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Lischka, Silke; Ayón, Patricia; Pinedo Arteaga, Elda Luz; Schukat, Anna; Taucher, Jan; Kiko, Rainer; Hauss, Helena; Dorschner, Sabrina; Hagen, Wilhelm; Segura-Noguera, Mariona (2023): KOSMOS 2017 Peru mesocosm study: Biomass of zooplankton taxa determined by ZooScan [dataset]. PANGAEA, https://doi.org/10.1594/PANGAEA.947826, In: Lischka, S et al. (2022): Response of zooplankton community succession and trophic links to simulated upwelling conditions during a mesocosm experiment in the coastal upwelling off Callao Bay (Peru) in austral summer 2017 (KOSMOS 2017 Peru mesocosm study) [dataset bundled publication]. PANGAEA, https://doi.org/10.1594/PANGAEA.947833

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Abstract:
Biomass of zooplankton taxa in µg DM per liter as determined by ZooScan, using published area to dry weight relationships (Lehette & Hernandez-Leon 2009). Each data point is one sampling day (date) in one mesocosm (MK). For details on experimental treatments and sampling, refer to Bach et al. 2021 (https://doi.org/10.5194/bg-17-4831-2020) and Ayon et al. 2022 (https://doi.org/10.5194/bg-2022-157). Raw images are stored in https://ecotaxa.obs-vlfr.fr/prj/3784. All taxonomic categories are self-expanatory.
Keyword(s):
Abundance; Biomass; Gut fluorescence; Humboldt Current System; Lipid; mesocosm experiment; Oxygen Minimun zone; Stable isotopes; Zooplankton
Funding:
Agence Nationale de la Recherche (ANR), grant/award no. ANR-19-MPGA-0012: Make Our Planet Great Again grant
Federal Ministry of Education and Research (BMBF), grant/award no. 03F0813A: Küstennahe Auftriebsgebiete CUSCO: Auswirkungen geänderter Auftriebsintensitäten auf Struktur, Funktion und Produktivität pelagischer Nahrungsnetze im peruanischen Humboldt-Auftriebsgebiet
German Research Foundation (DFG), grant/award no. 27542298: Climate - Biogeochemistry Interactions in the Tropical Ocean
German Research Foundation (DFG), grant/award no. RI-598/9-1: Leibniz Award 2012
Coverage:
Latitude: -12.055000 * Longitude: -77.235000
Date/Time Start: 2017-02-26T00:00:00 * Date/Time End: 2017-04-14T00:00:00
Event(s):
KOSMOS_2017_Peru * Latitude: -12.055000 * Longitude: -77.235000 * Date/Time Start: 2017-02-23T00:00:00 * Date/Time End: 2017-04-10T00:00:00 * Campaign: KOSMOS_2017 (KOSMOS Peru) * Method/Device: Mesocosm experiment (MESO)
Comment:
For more details or other computations please contact Helena Hauss.
Parameter(s):
#NameShort NameUnitPrincipal InvestigatorMethod/DeviceComment
Sample code/labelSample labelLischka, Silke
Mesocosm labelMeso labelLischka, Silke
DATE/TIMEDate/TimeLischka, SilkeGeocode
Sample volumeSamp vollLischka, Silke
Corycaeidae, biomass, dry massCorycaeidae biom dmµg/lLischka, Silke
Spionidae, biomass, dry massSpionidae biom dmµg/lLischka, Silke
Noctilucales, biomass, dry massNoctilucales biom dmµg/lLischka, Silke
Polychaeta, biomass, dry massPolychaeta biom dmµg/lLischka, Silke
Diatoms, centrales, biomass, dry massDiatoms centrales biom dmµg/lLischka, Silke
10 Acartia spp., biomass, dry massAcartia spp. biom dmµg/lLischka, Silke
11 Copepoda, biomass, dry massCopepoda biom dmµg/lLischka, Silkelike
12 Paracalanus spp., biomass, dry massParacalanus spp. biom dmµg/lLischka, Silke
13 Copepoda, nauplii, biomass, dry massCopepoda naup biom dmµg/lLischka, Silke
14 Hemicyclops spp., biomass, dry massHemicyclops spp. biom dmµg/lLischka, Silke
15 Ceratium spp., biomass, dry massCeratium spp. biom dmµg/lLischka, Silke
16 Tintinnida, biomass, dry massTintinnida biom dmµg/lLischka, Silke
17 Zooplankton, biomass, dry massZoopl biom dmµg/lLischka, Silkemulitple organisms
18 Calanoida, biomass, dry massCalanoida biom dmµg/lLischka, Silke
19 Diatoms, centrales, biomass, dry massDiatoms centrales biom dmµg/lLischka, Silkechain
20 Branchiostoma spp., biomass, dry massBranchiostoma spp. biom dmµg/lLischka, Silke
21 Bivalvia, biomass, dry massBivalvia biom dmµg/lLischka, Silke
22 Harpacticoida, biomass, dry massHarpacticoida biom dmµg/lLischka, Silke
23 Cnidaria, biomass, dry massCnidaria biom dmµg/lLischka, Silke
24 Cyclopoida, biomass, dry massCyclopoida biom dmµg/lLischka, Silke
25 Oncaeidae, biomass, dry massOncaeidae biom dmµg/lLischka, Silke
26 Gastropoda, biomass, dry massGastropoda biom dmµg/lLischka, Silke
27 Copepoda, biomass, dry massCopepoda biom dmµg/lLischka, Silkeegg_sac
28 Crustacea, larvae, biomass, dry massCrustacea larv biom dmµg/lLischka, Silke
Status:
Curation Level: Enhanced curation (CurationLevelC)
Size:
2430 data points

Data

Download dataset as tab-delimited text — use the following character encoding:


Sample label

Meso label

Date/Time

Samp vol [l]

Corycaeidae biom dm [µg/l]

Spionidae biom dm [µg/l]

Noctilucales biom dm [µg/l]

Polychaeta biom dm [µg/l]

Diatoms centrales biom dm [µg/l]
10 
Acartia spp. biom dm [µg/l]
11 
Copepoda biom dm [µg/l]
(like)
12 
Paracalanus spp. biom dm [µg/l]
13 
Copepoda naup biom dm [µg/l]
14 
Hemicyclops spp. biom dm [µg/l]
15 
Ceratium spp. biom dm [µg/l]
16 
Tintinnida biom dm [µg/l]
17 
Zoopl biom dm [µg/l]
(mulitple organisms)
18 
Calanoida biom dm [µg/l]
19 
Diatoms centrales biom dm [µg/l]
(chain)
20 
Branchiostoma spp. biom dm [µg/l]
21 
Bivalvia biom dm [µg/l]
22 
Harpacticoida biom dm [µg/l]
23 
Cnidaria biom dm [µg/l]
24 
Cyclopoida biom dm [µg/l]
25 
Oncaeidae biom dm [µg/l]
26 
Gastropoda biom dm [µg/l]
27 
Copepoda biom dm [µg/l]
(egg_sac)
28 
Crustacea larv biom dm [µg/l]
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M2_2017040822017-04-0824.062500.3770.0000.0580.00000.0002.74215.5830.01711.96100.0191.2223.82600.0000.0000.00001.3248.1660.00000.000
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M3_2017031032017-03-1096.250000.6510.3920.00016.08302.5511.73711.8390.01313.48600.0013.3962.92800.0000.0610.00001.4520.3140.00000.000
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M4_2017030742017-03-0748.125000.1662.0210.00016.42902.3915.40133.4160.14025.31300.72614.80011.64100.0000.0570.00002.1930.6360.15900.000
M4_2017031042017-03-1048.125000.2630.5160.00016.43005.0541.21622.9670.00610.86600.1795.7553.79400.0000.0000.00001.2010.3460.00002.348
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M4_2017032142017-03-2124.062500.0310.0000.0001.85300.1340.7677.0260.0003.68400.0020.2802.13200.0000.0000.00000.1680.0390.00000.000
M4_2017032742017-03-2724.062500.2700.0000.0002.36800.0001.0589.7680.0048.44100.0193.9640.56500.0000.0000.00000.5340.2630.00000.000
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M4_2017040842017-04-0824.062500.0650.3010.0000.00000.4264.1416.6520.0434.92100.0080.8795.02800.0000.0290.00000.5170.4790.138054.512
M4_2017041442017-04-1424.062500.1190.0000.0000.04700.6263.8766.5980.0042.61900.0150.0005.05300.0000.0000.00000.9110.1400.00000.000
M5_2017022652017-02-2648.125000.4690.1050.0000.07200.0743.0784.6840.0176.77500.0063.0883.50300.0000.0130.00003.5989.1740.00900.000
M5_2017030552017-03-0524.062500.0471.5060.0093.47800.6802.8087.4980.0572.49600.3071.8854.93400.0000.0000.00000.7082.9320.00000.000
M5_2017030752017-03-0724.062500.6732.5490.00023.24800.4613.41616.1480.05239.14400.0107.7332.52400.0000.0100.00001.9242.1560.00000.000
M5_2017031052017-03-10192.500000.0190.2150.2843.71100.7490.5664.9330.0037.30300.0152.4181.29200.0000.0020.02500.0950.1090.02302.756
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