# Can benthic foraminifera serve as proxies for changes in benthic macrofaunal community structure? Implications for the definition of reference conditions

Vincent M.P. Bouchet, Richard Telford, Brage Rygg, Eivind Oug, Elisabeth Alve

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Vincent M.P. Bouchet, Richard Telford, Brage Rygg, Eivind Oug, Elisabeth Alve. Can benthic foraminifera serve as proxies for changes in benthic macrofaunal community structure? Implications for the definition of reference conditions. Marine Environmental Research, 2018, 137, pp.24-36. 10.1016/j.marenvres.2018.02.023. hal-04364736

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1 Can benthic foraminifera serve as proxies for changes in benthic macrofaunal community

2 structure? Implications for the definition of reference conditions

3 Vincent M.P. Bouchet¹, ², Richard J. Telford³, Brage Rygg⁴, Eivind Oug⁵, Elisabeth Alve¹

4

5 ¹ Department of Geosciences, University of Oslo, PO Box 1047, Blindern 0316 Oslo, Norway

6 ² Univ. Lille, CNRS, Univ. Littoral Côte d'Opale, UMR 8187, LOG, Laboratoire d'Océanologie

7 et de Géosciences, F 62930 Wimereux, France

8 ³ Department of Biology, University of Bergen, Bjerknes Centre for Climate Research,

9 Allegaten 41, 5007 Bergen, Norway

10 ⁴ Norwegian Institute for Water Research (NIVA), Gaustadallèen 21, 0349 Oslo, Norway

11 ⁵ Norwegian Institute for Water Research (NIVA), Region South, Jon Lilletuns vei 3, 4879

12 Grimstad, Norway

13

14 * Corresponding author: Vincent M.P. Bouchet

15 Current address: Université de Lille, UMR CNRS-U. Lille-ULCO 8187 Laboratoire

16 d'Océanologie et de Géosciences, Station Marine de Wimereux, BP 80, 28 Avenue Foch,

17 62930 Wimereux, France

18 E-mail address: vincent.bouchet@univ-lille.fr

19 Telephone: +33 3 21 99 29 20

20 Fax: +33 3 21 99 29 01

21

22
23 **Keywords:** Norway – Environmental parameters - Benthic foraminifera – Benthic

24 macrofauna – Community structure - Indicator species – Fjords

25

26 **Abstract**

27 Benthic macrofauna is one of the most widely used biological groups to assess the ecological

28 status of marine systems. Lately, attention has been paid to similar use of benthic

29 foraminifera. In this study, distribution patterns of benthic foraminiferal and macrofaunal

30 species were investigated simultaneously in 11 fjords in southeastern Norway in order to

31 assess correlations and responses to environmental conditions. Selected fjords allowed to

32 investigate contrasted environmental conditions from low total organic carbon (TOC)

33 content (sediment TOC < 2.7%) in normoxia (bottom-water [O₂] > 2 mL O₂·L⁻¹) up to high

34 TOC content (> 3.4%) in severe hypoxia (< 0.5 mL O₂·L⁻¹). Environmental parameters

35 comprised bottom-water dissolved oxygen, grain size, total organic carbon, total nitrogen

36 (TN), pigments and depth below threshold (DBT). Foraminiferal and macrofaunal community

37 data were significantly correlated (Procrustes analysis *m*² = 0.66, *p* = 0.001). Hence, benthic

38 foraminiferal distribution patterns mirror those of benthic macrofauna. However, as

39 opposed to the foraminifera, macrofauna was not recorded at the most oxygen-depleted

40 stations and, hence, was more sensitive to severe oxygen depletion. With regard to

41 assigning species to ecological groups for ecological quality status assessment, the results

42 suggest that species, e.g. *Spiroplectammina biformis* (foraminifera), *Scalibregma inflatum*

43 (macrofauna), may exhibit different ecological requirements depending on their habitat.

44 Considering the observed congruent patterns of benthic foraminifera and macrofauna,

45 palaeo-communities of benthic foraminifera could be used as indicators of reference
46 conditions for benthic macrofaunal community structure. This would however need further

47 developments of algorithms to perform such a translation.
48 **1. Introduction**

49

50 Most benthic macro-invertebrate species are sedentary, making them dependent on
51 the local environmental conditions. Living at the sediment-water interface, they integrate
52 aquatic as well as sediment conditions. Their communities show dramatic changes in their
53 composition in response to organic matter loads (Pearson & Rosenberg 1978, Bouchet &
54 Sauriau 2008), oxygen depletion (Rosenberg et al. 2002), oil spills (Gray et al. 1990), sewage
55 (Glémarec & Hily 1981), heavy metals (Olsgard & Gray 1995) and physical disturbance
56 (Lavesque et al. 2009). Tolerant species thrive at the early stages of the perturbation,
57 followed by highly tolerant opportunistic species when the perturbation becomes severe
58 (Glémarec & Hily 1981). Hence, macrofauna are routinely used in environmental bio-
59 monitoring studies (e.g. Warwick 1986, Grall & Glémarec 1997, Borja et al. 2003, Bouchet &
60 Sauriau 2008). In response to the implementation of marine legislation such as the Water
61 Framework Directive (WFD), the Clean Water Act, and the Marine Strategy Framework
62 Directive (MSFD), numerous indices based on macrofauna have been established for
63 assessing the ecological quality status (EcoQ, see review in Pinto et al. 2009). Most of the
64 indices developed to assess the EcoQ of marine systems are based on the indicative value of
65 macrofaunal species. They have been classified into 5 ecological groups of sensitivity to
66 disturbances from sensitive to first-order opportunistic species (Glémarec & Hily 1981, Borja
67 2000). Lately, concerns arose about these indices (see review in Spilmont 2013). One of the
68 main concerns is the definition of reliable reference conditions for benthic macrofaunal
69 communities. This is a crucial point since in the European Water Framework Directive
70 (WFD), reference conditions are mandatory to assess the EcoQ. According to the WFD, the
71 reference conditions (also called “high” status) are defined as “for any surface water body
type reference conditions or high ecological status is a state in the present or in the past where there are no, or only very minor, changes to the values of the hydromorphological, physico-chemical, and biological quality elements which would be found in the absence of anthropogenic disturbance" (Common implementation strategy for the Water Framework Directive (2000/60/EC), Guidance Document No.5, transitional and coastal waters – typology, reference conditions and classification systems p. 106). Assessment of environmental quality is based on the extent of deviation from these reference conditions, following the definitions in the WFD (www.ec.europa.eu/environment/water/marine.htm). Most of the coastal areas are modified or have been modified by human activities (Diaz and Rosenberg 2008). Hence, EcoQ assessment within the WFD is facing issues to determine true reference condition (Nielsen et al. 2003, Elliott and Quintino 2007). As for benthic macrofauna, since there is almost no data from pre-impact time, reference conditions have to be determined using today's communities, which is an issue considering the aforementioned degradation of coastal areas.

There is an increasing interest in the use of benthic foraminifera to characterize the health of marine systems (e.g. Alve 1995, Scott et al. 2001, Mojtahid et al. 2006, Bouchet et al. 2007, Frontalini et al. 2009). Lately, indices to use benthic foraminifera routinely to assess EcoQs have been proposed (Hallock et al. 2003, Alve et al. 2009, Bouchet et al. 2012, Barras et al. 2014, Dimiza et al. 2016). Specifically, benthic foraminiferal species were assigned to ecological groups (EGs) according to their sensitivity/tolerance to increasing organic matter enrichment (Alve et al. 2016, Jorissen et al. 2018), inspired by work on benthic macrofauna to develop the AMBI index (Glémarec & Hily 1981, Borja et al. 2000). It led to the development of the Foram-AMBI to assess the ecological quality status of marine systems. In these studies, the response of species along a gradient of enrichment in organic
96 matter allowed their classification into groups of different sensitivity. Five ecological groups
97 were defined: sensitive (EG1), indifferent (EG2), tolerant (EG3), second-order opportunistic
98 (EG4) and first-order (most) opportunistic (EG5). The AMBI and the Foram-AMBI are
99 computed based on the proportion of the different ecological groups in the species
100 community, allowing assessment of ecological quality status.

101 Benthic foraminifera leave an easily accessible and abundant fossil record, which
102 allows reconstruction of the characteristics and timing of historical environmental variations
103 (e.g. Alve, 1991; Hayward et al., 2004, Dolven et al. 2013, Francescangeli et al. 2016).
104 Consequently, it is possible to trace the record of human-induced disturbance over decades
105 or centuries. Indeed, in a pilot study, Alve et al. (2009) suggested that in situ reference
106 conditions can be established using fossil benthic foraminiferal assemblages from dated
107 sediment cores. For example, by comparing the "background" fossil foraminiferal
108 assemblages to the modern living foraminiferal assemblages at the same site, it would be
109 possible to determine if a site is naturally anoxic or has become anoxic with recent human
110 influence. This kind of temporal, in situ monitoring is not possible with soft-bottom
111 sediment macrofauna because they do not leave abundant or, for most species, any fossil
112 records. Benthic foraminifera may thus provide a powerful tool for defining habitat-specific,
113 in situ reference conditions for soft-bottom coastal and transitional waters. Although the
114 response of macrofauna and foraminifera species to environmental gradients may partly
115 differ (Mojtahid et al. 2008), the few studies comparing the two groups have indicated that
116 their responses to environmental changes are basically similar (Schafer et al. 1975, Schafer
117 et al. 1995, Klitgaard-Kristensen & Buhl-Mortensen 1999, Bouchet 2007, Denoyelle et al.
118 2010, Dolven et al. 2013, Hess et al. 2013, Wlodarska-Kowalczuk et al. 2013). For instance,
119 benthic foraminiferal and macrofaunal communities showed similar response to oil-based
drill mud disposal with tolerant and opportunistic species dominating in the vicinity of the disposal area (Denoyelle et al. 2010). Furthermore, calcareous foraminifera can be reliable indicators for variability in density, diversity and species composition of benthic macrofauna in the Artic at Svalbard (Wlodarska-Koawalczuk et al. 2013). Hence, it is reasonable to suggest that macrofaunal and foraminiferal species with similar sensitivity to environmental changes may show co-occurrence. This would be of great interest when it comes to the definition of reference conditions. It is reasonable to think that fossil benthic foraminifera could be used as proxies to define reference conditions for benthic macrofauna communities. Further baseline studies are however necessary to validate such a hypothesis. It is thus urgent to quantify the level of correlation between the distribution patterns of these two groups in other environments.

In the present study, living benthic foraminifera and macrofauna were investigated in fjordic systems along the Norwegian Skagerrak coast to assess to which degree their responses to major driving environmental factors correspond. This work is part of a comprehensive project (PES), which includes both foraminifera and macrofauna collected at the same sites at the same time. An understanding of the driving forces of the benthic foraminifera communities, expressed as species diversity, was partly achieved in a previous analysis of the same data set (Bouchet et al. 2012, 2013). The present paper aims (i) to determine the driving environmental factors of both the benthic foraminiferal and macrofaunal community structures, (ii) to identify indicator species of both normal and poor environmental conditions, (iii) to compare species assignment in EG from this study to the existing Foram-AMBI and AMBI species lists, and (iv) to assess the correlation between benthic foraminiferal and macrofaunal communities patterns to identify the potential of
143 benthic foraminifera to serve as a proxy for benthic macrofauna in environmental
144 assessments.

145

146 **2. Material and methods**

147

148 **2.1 Study area and sampling sites**

149

150 In August 2008, 27 stations from 11 silled basins along the Norwegian Skagerrak
151 coast, NE North Sea (Figure 1), were sampled for bottom water, sedimentological,
152 biogeochemical and faunal analyses. Stations between 23 and 204 m water depth were
153 selected to provide an oxygen gradient with stable temperature (5-6°C; occasionally 8-9°C at
154 <40 m depth) and salinity (33-34) conditions (Table 1; see Bouchet et al. 2012 for further
details) using information from previous studies (Buhl-Mortensen et al. 2009 and
155 unpublished data from the Norwegian Institute for Water Research (NIVA) and Institute of
156 Marine Research (IMR)). The study basins commonly experience partial to complete deep-
157 water renewals during winter. In addition to measured variables, the depth below threshold
158 (DBT) i.e. the difference between the water depth at a station and the sill depth of the
159 fjord, has been characterized for stations. DBT is not a factor sensu stricto, but a measure
160 that reflects the degree or duration of water stagnation in the deep areas of the fjord.
161

162

163 **2.2 Field sampling**

164

165 Four sediment cores (8 cm diameter) were collected at each of the 27 stations with a
166 Gemini gravity corer, a modified Niemistö corer (Niemistö 1974). Three replicate cores were
167 used for benthic foraminifera and one for pigments, total organic carbon and total nitrogen
168 analyses. Once on deck, bottom water samples from just above the sediment-water
169 interface in two cores were immediately transferred to Winkler bottles for subsequent
dissolved oxygen analysis. All sediment cores were sectioned on board and, for the present
170 study, the top 0-1 and 1-2 cm slices were analysed. Sediment samples for pigments, total
171 organic carbon and total nitrogen analyses were frozen immediately after sectioning, and
172 kept away from the light. Foraminiferal samples were preserved in rose Bengal-stained 70%
173 ethanol (1 g l⁻¹) to avoid protoplasm degradation and to distinguish living (stained) from
174 dead specimens (Murray & Bowser 2000). At each station, macrofauna was sampled using a
175 0.1 m² van Veen grab (4 replicates) and a sub-sample of the top 0-1 cm from one grab per
176 station was collected for grain size analyses. The grab sediments were sieved on board
177 through 1 mm screens and fixed in 4% buffered formaldehyde in seawater to preserve
178 macrofauna specimens.
179

180

## 2.3 Biogeochemical analyses

182

183 Bottom-water dissolved oxygen concentrations at the time of sampling were
184 analysed using Winkler titration. Classification of stations as normoxic (bottom-water [O₂] >
185 2 mL O₂·L⁻¹), hypoxic (0.5 - 2 mL O₂·L⁻¹) or severe hypoxic (< 0.5 mL O₂·L⁻¹) follows Diaz and
186 Rosenberg (1995). Sediments were freeze-dried prior to sedimentological and geochemical
187 analyses. For grain size analyses, the dried sediment was weighed, soaked in tap water, and
188 washed on a 63 µm Endecote-sieve. The >63 µm fraction was dried and weighed and the
189 <63 µm-fraction was calculated based on the dry mass. Total organic carbon (TOC) and total
190 nitrogen (TN) were analysed following acid treatment (10% HCl) to remove inorganic C using
191 a CHN analyser (Carlo Erba Elemental Analyzer 1106). Classification of stations as low
192 (<2.7%), medium (2.7-3.4%) and high (>3.4%) TOC content follows that of Molvaer et al.
193 (1997). For pigment analyses, homogenised freeze dried sediment (0.3-0.6 g) was extracted
194 in 5 ml 90% acetone in water. The mixture was sonicated for 30s before overnight
195 extraction. The extract was centrifuged (15 min. at 3500 rpm), and 100 µL of the
196 supernatant was injected on the HPLC for pigment analysis. The analytical system was based
197 on a method described earlier (Wright et al. 1991, Jeffrey et al. 1997). Pigments were
198 identified by comparison of retention time and absorption spectra of authentic standards
199 (DHI Water and Environment, Denmark) and the literature (Jeffrey et al. 1997). Individual
200 pigments were quantified at 436 nm for chlorophylls and pheopigments, and 450 nm for
201 carotenoids. Response factors (RF) for each pigment were obtained by single standard runs.
202 When no standard was available, RF for similar pigments was used with a correction for
203 differences in mass. Pigment concentrations were standardised by the total organic carbon
204 content (Reuss et al. 2010).

205

206 **2.4 Faunal analyses**

207

208 Foraminiferal samples were washed through 500 and 63 µm mesh sieves, and the
209 63-500 µm fraction was split into 8 using a modified Elmgren wet splitter (Elmgren 1973).
210 One eighth of each sample was re-sieved and all live (stained) foraminifera in the 63-125
211 and 125-500 µm fractions were identified to species level and counted in the wet state. The
212 number of individuals >500 µm relative to smaller ones was trivial (<0.1%) so including them
213 would not influence the results. Wet-sample analysis allows preservation of all species,
214 including fragile organic-walled and loosely cemented agglutinated foraminifera. This study
215 is based on the 63-500 µm fraction i.e. the sum of 63-125 and 125-500 µm fractions.

216 In the laboratory, macrofaunal samples were rinsed on 1 mm-mesh sieves and
217 transferred to 70% ethanol. All macrofaunal specimens were counted and identified to
218 species level, or the lowest identifiable taxonomic unit.

219 Assignments of foraminiferal and macrofaunal species into ecological groups (EG)
220 were made according to Alve et al. (2016) and Borja et al. (2000), respectively. The concept
221 is based on the classification of species (or groups of species) into five EGs (sensitive,
222 indifferent, tolerant, 2nd order opportunist and 1st order opportunist) representing specific
223 sensitivity levels to an increasing gradient of organic matter (Borja et al. 2000). The groups
224 allow the assessment of the ecological quality status of marine systems.

225

226 **2.5 Numerical analyses**

227

228 Principal components analysis (PCA) was applied on the set of environmental
229 variables to characterize the main natural gradients and describe relationships between
230 sediments, oxygen and fjord topography. For the species community data, initial detrended
231 correspondence analyses indicated that the gradient is short (1.6 SD) in the foraminiferal
232 data and long (3.3 SD) in the macrofaunal data. Consequently, redundancy analysis (RDA)
233 and canonical correspondence analysis (CCA), respectively, were applied to find which
234 environmental variables were most clearly related to the species communities. Analyses
235 were done on the subset of 15 stations with all chemistry data and at least 30 individuals
236 in the pooled macrofaunal sample (all pooled foraminiferal samples had many more than 30
237 individuals). Community data were log(x + 1) transformed prior to analysis; taxa occurring at
238 only one station were removed. Environmental variables were selected using forward selection with 999 permutations. Procrustes analysis (Peres-Neto & Jackson 2001) was used to compare unconstrained ordinations of the foraminiferal (PCA) and macrofaunal (correspondence analysis) community data. The m² statistics, which is analogous with the r² of a correlation, is reported. Co-correspondence analysis (Co-CA, Ter Braak & Schaffers 2004) was used to relate the foraminiferal and the macrofaunal communities in a direct way.

245 All calculations were performed using the statistical language R version 3.4.1 (R Core Team, 2017). Ordinations were run with the vegan version 2.4-3 (Oksanen et al. 2010). R code is archived at https://github.com/richardjtelford/PES.

248

249 **3. Results**

250

251 **3.1 Environmental conditions at sampling stations**

252

253 Depth-below threshold (DBT), bottom-water dissolved oxygen concentration, sediment grain size and sediment organics were rather different among the stations (Table 1). Sandnesfjord, Eidangerfjord, Risørbassenget (R60), Topdalsfjord, Groosefjord, Frierfjord (except F70) and Indre Hvaler have rather shallow DBT below 50 m, whereas the other fjords have DBT up to 169 m. In Kristiansandsfjord there is no sill. High (normoxic) bottom-water oxygen concentrations (>2 mL O₂·L⁻¹) characterized stations in the Indre Hvaler basin, Kragerøfjord, Topdalsfjord, the shallower stations in Groosefjord, Frierfjord (F30 and F50), Ærøydypet, Sandnesfjord, Eidangerfjord and Kristiansandsfjord as opposed to stations in Risørbassenget (except R60), the deeper stations in Frierfjord (F70 and F90) and Håøyfjord

254

255

256

257

258

259

260

261
262 where hypoxic (0.5-2 mL O₂·L⁻¹) to severe hypoxic (<0.5 mL O₂·L⁻¹) conditions are recorded.

263 Sediments at stations in Risørbassenget (except R160 and R180) and Kristiansandsfjord, as
264 well as station G50 were sandier than the others, with less than 90% of the sediment mass <
265 63 µm (Table 1). Total organic carbon concentrations were higher than 3.4% in Ærøydypet,
266 Kragerøfjord, Sandnesfjord, Eidangerfjord, Risøbassenget, Topdalsfjord, Frierfjord (F90) and
267 Groosefjord (Table 1).

268 In the PCA of environmental variables, the first two axes explained 75.2% of the
269 variance (Fig. 2). Two main gradients appear; one related to sediment components (particle
270 fine fraction, TOC) and one to oxygen and fjord basin topography (O₂, DBT). The sediment
271 gradient separates stations with very high fine fraction and moderate organic content
272 (lower left: Indre Hvaler IH, Frierfjord F) from stations with lower fine fraction and high
273 organic contents (upper right: Groosefjord G, Risørbassenget R). The oxygen - fjord
274 topography gradient separates stations in deep fjord basins with shallow sill and low oxygen
275 content (lower right: Risør basin R, Håøyfjord 102, deep Frierfjord F) from stations with
276 either shallow water depths or in fjords with deep sills (upper left). The pigments correlate
277 with DBT and characterized the deep basins, particularly the Risør basin. Most pigments
278 were intercorrelated, except allo-xanthin that appeared to be related also to the sediment
279 fine fraction.

280

281 **3.2 Environmental variables and fauna**

282

283 In total, 116 foraminiferal taxa and 290 macrofaunal taxa were identified. Benthic
284 foraminifera occurred in all samples, whereas macrofauna were absent from station F90
285 (replicate 1 and 2), station R120 (replicate 4), station R160 (all replicates) and station R180
286 (all but replicate 1). Based on RDA and CCA, respectively, benthic foraminifera and
287 macrofauna species were significantly related to the same subset of environmental
288 parameters, viz. TOC and DBT (Figs 3 and 4). Together, the selected parameters explained
289 43% and 29% of the variation for foraminiferal and macrofaunal species assemblages,
290 respectively.

291 The distribution of foraminiferal taxa in relation to TOC and oxygen, the latter being
292 related to DBT (Fig. 2), is illustrated in Fig. 5. The species *Micrometula hyalostriata*,
293 *Phainogullmia aurata* and *Spiroplectammina biformis* mainly occur at low TOC (<2.7%) and
294 high bottom-water oxygen concentrations. Highest abundances of *Cassidulina laevigata* and
295 *Bulimina marginata* were observed at stations with low to high TOC (0.8-9%) and high
296 bottom-water oxygen concentrations. *Cylindrogullmia alba* and *Leptohalysis scottii* occur at
297 similar TOC levels but at stations with high to low bottom-water oxygen concentrations.
298 *Liebusella goësi*, *Textularia earlandi* and *Recurvoides trochamminiforme* show highest
299 abundances under TOC concentrations between 3.0 and 4.3% and well-oxygenated
300 conditions. *Stainforthia fusiformis*, *Discorbinella bertheloti*, *Fissurina* sp. and *Bolivinellina*
301 *pseudopunctata* thrive under high TOC concentrations (>3.4%) and hypoxic to severe
302 hypoxic conditions.

303 Compared to the assignments of foraminifera in Alve et al. (2016) four new species
304 (*Micrometula hyalostriata*, *Phainogullmia aurata*, *Cylindrogullmia alba*, *Leptohalysis scottii*)
305 were assigned and three (*Cassidulina laevigata*, *Liebusella goësi*, *Bolivinellina*
306 *pseudopunctata*) were re-assigned based on their abundance relative to sediment TOC in
307 this new data set (Table 2).

308 The distribution of dominant macrofaunal species on TOC and oxygen is illustrated in
309 Fig. 6. *Pseupopolydora* sp., *Chaetozone setosa*, *Capitella capitata*, *Thyasira* cf. *sarsii* occurred
at hypoxic stations with high TOC. *Mediomastus fragilis* was overabundant in

Kristiansandfjord that is contaminated from trace elements. *Thyasira equalis* and

*Spiophanes kroeyeri* occurred at well-oxygenated stations with medium TOC content.

*Amphiura chiajei*, *A. filiformis* and *Scalibregma inflatum* occurred at normoxic stations (Fig.

6B) with low organic matter concentrations (Fig. 6A).

Compared to the assignments of the AMBI list (Borja et al. 2000, last update: June

2017), two species (*Scalibregma inflatum* and *Thyasira cf. sarsi*) were re-assigned based on

their abundance relative to sediment TOC in this new data set (Table 2).

## 3.3 Foraminiferal and macrofaunal community relationships

Foraminiferal and macrofaunal community data were significantly correlated

(Procrustes analysis $m^2$ = 0.66, $p$ = 0.001). Using a co-correspondence analysis on

foraminiferal and macrofaunal community, 24% of the variance in the macrofaunal

community was explained by the foraminiferal community (Fig. 7).

## 4. Discussion

In the present study, patterns of distribution of foraminiferal and macrofaunal

species are best explained by the variables of TOC and DBT. Along the same lines, deep-

water renewal and oxygenation in a fjord depend on DBT as well as on the supply of organic

matter (i.e., impacts oxygen consumption). DBT will, however, also represent the influence

of other variables, e.g. pigments, different organic components and temperature, that
increase or decrease due to the gradually changing conditions with depth. In the following discussion, however, it will be made reference to oxygen rather than of DBT sensu stricto that may incorporate several unknown factors. This is further supported by Bouchet et al. (2012) who showed on the same dataset that benthic foraminiferal diversity is correlated to bottom-water dissolved water oxygen. These two variables (oxygen and TOC) are indeed known to be drivers of both diversity and species composition of benthic foraminifera and macrofaunal communities (Alve 1990, Riera et al. 1999, Gustafsson & Nordberg 2000, Rosenberg et al. 2002, Bouchet et al. 2012). In the studied Norwegian fjords, benthic foraminiferal and macrofaunal species responded in the same way to different environmental conditions (Procrustes analysis), except that macrofauna was less tolerant to the oxygen depleted conditions. This is because, unlike macrofauna, some foraminiferal species can perform anaerobic metabolism (e.g., Risgaard-Petersen et al. 2006). Our findings confirmed the results from the few studies assessing and comparing the response of benthic foraminifera and macrofauna to different environmental conditions, mentioned in the introduction.

349

## 4.1 Foraminiferal indicator species

351

In this study, *Micrometula hyalostriata*, *Phainogullmia aurata* and *Spiroplectammina biformis* are sensitive (EG1) to organic enrichment, occurring primarily in normoxic conditions. *Phainogullmia aurata* has been described as a pioneer species showing maximum abundance in the colonization phase on uncontaminated clay and almost disappearing with time as the amount of sediment organic material increased (Hess et al.

356
2014). The ecology of the soft-walled species *M. hyalostriata* is poorly known. In this study, it was common only at normoxic, low-TOC sites (Fig. 5). *Spiroplectammina biformis* was the second-most common species in the most hypoxic parts of the organic matter enriched Drammensfjord, southern Norway (Alve 1995) but it was not able to survive persistent severe hypoxia below 0.5 mL O₂·L⁻¹ (Alve 1991, 1995). It was also reported to tolerate organic enrichment in several eastern Canadian estuaries and embayments and in the North-east Atlantic (Alve et al. 2016, Schafer et al. 1991). In the present study, its highest abundance was at a low-TOC site. It was also sensitive to TOC in the Saguenay fjord and in a study in Canadian fish aquaculture sites (Schafer et al. 1991, 1995).

*Cassidulina laevigata* and *Cylindrogullmia alba* show the same distribution pattern along the TOC gradient as for species from the indifferent EG2. *Cassidulina laevigata* is a typical species of the Skagerrak-Kattegat fauna (sensu Nordberg et al. 2000), which used to flourish in several Scandinavian fjords until it was replaced by species associated with frequent coastal hypoxia (e.g., Alve 1991, Polovodova Asteman & Nordberg 2013, Polovodova Asteman et al. 2015). In the present study, *C. laevigata* is never abundant, it only occurs at stations with normoxic conditions and mainly, but not solely, where TOC is low to moderate (Fig. 5). Hence, *C. laevigata* may belong in the indifferent group EG2, although it has been classified as a sensitive species (Alve et al. 2016). The present results show that *C. alba* can survive under a wide range of TOC concentrations.

*Bulimina marginata*, *Recurvoides trochamminiforme*, *Liebusella goësi* and *Textularia earlandi* are all tolerant species (EG3) to organic enrichment in the studied fjords, occurring in normoxic conditions. *Bulimina marginata* is tolerant to oxygen-depleted conditions (Alve 1991, Barmawidjaja et al. 1992). However, it is not able to survive persistent severe hypoxia below 0.5 mL O₂·L⁻¹ (Filipsson & Nordberg 2004). In this study, it occurred over a broad
range of TOC concentrations, but only under normoxic conditions. As for *R.*

*trochamminiforme*, Alve et al. (2016) mentioned it as a tolerant species. *Liebusella goësi* is
known not to survive severe hypoxia (Nordberg et al. 2000, Filipsson & Nordberg 2004).

Tolerance to TOC enrichment under appropriate oxygen concentrations has already been
observed for *T. earlandi* (Schafer et al 1995). It is however sensitive to oxygen depletion
(Gustafsson & Nordberg 2000, Polovodova Asteman et al. 2015). Its abundance decreased at
dissolved-oxygen concentrations below 1.0 ml O₂.L⁻¹ (Gustafsson & Nordberg 2000).

*Bolivinellina pseudopunctata*, *Stainforthia fusiformis*, *Leptohalysis scottii* and
*Fissurina* sp. are assigned in the opportunistics EG4/5, thriving well in sediment with high
TOC content based on this study results, occurring at hypoxic to severe hypoxic stations. The
two first species are known to be able to survive at high TOC and hypoxic to severe hypoxic
conditions (Alve 1994, Gustafsson & Nordberg 2000, Alve 2003). These species
outcompeted the typical Skagerrak-Kattegat species throughout the degradation of the
environmental conditions in the area during the 1900s (Gustafsson & Nordberg 2001, Alve
et al. 2009, Dolven et al. 2013). *Bolivinellina pseudopunctata* is an opportunistic species able
to tolerate low oxygen conditions (Gustafsson & Nordberg 2001), although it has been
reported to disappear after periodic severe hypoxia or anoxia (Gustafsson & Nordberg
2000). The observation of this species in the most organic rich stations supports that it is an
opportunistic species, which is not in agreement with the classification of Alve et al. (2016)
in the indifferent EG2. Our results suggest that *L. scottii* is able to survive under hypoxic
conditions as opposed to what has been reported in Havstensfjord in Sweden (Gustafsson &
Nordberg 2000). Furthermore, it occurs in this study in fjords with a wide range of TOC
concentrations from 2 to 9%. It is a species known to tolerate environmental disturbances
such as paper mill and fish farming effluents (Alve & Nagy 1986, Scott et al. 2001,
Polovodova Asteman et al. 2015) and it is common in eutrophic environments (Scott et al., 2005; Sabbatini et al., 2012). *Stainforthia fusiformis* is a characteristic species of heavily disturbed environments (see review in Alve 2003). Except that species of *Fissurina* seem to be ectoparasites on *Discorbis vilardeboanus* (d'Orbigny) and *Rosalina bradyi* (Cushman) (see Collen & Newell, 1999, and references therein), little is known about the ecology of *Fissurina* spp. In the present material, *Fissurina* sp always co-occurs with *Discorbinella bertheloti*, perhaps as a parasite?

*Discorbinella bertheloti* (also found under the name *Cibicides bertheloti*) was found alive (stained) at hypoxic and severe hypoxic stations. With their epifaunal mode of life (Murray 2006), *Cibicides* spp. have been considered as sensitive species not directly linked to sedimentary TOC (Alve et al. 2016). They rather reflect the impact of bottom-near currents (Linke & Lutze 1993). Hence, occurrence of *D. bertheloti* at the most oxygen-depleted stations with high TOC content was probably due to recent transport of living specimens. It is thus difficult to conclude on the indicative value of this species.

419

## 4.2 Macrofaunal indicator species

421

In this study, *Amphiura chiajei*, *A. filiformis*, *Scalibregma inflatum* are sensitive species (EG1) to TOC, occurring at normoxic stations. They are known to not tolerate oxygen-depleted conditions (Aschan & Skullerud 1990, Nilsson & Rosenberg 1994, 2000, Rosenberg et al. 2001). The three species have been reported to solely occur at unpolluted sites in the Oslofjord (Mirza & Gray 1981). A high abundance and biomass of *A. filiformis* and *A. chiajei* has been observed at well oxygenated sites in the Skagerrak (Josefson 1990).
According to AMBI's ecological groups (EG) of sensitivity to disturbances (Borja et al. 2000),
A. chiajei and A. filiformis are indifferent species (EG2) and S. inflatum is a tolerant species (EG3). Amphiura filiformis has been reported to be sensitive to severe disturbances around oil platforms (Olsgard & Gray 1995). Note that the tolerance level of S. inflatum is rather uncertain since it has been reported to be either sensitive (Mirza & Gray 1981, Rygg 1985b, Nilsson & Rosenberg 1994, 2000, Rosenberg et al. 2001, Pabis & Sobczyk 2015) or tolerant (Rygg 1985a, Aschan & Skullerud 1990, Borja et al. 2000, Levin et al. 2009) to disturbances.

Thyasira equalis and Spiophanes kroeyeri dominate at well-oxygenated stations moderately rich in organic matter. They are not present at the hypoxic/severe hypoxic stations, suggesting that neither of the species would tolerate low oxygen concentrations.

This contradicts other works on these species (see review in Levin et al. 2009). For instance, T. equalis has been reported to survive low-oxygen concentrations (Josefson & Widbom 1988, Nilsson & Rosenberg 2000). It usually occurs in moderately disturbed areas (Pearson 1975, Mirza & Gray 1981, Rygg 1985a), although it has been reported not to tolerate copper pollution (Rygg 1985b). The results of the present study are in accordance with the classification of T. equalis in the tolerant EG 3 (Borja et al. 2000). Conversely, S. kroeyeri has been mostly reported to disappear in the early stage along a gradient of increasing disturbances i.e. oil platform activities, sewage outfall, copper, organic enrichment, oxygen depletion (Mirza & Gray 1981, Rygg 1985b, Aschan & Skullerud 1990, Nilsson & Rosenberg 2000, Mojtahid et al. 2008, Oug et al. 2012). Few studies nevertheless reported the presence of this species in low disturbed sites (Pearson 1975, Gray & Pearson 1982, Rygg 1985a, Moore & Rodger 1991). The classification of S. kroeyeri in the tolerant EG3 (Borja et al. 2000) is at least questionable.

Pseupopolydora sp., Chaetozone setosa, Capitella capitata and Thyasira cf. sarsii occur at stations with hypoxic conditions and high TOC contents. Mediomastus fragilis
dominates in the heavily polluted with trace metals Kristiansandfjord. It belongs together with *T. cf. sarsii* to the tolerant EG3, *C. setosa* and *P. sp.* belong to the second-order opportunistic EG4 and *C. capitata* to the first-order opportunistic EG5 (AMBI-list, Borja et al. 2000). They are all characterizing low-oxygenated environments (Levin et al. 2009).

*Mediomastus fragilis* can tolerate pollution such as oil spills, disturbances associated to oil platforms, metals and high level of organic enrichment (Pearson & Rosenberg 1978, Mirza & Gray 1981, Dauvin 2000, Mojtahid et al. 2008, Oug et al. 2012). *Thyasira cf. sarsii* is sensitive to low oxygen concentrations (Josefson & Widbom 1988, Nilsson & Rosenberg 2000) but it can colonize sediments polluted by copper, organic matter, and dredging materials from oil platform activities (Pearson 1975, Rygg 1985b, a, Olsgard & Gray 1995). *Capitella capitata* and *P. spp.* are known colonizers of completely anoxic sediments in fjord systems (Rosenberg et al. 2001). They are often the last species to survive these depleted conditions (Pearson & Rosenberg 1978, Mirza & Gray 1981, Oug et al. 2012). *Chaetozone setosa* and *C. capitata* are typical indicators of severe effects around oil platforms of the Norwegian continental shelf (Olsgard & Gray 1995). *Chaetozone setosa* usually thrives in depleted conditions (Rygg 1985a, Olsgard & Hasle 1993, Pabis & Sobczyk 2015). It is a common species in organic enriched areas (Gray et al. 1990).

### 4.3 Concerns about the indicative value of classified species

The use of the presence of certain species to assess the state of marine systems has a long history. The concept is based on an *a priori* apprehension that some species have narrow ecological requirements. Hence, species are meant to be indicative of the prevailing conditions where they are found. Based on numerous works (e.g., Pearson & Rosenberg
1978, Glémarec & Hily 1981, Hily 1983), lists of benthic macrofaunal species, assigned into groups of sensitivity to disturbances, have been established; the most widely used being the species associated to the AMBI index (Borja et al. 2000). Lately, following the suggestions of the FOBIMO working group, the same approach was used to assign benthic foraminiferal species to EGs of sensitivity/tolerance to conditions along an increasing stress (organic matter enrichment) gradient (Alve et al. 2016, Jorissen et al. 2018). So far, assignment of foraminiferal species has only been done for the North-East Atlantic and Arctic fjords, continental shelves, and slopes and for the Mediterranean (Alve et al. 2016, Jorissen et al. 2018). The use of a single species list classification means that the indicative value of a species is a static concept i.e. a species is expected to have a similar sensitivity or tolerance wherever it occurs and regardless of the adaptation ability of this species. However, it is known that some species are plastic enough to adapt to their environment and could change their autecology requirements along environmental gradients (see review in Zettler et al. 2013 and references therein). Hence, a species tolerance spectrum might be wider than a single category, i.e. "sensitive species" or "tolerant species". Species even exhibit different responses to disturbance depending on their habitat and the source of disturbances; they behave as sensitive species while they can be tolerant or opportunistic somewhere else or against a different pollution source (Zettler et al. 2013). The biogeographical/ecosystem-type restricted approach chosen to assign foraminiferal species tend to support the ability of species to adapt their sensitivity/tolerance level to their environment.

In this study, we reported discrepancies in the assignment in EG with the study of Alve et al. (2016) for *S. biformis*, *C. laevigata*, *L. goësi* and *B. pseudopunctata*. For *C. laevigata*, our study results suggest a classification in the indifferent EG2 instead of the
sensitive EG1 (Alve et al. 2016). These two EGs are rather close conceptually since they
include species that cannot tolerate any excess in organic matter. Some biotic indices, i.e.
Bentix (Simboura & Zenetos 2002), group these two EGs in one EG. This might be something
to consider in a further implementation of the Foram-AMBI list. Spiroplectammina biformis
was assigned to the tolerant EG in the Foram-AMBI list of species from the North-East
Atlantic (Alve et al. 2016). In several eastern Canadian estuaries and embayments, S.
biformis has been reported in moderately polluted local environments (Schafer et al. 1991).
This study results however suggest that it is a sensitive species to TOC enrichment. In the
Saguenay fjord, S. biformis abundances have also been reported to decrease with increasing
organic matter load from a pulp mill effluent (Schafer et al. 1991). In a study in four
Canadian aquaculture sites, it showed a significant negative correlation to TOC enrichment
due to the presence of fish cages (Schafer et al. 1995). These evidences suggest that it is
thus not sure whether this species belongs to the sensitive EG1 or the tolerant EG3.
Discrepancies in the response of species to TOC enrichment have been found between this
study results and previous work for both benthic foraminifera and macrofauna. As for
benthic macrofauna, there are eight studies, including this one, reporting a sensitive
behavior of the polychaete S. inflatum towards disturbances and at least four reporting a
tolerant one (see aforementioned references). In the AMBI species list, this species is
assigned to the tolerant EG. The assignment of S. inflatum within the AMBI list is rather
uncertain. The same concerns arose about T. cf. sarsii which behave like an opportunistic
species in this study and is assigned to tolerant EG in the AMBI-list. Occurrences of T.
equalis, S. kroeyeri and S. inflatum in several Norwegian fjords and coastal areas (Rygg &
Norling 2013) showed tolerance levels corresponding to EG3 (tolerant), thus supporting the
classification in the AMBI system. These discrepancies may be due to the fact that indices'
scores come from large dataset collections covering large geographical regions and subregions and not local scales (Borja et al. 2000, Rosenberg et al. 2004). Hence, they integrate the "experience" from a species behavior over a large span of data or literature data. Local adaptation of species ecological requirement may lead to wrong interpretation of the species indicative value (Dauvin et al. 2010, Zettler et al. 2013).

Zettler et al. (2013) reported that the response of macrofaunal species towards organic enrichment would change along a gradient of salinity. They concluded that the interaction between environmental variables should not be neglected when using static indicative value of a species. This study results tend to confirm the latest concerns about the concept of species lists of tolerance/sensitivity. Furthermore, this study shows that these concerns may apply to benthic foraminifera. At a large biogeographical scale, the indicative value may be reliable, but it is rather uncertain at a local geographical scale. This study results definitively support cautions (Dauvin et al. 2010, Zettler et al. 2013) when it comes to the use of indicator species lists. It seems obvious that more studies are needed to constrain these biases. Supplementary approaches should be considered, for instance rank-frequency diagrams (Frontier 1976, Bouchet et al. 2007, Seuront 2013) and diversity indices (Bouchet et al. 2012, Dolven et al. 2013, Francescangeli et al. 2016, Bouchet et al. 2018).

542

## 4.4 Benthic foraminifera as indicator of macrofaunal community structure

544

The assessment and quantification of cross-taxon congruence i.e. similar response along an environmental gradient of species belonging to different taxa, in space and time, represents a critical step in the identification of suitable indicator taxa for biodiversity. In this study, Procrustes rotation and co-correspondence analysis (Co-CA) were used to
quantify the strength of the congruence between foraminiferal and macrofaunal
communities along the studied environmental parameters gradient. Procrustes rotation and
Co-CA are powerful and robust methods to evaluate the degree of congruence between two
community datasets (Peres-Neto & Jackson 2001, Gioria et al. 2011). Patterns of
foraminiferal species distribution closely resembled those of the macrofauna, as is showed
by significant correlation between the groups. The strength of the congruence in species
composition between benthic foraminifera and macrofauna along the environmental
gradient reflects the similarity in their response to TOC enrichment. Interactions can explain
congruence in species between these two groups. First, there may be a trophic link between
the two groups; benthic macrofauna species being able to feed on benthic foraminifera
(Lipps 1983). Secondly, benthic macrofauna bioturbating activities enhance the vertical
distribution of foraminifera in deeper sedimentary layers (Bouchet et al. 2009). Last but not
least, there is an evident similarity in the patterns of distribution of species of both groups in
response to environmental gradients.

In this study, benthic foraminiferal and macrofaunal species composition appear to
respond to the same environmental factors, in particular bottom-water dissolved oxygen
and organic matter content. Changes in the composition of foraminiferal and macrofaunal
assemblages are expressed in increased dominance of tolerant/opportunistic species and
the progressive disappearance of sensitive species under degraded conditions i.e. increasing
TOC content and decreasing bottom-water oxygen concentrations. It supports other studies,
although there are few, showing similar response of the two groups to adverse
environmental conditions. Patterns of foraminiferal species distribution closely resembled
those of macrofauna in response to disturbances of a glacier (Wlodarska-Kowalczuk et al.
2013). Similar succession from sensitive to tolerant species has been reported for both
groups in response to different pollution sources such as sewage outfalls, industry, oil-based
573
drill mud disposal and aquaculture (Schafer et al. 1975, Schafer et al. 1995, Mojtahid et al.
574
2008, Denoyelle et al. 2010). However, some studies suggested that benthic foraminifera
575
could be more indicative than benthic macrofauna along a gradient of disturbances
576
(Mojtahid et al. 2008, Denoyelle et al. 2010). In this study, benthic foraminifera exhibited
577
more tolerance to the most depleted conditions (high TOC and anoxic conditions), by
578
maintaining higher densities than did the macrofauna. This confirms previous results
579
showing that benthic macrofauna is more sensitive than benthic foraminifera to depleted
580
oxygen conditions (Josefson & Widbom 1988) and, as previously mentioned, is directly
581
linked to the fact that some foraminiferal species perform anaerobic metabolism (e.g.,
582
Risgaard-Petersen et al. 2006). It implies that benthic foraminifera are able to occur along
583
the whole environmental gradient, which is an asset compared to benthic macrofauna in
584
monitoring studies when approaching the "bad" end of the environmental gradient. The
585
strength of the congruence between benthic foraminifera and macrofauna suggests that
586
foraminifera could be reliable indicators of benthic macrofauna community structure. This
587
has interesting implications, in particular with regard to defining reference conditions for
588
areas where the environmental conditions may have changed over time, as suggested by
589
Alve et al. (2009). Defining reference conditions are mandatory according to the WFD and
590
complying to MSFD when it comes to assessing the health of marine systems. Hindcasting is
591
one method that can be used to determine previous conditions. This is hardly possible with
592
benthic macrofauna since historical data are scarce. Mostly the molluscs can fossilise and
593
allow a reconstruction of palaeo-environments (Poirier et al. 2009), meaning that most of
594
the biological signal is lost in the fossil sediment. Conversely, most of the foraminiferal
595
community can fossilise and be preserved in the fossil sediment. It allows reconstruction of
596
597 palaeo-environments (e.g., Alve 1991, Alve et al. 2009, Dolven et al. 2013, Polovodova
598 Asteman et al. 2015, Francescangeli et al. 2016). Using fossil benthic foraminifera, it is
599 possible to determine objective and reliable reference conditions. Hence, fossil benthic
600 foraminifera could be used as proxies to assess the deviation from reference conditions for
601 benthic macrofauna communities. However, this requires an algorithm for translating
602 foraminiferal community data into macrofaunal community data (specified macrofaunal
603 species and their abundances). More conceivably, the ecological quality status has to be
604 estimated directly from the foraminiferal data. This requires an environmental classification
605 system using foraminiferal indices. The development of Foram-AMBI (Alve et al. 2016,
606 Jorissen et al. 2018) is one step towards such a system.
607

608 Acknowledgment
609

610 We are grateful to the crew of the R/V Trygve Braarud; S Holm, J. Sundøy and T.E.
611 Baade. Nina Reuss is warmly thanked for the analysis of pigment samples. Thanks are also
due to M. Hollerbach, and J. Håvardstun for assistance during fieldwork, and Y. Descatoire
612 for graphics. This study was supported by the Norwegian Research Council-funded project
613 PES (no. 184870) "Paleoecological reconstructions of marine soft-bottom Ecologic Status
614 and in situ reference conditions: calibrating benthic foraminifera with macrofauna and
615 hydrographic data". V.M.P.B. was supported through the PES project by a post-doctoral
616 fellowship. Thanks to Fede who waited few more days with the birth of Clelia for the first
617 version of this manuscript to be written.
618
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898 **Figure Captions**

899

900 Figure 1: Map of the sampling stations

901

902 Figure 2: Principal components analysis (PCA) of environmental variables: biplot of stations and variables for axes 1 and 2 (75 % of variation). Stations with one or more missing values have been omitted from analysis.

905

906 Figure 3: Redundancy analysis (RDA) of foraminiferal species assemblages: triplot of species (crosses), stations (dots) and significant environmental variables (vectors). Most dominant species are indicated by abbreviated names. Stations with missing data for environmental variables or strongly impoverished fauna have been omitted from analysis.

910

911 Figure 4: Canonical correspondence analysis (CCA) of macrofaunal species assemblages: triplot of species (crosses), stations (dots) and significant environmental variables (vectors). Most dominant species are indicated by abbreviated names. Stations with missing data for environmental variables or strongly impoverished fauna have been omitted from analysis.

915

916 Figure 5: Abundances (ind.m⁻²) of the main foraminiferal species at stations along (A) the TOC-gradient (%) and (B) the bottom-water dissolved oxygen concentration-gradient (mL O₂.L⁻¹). Definition of low (<2.7%), medium (2.7-3.4%) and high (>3.4%) level of TOC follows Molvaer et al. (1997). Definition of normoxia (bottom-water [O₂] > 2 mL O₂.L⁻¹), hypoxia (0.5 - 2 mL O₂.L⁻¹), severe hypoxia (< 0.5 mL O₂.L⁻¹) follows Diaz & Rosenberg (1995). Please note: different scales on the x-axes.
922

923

Figure 6: Abundances (ind.m⁻²) of the main macrofaunal species at stations along (A) the

924

TOC-gradient (%) and (B) the bottom-water dissolved oxygen concentration-gradient (mL

925

O₂.L⁻¹). Definition of low (<2.7%), medium (2.7-3.4%) and high (>3.4%) level of TOC follows

926

Molvaer et al. (1997). Definition of normoxia (bottom-water [O₂] > 2 mL O₂.L⁻¹), hypoxia (0.5

927

- 2 mL O₂.L⁻¹) and severe hypoxia (< 0.5 mL O₂.L⁻¹) follows Diaz & Rosenberg (1995). Please

928

note: different scales on the x-axes.

929

930

Figure 7: Biplot based on predictive co-correspondence analysis (CoCA) of foraminifera (left)

931

against macrofauna (right) showing 49% and 24% of the total variance in the foraminiferal

932

and macrofaunal data, respectively.

933

934

**Table captions**

935

936

Table 1: Characteristics of sampling stations (nd: no data): water depth, depth below

937

threshold (Norwegian Hydrographic Service), bottom-water dissolved O₂-concentration at

938

the time of sampling ([O₂]ₜ₀₅, mL O₂.L⁻¹), sediment grain size (%<63µm), total organic carbon

939

(TOC, %), Total nitrogen (TN, %) and C/N ratio of sampling stations. For location of areas, see

940

Fig. 1.

941

942

Table 2: Suggested new assignments into EGs for foraminifera and macrofauna species

943

according to Alve et al (2016) and Borja et al. (2000), respectively (na: not assigned).

944
<figure><img src="image_3.png" /></figure>
948

949 Figure2

<figure><img src="image_4.png" /></figure>

950

951
<figure><img src="image_5.png" /></figure>
<figure><img src="image_6.png" /></figure>
958 Figure5A

<figure><img src="image_7.png" /></figure>

959

960

961

962 Figure5B

<figure><img src="image_8.png" /></figure>

963

964
<figure><img src="image_9.png" /><figcaption>965 Figure6A</figcaption></figure>

966

<figure><img src="image_10.png" /><figcaption>967 Figure6B</figcaption></figure>

968

969
<figure><img src="image_11.png" /></figure>
<table><thead><tr><th></th><th>Station</th><th>Water depth (m) at stations</th><th>Depth below threshold (m)</th><th>[O<sub>2</sub>]<sub>tos</sub></th><th>Grain size</th><th>TOC</th><th>TN</th><th>C/N</th></tr></thead><tbody><tr><td>Ærøydypet</td><td>200</td><td>111</td><td>59</td><td>4.76</td><td>93</td><td>3.5</td><td>0.4</td><td>9.7</td></tr><tr><td rowspan="2">Kragerøfjord</td><td>71</td><td>138</td><td>118</td><td>4.25</td><td>98</td><td>4.3</td><td>0.5</td><td>7.9</td></tr><tr><td>KRG</td><td>102</td><td>79</td><td>4.67</td><td>94</td><td>3.6</td><td>0.5</td><td>7.2</td></tr><tr><td>Sandnesfjord</td><td>50</td><td>65</td><td>42</td><td>3.21</td><td>92</td><td>5.7</td><td>0.4</td><td>12.6</td></tr><tr><td>Eidangerfjord</td><td>106</td><td>103</td><td>43</td><td>4.31</td><td>96</td><td>3.7</td><td>0.2</td><td>15.5</td></tr><tr><td rowspan="6">Risørbassenget</td><td>R60</td><td>60</td><td>35</td><td>3.73</td><td>83</td><td>6.6</td><td>0.9</td><td>7.4</td></tr><tr><td>R80</td><td>80</td><td>56</td><td>1.36</td><td>89</td><td>5.8</td><td>0.6</td><td>10.1</td></tr><tr><td>R100</td><td>104</td><td>75</td><td>1.09</td><td>87</td><td>4.7</td><td>0.6</td><td>8.1</td></tr><tr><td>R120</td><td>124</td><td>99</td><td>0.47</td><td>90</td><td>6.0</td><td>0.6</td><td>10.5</td></tr><tr><td>R140</td><td>142</td><td>118</td><td>0.33</td><td>83</td><td>6.7</td><td>0.6</td><td>10.7</td></tr><tr><td>R160</td><td>157</td><td>134</td><td>0.29</td><td>91</td><td>7.0</td><td>0.7</td><td>10.4</td></tr><tr><td>R180</td><td>182</td><td>157</td><td>0.20</td><td>91</td><td>6.7</td><td>0.7</td><td>10.1</td></tr><tr><td>Håøyfjord</td><td>102</td><td>204</td><td>169</td><td>0.49</td><td>98</td><td>2.8</td><td>0.3</td><td>9.7</td></tr><tr><td>Topdalsfjord</td><td>6</td><td>74</td><td>42</td><td>2.52</td><td>94</td><td>6.7</td><td>0.5</td><td>12.5</td></tr><tr><td rowspan="4">Groosefjord</td><td>G40</td><td>40</td><td>17</td><td>3.85</td><td>nd</td><td>8.1</td><td>0.6</td><td>12.9</td></tr><tr><td>G50</td><td>54</td><td>31</td><td>3.25</td><td>84</td><td>9.0</td><td>0.7</td><td>12.5</td></tr><tr><td>G60</td><td>60</td><td>37</td><td>2.58</td><td>nd</td><td>8.8</td><td>0.7</td><td>11.7</td></tr><tr><td>G69</td><td>69</td><td>47</td><td>2.95</td><td>93</td><td>8.1</td><td>0.7</td><td>10.7</td></tr><tr><td rowspan="4">Frierfjord</td><td>F30</td><td>28</td><td>8</td><td>4.48</td><td>98</td><td>2.6</td><td>0.1</td><td>32.2</td></tr><tr><td>F50</td><td>52</td><td>32</td><td>3.30</td><td>92</td><td>3.2</td><td>0.2</td><td>13.3</td></tr><tr><td>F70</td><td>70</td><td>50</td><td>1.25</td><td>98</td><td>3.0</td><td>0.1</td><td>21.1</td></tr><tr><td>F90</td><td>91</td><td>70</td><td>0.67</td><td>98</td><td>4.2</td><td>0.2</td><td>17.8</td></tr><tr><td rowspan="3">Indre Hvaler</td><td>IH30</td><td>30</td><td>6</td><td>4.44</td><td>98</td><td>2.1</td><td>0.1</td><td>14.2</td></tr><tr><td>IH45</td><td>45</td><td>20</td><td>3.98</td><td>98</td><td>2.3</td><td>0.2</td><td>14.3</td></tr><tr><td>IH60</td><td>62</td><td>37</td><td>2.42</td><td>98</td><td>2.2</td><td>0.2</td><td>13.2</td></tr><tr><td rowspan="2">Kristiansandsfjord</td><td>KDR</td><td>23</td><td>nd</td><td>nd</td><td>58</td><td>0.8</td><td>0.1</td><td>14.6</td></tr><tr><td>KDC</td><td>31</td><td>nd</td><td>nd</td><td>52</td><td>2.7</td><td>0.2</td><td>14.6</td></tr></tbody></table>
<table><thead><tr><th></th><th>This study<br>EG</th><th>Foram-AMBI<br>EG</th></tr></thead><tbody><tr><td><strong>FORAMINIFERA</strong></td><td></td><td></td></tr><tr><td><em>Micrometula hyalostriata</em></td><td>1</td><td>na</td></tr><tr><td><em>Phainogullmia aurata</em></td><td>1</td><td>na</td></tr><tr><td><em>Cylindrogullmia alba</em></td><td>2</td><td>na</td></tr><tr><td><em>Leptohalysis scottii</em></td><td>4</td><td>na</td></tr><tr><td><em>Cassidulina laevigata</em></td><td>2</td><td>1</td></tr><tr><td><em>Liebusella goësi</em></td><td>3</td><td>2</td></tr><tr><td><em>Bolivinellina pseudopunctata</em></td><td>4</td><td>2</td></tr><tr><td><strong>MACROFAUNA</strong></td><td></td><td></td></tr><tr><td><em>Scalibregma inflatum</em></td><td>1</td><td>3</td></tr><tr><td><em>Thyasira cf. sarsii</em></td><td>4 or 5</td><td>3</td></tr></tbody></table>