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Zoobenthos as Indicators of Ecological Status in Coastal Brackish Waters: A Comparative Study from the Baltic Sea

Zoobenthos as Indicators of Ecological Status in Coastal Brackish Waters: A Comparative Study from the Baltic Sea
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  Jens Perus, Erik Bonsdorff, Saara Ba¨ck, Hans-Go¨ran Lax, Anna Villna¨s and Vincent Westberg Zoobenthos as Indicators of Ecological Statusin Coastal Brackish Waters: A ComparativeStudy from the Baltic Sea A new method for classifying soft-bottom zoobenthicassemblages along the Finnish coasts (northern BalticSea) is presented and tested against traditional physico-chemical monitoring data in the complex ArchipelagoSea. Although multivariate methods for assessing thestate of the marine environment have become widelyused, few numerical indices can operate over a widesalinity range. We compare indices currently in use andpropose a new index, BBI (brackish water benthic index),for the low-saline and species-poor Baltic coastal waters.BBI offers a salinity-corrected tool for classification of thesoft-bottom zoobenthos under the demands of theEuropean Union Water Framework Directive. INTRODUCTION Salinity in the Baltic Sea ranges from almost fully marine,greater than 25 practical saline units (PSU) at the entrance inthe Kattegat, to limnic, less than 1 PSU in the innermostreaches in the north (Gulf of Bothnia) and northeast (Gulf of Finland). There are strong vertical and horizontal gradients,including a permanent halocline at 50–70 m depth in the centralBaltic Sea (1).In the Baltic Sea, nutrient concentrations have increased fourto eight times during the twentieth century with profoundecological consequences, such as increased pelagic productivityand turbidity of surface layers (2), and shifts in biomassdistribution and altered trophic dynamics of the entireecosystem and food webs in it (3–5). Hypoxic and anoxicconditions in the Baltic Sea seem to be persistent in deep watersin open sea but have more of seasonal character in coastal areas.Karlson, et al. (6) give a good review of eutrophication andoxygen deficiency, and their effects on the benthic assemblagesin the Baltic Sea.Benthic soft-bottom communities in the Baltic Sea areprimarily structured by salinity, although depth, oxygensaturation, sediment characteristics, and nutrient concentra-tions also play significant roles in shaping the assemblages (7– 12). Many limnic and marine species meet their physiologicaltolerance limits in the Baltic Sea (see, e.g., 13).The European Union Water Framework Directive (EUWFD) (14) establishes a general framework for the protectionof groundwaters, inland surface waters, and transitional andcoastal waters; its aim is to achieve good ecological qualitystatus for all waters by 2015. The concept of ecological status isdefined in terms of the quality of the biological community(phytoplankton, macrozoobenthos, and macrophytes), accord-ing to the ecosystem approach philosophy, as well as thehydromorphological and physicochemical characteristics of thesystem. This requires robust methods to distinguish differentlevels of ecological quality when surface water areas areclassified. The concept of ecological status implies that in theabsence of comprehensive knowledge of all the pressures on awater body and of their combined biological effects, it willalways be necessary to get direct measures of the biologicalquality elements (15). This must be achieved by using biologicalindicators to validate any biological effects suggested bynonbiological indicators. Thus, the WFD highlights theimportance of measures able to elucidate the biological effectsof disturbance.Finnish coastal waters have been divided into 11 differenttypes, comprising inner and outer archipelago and sea areas indifferent geographic marine basins (16, 17). The typology, basedupon the B-system under the WFD (18, 19), has been tested forecological relevance and takes into account the biologicalcharacteristics of Finnish coastal areas (17). Until now, themonitoring and assessment of the coastal waters in Finlandhave mainly been based on physicochemical parameters and lesson biological parameters (20). In addition to integrating waterquality and biological monitoring, most national monitoringprograms need, to meet the WFD demands, to change theirstructure from station oriented to basin or system oriented withspecific cause–effect studies for highly dynamic coastal systems(21).One of the ecological quality elements in the WFD is benthicmacroinvertebrates, which is an established and long-recognizedcomponent in monitoring the environmental health of coastaland estuarine environments. Macrozoobenthos provide idealmeasures of community responses to environmental distur-bances and is an effective indicator of the extent and magnitudeof pollution impact in the local environment (22–24). Thedegree of pollution of the water is not necessarily the same asthat of the bottom, and the sediment–water interface, in whichthe long-term effects of discharged pollutants may be bettermonitored by using sessile or sedentary organisms as indicatorsintegrating the response to exposure and multiple stressors overrelatively a long time. Taxonomic diversity also ensures thatclassification into different functional response groups can bedone (25, 26). Signs of eutrophication in benthic communitiesare changes in abundance, biomass, and species composition,including increases in characterizing species or type species.Some of the species will respond to changes in food supply and/or sedimentation rates and/or lowered oxygen concentrations(9, 27). The complex benthic environment responds to anthro-pogenic loading and stress by creating a new communitystructure more tolerant to the increasingly unfavorable physi-ochemical conditions (28).Here we propose a classification method for environmentalstatus evaluation using benthic macroinvertebrate data fromcoastal monitoring programs in Finland. There is a variety of indices available for measuring the status of ecologicalconditions and trends in successions of marine benthic systems(Box 1). Indices integrate and simplify the masses of heteroge-neous information from monitoring, allowing for directcomparisons between data of varying volume and quality intime and space. In this paper we propose the brackish waterbenthic index (BBI; see Box 2), which follows the assumptionthat biodiversity increases with increasing distance from apollution source along a gradient of disturbance (7). 250  Ambio Vol. 36, No. 2–3, April 2007   Royal Swedish Academy of Sciences 2007  All of the Baltic Sea is regarded as being affected by humanactivities. Trying to reconstruct the structure of benthicassemblages of the past, historic data (at least 100 years of information—see, e.g., 29), serving as reference would be of greatest value. However, as for most areas in the Baltic, historicreference data are almost completely lacking from Finnishcoastal areas and the use of old data is therefore not an optionin determining reference conditions (30). In classifying coastalareas we have modified and adopted a model used in lake andriver studies in Finland (19).Caeiro et al. (31) argue that benthic indices generally fall intothree types based upon complexity and information content:  i) single community attribute measures (diversity, abundance/biomass-ratio),  ii)  multimetric indices (combined multiplemeasures of community responses into a single index), and  iii) multivariate methods (integrated species composition informa-tion). The use of a single indicator has not proven to be ideal formonitoring estuarine or coastal environments, which havehighly variable natural conditions (22, 32), and hence multivar-iate methods in assessing the state of the marine environmenthave become widely used (33).In this paper we introduce a new multimetric index, the BBI,which was developed while testing and evaluating alreadyexisting or proposed indices and their suitability for the species-poor brackish water conditions in the northern Baltic Sea (see,e.g., 34). The new index is tested for the most complex region,the Archipelago Sea, SW Finland. A comparison of BBI  vs. some commonly used indices (DKI, BMI, BQI, and AMBI; seeBox 1) is performed for a data set on degradation of the benthiccommunity by extensive organic loading (fish farming), and asubsequent recovery-period. MATERIALS AND METHODS The data used for the development of the BBI are from aFinnish environmental administration database for zoobenthos,covering the years 1990–2000, and contains some 8500 visitsfrom 1300 sites. The majority ( ; 90 % ) of the data were collectedusing an Ekman-Birge grab sampler and sieved on a 0.5-mmmesh. From each station the index is based on five replicategrab samples. When pooling grabs and transforming to m  2 units, the mean of abundances and total of species has beenused. Quality assurance of the database has included verifica-tion of taxonomy, and deleting synonyms or misspelled names.In this paper, taxonomy has been used at species level, exceptfor chironomids and oligochaetes, which were analyzed at thelevel of family and order, respectively.A depth separation of the water column (0–10 m and 10 þ m)was used in relation to the coastal typology. This was done to Box 1. Some European multimetric indices tested and evaluated duringclassification work on Finnish coastal waters AMBI  ¼  0  % I  ð Þ þ  1 ; 5  % II  ð Þ þ  3  % III  ð Þ þ  4 ; 5  % IV  ð Þ þ  6  % V  ð Þ½  = 100  ð Ref  :  24 ;  50 Þ BMI  ¼  2 1   AMBI7   þ  1    k 0 ð Þ 3  1    1 N    þ  1    1 S   2 ð Ref 50 Þ DKI  ¼ 1   AMBI7   þ  H  0 H  0 max 2  1    1 N    þ  1    1 S   2 ð Ref  :  50 Þ BQI  ¼ X Si ¼ 1 N  i N  tot   ES 50 0 ; 05 i  " #  10 log  S  þ  1 ð Þ  1    55  þ  N  tot     ð Ref  :  51 yÞ Definitions: H  0 ¼  X Si ¼ 1  p i    log  p i  ð log 2    base used Þ ð Shannon    Wiener  0 s index Þ k 0 ¼ X Si ¼ 1 N  i  N  i    1 ð Þ N N     1 ð Þ ð Simpson 0 s index Þ I–V   ¼  ecological groups classified according to sensitivity to environmental stress N   ¼  number of individuals S   ¼  total number of species or taxa (log 10-base used in BQI) ES  50  ¼  Hurlbert’s (52) modified rarefactionThese indices use 0.1 m  2 samples as calculation basis. Multiple indices have been tested and evaluated, and good overviews of existing indicesare found in (31) and (35).   When testing existing indices and starting developing and calculating the BBI-index only an older version of the BQI-index was published (53)where the abundance factor (right bracket) was absent. Ambio Vol. 36, No. 2–3, April 2007  251   Royal Swedish Academy of Sciences 2007  facilitate the interpretation of environmental status for theindividual types (17).The BBI was developed while testing and evaluating alreadyexisting indices used for environmental classification purposes(Box 1 and reviews by, e.g., 31, 35). Based on this experience,the BBI (Box 2) was developed for classification of zoobenthicassemblages for the Finnish low-saline and species-poor coastalwaters (for an overview of the biodiversity of the Baltic Seazoobenthos, see 13) in the Baltic Sea ecoregion. The BBIcompensates for the naturally low diversity in the Baltic Sea. Byclassifying species on a scale from sensitive to tolerant inrelation to mainly organic enrichment, and multiplying themaccording to their relative importance at a sampling site, we geta good estimate of the benthic community structure and itsfunction (for the species classification, see Box 2). Based on anevaluation of other indices, we added both abundance andbiodiversity as elements into the BBI for determining the qualityof the benthic community and therefore the index meets alldemands stated in Annex V of the WFD (14). To preventmisclassifications due to salinity gradients (34), type-specificmaximum values for BQI- and  H  0 variables have beencalculated from the entire content in the national database.BBI values are continuous between 0 and ; 1.For the actual classification of the coastal areas, we haveadopted and modified a model used for studies of lakes andrivers in Finland (19). Since true reference areas or conditionsare no longer present in the coastal areas in the Baltic Sea, thereference was defined as the median of the top 10 % highest BBI-values for each type and depth interval. Ecological quality ratio(EQR) values were then calculated by dividing observed valueswith the defined reference values. The border between ‘‘good’’and ‘‘high’’ environmental quality is set at the 10 % percentile of reference EQR. Values below this border are divided into fourequally broad classes (good–moderate–poor–bad).Here we propose classification results (Fig. 1) from a case-study area in the Archipelago Sea, SW Finland (59 8 45 0  –60 8 45 0 Nand 21 8 00 0  –23 8 00 0 E), containing three environmental types( Ls  ¼  inner,  Lv  ¼  middle, and  Lu  ¼  outer archipelago zone)(17, 19), ranging from inner sheltered archipelago areas to openand exposed coasts. Boundary values for the classification arefurther validated by checking species richness, abundance,diversity values (Table 1), and community composition of tolerant or sensitive species (Fig. 2a) against the defined criteriafor high, good, and moderate status in coastal waters describedin Annex V of the WFD. For each individual national Finnishcoastal type, comprehensive species lists have been compiled,and reference criteria can be set as a proportion of the totalnumber of species (alternatively number of sensitive species)that need to be present for the reference criteria to be met.An independent cross-evaluation of BBI in relationship tothe other indices in Box 1 was performed on a long-term dataset from the A ˚land Islands where effects from long-term fish Box 2. Information on the structure and content of the new brackish waterbenthic index. Explanation of factors in formulas and literature used inspecies classification is given. Brackish water benthic index (BBI) The BBI-index consists of following metrics:– Classification* (four levels) of sensitivity or tolerance of individual species (1, 5, 10, 15)1—very tolerant to pollution5—tolerant10—pollution sensitive15—very pollution sensitive– Relative abundance ( % ) of sensitive and tolerant species.– Shannon-Wiener diversity ( H  0 )(log2-base)– Abundance– Species richness BBI  ¼ BQIBQI max   þ  H  0 H  0 max  h i 2  1    1AB tot    þ  1    1S  h i 2 The index ranges from 0 to ; 1.Definitions:BBI  ¼  Brackish water bentic index BQI  ¼ X ni ¼ 1  A i tot   A 3 ES 50 0 : 05 i   ! 3 10 log  S  þ  1 ð Þ ð Ref  :  53 Þ BQI max  ¼  maximum BQI-value recorded within type after calculating all available data within national zoobenthos database H  0 ¼  Shannon-Wiener index (log 2 -base) H  0 max  ¼  maximum  H  0 -value recorded within type after calculating all available data within national zoobenthos databaseAB tot  ¼  totA  ¼  abundance at station (equal to  N   and  N  tot  in Box 1 indices) S   ¼  number of species/taxa at station ES  50 0.05 i   ¼  sensitivity values (where species are classified as 1  ¼  very tolerant, 5  ¼  tolerant, 10  ¼  sensitive, and 15  ¼  very sensitive todisturbance).* The classification list is the same as in Sweden, where it is used in the BQI-index (51, 53) and sensitivity and tolerance grouping is based onliterature (24, 28, 54–60) and expert judgment. The list is available at 252  Ambio Vol. 36, No. 2–3, April 2007   Royal Swedish Academy of Sciences 2007  farming (1981–2002) and a 2-year recovery period were studied(Perus et al., in prep.). RESULTS The information on soft-bottom zoobenthos gave a classifica-tion for the BBI (Fig. 1; Table 1) in accordance with the generalenvironmental status of the Archipelago Sea described in otherstudies using traditional physicochemical monitoring techniques(36–39). Species richness is highest in inner shallow archipelagoareas, where habitat complexity and variable substrates give riseto high biodiversity (Table 1) (11, 40). Species richness is alsoconsistently higher in the littoral depth interval (0–10 m) than inthe deeper stratum. Abundances vary greatly within allenvironmental types, regardless of classification status. How-ever, the magnitude in variation tends to increase as environ-mental status becomes deteriorated (predominantly in thecategories poor and bad). This high variation in abundancesunder poor conditions is also described in the Pearson– Rosenberg paradigm (7) indicating fluctuating conditions witha high proportion of opportunistic and tolerant species(Fig. 2a). The proportion of status bad is lowest in the outerarchipelago (coastal type  Lu ), where bad conditions are noteven registered for the shallow section. The middle archipelago(type  Lv ) shows a higher overall proportional distribution of poor and bad quality conditions than both the inner and outercoastal types (Fig. 1). The middle zone in the Archipelago Sea,as for the same zone in the A ˚land Islands, is the region wheremost changes have taken place in the benthic communitystructure over the last 30 years (11).Results from testing BBI and other indices on an organicallypolluted case study (fish farming) show that BBI correlates wellwith DKI ( r 2 ¼  0.86), BMI ( r 2 ¼  0.80), BQI (2006) ( r 2 ¼  0.78),and BQI (2004) ( r 2 ¼  0.75) but not with AMBI ( r 2 ¼  0.27).Tolerant species dominate the communities, and species verysensitive to organic enrichment are hardly present (Fig. 2b).BBI, DKI, BMI, and BQI show a similar response to changes inoxygen saturation, organic matter, and species richness(Fig. 3a–c), while the AMBI index is insensitive to changes inthese variables in low-saline species-poor regions. The averagenumber of taxa found at a single station visit (pooling five Table 1. Type- and depthwise information on ecological reference properties for different classification borders. Area Depth stratum Parameter H G M P B Ls   0–10 m S (25) 10.7  6  2.9 7.2  6  1.8 6.2  6  2.9 4.3  6  1.3 2.7  6  1.3(n  ¼  204) N 6764  6  6108 3498  6  2642 5141  6  5783 7097  6  18 574 9367 6  22 725H 0 (2.86) 2.32  6  0.4 1.89  6  0.24 1.38  6  0.34 0.87  6  0.34 0.36 6  0.28BBI-EQR 0.889 0.667 0.445 0.222  , 0.22210 þ  m S (14) 8.06  6  2.34 6.09  6  1.51 5.76  6  1.7 4.6  6  1.56 2.05 6  0.91(n  ¼  246) N 8787  6  8577 5783  6  5455 6994  6  7744 10 332  6  14 795 2853 6  3962H 0 (2.92) 1.82  6  0.57 1.71  6  0.35 1.42  6  0.32 0.78  6  0.33 0.28 6  0.27BBI-EQR 0.953 0.715 0.477 0.238  , 0.238 Lv   0–10 m S (17) 13.8  6  1.1. 9.57  6  4.2 8.7  6  3 6.3  6  1.6 2 6  1(n  ¼  52) N 4884  6  5958 6830  6  4499 10 573  6  10 675 15 811  6  19 297 3743 6  9299H 0 (3.15) 2.74  6  0.37 1.97  6  0.71 1.53  6  0.43 0.76  6  0.44 0.28 6  0.29BBI-EQR 0.928 0.696 0.464 0.232  , 0.23210 þ  m S (18) 9.19  6  2.87 6.89  6  2.37 7.06  6  2.62 5.15  6  2.09 2 6  1(n  ¼  290) N 10 324  6  6648 9568  6  13 583 18 581  6  17 107 18 692  6  21 764 7197 6  19 903H 0 (2.55) 1.61  6  0.52 1.46  6  0.36 1.03  6  0.3 0.54  6  0.31 0.14 6  0.16BBI-EQR 0.891 0.668 0.446 0.223  , 0.223 Lu   0–10m S (22) 16  6  2.6 13.8  6  2.8 10.7  6  3.8 6  6  2.9 —(n  ¼  45) N 18 269  6  6474 20 542  6  20884 60 162  6  60 890 6827  6  6860 —H 0 (3.23) 2.79  6  0.35 2.33  6  0.3 1.4  6  0.46 1.49  6  0.36 —BBI-EQR 0.920 0.690 0.460 0.230  , 0.23010 þ  m S (14) 8.88  6  1.02 8.08  6  2.36 7.09  6  2.68 6.78  6  2.66 3.05 6  2.15(n  ¼  210) N 5736  6  2957 8682  6  6105 11 773  6  11 050 25 197  6  19 627 17 211  6  26 148H 0 (2.90) 1.92  6  0.35 1.55  6  0.42 1.39  6  0.28 0.69  6  0.28 0.18 6  0.23BBI-EQR 0.903 0.677 0.452 0.226  , 0.226 Amount of information (n ¼ number of station visits), Species richness (maximum number in brackets), abundance, and Shannon-Wiener (log2-base) (maximum value in brackets) values areaverages 6 SD of values within specific classification borders. BBI-EQR values (ranging between 0 and ; 1 in WFD) scaling to different classification borders (H ¼ high, G ¼ good, M ¼ moderate,P  ¼  poor, and B  ¼  Bad) Figure 1. Proportional distribution of different environmental statusfor the classification of three archipelago zones (Ls  ¼  inner, Lv  ¼ middle, and Lu ¼ outer zone) and two depth intervals (0–10 m, 10 þ m)using the BBI. (Environmental status: B  ¼  bad, P  ¼  poor, M  ¼ moderate, G  ¼  good, and H  ¼  high)Figure 2. Changes in species composition as environmental qualityimproves in (a) the depth stratum 10 þ  m in the outer archipelagotype  Lu,  and (b) a fish farming case study from the A˚land Islands.The proportion of species classified as tolerant and very tolerant tostress dominate at low BBI values, while species sensitive and verysensitive to stress dominate at higher values or are lacking instressed environments during recovery. Distribution shown byleast-square smoothing lines (DWLS, stiffness 0.5). Ambio Vol. 36, No. 2–3, April 2007  253   Royal Swedish Academy of Sciences 2007  replicate grabs; average species richness 5.3  6  3.1) or station(pooling station visits; average species richness 7.6  6  5.2) isnaturally low along the Finnish coastline. DISCUSSION The brackish Baltic Sea is semienclosed, nontidal, andconnected to fully marine waters only by the narrow andshallow Danish straits. Vertical and horizontal gradients in bothhydrography and biology characterize the Baltic Sea today.Conditions for the macrozoobenthos therefore differ signifi-cantly, not only between the Baltic Sea and the Atlantic Ocean,but also between subbasins inside the Baltic Sea (25, 26, 34).Characteristics such as the impoverishment of the zoobenthiccommunities along the south–north salinity–temperature gra-dient (13, 25), seasonally pulsed nutrient loads by rivers innorthern Baltic Sea, introduction of new species, and increas-ingly frequent seasonal–annual hypoxic or anoxic events in theBaltic Sea create mixed benthic communities inside an alreadystressed ecosystem. Although the entire Baltic Sea is affected byeutrophication, the effects and consequences vary betweensubbasins (41). Regional differences occur especially in thecoastal areas (42) and thus require methods and tools capable of correctly describing environmental changes.Traditional monitoring techniques, using physicochemicaland hydrographical parameters, have produced a classificationof surface waters in the Archipelago Sea (36–39) that wasverified by the BBI using soft-bottom macroinvertebrates. TheBBI, like most of the other tested indices here, behaved asintended when compared against neutral case-study datacontaining large variations in environmental characteristics.Hence, we feel that zoobenthos is a valid tool for quality- andclassification purposes, and that the new BBI provides a reliablemethod for low-saline coastal brackish waters in the Baltic Sea.Biodiversity of marine macroinvertebrate species decreasesrapidly, moving northward and eastward in the Baltic Seabecause of decreasing salinity, harsh climatic conditions, andpossibly the distance to the marine donor area (13). This holdstrue for open sea areas, but closer to the coast and in shallowwaters (0–10 m) species of limnic, brackish, and marine srcinform mixed assemblages, and freshwater species (includinginsect larvae) make up a high proportion of the total speciesrichness, thus compensating for the losses in the open sea.Macroinvertebrate diversity remained almost similar in thesouthern Finnish coastal waters, where salinity is  ; 6 PSU andin the northern- and easternmost parts of the Baltic Sea, wheresalinity is  ; 1 because of the importance of limnic species (13).Species richness is generally higher at littoral depths (0–10 m)than in deeper waters (10 þ m) (Table 1). Depth alone is not thestructuring factor for this difference, but a higher habitatcomplexity and variable substrates is usually encountered inshallow areas (11, 25, 40).To avoid ambiguous results due to relationships to salinitygradients (34), the BBI works on predefined type-specific (andtheir depth strata) maximum values of BQI and H 0 . Thereby therisk of misclassifying landlocked low-saline areas comparedwith outer sea areas is minimized.The use of indicators (specific species, various indices, etc.) isbecoming an integral part of decision support systems forcoastal zone management, and there is a plethora of techniquesfor determining change at all levels of biological organization(43). The apparent elegance and authority of a scaled metric toportray complex environmental data to managers, politicians,and public has kept interest high.When testing the marine index AMBI, widely used andaccepted in organic pollution studies globally (see, e.g.,overview in 44), in the conditions of the northern Baltic Seawe found highly divergent results (Fig. 3a–c) because of thenatural poverty of the system, even under nondisturbedconditions. The number of taxa found at a station or a stationvisit is very low in our case, and Borja, et al. (45) report that therobustness of their index is reduced when a low number of taxaand/or individuals are found in a sample. In the instructions forusing the AMBI, they recommend using replicates as the basisfor calculations to avoid ambiguous results (45). However,doing so in areas of low species diversity proved impossible. Inthe Finnish database, 31 %  of all station visits have a speciesrichness of three taxa or less. Further, the absence in AMBI of anumerical factor correcting for low abundances led to situationswhere almost abiotic conditions at heavily polluted sites weregiven a high status because of the occurrence of single specimens Figure 3. Relationship between tested indices [BBI, DKI, BMI, BQI(2004), BQI (2006), and AMBI] and (a) organic matter, (b) oxygensaturation, and (c) species richness on a fish farming case-studydata set from the A˚land Islands. (Note that AMBI 0 [zero] indicateshealthy conditions while 0 indicates azoic conditions in otherindices) (LOWESS smoother, tension 0.5 used). 254  Ambio Vol. 36, No. 2–3, April 2007   Royal Swedish Academy of Sciences 2007
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