Rapid assessment methods (RAMs) have become an integral part of state and federal wetland programs by providing a consistent method for monitoring and prioritizing wetland conservation efforts. RAMs ...evaluate condition along an anthropogenic disturbance gradient based on qualitative and quantitative measures of wetland indicators. However, RAM applicability outside of the intended region may be difficult or inappropriate due to differences in wetland types, natural variability, and types of stressors. Given the influence of regional and wetland variability on the effectiveness of RAMs, our approach focused on the development and validation of a method applicable to specific wetland types found in Oklahoma and other regions in the Central Great Plains. We applied the Oklahoma Rapid Assessment Method (OKRAM) in 28 depressional wetlands across the state and evaluated the method’s ability to detect condition along a disturbance gradient. We found consistent relationships between OKRAM scores and plant data (e.g., Floristic Quality Index, species richness, and diversity) and with a landscape assessment of anthropogenic disturbance. Based on our results, OKRAM has utility as a tool for differentiating between high and low quality depressional wetlands in Oklahoma, with potential for applicability across other regions of the Central Great Plains.
•Floristic Quality Index can evaluate depressional wetland condition in Oklahoma.•Regional environmental differences can influence Floristic Quality Index results.•Reference criteria should be ...established based on ecoregions.
Floristic Quality Assessment (FQA) has been recognized as a useful tool for evaluating wetland condition and guiding conservation and management efforts. However, FQA validation to confirm that results represent actual wetland condition is limited. Moreover, FQA has been applied across large regions without consideration for the high environmental variability (e.g., temperature, precipitation, and topography) within application areas, which may limit the effectiveness of FQA as an assessment tool. Because Oklahoma contains diverse ecoregions and extreme environmental gradients, this provides an opportunity to examine the influence of spatial and environmental variability on FQA results. We sampled 68 depressional wetlands dispersed across the state to (1) validate an FQA metric, Floristic Quality Index (FQI), with two established condition assessment methods (i.e., Landscape Development Intensity Index LDI and Oklahoma Rapid Assessment Method OKRAM) and (2) evaluate the influence of environmental variation (e.g., high and low precipitation) on FQI scores. In our validation analysis, we found a strong positive relationship between FQI and OKRAM, indicating the FQI was able to detect changes in wetland condition in depressional wetlands along a disturbance gradient. Additionally, strong negative relationships between FQI and LDI suggest that FQI is responsive to stressors within the surrounding landscape. When evaluating environmental influence on FQI scores, we found substantial variation between reference wetlands based on location, with higher scores occurring in eastern sites (high precipitation) and lower scores occurring in western sites (low precipitation). We used Canonical Correspondence Analysis (CCA) to assess the relationship between plant communities and environmental variables, and found that precipitation was more indicative of plant species distribution than wetland condition (i.e., disturbed or reference condition). Thus, C-values of plant species (i.e., predetermined values assigned to individual plant species) and corresponding FQI scores differed significantly across ecoregions based on high and low precipitation, regardless of wetland condition. This phenomenon highlights the importance of considering regional environmental differences when developing FQI thresholds for wetland assessments, especially across diverse states or ecoregions. To reduce the influence of regional differences on FQIs, as well as other vegetation-based methods, condition class thresholds and reference criteria should be established based on ecoregions to more accurately capture wetland condition using FQI.
Wetlands provide many important ecosystem functions and services worldwide and are hotspots of biological diversity. However, depressional wetlands are particularly vulnerable to effects of climate ...change due to the significant role that precipitation and surface runoff play in shaping their hydrology. In the Southern Great Plains of North America, climate projections predict more extreme storm events, higher temperatures, and severe droughts, which could threaten natural hydrological patterns of depressional wetlands in this region. Regional hydrological models that accurately predict water dynamics are critical for developing effective climate change adaptation strategies. We developed a model to predict wetland inundation status for depressional wetlands in the Pleistocene Sand Dunes Ecoregion of Oklahoma, USA, that evaluated effects of weather variables, wetland characteristics, and landscape-level variables. We then predicted numbers of inundated wetlands and frequency of wetland inundation under three climate change scenarios for the middle and end of the century (2036–2050 and 2084–2099, respectively). Total precipitation measured in the 2 months prior to an inundation event and average daily temperature were the most important variables predicting wetland inundation status, and land use and wetland characteristics explained relatively little variation in water dynamics. Projections of wetland inundation status indicate numbers of inundated wetlands will decrease in spring and summer by as much as 42% and 79%, respectively, by midcentury. Future inundation patterns during fall and winter were less clear but will likely be similar to current, highly variable conditions. These results suggest climate change may threaten persistence of wetlands during key seasonal periods when humans, plants, and wildlife depend on them for crucial resources and services.
In areas with a high density of ephemeral wetlands, traditional mapping protocols may underestimate occurrence of wetlands when single-date base-imagery is utilized. In the Pleistocene Sand Dunes ...Ecoregion in Oklahoma, National Wetland Inventory (NWI) maps created using base-imagery from a dry year omitted large numbers of ephemeral wetlands. To improve the likelihood of capturing inundated depressions, we classified water pixels from 51 Landsat images (3 images per year: pre/early, peak, and late/post growing season) from 1994 to 2011. Several image classification methods were tested but decision tree analysis with training pixels from multi-season imagery provided the greatest accuracy. Accuracy was determined through manual comparison of two Landsat images with concurrent aerial imagery (Kappa =0.96 and 0.93 for the two images). Wetland polygons were created from water/non-water rasters and given hydroperiod designations based on the number of inundated periods. Landsat-derived wetland maps identified 3156 wetland units, 718 more than the original 1980s NWI, with only 33.9 % agreement between the two maps. Finally, one meter LiDAR data were combined with classified Landsat images to determine the volume of water in wetlands during each image date. These wetland maps can assist with estimating the availability of inundated habitat during wet, dry, and average rainfall periods.
Invertebrates play an important role influencing wetland functions. Specifically, they provide important food for many waterbirds and other wetland species. To better understand the role ...environmental factors play in influencing invertebrates, we examined the influence of local and landscape factors on invertebrate communities inhabiting depressional wetlands in Oklahoma. We sampled invertebrates from 58 wetlands during 2009 and 2010. Diversity and taxa richness increased as the season progressed and with vegetation complexity and cover. Diversity and richness decreased as water quality was impacted by nutrient and sediment loading. Local variables occurred more consistently in taxa models than landscape variables. Important local variables included wetland hydrology, vegetation complexity, and water quality, while important landscape variables included density and type of wetlands surrounding wetlands. Land-use practice was the least important landscape variable, but is an important variable due to potential relationships with local variables such as water quality. Low variation (12–26 %) explained by the pCCA suggests other variables may be influencing invertebrate communities, but an alternative explanation is that invertebrates are insensitive to environmental variation. These findings can guide both local management of wetlands and conservation strategies at the watershed or regional scale to benefit not only invertebrates but other wetland dependent species.
The hydrogeomorphic approach (HGM) to wetland classification and functional assessment has been applied regionally throughout the United States, but the ability of HGM functional assessment models to ...reflect wetland condition has limited verification. Our objective was to determine how variability derived from anthropogenic effects and natural variability impacted site assessment variables within regional wetland subclasses in central Oklahoma. We collected data for nine potential assessment variables including vegetation physiognomy (e.g., tree basal area, herbaceous cover, canopy cover, etc.) and soil organic matter at wetlands of two HGM riverine subclasses (oxbow and riparian) in May and June, 2010. Using Akaike Information Criteria, we identified limited relationships between landscape disturbance metrics and assessment variables within subclasses. The high degree of natural variability from climatic and hydrologic factors within both subclasses may be masking the impact of landscape disturbance on the other measured assessment variables. Precipitation had significant effects on assessment variables within each of the subclasses. To reduce natural climatic variability, the reference domain may need to be further subdivided. The approach used in this study provides fairly rapid and quantitative methods for evaluating the effectiveness of using HGM assessment variables in assessing wetland condition regionally.
Summary
Species occurrences have multiple ecological states that may strongly influence community analysis and inference. This may be especially true in freshwater systems where many animals have ...complex life cycles with adult dispersal and juvenile resident stages.
The effects of ecological state variation on standard empirical approaches are largely unknown. Here, we analysed the effects of natal resident versus non‐natal immigrant species occurrence on community‐level environmental gradient modelling and spatial–environmental hypothesis testing using adult dragonflies and damselflies as model taxa.
Resident and total (resident + immigrant) occurrences of these taxa responded to different sets of environmental variables and resident occurrences reduced model selection uncertainty in 75% of test cases.
Effects of environmental gradients, spatial gradients or both were observed in residents but not immigrants, and supported predictions of dispersal limitation and niche‐based species sorting often implicated for structuring freshwater communities.
These results indicate that resident‐only analysis of the dispersal stage should improve multi‐model inference and detection of spatial–environmental effects in freshwater community ecology. The species resident–immigrant dichotomy neglects population dynamics and individual variation yet apparently marks an ecologically significant boundary that scales up to influence community‐level occurrence patterns.
The National Wetlands Inventory (NWI) is the most extensive inventory of wetland resources in the U.S., but it has limited ability to contribute to characterizations of wetland functions. We provide ...a methodology for reclassifying NWI polygons into Hydrogeomorphic (HGM) classes to facilitate monitoring wetland functions. We conducted this reclassification using spatial and attribute queries within Geographic Information Systems (GIS) for wetlands in central Oklahoma. Once classified, 149 randomly selected wetlands in four HGM classes (depressional, lacustrine fringe, riverine, and impounded depressional) were field verified. The overall accuracy of the GIS classification was 60%. Inherent issues with NWI due to attribute accuracy, spatial accuracy, and map age accounted for >50% of the misclassified sites in this analysis. The results from this analysis were also used to provide an inventory of wetlands in each HGM class and subclass based on user’s accuracy metrics. Reclassifying NWI polygons into HGM classes can assist with determining the spatial distribution and relative abundance of specific wetland classes which allows for more focused wetland restoration and monitoring efforts. However, the error rate associated with reclassification should be calculated to ensure that incorrect conclusions are not drawn regarding the abundance of HGM wetland classes and their associated functions.
(1) Accurate wetland maps are an important resource for wetland management with applications including prioritizing restoration and tracking habitat loss. Traditional wetland maps utilize single-date ...imagery often underestimating ephemeral wetlands. High-recurrence satellite imagery was classified to identify patterns of inundation in regional wetlands over an 18 year period with high accuracy. Updated maps identified over 700 more wetlands than maps previously available for the area. Because new maps were created using long-term inundation information, they also included more accurate water regime attributes. (2) Classified satellite images were also used to develop regional wetland hydrologic models. Inundation in approximately 500 wetlands was modeled over 18 years using climate data, land-use and wetland size as independent variables. The quantity, intensity and timing of rainfall as well as long-term drought indices were all important in predicting wetland inundation. Furthermore, small wetlands in grassland watersheds were less likely to be inundated than large wetlands surrounded by agriculture. Under future climate scenarios, regional wetlands are potentially at risk of decreased frequency of inundation, with small grassland wetlands most vulnerable. (3) Landscape connectivity of inundated wetlands also impacts biotic communities. This study provides evidence for temporally variable effects of connectivity and vegetation complexity on wetland invertebrate richness and metacommunity organization. Late in the growing season vegetation complexity had a greater effect on richness and sites with similar vegetation increased in community similarity. Permanent wetlands appear to act as refuges during periods of drought and supply colonists to temporary wetlands early in the growing season. Early in the season dispersal increases wetland richness and makes proximate sites more compositionally similar. Late in the season, the spatial scale at which wetlands are connected appears to depend on the number of inundated wetlands regionally. Understanding the temporal fluctuations in local and regional effects is likely to elucidate the complex patterns of wetland invertebrate community organization.
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