Ecosystems Research Division

Biographical Information

Name: John Johnston
Title: Supervisory Ecologist
Email: johnston.johnm@epa.gov

Education:
B.S. Xavier University (Chemistry)
Ph.D. Institute of Ecology, University of Georgia (Ecology)

Expertise/Research Interests:
Research Ecologist, USEPA, Spatial modeling, community ecology, GIS integration with simulation models
ORISE Postdoctoral Fellow, USEPA, Watershed hydrologic model comparisons, land use change
Guest Lecturer, School of Ecology, University of Georgia, Community ecology
Graduate Research Assistant, University of Georgia, Soil biological and chemical analysis
GC/MS Chemist, International Technologies, Air toxics (volatile organics)
Organic Extraction Chemist, Pearson Environmental, Inc, Extraction of environmental contaminants

Professional Activities:
Ecological Society of America

Sigma Xi

Publications:

Babendreier, L.S. Matott, J. Hameedi, R. Dennis, C. Knightes, R. Mathur, Y. Mohamoud, J.M. Johnston, C. West, G. Laniak, N. Gaber, P. Pascual, and R. Araujo. 2007. Managing Multimedia Pollution for a Multimedia World. Environmental Management 12:6-11.

Johnston, J.M. 2007. Diversity Surfaces and Species Wavefronts: Adding the Dimension of Time. Pedobiologia 50(6):527-533.

R. Dennis, R. Haeuber, T. Blett, J. Cosby, C. Driscoll, J. Sickles and J.M. Johnston. 2007. Sulfur and Nitrogen Deposition on Ecosystems in the United States. Environmental Management 12:12-17. J.

Johnston, J.M. et al. 2006. Watershed Health Assessment Tools Investigating Fisheries WHAT IF version 2.0: A Manager's Guide to New Features. EPA/600/R-06/109. http://www.epa.gov/athens/publications/reports/Johnston600R06109WatershedHealthAssessment.pdf (PDF) (94pp, 3M)

B. Rashleigh, C. Barber, M. Cyterski, J. Johnston, Y. Mohamoud and R. Parmar. 2006. Watershed Health Assessment Tools-Investigating Fisheries (WHAT-IF): A modeling toolkit for watershed and fisheries management. In: Voinov, A., Jakeman, A.J., Rizzoli, A.E. (eds). Proceedings of the iEMSs Third Biennial Meeting: " Summit on Environmental Modelling and Software". International Environmental Modelling and Software Society, Burlington, USA.

Ambrose, R.B., Johnston, J.M., Knightes, C.D. and Sunderland, E. 2005. Ecosystem Scale Modeling for Mercury Benefits Analysis. In: Regulatory Impact Analysis for the Clean Air Mercury Rule. Office of Air Quality Planning and Standards. EPA-452/R-05-003. http://www.epa.gov/ttn/atw/utility/ria_final.pdf (PDF) (566pp, 13M)

Rashleigh, B., R. Parmar, J. M. Johnston, and M.C. Barber. 2005. Predictive habitat models for the occurrence of stream fishes in the Mid-Atlantic Highlands. North American Journal of Fisheries Management 25:1353-1366.

Rashleigh, B., M.C. Barber, M.J. Cyterski, J.M. Johnston, R. Parmar, and Y. Mohamoud. 2004. Population models for stream fish response to habitat and hydrologic alteration: the CVI Watershed Tool. EPA/600/R-04/190, U.S. Environmental Protection Agency, Athens, Georgia. http://www.epa.gov/athens/publications/reports/Rashleigh_600_R04_190_Population_Models.pdf (PDF) (102pp, 7M)

Doherty, J. and J.M. Johnston. 2003. Methodologies for Calibration and Predictive Analysis of a Watershed Model. Journal of the American Water Resources Association, 39(2):251-265.

Johnston, J. M., Crossley, Jr. D. A. 2002. Ecosystem Recovery in the Southeastern U. S.: Soil Ecology as Essential Component of Ecosystem Management. Forest Ecology and Management, 155(1-3): 189-205.

Johnston . J. M. 2001. A scientific and theoretical framework for ecological risk assessment: an overview of the BASE program. In J. B. H. J. Linders (Editor), Modelling of Environmental Chemical Exposure and Risk. NATO Science Series. IV. Earth and Environmental Sciences - Vol. 2. Kluwer Academic Publishers, Dordrecht, Netherlands , 275 pp.

Johnston, J. M., Novak, J., Kraemer, S. R. 2000. Multimedia Modeling for Environmental Protection: Introduction to a Collaborative Framework. Environmental Monitoring and Assessment, 63(1): 253-263.

Johnston, J. M. 2000. The Contribution of Microarthropods to Aboveground Food Webs: A Review and Model of Belowground Transfer in a Coniferous Forest. American Midland Naturalist, 143: 226-238.

Lassiter, R., Box, E. O., Wiegert, R., Johnston , J. M., Suarez, L., Bergengren, J. 2000. Vulnerability of Ecosystems of the Mid-Atlantic Region, USA , to Global Climate Change. Environmental Toxicology and Chemistry, 19:4(2) 1153-1160.

Johnston, J. M. (Editor). 2000. Ecological Research Integration in ORD: Report of a Workshop. EPA/600/X-00/003.

Current Projects:

Watershed Management and Decision Support: Collaborative Software Development and Model Application in the Canaan Valley Highlands

The USEPA Mid-Atlantic Highlands Streams Assessment report concluded that over 31% of stream miles in the Mid-Atlantic Highlands were in poor condition, and only 17% stream miles could be considered to be in good condition, based on their fish populations. Insect populations gave a slightly better reading, with 27% of stream miles in poor condition and 25% stream miles in good condition, as judged by the aquatic insects present. Within the Allegheny Monongahela watershed that encompasses a majority of the Highlands region, riparian habitat alteration (28%), acidic deposition (26%), mine drainage (20%), and fish tissue contamination (19%) were the major stressors associated with stream miles. All of these stressors were associated with at least 20% of the stream miles in this watershed. Non-native fish species were found in 46% of the stream miles in this watershed.

Watershed and surface water management decisions (including TMDLs) are often based on water quality criteria that are used as measurement endpoints for ecological or human health endpoints too difficult, costly, or time consuming to measure directly. Although nothing is intrinsically wrong with such an approach, these methods introduce an unknown or unquantified degree of scientific uncertainty into ecological risk assessments since linkages between environmental exposures and resulting ecological effects are not explicitly addressed. Often the cause and effect relationships in these systems are implied, assumed or simplified to statistical relationships.

Although there are many ecological endpoints that are important indicators of the condition of aquatic communities and their associated watersheds, fish health is arguably one of the most important. For example, fishability is a principal designated use for surface waters under the Clean Water Act. Chemical bioaccumulation in fish is a major assessment endpoint used by the Office of Pesticide Programs and the Office of Toxic Substances to evaluate the proposed registration and use of chemicals regulated under the Federal Insecticide, Fungicide, and Rodenticide Act (FIFRA) and the Toxic Substance Control Act (TSCA). Chemical bioaccumulation in fish is also an important assessment endpoint for EPA Regional Offices charged with establishing total maximum daily loads (TMDLs) for mercury and other toxics.

An outcome of this research will be the identification of data and methodological gaps in the desired unification of spatial modeling (GIS, landscape ecology and spatial analysis) and process modeling (mathematical descriptions of causal relationships in complex systems). Although a longer term research goal, this does not preclude the development of software tools using best available data and knowledge bases to meet short term client needs.

Objective:
The overall objective is to develop watershed modeling tools for the immediate client (CVI) and their stakeholders in the Mid-Atlantic Highlands. This research continues the contributions that ReVA has made to the CVI toolset and adds modeling and decision support capabilities for more general use by managers. To facilitate the prediction and analysis of fish health issues by EPA Program and Regional Offices and other environmental agencies, process-based models that describe

• the expected trophic dynamics of the dominant fish species,
• the spawning and recruitment dynamics of the dominant fish species,
• the bioaccumulation of organic chemicals and metals in aquatic biota, and
• how physical habitat and chemical water quality impact fish feeding, reproduction, survival, and migration.

To facilitate the use and application of these models, graphical user interfaces (GUI), supporting databases, and libraries of canonical scenarios will also be developed. Models will be linkable to integrated water quality and hydrologic models that simulate habitat characteristics (e.g., water depth, current velocity, water temperature, sediment loadings, etc.) that determine the survival, reproduction, and recruitment of fish and aquatic invertebrates. Similar to what has been achieved in ReVA, frameworks based on the biogeography of fish will be developed to apply these models spatially for regional assessments of important fish health issues.

Mercury Source Identification and Risk Management Recommendations for Fish Tissue Consumption from Livestock Ponds on the Cheyenne River Sioux Tribal Lands: RARE Project with Region 8

Methyl mercury contamination found in preliminary data collections of fish inhabiting livestock ponds is a potential human health concern to the Tribe. However, not all fishes and all ponds demonstrate similar patterns of contamination and biomagnification, so there are significant scientific uncertainties in evaluating the human and ecological risks due to methyl mercury biomagnification. Presumably, atmospheric mercury deposition inputs are similar among the ponds, and soils and landforms are known to be fairly homogeneous between pond systems. Thus, additional environmental sampling is required to fully characterize total and methyl mercury dynamics in each environmental media in ponds and riparian areas, including the biotic compartments of fishes, plankton and algae. A watershed approach is to be taken, whereby soils, shallow groundwater and surface waters are sampled and the data used to parameterize a model of mercury loading. Provided that source characterizations reveal loading between watersheds to be uniform, additional modeling and analyses will be performed to evaluate ecological parameters influencing variable methyl mercury body burden in predatory fishes (bass and catfish) among ponds: size of pond and differing primary and/or secondary productivities; fraction riparian habitat responsible for increased methylation rates, or differences in food webs between ponds.

Soil Community Ecology: Spatial Modeling

Investigations of soil microarthropod communities in Old Growth longleaf pine/wiregrass have resulted in the discovery of new species and provided baseline information for soil characteristics in the Southeast U.S. to contrast with regional land use changes and the effects on our soil resource. Field studies at the Tall Timbers Research Station are ongoing that test the effects of soil tillage and seasonal controlled burning.