Environmental Management (2014) 54:30–50 DOI 10.1007/s00267-014-0274-2

Effects of Disturbance Associated With Seismic Exploration for Oil and Gas Reserves in Coastal Marshes Rebecca J. Howard • Christopher J. Wells Thomas C. Michot • Darren J. Johnson



Received: 13 June 2013 / Accepted: 2 April 2014 / Published online: 1 May 2014 Ó Springer Science+Business Media New York (outside the USA) 2014

Abstract Anthropogenic disturbances in wetland ecosystems can alter the composition and structure of plant assemblages and affect system functions. Extensive oil and gas extraction has occurred in wetland habitats along the northern Gulf of Mexico coast since the early 1900s. Activities involved with three-dimensional (3D) seismic exploration for these resources cause various disturbances to vegetation and soils. We documented the impact of a 3D seismic survey in coastal marshes in Louisiana, USA, along transects established before exploration began. Two semiimpounded marshes dominated by Spartina patens were in the area surveyed. Vegetation, soil, and water physicochemical data were collected before the survey, about 6 weeks following its completion, and every 3 months thereafter for 2 years. Soil cores for seed bank emergence experiments were also collected. Maximum vegetation height at impact sites was reduced in both marshes 6 weeks following the survey. In one marsh, total vegetation cover was also reduced, and dead vegetation cover increased, at impact sites 6 weeks after the survey. These effects, however, did not persist 3 months later. No effects on soil or water properties were identified. The total number of seeds that germinated during greenhouse studies increased R. J. Howard (&)  C. J. Wells  T. C. Michot U.S. Geological Survey, National Wetlands Research Center, 700 Cajundome Blvd., Lafayette, LA 70506, USA e-mail: [email protected] Present Address: T. C. Michot Institute for Coastal Ecology and Engineering, University of Louisiana, Lafayette, LA 70504, USA D. J. Johnson Five Rivers Services, National Wetlands Research Center, 700 Cajundome Blvd., Lafayette, LA 70506, USA

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at impact sites 5 months following the survey in both marshes. Although some seed bank effects persisted 1 year, these effects were not reflected in standing vegetation. The marshes studied were therefore resilient to the impacts resulting from 3D seismic exploration because vegetation responses were short term in that they could not be identified a few months following survey completion. Keywords Brackish marsh  Disturbance  Plant response  Resiliency  Seed bank  Three-dimensional seismic survey

Introduction The northern Gulf of Mexico coast in Louisiana, USA, has been a focal area for extensive oil and gas extraction and production since the first successful well was established in the state in 1926 (Lindstedt et al. 1991). Significant attention has been focused on ecosystem impacts of these activities, including hydrologic alterations resulting from construction of levees and pipeline canals, water quality issues related to produced waters, and toxicity and physical damage from oil spills (reviewed in Ko and Day 2004). Before actual extraction of reserves, actions associated with the exploration for oil and gas can also result in environmental impacts. Reflection seismology has been used to map subsurface structures and stratigraphic features since the 1920s, but the technology developed slowly until the advent of three-dimensional (3D) seismic techniques beginning in the 1980s (Cartwright and Huuse 2005). As noted by Cartwright and Huuse (2005), 3D seismic technology has been so widely embraced by the petroleum industry that few exploration wells are established without a pre-drill 3D survey. The South Louisiana Oil Scouts

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Association (2013) reported that 538 3D seismic surveys were conducted in south Louisiana since 1987. Oil and gas exploration in wetland habitats can result in various disturbances to plant communities; disturbance is used here in the sense of Pickett et al. (1989) as a change in the minimal structure of an object caused by an external factor. Seismic surveys require frequent vehicle passes over an area, usually by airboat or marsh buggy. Other activities associated with seismic exploration include drilling holes for placement of explosive charges beneath the substrate surface and use of helicopters for moving and positioning heavy equipment. Direct impacts from these activities can include hydrologic (e.g., disruption of water flow patterns), edaphic (e.g., soil compression and mixing), and vegetative aspects. The response of plant assemblages to disturbance varies depending on the species present (McIntyre et al. 1995) and on the spatial and temporal structure of the disturbance regime (Allison 1995; Moloney and Levin 1996). The overall effect of disturbance on plant communities also depends on duration, intensity, and frequency of the disturbance (Keddy 2000). Plant species resistance and resilience to disturbance can affect their competitive ability; more resistant or resilient species may interfere with the ability of competitors to recover (Brewer 2011). Impacts to vegetation from 3D seismic surveys can involve repeated compression, uprooting, leaf removal, stem breakage, and cover reduction in traffic lanes as well as complete removal or burial of aboveground biomass in drilling and explosive charge burial locations. A literature review on the effects of disturbance in wetlands indicated that about half of the 54 studies reviewed, none of which involved seismic exploration, showed no permanent change in percent vegetation cover, whereas the remainder indicated cover decreases (McKee and Baldwin 1999). The number of species (species richness) present at disturbed sites was also not affected at about half of the studies reviewed, but the remainder of studies showed both increases and decreases in this measure (McKee and Baldwin 1999). Climate-related disturbances, including sea-level rise and alteration to sediment supply, are predicted to have increasingly significant effects on coastal marsh vegetation structure and function (Kirwan et al. 2008; Stevenson and Kearney 2009; Zedler 2010). Interactions between anthropogenic disturbance and biotic factors (e.g., herbivory and competition) have been demonstrated to affect system recovery in wetlands following disturbance (Bromberg Gedan and Silliman 2009; Angelini and Silliman 2012; Coverdale et al. 2013). Sidle et al. (2013) emphasized the need to understand the magnitude, frequency, and interrelationships among stressors and disturbance factors to assess when thresholds to perturbation may be exceeded, leading to system change.

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Many of the studies on environmental impacts of oil and gas exploration have been focused on the arctic tundra, a region characterized by the presence of a fragile permafrost layer beneath the soil surface (Kemper and Macdonald 2009). Reduced vegetation cover and species shifts were identified in northeastern Alaska arctic plant communities after seismic exploration (Emers et al. 1995), and these impacts persisted 18 growing seasons later (Jorgenson et al. 2010). Because of major differences in climate, soils, and vegetation, seismic exploration impacts in the southern United States are likely to differ significantly from those found in tundra regions. A seismic survey in a coastal southeastern Texas marsh that employed large, multi-ton terra-tire vehicles displayed reduced plant cover 1 year after the survey was completed, but it was concluded that this effect would not persist and that original diversity and density of the plant community would be restored in 18–24 months (Drawe and Ortega 1996). Studies conducted in semi-impounded coastal marsh habitat on Rockefeller State Wildlife Refuge (SWR) in southwestern Louisiana determined there was no effect on the dominant plant species, Spartina patens, 1 year following a 3D seismic survey (Wilson et al. 1999). S. patens is often dominant in northern Gulf of Mexico brackish marshes, where salinity typically ranges from 0.5 to 18 ppt (i.e., oligohaline to mesohaline conditions). Post-survey data were collected several months after the survey was completed in the Wilson et al. (1999) study and, therefore, did not record short-term impacts. Another study at Rockefeller SWR, conducted in semi-impounded and tidal brackish marshes, indicated that soil elevation was not affected by seismic survey traffic (Hess et al. 1999). In contrast to these studies, Bass (2004) found impacts from a 3D seismic survey at Lacassine National Wildlife Refuge (NWR), also in southwestern Louisiana; live vegetation cover and dead biomass were reduced in a freshwater impoundment 2 years following the survey. Interpretation of color-infrared aerial photography following a 3D survey in a freshwater marsh indicated that while vegetation recovery was apparent along some survey travel lanes, depending on the type of traffic (e.g., marsh buggy or airboat) up to 92 % of the lanes displayed moderate to high impacts one growing season following a survey (Bass 1997). It can be concluded from these studies that potential impacts of 3D seismic exploration in wetlands along the northern Gulf of Mexico (gulf) coast will vary with wetland type, equipment used (e.g., type of vehicles), and intensity of the activities, including the number of passages along travel lanes. As noted by Bass (2004), more information is needed on the impacts of seismic surveys in fragmented brackish and salt marshes. Public lands along the gulf coast have been subjected to repeated surveys for oil and gas reserves in wetlands as technological advances

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improved recording and imaging abilities. This region is inherently vulnerable to wetland loss because of high subsidence rates and accelerated sea-level rise (Pendleton et al. 2010). We believe that additional documentation of the effects of 3D seismic surveys is especially important in degraded and fragile marsh habitats of this region that have been subjected to repeated seismic surveys. The objectives of this study were to describe the impacts of 3D seismic exploration on plant community structure and composition and soil characteristics in a fragmented coastal marsh and to document ability of the marsh to recover from any identified exploration effects. In contrast to previous studies, we studied relatively short-term impacts by visiting the survey site a few weeks following survey completion. The following questions were addressed: (1) did 3D seismic exploration activities affect standing vegetation, seed bank, soil, or water physicochemical characteristics, and, if impacts were identified, did they vary temporally?; (2) did impacts vary depending on the category (i.e., intensity) of disturbance?; (3) did response differ between plant communities?; and (4) was the marsh able to recover to pre-survey conditions during the 2 years following exploration?

Methods Study Area and Experimental Design This study was conducted at Sabine National Wildlife Refuge (NWR) in southwestern Louisiana, USA (Fig. 1). The refuge was established primarily for the purpose of maintaining wetland habitats for wintering waterfowl species. Sabine NWR encompasses 50,907 ha and includes about 36,900 ha of fresh to brackish marshes (U.S. Department of Interior 2007). When land for the refuge was purchased in 1937, subsurface mineral rights were retained by the original owners along with the right to access and develop those resources. By 2007, a total of 107 wells had been drilled on the refuge, and more than 40 ha were occupied for oil and gas production (U.S. Department of Interior 2007). A 3D seismic survey program to identify oil and gas resources was conducted on the refuge over 4 weeks in April to May 1997, affecting about 93 km2 of refuge land. A diagonal (45° magnetic north) pattern for explosive charge locations (i.e., source lines) was employed for the survey, with lines placed at 445-m intervals (Anonymous 1997). To bury explosive charges, holes were drilled to a depth ranging from about 18–49 m; the holes were spaced at 67-m intervals, and 4.08 kg explosive charges were employed. An airboat-mounted backhoe was used to backfill the holes once the explosives were in place. Receiver lines where geophones were placed

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were orientated north–south and spaced at 402-m intervals (Anonymous 1997). Sabine NWR staff identified a limited number of access points to minimize damage and required the presence of an independent monitor (i.e., not an employee of the survey company) to supervise activities. The survey avoided use of tracked vehicles and primarily deployed airboats for activities, including drilling shot holes, in an attempt to minimize impacts to wetlands. It was estimated by the survey company that a total of at least six passes would be required on source lines, to complete surveying and deploying, servicing, and removing geophones, and ten passes on receiver lines, for surveying, installing explosives, and removing wiring (Anonymous 1997). Although we requested that the survey crew record the actual number of passes along travel lanes, this information was not collected. We applied an adaptation of a sampling design described by Green (1979) that is often used for detecting environmental impacts, referred to as a before-after-control-impact (BACI) design (Stewart-Oaten et al. 1986). The study has attributes considered to be optimal for this design, because we collected information before the impact occurred, the location of the impact was known, and there were nearby control areas (Green 1979, p 68). Two semi-impounded marsh areas on Sabine NWR (Fig. 1) that were within the seismic survey boundaries were included in the study. Unit 1, a brackish marsh, was dominated by S. patens (Aiton) Muhl. and included stands of Typha sp. and Schoenoplectus americanus (Pers.) Volkart ex Schinz & R. Keller; this unit contained several interspersed shallow ponds (i.e., the marsh was fragmented). Unit 4 was an oligohaline marsh (a category of brackish marsh with 0.5–5.0 ppt salinity) dominated by S. patens, but it included scattered, large stands of Schoenoplectus californicus (C.A. Mey.) Palla and large, shallow open water areas; this unit was transected by North Bayou. In this marsh, we selected an area with high presence of S. californicus for study. To document impacts of exploration activities in the marsh, we established permanent transects in April 1997 prior to initiation of the survey; transects were located within the seismic survey grid and in control areas outside of the grid in each unit. Control sites with vegetation similar to that in impact sites were selected as close as possible to the survey area. Global positioning system (GPS) data on receiver and source line locations were obtained prior to the initiation of the survey, and these data were used to locate transects that included different anticipated impact categories. Four transects were located within each disturbance treatment (control and impact) in each unit (unit 1 and unit 4). The first transect in impact sites was aligned along a receiver line, with the first sampling station located about

Environmental Management (2014) 54:30–50 93°50'

33

93°40'

93°30'

93°20' Moss Lake

Clear Marais

TEX AS LOU ISIA NA Sab ine

87

CALCASIEU PARISH CAMERON PARISH

Ri ve r

ORANGE COUNTY

k Ba Blac

I

Central Canal

u

Calcasieu Lake

UNIT 1B West Cove

West Cove Canal

I Southline Canal

No

TEXAS

Oyster Mud Lake Lake Holly Beach 27

you Hamilton Old East Ba Lake Constance GULF BEACH HIGHWAY Beach 82

Cameron 82

A N IA IS U

rth

UNIT 1A

LO

yo Ba UNIT 4 UNIT 2 C

UNIT 7 UNIT 6

Sabine Lake

27

Browns UNIT 3 C UNIT 1 Lake SABINE NATIONAL WILDLIFE REFUGE

UNIT 5 Willow Bayou Canal

29°50'

Hackberry

Northline Canal

Ba c Cak Ri na dg l e

JEFFERSON COUNTY

Black Lake

you

30°00'

Area enlarged

N Gulf of Mexico Base modified from U.S. Geological Survey digital data Universal Transverse Mercator, zone 15 North American Datum of 1983

0

5

10

15

20 KILOMETERS

Fig. 1 Sabine National Wildlife Refuge, Louisiana, showing the location of management units. The seismic 3D survey affected portions of units 1 and 4. The approximate locations of the control (C) and impact (I) sites are indicated with black boxes

Receiver Source Double None

Fig. 2 Layout of sampling stations along four transects in areas affected by a 3D seismic survey at Sabine National Wildlife Refuge, Louisiana. Solid lines indicate source lines; dashed lines indicate receiver lines. Symbols indicate sampling stations located on receiver lines (Receiver), source lines (Source), intersections of receiver and source lines (Double), and offset from receiver and source lines (None). At impact areas, these four station types were considered different potential-impact categories. The layout pattern was duplicated at control areas

222 m north of an intersection with a source line (Fig. 2). A second station was located at the intersection of the receiver and source lines immediately to the south. Subsequent stations were located at intervals of 222 m southward for a total of six stations on the transect. The stations were 9 m2 (3 9 3 m2), and the center of each station was recorded using a GPS. Each station was marked with a plastic (PVC) pole that extended above the vegetation; to prevent fertilization by roosting birds, the pole was placed

2 m north of the northeastern corner of each plot. A second transect was located about 200 m to the east of the first, and was midway between, and parallel to, two receiver lines. The first station on this transect was located on the same source line as the second station on transect 1, and five additional stations were located at 222-m intervals southward. Three of the stations on this line were not on travel lanes. When the sampling scheme resulted in a location lacking emergent vegetation (e.g., an open water area), the station was placed at the nearest point along the line with emergent plants. The pattern for station selection was repeated for the two remaining transects at each site (Fig. 2). The four areas sampled (unit 1 control, unit 1 impact, unit 4 control, and unit 4 impact) were about 800 m wide and 1.8 km long. The center of the unit 1 control site was about 2,100 m north of the impact site center, and the unit 4 control site center was about 5,300 m west of the impact site center. The sampling stations were reached by airboat; care was taken during each visit to travel parallel to and on the east side of the transect lines (visible because of the PVC marker posts) at a distance of 5 m or more. The systematic location of sampling stations resulted in six replicates within each of four impact categories: (1) receiver line; (2) source line; (3) receiver and source line intersections; and (4) offset from travel lanes. We anticipated the most severe impacts would occur at the intersection of receiver and source lines and along receiver lines. The fourth category was included to test for indirect impacts, such as salinity or plant composition changes. Transects and sampling stations in the control sites were

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34

aligned in the same manner as on areas impacted by the survey. A total of 96 sampling stations, 24 within each site, was established. Vegetation composition and cover, water physicochemical parameters, and soil characteristics were determined at the stations along the transects in April 1997, before the survey affected the stations. The transects were sampled again in June, about 6 weeks after the seismic crew completed work. It was discovered at this time that the survey crew had used North American datum 1927 (NAD 27) for navigation while we used World Geodetic System 1984 (WGS 84). As a result, our initial sampling locations were laterally displaced from the actual receiver and source lines by about 6 m. Sampling stations for three of the four designated impact categories—receiver line, source line, and receiver and source line intersections— were re-located at this time (June 1997) to coincide with actual survey lines, which were readily visible. All stations were sampled throughout the remainder of the study on a quarterly basis (September, December, March, and June) for 2 years, for a total of ten sampling events.

Data Collection Plant species composition and cover by species were determined within four 1-m2 quadrats at each sampling station; these quadrats were considered subsamples. Cover was visually estimated, and each species was assigned to a class based on a modified Daubenmire cover scale (Bonham 1989). The six classes used, based on percent cover, were: (P) \ 1 %, (1) 1–10 %; (2) 11–25 %; (3) 26–50 %; (4) 51–75 %; and (5) [75 %. Dead vegetation and unvegetated bare ground were also assigned cover classes at each station. We characterized plant assemblages by calculating diversity, as indicated by the Shannon entropy measure, evenness (Pielou 1975), and similarity (Sørensen coefficient). These metrics were determined as described by Kent (2012); Shannon entropy index values were converted to effective numbers of species (Jost 2006) prior to analyses. Water depth to the nearest cm was measured at the center of each quadrat. Interstitial soil water was collected at a depth of 15 cm at the center of the station using a syringe and tubing. Salinity, specific conductivity (25 °C), temperature, and pH of an unfiltered portion of interstitial water were measured within 10 min of collection. A 30-ml portion of the interstitial water was filtered through a 0.45-lm filter, placed in a plastic tube, and immediately stored on ice. The samples were frozen within 12 h of collection for later determination of NH4 and PO4 content using an autoanalyzer (Alpkem Model 3570). Salinity and specific conductivity of standing water above the marsh surface were measured when present. At control sites, the interstitial and surface water measurements were

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Environmental Management (2014) 54:30–50

obtained at eight stations that were systematically selected (two per transect) from the total of 24 stations per site. Soil cores were collected for determination of soil properties (organic matter content and bulk density, 11 cm diameter by 25 cm deep) and for use in a greenhouse study to document the vegetation seed bank (11 cm in diameter by 15 cm deep). Cores were obtained on three occasions: April 1997 (prior to seismic survey activities), June 1997, and June 1998 for soil properties, and April 1997, September 1997, and March 1998 for seed bank experiments. Core samples were collected outside of the 9-m2 vegetation sampling area at each station in the impact areas and at the same eight stations in the control area selected for water sampling. Cores were placed in plastic bags, immediately stored on ice in the field, and refrigerated within 24 h of collection. Within 1 week of collection, cores for soil properties were weighed and then oven-dried at 100 °C to a constant mass; bulk density was obtained on a subsample of the thoroughly mixed oven-dried soil. Organic matter content of a second subsample of dried soil was determined following ashing in a muffle furnace for 8 h at 400 °C. The cores collected for use in seed bank experiments were stored in the dark at 4 °C until the experiments were initiated. The seedling emergence method was used to describe seed bank composition and seed abundance (van der Valk and Davis 1978; Poiani and Johnson 1988). Each core sample was sliced longitudinally into two subsamples; the subsamples were thoroughly mixed by hand, and rhizome fragments were removed. A growth medium was prepared by filling 26-cm2 shallow (5-cm deep) trays containing a 2-cm layer of a commercially available allpurpose potting soil. Each subsample was spread evenly across the soil surface in a tray. The trays were randomly placed on one of three plastic-lined greenhouse tables, where water was maintained at a depth within 1 cm of the soil surface. To monitor allochthonous seed supply, two control trays on each table contained only the commercial soil mixture. Seedlings that emerged were allowed to grow until they could be identified to species, at which time they were removed from the trays and counted. Large seedlings that could not be identified to species and may have interfered with emergence of new seedlings were removed from the trays, planted in a separate pot, and allowed to grow for another 2 months. Any seedlings that could not be accurately identified after 2 months were identified to the genus level only. The experiment using the April 1997 samples was initiated in early August 1997 and was concluded after 26 weeks, in early February, when no new seeds had emerged in any trays for 1 week. This protocol was followed for the September 1997 samples (experiment initiated in February 1998 and concluded in August 1998) and March 1998 (experiment initiated in October 1998 and concluded in May 1999). The greenhouse was exposed to

Environmental Management (2014) 54:30–50

ambient light conditions during all experiments. Water was circulated through cooling pads to avoid excessive heating in the greenhouse during the summer, and gas heaters were used during the winter months to maintain the air temperature above 8 °C.

35

completion. Soil bulk density, soil organic matter content, and interstitial soil water nutrient content were available for measurement times 2 and 6 only. Repeated measures two-way analysis of covariance was applied with disturbance treatment and time as independent factors and presurvey (time 1) measurements as a covariate.

Data Analyses Plant Assemblages Vegetation, Soil, and Physicochemical Attributes Two series of statistical analyses were performed to address the impact of the 3D seismic exploration survey on marsh habitats at Sabine NWR. In the first series, consisting of five separate analyses, we assigned response variables to one of three groups: (1) vegetation characteristics (species richness, total cover, maximum height, dead plant material cover, unvegetated [bare ground], cover of the dominant plant species S. patens and S. californicus, and cover of any subdominant species with a frequency of occurrence in quadrats that exceeded 5 %); (2) soil characteristics (bulk density and organic matter); and (3) physicochemical attributes (water depth, surface and soil interstitial water salinity, and interstitial water phosphate and ammonium concentration). Cover class values were converted to the class midpoint for analyses. The independent factors in each analysis were assigned based on the specific question being addressed. The first analysis in this series determined if the control and impact sites within a unit were similar. Disturbance treatment (impact or control) was the independent factor, and a t test was applied to compare characteristics of treatments by unit before the survey (i.e., at time 1). A t test was also used in a second analysis to determine if the marshes were similar before the survey; unit (1 or 4) was the independent factor, and the control and impact sites were pooled within unit. Since the marshes differed in most of the response variables studied (see results), all the subsequent analyses were performed by unit. In a third analysis using impact category (Fig. 2) as the independent factor, a one-way analysis of variance (ANOVA) was applied by time using data from measurement times 2 through 10 to determine if there were differences among the four categories. In a fourth analysis, conducted to determine if exploration activities had an immediate impact, a two-way ANOVA with measurement time and disturbance treatment as independent factors compared response variables in time 1 (pre-seismic exploration) and time 2 (first measurement post-seismic survey). The final analysis in this series examined the ability of the marsh to recover using data collected at three times during the middle of the growing season, in June 1997, 1998, and 1999 (measurement times 2, 6, and 10). These analyses also allowed detection of any delayed impacts that were not evident within a few weeks of survey

In the second series of analyses, consisting of four analyses, we investigated the impact of the seismic survey on specific aspects of the plant assemblages. First, effect on the cover of species that can be considered typical of disturbed sites was compared by unit for disturbance treatment (i.e., control versus impact) at each time using t tests. Species included in these analyses were selected based on coefficient of conservation (CC) score, as described by Cretini et al. (2012). The CC was assigned by a panel of experts based on their knowledge of species tolerance to disturbance and fidelity to a habitat relative to other species. The CC score for a species ranges from 0 to 10. We selected species that were assigned a score of 1 to 3, described as ‘‘plants that are opportunistic users of disturbed sites’’ (Cretini et al. 2012). Only species with a frequency of occurrence greater than 5 % were included. The second analysis was conducted to determine if the seismic survey affected calculated variables used to characterize the assemblages. Disturbance treatment was the independent factor, and t tests were conducted for each data collection time. The Sørensen similarity coefficient between disturbance treatments was calculated by time; since this metric lacks replication, no statistical analyses were conducted. The remaining two analyses in this series included seed bank data. Data from sites offset from airboat travel lanes at the impact sites were not included in these analyses because they were not subject to direct disturbance. The composition of the seed bank was compared to that of the standing vegetation at three times when data for both were collected concurrently: April 1997, September 1997, and March 1998. Paired t tests were made by disturbance treatment by time, with species richness as the response variable. The Sørensen coefficient was used to determine species similarity between the standing vegetation and the seed bank in each unit. The final analyses in this series focused on the seed bank results. The total number of seedlings that emerged from a sample was examined: this variable included all plants, regardless of whether they could be identified to genus and species. Seedlings of Utricularia species were excluded from this analysis, because they were too difficult to be distinguished as individual plants; so, an accurate count was not possible. Other response variables were species richness, Shannon entropy, and similarity and included only seedlings that

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Environmental Management (2014) 54:30–50

Table 1 Plant species identified in standing vegetation (Field) and in seed bank samples collected at Sabine National Wildlife Refuge, Louisiana. Nomenclature follows the Integrated Taxonomic Information System (2013)

Table 1 continued Name

Field

Name

Mikania scandens (L.) Willd.

X

Nymphaea odorata Aiton

X

Field

Alternanthera philoxeroidesa (Mart.) Griseb.

X

Amaranthus cannabinus (L.) J.D. Sauer Amaranthus tuberculatusa (Moq.) J.D. Sauer

X

Amaranthus sp. L. Andropogon virginicus L. Azolla filiculoides Lam.

X

P

X

A

X

– P

X X

Baccharis halimifolia L.

X

Bacopa monnierib,d (L.) Pennell

X

Bacopa sp. Aubl.

P A W

X X

Borrichia frutescens (L) DC

Duration

P

X

Axonopus fissifolius (Raddi) Kuhlm. d

Seed bank

X

P – P

Cladium jamaicense Crantz

X

X

P

Cyperus erythrorhizosa,b,d Muhl.

X

X

A

Cyperus esculentus L.

X

Cyperus haspan L.

X

Cyperus iria L. Cyperus polystachyosb Rottb.

X

Cyperus virens Michx. Cyperus sp. L.

X

Distichlis spicata (L.) Greene

X

Echinochloa walterib (Pursh) A. Heller

X

Eclipta prostrataa (L.) L.

X

Eleocharis cellulosa Torr.

X

Eleocharis fallax Weath.

X

Eleocharis flavescens (Poir.) Urb.

P X

P

X

A

Oxalis sp. L.

Seed bank

P X X

Panicum hemitomon Schult.

X

Panicum sp. L.

X

X X

d

Persicaria punctata (Elliott) Small

X

Persicaria sp. (L.) Mill.

X

Phyla lanceolatac (Michx.) Greene

X

Pluchea odorataa,b,d (L.) Cass.

X

Pluchea sp. Cass. Ptilimnium capillaceum (Michx.) Raf.

X

Rumex sp. L.

X

Ruppia sp. L.

X

Sacciolepis striata (L.) Nash

X

Salix nigra Marshall

– – A/P – P

X

A/P

X

– A

X

Ricciocarpos sp. Corda

P P

X

Riccia sp. L.

Duration

X

– – – –

X

P

X

W

Schoenoplectus americanusc,d (Pers.) Volkart ex Schinz & R. Keller

X

X

P

X

P

X

P

P

Schoenoplectus californicusb,d (C.A. Mey.) Soja´k

X

X

X

X



X



Schoenoplectus sp. (Rchb.) Palla

P

Sesbania herbacea (Mill.) McVaugh

X

A

Sesbania vesicaria (Jacq.) Elliott

X

A/P

Solidago sempervirens L.

X

P

P

Solidago sp. L.

X



X

X

A

X

A

P

Spartina patensc,d (Aiton) Muhl.

X

X

P

Spartina sp. Schreb.

X



X

P

Eleocharis obtusaa (Willd.) Schult.

X

X

A/P

Spirodela polyrrhizad L.) Schleid.

X

P

Eleocharis parvulaa,b (Roem. & Schult.) Link ex Bluff, Nees & Schauer

X

X

A

Symphyotrichum subulatum (Michx.) G.L. Nesom

X

A

Eleocharis sp.d R. Br.

X

X



Typha latifoliaa,c L.

X

Erechtites hieraciifolius (L.) Raf. ex DC.

X

X

A

Typha sp.d L.

X

Eupatorium capillifolium (Lam.) Small

X

X

P

Utricularia sp.d L.

X

Galium obtusum Bigelow

X

P

Vigna luteolaa (Jacq.) Benth.

X

Galium tinctorium L.

X

X

P

Wolffia sp.d Horkel ex Schleid.

X

Habenaria repens Nutt.

X

X

P

Wolffiella sp.d Hegelm.

X

Hydrocotyle ranunculoidesd L. f.

X

X

P

Ipomoea sagittatac,d Poir.

X

X

P

a

X



Species typical of disturbed sites

b

P

Common species that germinated in the seed bank

c

a

Juncus sp. L. Kosteletzkya virginica (L.) C. Presl ex A. Gray d

X

Lemna sp. L.

X

Leptochloa fusca ssp. fascicularisa (Lam.) N.W. Snow

X

Leptochloa panicea ssp. brachiata (Steud.) N.W. Snow

X

Limnobium spongia (Bosc) Rich. ex Steud.

X

Ludwigia leptocarpab,d (Nutt.) H. Hara

X

Ludwigia peploides (Kunth) P.H. Raven

X

Ludwigia sp.d L.

X

Lythrum sp. L.

X

123

X

X

P –

X

– P –

X



A annual, P perennial, W woody



Species that occurred with greater than 5 % frequency in the standing vegetation in unit 1

A/P

d

Species that occurred with greater than 5 % frequency in the standing vegetation in unit 4

A/P P

X

A P

X

– –

could be identified to genus or species. Disturbance treatment was the independent variable for t tests with total seedling number, richness, and Shannon entropy as dependent variables. Finally, we analyzed a subset of

Environmental Management (2014) 54:30–50

results from the seed bank experiment that used soil cores collected in fall 1998. Common species, including both annuals and perennials, were selected to determine if seedling number was affected by disturbance. All analyses were conducted using SAS ver. 9.2 (SAS Institute, Cary, North Carolina, USA). We checked models for normality and homogeneity, and transformed response variables when assumptions were not met. The alpha level used for analyses was 0.05. For analyses using t tests, each test was considered independent because the response variables were independent of each other; alpha levels were not adjusted for these analyses. Since multiple tests were conducted, p values are provided to allow assessment of possible Type I errors. Significant main effects in ANOVA models were evaluated using the Tukey multiple comparison test, and means of variables with significant main effect interactions were examined using a Bonferroni adjustment for the number of comparisons.

Results Vegetation, Soil, and Physicochemical Attributes We identified 48 plant species at sampling stations on Sabine National Wildlife Refuge; an additional 17 plants were identified to genus only (Table 1). A total of 34 species was identified during the seed bank studies, with an additional 15 seedlings identified to genus only (Table 1). There were 30 species/genera unique to the standing vegetation and 14 unique to the seed bank; 35 species/genera were found in both. In unit 1, four species in addition to S. patens occurred with frequency greater than 5 %, and in unit 4, there were 17 species in addition to S. patens and S. californicus with greater that 5 % frequency (Table 1). There were 11 species that met the criteria as typical of disturbed sites (Table 1). Two species that germinated in control trays during the seed bank studies, Cardamine parviflora and Leontodon sp., were omitted from analyses as they were considered contaminants (i.e., the seeds were either present in the planting media or were introduced to the greenhouse through wind dispersal). Utricularia sp., which was excluded from analyses examining total seedling count, was present in unit 4 samples only; of the 30 stations in unit 4, this species was present at 3 stations in April 1997, 9 in September 1997, and 12 in March 1998. Species richness was highest in the unit 4 impact sites at all measurement times (Fig. 3). Seasonal variation in total vegetation and Spartina patens cover (Fig. 4) and in maximum height (Fig. 5) was apparent in both marshes. The cover of unvegetated bare ground at impact sites often exceeded that at control sites (Fig. 6). Analyses of initial

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Fig. 3 Mean species richness (vertical bars indicate standard error) at control and impact sites at Sabine National Wildlife Refuge, Louisiana

(i.e., pre-survey) data indicated that control and impact sites in both marshes differed significantly in several aspects (Table 2). For example, control sites in both marshes had significantly greater total cover and cover of Spartina patens than did impact sites, species richness was significantly greater in unit 4 impact sites compared to control sites, and interstitial salinity was greater in unit 1 impact sites than in control sites. Comparison of the marshes also indicated significant differences. While total vegetation percent cover did not differ between marshes (P = 0.7850), unit 1 had significantly (P \ 0.0001) higher percent cover of S. patens (78.77 ± 2.12 vs. 38.78 ± 5.14 % [data presented as mean ± 1 standard error]) and dead plant material (66.09 ± 3.39 vs. 41.48 ± 4.03 %, P \ 0.0001), and greater surface salinity (1.97 ± 0.13 ppt vs. 0.57 ± 0.12 ppt, P \ 0.0001) and interstitial salinity (3.29 ± 0.19 ppt vs. 1.09 ± 0.12 ppt, P = 0.0001) compared to unit 4. Compared to unit 1, unit 4 had higher species richness (3.25 ± 0.23 vs. 1.51 ± 0.08, P = 0.0001), greater maximum height (132.9 ± 5.65 cm vs. 102.0 ± 15.76 cm, P = 0.0001), and greater water depth (19.92 ± 1.38 cm vs. 15.95 ± 1.09 cm, P = 0.0269). Unit 1 ammonium concentration (118.90 ± 18.28 lM) exceeded (P = 0.0033) that in Unit 4 (51.21 ± 11.45 lM). All further analyses were conducted separately by unit because of the differences identified. Data collected within 6 weeks of the survey completion (June 1997) indicated that the disturbance categories varied in a single variable (Table 3). Maximum vegetation height in both marshes was greater at sites offset from airboat trails (100.4 ± 4.9 cm, unit 1; 190.0 ± 28.0 cm, unit 4) than in sites along the source lines (74.6 ± 4.0 cm, unit 1; 81.7 ± 20.1 cm, unit 4), receiver lines (83.3 ± 2.5 cm,

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Environmental Management (2014) 54:30–50

A

B Fig. 6 Mean percent cover of unvegetated bare ground (vertical bars indicate standard error) at control and impact sites at Sabine National Wildlife Refuge, Louisiana

Fig. 4 Mean total percent vegetation cover and mean Spartina patens cover (vertical bars indicate standard error) at control and impact sites in a unit 1 and b unit 4 at Sabine National Wildlife Refuge, Louisiana

Fig. 5 Mean maximum stem height (vertical bars indicate standard error) at control and impact sites at Sabine National Wildlife Refuge, Louisiana

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unit 1; 106.5 ± 15.8 cm, unit 4), and source/receiver intersections (64.0 ± 5.3 cm, unit 1; 82.9 ± 11.6 cm, unit 4). In unit 1, maximum height at source/receiver intersections was less than that at receiver lines. With the exception of interstitial water salinity in unit 1 in December 1997, which was lower at source/receiver line intersections (5.00 ± 0.39 ppt) than at source lines (6.83 ± 0.21 ppt), no difference among the four disturbance categories was found in analyses at later measurement times (Table 3). Disturbance categories were combined for subsequent analyses that compared control and impact sites. To identify immediate impacts from seismic exploration, pre-impact (time 1) and post impact (time 2) measurements were compared. Analysis for maximum height did not include measurements from the sites offset from the travel lanes. Several differences were found in response variables (Table 4). The time and treatment interaction was significant for four variables in unit 1 (total cover, maximum stem height, dead plant cover, and water depth) and two variables in unit 4 (maximum stem height and surface salinity) (Table 4). Since a significant interaction term indicates that the disturbance treatments responded differently by time, these results are described in detail. Total cover in unit 1 at time 2 was less at impact sites (71.61 ± 3.81 %) than at control sites (95.04 ± 3.25 %), whereas it did not differ at time 1. Note that although preliminary comparison of disturbance treatments for unit 1 indicated that time 1 total cover was also less at impact compared to control sites, this relationship lost significance when the Tukey multiple comparison test was applied in this analysis. Maximum vegetation height in both marshes responded differently with time. In unit 1 control sites,

Environmental Management (2014) 54:30–50

39

Table 2 Results of t tests comparing mean values of vegetation, soil, and water quality characteristics in control and impact sites in unit 1 and unit 4, Sabine National Wildlife Refuge, prior to initiation of 3D seismic exploration activities Variable

Unit 1 Control

Richness

Unit 4 Impact

t value

P

Control

Impact

t value

P

1.67 (0.12)

1.38 (0.09)

1.94

0.0584

2.32 (0.25)

3.99 (0.31)

-4.07

0.0002

Total cover (%)

87.27 (1.30)

77.34 (3.96)

2.38

0.0245

93.94 (4.73)

70.04 (5.38)

3.25

0.0020

Sppa cover (%) Scca cover (%)

85.14 (1.30) –

73.32 (3.49) –

3.17 –

0.0038 –

51.20 (7.68) 16.55 (4.92)

28.85 (6.47) 17.81 (3.44)

2.24 -0.22

0.0292 0.8300

108.33 (2.10)

96.55 (3.34)

2.99

0.0061

126.73 (7.56)

137.91 (8.19)

-0.98

0.3307

Maximum height (cm) Dead material (%)

80.08 (3.04)

55.61 (4.84)

4.29

0.0002

56.37 (5.27)

29.58 (4.94)

3.69

0.0005

Unvegetated (%)

3.96 (1.74)

16.93 (3.02)

-3.73

0.0010

8.87 (2.32)

19.54 (3.39)

-2.60

0.0151

Surface salinity (ppt)

1.50 (0.29)

2.06 (0.13)

-1.67

0.1124

0.81 (0.14)

0.26 (0.08)

3.00

0.0110

Interstitial salinity (ppt)

2.25 (0.16)

3.59 (0.22)

-4.95

0.0004

1.41 (0.28)

1.01 (0.13)

1.34

0.1903

Water depth (cm)

10.31 (0.97)

20.78 (1.28)

-6.35

Effects of disturbance associated with seismic exploration for oil and gas reserves in coastal marshes.

Anthropogenic disturbances in wetland ecosystems can alter the composition and structure of plant assemblages and affect system functions. Extensive o...
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