Environmental Modeling & Assessment

, Volume 18, Issue 1, pp 1–12 | Cite as

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

  • Kelly O. MaloneyEmail author
  • Donald E. Weller
  • Daniel E. Michaelson
  • Patrick J. Ciccotto


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.


Conditional random forests Landscape Prediction Classification Habitat suitability 



We thank the Maryland Department of Natural Resources and the MBSS field crew members for providing the MBSS data and Matt Baker for watershed boundaries. We thank Lori Davias and an anonymous reviewer for constructive feedback on an earlier version of this manuscript. This research was partly funded by an REU fellowship to DEM. Additional support was provided by a Smithsonian Post-Doctoral Research Fellowship awarded to KOM.

Supplementary material

10666_2012_9325_MOESM1_ESM.jpg (1.3 mb)
Online resource 1 Level III ecoregions and Maryland Biological Stream Survey (MBSS) sampling locations within the Chesapeake Bay watershed. The inset shows the study area (dark gray) within the Chesapeake Bay watershed (light gray) and the states of the mid-Atlantic region of the US. The state abbreviations are DE = Delaware, MD = Maryland, NJ = New Jersey, NY = New York, PA = Pennsylvania, VA = Virginia, and WV = West Virginia (JPEG 1294 kb)
10666_2012_9325_MOESM2_ESM.pdf (33 kb)
Online resource 2 (PDF 33 kb)
10666_2012_9325_MOESM3_ESM.pdf (70 kb)
Online resource 3 Histograms and summary statistics for the land cover change in study watersheds between 1992 and 2001. Land use data were from the USGS Chesapeake Bay Watershed Land Cover Data Series (CBLCD) available at (PDF 69.7 kb)
10666_2012_9325_MOESM4_ESM.pdf (13 kb)
Online resource 4 Confusion matrices from presence/absence models for four example species (PDF 12.9 kb)
10666_2012_9325_MOESM5_ESM.pdf (78 kb)
Online resource 5 (PDF 78 kb)
10666_2012_9325_MOESM6_ESM.pdf (1.5 mb)
Online resource 6 Habitat suitability based on presence/absence predictions for all 30 species in all small, nontidal reaches in the study area (Online resource 1). The insets show enlarged views of the results near Baltimore, Maryland (PDF 1576 kb)


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Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  • Kelly O. Maloney
    • 1
    • 4
    Email author
  • Donald E. Weller
    • 1
  • Daniel E. Michaelson
    • 1
    • 2
  • Patrick J. Ciccotto
    • 3
  1. 1.Smithsonian Environmental Research CenterEdgewaterUSA
  2. 2.Departments of Environmental Science and Engineering ScienceUniversity of VirginiaCharlottesvilleUSA
  3. 3.Monitoring and Non-tidal AssessmentMaryland Department of Natural ResourcesAnnapolisUSA
  4. 4.Northern Appalachian Research LaboratoryU.S. Geological Survey-Leetown Science CenterWellsboroUSA

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