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University of Michigan Biological Station

The University of Michigan Biological Station (UMBS) was founded in 1909.

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How will climate change and latitude interact to affect tree species in the Great Lakes Region?

Project Abstract: 
Climate change has historically had a profound impact on plant species, inducing adaptation (Cheddadi et al. 2016), long-distance migration (Davis and Shaw 2001), and even extinction (Jackson and Weng 1999), however, climate change does not affect communities uniformly, nor are its effects uniform across species ranges. Mixed responses among species can cause communities to break apart and new associations to form, and mixed responses within a species range can cause some populations to decline, and others to thrive (Davis 1983). Modern climate change may produce effects similar to those of prior climate change, or, because modern change is proceeding more rapidly than historic change, more severe effects. Indeed, plant phenology (Willis et al. 2008), distribution (Harsch et al. 2009), and growth (Liu et al. 2013, Silva et al. 2016) have already been affected, particularly at the edges of species ranges. Populations at the warm edges tend to be in decline, while those at cold edges are on the ascent, portending potential changes in species distribution and community composition (Parmesan 2006). Climate-change responses will not only differ among species and populations, but they will likely differ around the earth. The Great Lakes Region is a region with a unique climate and a high concentration of forests, which are ecologically and economically important. How will climate change affect these communities? Who will be the winning and losing species, and how will this vary with latitude, a factor thought to influence range limits? Further, the region contains long-lived tree species, the tree rings of which have been used for reconstructing climate of times preceding the instrumental record (Ford 2014), however, the ability to reconstruct climate depends on a temporally consistent relationship between tree growth and climate. This relationship may be breaking down in some regions (D’Arrigo et al. 2008). Is that the case in the Great Lakes Region? Below I discuss plans to address the above questions, by studying the tree rings of nine species of the Great Lakes Region along a gradient of latitude. Tree rings can tell us how the growth of a species responds to seasonal climate, such as temperature, precipitation, moisture indices, and Great-Lakes ice cover. I will use principal-component regression to quantify growth responses to climate, and compare responses among species at a given site and within species along a latitudinal gradient. Quantifying responses to current and historic climate will help me predict how a species or population will fare under ongoing climate change. A model will be established, based on the climate variables that most strongly influence growth, and used, along with projections of future climate, to predict future growth. Growth is indicative of vigor, and if a population will lack vigorous growth under its future climate, then it may lack enough vigor to reproduce at rates necessary for long-term persistence. On the other hand, if a population on the edge of its species’ distribution will exhibit accelerated growth under its future climate, then it will likely be vigorous enough to persist at the site, and potentially even expand its range. Tree rings can also tell us how consistent the relationship between growth and climate is over time. I will assess this by using a historic segment of the growth models that I establish to predict recently observed climate. If the model successfully predicts recent climate, then the growth-climate relationship is temporally stable, but if the model is unsuccessful, then tree-ring-based climate reconstructions in the Great Lakes Region will be viewed with more skepticism. Regarding the above questions, I hypothesize (1) that growth-temperature responses will be more negative at southern and more positive at northern limits, (2) that growth-precipitation responses will be more positive at southern limits, (3) that growth will increase at northern and decrease at southern limits over the rest of the century, and (4) that the growth-climate relationship is not temporally stable—growth-climate models based on older data will inadequately predict recent climate. Finally, I discuss below the importance to my study of the Colonial Point Hardwoods, the trees of which are mature enough to provide a growth record long enough to test the temporal stability of the growth-climate relationship. I am taking a novel approach with this project, using tree rings from species with both northern and southern limits to make predictions about community responses to climate change. I will study a larger latitudinal gradient and include more species than other, similar studies. Understanding how responses to climate change differ across species ranges and within communities will aid predictions about species migrations and the resultant changes in biotic interactions, which can greatly alter communities. This work will help guide decisions about planting location and conservation priorities in the Great Lakes Region, but it has implications for ecology and conservation science at-large. If differential growth-climate responses are found among species within mesic forest communities of the Great Lakes Region, then differential responses likely exist in other community types and regions, too.
Methods: 
Study Sites and Species The study region spans a seven-degree latitudinal gradient from southern Indiana to the Upper Peninsula of Michigan. Within that gradient is a tension zone in which the southern hardwood forests give way to mixed hardwood-conifer forests of the north (Anderson 2005). At and near the tension zone is a high concentration of both southern and northern range limits, which allows me to compare northern-limit, southern-limit, and mid-range populations within a relatively small region. The study’s focal species are divided into three categories: southerly species, with a northern limit in the region, northerly species, with a southern limit, and trans-study-area species, without a northern or southern range limit in the region. The southerly species are Carya ovata (shagbark hickory), Liriodendron tulipifera (tulip poplar), and Quercus alba (white oak), the northerly species are Betula alleghaniensis (yellow birch), Pinus strobus (eastern white pine), and Tsuga canadensis (eastern hemlock), and the trans-study-area species are Acer saccharum (sugar maple), Fagus grandifolia (American beech), and Quercus rubra (red oak). There will be at least 12 study sites in the study region, nine of which have already been sampled by field assistants and I over the past two years. This included a total of 36 populations divided among all nine focal species. I am now seeking permission to sample from the Colonial Point Hardwoods, along with two other sites during the 2018 season. Field Methods Standard techniques of dendrochronology will be used (Stokes and Smiley 1996). I and at least one field assistant, but up to three if allowed, will extract cores from both living and recently deceased trees using increment borers. I seek to obtain cores from 12–15 dominant trees for each of the following: A. saccharum, F. grandifolia, Q. rubra, B. alleghaniensis, P. strobus, and T. canadensis. I am open to limiting myself to fewer species, and am especially targeting B. alleghaniensis, P. strobus, and T. canadensis, as those are the least-represented species in the study thus far. From each dead tree, I hope to extract three cores, and from each living tree, two. In pilot analyses of other cores from mesic Michigan forests, taking two cores from 10–12 trees per species has been necessary for obtaining a robust growth chronology, as indicated by an expressed population signal of at least 0.85 (Briffa and Jones 1990). Coring up to 15 trees per species is requested, in case of un-datable cores, which are not common, but which I have observed, particularly in A. saccharum. To increase sample size, a third core will be taken from dead trees only. A long-term record of radial growth is required for this project. To this end, taking increment cores is the method that harms trees the least. Unfortunately, it still involves risk. Vigorous trees are typically able to grow over a coring-induced wound. They also compartmentalize the wound by forming an antiseptic barrier in their sapwood which seals off the wound from the living parenchyma in the sapwood that surrounds it (Shigo and Hillis 1973). Nevertheless, coring still leaves a chance of microorganism infection and spread, and decay (Tsen et al. 2016). I seek to wound living trees as little as possible. Thus, I aim to take half of the cores from recently dead trees, if I am able to find enough after a reasonable search. Living trees will only be sampled after either sampling from 6-8 dead trees per focal species or running out of dead trees from which to sample. Only two cores will be taken from any living trees sampled. If permitted, trees will be labeled with small aluminum tags, which will be fixed to trees with aluminum nails, as near to the ground as possible, on exposed roots if available. Tags will face away from trails and buildings, and I will remove them at the end of the study period. Alternatively tags will be foregone, and careful notetaking and latitude/longitude, obtained with a Global Positioning System (G.P.S.), will be used to keep track of trees. Because of the beauty, ecosystem services, and scientific value they provide, mature forests are an invaluable resource. That is both why my sampling protocol is cautious, and why the site is important to the study. Because the climate record goes back to 1895, I seek trees that are at least that old, to obtain the longest data record possible, which will help me detect any divergence between growth and climate. Further, the long history of relatively disturbance-free growth eliminates the confounding factor of growth release due to disturbance-induced opening of the canopy. I, in turn, will provide baseline data that has not been reported for Colonial Point Hardwoods: an annual growth chronology for each species depicting population-wide annual growth, and models relating the relationship between growth and seasonal climate. Lab Methods Standard methods of dendrochronology will be used to prepare cores for analysis (Stokes and Smiley 1996). Once prepared, visual cross-dating will be used to assign a date to each tree ring (Stokes and Smiley 1996), and the process will be statistically confirmed with the program COFECHA (Grissino-Mayer 2001). Ring widths will then be measured with the program CooRecorder (version 9.0.1, Cybis Elektronik & DATA AB, Saltsjӧbaden, Sweden), and the raw ring widths will be de-trended in program ARSTAN (Cook and Holmes 1984). That is, the influence of age, size, and endogenous stand-disturbance will be attenuated by filtering the data with a cubic-smoothing spline. To compare growth-climate relationships along a latitudinal gradient, principal-component regression will be performed in the program DendroCLIM2002 (Biondi and Waikul 2004). Through this method a causal relationship between growth and climate data can be inferred. To obtain a complete dataset, climate data will be interpolated, because there is no weather station near Colonial Point Hardwoods that has continuously taken data since 1895. The data will be generated with the Oregon State University PRISM Climate Group’s website (http://prismmap.nacse.org/nn/) (Daly et al. 2008). The group uses spatially weighted data from weather stations throughout a region to generate 4-km gridded data. The correct grid is assigned by entering a site’s latitude and longitude. Of course, Colonial Pointe has a microclimate that is slightly different from the neighboring weather stations used to interpolate its climate data, but using PRISM is the best option for utilizing this important site, and PRISM-interpolated data have often been used in other tree-ring studies (e.g. Chhin and O’Brien 2015, Bishop et al. 2015). Based on Hypotheses 1 and 2, range-limit populations are expected to be more sensitive to climate. If that is indeed the case, then growth-temperature responses will be more positive at northern limits, and at southern limits growth-temperature responses will be more negative and growth-precipitation responses more positive. Those are the predicted results of principal-component regression. To project future growth of each population, I will obtain a parsimonious model—one that includes only the most influential monthly/seasonal climate variables—through forward stepwise multiple regression in program R (R Core Team 2013). Using the model and projections of future climate, I will project growth over the rest of this century. If range-limit proximity will indeed modulate climate-change responses, then ring-width projections will be larger in northern-limit and smaller in southern-limit populations than their respective historic sizes (Hypothesis 3). Finally, divergence will be tested for. Recall from the abstract that divergence is the phenomenon in which the historic relationship between growth and climate weakens over time. To test for this, model selection will proceed as above, but not over the entire record. An 1895–1979-based model—a historic one—will be used to predict climate from 1980–present. This corresponds with the warming that began in Michigan in 1980 (Andresen 2012). If linear regression reveals a non-significant relationship between predicted and observed recent climate, divergence did occur (Hypothesis 4), and tree-ring-based climate reconstruction in the Great Lakes Region will be viewed with more skepticism. Conclusion Those are the methods with which I will test for divergence, project future growth, and compare growth-climate relationships along a latitudinal gradient. I hope the reviewers of this proposal agree that the project is meritorious. After sampling from 36 populations and analyzing growth-climate relationships in 11 of them, I presented some of the preliminary results at Botany 2017, an annual meeting of several botany-related professional societies. The poster was recognized as the best in the physiology/ecophysiology category. Further, my formal proposal was accepted by my Ph.D. committee, allowing me to become an official candidate. If more background information, more methodological details, or preliminary results are desired by the reviewers, I would be quite happy to provide them, and I thank you for your consideration. Literature Cited (for both Abstract and Methods) Anderson BJ. 2005. The historical development of the tension zone concept in the Great Lakes region of North America. The Michigan Botanist. 44:127–38. Andresen JA 2012. Historical climate trends in Michigan and the Great Lakes Region. In Climate change in the Great Lakes Region: Navigating an Uncertain Future. Edited by T Dietz & D Bidwell. Michigan State University Press, East Lansing, Mich. Biondi F & Waikul K. 2004. DENDROCLIM2002: A C++ program for statistical calibration of climate signals in tree-ring chronologies. Comput. Geosci. 30:303–11. Bishop DA, Beier CM, Pederson N, Lawrence GB, Stella JC & Sullivan TJ. 2015. Regional growth decline of sugar maple (Acer saccharum) and its potential causes. Ecosphere. 6(10):179. Briffa KR & Jones PD. 1990. Basic chronology statistics and assessment. In Methods of Dendrochronology. Applications in the Environmental Sciences. Edited by ER Cook and LA Kairiukstis. Kluwer Academic, Dordrecht. Cheddadi R, Araújo MB, Maiorana L, Edwards M, Guisan A, Carré M, Chevalier M, & Pearman PB. 2016. Temperature range shifts for three European tree species over the last 10,000 years. Front. in Plant Sci. 7:1–13. Chhin S. & O’Brien J. 2015. Dendroclimatic analysis of red pine affected by Diplodia shoot blight in different latitudinal regions in Michigan. Canadian Journal of Forest Research. 45:1757-67. Cook ER & Holmes RL. 1984. Users Manual for Program ARSTAN. Laboratory of Tree-Ring Research, Tucson, Arizona, U.S.A. URL: https://www6.nancy.inra.fr/foret-bois-lerfob/Media/Fichier/Francois-Lebourgeois/Arstan-Manual. Daly C, Halbleib M, Smith JI, Gibson WP, Doggett MK, Taylor GH, Curtis J, & Pasteris PP. 2008. 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A global meta-analysis of treeline response to climate warming. Ecol. Lett. 12:1040–9. Jackson ST & Weng C. 1999. Late Quaternary extinction of a tree species in eastern North America. Proc, Natl, Acad, Sci. USA. 96:13847–52. Liu H, Williams AP, Allen CD, Guo D, Wu X, Anenkhonov OA, Liang E, Sandanov DV, Yin Y, & Qi Z. 2013. Rapid warming accelerates tree growth decline in semi-arid forests of Inner Asia. Global Change Biol. 19:2500–10. Parmesan C. 2006. Ecological responses to recent climate change. Annu. Rev. Ecol. Evo. Syst. 37:637–69. R Core Team. 2013. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL: http://www.R-project.org/. Shigo, AI & Hillis WF. 1973. Heartwood, discolored wood, and micro-organisms in living trees. Annual Review of Phytopathology. 11:197–222. Silva LCR, Sun G, Zhu-Barker X, Lian Q, Wu N, & Horwath WR. 2016. Tree growth acceleration and expansion of alpine forests: The synergistic effect of atmospheric and edaphic change. Sci. Adv. 2 (8):e1501302. Stokes MA & Smiley TL. 1996. An introduction to tree-ring dating. The University of Arizona Press, Tucson, Arizona. Tsen EWJ, Sitzia T, & Webber BL. 2016. To core, or not to core: the impact of coring on tree health and a best-practice framework for collecting dendrochronological information from living trees. Biol. Revs. Camb. Philos. Soc. 91:899–924. Willis CG, Ruhfel B, Primack RB, Miller-Rushing AJ, & Davis CC. 2008. Phylogenetic patterns of species loss in Thoreau’s woods are driven by climate change. Proc, Natl, Acad, Sci. USA. 105:17029–33.