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Tyler Wagner, Ph.D.

  • Adjunct Professor of Fisheries Ecology
  • Assistant Unit Leader, PA Cooperative Fish and Wildlife Research Unit
Tyler Wagner, Ph.D.
402 Forest Resources Building
University Park, PA 16802
Email:
Work Phone: 814-865-6592

Areas of Expertise

  • Fisheries ecology
  • Hierarchical modeling
  • Macrosystems ecology
  • Ecological stressors
  • Species of management concern
  • Monitoring and assessment

Education

  1. Ph.D., Michigan State University (2006)
  2. M.S., University of Idaho (2000)
  3. B.S., University of Idaho (1999)

Academic Interests:

  • Fisheries ecology
  • Hierarchical modeling
  • Macrosystems ecology
  • Ecological stressors
  • Species of management concern
  • Monitoring and assessment

Courses taught:

Quantitative Methods in Ecology

Professional Affiliations:

The Ecological Society of America
American Fisheries Society
North American Lake Management Society

Current and Past Research Projects:

A macrosystems ecology framework for continental-scale prediction and understanding of lakes

In the past decade, our understanding of how inland waters influence regional, continental, and global biogeochemical cycles has fundamentally changed. We have moved from discounting their contributions, to now recognizing these ecosystems as significant hotspots for the storage and transformation of nitrogen, phosphorus, and carbon. This realization has come about through careful and labor-intensive collection, integration, and synthesis of often-scattered data sources, combined with a variety of different approaches to extrapolate site-level measures to unsampled sites across regions and continents. Today, although this view of the role of inland waters in large-scale cycling is supported by numerous studies, substantial gaps in our understanding remain. Estimates for the same flux (e.g., organic carbon burial in lakes) often differ substantially among studies. Further, most attempts to quantify continental or global fluxes or pools come with caveats regarding the often high– and often unknown– uncertainty associated with these estimates. To better understand the role of inland waters in macroscale nutrient cycling, new approaches are needed to reduce uncertainty in extrapolating site-level estimates to larger geographical scales. The overarching goal of this NSF-funded research is to understand and predict nutrient patterns for ALL continental US lakes to inform estimates of lake contributions to continental and global cycles of nitrogen (N), phosphorus (P), and carbon (C), while also providing locally valuable information about conditions in unsampled lakes.

Establishing a strategy for assessing the risk of endocrine-disrupting compounds to aquatic and terrestrial organisms

Endocrine disruption is a national and global concern that affects fish, wildlife and human populations. Through interactions with neural, endocrine, and immune systems, endocrine disrupting compounds (EDCs) can influence growth, development, reproduction, disease, and mortality, with adverse outcomes for populations, communities, and ecosystems. Within the Chesapeake Bay, understanding the effects of EDCs on fish and wildlife populations has been identified as a priority to help inform natural resource management. Specifically, there is a need for assessing the risk of EDCs to fish and wildlife populations and their health. The risk assessment will integrate our understanding of the (1) population dynamics of the fish or wildlife species of interest, (2) mechanisms through which EDCs interact with individuals, and (3) exposure pathways between sources of EDCs, including hydrological conditions and land use practices, and fish and wildlife populations. This will help identify short and long-term impacts of compounds or classes of chemicals of concern, potential environmental conditions and stressors that may mediate the effects of EDCs, and how land use management practices may reduce exposure to EDCs.

Linking fish health, contaminants, and population dynamics of smallmouth bass populations in the Susquehanna River, Pennsylvania

Since 2005, diseased smallmouth bass have been detected throughout the Susquehanna River and its tributaries raising concern regarding the overall health of smallmouth bass and the Susquehanna River basin. In a collaborative effort with Pennsylvania Fish and Boat Commission, PA Department of Environmental Protection, U.S. Geological Survey, and Penn State University, this project aims to investigate a wide-range of variables (i.e., fish health analysis, contaminants, population modeling, radio telemetry, etc.) to gain a better understanding of factors that could relate to disease in smallmouth bass.  

An investigation into the role of groundwater as a point source of emerging contaminants to smallmouth bass in the Susquehanna River basin

There is currently a paucity of information on the role of groundwater discharge into surface waters as point sources of contaminants from polluted aquifers. This is critical to understand because the use of groundwater seeps are important for smallmouth bass, particularly during spawning season, and there use is related to increased hatch success and survival of age 0 fish. In addition, previous work has shown smallmouth bass utilizing areas of groundwater upwelling for spawning in the Susquehanna River basin. Exposure to EDCs during this critical life-stage of egg development could have detrimental short- and long-term consequences on immune function and fish health. Therefore, the objective of this research is to investigate the role of groundwater as a point source of emerging contaminants to smallmouth bass in the Susquehanna River basin.

Can plasticity protect populations from rapid environmental fluctuation?

Rates of population extirpation from habitat loss have reached unprecedented levels and climate change is predicted to be a leading cause of future species extinctions. Accordingly, conservation of emergent properties that promote resistance and resilience to environmental perturbation will be vital to future population persistence. Though it has been demonstrated that phenotypic plasticity increases resilience to habitat loss, the ability for plasticity to promote population persistence under climate change and habitat degradation has not been explored. If plasticity does increase survival, failure to conserve highly plastic genotypes could accelerate species extinction. This research focuses on an economically and socially important species, brook trout (Salvelinus fontinalis), to determine how the interactive effects of genetics and behavior influence differential survival of fish populations under a changing climate.

Preliminary determination of density and distribution of Flathead Catfish Pylodictis olivaris in the Susquehanna River and select tributaries

The goal of this project is to estimate the relative abundance and age and growth characteristics of invasive Flathead Catfish in three reaches of the mainstem Susquehanna River with different degrees of population establishment. By examining river reaches with different degrees of population establishment, data collected during this study will serve to help understand current distribution and population characteristics (e.g., size distribution, growth rates). In addition, we will develop models (based on population vital rates and habitat use) to predict future changes in establishing populations as well as to evaluate potential impacts to areas where Flathead Catfish have not yet invaded. These models can be used to help inform management of Flathead Catfish and native species throughout the Susquehanna River Basin.

 

Macrosystems biology research in US lakes across space and time

As part of a dynamic multidisciplinary research team (http://csi-limnology.org/), we seek to identify and study cross-scale interactions (CSIs) at sub-regional to continental scales. A CSI exists where a driver at one scale, such as local land use, interacts with a driver at another scale, such as regional climate. These CSIs can lead to nonlinear and often unexpected relationships between drivers and responses.

Transboundary management and conservation: linking large-scale dynamics to ecological monitoring and management
 
A central challenge to natural resource management is to understand and predict ecological responses to management and environmental change over large spatial scales. It is recognized, however, that the management and conservation of many important ecological systems and the services they provide must be addressed at spatial scales that transcend jurisdictional and political boundaries. For example Landscape Conservation Cooperatives (LCCs) recognize that managing natural resources is complex and requires landscape-scale (i.e., trans-boundary) approaches. Although trans-boundary approaches are necessary to understand large-scale phenomenon (e.g., species range), it remains unclear in many cases how best to address the inherent complexities in managing ecosystems at large (e.g., regional) spatial scales. In addition to challenges associated with performing trans-boundary research, it is often unclear how to link large-scale system dynamics with on-the-ground decision-making processes, which are often done using adaptive management principles. For example, a critical component for successfully implementing adaptive management is the development of a rigorous monitoring program, which provides a critical feedback loop for learning about system dynamics. It is unclear, however, how the interplay between components acting at different, hierarchical scales will affect the ability of natural resource managers to detect changes in important state variables (e.g., animal abundance, occupancy, etc.) at trans-boundary spatial scales. Thus, our overarching objective is to use freshwater stream fish populations as model systems to develop a framework and tools for addressing the inherent challenges in performing trans-boundary research and for linking large-scale dynamics to ecological monitoring and management.
 
Great Lakes Fisheries Trophic Structure Response to Climate Change
 

Predicting population responses to climate change requires an understanding of how population dynamics vary over space and time.  Although variability has historically been viewed as an impediment to understanding population responses to ecological changes, it can provide an important signal, rather than just being viewed as noise.  In this project, we will build upon recently completed analyses of fish population data in the Great Lakes basin to help predict how spatial and temporal variation in fish populations may respond to climate change and other important drivers.  We suggest that shifting variance structure can be indicative of population-level responses to climate change.  Our proposed research will help elucidate the extent to which quantifiable responses in spatial and temporal variability occur in different forms of fish population data.

Fish Community Assessment in the Eastern Rivers and Mountains Network and Integration with Existing Monitoring Data


The National Park Service (NPS) has initiated a long-term ecological monitoring program, known as “Vital Signs Monitoring”, to provide the minimum infrastructure to allow more than 270 national park system units to identify and implement long-term monitoring of their highest-priority measurements of resource condition. The Eastern Rivers and Mountains Network (ERMN) includes nine parks in New York, New Jersey, Pennsylvania, and West Virginia which together encompass nearly 91,000 ha of land area and more than 600 stream and river miles within the parks’ authorized boundaries. A primary objective of the ERMN monitoring program is to evaluate status and trends in the condition of tributary watersheds flowing into and through member parks. Currently, the monitoring of fish communities is not part of the monitoring program. Consequently, methodology is needed to estimate the current condition of fish communities in ERMN wadeable streams in a rigorous and repeatable manner. Estimates of the current fish community’s condition at ERMN stream sites will complement data collected on an annual basis (i.e., Vital Signs Monitoring) and enable an integrated measure of ecosystem condition that can be monitored over time. The specific objectives of this study are to: (1) characterize fish communities in selected ERMN stream reaches, and (2) combine fish community data with existing monitoring data (e.g., macroinvertebrates) to provide an integrated measure of stream ecological condition.

Selected Publications

Soranno, P.A., L.C. Bacon, M. Beauchene, K.E. Bednar, E.G. Bissell, C.K. Boudreau, M.G. Boyer, M.T. Bremigan, S.R. Carpenter, J.W. Carr and 70 co-authors. LAGOS-NE: A multi-scaled geospatial temporal database of lake ecological context and water quality for thousands of U.S. Lakes. In press. GigaScience.

Yuan, S., J. Zhou, P-N., Tan, E. Fergus, T. Wagner, and P.A. Soranno. Accepted. Multi-Level Multi-Task Learning for Nested Geospatial Data. The IEEE International Conference on Data Mining series (ICDM).

Oliver, S.k., S.M. Collins, P.A. Soranno, T. Wagner, E.H. Stanley, J.R. Jones, C.A. Stow, and N.R. Lottig. 2017. Unexpected stasis in a changing world: Lake nutrient and chlorophyll trends since 1990. Global Change Biology.

Schall, M.K., M.L. Bartron, T. Wertz, J. Niles, V.S. Blazer, and T. Wagner. 2017. Evaluation of genetic population structure of Smallmouth Bass in the Susquehanna River Basin, PA. North American Journal of Fisheries Management 37:729-740.

Hansen, G.J.A., S.R. Midway, T. Wagner. 2017. Walleye recruitment is less resilient to warming water temperatures in lakes with abundant largemouth bass populations. Canadian Journal of Fisheries and Aquatic Sciences.

Grossman, G.D., R.F. Carline, and T. Wagner. Brown trout (Salmo trutta) in Spruce Creek Pennsylvania: a quarter-century perspective. 2017. Freshwater Biology 62:1143-1154.

Collins, S.M., S.K. Oliver, J.F. Lapierre, E.H. Stanley, J.R. Jones, T. Wagner. and P.A. Soranno. 2017. Lake nutrient stoichiometry is less predictable than nutrient concentrations at regional and sub-continental scales. Ecological Applications 27:1529-1540.

Vidal, T. E., B. J. Irwin, T. Wagner, L. G. Rudstam, J. R. Jackson, and J. R. Bence. 2017. Using Variance Structure to Quantify Responses to Perturbation in Fish Catches. Transactions of the American Fisheries Society 146:584-593.

Sweka, J.A., L.A. Davis, T. Wagner. 2017. Fall and winter survival of brook and brown trout in a North-Central Pennsylvania watershed. Transactions of the American Fisheries Society 146:744-752.

Cheruvelil, S. K., S. Yuan, K.E. Webster, P-N Tan, J.F. Lapierre, S.M. Collins, C.E. Fergus, C.E. Scott, E.N. Henry, P.A. Soranno, C.T. Filstrup, T. Wagner. 2017. Creating multi-themed ecological regions for macrosystems ecology: Testing a flexible, repeatable, and accessible clustering method. Ecology and Evolution 7:3046-3058.

Wagner, T. J.B. Whittier, J.T. DeWeber, S.R. Midway, and C.P. Paukert. 2017. Annual changes in seasonal river water temperatures in the eastern and western United States. Water 9(2), 90; doi:10.3390/w9020090

Peoples, B., S.R. Midway, J.T. DeWeber, and T. Wagner. 2017. Catchment scale determinants of nonindigenous minnow richness in the eastern United States. Ecology of Freshwater Fish.

Midway, S.R., C.T. Hasler, T. Wagner, and C.D. Suski. 2017. Predation of freshwater fish in elevated carbon dioxide environments. Marine and Freshwater Resources.

Fergus, C.E., A.O. Finley, P.A. Soranno, T. Wagner. 2016. Spatial Variation in Nutrient and Water Color Effects on Lake Chlorophyll at Macroscales. PLoS ONE 11(10): e0164592.doi:10.1371/journal.pone.0164592.

White, S.L., T. Wagner, C. Gowand, and V.A. Braithwaite. 2017. Can personality predict individual differences in brook trout spatial learning ability? Behavioural Processes 141:220-228. 

Wagner, T., C.E. Fergus, C.A. Stow, K.S. Cheruvelil, and P.A. Soranno. 2016. The statistical power to detect cross-scale interactions at macroscales. Ecosphere 7(7):e01417.

Oliver, S.K., P.A. Soranno, C.E. Fergus, T. Wagner, L.A. Winslow, C.E. Scott, K.E. Webster, J.A. Downing, and E.A. Stanley. 2016. Prediction of lake depth across a 17-state region in the U.S. Inland Waters 6:314-324.

Davis, L.A. and T. Wagner. 2016. Scale-dependent seasonal pool habitat use of sympatric wild Brook Trout and Brown Trout populations. Transactions of the American Fisheries Society 145:888-902.

Wagner, T., S.R. Midway, T. Vidal, B.J. Irwin, and J.R. Jackson. 2016. Detecting unusual temporal patterns in fisheries time series data. Transactions of the American Fisheries Society 145:786-794.

Midway, S.R., T. Wagner, J.D. Zydlewski, B.J. Irwin, and C.P. Paukert. 2016. Transboundary Fisheries Science: Meeting the Challenges of Inland Fisheries Management in the 21st Century. Fisheries 41:536-546.

Midway, S.R. and T. Wagner. 2015. The first description of oarfish Regalecus glesne (Regalecidae) ageing structures. Journal of Applied Ichthyology 1-4.

Soranno, P.A., K.S. Cheruvelil, T. Wagner, K.E. Webster, and M.T. Bremigan. 2015. Effects of land use on lake nutrients: The importance of scale, hydrologic connectivity, and region. PLoS ONE 10(8): e0135454.

Smith, L.A., T. Wagner, M.L. Bartron. 2015. Spatial and temporal movement dynamics of brook Salvelinus fontinalis and brown trout Salmo trutta. Environmental Biology of Fishes 98:2049-2065. 

Soranno, P.A., E.G. Bissell, K.S. Cheruvelil, S.M. Collins, C.E. Fregus, C.T. Filstrup, J-F. Lapierre, N.R. Lottig, S.K. Oliver, C.E. Scott, N.J. Smith, S. Stopyak, S. Yuan, M.T. Bremigan, J.A. Downing, C. Gries, E.N. Henry, N.K. Skaff, E.H. Stanley, C.A. Stow, P-N. Tan, T. Wagner, and K.E. Webster. 2015. Building a multi-scaled geospatial temporal ecology database from disparate data sources: Fostering open science and data reuse. GigaScience 4:28.

Midway, S. R., T. Wagner, S. Arnott, P. Biondo, F. Martinez-Andrade, and T. Wadsworth. 2015. Spatial and temporal variability in growth of southern flounder (Paralichthys lethostigma). Fisheries Research 167:323-332.

DeWeber, J.T. and T. Wagner. 2015. Translating climate change effects into everyday language: an example of more driving and less angling. Fisheries 40:395-398.

DeWeber, J.T and T. Wagner. 2015. Predicting brook trout occurrence in stream reaches throughout their native range in the eastern United States. Transactions of the American Fisheries Society 144:11-24. 

Midway, S., T. Wagner, B. H. Tracy, G. M. Hogue, and W.C. Starnes. 2015. Evaluating changes in stream fish species richness over a 50-year time-period within a landscape context. Environmental Biology of Fishes 98:1295-1309.

Wagner, T., and S. R. Midway. 2014. Modeling spatially varying landscape change points in species occurrence thresholds. Ecosphere 5(11):145. http://dx.doi.org/10.1890/ES14-00288.1 

DePasquale, C., T. Wagner, G.A. Archard, B. Ferguson, and V.A. Braithwaite. 2014. Learning rate and temperament in a high predation risk environment. Oecologia 176:661-667.

Kepler, M.V., T. Wagner, and J.A. Sweka. 2014. Comparative bioenergetics modeling of two Lake Trout morphotypes. Transactions of the American Fisheries Society 143:1592–1604.

Filstrup, C.T., T. Wagner, P.A. Soranno, E.H. Stanley, C.A. Stow, K.E. Webster, and J. A. Downing. 2014. Regional variability among nonlinear chlorophyll-phosphorus relationships in lakes. Limnology and Oceanography 59:1691-1703.

Perles, S.J., T. Wagner, B.J. Irwin, D.R. Manning, K.K. Callahan, and M.R. Marshall. 2014. Evaluation of a regional monitoring program's statistical power to detect temporal trends in forest health indicators. Environmental Management 54:641-655.

Deweber, J.T. and T. Wagner. 2014. A regional neural network model for predicting mean daily river water temperature. Journal of Hydrology 517:187-200.

Midway, S.M., T. Wagner, and B. Tracy. 2014. A hierarchical community occurrence model for North Carolina stream fish. Transactions of the American Fisheries Society 143:1348-1357.

Lottig, N.R., T. Wagner, E. Norton Henry, K. Spence Cheruvelil, K.E. Webster, et al. 2014. Long-term citizen-collected data reveal geographical patterns and temporal trends in lake water clarity. PLoS ONE 9(4): e95769. doi:10.1371/journal.pone.0095769

Levy, O., B.A. Ball, B. Bond-Lamberty, K.S. Cheruvelil,  A.O. Finley, N. Lottig, S.W. Punyasena, J. Xiao, J. Zhou, L.B. Buckley, C.T. Filstrup, T. Keitt, J.R. Kellner, A.K. Knapp, A.D. Richardson, D. Tcheng, M. Toomey, R. Vargas, J.W. Voordeckers, T.  Wagner, J.W. Williams. 2014. Approaches to advance scientific understanding of macrosystems ecology. Frontiers in Ecology and the Environment 12:15-23. 

Deweber, J.T., Y., Tsang, D.M. Krueger, J.B. Whittier, T. Wagner, D.M. Infante, and G. Whelan. 2014. Importance of understanding landscape biases in USGS gage locations: Implications and solutions for managers. Fisheries 39:155-163. 

Wagner, T., J.T. Deweber, J. Detar, D. Kristine, and J.A. Sweka. 2014. Spatial and temporal dynamics in Brook Trout density: implications for population monitoring. North American Journal of Fisheries Management 34:258-269.

Detar, J. D. Kristine, T. Wagner, and T. Greene. 2014. Evaluation of catch-and-release regulations on Brook Trout in Pennsylvania streams. North American Journal of Fisheries Management 34:49-56.

Soranno, P.A., K. Spence Cheruvelil, E. Bissell, M. Tate-Bremigan, J.A. Downing, C.E. Fergus, C. Filstrup, N.R. Lottig, E.N. Henry, E.H. Stanley, C.A. Stow, P.N. Tan, T. Wagner, and K.E. Webster. 2014. Cross-scale interactions: A conceptual framework for understanding multi-scaled cause-effect relationships in macrosystems. Frontiers in Ecology and the Environment 12:65-73. 

Mollenhauer, R. T. Wagner, M.V. Kepler, J.A. Sweka. 2013. Fall and early winter movement and habitat use of wild brook trout. Transactions of the American Fisheries Society 142:1167-1178.

Wagner, T. B.J. Irwin, J.R. Bence, and D.B. Hayes. 2013. Detecting temporal trends in freshwater fisheries surveys: statistical power and the important linkages between management questions and monitoring objectives. Fisheries 38:309-319.

Wagner, T. , J.T. Deweber, J. Detar, and J.A. Sweka. 2013. Landscape-scale evaluation of asymmetric interactions between brown trout and brook trout using two-species occupancy models. Transactions of the American Fisheries Society 142:353-361.

Irwin, B. J., T. Wagner, J. R. Bence, M. V. Kepler, W. Liu, and D. B. Hayes. 2013. Estimating spatial and temporal components of variation for fisheries count data using negative binomial mixed models. Transactions of the American Fisheries Society 142:171-183.

Sweka, J. A., T. Wagner, J. Detar, and D. Kristine. 2012. Combining Field Data with Computer Simulations to Determine a Representative Reach for Brook Trout Assessment. Journal of Fish and Wildlife Management 3:209-222.

Rennie, M.D., M.P. Ebener, and T. Wagner. 2012. Can migration mitigate the effects of ecosystem change? Patterns of dispersal, energy acquisition and allocation in Great Lakes lake whitefish (Coregonus clupeaformis). Proceedings of the 10th Annual Coregonid Symposium. Advances in Limnology 63:455-476. 

Wagner, T., D.R. Diefenbach, A.S. Norton, and S.A. Christensen. 2011. Using multilevel models to quantify heterogeneity in resource selection. Journal of Wildlife Management 75:1788-1796.

Wagner, T., P.A. Soranno, K.E. Webster, and K. Spence Cheruvelil. 2011. Landscape drivers of regional variation in the relationship between total phosphorus and chlorophyll in lakes. Freshwater Biology 56:1811-1824. doi:10.1111/j.1365-2427.2011.02621.x 

Soranno, P.A., T. Wagner, S. Martin, L. McLean, L. Novitski,C. Provence, and A. Rober. 2011. Quantifying regional reference conditions for freshwater ecosystem management: A comparison of approaches and future research needs. Lake and Reservoir Management 27:138-148. 

Wagner, T. and J.A. Sweka. 2011.Evaluation of hypotheses for describing temporal trends in Atlantic salmon parr densities in Northeast U.S. Rivers. North American Journal of Fisheries Management 31:340–351.

Soranno, P.A., K. Spence Cheruvelil, K.E. Webster, M.T. Bremigan, T. Wagner, and C.A. Stow. 2010. Freshwater Ecosystem Classification for Landscape-scale Management. BioScience 60:440-454.

Wagner, T. and 7 coauthors. 2010. Spatial and temporal dynamics of lake whitefish (Coregonus clupeaformis) health measures: linking individual-based indicators to a management-relevant endpoint. Journal of Great Lakes Research 36:121-134.

Wagner, T., C.S. Vandergoot, and J. Tyson. 2009. Evaluating the Power to Detect Temporal Trends in Fishery-Independent Surveys: A Case Study Based on Gillnets Set in the Ohio Waters of Lake Erie for Walleye. North American Journal of Fisheries Management 29:805-816.

Wagner, T., M.E. Benbow, T.O. Brenden, J. Qi, and R.C. Johnson. 2008. Buruli ulcer disease prevalence in Benin, West Africa: associations with land use/cover and the identification of disease clusters. International Journal of Health Geographics 7:25.

Wagner, T., P.A. Soranno, K. Spence Cheruvelil, B. Renwick, K. Webster, P. Vaux, and R. Abbitt. 2008. Quantifying sample biases of inland lake sampling programs in relation to lake surface area and land use/cover. Environmental Monitoring and Assessment 131-147.

Wagner, T., J.R. Bence, M.T. Bremigan, D.B. Hayes, and M.J. Wilberg. 2007. Regional trends in fish mean length at age: components of variance and the power to detect trends. Canadian Journal of Fisheries and Aquatic Sciences 64:968-978.

Wagner, T., M.T. Bremigan, K. Spence Cheruvelil, P.A. Soranno, N.N. Nate, and J.E. Breck. 2007. A multilevel modeling approach to assessing regional and local landscape features for lake classification and assessment of fish growth rates. Environmental Monitoring and Assessment 130:437-454.

Wagner, T. A.K. Jubar, and M.T. Bremigan. 2006. Can habitat alteration and spring angling explain black bass nest distribution and success? Transactions of the American Fisheries Society 135:843-852.

Wagner, T., D.B. Hayes, and M.T. Bremigan. 2006. Accounting for multilevel data structures in fisheries data using mixed models. Fisheries 31:180-187.

Congleton, J. L., and T. Wagner. 2006. Blood-chemistry indicators of nutritional status in juvenile salmonids. Journal of Fish Biology 69:473-790.

Zabel, R.W., T. Wagner, J.L. Congleton, S.G. Smith, and S.G. Williams. 2005. Survival and selection of migrating salmon from capture-recapture models with individual traits. Ecological Applications 15:1427-1439. 

Wagner, T., and J.L. Congleton. 2004. Blood-chemistry correlates of nutritional condition, tissue damage, and stress in migrating juvenile chinook salmon (Oncorhynchus tshawytscha). Canadian Journal of Fisheries and Aquatic Sciences 61:1066-1074.

Wagner, T., J.L. Congleton, and D.M. Marsh. 2004. Smolt-to-adult return rates of juvenile chinook salmon transported through the Snake-Columbia River hydropower system, USA, in relation to densities of co-transported juvenile steelhead. Fisheries Research 68:259-270.