OCS Study

BOEM 2015-045

US#Department#of#Interior

Bureau#of#Ocean#and#Energy#Management

Alaska#OCS#Region

Sediment Characteristics and Infauna of 

Deltaic Mudflats Along the Alaskan 

Beaufort Sea

OCS Study

BOEM 2015-045

US#Department#of#Interior

Bureau#of#Ocean#and#Energy#Management

Alaska#OCS#Region

Sediment Characteristics and Infauna of 

Deltaic Mudflats Along the Alaskan 

Beaufort Sea

Authors

Abby N. Powell, Roy T. Churchwell, Kenneth H. Dunton, Jeffrey G. Baguley, Anthony D. 

Kamikawa, Colleen T. E. Kellogg, Byron C. Crump, Philip Bucolo

Prepared under BOEM Award

Cooperative Agreement No. M11AC0006

by

Abby Powell

U.S. Geological Survey Alaska Cooperative Fish and Wildlife Research Unit

University of Alaska Fairbanks

Fairbanks, Alaska 99775-7020
Disclaimer

Study collaboration and funding were provided by the US Department of the Interior, Bureau of 

Ocean Energy Management, Environmental Studies Program, Washington, DC, under 

Agreement Number M11AC0006, University of Alaska Fairbanks through the North and West 

Alaska Cooperative Ecosystem Studies Unit. This report has been technically reviewed by 

BOEM and it has been approved for publication. The views and conclusions contained in this 

document are those of the authors and should not be interpreted as representing the opinions or 

policies of the US Government, nor does mention of trade names or commercial products 

constitute endorsement or recommendation for use. 

Availability

To download a PDF file of this Environmental Studies Program report, go to the US Department 

of the Interior, Bureau of Ocean Energy Management, Environmental Studies Program 

Information System website and search for OCS Study BOEM 2015-045. 

This report can be viewed at select Federal Depository Libraries. It can also be obtained from the 

BOEM Alaska Outer Continental Shelf Regional Office. 

US Department of the Interior 

Bureau of Ocean Energy Management 

Alaska OCS Region 

3801 Centerpoint Drive, Suite 500

Anchorage, AK 99503-5820 

Phone: 907-334-5200 

Fax: 907-334-5202

Recommended Citation

Powell AN, Churchwell RT, Dunton KH, Baguley JG, Kamikawa AD, Kellogg CTE, Crump

BC, Bucolo P. 2016. Sediment Characteristics and Infauna of Deltaic Mudflats Along the 

Alaskan Beaufort Sea. US Dept. of the Interior, Bureau of Ocean Energy Management, 

Alaska OCS Region, Anchorage. OCS Study BOEM 2015-045. 77 pp.
Acknowledgements

Study collaboration and funding were provided by the US Department of the Interior, Bureau of 

Ocean Energy Management, Environmental Studies Program, Washington, DC under 

Cooperative Agreement Number M11AC0006. The National Fish and Wildlife Foundation, US 

Fish and Wildlife Service Arctic National Wildlife Refuge, and the Arctic Landscape

Conservation Cooperative provided additional funding and support. The US Fish and Wildlife 

Service Arctic National Wildlife Refuge, USGS Alaska Cooperative Fish and Wildlife Research 

Unit and the Institute of Arctic Biology at the University of Alaska Fairbanks, and Manomet 

Conservation Sciences provided logistical support. Lab support was provided by the University 

of Alaska, Fairbanks (Mark Wipfli aquatic invertebrate lab, Alaska Stable Isotope Facility, 

University of Alaska Forestry Soil Sciences Lab, Alaska Monitoring and Assessment Program), 

Oregon State University Center for Genome Research and Biocomputing, and Argonne National 

Laboratory Institute for Genomics and Systems Biology Next Generation Sequencing Core. We 

thank Colin Morrison, Paul Bennetts, Greg Saiyo, Morgan Ricci, Erin Parsons, and Nathan 

Conrad-Forrest who assisted with meiofauna laboratory analyses at the University of NevadaReno. We are thankful to the Kaktovik Inupiat Corporation for letting us conduct research on 

their lands and the people of the village of Kaktovik for their help and friendship. We thank the 

many dedicated field technicians who helped collect samples. Richard Raymond, Cathy Coon, 

Mike Rasser, John Pearce, and Craig Davis provided comments on drafts of this report. We are 

extremely grateful for Kathy Pearse for her assistance in editing this report. Any use of trade, 

firm, or product names in this publication is for descriptive purposes only and does not imply 

endorsement by the US Government.
i

Table of Contents

Table of Contents .............................................................................................................................i

List of Figures................................................................................................................................ iii

List of Tables..................................................................................................................................vi

Abbreviations and Acronyms....................................................................................................... vii

1. Executive Summary.....................................................................................................................1

2. Introduction .................................................................................................................................4

2.1 Objectives..............................................................................................................................6

2.2 Tasks......................................................................................................................................6

3. Sediment Meiofaunal Populations...............................................................................................9

3.1 Introduction ...........................................................................................................................9

3.2 Methods...............................................................................................................................10

3.3 Results .................................................................................................................................12

3.4 Discussion............................................................................................................................19

3.5 References ...........................................................................................................................20

4. Sediment Microbial Populations ...............................................................................................23

4.1 Introduction .........................................................................................................................23

4.2 Materials and Methods........................................................................................................24

4.2.1 Microbial community composition ..............................................................................24

4.3 Results and Discussion ........................................................................................................25

4.3.1 Bacterial Community....................................................................................................25

4.3.2 Microeukaryotic Community .......................................................................................26

4.4 References ...........................................................................................................................29

5. Sediment Parameters: Chlorophyll, Microalgal Composition, Ammonium, and Stable Isotopic 

Measurements................................................................................................................................33

5.1 Introduction .........................................................................................................................33

5.3 Materials and Methods........................................................................................................34

5.3.1 Pigment Analysis..........................................................................................................34

5.3.2 Isotopic Analysis, C:N Ratios, and TOC......................................................................37

5.3.3 Porewater Salinity and Ammonium .............................................................................38

5.4 Results and Discussion ........................................................................................................38

5.4.1 Pigment and TOC Analysis..........................................................................................39

5.4.2 Isotope and C:N Analysis.............................................................................................43

5.4.3 Porewater Salinity and NH4

+ ........................................................................................45

5.5 References ...........................................................................................................................46

6. Environmental Variables and Sediment Macroinvertebrates....................................................47

6.1 Introduction .........................................................................................................................47

6.2 Methods...............................................................................................................................48

6.2.1 Species Diversity, Distribution, and Statistical Analyses ............................................50

6.3 Results .................................................................................................................................52

6.3.1 Taxa and Occurrence....................................................................................................52

6.4.2 Invertebrate Abundance and Distribution ....................................................................57
ii

6.3.3 Stable Isotopes..................................................................................................................65

6.4 Discussion............................................................................................................................67

6.4.1 Taxa and Occurrence....................................................................................................67

6.4.2 Invertebrate Abundance................................................................................................69

6.4.3 Invertebrate Distribution ..............................................................................................69

6.4.4 Isotopic Analysis of the Trophic Community ..............................................................70

6.4.5 Study Implications........................................................................................................71

6.5 References ...........................................................................................................................73
iii

List of Figures

Figure 2.1. Location of the three river deltas (JOHC) in the eastern Beaufort Sea in northern 

Alaska. .............................................................................................................................................5

Figure 3.1. Sediment core sampling at the Jago River delta. ........................................................10

Figure 3.2. Average meiofaunal abundance from each site [Canning (CRD), Jago, 

Okpilak/Hulahula (OKP)] in 2011, broken down by sampling session (July/August) with 

standard error (δ/㲋(n)). ................................................................................................................14

Figure 3.3. Average meiofaunal abundance from each site [Canning (CRD), Jago, 

Okpilak/Hulahula (OKP)] 2012, broken down by sampling session (July/August) with standard 

error (δ/㲋(n))................................................................................................................................14

Figure 3.4. Average meiofaunal diversity (Hill’s N1) from each site [Canning (CRD), Jago, 

Okpilak/Hulahula (OKP)] 2011, broken down by sampling session (July/August) with standard 

error (δ/㲋(n))................................................................................................................................16

Figure 3.5. Average meiofaunal diversity (Hill’s N1) from each site [Canning (CRD), Jago, 

Okpilak/Hulahula (OKP)] 2012, broken down by sampling session (July/August) with standard 

error (δ/㲋(n))................................................................................................................................16

Figure 3.6. MDS ordination of meiofauna community structure across all sites [Canning (CRD), 

Jago, Okpilak/Hulahula (OKP)] 2011. Data were fourth root transformed prior to Bray Curtis 

similarity analysis. Ordination of stations reveals lower similarity between Canning and Jago, 

with Okpilak/Hulahula having overlapping similarity with both Canning and Jago. ...................17

Figure 3.7. MDS ordination of meiofauna community structure across all sites [Canning (CRD), 

Jago, Okpilak/Hulahula (OKP)] 2012. Data were fourth root transformed prior to Bray Curtis 

similarity analysis. Ordination of stations reveals lower similarity between Canning and Jago, 

with Okpilak/Hulahula having overlapping similarity with both Canning and Jago. ...................18

Figure. 4.1. Relative proportion of bacterial taxa across all samples, as calculated from 16S 

amplicon Illumina MiSeq sequence analyses. These data were randomly subsampled to 6802 

sequences per sample to avoid potential biases in diversity based on uneven sample sizes. After 

subsampling, 13,463 taxa (OTUs) were observed among these 53 samples.................................27

Figure 4.2. Ordination of nonmetric multidimensional scaling plot of subsampled mudflat 

bacterial communities from the Jago, Okpilak/Hulahula, and Canning river deltas, northern 

Alaska. Sequence reads were first normalized using a Hellinger transformation and then BrayCurtis distance was used for calculation of beta diversity. ...........................................................28

Figure 4.3. Ordination of nonmetric multidimensional scaling plot of subsampled mudflat 

eukaryotic communities from the Jago, Okpilak/Hulahula, and Canning river deltas, northern 

Alaska. Sequence reads were first normalized using a Hellinger transformation and then BrayCurtis distance was used for calculation of beta diversity. ...........................................................28

Figure 5.1. Average chlorophyll a concentrations from three Arctic river deltas (Jago: JAG; 

Okpilak/Hulahula: OKP; Canning: CAN) during 2011 and 2013 sampling regimes across two 

sampling periods. Error bars represent standard errors. ................................................................39
iv

Figure 5.2. Average chlorophyll a concentrations from three Arctic river deltas (Jago: JAG; 

Okpilak/Hulahula: OKP; Canning: CAN) during 2011 and 2013 sampling regimes across two 

sampling periods. Error bars represent standard errors. ................................................................40

Figure 5.3. Average chlorophyll a:total pheopigment concentrations from three Arctic river 

deltas (Jago: JAG; Okpilak/Hulahula: OKP; Canning: CAN) during 2013 sampling regimes. 

Error bars represent standard errors. Numbers above bars are calculated ratio of chlorophyll 

a:total pheopigments. ....................................................................................................................42

Figure 5.4. Average pheopigment concentrations from three Arctic river deltas (Jago: JAG; 

Okpilak/Hulahula: OKP; Canning: CAN) during 2013 sampling regimes across two sampling 

periods. Error bars represent standard errors.................................................................................42

Figure 5.5. Average total organic carbon concentrations from three Arctic river deltas (Jago: 

JAG; Okpilak/Hulahula: OKP; Canning: CAN) during 2011 and 2013 sampling regimes across 

two sampling periods. Error bars represent standard errors. .........................................................43

Figure 5.6. Isotopic δ13C and δ15N values for sediment samples from three Arctic river deltas 

(JOHC) during 2011 sampling periods..........................................................................................44

Figure 5.7: Isotopic δ13C and δ15N values for sediment samples from three Arctic river deltas 

(JOHC) during 2013 sampling periods..........................................................................................44

Figure 5.8. Average sediment ammonium concentrations from three Arctic river deltas (Jago: 

JAG; Okpilak/Hulahula: OKP; Canning: CAN) during 2011 and 2013 sampling regimes across 

two sampling periods. Error bars represent standard errors. .........................................................45

Figure 6.1. Grid used for sampling sediment characteristics and macroinvetrebrates on the Jago 

River Delta.....................................................................................................................................49

Figure 6.2. Mean salinity and temperature for each Beaufort Sea river delta (JOHC), 2010 –

2011. The box represents the first and third quartile, the whiskers represent one standard 

deviation, and the dots are outliers. ...............................................................................................55

Figure 6.3. Shannon and Simpson’s diversity indices and evenness for taxa sampled on Beaufort 

Sea river deltas (JOHC) 2011. Individuals were identified to the family level or assumed to 

contain one family if identified at a higher taxonomic level.........................................................55

Figure 6.4. Percent occurrence of macroinvertebrates sampled at Beaufort Sea river deltas 

(JOHC) in 2010 and 2011..............................................................................................................56

Figure 6.5. Predicted distribution of all invertebrate taxa combined during late-season sampling 

at the Jago River Delta 2010 – 2011. ............................................................................................62

Figure 6.6. Predicted distribution of invertebrate taxa through three sampling sessions (early = 21 

July – 1 August, mid = 1 – 8 August, late = 10 – 22 August) at the Jago River Delta 2011. The 

area of the delta changes during the mid-season due to lower water levels during that session...63

Figure 6.7. Sediment grain size with respect to the silt/clay fraction (bottom left panel), soil 

moisture, and C:N data from Beaufort Sea river deltas, 2010-2011. The unquantified portion of 

the sample is sand. The proportion of clay or silt in the combined silt/clay fraction by weight 

fraction for each delta sediment sample is included (bottom right panel).....................................64
v

Figure 6.8. Stable isotopic values (δ15N and δ13C) of the major invertebrate taxa found on 

Beaufort Sea river deltas. Separate circles encompass all of the samples collected on the delta 

and within tundra ponds except for Culicidae, which were collected on the delta as adults that we 

believe had just migrated from nearby tundra ponds as reflected in their depleted δ13C values. 

The four larger circles and squares are isotopic values of suspended particulate organic matter 

(SPOM) and benthic particulate organic matter (BPOM) from the lagoons and rivers (estimates 

from Dunton et al. 2012) that we hypothesized would be the base food source for delta 

invertebrates. .................................................................................................................................66
vi

List of Tables

Table 3.1. Total number of core samples processed from each site [Canning (CRD), Jago, 

Okpilak/Hulahula (OKP)], month, and year. All completed samples include 3 depth profiles (0-1, 

1-3, and 3-5 cm). *Only 8 samples were taken due to inundation of the mudflat at time of 

sampling. .......................................................................................................................................13

Table 3.2. Two-way ANOVA results for the test of total meiofauna abundance (N) differences 

across year, site (Canning, Jago, Okpilak/Hulahula), and session, including the interactions......15

Table 3.3. Two-way ANOVA results for the test of total meiofauna diversity (Hill’s N1) 

differences across year, site (Canning, Jago, Okpilak/Hulahula), and session, including the 

interactions. ...................................................................................................................................15

Table 5.1. Results of parameters measured (means ± standard errors), dates collected, and the 

number of samples used in the analyses from 2011 and 2013 sediment sampling of Jago, 

Okpilak/Hulahula, and Canning river deltas. ................................................................................35

Table 6.1. Taxonomic list of invertebrates sampled at Beaufort Sea river deltas (JOHC), 2010 –

2011. Taxa are underlined at the level at which we conducted the analysis. Superscript F= 

freshwater taxa, S = saltwater taxa, B = commonly found in both salt and freshwater, and T= 

terrestrial taxa. ...............................................................................................................................53

Table 6.2. The percentage that each taxa contributed to invertebrate occurrence for each river 

delta and season on the Beaufort Sea coast. Percentage is the number of cores where taxon was 

present divided by total cores collected for that period x 100. Nematodes were only quantified in 

2011. Species in the Other category include those species that only occurred once within a 

season and delta, including Capniidae, Cicadellidae, Arachnida, Copepoda, Empididae, 

Ephydridae, Hydrachnidia, and Hymenoptera. The “**” represents no detection of a taxa.........58

Table 6.3. Abundance estimates (mean ± S.E.) of macroinvertebrate taxa from the Canning, 

Jago, and Okpilak/Hulahula river deltas. Measurements are abundance m-2. The “**” represents 

no detection of a taxa.....................................................................................................................59

Table 6.4. Effects of environmental factors on Chironomidae abundance (a) and Oligochaeta 

abundance (b) on Beaufort Sea river deltas based on a linear model in which we found a 

significant interaction between the random temporal variables year and session for both 

Chironomidae (p < 0.05) and Oligochaeta (p = 0.04). All variables for the best model are shown 

and only significant random variables are reported. Significance of fixed factors was used in a 

stepwise model selection using backwards elimination of non-significant factors.......................61

Table 6.5. Carbon and nitrogen isotopic values for benthic macroinvertebrates (mean ± SE) and 

the C:N ratio for corresponding samples collected from Beaufort Sea river deltas and three 

tundra ponds < 2 km from the Jago Delta, 2010–2011. ................................................................62
vii

Abbreviations and Acronyms

ANWR Arctic National Wildlife Refuge

C carbon

chl a chlorophyll a

DOC dissolved organic carbon

HPLC high pressure liquid chromatography

JOHC Jago, Okpilak/Hulahula, and Canning River deltas

MDS multidimensional scaling

N nitrogen

NH4 ammonium

NWR National Wildlife Refuge

OCS Outer Continental Shelf

OTUs Operational Taxonomic Units

PCR polymerase chain reaction

POM particulate organic matter

rRNA ribosomal ribonucleic acid

TOC total organic carbon

USFWS US Fish and Wildlife Service
1

1. Executive Summary

Nearshore shelf areas of the Beaufort Sea are defined by biological and physical gradients that 

have influence on the Arctic ecosystem including trophic structure, productivity, and the species 

that inhabit the area. The coast's biologically productive habitats support diverse biota during the 

summer that could be affected by oils spills or other physical disturbances resulting from 

offshore oil exploration in the Beaufort Sea. A greater understanding of benthic community 

structure and function is necessary to better understand the importance of these systems as food 

resources for migratory shorebirds. The primary objectives of this study were to (1) quantify the 

spatial and temporal distribution of bacterial assemblages, meiofauna, and macrofauna at coastal 

lagoons and river deltas along the Beaufort Sea coast, and (2) characterize the sediment pore 

water chemistry for salinity, ammonium, organic carbon, chlorophyll a, stable carbon isotopic 

signature, and sediment grain size at sample locations representative of each site. We describe 

the underlying characteristics of sediments and their influence on lower trophic levels to better 

understand the food webs that ultimately support shorebirds on their migration out from their 

arctic breeding grounds.

Single-celled organisms in sediments are the principal diet for the meiobenthos and 

macrobenthos that sustain shorebird communities, but little is known about the species 

composition of these microbenthic communities or their sensitivity to oil exposure. We 

investigated taxonomic composition of prokaryotic and eukaryotic communities in deltaic 

mudflats of the Jago, Okpilak/Hulahula, and Canning river deltas (JOHC) using DNA 

sequencing. Bacterial communities were highly diverse in all samples, and variability was 

explained by salinity, ammonium concentrations, total organic carbon content, and organic 

carbon and nitrogen stable isotope ratios. Bacterial communities showed minimal interannual 

variability and only slight geographic variability, suggesting a broadly distributed and persistent 

community that may serve as a sensitive indicator of shifts in detrital organic matter including 

oil-associated hydrocarbons. One genera of bacteria that includes known hydrocarbon-degrading 

species (Marinobacter) was detected in high proportions in the Okpilak and Canning deltas, 

suggesting prior or ongoing exposure to hydrocarbons associated with oil. Microeukaryotic 

communities showed greater interannual variability than prokaryotic communities suggesting 
2

that microeukaryotic community composition is less predictable and thus less useful as an 

indicator of environmental change.

Metazoan meiofauna are abundant and diverse benthic invertebrates that reside in marine, 

estuarine, and freshwater soft-sediment habitats. With rapid growth rates and short generation 

times, their biomass and production are a vital component of benthic food webs. We found

abundances of meiofauna comparable to other estuarine habitats studied in the Arctic. Meiofauna 

diversity was relatively low. There were only minor spatiotemporal differences in abundance and 

diversity. Based on their high abundance, meiofauna presumably contribute significantly to the 

annual biomass bloom and provide a vital carbon source that is transferred up the food web.

On shallow tidal flats, benthic microalgae are among the most prolific primary producers of 

labile carbon, but there is little quantitative data to assess their overall importance. We 

determined the nutritional quality of deltaic sediments at JOHC based on analyses of sediment 

chlorophyll, stable δ13C and δ15N isotopic signatures, total organic carbon, C:N ratios, and 

sediment porewater ammonium (NH4

+

) and salinity. Our analyses revealed the presence of a 

healthy microphytobenthos based on chlorophyll a concentrations ranging from 3.6 – 203.9 mg 

m-2 with consistent presence of fucoxanthin reaching 93 mg m-2, indicating that the 

microphytobenthos consisted primarily of diatoms. The chlorophyll a compound is degraded into 

pheopigments by bacterial and metazoan foraging. Pigment analysis revealed that 

chlorophyll a:total pheopigments ratios were < 1, providing clear evidence for the importance of 

the microphytobenthos to primary consumers. Sediment porewaters were clearly estuarine, and 

sediment geochemical parameters clearly reveal strong contributions of terrestrial organic matter 

based on low δ13C and δ15N signatures and high C:N ratios.

Shorebirds are dependent on benthic invertebrates as energy and nutrient sources to fuel 

migration, and the JOHC river deltas are used by thousands of shorebirds as migratory stopover 

sites. We found that the fauna of JOHC were depauperate compared to river deltas at more 

boreal latitudes, reflecting a highly stressed environment for macroinvertebrates in the Arctic. 

Only six taxa regularly occurred in our samples: Oligochaeta, Chironomidae, Tipulidae, 

Amphipoda, Chaetiliidae, and Spionidae; however, these taxa were not found at every river 
3

delta. The Jago and Okpilak/Hulahula deltas had similar sediment environmental characteristics, 

but the Canning Delta had four times higher salinity and carbon values and tended to be cooler 

and drier on average than the other two sites. These differences resulted in variable abundances 

and distributions of macroinvertebrates among deltas. In addition, despite nine-month periods of

frozen sediments, JOHC deltas were populated by a range of taxa represented by both marine 

and freshwater assemblages. Freshwater taxa such as Diptera and Oligochaeta survived extreme 

freezing events, and marine organisms such as Amphipoda and Polychaeta rapidly recolonized

deltas following ice ablation. Stable isotopic analyses revealed that both marine and freshwater 

assemblages of macroinvertebrates assimilated both marine and terrestrial sources of organic 

carbon. Sediment accretion in river deltas of the Beaufort Sea may be greater now than in the 

past due to increased melting of glaciers in the Brooks Range and sediment transport will likely 

decline in the next 50-75 years when glacial ice disappears. Changes in sedimentation rates will 

likely transform sediment structure by increasing grain size, a change that could further affect 

some invertebrates, especially those associated with more fine-grain sediments (e.g. 

Chironomidae). Although the deltaic mudflats of JOHC river deltas had different characteristics

in terms of sediments and associated infauna, they each provide critical food resources for 

shorebirds as they leave their arctic breeding grounds on fall migration.
4

2. Introduction

Nearshore shelf areas of the Beaufort Sea are defined by specific biological and physical 

gradients that have influence on the Arctic ecosystem including trophic structure, productivity, 

and the species that inhabit there. Massive freshwater discharges from the Mackenzie River 

along with numerous smaller rivers including the Jago, Okpilak/Hulahula, and Canning River 

delta systems (JOHC) produce an environment that is estuarine in characteristic (Figure 2.1). The 

features of these estuarine ecosystems vary in trophic structure and productivity. The role of 

terrestrial carbon in these estuarine food webs is especially important in view of current warming 

trends in the Arctic and from Outer Continental Shelf (OCS) post-lease exploration and 

development (Dunton et al. 2006; 2012). Shorebirds depend on invertebrates for food for premigratory fattening along the delta mudflats that are at the river face (Connors et al. 1979; Taylor 

et al. 2011, Churchwell 2015). Smaller organisms that supply food sources for these organisms 

also make important contributions to estuarine food webs (Crump et al. 2013). However, there is 

little information on species composition, abundance, or distribution of the microfauna and 

meiofauna living within the intertidal habitats of the littoral zones along the Beaufort Sea coast

(Churchwell et al. 2015). In addition, the distribution of these microfauna and meiofauna may be 

linked to sediment grain size characteristics, as has been shown elsewhere along the Beaufort 

Sea coast (Dunton and Schonberg 1980).

The Beaufort Sea coast includes a variety of biologically productive habitats in lagoons, barrier 

islands, river deltas, and adjacent tundra areas. These habitats support diverse biota and could be 

affected by oils spills or other physical disturbances resulting from offshore oil exploration in the 

Beaufort Sea. Oil spills, disruption of tundra surfaces, impoundments, and human activities, 

among other changes could potentially impact the benthic invertebrate community including 

important shorebird prey (Truett 2000). These ecosystems are particularly vulnerable to 

predicted climate-change effects, such as inundation and increased erosion caused by rising sea 

levels, glacial melt, and longer periods of open water (Churchwell et al. 2015). Recent studies, 

focused on the trophic linkages among estuarine and lagoon fauna and the assimilation of various 

carbon sources have provided valuable insights into the sensitivity and resilience of these 

systems to anthropogenic changes (Dunton et al. 2012), but have not addressed the intimate 
5

linkages with higher trophic level species, including shorebirds, that are summer residents of 

arctic nearshore systems.

Figure 2.1. Location of the three river deltas (JOHC) in the eastern Beaufort Sea in northern Alaska.

It is known that oils spills adversely affect invertebrate communities, including microfauna (e.g. 

bacterial, fungal, or protozoan populations), and meiofauna (nematodes, gastrotriches, and other 

eukaryotic organisms) living within the interstitial spaces of sediments on the seabed (for review 

see Churchwell et al. 2015). Baseline information pertaining to the biogeochemistry of these 

benthic environments (e.g. sediment characteristics, porewater nutrients, organic matter) would 

allow scientists to identify river and coastal ecosystem processes that may result from 

anthropogenic or regional climate change along the Beaufort Sea coast. A secondary component 

of the estuarine chemistry is the degree of the water-borne constituents (i.e. sediment, nutrients, 

and organic matter) from the JOHC rivers coming from glacier melt (Nolan et al. 2011). To date 
6

it is unclear how inputs from these rivers affect the coastal ocean ecosystem, and how this likely 

to change as the glaciers disappear. Biogeochemical studies of arctic coastal estuarine 

environments may provide more insights into the function of these systems.

2.1 Objectives

The specific objectives of this study were to:

1. Quantify the spatial and temporal distribution of bacterial assemblages, meiofauna, and 

macrofauna at coastal lagoons and river deltas along the Beaufort Sea coast within the US

Fish and Wildlife Service (USFWS) Arctic National Wildlife Refuge at three sites associated 

with the coastal lagoons and deltas of the JOHC rivers.

2. Characterize the sediment pore water chemistry for salinity, ammonium, organic carbon, 

chlorophyll a, stable carbon isotopic signature, and sediment grain size at sample locations 

representative of each site. 

2.2 Tasks

There were seven tasks within the scope of work:

1. Quantify the spatial and temporal distribution of macrofaunal benthic invertebrates at 

three coastal lagoons and river deltas along the Beaufort Sea coast within the USFWS Arctic 

National Wildlife Refuge.

2. Examine the role of meiofaunal populations as food resources through quantitative 

analysis of benthic cores taken at all three sites.

3. Conduct a census of the microbial populations (bacteria archaea, and eukarya) in the 

sediments of the three research sites using DNA sequencing.

4. Quantify sediment chlorophyll and describe the predominant sediment microalgae.

5. Describe the associated sediment characteristics at the three sites. Include salinity, 

organic carbon, ammonium, and sediment grain size at each sample location.

6. Relate the organic composition of the sediments to river sources of organic matter based 

on stable carbon isotopic measurements of sediments to identify the relative importance of 

allochthonous and autochthonous carbon sources.
7

7. Provide a synthesis that links shorebirds and their macro-invertebrate prey within mudflat 

habitats to broader and multiple trophic food web levels (include meio- and macrofauna 

population assemblages) and the nature of their carbon footprints.

The results of these tasks are presented herein in the following manner. Tasks 2, 3, and 4 are 

presented as separate chapters of this report (Chapters 3, 4, and 5). Task 5 is incorporated 

into several sections. Finally, we present Tasks 1 and 7 as a cohesive section (Chapter 6; 

Churchwell et al. 2015).

2.3 References

Churchwell RT. 2015. Stopover ecology of semipalmated sandpipers (Calidris pusilla) at coastal 

deltas of the Beaufort Sea, Alaska. PhD Dissertation, University of Alaska, Fairbanks. 149 

pp.

Churchwell RT, Kendall SJ, Blanchard AL, Dunton KH, Powell AN. 2015. Natural disturbance 

shapes benthic intertidal macroinvertebrate communities of high latitude river deltas. 

Estuaries and Coasts. DOI 10.1007/s12237-015-0028-2

Connors PG, Myers JP, Pitelka FA. 1979. Seasonal habitat use by arctic Alaskan shorebirds. 

Studies in Avian Biology. 2:101–111.

Crump BC, Ducklow HW, Hobbie JE. 2013. Estuarine Microbial Food Webs. Day JH et al., 

editors. Estuarine Ecology. Second Edition. John Wiley and Sons, Inc. p. 263-284. 

Dunton KH, Schonberg SV. 2000. The benthic faunal assemblage of the Boulder Patch kelp 

community. Truett JC, Johnson SR, editors. The Natural History of an Arctic Oil Field. 

Academic Press. p. 371-397.

Dunton KH, Schonberg SV, Cooper LW. 2012. Food web structure of the Alaskan nearshore 

shelf and estuarine lagoons of the Beaufort Sea. Estuaries and Coasts. 35:416-435. 

Dunton KH, Weingartner T, Carmack EC. 2006. The nearshore western Beaufort Sea ecosystem: 

circulation and importance of terrestrial carbon in arctic coastal food webs. Progress in

Oceanography. 71:362-378. DOI:10.1016/j.pocean.2006.09.011. 

Taylor AR, Lanctot RB, Powell AN, Kendall SJ, Nigro DA. 2011. Residence time and 

movements of postbreeding shorebirds on the northern coast of Alaska. Condor. 113:779–

794.
8

Nolan, MR, Churchwell R, Adams J, McClelland J, Tape KD, Kendall S, Powell AN, Dunton K, 

Payer D, Martin P. 2011. Predicting the Impact of Glacier Loss on Fish, Birds, Floodplains, 

and Estuaries in the Arctic National Wildlife Refuge. US Geological Survey Scientific 

Investigations Report 2011-5169, Reston, Virginia.

Truett JC. 2000. Introduction. Truett JC, Johnson SR, editors. The Natural History of an Arctic 

Oil Field. Academic Press. p. 3-13.
9

3. Sediment Meiofaunal Populations

Jeffrey G. Baguley and Anthony D. Kamikawa, Marine Ecosystems Analysis 

Laboratory, University of Nevada-Reno

3.1 Introduction 

Meiofauna are small benthic invertebrates ranging in size from 0.063–0.500 mm, and include

members of 22 of 35 known animal phyla (mostly marine). Metazoan meiofauna are ubiquitous 

in marine, estuarine, and freshwater soft-sediments with high abundance, biomass, and diversity 

(Coull and Bell 1979; Baguley et al. 2006a; Giere 2009). Meiofauna live on smaller spatial and 

temporal scales (Bell 1980; Schwinghamer 1981) and have shorter generation times and higher 

metabolic rates (Mahaut et al. 1995) compared to the larger macrobenthos, and lack planktonic 

larval dispersal (Giere 2009). These life-history characteristics make meiobenthos useful for 

studying ecological and evolutionary mechanisms (Thistle 2003), but also aid in assessing 

environmental or ecotoxicological effects (Montagna and Harper 1996; Bejarano et al. 2006).

Meiofauna have been unequivocally identified as food for higher trophic levels (Coull 1990 and 

references therein). Macrobenthos and zooplankton also feed on meiofauna, providing additional 

mechanisms for transfer of carbon to higher trophic levels (Coull 1990). Predator 

exclusion/inclusion experiments report reductions in meiofauna biomass during inclusions (e.g.,

Gee et al. 1985; Smith and Coull 1987). Based on our understanding of meiofauna as food for 

higher trophic levels, it is expected that this group of microscopic metazoan and protistan 

organisms serves as sources of secondary production and fuels higher trophic levels in benthic 

estuarine food webs of the high Arctic. A detailed study of meiofauna community structure and 

function is necessary to understand potential trophic linkages that may fill important knowledge 

gaps.

Here, the first report of metazoan meiofauna community structure is presented for high Arctic 

estuarine habitats within the Arctic National Wildlife Refuge (ANWR). The objectives of this 

study were to quantify the spatial and temporal distribution of meiofauna assemblages at three 

coastal lagoons along the Beaufort Sea coastline within ANWR.
10

3.2 Methods

Sampling occurred during field seasons in 2011 and 2012. During the first field season 

(July/August 2011), meiobenthic samples were randomly collected from three JOHC coastal 

lagoon sites. Approximately 100 core samples from separate sampling stations were collected 

from the Jago and Okpilak/Hulahula deltas, while approximately 50 core samples from separate 

sampling stations were collected from the Canning Delta (Figure 3.1). During the second field 

season (July/August 2012), core samples were collected from the same three deltas. 

Approximately 50 core samples from separate sampling stations were collected from the Jago

and Okpilak/Hulahula deltas, while 30 core samples were collected from the Canning Delta. 

During both 2011 and 2012 field seasons temporal replication occurred between the two months, 

July and August. 

Figure 3.1. Sediment core sampling at the Jago River delta.
11

Metazoan meiofauna (0.5 mm to 45 μm) were collected using a modified 50-cc syringe as a 

coring device (2.9 cm i.d.). The cores were then sectioned into three vertical depth profiles: 0-1,

1-3, and 3-5 cm. Each section was collected and stored in separate 100-ml plastic sample jars. 

Within each sample jar, animals were narcotized with 20 ml of a 7% magnesium chloride 

solution for 10 min before being preserved in an equal volume of 10% buffered formalin 

(resulting in a final 5% formalin concentration) mixed with a small amount of Rose Bengal dye. 

Buffered formalin was made from estuarine water filtered through a 0.042 mm sieve to exclude 

pelagic and contaminant organisms. Sample jars were then closed tightly and lids were wrapped 

in electrical tape to prevent leakage during shipping. No sieving or sorting of meiofauna 

occurred in the field. Intact sediment samples were shipped to the University of Nevada-Reno for 

analysis in the Marine Ecosystems Analysis Laboratory.

In the laboratory, samples were rinsed over 0.500-mm and 0.045-mm mesh sieves. Macrofauna 

were removed from the meiofauna sample by the 0.500-mm mesh sieve, and meiofauna were 

retained on the 0.045-mm mesh sieve. Fine sediments (silt and clay) pass through the 0.045-mm 

sieve, but the coarser fraction remains. Meiofauna were separated from coarse sediments using 

isopynic centrifugation in Ludox HS-40 (Burgess 2001). Meiofaunal specimens were counted 

and identified to the major taxonomic level, which will yield estimates of total abundance as well 

as major taxonomic diversity. The methods are consistent with those used in previous Minerals 

Management Service-funded studies by members of the project team (e.g., Baguley et al. 2006b).

Meiofauna community structure was analyzed using univariate and multivariate statistical 

procedures to test the following null hypotheses:

H01: There is no difference in community structure between the three estuarine basins (“sites”).

H02: There is no difference in community structure between sampling years (“years”).

H03: There is no difference in community structure between sampling months (“sessions”).

Two-way analysis of variance (ANOVA) was used to test for differences in community metrics 

of total abundance (N) and diversity (Hill’s N1) across the main effects of site, year, and session 

and also the interactions of site by year, site by session, and year by session. Within the 

randomized design, each sample was considered a multivariate replicate; therefore, there were 10 
12

replicate samples per basin, per month, for a total of 20 spatial replicates per year. Tukey’s 

Studentized Range test was used for post-hoc analysis of group means across the main effects. 

Abundance was log(x+1) transformed prior to analysis to conform to the assumptions of the 

general linear model. N1 is already a log transformation and therefore did not require additional 

transformation prior to analysis. Descriptive statistics and ANOVA were carried out using PROC 

MEANS and PROC GLM in SAS Statistical Software, version 9.3 (SAS Institute Inc.). 

Community structure was analyzed with non-parametric multivariate statistical routines. Nonmetric Multidimensional Scaling (MDS) was used to ordinate samples based on similarity and 

multivariate community structure differences were tested using analysis of similarity 

(ANOSIM). Similarity percentages were calculated to explain differences in community 

structure. Community structure data was fourth root transformed prior to calculation of sample 

similarity using the Bray Curtis index. All multivariate routines were carried out in PRIMER, 

version 6.1.2. Diversity indices were also calculated in PRIMER. 

3.3 Results

A total of 120 samples were processed from the 2011 (60 samples) and 2012 (60 samples) field 

seasons (Table 3.1). We processed samples from the 2011/2012 field seasons for a balanced 

design as follows: 10 samples per month, per year, and per delta, with the only exception being 

that 8 samples were taken during the July 2012 field season at the Canning Delta due to 

excessive inundation of the delta. In order to balance the sampling design between years, 12 

samples were analyzed from the August 2012 field season at the Canning Delta. 

Of the 120 samples processed in the study, a total of 1.57x105 individuals were enumerated from 

21 major meiofaunal taxa. Mean core abundance extrapolated to N m-2was 1.98 x 106 with a 

standard deviation of 1.58 x 106. The maximum abundance collected at each lagoon was found in 

2012. Nematoda, Harpacticoida, nauplii, and Tardigrada were the three dominant groups 

accounting for 99.3%. The remaining 0.7% of the meiofaunal community was comprised of 

Kinorhyncha, Ostracoda, Gastrotricha, Rotifera, Nemertinea, Cyclopoida, Bivalvia, Gastropoda, 

Acari, Oligochaetea, Sipuncula, Amphipoda, Aplacophora, Chironomidea, and unknowns. 

Unknown or unidentifiable individuals contributed less than 0.02% to the overall abundance. 

These unknowns are most likely soft-bodied taxa (such as Turbellaria, Bryozoans, and protists), 
13

which often become morphologically distorted during fixation with formalin and are therefore 

unrecognizable. 

Table 3.1. Total number of core samples processed from each site [Canning (CRD), Jago, 

Okpilak/Hulahula (OKP)], month, and year. All completed samples include 3 depth profiles (0-1, 1-3, and 

3-5 cm). *Only 8 samples were taken due to inundation of the mudflat at time of sampling. 

YEAR BASIN SESSION SAMPLES#

COMPLETED

ANNUAL#TOTAL#SAMPLES#

COMPLETED

2011 CRD July 10

20

2011 CRD August 10

2011 JAGO July 10

20 2011 JAGO August 10

2011 OKP July 10

20

2011 OKP August 10

2012 CRD July 8* 20

2012 CRD August 12

2012 JAGO July 10

20

2012 JAGO August 10

2012 OKP July 10

20

2012 OKP August 10

Meiofauna abundance patterns differed across sites in both 2011 (Figure 3.2) and 2012 (Figure 

3.3). In 2011, abundance showed an increasing trend between July and August at the Canning 

and Okilpilak/Hulahula deltas, but not at the Jago Delta. In 2012, there was no apparent trend of 

abundance changes across sessions or sites. At the Canning Delta, abundance increased between 

July and August, but did not vary at the Jago Delta, and showed the opposite trend at 

Okilpilak/Hulahula Delta. 

Meiofauna abundance was not significantly different between years (P = 0.3781) or sessions (P

= 0.4419), but was significantly different among sites (P = 0.0120) (Table 3.2). There were no 

significant interactions (Table 3.3). Tukey post-hoc comparison revealed significant differences 

between Canning and Jago deltas, but the Okpilak/Hulahula Delta was not significantly different 

than either the Canning or Jago deltas. Across both years, average abundance was highest at the 

Canning Delta and lowest at the Jago Delta. At the Canning Delta, meiofauna abundance 

averaged 1152.8 individuals per core, or 1.74X106
14

individual per m-2. At the Okpilak/Hulahula Delta, meiofauna abundance averaged 994.1 

individuals per core, or 1.50X106 individual m-2. At the Jago Delta, meiofauna abundance 

averaged 592.3 individuals per core, or 8.96X105 individual m-2. 

Figure 3.2. Average meiofaunal abundance from each site [Canning (CRD), Jago, Okpilak/Hulahula 

(OKP)] in 2011, broken down by sampling session (July/August) with standard error (δ/√(n)). 

Figure 3.3. Average meiofaunal abundance from each site [Canning (CRD), Jago, Okpilak/Hulahula 

(OKP)] 2012, broken down by sampling session (July/August) with standard error (δ/√(n)).

0#

200#

400#

600#

800#

1000#

1200#

1400#

1600#

1800#

2000#

CRD# Jago# Okpilak#

Average'Meiofauna'Abundance'

Per'Core'(N)'

July#2011#

August#2011#

0#

500#

1000#

1500#

2000#

2500#

3000#

CRD# Jago# Okpilak#

Average'Meiofauna'Abundance'

Per'Core'(N)'

July#2012#

August#2012#
15

Table 3.2. Two-way ANOVA results for the test of total meiofauna abundance (N) differences across year, 

site (Canning, Jago, Okpilak/Hulahula), and session, including the interactions.

Source DF Type III SS Mean Square F Value Pr > F

Year 1 0.51280128 0.51280128 2.15 0.1453

Site 2 0.96663345 0.48331672 2.02 0.1365

Session 1 2.55883306 2.55883306 10.73 0.0014

Year*Site 2 0.07531043 0.03765522 0.16 0.8541

Year*Session 1 0.05821690 0.05821690 0.24 0.6221

Site*Session 2 0.00778965 0.00389483 0.02 0.9838

Table 3.3. Two-way ANOVA results for the test of total meiofauna diversity (Hill’s N1) differences across 

year, site (Canning, Jago, Okpilak/Hulahula), and session, including the interactions.

Source DF Type III SS Mean Square F Value Pr > F

Year 1 0.15031662 0.15031662 0.78 0.3781

Site 2 1.76829870 0.88414935 4.61 0.0120

Session 1 0.11432323 0.11432323 0.60 0.4419

Year*Site 2 0.28895165 0.14447583 0.75 0.4735

Year*Session 1 0.38462033 0.38462033 2.00 0.1597

Site*Session 2 0.66812140 0.33406070 1.74 0.1802

Meiofauna diversity patterns were more consistent across sites, years, and sessions. Diversity 

increased between July and August at all sites in both 2011 (Figure 3.4) and 2012 (Figure 3.5). 

Diversity trends were generally similar across sites. 

Meiofauna diversity was not different between years (P = 0.1453) or sites (P = 0.1365), but was 

different between sessions (P = 0.0014) (Table 3). There were no significant interactions (Table 

3). Diversity increased significantly in August compared to July. Hill’s N1 is a measure of the 

effective number of dominant species (in this case taxa). The average number of dominant taxa 

was 1.22 in July, compared to 1.55 in August. 

Multivariate analysis of meiofauna community structure was carried out to test differences 

between years and also test differences within years. In the one-way ANOSIM to test for year 

differences, community structure was significantly different (P = 0.001) from a multivariate 

perspective. The SIMPER routine revealed that the average community dissimilarity between 
16

Figure 3.4. Average meiofaunal diversity (Hill’s N1) from each site [Canning (CRD), Jago, 

Okpilak/Hulahula (OKP)] 2011, broken down by sampling session (July/August) with standard error 

(δ/√(n)).

Figure 3.5. Average meiofaunal diversity (Hill’s N1) from each site [Canning (CRD), Jago, 

Okpilak/Hulahula (OKP)] 2012, broken down by sampling session (July/August) with standard error 

(δ/√(n)).

years was 47.9%, and nematodes contributed to 84% of the overall community dissimilarity, 

while harpacticoid copepods and tardigrades contributed to 4.97% and 4.96% of the community 

dissimilarity across years, respectively. In 2011, nematodes accounted for 96.8% of total 

community structure across all years, sites, and sessions, but in 2012 nematodes accounted for 

99.0% of community structure. 

0#

0.2#

0.4#

0.6#

0.8#

1#

1.2#

1.4#

1.6#

1.8#

2#

CRD# Jago# Okpilak#

Average'Meiofauna'Diversity'Per'

Core'(Hill's'N1)'

July#2011#

August#2011#

0#

0.2#

0.4#

0.6#

0.8#

1#

1.2#

1.4#

1.6#

1.8#

2#

CRD# Jago# Okpilak#

Average'Meiofauna'Diversity'Per'

Core'(Hill's'N1)'

July#2012#

August#2012#
17

MDS ordination of samples from 2011 suggested that sites were clustering differently (Figure 

3.6). The Canning and Jago delta samples clustered farther apart, while Okpilak/Hulahula 

samples overlapped with both Canning and Jago. Community structure differences were 

independently tested within years using two-way ANOSIM to test for differences between sites

and sessions. In 2011, two-way ANOSIM revealed a significant difference between sites across 

all session groups (P = 0.021), but no significant difference between session groups across all 

sites (P = 0.074). Although, it should be noted that the lack of session significance was marginal. 

So, while community structure differed spatially in 2011, it did not vary temporally. Pairwise test 

of site groups revealed significant differences in community structure between the Canning and 

Jago delta samples (P = 0.001), but no difference between the Canning and Okpilak/Hulahula 

delta samples (P = 0.199) or the Jago and Okpilak/Hulahula delta samples (P = 0.212). The 

SIMPER routine found an average dissimilarity of 39.6% 

Figure 3.6. MDS ordination of meiofauna community structure across all sites [Canning (CRD), Jago, 

Okpilak/Hulahula (OKP)] 2011. Data were fourth root transformed prior to Bray Curtis similarity analysis. 

Ordination of stations reveals lower similarity between Canning and Jago, with Okpilak/Hulahula having 

overlapping similarity with both Canning and Jago.

between the Canning and Jago deltas. Nine different taxa accounted for 91% of the community 

dissimilarity between these two sites in 2011. Four taxa accounted for 71.5% of the dissimilarity, 

Beaufort

Transform: Fourth root

Resemblance: S17 Bray Curtis similarity

Site

CRD

Jago

Okpilak

2D Stress: 0.15
18

and were nematodes (20.15%), tardigrades (18.95%), harpacticoids (16.6%), and nauplii 

(15.85%). 

In 2012, the MDS ordination of samples was similar to 2011 with samples from the Canning and 

Jago deltas clustering farthest from one another and Okpilak/Hulahula samples overlapping with 

both the Canning and Jago delta samples (Figure 3.7). However, two-way ANOSIM revealed 

significant differences between site groups across all session groups (P = 0.001) and significant 

session differences across all site groups (P = 0.007). So, in 2012 community structure differed 

both temporally and spatially. Pairwise differences of site groups suggested that all sites differed 

from each other as follows: Canning/Jago (P = 0.006); Canning /Okpilak (P = 0.002); and 

Jago/Okpilak (P = 0.048). Community structure differences between the Canning and Jago deltas 

Figure 3.7. MDS ordination of meiofauna community structure across all sites [Canning (CRD), Jago, 

Okpilak/Hulahula (OKP)] 2012. Data were fourth root transformed prior to Bray Curtis similarity analysis. 

Ordination of stations reveals lower similarity between Canning and Jago, with Okpilak/Hulahula having 

overlapping similarity with both Canning and Jago.

were due to nematodes, tardigrades, nauplii, harpacticoids, and rotifers that together accounted 

for a total of 77.8% of total between-site dissimilarity. Community structure differences between 

Canning and Okpilak/Hulahula were due to nematodes, harpacticoids, tardigrades, nauplii, and 

turbellarians that together accounted for 73.8% of the between-site dissimilarity. Community 

Beaufort

Transform: Fourth root

Resemblance: S17 Bray Curtis similarity

Site

CRD

Jago

Okpilak

2D Stress: 0.17
19

structure differences between the Jago and Okpilak/Hulahula deltas were due to nematodes, 

nauplii, tardigrades, rotifers, and harpacticoids that together accounted for 74.7% of the betweensite dissimilarity. Between July and August 2012, nematode abundance dropped from 80% of 

total community structure to 74% of total community structure, which explains this within-year 

temporal difference in community structure. 

3.4 Discussion

The meiofauna community is ubiquitous in marine, estuarine, and freshwater soft-sediment 

habitats (Coull and Bell 1979) and is a crucial component of associated benthic food webs (Coull 

1990; Montagna 1995). Meiofauna feed on bacteria, benthic microalgae, detritus, and prey upon 

other meio- or microfauna (Weiser 1960; Montagna 1995). Macrobenthos are known to feed on 

meiofauna, thus providing a mechanism for transfer of meiofauna secondary production to 

higher trophic levels (Coull 1990). With high abundance, biomass, and short generation times, 

meiofauna respond quickly to spring bloom conditions, allowing for rapid transfer of primary 

produced carbon up the food web. With abundances on the order of 105 – 106 individuals m-2

(Figures 3.2 & 3.3), estuarine sediments within the Jago, Canning, and Okpilak/Hulahula deltas 

have densely populated meiofauna communities that are comparable to other estuarine habitats at 

lower latitudes (Geire 2009). 

When pooling samples across both sampling years, meiofauna abundance varied spatially 

suggesting that environmental conditions across the three sampling sites were not similar, with 

Canning having highest meiofauna abundance year over year (Figures 3.2 & 3.3). Seasonally, 

meiofauna abundance increased from July to August consistently at the Canning Delta, while the 

Jago Delta did not see consistent seasonal changes in abundances in either year (Figures 3.2 & 

3.3). At the Okpilak/Hulahula Delta, the pattern of abundance change from July to August 

differed in 2011 and 2012 (Figures 3.2 & 3.3). When independently analyzing 2011 and 2012 

data, it was clear that community structure varied spatially in both years. Further, community 

structure patterns were similar between years, with the Canning and Okpilak/Hulahula deltas 

being least similar to each other. The Jago Delta had overlapping community similarity with the 

Canning and Okpilak/Hulahula deltas in 2011, but became less similar to both sites in 2012 

(Figures 3.6 & 3.7). 
20

Patterns of abundance are subject to biotic and abiotic factors that can stimulate or disturb 

community structure. For example, increased freshwater inundation can disturb estuarine and 

marine communities that favor higher salinities. Fully understanding the dynamics of 

meiobenthic community structure and function in Arctic communities will require detailed 

analyses of sediment characteristics, water quality, thermal variation, as well as potential 

physical and biological sources of disturbance. Unfortunately, an environmental variable dataset 

was not collected that allowed for direct comparison to meiobenthic community structure in 

order understand how environmental conditions are help structure biotic patterns. 

Diversity patterns were similar across sites and exhibited consistent seasonal changes within sites 

from July to August (Figures 3.4 & 3.5). At all sites, in both years, diversity increased from July 

to August. Meiofauna community diversity was clearly dominated by nematode worms in all 

samples, which is consistent with our understanding of meiofauna communities in general (Coull 

and Bell 1979; Giere 2009). Nematodes are likely competitively superior to other meiofauna, and 

respond quickly to increases in food supply, and may be more tolerant to disturbance (Giere 

2009). Here, nematode dominance was always greatest in July, perhaps due to faster responses 

by nematodes to relative to other taxa after the onset of the spring bloom. Between July and 

August, other minor taxa, principally harpacticoid copepods, rotifers, and tardigrades increased 

in proportional abundance, but their relative contributions to community abundance and diversity 

differed by year, site, and session as presented above. The short annual period without ice cover 

likely favors the highly tolerant nematodes, only allowing brief windows in the late summer for 

less competitive taxa to flourish. 

3.5 References

Baguley JG, Montagna PA, Lee W, Hyde LJ, Rowe GT. 2006a. Spatial and bathymetric trends in 

Harpacticoida (Copepoda) community structure in the Northern Gulf of Mexico deep-sea. 

Journal of Experimental Marine Biology and Ecology. 330:327-341. 

Baguley JG, Montagna PA, Hyde LJ, Kalke RD, Rowe GT. 2006b. Metazoan meiofauna 

abundance in relation to environmental variables in the northern Gulf of Mexico deep sea. 

Deep-Sea Research I. 53:1344-1362.
21

Bejarano AC, Chandler GT, Lijian H, Coull BC. 2006. Individual to population level effects of 

South Louisiana crude oil water accommodated hydrocarbon fraction (WAF) on a marine 

meiobenthic copepod. Journal of Experimental Marine Biology and Ecology. 332:49-59

Bell SS. 1980. Meiofauna–macrofauna interactions in a high saltmarsh habitat. Ecological 

Monographs. 50:487-505.

Burgess R. 2001. An improved protocol for separating meiofauna from sediments using colloidal 

silica sols. Marine Ecology Progress Series. 214: 161-165.

Coull BC. 1990. Are members of the meiofauna food for higher trophic levels? Transactions of 

the American Microscopical Society. 109: 233-246. 

Coull BC, Bell SS. 1979. Perspectives of marine meiofauna ecology. In: Livingston RJ, editor.

Ecological processes in coastal and marine systems. New York (NY): Plenum Publishing 

Corp. p. 189-216. 

Gee MJ, Warwick RM, Schaanning M, Berge JA, Ambrose WG. 1985. Effects of organic 

enrichment on meiofaunal abundance and community structure in sublittoral soft sediments. 

Journal of Experimental Marine Biology and Ecology. 91:247-262. 

Giere O. 2009. Meiobenthology: the microscopic motile fauna of aquatic sediments. Heidelburg: 

Springer-Verlag Berlin. 

Mahaut ML, Sibuet M, Shirayama Y. 1995. Weight-dependent respiration rates in deep-sea 

organisms. Deep-Sea Research 42:1575-1582. 

Montagna PA. 1995. Rates of metazoan meiofauna microbivory: a review. Vie et Milieu. 45:1-9. 

Montagna P, Harper Jr DE. 1996. Benthic infaunal long-term response to offshore production 

platforms in the Gulf of Mexico. Canadian Journal of Fisheries and Aquatic Sciences. 

53:2567-2588. 

Schwinghamer P. 1981. Characteristic size distributions of integral benthic communities. 

Canadian Journal of Fisheries and Aquatic Sciences. 38:1255-1263. 

Smith LD, Coull BC. 1987. Juvenile spot (Pisces) and grass shrimp predation on meiobenthos in 

muddy and sandy substrata. Journal of Experimental Marine Biology and Ecology. 105(2): 

123-136. 

Thistle D. 2003. The deep-sea floor: An overview. In: Tyler PA, editor. Ecosystems of the deep. 

Amsterdam (the Netherlands): Elsevier Science B.V. Chapter 2, p. 5-38. 
22

Weiser W. 1960. Benthic studies in Buzzards Bay. II. The meiofauna. Limnology and

Oceanography. 5:121-137. 
23

4. Sediment Microbial Populations

Colleen T. E. Kellogg, University of British Columbia, Vancouver, BC, Canada

Byron C. Crump, Oregon State University, Corvallis, OR

4.1 Introduction

Single-celled organisms in sediments (i.e., microbenthos) are the principle diet for the 

meiobenthos and macrobenthos that sustain shorebird communities (Gerlach 1978, Tsuchiya and 

Kurihara 1979, Andresen and Kristensen 2002, van Oevelen et al. 2006a), but little is known 

about the species composition of these communities in the nearshore shelf areas of the Beaufort

Sea. Microbenthos, including Bacteria, Archaea, heterotrophic protists (e.g., ciliates, flagellates), 

and microphytobenthos (e.g., diatoms) form a complex, species-rich microbial food web in 

estuaries that consume detrital organic matter from terrestrial and planktonic environments 

(Carlsson et al. 1993, Hamels et al. 2004, McCallister et al. 2004, van Oevelen et al. 2006b). The 

species composition of these communities is highly variable and has been found to be driven by 

temporal and spatial variability in environmental conditions (e.g., organic matter source) and the 

physical constraints of sediment environments (e.g., interstitial space size/shape and 

hydrodynamic disturbances) (Tankere et al. 2002, Crump et al. 2003, Hamels et al. 2004, Judd 

2004, Judd et al. 2006, Crump et al. 2009, Feng et al. 2009, Auguet et al. 2010).

Recent research also demonstrated that the diversity of sediment microbial communities is 

sensitive to oil exposure, and suggested that several genera of bacteria may serve as useful 

indicators of oil contamination in coastal sediments (dos Santos et al. 2011). Similarly, shifts in 

microbial community composition were observed over winter months in sea ice experimentally 

contaminated with crude oil (Brakstad et al. 2008), suggesting that only a subset of the polar 

microbial community possesses the capacity to use hydrocarbon sources for growth. Enrichment 

cultures and bacterial isolates from polar waters and sea ice were found to effectively degrade 

hydrocarbons at cold temperatures (<5°C; Deppe et al. 2005, Lin et al. 2009). 

We hypothesized that the composition of microbial communities in sediments of the Beaufort 

Sea coastal lagoons will correlate with seasonal and site-specific variation in organic matter 

source and character. Microbial communities are more diverse and dynamic than meiobenthos 

communities and can change in composition in a matter of days to weeks. Thus, the composition 
24

of these communities may serve as a sensitive indicator of environmental shifts, including shifts 

in the character of organic matter and the introduction of oil contamination in the Beaufort Sea 

coastal lagoons.

4.2 Materials and Methods

4.2.1 Microbial community composition

The taxonomic composition of prokaryotic and microeukaryotic communities was investigated in 

deltaic mudflats of the Canning, Jago, and Okpilak/Hulahula rivers using PCR amplicon Illumina 

DNA sequencing of 16S and 18S rRNA genes in summer 2011 and 2013. Microbial community 

composition was determined for a subset of samples collected in 2011 (n=20) and 2013 (n=33). 

DNA extracted from ~0.5 g of sediment using the MoBio PowerSoil DNA extraction kit was 

PCR-amplified with primers targeting the V4 region (515F, GTGCCAGCMGCCGCGGTAA 

and 806R, GGACTACHVGGGTWTCTAAT) of the 16S rRNA gene for prokaryotic 

composition and the V9 region (1391F, GTACACACCGCCCGTC and EukBr, 

TGATCCTTCTGCAGGTTCACCTAC) of the 18S rRNA gene for microeukaryotic composition 

for sequencing on the Illumina MiSeq platform using Earth Microbiome Project (Gilbert et al. 

2014) protocols, but with only 30 total cycles. Amplicons from each sample were pooled in 

equimolar concentrations and sent either to Argonne National Lab (2011 16S amplicons) or to 

Oregon State University Center for Genome Research and Biocomputing (all 18S amplicons and 

2013 16S amplicons) for sequencing at 2x150 bp read lengths. Sequences were paired using 

fastq-join (Aronesty 2013), quality controlled and clustered using USEARCH (Edgar 2013), and 

assigned taxonomy using the RDP classifier in QIIME (Caporaso et al. 2010). Chloroplast, 

mitochondria, and Archaea were removed from the prokaryote sequences prior to analysis. 

Microeukaryote analysis focused only on protist and fungal sequences by removing sequences 

assigned to multicellular organisms (metazoan, unassigned eukaryotes, unassigned holozoans, 

and multicellular Archaeplastida). Note that quantitative assessment of microeukaryotic 

communities using rRNA gene sequencing is less reliable than for prokaryotes due to large 

variation in gene copy number per cell, which is not well understood but ranges from <30 to 

>30,000 (Prokopowich et al. 2002).
25

4.3 Results and Discussion

4.3.1 Bacterial Community

Bacterial community composition showed minimal interannual variation across the three river 

deltas sampled (ANOSIM R = 0.1208, P = 0.015) and was consistently dominated by 

Proteobacteria (Figure 4.1). Slight geographic differences in community composition were 

observed (Figure 4.2; ANOSIM R = 0.2816, P = 0.001) and were mainly driven by 2013 

samples. The Canning River delta had higher proportions of gammaproteobacteria (average = 

15%) while the Jago and Okpilak/Hulahula mudflats had lower proportions (6% and 9% on 

average) in favor of higher average proportions of betaproteobacteria (13% and 11%, 

respectively, Figure 4.1). These differences likely result from the longer residence time of 

freshwater in the Jago and Okpilak/Hulahula River deltas compared to the Canning Delta, due to 

the presence of barrier islands in the Jago and Okpilak/Hulahula delta regions. 

Availability of δ15N, δ13C, TOC, ammonium, and salinity measurements for 2013 samples 

allowed for direct comparison between prokaryotic community composition and sediment 

characteristics. These data explained approximately 41% of the variation in 2013 bacterial 

community structure. Salinity accounted for 20% of the total variation explained, which is 

consistent with several studies that show salinity is an important control on estuarine microbial 

communities (Crump et al. 2004, Fortunato and Crump 2011, Herlemann et al. 2011). δ15N and 

δ13C accounted for 12% and 8% of the total variation explained, respectively, supporting the 

hypothesis that microbial community composition correlates with seasonal and site-specific 

variation in organic matter source and character (Bowen et al. 2009).

Given the development of oil fields in nearshore arctic environments, we were also interested in 

detecting known hydrocarbon degraders (e.g., Marinobacter sp., Alcanivorax sp., Colwellia sp., 

Oleiphilaceae sp., etc.) (dos Santos et al. 2011, Beazley et al. 2012). One genera of bacteria that 

includes known hydrocarbon-degrading species (Marinobacter; Gauthier et al. 1992) was

observed at concentrations between 0.5-10% in Okpilak/Hulahula and Canning deltas, 

suggesting prior or ongoing exposure to hydrocarbons associated with oil (Yakimov et al. 2005, 

Al-Mailem et al. 2010, Kostka et al. 2011, Jurelevicius et al. 2013, Lamendella et al. 2014). This 

species was more rare in Jago mudflats. Alcanivorix, Colwellia and Oleiphilaceaea spp. were 
26

present in low proportions throughout the dataset. Thus, the broadly distributed and persistent 

bacterial community detected in Beaufort lagoons may serve as a sensitive indicator of shifts in 

detrital organic matter including oil-associated hydrocarbons. Future work on this topic will 

allow us to begin to address the degree to which mudflat microbiota are poised to remediate 

hydrocarbon spills in this region. 

4.3.2 Microeukaryotic Community

Based on 18S gene abundance, microeukaryotic communities were dominated by diatoms and 

other Stremanopiles, and by dinoflagellates and other Alveolates. Interannual differences were 

more apparent in the Protistan and Fungal communities than Bacterial communities in these 

mudflats (Figure 4.2; ANOSIM R = 0.2231, P = 0.001), but among-lagoon variation was not as 

strong (ANOSIM R = 0.22, P= 0.001). In general, 2011 microeukaryotic communities had a 

higher proportion of diatom sequences, particularly Bacillariophytes, while 2013 communities

had a higher proportion of Alveolate sequences (Figure 4.3). As was done for the bacterial 

community, we compared microeukaryotic community composition with mudflat chemical 

characteristics measured in 2013. These data explained nearly 34% of the variation in 2013 

microeukaryotic community structure, with salinity (10%) and δ15N (8%) explaining the largest 

amount of variation, followed by δ13C (6%). When chemical data from 2011 becomes available 

we will examine temporal variability in the sediment environment that gave rise to the shift from 

a diatom to an alveolate-dominated microeukaryotic community. These findings suggest the 

importance of salinity and organic matter source as important determinants of microeukaryotic

community composition. Future shifts in these environmental variables could have dramatic 

impacts on the microeukaryotic communities in these mudflats and have far-reaching 

implications for higher trophic levels that use this habitat as breeding and feeding grounds. 
27

Figure. 4.1. Relative proportion of bacterial taxa across all samples, as calculated from 16S amplicon Illumina MiSeq sequence analyses. These 

data were randomly subsampled to 6802 sequences per sample to avoid potential biases in diversity based on uneven sample sizes. After 

subsampling, 13,463 taxa (OTUs) were observed among these 53 samples. 
28

Figure 4.2. Ordination of nonmetric multidimensional scaling plot of subsampled mudflat bacterial 

communities from the Jago, Okpilak/Hulahula, and Canning river deltas, northern Alaska. Sequence 

reads were first normalized using a Hellinger transformation and then Bray-Curtis distance was used for 

calculation of beta diversity. 

Figure 4.3.!Ordination!of!nonmetric!multidimensional!scaling!plot!of!subsampled!mudflat!

eukaryotic!communities from!the!Jago,!Okpilak/Hulahula,!and!Canning!river!deltas,!northern!

Alaska.!Sequence!reads!were!first!normalized!using!a!Hellinger!transformation!and!then!BrayG

Curtis!distance!was!used!for!calculation!of!beta!diversity.!
29

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van Oevelen, D, Soetaert K, Middelburg JJ, Herman PMJ, Moodley L, Hamels I, Moens T, Heip

CHR. 2006b. Carbon flows through a benthic food web: Integrating biomass, isotope and 

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33

5. Sediment Parameters: Chlorophyll, Microalgal Composition, Ammonium,

and Stable Isotopic Measurements

Ken Dunton and Philip Bucolo, The University of Texas Marine Science Institute

5.1 Introduction

Arctic nearshore shallow river deltas are foraging sites for migratory shorebirds dependent on 

resident invertebrate food sources for pre-migratory fattening (Brown 2006). Following freshet, 

Arctic river freshwater discharge mixes with marine waters at the mouth of these shallow river 

deltas. Dunton et al. (2012) provided strong evidence that terrestrially derived organic inputs 

such as those from riverine discharge and erosion are assimilated by primary consumers in 

several shallow Arctic lagoons. Consumers included epibenthic amphipods, mysids, and infaunal 

mollusks, all of which are food sources for foraging shorebirds (Craig et al. 1984). Invertebrates 

of this trophic guild rely on sediment-associated microalgae and bacteria, particulate organic 

matter (POM), and subsequent biogeochemical processes that produce dissolved organic carbon 

(DOC) to flourish in estuarine habitats (Dunton et al. 2012; McTigue and Dunton 2014). Overall 

there is a paucity of studies investigating the community structure and biogeochemical processes 

of the sediment microbial community and associated abiotic characteristics of Arctic river delta 

sediments. In order to better describe the ecological structure and biogeochemical contributions 

of the micro-epibenthic community, our group characterized the sediment microalgal 

assemblages based on pigment analysis, and sediment chemistry characteristics (including stable 

isotope δ13C and δ15N signatures, TOC, C:N ratios, levels of sediment porewater ammonium 

(NH4

+

), and salinity) from the Jago, Okpilak, and Canning river deltas of the Alaskan Arctic. 

In addition to providing a food source for micro- and macro-invertebrates important to shorebird 

sustainability, sediment associated microalgae, or microphytobenthos, contribute up to 50% of 

primary production in mud flats (Underwood and Kromkamp 1999) and exceed pelagic 

production by a factor of 1.5 along the Arctic shelf to depths of 30 m (Glud et al. 2009). High 

pressure liquid chromatography (HPLC) pigment analyses can elucidate microphytobenthic 

viability and the taxonomic composition of major algal contributors to sedimentary community 

production. Our analyses included calculation of the universal photosynthetic pigment chlorphyll 

a (chl a), microalgal accessory pigments indicative of specific algal taxonomic groups, and chl a

degradation products known as pheopigments. To further investigate primary production from 
34

sediment microalgae of the river deltas, we also measured TOC, which reflects the total reservoir 

of carbon in sediments, but provides little information on source or lability. Sedimentary stable 

isotope (δ13C and δ15N) and molar C:N analyses were employed to trace terrestrial and marine 

contributions to the microepibenthic community. Sediment porewater measurements of salinity 

and NH4

+ provided information on the relative magnitude of sediment organic decomposition 

and mixing of river runoff and marine waters, respectively. 

5.3 Materials and Methods 

Approximately 340 and 120 sediment cores were collected during summer 2011 and 2013 

respectively, from sampling stations across the Jago, Canning, and Okpilak/Hulahula river deltas 

during two separate sampling periods, 15 July to 8 August and from 11 to 22 August. Due to 

inclement weather, only the Jago River delta was sampled during the second sampling period in 

2013. At each station three replicate sediment cores were extracted to 5 mm into the sediment 

with a 20-cc (radius = 1 cm) syringe to collect material for sediment pigments, TOC, isotopic 

and C:N analysis. Each core was placed in a pre-labeled Falcon tube and those used for pigment 

analysis were wrapped in foil to avoid sunlight. Two separate 60-cc (radius = 1.46 cm) syringe 

cores were used to collect sediments to analyze porewater salinity and NH4

+

, and to collect 

additional sediment for further microalgal analysis if needed. Those samples were placed into 

pre-labeled Whirl-pac® bags. All samples were immediately frozen until analysis. A 

representative subsample was used to quantify each parameter across each delta in each sampling 

period (Table 5.1).

5.3.1 Pigment Analysis

HPLC provides the most reliable method of sedimentary pigment analysis and was used here to 

measure chl a concentrations, pheopigment chl a degradation products, and accessory pigments 

indicative of specific algal groups. Prior to analysis, pigments were extracted using 10 ml of 

100% acetone to account for acetone dilution by residual porewater. Volume of porewater was 

determined by evaporation and accounted for during extraction. Samples were sonicated for 15 

min in darkness during extraction and were centrifuged for 5 min at 4000 rpm. The supernatant 

was decanted and filtered. This process was repeated and both filtered supernatants were
35

Table 5.1. Results of parameters measured (means ± standard errors), dates collected, and the number of samples used in the analyses from 

2011 and 2013 sediment sampling of Jago, Okpilak/Hulahula, and Canning river deltas.

Jago Okpilak/Hulahula Canning

year sampling 

period

collection 

date(s) n mean ± SE collection date(s) n mean ± SE

collection 

dates(s) n mean ± SE

δ15N (‰) 2011 1 7/23,28,30 4 1.59 ± 0.14 7/25,26,30; 8/8 5 2.39 ± 0.39 7/30; 8/1 4 2.94 ± 0.35

2011 2 8/11,13,16 3 1.95 ± 0.13 8/17,22 2 1.94 ± 0.43 8/13 1 1.68

2013 1 8/3,6 11 1.74 ± 0.84 8/8 9 2.09 ± 0.16 8/5,4 10 2.50 ± 0.14

2013 2 8/19 4 1.70 ± 0.38 0 0

δ13C (‰) 2011 1 7/23,28,30 4 -26.38 ± 0.48 7/25,26,30; 8/8 5 -24.90 ± 0.21 7/30; 8/1 4 -25.05 ± 0.92

2011 2 8/11,13,16 3 -26.36 ± 0.16 8/17,22 2 -25.65 ± 0.59 8/13 1 -25.31

2013 1 8/3,6 11 -25.78 ± 0.14 8/8 9 -24.28 ± 0.31 8/4,5 10 -24.82 ± 0.18

2013 2 8/19 4 -25.94 ± 0.72 0 0

C:N (mol/mol) 2011 1 7/28,29 4 11.27 ± 0.56 7/25,26,30; 8/8 5 9.90 ± 1.30 7/30; 8/1 4 12.13 ± .72

2011 2 8/11 3 11.20 ± 0.86 8/17,22 2 17.09 ± 8.11 8/13 1 24.87

2013 1 8/3,4 11 10.22 ± 0.54 8/8 9 12.78 ± 2.82 8/4,5 10 13.46 ± 1.37

2013 2 8/19 4 13.49 ± 1.48 0 0

Total Organic 

Carbon (% g 

sample-1)

2011

1 7/23,28,30 3 1.73 ± 0.10 7/25,26,31 3 2.09 ± 0.68 7/30 3 3.46 ± 0.39

2011 2 8/19 3 2.44 ± 0.17 8/17,19 3 2.48 ± 0.78 8/14 3 4.02 ± 0.76

2013 1 8/3,4 11 2.24 ± 0.24 8/8 9 1.77 ± 0.19 8/4,5 10 3.10 ± 0.23

2013 2 8/19 5 2.26 ± 0.38 0 0

NH4 (μmol L-1) 2011 1 7/15-30 40 169.00 ± 18.39 7/19,25-31; 8/1,7,8 47 69.90 ± 10.75 7/29,30; 8/1,2 47 69.90 ± 10.75

2011 2 8/11-16 70 203.42 ± 15.14 8/12,15-26 91 101.46 ± 9.46 8/12-15 92 101.46 ± 9.46

2013 1 8/3,4 27 79.15 ± 17.22 8/8 34 73.38 ± 10.77 8/4,5,8 34 73.38 ± 10.77

2013 2 8/18,19 18 96.67 ± 18.60 0 0
36

Chlorophyll a 

(mg m-2) 2011 1 7/23-30 9 90. 98 ± 13.52 7/23-30 10 74.03 ± 16.42 7/23-30 10 55.99 ± 8.91

2011 2 8/11,13,16 8 74.11 ± 7.94 8/11,13,16 10 55.91 ± 16.73 8/11,13,16 10 52.84 ± 3.66

2013 1 8/3,4,8 10 35.90 ± 9.20 8/3,4,8 10 16.29 ± 5.28 8/3,4,8 10 15.06 ± 3.4

2013 2 8/18,19 10 64.33 ± 20.03 0 0

Fucoxanthin 

(mg m-2) 2011 1 7/23-30 9 36.01 ± 8.44 7/23-30 10 20.32 ± 3.43 7/23-30 10 15.10 ± 2.80

2011 2 8/11,13,16 8 30.23 ± 3.83 8/11,13,16 10 26.64 ± 6.04 8/11,13,16 10 23.90 ± 2.48

2013 1 8/3,4,8 10 10.84 ± 2.07 8/3,4,8 10 4.60 ± 1.06 8/3,4,8 10 5.45 ± 1.99

2013 2 8/18,19 10 14.41 ± 2.51 0 0

Total 

Pheopigment 

(mg m-2)

2013

1 8/3,4,8 10 40.17 ± 9.78 8/3,4,8 10 24.58 ± 7.04 8/3,4,8 10 26.80 ± 4.22

2013 2 8/18,19 10 44.06 ± 11.39 0 0

Pheophytin a

(mg m-2) 2013 1 8/3,4,8 10 13.42 ± 3.67 8/3,4,8 10 8.35 ± 2.26 8/3,4,8 10 8.55 ± 2.04

2013 2 8/18,19 10 11.62 ± 3.04 0 0

Pheophorbide a

(mg m-2) 2013 1 8/3,4,8 10 13.28 ± 2.89 8/3,4,8 10 11.22 ± 3.61 8/3,4,8 10 9.77 ± 2.18

2013 2 8/18,19 10 19.80 ± 5.94 0 0

Pyropheophytin 

a (mg m-2) 2013 1 8/3,4,8 10 12.89 ± 4.75 8/3,4,8 10 5.01 ± 2.07 8/3,4,8 10 8.48 ± 1.61

2013 2 8/18,19 10 13.22 ± 4.17 0 0

Salinty (ppt) 2011 1 7/28 2 2.00 ± 2.00 7/19,25-31; 8/1,8 40 7.00 ± 1.90 0

2011 2 0 8/19,22 30 3.00 ± 0.61 0

2013 1 8/3,4 28 4.00 ± 0.90 8/8 33 6.00 ± 1.58 8/4,5,8 18 11.00 ± 1.91
37

combined for HPLC analysis. HPLC pigment analysis followed the protocol of the Danish 

Hydraulic Institute in a C8 HPLC column (Agilent Eclipse XDB, 3.5μm, 4.6 mm diameter x 150 

mm length) where eluted pigments were detected by ultraviolet-vis absorbance. Pigment peaks 

were compared to certified commercial standards to determine concentrations of each compound 

(mg m-2). Pigments targeted for analysis were chl a, accessory pigments chlorophyll b, 

fucoxanthin, zeaxanthin from samples collected during 2011 and 2013; lutein, violaxanthin, and 

alloxanthin from 2011; and peridinin, 19-hex-fucoxanthin and pheopigments from 2013. Chl a

was targeted as a proxy for fresh algal organic matter in sediments. Chl b was targeted to identify 

chlorophytes, fucoxanthin for the diatom lineage, the carotenoid zeaxanthin for cyanobacteria, 

chlorophytes and land plants. From 2011 sampling, lutein was targeted for presence of 

rhodophytes and glaucophytes, violaxanthin for chlorachniophytes, and alloxanthin for 

cryptomonads. Due to a lack of signatures of those pigments from 2011, targeted pigments were 

altered for 2013 analysis. In 2013 pigment analysis peridinin was targeted for dinoflagellate 

signals, 19-hex-fucoxanthin targeted haptophytes, and pheopigments were used to assess the 

standing stock of chl a breakdown derivatives where the formation of these breakdown products 

depends on specific diagenic events. Herbivorous metazoan grazing primarily forms 

pheophorbide a and secondary degradation product pyropheophorbide a while bacterial 

degradation of the chl a compound forms pheophytin a.

5.3.2 Isotopic Analysis, C:N Ratios, and TOC

Stable isotope analyses were performed on sediment cores on automated systems for coupled 

δ13C and δ15N measurements using a mass spectrometer and elemental analyzer. Samples were 

combusted at 1020°C and injected into mass spectrometer with continuous flow. Isotopic ratios 

are denoted in standard δ notation relative to carbon and nitrogen standards of Vienna PeeDee 

Belemnite and atmospheric N2 respectively where

δX = [(Rsample/Rstandard)-1] X 1000

and X is either 13C or 15N of the sample and R corresponds to the 13C:12C or 15N:14N ratio. 

Instrumental analytical error was ± 0.20‰ based on internal standards (casein and glutamic acid) 

checked against certified standards from the US National Institute of Science and Technology 
38

and the International Atomic Energy Agency. Sediment isotopic signatures and C:N (mol/mol) 

ratios were calculated from these analysis. 

TOC samples were dried at 105°C and weighed, combusted at 550°C for 4 h and reweighed. The 

weight loss is proportional to the amount of organic carbon contained in the sample. Carbon lost 

on ignition during combustion was calculated where

Loss on Ignition (%) = [(DW105 – DW550 / DW105] X 100

and DW is dry weight of samples at 105°C or 550°C in drying oven or muffle furnace 

respectively resulting in TOC (%). 

5.3.3 Porewater Salinity and Ammonium

Sediment porewater was extracted by centrifuging thawed sediments at 10,000 rpm for 20 min 

and analyzing the supernatant for salinity and NH4

+

. Salinity was measured with a refractometer. 

Sediment NH4

+ (μmol L-1

) concentrations were calculated following Parsons et al. (1984) with 

colorimetric analysis based on comparisons at 640 nm absorbance on spectrophotometer and 

regressing to a standard curve. 

5.4 Results and Discussion

Representative subsamples of sediment collections from both sampling periods during 2011 and 

2013 sampling were averaged for each parameter measured and reported here (Table 5.1). 

Although attempts were made to quantify subsampled pigments and sediment chemistry from the 

same stations across sampling periods for each delta, some materials only allowed for analysis of 

samples from stations in close geographic proximity. Number of subsamples dedicated to 

quantify each parameter varied only slightly across most parameters but sediment porewater 

salinity and NH4

+ varied greatly within and between deltas due to an insufficient amount of 

water available for extraction for the analysis. As reported previously, due to inclement weather, 

Okpilak/Hulahula and Canning deltas could not be sampled during the second sampling period 

of 2013 (Table 5.1).
39

5.4.1 Pigment and TOC Analysis

Chl a concentrations ranged from 3.58 to 203.91 mg m-2 which are within recently reported 

ranges for Arctic subtidal sediments (McTigue et al. 2015 and references therein). Jago, Okpilak, 

and Canning chlorophyll concentrations ranged from 3.58 to 203.91, 5.48 to 191.58, and 4.58 to 

116.18 mg m-2 respectively for each delta. These values are reflective of a strong signal for 

viable microphytobenthos. Mean concentrations of chl a from the Jago River Delta were 

consistently greater than the Okpilak/Hulahula and Canning deltas across both years with the 

Okpilak/Hulahula and Canning deltas following in order for each period (Figure 5.1). All chl a

concentrations were significantly higher during 2011 than the first sampling period of 2013. 

However chl a concentrations from the late sampling of 2013 Jago River delta were similar to 

previous year’s findings (Figure 5.1). The presence of chl a throughout these deltas is an 

indicator of a healthy microphytobenthic community inhabiting the upper layer of these 

sediments. 

Figure 5.1. Average chlorophyll a concentrations from three Arctic river deltas (Jago: JAG; 

Okpilak/Hulahula: OKP; Canning: CAN) during 2011 and 2013 sampling regimes across two sampling 

periods. Error bars represent standard errors.
40

Evaluation of accessory pigments yielded a strong fucoxanthin signal reaching 92.96 mg m-2

with a steady signal throughout each delta at each sampling period. This result illustrates an 

established diatom community throughout each delta (Figure 5.2). Average sediment 

concentration of zeaxanthin from the Jago River delta during the second sampling period of 2011

reached 9.22 mg m-2 but never reached > 2.74 mg m-2 in any other delta at any other period of 

sampling. This signal could be indicative of decaying plant matter, cyanobacteria, or chlorophyte 

presence. However, the signal is very slight and not common throughout the sampling periods of 

any other delta. All other targeted pigments were found at very low concentrations ( x < 5 mg m2

) and sporadically throughout sampling periods in different deltas without trend. However, the 

presence of the strong diatom signal suggests an autogenous source of primary productivity 

during the summer months which is in congruence with our chl a findings. We confirmed the 

presence of a rich diatom community via light microscopy following a ludox extraction and 

centrifugation of additional sediment samples following HPLC results. The community consisted 

of large (> 40 μm) naviculoid diatoms with high concentrations of lipids providing a nutrient rich 

food source for primary consumers.

Figure 5.2. Average chlorophyll a concentrations from three Arctic river deltas (Jago: JAG; 

Okpilak/Hulahula: OKP; Canning: CAN) during 2011 and 2013 sampling regimes across two sampling 

periods. Error bars represent standard errors. 
41

Total pheopigment concentrations combining pheophytin a, pheophorbide a, and 

pyropheophorbide a signals from each delta in early August 2013, and from the Jago River delta 

in 2013, were relatively high for pheopigments ranging up to 113.00 mg m-2. In the early 

sampling period (3–8 August) average chl a : total pheopigment concentrations were < 1 in each 

of the deltas, although late season Jago sampling showed the opposite trend (Figure 5.3). This 

indicates that bacterial cleaving and metazoan grazing have led to a higher concentration of chl a

breakdown products than live, intact chl a compounds in these deltas. Each of the degradation 

products was analyzed individually across each delta, and there was no statistical difference 

between concentrations of the bacterial breakdown product pheophytin a and metazoan 

breakdown products pheophorbide a and pyropheophorbide a in any delta (Figure 5.4). Overall, 

the pigment analyses from all three deltas reveal the strong presence of chl a. This is indicative 

of a healthy microphytobenthic community consisting mostly of diatoms identified by consistent 

signals of fucoxanthin across deltas and sample periods. However, chl a:total pheopigment ratios 

< 1 and high pheopigment concentrations show that bacterial and metazoan populations are 

dependent on microphytobenthic availability. Clearly, nitrogen is not a limiting resource for 

these benthic microalgal populations based on the high levels of porewater ammonium measured 

in the sediments (see porewater section). 

Sedimentary total organic carbon ranged from 1.52–5.21% indicative of active carbon fixation 

via microphytobenthic photosynthesis across the three Arctic river deltas as expected from the 

strong chl a concentrations previously reported above. There was no significant difference in 

TOC (%) between sampling periods in any delta (Figure 5.5) which can be attributed to the 

widespread deposition of terrestrial organic matter from local sources and consistent 

photosynthetic fixation by microphytobenthos during each period. Curiously, Canning River

delta sedimentary TOC (%) were significantly greater than Jago or Okpilak/Hulahula deltas 

(Figure 5.5) even though Canning had the lowest chl a concentrations and lowest chl a:total 

pheopigments ratios (Figure 5.3). This observation may simply reflect the overarching 

importance of terrestrial materials in the sediments, which was confirmed isotopically (see next 

section). Nonetheless, the photosynthetically active microphytobenthos does contribute 

substantially to in situ primary production but also acts as a source of nutrients for the microbial 

heterotrophs as illustrated by the high signals of pheopigments.
42

Figure 5.3. Average chlorophyll a:total pheopigment concentrations from three Arctic river deltas (Jago: 

JAG; Okpilak/Hulahula: OKP; Canning: CAN) during 2013 sampling regimes. Error bars represent 

standard errors. Numbers above bars are calculated ratio of chlorophyll a:total pheopigments. 

Figure 5.4. Average pheopigment concentrations from three Arctic river deltas (Jago: JAG; 

Okpilak/Hulahula: OKP; Canning: CAN) during 2013 sampling regimes across two sampling periods. 

Error bars represent standard errors.
43

Figure 5.5. Average total organic carbon concentrations from three Arctic river deltas (Jago: JAG; 

Okpilak/Hulahula: OKP; Canning: CAN) during 2011 and 2013 sampling regimes across two sampling 

periods. Error bars represent standard errors.

5.4.2 Isotope and C:N Analysis

Stable isotopic composition of organic matter in sediments reflected strong terrestrial 

contributions based on δ13C and δ15N values ranging from -27‰ to -24‰ and 1‰ to 3.5‰ 

respectively (Dunton et al. 2012). These were well constrained throughout sampling (Table 5.1; 

Figures 5.6 and 5.7). There were no significant differences within or between deltas during all

sampling periods. In addition C:N ratios averaging 4 to 10:1 are indicative of terrestrial 

signatures within sediments as well as high lipid content (Post et al. 2007). Mean of C:N ratios 

were > 9:1 across all deltas and sampling periods. These data show significant influences of 

terrestrial matter in sediments of these three Arctic river deltas as well as high lipid content from 

the terrestrial matter. High lipid content in the sediments is most likely a product of the lipid-rich 

diatom community observed microscopically and quantified in the high fucoxanthin 

concentrations from pigment analysis.
44

Figure 5.6. Isotopic δ13C and δ15N values for sediment samples from three Arctic river deltas (JOHC) 

during 2011 sampling periods. 

Figure 5.7: Isotopic δ13C and δ15N values for sediment samples from three Arctic river deltas (JOHC) 

during 2013 sampling periods.
45

5.4.3 Porewater Salinity and NH4

+

Sediment porewater salinities ranged from 0 – 42 across the three deltas. However, average 

salinities in all three deltas were relatively low for estuarine habitats (< 12; Table 5.1). These 

values reflect brackish water conditions which are a product of the large amounts of freshwater 

inflow into the deltas from rivers, even during periods of lower flow following the June freshet.

Concentrations of sediment NH4

+ reached as high as 417.62 μmol L-1 but averages across three 

deltas never rose above 203.42 μmol L-1 (Figure 5.8). Ammonium is a reduced nitrogen species 

and although normally present in concentrations within the range reported here, the compound is 

usually associated with active aerobic organic matter decomposition, or in deeper soils, processes 

of nitrate or sulfate reduction in the presence of organic matter (Fenchel and Riedl 1970). Mean 

concentrations of NH4

+ were highest in the Jago River delta during 2011 (Figure 5.8) which 

correlates with the low TOC (%) as a result of carbon remineralization. The Jago also possessed 

the highest concentrations of chl a that we can attribute to the high NH4

+ concentrations found in 

these sediments that would support appreciable algal biomass. Interestingly, terrestrial organic 

matter may be more important as a substrate for bacterial production of inorganic-N for benthic 

microalgae than as a carbon source for sediment consumers such as amphipods, polychaetes, and 

small molluscs. 

Figure 5.8. Average sediment ammonium concentrations from three Arctic river deltas (Jago: JAG; 

Okpilak/Hulahula: OKP; Canning: CAN) during 2011 and 2013 sampling regimes across two sampling 

periods. Error bars represent standard errors.
46

5.5 References

Craig PC, Griffen WB, Johnson SR, Schell D. 1984. Trophic dynamics in an arctic lagoon. In 

The Alaskan Beaufort Sea-a review. Transactions of the American Fisheries Society. 113: 

265-282. 

Dunton KH, Schonberg SV, Cooper LW. 2012. Food web structure of the Alaskan nearshore 

shelf and estuarine lagoons of the Beaufort Sea. Estuaries and Coasts. 35:416-435. 

Fenchel TM, Riedl JR. 1970. The sulfide system: A new biotic community under the oxidized 

layer of marine sandy bottoms. Marine Biology. 7:255-268

Glud RN, Woelfel J, Karsten U, Kuhl M, Rysgaard S. 2009. Benthic microalgal production in 

the Arctic: applied methods and status of the current database. Botanica Marina. 52:559-571. 

Kazlowski S, Stewart M. 2006. Arctic wings: birds of the Arctic National Wildlife Refuge.

Brown S, editor. Seattle (WA): Mountaineers Books. 

McTigue ND, Bucolo P, Liu Z, Dunton KH. 2015. Pelagic-benthic coupling, food webs, and 

organic matter degradation in the Chukchi Sea: insights from sedimentary pigments and 

stable carbon isotopes. Limnology and Oceanography. 60:429-445. 

McTigue ND, Dunton KH. 2014. Trophodynamics and organic matter assimilation pathways in 

the northeast Chukchi Sea, Alaska. Deep-Sea Research. 102:84-96. 

Parsons TR, Maita Y, Lalli CM. 1984. A manual of chemical and biological methods for 

seawater analysis. Oxford: Pergamon Press.

Post DM, Layman CA, Arrington DA, Takimoto G, Quattrochi J, Montana CG. 2007. Getting to 

the fat of the matter: models, methods, and assumptions for dealing with lipids in stable 

isotope analysis. Oecologia. 152:179-189. 

Underwood GJC, Kromkamp J. 1999. Primary production by phytoplankton and 

microphytobenthos in estuaries. Advances in Ecological Research. 29:93-153. 
47

6. Environmental Variables and Sediment Macroinvertebrates

Roy Churchwell, University of Alaska Fairbanks

Abby Powell, U S Geological Survey, Alaska Cooperative Fish and Wildlife 

Research Unit

Ken Dunton, The University of Texas Marine Science Institute

6.1 Introduction

Tens of thousands of shorebirds use Alaska’s Beaufort Sea coastal river deltas as stopover sites 

and as first stops on their fall migration to forage on invertebrates and deposit fat stores to fuel 

their long-distance flights (Taylor et al. 2010; Brown et al. 2012; Churchwell 2015). There is a 

paucity of information on the macroinvertebrate community inhabiting these intertidal habitats or 

the physical and chemical characteristics of deltaic sediments. In fact, these deltas have been 

reported as uninhabited by benthic macroinvertebrates (Crane 1974; Feder and Schamel 1976; 

Gutt 2001), despite the fact that shorebirds have been observed foraging there. However, few 

unpublished reports describe persistent intertidal macroinvertebrate communities (Connors and 

Risebrough 1977; Andres 1989). 

Our first objective was to identify the macroinvertebrate taxa at the JOHC deltas. Second, we 

examined within-year variability of invertebrate abundance during three time periods

corresponding to shorebird migration. Because invertebrate abundance is partially determined by 

the environmental factors, we modeled the association between abundance and environmental 

variables while accounting for spatial and temporal effects. Specifically, we predicted that 

invertebrate abundance would show a positive relationship with the proportion of fine sediment 

and soil moisture. Glaciers are a major source of fine sediments in some of these river deltas, but 

they are expected to disappear in the future, which may ultimately change the characteristics of 

mudflats (Nolan et al. 2011).

Finally, we used stable isotope comparisons to determine whether intertidal invertebrates were 

freshwater- or marine-carbon based, and to describe trophic structure of shorebird food webs. 

Stable nitrogen (δ15N) and carbon (δ13C) isotopes quantify trophic level and forage dynamics, 

respectively. Nitrogen isotope values increase about 3.4‰ through fractionation with each step 

up in trophic level, and thus can estimate relative placement of taxa within a food web (Fry 2006; 

Dunton et al. 2012). Carbon isotopic values distinguish marine from terrestrial sources based on 
48

photosynthetic processes and carbon assimilation through the food chain (Fry 2006). There is a 

significant east-west gradient in carbon isotopic values of sediments from the Mackenzie River 

westward along the Beaufort Sea coast, owing to the large input of terrestrial organic carbon 

from the Mackenzie and the advection of marine carbon from the Chukchi Sea on the west 

(Dunton et al. 2006). Within lagoons, isotopic signatures of amphipods become more terrestrial 

with proximity to freshwater inputs and drainages (Craig et al. 1984). We hypothesized that 

freshwater invertebrate taxa collected on deltaic mudflats would have a terrestrial isotopic 

signature while marine taxa would have a marine signature, and that there may be a gradient 

from marine to terrestrial from the lagoon to the high water mark on a mudflat.

6.2 Methods

We collected invertebrate data in July and August 2010 and 2011 on the JOHC deltas. One

sample was collected from a random location within 250 m2 grid cells, which covered all 

available shorebird foraging habitat at each site (Figure 6.1). We collected samples across the 

grids at each delta during three sessions representing fall migration of shorebirds: early (21 July–

1 August), mid- (1–8 August), and late season (10–22 August). Sampling occurred in areas 

accessible to feeding shorebirds: water depths ≤ 5 cm and up to the tundra edge of the delta 

mudflat. At each sampling location, we collected an invertebrate core and a sediment core, and 

recorded water depth to the nearest cm. The invertebrate core was collected with a piece of PVC 

pipe (1/100 m2) pushed in the sediment to 5-cm depth (volume = 501.2 cm3). We sifted the core 

through a 500-μm sieve and stored the macroinvertebrates and residual sediment in a plastic jar 

with 70% alcohol for preservation. The sediment core was obtained using a 50-cc syringe barrel 

and analyzed later for grain size, moisture, and carbon/nitrogen. The syringe plunger was pushed 

in the sediment 5 cm (volume = 24.5 cm3), and the sample was stored in a Whirl-pac® and 

frozen as soon as possible. All samples were shipped back to the University of Alaska Fairbanks 

for analysis.

We sorted invertebrate samples by taxa to the family level when possible. We identified samples 

to a higher taxonomic level than family when individuals were difficult to identify and required
49

Figure 6.1. Grid used for sampling sediment characteristics and macroinvetrebrates on the Jago River 

Delta.

an expert in the taxon. Nematoda were not counted in 2010 because they are not considered a 

shorebird food, but were quantified in 2011. We counted individuals in the invertebrate core and

extrapolated this to m2 (± S.E.) to obtain a density estimate. The percent occurrence estimate was 

calculated as the number of cores where the taxon was present divided by the total number of 

cores for that sampling session x 100. 

We weighed and dried at 65°C sediment cores for 48 h to a constant weight to determine percent 

moisture by weight. We also subsampled two 0.1-g samples that were analyzed using a TruSpec 

Carbon/Nitrogen Determinator® to calculate percentage by weight for total carbon and nitrogen. 

The remaining sample was used to determine grain size. In 2010, sediment samples were

weighed and suspended in water using a mixer; then the sand was allowed to settle for 40 sec. 

Then the solution containing the silt and clay portion was decanted leaving the sand, which was 
50

sifted using a 46-μm sieve to make sure all of the silt and clay were removed. After drying once 

more, the sample was weighed a final time to determine percent sand. We used the percentage 

silt/clay determined by 100 - sand. In 2011, after the subsamples for carbon and nitrogen were 

taken, the remaining sample was suspended in 100 ml of 70% hydrogen peroxide (H2O2) for 48 h 

to remove any organic material. The silt/clay portion was removed using a 63-μm sieve. Both the 

sand and silt/clay portions were dried to constant mass. 

We also determined stable isotopic (13C and 15N) values for macroinvertebrate samples collected 

on the delta and nearby terrestrial tundra ponds. Samples of the dominant taxa were collected 

throughout the season as time allowed from areas where they were present during past sampling 

using a core and sieve, and then were frozen as soon as possible. Soft-bodied taxa were dried at 

65°C for 48 h to a constant weight, and then the sample was homogenized and weighed into 

aluminum capsules. Taxa with a calcified exoskeleton were immersed in 2 M HCL for 24 h, 

rinsed in deionized water, and dried at 65°C for 48 h until constant weight was achieved; the 

sample was homogenized and weighed into aluminum capsules. Samples were analyzed at the 

Alaska Stable Isotope Facility (University of Alaska Fairbanks) using continuous flow stable 

isotope-ratio mass spectrometry in a Costech ECS4010 Elemental Analyzer (Costech Scientific, 

Valencia, CA) and Finnigan Delta Plus XP isotope ratio mass spectrometer through the Conflo 

III interface (Thermo-Finnigan, Bremen, Germany). We report our results in delta (δ) notation ‰ 

relative to the international standard (13C = Viennna PeeDee Belemnite; 15N = atmospheric 

nitrogen) using the equation: δ13C = [Rsample/Rstandard) – 1] x 1,000 with R representing the ratio of 

13C/12C or 15N/14N. Laboratory standards (peptone) were run with samples, and using the 

standard deviation of replicate measurements the analytical error was estimated to be < ±0.2%. 

6.2.1 Species Diversity, Distribution, and Statistical Analyses

We calculated diversity indices using data from 2011 to compare the invertebrate communities 

among the three study deltas using both Simpson’s and Shannon’s log base 10 diversity indices 

and evenness (Krebs 1989). Data from 2011 were selected because we had better detection of 

rare species that year. We are uncertain if the low number of rare species in 2010 was due to 

observer bias or a lack of rare species. We used both diversity indices because the Simpson’s 

Index reduces bias of rare species, while Shannon’s Index reduces bias of abundant species, but 
51

both indices increase with the number of species detected (Krebs 1989). We made identifications 

to different taxonomic levels, but most to the family level, and so we have to assume each taxon 

that we made identifications to at our sites has only one family, because it is the lowest 

taxonomic level of the analysis. 

We developed models using the statistical program R version 2.15.2 (R Development Core Team 

2013) to evaluate the effect of site, year, session, and environmental factors on invertebrate 

abundance. We created linear mixed-effects (random and fixed effects) restricted maximum 

likelihood (REML) models using the R library lmerTest (Kuznetsova et al. 2013) and used 

stepwise model selection using backwards elimination of non-significant factors that were then 

further evaluated for fit. The dependent variable was invertebrate abundance of Chironomidae 

and Oligochaeta modeled respectively, which were the only two taxa with a significant sample 

size for this analysis. Chironomidae were only modeled for the Jago and Okpilak/Hulahula deltas 

because they were not present at the Canning. Modeled random effects included year, session, 

and delta, as well as interactions between these three variables. Modeled fixed effects included 

delta; spatial variables latitude and longitude from sample locations; and continuous variables for 

nitrogen, carbon, water depth, moisture, and percent silt/clay from sample locations. We started 

with a full model containing the interaction ‘delta x longitude x water depth x moisture x 

silt/clay’ and the other variables as non-interactive terms, based on past experience from 

modeling invertebrate populations in benthic habitats. We tested model and variable diagnostics 

using the variance inflation factor in the R library car (Fox et al. 2013) and Q-Q plots and 

residual plots in the lme4 library (Bates et al. 2013). Significance was set at α = 0.05.

To determine invertebrate distribution, we used kriging with the R library geoR (Ribeiro and 

Diggle 2013). Kriging is a geostatistical technique that uses the spatial variance between pairs of 

sample points to model the predicted values from each sample location, which is then 

extrapolated across the study area (Fortin and Dale 2005). We created variograms using an 

exponential model, fit the model, and projected the model as a predictive map. 

In order to calculate the spatial extent of invertebrate patches, with used Moran’s I with R library 

spatial (Ripley 2013) for each year, sample session, and major taxa combination. Moran’s I is a 
52

spatial parameter that describes the spatial autocorrelation of a dataset by distance class (Fortin 

and Dale 2005). Moran’s I can also be used to interpret patch size as a linear distance across the 

patch.

Finally, we used MANOVA in R to test for differences between isotopic values of invertebrates 

collected in delta (marine) and tundra pond (terrestrial) habitats from three ponds in tundra 

habitat < 2 km from the Jago River Delta. We calculated trophic level for invertebrates using a 

fractionation coefficient of 3.4‰ (Dunton et al. 2012), and the equation: TL(POM) = δ15NConsumer

- δ15NPOM/ 3.4 + 1 (Iken et al. 2010). The variable TL = trophic level and POM = particulate 

organic matter, which is the base measurement for δ15N in the food chain.

6.3 Results

6.3.1 Taxa and Occurrence

We collected samples at 247, 525, and 487 sites over two years on the Canning, 

Okpilak/Hulahula, and Jago deltas respectively. Salinity and water temperature were similar at 

the Jago and Okpilak/Hulahula Delta (Figure 6.2), and most values were near zero with patches

of saline water near gaps in the barrier islands. The Canning Delta had higher salinity values and 

lower temperatures (Figure 6.2) because of the proximity of this delta to an outlet to the ocean. 

Overall, we collected 18 taxa: 11 freshwater, 3 marine, 3 terrestrial, and 1 taxon that inhabits all 

habitats (Table 6.1). Indices of diversity and evenness were highest at the Jago Delta and lowest 

at the Canning Delta (Figure 6.3). 

Six taxa regularly occurred in our samples: Oligochaeta, Chironomidae, Tipulidae, Amphipoda, 

Chaetiliidae, and Spionidae (Table 6.2, Figure 6.4), but these taxa were not found at all sites. 

Chironomidae larvae were never observed at the Canning Delta (although a few adults were 

present) despite the fact that they were sometimes the most common taxa at other deltas. 

Likewise, Tipulidae larvae were only found on one occasion at the Canning Delta, but were 

common at the other two deltas. In contrast, Spionidae were common at the Canning Delta but 

uncommon at the Okpilak/Hulahula Delta and never found at the Jago Delta. Overall, marine 
53

Table 6.1. Taxonomic list of invertebrates sampled at Beaufort Sea river deltas (JOHC), 2010 – 2011. 

Taxa are underlined at the level at which we conducted the analysis. Superscript F = freshwater taxa, S= 

saltwater taxa, B = commonly found in both salt and freshwater, and T = terrestrial taxa. 

Phylum Class Order Family Genus Species

NematodaB

Annelida

Clitellata

OligochaetaF

Polychaeta

Canalipalpata

SpionidaeS

Spio% filicornis

Arthropoda

Maxillipoda

CopepodaF

Malacostraca

AmphipodaS

Lysianassidae

Orchomene

Pontoporeiidae

Pontoporeia% femorata

Isopoda

ChaetiliidaeS

Saduria entomon

Arachnida

AraneaeT

Trombidiformes

HydrachnidiaeF

Entognatha

CollembolaF

Insecta

HymenopteraT

Hemiptera

CicadellidaeT

Plecoptera

CapniidaeT

Diptera

ChironomidaeF

Diplocladius

Chironomus
54

TipulidaeF

Ormosia

CulicidaeF

EmpididaeF

EphydridaeF

CeratopugonidaeF
55

Figure 6.2. Mean salinity and temperature for each Beaufort Sea river delta (JOHC), 2010 – 2011. The 

box represents the first and third quartile, the whiskers represent one standard deviation, and the dots are 

outliers.

Figure 6.3. Shannon and Simpson’s diversity indices and evenness for taxa sampled on Beaufort Sea 

river deltas (JOHC) 2011. Individuals were identified to the family level or assumed to contain one family 

if identified at a higher taxonomic level.
56

Figure 6.4. Percent occurrence of macroinvertebrates sampled at Beaufort Sea river deltas (JOHC) in 2010 and 2011.
57

invertebrates were more prominent at the Canning Delta compared to the other two deltas where 

freshwater invertebrates dominated. Variation in invertebrate occurrence within deltas was 

similar between years (Table 6.2, Figure 6.4). The Canning tended to have fewer invertebrates 

during early and mid-season sessions, but invertebrate occurrence, especially for marine 

invertebrates, increased in the late session.

6.4.2 Invertebrate Abundance and Distribution

We determined invertebrate abundance at all three deltas for each year and sampling session 

(Table 6.3). Environmental variables were sampled for each invertebrate sample location at each 

delta (Figures 6.5 and 6.6). In summary, the Jago and Okpilak/Hulahula deltas had similar 

sediment environmental characteristics, but the Canning Delta had four times higher salinity and 

carbon values and tended to be cooler and drier on average than the other two sites. 

Chironomidae and Oligochaeta were the only two taxa common enough to make visual 

comparisons across years and sessions and to model abundance (Table 6.4a and b). There was a 

significant interaction between the random temporal variables year and session for both 

Chironomidae (P < 0.05; Table 6.4a) and Oligochaeta (P = 0.04; Table 6.4b). In the 

Chironomidae regression model the spatial variable Latitude was significant with a positive 

effect (P < 0.001), but spatial variables were not significant in the Oligochaeta model. The fixed 

environmental variables related to resources (total carbon and nitrogen) were not significant 

model predictors for either Chironomidae or Oligochaeta abundance. However, environmental 

variable interactions for moisture were significantly positive (delta:moisture P = 0.003; 

silt:moisture P = 0.011) for Chironomidae, but negative (delta:moisture P < 0.001) for 

Oligochaeta (Tables 6.4a and b).

Spatial maps demonstrated consistent distribution but varying abundance patterns across the 

spatial domain, which we were able to relate to invertebrate life history. Kriged maps of all 

invertebrates combined indicate invertebrate distributions were generally similar among years 

with core patches found on the edges and middle of the Jago Delta, but abundance within patches 

varied (Figure 6.5). We saw similar consistency in patches at the other deltas, but were limited in 

our ability to present all of the data. The kriged abundances for some taxa were quite variable 
58

Table 6.2. The percentage that each taxa contributed to invertebrate occurrence for each river delta and 

season on the Beaufort Sea coast. Percentage is the number of cores where taxon was present divided 

by total cores collected for that period x 100. Nematodes were only quantified in 2011. Species in the 

Other category include those species that only occurred once within a season and delta, including 

Capniidae, Cicadellidae, Arachnida, Copepoda, Empididae, Ephydridae, Hydrachnidia, and 

Hymenoptera. The “**” represents no detection of a taxa.

Canning!2010 Canning!2011

Early!

Season

Mid!

Season Late!Season Early!Season Mid!Season

Late!Season

Amphipoda 4.4 4.6 26.3   18.1

Chaetiliidae 4.4 **  5.0 **  

Chironomidae 4.4 4.6 **  3.7 ** 1.4

Culicidae   **  3.7 ** **

Oligochaeta 13.0 4.6 27.5 7.4 34.2 34.7

Spionidae   11.2 **  4.9 8.3

Tipulidae **   **  ** 1.4

Other   **  7.4 ** 1.4

No!Invertebrates 73.9 86.4 30.0 77.8 61.0 33.3

Jago!2010 Jago!2011

Amphipoda 3.3 5.2 6.5 2.3 3.0 10.5

Chaetiliidae 1.1 1.7 1.1   2.2

Chironomidae 30.0 24.1 33.7 19.3 24.0 23.9

Culicidae 2.2 3.5 **  ** 1.0 **

Nematoda   **  2.3 5.0 4.5

Oligochaeta 14.4 10.3 21.7 25.0 19.0 16.4

Tipulidae 21.1 20.7 17.4 15.9 12.0 10.5

Other ** ** 1.1 2.3 2.0 1.5

No!Invertebrates 27.8 34.5 18.5 33.0 34.0 30.6

Okpilak/Hulahula!2010 Okpilak/Hulahula!2011

Amphipoda 3.2   1.3 2.4 3.6

Chaetiliidae 5.4 **  5.3 ** 0.8 1.2

Chironomidae 39.8 37.2 42.7 30.3 30.4 23.8

Culicidae 1.1   **  ** **

Nematoda   **  1.3 5.6 10.1

Oligochaeta 8.6 7.0 13.3 23.7 22.4 25.0

Spionidae **   **  ** 1.8

Tipulidae 4.3 9.3 13.3 7.9 3.2 6.6

Other 1.1   2.6 4.8 1.2

No!Invertebrates 36.6 46.5 25.3 32.9 30.4 26.8
59

Table 6.3. Abundance estimates (mean ± S.E.) of macroinvertebrate taxa from the Canning, Jago, and Okpilak/Hulahula river deltas. 

Measurements are abundance m-2. The “** ” represents no detection of a taxa. 

Canning!2010 Canning!2011

Early!Season Mid!Season Late!Season Early!Season Mid!Season Late!Season

Amphipoda 8.7!±!8.7 4.6!±!4.6 172.5!±!59.1 ** ** 158.9!±!85.8

Chaetiliidae 4.4!±!4.4 ** 5.0!±!5.0   ** 

Chironomidae 4.4!±!4.4 ** 10.0!±!10.0 3.7!±!3.7 ** 3.6!±!3.6

Collembola   **  7.4!±!7.4 ** **

Culicidae   **  3.7!±!3.7 ** **

Ephydridae   **  ** ** 1.8!±!1.8

Nematoda   **  ** ** 3.6!±!3.6

Oligochaeta 69.6!±!56.7 9.1!±!9.1 490.0!±!139.8 55.6!±!48.4 943.6!±!293.6 876.8!±!294.4

Spionidae   52.5!±!22.3 **  5.1!±!3.6 28.6!±!15.7

Tipulidae **   **  ** 1.8!±!1.8

Jago!2010 Jago!2011

Amphipoda 4.3!±!2.6 31.7!±!24.2 28.6!±!22.1 2.9!±!2.0 3.8!±!2.2 69.5!±!31.5

Arachnida   **  ** 1.3!±!1.3 **

Capniidae   **  1.5!±!1.5 ** 1.1!±!1.1

Chaetiliidae 1.1!±!1.1 1.7!±!1.7 1.1!±!1.1   3.2!±!1.8

Chironomidae 235.5!±!68.7 185.0!±!70.9 575.8!±!123.5 108.7!±!36.9 496.2!±!141.8 539.0!±!118.5

Cicadellidae **  ** 1.1!±!1.1   ** 

Collembola **   1.5!±!1.5 **  1.1!±!1.1

Copepoda **   **  ** 1.1!±!1.1

Culicidae 2.2!±!1.5 3.3!±!2.3   1.3!±!1.3 ** 

Ephydridae **   **  1.3!±!1.3 **

Nematoda   **  2.9!±!2.9 21.5!±!12.7 10.5!±!4.6

Oligochaeta 211.8!±!100.4 15.0!±!7.5 205.5!±!62.8 349.3!±!132.6 311.4!±!203.8 543.2!±!206.9

Tipulidae 36.6!±!9.6 56.7!±!22.1 51.7!±!15.2 40.6!±!12.4 40.5!±!15.0 72.6!±!26.8
60

Okpilak/Hulahula!2010 Okpilak/Hulahula!2011

Amphipoda 8.7!±!6.7 ** ** 1.7 ±!1.7 4.1!±!2.5 17.3!±!11.0

Capniidae 1.1!±!1.1   **  2.1!±!2.1

Chaetiliidae 6.5!±!3.0 ** 5.3!±!2.6 ** 1.0!±!1.0 2.4!±!1.8

Chironomidae 226.1!±!70.3 143.2!±!60.1 228.0!±!56.1 198.3!±!80.7 217.5!±!49.0 178.7!±!42.1

Collembola   **  3.5!±!3.5 1.0!±!1.0 1.6!±!1.6

Copepoda **   **  3.1!±!3.1 0.8!±!0.8

Culicidae 1.1!±!1.1 **   **  **

Empididae   **  ** 1.0!±!1.0 **

Hydrachnidia   **  ** 1.0!±!1.0 **

Hymenoptera   **  1.7!±!1.7 1.0!±!1.0 **

Nematode   **  1.7!±!1.7 59.8!±!34.3 68.5!±!29.3

Oligochaeta 130.4 ±!85.6 161.4!±!115.8 109.3!±!57.8 613.8!±!224.1 857.7!±!245.0 1339.4!±!305.7

Spionidae **   **  ** 7.1!±!5.6

Tipulidae 5.4!±!2.8 25.0!±!13.5 17.3!±!5.5 31.0!±!21.0 10.3!±!6.6 32.3!±!20.1
61

Table 6.4. Effects of environmental factors on Chironomidae abundance (a) and Oligochaeta abundance 

(b) on Beaufort Sea river deltas based on a linear model in which we found a significant interaction 

between the random temporal variables year and session for both Chironomidae (p < 0.05) and 

Oligochaeta (p = 0.04). All variables for the best model are shown and only significant random variables 

are reported. Significance of fixed factors was used in a stepwise model selection using backwards 

elimination of non-significant factors.

a.

Random!Factors Fixed!Factors

Variable Variance S.D. Variable Estimate S.E. t7value p7value

Year:Session 0.00 0.06 Intercept 7629.60 128.40 74.91 0.000

Residual 0.18 0.42 Latitude 8.99 1.83 4.91 0.000

Delta 71.09 0.22 74.95 0.000

Moisture 70.01 0.01 71.32 0.188

Silt/clay 70.01 0.01 72.38 0.018

Delta:Moisture 0.03 0.01 2.96 0.003

Moisture:Silt/clay 0.00 0.00 2.56 0.011

Random!Factors Fixed!Factors

Variable Variance S.D. Variable Estimate S.E. t7value p7value

Year:Session 0.01 0.07 Intercept 70.77 0.27 72.88 0.004

Residual 0.26 0.51 Delta 0.44 0.12 3.74 0.000

Moisture 0.06 0.01 4.52 0.000

Delta:Moisture 70.02 0.01 74.39 0.000
62

Table 6.5. Carbon and nitrogen isotopic values for benthic macroinvertebrates (mean ± SE) and the C:N 

ratio for corresponding samples collected from Beaufort Sea river deltas and three tundra ponds < 2 km 

from the Jago Delta, 2010–2011.

N δ15N!(‰!±!SE) δ13C!(‰!±!SE) C:N!(Moles/mole!±!SE)

Delta

Amphipoda 5 4.5!±!0.3 A22.0!±!0.7 5.6!±!0.2

Chironomidae 2 3.0!±!0.5 A22.3!±!1.6 5.8!±!0.4

Culicidae 1 3.3 A31.3 4.1

Oligochaeta 1 5.2 A22.0 5.3

Saduria 2 6.6!±!2.0 A19.8!±!0.7 4.8!±!0.1

Spionidae 2 5.1!±!0.0 A24.2!±!0.4 5.9!±!0.0

Tipulidae 6 1.3!±!0.4 A23.7!±!0.1 5.8!±!0.2

Tundra!Ponds

Anostraca 2 1.4!±!0.0 A36.2!±!0.6 4.1!±!0.1

Chironomidae 6 1.7!±!0.3 A31.6!±!0.9 4.8!±!0.1

Cladocera 1 0.2 A34.6 5.1

Coleoptera 3 2.6!±!0.4 A31.8!± 1.9 4.7!±!0.4

Oligochaeta 5 0.7!±!0.2 A31.7!±!0.9 4.7!±!0.1

Ostracoda 1 0.8 A34.4 5.1

Plecoptera 1 1.1 A35.4 4.8

Figure 6.5. Predicted distribution of all invertebrate taxa combined during late-season sampling at the 

Jago River Delta 2010 – 2011.
63

Figure 6.6. Predicted distribution of invertebrate taxa through three sampling sessions (early = 21 July – 1 

August, mid = 1 – 8 August, late = 10 – 22 August) at the Jago River Delta 2011. The area of the delta 

changes during the mid-season due to lower water levels during that session. 
64

Figure 6.7. Sediment grain size with respect to the silt/clay fraction (bottom left panel), soil moisture, and 

C:N data from Beaufort Sea river deltas, 2010-2011. The unquantified portion of the sample is sand. The 

proportion of clay or silt in the combined silt/clay fraction by weight fraction for each delta sediment 

sample is included (bottom right panel).
65

!

within the delta and among survey session, with abundances increasing later in the season 

(Figure 6.6). Seasonally, patches of Tipulidae larvae expanded from terrestrial tundra origins as 

summer progressed, while patches of Chironomidae larvae expanded from east to west. In 

contrast, Oligochaeta were consistently found in the same patches throughout the season.

Moran’s I estimates of patch size for all invertebrates combined and individual taxa were 400 –

600 m. Almost all estimates were ≈ 400 m except there were a few estimates of ≈ 600 m 

measured for the Okpilak/Hulahula.

6.3.3 Stable Isotopes

With just one exception (noted below), freshwater and marine taxa collected on Beaufort Sea 

river deltas had average δ13C values ranging from -19.8 to -24.2‰, compared to organisms 

collected on tundra ponds on the Jago Delta that had more depleted mean δ13C signatures ranging 

from -31.7 to -36.2‰. Most invertebrate consumers were characterized as either dependent on 

terrestrial organic carbon as defined by isotopic values less than about -28‰ or mainly by 

autochthonous sources of carbon as denoted by values greater than -24‰ (Figure 6.8, Table 6.5). 

There was a significant difference in the δ13C and δ15N isotopic signature between delta and 

terrestrial samples (P < 0.001). The one exception were the Culicidaea; although they were 

collected on the delta, they had a strong terrestrial signature (δ13C -31.0‰). We suspect that 

these organisms had likely just hatched and migrated from nearby tundra ponds to the delta. The 

mean nitrogen isotopic signature for delta invertebrates ranged from δ15N 1.3 to 6.6‰, and based 

on a trophic step fractionation of 3.4‰, delta consumers likely fall within two trophic levels, 

assuming that the δ15N values for ultimate carbon sources on the deltas fall between 0 and 3‰ 

(Dunton et al 2012; Figure 6.8). Based on δ15N values of 4.7‰ and 8.7‰, Saduria was the only 

taxon that spanned multiple trophic levels, which reflects the opportunistic feeding behavior of 

this invertebrate. 
66

Figure 6.8. Stable isotopic values (δ15N and δ13C) of the major invertebrate taxa found on Beaufort Sea 

river deltas. Separate circles encompass all of the samples collected on the delta and within tundra ponds 

except for Culicidae, which were collected on the delta as adults that we believe had just migrated from 

nearby tundra ponds as reflected in their depleted δ13C values. The four larger circles and squares are 

isotopic values of suspended particulate organic matter (SPOM) and benthic particulate organic matter 

(BPOM) from the lagoons and rivers (estimates from Dunton et al. 2012) that we hypothesized would be 

the base food source for delta invertebrates.

0.00 

1.00 

2.00 

3.00 

4.00 

5.00 

6.00 

7.00 

8.00 

9.00 

10.00 

-38.00 -33.00 -28.00 -23.00 -18.00 

δ15N 

δ13C 

Amphipod 

Chironomid 

Culicid 

Oligiocheate 

Saduria 

Spionid 

Tipulid 

Lagoon BPOM 

Lagoon SPOM 

River BPOM 

River SPOM 

Anostraca 

Cladoceran 

Coleoptera 

Ostracoda 

Plecoptera 
67

6.4 Discussion

6.4.1 Taxa and Occurrence

The fauna of the Beaufort Sea river deltas (70°N) are comparably more depauperate than the 

faunal communities of river deltas at more boreal latitudes (Lees et al. 1979; Lees et al. 1980; 

Powers et al. 2002). Taxa found at coastal sites of the Gulf of Alaska in southcentral Alaska 

(Copper River Delta, Port Valdez, and Cook Inlet at ~60°N) included Amphipoda, 

Chironomidae, and Polychaeta, but at most sites the dominant group was Macoma in the family 

Tellinidae (Lees et al. 1979; Lees et al. 1980; Powers et al. 2002). Although we did not find adult 

bivalves at our study sites, we found bivalve larva in a few locations (Baguley, unpublished 

data). Macoma and other bivalves were found in a nearby lagoon at 4.5-m depth providing a 

source population for young-of-the-year bivalves found on the mudflats (Dunton et al. 2012). In 

high Arctic regions, ice drove community dynamics of intertidal areas including Spitsbergen 

(near 78°N) where all marine benthic invertebrates except Nematoda disappeared each winter 

(Weslawski and Szymelfenig 1999) and in the Canadian high Arctic (65°N-70°N), which had 

reduced or no macroinvertebrate benthic community in solid ice zones (Dale et al. 1989). 

Previous studies have attributed the absence of marine fauna in the Beaufort Sea intertidal to the 

damaging physical disturbances of ice scour (Crane 1974; Feder and Schamel 1976; Gutt 2001). 

However, while ice scour likely contributes to the loss of relatively large metazoans, the multiple 

generations of freshwater dipteran larvae indicate that they survive total freezing of the intertidal 

and that such disturbances do not permanently eliminate all macroinvertebrates from the 

sediments. At the nearby Mackenzie Delta, scouring was less common at water depths < 2 m, 

perhaps because the entire water column is frozen at this depth (Hill et al. 2001). The lack of 

dynamic tides in lagoons on the Beaufort Sea coast may also minimize scouring, although Baffin 

Island intertidal fauna did survive in areas where tidal fluctuations prevented freezing to the 

bottom (Dale et al. 1989). 

Freezing of the water column and sediments that annually kills some taxa during the winter, as 

observed on Spitsbergen and Baffin Island, likely drives the low diversity in marine invertebrates 

in Beaufort Sea deltas. There is considerable evidence that marine invertebrates survive at depths 

where freezing to the bottom is prevented (Dale et al. 1989; Dunton et al. 2012). Hard-shelled 
68

taxa like bivalves, periwinkles, and barnacles in hard bottom environments can withstand 

freezing temperatures to -10°C ( Ellis and Wilce 1961; Gutt 2001), but bivalves dwelling in soft 

sediments do not survive freezing (Gutt 2001). Freezing is lethal to Amphipoda, Spionidae, and 

Chaetiliidae as well (Weslawski and Szymelfenig 1999), but these species can recolonize the 

intertidal each year from nearby lagoons (Zajac 1991; Drolet et al. 2013), where source 

populations can escape freezing (Dale et al. 1989; Weslawski and Szymelfenig 1999). 

The low diversity of our study areas reflects responses to a highly stressed environment. Strong 

disturbances exceeding a community’s resilience (Boesch and Rosenberg 1981) have a negative 

effect on invertebrate occurrence. Also, the intermediate disturbance hypothesis predicts highly 

disturbed areas will have lower species diversity (Huston 1979). Annual freezing of Beaufort Sea 

intertidal habitats is a strong disturbance that exceeds the resilience of some taxa with the effect 

of reduced species diversity. Likewise, invertebrate occurrence at high Arctic deltas on 

Spitsbergen was low. Only one taxa was found at a similar depth as our sites (Wlodarskakowalczuk et al. 2007), and another study found four to nine taxa in samples collected at 

unknown depths at six different deltas (Weslawski and Szymelfenig 1999). In the Canadian high 

Arctic on Baffin Island, macroinvertebrate taxa were few to absent (Dale et al. 1989). Lower 

species diversity is due to greater disturbance in shallow water habitat (Kendall 1996) and the 

lack of resistance and resilience in marine species to freezing (Boesch and Rosenberg 1981). 

Thus, Beaufort Sea intertidal habitats are populated with pioneering marine species that 

recolonize the benthos annually. 

Unlike marine invertebrates, freshwater invertebrates are capable of surviving freezing events 

within the sediment (Strathdee and Bale 1998; Danks 2007). Beaufort Sea delta sediments 

probably freeze all the way through to the underlying permafrost (Walker 1998); thus the 

strategy of burrowing deep into sediments to escape the ice is not possible. Chironomidae 

(Danks 1971; Andrews and Rigler 1985), Oligochaeta (Andrews and Rigler 1985), and Tipulidae 

(Pritchard 1983) survive freezing events through freeze tolerance and supercooling (reviewed by 

Danks 1971; Strathdee and Bale 1998). Another strategy to withstand freezing events is seen in 

Chironomidae; they may withstand the mechanical stresses due to changes in sediment structure

with ice crystal formation during freezing events by burrowing into fine silt/clay sediments 
69

(Danks 2007). Indeed, we found that Chironomidae abundance was associated with fine 

sediments. This finding is important as climate change will likely alter delta sediments; fine 

grain sediment accretion will decrease as glaciers in the Brooks Range disappear in the next 50-

75 years (Nolan et al. 2011). A final adaptation to this cold and variable environment is found in 

the order Diptera including Chironomidae, which has a population consisting of multiple 

generations (MacLean and Pitelka 1971; Butler 1982; Danks 2007). This trait is thought to 

increase persistence of a population in harsh environments in the event that one generation is 

unsuccessful (MacLean 1975).

6.4.2 Invertebrate Abundance

Environmental extremes like desiccation, freezing, predation, and other factors in large part 

determine the survival and vertical distribution of intertidal biota (Anderson 1983). For deltas 

that have little vertical relief, the fauna still reflect habitat heterogeneity, food availability, 

exposure to predators and physical dynamics. We investigated the association between 

invertebrates and some environmental variables by testing interactions between water depth, 

moisture, and fine sediments and found they were important predictors of Chironomidae and 

Oligochaeta abundance. In comparison, inundation time and fine sediment grain size were 

positively correlated with invertebrate abundance in other studies (Yates et al. 1993; Powers et 

al. 2002; Kraan et al. 2010), but they did not investigate interactions. The significant interactions 

in the present study indicate that associations between abundance and environmental variables 

may be more complex than previously reported. Sediment grain-size is usually a covariate with 

physical dynamics such that finer sediments persist in areas with reduced dynamics (Naidu and 

Mowatt 1983; Naidu and Klein 1988). Here, due to freezing, low tidal influences, and reduced 

available carbon due to glacial sediments (Wlodarska-Kowalczuk and Pearson 2004; Hood and 

Scott 2008), the complexity of environmental interactions may be greater. 

6.4.3 Invertebrate Distribution

Survival strategies preventing freshwater invertebrates from freezing allow them to survive on 

the deltas, but we propose that freezing also plays an important role in shaping invertebrate 

distribution. For example, we found the distribution of Oligochaeta was constant from one year 
70

to the next and within a season, but patches were small and habitat may be limited due to the 

frozen sediment in winter. In contrast, Chironomidae distribution increased across the mudflats 

as the summer progressed suggesting that in areas where populations were negatively impacted 

by freezing, they were able to recolonize through the summer. Tipulidae larvae radiated from the 

tundra’s edge with increasing abundance over the summer coupled with a spread from the shore 

towards the water. Tipulidae adults lay eggs in south-facing tundra slopes, which collect heat 

early in the summer helping to initiate egg hatching (MacLean 1975; Pritchard 1983). Tipulidae 

pupae and adults were very rare in our samples, suggesting that these life stages occur outside 

delta habitats. Tipulidae may migrate out onto deltas during the larval stage to feed, but then 

migrate back to upland tundra to pupate and finish their life cycle. Their tracks stretching for 

meters are common on the sediment surface. If this is a true migration by this taxon, then, future 

research should address how these insects return to specific habitats during different life stages, 

and how the linkages between the marine and terrestrial environments enhance survival in these

river deltas.

6.4.4 Isotopic Analysis of the Trophic Community

The macroinvertebrate community of Beaufort Sea river deltas was composed of two life history 

strategies, one marine and one with terrestrial freshwater origins. We hypothesized that these two 

groups would maintain some degree of fidelity to their natal carbon sources, with one reflecting a 

marine signature and the other a terrestrial signature. However, our data did not support this 

hypothesis; the range in δ13C values for biota collected on the deltas clearly reflects a fauna that 

preferentially assimilates marine-derived carbon, with some fauna exhibiting a greater proportion 

of autochthonous carbon than others (e.g. Saduria compared to Spio filicornis) regardless of the 

life history strategy of the taxa. In addition, carbon isotopic values for some species are similar to 

those of the same species collected in Beaufort Sea lagoons at ≤ 4.5 m depth (Spio filicornis -

22.3‰, Gammarus setosus -23.4‰, and Saduria entomon -21.0‰; Dunton et al. 2012). 

We did not observe a gradient of enriched to depleted δ13C values from the lagoon to the delta as 

found by researchers on the Colville River Delta (Craig et al. 1984), but these three deltas are 

relatively small in comparison. The isotopic signatures we observed from resident delta fauna 

were distinctly more 13C enriched than values observed in nearby tundra ponds, although a 
71

representative of the Culicidae collected on deltaic mudflats had a δ13C value of -31.5‰. It is 

likely that this organism had just emigrated from its tundra pond base since Culicidae are an 

infrequent component of the delta community assemblage (Table 5.3) and larvae are never 

found. Thus, our data clearly show the importance of terrestrial sources of carbon for freshwater 

species that reside in the ponds, but also demonstrate the clear assimilation of marine sources of 

carbon by benthic fauna that inhabit the deltas. Other recent work (Dunton, unpublished data) 

has shown that sediment chlorophyll concentrations range up to 204 mg m-2, which would 

provide a significant source of labile carbon for the benthic infauna living on the tidal flats of the 

these deltas. In addition, concentrations of various phaeopigments reveal very active grazing of 

the sediment microalgae by benthic metazoans (Dunton, unpublished data). This information, 

along with the evidence from stable isotope data, indicates that the food webs of the high latitude 

river deltas may shift from allochthonous (terrestrial) to autogenous (marine benthic microalgae) 

sources of carbon once the deltas become ice-free.

6.4.5 Study Implications

The disturbance prone intertidal habitats we surveyed had fewer taxa than temperate areas, and 

furthermore, the marine taxa were generalists. However, some of the freshwater taxa were 

specialists that could be impacted by climate change including changes in sediment aggregation, 

erosion from storm surges, and sea level rise. Sediment accretion in river deltas of the Beaufort 

Sea may be greater now than in the past due to increased melting of glaciers in the Brooks Range 

(Hinzman et al. 2005; Nolan et al. 2011). However, sediment transport will decline in the next 

50-75 years when glacial ice disappears and is replaced by annual snow fields (Nolan et al. 

2011). Changes in sedimentation rates will likely transform sediment structure by increasing 

grain size, a change that could further affect some invertebrates, especially those associated with 

more fine-grain sediments (e.g. the Chironomidae). 

Glacial sediments in particular have unique characteristics due to high ion exchange and low 

carbon content that will impact the invertebrate community from the bottom up with more 

available carbon if glacial sediments are absent (Naidu and Klein 1988; Hood and Scott 2008). In 

our samples we find a four-fold increase in total carbon measurements between glacial fed and 

non-glacial fed deltas (Figure 5.5). Storm surge frequency is increasing on the Beaufort Sea coast 
72

(Hinzman et al. 2005; Walsh 2008), and storm surges are often observed first-hand (Crane 1974; 

Martin 1983). However, the effects of these events on deltaic habitats are unknown, although the 

invasion of seawater likely increases salinity in brackish water areas and increases erosion. Sea 

level rise could also change delta habitats, but with little knowledge of the extent of the change 

in the Beaufort Sea it is difficult to predict actual impacts to river deltas (Proshutinsky and 

Bourke 2001). Regardless, expectations are that sedimentation rates will not counter sea level 

rise (Weston 2014).

Resource development for oil could also impact coastal delta areas; offshore drilling has already 

begun within 7 km of the Canning River Delta, and more development along the coast is 

expected. Oil spills adversely affect invertebrate communities (Percy 1976; Miller et al. 1986; 

Feder et al. 1990; Peterson et al. 2003). The full impact of an Arctic oil spill is currently 

unknown, but biodegradation of oil in Arctic conditions is being researched to prepare for spill 

response and assess Arctic conditions (this study; McFarlin et al. 2011; Prince et al. 2013). Our 

data provide baseline information on pre-development invertebrate communities of the Beaufort 

Sea that could help assess impacts and restore habitats to their previous condition. Our data also 

provide insights into the potential resilience of macroinvertrbrate communities. The absence of 

many marine fauna on deltaic mudflats suggests source populations from nearby lagoons. In the 

event of a large but temporally short disturbance, the perturbation may have limited effects as 

marine fauna repopulate rapidly on an annual basis. Freshwater fauna would likely recolonize 

from source populations in the river.

In conclusion, invertebrate communities on the Beaufort Sea coast are dominated by 

disturbances (prolonged annual freezing) unique to high latitudes. Beaufort Sea river deltas are 

important sources of food for wading birds and migrating estuarine fishes during the summer. 

The availability of food resources is a product of the survival of various freshwater invertebrate 

species that are resilient to freezing and the active annual migration and colonization of 

invertebrates from protected marine invertebrate “source” populations in adjacent lagoons. 

Because of their contributions to estuarine ecology as well as their contributions to migrating 

birds, future research of lagoon ecosystems on the Beaufort Sea should include intertidal habitats 
73

and the freshwater taxa that live in these highly physically stressed habitats, which will require 

new sampling approaches. 

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