Developing an efficient macrofauna monitoring index from an impact study — A dredge spoil example

MarinePollutionBulletin,Vol.36,No.3, pp. 231-235.1998 Pergamon PII: S0025-326X(97)00183-5

© 1998ElsevierScienceLtd.Allrightsreserved Printedin GreatBritain 111/25-326X/98$19.11/1+11/00

Developing an Efficient Macrofauna Monitoring Index from an Impact Study - - A Dredge Spoil Example RODNEY D. ROBERTS*S, M U R R A Y R. GREGORY$ and BRIAN A. FOSTER§,¶

tEnvironmental Science Programme, University of Auckland, Auckland, New Zealand SGeology Department, University of Auckland, Private Bag 92019, Auckland, New Zealand §Zoology Department, University of Auckland, Private Bag 92019, Auckland, New Zealand Data from an initial impact study 'were used to develop a labour-efficient index for biolegical monitoring of dredge spoil disposal. Each of 12 indicator species was assigned a score, based primarily on the ratio of its abundance in control vs impacted samples. The 'Index' value was the average score of those indicator species present in the sample. The Index was tested during a second survey. Sample processing for Index calculation took only 25% of the time required to process all macrofauna. The Index value provided a sensible, semi-quantitative indication of impact on benthic macrofauna. Index values of 6 were indicative of 'severe', 'patchy' and 'no' impact respectively. Mean Index value correlated with mean macrofaunal richness (r= 0.93, P < 0 . 0 5 ) and abundance ( r = 0 . 9 2 , P < 0 . 0 5 ) . While the Index is site- and impact-specific, the process of developing efficient monitoring tools from an initial impact study should be widely applicable. © 1998 Elsevier Science Ltd. All rights reserved Keywords: benthos; dredging; efficiient; index; indicator species; monitoring.

Assessment of impacts on marine ecosystems often involves a major study to document existing effects, followed by scaled-down monitoring to check for further change. Benthic macrofauna are commonly used to measure impacts, and numerous techniques have been developed to detect pollution-induced changes (e.g., Warwick and Clarke, 1991). Many techniques require that all benthic macrofauna are extracted from samples, identified and enumerated. These methods: (1) may generate redundant data because impacts on total macrofauna may be *Corresponding author. Current address: Cawthron Institute, Private Bag 2, Nelson, New Zealand. ¶Deceased.

adequately reflected by a subset of animals (Marchant

et al., 19951; (2) often require very labour-intensive sample sorting, with a large amount of the effort devoted to identifying a few difficult taxa (Warwick, 1988); (3) can be hampered by nuisance variation caused by environmental factors (Gray et al., 1988). Monitoring could be more effective and more efficient if it focussed on species which were informative, easy to identify and readily extracted from samples. The indicator species concept is appealing in this context. An initial study can characterize the impact of an activity, allowing indicator species to be selected for efficient ongoing monitoring. Rygg (1985) identified positive and negative indicator species. Positive indicators were pollution tolerant and dominated the macrofauna of low-diversity samples. Negative pollution indicators were non-tolerant species whose presence indicated little or no impact but whose collective absence implied high impact. Indicator taxa may be selected for their importance in the community (Clements et al., 1992), sensitivity to change (Bellan, 1980; Gray and Pearson, 1982; Daan et al., 19941, or labour efficiency (Mouthon, 1993). Data on indicator species can be combined to provide an index of biological impact (e.g. Clements et al., 1992; Mouthon, 1993). This paper describes a method for developing a monitoring index from an initial impact study, with an emphasis on labour efficiency. Our example relates to the impact of dredge spoil dumping on benthic macrofauna. Methods

Study area, dumping history and surveys Fine-grained dredgings (80-90% mud, remainder sand) from the Port of Auckland, New Zealand (174°46'E, 36°51'S) were dumped onto a shallow ( 7 - 1 2 m below MLWS), current-swept seafloor near Rangitoto Island (Roberts, 1990). Dumping was 231

Marine Pollution Bulletin

centred at two locations: Dump Point B (174°49'39"E, 36°46'32"S) from 1979 to 1987 and Dump Point A (174°49'52"E, 36°46'13%) from 1988 to 1990. A control area was located 1 km across-current to the west. Dumped muds contrasted with the shelly sediments natural to the spoil ground and control sites. An initial survey (May 1988) described the effect of dumping on sediments and macrofauna by comparing impacted samples (2 sites near Dump Point B, 1 at Dump Point A, n = 16) with unimpacted samples (5 sites, n = 27). From that data set, an index (hereinafter termed the 'Index') of dumping impact was developed, as described in 'Results'. The performance of the Index as a monitoring tool was tested with a second survey in August 1989. Some 30 000 m 3 of sediment was dumped at Dump Point A between the two surveys, while none was dumped at Dump B. This allowed sampling of 'recovering' sites near Dump Point B. Around Dump Point A, samples were taken from a central zone of continuous spoil cover, from the adjacent zone where spoil deposits were patchy, and at unimpacted sites. These zones were defined by sediment sampling, seismic reflection profiling and diver observations. Samples collected with a 0.1 m 2 Peterson grab were sieved on a 1.1 mm mesh, and the residue was preserved with 4% formalin for later processing.

30-45% of dry weight), sand (30-45%) and mud (15-30%). Sites impacted by dumping were identified by a mud content > 30%, or a fine-sand plus very-finesand content >40%. Impacted samples had lower macrofaunal richness, abundance and diversity than unimpacted samples (Fig. 1). However, many of the 161 taxa recorded showed no clear dumping effect, because their abundance was too low and/or too variable. These taxa were of limited use as indicators of impact. Some taxa showed potential as indicators - their abundance was consistently higher or lower in impacted samples (Table 1). The twelve indicator species chosen (Table 2) were: (1) easy to identify to species level; (2) readily extracted from samples; and (3) representative of the range of responses observed. Each of the 12 indicator species was assigned a score from 1 to 10 (Table 2). This score reflected primarily the impact which dredge spoil dumping had on its abundance (Table 1). For high scoring species, the ability of the animal to migrate upwards through sediment overburdens (Table 3) was also considered. A score of 10 indicated a species which was very intolerant of dredge spoil dumping. A score of zero indicated a species which was more common in impacted samples than in unimpacted samples. Species were chosen to provide a range of tolerances, so the Index reflected the degree of impact on benthic macrofauna. The Index value for each sample was calculated as the average score of those scoring species present in the sample. For example, a typical control sample contained the seven highest scoring taxa, but none of the five low-scoring taxa, so its Index value would be ( 5 + 5 + 5 + 7 + 8 + 9 + 1 0 = 49)/7 = 7. An Index value of 0 was given if none of the 12 indicator species was present. The theoretical range of Index values was 0-10. When the Index was applied to the initial survey data (from which it was derived) it separated impacted and unimpacted samples (Figs 1 and 2). It also gave some quantitative information on the degree of impact on macrofauna. The Index value correlated positively with both macrofaunal richness (r=0.82, P<0.001) and macrofaunal abundance (r = 0.59, P<0.001) (Fig. 2). Index values fell into three groups (Fig. 2): (1)

Sediment burial experiments Intact sediment samples and live macrofauna were obtained from control sites and maintained in aquaria at 13-15°C with aeration and a 10:14 L/D cycle. Surficial muds from the Port of Auckland (source of dredgings) were collected with a van Veen grab and maintained as above. Overburdens of port mud ranging from 1 to 30 cm thickness were placed onto natural or constructed macrofaunal assemblages. Inspections were made over several days, and any macrofauna which had established surface contact were noted.

Results Initial survey The sediments natural to the spoil ground and control area were mixtures of shell gravel (typically 60

+t

v

Richness

600

Abundance

3.5

Diversity

8

50

500

3

7

40

400

2.5 2

30

300

20

200

1.5 1

6 5 4 3 2

10

100

0.5

1

0

0

0

0

C

t

C

I

C

I

Fig. 1 Comparison of macrofaunal richness, abundance, ShannonWeaver diversity and Index values at unimpacted sites (white bars labelled 'C'; 5 sites; n = 27) and physically impacted sites (black bars labelled T , 3 sites; n = 16) in the initial survey. The 'Index' is that developed in this study.

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Index

C

I

Volume 36/Number 3/March 1998 TABLE 1

Comparison of the abundance of selected macrofaunal taxa at unimpacted sites (5 sites; 27 samples), and physically impacted sites (3 sites; 16 samples). Groups are defined on the basis of the ratio of abundance in impacted samples (column 4) to that in unimpacted samples (column 3). Data are from the initial survey. Mean number per sample (_+95% CI) Group

Taxon

Ratio impacted:unimpacted

Unimpacted sites

Impacted sites

Limaria orientalis Corbula zelandica Maoricolpus roseus Leptochiton inquinatus Amphipholis squamata Anthuridae sp. 1 Flabelligeridae Hesionidae Dorvilleidae Scalibregmidae Syllidae

9.2 ± 2.3 5.8 ± 1.8 2.6 _+1.2 6.5 _+1.3 67.3 i 13.7 34.3 _+10.0 8.6 _+2.5 5.5 ± 1.5 5.4 ± 1.6 2.9 _+1.1 39.0_+ 13.2

0.6 + 0.8 0.6_+0.4 0.1 ± 0.1 0.6 ± 0.8 5.0 i 2.8 2.4 i 1.5 0.2 _+0.4 0.4 ± 0.4 0.5 ± 0.6 0.1 ± 0.3 7.1 +_2.5

Leptomya retiaria Tawera spissa Ruditapes largillierti Capitellidae Ampharetidae

4.5 + 1.8 3.2_+0.8 0.9 _+0.4 40.4 _+10.8 21.7 _+3.1

2.7 ± 2.8 1.4_+ 1.1 0.9 ± 0.9 23.8 ± 17.7 10.1 _+7.4

0.2 ± 0.2 2.0 _+2.0

1.7 ± 1.4 22.4 +_ 18.7

Ratio <0.2 0.07 0.10 0.02 0.09 0.07 0.07 0.02 0.07 0.09 0.03 0.18 Ratio 0.4-1.0 0.6 0.44 1.00 0.5"9 0.47 Ratio > 5 8.5 11.2

0 0 0 0

0.2 _+0.2 0.1 _+0.1 O.1 ± O.1 0.7 _+0.7

----

G R O U P 1:

Abundance in control samples >5 times higher than in impact samples

G R O U P 2:

Abundance in control samples 0.4-1.0 times higher than in impact samples G R O U P 3:

Pleuromeris zelandica Spionidae

Abundance in control samples > 5 times lower than in impact samples GROUP 4: Absent from controls, present at impacted sites

Dosinia lambata Tellinota edgari Theora lubrica Echinocardium cordatum

unimpacted samples with Index values >6; (2) impacted sites with Index values between 2 and 6; (3) impacted sites with Index values of zero.

animals were extracted and identified from an equivalent sample in ~ 1.5 hours. All control sites yielded consistent and precise mean Index values (Fig. 3). Two sites were in a transitional

Testing the Index during a second survey

The Index reduced sorting/identification time by ~75%. Sorting and identification of the full macrofauna from a control sample (200-800 individuals, 40-70taxa) took ~ 6 hours on average, and many animals were not identified to species level. Indicator TABLE 2

Species

Scores for indicator species used for the calculation of the Index. Index value = average of the scores of those scoring taxa present in the sample. If no scoring taxa are present, Index value = 0. Species

Type of animal

Limaria odentalis Leptochiton inquinatus Maoricolpus roseus Corbula zelandica Leptomya retiaria Tawem spissa Ruditapes largillierti Pleurorneris zelandica Dosinia lambata Tellinota edgari Zenatia acinaces Echinocardium cordatum None of above species present

Byssus/shell 'nesting' bivalve Epifaunal chiton Epifaunal gastropod Infaunal bivalve Infaunal bivalve Infaunal bivalve Infaunal bivalve Infaunal bivalve Infaunal bivalve Infaunal bivalve Infaunal bivalve Infaunal heart urchin

TABLE 3

Observations on the ability of selected indicator species to re-establish surface contact through overburdens of dredge spoil in laboratory aquaria. Animals were resident in shelly control site sediments when mud from dredged areas was overlain. Maximum overburden (cm) escaped

Limaria orientalis

This bivalve lives in a byssus-bound nest of shell, which precluded escape. A passage to the surface was blasted through thin ( 1-2 cm) overburdens by valve clapping This chiton probably requires a hard attachment surface to crawl up through mud overburdens

Score 10 9 8 7 5 5 5 2 1 1 1 1 0

Leptochiton inquinatus Maoricolpus roseus Corbula zelandica Leptomya retiaria

Tawera spissa

Notes

8 15 8

Extension of the long siphons aided reestablishment of surface contact

6

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Marine Pollution Bulletin 70

O9

@

r = 0.89, P<0.01

60

+1

50 t-

40

[~No impact

30

Impact

o 'r-

e-

20 t0

o o

0 2

4

6

3).

Index value ( + SE)

800 +E

Discussion

700 r = 0.79, P<0.02

6oo r-

500

1D t-

=

400

-~

300

I o No impact

&

r--

= 200

9

g

I" mpact

@

100 0 0

r

i

,

i

2

4

6

8

Index value ( _+ SE)

Fig. 2 Relationship of Index value to macrofaunal richness (top graph) and macrofaunal abundance (bottom graph) in the initial survey. The r values are Pearson's correlation coefficients.

zone where spoil deposits were patchy on a scale of a few metres (diver observations). This variability was visually evident in consecutive replicate grabs, so the wide error bars at these sites (Fig. 3) reflected real variation. These patchy spoil deposits hampered statistical detection of impact at some sites (Fig. 3). The Index provided a semi-quantitative measure of impact on macrofauna. Mean Index value correlated

8.

--z-

~ " 76 +ID~ 5 4.

3 x 2 c

1 0

Extreme Patchy Recovering

Unim ~acted

Impact category Fig. 3 Comparison of Index value at 13 sites (n = 5) of differing impact status during the second survey. The bars above columns are Tukey's HSD groupings from an ANOVA. Columns joined by a line are not significantly different (P>0.05). 'Extreme' and 'patchy' impact sites are in zones of continuous and patchy spoil cover respectively near the recently used Dump Point A. 'Recovering' sites are near Dump Point B which was not used for 19 months prior to sampling.

234

strongly with mean macrofaunal richness (r= 0.93, P<0.05) and abundance (r=0.92, P<0.05) at five impactsites. Unimpacted sites had mean Index values > 6, whereas all physically impacted or recovering sites had mean Index values <6 (Fig. 3). Sites classified as 'extreme impact' (from physical data and diver observations) had Index values <2 and low macrofaunal richness and abundance. Intermediate mean Index values (2-6) occurred where spoil deposits were patchy, and at sites recovering from past impacts (Fig.

Environmental impact assessments are often followed by ongoing monitoring. This study demonstrates the potential to develop site-specific monitoring indices which are statistically precise, biologically meaningful and very cost effective. Monitoring indices based on the sensitivity of indicator taxa have been described elsewhere (Bellan, 1980; Clements et al., 1992; Mouthon, 1993; Stark, 1993; Engle et al., 1994). The idea of selecting subsets of useful species for reduced-scale marine monitoring (Gray and Pearson, 1982) and that of using suites of indicator species (Bellan, 1980; Rygg, 1985) have been discussed. We combined these ideas to generate a monitoring index with the emphasis on labour efficiency. We capitalized on the redundancy in data sets (Marchant et al., 1995) by using a small, informative subset of the fauna. Our selection process was based on empirical data, but was not objective (Gray and Pearson, 1982). Rather, we deliberately chose species which were readily sorted from samples and simple to identify. Sample processing was our major labour component due to the coarse shelly sediments. This was reduced by ~75% if the Index was used in place of a method based on the full macrofauna. This time saving would have been greater if identification of all macrofauna had been pursued - - we lumped polychaetes into families and left many crustaceans unnamed. Further labour savings would result if a larger mesh size were used for sample sieving. All 12 indicator species would be retained on a coarser mesh once they had grown beyond the early juvenile stage. This could even improve the reliability of the Index by excluding recent recruits which were unable to survive. The Index gave very consistent and precise mean values for control sites (Fig. 3) because it was based on common and widespread species. Index values varied widely between replicates where impacts were patchy, indicating a need for more targeted sampling. The Index provided a semi-quantitative measure of the degree of impact on macrofauna, correlating strongly with macrofaunal richness and abundance. Sites could be classified as having high, intermediate/patchy, or low/no impact on the basis of mean Index values of <2, 2-6 and >6 respectively. These semi-quantitative

Volume 36/Number 3/March 1998 i m p a c t c a t e g o r i e s w e r e evident in the initial survey, and held true in the s e c o n d survey. W h e n a single species is used as an indicator of e n v i r o n m e n t a l conditions, its a b s e n c e can not be attrib u t e d to any p a r t i c u l a r cause (Rygg, 1985). O u r Index was relatively i m m u n e to this p r o N e m b e c a u s e (1) the higher scoring species were p r e s e n t in almost every u n i m p a c t e d sample, a n d (2) the Index value is d e r i v e d from a suite o f i n d i c a t o r species. O u r e x p e r i e n c e was consistent with Rygg's (1985) o b s e r v a t i o n that the collective a b s e n c e o f a g r o u p o f i n t o l e r a n t species i m p l i e d impact. T h e Index was d e v e l o p e d p r i m a r i l y from the observation that certain species were more, or less, a b u n d a n t at sites affected by s e d i m e n t d u m p i n g ( T a b l e 1). T h o s e d a t a reflect two m a j o r factors: (1) burial, and (2) persistent changes in s e d i m e n t texture. Burial impact was m o s t evident at r e c e n t d u m p i n g sites, w h e r e virtually no m a c r o f a u n a w e r e p r e s e n t and Index values were zero. D u m p i n g of m u d o n t o a shelly seafloor resulted in m u d - d w e l l i n g species colonizing the spoil ground. T h e f o u r lowest-scoring i n d i c a t o r species ( T a b l e 2) are all c h a r a c t e r i s t i c of m u d d y s e d i m e n t s (Powell, 1937) but w e r e not p r e s e n t in dredgings ( R o b e r t s , 1990). W e expect recovery o f Index values after d u m p i n g ceases to b e largely driven by s e d i m e n t texture. W h i l e s e d i m e n t s r e m a i n m u d d y with little shell, Index values a r e e x p e c t e d to r e m a i n low. If s e d i m e n t deposits b e c o m e m o r e c o a r s e - g r a i n e d , then Index values will rise. T h e m a c r o f a u n a l a s s e m b l a g e we s t u d i e d was rich in species, a n d c o n t a i n e d m a n y c o m m o n taxa. T h e d e v e l o p m e n t o f a similar index w o u l d be m o r e difficult in d e p a u p e r a t e assemblages. T h e Index d e s c r i b e d is location- and impact-specific. Its p e r f o r m a n c e will decline as m a c r o f a u n a l assemblage, s, or the n a t u r e of the impact, diverge from those which we studied. However, the c o n c e p t of d e v e l o p i n g a site-specific m o n i t o r i n g index from an initial survey should b e widely applicable. RDR received funding from the Department of Conservation and the Auckland Regional Council. Boat support was donated by Ports

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