Effects of Feral Pig (Sus scrofa) Exclusion on Enterococci in Runoff from the Forested Headwaters of...

Effects of Feral Pig (Sus scrofa) Exclusion on Enterococciin Runoff from the Forested Headwatersof a Hawaiian Watershed

Dashiell O. Dunkell & Gregory L. Bruland &

Carl I. Evensen & Mark J. Walker

Received: 27 July 2010 /Accepted: 7 March 2011 /Published online: 24 March 2011# Springer Science+Business Media B.V. 2011

Abstract The role feral pigs (Sus scrofa) as a sourceof fecal contamination in Pacific Island ecosystems isnot well understood. This study investigated theeffects of feral pigs on enterococci (ENT) in runoffand soils of a Hawaiian forest. Seven sites wereestablished with paired fenced/unfenced runoff plotsin the Manoa watershed. Runoff was collectedmonthly from these plots after rain events from June2008 to April 2009; soil ENT at each plot were alsoquantified. ENT in runoff were highly variableranging from below the detection limit to >4.38log10 most probable number (MPN) 100 mL−1. Arepeated measures ANOVA found no overall fencingeffects. This ANOVA did reveal a month by siteinteraction, indicating that while ENT in runoff werethe highest in the wet season, this was not consistentacross all sites. Soil ENT ranged from 14 to 511MPN g−1 and differed among sites but not betweenfencing treatments. The only variables that were

significantly correlated to ENT in runoff were runoffvolume and soil ENT; slope, throughfall, soil mois-ture, bare soil cover, and total suspended solids inrunoff were not correlated with ENT. While concen-trations of ENT in runoff were highly variable acrossthe months and sites, these forested headwaters didserve as sources of ENT to downstream ecosystemsthroughout the year. To minimize effects on humanhealth, we recommend that public authorities employgreater warnings (i.e., signage) at streams and beachesin the lower reaches of this and other forestedHawaiian watersheds that are frequently used by bothresidents and tourists.

Keywords Enterococci . Erosion . Fecal indicatorbacteria . Feral pigs . Forests . Runoff . Soils .

Watershed management

1 Introduction

Of the hundreds of invasive species in Hawaii, theferal pig (Sus scrofa) has arguably caused the mostdamage, especially in wet forests (Tomich 1979;Nogueira et al. 2007; Bruland et al. 2010). Pigactivities such as rooting, browsing, digging, andtrampling may lead to a loss of biodiversity, propa-gation of invasive plants, and increased erosion (Honeand Stone 1989; Huenneke and Vitousek 1990; Spearand Chown 2009; Dunkell et al. 2011). As a result ofthese activities, feral pigs in Hawaii are considered by

Water Air Soil Pollut (2011) 221:313–326DOI 10.1007/s11270-011-0792-y

D. O. Dunkell :G. L. Bruland (*) :C. I. EvensenNatural Resource and Environmental ManagementDepartment, University of Hawaii Manoa,1910 East–west Rd., Sherman Lab 101,Honolulu, HI 96822, USAe-mail: [email protected]

M. J. WalkerDepartment of Natural Resources and EnvironmentalScience, University of Nevada, Reno,132 Fleischmann Agriculture-MS370,Reno, NV 89557, USA

many to be a threat to native flora and fauna, andminimizing their impact is a top priority for many ofHawaii’s parks and reserves (Hone and Stone 1989;Huenneke and Vitousek 1990; Donlan and Wilcox2008). Much less is known about the watershed-scale effects of non-native feral pigs on processessuch as runoff, erosion, and fecal contamination(Bruland et al. 2010).

Fecal indicator bacteria (FIB) reside in the gastro-intestinal tracts of humans and animals and are usedthroughout the world to assess the microbiologicalsafety of drinking, recreational, and shellfish waters.They are found in fecal material at high concen-trations and are relatively easy to measure in theenvironment. The high diversity of pathogenic micro-organisms transmitted by contaminated water and thedifficulty and cost of directly measuring thesemicrobial pathogens in environmental samples haveled to the use of FIB to test for the presence of fecalcontamination (Gersberg et al. 2006; Wade et al.2006; Surbeck 2009). The US Environmental Protec-tion Agency (US EPA) recommends the use ofEscherichia coli, a member of the fecal coliformgroup, as a FIB for recreational freshwater bodies andmembers of the genus Enterococcus for both fresh-water and saltwater (US EPA 2000). FIB arecommonly used as an indicator that guides develop-ment of water management plans (Plummer and Long2007; Surbeck 2009). Such plans generally involveinterventions to reduce FIB loadings to receivingwaters.

This study employs Enterococcus spp. bacteria (theenterococci) as a FIB to investigate water quality ofrunoff in a mixed-use, subtropical Pacific Islandwatershed. Enterococci abundance is one of the threemost common water quality tests in the USA(Noble et al. 2003). From Santa Monica Bay,California to the Great Lakes, levels of FIB havebeen shown to correlate reasonably well withincidence of illness reported by swimmers (Haile etal. 1999; Wade et al. 2006). Though some researchsuggests that ENT are free living in Hawaiian soils(Hardina and Fujioka 1991; Byappanahalli andFujioka 2004), mesocosm experiments have foundthat ENT do not multiply in subtropical waters andsediments (Anderson et al. 2005). Recent unpub-lished data from remote, undisturbed locations onOahu revealed extremely low ENT levels in fresh-water streams (Ragosta 2007).

While feral pigs have been shown to have negativeeffects on native vegetation and biodiversity in bothcontinental and island settings (Hone 2002; Donlanand Wilcox 2008; Campbell and Long 2009;Nogueira-Filho et al. 2009; Siemann et al. 2009),few, if any, studies have investigated the role of feralpigs as a potential FIB source in surface runoff. Whilecertain species of Enterococcus are only recognizedas opportunistic pathogens (i.e., Enterococcus faecalisand Enterococcus faecium), feral pigs have beenshown to be reservoirs for other more harmfulpathogens (US EPA 1986; Pruss 1998). In Hawaiiand other Pacific Island watersheds, streams andcoastal waters are highly valued for fisheries, recre-ation, and tourism. More research is needed todetermine the threats to human and ecological healthposed by feral pig activity in the forested areas ofthese watersheds where feral pigs are commonlyfound.

The overall goal of this study was to investigate theeffects pigs on runoff, erosion, and FIB (Enterococcussp.) in a Hawaiian watershed. The specific objectivesof this paper were to (1) quantify ENT in runoff fromforested areas of the watershed, (2) determine if feralpigs impact ENT in runoff and soils, (3) investigatetemporal and spatial differences of ENT in runoff, and(4) examine correlations among environmental varia-bles (i.e., slope, infiltration rate, soil moisture, groundcover, etc.) and ENT in runoff. Based on a literaturereview and results of previous research at these sites,four hypotheses were developed: (1) Higher rainfallintensity and throughfall will lead to higher ENTlevels in runoff during the wet season (November–April) than in the dry season (May–October); (2)higher fecal inputs to unfenced plots exposed to feralpig activity will lead to higher ENT levels in runoffand soil from the unfenced compared to fenced plots;(3) of all environmental variables measured, groundcover and soil moisture will have strongestcorrelations with ENT in runoff as ground coverinfluences soil infiltration and erosion processes,and ENT survival is thought to be higher underwetter antecedent soil conditions (Cools et al.2001; Byappanahalli and Fujioka 2004) whichdirectly affect runoff; and (4) TSS in runoff willpositively correlate with ENT in runoff as bacteriaare thought to associate with soil particles in porewater, runoff, and surface water (Goulder 1977; Frieset al. 2006).

314 Water Air Soil Pollut (2011) 221:313–326

2 Materials and Methods

2.1 Study Area

Manoa is a 2,528-ha, heavily populated, mixed-usewatershed that includes downtown Honolulu andWaikiki Beach. Although highly urbanized in thelower and middle reaches, the upper reaches of thewatershed are mostly forested and uninhabited bypeople. Feral pigs are the only large non-humanmammal that occurs in the watershed, unlike otherHawaiian Islands where deer (Axis axis, Odocoileushemionus), cattle (Bos taurus), and goats (Capraaegagrus) occupy the same habitat as pigs. The upperparts of the watershed include areas with varyingslope, rainfall, and vegetative cover (Table 1).

2.2 Site Selection and Layout

In the spring of 2007, eight sites in the Manoawatershed were selected to investigate runoff process-es and the effects of feral pig exclusion (Browning2008). Using a geographic information system (GIS;ESRI, Redlands, CA, USA), a map of slope character-istics throughout the watershed was created and areaswith slopes between 5% and 30% were identified aspotential sites. Final site selection was based on easeof accessibility and proximity to existing trail net-works as well as homogeneity of slope/vegetation ateach site. Randomization of slope during site selec-tion was not feasible due to the limited areas that metboth criteria. Unfortunately the Palolo site wasvandalized repeatedly throughout the study period

and had to be abandoned, leaving only seven sites forthis study (Dunkell 2009).

Each site is approximately 10×10 m. Twopaired 10×5-m plots were established at each site:one plot surrounded by exclusion fencing and theother unexclosed (Fig. 1). The plots were orienteddown the slope to effectively capture the natural pathof overland flow at each site. Fences were con-structed of 14-gauge utility fencing 0.91 m tall andheld in place with metal posts. Barbed wire wasstrung along the bottom edge of each fence to furtherprevent pig ingress. During construction, throughfallgauges were affixed to posts directly centeredbetween the paired plots at each site. In December2008, four more throughfall gauges were added toeach site.

2.3 Runoff Plot Design and Maintenance

Following fence installation, runoff plots were con-structed within both unfenced and fenced plots at eachsite. Runoff plots were 4.2 m long×1.2 m wide,oriented down the prevailing slope of each site. Toprevent additional runoff entering from outside theplot, 15-cm tall plastic dividers were buried roughly7.5 cm into the soil along the upslope and outer edgesof each runoff plot. These plastic pieces formed theframework that channeled runoff to a central collector.This central collector was located at the down slopeend of the runoff plot, consisting of a triangular metalrunoff collector that funneled all runoff into a 10×5-cm opening. A feed tray connected the collector to an18.9-L bucket for storing runoff. Water-tight lids were

Table 1 Characteristics of the seven sites in Manoa watershed

Site Elevation (m)a Slope (%)b Soil seriesa,c

Lyon 215 15.5 Lolekaa (Palehumults)

Manoa Cliffs 450 8.0 Rough mountainous land (unclassified)

Manoa Falls 171 17.0 Lolekaa (Palehumults)

Pauoa Flats 538 6.0 Rough mountainous land (unclassified)

Puu Pia 209 26.0 Lolekaa (Palehumults)

Round Top 340 25.5 Tantalus (Hapludands)

Waahila Ridge 340 14.0 Manana (Palehumults)

a Elevation and soil series information were obtained through a GIS analysisb Slopes were recorded on site using a handheld clinometerc Soil taxonomic classification in parentheses according to USDA (1972)

Water Air Soil Pollut (2011) 221:313–326 315

affixed to the top of each bucket to prevent through-fall from directly entering the bucket. Runoff collectorcovers were constructed to prevent direct throughfallon the collector and installed in December 2008.

During initial monitoring of runoff, three of theeight sites (Pauoa Flats, Manoa Cliffs, and Lyon)were observed to receive particularly high throughfall.In an attempt to prevent collection buckets fromoverflowing, these sites were fitted with a feed traythat diverted half of all runoff into the collectionbuckets instead of receiving 100% (El-Swaify 1989).The other half was diverted around the bucket andcontinued down slope. For these sites, the volumewas doubled after initial calculation. During allinstallation, maintenance, activation, and collectionactivities, no one ever set foot in any of the runoffplots. Soil samples were taken within the sites, yetoutside the runoff plots so as not to disturb thevegetation, litter, and soils.

2.4 Activation and Sampling

Runoff samples were collected from June 2008 toApril 2009. Activation included emptying throughfallgauges, collecting soil samples for moisture analysis,and emptying and cleaning the runoff collectionbuckets. Runoff was removed with a hand-operated

suction pump, and then the inside surfaces ofcollection buckets were thoroughly cleaned and dried.Sterile latex gloves were worn at all times duringemptying and cleaning procedures. Collection timeswere determined by observing weather conditions andmonitoring the online USGS rain gauge located in theManoa watershed. When the rain gauge recordedsignificant rainfall (typically >2 cm) during theactivation period, collection was initiated. Collectionoccurred immediately or shortly after the rain events(within 6–8 h) to minimize the amount of time therunoff water would remain in the collection buckets.

2.5 Runoff Collection and Analysis

Before any samples were removed from the collectionbuckets, the depth of runoff in the bucket wasmeasured with a meter stick to calculate the totalrunoff volume. Sterile latex gloves were worn at alltimes and changed prior to each new measurement.The runoff in the bucket was then thoroughly mixedwith the meter stick, and a water sample was collectedin an acid-washed 500-mL bottle. One runoff watersample was collected from each plot (fenced andunfenced) at each site (n=7) for a total of 14 samples(2 plots×7 sites) per rain event. Samples were takenback to the lab and total suspended solids (TSS) in therunoff were measured by vacuum filtration of 100 mLof sample (US EPA 1971).

2.6 Analysis of ENT in Runoff

After collecting a subsample for TSS, a second runoffwater sample was taken in a sterile 100-mL IDEXXcontainer (IDEXX Laboratories, Westbrook, ME,USA). Samples were taken to the laboratory on iceand immediately processed for ENT. In some cases,samples were refrigerated until analysis, which wouldfollow within 12 h of sample collection. In the lab, thesamples were transferred by pipette (using sterile,disposable tips for each sample) to a new sterilecontainer and mixed with Enterolert reagent (IDEXXLaboratories, Westbrook, ME, USA). Samples wereshaken by hand a minimum of 40 times to ensureproper mixing. Samples were diluted when the runoffcontained high levels of sediment, or if ENT levelsfrom previous samplings at that plot were >2,500MPN 100 mL−1. At least one duplicate was made persample per sampling event. A control sample consist-

Fig. 1 Plot layout at each of the seven sites in the Manoawatershed. Each site was oriented so both fenced and unfencedplots had similar slope and vegetation. The letter R denotesrunoff collection buckets and the letter T denotes throughfallgauges


ing of 100 mL of deionized water was also processedaccording to the same methods.

After mixing, samples were poured into Quanti-Trays (IDEXX Laboratories, Westbrook, ME, USA).The trays were heat-sealed and placed into a 41°Cincubator for 24–28 h. After incubation, samples wereremoved and placed under an ultraviolet light to countthe number of fluorescing wells. Wells were countedonly if fluorescence was complete (only brightestwells were counted as positive). To determine theMPN of colony forming units, the IDEXX Quanti-Tray MPN sheet was used. For the June and Julyevents, MPNs were determined on undiluted samples.As a number of the MPN values for July exceeded thedetection limits (2,419 MPN 100 mL−1), the MPNvalues for the remaining months were calculatedbased on tenfold dilution with DI water. MPN forthese dilutions was multiplied by a factor of 10 todetermine the final value. For statistical analyses,MPN values below and above the detection limitswere set to the detection limits (1 and 24,196 MPN100 mL−1) and values were then log10-transformedprior to statistical analyses.

2.7 Analysis of Soil ENT

Soils were collected from all 14 plots in August 2009which occurred after runoff sample collection periodended. Individual sterile plastic spoons were used tocollect soils at each plot to ensure no cross contam-ination. Samples were taken at approximately 30 cmfrom each corner of the runoff plots (n=4 per plot),composited in sterile plastic bags, and transported onice to the laboratory. Quantification of soil ENT wasbased on USGS techniques (Myers et al. 2007) and aprevious study in Hawaii (Ragosta 2007). Briefly, 5 gof soil was weighed and placed in a sterile IDEXXbottle. One hundred milliliters of 0.15-M NaCldispersant solution was added to the sample. Samplebottles were then shaken on a rotary shaker table for45 min.

After shaking, samples were left to settle for 30 s,and a 10-mL aliquot was then removed from the topof the solution by sterile pipette and transferred to anew sterile IDEXX bottle (Boehm 2007). Ninetymilliliters of DI water was added along with theEnterolert reagent. Samples were placed on a shakertable for another 5 min. After the final shaking,samples were then heat-sealed in Quanti-Tray 2000

trays and processed as described previously. Soil ENTdata were expressed as MPN per dry weight of soilsample. As MPN values for the soils did not exceedthe detection limits and were more normally distrib-uted, the soil ENT data was not log10-transformed.

2.8 Estimation of Other Environmental Variables

A number of other environmental variables thought toinfluence runoff and ENT levels were measuredincluding slope, soil series, soil water content,throughfall, infiltration rate, forest canopy andunderstory species composition, stem density, basalarea, and ground cover. The paragraphs belowsummarize the methodology used to determinethese characteristics.

Global positioning system (GPS) coordinates foreach site were recorded in the field and added to aGIS. These GPS coordinates were overlaid on a GISthat included maps of NRCS soil series based on thelatest soil survey of Oahu (USDA 1972). The sevensites represented four different soil series: Tantalus,Lolekaa, Manana, and Rough Mountainous Land(Table 1).

Gravimetric soil water content was determinedduring the activation phase each month from eachsite. A 2-cm-diameter soil corer was used to collectthree separate randomly located samples from theupper 5 cm of the soil profile. Samples were collectedfrom inside the fenced and unfenced area (but outsideof the runoff plots). Individual samples were thencomposited in a sterile plastic bag for each plot ateach site. A standard all-weather rain gauge (Produc-tive Alternatives, Fergus Falls, MN, USA) was usedto measure throughfall (millimeters) of rain events. Aspart of the activation process, each throughfall gaugewas emptied and a thin layer of mineral oil was addedto prevent evaporation. Infiltration rate and thecoefficient of saturation (Ksat) were determined ateach plot using a tension infiltrometer (Soil Measure-ment Systems, Tucson, AZ, USA).

Ground cover at all sites was recorded for bothrunoff plots. A measuring tape was used to establish atransect line, and a visual assessment of ground coverwas taken every 3 cm along three 1.2-m transectsequally spaced along the runoff plot. Visual determi-nation of ground cover was made from a top-downview above the transects. Ground cover was dividedinto the following categories: live plant, standing dead


plant, coarse woody debris, litter, bare soil, rock, androot. Coarse woody debris was defined as woodydebris >2 cm diameter. Litter included detritus,leaves, and any woody debris <2 cm diameter. Inaddition, photos were taken of the plots throughoutthe monitoring period, and descriptions of pig activity(i.e., hoofprints, browsing, and rooting) within theplots were recorded for each month of the study.Finally, motion-activated game cameras (CuddlebackCapture Infrared 3.0 Megapixel model; Non Typical,Inc., Green Bay, WI, USA) were installed at Round-top, Manoa Falls, Manoa Cliffs, and Waahila Ridgeafter runoff collection stopped during summer 2009 tomonitor feral pig activity at these sites.

2.9 Statistical Analyses

All statistical analyses were performed using SASversion 9.1 (SAS Institute, Cary, NC, USA). A GLMANOVA was used to determine site differences invariables that were only measured once such asground cover and soil ENT. For the GLM ANOVAs,a post hoc comparison of means was carried out usingDuncan’s multiple range test. A repeated measuresANOVA (Proc MIXED) was used to distinguishdifferences over time (i.e., across months), amongsites, and between fenced and unfenced treatments.Month was the repeated factor in these analyses. ProcMIXED uses the “containment method,” and depend-ing on the homogeneity of variances, denominatordegrees of freedom may vary from one model toanother. A least squares procedure was used for posthoc mean comparisons. As the runoff ENT data werehighly variable, the tables and figures report thestatistics from the log10 data. The more normallydistributed soil ENT data were reported in the rawunits. Spearman correlation was used to evaluaterelationships among ENT and all environmentalvariables. A multiple stepwise regression (MSR) wasalso used to determine the best predictors of ENT inrunoff.

3 Results

3.1 Enterococci in Runoff

Out of a total of 154 measurements (7 sites×2 plots×11 events), ENT values were below the detection limit

for 11 measurements and above the detection limit(>4.38 log MPN 100 mL−1 or >24,196 MPN100 mL−1) for 28 measurements. For nine measure-ments (three in July, two in August and September,and one in February; eight of nine were from thePauoa Flats site), no runoff was observed andtherefore no determination of ENT in runoff couldbe made. Throughout the course of the study, ENTlevels in runoff were highly variable in space and timewith the mean log ENT of 2.52 (±0.13 or 1 standarderror (SE)) MPN 100 mL−1. The median log ENT was2.68 MPN CFU 100 mL−1. The mean log ENT inrunoff from fenced plots was 2.38 MPN 100 mL−1,and the median was 2.68 MPN 100 mL−1. The meanlog ENT for the unfenced plots was 2.65 MPN100 mL−1, and the median was 3.06 MPN 100 mL−1.The repeated measures ANOVA indicated that monthand the month×site interaction accounted for asignificant proportion of the variance in the ENT inrunoff data (Table 2; Fig. 2a). Neither site, treatment,nor any other interaction term accounted for asignificant proportion of the variance (Table 2).

The wet season months of October, November, andDecember had higher ENT in runoff than any of theother months (Fig. 2b). The December event had thehighest throughfall, TSS in runoff, and one of thehighest ENT in runoff values. The dry season monthsof June, July, and September had the lowest ENTlevels in runoff, each with <2.0 log (MPN 100 mL−1;Fig. 2b).

Although not significantly different, mean log ENTin runoff values were lower at Pauoa Flats andWaahila Ridge than any of the other sites (Fig. 2c).Lyon and Round Top appeared to have slightly highermean log ENT in runoff than Manoa Cliffs, ManoaFalls, and Puu Pia. While Pauoa Flats had the highest

Table 2 Repeated measures ANOVA model for enterococcilevels in runoff

Source Num. df Den. df F statistic p value

Month 10 60 18.20 <0.0001

Site 6 1 8.42 0.26

Treatment 1 1 3.02 0.33

Site×month 60 60 1.80 0.01

Month×treatment 10 60 0.83 0.60

Site×treatment 6 1 0.18 0.94

df degrees of freedom


TSS in runoff, it also had lowest ENT in runoff.Waahila Ridge had the lowest throughfall and runoffvolume and correspondingly low ENT in runoff.

3.2 Enterococci in Soils

In August 2009, soil ENT ranged from 14 to 511MPN g−1. The mean soil ENTwas 128 MPN g−1 (±43(1 SE)) and the median was 58 MPN g−1. Due to alack of replication, the soil ENT data were analyzedas two one-way ANOVAs: the first comparing meansamong sites and the second comparing meansbetween treatments. The first ANOVA indicatedsignificant differences in soil ENT among sites(Table 3; Fig. 3). Specifically, Lyon Arboretum hadthe highest mean soil ENT, followed by Manoa Cliffsand Manoa Falls. Waahila Ridge had the lowest soilENT, followed by Roundtop and Pauoa Flats. Thesecond one-way ANOVA indicated no significantdifference between treatments (F=0.01, p=0.94)

While the treatment effect was not significant,unfenced plots had a median value of 77 MPN g−1

compared to a median value of 24 MPN g−1 forfenced plots. Sites with the greatest pig disturbance(based on visual observations and ground covertransects) also had higher soil ENT in unfenced plots(Fig. 4). For example, Puu Pia had eight times highermean soil ENT in the unfenced (114 MPN g−1) thanthe fenced plot (14 MPN g−1) and Roundtop hadnearly two times the soil ENT levels in the unfenced(39 MPN g−1) than the fenced (20 MPN g−1) plot.

3.3 Correlation of ENT with Environmental Variables

The only variables that had significant Spearmancorrelations with ENT in runoff were runoff volumeand soil ENT (Table 4). The strongest correlation ofENT in runoff was with soil ENT (r=0.74, p=0.002).While ENT levels in runoff and soils were positivelycorrelated, neither was correlated with TSS or soil

Fig. 2 a Mean log enterococci (ENT) levels in runoff per sitefor each month (site×month interaction). Error bars represent ±1standard error. Data are arranged alphabetically by sites and then

from June 2008 to April 2009 within sites. b Mean log ENTlevels in runoff per month averaged across months. c Mean logENT levels in runoff per site averaged across sites


moisture. Throughfall, soil moisture, and bare soilcover were thought to perhaps be important environ-mental predictors of ENT in runoff, however none ofthese variables was significant even at α=0.1. Slopehad a Spearman correlation of 0.53 with runoff ENTwith a p value of 0.0504, which just missed the α=0.05 cutoff for significance.

Soil ENT was positively correlated with rockcover, runoff volume, and RTR (Table 4). Runoffvolume had a high Spearman correlation with soilENT (r=0.67, p=0.01), which was even stronger thanthe correlation of runoff volume with ENT in runoff.Soil ENT was not correlated with either soil moistureor soil total carbon (Ct, previously measured at theseven sites; Browning 2008). The correlations of ENTin runoff with the environmental variables were alsotested separately for dry season and wet seasonmonths (Table 4). During the dry season, TSS andsoil moisture had negative correlations with runoffENT and RTR had a positive correlation with runoffENT. During the wet season, runoff ENT wassignificantly correlated with runoff volume, soilENT, and RTR.

Runoff volume, slope, and soil ENT were selectedas important predictors of log ENT in runoff andentered into a MSR. The runoff–throughfall ratio wasnot selected as an important predictor variable

because of the direct relationship with runoff volume.Runoff volume and slope were significant predictorsof ENT in runoff (Log ENT fMPN100mL�1g� � ¼ 1:02þ0:11 ROVolume fLg½ � þ 0:04 Slope f%g½ �; r2 ¼ 0:65;p ¼ 0:01).

4 Discussion

4.1 Enterococci in Runoff

The first objective of this paper was to quantify ENTin runoff from forested areas of the Manoa watershed.Previous research has suggested that ENT are natu-ralized and reproduce in the moist, warm environmentof subtropical islands such as Hawaii, Guam, andPuerto Rico (Fujioka et al. 1999; Byappanahalli andFujioka 2004; Hartel et al. 2005), and these resultspartially agreed with their findings. While ENT inrunoff was not observed at every site for every rainevent, each site did have ENT in runoff for multiplerain events.

The second objective was to determine whetherferal pigs increase ENT levels in runoff and soils. Theexclusion fences had been in place over a year at thestart of the study, so the fenced plots were free of piginfluence for at least that amount of time. Wehypothesized that both runoff and soil ENT wouldbe increased by the presence of feral pigs. Thishypothesis was partially supported by the data. Whilemedian ENT levels in runoff from unfenced plotswere 2.4 times higher than fenced plots, differencesacross the fencing treatment were inconsistent acrossall sites and months. Another recent feral pigexclusion study observed similar results with tempo-ral effects having a greater influence on variables suchas turbidity, pH, and anoxia than the exclusionfencing (Doupe et al. 2010).

There were other trends in our dataset such ashigher runoff and soil ENT from unfenced plots atcertain sites that had a higher occurrence of pigdisturbance (Manoa Cliffs, Puu Pia, Waahila Ridge,

0

100

200

300

400

500

600

LY MC MF PF PP RT WR

MP

N/g

so

il

Site

A

C

B

BC

CBC

C

Fig. 3 Mean enterococci (ENT) levels in soil among sites inAugust 2009. Error bars represent ±1 standard error. Lettersindicate significantly different means according to least squaredmeans

Source df Sum of squares Mean squares F statistic p value

Site 6 321,449.72 53,574.95 46.09 <0.0001

Error 7 8,136.87 1,162.41

Total 13 329,586.59

Table 3 One-way ANOVAfor soil enterococci with siteas the main effect

df degrees of freedom


and Roundtop). For example, at Manoa Cliffs, pigrooting was observed several times during the runoff

collection period, and pig disturbance of the unfencedrunoff plot was confirmed after runoff sampling wascompleted on multiple occasions by game cameras.Thus, it was no surprise that ENT in runoff from theunfenced plot at this site was on average 2.7× greaterthan the unfenced plot (unfenced plot=2.94 log MPN100 mL−1 or 866 MPN 100 mL−1; fenced plot=2.50log MPN 100 mL−1 or 317 MPN 100 mL−1). WaahilaRidge was another site where pig rooting wasobserved in the unfenced plot, and ENT levels wereon average 2.3× as high in the unfenced plot (2.23 logMPN 100 mL−1) compared to the fenced plot (1.85log MPN 100 mL−1).

However, fenced plots also showed high levels ofENT in runoff and soils. The presence of rats (Rattusspp.) and/or mongoose (Herpestes javanicus) insidethe fenced plots may explain this result. At Roundtop,for instance, avocado fruits that fell inside the fencedplot were seen to be partially eaten, and tooth marksthe size of rats and mongooses were evident in theflesh. Feces from rats and mongoose are potentialsources of ENT (Oshiro and Fujioka 1995), and bothcould presumably access the fenced plot. However,no obvious rat or mongoose feces were observed inthe plots.

While the increase in ENT suggested fecal con-tamination, the use of ENT as an indicator of fecalcontamination is a contentious subject. This isespecially true for subtropical and tropical environ-ments where soil, water, and even plants arethought to be potential reservoirs or sources ofENT (Hardina and Fujioka 1991; Fujioka et al.1999). Some have suggested that ENT have limitedutility and should be used with caution especially inHawaii and other sub/tropical locations (Hardina andFujioka 1991; Fujioka et al. 1999; Byappanahalli andFujioka 2004). Others have taken an opposing view,believing ENT are the best option available as nosuperior method to rapidly and inexpensively mea-sure fecal contamination exists (Ragosta 2007).Another reason for not recovering ENT in thesesoils may be due to temporal and spatial patchinessin distributions of these FIB in the environment(Hartel et al. 2005; Boehm 2007).

The data from this study suggested that there wasno overall effect of pigs across all sites and rainevents. It may be that more time is needed for theeffects of fencing to emerge, or that more sites areneeded to provide a better estimates of the processes

Table 4 Spearman correlation coefficients for ENT andenvironmental variables

Enterococcia Soil ENTb ENT dryc ENT wetd

TSS – – −0.71 –

Throughfall – – −0.75 –

Soil moisture – – – –

Litter – – – –

Bare – – – –

Rock – 0.61 – –

Live – – – –

CWD – – – –

ROVol 0.56 0.68 – 0.79

Stem density – – – –

Basal area – – – –

Slope – – – –

Ksat – – 0.63 –

Soil ENT 0.55 – – 0.67

Soil carbon – – – –

RTR – 0.71 – 0.69

Non-significant results labeled with a hyphen

TSS total suspended solids, Litter plant litter ground cover, Barebare soil ground cover, Rock rock ground cover, Live live plantground cover, CWD coarse woody debris cover, ROVol runoffvolume, Ksat saturated hydraulic conductivity, RTR runoff tothroughfall ratioa Correlations with the mean ENT in runoff across all monthsb Correlations with soil ENT measured in August 2009c Correlations with mean ENT in runoff from the dry seasonmonthsd Correlations with mean ENT in runoff from the wet seasonmonths

0

100

200

300

400

500

600

700

LY MC MF PF PP RT WR

MP

N/g

so

il

Site

Fenced

Unfenced

Fig. 4 Mean enterococci (ENT) levels in soils in fenced versusunfenced plots across all sites. Error bars represent ±1 standarderror


being studied and more power for the statisticalanalyses. Alternatively, the contribution of feral pigsto total fecal loading may be relatively smallcompared to contributions from other mammals andbirds. However, as feral pigs are the only largeungulate in this watershed, it seems unlikely thatother mammals would have a larger contribution tototal fecal loading.

Feral pig activity may increase ENT in runoffthrough a variety of mechanisms. First, they mayincrease soil ENT level via direct fecal inputs. Thissoil may then be detached during rain events beexported from the plot in surface runoff as rainfallintensity and duration increase. Second, even in theabsence of fecal inputs, pig activity may disturbsurface soils and increase detachment and erosion ofsoils and ENT already present within the soil. As TSSin runoff was not significantly different betweenfenced and unfenced plots, it seems likely that theincrease in ENT in runoff from unfenced plots iscoming directly from the pigs rather than fromphysical erosion processes.

The third objective was to investigate temporal andspatial differences in ENT levels in runoff. Entero-cocci in runoff ranged from below detection limitduring the lighter summer rain events to above thedetection limits for the larger winter rain events. Thisbehavior was different from that observed with otherpollutants that often build up during dry conditionsand then wash off in rain events regardless of theseason (Kayhanian et al. 2007). It could be that ENTare dislodged from the soil by the greater raindropimpacts potentially associated with larger rain events.Another study of ENT in sediments from Georgia,New Hampshire, and Puerto Rico also showed thistype of extremely high temporal variability (Hartel etal. 2005). We hypothesized that ENT in runoff wouldbe higher in the wet season (November–April) than inthe dry season (May–October). Our data did notsupport this hypothesis, as a month×site interactionindicated that seasonal (monthly) trends were notconsistent across the sites (Fig. 2). Despite theinteraction, there was a trend of higher ENT in runofffrom the wet season months (i.e., October, November,December) than the dry season months (i.e., June,July, September). October is a month when strawberryguava (Psidium cattleianum), a food source of feralpigs, is fruiting in many parts of the watershed, andseveral of the sites are located near large strawberry

guava stands. This may help to explain the higher ENTvalues observed in the October event. Another study ofENT in California streams found that FIB levels werethe highest in summer months and that there was apositive relationship between FIB levels on streamwater temperature, but they sampled baseflowrather than storm event conditions unlike our study(Tiefenthaler et al. 2009).

In terms of spatial variability, Roundtop, Lyon,Manoa Falls, and Manoa Cliffs had the highest ENTlevels in runoff, and these sites also showed evidenceof pig disturbance in the form of hoof prints,browsing and rooting on multiple occasions. Therewas less observed pig damage at Lyon, perhapsbecause the Arboretum has a pig hunting programand has even set up a pig blind in an area severalhundred yards upslope from the runoff plots. TheArboretum staff report that many rats live in this area,and this may partially contribute to the high ENTvalues observed at this site. Manoa Cliffs, ManoaFalls, and Lyon Arboretum also had high throughfalllevels suggestive of a relationship between through-fall and ENT in runoff, but another site with highthroughfall, Pauoa Flats, had the second lowest ENTlevels in runoff.

4.2 Enterococci in Soils

The range in soil ENT values reported in this studywas similar to a previous study where valuesoccasionally exceeded 1,000 MPN g−1 but frequentlywere as low as 10 MPN g−1 (Hartel et al. 2005). Astudy conducted in the Waipa watershed on the islandof Kauai showed a lower range of soil ENT (Ragosta2007) than our study. Samples from multiple locationsin the Waipa watershed contained <3–60 MPN g−1,and 75% of samples had levels of ENT below thedetection limit (Ragosta 2007). Another study of theWaipa watershed found that the 95% confidencelevels for ENT in beach sands above the high tideline were 32–316 MPN (100 mL sand)−1 and near theshoreline were 20–100 MPN (100 mL sand)−1 (Kneeet al. 2008). In our study, the Lyon Arboretum sitehad the highest soil ENT, and these values were morethan double those of any other site in our study. Meansoil moisture at Lyon was just over 50%, less thanManoa Cliffs or Pauoa Flats. Lyon also containedhigher levels of rock cover than any of the other sitesand usually had some of the highest runoff volumes.


The values from Lyon were lower than those reportedfor sediments from Georgia, New Hampshire, andPuerto Rico (Hartel et al. 2005) and lower than thosereported for foreshore sand at a Lake Ontariofreshwater beach (105 MPN g−1; Edge and Hill 2007).

Soil ENT in this study did not show significantdifferences between fenced or unfenced treatments,though there were significant site differences. As soilswere only sampled in August 2009, seasonal differencesremain unmeasured. The largest difference betweenfencing treatments was seen at Puu Pia where mean soilENTwas eight times higher in the unfenced than fencedplot. Pig disturbance was observed in the unfenced plotduring at least six of the 11 months of study. An obviouspig trail passed approximately 20 m south from the site,and pig rooting was common throughout the generalarea. This site also contained much higher levels of TSSand ENT in runoff in the unfenced versus the fencedplot.

4.3 Correlation of ENT with Environmental Variables

The final objective was to investigate correlationsamong environmental variables and ENT in runoff.Hypothesis 3 predicted that of all environmentalpredictors, ground cover, and soil moisture wouldhave the strongest correlation with ENT in runoff.The data did not support this hypothesis as ENT inrunoff was correlated with runoff volume and soilENT, but not with soil moisture or any of the groundcover variables. The positive correlation with runoffvolume could be explained by the fact that largerrunoff events had high intensity throughfall andtherefore were more likely to detach ENT from soilsand other surfaces. Similar results were reported for astudy of ENT in runoff from pastureland in Virginiawhere, for the majority of cases, the authors observedthe highest FIB concentrations at the highest runoffflow rates (Soupir et al. 2006). An analogous study inVirginia found that increases in runoff volume andpeak runoff rate helped increase bacterial concen-trations in runoff (Mishra et al. 2008). A study in theNeuse River Estuary in North Carolina reported thaton average the majority of FIBs were free livingrather than associated with sediments (Fries et al.2006). In our study, the fact that only two of 14variables measured were related to ENT in runoffsuggests that more research is needed on this processin Hawaiian and other watersheds.

Hypothesis 4 stated that TSS in runoff wouldpositively correlate with ENT in runoff. This hypoth-esis was also not supported by the data. It could bethat the bacteria are more prevalent on the groundsurface and therefore are carried in runoff regardlessof sediment disturbance. Alternatively, while ENTwere present in soils, the levels were less than theupper limits of levels seen in studies from thecontinental USA. This suggests that ENT may beassociated with animals and deposited on litter, rocks,plants, and soil. Birds are also known to be a sourceof ENT contamination at beaches (Oshiro and Fujioka1995; Haack et al. 2003) and could have depositedthese bacteria inside both fenced and unfenced areas,although birds were not observed to perch on the sitefencing nor were bird nests found on the fencing orrain gauges. Chickens were observed on severaloccasions near two sites (Roundtop and WaahilaRidge) but never within fenced or unfenced areas.Another explanation for the lack of correlation of TSSin runoff and ENT in runoff may be due to thepotentially limited efficacy of bacterial elutriationsfrom soils with the IDEXX methods. Many Hawaiiansoils have high clay contents (USDA 1972) that canaffect recovery of bacteria such as ENT as thesebacteria will sorb to clay particles in runoff (Soupirand Mostaghimi 2010). Thus, ENT could still bepresent in runoff but not detected with the IDEXXassay.

The positive correlation of runoff ENT with soilENT seems obvious; sites with more soil ENT wouldlikely have more runoff ENT. It was surprising thatthere were no other correlations in the data. The lackof correlation with soil moisture was also unexpectedas wet soils are thought to be more accommodating tosurvival of the bacteria (Hartel et al. 2005; Donlan etal. 2007). Likewise, the lack of correlation of soilENT with TSS in runoff was unexpected. Bacteria areknown to associate with sediment particle surfaces,and sediments in water protect bacteria from environ-mental conditions (i.e., sunlight/UV radiation, preda-tion) that could be hazardous to their survival(Anderson et al. 2005).

5 Conclusions

While ENT in runoff from unfenced sites was notdifferent than that from paired fenced sites, ENT in


runoff was highly variable across months and sites.The data suggest that other factors such as presenceof other mammal (i.e., rat, mongoose) or birdspecies, unmeasured soil properties such as textureor temperature, or other environmental variablesmay be important in influencing ENT in runoff andsoil. Soil ENT were present at all sites and at levelssimilar to those reported in studies from areas inthe continental USA. There were high ENT levelsin both runoff and soils from unfenced plots withthe high levels of pig disturbance (Puu Pia, WaahilaRidge, and Roundtop).

Effects of pig disturbance on runoff and soils weredifficult to elucidate, but it appears pigs and othermammals are influencing ENT levels in runoff andsoil at certain sites. However, an overall effectacross all sites and months was not detected. Ourresults do indicate that the forested headwaters ofHawaiian watersheds can serve as sources of ENTto downstream freshwater and coastal ecosystems.Export of ENT appears to be greatest in the wetseason. To minimize effects on human and ecosys-tem health, we recommend that public healthauthorities employ greater signage and warnings toresidents and tourists who use and recreate instreams and coastal waters.

Comparative studies of fencing to exclude feralpigs or inhibit their access into sensitive forestedareas are few (Campbell and Long 2009), and thesepaired plots provide an excellent opportunity tostudy feral pig impacts on soils, vegetation, waterquality, and FIB transport. In addition to elucidatingmonthly and site differences in runoff and theirinteractions, this research provides baseline condi-tions for further research at the runoff plots. As timegoes on, differences between fenced and unfencedplots are expected to continue to develop, and furtherresearch is needed verify this expectation.

Acknowledgments We would like to thank Drs. C. Litton,C. Lepczyk, and A. Fares for their guidance, help withstatistics, and use of equipment. Thanks also to C.Browning, B. Cooke, M. Chynoweth, S. Henly-Shepard,S. Khan, D. Marciel, L. Muller, E. Phares, A. Quidez, S.Stebbing, and A. Williams for assistance with field and labwork. This work was supported by USDA NationalIntegrated Water Quality Program Agreement No. 2004-51130-02258 to C.E. and McIntire-Stennis Forestry Re-search grant HAW00108-M to G.B.

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