The following working document is just a technical analysis of the WGBAST database. It uses different sources, ICES vocabulary, the stock annex (ICES 2021), to analyse the structure of the wgbast database before assessing whether we could integrate it in a single database (wgnas, wgbast, wgeel) in the DIASPARA project. This document does not engage the WGBAST it’s to try to get how this works. At this stage answers were kindly provided by Tapani. This document is listed as a task there github link to diaspara
Spatial units
River stock
“river stock” correspond salmon that belongs to a particular river. In most cases, river stocks most likely correspond to biological populations which lend support for this level of division from a conservation genetic perspective. However, it should be noted that some larger rivers may harbour several salmon subpopulations that are genetically separated spatially and/or temporally (Lind et al. 2015) (ICES 2021).
Salmon population
According to the results of Säisä et al. (2005), there are three main groups of salmon populations in the Baltic Sea: 1) Gulf of Bothnia populations, 2) populations in southern Sweden, and 3) eastern populations (Gulf of Finland and eastern Main Basin). These groups or lineages are assumed to mirror three distinct post-glacial colonization events. About 5% of the total genetic diversity of the Baltic salmon is explained by differences between rivers within groups, whereas 6% is explained by differences between the lineages (Säisä et al., 2005) (ICES 2021).
Assessment units within the Baltic Sea area
Within the Baltic Sea area, currently six different assessment units (AUs) have been established (Figure A.1.1.1). The grouping of rivers within an assessment unit is based on management objectives and biological and genetic characteristics of the river stocks contained in a unit. The partition of rivers into assessment units needs to make sense from a management perspective. River stocks of a particular unit are believed to exhibit similar migration patterns at sea. It can therefore be assumed that they are subjected to the same sea fisheries, experience the same exploitation rates and are affected by management of sea fisheries in the same way. In addition, the genetic variability between river stocks of an assessment unit is smaller than the genetic variability between river stocks of different units (see above). Although the rivers of assessment units 5 and 6 are relatively small in terms of their production capacity compared with rivers in the other assessment units, they are very important from a conservation perspective because of their unique genetic background. The six assessment units in the Baltic Sea consist of:
1 ) Northeastern Bothnian Bay river stocks, starting at Perhonjoki up till the river Råneälven.
2 ) Western Bothnian Bay river stocks, starting at Lögdeälven up to Luleälven.
3 ) Bothnian Sea river stocks, from Dalälven up to Gideälven and from Paimionjoki up to Kyrönjoki.
4 ) Western Main Basin river stocks, i.e. southeastern part of Sweden.
5 ) Eastern Main Basin river stocks, i.e. rivers in Estonia, Latvia and Lithuania.
6 ) Gulf of Finland river stocks. Wild river stocks belonging to each assessment unit are listed in the next section(ICES 2021).
Figure 1: Grouping of salmon river stocks in six assessment units in the Baltic Sea. The genetic variability between river stocks of an assessment unit is smaller than the genetic variability between river stocks of different units. In addition, the river stocks of a particular unit exhibit similar migration patterns. Wild salmon rivers (dark blue), mixed salmon rivers (light blue), reared salmon rivers (red), river stretches not accessible for salmon (grey). (source wgbast stock annex)
QUESTION WGBAST
Could we have access to a gis of this map (river type) to create the referentials in WP3.1 habitat
GUID Key
463 7823c0a9-eeba-4766-9823-4578026786d2 RiversAndCatchments
Description
463 National Rivers and Catchment Areas
LongDescription
463 Codes for fresh water bodies as defined by national authorities, preceeded by the country code.
Modified
463 2023-09-21
Table 1: = ICES Vocab for River and Catchments (RiversAndCatchments)
(a) RiverAndCatchments, 10 first lines
GUID
Key
Description
LongDescription
Modified
Deprecated
58e80ffa-4f0f-41f8-8c2e-5b4f485d4852
DK0100
Pissebæk
NA
2023-07-11
FALSE
491a52c2-a2f4-487d-a009-fd43f16a05a8
DK0101
Møllebæk ved Vang
NA
2023-07-11
FALSE
874181b9-e3d0-4282-a9ab-0ad77371ffba
DK0101a
Askebæk
NA
2023-07-11
FALSE
0cb3f7c1-e541-4da2-8f38-6879e1faac64
DK0106
Ormebæk
NA
2023-07-11
FALSE
92823a74-dd64-4b62-b970-da0f783975af
DK0107
Onsbæk
NA
2023-07-11
FALSE
b8d456d6-1b36-4d5a-9a1c-afea66393979
DK0110
Risebæk
NA
2023-07-11
FALSE
3bf70f6a-305f-46fc-9761-e7a2f9fe3a61
DK0113
Hullebæk
NA
2023-07-11
FALSE
a25f0904-fe7c-4ed8-8862-d651817277ab
DK0117
Munkebæk
NA
2023-07-11
FALSE
4f914977-11ed-4529-90ba-6959caeef57d
DK0117a
Stangebæk
NA
2023-07-11
FALSE
98ac4f1d-2220-4c40-a27b-3e8f9a4ae292
DK0118
Melå
NA
2023-07-11
FALSE
(b) This row has a problem
GUID
Key
Description
LongDescription
Modified
Deprecated
NA
NA
NA
NA
NA
NA
:----
:---
:-----------
:---------------
:--------
:----------
ICES
Note the url in this table (Table 1): https://opendata-download.smhi.se/svar/SVAR_Basprodukter_2016_6.pdf is no longer accessed anywhere
It does not seems as if there is a hierarchy in these geographic units.
ICES
Just for information there is a line with NA ?
TODO
We’ll have to reconcile this table with GIS, we have to if there is a GIS map somewhere in ICES.
TODO
link ICES codes in our referential (which will be a map polygon in postgis).
NOTE
River stock, assessment units and rivers align with the envisioned db hierachical structure for spatial data.
Category of rivers
Table 2: Classification criteria for wild, mixed, reared and potential salmon rivers in the Baltic Sea (ICES 2021)
Category of salmon river
Management plan for salmon stock in the river
Releases
Criteria for wild smolt production
Wild
Self-sustaining
No continuous releases
>90% of total smolt prod.
Mixed
Not self-sustaining at these production levels
Releases occur
10–90% of total smolt prod.
Reared
Not self-sustaining
Releases occur
<10% of total smolt prod.
Potential leading to category wild
Lead to self-sustaining river stock
Releases occur during re-establishment
Long-term >90% wild smolt prod.
Potential leading to category mixed
Not self-sustaining river stock
Releases occur
Long-term 10–90% wild smolt prod.
QUESTION WGBAST
The rivers are stored in the db, but these details (Table 2) might vary within one basin (see Figure 1), maybe this information should be stored alongside the referential as a separate table assessing the category of river but also including a period, as the status might change over time ?
part I - Fishery
Figure 2: Catches of salmon in % of TAC in 1993-2023. For years 1993–1997 (1993–1998 for Gulf of Finland) it is not possible to divide the total reported catch into commercial and recreational catches. (source (ICES 2024))
NUMB states the number of occasions when seal damage was reported by commercial fishermen (SAL and TRS are combined)
NA
NA
NA
NA
NA
NA
EE
2021
0
Year
28
22-31
200
C
SEAL
MIS
NA
NA
NA
33
LOG
NA
NUMB states the number of occasions when seal damage was reported by commercial fishermen (SAL and TRS are combined)
NA
NA
NA
NA
NA
(c) First two entries where species = SAL&TRS
species
country
year
time_period
tp_type
sub_div
sub_div2
sub_div3
fishery
f_type
gear
effort
weight
w_type
numb
n_type
river
notes
w_ci
n_ci
gear2
subdiv_ic
hyr
SAL&TRS
EE
2023
0
YR
28
22-31
200
C
SEAL
FYK
NA
NA
NA
2
LOG
NA
NUMB states the number of occasions when seal damage was reported by commercial fishermen (SAL and TRS are combined)
NA
NA
NA
NA
NA
SAL&TRS
EE
2023
0
YR
28
22-31
200
C
SEAL
GNS
NA
NA
NA
66
LOG
NA
NUMB states the number of occasions when seal damage was reported by commercial fishermen (SAL and TRS are combined)
NA
NA
NA
NA
NA
QUESTION WGBAST : species
Some ‘NA’ are character (11 rows) (Table 4) for EE. This is for seal damage. Is there a need for this ? It’s not reported the same way every year ?
ANSWER WGBAST
Estonia cannot distinguish whether seal damaged catch is SAL or TRS. Split to the species could base on expert elicitation but has remained undone.
Catch habitat
Countries participating in the Baltic salmon fishery are asked to deliver catch data of salmon and sea trout. Catches are given by economic zone, ICES subdivision, as well as type of fishery separated by offshore, coastal and river(ICES 2021).
Catches are divided into four different fishing area categories: River (R), Coastal (C), Open sea (O) and Sea (S). Sea (S) is only used when it is not possible to separate between coast and open sea. There is no standardized way of distributing sea catches into either of the two WGBAST fishing area categories Coast (C) or Open sea (O). For the commercial fisheries, a majority of the countries divide the commercial landings on fishing area depending on which gear that has been used, where longlines and driftnets are categorised as open sea (O) and trapnets as coastal (C) (ICES 2021).
Exceptions:
In Latvia, the distribution is depending on how the catches are reported into the official catch statistics. Here catches from vessels carrying EU logbook are categorised as open sea (O), whereas catches from vessels reporting in the national logbook system are categorised as coastal (C). Latvian vessels that are active 2 nautical miles (NM) or more off the coast are obliged to use EU logbook.
In Lithuania, catches outside territorial water, i.e. 12 NM or more from the coast, are categorised as open sea (O). Inside this border catches are categorised as coastal (C).
In Poland, length of the vessel defines if the catch is coastal (C) or open sea (O). Catches from vessels 10 meters or less are coastal (C) and catches from vessels longer than 10 meters are categorised as open sea (O).
Latvia and Lithuania are the only two countries directly using the actual geographical position when categorising the catches as either coastal (C) or open sea (O). For the recreational fisheries, all countries define trolling as open sea (O) whereas catches from other gears are defined as coastal (C) (ICES 2021).
Table 5: Habitat and fishery
(a) Habitat type in column `fishery` in wgbast catch database. Rows correspond to the values in sub_div, columns to habitat type
C
O
R
NA
200
108
412
50
14
21
3
0
0
0
22
105
428
0
64
22-32
6
0
0
0
23
76
436
0
0
24
407
954
2
80
25
665
1296
118
0
26
854
1086
190
0
27
426
161
54
0
28
1933
351
320
0
29
1167
123
38
0
30
1138
112
530
0
300
110
51
51
0
31
955
7
980
0
32
1375
212
268
0
NA
0
0
0
12
(b) Contingency table for `sub_div`and `sub_div2` including NA
0
21
22-31
22-32
32
200
0
0
584
0
0
21
0
3
0
0
0
22
0
0
597
0
0
22-32
0
0
0
6
0
23
0
0
512
0
0
24
0
0
1443
0
0
25
0
0
2079
0
0
26
0
0
2130
0
0
27
0
0
641
0
0
28
0
0
2603
0
1
29
0
0
1327
0
1
30
0
0
1780
0
0
300
0
0
212
0
0
31
0
0
1942
0
0
32
0
0
0
0
1855
NA
12
0
0
0
0
(c) Contingency table for `sub_div2`and `sub_div3` including NA
0
200
21
22-32
30
300
31
32
0
12
0
0
0
0
0
0
0
21
0
0
3
0
0
0
0
0
22-31
0
11916
0
0
54
3783
97
0
22-32
0
0
0
6
0
0
0
0
32
0
0
0
0
0
0
0
1857
Figure 3: Double dekker plot showing the importance of habitat type per species and subdivision. Cell importance according to the number of rows
The values for habitat are : O, C, R, NA there are 170 NA values in the database. 200=MainB(22-29); 300=GoB(30-31). :::{.callout-note appearance=“simple”} ## TODO Create geographical grouping of areas + use ICES subdiv3 :::
QUESTION WGBAST : habitat
In the stock annex there is a mention to sea S but it does not seem to be present in the database ?
The name of the column fisheryis not very explicit, would the use of habitat_type be more in line with data ?
Can you confirm that 200 is 22-31 and not 22-29, and that 300 is 30-31 ?
ANSWER WGBAST
In the stock annex there is an old notation. Today we use “O” (open sea) instead of “S”.
The best match for fishery habitat in ICES vocabulary seems to be WLTYP.
Transitional water (Tidal) - significant tide and reduced salinity
NA
2024-09-10
FALSE
ICES vocabulary for water types (stations)
QUESTION ICES : vocabulary for habitat
Should we use this vocabulary for catch habitat ?
ANSWER WGBAST
I agree, we could use ICES vocabulary for catch habitat (i.e MO, MC, C and CR/FW)
QUESTION WGBAST: 4 nm from the baseline ?
Currently the definition in ICES vocab is WFD coastal water (C) or MC (Marine water (coast)) Marine water within 4 nm from the baseline. It seems that there are country difference in the interpretation of coastal or marine 2 10 12, so what do we choose ?
ANSWER WGBAST
In the WGBAST thinking we have only one coastal water category independently from the distance to the baseline. All trapnet fishing is considered coastal even though fishing sites may varies from very close to shoreline out to beyond base line. At the Finnish coast baseline goes far out at sea in some places.
NOTE WGBAST
Currently subdivisions are used but for some historical data it is not possible to separate ICES subdivisions, so for these historical data these data are lumped together.
Catches type
Catches are further classified as commercial, recreational, discard, and seal damage(ICES 2021). The excel tables gives more types than the stock annex : commercial=COMM, recreational=RECR, discard=DISC, sealdamage=SEAL, unreported=UNRP, ALV=released alive back in water.
Table 7: Frequency of catches classification f_type in the database.
f_type
Freq
ALV
537
BMS
77
BROOD
39
COMM
12920
DISC
334
RECR
2473
SEAL
980
NA
368
QUESTION WGBAST: what are ‘BMS’ and ‘BROOD’ ?
There is a difference between the stock annex, the excel table and the database. The stock annex lists four types COMM, RECR, DISC and SEAL. The excel also describes ALV, UNRP which does not exist. The db has two additional types BROOD and BMS which are reported neither in the stock annex nor in the excel table. These correspond to very few lines. Do you want to keep those values? Do you agree that UNRP should not be in the excel description ?
ANSWER WGBAST
The Stock annex seems to miss part of catch categories. * BROOD means broodstock fishery and BMS is catch of undersized salmon (below minimum landing size, landing obligation). * ALV is caught fish that has been releases back to sea/river alive. UNRP is unreported catch. * At some point intention was to include unreported catch estimates to the catch data but has not realised so far. Might be OK to drop from the excel description.
NOTE
There are 368 NA values for f_type.
Source of fishery data
Logbooks provide primary information on catches taken on board the vessels, where real count and weight estimates are normally difficult to obtain. The catch statistics in different countries are obtained by combination of data included in logbooks, landing declarations, first sales notes and fisheries companies catch reports. From 2005 EU type logbooks were implemented in the new member states Latvia, Estonia, Poland and Lithuania (ICES 2021).
In the excel table the possible values are indicated as : logbook=LOG, extrapolated=EXT, estimated=EST, expert evaluation=EXP.
The ICES vocab DataSourceOfScientificWeight seems to provide the closest match with these data, however it lacks extrapolated, estimated.
Table 8: Catches according to source of capture and outcome f_type in the WGNAS fisheries database.
(a) Frequency of each type in the database including NA
n_type
Freq
EST
944
EXP
28
EXT
335
EXV
1295
GST
9
LOG
14117
NA
1000
(b) Contingency table for `n_type`and `f_type`including NA
ALV
BMS
BROOD
COMM
DISC
RECR
SEAL
NA
EST
118
0
0
82
0
742
0
2
EXP
0
0
0
0
0
28
0
0
EXT
0
0
0
196
0
48
91
0
EXV
391
0
0
15
14
873
2
0
GST
0
0
0
1
0
8
0
0
LOG
28
73
39
12101
315
655
882
24
NA
0
4
0
525
5
119
5
342
Table 9: ICES vocabulary for DataSourceOfScientificWeight.
DataSourceOfScientificWeight table
GUID
Key
Description
LongDescription
Modified
Deprecated
7eb92e58-87b0-4f61-9a3f-54c07aaaa3f1
Combcd
Combination of census data
Combination of census data
2021-12-22
FALSE
7c5c1d9d-7e4a-4006-b5db-f6ecbf0ceba0
ExpertEval
Expert evaluation
NA
2022-06-28
FALSE
8495beb2-2e75-47c8-ba42-d2deb881df6e
Logb
Logbook
Logbook
2021-12-22
FALSE
4b90937e-f2cc-4656-b6fe-41e7e22f21ff
Othdf
Other declarative forms
Other declarative forms
2021-12-22
FALSE
d25929d1-c40c-4bd9-abe0-346955226e8f
Saln
Sales notes
Sales notes
2021-12-22
FALSE
fc49c8ea-85b5-4b99-aafe-741ee4a6998f
Sampld
Sampling data
Sampling data
2021-12-22
FALSE
QUESTION / ANSWERS WGBAST
Could you provide definitions of extrapolated and estimated. ?
All GST -values should be updated as “expert evaluated”.
The source of fishery data might partially correspond to the vocab dataSourceOfScientificWeight (Table 9). At least there is a Logbook, Expert evaluation, any idea if something in this vocab might correspond to extrapolated or estimated ?
The “Combcd” might do best for these.
Do you want to allow NA values there ?
No, I don’t think so. Better to give a value from vocab here.
Would you treat things differently if tables for Baltic TRUTTA and SALMON were separated ?
No, not to my understanding
NOTE
w_typeand n_type source of data are similar and will be treated in the same column in the database There are 876 NA values for w_type.
Table 10: Catches according to data source for weight w_type in the WGNAS fisheries database.
(a) Frequency of each type datasource for weight in the database including NA
w_type
Freq
EST
893
EXP
28
EXT
495
EXV
1218
GST
30
LOG
14188
NA
876
(b) Contingency table for `n_type`and `w_type`including NA
EST
EXP
EXT
EXV
GST
LOG
NA
EST
679
0
2
8
18
181
56
EXP
0
28
0
0
0
0
0
EXT
2
0
256
0
0
75
2
EXV
51
0
0
1210
0
0
34
GST
1
0
0
0
8
0
0
LOG
106
0
237
0
0
13704
70
NA
54
0
0
0
4
228
714
gear
TODO analyse gear according to ftype
Part II. Electrofishing and river data
The data are read from the WGBAST_2024_Young_fish xlsx file. This file has two sheets. The number of young fish is the number of fish released in water (stocking), and the smolt corresponds to smolts counts.
smolts <- readxl::read_xlsx(file.path(datawd, "WGBAST_2024_Young_fish_26-02-2024.xlsx"), sheet ="number of wild smolts")young_fish <- readxl::read_xlsx(file.path(datawd, "WGBAST_2024_Young_fish_26-02-2024.xlsx"), sheet ="numb of young fish")smolts <- janitor::clean_names(smolts)young_fish <- janitor::clean_names(young_fish)smolts %>%skim()
R1168C15 3,4 (probably two values….) probably need correction
Electrofishing data are obtained along with smolt counts at rivers Tornionjoki, Simojoki, Åbyälven, Rickleån, Sävarån, Ume/Vindelälven, Öreälven and Lögdeälven (Assessment unit 1-3), Mörrumsån, Emån and Testeboån (AU 4) to estimate smolt production based on parr density in electrofishing.
Annual number of sampling sites electrofished
Estimated density of age 0+
1+
>1+ parr.
The number of sampling sites is used as a measure of precision of the parr density.
Question WGBAST
There must be a dataset of electrofishing somewhere. This should be part of the template db on electrofishing, can we have access ?
Would it be usefull to start from a full db of electrofishing data ?
ANSWER WGBAST
There is an input dataset for the river model. This has been compiled from the national data set for 17 rivers (that are included in the full life history model at present). In other words that dataset is missing AU5-6 rivers, which parr densities and the corresponding smolt production estimates are presented in the WGBAST report tables only. Atso knows more about this.
Yes, I think this would be good. Would it be possible to apply same data construction for SAL, TRS and EEL ?
Yes we think so and will try
Species
Table 11: Frequencies of species type in the young fish and smolt database.
smolts
young_fish
SAL
1391
2883
TRS
1087
4831
Country
Table 12: Countries in the young fish and smolt database.
smolts
young_fish
DE
0
337
DK
72
302
EE
266
345
EU
0
15
FI
110
3100
LT
429
1098
LV
541
378
PL
0
954
RU
538
154
SE
522
1031
Time
Table 13: Number of values per year and sheet in the database
smolts
young_fish
1984
0
13
1985
0
27
1986
0
24
1987
16
69
1988
16
88
1989
16
155
1990
16
152
1991
16
162
1992
16
141
1993
17
139
1994
17
145
1995
17
155
1996
17
160
1997
17
154
1998
17
160
1999
17
159
2000
29
165
2001
62
154
2002
75
193
2003
77
194
2004
84
223
2005
87
248
2006
96
271
2007
115
249
2008
115
266
2009
123
282
2010
123
234
2011
93
283
2012
110
276
2013
109
343
2014
110
275
2015
110
306
2016
108
292
2017
109
286
2018
107
235
2019
105
268
2020
88
249
2021
53
257
2022
55
262
2023
57
0
2024
50
0
2025
13
0
NOTE
Years distributed from 1984, nothing special (Table tbl-youngfishdbdbtime), this db does not use time periods lower than year.
Geography
Table 14: Geographical units in the young fish and smolt database
(a) Rivers (note that some labels seem to be duplicated in the database)
smolts
young_fish
81
0
4
83
0
1
Åby älv
39
0
Age
18
0
Aģe
3
0
Agluona
0
13
Ähtävänjoki
0
2
Ahvenanmaa
0
7
Ahvenanmaa, Saaristo
0
4
Aitra
0
1
Akmena
0
25
Akmena-Dane
18
0
Akmena - Danė
2
0
Aland
0
137
Åland
0
6
Alantas
0
6
Amarnia
0
9
Amata
0
8
Ancia
0
7
Ančia
0
3
Anyksta
0
1
Armona
2
9
at sea
0
389
Aurajoki
0
97
Barta
40
1
Bārta
4
0
Bartuva
20
0
Bauda
0
18
Bebirva
0
8
Beke
0
1
Beste
0
10
Bezdone
0
10
Bezdonė
0
2
Blotnica
0
13
Błotnica
0
1
Bokenau
0
4
Bornholm
18
3
Brasla
0
11
Brazuole
0
17
Bražuole
0
1
Bražuolė
0
1
Bremena
0
4
Byske älv
39
0
Bystryi
16
0
Cirvija
0
4
Curau
0
1
Czarna Wda
0
19
Czerwona
0
14
Damshäger Bach
0
1
Darba
0
5
Daugava
24
77
Debosznica
0
8
Dratvainys
0
4
Dratvinys
0
6
Dratvuo
0
2
Dubysa
40
60
Duksta
2
20
Dūkšta
0
3
Egluona
0
2
Eleruona
0
1
Emån
38
0
Eurajoki
0
31
Ezeruona
0
2
Farver
0
2
Farver Au
0
7
Fiskarsinjoki
0
3
Funen
18
0
Gauja
45
93
Gauja (Vizla)
0
1
Gladyshevka
33
10
Grabuosta
0
11
Grimsnisau
0
8
Haaler Au
0
1
Habernis
0
9
Halikonjoki
0
4
Hanshagener
0
1
Hanshagener Bach
0
2
Hanshäger Bach
0
6
Hellbach
0
3
Hirvijoki
0
1
Hounijoki
0
7
Huttener
0
2
Huttener Au
0
4
Hüttener Au
0
2
Iijoki
0
174
Ilolanjoki
0
15
Ingarskila
0
1
Ingarskilajoki
0
2
Ingarskilanjoki
0
1
Irbe
45
0
Irtuona
0
6
Jägala
21
19
Jarubynas
0
1
Jevenau
0
1
Jukkola east
14
0
Jukkola middle
14
0
Jukkola west
14
0
Juodupis
0
10
Jura
20
47
Jūra
0
7
Jusine
2
12
Jusinė
0
3
Jutland
18
0
Juustilanjoki
0
1
Kaakamojoki
0
9
Kaberla oja
0
1
Kåge älv
18
0
Kalajoki
0
39
Kalix älv
39
0
Kälviänjoki
0
1
Karjaanjoki
0
25
Karvianjoki
0
106
Keila
25
0
Kello-oja
14
0
Kemijoki
0
111
Kena
1
32
Khabolovka
17
0
Kiiminkijoki
0
203
Kisko-Perniönjoki
0
5
Kisko-Perniönki
0
2
Kiskonjoki
0
2
Kiskonjoki-Perniönjoki
0
13
Kisupe
16
0
Klosterbach
0
7
Köhntop
0
7
Köhntop/Schiefe Möhn
0
2
Kohtla
0
2
Koivistonpuro
14
0
Koja, Letiza, Skervelis
0
1
Kokemäenjoki
0
105
Köppernitz
0
1
Korleputer Bach
0
1
Koseler
0
2
Koseler Au
0
7
Koskenkylänjoki
0
47
Koskenkylänjoki eli
0
1
Krazante
0
7
Kražantė
0
6
Kriesebyau
0
10
Kronsbek
0
10
Krusau
0
6
Kruunupyynjoki
0
6
Kuivajoki
0
47
Kulse
0
9
Kulšė
0
3
Kunda
25
0
Kuninkoja
0
1
Kymijoki
32
178
Kyröjoki
0
2
Kyrönjoki
0
27
Laajoki
0
25
Laihianjoki
0
3
Lakaja
0
8
Langballigau
0
8
Lange Rie
0
7
Lapinjoki
0
1
Lapise
0
6
Lapišė
0
3
Lapuanjoki
0
2
Lapväärtinjoki
0
76
Laukysta
0
18
Leba
0
78
Lestijoki
0
90
Liela Jugla
0
12
Lielā Jugla
0
1
Lielupe
0
17
Limingoja
0
6
Lindaubach
0
6
Lindaubach (Güderotter Au)
0
2
Linde
0
2
Liolinga
0
5
Lippingau
0
2
Ljungan
39
0
Lögde
39
0
Loiter
0
2
Loiter Au
0
16
Lomena
0
10
Loo
0
2
Loobu
25
26
Lososinka
14
0
Loviisanjoki
0
8
Luga
41
15
Luhnau
0
1
Lukne
0
3
Luknė
0
3
Luoba
0
7
Lupawa
0
42
Lusis
0
4
Maalahdenjoki
0
2
Maibach
0
7
Malinovka
14
0
Mäntsäläjoki
0
3
Maza Jugla
0
14
Melnichnyi
14
0
Melnsilupe
16
0
Mera
23
13
Merenkurkku
0
1
Merkys
0
9
Mildenitz
0
4
Minija
34
34
Minijos bas
0
1
Mišupis
0
1
Mlinovka
1
0
Mörrumsån
38
0
Mühlbach
0
1
Muke
0
4
Muse
2
30
Musė
0
3
Mustijoki
0
36
MV
0
13
Mynäjoki
0
20
Narva
0
16
Närvijoki
0
1
Nelma
18
0
Nemencia
2
3
Nemenčia
0
6
Neris
43
59
Neris B
0
2
Neva
19
13
Neveza
0
9
Notkopuro
14
0
Nova jogi
0
2
Odra
0
114
Olhavanjoki
0
13
Oravaistenjoki
0
2
Öreälv
39
0
Osterbek
0
6
Other
2
0
other rivers
2
0
others
8
0
Others
11
0
Oulujoki
0
123
Paimionjoki
0
22
Parnu
1
1
Pärnu
14
23
Parseta
0
93
Pasleka
0
34
Peipiya
0
2
Pelysa
0
8
Penttilan-oja
14
0
Perämeri
0
2
Perhojoki
0
15
Perhonjoki
0
59
Persoksna
2
15
Peršoksna
0
2
Peršokšna
0
2
Peršokšnos
0
1
Peschanaya
16
0
Peterupe
40
0
Pēterupe
5
0
Petrovka
18
0
Piasnica
0
10
Piehinkijoki
0
12
Pirita
26
13
Piteälven
13
0
Plastaka
0
15
Plaštaka
0
2
Polchow
0
9
Porvoonjoki
0
60
Pregola
18
0
Privetnaya
14
0
Prochladnaja
18
0
Pudisoo
0
16
Pulverbek
0
8
Purtse
16
49
Pyhajogi
0
18
Pyhäjoki
0
62
Raaseporinjoki
0
1
Råne älv
39
0
Ratnycia
0
2
Rauna
0
2
Reda
0
60
Rega
0
82
Reppeliner
0
1
Reppeliner Bach
0
6
Rickleån
39
0
Riva
18
0
Roja
0
9
Rompotinpuro
14
0
Rosengartener
0
1
Rosengartener Beek
0
2
Saaristomeri
0
3
Saida
0
11
Saide
0
1
Saka
45
0
Salaca
45
4
Salcia
0
4
Saltuona
0
2
Saria
0
7
Sarios
0
1
Sata
0
7
Šata
0
1
Sausdravas
0
2
Sävarån
39
0
Schwartau
0
3
Schwastrumer
0
2
Schwentine
0
2
Schwinge
0
9
Sealand
18
0
Seleznevka
15
0
Selja
25
24
Selkämeri
0
5
Serga
16
0
Serksne
0
10
Šerkšnė
0
3
Sesuola
0
4
Šešuola
0
3
Sesuvis
0
14
Sešuvis
0
1
Šešuvis
0
1
SH
0
33
Siesartis
24
30
Siikajoki
0
72
Simo
39
0
Simojoki
0
84
Sipoonjoki
0
4
Sirvinta
4
26
Širvinta
0
6
Sista
18
0
Siuntionjoki
0
5
Siusis
0
10
Šiušis
0
2
Slupia
0
66
Smiltele
2
0
Smolyachkov
14
0
Spengla
0
4
Spolsau
0
4
Steinbek
0
4
Store
2
0
Strasburger Mühlbach
0
6
Strasburger Mühlenbach
0
2
Strikupe
0
1
Summajoki
0
50
Summanjoki
0
2
Sunija
0
15
Šunija
0
2
Sustis
0
2
Sventoji
59
65
Šventoji
0
10
Sventoji (Neris)
0
2
Sventoji B
20
10
Svetupe
18
0
Svētupe
3
0
Sysa
20
5
Taasianjoki
0
14
Temmesjoki
0
12
Tenenys
0
4
Terteboån
25
0
Tervajoki
0
5
Teuvanjoki
0
16
Toivola
14
0
Torne
39
0
Tornionjoki
0
172
Trave
0
18
Tvarkante
0
5
Ula
0
4
Ume/Vindel
39
0
Uniesta
0
9
Upyna
0
9
Urpalanjoki
0
1
Ushkovskii
16
0
Uskelanjoki
0
9
Uzava
40
1
Užava
5
0
Vaalimaanjoki
0
12
Vääna
25
0
Valgejogi
22
52
Valgejõgi
3
0
Valpperinjoki
0
5
Vanajogi
0
2
Vantaanjoki
0
130
Vasalemma
25
0
Vecpalsa
0
3
Vehkajoki
0
30
Veivirza
0
1
Velikaja
18
0
Venta
48
68
Verseka
0
1
Veskijogi
0
2
Viantienjoki
0
3
Viesvile
0
7
Vija
0
2
Vija, Vecpalsa
0
1
Vilnia
24
29
Virinta
9
36
Virojoki
0
6
Visete
0
5
Vistula
0
150
Vitrupe
45
0
Vizla
0
2
Vizla, Palsa, Vija
0
1
Voke
4
29
Vokė
0
5
Voronka
17
0
Vruda
0
13
Wallbach
0
8
Wallensteingraben
0
8
Warnow
0
7
Wehrau, Mühlenau, Reidsbek
0
1
Wieprza
0
68
Wolfsbach
0
8
Zalesa
0
7
Žalesa
0
2
Žalėsa
0
1
Zeimena
43
1
Zelenogorsky
14
0
Ziezmara
0
3
Žiežmara
0
3
Zvelsa
0
4
Zyba
0
3
(b) Duplicated values for name in ICES vocab
GUID
Key
Description
LongDescription
Modified
Deprecated
description0
41d3b782-c404-4029-9c59-5ccc0ae920da
FI83004
Alhonoja
NA
2023-07-11
FALSE
Alhonoja
1a35a5f0-069a-4e71-a1c7-8ed1f886e293
FI83035
Alhonoja
NA
2023-07-11
FALSE
Alhonoja
92fa064c-2c1f-4108-a100-da74748008d9
DK0507
Ellebæk
NA
2023-07-11
FALSE
Ellebaek
f870f9d4-ac9a-46a0-a78d-f4341f2a94f6
DK1155b
Ellebæk
NA
2023-07-11
FALSE
Ellebaek
cec6fbe3-a563-4846-9478-472f3f83777e
FI16000
Koskenkylänjoki
NA
2023-07-11
FALSE
Koskenkylanjoki
9a0ed388-775c-4a01-a1cd-3af13b5385eb
FI84055
Koskenkylänjoki
NA
2023-07-11
FALSE
Koskenkylanjoki
d9f7cc5d-b4b8-4b49-96fe-df2548525fd0
DK0744c
Pomlerende
NA
2023-07-11
FALSE
Pomlerende
2f80e1ab-476e-444f-9e2f-9813efe5002f
DK0748
Pomlerende
NA
2023-07-11
FALSE
Pomlerende
b8d456d6-1b36-4d5a-9a1c-afea66393979
DK0110
Risebæk
NA
2023-07-11
FALSE
Risebaek
9681b8dc-18d2-4c6a-ae9e-9b37244d52df
DK0127
Risebæk
NA
2023-07-11
FALSE
Risebaek
70ee765f-9d3d-403b-8282-378632dea293
FI82062
Ruonanoja
NA
2023-07-11
FALSE
Ruonanoja
4a9e3458-8ae2-41c2-a6c1-df903bebe81d
FI84136
Ruonanoja
NA
2023-07-11
FALSE
Ruonanoja
719312c8-ebdb-48d1-9179-f23cb01e6f9b
FI82008
Storträsket
NA
2023-07-11
FALSE
Stortrasket
e073e339-2dde-4651-9f03-71a0fdf65aff
FI83094
Storträsket
NA
2023-07-11
FALSE
Stortrasket
699f678a-96e2-4eff-8fe3-886e5e1253b9
FI81037
Storängsbäcken
NA
2023-07-11
FALSE
Storangsbacken
3f4725d1-24b3-42a5-af71-9f8745c78e2b
FI81075
Storängsbäcken
NA
2023-07-11
FALSE
Storangsbacken
4c875927-fabb-408e-aab8-2055c8d85822
DK0134
Vasebæk
NA
2023-07-11
FALSE
Vasebaek
b804f016-7ed6-4e09-ad7f-631492cabd4e
DK0528
Vasebæk
NA
2023-07-11
FALSE
Vasebaek
(c) Rivers with more than one ICES division
more_than_1_ICES_div
Eurajoki
2
Fiskarsinjoki
2
Karjaanjoki
2
Kyrönjoki
2
Mynäjoki
2
Nelma
2
Pärnu
2
Pregola
2
Prochladnaja
2
Sealand
2
Valpperinjoki
2
Venta
2
Wallensteingraben
2
Bornholm
3
Laajoki
3
at sea
4
(d) Table for values corresponding to more than one ICES division
200
22
22-23-24
24
24-25
25
26
28
29
30
31
32
at sea
0
0
0
0
0
0
0
0
95
73
79
142
Bornholm
4
0
0
0
14
3
0
0
0
0
0
0
Eurajoki
0
0
0
0
0
0
0
0
3
28
0
0
Fiskarsinjoki
0
0
0
0
0
0
0
0
1
0
0
2
Karjaanjoki
0
0
0
0
0
0
0
0
2
0
0
23
Kyrönjoki
0
0
0
0
0
0
0
0
0
24
3
0
Laajoki
0
0
0
0
0
0
0
0
4
20
1
0
Mynäjoki
0
0
0
0
0
0
0
0
5
15
0
0
Nelma
0
0
0
0
0
0
17
0
0
0
0
1
Pärnu
0
0
0
0
0
0
0
36
0
0
0
1
Pregola
0
0
0
0
0
0
17
0
0
0
0
1
Prochladnaja
0
0
0
0
0
0
17
0
0
0
0
1
Sealand
4
0
14
0
0
0
0
0
0
0
0
0
Valpperinjoki
0
0
0
0
0
0
0
0
1
4
0
0
Venta
0
0
0
0
0
0
3
113
0
0
0
0
Wallensteingraben
0
6
0
2
0
0
0
0
0
0
0
0
Question / ANSWERS WGBAST
Could you please confirm the duplicated values here (values with similar names) in Table 14.
Yes, there are dublicates (with minor differences in writing). Need to check river by river.
Why are some entries for some rivers corresponding to more than one area ?
No, there should not be such as long as the key value in ICES vocab will be used. River name (“Description”) don’t always specify the river because several rivers/brooks may have the same name.
River_category
Table 15: River categories in the young fish and smolt database
smolts
young_fish
mixed
527
0
wild
860
0
NA
1091
7714
Age
Table 16: Age in the young fish database
(a) Age for smolts
SAL
TRS
1s parr
0
8
(b) Age for young fish
SAL
TRS
1s parr
253
379
1yr
552
673
1yr parr
424
438
2s
1
0
2s parr
83
184
2yr
903
1137
2yr parr
8
3
3s
0
1
3yr
21
158
alevin
153
325
eyed egg
77
221
fry
408
1312
Question WGBAST
What is the meaning of the different age categories ?
There are 9 lines in the smolts database who have a stage corresponding to 1s parr Are these caught in downstream traps ?
ANSWER WGBAST
In this you have smolts and parr corresponding to release of aquaculture raised salmons. 2sshould be replaced by 2 s parr. yr correspond to 1yr old smolt. 1 yr parr correspond to parr relase at 1 yr old. There are very few parr in hatcheries that will not have smoltified at 2 yr (2yr parr), most will smoltify at age 1 so that’s why the number are low. Fry correspond to alevins with the yolk sack.
Origin
Table 17: Origin in the young fish and smolt database
smolts
young_fish
R
0
7705
W
2478
0
NA
0
9
Question / ANSWERS WGBAST
There are just 9 NA values, is this an error ?
NA are errors.
Type of smolt number estimation method
Complete count of smolts.
Sampling of smolts and estimate of total smolt run size.
Estimate of smolt run from parr production by relation developed in the same river.
Estimate of smolt run from parr production by relation developed in another river.
Inference of smolt production from data derived from similar rivers in the region.
Count of spawners.
Estimate inferred from stocking of reared fish in the river.
Salmon catch, exploitation and survival estimate.
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
1.000 3.000 3.000 3.469 4.000 8.000 8666
WGBAST
NOTE There are character values, “na”, “n.e.”,“0,3”, “0 .1”
QUESTION There are missing values there … Is that correct ?
Need to look closer all cases to be able to evaluate
part III - TRUTTA electrofishing densities dataset
Table 18: Frequencies of species type in the trutta densities dataset
(a) Frequency of values
Var1
Freq
TRS
10127
NA
2
(b) Lines with missing value for species
species
country
year
sub_div
main_river
river
age
density_n_100m2
number_of_sites
NA
FI
2002
31
Torniojoki
Äkäsjoki
>0+
9.10
9
NA
PL
2023
24
Odra
Drawa
>0+
1.46
5
NOTE WGBAST
Two values without species, we can correct while integrating
Country
Table 19: Countries in the trutta density dataset
country
Freq
DK
394
EE
2560
FI
416
GER
1598
LT
341
LV
842
PL
359
RU
464
SE
2403
SE-S
752
Question WGBAST
GER should be DE
Yes
What is SE-S, it’s not a country how do we deal with this. Why is it needed ? Could we use some other column from the other datasets (as they will be in the joined database structure) ?
This is notation for the assessment unit southern Sweden. Should not be used as the country value.
Time
Table 20: Number of values per year and sheet in trutta density dataset
country
Freq
1975
12
1976
16
1977
2
1978
12
1982
12
1983
22
1984
10
1986
6
1987
3
1988
10
1989
16
1990
11
1991
9
1992
33
1993
35
1994
41
1995
73
1996
104
1997
69
1998
86
1999
116
2000
154
2001
170
2002
176
2003
225
2004
301
2005
354
2006
342
2007
342
2008
414
2009
452
2010
386
2011
383
2012
459
2013
387
2014
412
2015
473
2016
373
2017
505
2018
558
2019
811
2020
543
2021
595
2022
560
2023
56
NOTE
Years distributed from 1975, nothing special (Table Table 20), this db does not use time periods lower than year.
Age
Table 21: Age in the trutta density dataset
age
Freq
>0+
4913
0+
5161
NA
55
ANSWER WGBAST
Yes for Trutta the ages are divided between 0+ and older than 0+ which is a grouping of several ages.
Geography
Table 22: Geographical units in the trutta densities dataset
(a) Rivers (note that some labels seem to be duplicated in the database)
river
Freq
Aapuajoki
10
Abava
14
Abuls
4
Äkäsjoki
68
Akmena
7
Akmenos - Danės basin
24
Älandsån
32
Ålsån
4
Alte Schwentine / Kührener Au UL
2
Althoefer
4
Althöfer Bach
7
Altja oja
66
Amata
46
Angerja oja
14
Angla kraav
4
Araka oja
2
Arakaoja
2
Audru jõgi
4
Augraben
10
Åvaån
44
Azika
14
Bach aus Bernstorf
4
Bach aus Blowatz
6
Bach aus Grundshagen
6
Bach aus Hanshagen
6
Bach aus Huckstorf
4
Bach aus Körchow
4
Bach aus Neu Karin
6
Bach aus Parchow
6
Bach aus Ravensberg
4
Bach aus Zapkendorf
4
Bach aus Zierow
4
Bach bei Karschau
2
Bach Bernstorf
4
Bachgraben
5
Bachgraben (Ryckgraben)
4
Bagge
2
Baltic - Šventoji basin
12
Barnitz
14
Bartuva
7
Bartuvos basin
24
Beke
12
Bergshamraån
42
Beste
10
Bienebek
2
Birkenmoorgraben
4
Björkån
24
Blowatzer Bach
1
Blykobbe
2
Bollhaegerfliess
4
Bollhäger Fließ
6
Böllhäger Fließ
1
Bollstaån
8
Bönälven
14
Borgforsälven
22
Börrumsån
44
Brændemølle å
7
Brandsau ML
4
Brandsau UL
8
Brasla
24
Brebowbach
10
Brüeler Bach
4
Buslovka
2
Buurdieksgraben
4
Byskebäcken
42
Bystryi
6
Carbäck
4
Carbäk
6
Chernaya
12
Ciecere
6
Curau
10
Damshäger Bach
7
Degerbäcken
46
Dingwatter Au
6
Drawa
2
Drwęca
12
Dubysa
7
Dubysos basin
24
Durbe
4
Edstabäcken
22
Eglupe
2
Egļupe
8
Ekeberger Au OL
2
Ekeberger Au UL
12
Emakraav
2
Enångersån
24
Eru kr.
2
Esgruser Mühlenstrom
4
Esna jõgi
2
Fällforsån
44
Farpener Bach
4
Farver Au
8
Farver Au OL
2
Farver Au Wald
2
Faule Trave UL
8
Fauler Bach
2
Fauler Bach/Plastbach
4
Flaruper Au
4
Gådeån
2
Gladyschevka
18
Glazupe
2
Glāžupe
10
Glomså
17
Goddestorfer Au
4
Goldbach
10
Gorohovka
4
Gösebek
2
Göwe
10
Graben aus Ahrendsee
9
Graben aus Thorstorf
2
Grimsau OL
4
Grimsau UL
12
Grinau OL
2
Grinau UL
2
Große Hüttener Au
10
Große Schierbek
4
Gumbölenjoki
16
Gusinaya
21
Häädemeeste jõgi
30
Haberniser Au
4
Habernisser Au
8
Hagbyån
38
Hagener Au
4
Haisterbek OL
4
Haisterbek UL
12
Hällkroksbäcken
6
Halmstadsbäcken
46
Hanshäger Bach
7
Harku oja
2
Harrijoki
14
Heilsau
2
Hellbach
11
Hernespuu oja
4
Höbringi oja
32
Hohenfelder Mühlenau
8
Hohler Bach UL
8
Holmbacher Graben
10
Hopfenbach (Brüeler Bach)
4
Hugraifsån
38
Humalaste jõgi
4
Huumosen-oja
4
Idbyån
20
Ikla pkr
2
Ina
16
Ingarskilanjoki
16
Inviksån
26
Isojoki
16
Jägala jõgi
48
Jämaja oja
26
Järveoja
4
Jaunupe
54
Jeksen Bæk
20
Johannisbek OL
8
Jūra
7
Jūros basin
24
Jyryjoki
12
Kääntöjoki
10
Kaberla oja
46
Kabli oja
2
Kadaka oja
20
Kagghamraån
46
Kaldamäe oja
12
Kana-oja
2
Kanan-oja
4
Kanaoja
2
Kangosjoki
57
Karepa oja
4
Käsmu oja
2
Katzbach
10
Keibu pkr
18
Keila jõgi
56
Kello-oja
6
Keräntöjoki
6
Khabolovka
14
Khrevitsa
2
Kiebitzbek
4
Kiljatu oja
2
Kirrin-oja
2
Kiruma pkr
20
Kiruma pkr ülemine haru
2
Kitkiöjoki
40
Klaasbach
4
Klappmarksbäcken
46
Kloostri jõgi
38
Klosterbach
7
Kluetzer Bach
4
Klützer Bach
6
Kobek
4
Koerchow
4
Koesterbeck
2
Köhntop
5
Kohtla jõgi
2
Kohtla oja
2
Koivistonpuro
6
Kolga jõgi
2
Kolga oja
38
Kolmårdsbäcken
44
Kongla oja
2
Koolimäe oja
4
Kopparviksbäcken
38
Köppernitz
11
Korge
2
Korģe
50
Körkwitzer Bach
1
Korleputer Bach
2
Korleputer Mühlbach
1
Kõrtsioja
12
Koseler Au
18
Koseler Au Ol / Graben II
10
Kossau ML
10
Kossau UL
8
Kossau unterhalb Tresdorfer See
2
Kösterbeck
10
Kramforsån
8
Kremper Au
8
Kremper Au Mündung
4
Kremper Au UL
8
Krieseby Au
2
Kriesebyau
10
Krohnhorster Trebel
4
Kronsbek-Aschau
8
Kronsbek - Aschau
14
Krusau
2
Kuivajõgi
14
Kulleån
46
Kumada
4
Kunda jõgi
64
Künnapõhja oja
2
Künnimaa oja
2
Kuokkalan
4
Küti oja
2
Kutsasjoki
10
Kuusalu oja
6
Kuusiku oja
2
Kvarnån
16
Kvarsebobäcken
34
Laagna oja
2
Lachsbach Wald
4
Lachsbach/Steinbach
14
Læså
2
Lähkma jõgi
4
Lahnajoki
12
Landsgraben UL
2
Langballigau
12
Lange Rie
7
Långträskån
2
Lehbekerau
2
Leipiöjoki
8
Leisi jõgi
22
Leivajõgi
28
Lemmejõgi
20
Lemovzha
26
Lencupe
4
Lenčupe
8
Leppoja
2
Lestijoki
11
Lētiža
12
Lētīža
6
Lielā Jugla
18
Ligatne
2
Līgatne
10
Ligeoja
24
Lilleå
22
Lindau
6
Linde
10
Lipping Au
8
Lippingau
10
Lippingau ML
4
Ljustorpsån
36
Loån
42
Lodmannshäger Bach
4
Lõhavere oja
2
Lohja oja
4
Loiter Au OL
14
Loiter Au UL
12
Loja
12
Longinoja
16
Loo oja
42
Loobu jõgi
62
Loode oja
20
Lorumupe
2
Lorupe
4
Lososinka
4
Lößnitz
8
Lübscher Mühlenbach
2
Lyckebyån
44
Mägara oja
38
Maibach
7
Malbäcken
46
Malda oja
2
Malenter Au ML
10
Malenter Au UL
10
Malinovka
24
Malliner Wasser
10
Männiku oja
40
Männiku(Kolga) jõgi
6
Marlower Bach
9
Maurine
11
Maza Jugla
4
Mazā Jugla
8
Mazupīte
8
Mechelsdorfer Bach
11
Melnichnyi
2
Melsted
2
Merasjoki
10
Meriküla oja
4
Mildenitz
10
Minijos basin
24
Mittlere Trave
18
Mittlere u Untere Trave
8
Moltenower Bach
6
Moltenower Bach (Beke)
4
Moraån
42
Motel
2
Motel3
2
Muehlenfliess
4
Mühlbach (Hohensprenz)
4
Mühlbach Hohensprenz
6
Mühlbach Strelasund
4
Mühlenau
4
Mühlenau, Flaßlandbek, Schmiedenau
6
Mühlenau, Mühlenbach
6
Mühlenbach Strelasund
1
Mühlenbach UL
6
Mühlenbach(Strelasund)
4
Mühlenfließ
7
Mühlenstrom
4
Mustajoki
16
Mustoja jõgi
66
Naamijoki
61
Nätraån
20
Navesti jõgi
2
Nebel
10
Nepste oja
2
Neris
7
Neris basin
24
Nessendorfer Mühlenau
8
Neu Karin
5
Nianån
18
Niinemäe peakraav
2
Nimetu oja Laugu küla juures
2
Nonnenbach
4
Notkopuro
2
Nõva jõgi
46
Nurmizupite
2
Nurmižupīte
8
Nuutri jõgi
16
Ogerna oja
2
Oitme oja
4
Oju pkr
10
Õngu jõgi
18
Örupsån
32
Osterbek
6
Ostpeene
4
Oxbek
12
Paadrema jõgi
4
Pada jõgi
58
Pähkla oja
2
Pähkla pkr
2
Pakajoki
69
Pålböleån
40
Panzower
4
Panzower Bach
7
Parchow
5
Parkajoki
2
Pärlijõgi
2
Pärnu jõgi
50
Paskapuro
6
Peezer Bach
13
Peipiya
2
Pennewitter Bach (in Teppnitzbach)
4
Pennu oja
2
Penttilan-oja
8
Perjatsi oja
2
Pērļupe
2
Peschanaya
8
Petrovka
8
Pidula nimetu oja
2
Pidula oja
30
Piirsalu jõgi
16
Pikasoo oja
2
Pikkmetsa jõgi
2
Pikku Vammeljoki
2
Pilkenbek
2
Pirita jõgi
52
Platenes kanāls
4
Poama oja
10
Poischower Muehlenbach
4
Poischower Mühlenbach
7
Polchow
7
Polevaya
6
Poolnõmme oja
2
Prandi jõgi
2
Prästbäcken
46
Priivitsa oja
20
Privetnaya
8
Pudisoo jõgi
58
Pühajõgi
42
Pulverbek
12
Punapea jõgi
30
Puro (Repino)
2
Purtse jõgi
42
Råån
46
Rabeler Scheidebach
2
Radebach
12
Radegast
8
Radunia
4
Raksupe
2
Raķupe
4
Ramlösabäcken
46
Randkanal
11
Ranna oja
4
Rannametsa jõgi
4
Råtjärnbäcken
44
Rauna
12
Raunis
18
Ravensberg
1
Recknitz
1
Reiu jõgi
8
Reppeliner Bach
7
Riežupe
2
Riguldi jõgi
44
Rihula oja
4
Rinda
10
Risängesbäcken
46
Risebergabäcken
42
Risti oja
18
Ritzerauer Mühlenbach
2
Rompotinpuro
6
Roschinka
10
Rosengartener Beek
6
Rosengartener Bek
7
Rotbaeck
4
Runtiņš
2
Saarjõgi
4
Saegebach
4
Sagader Bach
4
Sagarder Bach
1
Sägebach
6
Sälgträskbäcken
2
Salme jõgi
2
Saluån
42
Salzau
4
Sandhagen
4
Sargarder Bach
4
Sauga jõgi
4
Saula kr
2
Schmieden Au
8
Schwartau
14
Schwartau bis Barkauer See
10
Schwartau UL
8
Schwastrumer Au
6
Schwennau
2
Schwentine bei Klausdorf
10
Schwentine Zulauf Sibbersdorfer See
2
Schwinge
13
Seebach (Steinhagen-Rühn)
4
Sege å
46
Sehrowbach
8
Seleznevka
20
Selja jõgi
52
Selker Mühlenbach
4
Šepka
6
Serga
8
Sestra
2
Siesbek
2
Sikån
24
Sista
26
Själsöån
30
Skalupe
2
Skaļupe
8
Skärjån
18
Skeboån
34
Šķērvelis
10
Šķervēlis
8
Smiltelė Baltic sea
12
Smolyakov
2
Smörbäcken
46
Solka
30
Sõmeru oja
2
Sommerdorfer Mühlbach
4
Soonda oja
6
Sõreda oja
6
Sõtke jõgi
8
Stadtgraben
4
Steinau/bei Nusse
14
Steinhagen
4
Stenbitbäcken
14
Stepenitz
10
Strasburger Mühlbach
3
Straßburger MB
2
Strehlower Bach
10
Stridbäcken
46
Strikupe
2
Strīķupe
20
Strinneån
26
Stubberup bæk
20
Süderbeste
6
Svenskebæk
16
Šventosios basin
24
Svētupe
2
Swinow
13
Šyša
7
Šyšos basin
24
Taaliku pkr
24
Tammispea oja
8
Tarnewitzer Bach
7
Tążyna
4
Tchernaya
2
Tebra
30
Teetzlebener Mühlenbach
4
Tegelbek/Twisselbek
10
Tehumardi pkr
2
Tensfelder Au
10
Tensfelder Au OL/Schlamersdorfer Moorgraben
4
Teppnitzbach
4
Tessenitz
10
Testorfer Au
6
Thorstorf
1
Timmkanal
36
Tirtsi jõgi
30
Tiskre
2
Tjærbæk
21
Tohrstorfer Bach
4
Toivola
4
Tolkkijoki
14
Tolkuse oja
2
Tollense
6
Toolse jõgi
54
Torsbäcken
44
Tõrvajõgi
6
Tõrvanõmme oja
2
Tõstamaa jõgi
32
Tostarpsbäcken
46
Trave I
14
Treimanni oja
6
Treppoja
6
Trunnerupsbäcken
42
Tryssjöbäcken
44
Tuhala jõe suudmest 2 haruoja
8
Tuhala jõgi
6
Türisalu
2
Tuuraste oja
8
Tvärån
56
Twisselbek
2
Udria oja
6
Udriku oja
2
Uecker
2
Üecker
2
Ukhora
12
Ura jõgi
6
Uruste oja
2
Uschkovsky
10
Uuemõisa oja
2
Vääna jõgi
52
Vaidava
4
Vaidava jõgi
2
Vainupea jõgi
58
Vaive
18
Valdimurru oja
2
Valgejõgi
58
Valkla oja
38
Valtiojoki
44
Vanajõgi
18
Vanakubja oja
4
Vanka
10
Varja oja
2
Vasalemma jõgi
56
Vaskjõgi
2
Västanbäcken
45
Veån
24
Vecpalsa
14
Vedruka oja
20
Vejupite
2
Vējupīte
8
Velikaya
6
Venta basin
8
Verkaån
44
Vesiku oja
20
Veski jõgi
44
Veskioja
20
Vēždūka
2
Vidon
14
Vidon'
2
Viešviles basin
16
Vihterpalu jõgi
54
Vildoga
10
Virån
40
Virbupe
4
Vitsån
40
Vodja jõgi
2
Voka oja
4
Võlupe jõgi
10
Vorfluter Kronstrang
4
Voronka
22
Võsu jõgi
52
Vruda
22
Waidbach
8
Wallbach
7
Wallensteingraben
11
Warbel
4
Warnow
10
Wellspanger Au
10
Westpeene
2
WestPeene
4
WestPeene (hinter Malchiner See)
4
Wietingsbach
4
Wittbeck
5
Wolfsbach
7
Yukkola east
12
Yukkola middle
4
Yukkola west
2
Zarnow
17
Zarow
2
Žeimena
7
Žeimenos basin
24
Zelenogorsky
4
Ziddorfer Mühlenbach
4
Zielona Struga
12
Zierower Bach
5
NA
1938
(b) Rivers with more than one ICES division
more_than_1_ICES_div
Bachgraben
2
Beke
2
Brebowbach
2
Degerbäcken
2
Kopparviksbäcken
2
Kösterbeck
2
Maurine
2
Peezer Bach
2
Punapea jõgi
2
Randkanal
2
Sägebach
2
Schwinge
2
Själsöån
2
Stepenitz
2
Swinow
2
Trunnerupsbäcken
2
Veskioja
2
Zarnow
2
(c) Table for values corresponding to more than one ICES division
22
23
24
27
28
29
30
31
32
Bachgraben
1
0
4
0
0
0
0
0
0
Beke
10
0
2
0
0
0
0
0
0
Brebowbach
4
0
6
0
0
0
0
0
0
Degerbäcken
0
0
0
0
0
0
42
4
0
Kopparviksbäcken
0
0
0
4
34
0
0
0
0
Kösterbeck
8
0
2
0
0
0
0
0
0
Maurine
7
0
4
0
0
0
0
0
0
Peezer Bach
11
0
2
0
0
0
0
0
0
Punapea jõgi
0
0
0
0
0
8
0
0
22
Randkanal
10
0
1
0
0
0
0
0
0
Sägebach
5
0
1
0
0
0
0
0
0
Schwinge
1
0
12
0
0
0
0
0
0
Själsöån
0
0
0
4
26
0
0
0
0
Stepenitz
9
0
1
0
0
0
0
0
0
Swinow
1
0
12
0
0
0
0
0
0
Trunnerupsbäcken
0
40
2
0
0
0
0
0
0
Veskioja
0
0
0
0
12
8
0
0
0
Zarnow
15
0
2
0
0
0
0
0
0
(d) Table of main rivers
main_river
Freq
Aarhus å
20
Åbyälven
50
Age
2
Aģe
28
Älandsån
32
Althöfer Bach
8
Altja oja
68
Amata
4
Angerja oja
2
Ångermanälven
50
Angla kraav
4
Araka oja
2
Arumetsa oja
2
Audru jõgi
4
Augraben
12
Åvaån
44
Bach aus Bernstorf
6
Bach aus Blowatz
6
Bach aus Grundshagen
6
Bach aus Hanshagen
6
Bach aus Körchow
4
Bach aus Neu Karin
8
Bach aus Parchow
8
Bach aus Ravensberg
4
Bach aus Thorstorf
2
Bach aus Zierow
6
Bach bei Karschau
2
Bachgraben
6
Bäk
2
Baltic - Šventoji basin
30
Barthe
1
Bartuva (Barta)
6
Bartuva(Barta)
6
Beke
16
Bergshamraån
42
Bienebek
2
Blowatzer Bach
3
Bollhaeger Fliess
8
Bollhaegerfliess
4
Bollhäger Fließ
8
Böllhäger Fließ1
1
Bollstaån
8
Bornholm
8
Bornholm area
38
Börrumsån
44
Brændemølle å
8
Brebowbach
6
Broendstrup Moelleaa
2
Brøndstrup Mølleå
16
Byskeälven
158
Bystryi
6
Carbäk
8
Czarna Wda
14
Damshäger Bach
4
Daugava
30
ec_02
6
ec_03
4
ec_07_a
4
ec_07_b
14
ec_08
4
ec_09
4
Elverdams Å
2
Elverdams Å st2
16
Emån
60
Enångersån
24
Eru kr.
2
Espoonjoki
17
Farpener Bach
5
Farver Au
8
Fauler Bach
4
Fauler Bach/Plastbach
4
ff_01
4
ff_04
2
ff_05_b
12
ff_06_b
6
ff_07
4
ff_08
4
ff_09_a
4
ff_09_b
10
ff_10
2
ff_16
2
Fruebæk
2
Fruerskov Bæk
10
Gådeån
2
Gätenbach
2
Gauja
290
Gladyschevka
19
Goldbach
8
Gorohovka
4
Göwe
8
Graben aus Ahrendsee
10
Graben aus Sandhagen
2
Graben aus Thorstorf
2
Gudenå
43
Häädemeeste jõgi
29
Habernisser Au
8
Hagbyån
38
Halleby å
7
Hällkroksbäcken
6
Hanshagener Bach (Ziese)
2
Hanshäger Bach
6
Harkenbaek
4
Harku oja
2
Haubach
2
Hellbach
45
Hernespuu oja
4
Höbringi oja
2
Hohen Sprenzer Mühlbach
2
Hohenfelder Mühlenau
8
Holmbacher Graben
8
Hopfenbach
2
Hörnån
46
Hugraifsån
38
Humalaste jõgi
2
Huumosen-oja
4
Idbyån
20
Ikla pkr
2
Inčupe
4
Indalsälven
40
Ingarskilanjoki
28
Inviksån
26
Irbe
22
Isojoki
34
Jägala jõgi
50
Jämaja oja
26
Järveoja
4
Kaberla oja
48
Kabli oja
2
Kacza
11
Kadaka oja
21
Kågeälven
38
Kagghamraån
46
Kaldamäe oja
2
Kalixälven
194
Karepa oja
4
Käsmu oja
2
Katzbach
8
Keibu pkr
18
Keila jõgi
57
Kello-oja
6
Khabolovka
17
Kiljatu oja
2
Kirrin-oja
2
Kiruma pkr
22
Ķīšupe
6
Kloostri jõgi
39
Klosterbach
9
Kluetzer Bach
4
Klützer Bach
6
ko_02
6
ko_10_a
2
ko_10_b
10
ko_10_c
8
ko_13
6
ko_15
4
ko_20
4
ko_23
4
Koerkwitzbach
4
Koesterbeck
2
Köhntop
4
Kohtla oja
2
Koivistonpuro
6
Kolding
2
Kolding Å
18
Kolga jõgi
2
Kolga oja
39
Kolmårdsbäcken
78
Koolimäe oja
4
Kopparviksbäcken
38
Köppernitz
13
Körkwitzbach
3
Körkwitzer Bach
1
Korleputer Bach
4
Korleputer Mühlbach
2
Kõrtsioja
2
Koseler Au
8
Kösterbeck
8
Kramforsån
40
Kremper Au
8
Krieseby Au
2
Kronsbek-Aschau
8
Kunda jõgi
65
Künnapõhja oja
2
Künnimaa oja
2
Kuokkalan
4
Küti oja
2
Kuusalu oja
6
Kuusiku oja
1
Laagna oja
2
Lāčupīte
8
Læså
16
Lange Rie
4
Leba
38
Leisi jõgi
22
Leivajõgi
2
Lemmejõgi
21
Lestijoki
34
Ligeoja
24
Linde
12
Lipping Au
8
Ljungan
18
Loån
42
Lögdeälven
146
Lohja oja
4
Lollikebaek
2
Lollikebæk
20
Lollikebæk_site 2
2
Lonaste
2
Loo oja
44
Loobu jõgi
66
Loode oja
21
Lososinka
4
Lößnitz
4
lue_01_c
8
lue_01_d
4
lue_02
2
lue_03_b
4
lue_03_c
14
lue_08
2
Luga
95
Lupawa
12
Lyckebyån
44
Mägara oja
6
Maibach
4
Malda oja
2
Malinovka
42
Malliner Wasser
6
Mankinjoki
16
Männiku oja
41
Männiku(Kolga) jõgi
6
Marlower Bach
11
Maurine
8
Mechelsdorfer Bach
11
Melnichnyi
2
Melnsilupe
2
Meriküla oja
4
Mildenitz
8
Moellebaek
2
Møllebæk
18
Moltenower Bach
8
Moraån
42
Mörrumsån
62
Motel
2
Motel3
2
mtr_01
8
mtr_02
12
mtr_03
2
mtr_04
4
mtr_07_a
12
mtr_07_b
4
mtr_08_a
6
mtr_09
14
mtr_10
10
mtr_14
2
mtr_15
8
mtr_18_a
2
mtr_19_a
10
mtr_19_c
2
Muehlenfliess
8
Mühlbach Hohensprenz
6
Mühlbach Strelasund
4
Mühlenbach (Strelasund)
2
Mühlenbach(Strelasund)
4
Mühlenfließ
8
Mühlenfliess
1
Mühlenfließ1
1
Mustajoki
16
Mustoja jõgi
68
Nätraån
20
Nebel
16
Nemunas
269
Nepste oja
2
Nessendorfer Mühlenau
8
Nianån
18
Nimetu oja Laugu küla juures
2
Notkopuro
2
Nõva jõgi
48
Nuutri jõgi
16
Nybroån
78
Odense Å
17
Odra
18
og_10
4
og_15
8
og_16_a
2
og_16_b
2
og_16_c
6
Ogerna oja
2
Oitme oja
4
Oju pkr
10
Õngu jõgi
18
Öreälven
56
Orzechowka
14
otr_12_b
4
otr_13_b
8
otr_13_c
8
otr_14
8
otr_15_b
14
otr_15_c
10
Paadrema jõgi
4
Pada jõgi
62
Pähkla oja
2
Panzower Bach
8
Pärnu jõgi
81
Parsęta
40
Peene
38
Peezer Bach
12
Peipiya
4
Penttilan-oja
8
Perjatsi oja
2
Peschanaya
8
Peterupe
2
Pēterupe
28
Petrovka
8
Piasnica
14
Pidula oja
46
Piirsalu jõgi
4
Pikku Vammeljoki
2
Pilsupe
8
Pirita jõgi
120
Piteälven
70
Pitragupe
10
Poama oja
10
Põduste
13
Põduste jõgi
2
Poischower Mühlenbach
6
Polchow
4
Polevaya
6
Poolnõmme oja
2
Prästbäcken
46
Priivitsa oja
21
Privetnaya
8
Pudisoo jõgi
60
Pühajõgi
76
Punapea jõgi
32
Puro (Repino)
2
Purtse jõgi
50
Råån
184
Rabeler Scheidebach
2
Radebach
10
Radegast
8
Randkanal
13
Råneälven
54
Ranna oja
4
Recknitz
28
Reda
38
Rega
28
Reiu jõgi
4
Reppeliner Bach
4
Rickleån
94
Riguldi jõgi
78
Rihula oja
4
Risti oja
17
Riva
2
Rīva
18
Roja
16
Rompotinpuro
6
Roschinka
5
Rosengartener Beek
6
Rosengartener Bek
11
Ryck
4
Ryckgraben
1
Sagader Bach
4
Sagarder Bach
2
Sagarder Bach1
1
Sägebach
6
Saka
28
Salaca
142
Salme jõgi
2
Saluån
42
Sargarder Bach
4
Sauga jõgi
4
Saula kr
2
Sävarån
184
Schmieden Au
8
Schwinge
10
Segeå
88
Sehrowbach
10
Seleznevka
38
Selja jõgi
54
Serga
8
Sestra
2
Siesbek
2
Sista
28
Själsöån
30
Skärjån
18
Skeboån
34
sl_03_b
4
sl_05_a
2
sl_05_b
12
sl_07
6
sl_08
4
sl_09_a
12
sl_09_b
10
sl_10_a
12
sl_10_b
14
sl_11
10
sl_12
6
sl_13
10
sl_15
10
sl_16
10
sl_17
6
sl_18_a
12
sl_18_b
4
Słupia
38
Smiltelė Baltic sea
18
Smolyakov
2
Sõmeru oja
2
Soonda oja
6
Sõreda oja
6
Sõtke jõgi
8
st_03_a
10
st_03_d
10
st_04
8
st_06
14
Stavids Å
18
Stavidså
2
Stepenitz
30
Stokkebæk
26
Storå
18
Storaa
2
Strasburger Mühlbach
4
Straßburger MB
2
Strehlower Bach
12
Stridbäcken
46
Svetupe
2
Svētupe
48
sw_01_a
10
sw_02
10
sw_05
2
sw_13_b
10
sw_21
4
sw_28
2
sw_35_b
10
sw_38
4
Swinow
12
Taaliku pkr
24
Tammispea oja
8
Tarnewitzer Bach
19
Tavelån
44
Teetzlebener Mühlenbach
4
Tehumardi pkr
2
Tessenitz
8
Testeboån
16
Timmkanal
49
Tirtsi jõgi
30
Tiskre
2
Toivola
4
Tollense
18
Toolse jõgi
56
Torneälven
104
Torniojoki
289
Torsbäcken
44
Tõrvajõgi
4
Tõrvanõmme oja
2
Tõstamaa jõgi
33
Trebel
4
Treimanni oja
6
Treppoja
6
Trunnerupsbäcken
42
Türisalu
2
Tuuraste oja
7
Udria oja
6
Uecker
4
Üecker
2
Umeälven
91
Ura jõgi
4
Uruste oja
2
Uschkovsky
9
utr_09
2
utr_10
14
utr_15
2
utr_16
2
Uuemõisa oja
2
Uzava
2
Užava
32
Vääna jõgi
54
Vainupea jõgi
60
Valgejõgi
62
Valkla oja
40
Vanajõgi
18
Vanakubja oja
4
Vantaanjoki
16
Vasalemma jõgi
58
Veån
24
Vejstrup Å
20
Velikaya
6
Venta
70
Venta basin
12
Verkaån
44
Vesiku oja
40
Veski jõgi
46
Veskioja
6
Vihterpalu jõgi
93
Villestrup å
39
Vindelälven
54
Virån
40
Vistula
32
Vitrupe
30
Vitsån
40
Voka oja
4
Võlupe jõgi
10
Voronka
24
Võsu jõgi
54
Waidbach
6
Wallbach
2
Wallensteingraben
13
Warnow
99
Westpeene
2
WestPeene
4
Wieprza
40
Wittbeck
3
Wolfsbach
8
Yukkola east
12
Yukkola middle
4
Yukkola west
2
Zagórska Struga
22
Zaķupe
8
Zarnow
12
Zarow
2
Zelenogorsky
4
Zierower Bach
6
Ziese
1
NA
53
Question / answers WGBAST
Would it be usefull to start from a full db of electrofishing data ?
Yes, I thing would be good. Like for SAL electrofishing data too.
Could you please confirm the duplicated values here (values with similar names) in Table 22.
Potentially dublicates, but several rivers/brooks may have the same name.
Do you have GIS information corresponding to those rivers ?
The gis information is available in national geographic data bases. For example the Finnish Environmental Institute host the data concerned.
Some values are ‘at sea’ what does it means ?
These are release to the marine water at the coast away from any river mouth (no imprinting to the river).
Why are some entries for some rivers corresponding to more than one area ?
by river names yes but not if key code is used
Question ICES
There are duplicated names in the ICES Vocab, is it the same rivers ? Do you have ways to separate the rivers (gis information) ?
ANSWER WGBAST : The key code of the ICES vocab separates the rivers, not the river names (“Description”).
part IV - Electrofishing dataset for Salmon
TODO
Get the dataset from WGBAST (Atso)
part V The model
Overview of the different types of data available for the different Baltic salmon stocks. The table also indicates for which stocks the current assessment methodology is estimating smolt abundance, spawner abundance and associated stock–recruit function. River categories: W=wild, M=mixed, R=reared. (source wgbast stock annex)
Salmon populations in Gulf of Bothnia and southern Sweden (AUs 1–4), eastern Main Basin (AU5) and Gulf of Finland (AU6) are assessed separately (ICES 2021).
Overview of the assessment methodology for Baltic salmon stocks. The results from five uppermost analyses provide informative prior probability distributions for the full life-history model. These priors become automatically updated by the information contained in the data and by the biological knowledge of the Baltic salmon life cycle used to build a full life-history model. PSPC=Potential Smolt Production Capacity. Note that smolt trapping data is available from more rivers than indicated in the figure. (source wgbast stock annex)
TODO
Look at the report
Mark recapture
Mark–recapture experiments combined with smolt trapping have been used in eleven rivers (Tornionjoki, Simojoki, Åbyälven, Rickleån, Sävarån, Ume/Vindelälven, Öreälven, Lögdeälven, Testeboån, Mörrumsån and Emån).
number of untagged fish caught by the smolt trap
the number of tagged smolts released upstream from the trap
number of recaptured tagged smolts.
different time intervals, like days, or annual totals
daily water level
water temperature data
Sea marking recapture
Schematic presentation of the mark–recapture model for Baltic salmon. The offshore driftnet and longline fisheries in the Baltic Main Basin are assumed to take place in October and December, respectively. During the migration to the spawning grounds, the salmon can be intercepted by the coastal driftnet fishery in May, the trapnet and gillnet fisheries in June and the river fishery in August (Michielsens et al., 2006a).(source wgbast stock annex)
Parameters
Kmaximum smolt production (K, i.e. the smolt production that would be obtained with an infinite number of spawners under the Beverton–Holt model). Lognormal distributions with median and coefficient of variation matching with the ones of exact distributions are used for approximation. K priors are river specific. They might change (data call specific values can be stored each year).
Individual expert judgement on the productivity of each rivers for :
chance for successfull spawing
habitat quality of parr area
smoltification age
mortality during migration
size of production area
the model produces a probabilistic justification for the expert views of salmon smolt production
parr density capacity (5 discrete classes from the poorest river in the Northern Baltic area to the best river in the Baltic).
pre-smolt density capacity (5 classes).
smolt production capacity.
Yearly smolt production for the rivers Tornionjoki, Simojoki, Åbyälven, Rickleån, Sävarån, Ume/Vindelälven, Öreälven, Lögdeälven, Testeboån and Mörrumsån.
Smolt abundance estimated forall other rivers in AU1-4 for which only parr density estimates are available, based on the hierarchical linear regression analysis
Mark–recapture analysis : independent estimates of relative parr density and smolt abundance in a form of statistics of posterior distributions. Medians and CV.
Maturation rates,
Natural mortality rates,
Mortality F [year, age, category, fishery]
where fishery is :
offshore driftnet
offshore longline
coastal driftnet
trapnet and gillnet
river fishery
And category is :
wild / hatchery raised
Annual yolk sack mortality,
Annual M74 yolk sack mortality
Stock recruitment posterior distribution
proportion of MSW (multi-sea-winter) spawners encountered in the rivers Tornionjoki, Kalixälven, Byskeälven, Ume/Vindelälven, Öreälven and Piteälven
model-predicted catches are raised by the proportions of smolts produced in assessment units 5 and 6 (not yet been included in the model) compared with the total smolt production of all units.
the relative occurrence of wild vs. reared salmon in catches
Sex ratio (annually changing) for multi-sea-winter salmon for Ume/Vindelälven
Sex ratio per stock (outside from Ume/Vindelälven)
egg/female per stock
… might have missed a lot of things !
References
ICES. 2021. “Stock Annex: Salmon (Salmo Salar) in Subdivisions 22–31 (Main Basin and Gulf of Bothnia) and Subdivision 32 (Gulf of Finland),” April. https://doi.org/10.17895/ices.pub.18623147.v1.
