BACTERIA FATE, TRANSPORT, GROWTH & PERSISTENCE STUDY...

Texas Watershed Coordinator Roundtable Col lege Stat ion – Jan 11 , 2016

BACTERIA FATE, TRANSPORT, GROWTH & PERSISTENCE STUDY RESULTS

LUCAS GREGORY TERRY GENTRY, DAREN HARMEL, KEVIN WAGNER, R. KARTHIKEYAN, ROEL LOPEZ, SAQIB MUKHTAR JACQUI AITKENHEAD-PETERSON,

1 January 11, 2016

Assess influence of water chemistry on instream E. coli growth and persistence Continue developing the understanding environmental

impacts on E. coli fate Improve fate and transport modeling capability

Build upon and extend previous work Individual or small number of parameters Non-natural conditions Sterilized lab environments Limited environmental factors Lab strain E. coli

OBJECTIVE 1

2 January 11, 2016

APPROACH

Monitor culturable E. coli response to nutrient amendments in re-created natural stream mesocosms under varying flow conditions

Hypothesis: E. coli life cycle response (decay constants) means

are different based on nutrient and flow amendment scenarios

3 January 11, 2016

“low” and “high” nutrient dose

“low” and “high” flow rates applied

Semi-controlled lab setting

Evaluate change over time

EXPERIMENTAL DESIGN

Old algae raceways

4 January 11, 2016

Initial sample from each mesocosm when filled Establish baseline

conditions Initial nutrient levels used

to develop ‘low’ and ‘high’ nutrient doses

Nutrient dose applied at Day 1

Sample over 22 day period

Each sample analyzed for: E. coli (mTEC) (EPA 1603) Heterotrophic plate counts pH DO Conductivity Water Temp Turbidity Nitrate Ammonium Total Nitrogen Dissolved Organic Nitrogen Dissolved Organic Carbon Orthophosphate

SAMPLING SCHEME

5 January 11, 2016

January 11, 2016 6

y = -1.3025x + 6.2156R² = 0.9118

y = -0.0506x + 0.8764R² = 0.4042

0

2

4

6

8

0 2 4 6 8 10 12 14 16 18 20 22

E. c

oli

(LN

CFU

/100

mL

)

Time (d)

a)

y = -0.9894x + 7.1176R² = 0.726

y = -0.1567x + 3.2879R² = 0.4133

0

2

4

6

8

0 2 4 6 8 10 12 14 16 18 20 22

E. c

oli

(LN

CFU

/100

mL

)

Time (d)

b)

y = -1.5023x + 6.7438R² = 0.9007

y = -0.0652x + 1.3948R² = 0.2169

0

2

4

6

8

0 2 4 6 8 10 12 14 16 18 20 22E. c

oli

(LN

CFU

/100

mL

)

Time (d)

c)y = -0.8733x + 7.1781

R² = 0.4932

y = -0.151x + 3.9196R² = 0.2948

0

2

4

6

8

0 2 4 6 8 10 12 14 16 18 20 22E. c

oli

(LN

CFU

/100

mL

)

Time (d)

d)

y = -1.5894x + 6.3342R² = 0.9621

y = -0.0359x + 0.749R² = 0.1618

0

2

4

6

8

0 2 4 6 8 10 12 14 16 18 20 22E. c

oli

(LN

CFU

/100

mL

)

Time (d)

e)y = -1.0516x + 7.1964

R² = 0.6309

y = -0.1399x + 3.1634R² = 0.2939

0

2

4

6

8

0 2 4 6 8 10 12 14 16 18 20 22E. c

oli

(LN

CFU

/100

mL

)

Time (d)

f)

E. coli Decay Constants P = 0.222 & 0.637 a) Control Low Speed

b) Control High Speed

c) High Nutrient Low Speed

d) High Nutrient High Speed

e) Low Nutrient Low Speed

f) Low Nutrient High Speed

January 11, 2016 7

Influence of Nutrient Amendments on E. coli decay p values ≥ 0.199 a) Low Flow

b) High Flow

-1.00

0.00

1.00

2.00

3.00

4.00

0 2 4 6 8 10 12 14 16 18 20 22Mea

n E

. col

i (L

OG

C

FU/1

00m

L)

Time (d)

a)

Control Low Nutrient High Nutrient

-1.00

0.00

1.00

2.00

3.00

4.00

0 2 4 6 8 10 12 14 16 18 20 22Mea

n E

. col

i (L

OG

C

FU/1

00m

L)

Time (d)

b)

Control Low Nutrient High Nutrient

January 11, 2016 8

Influence of Flow Velocity on E. coli decay p values ≥ 0.08 a) Control

b) High Nutrient

c) Low Nutrient

-1.00

0.00

1.00

2.00

3.00

4.00

0 2 4 6 8 10 12 14 16 18 20 22

Mea

n E

. col

i (L

OG

C

FU/1

00m

L)

Time (d)

a)

Low Flow High Flow

-1.00

0.00

1.00

2.00

3.00

4.00

0 2 4 6 8 10 12 14 16 18 20 22

Mea

n E

. col

i (L

OG

C

FU/1

00m

L)

Time (d)

b)

Low Flow High Flow

-1.00

0.00

1.00

2.00

3.00

4.00

0 2 4 6 8 10 12 14 16 18 20 22

Mea

n E

. col

i (L

OG

C

FU/1

00m

L)

Time (d)

c)

Low Flow High Flow

January 11, 2016 9

Heterotroph Response p values ≥ 0.243 a) Control Low Speed

b) Control High Speed

c) High Nutrient Low Speed

d) High Nutrient High Speed

e) Low Nutrient Low Speed

f) Low Nutrient High Speed

y = -0.5377x + 12.274R² = 0.4688

y = 0.0646x + 10.623R² = 0.0731

y = -0.2127x + 13.961R² = 0.1383

2468

10121416

0 2 4 6 8 10 12 14 16 18 20 22

Het

erot

roph

(LN

CFU

/mL

)

Time (d)

a) y = -0.0533x + 12.545R² = 0.0072

y = -0.1308x + 12.424R² = 0.3788

y = -0.21x + 13.82R² = 0.143

2468

10121416

0 2 4 6 8 10 12 14 16 18 20 22

Het

erot

roph

(LN

CFU

/mL

)

Time (d)

b)

y = 0.5535x + 11.474R² = 0.3019

y = -0.1738x + 13.923R² = 0.1415

y = -0.2929x + 15.742R² = 0.2496

2468

10121416

0 2 4 6 8 10 12 14 16 18 20 22

Het

erot

roph

(LN

CFU

/mL

)

Time (d)

c)

y = 0.7578x + 12.367R² = 0.7651

y = -0.3092x + 15.946R² = 0.5483

y = -0.2478x + 15.768R² = 0.1931

2468

10121416

0 2 4 6 8 10 12 14 16 18 20 22

Het

erot

roph

(LN

CFU

/mL

)

Time (d)

d)

y = 0.3815x + 11.765R² = 0.2706

y = -0.1368x + 13.139R² = 0.0605

y = -0.2641x + 14.828R² = 0.2157

2468

10121416

0 2 4 6 8 10 12 14 16 18 20 22

Het

erot

roph

(LN

CFU

/mL

)

Time (d)

e)

y = 0.4295x + 12.11R² = 0.1484

y = -0.1566x + 14.285R² = 0.1562

y = -0.2684x + 15.628R² = 0.2168

2468

10121416

0 2 4 6 8 10 12 14 16 18 20 22

Het

erot

roph

(LN

CFU

/mL

)Time (d)

f)

E. coli response not affected by single nutrient amendment

Heterotrophs quickly utilized added nutrient Suggests that competition prevents E. coli

growth Flow rate had larger impact on E. coli decay

than nutrients Nutrients were found to be significant factors

in multiple regression models explaining E. coli decay

KEY FINDINGS

10 January 11, 2016

Evaluate sources of background E. coli on varying land uses/land covers

Evaluate differences in water quality from selected land

uses/land covers Conduct source surveys to identify species present Physical observations and documentation of sources Camera trapping to capture relative abundance data

Bacterial source tracking ID sources of E. coli present in soil samples ID sources of E. coli in water samples

OBJECTIVE 2

11 January 11, 2016

STUDY AREA: USDA-ARS GRASSLAND RESEARCH FACILITY NEAR RIESEL, TX

12 January 11, 2016

APPROACH

Monitor surface runoff E. coli loads from 3 intensively managed watersheds

Quantify E. coli levels in the upper 2.5 cm of soil in each plot

Supplement Texas E. coli BST Library with additional known source samples

Screen soil and water E. coli DNA against existing Texas E. coli BST Library

Compare differences in soil and water bacterial levels

from each land use and between land uses 13 January 11, 2016

Native PrairieManaged Hay PastureCropland

6

5

4

3

2

1

Land Use / Land Cover

Log

10

E. c

oli c

fu/1

00 m

L

Riesel E. coli Concentrations October 2013 - May 2015

Statistics (cfu/100mL)

Native Prairie

Managed Hay Pasture

Cropland

N 25 14 22 Mean 8,811 14,490 14,578 Geometric Mean 1,372.1 3,425.2 3,991.8 Median 1,000 5,950 4,700 Standard Deviation 31,701 21,723 31,424 Minimum 160 20 70 Maximum 160,000 80,000 150,000

E. COLI FINDINGS: RUNOFF

January 11, 2016 14

E. coli concentration statistics

Statistics (cfu/wet g) Native Prairie

Managed Hay

Pasture Cropland

N 51 51 51 Mean 22.75 50.10 13.63 Geometric Mean 13.86 15.71 10.81 Median 10 10 10 StDev 47.45 156.23 23.81 Minimum 10 10 10 Maximum 335 1065 180 Number of Samples Yielding E. coli 14 17 8

E. COLI FINDINGS: SOIL

January 11, 2016 15

SOURCE ID: CAMERA TRAPS

January 11, 2016 16


January 11, 2016 17


January 11, 2016 18

Species Individual

Animal Count

Species Richness By Site # of Sites Where Species

Identified

Relative Abundance

SW12 SW17 Y6 Armadillo 1 0 1 0 1 0.05 Avian 321 84 119 118 3 17.2 Bobcat 8 8 0 0 1 0.43 Cattle 4 0 3 1 2 0.21 Cottontail Rabbit 228 222 6 0 2 12.22 Coyote 174 89 23 62 3 9.32 Deer 24 24 0 0 1 1.29 Dog 8 7 1 0 2 0.43 Feral Cat 12 12 0 0 1 0.64 Jackrabbit 220 2 85 133 3 11.79 Opossum 28 28 0 0 1 1.5 Raccoon 3 2 0 1 2 0.16 Rat 27 18 8 1 3 1.45 Skunk 339 183 95 61 3 18.17 Unknown 469 241 78 150 3 25.13 Total Counts 1,866 920 420 526 NA NA

E. COLI CONCENTRATION IN FECES (cfu/g)

January 11, 2016 19

E. COLI CONCENTRATION IN FECES (cfu/g)

January 11, 2016 20

Findings from the Bacteria Fate and Transport Project (Cedar Creek in Brazos County)

Primarily rely on Texas Library Supplement with

local small and meso- mammal samples ID sources of E. coli

in soils and surface runoff

LIBRARY DEPENDENT BST

21 January 11, 2016

SOIL BST RESULTS

22 January 11, 2016

Native Prairie n = 63

Cropland n = 19

Managed Hay Pasture n = 113

RUNOFF BST RESULTS

23 January 11, 2016

Native Prairie n = 160 Cropland n = 80

Managed Hay Pasture n = 60

Site Soil Runoff % Difference SW12 7-way 7-way 7-way

Wildlife Avian 16 12 28.6 Non-Avian 65 50 26.1

Livestock and Domesticated

Cattle 5 4 22.2 Pets 0 9 200 Other Avian 3 2 40 Other Non-Avian 1 8 155.6

Human 5 5 0 Unidentified 5 9 57.1

SW17 7-way 7-way 7-way



Cattle 19 12 45.2 Pets 0 7 200 Other Avian 0 5 200 Other Non-Avian 3 15 133.3


Y6 7-way 7-way 7-way



Cattle 0 6 200 Pets 0 1 200 Other Avian 0 3 200 Other Non-Avian 16 8 66.7


Use caution: small sample sizes!

ANOVA suggests no significant differences between sampling site and ID for soil and runoff:

0.162 < p < 0.65

Pearson’s Chi-squared test suggests differences between: IDs and sampling media (runoff

or soil) P = 0.042

IDs and sampling site P = 0.00043

BST STATISTICS

January 11, 2016 24

E. coli identification results for soil and runoff samples from each watershed and the relative

percent difference in source identification between soil and runoff samples

Wildlife sources dominated runoff and soil samples at all sites as expected

Cattle and Human influences a bit surprising Game cams show cattle presence at two sites Raises questions of possible transmission vectors or

cosmopolitan nature of E. coli isolates

General lack of E. coli in soil samples suggests recent fecal depositions rather than naturalized E. coli

Potential differences in E. coli IDs suggested between watersheds and sampling media

KEY FINDINGS

25 January 11, 2016

Lucas Gregory [email protected]

QUESTIONS?

26

Funding Support provided by the Texas State Soil and Water Conservation Board State Nonpoint Source Grant Program

January 11, 2016

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