Journal of Applied Ecology 2012, 49, 174–181
doi: 10.1111/j.1365-2664.2011.02063.x
Local and landscape influences on plant communities in playa wetlands Jo-Szu Tsai1,2*, Louise S. Venne2, Scott T. McMurry3 and Loren M. Smith3 1
Wildlife and Fisheries Management Institute, Texas Tech University, Lubbock, TX 79409, USA; 2Department of Wildlife Ecology and Conservation, University of Florida, Gainesville, FL 32611, USA; and 3Department of Zoology, Oklahoma State University, Stillwater, OK 74078, USA
Summary 1. Hydroperiod, wetland size and land use of watersheds surrounding wetlands have important individual influences on plant communities in wetlands. Our objectives were to determine the effect and relative importance of local and landscape factors on plant species richness, diversity and composition of different functional groups (i.e. total, wetland-dependent, perennial, annual and exotic species) in recently inundated playa wetlands. 2. We surveyed plant communities in 80 wet playas in the Southern High Plains, USA, and measured local factors: water depth, playa volume loss, sediment depth and playa area. We included landscape variables within 3 km: number of playas, edge density, percentage urban area and percentage Conservation Reserve Program area (CRP; conversion from highly erodible cropland to mostly introduced perennial grassland). We also recorded dominant land use as native grassland or cropland. 3. Water depth negatively influenced all plant community metrics (i.e. richness, diversity and cover) while playa volume loss (sediment eroded from watershed filling the basin) had a negative influence on total, wetland-dependent and perennial richness and cover. Playas with more cropland within their watersheds had greater annual and exotic richness and cover, suggesting that agricultural activities within playa watersheds have changed plant composition and facilitated biological invasion. 4. Playa area was less important in predicting plant community metrics in playas. Although not as dominant as local variables, edge density had a positive influence on species richness. Other landscape factors such as number of playas, percentage urban area and percentage CRP area were less important and consistent among different plant community metrics. 5. Synthesis and applications. Our results show that continued unsustainable sedimentation will result in loss of perennial species and promotion of exotic and annual species in playas. Watershed management to limit unsustainable sedimentation has the potential to maintain original playa plant communities dominated by perennial ⁄ native species and should also reduce the loss of playa functionality. Key-words: annual species, exotic species, perennial species, plant composition, plant species richness, playa wetlands, sediment, southern high plains
Introduction Wetland plant community composition can be influenced by factors such as hydrology, surrounding land use, propagule sources and dispersal capabilities (e.g. Casanova & Brock 2000; Smith & Haukos 2002). Wetland vegetation composition and cover responds to hydrology and concomitant changes *Correspondence author. E-mail:
[email protected]
through time (Euliss et al. 2004). In addition, the surrounding vegetation matrix may influence the plant community of a habitat patch (Wiser & Buxton 2008). For example, land use adjacent to wetlands (e.g. 250–300 m) influences plant diversity and species richness via the abundance and distribution of propagules and the route by which propagules disperse (Houlahan et al. 2006). Surrounding habitat patches with more edges (e.g. roads and ditches) may increase the likelihood of introducing invasive species by providing corridors (Wilcox
2011 The Authors. Journal of Applied Ecology 2011 British Ecological Society
Plant communities in playa wetlands 175 1989; Parendes & Jones 2000). However, wetland seed banks are important for species that do not disperse readily. At a landscape scale, wetland area, wetland isolation and surrounding land use may influence plant species composition via the rate at which propagules are generated (Matthews et al. 2009a) and dispersed (Boughton et al. 2010). Wetland area also has been shown to be somewhat predictive of wetland plant richness as larger wetlands may hold water longer (Smith & Haukos 2002). Determining the strength of these factors in dictating wetland plant communities is important in selecting potential future restoration endpoints. If vegetation (e.g. richness, composition) is to be used as a restoration endpoint, an understanding of how wetlands and their surrounding landscape attributes influence the plant community is necessary in decision making. Loss of wetlands reduces landscape connectivity for wetland-dependent species relying on these habitats for reproduction, productivity and dispersal. This, in turn, can decrease landscape level biodiversity (Semlitsch & Bodie 1998; Gibbs 2000; Houlahan & Findlay 2003). In the conterminous United States, more than 53% of historical wetland area has been lost to filling, draining and modification of wetlands (Dahl 1990). Degradation has resulted further in functional and physical loss of wetland area and species (Holland et al. 1995; Davis & Froend 1999). Species will succeed or fail in impacted wetlands as dictated by local and landscape factors coupled with species dispersal and tolerance of environmental gradients (van der Valk 1981; Wright, Flecker & Jones 2003). Conservation and restoration efforts require that we understand how wetland degradation impacts biota and the function and longevity of wetlands (Kentula 2000). Approximately 25 000–30 000 playa wetlands in the Southern High Plains (SHP, c. 82 000 km2), USA, serve as focal points of biodiversity for plants, invertebrates, birds and amphibians (Haukos & Smith 1994). Playas are shallow, circular, depressional wetlands that formed and are maintained through combined processes of wind, waves and dissolution (Smith 2003). Playas average 6Æ3 ha (Guthery & Bryant 1982) and comprise c. 2% of the SHP landscape (Haukos & Smith 1994). Native prairie surrounding playa wetlands has mostly been converted to row-crop agriculture. Over the past 80 years (Smith 2003), intensive cultivation of the SHP has resulted in significant erosion of playa watersheds and unsustainable sediment accumulation in playas. Through enrolment in the Conservation Reserve Program (CRP; the dominant conservation program in the SHP, designed in part to conserve highly erodible soils throughout the US), unsustainable sedimentation from cropland surrounding playas should be curtailed. Playas embedded in the cropland landscape have lost more than 100% of their hydric-soil defined volume (Luo et al. 1997; Tsai et al. 2007). Playas with more cropland within their watersheds have shorter hydroperiods and higher water loss rates (Tsai et al. 2007, 2010). Playas surrounded by cropland also have fewer perennials and more exotic plant species than playas embedded in native grassland (Smith & Haukos 2002). However, influences of hydrology and landscape variables on vegetation communities have not been studied.
Our objectives were to test the influence of local and landscape variables on plant species richness, diversity and composition to determine their relative influence on plant communities in wet playas. We included local factors such as water depth, playa area, sediment depth and percentage playa volume loss that were hypothesized to impact plant presence and cover. While other studies have simply discussed land use as an influencing factor on wetland plant communities, we investigated more specific landscape scale factors such as percentage urban area, percentage CRP area and tilled index (ratio of tilled to untilled land within each watershed) to determine the impact of various anthropogenic land disturbances. We also incorporated edge density (i.e. total length of edges per area) to represent potential exotic source locations or dispersal routes (e.g. ditches along roads) and number of playas as potential source populations. We hypothesized that land use and surrounding playas are the dominant landscape factors determining plant species richness, diversity and composition (e.g. Smith & Haukos 2002; Houlahan et al. 2006; Matthews et al. 2009a).
Materials and methods STUDY AREA
We conducted this study in the Texas portion of the SHP (N 3037Æ9¢–N 3544Æ2¢, W 100 2Æ1¢–W 103 6Æ4¢; Fig. 1), which is the largest plateau in the USA (Sabin & Holliday 1995). Precipitation falls irregularly, annually averaging 450 mm in the northeast to 330 mm in the southwest portion of the SHP, mainly occurring in
Fig. 1. Location of study playas (n = 80) in the Southern High Plains, USA, in 2003 and 2004, with county names listed.
2011 The Authors. Journal of Applied Ecology 2011 British Ecological Society, Journal of Applied Ecology, 49, 174–181
176 J.-S. Tsai et al. spring and early autumn (Bolen, Smith & Schramm 1989). Playas are isolated from groundwater flow, thus precipitation and runoff are their only sources of inundation (Wood & Osterkamp 1987). Because of the localized nature of precipitation, not all playas hold water in the same year. As evapotranspiration (2000–2500 mm year)1; Bolen, Smith & Schramm 1989) and infiltration (Zartman, Evans & Ramsey 1994) exceed precipitation and runoff, most playas dry annually (Smith 2003).
obtained digitized U. S. Geological Survey contour maps (TNRIS 2006) and estimated the watershed of each study playa (Ekanayake et al. 2009). We followed Tsai et al. (2007) to calculate tilled index [amount of tilled (i.e. cropland and CRP) vs. untilled landscape (i.e. native grass) within the watershed]. The values for tilled index range from )1 (100% native grass watershed) to 1 (100% cropland ⁄ former cropland watershed).
DATA ANALYSES DATA COLLECTION
Forty playas containing surface water were selected in each year (80 total), after inundation precipitation events in late May and early June in 2003 and 2004. Selected playas were split evenly between cropland and grassland using the predominant surrounding land use for categorization. We determined vegetation composition in playa wetlands in early July, August and September in 2003 and 2004 (total of 240 surveys) using step-point sampling (Bonham 1989) along two parallel transects of approximately equal length. Each transect ran along a 45 angle from the southwest to the northeast edge of the playa. We also recorded water depth concurrent with vegetation surveys at three equidistant locations across the diameter of the playa basin. We measured playa characteristics when playas were dry. We measured playa area by walking along the visual edge of each playa with a Global Positioning System unit (Applied Field Data Systems, Houston, TX, USA) and Fieldworker software (FieldWorker Products Ltd., Toronto, ON, Canada). The visual edge is distinguished by obvious changes of slope, soil colour and vegetation type (i.e. upland to wetland; Luo et al. 1997). We used a soil auger to determine sediment depth from the top of the sediment to the Randall clay (i.e. hydric soil; Allen et al. 1972) at 5–6 points in the playa basin. We obtained basin elevation with a level using the centre of each playa and each of eight equally spaced points along the visual edge. We determined playa soil edge (change from Randall clay to upland soil) by taking a series of sediment cores perpendicular to the visual edge. We then used mean sediment depth, playa area, location of soil edge, distance from the visual edge to the edge of playa basin and mean basin elevation to calculate sediment volume and original playa volume (Luo et al. 1997; Tsai et al. 2010). Finally, playa volume loss was calculated as sediment volume divided by original playa volume. Three assumptions were made for volumetric calculations: (i) Sediment was evenly distributed across the playa basin, (ii) Playa is elevated after sedimentation with the same shape and (iii) The shape of playa was a truncated cone (Tsai et al. 2010). We obtained Digital Orthophoto Quarter Quadrangle aerial photos from the Texas Natural Resources Information System website (TNRIS 2006) and digitized a 3-km radius plot (i.e. 2827 ha) from the centre of each playa. We chose a 3-km radius to study the effect of landscape level variables as suggested by previous studies (e.g. Houlahan & Findlay 2004; Declerck et al. 2006). Land uses were classified as playa, grassland, cropland, CRP, urban and other (e.g. reservoir). We used farm folders from the Farm Service Agency of U. S. Department of Agriculture in Deaf Smith and Floyd counties to verify our land use data layers. We used FRAGSTATS*ARC (The Sanborn Map Company Inc. Colorado Springs, CO, USA) to calculate landscape variables within the 3-km buffer, including number of playas, Shannon diversity index of land use, percentage urban and CRP area and edge density (McGarigal & Marks 1995). Shannon diversity index of land use is calculated based on the number and evenness of land use types, which uses the equation for Shannon index of diversity (Magurran 1988). Edge density is the total length of edges (e.g. roads, field edges) of all patches within a given area (m ha)1). We also
Species richness included species encountered on both step-point transects, including points with no vegetation (i.e. bare soil or water). We calculated percentage composition (cover) by dividing number of points with vegetation by total points. We calculated Shannon index of diversity (hereafter diversity) using the number of points at which a plant species was encountered to represent the relative abundance of individuals (Magurran 1988). We categorized plant species into functional groups as follows: perennial or annual, native or exotic and wetland-dependent (i.e. facultative wetland and obligate wetland plants) or non-wetland (i.e. facultative, facultative upland and obligate upland plants) following the U.S. National Wetlands Inventory (1996). We calculated species richness and cover in functional groups. We tested variance inflation factor for all variables to assess collinearity and exclude highly correlated variables (Kutner et al. 2004) to avoid decreasing statistical power and parameter accuracy of models (Graham 2003). After testing multicollinearity, we used the remaining eight variables (i.e. water depth, tilled index, playa volume loss, playa area, edge density, number of playas, percentage urban area and percentage CRP area) to build candidate model sets. Although sediment depth is an easier measurement to obtain than playa volume loss, we chose playa volume loss instead of sediment depth for models because playa volume loss is a standardized way to evaluate the influence of sedimentation on playa function. We constructed 46 a priori generalized models based on biological relevance and field observations using the eight variables to describe species richness, diversity and cover of different plant functional groups. To ensure a balanced model set, candidate model sets were built considering that each variable appeared approximately an equal number of times. We treated playa as the experimental unit and three vegetation surveys for each playa as repeated measures. We tested normality and homogeneity of variance and used Poisson distribution with log-link function for species richness and cover of different plant functional groups and normal distribution with identity-link function for plant diversity. We performed the analyses using generalized linear mixed models (lmer function in lmer4 package) in R (version 2.9.2; R Development Core Team 2009). Additionally, we used Student’s t-test to compare sediment depth and playa volume loss between playas in cropland (tilled index > 0)- and grassland (tilled index < 0)- dominated watersheds. We selected models using corrected Akaike’s Information Criterion (AICc) (Burnham & Anderson 2002). We considered models with DAICc < 2 as best fit models for each response variable because they had support given the data. We used the concept of multimodel inference to calculate relative importance of each variable (Burnham & Anderson 2002:149). We also calculated the direction and effect size of variables in the models with DAICc value
