macrozoobenthic production and productivity jennifer

1
Tromsøflaket Jennifer Dannheim 1,2 Anne Helene Tandberg 2 Pål Buhl-Mortensen 2 Lene Buhl-Mortensen 2 Margaret F.J. Dolan 3 Børge Holte 2 Macrozoobenthic production and productivity on the northern Norwegian shelf Correspondence: Jennifer Dannheim Alfred Wegener Institute Bremerhaven, Germany [email protected] Brey T (2001). Empirical relations in aquatic populations for estimation of production, productivity, mortality, respiration. Population dynamics in benthic invertebrates. A virtual handbook. Version 01.2. www.thomas- brey/science/virtualhandbook Buhl-Mortensen L, Buhl-Mortensen P, Dolan MFJ, Dannheim J, Bellec V, Holte B (2012). Habitat complexity and bottom fauna composition at different scales on the continental shelf and slope of northern Norway. Hydrobiologia 685: 191-219 Buhl-Mortensen P, Dolan MFJ, Buhl-Mortensen L (2009). Prediction of benthic biotopes on a Norwegian offshore bank using a combination of multivariate analysis and GIS classification. ICES J Mar Sci, 66: 2026-2032. Cusson M, Bourget E (2005). Global patterns of macroinvertebrate production in marine benthic habitats. Mar Ecol Prog Ser 297: 1-14. Dolan MFJ, Buhl-Mortensen P, Thorsnes T, Buhl-Mortensen L, Bellec VK, Bøe R (2009). Developing seabed nature-type maps offshore Norway: initial results from the MAREANO programme. Norw J Geol 89: 17-28. Gogina M, Glockzin M, Zettler ML (2010). Distribution of benthic macrofaunal communities in the western Baltic Sea with regard to near-bottom environmental parameters. 1. Causal analysis. J Mar Sys 79: 112-123. Nilsen M, Pedersen T, Nilssen EM (2006). Macrobenthic biomass, productivity (P/B) and production in a high-latitude ecosystem, North Norway. Mar Ecol Prog Ser 321: 67-77. Tandberg AH, Dannheim J, Jensen H, Dolan M, Bellec V, Buhl-Mortensen P, Holte B (2013): Spatial distribution of macrozoobenthic production on the northern Norwegian shelf. Arctic Frontiers, 20-25 January 2013, Tromsø, Norway figure 1. Biotopes of Tromsøflaket (biotopes B1-B6) with typical species according to Buhl-Mortensen et al. (2009). B1 B3 B2 B4 B5 B6 B1: muddy sediments in basins with pockmarks B3: sandy sediments on broadly elevated areas B4: sandy-gravelly sediments on broad slopes, with iceberg ploughmarks B5: gravelly-sandy sediments on broad slopes, with iceberg ploughmarks B6: sandy-gravelly sediments with cobbles on moraine ridges Pelosina Asbestopluma B2: sandy muddy sediments with iceberg ploughmarks, “sponge grounds” calcic Foraminifera Aplysilla, Geodia Bolocera Stichopus Phakellia Brachiopoda Antho Polymastia Stylocordyla Aphrodite acknowledgements We thank Arne Hassel, Hannu Koponen, Jon Rønning and Tom Alvestad for processing a large part of the samples. 3 2 1 environmental correlations figure 4. Canonical correspondence analysis of production (g m -2 y -1 ; A: infauna, B: epifauna) and productivity (y - 1 ; C: infauna, D: epifauna) of biotopes (B1-B5). Arrow length indicate strength of relationships between biological data and terrain parameters, %-values = variance in species data explained by axis. Pebble, cobble and boulders are %-cover of bottom substrate. bc = backscatter (i.e. degree of bottom softness/hardness), bpi 50 = bathymetric position index (50 grid size, i.e. concave/convex bottom surface), curva = curvature (i.e. change rate of aspect), trtracks = trawl tracks (N/100m 2 ). background & methods Benthic animals produce food resources for organisms from higher trophic levels (fish, birds, mammals, and ultimately humans). The spatial distribution of benthic production and productivity are of direct relevance for the identification of essential feeding habitats (i.e. highly productive areas). This is important information for sustainable ecological management. In this context, the MAREANO programme aims to map the environment and fauna off the Norwegian coast by linking environmental parameters to the benthic ecosystem. In a case study, 6 different biotopes were defined from benthos sampled at the Tromsøflaket Bank (Barents Sea) (fig.1, Buhl- Mortensen et al. 2009). Species biomass (B) and abundance were recorded at each station (N = 23, grab and beam-trawl). Production (P) and productivity (P/B) was estimated by using the model of Brey (2001) and correlated with terrain/ environmental parameters from multibeam echosounder/ videos (see Buhl-Mortensen et al. 2009, Dolan et al. 2009). results & conclusions Production was lowest in deep, muddy and sandy muddy biotopes (B1, B2; fig. 2) and highest on shallow sandy to gravel banks (B3, B4: mainly Mollusca & Brachiopoda). Production decreased with depth but increased towards harder bottoms (fig. 4; Nilsen et al. 2006, Cusson & Bourget 2005). Productivity of infauna was diametrically affected by depth and bottom structure (fig. 2, high P/B by Polychaeta). Bottom-trawling frequency was higher on soft sediments, thus trawling indirectly affected benthic production at the Norwegian shelf (fig. 4). At the spatial scales investigated, terrain parameters are poor descriptors of spatial variability of production and productivity (see low %-values in fig. 4). Other environmental variables such as organic input into the system and biological parameters (e.g. biodiversity, species life-span, mobility, feeding mode) seem to be locally more important than terrain parameters (Buhl- Mortensen et al. 2012, Gogina et al. 2010, Cusson & Bourget 2005, see also fig. 3 & table 1). At broader scales (e.g. landscape scale), terrain parameters might be more appropriate descriptors for mapping of production (fish-feeding habitats) for e.g. ecological management (Buhl-Mortensen et al. 2012, see talk of Tandberg et al. 2013, this conference). biotope differences production (g m -2 y -1 ) 0 5 10 15 20 25 30 35 0 2 4 6 8 A AB B B B B1 B2 B3 B4 B5 0.0 0.2 0.4 0.6 0.8 1.0 1.2 A AB B AB AB B1 B2 B3 B4 B5 productivity (y -1 ) 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 B1 B2 B3 B4 B5 0.0 0.1 0.2 0.3 0.4 0.5 0.6 A AB AB B B B1 B2 B3 B4 B5 0.0 0.1 0.2 0.3 0.4 0.5 0.6 infauna epifauna production productivity figure 2. Average (± S.D.) production (P, g m -2 y -1 ) and productivity (P/B, y -1 ) of in- and epifauna from biotopes B1-B5. Different letters indicate significant differences. Inserts show results without the dominant brachiopod Macandrevia cranium. production (%) 0 20 40 60 80 100 Polychaeta Porifera Mollusca Crustacea Brachiopoda Bryozoa Others Ascidiacea Echinodermata B1 B2 B3 B4 B5 production (%) 0 20 40 60 80 100 B1 B2 B3 B4 B5 interface feeder suspension feeder subsurface deposit feeder surface deposit feeder predator, active carnivore predating, deposit feeding parasite omnivore, predator/scavenger not defined unknown figure 3. Contribution of taxonomic groups (A: infauna, B: epifauna) and feeding-guilds (C: infauna, D: epifauna) to the total production in biotopes B1-B5. group/guild biotope differences infauna Mollusca B3 ≠ all others Ascidiacea B3 ≠ B1,B5 Omnivore, predator/scavenger B1 ≠ B5 suspension feeder B1 ≠ B3,B4,B5 interface feeder B1 ≠ B4,B5 epifauna predator B1 ≠ B4 table 1. Taxonomic groups and feeding guilds that differed significantly in production between biotopes B1-B5. depth cobble boulder bc curva Axis 1 Axis 2 depth pebble cobble boulder bc bpi50 trtracks Axis 1 Axis 2 depth pebble cobble boulder bc aspect Axis 1 Axis 2 depth cobble boulder bc bpi50 curva trtracks Axis 1 Axis 2 B1 B2 B4 B3 B5 biotopes 14% 13% 9% 11% 6% 9% 7% 7% A B C D A B C D

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Tromsøflaket

Jennifer Dannheim1,2

Anne Helene Tandberg2 Pål Buhl-Mortensen2

Lene Buhl-Mortensen2

Margaret F.J. Dolan3

Børge Holte2

Macrozoobenthic production and productivity on the northern Norwegian shelf

Correspondence: Jennifer Dannheim

Alfred Wegener Institute Bremerhaven, Germany

[email protected]

Brey T (2001). Empirical relations in aquatic populations for estimation of production, productivity, mortality, respiration. Population dynamics in benthic invertebrates. A virtual handbook. Version 01.2. www.thomas-brey/science/virtualhandbook Buhl-Mortensen L, Buhl-Mortensen P, Dolan MFJ, Dannheim J, Bellec V, Holte B (2012). Habitat complexity and bottom fauna composition at different scales on the continental shelf and slope of northern Norway. Hydrobiologia 685: 191-219 Buhl-Mortensen P, Dolan MFJ, Buhl-Mortensen L (2009). Prediction of benthic biotopes on a Norwegian offshore bank using a combination of multivariate analysis and GIS classification. ICES J Mar Sci, 66: 2026-2032. Cusson M, Bourget E (2005). Global patterns of macroinvertebrate production in marine benthic habitats. Mar Ecol Prog Ser 297: 1-14. Dolan MFJ, Buhl-Mortensen P, Thorsnes T, Buhl-Mortensen L, Bellec VK, Bøe R (2009). Developing seabed nature-type maps offshore Norway: initial results from the MAREANO programme. Norw J Geol 89: 17-28. Gogina M, Glockzin M, Zettler ML (2010). Distribution of benthic macrofaunal communities in the western Baltic Sea with regard to near-bottom environmental parameters. 1. Causal analysis. J Mar Sys 79: 112-123. Nilsen M, Pedersen T, Nilssen EM (2006). Macrobenthic biomass, productivity (P/B) and production in a high-latitude ecosystem, North Norway. Mar Ecol Prog Ser 321: 67-77. Tandberg AH, Dannheim J, Jensen H, Dolan M, Bellec V, Buhl-Mortensen P, Holte B (2013): Spatial distribution of macrozoobenthic production on the northern Norwegian shelf. Arctic Frontiers, 20-25 January 2013, Tromsø, Norway

figure 1. Biotopes of Tromsøflaket (biotopes B1-B6) with typical species according to Buhl-Mortensen et al. (2009).

B1

B3

B2

B4

B5 B6

B1: muddy sediments in basins with pockmarks

B3: sandy sediments on broadly elevated areas

B4: sandy-gravelly sediments on broad slopes, with iceberg ploughmarks

B5: gravelly-sandy sediments on broad slopes, with iceberg ploughmarks

B6: sandy-gravelly sediments with cobbles on moraine ridges

Pelosina Asbestopluma

B2: sandy muddy sediments with iceberg ploughmarks, “sponge grounds”

calcic Foraminifera Aplysilla, Geodia

Bolocera

Stichopus

Phakellia Brachiopoda Antho Polymastia

Stylocordyla

Aphrodite

acknowledgements

We thank Arne Hassel, Hannu Koponen, Jon Rønning and Tom Alvestad for processing a large part of the samples.

3 2 1

environmental correlations

figure 4. Canonical correspondence analysis of production (g m-2 y-1; A: infauna, B: epifauna) and productivity (y-

1; C: infauna, D: epifauna) of biotopes (B1-B5). Arrow length indicate strength of relationships between biological data and terrain parameters, %-values = variance in species data explained by axis. Pebble, cobble and boulders are %-cover of bottom substrate. bc = backscatter (i.e. degree of bottom softness/hardness), bpi 50 = bathymetric position index (50 ≙ grid size, i.e. concave/convex bottom surface), curva = curvature (i.e. change rate of aspect), trtracks = trawl tracks (N/100m2).

background & methods Benthic animals produce food resources for organisms from higher trophic levels (fish, birds, mammals, and ultimately humans). The spatial distribution of benthic production and productivity are of direct relevance for the identification of essential feeding habitats (i.e. highly productive areas). This is important information for sustainable ecological management. In this context, the MAREANO programme aims to map the environment and fauna off the Norwegian coast by linking environmental parameters to the benthic ecosystem. In a case study, 6 different biotopes were defined from benthos sampled at the Tromsøflaket Bank (Barents Sea) (fig.1, Buhl-Mortensen et al. 2009). Species biomass (B) and abundance were recorded at each station (N = 23, grab and beam-trawl). Production (P) and productivity (P/B) was estimated by using the model of Brey (2001) and correlated with terrain/ environmental parameters from multibeam echosounder/ videos (see Buhl-Mortensen et al. 2009, Dolan et al. 2009).

results & conclusions Production was lowest in deep, muddy and sandy muddy biotopes (B1, B2; fig. 2) and highest on shallow sandy to gravel banks (B3, B4: mainly Mollusca & Brachiopoda). Production decreased with depth but increased towards harder bottoms (fig. 4; Nilsen et al. 2006, Cusson & Bourget 2005). Productivity of infauna was diametrically affected by depth and bottom structure (fig. 2, high P/B by Polychaeta). Bottom-trawling frequency was higher on soft sediments, thus trawling indirectly affected benthic production at the Norwegian shelf (fig. 4). At the spatial scales investigated, terrain parameters are poor descriptors of spatial variability of production and productivity (see low %-values in fig. 4). Other environmental variables such as organic input into the system and biological parameters (e.g. biodiversity, species life-span, mobility, feeding mode) seem to be locally more important than terrain parameters (Buhl-Mortensen et al. 2012, Gogina et al. 2010, Cusson & Bourget 2005, see also fig. 3 & table 1). At broader scales (e.g. landscape scale), terrain parameters might be more appropriate descriptors for mapping of production (fish-feeding habitats) for e.g. ecological management (Buhl-Mortensen et al. 2012, see talk of Tandberg et al. 2013, this conference).

biotope differences

prod

uctio

n (g

m-2

y-1

)

0

5

10

15

20

25

30

35

0

2

4

6

8

A AB B B B

B1 B2 B3 B4 B50.0

0.2

0.4

0.6

0.8

1.0

1.2

AAB B AB AB

B1 B2 B3 B4 B5pr

oduc

tivity

(y-1

)0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

B1 B2 B3 B4 B50.0

0.1

0.2

0.3

0.4

0.5

0.6

A AB AB B B B1 B2 B3 B4 B50.0

0.1

0.2

0.3

0.4

0.5

0.6

infauna epifauna

prod

uctio

n pr

oduc

tivity

figure 2. Average (± S.D.)

production (P, g m-2 y-1) and productivity (P/B,

y-1) of in- and epifauna from biotopes B1-B5.

Different letters indicate significant differences. Inserts

show results without the dominant

brachiopod Macandrevia cranium.

prod

uctio

n (%

)

0

20

40

60

80

100

PolychaetaPorifera

MolluscaCrustacea

BrachiopodaBryozoa

OthersAscidiaceaEchinodermata

B1 B2 B3 B4 B5

prod

uctio

n (%

)

0

20

40

60

80

100p

B1 B2 B3 B4 B5

interface feedersuspension feeder

subsurface deposit feedersurface deposit feeder

predator, active carnivorepredating, deposit feeding

parasiteomnivore, predator/scavenger

not defined unknown

figure 3. Contribution of

taxonomic groups (A: infauna, B:

epifauna) and feeding-guilds (C: infauna, D:

epifauna) to the total

production in biotopes B1-B5.

group/guild biotope differences

infauna Mollusca B3 ≠ all others Ascidiacea B3 ≠ B1,B5 Omnivore, predator/scavenger

B1 ≠ B5

suspension feeder B1 ≠ B3,B4,B5 interface feeder B1 ≠ B4,B5 epifauna predator B1 ≠ B4

table 1. Taxonomic groups and feeding guilds that differed significantly in production between biotopes B1-B5.

depth

cobble

boulder

bccurva

Axis 1

Axis

2

depth

pebblecobble

boulder

bc

bpi50

trtracks

Axis 1

Axis

2

depth

pebble

cobbleboulder

bcaspect

Axis 1

Axis

2

depth cobble

boulderbc

bpi50curva

trtracks

Axis 1

Axis

2

B1

B2 B4

B3 B5 biotopes

14%

13%

9%

11%

6%

9%

7%

7%

A B

C D

A B

C D

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