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Effects of Fire and Groundwater Extraction on Alkali MeadowHabitat in Owens Valley, CaliforniaAuthor(s): Daniel W. Pritchett and Sara J. ManningSource: Madroño, 56(2):89-98. 2009.Published By: California Botanical SocietyDOI: http://dx.doi.org/10.3120/0024-9637-56.2.89URL: http://www.bioone.org/doi/full/10.3120/0024-9637-56.2.89

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EFFECTS OF FIRE AND GROUNDWATER EXTRACTION ON ALKALIMEADOW HABITAT IN OWENS VALLEY, CALIFORNIA

DANIEL W. PRITCHETT

401 East Yaney St., Bishop, CA 93514skypilots@telis.org

SARA J. MANNING1

Inyo County Water Department, P. O. Box 337, Independence, CA 93526smanning@telis.org

ABSTRACT

Alkali meadow habitat—a groundwater dependent ecosystem—is rare in California, and itsresponse to fire has not been documented. We sampled vegetation in this habitat across a pumping-induced depth-to-water (DTW) gradient immediately before, then eight weeks after, a summerwildfire. After the fire in the burned area, we documented vigorous re-growth of native perennialgrasses in areas of shallow groundwater but no re-growth of shrubs. The dominant grass Sporobolusairoides flowered in the shallow end of the DTW gradient but never advanced beyond vegetativephenology (leaves) in the drawn-down end. DTW explained 77% of the grass cover variance in thepost-fire burned area, and 87% and 94% of the grass cover variance in the pre-fire and post-fireunburned (control) areas, respectively. This suggests that post-fire re-growth was re-establishing acover-DTW relationship already present before the fire. The principal short-term fire effect was theelimination of shrub cover due to apparent shrub mortality. Our study shows fire may be an effectivemanagement tool for regenerating alkali meadow in areas of shallow groundwater. However, in areassubject to long-term water table drawdowns we found negligible grass re-growth and increasedvulnerability to erosion, suggesting fire may accelerate the process of type-conversion from meadow toxeric shrubland.

Key Words: Distichlis spicata, fire, groundwater-dependent, groundwater pumping, habitat loss,Sporobolus airoides, vegetation change, water table.

On July 6, 2007, lightning strikes along thebase of the eastern escarpment of the SierraNevada in Owens Valley, California, startedseveral fires. They became known as the InyoComplex fire as they coalesced and burned.14,000 ha, almost destroying the towns ofIndependence and Big Pine. The fires started insagebrush/bitterbrush shrubland high on alluvialfans and were blown by strong winds downslopethrough Mojave Desert shrubland to burn alkalimeadow habitat at the fan toes.

Re-growth after the fire varied considerably inthe alkali meadow. In some areas we observednative perennial C4 grasses, Sporobolus airoides(alkali sacaton) and Distichlis spicata (saltgrass,nomenclature follows Baldwin et al. 2002), re-sprouting within days after the fire. In other areaswe saw no re-growth. After several weeks, grassre-growth was so robust in some areas it wasdifficult to tell that a fire had occurred.

Alkali meadow habitat is rare in California(Sawyer and Keeler-Wolf 1995), and there are fewquantitative data regarding its response to fire.Anecdotal observations made after other recentOwens Valley fires suggest S. airoides and D.

spicata recover rapidly in areas of shallowgroundwater, but we had not had the opportunityto closely monitor recovery after fires in areassubject to groundwater drawdowns. Understand-ing the response of alkali meadow to fire in areasof lowered water table is important becausedrawn-down water tables underlie much of thishabitat in Owens Valley. The Inyo Complex fireburned a portion of alkali meadow habitat whichcovered a large gradient in depth-to-water table(DTW) at the time of the fire. It thus offered anunplanned opportunity to observe alkali meadowresponse to fire in areas of both shallow anddeeply drawn-down groundwater.

Our primary objectives were to: 1) documentspecies composition, cover, frequency, and phe-nology of the observed post-fire growth through-out the burned portion of the study area; 2)compare characteristics of pre- and post-firevegetation; and 3) determine the extent to whichDTW could account for vegetation patterns inthe study area.

METHODS

Study Site

Owens Valley lies on the western edge of theGreat Basin in eastern California at an elevation

1 Present address: Big Pine Paiute Tribe Environmen-tal Department, P.O. Box 700, Big Pine, CA 93513.

MADRONO, Vol. 56, No. 2, pp. 89–98, 2009

of approximately 1200 m above mean sea level.The Sierra Nevada borders the valley on the west,and the White and Inyo Mountains flank itseastern side. Owens Valley summers are hot anddry; winters are cold, and more than three-quarters of average annual precipitation fallsduring the October to March cold period.Although the climate is arid, with average annualprecipitation of 130 mm, abundant water fromSierran snowmelt flows into Owens Valley andannually recharges shallow groundwater aquiferswhich underlie thousands of hectares of the valleyfloor (Hollett et al. 1991). As a result, valley floorvegetation is dominated by phreatophytic plantspecies assembled in alkali meadow and sinkhabitats (City of Los Angeles and County of Inyo1991; Howald 2000). The growing season foralkali meadow species in Owens Valley com-mences in late March (first of spring), reaches apeak in late June when leaves and stems are fullygrown, then enters winter dormancy in earlyOctober (Sorenson et al. 1991).

Alkali meadow vegetation is characterized asgroundwater dependent because its estimatedactual evapotranspiration exceeds annual precip-itation (City of Los Angeles and County of Inyo1991). Under the classification of groundwater-dependent ecosystems by Eamus et al. (2006),alkali meadow habitat falls under the ‘‘phreato-phytic’’ category, because groundwater is notregularly expressed on the ground surface. InOwens Valley, large expanses of alkali meadowoccur at the toes of Sierran alluvial fans locatedseveral miles from open water or Owens River,and the study site is in such a setting.

Most alkali meadow habitat in Owens Valleyis on land owned by the City of Los Angeles andis managed for grazing and water export to LosAngeles by the Los Angeles Department ofWater and Power. In the mid 1980’s, ‘‘parcels’’of relatively homogeneous vegetation in LosAngeles’ holdings were delimited, mapped, andinventoried for species composition and cover.Groundwater levels and vegetation cover andcomposition on selected parcels have beenregularly monitored since 1991. The study site(Fig. 1), located approximately 12 km north ofthe town of Independence, consists of twoadjoining parcels classified in the 1980’s asalkali meadow, a classification consistent withLee’s (1912) ‘‘grassland’’ classification madeover 70 yr before. Both study site parcels weredominated before the fire by two nativephreatophytic grasses S. airoides and D. spicata,and, in places, by the encroaching shrubsArtemisia tridentata, Atriplex lentiformis subsp.torreyi, and/or Chrysothamnus nauseosus. Histor-ically, livestock grazing had occurred throughoutthe study area (typically from October throughMay), including during spring 2007. After theJuly 2007 fire, livestock were excluded from the

study area for the remainder of the 2007 growingseason.

Substrate of the study site is a combination ofancient beach, bar, or river channel sediments.These deposits lie between alluvial fan depositsupslope to the west and fluvio/lacustrine depositsof the valley floor downslope to the east (Hollettet al. 1991). Soils are moderately- to poorly-drained loams (USDA Natural Resources Con-servation Service 2002).

Vegetation Sampling

Inyo County Water Department (ICWD)monitors vegetation composition and cover eachsummer along randomly-located 50-m transectsin selected parcels. ICWD uses the point-inter-cept technique (Bonham 1989) to determinespecies composition of the top canopy layer at0.5-m intervals along the transect. The endpointsof these transects are not permanently marked,but the starting location is recorded with a GPSunit, and its randomly-generated compass bear-ing is recorded. Two weeks before the InyoComplex fire, ICWD read point-intercept tran-sects at 48 random locations throughout the twoparcels comprising the study area (Fig. 1).

We conducted visual reconnaissance of theburned area several times, starting one week afterthe fire. Eight weeks after the fire, August 30–September 6, 2007, we used GPS and compassbearings to approximately relocate then re-sample the 48 pre-fire random transect locationsin the study area. Twenty were in burned areasand 24 in un-burnt areas. Four of the 48 transectswere not sampled because they crossed the burnboundary. To increase the size and spatial extentof post-fire sampling, we randomly selected 22additional transects throughout the study site.Altogether, we obtained data from 37 transects inthe burned area and 29 from the unburned‘‘control’’ area after the fire (Fig. 1). We em-ployed the same point-intercept method usedbefore the fire to measure species compositionand estimate top layer canopy cover. We alsonoted the most advanced phenology of eachspecies sampled along each transect in the burnedarea. Phenology was not recorded along pre-firetransects nor along transects in the unburnedcontrol area.

Precipitation and Water Table Data

ICWD maintains a precipitation gauge in thestudy area, and its precipitation totaled 31 mmfor the period October 1, 2006–April 30, 2007.No precipitation was recorded from April 17,2007, until August 28–30, when 3 mm wererecorded. Average precipitation for the ICWDgauge period of record (1993–2006) was 160 mm.

90 MADRONO [Vol. 56

To show the historic DTW gradient in thestudy area we digitized the 8 ft (2.4 m) and 4 ft(1.2 m) contours from Lee’s (1912) map andincluded them in Fig. 2. Lee (1912) estimatedDTW in southern Owens Valley during theperiod 1908–1911 based on readings of 169observation wells, seven of which were in oradjacent to the study area. Lee gathered his databefore large scale groundwater pumping hadbeen initiated in Owens Valley.

To show the 2007 DTW gradient, we ob-tained DTW data collected on or near April 1,2007, from 14 observation wells in or immedi-ately adjacent to the study area (Fig. 2). Wechose April 1 DTW data because early springgroundwater levels typically represent the an-

nual high stand before decline due to the onsetof seasonal evapotranspiration (Lee 1912), andbecause they are used by ICWD and otherresearchers for tracking annual changes ingroundwater depth as well as for investigationsof DTW-cover relationships (Elmore et al.2006). Next, we applied ordinary kriging, asimplemented in ArcGIS 9.2, Spatial Analystextension software (circular variogram, 10-mgrid cells, and default values for other param-eters), to the April 2007 DTW data to create aDTW grid covering the study area. We chosekriging as opposed to other interpolationtechniques because it is recommended in caseswhere sample sites are irregularly spaced (Le-gendre and Legendre 1998). We derived DTW

FIG. 1. Study area and sample sites. The 204-ha study area is outlined in black. The burned portion is indicated bystippling and covers 76 ha. Open circles represent start points of transects read before the fire; solid trianglesrepresent start points of transects read after the fire in the burned area; open squares represent start points oftransects in the unburned (control) area. Map projection: UTM Zone 11, NAD 27.

2009] PRITCHETT AND MANNING: EFFECTS OF FIRE ON ALKALI MEADOWS 91

contours from the grid and included them inFig. 2.

The current DTW gradient in the study area—with drawdowns of up to 5 m and alterations ofsubsurface flow relative to conditions mapped byLee (1912)—is controlled by large scale ground-water extraction which began in 1970 (Fig. 3)(City of Los Angeles and County of Inyo 1991;Steinwand and Harrington 2003a, b; City of LosAngeles Department of Water and Power andInyo County 2007).

To estimate DTW under each vegetationtransect, we overlaid the 2007 transects on thekriged 2007 DTW grid and calculated the DTWas the mean of all grid cells intersected by thetransect.

Analysis

We grouped transect data into three sets foranalysis: 1) pre-fire data covering the entire studyarea; 2) post-fire data from the burned portion ofthe study area; and 3) post-fire data from theunburned control portion of the study area. Tocharacterize vegetation we calculated each spe-cies’ mean cover and frequency based on thetransects sampled in each dataset. We used abootstrap technique to estimate standard errorsbecause of the skewed distributions of mostspecies (Elzinga et al. 1998). We calculated theMann-Whitney U statistic to determine if themean cover of S. airoides, the dominant species inthe post-fire burned area, differed from its cover

FIG. 2. Historic and 2007 water table gradient. Solid black line outlines study area. Dotted lines represent April2007 water table contours (labeled in meters from ground surface). Bold-faced dashed lines represent the 28 ft(22.4 m) and 24 ft (21.2 m) water table contours mapped by Lee (1912). Crossed circles represent monitoringwells used for kriging, and adjacent numbers represent April 2007 DTW values at the wells. Scale and mapprojection as in Fig. 1.

92 MADRONO [Vol. 56

in the pre-fire and post-fire control datasets. Wecalculated the chi square statistic to find out iffrequencies of the three most common species inthe post-fire burned area differed significantlyfrom their frequencies in the pre-fire and post-firecontrol datasets. We calculated the Mann-Whit-ney U statistic to determine if there was asignificant difference in mean DTW betweenpost-fire burned transects with flowering S.airoides versus those with vegetative-only indi-viduals. To allow visual comparison of cover andfrequency of each species among the threedatasets we juxtaposed data in a table.

We used ordinary least-squares regression (asimplemented in Sigma Plot 10.0 software) toattempt to explain variance in grass cover(summed cover of S. airoides and D. spicata ateach transect) as a function of estimated April2007 DTW at each transect in each dataset. Eachtransect’s grass cover and DTW represented asingle data point in these regression analyses. Weperformed exploratory linear regressions on rawdata, then transformed grass cover data byadding one to each value and taking the naturallog of the sum. We then regressed the trans-formed data against DTW using a sigmoid curve.We chose the sigmoid curve rather than thestraight line for both practical and theoreticalreasons: it explained more variance, and speciesabundance can be better related to environmentalgradients by unimodal curves (ter Braak 1996), ofwhich sigmoid curves are special cases (ter Braakand Looman 1995).

RESULTS

Fire Effects

At our first site reconnaissance within days afterthe fire, virtually all above-ground biomass hadbeen reduced to ash or charred wood. By eightweeks after the fire, seven species showed measur-able re-growth in the burned area (Table 1). Total

transect cover ranged from zero to 38%.Sporobolius airoides and D. spicata were thedominant graminoid species, dominant overall,and showed great spatial variation in cover.Glycyrrhiza lepidota was the third most abundantherb. Sporobolius airoides and Heliotropiumcurassavicum sampled in burned-area post-firetransects were in both vegetative and floweringstates, while we sampled D. spicata only invegetative state.

Average cover of S. airoides, the dominantspecies in the burned area after the fire, wassignificantly lower than S. airoides measured inpre-fire and post-fire control datasets (P , 0.05)(Table 1). However, post-fire frequencies of thethree most common species in the burned areadid not differ significantly from frequencies in thepre-fire and post-fire un-burned control areadatasets (Table 1). Although most graminoidspecies recorded before the fire were recordedafter the fire, few other herbaceous and woodyspecies were sampled on post-fire transects in theburned area. A single hit on Salix exigua was theonly documentation of post-fire shrub re-growth(Table 1).

DTW Effects

Grass cover was significantly correlated withDTW in all three datatsets (P , 0.01). DTWexplained 87% of the variance in pre-fire grasscover, 77% of the variance in the post-fire burnedarea, and 94% of the variance in the post-firecontrol area (Fig. 4).

The mean DTW for transects with flowering S.airoides was 2.6 m (SE 5 0.20) and was shallowerthan the mean for transects in which S. airoideswas in vegetative state only, 3.6 m (SE 5 0.32),and the difference was significant (P , 0.05).Heliotropium curassavicum was also observedflowering along transects after the fire, but thesample size was too low for statistical analysis.

FIG. 3. Groundwater pumping from wellfield in which study site is located. Amounts (in ha-m) are shown as fivewater-year cumulative totals, 1931–2005.

2009] PRITCHETT AND MANNING: EFFECTS OF FIRE ON ALKALI MEADOWS 93

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DISCUSSION

Fire Effects

The fire’s timing in summer, the notedthoroughness of combustion of above-groundbiomass, and the meager precipitation in 2007

(both before the fire and in the eight weeks afterthe fire), led us to expect little re-growth beforethe 2008 growing season (following winterprecipitation). We sampled vegetation just eightweeks after the fire because, contrary to ourexpectations, we had observed vigorous re-growth in places, and we desired to documentthe species showing re-growth and investigate thespatial variation in that re-growth. We had noexpectation that re-growth was complete and,therefore, expected mean cover over the burnedarea to be lower than mean cover of the pre-burnand post-burn control areas (Table 1). A note-worthy finding was that short-term re-growth oftwo grasses (and the herb G. lepidota) did attainpre-fire and post-fire control levels in terms offrequency (Table 1), suggesting the fire causedlittle mortality among the dominant herbaceousspecies. This finding is consistent with the resultsof Smith and Kadlec (1985), who found nosubstantial below-ground mortality of saltgrassafter burning in a Utah marsh.

The four graminoid and forb species whichattained greater than trace cover values after thefire in the burned area (Table 1) show anatom-ical/physiological traits which facilitate survivalafter fire. Perennating buds occur below groundon rhizomes for D. spicata and at the root crownfor the bunchgrass, S. airoides. Glycyrrhizalepidota is rhizomatous while H. curassavicumhas underground rootstocks able to give rise tonew stems. For these reasons, in addition to thedry, hot, post-fire conditions which made seedgermination and seedling survival extremelyunlikely, we treated live cover sampled in thepost-fire burned area as re-growth from plantsalready established before the fire, rather thannew recruits.

In contrast to the re-growth of herbaceousspecies, shrubs may have suffered high mortality.Artemisia tridentata is known to be killed by fireand re-establish by seed (Tirmenstein 1999a). Theabsence of C. nauseosus after the fire (Table 1)suggests mortality because it has been reportedby several researchers to show ‘‘rapid’’ post-firerecovery through re-sprouting as well as by seedgermination (Tirmenstein 1999b), and we haveobserved it re-sprouting within weeks after otherOwens Valley fires. Fire effects on A. lentiformissubsp. torreyi have not been systematicallystudied, though some data suggest post-firerecovery is by seed germination rather than re-sprouting (Meyer 2005). Observations in OwensValley show high rates of A. lentiformis subsp.torreyi germination in spring following winterswith abundant precipitation (ICWD data on file).We found no data regarding fire effects onMachaeranthera carnosa. Overall, the absence ofmost shrub species in our observations andsampling data eight weeks after the fire suggestsshrub mortality.

FIG. 4. Grass cover as a function of DTW in metersbelow ground surface. Dotted lines represent 95%confidence limits: (A) Pre-fire dataset, n 5 48; (B)Post-fire burned area dataset, n 5 37; (C) Post-fire un-burned control dataset, n 5 29. All coefficients weresignificant at P , 0.01.

2009] PRITCHETT AND MANNING: EFFECTS OF FIRE ON ALKALI MEADOWS 95

DTW Effects

One of the principal reasons we sampled post-firevegetation was to investigate the spatial variation inre-growth observed in reconnaissance site visits.DTW explained most of the variance (Fig. 4b) ingrass cover in our post-fire sample of the burnedarea. The significant difference in DTW betweenflowering and vegetative S. airoides samples isfurther evidence for the importance of DTW—asopposed to properties of the fire itself—incontrolling patterns of re-growth. The fact thatDTW also explained most of the variance in grasscover in both pre-fire and post-fire controldatasets (Figs. 4a, 4c) suggests the post-firerecovery in the burned area is re-establishingcover—DTW relationships which existed beforethe fire. These patterns had previously beenobscured from view by encroaching shrubs.

These relationships between grass cover, phe-nology, and DTW may be understood as effectsof differential water availability across the DTWgradient in both burned and un-burned portionsof the study area. Cox et al. (1990) asserted that a‘‘waving sea’’ of alkali sacaton could not bemaintained where annual precipitation rangesfrom 150–400 mm, while revegetation experi-ments elsewhere in Owens Valley have docu-mented water requirements for D. spicata torange from 200–800 mm/yr (Dickey et al. 2005).However, with average annual precipitation of160 mm and only 34 mm total precipitation priorto and during the 2007 growing season, abeautiful, ‘‘waving sea’’ of alkali sacaton andsaltgrass developed in the burned area at theshallow end of the DTW gradient eight weeksafter the fire, but not at the drawn-down end. Thesimplest explanation for the observed patterns isdifferential groundwater availability.

Livestock grazing is another important factorpotentially controlling patterns of cover andphenology, but because livestock were notpermitted in the study area after the fire, lowcover in parts of the burned area was not a directresult of grazing. The pattern of un-grazed post-fire grass re-growth was similar to the pattern ofgrazed pre-fire grass distribution. While grazingundoubtedly affects the site, our results argueagainst differential grazing as a direct explanationfor the observed variation in grass cover.

We are not the first to infer the importance ofDTW as a primary factor in controlling vegetationpatterns in arid lands. Los Angeles Department ofWater and Power engineer C. H. Lee (1912)documented the ‘‘very striking’’ relationship be-tween vegetation and DTW in this portion ofOwens Valley nearly a century ago, and ground-water availability is used to explain vegetationpatterns on valley floors throughout the GreatBasin (Coville 1893; Odion et al. 1992; Castelli et al.2000; West and Young 2000; Cooper et al. 2006).

The 2007 DTW gradient, which explains a highpercentage of current variation in grass cover, iscontrolled by groundwater extraction (previouslynoted) and is quite different from the gradientLee mapped in 1912 (Fig 2). The 2007 distribu-tion in grass cover, therefore, is best interpretedas a response to this altered hydrologic regime.Elmore et al. (2006) explained changes inperennial cover of Owens Valley alkali meadowhabitat over 20 yr as a function of changes inDTW and precipitation. Cooper et al. (2006)described a similar case in Colorado. In our studywe substituted space for time by examining grasscover before and after fire in a single growingseason and obtained similar results.

Management Implications

At the shallow end of the DTW gradient(Fig. 2) the robust recovery of native grassprovided dramatic evidence that fire can serveas a force for meadow regeneration. This findingis not surprising: burning to remove shrubs andpromote grasses has been practiced in Californiasince pre Euro-American settlement (Anderson2006).

More relevant to our research, Wright andChambers (2002) conducted and studied resultsof controlled burns in Great Basin riparianmeadow habitat located in both shallow anddrawn-down water table sites. They concludedthat burning is an effective tool for restoringmeadows with shallow groundwater.

At the drawn-down end of the DTW gradient,fire may be an agent of community change ratherthan a force for meadow regeneration. We expectvegetation there will cease to meet criteria forclassification as groundwater dependent meadowand, instead, will come to resemble that of nearbyprecipitation-dependent desert shrublands. Theexpected multi-year period for shrub re-coloniza-tion, combined with negligible grass cover, willleave the drawn-down end of the DTW gradienthighly vulnerable to erosion. In Owens Valley,wind poses an especially great erosional force,and a major highway (US 395) was closed on atleast one occasion after the fire due to the densityof airborne meadow soil where the highwaycrossed the study area. Other studies predictvegetation change as a response to hydrologicalterations under phreatophytic communities(Odion et al. 1992; Manning 1999; Wright andChambers 2002; Naumburg et al. 2005; Patten etal. 2008). Our data suggest fire may accelerate therate of the predicted vegetation change.

Conclusion

We conclude that if the 2007 DTW gradient ismaintained in the future, vegetation at oppositeends of the gradient will follow different trajec-

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tories. At the shallow end we expect grass coverwill reach or exceed pre-fire levels in summer2008 (preliminary data suggest this outcome) andalkali meadow habitat will be maintained. At thedrawn-down end the fire will facilitate theconversion of groundwater-dependent alkalimeadow to a more xeric community of annualsand, eventually, shrubs. Rather than acting as anindependent force shaping patterns of vegetation,our short-term response data suggest the effect ofthe fire over the entire DTW gradient will be thelong-term amplification of differences alreadypresent before the fire. These differences areassociated with differential water availability.Our examination of fire effects led to documen-tation of groundwater dependence and the effectsof groundwater limitation.

ACKNOWLEDGMENTS

We thank Jerry Zatorski and Sondra Grimm of theInyo County Water Department for conducting thefield work. We also thank the University of CaliforniaWhite Mountain Research Station, John Callaway, andan anonymous reviewer.

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