Change in Average Trophic Level of Marine Predators in the Bay of Biscay
D4 - Marine Food Webs
D4.2 - Proportion of selected species at the top of food webs
D4.3 - Abundance/distribution of key trophic groups/species
The assessment of changes to Mean Trophic Level in the Bay of Biscay showed no apparent change in overall food web structure over recent decades. However there were some signs of increase in the biomass of marine predators.
Food webs are networks within which organisms are related by feeding relationships (i.e. predator-prey interactions). This is one of three food web indicators, which describes changes in the structure of the food web with respect to fish and invertebrates.
Trophic level, determined by diet studies, expresses the position of an organism in a food web. A low trophic level (TL) value (e.g. 1) is assigned to the primary producers at the base of the food web whereas a high TL value (e.g. 4 or more) is assigned to predators at the top.
Mean Trophic Level (MTL) is calculated using species biomass data from different sources (e.g. scientific surveys and fisheries landings), and their assigned TL values. As the diet of species may vary among regions, it is important to use regionally-specific diet studies to determine regionally relevant TL values. These values are used to represent the feeding pathways / relationships in a given region, i.e. what-eats-what.
This indicator, currently based on invertebrates and fish, is mainly sensitive to fishing pressure. Fisheries usually target species at a high TL and thus drive a decrease in the availability of predators within the ecosystem. This in turn forces fisheries into targeting species at ever lower trophic levels and thus a decline in the MTL of fisheries landings. This is referred to as ‘fishing down marine food webs’ (Figure 1). If the phenomenon persists, the changes in food web structure could leave marine ecosystems increasingly vulnerable to natural and human-induced pressures.
Food webs represent the trophic interactions between predators and their prey. Each life stage of an organism is associated with a particular trophic level and, at its most simplistic, the energy is transferred from the lower trophic levels to the higher trophic levels following the interconnections between organisms within the food web. The tropic level (TL) value assigned to a particular organism is determined by the proportion of each category of species constituting the diet of a particular consumer (knowing that TL=1 for primary producers, and TL=2 for primary consumers, etc. (see Figure a)). TL can be estimated using dietary analysis (stomach content analysis), stable isotopes analysis, and modelling.
Within the scientific community, it is considered to be important that food web status should be based on ecosystem indicators that do not just use fish data (i.e. high trophic level species such as hake, monkfish, sharks, rays) but also data concerning invertebrates and species from intermediate trophic levels. The Mean Trophic Level (MTL) indicator meets this requirement because it takes into account food web structure and uses a metric (the TL) that reflects energy transfer between predators and prey. MTL is calculated using biomass data from scientific surveys and fisheries landings and the associated TL of the species. In this assessment, the indicator has been calculated taking into consideration vertebrates and invertebrates where possible. Eventually, however it is expected that this indicator will be adapted to consider all vertebrate and invertebrate.
The original concept that uses the MTL indicator, developed by Pauly et al. (1998), is known as ‘fishing down marine food webs’. A decline in the MTL of the global fisheries catch reveals a shift from intense fishing pressure on the highest trophic levels to increasing fishing pressure on lower trophic levels, due to the decline in biomass of high trophic level species. Thus, this indicator aims at highlighting the unsustainable fisheries practices of past decades. The indicator could inform political decisions to enforce regulations upon fisheries catches / quotas. The indicator was adopted by the Conference of the Parties to the Convention on Biological Diversity as one of eight indicators to monitor achievement of a significant reduction in the rate of biodiversity loss by 2010.
Since then, the use of MTL of landings has been further explored and additional hypotheses suggested to explain the patterns in MTL observed. The ‘fishing down food webs’ concept as defined above was actually detected in the North Atlantic. Other scenarios were described in other parts of the world (Essington et al., 2006; Morato et al., 2006; Swartz et al., 2010; Stergiou and Tsikliras, 2011; Shannon et al., 2014), for example, the concept of fishing through the food webs (sequential addition of low trophic level species in fisheries); fisheries expansion (into deeper and further offshore waters with the inclusion of new high trophic level species); and fishing up the food webs (addition of new previously unfished high trophic level species).
To compute the MTL indicator, landings have traditionally been the only source of biomass data, raising many concerns around their suitability for describing the ecosystem as a whole, due to the shortcomings and / or uncertainties associated with this type of data. First, the landings data are incomplete (i.e. they do not take into account discards, illegal, unreported, and unregulated fishing, or bycatch), and second, landings data are subject to multiple biases induced by fisheries drivers (Branch et al., 2010; Pauly et al., 2013). However, landings data do have the advantage of a high frequency of data availability that includes all gear types and thus many species. On the other hand, data from scientific surveys reflect actual changes in community structure because they are not influenced by market forces (i.e. selectively fishing for particular commercial species only). However, data from scientific surveys are usually limited to a specific season and one type of fishing gear. Thus, scientific surveys should be the main data source when using the MTL indicator to assess the food web, with landings providing complementary information.
Mean trophic level (MTL) is calculated using two types of data: (1) biomass data per species for fish and invertebrates from surveys and landings and (2) data on the trophic level of each species.
Past and present fish and invertebrate biomass data for the Bay of Biscay are compiled from research surveys and landings.
Annual biomass per species, collected during the DEMERSALES surveys on ICES subdivisions VIIIc and IXa-north of the Bay of Biscay for the period 1992–2015 were used for the southern Bay of Biscay analyses. Data were directly extracted from the Instituto Español de Oceanografía (IEO) database and include both invertebrate and fish data because invertebrates constitute a large part of the survey catches.
Annual biomass per species collected during the EVHOE surveys on ICES subdivisions VIIIa and VIIIb of the Bay of Biscay for the period 1997-2015 were used for the northern Bay of Biscay analyses. Survey data were extracted from the 2017 OSPAR Groundfish survey monitoring and assessment data product (Moriarty and Greenstreet, in prep), which focuses on fish communities across the Northeast Atlantic region and does not include any invertebrate data.
Data were selected for the depth range of the continental shelf in the Bay of Biscay (<200 m depth).
The DEMERSALES and EVHOE surveys are bottom trawl surveys, which are part of the Data Collection Framework of the Common Fisheries Policy (EC regulation No. 665/2008).
Annual biomass per species, from the official landings dataset were used for the analyses in subdivisions VIIIa and VIIIb for the northern Bay of Biscay, and subdivisions VIIIc of the southern Bay of Biscay. These data can be downloaded from the ICES website (ICES Historical catch statistics 1950–2010 and Official catch statistics 2006–2014).
French landings data are the main data source for the northern Bay of Biscay. The data were however missing for 1999 and so could not be included in this analysis.
Trophic Level Data
Some preliminary work is needed to collate regional TL values per species. This improves the reliability of TL values for the Bay of Biscay because the diet of species (and hence the predator-prey relationships) may vary among regions. Three sources of TL information are prioritised to ensure the most appropriate TL value for each species (Figure b).
However, because TL values are assigned at the species level, it did not seem appropriate to assign TL values to large groups that would include species from low to high trophic levels (e.g. Osteichthyes; the bony fishes). High taxonomic ranks (i.e. phylum, sub-phylum, class, superorder, order, suborder and infraorder) were thus removed from the MTL computation. Only the ranks of genus and family were considered. For these, their TL is derived by averaging the TL values of all relevant species present in the Bay of Biscay.
The regional TL values estimated from stomach content analyses were based on the IEO’s non-public database corresponding to DEMERSALES surveys in the Spanish part of the Bay of Biscay, for the period 1990–2013. The remaining TL values, estimated from stomach content analysis, stable isotope analysis or models, were collected from the published literature for regions and surrounding regions (Jennings et al., 2002; Pinnegar et al., 2002; Le Loc’h and Hily, 2005; Bodin et al., 2008; Le Loc’h et al., 2008; Navarro et al., 2011; Chouvelon et al., 2012; Lassalle et al. 2011; Lassalle et al., 2014).
Calculation of the MTL indicator
The MTL indicator for each year is calculated using the biomass and TL of species according to the following formula:
where MTLk refers to the MTL indicator for each year k, TLi refers to the trophic level value of species (group) I, and Yik refers to the biomass (Y) of species (group) i in year k, as included in landings data or in surveys data.
The MTL is then calculated each year in order to identify trends.
While assessing this indicator, the group of species considered can be changed by applying a TL cut-off (e.g. 3.25). The purpose of these cut-offs is to eliminate low trophic level species in order to focus on predators (i.e. high trophic level species) and detect changes in the upper food web structure.
Pauly and Watson (2005) stated that using the mean TL for the Marine Trophic Index should always be done with an explicitly stated cut off and proposed a first TL cut-off value of 3.25, it excluded all landed species under a TL of 3.25. In this assessment three TL cut-offs were identified: a TL cut-off value of 2.0 (expressed as MTL_2.0, which includes all consumers into the analysis; the MTI cut-off value of 3.25 described by Pauly and Watson (200t) (expressed as MTL_3.25). The third cut-off fixed at 4.0 has also been applied to the data (i.e. MTL_4.0) to focus on higher predators.
The MTL indicator with different cut-offs was first calculated using the whole community (all species included), and then by eliminating pelagic species from the computation to give information on bentho-pelagic species. Excluding pelagic species, helped reduce bias in the biomass data, linked to interannual variability in the pelagic species data. Indeed, the EVHOE and DEMERSALES surveys are bottom trawl surveys, meaning they are designed to capture and evaluate bentho-demersal species. The pelagic species of the Bay of Biscay were defined according to Quéro et al. (1989) and Fishbase (www.fishbase.org).
Uncertainty exists around each TL value estimated by diet studies, which is related to spatio-temporal variability and species ontogeny (Pinnegar et al., 2002; Chassot et al., 2008; Vinagre et al., 2012). This uncertainty was reported as a standard error for each TL value of a species. In order to include uncertainty in the MTL model, a bootstrap methodology was developed using the R software (R version 3.1.0). Random sampling was applied on TL values and their standard error, performing 500 MTL computations per year studied. The model was then fitted as a mean value of the 500 MTLs generated with an uncertainty related to its standard error. The uncertainty around the MTL model is thus linked to the uncertainty of the TL estimations.
For statistical analysis, preliminary tests of normality (Shapiro test), homoscedasticity (Harrison-McCabe test) and autocorrelation (Durbin–Watson test) of the data were applied for the use of parametric methods. When these tests were verified, a linear model was fitted to the temporal series (mean values for each year generated by the model) in order to test the significance of the trend. When normality or homoscedasticity were not verified, evolution of MTL over time was assessed by means of Mann-Kendall analyses (Scherrer, 1984). Differences were considered significant when p<0.05. R software and packages were used for statistics and graphics (R core team, 2015).
The Mean Trophic Level (MTL) indicator was assessed over a period of 18 to 23 years for the northern and southern parts of the Bay of Biscay (Figure 2), using biomass survey data complemented by fisheries landings data and region-specific TL values for species concerned. Initially, the entire community was studied, followed by a focus on the bentho-demersal community (i.e. those species living on or close to the seabed) by excluding pelagic species (i.e. those living within the water column). Species above a certain TL value were selected in order to concentrate on the predator community.
In the Bay of Biscay (northern and southern parts), food webs indicate a general improvement from the unsustainable fishing pressure of previous decades, shown in this assessment by a significant increase in MTL. The biomass of predators has increased meaning that the structure of the food web is gaining stability and therefore resistance to perturbations.
To better reflect changes in the upper TLs of individual ecosystems, three MTL cut-off scenarios were used to assess trends in changes to MTL in the Bay of Biscay (Table 1): Above a TL of 2.0 (TL_2.0) includes all consumers; Above a TL of 3.25 (TL_3.25) includes higher trophic length fish; and Above a TL of 4 (TL_4.0) includes higher level predators.
This increase in MTL was detected in the northern part of the Bay of Biscay when assigning the MTL_3.25 and MTL_4.0 cut-offs to both survey and landings data and thus selecting predators for the assessment (Table 1). The increase was also identified in the southern Bay of Biscay, but only for survey data when excluding pelagic species and low trophic level species (MTL_3.25). The positive trends observed for this indicator reflect an increase in predator biomass in the northern part of the Bay of Biscay and to a lesser extent in the southern part. It conveys an apparent reduction in fishing pressure on high trophic level bentho-demersal predators, presumably allowing communities to begin recovery from past perturbations.
There is moderate / low confidence in the methodology used and high / moderate confidence in the availability of data.
Table 1: Trends in changes to MTL in the Bay of Biscay
Analyses performed using landings and survey data over different Mean Trophic Level (MTL) cut-off scenarios. Statistically demonstrated increases in MTL are shown as green with up arrows and significance; where no increase is calculated, this is shown as green with a horizontal arrow. p-value for the statistical tests significance (linear model), *: p<0.05, **: p<0.01 ***: p<0.001. sp. : species.
The collation of regional TL values for calculating MTL was possible for the main representative species of the landings and survey data, for both the northern and southern parts of the Bay of Biscay. Uncertainty around the MTL indicator is linked to uncertainty around the TL values. Arroyo et al. (2017) showed there was less uncertainty around the MTL indicator when using regional TL values as opposed to global average values (e.g. Fishbase). These results confirm the necessity of giving priority to the development of regional TL values in order to improve the confidence in the assessment of food webs.
Northern Bay of Biscay (subdivisions VIIIa and VIIIb)
Using the scientific survey data, the MTL_2.0 (considering all trophic levels) showed no significant trend in either scenario (i.e. with all species or excluding pelagic species) (Figure c). When applying a mid (MTL_3.25) or high (or MTL_4.0) cut-off, the MTL indicator displayed significant increasing trends (Figure c). The influence of the main species in terms of biomass on the indicator was investigated as part of the EcApRHA (Arroyo et al. 2017).
The MTL calculated using landings data and considering all trophic levels (MTL_2.0 in Figure d) displayed no significant trend over the study period, whether all species were considered or pelagic species were excluded. However, significant increases in the MTL indicator were detected when MTL cut-offs were applied. A significant positive trend in MTL_3.25 was observed when pelagic species were excluded. It underlined the effect that the variability in pelagic species biomass has in masking the evolution of the bentho-demersal biomass. MTL_4.0 (top predators only) increased significantly in both cases (with or without pelagic species).
Southern Bay of Biscay (subdivisions VIIIc and IXa-north)
The MTL_2.0 (including all trophic levels) based on the scientific survey data, showed no significant trend with all species included or with pelagic species excluded (Figure e). When applying a mid (MTL_3.25) or high (MTL_4.0) cut-off, analysis revealed a significant trend only for MTL_3.25 without pelagic species. The EcApRHA project (Arroyo et al., 2017) investigated the influence of the main species ontogeny on the MTL indicator to see if its variation could be due to differences in the age composition of the species caught during the survey (and thus in TL values). Results showed no apparent ontogenetic effect on overall MTL trends at any cut-off level, although further studies are needed to confirm these results with a larger number of species.
No significant trends were detected in the MTL indicator on historical landings data whether considering all species, excluding pelagic species or applying different cut-offs (MTL_3.25 and MTL_4.0 in Figure f). However, the EcApRHA project highlighted that MTL trends for predator communities can vary depending on the length and the source of the landings time series chosen (Arroyo et al., 2017) and that short terms trends can be masked by long-term analysis. For example, an increasing trend of intermediate TL, driven by pelagic species and a decreasing trend in demersal top predators were observed in the last years of landings data.
Analyses of scientific survey data and landings data show no major variation in the MTL indicator in the Bay of Biscay. This indicates no apparent signal of the state of the marine food web. The results also highlight that the bentho-demersal predator community seems to have been slowly recovering in this area since the beginning of the 21st century, almost certainly due to management regulations set in place, especially in the northern part of the Bay of Biscay. Nevertheless, these findings need to be treated with care as they are highly dependent on the length and source of the time series considered, especially for the landings data (Arroyo et al., 2017).
The methodology has been commonly used but consensus in the scientific community has not yet been achieved, resulting in a confidence of low / moderate.
For data availability the rating is moderate / high. There is sufficient spatial coverage for landings data and ground fish survey data. There appears to be sufficient spatial scale for the trophic level information.
The Mean Trophic Level (MTL) in the southern and northern Bay of Biscay showed no apparent change in the overall food web structure resulting from fishing pressure (MTL 2.0 in Table 1). However there were some signs of improvements when focusing in on the predator community (MTL 3.25 and 4.0 in Table 1).
The Marine Trophic Level (MTL) in the southern and northern parts of the Bay of Biscay showed no apparent sign of changes in food web structure owing to fishing pressure. An increasing trend in the MTL indicator is considered to reflect decreasing impacts of fisheries on food webs; while a stable or decreasing trend should be further investigated in order to determine possible causes. Knowledge of the fisheries history in the region also helps to interpret trends: the implementation of fisheries regulations may have decreased fishing pressure on top predators. Other information about the communities inhabiting the area and the environmental variability may be necessary to confirm the findings of this assessment. Linking the MTL indicator to other biodiversity and food webs indicators (e.g. Typical Length) would also allow a more detailed examination of the impact of fisheries on the ecosystem.
Further work can be undertaken to improve the assessment of the state of the food web. This assessment is based on invertebrates and vertebrates species in most cases, mainly bentho-demersal species. Incorporating additional datasets on other biological compartments (e.g. benthos, mammals, or birds) and / or from other sources (e.g. pelagic survey data or models) into the MTL indicator will enable a more holistic assessment of the area. For instance, using the OSPAR Groundfish survey monitoring and assessment data product in the northern Bay of Biscay, was a first step in the assessment of this indicator. However, data on invertebrates (including cephalopods), which represent an important component of the biomass in the Bay of Biscay food web, which are important prey items with a fundamental role in the food web, and which can influence the indicator trends, should also be included.
It would beneficial for the further development of this indicator if the work started in the EcApRHAproject was continued. Specifically, the influence of some important demersal / pelagic species on the MTL indicator trends, and how they influence the overall assessment should be examined in more detail (Arroyo et al., 2017). Investigating the direct influence of particular anthropogenic pressures on MTL variations (e.g. fishing mortality of species or indicators linked to habitat loss due to fisheries) also needs to be further explored.
Applying the indicator to finer geographic scales and assessment units would help map regional variation in the MTL indicator, and so identify particularly impacted areas within those subject to high fishing pressure.
Understanding the feeding relationships between species occurring in a specific region is essential to conduct a robust assessment of the food web, whether using the MTL indicator or any other Trophic Level based indicator. It is not currently possible to apply the MTL indicator anywhere other than the Bay of Biscay, owing to a lack of detailed information on feeding interactions and region-specific Trophic Level (TL) values. Repeated dietary studies implemented at the (sub)-regional scale and the computation of TL values would help fill this gap in knowledge.
To improve the assessment of the state of the food web, further work on the MTL indicator could include: incorporating additional datasets on biological compartments that are not currently included (e.g. benthos, mammals, or birds); investigating the influence of various anthropogenic pressures; exploring finer geographic scales; and further defining assessment values.
In order to establish trophic relationships more accurately so that TL values can be determined, data are required on species feeding habits and their variations with ontogeny, where this is lacking. Comprehensive datasets on the feeding ecology of many of the key species in marine food webs are currently insufficient for the purposes of conducting this type of assessment, and this is especially the case for species at lower trophic levels.
The first step in filling these gaps in knowledge of food web structure and connectivity is to extend data collection on feeding ecology at a sub-regional scale (Carafa et al., 2007; Moloney et al., 2010; Rossberg et al., 2011). Large-scale surveys (such as the Data Collection Framework (DCF) bottom-trawl and pelagic surveys) could aim at systematically collecting; as many species as possible in the food web; and data for dietary analyses using stomach content and / or stable isotope analyses for the different size classes of a given species (in order to account for the ontogeny effect on species TL values). Analyses of stomach contents can provide accurate information on the species consumed as well as serving as a sampler of the smaller invertebrates and other benthic components not retained by the sampling gear and so not represented in the survey data. Stable isotope analyses indicate trophic level based on a longer feeding signature, and so provide a broader view of feeding strategy of a given species.
Arroyo, N.L., Le Loc’h, F., Preciado, I., Niquil, N., Vouriot, P., Safi, G. 2017. Implementation of the mean trophic level indicator (MTL FW4) and assessment of its use at a sub-regional level (OSPAR region IV), as a contribution to the EU Co-financed EcApRHA project (Applying an ecosystem approach to (sub) regional habitat assessments), deliverable No. 3.1.
Bodin, N., Le Loc’h, F., Caisey, X., Le Guellec, A.M., Abarnou, A., Loizeau, V., and Latrouite, D. 2008. Congener-specific accumulation and trophic transfer of polychlorinated biphenyls in spider crab food webs revealed by stable isotope analysis. Environmental Pollution 151: 252-261.
Branch, T., Watson, R., Fulton, E., Jennings, S., McGillard, C., Pablico, G., Ricard, D., and Tracey, S. 2010. Trophic fingerprint of marine fisheries. Nature 468: 431-435.
Carafa, R., Dueri, S., Zaldívar, and J.M. 2007. Linking terrestrial and aquatic ecosystems: Complexity, persistence and biodiversity in European food webs. In: EUR 22914 EN, Joint Research Centre.
Chassot, E., Rouyer, T., Trenkel, V.M., and Gascuel, D. 2008. Investigating trophic-level variability in Celtic Sea fish predators. Journal of Fish Biology 73: 763–781.
Chouvelon, T., Spitz, J., Caurant, F., Mèndez-Fernandez, P., Autier, J., Lassus-Débat, A., Chappuis, A., and Bustamante, P. 2012. Enhanced bioaccumulation of mercury in deep-sea fauna from the Bay of Biscay (north-east Atlantic) in relation to trophic positions identified by analysis of carbon and nitrogen stable isotopes. Deep Sea Research Part I: Oceanographic Research Papers 65: 113–124.
Essington, T.E., Beaudreau, A.H., and Wiedenmann, J. 2006. Fishing through marine food webs. Proceedings of the National Academy of Sciences USA 103: 3171−3175.
Jennings, S., Greenstreet, S., Hill, L., Piet, G., Pinnegar, J., and Warr, K.J. 2002. Long-term trends in the trophic structure of the North Sea community: evidence from stable-isotope analysis, size-spectra and community metrics. Marine Biology 141: 1085-1097.
Lassalle, G., Lobry, J., Le Loc’h, F., Bustamante, P., Certain, G., Delmas, D., Dupuy, C., Hily, C., Labry, C., Le Pape, O., Marquis, E., Petitgas, P., Pusineri, C., Ridoux, V., Spitz, J., and Niquil, N. 2011. Lower trophic levels and detrital biomass control the Bay of Biscay continental shelf food web: implications for ecosystem management. Progress in Oceanography 91: 61–75
Lassalle G., Gascuel D., Le Loc’h F., Lobry J., Pierce G.J., Ridoux V., Santos M.B., Spitz J. & Niquil N. (2012) An ecosystem approach for the assessment of fisheries impacts on marine top-predators: the Bay of Biscay case study. ICES Journal of Marine Science 69: 925-938.
Lassalle, G., Chouvelon, T., Bustamante, P., and Niquil, N. 2014. An assessment of the trophic structure of the Bay of Biscay continental shelf food web: Comparing estimates derived from an ecosystem model and isotopic data. Progress in Oceanography 120: 205-2015.
Le Loc’h, F. and Hily, C. 2005. Stable carbon and nitrogen isotope analysis of Nephrops norvegicus / Merluccius merluccius fishing grounds in the Bay of Biscay (Northeast Atlantic). Canadian Journal of Fisheries and Aquatic Sciences 62: 123–132.
Le Loc’h, F., Hily, C., and Grall, J. 2008. Benthic community and food web structure on the continental shelf of the Bay of Biscay (North Eastern Atlantic) revealed by stable isotopes analysis. Journal of Marine Systems 72: 17–34.
Moloney, C.L., St John, M.A., Denman, K.L., Karl, D.M., Koster, F.W., Sundby, S., and Wilson, R.P. 2010. Weaving marine food webs from end to end under global change. Journal Of Marine System 84: 106-116.
Morato, T., Watson, R., Pitcher, T.J., and Pauly, D. 2006. Fishing down the deep. Fish 7: 24−34.
Moriarty, M. and Greenstreet, S.P.R. (in prep). Derivation of Groundfish survey monitoring and assessment data products for the Northeast Atlantic area. Scottish Marine and Freshwater Science Report Vol xx Noxx.
Navarro, J., Coll, M., Louzao, M., Palomera, I., Delgado, A., and Forero, M.G. 2011. Comparison of ecosystem modelling and isotopic approach as ecological tools to investigate food webs in the NW Mediterranean Sea. Journal of Experimental Marine Biology and Ecology 401: 97-104.
Pauly, D., and Watson, R. 2005. Background and interpretation of the ‘Marine Trophic Index’ as a measure of biodiversity. Philosophical Transactions of the Royal Society: Biological Sciences 360: 415-423.
Pauly, D., Christensen, V., Dalsgaard, J., Froese, R., and Torres Jr., F. 1998. Fishing down marine food webs. Science 279: 860 – 863.
Pauly, D., Hilborn, R., and Branch, A. 2013. Does catch reflect abundance? Nature 494: 303-306.
Pinnegar, J.K., Jennings, S., Brien, C.M.O., and Polunin, N.V.C. 2002. Long-term changes in the trophic level of the Celtic Sea fish community and fish market price distribution. Journal of Applied Ecology 39: 377-390.
Quéro, J-C., Dardignac, J., and Vayne, J-J. 1989. Les poissons du Golfe de Gascogne. Institut Français de Recherche pour l’Exploitation de la Mer. 229pp.
R Core Team (2015). R: A language and environment for ## statistical computing. R Foundation for Statistical Computing, ## Vienna, Austria. URL https://www.R-project.org/.
Rossberg, A. G., Farnsworth, K. D., Satoh, K., and Pinnegar, J. K. 2011. Universal power-law diet partitioning by marine fish and squid with surprising stability-diversity implications. Proceedings of the Royal Society B 278 (1712): 1617–1625.
Scherrer, B. 1984. Biostatistique. Gaëtan Morin éditeur. 850pp.
Shannon, L., Coll, M., Bundy, A., Gascuel, D., Heymans, J. J., Kleisner, K., Lynam, C. P., Piroddi, C., Tam, J., Travers-Trolet, M., and Shin, Y. 2014. Trophic level-based indicators to track fishing impacts across marine ecosystems. Marine Ecology Progress Series 512: 115-140.
Stergiou, K.I., and Tsikliras, A.C. 2011. Fishing down, fishing through and fishing up: fundamental process versus technical details. Marine Ecology Progress Series 441: 295−301.
Swartz, W., Sala, E., Tracey, S., Watson, R., and Pauly, D. 2010. The spatial expansion and ecological footprint of fisheries (1950 to present). PLoS ONE 5: e15143.
The University of Waikato, 2017. Marine food webs. Science learning hub, sciencelearn.org.nz https://www.sciencelearn.org.nz/resources/143-marine-food-webs
Vinagre, C., Salgado, J., Mendonca, V., Cabral, H., and Costa, M. 2012. Isotopes reveal fluctuation in trophic levels of estuarine organisms, in space and time. Journal of Sea Research 72:49-54.
Biological Diversity and Ecosystems - Management of specific human pressures
OSPAR CEMP Guideline on the Change in average/mean trophic level of marine predators in the Bay of Biscay (FW4) (OSPAR 2016-01)
D4 – Marine Food Webs
|Context (4)||D4.3 - Abundance/distribution of key trophic groups/species, D4.2 - Proportion of selected species at the top of food webs|
|Point of contact|
Change in Mean Trophic Level of Marine Predators
The Mean Trophic Level indicator assesses the state of the food web taking into account its structure (via biomasses) and the Trophic Level metric, which reflects the energy transfer between preys and predators. This indicator is mainly sensitive to the fishing pressure.
|Indirect spatial reference|
|Date of publication|
|Conditions applying to access and use||https://www.ospar.org/site/assets/files/1215/ospar_data_conditions_of_use.pdf|
|Conditions applying to access and use||http://www.ices.dk/marine-data/dataset-collections/Pages/Fish-catch-and-stock-assessment.aspx|
|Conditions applying to access and use|
For ES (survey data) IEO data policy applies;