Non-native plant associations with wildfire, tree removals, and deer in the eastern United States
Keywords:biotic resistance, disturbance, exotic, invasive
Wildfires, tree removals, and deer herbivory are potential pathways for spread of non-native plants. I modeled the number of recorded nonnative plant species by county compared to wildfire area, tree removals, and deer densities in the eastern United States and also eastern forests. Species richness of 1016 plant species in 780 primarily forested counties decreased with increased values of the three variables; models equally showed negative relationships. For model predictions, based on withheld samples of non-native species counts, percentage wildfire area alone had the greatest association (R2 value of 31%) for non-native species richness in eastern forests; non-native species richness decreased with wildfire area until stabilizing at >1% wildfire area to a neutral relationship. For 1581 species in 2431 counties in the eastern U.S., the three variables each had an overall negative relationship with non-native species richness (R2 value up to 14%), without a consensus by three regression types of most influential variables. These formal models suggest that wildfire, tree removals, and deer herbivory generally may be nominal pathways for non-native plant spread at landscape scales in the eastern United States.
Abella, S.R., Springer, J.D. 2015. Effects of tree cutting and fire on understory vegetation in mixed conifer forests. Forest Ecology and Management 335, 281-299. https://doi.org/10.1016/j.foreco.2014.09.009 DOI: https://doi.org/10.1016/j.foreco.2014.09.009
Abrams, M.D., Nowacki, G.J. and Hanberry, B.B., 2022. Oak forests and woodlands as Indigenous landscapes in the Eastern United States. The Journal of the Torrey Botanical Society 149, 101-121. https://doi.org/10.3159/TORREY-D-21-00024.1 DOI: https://doi.org/10.3159/TORREY-D-21-00024.1
Adams, K., Hamilton, R.J., Ross, M. 2009. QDMA’s whitetail report 2009. QDMA, Bogart, GA.
Alba, C., Skálová, H., McGregor, K. F., D'Antonio, C., Pyšek, P. 2015. Native and exotic plant species respond differently to wildfire and prescribed fire as revealed by meta‐analysis. Journal of Vegetation Science 26, 102-113. https://doi.org/10.1111/jvs.12212 DOI: https://doi.org/10.1111/jvs.12212
Allen, J.M., Bradley, B.A. 2016. Out of the weeds? Reduced plant invasion risk with climate change in the continental United States. Biological Conservation 203, 306-312. https://doi.org/10.1016/j.biocon.2016.09.015 DOI: https://doi.org/10.1016/j.biocon.2016.09.015
Averill, K.M., Mortensen, D.A., Smithwick, E.A., Kalisz, S., McShea, W.J., Bourg, N.A., Parker, J.D., Royo, A.A., Abrams, M.D., Apsley, D.K., Blossey, B. 2018. A regional assessment of white-tailed deer effects on plant invasion. AoB Plants 10, plx047. DOI: 10.1093/aobpla/plx047 DOI: https://doi.org/10.1093/aobpla/plx047
Balch, J.K., Bradley, B.A., Abatzoglou, J.T., Nagy, R.C., Fusco, E.J. and Mahood, A.L., 2017. Human-started wildfires expand the fire niche across the United States. Proceedings of the National Academy of Sciences 114, 2946-2951. https://doi.org/10.1073/pnas.1617394114 DOI: https://doi.org/10.1073/pnas.1617394114
Belote, R.T., Jones, R.H., Hood, S.M. and Wender, B.W. 2008. Diversity–invasibility across an experimental disturbance gradient in Appalachian forests. Ecology 89, 183-192. https://doi.org/10.1890/07-0270.1 DOI: https://doi.org/10.1890/07-0270.1
Black, D.E., Poynter, Z.W., Cotton, C.A., Upadhaya, S., Taylor, D.D., Leuenberger, W., Blankenship, B.A. and Arthur, M.A. 2018. Post-wildfire recovery of an upland oak−pine forest on the Cumberland Plateau, Kentucky, USA. Fire Ecology 14, 1-12. https://doi.org/10.1186/s42408-018-0013-9 DOI: https://doi.org/10.1186/s42408-018-0013-9
Blackburn, T.M., Pyšek, P., Bacher, S., Carlton, J.T., Duncan, R.P., Jarošík, V., Wilson, J.R. and Richardson, D.M., 2011. A proposed unified framework for biological invasions. Trends in Ecology & Evolution, 26, 333-339. https://doi.org/10.1016/j.tree.2011.03.023 DOI: https://doi.org/10.1016/j.tree.2011.03.023
Center for Invasive Species and Ecosystem Health. 2020. EDDMapS Invasive Species Database. Warnell School of Forestry and Natural Resources, Athens, GA. Available at https://www.eddmaps.org/species/ Accessed 28 February 2021.
Colautti, R.I., Grigorovich, I.A. and MacIsaac, H.J. 2006. Propagule pressure: a null model for biological invasions. Biological invasions, 8, 1023-1037. https://doi.org/10.1007/s10530-005-3735-y DOI: https://doi.org/10.1007/s10530-005-3735-y
Crooks, J.A. 2005. Lag times and exotic species: The ecology and management of biological invasions in slow-motion. Ecoscience, 12, 316-329. https://doi.org/10.2980/i1195-6860-12-3-316.1 DOI: https://doi.org/10.2980/i1195-6860-12-3-316.1
Epanchin‐Niell, R.S. and Hastings, A. 2010. Controlling established invaders: integrating economics and spread dynamics to determine optimal management. Ecology Letters, 13, 528-541. https://doi.org/10.1111/j.1461-0248.2010.01440.x DOI: https://doi.org/10.1111/j.1461-0248.2010.01440.x
Epanchin-Niell, R.S., Hufford, M.B., Aslan, C.E., Sexton, J.P., Port, J.D. and Waring, T.M. 2010. Controlling invasive species in complex social landscapes. Frontiers in Ecology and the Environment, 8, 210-216. https://doi.org/10.1890/090029 DOI: https://doi.org/10.1890/090029
Eschtruth, A.K. and Battles, J.J., 2009. Assessing the relative importance of disturbance, herbivory, diversity, and propagule pressure in exotic plant invasion. Ecological Monographs 79, 265-280. https://doi.org/10.1890/08-0221.1 DOI: https://doi.org/10.1890/08-0221.1
Gavier-Pizarro, G.I., Radeloff, V.C., Stewart, S.I., Huebner, C.D., Keuler, N.S. 2010. Housing is positively associated with invasive exotic plant species richness in New England, USA. Ecological Applications, 20, 1913-1925. https://doi.org/10.1890/09-2168.1 DOI: https://doi.org/10.1890/09-2168.1
Greenwell, B. M. 2017. pdp: An R package for constructing partial dependence plots. The R Journal, 9, 421-436. DOI: https://doi.org/10.32614/RJ-2017-016
Habeck, C. W., and Schultz, A. K. 2015. Community-level impacts of white-tailed deer on understorey plants in North American forests: a meta-analysis. AoB plants, 7, plv119. https://doi.org/10.1093/aobpla/plv119 DOI: https://doi.org/10.1093/aobpla/plv119
Hanberry, B.B., 2020. Classifying large wildfires in the United States by land cover. Remote Sensing 12, 2966. https://doi.org/10.3390/rs12182966 DOI: https://doi.org/10.3390/rs12182966
Hanberry, B. B., Hanberry, P. 2020. Rapid digitization to reclaim thematic maps of white-tailed deer density from 1982 and 2003 in the conterminous US. PeerJ, 8, e8262. https://doi.org/10.7717/peerj.8262 DOI: https://doi.org/10.7717/peerj.8262
Hanberry, B.B., Abrams, M.D., Arthur, M.A., Varner, J.M. 2020. Reviewing fire, climate, deer, and foundation species as drivers of historically open oak and pine forests and transition to closed forests. Frontiers in Forests and Global Change, 3, 56. https://doi.org/10.3389/ffgc.2020.00056 DOI: https://doi.org/10.3389/ffgc.2020.00056
Hanberry, B.B., 2021a. Addressing regional relationships between white‐tailed deer densities and land classes. Ecology and Evolution, 11, 13570-13578. https://doi.org/10.1002/ece3.8084 DOI: https://doi.org/10.1002/ece3.8084
Hanberry, B.B. 2021b. Timing of tree density increases, influence of climate change, and a land use proxy for tree density increases in the eastern United States. Land, 10, 1121. https://doi.org/10.3390/land10111121 DOI: https://doi.org/10.3390/land10111121
Hanberry, B.B. 2021c. Transition from fire-dependent open forests: Alternative ecosystem states in the southeastern United States. Diversity, 13, 411. https://doi.org/10.3390/d13090411 DOI: https://doi.org/10.3390/d13090411
Homer, C., Dewitz, J., Jin, S., Xian, G., Costello, C., Danielson, P., Gass, L., Funk, M., Wickham, J., Stehman, S., Auch, R. 2020. Conterminous United States land cover change patterns 2001–2016 from the 2016 national land cover database. ISPRS Journal of Photogrammetry and Remote Sensing, 162, 184-99. https://doi.org/10.1016/j.isprsjprs.2020.02.019 DOI: https://doi.org/10.1016/j.isprsjprs.2020.02.019
Kerns, B.K., Poland, T.M., Venette, R.C., Patel-Weynand, T., Finch, D.M., Rowley, A., Hayes, D.C. and Ielmini, M. 2021. Future invasive species research challenges and opportunities. In: Poland, T.M., Patel-Weynand, T., Finch, D.M., Miniat, C.F., Hayes, D.C., Lopez, V.M. (eds.) Invasive Species in Forests and Rangelands of the United States: A Comprehensive Science Synthesis for the United States Forest Sector. Springer International Publishing, Heidelberg, Germany: 329 - 334. DOI: https://doi.org/10.1007/978-3-030-45367-1_16
Khaledian, Y. and Miller, B.A. 2020. Selecting appropriate machine learning methods for digital soil mapping. Applied Mathematical Modelling, 81, 401-418. https://doi.org/10.1016/j.apm.2019.12.016 DOI: https://doi.org/10.1016/j.apm.2019.12.016
Kuhn, M. 2008. Building predictive models in R using the caret package. Journal of Statistical Software, 28, 1-26. DOI: https://doi.org/10.18637/jss.v028.i05
Levine, J.M., Adler, P.B., Yelenik, S.G. 2004. A meta-analysis of biotic resistance to exotic plant invaders. Ecology Letters, 7, 975–989. https://doi.org/10.1111/j.1461-0248.2004.00657.x DOI: https://doi.org/10.1111/j.1461-0248.2004.00657.x
Lockwood, J.L., Cassey, P. and Blackburn, T. 2005. The role of propagule pressure in explaining species invasions. Trends in Ecology & Evolution, 20, 223-228. https://doi.org/10.1016/j.tree.2005.02.004 DOI: https://doi.org/10.1016/j.tree.2005.02.004
Means, D. B. 2006. Vertebrate faunal diversity in longleaf pine savannas. In Jose, S., Jokela, E., Miller, D. (eds.), Longleaf Pine Ecosystems: Ecology, Management, And Restoration. Springer, New York, NY, 155-213.
Moles, A.T., Flores‐Moreno, H., Bonser, S.P., Warton, D.I., Helm, A., Warman, L., Eldridge, D.J., Jurado, E., Hemmings, F.A., Reich, P.B., Cavender‐Bares, J. 2012. Invasions: the trail behind, the path ahead, and a test of a disturbing idea. Journal of Ecology, 100, 116-127. https://doi.org/10.1111/j.1365-2745.2011.01915.x DOI: https://doi.org/10.1111/j.1365-2745.2011.01915.x
Natural Resources Conservation Service [NRCS]. 2022. Soil orders map of the United States. https://www.nrcs.usda.gov/wps/portal/nrcs/main/soils/survey/class/maps/ [Accessed 27 June 2022].
Parker, J.D., Burkepile, D.E., Hay, M.E. 2006. Opposing effects of native and exotic herbivores on plant invasions. Science, 311, 1459–1461. DOI: 10.1126/science.1121407 DOI: https://doi.org/10.1126/science.1121407
Pearson, D.E., Ortega, Y.K., Eren, Ö. and Hierro, J.L. 2016. Quantifying “apparent” impact and distinguishing impact from invasiveness in multispecies plant invasions. Ecological Applications, 26, 162-173. DOI: 10.1890/14-2345 DOI: https://doi.org/10.1890/14-2345
PRISM Climate Group. 2022. Oregon State University. https://prism.oregonstate.edu.
R Core Team. 2021. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.
Simberloff, D., 2009. The role of propagule pressure in biological invasions. Annual Review of Ecology, Evolution and Systematics, 40, 81-102. https://doi.org/10.1146/annurev.ecolsys.110308.120304 DOI: https://doi.org/10.1146/annurev.ecolsys.110308.120304
Short, K. C. 2017. Spatial wildfire occurrence data for the United States, 1992-2015 [FPA_FOD_20170508]. 4th Edition. Forest Service Research Data Archive, Fort Collins, CO.
USDA Forest Service. 1920. National forest fire report, calendar year 1920. Washington, D.C.: U.S. Department of Agriculture, Forest Service.
USDA Forest Service, Forest Inventory and Analysis Program. 2021. Forest Inventory EVALIDator web-application Version 1.8.0.01. St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station. http://apps.fs.usda.gov/Evalidator/evalidator.jsp [Accessed 26 April 2021].
Westbrooks, R.G., 2004. New approaches for early detection and rapid response to invasive plants in the United States. Weed Technology, 18, 1468-1471. https://doi.org/10.1614/0890-037X(2004)018[1468:NAFEDA]2.0.CO;2 DOI: https://doi.org/10.1614/0890-037X(2004)018[1468:NAFEDA]2.0.CO;2
Zhang, W., Wu, C., Zhong, H., Li, Y. and Wang, L. 2021. Prediction of undrained shear strength using extreme gradient boosting and random forest based on Bayesian optimization. Geoscience Frontiers, 12, 469-477. https://doi.org/10.1016/j.gsf.2020.03.007 DOI: https://doi.org/10.1016/j.gsf.2020.03.007
Zouhar, K., Smith, J. K., Sutherland, S., Brooks, M. L. 2008. Wildland fire in ecosystems: fire and nonnative invasive plants. U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, Ogden, UT. DOI: https://doi.org/10.2737/RMRS-GTR-42-V6
How to Cite
Copyright (c) 2022 Brice B. Hanberry
This work is licensed under a Creative Commons Attribution 4.0 International License.