The STVI (Scuba Trail Vulnerability Index, Di Franco et al., 2009) is based on a census of vulnerable benthic species populations that can potentially be affected by the direct (mechanical) or indirect (sediment resuspension) impacts of diving activity on the coralligenous. The suggested protocol is easy to be applied, however its usefulness is limited to narrow scuba trails where divers are in close proximity to walls/ceiling/substrates (i.e., submerged caves, tunnels, arcs, or canyons) and the damage caused can be reliably attributed to divers.

The CAI (Coralligenous Assemblage Index, (Deter et al., 2012)) was designed considering three metrics (i.e., the percentage coverage of sludge, builder taxa and bryozoans) correlated with anthropogenic pressures affecting water quality. The ‘builders’ of the coralligenous framework considered include coralline algae, bryozoans, scleractinians, and the foraminifera Miniacina miniacea (Pallas, 1766). Other animal builders such as serpulids polychaetas or sponges (Ballesteros, 2006) are not considered. Metrics referring to gorgonian demography (colony height and necrosis) are discarded because injuries to these long-living organisms may be related to ancient stress, such as heat waves (Garrabou et al., 2022a), and not to more recent anthropogenic pressures. Other indexes (i.e., MAES, CBQI, 3D complexity, STAR, MACS, see ahead) addressed this issue by linking the level of epibiosis to the age of the impact.

Biocenosis of semi-dark caves (at least at the entrance) can overlap with those of the coralligenous (Bellan-Santini et al., 2015), therefore the CavEBQI (Cave Ecosystem-Based Quality Index, Rastorgueff et al., 2015) was considered in this review. The index aims to evaluate the ecological quality of marine submerged caves by adapting the approach used to gauge the ecological quality of Posidonia oceanica meadows (Personnic et al., 2014). The data collection combines photo sampling, underwater estimations (volume stratification) and visual census to evaluate the status of seven ecological cave components (see details in Table 1 ). However, there is inherent risk associated with applying these complex protocols in an entire (accessible) underwater cave. Moreover, occurrence, abundance, and spatial distribution of vagile components (for example, cave-dwelling mysids) inside a cave may vary in relation to season, abiotic factors and reproductive behavior (Ribes et al., 1996), leading to inaccuracies when applying the index. Passive filter feeders are considered as the most valuable target given their sensitivity to pressures, but this component includes taxa that differ greatly in morphology, tolerance to disturbance and lifespan (e.g., hydrozoans and gorgonians). In these dark habitats, the geological structure of the caves, their rock composition and the possible occurrence of freshwater springs or hydrothermal emissions can greatly affect the composition of the benthic assemblage, which influences the outcomes of the index and how they are interpreted.

The ESCA (Ecological Status of Coralligenous Assemblages, Cecchi et al., 2014) index considers deep macroalgae (ten taxa/morphological groups) and three metrics to evaluate coralligenous status. The index is expressed as Ecological Quality Ratio (EQR) i.e., the ratio between the measured value for each metric (or Ecology Quality Value, EQV) and its expected value in the absence of major human disturbance (Reference Condition (RC), Water Frame Directive (WFD), 2000/60/EC).

Sessile macroinvertebrates are considered along with seaweeds to compute the ESCA-TA (Piazzi et al., 2017a) and to evaluate the response to disturbance of the “Total Assemblage”. The application of this last index highlighted that macroalgae are more suitable to detect pressures such as, the increase in nutrients or water turbidity, while the macroinvertebrates are more sensitive to the effects of water warming or mechanical damage, as reported previously (see Coma et al., 2006; Cerrano and Bavestrello., 2009; de la Nuez-Hernández et al., 2014). In general, the methodology is simple to apply and easy to replicate. However, reference conditions are not available for all sites (Ponti et al., 2009; Piazzi et al., 2021a) and may be difficult to define (Bouleau and Pont, 2015), especially if there is scarce knowledge of the possible exploitation of the study area.

The COARSE (COralligenous Assessment by ReefScape Estimate) index, (Gatti et al., 2015) evaluates the coralligenous integrity as a descriptor of the marine environmental status (as required by the MSFD) rather than water quality (as per WFD). Here, the vulnerability towards physical stress and mechanical damage of the multi-layer architecture of this habitat is considered. The COARSE index is based in part on a Rapid Visual Assessment (RVA), providing a time and cost-effective methodology, which allows for the direct collection of a sufficient amount of data with a congruent diving effort (Gatti et al., 2012). However, visual estimations of percentage cover (Meese and Tomich, 1992) and species identification (Thompson and Mapstone, 1997) may be inaccurate at 30 m or deeper, given the limited dive time and need to collect other underwater measurements.

The combination of two indexes (COARSE and ESCA) was tested in the same area obtaining different but complementary information (Piazzi et al., 2017b) given the different objectives of the two indexes. However, the implementation of two or more underwater protocols is more demanding in terms of time and cost.

The INDEX-COR (Sartoretto et al., 2017) is based on in situ observation/estimations, combined with photographic sampling. The metrics Ratio between Sensitive and Tolerant Species (RSTS), Observable Taxonomic Richness (OTR), and Structural Complexity (SC) seems to be related to human pressures defined by expert judgment; however, the authors themselves stated that a more objective impact index is needed to correlate the structural complexity with anthropogenic pressures at a lower scale.

The Index of 3D - Structural Complexity (Valisano et al., 2019) aims to assess the status of coralligenous assemblages by aggregating taxa according to their morpho-functional role in the multi-layer structure of the habitat. A different weight is assigned to each cluster reflecting its relevance in the bioconstruction/bioerosion equilibrium and as ecosystem engineers building animal forests (Cerrano et al., 2019). The index assesses the 3D architectural complexity of coralligenous assemblages.

The STAR (STAndaRdized coralligenous evaluation procedure, Piazzi et al., 2019a) is the first attempt to standardize metrics and protocols to collect and to interpret data on the status of the coralligenous. Findings of a literature review revealed April-June to be the best period to carry out sampling activities according to seasonal dynamics of native and invasive macroalgae; while 35 m and 85–90 m were considered as optimal depth and slope, respectively to carry out photo-surveys. The authors also suggested carrying out sampling with high replication at small scales (i.e., tens of meters) and less replicates at intermediate or large scales (i.e., hundreds of meters to kilometers). The ideal sampling design should consider three areas of 4 m², tens of meters apart, with at least 10 replicates of 0.2 m² at each area, for a total sampling surface of 6 m².

The ISLA Index (Integrated Sensitivity Level of coralligenous Assemblages, Montefalcone et al., 2017), allows for the change experienced by the coralligenous assemblages to be estimated in both space and time by multiplying abundance (i.e., percentage cover) of several target taxa/morphological groups per an integrated index that considers both sensitivity to disturbance and sensitivity to stress. Disturbance causing mortality or physical damage (subtraction of biomass) is evaluated considering the biological traits of the target taxa. Stress causing physiological alteration (reduction in productivity) and sensitivity to stress is estimated based on expert judgment.

The MedSens sensitivity index (Turicchia et al., 2021a) is a biotic index developed to provide information on the environmental status of subtidal rocky coastal habitats, and above all, coralligenous reefs. It uses data collected by trained volunteers (scuba divers, free divers, snorkelers) which record the abundance and depth ranges of the searched taxa through a protocol of simple application (The Reef Check Med Underwater Coastal Environment Monitoring (RCMed U-CEM) Protocol, Turicchia et al., 2021b). Despite the need for rigorous participant training (subject to learning tests) and steps to assure data quality, the protocol is easy to learn and provides a large amount of timely, up to date geo referenced data (Turicchia et al., 2021b, c) which is the greatest benefit of this approach. The sensitivity level to physical, chemical, and biological pressures is attributed to selected taxa according to the Marine Evidence-based Sensitivity Assessment (MarESA, Tyler-Walters et al., 2018). The index calculates the mean sensitivity of the various taxa considered weighted for the abundance class of the taxa.

Three indexes were based on photography and video footage collected by Remotely Operated Vehicle (ROV): the CBQI (Coralligenous Bioconstructions Quality Index, Ferrigno et al., 2017) focused on fishing pressure, the MAES (Mesophotic Assemblages Ecological Status, Cánovas-Molina et al., 2016), and the MACS (Mesophotic Assemblages Conservation Status, Enrichetti et al., 2019) to monitor the environmental status of mesophotic temperate reefs. ROVs allow exploration of deep reefs (Jones et al., 2007; Enrichetti et al., 2019) providing sufficient levels of detail and a large amount of recorded information (Smith and Rumohr, 2005).

The NAMBER Index (North Adriatic Mesophotic BiogEnic Reefs, Piazzi et al., 2023), draws inspiration from the STAR and ESCA-TA indices, by selecting the metrics and adapting the interpretation scales to the ecological and operational conditions encountered when investigating the mesophotic coralligenous banks in the northern Adriatic Sea. Starting with a close-up photographic sampling strategy, the degree of bioconstruction (expressed as percentage cover of crustose coralline algae), α diversity (expressed as the mean number of taxa), and the degree of sensitivity to human disturbances and climate changes (based on literature data and expert judgement) of the benthic assemblages are combined in the index, in terms of ecological quality ratios (sensu WFD) using as a reference the best values that the three metrics can currently achieve in the studied region.

Lastly, the OCI (Overall Complexity Index, Paoli et al., 2016) aims to measure habitat structural and functional complexity through a thermodynamic analysis, based on exergy and specific exergy, and a network analysis. The index was tested in an MPA where the most complex habitats were found to be the seagrass meadows and the coralligenous reefs. The information about environmental quality and natural capital was already available for the study area, but a larger scale application of this index would require considerable data collection and a sound baseline.

Table 2 summarizes and compares the underwater scientific methodologies applied in the studies considered to collect data and the components (i.e., metrics and parameters useful to obtain metrics, such as abundance) to calculate the indexes. All the proposed approaches ( Tables 1 , 2 ) are based on non-destructive methods but, when considered, the thickness of the calcareous layer is measured in a destructive way (insertion of a tool marked with a millimetric scale in the biogenic concretion, Piazzi et al., 2019a). However, the damage caused is limited.

Three indexes (CBQI, MAES, MACS), use ROV exploration, one (CAI) uses CCUBA (Closed Circuit Underwater Breathing Apparatus) to sample down to 84 m, while the others use SCUBA diving. According to Gennaro et al. (2020), sampling within a depth of 40 m should be carried out via SCUBA divers while, for safety reasons, below this depth the coralligenous should be explored using ROVs. However, trimix diving (either open or closed breathing circuits) by well-trained operators could be useful to conduct the surveys with high levels of safety down to 90-100 m depth.

Higher performing ROV systems, intended for > 80 m depth, are more expensive, and often require specialized operators to be maneuvered and large boats to be transported.

Photo surveys are the preferred method for underwater data collection (10 indexes), followed by visual census (6) and video surveys (5). Percent cover estimates from photo samples is the most applied procedure to estimate benthic species’ abundance.

The same index could be calculated using more than one underwater sampling method, for example photo/video surveys could be carried out via SCUBA diving or an ROV.

Video-surveys and photo quadrats appear to be the best methods to collect data on the coralligenous. Video transects randomly conducted in georeferenced repeatable stations are the most efficient, fastest, and simplest method to detect general changes in the habitat architecture. Besides supplying permanent records about density and size of habitat-formers (i.e., gorgonians, Savalia savaglia (Bertoloni, 1819), erect sponges…), the videos contain information about the geomorphological features of the site, occurrence of macro-invasive species and lost fishing gears. Photo-surveys provide a better estimate of the percentage coverage of organisms with a low elevation from the substrate (e.g., encrusting, massive or little branched phyto/zoobenthos).

Despite their accuracy, the complexity of some approaches renders them unsuitable for the citizen science context (a helpful strategy fostering the continuous monitoring of the effects of thermal stress and anthropic pressures on a larger spatial and temporal scale (Krželj et al., 2020)).

Even if citizen science cannot override professional monitoring activities, with the number of target species often being lower than the taxa considered by scientists, an easy-to-apply citizen science-based index for the Mediterranean Sea, providing a community-based monitoring strategy, would be a valuable tool to gather a constant flux of data on benthic communities (Kelly et al., 2020). Examples of citizen science projects engaging divers in the study and monitoring of Mediterranean coralligenous assemblages are the CIGESMED SeasEra (ERAnet) (Gerovasileiou et al., 2016), the Reef Check Mediterranean Underwater Coastal Environment Monitoring Protocol (Ponti et al., 2021; Turicchia et al., 2021b; Turicchia et al., 2021c), and the derived MedSens index.

Establishing an unambiguous list of anthropic pressure and environmental stressors on the coralligenous habitat is fundamental to assess its environmental and ecological quality. Given that different descriptions of pressures were used in the reviewed papers, here, a standardized nomenclature for 15 forms of pressure/stressors on the coralligenous has been devised ( Table 3 ). Attempts were made to align the pressures with those defined by EU regulations (the Habitat Directive (Council Directive 92/43/EEC), the MSFD, and the EU Water Frame Directive (WFD, Directive 2000/60/EC), according to Article 17 report formats of the Habitats Directive (https://cdr.eionet.europa.eu/last updated: 24/01/2023)).

Pollution is the most considered pressure in the indexes (47%) reviewed, followed by abandoned, lost or discarded fishing gear (40%, ALDFG, Macfadyen et al., 2009).

Some pressures/stressors on coralligenous habitat are easy to detect and quantify due to the presence of long-lasting macroscopic signs (such as presence of marine litter, lost fishing gear, benthic mucilage, invasive and non-indigenous macrozoo- and phytobenthos, high sedimentation, collection of date mussels). On the contrary, it could be tough to attribute signs of damage (breakages, necrosis/epibiosis) to intangible and temporary pressures/stressors (liquid waste, contacts of divers, heatwaves, storms), above all in case of cumulative impacts. In the next paragraph we better analysed these issues and explored some solutions.

The indexes can produce inaccurate assessments of the environmental status where the low diversity is related to intrinsic traits of the site (water movements, light, geomorphology, food availability) rather than human disturbance (Enrichetti et al., 2019; Valisano et al., 2019; Pierdomenico et al., 2021), such as the assemblage of the coralligenous developed on granitic substrates (Canessa et al., 2020). Another issue detected in this review is how to define intermediate environmental status classes (i.e., good, moderate, poor) if historical data about biodiversity and pressures are unavailable and the pristine conditions are unknown (Ponti et al., 2009 and references therein). However, these obstacles will be overcome once periodic and continuous monitoring campaigns are established to detect the evolution of benthic communities and to differentiate among fluctuations, disease events and human pressure (Franz et al., 2019). As for other monitoring programs of the MSFD, the establishment of fixed stations (García-Gómez et al., 2020) will be indispensable for observing the dynamics of benthic communities and to assess their environmental status. These could be in known coralligenous hotspots (Martin et al., 2014; Di Camillo et al., 2018a), independent of their level of protection, within which random sampling could be conducted.

To establish the causes of biodiversity loss that are unrelated to mechanical damage, trends in physical and chemical parameters should be considered. Funding should be provided to increase the analysis of water/biota and to provide the fixed stations with benthic temperature loggers placed at different depths and multisensory buoys transmitting real-time data to a monitoring network. The analysis of the collected data would be valuable in helping link the transformation occurring in the coralligenous to atmospheric, oceanographic, and biogeochemical conditions (Bahamon et al., 2020; Garrabou et al., 2022b).

One of the major issues in designing an index to define the ecological status of a habitat is the attribution of a sensitivity level to taxa/morphological groups. The sensitivity level may be available in the literature, or expert judgement may be used (Piazzi et al., 2017a and references therein). However, sometimes it is unclear why some taxa are more sensitive than others; for example, Eunicella cavolini and Cystoseira spp. are considered more sensitive than Paramuricea clavata by the ESCA, while P. clavata was the most sensitive taxon for the MedSens index (Turicchia et al., 2021a) because of its sensitivity to physical, chemical, and biological pressures. According to Turicchia et al. (2021a), most sensitive taxa are long-living cnidarians. Since these species reflects the highest complexity level of the coralligenous, it would be crucial to assign one of the largest weights in the design of a new index.

To evaluate the status of coralligenous health, it is crucial to know its successional stages. The accretion rate of the coralligenous is very low (0.006–0.83 mm yr^–1) and variable depending on depth and period (Sartoretto, 1994; Turicchia et al., 2022), suggesting that dynamics of this environment are difficult to study on a short-term timescale (Garrabou and Harmelin, 2002). Mortality events drive a shift from ecosystem engineering (e.g., Paramuricea clavata, Corallium rubrum) to fast-growing and photophilous species (among which are encrusting organisms, serpulids, hydrozoans, turf-forming algae (Ponti et al., 2014; Cerrano et al., 2019; Gómez-Gras et al., 2021)). In some cases, bryozoans recolonize bare coralligenous after a severe impact in a few years (Cocito and Sgorbini, 2014; Casoli et al., 2020, and personal observations), but also other patterns are documented (Piazzi et al., 2021b). On the contrary, re-settlement and growth of gorgonians or red coral may be very slow (Garrabou and Harmelin, 2002; Cerrano et al., 2005; Cupido et al., 2009; Huete-Stauffer et al., 2013); in some cases, no signs of recovery have been registered even after a ten-year period (Ruffaldi Santori et al., 2021). Information about recovery of habitat-formers after mortality is scant and highlights a knowledge gap that needs to be filled urgently.

Heatwaves, changes in thermohaline circulation, and mucilage events are rapidly re-shaping bioconstructions in the Mediterranean basin (Cramer et al., 2018; Bevilacqua et al., 2021; Garrabou et al., 2022a); therefore, in these unprecedent critical conditions, the index design should focus first on the response of the coralligenous to these stressors.

Considering that heatwaves and mucilage events occur from late spring to late autumn (Garrabou et al., 2009), data collection should be carried out in early spring (April or May) and autumn (October) to have a better understanding of the effects of these pressures and the resistance and resilience of coralligenous bioconstructions (Ponti et al., 2014).

Based on these reflections, a list of priority anthropic pressures and environmental stressors and relative indicators are suggested below ( Table 4 ).