Marcia S. Meixler

Landscape scale assessment of stream channel and riparian habitat restoration needs

Human modifications of streams and rivers have caused extensive stream channel and riparian degradation. Cost-effective, rapid assessment tools can be used to better manage such areas by identifying the status of habitats for restoration planning and protection. We used a spatially explicit, reach-scale geographic information system modeling strategy to examine stream channel and riparian condition and prioritize restoration actions. The stream channel condition index uses information on land use, road and railroad density, and sinuosity. The riparian condition index uses calculations of percent forest, patch density, and convexity based on land cover in the floodplain. Reaches were classified into restoration categories based on stream channel and riparian condition model results, land ownership, slope, position in the subwatershed, and adjacency to high-quality habitat. We compared modeled restoration priority rankings with those in the management plan for the East Credit subwatershed in Ontario, Canada. Predicted stream channel restoration priority rankings matched field-based classifications for 86% of the reaches in the East Credit subwatershed. Predicted riparian restoration priority rankings matched field-based classifications for 81% of the reaches. Our methods replicate with fairly good accuracy the results obtained using intensive field surveys and stakeholder input. Managers can use these cost-effective strategy development tools to identify candidate reaches for further study and prioritize stream channel and riparian restoration actions over large regions.

A Water Quality Model for Regional Stream Assessment and Conservation Strategy Development

Non-point-source (NPS) pollution remains the primary source of stream impairment in the United States. Many problems such as eutrophication, sedimentation, and hypoxia are linked with NPS pollution which reduces the water quality for aquatic and terrestrial organisms. Increasingly, NPS pollution models have been used for landscape-scale pollution assessment and conservation strategy development. Our modeling approach functions at a scale between simple landscape-level assessments and complex, data-intensive modeling by providing a rapid, landscape-scale geographic information system (GIS) model with minimal data requirements and widespread applicability. Our model relies on curve numbers, literature-derived pollution concentrations, and land status to evaluate total phosphorus (TP), total nitrogen (TN), and suspended solids (SS) at the reach scale. Model testing in the Chesapeake Bay watershed indicated that predicted distributions of water quality classes were realistic at the reach scale, but precise estimates of pollution concentrations at the local scale can have errors. Application of our model in the tributary watersheds along Lake Ontario suggested that it is useful to managers in watershed planning by rapidly providing important information about NPS pollution conditions in areas where large data gaps exist, comparisons among stream reaches across numerous watersheds are required, or regional assessments are sought.

Influences of habitat and land cover on fish distributions along a tributary to Lake Ontario, New York

Influences of habitat and land cover on fish distributions were determined along a lentic–lotic gradient along a tributary to Lake Ontario, New York. Nonmetric multidimensional scaling, cluster analysis, and specific characterization methods were used to classify the fish species into five groups based on their similar patterns of distribution, species-specific habitat relationship, and relative abundance observed along the gradient. A stepwise regression approach was used to select the best habitat and land cover variables to explain variations in the distribution pattern of each fish group. Distribution patterns of the five fish groups were significantly explained by either a set of the selected habitat or land cover predictor variables or a combination of both. Of the 10 habitat variables, water depth, current velocity, aquatic plants, algae, woody debris, sand, and rock-bedrock were selected to explain the variations in distribution patterns of one or more fish groups. Of the 16 land cover types, evergreen wetlands, evergreen plantations, successional shrubs, shrub swamps, roads, and urban areas were selected to explain the variations in distribution patterns of at least one fish group.

Fish Community Support in Wetlands within Protected Embayments of Lake Ontario

Abstract Fish community data were collected to investigate the role of wetlands in supporting fish communities of protected embayments in Lake Ontario. Wetland and deeper, more open, littoral sites were sampled in five protected embayments using gill nets, fyke nets, minnow traps, and electrofishing gear during the summers of 2001 and 2002. Pooled gear data were used to analyze community composition, size frequency, and species richness. We found that even within protected embayments where community composition of both habitats is similar, wetlands support a community of fish different in species dominance and size structure than littoral embayment habitats. The abundance of young-of-year fish suggests that wetlands support fish populations by providing important nursery habitat. The similarity in fish community composition between wetland and littoral habitats indicates that wetlands remain important in supporting a subset of the embayment fish community. These results demonstrate that both wetlands and littoral areas in embayments are valuable and intensively utilized fish habitats that should receive special consideration in ecosystem management plans for the Great Lakes.

Application of the target fish community model to an urban river system.

Several models have been developed to assess the biological integrity of aquatic systems using fish community data. One of these, the target fish community (TFC) model, has been used primarily to assess the biological integrity of larger, mainstem rivers in southern New England with basins characterized by dispersed human activities. We tested the efficacy of the TFC approach to specify the fish community in the highly urbanized Charles River watershed in eastern Massachusetts. To create a TFC for the Charles River we assembled a list of fish species that historically inhabited the Charles River watershed, identified geomorphically and zoogeographically similar reference rivers regarded as being in high quality condition, amassed fish survey data for the reference rivers, and extracted from the collections the information needed to define a TFC. We used a similarity measurement method to assess the extent to which the study river community complies with the TFC and an inference approach to summarize the manner in which the existing fish community differed from target conditions. The five most abundant species in the TFC were common shiners (34%), fallfish (17%) redbreast sunfish (11%), white suckers (8%), and American eel (7%). Three of the five species predicted to be most abundant in the TFC were scarce or absent in the existing river community. Further, the river was dominated by macrohabitat generalists (99%) while the TFC was predicted to contain 19% fluvial specialist species, 43% fluvial dependent species, and 38% macrohabitat generalist species. In addition, while the target community was dominated by fish intolerant (37%) and moderately tolerant (39%) of water quality degradation, the existing community was dominated by tolerant individuals (59%) and lacked intolerant species expected in the TFC. Similarity scores for species, habitat use specialization, and water quality degradation tolerance categories were 28%, 35% and 66%, respectively. The clear pattern of deviations from target conditions when observing fish habitat requirements strongly suggests that physical habitat change should be a priority for river enhancement in the Charles River. Comparison of our target and existing fish communities to those from a comprehensive study of Northeastern fish assemblage responses to urban intensity gradients revealed very similar results. Likewise, comparison of our TFC community and affinity scores to those of other TFCs from similar regions also yielded similar results and encouraging findings. Based on the positive results of these comparisons, the utility of the findings from the inference approach, and the widespread adoption of the TFC in the Northeast US, it appears that the TFC approach can be used effectively to identify the composition of a healthy fish community and guide river enhancements in both highly urbanized and non-urbanized streams and rivers in the Northeast US.

Modeling Coastal Vulnerability through Space and Time

Coastal ecosystems experience a wide range of stressors including wave forces, storm surge, sea-level rise, and anthropogenic modification and are thus vulnerable to erosion. Urban coastal ecosystems are especially important due to the large populations these limited ecosystems serve. However, few studies have addressed the issue of urban coastal vulnerability at the landscape scale with spatial data that are finely resolved. The purpose of this study was to model and map coastal vulnerability and the role of natural habitats in reducing vulnerability in Jamaica Bay, New York, in terms of nine coastal vulnerability metrics (relief, wave exposure, geomorphology, natural habitats, exposure, exposure with no habitat, habitat role, erodible shoreline, and surge) under past (1609), current (2015), and future (2080) scenarios using InVEST 3.2.0. We analyzed vulnerability results both spatially and across all time periods, by stakeholder (ownership) and by distance to damage from Hurricane Sandy. We found significant differences in vulnerability metrics between past, current and future scenarios for all nine metrics except relief and wave exposure. The marsh islands in the center of the bay are currently vulnerable. In the future, these islands will likely be inundated, placing additional areas of the shoreline increasingly at risk. Significant differences in vulnerability exist between stakeholders; the Breezy Point Cooperative and Gateway National Recreation Area had the largest erodible shoreline segments. Significant correlations exist for all vulnerability (exposure/surge) and storm damage combinations except for exposure and distance to artificial debris. Coastal protective features, ranging from storm surge barriers and levees to natural features (e.g. wetlands), have been promoted to decrease future flood risk to communities in coastal areas around the world. Our methods of combining coastal vulnerability results with additional data and across multiple time periods have considerable potential to provide valuable predictions that resource managers can effectively use to identify areas for restoration and protection.

A GIS Framework for Fish Habitat Prediction at the River Basin Scale

We present a geographic information system (GIS) framework to classify stream habitats and provide fish distribution predictions comprehensively at the landscape scale. Stream segments were classified into one of eighteen habitat types using three landscape attributes: stream size (three categories), stream quality (three categories), and water quality (two categories). An extensive literature search was undertaken to classify fish species into the same eighteen habitat types based on preferences for the three landscape attributes. We tested our framework in 39 sites throughout the upper Allegheny River basin in western New York. No difference was detected between observed and predicted numbers of fish species among stream habitats. Further, field collected bankfull width measurements, stream quality ratings, and water quality sampling results were largely consistent with predicted values. The habitat type expected to have the greatest fish species richness was large streams or small rivers with intact stream quality and suitable water quality. Our framework is rapidly applied, comprehensive, inexpensive, and built on widely available data thereby offering an efficient alternative to traditional field-based efforts for regional habitat classification and fish distribution prediction.

Modeling Aquatic Macroinvertebrate Richness Using Landscape Attributes

We used a rapid, repeatable, and inexpensive geographic information system (GIS) approach to predict aquatic macroinvertebrate family richness using the landscape attributes stream gradient, riparian forest cover, and water quality. Stream segments in the Allegheny River basin were classified into eight habitat classes using these three landscape attributes. Biological databases linking macroinvertebrate families with habitat classes were developed using life habits, feeding guilds, and water quality preferences and tolerances for each family. The biological databases provided a link between fauna and habitat enabling estimation of family composition in each habitat class and hence richness predictions for each stream segment. No difference was detected between field collected and modeled predictions of macroinvertebrate families in a paired t-test. Further, predicted stream gradient, riparian forest cover, and total phosphorus, total nitrogen, and suspended sediment classifications matched observed classifications much more often than by chance alone. High gradient streams with forested riparian zones and good water quality were predicted to have the greatest macroinvertebrate family richness and changes in water quality were predicted to have the greatest impact on richness. Our findings indicate that our model can provide meaningful landscape scale macroinvertebrate family richness predictions from widely available data for use in focusing conservation planning efforts.