CORRELATIONS BETWEEN FISH ABUNDANCE and PHYSICOCHEMICAL PARAMETERS in HUMBOLDT BAY, CALIFORNIA by Kirsten C. Lomeli a Thesis

CORRELATIONS BETWEEN FISH ABUNDANCE AND PHYSICOCHEMICAL

PARAMETERS IN HUMBOLDT BAY, CALIFORNIA

Kirsten C. Lomeli

A Thesis

Presented to

The Faculty of Humboldt State University

In Partial Fulfillment

Of the Requirements for the Degree

Master of Science

In Natural Resources: Fisheries Biology

September, 2011

ABSTRACT

Correlations between fish abundance and physicochemical parameters in Humboldt Bay, California.

Kirsten C. Lomeli

Eelgrass habitats, within estuaries, are known to be important nursery zones for several fish species. However, they are considered to be harsh environments due to wide fluctuations in physicochemical factors. The objectives of this study were to determine the extent of correlations between fish and their physical surroundings, to minimally explore interactions between climatic and physicochemical parameters, and to investigate the use of geostatistical interpolation tools to elucidate physicochemical changes spatially and temporally. This research was conducted in Humboldt Bay, Humboldt County,

California from June 2006 to August 2008. Three eelgrass sites (Samoa, Indian Island and North Bay) were sampled monthly using an epibenthic otter trawl. In addition to fish populations, physicochemical and climatic parameters were assessed. These included water temperature, salinity, dissolved oxygen, pH, turbidity, average monthly precipitation and average monthly wind speed. A Canonical Correspondence Analysis was run to evaluate fish community/environment relationships. To examine fish species/environment relationships, an empirical distribution function was constructed using the physicochemical parameters and weighted by fish species abundances. Then a randomization test using the Kolmogorov-Smirnov test statistic indicated the strength of the cdf correlations. Universal Krig estimates of water temperature and salinity were

iii calculated using Geographic Information Systems geostatistical analyst to transform data into spatially referenced surfaces. A total of 16,261 fish, representing 21 families and 40 species were captured in this study. Fish abundance was greatest during 2007. Twelve fish species accounted for 94% of the total fish catch. Annually, species richness and diversity were significantly different; each being greatest in 2008. Within each year, species diversity and fish abundances were highest during the spring and summer months. Fish were strongly correlated with environmental parameters. Juvenile

Cymatogaster aggregata preferred warmer water temperatures, greater than 16°C, while adults were found at lower water temperatures. Pholis ornata exhibited the highest abundances during 2007 warmer water temperatures and lower precipitation rates.

Gasterosteus aculeatus and Pholis ornata showed strong associations to both water temperature and precipitation. Gasterosteus aculeatus adults appeared to prefer warmer water temperatures than juveniles, but both life stage abundances decreased with slight increases in precipitation. Sebastes melanops and Embiotoca lateralis showed strong associations with high turbidity, while Osmerid spp. showed a strong correlation with high dissolved oxygen readings. In general, the warmer summer water temperatures at the

North Bay location attracted juvenile fish, while adult fish were more common at the

Samoa location. Interpolated water temperature and salinity surfaces successfully showed general patterns in physicochemical parameters over space and could prove very useful in simplifying complex spatial physicochemical and fish distribution patterns.

AKNOWLEDGEMENTS

Funding for this project was provided by California Center for Integrated Coastal

Observation, Research and Education (CICORE). Many thanks to my major advisor Dr.

Timothy Mulligan and my committee members Dr. Helen Mulligan and Dr. Steve

Steinberg for all the support and the hours they spent carefully reviewing this paper. I would like to thank my husband, Mark Lomeli for his patience, support and guidance throughout this process. Thank you to Dave Hoskins, Grant Eberle for the boat handling and others who helped with the trawling including Dave Kyle, Jolyon Walkley, Carl

Meredith, Russell Black, Ryan Slezak, and Drew Barrett.

TABLE OF CONTENTS

ABSTRACT ...... iii

AKNOWLEDGEMENTS...... v

TABLE OF CONTENTS ...... vi

LIST OF TABLES ...... vii

LIST OF FIGURES ...... ix

LIST OF APPENDICES ...... xv

INTRODUCTION ...... 1

METHODS ...... 6

Site Description ...... 6

Statistical Analyses ...... 14

Spatial Analysis ...... 21

RESULTS ...... 28

Correlation Matrix ...... 39

Fish Associations with Environmental Parameters using Canonical Correspondence Analysis...... 42

Empirical Cumulative Distribution Functions (cdf) to Test the Strength of Fish and Environmental Associations...... 49

Kriging of Environmental Parameters ...... 79

Physicochemical Comparisons ...... 90

DISCUSSION ...... 96

REFERENCES ...... 103

APPENDICES ...... 108

LIST OF TABLES

Table Page

1 Physicochemical parameters sampled on Humboldt Bay, Humboldt County, California. Instruments utilized are coded below as: A = thermometer and refractometer, B = Datasonde 600xl multiprobe and C = Datasonde 1600 multiprobe...... 12

2 Grouping of physical parameters filtered through Principle Components Analysis (PCA) as a variable selection routine for Canonical Correspondence Analysis. X indicates inclusion...... 15

3 Fish caught in Humboldt Bay, California from June 2006 to August 2008. Percent equals % of total for given year...... 28

4 Fish species caught at each sample location in Humboldt Bay, California from June 2006 to August 2008. X indicates capture of at least one specimen. .. 30

5 Seasonal abundances of the 12 most abundant fish species caught in Humboldt Bay, California from June 2006 to August 2008...... 33

6 Lengths (mm) of the 12 most abundant fish species caught in Humboldt Bay, California from June 2006 to August 2008...... 34

7 Yearly ranges of environmental variables, Humboldt bay, California measured from June 2006 to August 2008...... 36

8 Ranges of environmental variables for each sample location, Humboldt Bay, California measured from June 2006 to August ...... 37

9 ANOVA results of fish abundances and each physicochemical parameter in Humboldt Bay, California measured from June 2006 to August 2008. * indicates a significant result at p≤0.05...... 38

10 Range of physicochemical parameters for the 12 most abundant fish species caught from June 2006 to August 2008, Humboldt Bay, California...... 40

11 Pearson Correlation Coefficients of climatic and physicochemical parameters, Humboldt Bay, California from June 2006 to August 2008. Bold values indicate significant results (p≤0.05)...... 41

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LIST OF TABLES (CONTINUED)

Table Page

12 Cumulative distribution function of the Kolmogorov-Smirnov test statistic summary of pooled (first row), annual and sample location fish catch data from June 2006 to August 2008. *** = very strong, ** = moderate, and * = mild relationships with physical parameters...... 62

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LIST OF FIGURES

Figure Page

1 Study location, Humboldt Bay, Humboldt County, California...... 7

2 Samoa sample site (N40.4639, W124.1262) Humboldt Bay, California. Samoa was sampled by otter trawl from June 2006 to August 2008. (Source: “Humboldt Bay.” 40° 46’ 32.07”N and 124° 12’ 13.10”W. Google Earth. June 9, 2006 to September 25, 2006. November 30, 2009.) ...... 9

3 Indian Island sample site (N40.4900, W124.1028), Humboldt Bay, California. Indian Island was sampled by otter trawl from June 2006 to February 2007. (Source: “Humboldt Bay.” 40° 49’ 37.22”N and 124° 08’ 55.17”W. Google Earth. February 8, 2006 to June 9, 2006. November 30, 2009.) ...... 10

4 North Bay sample site (N40.8198, W124.1335), Humboldt Bay, California. North Bay sampled by otter trawl from March 2007 to August 2008. (Source: “Humboldt Bay.” 40° 49’ 47.47”N and 124° 08’ 05.12”W. Google Earth. February 8, 2006 to September 25, 2006. November 30, 2009.) ...... 11

5 Illustration of the calculation of the Kolmogorov-Smirnov test statistic. The “max” indicates the maximum vertical distance between the environmental cumulative distribution function (f(t)) and the fish species weighted cumulative distribution function g(t))………………………………………………………...20

6 Universal Krige interpolated sample locations, Humboldt Bay, Humboldt County, California...... 25

7 Canonical Correspondence Analysis on Group 1 environmental parameters with salinity (precipitation removed) and the top 12 fish species captured in Humboldt Bay, California in the summer, winter, fall and spring from 2007 to 2008. (The species are listed by the first three letters of the genus and the specific epithet, they include: Hypomesus pretiosus, Gasterosteus aculeatus, Aulorhynchus flavidus, Syngnathus leptorhynchus, Sebastes melanops, Hexagrammos decagrammus, Leptocottus armatus, Cymatogaster aggregata, Embiotoca lateralis, Pholis ornata, Parophrys vetulus and Osmerid spp. = Osmspp.) ...... 43

LIST OF FIGURES (CONTINUED)

Figure Page

8 Canonical Correspondence Analysis on Group 1 environmental parameters with precipitation (salinity removed) and the top 12 fish species captured in Humboldt Bay, California in the summer, winter, fall and spring from 2007 to 2008. (The species are listed by the first three letters of the genus and the specific epithet, they include: Hypomesus pretiosus, Gasterosteus aculeatus, Aulorhynchus flavidus, Syngnathus leptorhynchus, Sebastes melanops, Hexagrammos decagrammus, Leptocottus armatus, Cymatogaster aggregata, Embiotoca lateralis, Pholis ornata, Parophrys vetulus and Osmerid spp. = Osmspp.) ...... 44

9 Canonical Correspondence Analysis on Group 2 environmental parameters with salinity (precipitation removed) and the top 12 fish species captured in Humboldt Bay, California in the summer, winter, fall and spring from 2007 to 2008. (The species are listed by the first three letters of the genus and the specific epithet, they include: Hypomesus pretiosus, Gasterosteus aculeatus, Aulorhynchus flavidus, Syngnathus leptorhynchus, Sebastes melanops, Hexagrammos decagrammus, Leptocottus armatus, Cymatogaster aggregata, Embiotoca lateralis, Pholis ornata, Parophrys vetulus and Osmerid spp. = Osmspp.) ...... 45

10 Canonical Correspondence Analysis on Group 2 environmental parameters with precipitation (salinity removed) and the top 12 fish species captured in Humboldt Bay, California in the summer, winter, fall and spring from 2007 to 2008. (The species are listed by the first three letters of the genus and the specific epithet, they include: Hypomesus pretiosus, Gasterosteus aculeatus, Aulorhynchus flavidus, Syngnathus leptorhynchus, Sebastes melanops, Hexagrammos decagrammus, Leptocottus armatus, Cymatogaster aggregata, Embiotoca lateralis, Pholis ornata, Parophrys vetulus and Osmerid spp. = Osmspp.) ...... 46

11 Cumulative distribution function of water temperature relationship for Cymatogaster aggregata in Humboldt Bay, California from June 2006 to August 2008. The p-value represents the probability of attaining the Kolmogorov- Smirnov test statistic in a randomized distribution under the null hypothesis. .... 50

12 Cumulative distribution function of precipitation relationship for Gasterosteus aculeatus in Humboldt Bay, California from April 2006 to August 2008. The p value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis...... 51

LIST OF FIGURES (CONTINUED)

Figure Page

13 Cumulative distribution function of water temperature relationships for Cymatogaster aggregata in Humboldt Bay, California from January 2007 to August 2008. The p-value represents the probability of attaining the Kolmogorov- Smirnov test statistic in a randomized distribution under the null hypothesis. .... 52

14 Cumulative distribution function of water temperature relationships for Gasterosteus aculeatus in Humboldt Bay, California from January 2007 to August 2008. The p-value represents the probability of attaining the Kolmogorov- Smirnov test statistic in a randomized distribution under the null hypothesis. .... 53

15 Cumulative distribution function of turbidity relationship for Sebastes melanops in Humboldt Bay, California from January 2007 to August 2008. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis...... 54

16 Cumulative distribution function of turbidity relationship for Cumulative distribution function of turbidity relationship for Embiotoca lateralis in Humboldt Bay, California from January 2007 to August 2008. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis...... 55

17 Cumulative distribution function of precipitation relationship for Sebastes melanops and Pholis ornata in Humboldt Bay, California from January to December 2007. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis...... 56

18 Cumulative distribution function of precipitation relationship for Sebastes melanops and Pholis ornata in Humboldt Bay, California from January to August 2008. The p-value represents the probability of attaining the Kolmogorov- Smirnov test statistic in a randomized distribution under the null hypothesis. .... 57

19 Cumulative distribution function of dissolved oxygen relationship for Osmerid spp. in Humboldt Bay, California from January 2007 to August 2008. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis...... 58

LIST OF FIGURES (CONTINUED)

Figure Page

20 Cumulative distribution function of the Samoa and North Bay sample sites water temperature relationship for Cymatogaster aggregata (Cagr in figure) in Humboldt Bay, California from June 2006 to August 2008. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis...... 59

21 Cumulative distribution function of the Samoa and North Bay sample sites water temperature relationship for Pholis ornata (Porn in figure) in Humboldt Bay, California from June 2006 to August 2008. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis...... 60

22 Cymatogaster aggregata abundances in Humboldt Bay, California from June 2006 to August 2008...... 65

23 Pholis ornata abundances in Humboldt Bay, California from June 2006 to August 2008...... 66

24 Gasterosteus aculeatus abundances in Humboldt Bay, California from June 2006 to August 2008...... 67

25 Embiotoca lateralis abundances in Humboldt Bay, California from June 2006 to August 2008...... 68

26 Sebastes melanops abundances in Humboldt Bay, California from June 2006 to August 2008...... 69

27 Number of adult and juvenile Cymatogaster aggregata at Samoa site, Humboldt Bay, California from June 2006 to August 2008...... 71

28 Number of adult and juvenile Cymatogaster aggregata at North Bay site, Humboldt Bay, California from June 2006 to August 2008...... 72

29 Number of adult and juvenile Pholis ornata at Samoa site, Humboldt Bay, California from June 2006 to August 2008...... 73

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LIST OF FIGURES (CONTINUED)

Figure Page

30 Number of adult and juvenile Pholis ornata at North Bay site, Humboldt Bay, California from June 2006 to August 2008...... 74

31 Number of adult and juvenile Gasterosteus aculeatus at Samoa site, Humboldt Bay, California from June 2006 to August 2008...... 75

32 Number of adult and juvenile Gasterosteus aculeatus at North Bay site, Humboldt Bay, California from June 2006 to August 2008...... 76

33 Number of adult and juvenile Embiotoca lateralis at Samoa site, Humboldt Bay, California from June 2006 to August 2008...... 77

34 Number of adult and juvenile Embiotoca lateralis at North Bay site, Humboldt Bay, California from March 2007 to August 2008...... 78

35 Summer 2006 average water temperatures in Humboldt Bay, California and offshore Pacific Ocean waters from June to August 2006. Values derived from buoy, datasonde and sample data...... 80

36 Summer 2007 average water temperatures in Humboldt Bay, California and offshore Pacific Ocean waters from June to August 2007. Values derived from buoy, datasonde and sample data...... 81

37 Summer 2008 average water temperatures in Humboldt Bay, California and offshore Pacific Ocean waters from June to August 2008. Values derived from buoy, datasonde and sample data...... 82

38 Winter 2006/2007 average water temperatures in Humboldt Bay, California and offshore Pacific Ocean waters from December 2006 to February 2007. Values derived from buoy, datasonde and sample data...... 83

39 Winter 2007/2008 average water temperatures in Humboldt Bay, California and offshore Pacific Ocean waters from December 2007 to February 2008. Values derived from buoy, datasonde and sample data...... 84

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LIST OF FIGURES (CONTINUED)

Figure Page

40 Summer 2006 average salinity (ppt) in Humboldt Bay, California from June to August 2006. Values derived from buoy, datasonde and sample data. Areas in black represent no data...... 85

41 Summer 2007 average salinity (ppt) in Humboldt Bay, California from June to August 2007. Values derived from buoy, datasonde and sample data. Areas in black represent no data...... 86

42 Summer 2008 average salinity (ppt) in Humboldt Bay, California from June to August 2008. Values derived from buoy, datasonde and sample data. Areas in black represent no data...... 87

43 Winter 2006/2007 average salinity (ppt) in Humboldt Bay, California from December 2006 to February 2007. Values derived from buoy, datasonde and sample data. Areas in black represent no data...... 88

44 Winter 2007/2008 average salinity (ppt) in Humboldt Bay, California from December 2007 to February 2008. Values derived from buoy, datasonde and sample data. Areas in black represent no data...... 89

45 Mean monthly surface water temperature for Humboldt Bay, California from June 2006 to August 2008...... 91

46 Salinity for Humboldt Bay, California from June 2006 to August 2008...... 92

47 Dissolved oxygen for Humboldt Bay, California from June 2006 to August 2008...... 93

48 Average monthly precipitation on Humboldt Bay, California from June 2006 to August 2008...... 94

49. Turbidity values for Humboldt Bay, California from June 2006 to August 2008. 95

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LIST OF APPENDICES

Appendix Page

A Cumulative distribution function of temperature relationship for Osmerid spp., Aulorhynchus flavidus and Pholis ornata in Humboldt Bay, Humboldt County, CA from June 2006 to August 2008. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis...... 108

B Cumulative distribution function of the 2007 temperature relationship for Osmerid spp. and Sebastes melanops in Humboldt Bay, Humboldt County, CA for January 2007 to December 2007. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis...... 109

C Cumulative distribution function of 2008 temperature relationship for Osmerid spp., Aulorhynchus flavidus and Pholis ornata in Humboldt Bay, Humboldt County, CA from January 2008 to August 2008. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis...... 110

D Cumulative distribution function of temperature at the North Bay site’s relationship for Osmerid spp., Syngnathus leptorhynchus in Humboldt Bay, Humboldt County, CA from March 2007 to August 2008. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis...... 111

E Cumulative distribution function of salinity relationship for Osmerid spp. in Humboldt Bay, Humboldt County, CA from June 2006 to August 2008. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis...... 112

F Cumulative distribution function of 2007 salinity relationship for Hypomesus pretiosus in Humboldt Bay, Humboldt County, CA from January 2007 to December 2007. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis...... 113

LIST OF APPENDICES (CONTINUED)

Appendix Page

G Cumulative distribution function of 2008 salinity relationship for Leptocottus armatus and Cymatogaster aggregata in Humboldt Bay, Humboldt County, CA from January 2008 to August 2008. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis...... 114

H Cumulative distribution function of the Samoa site salinity relationship for Osmerid spp. and Leptocottus armatus in Humboldt Bay, Humboldt County, CA from June 2006 to August 2008. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis...... 115

I Cumulative distribution function of the North Bay site salinity relationship for Cymatogaster aggregata in Humboldt Bay, Humboldt County, CA from March 2007 to August 2008. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis...... 116

J Cumulative distribution function of 2008 dissolved oxygen relationship for Pholis ornata in Humboldt Bay, Humboldt County, CA for January 2008 to August 2008. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis...... 117

K Cumulative distribution function of 2007 pH relationship for Cymatogaster aggregata in Humboldt Bay, Humboldt County, CA from January 2007 to December 2007. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis...... 118

L Cumulative distribution function of 2008 pH relationship for Syngnathus leptorhynchus in Humboldt Bay, Humboldt County, CA from January 2008 to August 2008. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis...... 119

xvi

LIST OF APPENDICES (CONTINUED)

Appendix Page

M Cumulative distribution function of the North Bay site pH relationship for Cymatogaster aggregata in Humboldt Bay, Humboldt County, CA from March 2007 to August 2008. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis...... 120

N Cumulative distribution function of 2007 turbidity relationship for Cymatogaster aggregata in Humboldt Bay, Humboldt County, CA from January 2007 to December 2007. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis...... 121

O Cumulative distribution function of 2008 turbidity relationship for Hypomesus pretiosus in Humboldt Bay, Humboldt County, CA from January 2008 to August 2008. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis...... 122

P Cumulative distribution function of the Samoa site turbidity relationship for Embiotoca lateralis, Sebastes melanops and Hypomesus pretiosus in Humboldt Bay, Humboldt County, CA from June 2006 to August 2008. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis...... 123

Q Cumulative distribution function of the North Bay site turbidity relationship for Embiotoca lateralis and Syngnathus leptorhynchus in Humboldt Bay, Humboldt County, CA from March 2007to August 2008. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis...... 124

R Cumulative distribution function of precipitation relationship for Embiotoca lateralis, Pholis ornata and Hexagrammos decagrammus in Humboldt Bay, Humboldt County, CA from June 2006 to August 2008. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis...... 125

xvii

LIST OF APPENDICES (CONTINUED)

Appendix Page

S Cumulative distribution function of precipitation relationship for Cymatogaster aggregata and Osmerid spp. in Humboldt Bay, Humboldt County, CA from June 2006 to August 2008. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis...... 126

T Cumulative distribution function of 2007 precipitation relationship for Pholis ornata in Humboldt Bay, Humboldt County, CA from January 2007 to December 2007. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis...... 127

U Cumulative distribution function of 2008 precipitation relationship for Gasterosteus aculeatus, Hexagrammos decagrammus and Osmerid spp. in Humboldt Bay, Humboldt County, CA from January 2008 to August 2008. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis...... 128

V Cumulative distribution function of 2008 precipitation relationship for Pholis ornata and Embiotoca lateralis in Humboldt Bay, Humboldt County, CA from January 2008 to August 2008. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis...... 129

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INTRODUCTION

Environmental conditions influence fish distributions, communities and seasonal movements. To minimize energy expended for survival, species typically favor areas that optimize their physiological processes (Matthews 1990).

Estuaries, and eelgrass habitats within estuaries, are known to be important nursery zones for estuarine and marine fish species (Kennish 1990, Blaber et al. 1995).

The majority of worldwide commercial fish landings rely on species that utilize estuarine waters for parts of their life cycle (Kennish 1990, Pauly et al. 1998). Despite being optimal nursing grounds, estuaries are considered harsh environments, due to wide fluctuations in water movement and physicochemical factors. Consequently, resident estuarine fishes typically have wide ranging environmental tolerances as an adaptation to these extreme fluctuations (Kennish 1990).

Several estuarine studies have shown correlations between fish occurrences and specific physicochemical and habitat parameters. Short term studies on fish communities note water temperature (Peterson and Ross 1991, Marshall and Elliott 1998), salinity

(Able et al. 2001, Franco et al. 2006), dissolved oxygen (Maes et al. 1998, 2004), pH

(Martino and Able 2003), turbidity (Blaber and Blaber 1980, Franco et al. 2006), tidal state (Marshall and Elliott 1998), depth (Paterson and Whitfield 2000b, Akin et al. 2003), eelgrass habitat (Weinstein and Brooks 1983, Paterson and Whitfield 2000a, Able et al.

2002), substrate (Able et al. 2001), presence of structure (Maes et al. 1998), distance to estuary mouth (Akin et al. 2003, Martino and Able 2003), and prey density (Peterson and

1 2

Ross 1991) to be factors structuring fish distributions.

Confounding the understanding of ephemeral seasonal environmental conditions are predator/prey interactions and physiological tolerances of individual fish species.

Marshall and Elliott (1998) noted significant correlations between a number of fish species and water temperature, salinity, dissolved oxygen, tidal state and depth in

Humber Estuary, United Kingdom. Similarly, DO concentrations appeared to structure fish communities in Sheldt estuary on the Belgian-Dutch border. Blaber and Blaber

(1980) suggested that turbidity is associated with productive feeding areas and provides cover for fishes in South African estuaries. There, filter feeding adult fish were found only in highly turbid waters. Other studies have determined that fish move away from alkaline waters when pH levels approach 9.06 – 10.0, unless more important survival factors outweigh avoidance, including food availability or lower predation levels (Serafy and Harrell 1993, Scott et al. 2005). Fish species often segregate along a dissolved oxygen gradient based on internal tolerances (Thiel et al. 1995, Moller and Scholz 2007).

In a Belgian estuary, freshwater species were more abundant in brackish waters, with higher DO levels, than in freshwater (Maes et al. 1998). Many studies have shown similar trends for salinity gradients. Gracia-Lopez et al. (2006) suggested that for juvenile snook

(Centropomus undecimalus) oxygen consumption and nitrogen excretion increased with increasing salinity due to the higher amounts of energy expenditure for osmoregulation associated with elevated salinities. Snook used different types of energy reserves

(glycogen, and lipids versus protein) based on salinity gradients and also used more energy digesting food at high salinities. In a low salinity estuary in New Jersey,

U.S.A., Martino and Able (2003) found that the salinity gradient correlated with species richness. Species richness was lowest at salinity levels between 12-14 ppt, because this appeared to be the upper limit for freshwater fish species and the lower limit of most marine fish species.

Offshore studies also have found strong relationships connecting teleosts to their environmental surroundings. In the Faroe Island area of the North Atlantic, species diversity increased significantly with increasing depth (Magnussen 2002, Persohn et al.

2009). Perry and Smith (1994) found strong relationships between specific fish species and water temperature, salinity and bottom depth in the eastern Scotian Shelf of the

Atlantic. Here yellowtail flounder (Pleuronectes ferruginens) preferred shallow, cool, less saline areas; silver hake (Merluccius bilinearis) preferred deep, warm, saline areas; while haddock (Melanogrammus aeglefinus) tended to prefer median water temperatures.

Similarly, Atlantic cod (Gadus morhua) were shown to avoid cooler water temperatures and low dissolved oxygen in the Gulf of St. Lawrence (D’Amours 1993). The scaled herring (Harengula jaguana), scad (Decapterus punctatus) and round sardinella

(Sardinella aurita) were strongly connected to warmer water temperatures and higher salinities in the south Atlantic (Paramo et al. 2003). Distributions of the early life history stages have been related to environmental factors. Jack mackerel (Trachurus murphyi) egg distributions were correlated with high water temperatures (Cubillos et al. 2008).

Herring (Clupea pallasii) year class spawning success appears to hinge on the duration of warmer water masses (Watanabe et al. 2008). Finally, in a frontal zone study, Ciannelli et

4 al. (2002) found juvenile walleye Pollock utilizing high prey density and low predator areas in the Pribilof Islands of the Bering Sea.

Without visible, identifiable boundaries such as those found in terrestrial systems, aquatic habitats are difficult to quantify spatially. Boundary ambiguities coupled with the mobility of aquatic organisms easily confound results. Water quality measurements are commonly collected during fish studies to characterize short and long term trends.

Establishing maps of physicochemical, benthic and climatic measurements, using geostatistical interpolation provides a powerful tool to quantify spatial relationships in complex open systems over time. Krig interpolation uses spatial distance to calculate statistically probable values from point data (Porter et al. 1997). Interpolation procedures are regularly used to predict climate, to map sea surface temperature and in marine biology, to map fish distributions offshore. Reese and Brodeur (2006) mapped biological

“hotspots” along the California Current in the Pacific Northwest by overlaying krig interpolated surfaces of nekton density, biomass and species richness. They found sea surface temperature, salinity and water density were the most useful predictors of nekton patches. In a related study, Reese et al. (2005) interpolated sea surface temperature, salinity, chlorophyll, zooplankton concentration, and zooplankton species richness. They noted that sea surface temperature was consistently correlated with zooplankton distributions along the California current. Sea surface temperature, salinity, dissolved oxygen and transmissivity were krig interpoloated in Santa Monica Bay, California

(Nezlin et al. 2004). There, environmental variation was driven by meteorological factors

(air temperature, wind, atmospheric precipitation and El Nino-Southern Oscillation

Cycle). Stelzenmuller et al. (2007) also krig interpolated total catch, specific fish species catch and length to evaluate placement and local influence of marine protected areas off the coast of Barcelona, Spain. Optimal zones for potential clam farming in a

Mediterranean lagoon were identified using habitat suitability overlays of sediment size, dissolved oxygen, salinity, hydrodynamism, bathymetry and chlorophyll “A” (Vincenzi et al. 2006). Finally, krig interpolated scallop densities in Uruguay were shown to follow a distinct latitudinal and bathymetric gradient (Gutierrez and Defeo 2003). These distribution patterns were useful guides to determining whether a new scallop fishery in

Uruguay would be sustainable.

There is no doubt that fish are driven by their physical surroundings to areas that are physiologically optimal. An inventory of the influential physicochemical parameters on fish populations is necessary to understand ecological and environmental pathways shaping our changing aquatic resources. The objectives of this study were to determine correlations between fish and their physical surroundings, to minimally explore the interactions between climatic and physicochemical parameters, and to explore the use of geostatistical interpolation tools to highlight environmental changes in space and time.

METHODS

Site Description

This study was conducted in Humboldt Bay, Humboldt County, California.

Humboldt Bay can be divided into three geographic sections: South, Central and North

Bays. North Bay is characterized by oyster culture, eelgrass (Zostera marina) beds and shallow mudflats that drain during low tides (Pinnix et al. 2005). South Bay is characterized by thick eelgrass beds, a national wildlife refuge and mudflats that also drain during low tides. Central Bay is more heavily influenced by industrial activities, including shipping traffic, pulp production, power plants, and dredging operations to maintain channel depths. Humboldt Bay is primarily influenced by marine water, because freshwater input during the winter is inconsistent and limited (Pinnix et al. 2005).

Skeesick (1963) noted the water quality in the estuary is influenced by climatic conditions, distance from the entrance channel and the quality of water entering the bay.

Conditions in North and south bay are more variable than the central bay based on their distal locations from the mouth. Skeesick (1963) found that significant evaporation increased North Bay salinity levels and that dissolved oxygen levels were higher during times of increased wind action. Additionally, upwelling events elevated salinity readings and suppressed water temperatures and dissolved oxygen levels.

Three sample locations were studied in Humboldt Bay: Samoa, Indian Island, and

North Bay (Figure 1). These sample sites support eelgrass habitats, but with regard to

6 7

Figure 1. Study location, Humboldt Bay, Humboldt County, California.

8 other environmental parameters, they are very different from one another. The Samoa site

(N40.4639, W124.1262) is approximately two kilometers (km) north of the bay entrance, on the western bank in the central part of the Bay (Figures 1, 2). The Samoa site is primarily sandy bottom which is physically impacted by reflective waves from the bay entrance, tidal currents and winter freshwater input from the Elk River. This site had depths between 0.9 and 2.3 meters (m) and was sampled from June 2006 to August 2008.

The Indian Island site (N40.4900, W124.1028) is approximately 8.5 km north of the bay entrance, on the western bank of Indian Island in the northern section of the Bay

(Figures 1, 3). This site is adjacent to a higher elevation mudflat shelf, which drains at low tide. The substrate is primarily mud. Indian Island was sampled from June 2006 to

February 2007.

The North Bay site (N40.8198, W124.1335) is located approximately 9.5 km from the bay entrance in the north section of the bay (Figures 1, 4). This site has a shallow gradient, winter freshwater influence from Eureka Slough and is adjacent to oyster culture areas. This site is similar to Indian Island, located adjacent to an elevated mud flat shelf that drains periodically at low tide. The substrate at this site is primarily mud. The mean depth ranges between 1.2 and 2.5 m. Due to a lack of fish catch at the

Indian island site, North Bay replaced the Indian Island site and was sampled from March

2007 to August 2008.

From June 2006 to August 2008, two eelgrass beds were sampled monthly in

Humboldt Bay. Fish were collected using an epibenthic otter trawl towed by a 24 foot pontoon boat. Four, five minute tows were conducted at each site. Fish captured were

Figure 2. Samoa sample site (N40.4639, W124.1262) Humboldt Bay, California. Samoa was sampled by otter trawl from June 2006 to August 2008. Image obtained from Google Earth 2009.

Figure 3. Indian Island sample site (N40.4900, W124.1028), Humboldt Bay, California. Indian Island was sampled by otter trawl from June 2006 to February 2007. Image obtained from Google Earth 2009.

Figure 4. North Bay sample site (N40.8198, W124.1335), Humboldt Bay, California. North Bay sampled by otter trawl from March 2007 to August 2008. Image obtained from Google Earth 2009.

12 identified to species, counted, and measured to the nearest millimeter (mm) in total length before being released. During trawl operations, depth was measured several times using a

10 foot stadia rod from March 2007 to August 2008.

Water quality parameters were measured prior to fish sampling (Table 1). Surface water temperature (°C), and salinity (ppt) were collected June 2006 to July 2006 using a handheld thermometer and a refractometer. With the acquisition of a 600xl Datasonde, water temperature, salinity, dissolved oxygen (DO, mg/L), conductivity (µS/cm), and pH were then collected from August 2006 to August 2008. In April 2007, acquisition of a

1600 Datasonde allowed measurements of turbidity (ntu) to be acquired for the rest of the study. Sampling from November 2006 to August 2008 included benthic physicochemical measurements. A one- way ANOVA revealed the surface and bottom measurements were not significantly different (p<0.05). Consequently, these measurements were averaged for each month until the end of the study.

Climate data were obtained from the National Weather Service Woodley Island

Marina, Eureka and Arcata, California weather stations. Woodley Island daily average air temperature (°C) was utilized. Eureka daily average air temperature readings were used when Woodley Island measurements were missing. Average daily wind speed (kmh) data from Eureka were used. Arcata readings were substituted when Eureka measurements were missing. Average daily precipitation in millimeters was calculated using total monthly accumulations from Arcata and Eureka weather measurements. Average daily

Table 1. Physicochemical parameters sampled on Humboldt Bay, Humboldt County, California. Instruments utilized are coded below as: A = thermometer and refractometer, B = Datasonde 600xl multiprobe and C = Datasonde 1600 multiprobe. Sample Temperature Salinity DO Conductivity Turbidity Month/Year Site Instrument (°C) (ppt) (mg/L) (µS/cm) pH (ntu) Jun-06 to Jul-06 Samoa A X X

Indian Island A X X

Aug-06 to Feb-07 Samoa B X X X X X

Indian Island B X X X X X

Mar-07 to Aug-08 Samoa B X X X X X

North Bay B X X X X X

Apr-07 to Aug-08 Samoa C X X X X X X

North Bay C X X X X X X

Barometric pressure (mmHg) from the National Weather Service at Woodley Island was used. When this information was missing, Eel River buoy data from the National Oceanic and Atmospheric Administration (NOAA) National Data Buoy Center was used.

Statistical Analyses

To elucidate relationships between physicochemical and climatic variables a

Pearson Correlation Matrix was constructed (Harrison 2004, Nezlin and DiGiacomo

2005). To determine if physicochemical variables and fish populations varied statistically between years and sample locations, One-way Analysis of Variance (ANOVA) was used.

ANOVA was useful in evaluating these relationships because of uneven sampling between years and sites (Grafen and Hails 2002). Fish abundance, fish density (catch per unit effort (CPUE)), Shannon-Weiner diversity index (H’) (Thiel et al. 1995) and species richness were used to determine whether there were spatial and temporal statistical differences in fish populations (Akin et al. 2003).

Principle Components Analysis was used for environmental variable selection in preparation for Canonical Correspondence Analysis. Habitat data were separated into two groupings (Table 2), to include the breadth of environmental and climatic variables.

These groupings blocked data together based on data consistency. Some parameters collected later in the study due to equipment upgrades were grouped separately (Group 2) from parameters with more numerous, consistent measurements (Group 1). Records with missing data were dropped from the analysis. Principle Components Analysis runs

Table 2. Grouping of physical parameters filtered through Principle Components Analysis as a variable selection routine for Canonical Correspondence Analysis. X indicates inclusion in Principle Components Analysis.

Air Barometric Avg. Daily Avg. Daily Water Avg. Temperature Pressure Wind speed Precipitation Temperature Salinity DO pH Depth Turbidity Group 1 X X X X X X X X

Group 2 X X X X X X X X X X

16 eliminated barometric pressure and wind speed in Group 1 from the Canonical

Correspondence Analysis (Table 2). In Group 2, Principle Components Analysis runs eliminated barometric pressure, average depth and DO from the Canonical

Correspondence Analysis (Table 2). Variables with low communality, standard deviations greater than 10, or whose loss from the analysis improved the eigenvalues were dropped (Grafen and Hails 2002).

Canonical Correspondence Analysis was used to examine correlations between fish abundances and environmental characteristics. This statistical procedure is commonly used for fish community and environmental parameter comparisons (Marshall and Elliott 1998, Akin et al. 2003, Franco et al. 2006, Selleslagh and Amara 2008).

Canonical Correspondence Analysis requires normally distributed data and is susceptible to bias if the environmental factors are highly collinear (Ter Braak 1986). To explore potential collinearity between physicochemical and climatic variables, the environmental data was put into a correlation matrix and variables with Pearson Correlation Coefficients greater than 0.75 were removed from the analysis or run separately (VanKirk 2008, personal communication). Fish abundance was transformed (log(x+1)) to attain a normal distribution (Maes et al. 2004, VanKirk 2008, personal communication). Fish species that represented less than 1% of the total catch were excluded from the fish abundance data.

One percent was chosen arbitrarily to eliminate less common fish species from the analysis. Physicochemical and climatic measurements were standardized ((x- x )/std dev), for each Canonical Correspondence Analysis run (Marshall and Elliott 1998). Fish species are ordinated to indicate the relative strengths of those associations. Species

17 located near the origin have little association with the environmental variables tested or no particular preference. Those proximal to the distal portion of each vector and beyond indicate strong positive relationships with that environmental parameter and other nearby fish species. Species located directly in line in the opposite direction from each vector indicate strong negative relationships with that parameter.

Due to seasonal variation in the data, a temporal component was included.

Principle Components Analysis was used to establish the number of seasons and the separation of the seasons using barometric pressure and water temperature (Marshall and

Elliott 1998, Martino and Able 2003). Seasonal endpoints were obtained by shifting blocks of months back and forth until the most variation was explained. Seasons were categorized as followed: Winter (December to February), Spring (March to May),

Summer (June to August) and Fall (September to November). Then, using these temporal segments, a month at the middle of each season was chosen to obtain the highest potential for orthogonal measurements (January, April, July and October). Therefore, a seasonal/site breakdown was used for Canonical Correspondence Analysis (Marshall and

Elliott 1998, Martino and Able 2003). Due to insufficient data, 2006 was dropped from the analysis, while 2007 and 2008 had four and three seasons respectively.

Relationships between fish and the physical parameters were explored in more detail using methods similar to those of Perry and Smith (1994), Paramo et al. (2003), and Persohn et al. (2009). For specific fish species and environmental associations, generalized additive models (GAM) are also utilized, but generalized additive models were avoided here because they can be complicated to interpret and more suitable for use

18 with larger datasets. This study did not require the stratification approach of Perry and

Smith (1994) because the sample areas were similar in depth. Therefore, an empirical cumulative distribution function for each environmental variable was calculated as:

1 f(t) =  I(xi) i n with an indicator function:

1, if xi  t;  I(xi) =   0, otherwise. where xi = the environmental variable measurement in set i, n = the number of tows and t = an index for the steps ranging from the lowest to highest value of the environmental variable. The cumulative distribution function was then weighted using the fish abundance data and g(t) was calculated as:

1 yi g(t) =  I(xi) i n y

where yi = fish abundance and y = mean fish abundance.

Graphing these cumulative distribution functions characterized the relationship between each species and a particular environmental parameter. The assumption is that if fish abundance has no relationship with a particular environmental parameter, the fish weighted cumulative distribution should follow closely along the environmental parameter trendline. Diversion from the environmental variable trendline indicates that a fish species has a preference for or aversion to particular measurements of that environmental condition. To quantify the strength of this relationship, 1000 trial

19 randomizations were executed using the statistical program R (R Development Core

Team 2008), calculating a Kolmogorov-Smirnov test statistic. The test statistic was calculated as the point of maximum vertical distance between the f(t) and g(t) trendlines

(Figure 5) calculated as:

tstat = max|g(t) – f(t)|

The accumulated test statistics from each permutation established a test statistic distribution to calculate the p-value. Under the null hypothesis, the relationship between the fish and their environment is considered random. If it is not, p ≤ 0.05 indicates a significant non-random relationship. The cumulative distribution function were run on pooled data, and separated by year and by site. Environmental variable readings were tallied into measurement “levels” on the x axis (f(t)). The y axis spreads these environmental measurement events into a cumulative frequency distribution pattern. Fish species present at each environmental measurement “level” were used to weight the environmental trendline to fish abundance (g(t)). The resulting p value of each permutation analysis using the Kolmogorov-Smirnov test statistic were entered along the g(t) trendline on each figure to indicate the statistical strength of each relationship. The strength of the relationships generally judged as a p- value less than or equal to 0.05 is strong, p-value less than or equal to 0.10 is moderate and any p-value above 0.10 is weak (Perry and Smith 1994).

Fish species showing high correlations with environmental parameters were further delineated into juvenile and adult abundances by looking at length frequency histograms of monthly total fish length data. When two apparent cohorts existed,

1.2

1.0

0.8

0.6 f (t) g(t) max 0.4

Cumulative Frequency Cumulative 0.2

0.0

6 8 10 12 14 16 18 20 22 Temperature (oC)

Figure 5. Illustration of the calculation of the Kolmogorov-Smirnov test statistic. The “max” indicates the maximum vertical distance between the environmental cumulative distribution function (f(t)) and the fish species weighted cumulative distribution function g(t)).

21 evidenced by two peaks in length frequency histograms, these data were used to compile monthly numbers of juvenile versus adult populations. Some months contained two cohorts, without distinct or discernable juvenile/adult boundaries. In this instance the cohorts were considered adults.

Spatial Analysis

Krige interpolation is a geostatistical procedure of creating a two and one half dimensional surface using the distance between points and a statistical relationship based on that distance. Kriging interpolation was chosen over other types of interpolators due to a statistical basis for cell estimates and a versatility in characterizing continuous types of data. Universal Kriging was selected over other forms of kriging because environmental parameters have potential for exhibiting anisotropic trends. They are characterized by different ranges in different directions (Verfaillie et al. 2006). Unlike global trends, anisotropic trends are often unknown, but accounted for in Universal

Kriging. It was assumed that physicochemical and climatic parameters would exhibit anisotropy. Despite the difficulties related to anisotropy, Reese and Brodeur (2006) note

Universal Kriging has the ability to accurately characterize important biological gradients. An assumption of this procedure is that the data points are dense enough to be autocorrelated. The further points are from one another, the less statistical weight and less related their values are considered to be. Higher data point densities encourage better geostatistical accuracy.

A semivariogram is the calculation of variance based on the distances between points. The shape and orientation of the semivariogram is useful when deciding the orientation of the kriging process. Krig parameters are the range, sill, and nugget. The nugget is the y-intercept of the graph. The sill is the y-axis where the semivariogram plateaus and the range is the value on the x-axis where this plateau is reached. Increased spacing between points tends to increase range values (Western et al. 1998, Garibaldi and

Caddy 1998). Paramo and Roa (2003) found two different patches in fish sounding data based on semivariogram behavior. Of the omnidirectional and directional semivariograms constructed, the directional semivariogram had a sill formation in a north and south direction. There was no sill formation on the omnidirectional variogram. Consequently, they were able to separate one fish species into two groups for the analysis. A customized theoretical shape is chosen based on the shape of the semivariogram. This shape determines the orientation for resulting krige prediction values.

The nugget effect occurs when the data in the semivariogram does not pass through the origin, but rather intercepts the y-axis at a positive value. Outliers in data increase nugget effect (Reese and Brodeur 2006).

Sample spacing and topography contribute to data variability and therefore the extent of the nugget effect (Western et al. 1998). Lookman et al. (1995) noted that the nugget effect in soil data indicated the sampling grid density was not dense enough to assess spatial autocorrelation.

A search window of three was used in customizing the number of points calculated at one time through the kriging process. Lloyd and Atkinson (2004) note that,

23 generally, a smaller number of neighboring data points included in the window of the kriging procedure removes more variability.

Seasonally averaged offshore, Humboldt Bay buoy and datasonde water temperature data were interpolated using Universal Krig in ArcGIS using Geostatistical

Analyst. The data points had varying levels of resolution. Buoy data included Eel River

(N40.7591, W124.7705), North Spit (N40.7364, W124.2183) and South Spit (N40.7499,

W124.2945). Buoy data were obtained from the NOAA National Data Buoy Center

(National Oceanic and Atmospheric Administration, 2009). Readings are recorded every

30 minutes for 24 hours per day. Datasonde data locations were Indian Island (N40.8143,

W124.1565), DockB (N40.8013, W124.1816), Mad River (N40.8642, W124.1503),

South Bay (N40.7234, W124.2233), Mcnulty Slough (N40.6869, W124.2657) and

Trinidad Pier (N41.0554, W124.1471). The datasonde data were obtained from Humboldt

CeNCOOS (Central and Northern California Ocean Observing System 2009). The Dock

B, Trinidad and South Bay datasonde records data at intervals between 15-30 minutes, 24 hours per day unless maintenance eliminated blocks or seasons of data. Mad River,

McNulty Slough, and the Bay Entrance datasondes recorded readings twice a month every minute of an hour of deployment, typically in the morning hours. The fish sample locations, Samoa, North Bay and Indian Island readings were only taken once a day, during this study (Figure 6). Readings were taken from fish sample sites once per month.

Humboldt Bay water temperature and salinity data from buoys, datasondes and monthly fish sampling events were averaged for the summer and winter seasons. These values were used to create annual Universal Krig interpolated isoline maps of water temperature

24 for Humboldt Bay and offshore waters. Only water temperature and salinity kriged surfaces were constructed because: 1) the data was either insufficient to retain enough locations necessary for constructing a krige interpolated surface or; 2) the variability in measurements were such that the resulting surface was homogenous at most temporal scales (e.g. pH and DO). The krige interpolation procedure is not limited by land. Kriging proceeds to the outmost extent of the data points. Initial interpolations showed Humboldt

Bay water temperatures influencing offshore water temperature. To circumvent this inaccuracy, offshore and bay locations were separated for computation of interpolated surfaces. However, krige interpolating in GIS requires a minimum of 10 data points. Each surface only extends to the outermost extent of the data points. To get the kriging to run correctly and push the calculations to the extent of the water body perimeter, it was necessary to estimate seven points offshore and two points in the Bay. These values were calculated using an average of one to three neighboring points. All surfaces were constructed using a spherical model. For summer of 2007 water temperature data, it was necessary to remove the nugget effect. The final interpolated surfaces were then extracted to a mask and overlaid. Because the surfaces were constructed from data of different resolutions and over large areas of water, the semivariograms and cross validation steps were not included in the results. In addition, making calculations of values and quantities over distances using these maps is discouraged. The Winter 2007/2008 salinity surface had wide ranging values and was therefore treated differently by reclassifying measurements into larger ranges instead of showing individual increments. This allowed

Figure 6. Universal Krige interpolated sample locations, Humboldt Bay, Humboldt County, California.

26 an illustration of source areas of lower salinities balanced with source areas of higher salinities for easier comparison with other salinity surfaces.

Institutional Animal Care and Use Committee protocol number 07/08.F.74.A was used for this study.

RESULTS

A total of 16,261 fish representing 21 families and 40 species were captured

(Tables 3, 4). The 12 most abundant fish species accounted for 94% of the catch (Table

3). Annual differences in fish abundance were observed in this study (Table 3). There were 3,283 individuals from 16 families in 2006, 7,107 individuals from 17 families in

2007, and 5,871 individuals from 18 families in 2008. Syngnathus leptorhynchus was the most abundant fish species annually, except in 2008 where Sebastes melanops numbers dominated. However, this study ended in August of 2008, before the season in which

Syngnathus leptorhynchus were normally most abundant (Table 5). Osmerid spp. and

Sebastes melanops were limited to particular sampling instances and seasons. A large proportion of Osmerid spp. were captured during the winter (Table 5), and typically in only one sample annually (not shown in table). Sebastes melanops were primarily caught during summer (Table 5).

Fish populations varied by sample location (Tables 4, 6). Samoa yielded 10,747 fish, the most abundant being Aulorhynchus flavidus, Syngnathus leptorhynchus and

Sebastes melanops. Indian Island accounted for 1,101 fish, dominated by Syngnathus leptorhynchus and Osmerid spp., while North Bay yielded 4,413 fish dominated by

Cymatogaster aggregata, Syngnathus leptorhynchus, and Gasterosteus aculeatus. Samoa had 27 species, Indian Island, 35 and North Bay, 32 (Table 4).

The top 12 fish species (Table 3) showed seasonality and size differences at each sample location (Tables 5, 6). Gasterosteus aculeatus, Aulorhynchus flavidus, and

27 28

Table 3. Fish caught in Humboldt Bay, California from June 2006 to August 2008. Percent equals % of total for given year. 2006 2007 2008

Species (Common name) # % # % # %

Myliobatis californica (bat ray) - - 1 0.01 4 0.02

Clupea pallasii (Pacific herring) 135 4.11 - - 9 0.14

Engraulis mordax (northern anchovy) 25 0.76 48 0.68 19 0.24

Hypomesus pretiosus (surf smelt) 34 1.04 121 1.70 262 3.78

Spirinchus starski (night smelt) 1 0.03 - - - -

Osmerid spp. 202 6.15 476 6.70 838 13.00

Microgadus proximus (Pacific tomcod) - - - - 1 0.02

Porichthys notatus (plainfin midshipmen) 1 0.03 - - - -

Atherinops affinis (topsmelt) 52 1.58 4 0.06 6 0.09

Gasterosteus aculeatus (three spine stickleback) 111 3.38 844 11.88 320 5.23

Aulorhynchus flavidus (tubesnout) 729 22.21 1366 19.22 627 7.87

Syngnathus leptorhynchus (bay pipefish) 1348 41.06 2069 29.11 222 2.88

Sebastes melanops (black rockfish) 7 0.21 46 0.65 1459 14.27

S. paucispinis (bocaccio) - - 2 0.03 - -

S. caurinus (copper rockfish) 2 0.06 3 0.04 - -

Hexagrammos decagrammus (kelp greenling) 6 0.18 19 0.26 462 5.45

Ophiodon elongates (lingcod) - - 3 0.04 48 0.75

Hemilepidotus hemilepidotus (red irish lord) - - 5 0.07 25 0.41

Artedius notospilotus (bony head sculpin) - - 3 0.04 - -

Enophrys bison (buffalo sculpin) - - 4 0.06 8 0.12

Scorpaenichthys marmoratus (cabezon) 36 1.10 67 0.94 94 0.97

Artedius fenestralis (padded sculpin) - - 1 0.01 - -

Table 3. Fish caught in Humboldt Bay, California from June 2006 to August 2008. Percent equals % for a total given year. (continued). 2006 2007 2008

Species (Common name) # % # % # % Leptocottus armatus (Pacific staghorn sculpin) 75 2.28 163 2.29 44 0.73

Cottid spp. - - - - 1 0.02

Blepsias cirrhosus (silverspotted sculpin) - - - - 1 0.02

Liparis rutteri (ringtail snailfish) - - 1 0.01 - -

Liparid spp. - - - - 5 0.07

Icicthys lockintoni (medusafish) 1 0.03 - - - -

Amphistichus rhodoterus (redtail surfperch) - - 6 0.08 - -

Cymatogaster aggregata (shiner surfperch) 153 4.66 1329 18.70 763 10.68

Embiotoca lateralis (striped surfperch) 205 6.24 95 1.34 169 1.60

Hyperprosopon argenteum (walleye surfperch) 17 0.52 10 0.14 7 0.10

Phanerodon furcatus (white surfperch) 5 0.15 29 0.41 14 0.15

Rhacochilus vacca (pile surfperch) 4 0.12 5 0.07 5 0.09

Pholis ornata (saddleback gunnel) 74 2.25 180 2.53 57 0.82

Apodichthys flavidus (penpoint gunnel) 14 0.43 8 0.11 43 0.43

Gibbonsia montereyensis (crevice kelpfish) 1 0.03 1 0.01 - -

Clevelandia ios (arrow goby) - - 5 0.07 6 0.10

Citharichthys stigmaeus (speckled sanddab) - - 18 0.25 24 0.34

Paralichthys californicus (California halibut) - - 2 0.03 - -

Platichthys stellatus (starry flounder) 12 0.37 12 0.17 20 0.32

Parophrys vetulus (English sole) 29 0.883 161 2.27 307 4.46

Pleuronectid spp. 4 0.12 - - 1 0.02

Total Fish Caught 3283 7107 5871

Table 4. Fish species caught at each sample location in Humboldt Bay, California from June 2006 to August 2008. X indicates capture of at least one specimen. Indian Family, Scientific name, (Common name) Samoa Island North Bay

Myliobatidae

Myliobatis californica (bat ray) X X

Clupiedae

Clupea pallasii (Pacific herring) X X

Engraulidae

Engraulis mordax (northern anchovy) X X X

Osmeridae

Hypomesus pretiosus (surf smelt) X X X

Spirinchus starski (night smelt) X

Osmerid spp. X X X

Gadidae

Gadid spp. X

Batrachoididae

Porichthys notatus (plainfin midshipmen) X

Atherinidae

Atherinops affinis (topsmelt) X X X

Gasterosteidae

Gasterosteus aculeatus (three spine stickleback) X X X

Aulorhynchidae

Aulorhynchus flavidus (tubesnout) X X X

Syngnathidae

Syngnathus leptorhynchus (bay pipefish) X X X

Table 4. Fish species caught at each sample location in Humboldt Bay, California from June 2006 to August 2008. X indicates capture of at least one specimen. (continued). Indian Family, Scientific name, (Common name) Samoa Island North Bay

Scorpaenidae

Sebastes melanops (black rockfish) X X X

S. paucispinis (bocaccio) X

S. caurinus (copper rockfish) X X

Hexagrammidae

Hexagrammos decagrammus (kelp greenling) X X X

Ophiodon elongates (lingcod) X X

Cottidae

Hemilepidotus hemilepidotus (red irish lord) X X

Artedius notospilotus (bony head sculpin) X

Enophrys bison (buffalo sculpin) X X

Scorpaenichthys marmoratus (cabezon) X X X

Artedius fenestralis (padded sculpin) X

Leptocottus armatus (Pacific staghorn sculpin) X X X

Blepsias cirrhosus (silverspotted sculpin) X

Cottid spp. X

Liparidae

Liparis rutteri (ringtail snailfish) X

Liparid spp. X

Centrolophidae

Icicthys lockintoni (medusafish) X

Embiotocidae

Amphistichus rhodoterus (redtail surfperch) X

Table 4. Fish species caught at each sample location in Humboldt Bay, California from June 2006 to August 2008. X indicates capture of at least one specimen. (continued).

Indian Family, Scientific name, (Common name) Samoa Island North Bay

Cymatogaster aggregata (shiner surfperch) X X X

Hyperprosopon ellipticum (silver surfperch) X

Embiotoca lateralis (striped surfperch) X X X

Hyperprosopon argenteum (walleye surfperch) X X X

Phanerodon furcatus (white surfperch) X X X

Rhacochilus vacca (pile surfperch) X X X

Pholidae

Pholis ornata (saddleback gunnel) X X X

Apodichthys flavidus (penpoint gunnel) X X X

Pholid spp. X

Clinidae

Gibbonsia montereyensis (crevice kelpfish) X X

Gobiidae

Clevelandia ios (arrow goby) X X

Paralichthyidae

Citharichthys stigmaeus (speckled sanddab) X X

Paralichthys californicus (California halibut) X

Pleuronectidae

Platichthys stellatus (starry flounder) X X X

Parophrys vetulus (English sole) X X X

Pleuronectid spp. X

Number of Families 16 18 17

Number of Species 27 35 32

Table 5. Seasonal abundances of the 12 most abundant fish species caught in Humboldt Bay, California from June 2006 to August 2008.

No. Species Spring Summer Fall Winter % Total Rank caught Hypomesus pretiosus 135 202 12 70 419 2.6 10

Osmerid spp. 80 50 676 1171 1977 9.3 4

Gasterosteus aculeatus 486 561 210 20 1277 7.8 6

Aulorhynchus favidus 567 246 914 1015 2742 16.7 2

Syngnathus leptorhynchus 241 848 2298 267 3654 22.4 1

Sebastes melanops 1 1501 10 0 1512 9.3 5

Hexagrammos decagrammus 293 180 5 9 487 3.0 8

Leptocottus armatus 32 59 155 95 341 1.7 11

Cymatogaster aggregata 56 1995 183 12 2246 13.8 3

Embiotoca lateralis 34 413 8 14 469 2.9 9

Pholis ornata 23 247 29 12 311 1.9 12

Parophrys vetulus 284 135 26 55 500 2.9 7 Total 2232 6437 4526 2740 15935 94.3

Table 6. Lengths (mm) of the 12 most abundant fish species caught in Humboldt Bay, California from June 2006 to August 2008. Largest fish lengths are noted in bold. Samoa Indian Island North Bay Total length Total length Total length (mm) (mm) (mm) Species No. Avg. (range) No. Avg. (range) No. Avg. (range) Hypomesus pretiosus 215 65.0 46-92 81 64.2 45-87 121 73.0 47-147 Osmerid spp. 828 50.1 31-75 202 51.2 45-56 486 47.3 36-70 Gasterosteus aculeatus 667 61.2 30-135 49 46.2 30-71 559 57.7 22-78 Aulorhynchus favidus 2562 118.2 42-307 63 107.4 70-168 97 119.2 39-174 Syngnathus leptorhynchus 2534 172.8 55-306 353 164.8 40-360 752 172.3 67-322 Sebastes melanops 1502 61.6 46-86 - - - 10 56.2 50-57 Hexagrammos 483 124.5 45-349 1 103 - 3 56 55-57 decagrammus Leptocottus armatus 19 151.5 45-240 80 77.7 21-173 183 69.4 21-191 Cymatogaster aggregata 508 86.2 33-144 92 77 34-126 1645 78.3 34-125 Embiotoca lateralis 408 154.8 62-754 46 72.4 44-87 15 144.5 62-282 Pholis ornata 158 107.0 40-194 26 107.9 57-143 127 89.8 42-162 Parophrys vetulus 215 90.9 23-200 21 73.4 40-133 260 74.9 23-137 Total fish caught 10,747 1,101 4,413

Syngnathus leptorhynchus abundances were consistently present, but peaked during particular seasons or at particular locations. Sebastes melanops, Cymatogaster aggregata,

Embiotoca lateralis, Pholis ornata, Hypomesus pretiosus and Gasterosteus aculeatus abundances were highest during the summer. Osmerid spp. and Aulorhynchus flavidus abundances were highest in winter. Syngnathus leptorhynchus, Leptocottus armatus and

Osmerid spp. abundances were highest in fall. Hypomesus pretiosus, Osmerid spp.,

Gasterosteus aculeatus, Aulorhynchus flavidus, Syngnathus leptorhynchus, Sebastes melanops, Embiotoca lateralis, Hexagrammos decagrammus, Pholis ornata were more abundant at Samoa. Leptocottus armatus, Cymatogaster aggregata and Parophrys vetulus were more abundant in North Bay. Overall, the largest specimens of each species were caught at Samoa (Table 6).

During this study physicochemical and climatic measurements varied among sites and between years (Tables 7, 8). Bay water temperature ranged from 8.2 to 21°C. The

North Bay site marked both the upper and lower water temperature extremes throughout this study. Salinity ranged from 21.6 to 35.0 ppt. Dissolved oxygen readings ranged from

5.3 to 12.6 mg/L with the Samoa site showing the most extreme DO values. pH ranged from 7.3 to 8.1 and turbidity ranged from 3.3 to 39.4 ntu. Precipitation rate averaged

0.003 to 1.15 cm per day.

One-way Analysis of Variance between sites and between years showed sample site water temperatures to be significantly different between sites (p ≤ 0.05) (Table 9).

Despite the narrow range in pH readings, a significant annual difference (p ≤ 0.05) was observed. Yearly water temperature, salinity, and DO and sample location salinity, DO

Table 7. Yearly ranges of environmental variables, Humboldt Bay, California measured from June 2006 to August 2008.

Air Barometric Wind Avg. Daily Water Temperature Pressure speed Precipitation Temperature Salinity DO Turbidity Year (°C) (mmHg) (kmh) (mm) (°C) (ppt) (mg/L) pH (ntu) 2006 4.4 – 15.1 759 – 772 2.9 – 6.8 0.03-7.49 9.8 – 18.1 29.0 – 35.0 7.33 – 12.6 7.6 – 8.1 NA

2007 4.5 – 17.8 757 – 772 2.5 – 13.0 0.08-11.51 8.2 – 21.0 21.6 – 34.0 5.3 – 10.8 7.3 – 8.0 4.0 – 39.4

2008 7.0 – 17.8 759 – 770 4.0 – 11..5 0.05-9.27 9.5 – 18.5 23.9 – 34.2 7.4 – 10.9 7.6 – 8.1 3.3 – 18.8

Table 8. Ranges of environmental variables for each sample location, Humboldt Bay, California measured from June 2006 to August 2008. Air Barometric Wind Avg. Daily Water Temperature Pressure Speed Precipitation Temperature Salinity DO Turbidity Site (°C) (mmHg) (kmh) (mm) (°C) (ppt) (mg/L) pH (ntu) Samoa 4.4 – 17.8 757 – 772 2.5 – 13.0 0.03-11.51 9.0 – 17.3 21.6 – 35.0 5.3 – 12.6 7.5 – 8.1 3.5 – 39.4

Indian 4.4 – 15.1 759 – 772 6.5 – 11.2 0.03-11.51 9.1 – 18.1 22.2 – 34.0 7.3 – 10.3 7.3 – 8.1 NA

North Bay 4.5 – 17.8 757 – 770 2.5 – 13.0 0.05-9.27 8.2 – 21.0 23.9 – 34.2 6.6 – 10.4 7.6 – 8.1 3.3 – 26.7

Table 9. ANOVA results of fish abundances and each physicochemical parameter in Humboldt Bay, California measured from June 2006 to August 2008. * indicates a significant difference at p≤0.05.

Physicochemical Parameters Fish Parameters

Temperature Salinity DO Density Shannon-Weiner Parameters Tested (°C) (ppt) (mg/L) pH Abundance (CPUE) (H’) Richness

All Sample Locations p = 0.02* p = 0.60 p = 0.52 p = 0.22 p = 0.01* p = 0.01* p = 0.73 p = 0.03*

Samoa and North Bay Locations only p = 0.01* p = 0.44 p = 0.30 p = 0.21 p = 0.06 p = 0.06 p = 0.44 p = 0.05*

All Sample Years p = 0.95 p = 0.28 p = 0.48 p = 0.03* p = 0.38 p = 0.38 p = 0.07 p = 0.03*

2007 and 2008 only p = 0.82 p = 0.20 p = 0.28 p = 0.03* p = 0.86 p = 0.86 p = 0.02* p = 0.02*

39 and pH were not significantly different.

A significant difference (p ≤ 0.05) in abundance, density, species richness and water temperature among sites was also noted. Annually, species richness and diversity were significantly different, with both species richness and diversity being greatest in

2008. Yearly fish abundance and density and sample location diversity were not significantly different. The top 12 fish species were present in a variety of physicochemical conditions. The most abundant fish were highly tolerant of the fluctuating physicochemical characteristics of Humboldt Bay (Table 10).

Correlation Matrix

A correlation matrix was utilized to explore the relationships between physicochemical parameters (Table 11). All climatic variables, excluding wind speed had high correlations. Barometric pressure and average daily precipitation were significantly inversely correlated with air temperature. Average daily precipitation and barometric pressure were positively correlated. There were some correlations between climatic and aquatic variables. Water temperature showed significant positive correlation with air temperature, but a significant inverse correlation with barometric pressure. Salinity and air temperature were positively correlated, while salinity and average daily precipitation were significantly inversely correlated. Turbidity does not appear to be correlated with average daily rainfall. Average daily wind speed did not have an effect on dissolved oxygen, water temperature or turbidity. Compared to climatic variables, the aquatic variables did not show strong associations.

Table 10. Range of physicochemical parameters for the 12 most abundant fish species caught from June 2006 to August 2008, Humboldt Bay, California. Temperature Turbidity Wind Spd Species (°C) Salinity (ppt) DO (mg/L) pH (ntu) (kmh) Precip (mm) Osmerid spp. 8.24 - 14.50 23.9 - 33.77 7.61 - 10.92 7.58 – 8.09 3.3 – 18.8 2.5 – 11.5 0.30-9.3

Syngnathus leptorhynchus 8.24 - 20.96 21.55 - 35 5.31 - 12.64 7.32 - 8.12 3.3 - 39.35 2.5 – 13.0 0.03-11.5

Embiatoca lateralis 9.11 - 17.33 21.55 - 35 5.31 - 12.64 7.52 - 8.06 4.0 - 39.35 2.9 – 13.0 0.03-11.5

Cymatogaster aggregata 8.24 - 20.96 21.55 - 35 5.31 - 12.64 7.52 - 8.12 3.45 - 39.35 2.5 – 13.0 0.03-11.5

Aulorhynchus flavidus 8.24 - 20.96 21.55 - 35 5.31 - 12.64 7.32 - 8.12 3.3 - 39.35 2.5 – 13.0 0.03-11.5

Pholis ornata 8.98 - 20.96 21.55 - 35 5.31 - 10.83 7.52 - 8.12 3.45 - 39.35 2.5 – 13.0 0.03-11.5

Gasterosteus aculeatus 8.24 - 20.96 22.15 - 35 5.31 - 12.64 7.32 - 8.12 3.3 - 39.35 2.5 – 13.0 0.03-11.5

Leptocottus armatus 8.24 - 20.96 21.55 - 35 6.62 – 10.72 7.32 - 8.00 3.3 – 24.8 2.5 – 13.0 0.03-11.5

Hypomesus pretiosus 8.24 - 18.46 21.55 - 35 6.62 – 10.92 7.32 - 8.06 3.45 – 18.8 2.5 – 13.0 0.05-11.5

Hexagrammos decagrammus 8.98 - 17.33 21.55 - 35 7.05 - 12.64 7.55 -8.09 3.45 – 26.65 2.5 – 13.0 0.30-11.5

Parophrys vetulus 8.24 - 19.41 21.55 - 34.18 6.62 - 12.64 7.32 - 8.09 3.2 – 20.85 2.5 – 13.0 0.03-11.5

Sebastes melanops 12.32 – 20.96 33.32 - 35 5.31 – 10.72 7.52 - 8.03 4.0 - 39.35 4.0 – 13.0 0.05-0.1

40 40

Table 11. Pearson Correlation Coefficients of climatic and physicochemical parameters, Humboldt Bay, California from June 2006 to August 2008. Bold values indicate significant results (p≤0.05). Air BP Avg. Daily Avg. Daily Water Avg. Temp. Wind Spd. Precip. Temp. Salinity DO Depth pH Turbidity

Air Temp. 1 -0.687 0.295 -0.709 0.798 0.578 -0.243 0.248 -0.012 0.111

BP -0.687 1 -0.329 0.539 -0.582 -0.399 0.251 -0.453 0.005 -0.334

Avg. Wind Speed 0.295 -0.329 1 -0.134 0.160 -0.148 -0.194 -0.132 -0.145 0.059

Avg. Daily Precip. -0.709 0.539 -0.134 1 -0.596 -0.816 0.453 -0.254 -0.148 -0.137

Water Temp. 0.798 -0.582 0.160 -0.596 1 0.519 -0.167 0.244 0.203 0.216

Salinity 0.578 -0.399 -0.148 -0.816 0.519 1 -0.265 0.504 0.140 0.243

DO -0.243 0.251 -0.194 0.453 -0.167 -0.265 1 -0.350 0.387 -0.433

Avg. Depth 0.248 -0.453 -0.132 -0.254 0.244 0.504 -0.350 1 -0.276 0.279 pH -0.012 0.005 -0.145 -0.148 0.203 0.140 0.387 -0.276 1 -0.407

Turbidity 0.111 -0.334 0.059 -0.137 0.216 0.243 -0.433 0.279 -0.407 1

41 41

Fish Associations with Environmental Parameters using Canonical Correspondence Analysis

After Principle Components Analysis, Group 1 variables included air temperature, water temperature, precipitation, DO, pH, and salinity. Group 2 variables included air temperature, water temperature, wind speed, pH, turbidity, salinity, and precipitation.

Air temperature had a high Pearson correlation coefficient with water temperature

(0.80) and was consequently dropped from the analysis (Table 11). Since water temperature directly affects fish populations it was retained for further analyses.

Precipitation and salinity also had high Pearson correlation coefficients (0.82)

(Table 11). Both variables, particularly salinity, were considered to potentially have an affect on fish populations. Precipitation appears to be a good surrogate variable to reflect the varying magnitude of freshwater input into Humboldt Bay. Therefore, salinity and precipitation were both included, but run through the Canonical Correspondence Analysis separately.

In both Group 1 Canonical Correspondence Analysis (Figures 7, 8) and Group 2

Canonical Correspondence Analysis (Figures 9, 10) the most important environmental characteristics were water temperature, pH, salinity and precipitation. In the Group 2 ordination plot (precipitation removed), water temperature, wind speed, turbidity and salinity vectors are correlated as demonstrated by the close proximity of the vectors. In the Group 2 ordination plot (salinity removed), turbidity, wind speed and water temperature are correlated.

Figure 7. Canonical Correspondence Analysis on Group 1 environmental parameters with salinity (precipitation removed) and the top 12 fish species captured in Humboldt Bay, California in the summer, winter, fall and spring from 2007 to 2008. (The species are listed by the first letter of the genus and the first three letters of the specific epithet, they include: Hypomesus pretiosus, Gasterosteus aculeatus, Aulorhynchus flavidus, Syngnathus leptorhynchus, Sebastes melanops, Hexagrammos decagrammus, Leptocottus armatus, Cymatogaster aggregata, Embiotoca lateralis, Pholis ornata, Parophrys vetulus and Osmerid spp. = Osmspp.)

Figure 8. Canonical Correspondence Analysis on Group 1 environmental parameters with precipitation (salinity removed) and the top 12 fish species captured in Humboldt Bay, California in the summer, winter, fall and spring from 2007 to 2008. (The species are listed by the first letter of the genus and the first three letters of the specific epithet, they include: Hypomesus pretiosus, Gasterosteus aculeatus, Aulorhynchus flavidus, Syngnathus leptorhynchus, Sebastes melanops, Hexagrammos decagrammus, Leptocottus armatus, Cymatogaster aggregata, Embiotoca lateralis, Pholis ornata, Parophrys vetulus and Osmerid spp. = Osmspp.)

Figure 9. Canonical Correspondence Analysis on Group 2 environmental parameters with salinity (precipitation removed) and the top 12 fish species captured in Humboldt Bay, California in the summer, winter, fall and spring from 2007 to 2008. (The species are listed by the first letter of the genus and the first three letters of the specific epithet, they include: Hypomesus pretiosus, Gasterosteus aculeatus, Aulorhynchus flavidus, Syngnathus leptorhynchus, Sebastes melanops, Hexagrammos decagrammus, Leptocottus armatus, Cymatogaster aggregata, Embiotoca lateralis, Pholis ornata, Parophrys vetulus and Osmerid spp. = Osmspp.)

Figure 10. Canonical Correspondence Analysis on Group 2 environmental parameters with precipitation (salinity removed) and the top 12 fish species captured in Humboldt Bay, California in the summer, winter, fall and spring from 2007 to 2008. (The species are listed by the first letter of the genus and the first three letters of the specific epithet, they include: Hypomesus pretiosus, Gasterosteus aculeatus, Aulorhynchus flavidus, Syngnathus leptorhynchus, Sebastes melanops, Hexagrammos decagrammus, Leptocottus armatus, Cymatogaster aggregata, Embiotoca lateralis, Pholis ornata, Parophrys vetulus and Osmerid spp. = Osmspp.)

In the Canonical Correspondence Analysis runs the first and second axes explained the most variation and were therefore, the only axes shown. The first two axes in Group 1 and Group 2 explained greater than 81% of the total variation explained by all the axes together. Canonical Correspondence Analysis of Group 1 with precipitation and salinity removed, explained 81% and 83% of the variation respectively. Canonical

Correspondence Analysis of Group 2 with precipitation and salinity removed explained

81%, and 82% of the variation respectively. In Group 1, axis one explains the variation across the fish community related to water temperature and salinity (Figure 7) and water temperature and precipitation (Figure 8) shown by the parallel orientation of these vectors to axis one. In Group 2, axis one is related to water temperature, wind speed, turbidity and salinity (when precipitation is excluded, Figure 9) and water temperature, wind speed, turbidity and precipitation (when salinity is excluded, Figure 10). On axis two of

Group 1, pH and dissolved oxygen affect the variation in the fish community, while axis two of Group 2 fish distributions were affected by pH.

The Group 1 and 2 Canonical Correspondence Analysis ordination plots illustrate the structure of the fish community within their physical environment. In Group 1,

Gasterosteus aculeatus is not closely associated with any of the environmental variables analyzed (Figure 7). Sebastes melanops has a positive association with salinity while

Leptocottus armatus, Parophrys vetulus and Osmerid spp. have a negative association with salinity (Figure 7). Parophrys vetulus and Cymatogaster aggregata are mildly associated with warmer water temperatures and Syngnathus leptorhynchus, Hypomesus pretiosus, Aulorhynchus flavidus, and Hexagrammos decagrammus aggregate at cooler

48 water temperatures. Syngnathus leptorhynchus, Hypomesus pretiosus, Hexagrammos decagrammus and Aulorhynchus flavidus occur at lower pH levels (Figures 7, 8). The

Sebastes melanops, and Embiotoca lateralis are loosely associated with negative DO

(Figures 7, 8). Finally, Osmerid spp. have a mild and Parophrys vetulus have a strong connection with wetter climate conditions, while Sebastes melanops are mildly associated with dryer conditions (Figure 8). Based on proximity to one another in the Group 1 ordination diagrams, Syngnathus leptorhynchus, Hexagrammos decagrammus,

Hypomesus pretiosus, Gasterosteus aculeatus and Aulorhynchus flavidus seem to relate similarly to the physical parameters studied. Cymatogaster aggregata and Pholis ornata orient similarly at the positive end of the pH and water temperature gradients. Parophrys vetulus and Leptocottus armatus both accumulate at the positive end of the pH, DO, and precipitation gradient.

Group 2 plots indicate water temperature, wind speed and turbidity have positive associations with Pholis ornata and Cymatogaster aggregata (Figures 9, 10). Syngnathus leptorhynchus, Osmerid spp., Parophrys vetulus and Leptocottus armatus fall at the negative end of the salinity gradient, while Sebastes melanops and Embiotoca lateralis occur in more saline waters (Figure 9). Gasterosteus aculeatus, Parophrys vetulus and

Aulorhynchus flavidus loosely associate with the negative end of the turbidity, water temperature, wind speed gradients. Pholis ornata, Cymatogaster aggregata, Syngnathus leptorhynchus and Leptocottus armatus have a positive association with the pH gradient.

Gasterosteus aculeatus, Aulorhynchus flavidus, Hexagrammos decagrammus and

Hypomesus pretiosus occur at lower end of the pH spectrum. On the precipitation

49 gradient, Osmerid spp. associate with wetter conditions while Sebastes melanops and

Embiotoca lateralis associate with dryer conditions (Figure 10). In the Group 2 plots, fish community associations are loose, demonstrated by the lack of any close aggregations of fish species in these figures. Leptocottus armatus, Parophrys vetulus and Syngnathus leptorhynchus aggregate at the positive end of the pH and precipitation spectrums.

Gasterosteus aculeatus, Aulorhynchus flavidus and Parophrys vetulus congregate negatively with turbidity, wind speed and water temperature (Figure 10). Gasterosteus aculeatus, Aulorhynchus flavidus, Hypomesus pretiosus and Hexagrammos decagrammus loosely accumulate together at the negative end of the pH, wind speed, and water temperature gradients (Figure 9).

Empirical Cumulative Distribution Functions (cdf) to Test the Strength of Fish and Environmental Associations

The cumulative frequency distributions calculated using pooled data show significant fish and environmental connections (Figures 11-21). In the pooled data,

Cymatogaster aggregata and Gasterosteus aculeatus displayed the strongest associations with their environment. Cymatogaster aggregata showed a very strong relationship with warmer water temperatures, with numbers accumulating just above 14°C (Figure 11).

Eighty percent of Gasterosteus aculeatus accumulate at daily rates of rainfall of less than or equal to 1mm (Figure 12). Annually Cymatogaster aggregata had very strong associations with warmer water temperatures in 2007 and only a mild association to 2008 water temperatures (Figure 13). Gasterosteus aculeatus occurred most frequently at the

1.2

1.0 Temperature Cymatogaster aggregata

0.8

0.6

0.4

0.2 Cumulative FrequencyCumulative p  0.02

0.0

6 8 10 12 14 16 18 20 22 Temperature (°C)

Figure 11. Cumulative distribution function of water temperature relationship for Cymatogaster aggregata in Humboldt Bay, California from June 2006 to August 2008. The p-value represents the probability of attaining the Kolmogorov- Smirnov test statistic in a randomized distribution under the null hypothesis.

1.2

1.0 p  0.05

0.8

0.6

0.4

0.2

Cumulative Frequency Cumulative Precipitation Gasterosteus aculeatus

0.0

0 2 4 6 8 10 12 Precipitation (mm)

Figure 12. Cumulative distribution function of precipitation relationship for Gasterosteus aculeatus in Humboldt Bay, California from April 2006 to August 2008. The p value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis.

1.2 Temperature 2007 Temperature 2008 1.0 C. aggregata 2007 C. aggregata 2008

0.8

0.6

0.4 p  0.02

0.2

Cumulative Frequency Cumulative

p  0.23 0.0

6 8 10 12 14 16 18 20 22 Temperature (°C)

Figure 13. Cumulative distribution function of water temperature relationships for Cymatogaster aggregata in Humboldt Bay, California from January 2007 to August 2008. The p-value represents the probability of attaining the Kolmogorov- Smirnov test statistic in a randomized distribution under the null hypothesis.

1.2

1.0

0.8

0.6 p  0.93 0.4 p  0.02

0.2

Cumulative Frequency Cumulative Temperature 2007 Temperature 2008 G. aculeatus 2007 0.0 G. aculeatus 2008

6 8 10 12 14 16 18 20 22 Temperature (°C)

Figure 14. Cumulative distribution function of water temperature relationships for Gasterosteus aculeatus in Humboldt Bay, California from January 2007 to August 2008. The p-value represents the probability of attaining the Kolmogorov- Smirnov test statistic in a randomized distribution under the null hypothesis.

1.2

1.0

p  0.47 0.8

0.6

0.4

Turbidity 2007 0.2 Cumulative Frequency Cumulative Turbidity 2008 p  0.05 Sebastes melanops 2007 0.0 Sebastes melanops 2008

0 10 20 30 40 50 Turbidity (ntu)

Figure 15. Cumulative distribution function of turbidity relationship for Sebastes melanops in Humboldt Bay, California from January 2007 to August 2008. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis.

1.2

1.0

p  0.49 0.8

0.6

0.4 Turbidity 2007 Cumulative Frequency Cumulative Turbidity 2008 0.2 Embiotoca lateralis 2007 p  0.03 Embiotoca lateralis 2008

0.0 0 10 20 30 40 50 Turbidity (ntu)

Figure 16. Cumulative distribution function of turbidity relationship for Cumulative distribution function of turbidity relationship for Embiotoca lateralis in Humboldt Bay, California from January 2007 to August 2008. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis.

1.2

p  0.03 1.0

0.8

0.6 p  0.02 0.4

0.2 Precipitation 2007

Cumulative Frequency Cumulative Sebastes melanops Pholis ornata 0.0

0 2 4 6 8 10 12 Precipitation (mm)

Figure 17. Cumulative distribution function of precipitation relationship for Sebastes melanops and Pholis ornata in Humboldt Bay, California from January to December 2007. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis.

1.2

p  0.48 1.0

p  0.07

0.8

0.6

Cumulative Frequency Cumulative Precipitation 2008 0.4 Sebastes melanops Pholis ornata

0.2 0 2 4 6 8 Precipitation (mm)

Figure 18. Cumulative distribution function of precipitation relationship for Sebastes melanops and Pholis ornata in Humboldt Bay, California from January to August 2008. The p-value represents the probability of attaining the Kolmogorov- Smirnov test statistic in a randomized distribution under the null hypothesis.

1.2

Dissolved Oxygen 2007 p  0.95 1.0 Dissolved Oxygen 2008 Osmerid spp. 2007 Osmerid spp. 2008 0.8

0.6

p  0.00 0.4

0.2

Cumulative Distribution Cumulative

0.0

4 5 6 7 8 9 10 11 Dissolved Oxygen (mg/L)

Figure 19. Cumulative distribution function of dissolved oxygen relationship for Osmerid spp. in Humboldt Bay, California from January 2007 to August 2008. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis.

1.2 Temp. Samoa Temp. North Bay 1.0 Cagr Samoa Cagr North Bay 0.8

0.6

0.4 p  0.02 0.2

Cumulative Frequency Cumulative

0.0 p  0.07

6 8 10 12 14 16 18 20 22 Temperature (°C)

Figure 20. Cumulative distribution function of the Samoa and North Bay sample sites water temperature relationship for Cymatogaster aggregata (Cagr in figure) in Humboldt Bay, California from June 2006 to August 2008. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis.

1.2

1.0

0.8 p  0.88

0.6

0.4 p  0.04 0.2

Cumulative Frequency Cumulative Temp. Samoa Temp. North Bay 0.0 P. ornata Samoa P. ornata North Bay

6 8 10 12 14 16 18 20 22 Temperature (°C)

Figure 21. Cumulative distribution function of the Samoa and North Bay sample sites water temperature relationship for Pholis ornata (Porn in figure) in Humboldt Bay, California from June 2006 to August 2008. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis.

61 mid range water temperatures. In 2007, Gasterosteus aculeatus showed no relationship to water to mid range water temperatures, whereas in 2008 they did (Figure 14). In 2008, both Sebastes melanops and Embiotoca lateralis exhibited strong associations with lower turbidity levels (Figures 15 and 16). In 2007, both Sebastes melanops and Pholis ornata accumulate predominantly at lower levels of rainfall (Figure 17). However, in 2008

Sebastes melanops showed no relationship with precipitation, while Pholis ornata exhibited a strong association with reduced rainfall (Figure 18). In 2008, Osmerid spp. showed a strong connection with dissolved oxygen, with fish only accumulating at below

9.5 mg/L (Figure 19). In 2007 there was no relationship between Osmerid spp. and DO.

In the sample location break down, Samoa had generally cooler water temperatures than

North Bay (Table 8). Cymatogaster aggregata showed a strong association with water temperature at both locations, but was more pronounced at the Samoa location (Figure

20). In contrast, Pholis ornata occurred most often in the warmer North Bay water temperatures with no association to water temperature at Samoa (Figure 21).

Kolmogorov-Smirnov relationships are summarized in Table 12. Mild to moderate associations found between the 12 most abundant fish and physical parameters are provided in Appendices A through V.

Several fish species showed seasonal abundances (Figures 22-26). Cymatogaster aggregata, Pholis ornata, Embiotoca lateralis, and Sebastes melanops all showed peaks in summer at each sample location. Sebastes melanops abundances were far greater in summer 2008 than in other years. Gasterosteus aculeatus abundances also peaked in summer, but were greater in 2007 than in other years and showed a double peak for the

Species Temperature Salinity DO PH Turbidity Wind Speed Precipitation H. pretiosus 0.88 0.95 0.88 0.69 0.72 0.92 0.80 2007 0.69 *0.25 0.95 0.31 0.42 0.89 0.34 2008 0.97 0.94 0.46 0.67 **0.18 1.00 0.47 Samoa 0.99 0.72 0.41 0.49 *0.28 - - North Bay 0.97 0.65 0.94 1.00 0.73 - - Osmerid spp. **0.14 **0.14 0.75 0.99 0.48 0.82 **0.07 2007 *0.26 0.32 0.95 0.64 0.65 0.76 0.42 2008 *0.29 0.31 ***0.00 0.81 0.60 1.00 **0.17 Samoa 0.45 **0.13 0.58 0.90 0.88 - - North Bay **0.18 0.35 0.86 1.00 0.67 - - G. aculeatus 0.86 0.90 0.79 1.00 0.96 0.95 **0.05 2007 0.93 0.72 0.78 0.96 0.93 0.97 ***0.02 2008 ***0.02 0.58 0.33 0.95 0.65 0.98 *0.25 Samoa 0.75 0.82 0.63 0.64 0.66 - - North Bay 0.33 0.71 0.61 0.88 0.75 - - A. flavidus **0.16 0.85 0.58 1.00 0.88 0.99 0.37 2007 0.85 0.93 0.95 0.98 0.38 0.98 0.75 2008 **0.12 0.71 0.39 0.87 0.61 0.96 0.37 Samoa 0.34 0.75 0.63 0.99 0.71 - - North Bay 0.39 0.41 0.96 0.90 0.78 - -

Table 12. Cumulative distribution function of the Kolmogorov-Smirnov test statistic summary of pooled (first row), annual and sample location fish catch data from June 2006 to August 2008. *** = very strong, ** = moderate, and * = mild relationships with physical parameters. (continued). Species Temperature Salinity DO PH Turbidity Wind Speed Precipitation S. leptorhynchus 0.51 0.92 0.97 1.00 0.75 0.89 0.80 2007 0.39 1.00 0.91 1.00 0.85 0.57 0.50 2008 0.38 0.98 0.86 *0.23 0.97 0.91 0.47 Samoa 0.50 0.99 0.82 0.97 0.87 - - North Bay **0.14 0.71 0.60 0.53 *0.24 - - S. melanops 0.52 0.74 0.53 0.58 0.38 0.62 0.43 2007 *0.23 0.41 0.53 0.36 0.47 0.90 ***0.03 2008 0.67 0.58 0.36 0.37 ***0.05 1.00 0.48 Samoa 0.41 0.66 0.53 0.56 **0.18 - - North Bay 0.38 0.37 0.74 0.35 0.80 - - H. decagrammus 0.85 0.91 0.97 0.99 0.44 0.84 *0.27 2007 0.64 0.97 1.00 0.59 0.97 0.97 0.95 2008 0.51 0.88 0.80 1.00 0.39 0.51 *0.20 Samoa 0.76 0.89 0.97 0.91 0.35 - - North Bay 0.40 0.31 0.56 0.80 0.45 - - L. armatus 0.43 0.65 0.94 1.00 0.82 0.88 0.58 2007 0.72 0.46 0.94 0.41 0.71 0.65 0.60 2008 0.70 **0.09 0.74 0.85 0.65 0.62 0.32 Samoa 0.59 *0.25 0.57 0.93 0.68 - - North Bay 0.49 0.71 0.96 0.92 0.66 - -

Table 12. Cumulative distribution function of the Kolmogorov-Smirnov test statistic summary of pooled (first row), annual and sample location fish catch data from June 2006 to August 2008. *** = very strong, ** = moderate, and * = mild relationships with physical parameters. (continued). Species Temperature Salinity DO PH Turbidity Wind Speed Precipitation C. aggregata ***0.02 0.53 0.96 0.38 0.60 0.65 **0.15 2007 ***0.02 0.63 0.88 *0.29 *0.22 0.73 0.30 2008 *0.23 *0.27 0.85 0.38 0.93 1.00 0.31 Samoa ***0.02 0.54 0.72 0.46 0.68 - - North Bay **0.07 **0.18 0.88 *0.22 0.75 - - E. lateralis 0.92 0.34 0.82 0.74 0.44 0.88 **0.14 2007 0.95 0.68 0.98 0.77 0.49 0.96 0.49 2008 0.61 0.65 0.39 0.46 ***0.03 1.00 **0.15 Samoa 0.82 0.40 0.63 0.63 **0.11 - - North Bay 0.41 0.71 0.44 0.87 *0.20 - - P. ornata **0.16 0.81 0.99 1.00 0.87 1.00 **0.18 2007 0.40 0.76 0.90 0.56 0.85 0.96 **0.16 2008 *0.20 0.84 **0.11 0.61 0.88 0.86 **0.07 Samoa 0.88 0.79 0.91 0.98 0.47 - - North Bay ***0.04 0.57 0.89 0.87 0.41 - - P. vetulus 0.86 1.00 0.94 0.99 0.96 0.91 0.62 2007 0.78 0.93 0.28 0.99 0.93 0.95 0.41 2008 0.67 0.93 1.00 0.88 0.85 0.91 0.43 Samoa 0.96 1.00 0.93 0.92 0.68 - - North Bay 0.93 0.77 0.76 0.93 0.90 - -

800

Samoa Indian Island 600 North Bay

Abundance 400

200

Cymatogaster aggregata Cymatogaster

Jun08

Jul 06 Jul 07 Jul 08

Jan 07 Jan 08

Jun 06 Jun 07

Oct 06 Oct 07 Oct

Feb 07 Feb 08

Apr 07 Apr 08

Dec 06 Dec 07 Dec

Mar 07 Mar 08

Aug 06 Nov 06 Aug 07 Nov 07 Aug 08

Sept 06 Sept 07

May 07 May 08

Figure 22. Cymatogaster aggregata abundances in Humboldt Bay, California from June 2006 to August 2008.

Samoa 50 Indian Island North Bay 40

Abundance

Pholis ornata

Jun08

Jul 06 Jul 07 Jul 08

Jan 07 Jan 08

Jun 06 Jun 07

Oct 06 Oct 07 Oct

Feb 07 Feb 08 Feb

Apr 07 Apr 08 Apr

Dec 06 Dec 07 Dec

Mar 07 Mar 08 Mar

Aug 06 Aug 06 Nov 07 Aug 07 Nov 08 Aug

Sept 06 Sept 07

May 07 May 08 May

Figure 23. Pholis ornata abundances in Humboldt Bay, California from June 2006 to August 2008.

250

Samoa 200 Indian Island North Bay

150

Abundance

100

Gasterosteus aculeatus Gasterosteus

Jun08

Jul 06 Jul 07 Jul 08

Jan 07 Jan 08

Jun 06 Jun 07

Oct 06 Oct 07 Oct

Feb 07 Feb 08

Apr 07 Apr 08

Dec 06 Dec 07 Dec

Mar 07 Mar 08

Aug 06 Nov 06 Aug 07 Nov 07 Aug 08

Sept 06 Sept 07

May 07 May 08

Figure 24. Gasterosteus aculeatus abundances in Humboldt Bay, California from June 2006 to August 2008.

120

Samoa 100 Indian Island North Bay 80

Abundance 60

Embiotoca lateralis 0

Jun08

Jul 06 Jul 07 Jul 08

Jan 07 Jan 08

Jun 06 Jun 07

Oct 06 Oct 07 Oct

Feb 07 Feb 08

Apr 07 Apr 08

Dec 06 Dec 07 Dec

Mar 07 Mar 08

Aug 06 Nov 06 Aug 07 Nov 07 Aug 08

Sept 06 Sept 07

May 07 May 08

Figure 25. Embiotoca lateralis abundances in Humboldt Bay, California from June 2006 to August 2008.

1200

1000 Samoa North Bay 800

Abundance 600

400

200

Sebastes melanops Sebastes 0

Jun08

Jul 06 Jul 07 Jul 08

Jan 07 Jan 08

Jun 06 Jun 07

Oct 06 Oct 07 Oct

Feb 07 Feb 08 Feb

Apr 07 Apr 08 Apr

Dec 06 Dec 07 Dec

Mar 07 Mar 08 Mar

Aug 06 Aug 06 Nov 07 Aug 07 Nov 08 Aug

Sept 06 Sept 07

May 07 May 08 May

Figure 26. Sebastes melanops abundances in Humboldt Bay, California from June 2006 to August 2008.

North Bay sampling location. Juvenile and adult abundances at the Samoa and North Bay sample locations showed seasonal peaks (Figures 27-34). Osmerid spp. and Sebastes melanops total lengths did not exhibit double peak histograms therefore no figures were constructed for these species. Sebastes melanops were exclusively juveniles.

Cymatogaster aggregata have generally similar abundances in North Bay annually, but the Samoa location had a larger peak in 2007 and Samoa appeared to have a lower number of juveniles. Pholis ornata abundances were greater at the Samoa site annually, particularly in 2007. The adult life stage was more abundant at the Samoa location.

Juvenile Gasterosteus aculeatus accumulated in higher numbers in North Bay during late summer. Life stage delineations were clear for this fish species. When the juvenile life stage was present, it was present in large numbers. Both sample locations had abundant adult Gasterosteus aculeatus, but North Bay had a greater juvenile presence in late summer. Finally, Embiotoca lateralis showed a clear preference for the Samoa site with some spillover of juveniles in North Bay in June.

140

Adult 120 Cymatogaster aggregata Juvenile Cymatogaster aggregata 100

Number of Individuals Samoa Individuals of Number 20

July 06 July 07 July 08

May 07 May 08 May

June06 June07 June08

April 07 April 08 April

March 07 March 08 March

August 06 August 07 August 08

January 07 January 08

October 06 October 07 October

February 07 February 08

December 06 December 07 December

November 06 November 07 November

September 07 September

Sepetember 06 Sepetember

Figure 27. Number of adult and juvenile Cymatogaster aggregata at Samoa site, Humboldt Bay, California from June 2006 to August 2008.

140

Adult 120 Cymatogaster aggregata Juvenile Cymatogaster aggregata 100

Number of Individuals North Bay Individuals of Number 20

July 06 July 07 July 08

May 07 May 08 May

June06 June07 June08

April 07 April 08 April

March 07 March 08 March

August 06 August 07 August 08

January 07 January 08

October 06 October 07 October

February 07 February 08

December 06 December 07 December

November 06 November 07 November

September 07 September

Sepetember 06 Sepetember

Figure 28. Number of adult and juvenile Cymatogaster aggregata at North Bay site, Humboldt Bay, California from June 2006 to August 2008.

Adult 30 Pholis ornata Juvenile Pholis ornata 25

Number of Individuals Samoa Individuals of Number 5

July 06 July 07 July 08

May 07 May 08 May

June 06 June 07 June 08 June

April 07 April 08 April

March 07 March 08 March

August 06 August 07 August 08 August

January 07 January 08 January

October 06 October 07 October

February 07 February 08 February

December 06 December 07 December

November 06 November 07 November

September 07 September

Sepetember 06 Sepetember

Figure 29. Number of adult and juvenile Pholis ornata at Samoa site, Humboldt Bay, California from June 2006 to August 2008.

Adult Pholis ornata 40 Juvenile Pholis ornata

Number of Individuals North Bay Individuals of Number

July 06 July 07 July 08

May 07 May 08 May

June 06 June 07 June 08 June

April 07 April 08 April

March 07 March 08 March

August 06 August 07 August 08 August

January 07 January 08 January

October 06 October 07 October

February 07 February 08 February

December 06 December 07 December

November 06 November 07 November

September 07 September

Sepetember 06 Sepetember

Figure 30. Number of adult and juvenile Pholis ornata at North Bay site, Humboldt Bay, California from June 2006 to August 2008.

120 Adult Gasterosteus aculeatus 100 Juvenile Gasterosteus aculeatus

Number of Individuals Samoa Individuals of Number 20

July 06 July 07 July 08

May 07 May 08 May

June06 June07 June08

April 07 April 08 April

March 07 March 08 March

August 06 August 07 August 08

January 07 January 08

October 06 October 07 October

February 07 February 08

December 06 December 07 December

November 06 November 07 November

September 07 September

Sepetember 06 Sepetember

Figure 31. Number of adult and juvenile Gasterosteus aculeatus at Samoa site, Humboldt Bay, California from June 2006 to August 2008.

Adult Gasterosteus aculeatus Juvenile 60 Gasterosteus aculeatus

Number of Individuals North Bay Individuals of Number

July 06 July 07 July 08

May 07 May 08 May

June 06 June 07 June 08 June

April 07 April 08 April

March 07 March 08 March

August 06 August 07 August 08 August

January 07 January 08 January

October 06 October 07 October

February 07 February 08 February

December 06 December 07 December

November 06 November 07 November

September 07 September

Sepetember 06 Sepetember

Figure 32. Number of adult and juvenile Gasterosteus aculeatus at North Bay site, Humboldt Bay, California from June 2006 to August 2008.

100

Adult Embiotoca lateralis 80 Juvenile Embiotoca lateralis

Number of Individuals Samoa Individuals of Number

July 06 July 07 July 08

May 07 May 08 May

June06 June07 June08

April 07 April 08 April

March 07 March 08 March

August 06 August 07 August 08

January 07 January 08

October 06 October 07 October

February 07 February 08

December 06 December 07 December

November 06 November 07 November

September 07 September

Sepetember 06 Sepetember

Figure 33. Number of adult and juvenile Embiotoca lateralis at Samoa site, Humboldt Bay, California from June 2006 to August 2008.

Adult Embiotoca lateralis 8 Juvenile Embiotoca lateralis

Number of Individuals North Bay Individuals of Number

July 06 July 07 July 08

May 07 May 08 May

June 06 June 07 June 08 June

April 07 April 08 April

March 07 March 08 March

August 06 August 07 August 08 August

January 07 January 08 January

October 06 October 07 October

February 07 February 08 February

December 06 December 07 December

November 06 November 07 November

September 07 September

Sepetember 06 Sepetember

Figure 34. Number of adult and juvenile Embiotoca lateralis at North Bay site, Humboldt Bay, California from March 2007 to August 2008.

Kriging of Environmental Parameters

Both summer and winter water temperatures exhibited similar spatial trends during the span of this study (Figures 35-39). Summer 2006 had a slightly higher water temperature than 2007 and 2008 (Figures 35-37). Offshore summer water temperatures stabilized between 11 and 12 °C. The distal ends of the bay were always much warmer and a hot to cold water temperature gradient from north and south bay to the bay entrance is illustrated in each surface. Offshore winter water temperatures were warmest during the 2006/2007 winter season (Figures 38, 39). Humboldt Bay winter water temperatures did not vary greatly. Winter 2006/2007 showed slightly warmer offshore water temperatures, while 2007/2008 had generally homogenous water temperatures both inshore and offshore although South Humboldt Bay appeared to have slightly cooler waters. Differences in range of water temperature gradients between the summer and winter surfaces are very apparent.

Using salinity data, Universal Kriged surfaces were created (Figures 40-44). With fewer data points, the salinity surfaces are less accurate than the water temperature

79 estimates and offshore data was unavailable (Grafen and Hails 2002). Compared to 2007, summers of 2006 and 2008 exhibited much more variation in salinity throughout the bay

(Figures 40-42). In general, salinity was lowest during winter (Figures 43, 44). The scale of salinity in winter of 2007/2008 was wide-ranging and therefore treated differently for display purposes. Summer had higher salinities than winter. In 2007 and 2008 salinities were mostly homogenous. In 2006 salinities were more diverse and seemed to show

Figure 35. Summer 2006 average water temperatures in Humboldt Bay, California and offshore Pacific Ocean waters from June to August 2006. Values derived from buoy, datasonde and sample data.

Figure 36. Summer 2007 average water temperatures in Humboldt Bay, California and offshore Pacific Ocean waters from June to August 2007. Values derived from buoy, datasonde and sample data.

Figure 37. Summer 2008 average water temperatures in Humboldt Bay, California and offshore Pacific Ocean waters from June to August 2008. Values derived from buoy, datasonde and sample data.

Figure 38. Winter 2006/2007 average water temperatures in Humboldt Bay, California and offshore Pacific Ocean waters from December 2006 to February 2007. Values derived from buoy, datasonde and sample data.

Figure 39. Winter 2007/2008 average water temperatures in Humboldt Bay, California and offshore Pacific Ocean waters from December 2007 to February 2008. Values derived from buoy, datasonde and sample data.

Figure 40. Summer 2006 average salinity (ppt) in Humboldt Bay, California from June to August 2006. Values derived from buoy, datasonde and sample data. Areas in black represent no data.

Figure 41. Summer 2007 average salinity (ppt) in Humboldt Bay, California from June to August 2007. Values derived from buoy, datasonde and sample data. Areas in black represent no data.

Figure 42. Summer 2008 average salinity (ppt) in Humboldt Bay, California from June to August 2008. Values derived from buoy, datasonde and sample data. Areas in black represent no data.

Figure 43. Winter 2006/2007 average salinity (ppt) in Humboldt Bay, California from December 2006 to February 2007. Values derived from buoy, datasonde and sample data. Areas in black represent no data.

Figure 44. Winter 2007/2008 average salinity (ppt) in Humboldt Bay, California from December 2007 to February 2008. Values derived from buoy, datasonde and sample data. Areas in black represent no data.

90 lower salinities corresponding with greater freshwater inputs. Winter salinities were more heterogeneous with more saline waters in central Humboldt Bay and less saline in surrounding areas. Winter of 2007/2008 salinities were generally lower than 2006/2007.

Physicochemical Comparisons

The North Bay and Samoa sampling locations had very different biotic and physicochemical results. North Bay generally had higher water temperature, lower salinity and lower dissolved oxygen levels (Figures 45-47). Average monthly precipitation could not be separated by sample location, but generally peaked in winter

(Figure 48). Turbidity followed an opposing pattern at each location through summer of

2007 (Figure 49). In general, turbidity readings were generally slightly higher in summer.

Between the two sample sites, Samoa yielded predominantly adult stages, while North

Bay supported intermittent juvenile influxes (Table 6, Figures 27-34). Of fish with the strongest physicochemical associations, Cymatogaster aggregata, Pholis ornata,

Gasterosteus aculeatus, Embiotoca lateralis and Sebastes melanops had higher juvenile

populations proportionately in summer. During seasons other than summer, adults were 90

either not present or present in smaller abundances than the Samoa location. The largest recorded total length for 10 of the 12 top fish species were found at the Samoa sampling location (Table 6).

22 Samoa 20 Indian Island North Bay 18

Temperature Temperature (°C) 10

Jan 2007 Jan 2008

Oct 2006 Oct 2007

Feb 2007 Feb 2008

Dec 2006 Dec 2007 Dec

Mar 2007 Mar 2008

July 2006 July 2007 July 2008

Aug 2006 Nov 2006 Aug 2007 Nov 2007 Aug 2008

Sept 2006 Sept 2007

May 2007 May 2008

June 2006 June 2007 June 2008

April 2007 April 2008

Figure 45. Mean monthly surface water temperature for Humboldt Bay, California from June 2006 to August 2008.

Salinity (ppt)

24 Samoa Indian Island 22 North Bay

Jan 2007 Jan 2008

Oct 2006 Oct 2007

Feb 2007 Feb 2008

Dec 2006 Dec 2007 Dec

Mar 2007 Mar 2008

July 2006 July 2007 July 2008

Aug 2006 Nov 2006 Aug 2007 Nov 2007 Aug 2008

Sept 2006 Sept 2007

May 2007 May 2008

June 2006 June 2007 June 2008

April 2007 April 2008

Figure 46. Salinity for Humboldt Bay, California from June 2006 to August 2008.

Dissolved Oxygen (mg/L) 6 Samoa North Bay

Jan 2007 Jan 2008

Oct 2006 Oct 2007

Feb 2007 Feb 2008

Dec 2006 Dec 2007 Dec

Mar 2007 Mar 2008

July 2006 July 2007 July 2008

Aug 2006 Nov 2006 Aug 2007 Nov 2007 Aug 2008

Sept 2006 Sept 2007

May 2007 May 2008

June 2006 June 2007 June 2008

April 2007 April 2008

Figure 47. Dissolved oxygen for Humboldt Bay, California from June 2006 to August 2008.

Average Monthly Precipitation (mm) Precipitation Monthly Average

Jan 2007 Jan 2008 Jan

Oct 2006 Oct 2007 Oct

Feb 2007 Feb 2008 Feb

Dec 2006 Dec 2007 Dec

Mar 2007 Mar 2008 Mar

July 2006 July 2007 July 2008

Aug 2006 Aug 2006 Nov 2007 Aug 2007 Nov 2008 Aug

Sept 2006 Sept 2007 Sept

May 2007 May 2008 May

June 2006 June 2007 June 2008 June

April 2007 April 2008 April

Figure 48. Average monthly precipitation on Humboldt Bay, California from June 2006 to August 2008.

Samoa 40 North Bay

Turbidity (ntu)

Jan 2007 Jan 2008

Oct 2006 Oct 2007

Feb 2007 Feb 2008

Dec 2006 Dec 2007 Dec

Mar 2007 Mar 2008

July 2006 July 2007 July 2008

Aug 2006 Nov 2006 Aug 2007 Nov 2007 Aug 2008

Sept 2006 Sept 2007

May 2007 May 2008

June 2006 June 2007 June 2008

April 2007 April 2008

Figure 49. Turbidity values for Humboldt Bay, California from June 2006 to August 2008.

DISCUSSION

My study related the estuarine fish fauna of Humboldt Bay to their physical surroundings. Temperature, precipitation rate, salinity and in some cases turbidity and dissolved oxygen, were noted to have strong influences on fish distributions in Humboldt

Bay. In several instances, particular values of physicochemical parameters were shown to influence fish abundances. These values could be important in predicting the effects of environmental fluctuations on future fish populations. However, determining the meaning of physiological optima for any species of fish for one particular physicochemical or climatic variable is complicated. Many factors, such as life history stage, seasonality, reproductive stage, migration and food availability could obscure these connections

(Wootton 1984, Paramo et al. 2003, Watanabe et al. 2008). Differences in the biota and physicochemical factors at each sample location made it possible to examine specific fish life history stages at habitat preferences.

Other researchers have found correlations with atmospheric precipitation similar to the correlations in this study (Figures 12, 17, 18, Table 12). Nezlin et al. (2004) found correlations between average weekly precipitation and salinity, described by the influence that surface water runoff has on salinity. They suggested freshwater input from one creek was the main seasonal determinant behind Santa Monica Bay salinity patterns.

They note the spatio-temporal variation of physicochemical parameters in Santa Monica

Bay were driven by meteorological factors including air temperature, wind, atmospheric

97 precipitation and El Nino-Southern Oscillation Cycle. Zooplankton diversity was found to change dramatically with atmospheric precipitation in a study done in a Portugal estuary (Primo et al. 2009). These findings in addition to the findings in this study suggest food availability or preferences play a role in the Humboldt Bay precipitation rate/fish species correlations.

Cymatogaster aggregata are considered generalists, and are euryhaline with broad temperature tolerances (Allen et al. 2006). In my study within Humboldt Bay,

Cymatogaster aggregata showed a strong association with warmer water temperatures.

These data suggest Cymatogaster aggregata are attracted to warmer waters occurring during summer (Figures 22, 27, 28, 45, Table 12). The generally warmer North Bay temperatures appeared to be a haven for juvenile Cymatogaster aggregata (Figure 22, 28,

45). Spikes in Cymatogaster aggregata abundance corresponded with high temperatures as well as juvenile numbers during the summer of 2007 and 2008. In 2007, juvenile numbers were similar across the bay, while in 2008, juveniles dominated only the North

Bay location (Figures 27, 28). Cymatogaster aggregata cumulative distribution functions showed this species accumulated in greater numbers at greater than or equal to 16°C

(Figure 11, 13). In 2008 Samoa had water temperatures generally below 16°C and, as a result, there were lower relative abundances of juvenile Cymatogaster aggregate (Figure

20). In June 2008, a sharp decline in water temperature drove North Bay water temperatures below 16°C. This decline corresponded to lower numbers of North Bay juvenile Cymatogaster aggregata until July 2008 when water temperatures exceeded

16°C. These patterns show clear water temperature boundaries for juvenile Cymatogaster aggregata. At the Samoa location, summer adult Cymatogaster aggregata abundances were consistent over the course of this study (Figures 22, 27, 28). The Cymatogaster aggregata relationship with water temperature at Samoa was stronger than the North Bay water temperature relationship (Figure 20, Table 12). Dominance of adults at this site illustrated distinct differences in life history optima based on water temperature.

Cymatogaster aggregata at the Samoa site occurred in greater numbers at more median temperatures (Figure 20). This implies adult fish have lower temperature preferences than the greater than or equal to 16°C cut off noted for juveniles.

Pholis ornata abundances were strongly correlated with temperature particularly at the North Bay location (Figure 21, Table 12). Both sample locations exhibited relatively higher Pholis ornata abundances during the warmest temperatures. Temporal comparisons showed that 2007 had the highest annual abundances (Figure 23, 29, 30,

45). In August 2007, both Samoa and North Bay showed a decline in Pholis ornata abundances. This may be an initial response to the temperature decline noted during this period (Figure 45). Juvenile life history stages of most fish species typically have higher tolerances to environmental conditions, especially benthic species. But, our findings suggest juvenile Pholis ornata in Humboldt Bay may be sensitive to relatively fast declines in water temperature. The strong water temperature relationship at the North Bay site (fishes accumulating mostly above 14° C), versus a nonexistent water temperature

99 relationship at the Samoa site, suggests the juvenile life history stage is driving this association (Figure 21).

Pholis ornata’s association with precipitation is unclear (Figure 23 and 46, Table

12). During June and July 2007 Pholis ornata were present in their highest numbers during the lowest levels of rainfall (Figures 29, 30, 46). In 2008, despite similar rainfall patterns, they were rare. Further sampling would be necessary to explore this relationship.

Gasterosteus aculeatus are eurythermal and euryhaline, tolerating water temperatures of 8-35°C and salinities of 4 – 45 ppt, depending on season and life history stage (Wootton 1984). The abundances in Humboldt Bay drop off dramatically from

January to March each year (Figures 24, 31, 32). Gasterosteus aculeatus were found to have significant water temperature relationships in 2008 and significant precipitation relationships in the pooled data (Figures 12, 14, Table 12). It is unclear whether the strong 2008 water temperature correlation was due to prolific 2007 abundances, offshore water temperature cues or generally low water temperatures occurring in the bay. Water temperatures in 2008 were generally cooler than 2007 (Figure 45), and abundances of

Gasterosteus aculeatus were much higher in 2007 (Table 1). In 2007, there are two peaks in abundance. The first due to higher numbers of adult Gasterosteus aculeatus (Figures

24, 31, 32) and the second is juvenile offspring of those adults, which are more apparent at the North Bay location (Figure 32). The juvenile life stage abundances lingered longer in Northern Humboldt Bay, into the early wetter autumn months (Figure 32). The adult

100 populations (particularly at the Samoa location) correspond with higher water temperatures, while juveniles aggregate during water temperature decreases (particularly in the North Bay location) (Figure 32, 45). The juvenile influx in North Bay was explored only for August 2008, masking the complete 2008 abundance cycle of water temperature affects on Gasterosteus aculeatus distributions in Humboldt Bay. Adult and juvenile populations drop annually after the first autumn spike in precipitation (Figures 31, 32,

46). Further study is needed to determine why Gasterosteus aculeatus abundances decrease with higher precipitation rates and why juvenile life history stages relative abundance is so high in North Bay (Figure 32).

Embiotoca lateralis and Sebastes melanops exhibited strong associations with turbidity, particularly in 2008 (Figures 15, 16, Table 12). Both species largely utilized only the Samoa location, with some spillover of Embiotoca lateralis juveniles into North

Bay in 2008. Confounding the understanding of this relationship is the lack of a discernable pattern in turbidity readings during the study (Figure 47) low catches of

Embiotoca lateralis (Table 1) and infrequent, but prolific catches of Sebastes melanops

(Figure 26). Both species appear to accumulate in larger numbers at higher turbidities in

2008 (Figure 15, 16, 25, 26, 47, Table 1). But, the additional Sebastes melanops strong negative association with 2007 precipitation (Figures 8, 17, 18) may imply an aversion to higher turbidity as noted during the slightly wetter summer of 2007.

Maps resulting from Universal Kriging illustrate differences between winter and summer temperature, and salinity variations. Temperature shows marked changes from

101 summer to winter. Summer temperatures have wider ranges than the more homogenous winter temperatures. Summer water temperatures show a gradient spreading the length of central bay. The distal regions of the bay were warmer, while the central portion was cooler. Salinity values across the bay vary greatly over the winter and between years.

However, summer salinities are similar over much of the bay. Spatially summarizing environmental data, especially where there are dense aggregations of sample locations, could begin to answer quantitative questions surrounding fish distributions.

Patterns highlighted by kriging could provide a basis for formulating future questions. The salinity and temperature isolines show strong gradients throughout central bay. Winter salinity isolines imply areas of stronger freshwater influence over time.

Characterizing the nature of these gradients against water current and climatic information could lead to a better understanding of the driving physical forces in

Humboldt Bay. Some scientists have already utilized the spatial component of kriging with generalized additive model statistics to explore spatial interactions between fish and their environment (Swartzman et al. 2007).

The results of my study provide a baseline methodology for establishing predictions of fish population changes in Humboldt Bay. At the very least, continuation of water quality monitoring is justified in order to record environmental fluctuations over time and to make biotic predictions possible. Krige interpolation techniques, could isolate the physicochemical dynamics and document environmental changes in Humboldt Bay both spatially and temporally. Sampling the same two stations over a longer period of

102 time could reveal associations between less abundant fish species and physicochemical variables. Additional sampling sites, including more habitats, could reveal additional habitat relationships. Finally, a simple program could be developed to predict fish population changes over varying temporal and physicochemical measurement regimes.

103

REFERENCES

Able, K.W., D.M. Nemerson, R. Bush and P. Light 2001. Spatial variation in Delaware Bay (USA) Marsh Creek fish assemblages. Estuaries 24:441-452.

Able, K.W., M.P. Fahay, K.L. Heck, C.T. Roman, M.A. Lazzari, and S.C. Kaiser. 2002. Seasonal distribution and abundance of fishes and decapods crustaceans in a Cape Cod estuary. Northeastern Naturalist 9(3):85-302.

Akin, S., K.O. Winemiller and F.P. Gelwick. 2003. Seasonal and spatial variations in fish and macrocrustacean assemblage structure in Mad Island Marsh Estuary, Texas. Estuarine, Coastal and Shelf Science 57:269-282.

Allen, L.G., D.J. Pondella II, and M.H. Horn. 2006. The Ecology of marine fishes in California and adjacent waters. University of California Press, Berkeley and Los Angeles, California.

Blaber, S.J.M. and T.G. Blaber 1980. Factors affecting the distribution of juvenile estuarine and inshore fish. Journal of Fish Biology 17:143-162.

Blaber, S. J. M., D.T. Brewer, and J.T. Salini. 1995. Fish communities and the nursery role of the shallow inshore waters of a tropical bay in the Gulf of Carpentaria, Australia. Estuarine, Coastal and Shelf Science 40:177-193.

Central and Northern California Ocean Observing System 2009. cencoos.humboldt.edu.

Ciannelli, L., R.D. Brodeur, G.L. Swartzman, and S. Salo. 2002. Physical and biological factors influencing the spatial distribution of age-0 walleye Pollock (Theragra chalcogramma) around the Pribilof Islands, Bering Sea. Deep-Sea Research II 49:6109-6126.

Cubillos, L.A., J. Paramo, P. Ruiz, S. Nunez, and A. Sepulveda. 2008. The spatial structure of the oceanic spawning of jack mackerel (Trachurus murphyi) off central Chile (1998- 2001). Fisheries Research 90:261-270.

D’Amours, D. 1993. The distribution of cod (Gadus morhua) in relation to temperature and oxygen levels in the Gulf of St. Lawrence. Fisheries Oceanography 2:24-29.

Environmental Systems Research Institute Ltd. 2004. ArcGIS version 9.3 ESRI Redlands, California.

Franco, A., S. Malavasi, M. Zucchetta, P. Franzoi, and P. Torricelli. 2006. Environmental influences on fish assemblage in the Venice Lagoon, Italy. Chemistry and Ecology 22:S105-S118.

104

Garcia-Lopez, V., C. RosasVazquez and R. BritoPerez. 2006. Effects of salinity on physiological conditions in juvenile common snook centropomus undecimalis. Comparative Biochemistry and Physiology. Part A: Molecular and Integrative Physiology 145(3):340- 345.

Garibaldi, L. and J.F. Caddy 1998. Biogeographic characterization of Mediterranean and Black Seas faunal provinces using GIS procedures. Ocean and Coastal Management 39:211- 227.

GoogleEarth. 2009. www.earth.google.com

Gutierrez, N. and O. Defeo 2003. Development of a new scallop Zygochlamys patagonica fishery in Uruguay: latitudinal and bathymetric patterns in biomass and population structure. Fisheries Research 52:21-36.

Grafen, A. and R. Hails. 2002. Modern statistics for the life sciences. Oxford University Press, Oxford, NY.

Harrison, J.D. 2004. Physico-chemical characteristics of South African estuaries in relation to the zoogeography of the region. Estuarine, Coastal and Shelf Science. 61:73-87.

Kennish, M.J. 1990 Ecology of Estuaries Volume II Biological Aspects. CRC Press, Inc., Boca Raton, FL.

Lloyd, C.D. and P.M. Atkinson 2004. Increased accuracy of geostatistical prediction of nitrogen dioxide in the United Kingdom with secondary data. International Journal of Applied Earth Observation and Geoinformation 5:293-305.

Lookman, R., N. Vandeweert, R. Merckx, and K. Vlassak. 1995. Geostatistical assessment of the regional distribution of phosphate sorption capacity parameters (Fe ox and Al ox) in northern Belgium. Geoderma 66:285-296.

Maes, J., P.A. van Damme, A. Taillieu and F. Ollevier. 1998. Fish communities along an oxygen-poor salinity gradient (Zeeschelde Estuary, Belgium). Journal of Fish Biology 52:534:546.

Maes, J., P.A. van Damme,P. Meire, and F. Ollevier. 2004. Statistical modeling of seasonal and environmental influences on the population dynamics of an estuarine fish community. Marine Biology 145:1033-1042.

Magnussen, E. 2002. Demersal fish assemblages of Faroe Bank: species composition, distribution, biomass spectrum and diversity. Marine Ecology Progress Series 238:211- 225.

Marshall, S. and M. Elliott. 1998. Environmental influences on the fish assemblage of the Humber Estuary, U.K. Estuarine, Coastal and Shelf Science 46:175-184.

105

Martino, E.J. and K.W. Able 2003. Fish assemblages across the marine to low salinity transition zone of a temperate estuary. Estuarine, Coastal and Shelf Science 56:969-987.

Matthews, K.R. 1990. An experimental study of the habitat preferences and movement patterns of Copper, quillback, and brown rockfish (Sebastes spp.). Environmental Biology Fishes 29:161-178.

Moller, H. and U. Scholz 2007. Avoidance of oxygen-poor zones by fish in the Elbe River. Journal of Applied Ichthyology 7:176-182.

National Oceanic and Atmospheric Administration. 2009. www.ndbc.noaa.gov.

Nezlin, N.P. and P.M. DiGiacomo. 2005. Satellite ocean color observations of stormwater runoff plumes along the San Pedro Shelf (Southern California) during 1997 – 2003. Continental Shelf Research 25:1692-1711.

Nezlin, N.P., J.J. Oram, P.M. DiGiacomo and N. Gruber. 2004. Sub-seasonal to interannual variations of sea surface temperature, salinity, oxygen anomaly, and transmissivity in Santa Monica Bay, California from 1987 to 1997. Continental Shelf Research 24:1053- 1082.

Paramo, J., R.A. Quinones, A. Ramirez, and R. Wiff. 2003. Relationship between abundance of small pelagic fishes and environmental factors in the Colombian Caribbean Sea: an analysis based on hydroacoustic information. Aquatic Living Resources 16:239-245.

Paramo, J. and R. Roa. 2003. Acoustic-geostatistical assessment and habitat-abundance relations of small pelagic fish from the Colombian Caribbean. Fisheries Research 60:309-319.

Paterson, A.W. and A.K. Whitfield 2000a. The ichthyofauna associated with an intertidal creek and adjacent eelgrass beds in the Kariega estuary, South Africa. Environmental Biology of Fishes 58:145-156.

Paterson, A.W., and A.K. Whitfield 2000b. Do shallow water habitats function as refugia for juvenile fishes? Estuarine, Coastal and Shelf Science 51:359-364.

Pauly, D. V. Christensen, J. Dalsgaard, R. Froese, and F. Torres, Jr. 1998. Fishing down marine food webs. Science 279:860-863.

Perry, R.I. and Smith, S.J. 1994. Identifiying habitat associations of marine fishes using survey data: an application to the Northwest Atlantic. Can. J. Fish. Aquatic. Sci. 51:589-602.

Persohn, C., P. Lorance, and V.M. Trenkel. 2009. Habitat preferences of selected demersal fish species in the Bay of Biscay and Celtic Sea, North-East Atlantic. Fisheries Oceanography 18:268-285.

106

Peterson, M.S. and S.T. Ross 1991. Dynamics of littoral fishes and decapods along a coastal river-estuarine gradient. Estuarine, Coastal and Shelf Science 33: 467-483.

Pinnix, W.D., T.A. Shaw, K.C. Acker and N.J. Hetrick. 2005. Fish communities in eelgrass, oyster culture, and mudflat habitats of North Humboldt Bay, California Final Report. U.S. Fish and Wildlife Service, Arcata Fish and Wildlife Office, Arcata Fisheries Program Technical Report Number TR2005-02, Arcata, California.

Porter, D.E., D. Edwards, G. Scott, B. Jones, and W.S. Street. 1997. Assessing the impacts of anthropogenic and physiographic influences on grass shrimp in localized salt-marsh estuaries. Aquatic Botany 58:289-306.

Primo, A.L., U.M. Azeiteiro, S.C. Marques, F. Martinho and M.A. Pardal. 2009. Changes in zooplankton diversity and distribution pattern under varying precipitation regimes in a southern temperate estuary. Estuarine, Coastal and Shelf Science 82:341-347.

R Development Core Team. 2008. R: A language and environment for statistical computing. R Foundation for Statistical Computing. Vienna, Austria.

Reese, D.C., T.W. Miller and R.D. Brodeur. 2005. Community structure of near surface zooplankton in the Northern California Current in relation to oceanographic conditions. Deep Sea Research II 52:29-50.

Reese, D.C. and R.D. Brodeur 2006. Identifying and characterizing biological hotspots in the northern California Current. Deep Sea Research Part II: Tropical Studies in Oceanography 53:291-314.

Scott, D.M., M.C. Lucas, and R.W. Wilson. 2005. The effect of high pH on ion balance, nitrogen excretion and behavior in freshwater fish from a eutrophic lake: A laboratory and field study. Aquatic Toxicology 73:31-43.

Selleslagh, J. and R. Amara 2008. Environmental factors structuring fish composition and assemblages in a small macrotidal estuary (eastern English Channel). Estuarine, Coastal and Shelf Science 79:507-517.

Serafy, J.E. and R.M. Harrell 1993. Behavioral response of fishes to increasing pH and dissolved oxygen: field and laboratory observations. Freshwater Biology 30:53-61.

Skeesick, D. 1963. A study of some physical-chemical characteristics of Humboldt Bay. Master’s Thesis. Department of Natural Resources, Humboldt State University, Arcata, California.

Stelzenmuller, V., F. Maynou, and P. Martin. 2007. Spatial assessment of benefits of a coastal Mediterranean Marine Protected Area. Biological Conservation 136:571-583.

107

Swartzman, G. and Chisheng Huang 1992. Spatial analysis of Bering Sea groundfish survey data using generalized additive models. Canadian Journal of Fisheries and Aquatic Sciences 49:1366-1378. Ter Braak, C.J. 1986. Canonical Correspondence Analysis: A new eigenvector technique for multivariate direct gradient analysis. Ecology 67:1167-1179.

Thiel, R., A. Sepulveda, R. Kafemann, and W. Nellen. 1995. Environmental factors as forces structuring the fish community of the Elbe estuary. Journal of Fish Biology 46:47-69.

Van Kirk, R. 2008. Personal Communication. Humboldt State University, Department of Mathematics, 1 Harpst Street, Arcata, California 95521.

Verfaillie, E., V. Van lancker and M. Van Miervenne. 2006. Multivariate geostatistics for the predictive modeling of the surficial sand distribution in shelf seas. Continental Shelf Research 26:2454-2468.

Vincenzi, S., G. Caramori, R. Rossi, and G.A. De Leo. 2006. A GIS-based habitat suitability model for commercial yield estimation of Tapes philippinarum in a Mediterranean coastal lagoon (Sacca di Goro, Italy). Ecological Modeling 193:90-104.

Watanabe, Y., G.E. Dingsor, T. Yongjun, I. Tanaka and N.C. Stenseth. 2008. Determinants of mean length at age of spring spawning herring off the coast of Hokkaido, Japan.. Marine Ecology Progress Series 366:209-217.

Weinstein, M.P. and H.A. Brooks 1983. Comparative ecology of nekton residing in a tidal creek and adjacent seagrass meadow: community composition and structure. Marine Ecology Progress Series 12:15-27.

Western, A.W., S. Zhou, R.B. Grayson, T.A. McMahon, G. Bloschl and D.J. Wilson. 1998. Geostatistical characterization of soil moisture patterns in the Tarrawarra catchment. Journal of Hydrology 286:113-134.

Wootton, R.J. 1984. A Functional biology of sticklebacks. University of California Press Berkeley and Los Angeles, California.

APPENDICES

1.2

1.0 p  0.14

0.8 p  0.16

0.6

0.4 p  0.16 0.2 Temperature Cumulative Frequency Cumulative Osmerid spp. Aulorhynchus flavidus 0.0 Pholis ornata

6 8 10 12 14 16 18 20 22 Temperature (°C)

Appendix A. Cumulative distribution function of temperature relationship for Osmerid spp., Aulorhynchus flavidus and Pholis ornata in Humboldt Bay, Humboldt County, California from June 2006 to August 2008. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis.

108

109

1.2

1.0 p  0.26

0.8

0.6

p  0.23 0.4

0.2 Temperature 2007 Cumulative Frequency Cumulative Osmerid spp. Sebastes melanops 0.0

6 8 10 12 14 16 18 20 22 Temperature (°C)

Appendix B. Cumulative distribution function of the 2007 temperature relationship for Osmerid spp. and Sebastes melanops in Humboldt Bay, Humboldt County, California for January 2007 to December 2007. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis.

110

1.2

1.0 p  0.29

0.8 p  0.12

0.6

0.4 p  0.20

Temperature 2008 0.2 Cumulative Frequency Cumulative Osmerid spp. Aulorhynchus flavidus 0.0 Pholis ornata

8 10 12 14 16 18 20 Temperature (°C)

Appendix C. Cumulative distribution function of 2008 temperature relationship for Osmerid spp., Aulorhynchus flavidus and Pholis ornata in Humboldt Bay, Humboldt County, California from January 2008 to August 2008. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis.

111

1.2

1.0 p  0.18

0.8

0.6

0.4

p  0.14 0.2

Cumulative Frequency Cumulative Temperature North Bay 0.0 Osmerid spp. Syngnathus leptorhynchus

6 8 10 12 14 16 18 20 22 Temperature (°C)

Appendix D. Cumulative distribution function of temperature at the North Bay site’s relationship for Osmerid spp., Syngnathus leptorhynchus in Humboldt Bay, Humboldt County, California from March 2007 to August 2008. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis.

112

1.2

1.0 Salinity Osmerid spp.

0.8

0.6 p  0.14 0.4

0.2

Cumulative Frequency Cumulative

0.0

20 22 24 26 28 30 32 34 36 38 Salinity (ppt)

Appendix E. Cumulative distribution function of salinity relationship for Osmerid spp. in Humboldt Bay, Humboldt County, California from June 2006 to August 2008. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis.

113

1.2

Salinity 2007 1.0 Hypomesus pretiosus

0.8 p  0.25

0.6

0.4

0.2

Cumulative Frequency Cumulative

0.0

20 22 24 26 28 30 32 34 36 Salinity (ppt)

Appendix F. Cumulative distribution function of 2007 salinity relationship for Hypomesus pretiosus in Humboldt Bay, Humboldt County, California from January 2007 to December 2007. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis.

114

1.2

Salinity 2008 1.0 Leptocottus armatus Cymatogaster aggregata 0.8 p  0.09

0.6

0.4

0.2

Cumulative Frequency Cumulative p  0.27 0.0

22 24 26 28 30 32 34 36 Salinity (ppt)

Appendix G. Cumulative distribution function of 2008 salinity relationship for Leptocottus armatus and Cymatogaster aggregata in Humboldt Bay, Humboldt County, California from January 2008 to August 2008. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis.

115

1.2

1.0

p  0.13 0.8

0.6 p  0.25

0.4

0.2

Cumulative Frequency Cumulative

Samoa Salinity 0.0 Osmerid spp. Leptocottus armatus

20 22 24 26 28 30 32 34 36 Salinity (ppt)

Appendix H. Cumulative distribution function of the Samoa site salinity relationship for Osmerid spp. and Leptocottus armatus in Humboldt Bay, Humboldt County, California from June 2006 to August 2008. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis.

116

1.2

1.0

North Bay Salinity 0.8 Cymatogaster aggregata

0.6

0.4

0.2

Cumulative Frequency Cumulative p  0.18 0.0

22 24 26 28 30 32 34 36 Salinity (ppt)

Appendix I. Cumulative distribution function of the North Bay site salinity relationship for Cymatogaster aggregata in Humboldt Bay, Humboldt County, California from March 2007 to August 2008. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis.

117

1.2

1.0

0.8 p  0.11

0.6

0.4

Cumulative Frequency Cumulative Dissolved Oxygen 2008 0.2 Pholis ornata

0.0 6.5 7.0 7.5 8.0 8.5 9.0 9.5 10.0 10.5 Dissolved Oxygen (mg/L)

Appendix J. Cumulative distribution function of 2008 dissolved oxygen relationship for Pholis ornata in Humboldt Bay, Humboldt County, California for January 2008 to August 2008. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis.

118

1.2

1.0 PH 2007 Cymatogaster aggregata

0.8

0.6

0.4

0.2 p  0.29

Cumulative Frequency Cumulative

0.0

7.2 7.4 7.6 7.8 8.0 8.2 PH

Appendix K. Cumulative distribution function of 2007 pH relationship for Cymatogaster aggregata in Humboldt Bay, Humboldt County, California from January 2007 to December 2007. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis.

119

1.2

1.0 PH 2008 Syngnathus leptorhynchus

0.8

0.6 p  0.23

Cumulative Frequency Cumulative 0.4

0.2 7.5 7.6 7.7 7.8 7.9 8.0 8.1 PH

Appendix L. Cumulative distribution function of 2008 pH relationship for Syngnathus leptorhynchus in Humboldt Bay, Humboldt County, California from January 2008 to August 2008. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis.

120

1.2

1.0 North Bay PH Cymatogaster aggregata

0.8

0.6

0.4

Cumulative Frequency Cumulative p  0.22

0.2

0.0 7.5 7.6 7.7 7.8 7.9 8.0 8.1 PH

Appendix M. Cumulative distribution function of the North Bay site pH relationship for Cymatogaster aggregata in Humboldt Bay, Humboldt County, California from March 2007 to August 2008. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis.

121

1.2

1.0

0.8

Turbidity 2007 0.6 Cymatogaster aggregata

0.4 p  0.22

Cumulative Frequency Cumulative

0.2

0.0 0 10 20 30 40 50 Turbidity (ntu)

Appendix N. Cumulative distribution function of 2007 turbidity relationship for Cymatogaster aggregata in Humboldt Bay, Humboldt County, California from January 2007 to December 2007. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis.

122

1.2

1.0 Turbidity 2008 Hypomesus pretiosus 0.8

0.6

0.4 p  0.18

0.2

Cumulative Frequency Cumulative

0.0

2 4 6 8 10 12 14 16 18 20 Turbidity (ntu)

Appendix O. Cumulative distribution function of 2008 turbidity relationship for Hypomesus pretiosus in Humboldt Bay, Humboldt County, California from January 2008 to August 2008. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis.

123

1.2

1.0

Samoa Turbidity 0.8 Embiotoca lateralis Sebastes melanops 0.6 Hypomesus pretiosus

0.4 p  0.11 p  0.28

0.2

Cumulative Frequency Cumulative

0.0 p  0.18

0 10 20 30 40 50 Turbidity (ntu)

Appendix P. Cumulative distribution function of the Samoa site turbidity relationship for Embiotoca lateralis, Sebastes melanops and Hypomesus pretiosus in Humboldt Bay, Humboldt County, California from June 2006 to August 2008. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis.

124

1.2

1.0 p  0.20

0.8

0.6

0.4 p  0.24

0.2 North Bay Turbidity

Cumulative Frequency Cumulative Embiotoca lateralis Syngnathus leptorhynchus 0.0

0 5 10 15 20 25 30 Turbidity (ntu)

Appendix Q. Cumulative distribution function of the North Bay site turbidity relationship for Embiotoca lateralis and Syngnathus leptorhynchus in Humboldt Bay, Humboldt County, California from March 2007to August 2008. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis.

125

1.2

1.0 p  0.14

0.8 p  0.27 0.6

0.4 p  0.18

0.2 Precipitation Cumulative Frequency Cumulative Embiotoca lateralis Pholis ornata 0.0 Hexagrammas decagrammus

0 2 4 6 8 10 12 Precipitation (mm)

Appendix R. Cumulative distribution function of precipitation relationship for Embiotoca lateralis, Pholis ornata and Hexagrammos decagrammus in Humboldt Bay, Humboldt County, California from June 2006 to August 2008. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis.

126

1.2

1.0 p  0.15

0.8

0.6 p  0.07 0.4

Precipitation 0.2 Cumulative Frequency Cumulative Cymatogaster aggregata Osmerid spp. 0.0

0 2 4 6 8 10 12 Precipitation (mm)

Appendix S. Cumulative distribution function of precipitation relationship for Cymatogaster aggregata and Osmerid spp. in Humboldt Bay, Humboldt County, California from June 2006 to August 2008. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis.

127

1.2

1.0 p  0.16

0.8

0.6

0.4

0.2 Precipitation 2007 Cumulative Cumulative Frequency Pholis ornata

0.0

0 2 4 6 8 10 12 Precipitation (mm)

Appendix T. Cumulative distribution function of 2007 precipitation relationship for Pholis ornata in Humboldt Bay, Humboldt County, California from January 2007 to December 2007. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis.

128

1.2

p  0.25 1.0 p  0.20 0.8

0.6 Precipitation 2008 G. aculeatus 0.4 H. decagrammus Osmerid spp.

0.2 Cumulative Frequency Cumulative p  0.17

0.0

0 2 4 6 8 Precipitation (mm)

Appendix U. Cumulative distribution function of 2008 precipitation relationship for Gasterosteus aculeatus, Hexagrammos decagrammus and Osmerid spp. in Humboldt Bay, Humboldt County, California from January 2008 to August 2008. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis.

129

1.2

1.0 p  0.07 p  0.15

0.8

0.6

Precipitation 2008

Cumulative Frequency Cumulative Pholis ornata 0.4 Embiotoca lateralis

0.2 0 2 4 6 8 Precipitation (mm)

Appendix V. Cumulative distribution function of 2008 precipitation relationship for Pholis ornata and Embiotoca lateralis in Humboldt Bay, Humboldt County, California from January 2008 to August 2008. The p-value represents the probability of attaining the Kolmogorov-Smirnov test statistic in a randomized distribution under the null hypothesis.