Wenger, Seth: University of Georgia (Project Lead)
Project Funding:
2014 - 2018
NRA: 2012 NASA: Ecological Forecasting
Funded by NASA
Abstract:
Conservation management for salmonids (trout + salmon) as for other taxa often requires decisions on the allocation of scarce resources. These decisions are typically supported by spatial prioritization schemes that seek to identify those populations with the highest chance of persistence under current conditions, and often under future climate change scenarios as well. However, actual persistence (i.e., population viability over a defined time frame) is rarely estimated directly, due to methodological and data limitations. We propose to use new modeling approaches and novel high resolution stream and air temperature datasets coupled with NASA climate data and imagery to estimate population viability, genetic diversity and other key population characteristics of cutthroat trout (Oncorhynchus clarkii), redband trout (Oncorhynchus mykiss), bull trout (Salvelinus confluentus), and possibly other salmonid species in large areas of the interior western United States at spatial resolutions relevant to on-the-ground management. These estimates will be driven by empirical in situ data on trout abundance and genetics assembled from state, federal, and academic partners, as well as crowdsourced presence/absence observations from Trout Unlimited members. The fundamental goal of our project is to model population viability and genetic diversity simultaneously across populations as a function of covariates such as habitat size, stream temperature, stream flows and net primary productivity derived from NASA Landsat and MODIS imagery and other sources. Stream temperature models and refined flow projections, coupled with downscaled climate models, will allow us to incorporate predicted climate change into population viability and genetic diversity estimates. Once relationships between spatiotemporal covariates and population viability/genetic diversity are established, we can make projections of these population parameters across large landscapes and under climate change scenarios. We can also evaluate proposed management actions, such as riparian restoration, barrier removal, flow augmentation and assisted migration. We will work with managers throughout the course of the project to tie the modeling system into conservation planning decision support systems. These will include Trout Unlimited s own conservation planning framework, Forest Service prioritization and planning efforts, and other conservation planning systems used by the US Fish and Wildlife Service and the Bureau of Land Management.

Publications:
Amish, S. J., Ali, O., Peacock, M., Miller, M., Robinson, M., Smith, S., Luikart, G., Neville, H. 2019. Assessing thermal adaptation using family-based association and
F
ST
outlier tests in a threatened trout species. Molecular Ecology. 28(10), 2573-2593. DOI: 10.1111/mec.15100
Dauwalter, D. C., Fesenmyer, K. A., Bjork, R. 2015. Using Aerial Imagery to Characterize Redband Trout Habitat in a Remote Desert Landscape. Transactions of the American Fisheries Society. 144(6), 1322-1339. DOI: 10.1080/00028487.2015.1088471
Day, C. C., Landguth, E. L., Bearlin, A., Holden, Z. A., Whiteley, A. R. 2018. Using simulation modeling to inform management of invasive species: A case study of eastern brook trout suppression and eradication. Biological Conservation. 221, 10-22. DOI: 10.1016/j.biocon.2018.01.017
Escalante, M. A., Garcia-De Leon, F. J., Ruiz-Luna, A., Landguth, E., Manel, S. 2018. The interplay of riverscape features and exotic introgression on the genetic structure of the Mexican golden trout (Oncorhynchus chrysogaster
), a simulation approach. Journal of Biogeography. 45(7), 1500-1514. DOI: 10.1111/jbi.13246
Forester, B. R., Landguth, E. L., Hand, B. K., Balkenhol, N. 2018. Landscape Genomics for Wildlife Research in: Population Genomics: Population Genomics: Wildlife. Springer International Publishing, 145-184. DOI: 10.1007/13836_2018_56
Hemstrom, W., Dauwalter, D., Peacock, M. M., Leasure, D., Wenger, S., Miller, M. R., Neville, H. 2022. Population genomic monitoring provides insight into conservation status but no correlation with demographic estimates of extinction risk in a threatened trout. Evolutionary Applications. 15(9), 1449-1468. DOI: 10.1111/eva.13473
Isaak, D. J., Wenger, S. J., Young, M. K. 2017. Big biology meets microclimatology: defining thermal niches of ectotherms at landscape scales for conservation planning. Ecological Applications. 27(3), 977-990. DOI: 10.1002/eap.1501
Kormos, P. R., Luce, C. H., Wenger, S. J., Berghuijs, W. R. 2016. Trends and sensitivities of low streamflow extremes to discharge timing and magnitude in Pacific Northwest mountain streams. Water Resources Research. 52(7), 4990-5007. DOI: 10.1002/2015wr018125
Landguth, E. L., Bearlin, A., Day, C. C., Dunham, J. 2016. CDM
eta
POP
: an individual-based, eco-evolutionary model for spatially explicit simulation of landscape demogenetics. Methods in Ecology and Evolution. 8(1), 4-11. DOI: 10.1111/2041-210x.12608
Landguth, E. L., Holden, Z. A., Mahalovich, M. F., Cushman, S. A. 2017. Using Landscape Genetics Simulations for Planting Blister Rust Resistant Whitebark Pine in the US Northern Rocky Mountains. Frontiers in Genetics. 8. DOI: 10.3389/fgene.2017.00009
Leasure, D. R., Wenger, S. J., Chelgren, N. D., Neville, H. M., Dauwalter, D. C., Bjork, R., Fesenmyer, K. A., Dunham, J. B., Peacock, M. M., Luce, C. H., Lute, A. C., Isaak, D. J. 2018. Hierarchical multi-population viability analysis. Ecology. 100(1). DOI: 10.1002/ecy.2538
Mims, M. C., Day, C. C., Burkhart, J. J., Fuller, M. R., Hinkle, J., Bearlin, A., Dunham, J. B., DeHaan, P. W., Holden, Z. A., Landguth, E. E. 2019. Simulating demography, genetics, and spatially explicit processes to inform reintroduction of a threatened char. Ecosphere. 10(2), e02589. DOI: 10.1002/ecs2.2589
Nathan, L. R., Mamoozadeh, N., Tumas, H. R., Gunselman, S., Klass, K., Metcalfe, A., Edge, C., Waits, L. P., Spruell, P., Lowery, E., Connor, E., Bearlin, A. R., Fortin, M., Landguth, E. 2019. A spatially-explicit, individual-based demogenetic simulation framework for evaluating hybridization dynamics. Ecological Modelling. 401, 40-51. DOI: 10.1016/j.ecolmodel.2019.03.002
Neville, H., Dauwalter, D., Peacock, M. 2016. Monitoring Demographic and Genetic Responses of a Threatened Inland Trout to Habitat Reconnection. Transactions of the American Fisheries Society. 145(3), 610-626. DOI: 10.1080/00028487.2015.1131747
Pilliod, D. S., Arkle, R. S., Thurow, R. F., Isaak, D. J. 2022. Hydroclimatic Conditions, Wildfire, and Species Assemblages Influence Co-Occurrence of Bull Trout and Tailed Frogs in Northern Rocky Mountain Streams. Water. 14(7), 1162. DOI: 10.3390/w14071162
Schultz, L. D., Heck, M. P., Hockman-Wert, D., Allai, T., Wenger, S., Cook, N. A., Dunham, J. B. 2017. Spatial and temporal variability in the effects of wildfire and drought on thermal habitat for a desert trout. Journal of Arid Environments. 145, 60-68. DOI: 10.1016/j.jaridenv.2017.05.008
Scribner, K. T., Lowe, W. H., Landguth, E., Luikart, G., Infante, D. M., Whelan, G. E., Muhlfeld, C. C. 2016. Applications of Genetic Data to Improve Management and Conservation of River Fishes and Their Habitats. Fisheries. 41(4), 174-188. DOI: 10.1080/03632415.2016.1150838
More details may be found in the following project profile(s):
