environmental authorities to identify critical sites for, eventually, further investigations in specific target and implement restoration or mitigation measures, also considering the growing pressures that climate change can exert on transitional water ecosystems.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/environments11110251/s1, Table S1: TWQI data input and results; Table S2 TWEAM data input and results.

Author Contributions

Conceptualization, A.B., R.B.B. and E.P.; methodology, A.B., R.B.B., M.C., E.P. and A.S.; validation, V.B., A.B., R.B.B., F.C., M.N., E.P. and A.S.; formal analysis, V.B., A.B., F.C. and E.P.; data curation, V.B., A.B., F.C. and E.P., writing—original draft preparation, A.B. and E.P.; writing—review and editing, all authors; visualization, E.P.; project administration, R.B.B., F.C., M.N. and F.S.; funding acquisition, R.B.B. and F.S. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by ARPAV in the framework of the Mo.V.Eco V Project, funded by Veneto Region, according to WFD, under the contract between ISPRA and ARPAV of 10 November 2023.

Data Availability Statement

Data used in this study are included in the Supplementary materials and are available online in the open data Section of ARPAV’s website at https://www.arpa.veneto.it/dati-ambientali/open-data/idrosfera/acque-di-transizione/acque-di-transizione-laguna-di-venezia-monitoraggio-ecologico, accessed on 26 August 2024.

Conflicts of Interest

The authors declare no conflicts of interest.

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Environments 11 00251 g001
Figure 1. Map of the stations sampled in the Venice Lagoon during the period 2011–2022. Natural water bodies, according to WFD, are also indicated.
Figure 1. Map of the stations sampled in the Venice Lagoon during the period 2011–2022. Natural water bodies, according to WFD, are also indicated.
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Figure 2. Distribution (%) of the TWEAM trophic classes for each triennial monitoring cycle (MC). (A): data grouped per water body (WB); (B): data grouped per station (ST).
Figure 2. Distribution (%) of the TWEAM trophic classes for each triennial monitoring cycle (MC). (A): data grouped per water body (WB); (B): data grouped per station (ST).
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Figure 3. Eutrophic status assessment using the TWEAM in Venice Lagoon WBs (background color) and stations (dot color) during the first (A: 2011–2013) and last (B: 2020–2022) MC. Green = non-eutrophic; beige = mesotrophic; red = eutrophic.
Figure 3. Eutrophic status assessment using the TWEAM in Venice Lagoon WBs (background color) and stations (dot color) during the first (A: 2011–2013) and last (B: 2020–2022) MC. Green = non-eutrophic; beige = mesotrophic; red = eutrophic.
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Figure 4. Box plots of the scores of TWEAM metrics resulted at the 28 stations in the Venice Lagoon: (A) Dissolved Inorganic Nitrogen (DIN) (μM); (B) Orthophosphate (P-PO4) (μM); (C) MaQI index; (D) TWQI index. Data are grouped per monitoring cycle (MC). Dotted lines indicate the boundaries among ecological quality classes: H = high; G = good; M = moderate; P = poor; B = bad.
Figure 4. Box plots of the scores of TWEAM metrics resulted at the 28 stations in the Venice Lagoon: (A) Dissolved Inorganic Nitrogen (DIN) (μM); (B) Orthophosphate (P-PO4) (μM); (C) MaQI index; (D) TWQI index. Data are grouped per monitoring cycle (MC). Dotted lines indicate the boundaries among ecological quality classes: H = high; G = good; M = moderate; P = poor; B = bad.
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Figure 5. PCA biplot of the two main components for the whole dataset, including the TWEAM metrics as variables and TWEAM scores as supplementary quantitative variables. The data of the four cycles are grouped per TWEAM class. For each group, the centroids and the confidence ellipses (95% of samples) are shown.
Figure 5. PCA biplot of the two main components for the whole dataset, including the TWEAM metrics as variables and TWEAM scores as supplementary quantitative variables. The data of the four cycles are grouped per TWEAM class. For each group, the centroids and the confidence ellipses (95% of samples) are shown.
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Table 1. Trophic status assessment in the Venice Lagoon using the TWEAM at sampled stations over the four triennial MCs carried out in the period 2011–2022: (MC I = 2011–2013; MC II = 2014–2016; MC III = 2017–2019; MC IV = 2020–2022). Data are presented by water body (WB) and by sampled station (ST). N = non-eutrophic status (green background); M = mesotrophic status (beige background); E = eutrophic status (red background).
Table 1. Trophic status assessment in the Venice Lagoon using the TWEAM at sampled stations over the four triennial MCs carried out in the period 2011–2022: (MC I = 2011–2013; MC II = 2014–2016; MC III = 2017–2019; MC IV = 2020–2022). Data are presented by water body (WB) and by sampled station (ST). N = non-eutrophic status (green background); M = mesotrophic status (beige background); E = eutrophic status (red background).
Eutrophication Status
WBMC IMC IIMC IIIMC IVSTMCI MC IIMC IIIMC IV
ECNNNNEC_1NNNN
EC_2MNNN
EC_Ve_8NNNN
ENC1NNNNENC1_1NNNN
ENC1_2NNNN
ENC1_3MMNN
ENC1_4NNNN
ENC1_FINNNN
ENC1_VSNNNN
ENC2NNNNENC2_1NNNN
ENC2_VGMNNN
ENC3MNNNENC3_CHMNNN
ENC4NNNNENC4_1NMNM
ENC4_Ve_6NNNN
PC1MMNNPC1_1MMNN
PC1_1BMEMM
PC1_2MMNM
PC2MMMNPC2_1MMMN
PC2_16BMNNN
PC2_CCMMEN
PC3MMMMPC3_VDBMMMM
PC4EEEEPC4_10BEEEE
PNC1MEEMPNC1_1MEEE
PNC1_7BMEEM
PNC1_Ve-1EMEE
PNC2NMNNPNC2_1MEMM
PNC2_2MEEM
PNC2_SGNNNN
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MDPI and ACS Style

Ponis, E.; Cacciatore, F.; Bernarello, V.; Boscolo Brusà, R.; Novello, M.; Sfriso, A.; Strazzabosco, F.; Cornello, M.; Bonometto, A. Assessment of the Trophic Status and Trend Using the Transitional Water Eutrophication Assessment Method: A Case Study from Venice Lagoon. Environments 2024, 11, 251. https://doi.org/10.3390/environments11110251

AMA Style

Ponis E, Cacciatore F, Bernarello V, Boscolo Brusà R, Novello M, Sfriso A, Strazzabosco F, Cornello M, Bonometto A. Assessment of the Trophic Status and Trend Using the Transitional Water Eutrophication Assessment Method: A Case Study from Venice Lagoon. Environments. 2024; 11(11):251. https://doi.org/10.3390/environments11110251

Chicago/Turabian Style

Ponis, Emanuele, Federica Cacciatore, Valentina Bernarello, Rossella Boscolo Brusà, Marta Novello, Adriano Sfriso, Fabio Strazzabosco, Michele Cornello, and Andrea Bonometto. 2024. "Assessment of the Trophic Status and Trend Using the Transitional Water Eutrophication Assessment Method: A Case Study from Venice Lagoon" Environments 11, no. 11: 251. https://doi.org/10.3390/environments11110251

APA Style

Ponis, E., Cacciatore, F., Bernarello, V., Boscolo Brusà, R., Novello, M., Sfriso, A., Strazzabosco, F., Cornello, M., & Bonometto, A. (2024). Assessment of the Trophic Status and Trend Using the Transitional Water Eutrophication Assessment Method: A Case Study from Venice Lagoon. Environments, 11(11), 251. https://doi.org/10.3390/environments11110251

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