- Top of page
- Materials and methods
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.
- Top of page
- Materials and methods
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 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 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 6·3 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).
- Top of page
- Materials and methods
We recorded a total of 85 plant species during the survey. Mean tilled index was 0·51, indicating that watersheds of our study playas were dominated by cropland. Mean water depth was 32·3 cm, and maximum water depth was c. 150 cm (Table 1). Mean sediment depth for all playas was 27·1 cm. However, mean sediment depth for playas within grassland (9·5 cm, SE = 1·2) was smaller than cropland-dominated watersheds (44·8 cm, SE = 4·2; t = 6·68, P < 0·001). Mean playa volume loss for all playas was 109·7%, indicating that playas we sampled have lost more than their original hydric-soil defined volume. Mean playa volume loss for playas within grassland-dominated watersheds (32·1%, SE = 5·1%) was smaller than cropland-dominated watersheds (187·4%, SE = 30·7%; t = 4·00, P < 0·001). Playas are situated at the lowest point of closed watersheds hence impacted playas still occur in depressions that hold water even when the associated playas have lost their original volume.
Table 1. Mean, SE, minimum and maximum of explanatory variables measured in playas (n = 80) in the Southern High Plains, USA, from June 2003 to May 2005, to evaluate their influence on plant communities
|Water depth (WD, cm)||32·3||3·7||0·0||149·7|
|Tilled index (TI)*||0·51||0·07||−1·00||1·00|
|Playa volume loss (VL, %)||109·7||17·7||1·0||951·0|
|Sediment depth (SD, cm)||27·1||2·9||0·9||104·9|
|Area (AR, ha)||11·1||0·9||1·4||47·2|
|Shannon diversity index of land use within 3 km [SHDI(3)]||0·53||0·17||0·08||0·96|
|Edge density within 3 km [ED(3); m ha−1]||24·2||0·9||9·3||55·7|
|Number of playas within 3 km [NP(3)]||16·9||1·5||0||67|
|Conservation Reserve Program area within 3 km [PR(3), %]||23·0||1·7||0·0||61·4|
|Urban area within 3 km [PU(3), %]||1·4||0·3||0·0||14·9|
Water depth and playa volume loss were the two most important variables with the greatest effect sizes in best models of total, wetland-dependent and perennial species richness (negative influence; Tables 2 and 3). Edge density also had some support given the data on total, wetland-dependent and perennial species richness in playas (positive influence; Table 3). The Akaike’s weights of the best models for total, wetland-dependent and perennial richness were 0·60, 0·63 and 0·78, respectively (Table 2).
Table 2. Multiple regression models predicting plant species richness and diversity in playas (n = 80) in the Southern High Plains, USA, from June 2003 to May 2005, with number of parameters (k), Δ AICc and Akaike’s weights (wi). Only models with ΔAICc < 2 were presented for each response variable
|Total richness||−0·32 (0·03) WD − 0·32 (0·05) VL + 0·11 (0·04) ED(3)||4||0·00||0·60|
|Wetland-dependent richness||−0·39 (0·04) WD − 0·34 (0·07) VL + 0·13 (0·06) ED(3)||4||0·00||0·35|
|−0·40 (0·04) WD − 0·37 (0·08) VL + 0·13 (0·06) TI + 0·10 (0·07) ED(3) + 0·10 (0·06) NP(3) + 0·10 (0·05) PR(3) + 0·06 (0·05) AR − 0·03 (0·06) PU(3)||9||0·49||0·28|
|Perennial richness||−0·49 (0·07) VL − 0·29 (0·04) WD + 0·12 (0·04) ED(3)||4||0·00||0·78|
|Annual richness||−0·35 (0·05) WD + 0·16 (0·07) TI||3||0·00||0·18|
|−0·35 (0·05) WD + 0·17 (0·07) TI + 0·11 (0·07) ED(3) + 0·10 (0·06) AR||5||0·05||0·17|
|−0·35 (0·05) WD + 0·17 (0·07) TI + 0·09 (0·06) AR||4||0·26||0·16|
|−0·35 (0·05) WD + 0·16 (0·07) TI + 0·09 (0·06) AR + 0·08 (0·06) PR(3)||5||0·80||0·12|
|−0·36 (0·05) WD + 0·24 (0·07) TI − 0·17 (0·08) VL + 0·10 (0·06) PR(3) + 0·10 (0·07) NP(3) + 0·05 (0·06) AR + 0·04 (0·07) PU(3) + 0·03 (0·08) ED(3)||9||1·02||0·11|
|Exotic richness||+ 0·38 (0·10) TI − 0·15 (0·08) WD||3||0·00||0·29|
|+ 0·37 (0·10) TI||2||1·37||0·15|
|Diversity||−0·18 (0·04) VL − 0·18 (0·03) WD + 0·10 (0·04) PR(3)||4||0·00||0·50|
|−0·21 (0·04) VL − 0·18 (0·03) WD + 0·09 (0·05) ED(3) + 0·08 (0·04) TI + 0·08 (0·04) PR(3) − 0·05 (0·05) NP(3) + 0·04 (0·04) AR − 0·00 (0·05) PU(3)||9||1·85||0·20|
Table 3. Relative importance of explanatory variables from multiple regression models to predict plant species richness, diversity and composition in playas (n = 80) in the Southern High Plains, USA, from June 2003 to May 2005
For annual species richness, water depth had the greatest relative importance value and effect size (negative influence), followed by tilled index and playa area (positive influence; Tables 2 and 3). Number of playas, percentage urban area and percentage CRP area also appeared in the top models but those models had low weights and effect sizes, indicating less empirical support (Table 2). Akaike’s weight of best fit models for annual species was 0·74.
In the models of exotic species richness, tilled index had the strongest effect (positive influence; Tables 2 and 3). Water depth had the next strongest effect (negative influence). Playa area, playa volume loss and all the landscape variables were the least important (Table 3). Akaike’s weight of best fit models for exotic species was 0·44.
Total plant diversity
In models of diversity, water depth and playa volume loss had the strongest effect (negative influence; Tables 2 and 3). Percentage CRP area was the third most important variable (positive influence). Tilled index, playa area, number of playas, edge density and percentage urban area had less support given the data (Table 3). The combined Akaike’s weight of best fit models for total plant diversity was 0·70.
Water depth and playa volume loss had the strongest effect in best models of total, wetland-dependent and perennial plant cover (negative influence; Tables 3 and 4). Playa area (negative influence) and edge density (positive influence) also appeared in the best models of total, wetland-dependent and perennial cover. However, the effect sizes of playa area and edge density were small compared with water depth and playa volume loss. Akaike’s weight of best fit models for total and perennial cover was essentially the same at 0·85 and 0·84, respectively (Table 4), while Akaike’s weight of best fit models for wetland-dependent species was 0·94.
Table 4. Multiple regression models predicting percentage composition (cover) of plant species in playas (n = 80) in the Southern High Plains, USA, from June 2003 to May 2005, with number of parameters (k), ΔAICc and Akaike’s weights (wi). Only models with Δ AICc < 2 were presented for each response variable
|Total composition||−0·73 (0·02) WD − 0·52 (0·10) VL − 0·16 (0·10) AR||4||0·00||0·24|
|−0·73 (0·02) WD − 0·51 (0·10) VL − 0·17 (0·10) AR + 0·14 (0·09) PU(3)||5||0·00||0·24|
|−0·73 (0·02) WD − 0·49 (0·10) VL||3||0·49||0·19|
|−0·73 (0·02) WD − 0·48 (0·10) VL + 0·14 (0·09) ED(3)||4||0·55||0·18|
|Wetland-dependent composition||−0·72 (0·02) WD − 0·70 (0·14) VL − 0·24 (0·13) AR||4||0·00||0·28|
|−0·72 (0·02) WD − 0·64 (0·13) VL + 0·23 (0·12) ED(3)||4||0·07||0·27|
|−0·72 (0·02) WD − 0·64 (0·14) VL||3||1·22||0·15|
|−0·72 (0·02) WD − 0·70 (0·14) VL − 0·24 (0·13) AR + 0·11 (0·12) PU(3)||5||1·40||0·14|
|−0·72 (0·02) WD − 0·69 (0·14) VL − 0·25 (0·13) AR + 0·07 (0·13) NP(3)||5||1·95||0·10|
|Perennial composition||−1·04 (0·18) VL − 0·68 (0·03) WD + 0·19 (0·13) ED(3)||4||0·00||0·29|
|−1·03 (0·17) VL − 0·68 (0·03) WD||3||0·16||0·27|
|−1·08 (0·18) VL − 0·68 (0·03) WD − 0·15 (0·13) AR||4||1·10||0·17|
|−1·07 (0·18) VL − 0·68 (0·03) WD − 0·16 (0·13) AR + 0·15 (0·12) PU(3)||5||1·90||0·11|
|Annual composition||−0·83 (0·04) WD + 0·48 (0·17) TI − 0·28 (0·17) AR||4||0·00||0·34|
|−0·84 (0·04) WD + 0·50 (0·17) TI||3||0·43||0·27|
|−0·83 (0·04) WD + 0·48 (0·17) TI − 0·27 (0·17) AR + 0·18 (0·17) ED(3)||5||1·13||0·19|
|Exotic composition||−0·94 (0·10) WD + 0·56 (0·26) TI||3||0·00||0·29|
|−0·94 (0·10) WD + 0·57 (0·26) TI − 0·45 (0·25) PR(3) + 0·09 (0·25) AR||5||1·20||0·16|
|−0·94 (0·10) WD − 0·43 (0·26) PR(3)||3||1·80||0·12|
Water depth was the most important variable predicting annual cover (negative influence) with the greatest effect sizes (Tables 3 and 4). Tilled index (positive influence) and playa area (negative influence) also had high relative importance values. Akaike’s weight of best fit models for annual cover was 0·80.
Similar to annual cover, water depth (negative influence) was the most important variable in best models of exotic species, followed by tilled index (positive influence) (Tables 3 and 4). Percentage CRP area (negative influence) and playa area (positive influence) also appeared in the best fit model but effect sizes were small. The combined Akaike’s weight for the best fit models was 0·57.