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Hosted by The Marine Biological Association of the UK

Funded by :. Hosted by The Marine Biological Association of the UK. An ecosystem approach to long-term coastal observing – the western English Channel. Frost, M. T., Jenkins, S. R., Hinz, H., Genner, M. J., Sims, D. W., Budd, G., Araújo, J. N., Hart, P. J. B., Southward, A. J. & Hawkins, S. J.

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Hosted by The Marine Biological Association of the UK

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  1. Funded by: Hosted by The Marine Biological Association of the UK An ecosystem approach to long-term coastal observing – the western English Channel. Frost, M. T.,Jenkins, S. R., Hinz, H., Genner, M. J., Sims, D. W., Budd, G., Araújo, J. N., Hart, P. J. B., Southward, A. J. & Hawkins, S. J. Workshop on Coastal Observatories. Best practice in the synthesis of long-term observations and models Liverpool University, October 17th – 19th, 2006.

  2. MBA long-term observations • long history (>100 yrs) of MBA in situ observations 1899 The Plymouth research vessels 1902-1953 1936 “Long-Term Oceanographic and Ecological Research in the Western English Channel”. (Southward et al., Adv. Mar. Biol., 2005)

  3. MBA long-term observations 1975 The Plymouth research vessels 1953-2006 “The biomass figures……are intended to provide basic data for following changes in the bottom fauna in the future” 2006 (Holme, N.A. (1953)). The biomass of the bottom fauna in the English Channel off Plymouth. JMBA. 32:1-49

  4. Long-term monitoring • ‘Growing concern about human influence on marine ecosystems conflicts with our inability to separate man-made from ‘natural’ change. This limitation results from lack of adequate baselines and uncertainty as to whether observed changes are local or on a broad scale. Long-term monitoring programmes should be able to solve both these deficiencies’ (Duarte et al, 1992. Nature) • ‘long-term changes, such as those of climate change, can best be understood using long-term data sets, which can be costly and require long-term investment.’ (POST, 2004)

  5. Long-term monitoring • Research definition: • “..research occurring over decades or longer” • Monitoring definition (Parr et al): • “…the time scale which enables signals of environmental change to be distinguished from background noise” • practical definition: • “..any sites where there is a commitment to maintain scientific and monitoring programmes beyond the usual length of a scientific research programme”.

  6. Long-term monitoring • Specifically we are interested in: • what is the current state of the ecosystem? • How has the ecosystem changed? • How do interactions of climate and fishing effect ecosystems? • short term forecasts of ecosystem state • (PML, MBA – SO10 document)

  7. The western English Channel Major long-term sampling stations off Plymouth Regular intertidal stations From Southward et al., Adv. Mar. Biol., 2005

  8. MBA Time Series: English Channel Temperature and Salinity E1 1902-1987, 2001- Nutrients E1 1921-1987, 2001- Phytoplankton E1 1903-1987, 2001- Primary production E1 1964-1984 Zooplankton E1, L5 1903-1987, 1995-2000 Planktonic larval fish E1, L5 1924-1987, 1995-2000 Demersal fish L4 1913-1986, 2001- Intertidal organisms various 1950-1998, 1997- Infaunal benthos (intermittent) L4 1922-1950 Epifaunal benthos (intermittent) L4 1899-1986 n.b. There are many gaps in these series

  9. WEC: Physical changes • Fluctuations in sea temperature over 20th Century: both warm and cool periods • SST may be linked to solar activity- sunspots (Southward, 1980) and intensity of North Atlantic Oscillation (Sims et al., 2001; Stenseth et al., 2003) • Acceleration of warming (~ 1 ºC) since 1987 when time series stopped (later slide RSDAS data) • Warmer winter minimum temperatures (< 10 ºC now rare) • Predicted warming scenarios of 1.4 - 5.8 ºC over the next 100 years (Schneider, 2001)

  10. Sea-surface temperature offshore Plymouth 1871-2000 13.5 13.5 13.0 13.0 12.5 12.5 Mean annual SST (ºC) Mean annual SST (ºC) 12.0 12.0 11.5 11.5 11.0 11.0 1905 1905 1925 1925 1945 1945 1965 1965 1985 1985 2005 2005 Year Year Data source: Met Office Hadley Centre Grid square 50-51ºN, 4-5ºW

  11. CPR L5 Source: Coombs & Halliday, 2004 Note: work also carried out on CPR vs L4 (John et al, Journal of Sea Research. 2001) Monthly abundance of pilchard eggs from CPR sampling in the English Channel and adjacent areas and MBA station L5 sampling off Plymouth 1958-1980

  12. Sagitta setosa (warm water) 50 12 Sagitta elegans (cold water) 10 40 8 30 S. elegans (monthly mean x1000) 6 S. setosa (monthly mean x1000) 20 4 10 2 0 0 2000 1920 1940 1960 1980 Year • Originally thought that changes due to < inorganic nutrients due to reduced Atlantic inflow (Russell cycle) (leading to <PP etc) • But now shown nutrients reduced after community changed I.e. symptom not cause (and nutrients not reduced as dramatically as previously thought)

  13. Source: L5 data Pilchard eggs Flatfish larvae • Climate signal for egg abundance? – lags behind temp trend by several yrs. • Climate signal may then propagate down (top down forcing) as pilchard juveniles and adults prey on other smaller plankton • can be difficult to interpret plankton signals

  14. WEC Fish 8000 Herring - Clupea harengus • 1930s (warming) stocks of herring, collapsed Drivers: Climate + fishing? 7000 6000 5000 6000 Pilchard - Sardina pilchardus Catch (tonnes) 4000 5000 3000 2000 4000 1000 Catch (tonnes) 3000 0 2000 1920 1930 1940 1950 1960 1970 1980 1990 2000 Year 1000 • Herring ‘replaced’ during warmer 1950s by pilchard - never returned in abundance • Driver: over-fishing at regional scale 0 1920 1930 1940 1950 1960 1970 1980 1990 2000 Year • Mackerel increase but quickly ‘fished down’ • Last 20 years: increase in mean annual sea temperature = pilchard catches increased dramatically • Drivers: climate & fishing? 80000 Mackerel - Scomber scombrus 70000 60000 50000 Catch (tonnes) 40000 30000 • evidence of climate influence from phenological studies (squid migrate earlier in warm years with positive NAO; Flounder migrate to sea earlier in cooler years,) 20000 10000 0 1920 1930 1940 1950 1960 1970 1980 1990 2000 Year

  15. Demersal fish - separating Fishing and climate Southern Species from English Channel Mean CPUE [log10(x+1) transformed Source: MECN Final Report and Genner et al, 2004) • a) non-commercial species show +ve response to increase in SST • b) commercial species initially show similar response (1913-22 & 1950-57) but then any climate signal is overridden by fishing effects. • - Similar pattern observed in Bristol Channel but with different subset of species responding (local interactions / restraints) • Bottom-up forcing: abundance linked to temp-dependent resources?

  16. In Situ observations: Other • Long-term data has also been used to look at: • nutrient cycles (Joint et al, JMBA. 1997; Jordan & Joint, ECSS. 1998). • phytoplankton & Productivity (1964-84 main data collection) • Work on benthos is ongoing at present (ALSF) • Intertidal ecosystem particularly in response to climate (MarCLIM) • Current work now on ecosystem models • “Modelling food web interactions, variation in plankton production, and fisheries in the western English Channel ecosystem” Araujo et al (2006)

  17. Ecosystem Models • METHODS (kind of) • EwE (Ecopath with Ecosim) software • Model built representing ecosystem in 1994 (warm period) • structure / basic parameters of 1994 model used as baseline for 1973 (cold period) model and time series data up to 1999. Building past model and running to current allows modeller to monitor how biomasses have changed through time – model predicted biomasses can then be compared with stock assessment estimated biomasses – input parameters are then modified to get better fit (tuning). • 50 functional groups used to represent ecosystem* • time series of biomass ‘built’ + on PCI (used to estimate biomass forcing function driving PP) and zooplankton abundance (from CPR). • series of model runs with and without PP and with variations in parameters to assess relative roles of fishing, trophic interactions (v) + system productivity • v = maximum mortality predator can inflict on prey relative to baseline mortalities. low values = bottom-up control , high values = classic predator prey dynamics (Lotka-Volterra)

  18. Ecosystem Models • Results • Best fit for model included PBF (increases accuracy of model estimates by 25% compared with fishing only) - bottom-up mechanism contributing to production at high trophic levels. • including V (vulnerability) also improved accuracy of model • Biomass model of PP shows oscillations / peaks in early 1980s / late 1990s. • zooplankton similar trend but peak at end of 1980s (coincides with small peak in phytoplankton) Source: Araujo et al, 2006. Figure 2

  19. Conclusions • although PP kept increasing, many fish groups decreased after 1980s as did zooplankton • zooplankton not ‘tightly controlled’ by PP but correlated with SST. +ve - not Sig. +ve + Sig.

  20. Ecosystem Models many fish groups also increased in these years peaking during the 1980s e.g sole, plaice, cod increased (but catch) increased showing factors other than fishing as important Biomass (Thousands of tonnes) Catches (Thousands of tonnes) Source: Araujo et al, 2006. Figure 2

  21. Conclusions & WEC observatory • mixture of bottom-up and top down forcing on WEC ecosystem with climate playing increasingly important role • total ecosystem approach required in order to gain and understanding of ‘system drivers’ (e.g. Cushing (1961)) - observatory will aim to provide measurements of wide range of parameters • Linking in situ measurements to other observatory measurements enables: • filling in gaps (e.g. temp) Satellite data (RSDAS) E1 restarted in 2001

  22. Web (Webmap server) NERC datagrid interface Western Channel Observatory Data archive (BODC / DASSH, local SQL / Access) Virtual Observatory Modelling ERSEM Met Office (NCOF) Data Knowledge Transfer (via MECN) Remote Observatory in situ sampling (L4, E1, L5, buoy, etc.) long-term time-series scientific investigation (focus on ecosystem based studies) Remote Sensing SST, Ocean Colour Other sensors

  23. Observatory benefits • ground truthing for remote measurements (e.g. John, 2001 for L4:CPR). Issues with remote measurements of productivity/chlorophyll. • coordination and synthesis – modelling often reliant on fairly disparate datasets (various places collected in various ways at various times). • needs to be standardisation and methodological / technological audit trail. • WIDER NETWORKING TO INCREASE CAPACITY FOR DATA SYNTHESIS BEYOND WEC i.e. • Other NERC observatories • Other monitoring bodies (MECN)

  24. MECN NETWORK • 18 Partners: • DEFRA* • MBA • SAHFOS • PML • PEML • Dove ML • SAMS • SOS Bangor • DARD • CEFAS • FRS • POL • SOC • SMRU • JNCC* • BODC* • Met Office • EA*

  25. Observatory benefits • synthesis of data beyond WEC (continued) • European (MarBEF): Largenet e.g. Long-term pelagic stations in Europe. (Source: Karen Wiltshire, MECN Workshop, DEC 2005)

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