Identification and Prediction of Fish Assemblages in Streams of the Mid‐Atlantic Highlands, USA

Cyterski, Mike; Barber, Craig

doi:10.1577/t05-011.1

Cited by 8 publications

(5 citation statements)

References 17 publications

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“…For example variables describing catchment-scale land use or human disturbance can be useful predictors of freshwater fish distributions (e.g. Argent et al, 2003;Cyterski and Barber, 2006). However, it is important that the selected reference sites are not matched to exposure sites on environmental variables that can be causally affected by water abstraction.…”

Section: Discussionmentioning

confidence: 99%

Comparing apples with apples: use of limiting environmental differences to match reference and stressor‐exposure sites for bioassessment of streams

Chessman¹,

Muschal²,

Royal³

2007

River Research & Apps

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Human impacts on freshwater biota are often assessed by comparisons with regional reference sites judged to be free or nearly free from the influence of stressors of concern. These comparisons may involve predictive models that extrapolate from reference-site data to estimate the biota that would occur at each assessment site in the absence of the stressors. This extrapolation often involves selection or weighting of data from particular reference sites, but it is seldom demonstrated whether this process results in a more accurate, precise and sensitive assessment than would be achieved from comparison with a simple unweighted combination of data from all reference sites, that is a null model. In addition, predictive models often rely on additive combinations of environmental predictor variables, but such combinations may poorly represent the natural control of spatial variation in biological communities by multiple limiting factors. In this paper, we describe a different type of reference-site approach, based on the concept of limiting environmental differences (LEDs) as natural constraints on biological similarity among sites. In this method, an assessment site is compared with a sub-set of environmentally matched reference sites selected by application of LED criteria to individual environmental variables. We illustrate this approach by its application to a potentially subtle impact: the effect of water abstraction on fish assemblages in unregulated streams in northeastern New South Wales, Australia. We compared (1) a LED-based predictive model, (2) a null model and (3) a model based on cluster analysis and multiple discriminant analysis in the style of the widely followed River Invertebrate Prediction and Classification System (RIVPACS). The LED-based model was about as accurate as the RIVPACS-type model and the most precise and sensitive of the three, being best able to distinguish sites where fish assemblages departed from reference status.

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Section: Discussionmentioning

confidence: 99%

Comparing apples with apples: use of limiting environmental differences to match reference and stressor‐exposure sites for bioassessment of streams

Chessman¹,

Muschal²,

Royal³

2007

River Research & Apps

View full text Add to dashboard Cite

show abstract

“…1 is not guaranteed. We expected clustering to produce less well-defined assemblages than the analysis of MidAtlantic Highlands streams detailed in Cyterski and Barber (2006), because a stream reach is a more confined, self-enclosed unit than these sampling cells with no movement barriers between them. In addition, the size of the cells (55 km 2 ) makes it difficult to capture a truly representative biotic sample or to accurately depict environmental characteristics of such a large, heterogeneous area.…”

Section: Discussionmentioning

confidence: 97%

Relation of fish and shellfish distributions to habitat and water quality in the Mobile Bay estuary, USA

Rashleigh

Cyterski

Smith

et al. 2008

Environ Monit Assess

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The Mobile Bay estuary in the northern Gulf of Mexico provides a rich habitat for many fish and shellfish, including those identified as economically and ecologically important. The National Estuary Program in Mobile Bay has focused on restoration of degraded estuarine habitat on which these species depend. To support this effort, we used statistical techniques of ordination, cluster analysis, and discriminant analysis to relate distributions of individual fish and shellfish species and species assemblages to two dozen water quality and habitat variables in a geo-referenced database. Species appeared to respond to dominant gradients of low to high salinity and upland to offshore habitat area; many of the 15 communities identified via cluster analysis showed aggregated spatial distributions that could be related to habitat characteristics. Species in the Mobile River Delta were distinct from those in other areas of the estuary. This analysis supports habitat management in the Mobile Bay estuary; however, due to mobility of organisms among sampling locations and the dynamic environmental conditions in estuaries, we conclude that the analyses presented here are most appropriate for an evaluation of the estuary as a whole.

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“…The importance of watershed size for many species may be due to species-specific preference for smaller systems (i.e., headwater species). For example, creek chub and central stoneroller prefer smaller systems [67,68], which may explain the reduction in probability of presence for these two species at an area of ∼60 km 2 . The lack of a reduction in probability of presence for the other two species may be due to omission of streams larger than fourth order from the stream survey-extending the data set to include larger systems (up to rivers) may reveal similar patterns in the other fishes.…”

Section: Importance Of Watershed Attributesmentioning

confidence: 99%

Species Distribution Models of Freshwater Stream Fishes in Maryland and Their Implications for Management

Maloney

Weller

Michaelson

et al. 2012

Environ Model Assess

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Species distribution models (SDMs) are often used in conservation planning, but their utility can be improved by assessing the relationships between environmental and species response variables. We constructed SDMs for 30 stream fishes of Maryland, USA, using watershed attributes as environmental variables and presence/absence as species responses. SDMs showed substantial agreement between observed and predicted values for 17 species. Most important variables were natural attributes (e.g., ecoregion, watershed area, latitude/ longitude); land cover (e.g., %impervious, %row crop) was important for three species. Focused analyses on four representative species (central stoneroller, creek chub, largemouth bass, and white sucker) showed the probability of presence of each species increased non-linearly with watershed area. For these species, SDMs built to predict absent, low, and high densities were similar to presence/absence predictions but provided probable locations of high densities (e.g., probability of high-density creek chub decreased rapidly with watershed area). We applied SDMs to predict suitability of watersheds within the study area for each species. Maps of suitability and the environmental and species response relationships can help develop better management plans.

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Identification and Prediction of Fish Assemblages in Streams of the Mid‐Atlantic Highlands, USA

Cited by 8 publications

References 17 publications

Comparing apples with apples: use of limiting environmental differences to match reference and stressor‐exposure sites for bioassessment of streams

Comparing apples with apples: use of limiting environmental differences to match reference and stressor‐exposure sites for bioassessment of streams

Relation of fish and shellfish distributions to habitat and water quality in the Mobile Bay estuary, USA

Species Distribution Models of Freshwater Stream Fishes in Maryland and Their Implications for Management

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