The state of marine systems subject to natural or anthropogenic impacts can be generally summarized by suites of ecological indicators carefully selected to avoid redundancy. Length-based indicators capture the status of fish community structure, fulfilling the Marine Strategy Framework Directive (MSFD) requirement for Descriptor 3 (status of commercial fish species). Although the MSFD recommends the development of regional indicators, a comparison among alternative length-based indicators is so far missing for the Mediterranean Sea. Using principal component analysis and dynamic factor analysis, we identified the most effective subset of length-based indicators, whether or not based on maximum length. Indicator trends and time series of fishing effort and environmental variables are also compared in order to highlight the individual and combined capability of indicators to track system changes across geographical sub-areas. Two indicators, typical length and mean maximum length, constitute the smallest set of non-redundant indicators, capturing together 87.45% of variability. Only in combination can these indicators disentangle changes in the fish community composition from modifications of size structure. Our study supports the inclusion of typical length among the regional MSFD Descriptor 3 indicators for the Mediterranean Sea. Finally, we show dissimilarity between the western and eastern-central Mediterranean, suggesting that there are sub-regional differences in stressors and community responses.
Generalmente, el estado de los sistemas marinos sujetos a impactos naturales o antropogénicos puede ser resumido mediante un conjunto de indicadores ecológicos, cuidadosamente seleccionados para evitar la redundancia. Los indicadores basados en la talla reflejan el estado de la estructura de la comunidad de peces, cumpliendo el requisito de la Directiva Marco de la Estrategia Marina (MSFD) para el Descriptor 3 (estado de las especies de peces comerciales). Si bien MSFD recomienda el desarrollo de indicadores regionales, en el Mar Mediterráneo no se ha hecho hasta ahora una comparación entre los distintos indicadores disponibles basados en la talla. Mediante el análisis de componentes principales y el análisis de factores dinámicos, identificamos el subconjunto más eficaz de indicadores basados en la talla, estén o no basados en la talla máxima. Las tendencias de los indicadores y las series temporales del esfuerzo de pesca y las variables ambientales también son comparadas para resaltar la capacidad individual y combinada de los indicadores para detectar los cambios del sistema a través de las subáreas geográficas. Dos indicadores, Longitud Típica (TyL) y Longitud Máxima Media (MML), constituyen el conjunto más pequeño de indicadores no redundantes, captando juntos el 87.45% de variabilidad. Solo si se combinan, estos indicadores pueden discernir entre los cambios en la composición de la comunidad de peces y las modificaciones de la estructura de tallas. Nuestro estudio respalda la inclusión de TyL entre los indicadores regionales del descriptor 3 de MSFD para el mar Mediterráneo. Finalmente, mostramos diferencias entre el Mediterráneo occidental y el Mediterráneo central-oriental que sugieren diferencias subregionales en cuanto a factores impactantes y las respuestas de la comunidad.
Operational ecological indicators are generally used for summarizing the status of marine communities and ecosystems in a comprehensive and accessible way (
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 (
Because no single indicator can capture the diversity of dynamics and processes within a system, suites of indicators are indeed required (
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 (
Within the MSFD, suites of indicators of GES are outlined for commercial fish (Descriptor 3) and food webs (Descriptor 4) (
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 (
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.
The MEDITS bottom trawl survey data used in this paper were collected in 17 GSAs (according to the GFCM classification, GSAs 1, 2, 5, 6, 7, 8, 9, 10, 11, 15, 16, 17, 18, 19, 20, 22-23 and 25) following a random depth-stratified sampling and using a gear with a common design (
The pressure indicators explored to explain common trends were environmental and exploitation proxies. In particular, we used the North Atlantic Oscillation (NAO) index, sea surface temperature (SST), the annual average SST anomaly of the Mediterranean Sea (Med anomaly), and as a proxy for fishing intensity, the fleet capacity. The NAO index was obtained through the Climatic Research Unit NAO website (
Fish community indicators based on size structure
The analysis included data on bony and cartilaginous fish species, mostly but not limited to the commercially important ones, which have been MEDITS target species since 1999 (Supplementary material Table S1). The same species were used throughout the survey time series to avoid potential bias due to changes of target species in the MEDITS reference list over time.
The indicators were calculated from the length-frequency distributions (N km–2) according to
Indicator | Semantic definition | Equation | Reference | Interpretation |
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Large fish indicator | Proportion of fish biomass larger than a set threshold. |
lbig threshold 1; |
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A decrease in the LFI could be due to increasing exploitation. Exploitation reduces the biomass contribution to the community of the larger individuals/species ( |
Typical length | Geometric mean length of fish community, weighted by body mass. |
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TyL measures the size structure of fish and elasmobranch communities and decreases under high fishing pressure ( |
Evenness | Measure of the equitability in relative abundance among the length classes. |
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Reduction in evenness should reflect increasing dominance of the community by small-bodied, fast-growing, highly productive species caused by increased fishing mortality ( |
Mean maximum length | Mean maximum length in the community. |
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A decline in the MML indicates that the abundance of the most vulnerable fish and elasmobranch species is decreasing, leading to a change in the species composition ( |
Large species indicator | Biomass proportion of large species in a community. |
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A decline in LSI should indicate a decrease in the biomass of the predator species in the fish community ( |
Mean weight | Mean weight in the community. |
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A decreasing trend could be a signal of removal of larger individuals ( |
PCA was applied to select the minimum number of indicators to detect common trends among the GSAs and to reduce any redundancy in the six metrics considered. Redundancy may occur because several indicators are related to the relative abundance of large species. Data were first explored to check that the assumptions required to apply factor analysis were satisfied. The correlations among the six indicators for each GSA were tested using the Pearson coefficient. Next, data adequacy for the analysis was tested by the Kaiser-Meyer-Olkin (KMO) test (
The assessment of redundancy was performed through the Bartlett test, which compares the observed correlation matrix with the identity matrix. If the variables are perfectly correlated, only one factor is sufficient. If all the variables are orthogonal, we need as many factors as variables. In order to select the number of factors for the PCA, the Kaiser criterion (
DFA is a multivariate time-series technique used to detect
where
Four different hypotheses on the covariance matrix of the observation error were tested:
– same variance and no covariance (diagonal-equal);
– different variances and no covariance (diagonal-unequal);
– same variance and covariance (equalvarcov); and
– different variances and covariance (unconstrained).
All combinations of covariates (included at their original scale) were considered for a total of 12 combinations (with 0, 1, 2 or 3 covariates). A total of 12×4 (covariance models) ×3 (number of trends) models was tested. The performance of the models was evaluated according to the corrected Aikake information criterion (AICc;
The normality of residuals of the best model was tested through the Shapiro-Wilk test. In cases of deviation of residuals from the normal distribution, a scale finite mixture model (
The investigation of the canonical correlations between detected common trends and explanatory variables followed
All the analyses were carried out in the R environment (
The Pearson correlation coefficient showed several strong correlations among variables (Table S5). In almost all the GSAs the evenness was significantly and positively correlated with mean weight (p<0.05), while the LFI was significantly (p<0.05) and positively correlated with TyL, with the only exception of GSA 2 (Table S5).
For all GSAs the Kaiser criterion suggested the use of two factors, except for GSAs 1, 5, 15, 19 and 25, for which the use of only one factor was suggested. Thus, two factors were used for the PCA. The variance explained by the first component was 66.4%, while the variance explained by the second one was 20.9%, for a cumulative variance of 87.4% (
Variables | Correlation | |
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Dim1 | Dim2 | |
TyL | 0.94 | –0.27 |
LSI | 0.91 | 0.54 |
MW | 0.84 | –0.45 |
LFI | 0.81 | –0.25 |
Evenness | 0.76 | Not significant |
MML | 0.57 | 0.79 |
GSA | 0.74 | 0.76 |
YEARS | Not significant | –0.17 |
% explained variance | 66.4% | 20.9% |
Year did not seem to influence the grouping of the data (p<0.05), with all years clustered in the centre of the PCA space (
The PCA results separated the six indicators into two groups: one represented by indicators sharing a definition explicitly based on the Lmax parameter that focuses on the fraction of the community with large species (MML and LSI). The other group included indicators not based on Lmax. The subsequent analyses were carried out considering TyL and MML, the indicators most correlated with the principal components and the least correlated with each other. Each indicator represented one of the groups detected in the PCA.
The DFA results showed that the TyL trend decreased between 1999 and 2002 and increased steadily afterward, while the MML trend increased until 2004 before declining sharply between 2008 and 2012 (
The comparison among the models tested for TyL and MML showed that for both indicators the covariates did not improve the goodness of fit, giving an AICc higher than the baseline model. In Table S8, the best models are reported for each type (defined by the included covariates). The best model is characterized by one underlying common trend (
The common trends detected can be decomposed to effects at each GSA level through the factor loadings (
The factor loadings of the MML indicated that most GSAs were associated with the hidden common trend, except GSA 1, 15, 16 and 25 (
The covariates SST and Med anomaly were highly correlated with each other, and both showed a strong negative correlation with the fleet capacity (Fig. S8 and Table S9), with opposite patterns in time (Fig. S9). NAO showed no correlation with other covariates and no clear temporal patterns. The common trends for TyL and MML detected by the DFA were compared with the covariates under consideration (SST, NAO, Med anomaly and fleet capacity) through canonical correlations between the detected trends and the covariates. A significantly strong positive correlation was found between the trend of TyL and the covariates Med anomaly and SST, while a negative correlation was found between TyL and fleet capacity (
Covariates | no lag | 1-year lag | 5-year lag | 10-year lag | |
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TyL | NAO | 0.12 | –0.11 | –0.33 | –0.37 |
MedAnomaly | 0.72 | 0.7 | 0.59 | 0.76 | |
Fleet_cap | –0.94 | –0.9 | –0.6 | –0.72 | |
SST | 0.62 | 0.58 | 0.6 | 0.75 | |
MML | NAO | –0.23 | 0.02 | 0.4 | 0.2 |
MedAnomaly | –0.69 | –0.65 | –0.32 | –0.61 | |
Fleet_cap | 0.92 | 0.89 | 0.53 | 0.45 | |
SST | –0.5 | –0.44 | –0.36 | –0.59 |
In GSAs 1, 7, 8, 9, 10, 11, 15, 16 and 25, where TyL increased consistently with the common trend, TyL was strongly influenced by three species characterized by higher biomass:
In GSA 5 the increase in
In GSA 19 the decreasing trend in MML was influenced by the increase in
Contrasting patterns between areas were observed in the comparison between TyL and MML. In some GSAs, increasing trends of species showing both high abundance and biomass led to an increase in both indicators. This was the case for
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
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 (
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
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 (
The declining pattern in MML observed in GSA 6 and attributed to the faster decline in abundance than in biomass of
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 (
A complementary indicator that can account for changes in size structure has traditionally been identified in the LFI (
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
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 (
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.
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 (
This study was conducted in the framework of the MEDITS Project. We are grateful to Cristina Garcia, Enric Massutì and Antonio Esteban from the Instituto Español de Oceanografía (IEO) for providing the data for the analyses and to all participants of the MEDITS project for collecting these data. We gratefully acknowlege two anonymous reviewers for their comments, which helped improve the manuscript.