to environmental gradients - variability at temporal and different - - PowerPoint PPT Presentation

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• variability at temporal and different spatial scales

Coastal fish abundance in relation to environmental gradients

L Bergström*, U Bergström*, J Olsson*, J Carstensen** *Dept Aquatic Resources, Swedish University of Agricultural Sciences , SWE **Dept Bioscience - Applied Marine Ecology and Modelling, Aarhus Univ., DK

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Coastal fish indicators

• Not included in the WFD
• Assessed as part of the MSFD in Sweden and in the HELCOM

region

Cyprinids Key species Piscivores

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Assessment units for coastal fish

Coastal areas of 17 sub-units in the Baltic Sea

Example gives the current status

• f Key Species based on long

term monitoring data.

(HELCOM Core Indicator Fact Sheet 2015)

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How about spatial variation?

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• Poor density in relation to the

biology of the species

Available environmental monitoring data

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Coastal fish in the Baltic Sea

• Areas less than 20 m depth
• Dominated by relatively stationary species,

which may respond to environmental pressures originating from local as well as larger geographical scale.

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How does the status relate to changes in pressures?

Salinity Habitat availability Fishing Predation Food availability Habitat quality Topography NOT MUCH EXPLORED YET Eutrophication Temperature

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Questions:

• 1. How important is inter-annual versus geographical

variation?

• 2. What is the effect of small-scale environmental

variability? (temperature, salinity, wave exposure)

• 3. How does fish abundance relate to natural

environmental variables and anthropogenic pressures? (climate, salinity, eutrophication, fishing)

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Data included

• 41 areas from the Bothnian Bay to the Bornholm Basin

(Lat. 56-66oN)

• 2002-2013 (1-12 years per area, 30-45 stations per area)
• Various level of anthropogenic disturbance

Type Number of areas

Reference area for monitoring 13 Marine protected area 5 Fish no-take area 3 Commercial harbour 7 Seal protection area 8 High nutrient levels 4 Other 8

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Sampling method: test fishing with Nordic costal multimesh gill nets

9 panels Mesh sizes 10-60 mm common ratio 1.25 Depth X Length = 1.8 X 45 m Fish > 11 cm

Photo: Ulf Bergström

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Studied response variables

Abundance of Cyprinids Abundance of Perch Proportion of Perch above 25 cm

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Model 1: Components of variation

Temporal and spatial sources of variation (GLMM):

𝐽 = 𝜈 + 𝐵 + 𝑇 𝐵 + 𝑍 + 𝑍 × 𝐵 + 𝑓

Indicator value = mean level + random variation among areas + random variation among stations within areas + random interannual variation + random changes in interannual variation + dispersion factor

Where mean level (μ):

a function of depth (d), temperature (T) and wave exposure (SWM)

𝜈 = 𝑙1 ∙ 𝑒 + 𝑙2 ∙ 𝑒 + 𝑙3 ∙ 𝑈 + 𝑙4 ∙ log 𝑇𝑋𝑁 + 𝑙5 ∙ log2(𝑇𝑋𝑁)

Perch and Cyprinids analysed as Poisson variables, Proportion of large perch analysed as binomial variables.

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Result 1a: Variation among areas dominated over interannual variation

Relative variation explaned (%) Source CYP PER Large PER Between areas V[A]

10.3 3.8 19.3

Between stations V[S(A)]

5.0 1.7 8.6

Between years V[Y]

0.0 0.2 0.0

Between years and area V[Y×A]

1.9 1.3 7.9

Residual V[e]

82.8 93.0 64.2

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Result 1b: Variation among stations was partly explained by variation in depth, temperature at fishing and wave exposure

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20 40 60 80 5 10 15 20 25 Fish catch Depth (m) Cyprinids Cyprinidae A) 20 40 60 80 5 10 15 20 25 Temperature (C) Cyprinids Cyprinidae B) 20 40 60 80 1000 10000 100000 1000000 Wave exposure () Cyprinids Cyprinidae C) 10 20 30 40 50 5 10 15 20 25 Fish catch Depth (m) Perch Perca fluviatilis D) 10 20 30 40 50 5 10 15 20 25 Temperature (C) Perch Perca fluviatilis E) 10 20 30 40 50 1000 10000 100000 1000000 Wave exposure () Perch Perca fluviatilis F) 0% 20% 40% 60% 80% 100% 5 10 15 20 25 Proportion of larger perch Depth (m) Perch Perca fluviatilis G) 0% 20% 40% 60% 80% 100% 5 10 15 20 25 Temperature (C) Perch Perca fluviatilis H) 0% 20% 40% 60% 80% 100% 1000 10000 100000 1000000 Wave exposure () Perch Perca fluviatilis I)

Abundance

Cyprinids Perch Depth (m, 0-30) Temp (oC, 5-25)

Abundance Proportion

Large perch Wave exposure

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Model 2: Area specific means

𝐽 = 𝜈𝑏𝑠𝑓𝑏 + 𝑙 ∙ 𝑈 + 𝑡(𝑒) + 𝑡(𝑇𝑋𝑁) + 𝑓

Indicator value = mean value of all 41 areas + a linear temperature effect + spline model of depth + spline model of wave exposure (GAM). Area-specific marginal means were calculated for average values of T=15.9oC, d=7.4 m and log(SWM)=8 to allow for direct comparison between areas.

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Area-specific means

Calculated for average values

• f T=15.9oC, d=7.4 m and

log(SWM)=8 to allow for direct comparison between areas.

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How does fish abundance relate to environmental variables?

Natural variables:

• mean seasonal temperature (climate)
• salinity

Anthropogenic variables

• water transparency, as seen in eutrophic areas
• commercial catches of perch

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Relationship between fish abundance and the studied environmental variables

Cyprinids Perch Large perch Salinity ns decrease ns Temperature ns ns ns Water transparency decrease plateau ns Commercial fisheries ns Increase ns

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Cyprinids increase in areas of low water transparency

 10 20 30 40 1 2 3 4 5 6 7 8 Secchi depth (m) Cyprinidae Fish catch

Abundance Water transparency (Secchi depth, m)

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2 4 6 8 10 10 11 12 13 14 15 16 17 Fish catch Temperature (C) Perch Perca fluviatilis A) 2 4 6 8 10 2 3 4 5 6 7 8 Fish catch Salinity Perch Perca fluviatilis B) 2 4 6 8 10 1 2 3 4 5 6 7 8 Fish catch Secchi depth (m) Perch Perca fluviatilis C) 2 4 6 8 10 5 10 15 20 25 30 Fish catch Commercial perch landing (kg km-2) Perch Perca fluviatilis D)

Perch decrease with salinity and increase with commercial catches

Salinity Temperature Commercial catches Water transparency

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Conclusions

• Method development: extend the

geographical applicability of coastal fish status assessment

• Abundance of Cyprinids is a

useful indicator for assessing ecological status in relation to eutrophication

• No negative relationship between

commercial fisheries and perch abundance

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Thank you for listening!

Photo: Lena Bergström