Toads, Roads, and Nodes: Collaborative assessment of amphibian diversity in the Eastern and Central U.S.A. reveals pervasive effects of roads and traffic.

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Toads, Roads, and Nodes: Collaborative assessment of amphibian diversity in the Eastern and Central U.S.A. reveals pervasive effects of roads and traffic Questions Kristen S. Genet 1, J.J. Apodaca 2, Christopher Bates 3, Jessica Beach 4, Karen H. Beard 5, Kelsie Becklin 1, Jane Margaret Bell 2, Bradley J. Cosentino 6, Christopher Crockett 7, Kara Curtain 8, George Fawson 5, Jennifer Fjelsted 7, Elizabeth A. Forys 9, Melanie Grover 2, Jaimie Holmes 10, Katherine Indeck 9, Nancy E. Karraker 10, Eran Kilpatrick 3, Tom A. Langen 4, David Marsh 11, Stephen Mugel 6, Alessandro Molina 7, James R. Vonesh 7, Ryan Weaver 7 and Anisha Willey 5 (1)Biology, Anoka Ramsey Community College, Coon Rapids, MN, (2)Biology, Warren Wilson College, Swannanoa, NC, (3)Biology, University of South Carolina, Salkehatchie, Allendale, SC, (4)Biology, Clarkson University, Potsdam, NY, (5)Department of Wildland Resources and the Ecology Center, Utah State University, Logan, UT, (6)Biology, Hobart and William Smith Colleges, Geneva, NY, (7)Department of Biology, Virginia Commonwealth University, Richmond, VA, (8)Biology, George Mason University, Fairfax, VA, (9)Environmental Science and Biology, Eckerd College, St, Petersburg, FL, (10)Department of Natural Resources Science, University of Rhode Island, Kingston, RI, (11)Environmental Studies, Washington and Lee University, Lexington, VA 1.What landscape factors best explain amphibian species richness and presence/absence of individual species? 2.Are the negative effects of roads more associated with the number of roads or with the local volume of traffic? 3.Are roads or other land uses particularly bad for amphibian populations when they separate wetlands from uplands? 4.Are amphibians more sensitive to landscape composition or configuration? Results Conclusions Our results suggest that roads, and particularly traffic, exert strong negative effects on calling amphibians across the Eastern and Central U.S., affecting even species that are considered disturbance-tolerant. Our project demonstrates that networks of undergraduate students can be enlisted to analyze large data sets and provide students with a meaningful research experience in large-scale ecology. We plan to continue our investigation by examining landscape connectivity and the scales over which roads and development affect amphibian populations using this collaborative course-based research model. Background Habitat loss and fragmentation represent significant threats to amphibians. Fragmentation is particularly harmful because many amphibians migrate between aquatic and terrestrial habitats, and even narrow bands of unsuitable habitat can act as barriers to movement. Most previous studies of fragmentation and amphibians have been conducted in single landscapes. We created a network of undergraduate courses to study the relationship between roads, habitat fragmentation, and amphibian distributions across most of the Eastern and Central United States. Methods 1.Students from nine U.S. colleges summarized North American Amphibian Monitoring Program (NAAMP) data in the Eastern and Central U.S. from GIS used to extract and compile landscape data for 1620 sites across 14 states. 3. Landscape variables: car mean; road length; proportion developed, agriculture, or forest; number of wetlands and wetland area; habitat richness, adjacent forest, isolated wetland, habitat split and configuration. 4.Amphibian variables: individual species presence, species richness, total number of surveys, number of surveys with noise, and presence/richness variables for surveys without noise. Analyses  Generalized linear models to test hypotheses concerning the influence of landscape variables on amphibian species richness and site occupancy by individual species within 1000m of NAAMP survey locations.  PRESENCE to determine site occupancy in order to build cumulative detection probability curves.  Structural equation modeling to determine correlations between variables affecting species richness. ModelVariables FULL % forest + % developed + wetland area + road length + traffic ROADSroad length + traffic DETECTtotal surveys + noise level LANDCOVFULL w/o traffic LANDNAT% forest + wetland area TOTDEV% developed + road length + traffic + noise level Model Set Cars cause noise and noise reduces detection, making it difficult to isolate the influence of these factors. High coefficient between noise level and car mean creates difficulties in differentiating them in analyses, Species Richness Best Model Best Single Variable All speciesFULLTRAFFIC All species for surveys without noise FULLTRAFFIC Only species with >90% detection probability FULLTRAFFIC Sites with at least one rare species detected FULLTRAFFIC Models incorporating local traffic volume and development were the best predictors of amphibian species richness and occupancy by individual species. In 10 of 11 species examined, traffic volume was more closely associated with site occupancy than road length, though structural equation models suggested the two factors had effects of similar magnitude. SpeciesHabitat Split Type Hyla cinereaDEV Hyla chrysoscelis/versicolorDEV Lithobates sylvaticaDEV, ROADS We found little evidence for significant effects of habitat split by roads, agriculture, or development; with Bonferroni correction, none were significant. In general, landscape composition variables were more useful than configuration variables for predicting amphibian occupancy. Noise level has no direct effect on species richness. Car mean and road length appear to have independent, negative effects on richness. For more information: Please visit the project website ( or contact David Marsh or Kristen Genet