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Brian Gara

Publications and source records attributed to Brian Gara.

8 recordsLinked to original sources

Site-scale disturbance best predicts moss, vascular plant, and amphibian indices in Ohio wetlands

Loss of wetland habitats and their associated biological communities is a major environmental concern. Quality assessment indices (QAIs) and indices of biological integrity (IBIs) are useful for assessing the responses of taxa to wetland habitat quality and land use in the surrounding landscape. We synthesized the results of our previous predictive modeling studies of five IBIs and QAIs for communities of mosses, vascular plants, and amphibians in forested and emergent wetlands in Ohio (USA). Overall, the single best predictor of these indices was a metric that estimated site-scale (i.e., within the wetland boundaries) substrate and habitat development, alteration, and disturbance. The second most important predictor was a metric that assessed site-scale wetland plant community types and quality, degree of interspersion, and microtopography. Landscape-scale variables better predicted moss and amphibian indices than either vascular plant index. Our results indicate that applying management practices that reduce the effects of site-scale anthropogenic disturbances and increase habitat complexity, such as creating forested buffers surrounding wetlands, increasing wetland contiguity, and creating hummocks and tussocks may simultaneously enhance amphibian, vascular plant, and moss communities in forested and emergent wetlands. Such a focused strategy may enable management agencies to more effectively apportion resources for wetland restoration and construction projects.

Ecological Restoration

Surrounding land cover types as predictors of palustrine wetland vegetation quality in conterminous USA

The loss of wetland habitats and their often-unique biological communities is a major environmental concern. We examined vegetation data obtained from 380 wetlands sampled in a statistical survey of wetlands in the USA. Our goal was to identify which surrounding land cover types best predict two indices of vegetation quality in wetlands at the regional scale. We considered palustrine wetlands in four regions (Coastal Plains, North Central East, Interior Plains, and West) in which the dominant vegetation was emergent, forested, or scrub-shrub. For each wetland, we calculated weighted proportions of eight land cover types surrounding the area in which vegetation was assessed, in four zones radiating from the edge of the assessment area to 2 km. Using Akaike's Information Criterion, we determined the best 1-, 2- and 3-predictor models of the two indices, using the weighted proportions of the land cover types as potential predictors. Mean values of the two indices were generally higher in the North Central East and Coastal Plains than the other regions for forested and emergent wetlands. In nearly all cases, the best predictors of the indices were not the dominant surrounding land cover types. Overall, proportions of forest (positive effect) and agriculture (negative effect) surrounding the assessment area were the best predictors of the two indices. One or both of these variables were included as predictors in 65 of the 72 models supported by the data. Wetlands surrounding the assessment area had a positive effect on the indices, and ranked third (33%) among the predictors included in supported models. Development had a negative effect on the indices and was included in only 28% of supported models. These results can be used to develop regional management plans for wetlands, such as creating forest buffers around wetlands, or to conserve zones between wetlands to increase habitat connectivity.

Science of the Total Environment

Number of genera as a potential screening tool for assessing quality of bryophyte communities in Ohio wetlands

Bryophytes (mosses, liverworts, and hornworts) have numerous advantages as indicators of environmental quality. A quality assessment index for bryophyte species assemblages (BQAI) was developed for the State of Ohio, USA. Reliable identification of bryophytes to species often requires considerable training, practice, and time. In contrast, reliable identification to genera for most bryophytes in Ohio requires much less training. We identified 110 bryophyte species (14 liverworts and 96 mosses) belonging to 69 genera (13 liverwort and 56 moss) in 45 wetlands (27 emergent, 13 forested, and 5 shrub) in Ohio. As expected, there were more genera and higher BQAI scores in forested than in emergent wetlands. Number of genera was highly correlated ( r  ≥ 0.9) with BQAI in emergent and forested wetlands and for the combined set of wetlands. Number of genera and BQAI responded almost identically to an index of wetland disturbance. The results suggest that number of genera has potential as a screening tool for assessing bryophyte community quality in wetlands in some regions.

Wetlands

Moss and vascular plant indices in Ohio wetlands have similar environmental predictors

Mosses and vascular plants have been shown to be reliable indicators of wetland habitat delineation and environmental quality. Knowledge of the best ecological predictors of the quality of wetland moss and vascular plant communities may determine if similar management practices would simultaneously enhance both populations. We used Akaike's Information Criterion to identify models predicting a moss quality assessment index (MQAI) and a vascular plant index of biological integrity based on floristic quality (VIBI-FQ) from 27 emergent and 13 forested wetlands in Ohio, USA. The set of predictors included the six metrics from a wetlands disturbance index (ORAM) and two landscape development intensity indices (LDIs). The best single predictor of MQAI and one of the predictors of VIBI-FQ was an ORAM metric that assesses habitat alteration and disturbance within the wetland, such as mowing, grazing, and agricultural practices. However, the best single predictor of VIBI-FQ was an ORAM metric that assessed wetland vascular plant communities, interspersion, and microtopography. LDIs better predicted MQAI than VIBI-FQ, suggesting that mosses may either respond more rapidly to, or recover more slowly from, anthropogenic disturbance in the surrounding landscape than vascular plants. These results supported previous predictive studies on amphibian indices and metrics and a separate vegetation index, indicating that similar wetland management practices may result in qualitatively the same ecological response for three vastly different wetland biological communities (amphibians, vascular plants, and mosses).

Ohio

Mosses in Ohio wetlands respond to indices of disturbance and vascular plant integrity

We examined the relationships between an index of wetland habitat quality and disturbance (ORAM score) and an index of vascular plant integrity (VIBI-FQ score) with moss species richness and a moss quality assessment index (MQAI) in 45 wetlands in three vegetation types in Ohio, USA. Species richness of mosses and MQAI were positively associated with ORAM and VIBI-FQ scores. VIBI-FQ score was a better predictor of both moss species richness and MQAI than was either ORAM score or vegetation type. This result was consistent with the strict microhabitat requirements for many moss species, which may be better assessed by VIBI-FQ than ORAM. Probability curves as a function of VIBI-FQ score were then generated for presence of groups of moss species having the same degree of fidelity to substrate and plant communities relative to other species in the moss flora (coefficients of conservatism, CCs). Species having an intermediate- or high degree of fidelity to substrate and plant communities (i.e., species with CC ≥ 5) had a 50% probability of presence (P 50 ) and 90% probability of presence (P 90 ) in wetlands with intermediate- and high VIBI-FQ scores, respectively. Although moss species richness, probability of presence of species based on CC, and MQAI may reflect wetland habitat quality, the 95% confidence intervals around P 50 and P 90 values may be too wide for regulatory use. Moss species richness, MQAI, and presence of groups of mosses may be more useful for evaluating moss habitat quality in wetlands than a set of “indicator species.”

Ohio

Negative effects of excessive soil phosphorus on floristic quality in Ohio wetlands

Excessive soil nutrients, often from agricultural runoff, have been shown to negatively impact some aspects of wetland plant communities. We measured plant-available phosphorus (Mehlich-3: MeP) in soil samples, and assessed the vascular plant community and habitat degradation at 27 emergent and 13 forested wetlands in Ohio, USA. We tested two hypotheses: (1) that an index of vegetation biological integrity based on floristic quality was lower in wetlands with higher concentrations of MeP in the soil, and (2) that higher concentrations of MeP occurred in wetlands with more habitat degradation (i.e., lower quality), as estimated by a rapid assessment method. Hypothesis (1) was supported for emergent, but not for forested wetlands. Hypothesis (2) was marginally supported ( P = 0.09) for emergent, but not supported for forested wetlands. The results indicate that the effect of concentration of phosphorus in wetland soils and the quality of plant species assemblages in wetlands is more complex than shown in site-specific studies and may depend in part on degree of disturbance in the surrounding watershed and dominant wetland vegetation type. Woody plants in forested wetlands are typically longer lived than herbaceous species in the understory and emergent wetlands, and may persist despite high inputs of phosphorus. Further, the forested wetlands were typically surrounded by a wide band of forest vegetation, which may provide a barrier against sedimentation and the associated phosphorus inputs to the wetland interior. Our results indicate that inferences about soil nutrient conditions made from rapid assessment methods for assessing wetland habitat condition may not be reliable.

Ohio

Presence of indicator plant species as a predictor of wetland vegetation integrity

We fit regression and classification tree models to vegetation data collected from Ohio (USA) wetlands to determine (1) which species best predict Ohio vegetation index of biotic integrity (OVIBI) score and (2) which species best predict high-quality wetlands (OVIBI score >75). The simplest regression tree model predicted OVIBI score based on the occurrence of three plant species: skunk-cabbage (Symplocarpus foetidus), cinnamon fern (Osmunda cinnamomea), and swamp rose (Rosa palustris). The lowest OVIBI scores were best predicted by the absence of the selected plant species rather than by the presence of other species. The simplest classification tree model predicted high-quality wetlands based on the occurrence of two plant species: skunk-cabbage and marsh-fern (Thelypteris palustris). The overall misclassification rate from this tree was 13 %. Again, low-quality wetlands were better predicted than high-quality wetlands by the absence of selected species rather than the presence of other species using the classification tree model. Our results suggest that a species’ wetland status classification and coefficient of conservatism are of little use in predicting wetland quality. A simple, statistically derived species checklist such as the one created in this study could be used by field biologists to quickly and efficiently identify wetland sites likely to be regulated as high-quality, and requiring more intensive field assessments. Alternatively, it can be used for advanced determinations of low-quality wetlands. Agencies can save considerable money by screening wetlands for the presence/absence of such “indicator” species before issuing permits.

Ohio

Disturbance metrics predict a wetland Vegetation Index of Biotic Integrity

Indices of biological integrity of wetlands based on vascular plants (VIBIs) have been developed in many areas in the USA. Knowledge of the best predictors of VIBIs would enable management agencies to make better decisions regarding mitigation site selection and performance monitoring criteria. We use a novel statistical technique to develop predictive models for an established index of wetland vegetation integrity (Ohio VIBI), using as independent variables 20 indices and metrics of habitat quality, wetland disturbance, and buffer area land use from 149 wetlands in Ohio, USA. For emergent and forest wetlands, predictive models explained 61% and 54% of the variability, respectively, in Ohio VIBI scores. In both cases the most important predictor of Ohio VIBI score was a metric that assessed habitat alteration and development in the wetland. Of secondary importance as a predictor was a metric that assessed microtopography, interspersion, and quality of vegetation communities in the wetland. Metrics and indices assessing disturbance and land use of the buffer area were generally poor predictors of Ohio VIBI scores. Our results suggest that vegetation integrity of emergent and forest wetlands could be most directly enhanced by minimizing substrate and habitat disturbance within the wetland. Such efforts could include reducing or eliminating any practices that disturb the soil profile, such as nutrient enrichment from adjacent farm land, mowing, grazing, or cutting or removing woody plants.

Ecological Indicators