Operational ecological indicators are generally used for summarizing the status of marine communities and ecosystems in a comprehensive and accessible way (Cury and Christensen 2005, Shin and Shannon 2010). Indicators of anthropogenic pressure are useful for monitoring the impact of fishing on target species, communities (Greenstreet et al. 2012b) and ecosystems (e.g. Shin and Shannon 2010), thus helping to assess the effectiveness of management measures (e.g. Fulton et al. 2005, Houle et al. 2012). Ecological and impact indicators are crucial in the design of multiannual management plans, which, according to the Common Fishery Policy (EU Reg. 1380/2013), should consider ecosystem descriptors in addition to fishing mortality targets at stock level.

Indicators of fish community size structure can reveal the fishing effects caused by removing certain sizes and altering the abundance of different-sized species. Given their ability to summarize such complex dynamics, indicators of fish community size structure are increasingly used by national and transnational legislation, such as the European Marine Strategy Framework Directive (MSFD), which seeks to achieve Good Environmental Status (GES) by 2020 for all European seas (European Commission 2010).

Because no single indicator can capture the diversity of dynamics and processes within a system, suites of indicators are indeed required (Greenstreet et al. 2012a), though the selection of indicators to retain should be carefully considered: indicators included should be sensitive to specific impacts (Houle et al. 2012) or be unambiguous to monitor single species, communities or ecosystems (Rochet and Trenkel 2003, Shin and Shannon 2010). The suite of indicators should be based on criteria such as availability and accessibility of data, conceptual basis, ability to track different dynamics and processes, responsiveness, communicability and relevance to management (Rochet et al. 2010, Shin and Shannon 2010). The selected suite should also avoid redundancy (Methratta and Link 2006, Greenstreet et al. 2012a) and ensure applicability across different geographical areas (Shin et al. 2018).

Several studies have assessed existing indicators to identify suites that best capture the diversity of impacts and dynamics for fish communities or for whole ecosystems (Shin et al. 2018). Most studies have focused on North Atlantic fisheries (Methratta and Link 2006, Greenstreet et al. 2012a) or compared multiple systems (e.g. Shin and Shannon 2010), while only a few have assessed the situation for the Mediterranean fish communities (Rochet et al. 2010, Brind’Amour et al. 2016).

Within the MSFD, suites of indicators of GES are outlined for commercial fish (Descriptor 3) and food webs (Descriptor 4) (European Commission 2010). The suite provided by the MSFD is considered a guideline that Member States must integrate with indicators relevant at regional and national level. Previous studies highlighted issues with one MSFD indicator, the large fish indicator (LFI; Shephard et al. 2011, ICES 2014), in particular due to the required assumption about threshold level, which is area-specific. In the Mediterranean Sea, for example, Spedicato et al. (2014) found that the LFI is sensitive to the choice of species inclusion and to the threshold level. Recent research identified typical length (TyL), an indicator of the size structure of fish community, as a potential alternative which might provide similar results and avoid problematic assumptions (ICES 2014, Lynam and Rossberg 2017, ICES 2018).

This paper aims to explore six indicators representing the size structure of the fish community: TyL, mean maximum length (MML), the LFI, the large species indicator (LSI), mean weight and evenness. This set includes the size structure indicators currently recommended by the MSFD (LFI and MML) and a selection of potential alternative or complementary length-based indicators for monitoring GES at national, regional or European level (ICES 2014, Lynam and Rossberg 2017, ICES 2018). In this paper we estimated these six indicators for 17 geographical sub-areas (GSAs) in the northern Mediterranean Sea, using data of length-frequency distributions obtained from the MEDITS experimental trawl survey.

Given the emerging role of length-based indicators and their demand for complementing the MSFD at regional level, this study sets three goals. First, to evaluate which length-based indicators are essential and sufficient to explain the status and impacts of the Mediterranean Sea demersal fish community; second, to determine whether hidden common trends detected through dynamic factor analysis (DFA) across Mediterranean GSAs can be explained by basin-scale pressure indicators; and third, to determine whether TyL, proposed by ICES as an alternative to LFI, could be useful in the Mediterranean to complement or replace existing MSFD indicators.

We estimated a set of six size structure indicators of the fish community which are considered useful to detect changes at population and community level and are among those assessed by OSPAR (2017) and by the ICES Working Group on Ecosystem Effects of Fishing Activities (WGECO) (ICES 2014, 2018).

The first goal of this study was to address the redundancy within this set of proposed indicators in order to select those that effectively summarize the fish community dynamics over time. Previous studies used factor (Greenstreet et al. 2012b) and ordination techniques such as non-metric multidimensional scaling (Blanchard et al. 2010) to address indicator redundancy and compare the community size structure of different ecosystems. We, instead, combined different statistical techniques. Firstly, we used a factor technique (PCA) to select a non-redundant subset of two size-structure indicators of fish community. TyL and MML were found to be the indicators most linked to the principal components. Secondly, we explored the occurrence of common trends among the GSAs through DFA on the two selected indicators, following Zuur et al. (2003). The selected models were characterized by only one common trend, while Zuur et al. (2003) found three common trends in their analysis. The capability of DFA to identify more common trends in our case might be limited by the spatial and temporal scale of the analysis: the fine-scale geographical patterns shown by PCA are not captured by DFA. Moreover, the relatively short time series lacking contrasted patterns and the fact that the indicators smooth over the trends of individuals species might limit the capability of capturing potential additional trends that may be masked by the main common trend. While the two selected indicators are expected to show community-wide improvement upon reduction of fishing pressure, here we found asynchronous and contrasting patterns. This result could be explained by the second goal of our study: to explore through DFA the relationships between the common trends detected among the GSAs for the two selected indicators and the times series of environmental and anthropogenic drivers at basin scale. While DFA showed no significant link between the indicators and the covariates, correlation analysis revealed significant relationships. As observed by Zuur et al. (2003), the fact that the tested models incorporating covariates were not selected as the best models does not necessarily mean that these covariates had no influence on the time series. The higher AICc for the models including covariates could indicate that the explanatory variables did not produce an overall improvement in the model, the covariates being related to only some of the time series. Indeed, for both selected indicators, the inclusion of each covariate implies the estimation of 17 extra parameters (one for each GSA), which could make the model worse for covariates not linked to all the time series. This implies that the relationship between trends and covariates is area-specific, as also confirmed by the fact that the factor loadings seem to show geographical patterns: TyL is related to the common trend positively in most western Mediterranean GSAs and negatively in the eastern Mediterranean ones (Fig. 3). Different patterns between the eastern-central Mediterranean and the western Mediterranean also emerged from the PCA (Fig. 1B). Similarly, sub-regional patterns were observed in the North Sea, where OSPAR (2017) highlighted that the increasing TyL trend observed in northern areas was not observed in southern areas.

The fleet capacity showed a strong negative correlation with the trend detected for TyL. This result indicates that the increase in TyL (Fig. S2) observed in 10 out of 17 GSAs (mostly in the western Mediterranean) could be associated with a decrease in fleet capacity. This effect could be confounded with that determined by the increasing SST: TyL is indeed linked to the biomass of the fish community and thus strongly influenced by the species with higher biomass, which in the western Mediterranean include thermophile species such as P. erythrinus and M. barbatus (Fig. S4; Cheung et al. 2013). Notably, in the last few decades, landings of thermophile species in the Mediterranean have increased, contrasting with a general decrease in landings and a widely reported impact of increasing temperature on species and ecosystems (e.g. Vasilakopoulos et al. 2017). However, the increasing trend of biomass in our case is observed also for non-thermophile species such as G. melastomus, S. smaris and, to a smaller extent, L. piscatorius and L. budegassa. Therefore, the increasing common trend detected in TyL is most likely due to a decrease in fishing pressure, although a synergic effect with SST cannot be excluded for some species.

Conversely, MML showed a positive correlation with fleet capacity. Based on its definition, MML is expected to decline with an increase in fishing pressure, so the reduction in fishing effort observed in all GSAs is expected to result in an increase in MML. Instead, a decrease was observed for the general trend (Fig. 3) and for the majority of sub-areas (GSA 5, 6, 7, 9, 10, 17, 18, 19, 20; Fig. S7), indicating an asymmetric response of MML to increasing and decreasing pressures. MML is related to the abundance of species characterized by large maximum size (L_max), which generally also show slow growth and late maturation (Winemiller and Rose 1992). We can therefore expect a lag between a decrease in fishing pressure and an increase in MML. The decrease in the observed correlation with a time lag of 5 and 10 years (Table 3) is consistent with our hypothesis. The observed pattern could also indicate an increase in the abundance of species characterized by small L_max. These generally show a faster positive response to reduction in fishing pressure than species with large L_max, and thus an increase in abundance of the former leads in the short term to a decrease in MML. This pattern, known for other areas (OSPAR 2017), emerges in individual examination of GSAs (Table S5 and S6), where the dynamics of the most abundant species, such as M. barbatus and S. smaris, explain indicator patterns. The trend of MML therefore seems to be driven by these two contrasting factors, which act synergistically to produce the observed asymmetric response to decreasing pressure. Contrary to the expectation, a reduction in fishing pressure leads to an initial decline of MML driven by an increase in small, short-living species caused by release of fishing pressure. Not before several years, an increase in MML can be expected as the large fish species recover. In our case, with a lag of 10 years, the trend shows signs of inversion, with loss of the positive correlation between decreased fishing pressure and decreased MML. While this pattern might be driven by an increase in small species with preference for high SST, in our case the small species that showed an increase in abundance include both thermophile species (e.g. M. barbatus) and non-thermophile species (e.g. S. smaris; Table S3), indicating that SST does not explain the increasing patterns for all the small species.

The declining pattern in MML observed in GSA 6 and attributed to the faster decline in abundance than in biomass of M. merluccius could be indicative of fishing pressure targeting smaller individuals (for example, if larger individuals are distributed in areas not reached by trawlers), but could also be driven by a succession of poor recruitments (Lynam and Rossberg 2017).

The two indicators selected by our analysis correspond to those currently proposed by OSPAR and ICES WGECO. MML, in particular, is recommended by the MSFD to assess objective 3.3, "population age and size distribution", to account for the relative abundance of old, large fish in the community. Maximum length is considered a proxy for species vulnerability, as species with larger maximum length given their life history traits tend to be more vulnerable to fishing. These species are also expected to be the first to decline under high fishing pressure, with a decline in MML implying a decrease in abundance of the most vulnerable fish species (OSPAR 2017).

A complementary indicator that can account for changes in size structure has traditionally been identified in the LFI (European Commission 2010, OSPAR 2017), currently included for MSFD Descriptor 4 (namely, 4.2.1). Recent research has however identified some difficulties related to the implementation of the LFI for the MSFD. Critically, the determination of the threshold for what constitutes a "large fish" is prone to arbitrary choices. Furthermore, methods developed for estimation of this parameter have revealed sensitivity to the fish communities studied, to the species included and to the length of the time series (Shephard et al. 2011, Spedicato et al. 2014), rendering a standardized definition between areas problematic. Despite the fact that we calculated LFI by applying a 6^th degree polynomial for optimal threshold determination, as suggested by Shephard et al. (2011), the LFI was not selected in our analysis. TyL has been suggested to replace or complement the LFI. While possessing similar statistical properties to the LFI, TyL is considered more robust to the LFI’s limitations (ICES 2014, Lynam and Rossberg 2017, ICES 2018).

Our analysis improves present comprehension about the performance of TyL and LFI for Mediterranean demersal fish community, showing that the TyL has lower overlap with other indicators, emerging as a potential alternative. Additionally, our study confirms the complementarity of TyL to MML, already highlighted by Lynam and Rossberg (2017), because the joint application of both indicators can help disentangle changes in community composition from changes in size structure.

Finally, we highlight three general aspects pertaining to the indicators’ capability to track the responses of the system to different exogenous and endogenous drivers. First, indicators are generally developed and defined to track community response to increasing pressure, whereas the effect of pressure release is rarely assessed and generally assumed to be inverse to pressure increase. We propose that indicators can behave asymmetrically to increasing and decreasing pressures: while most indicators can generally track a decline in community status due to increasing pressure, they might differ in their capability to capture community response to pressure release. In our study, for example, MML patterns might be indicative of a time-lagged response to decreasing pressure. There is limited understanding of indicators’ responsiveness to decreasing pressures (Lynam and Rossberg 2017, OSPAR 2017), and the choice of indicators rarely takes this characteristic explicitly into account, as shown by their definitions (Table 1). Our study suggests that MML might perform worse (i.e. slower) than TyL in capturing a community’s recovery after fishing pressure reduction. Nominal effort reduction is assumed to correspond to a reduction in fishing pressure in our study. Effort and fishing mortality, however, cannot be linearly related and the observed delay might be due to reduction in fishing mortality declining less rapidly than decline in effort. Nevertheless, our metric of fleet capacity emphasizes the capacity of larger, more powerful boats, which exert the bulk of the pressure on the stocks. Combined metrics of fleet capacity is thus a better proxy of fishing impact than other metrics of fishing effort.

Second, the complementarity between indicators in responsiveness should be accounted for. We show that the indicators’ complementarity should extend to the capability to account for impacts across different time lags: MML shows a likely time-lagged response to pressure reduction, while the trend of TyL is associated with fast response of large-sized species to changes in fishing pressure and/or environmental conditions. This aspect is critical, as the responsiveness of indicators is therefore vulnerable to the length of time series, masking relationships or leading to spurious relationships and potentially confounding the interpretation of indicators (see for example the positive correlation between MML and fleet capacity).

Third, we highlight how definitions do not consider multiple stressors, so combinations of SST and effort can have antagonistic/synergistic effects, leading to an unclear interpretation of the indicators’ trends. OSPAR (2017) noted that the influence of SST and fishing on TyL can be hard to disentangle. In our study, we were able to tell the two drivers apart by taking into account the thermal preference of increasing species. We noted that the increase in TyL could mainly be attributed to decline in fishing pressure rather than increase in SST or, at best, to synergistic effects for a few species. Similarly, also for MML we determined that the observed changes could not be univocally driven by increase in SST: in fact, the increase in abundance potentially driving the MML pattern was observed in small-sized thermophile and non-thermophile species alike. This would reinforce the hypothesis of the increase in small species following fishing pressure release. Only through knowledge of the underlying biology of the species can we disentangle drivers’ effects on species patterns.

Overall, these considerations reinforce the importance of assessing the indicators’ capability to capture trends across diverse ranges of time lags and to interpret their patterns according to multiple drivers, especially in light of changing communities driven by climatic change.

Our results strongly support the inclusion of TyL as one of the regional MSFD indicators for detecting changes in the demersal fish community throughout the Mediterranean Sea. The results of this study will therefore be of support to regional application of MSFD targets by reinforcing scientific knowledge of length-based indicators in Mediterranean Sea. Additionally, these results can be applied in the context of multiannual management plans, allowing community and ecosystem dynamics to be considered, as required by the Common Fishery Policy (EU Reg. 1380/2014). The identification of reference levels for these indicators remains a critical point to be addressed. For North Atlantic areas, reference levels for TyL, MML and the LFI have been identified (ICES 2018). In the Mediterranean, these values do not yet seem to have been determined (Dupont et al. 2018), and future studies should therefore focus on this issue at different spatial scales.