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Trait Correlations Equalize Spread Velocity Across Plant Life Histories

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Trait Correlations Equalize Spread Velocity Across Plant Life Histories UC Merced UC Merced Previously Published Works Title Trait correlations equalize spread velocity across plant life histories Permalink https://escholarship.org/uc/item/1tn571nk Journal GLOBAL ECOLOGY AND BIOGEOGRAPHY, 26(12) ISSN 1466-822X Authors Lustenhouwer, Nicky Moran, Emily V Levine, Jonathan M Publication Date 2017-12-01 DOI 10.1111/geb.12662 License https://creativecommons.org/licenses/by-nc-nd/4.0/ 4.0 Peer reviewed eScholarship.org Powered by the California Digital Library University of California Received: 23 June 2017 | Revised: 23 August 2017 | Accepted: 25 August 2017 DOI: 10.1111/geb.12662 RESEARCH PAPERS Trait correlations equalize spread velocity across plant life histories Nicky Lustenhouwer1 | Emily V. Moran2 | Jonathan M. Levine1 1Institute of Integrative Biology, ETH Zurich, Universitätstrasse 16, 8092 Zurich, Abstract Switzerland Aim: Forecasting species migration with climate change and the advance of biological invasions 2 Life & Environmental Sciences, University requires a better understanding of species’ relative migration capacity. Although theory predicts of California Merced, 5200 Lake Road, Merced, California that species combining high fecundity and dispersal with early maturation should spread the fast- est, possible correlations between these traits greatly complicate predictions of species’ relative Correspondence spread velocity. We asked whether the demographic and dispersal rates controlling plant popula- Nicky Lustenhouwer, Institute of tion spread are correlated across species, and which observed association of these traits leads to Integrative Biology, ETH Zurich, Universitätstrasse 16, 8092 Zurich, the fastest spread. Switzerland. Location: Worldwide. Email: [email protected] Time period: Current. Funding information Swiss National Science Foundation, Grant/ Major taxa studied: Eighty species of herbaceous and woody plants from 35 families and 64 Award Number: 31003A_141025; UC genera. Merced Methods: We examined the relationships between age at maturity, dispersal and fecundity for 80 Editor: Greg Jordan plant species, ranging from annual herbs to trees. We incorporated these rates into a model predict- ing spread velocities, in order to estimate species’ spread capacity as a function of their life history. Results: Across species, age at maturity was positively associated with both dispersal and fecun- dity. Given that these traits have opposing effects on spread, our models predict that species widely spaced along an age-at-maturity gradient should spread at comparable rates. This result was driven by variation between rather than within life-forms; the traits controlling spread were not correlated within annual herbs, perennial herbs or trees. The predicted spread velocities for these plant life-forms overlapped considerably, although on average, trees were predicted to spread faster than herbaceous species. Main conclusions: Our results suggest that very different plant life histories allow for similar rates of biological invasion or native species migration under climate change. Determining where species fall within the correlated suite of traits controlling spread might provide the most effective way to predict relative spread velocities. KEYWORDS age at maturity, demography, dispersal, fecundity, migration, population spread, range expansion 1 | INTRODUCTION Roy, & Thomas, 2011; Lenoir, Gegout, Marquet, Ruffray, & Brisse, 2008; Parmesan, 2006), yet others show no evidence of migration at The persistence of many plant populations in a warming climate all (Bertrand et al., 2011; Corlett & Westcott, 2013; Zhu, Woodall, & depends on their ability to migrate (Aitken, Yeaman, Holliday, Wang, & Clark, 2012). This variation among species in the speed and extent of Curtis-McLane, 2008; Thuiller et al., 2008). Some taxa have already range shifts is expected to create no-analogue communities, where shifted their ranges to track climate change (Chen, Hill, Ohlemuller,€ novel interactions may have large impacts on species persistence Global Ecol Biogeogr.2017;1–10. wileyonlinelibrary.com/journal/geb VC 2017 John Wiley & Sons Ltd | 1 2 | LUSTENHOUWER ET AL. (Alexander, Diez, & Levine, 2015; Urban, Tewksbury, & Sheldon, 2012). such as individual-based simulations (Harris, Stanford, Edwards, Travis, Variation in spread among taxa is also a prominent feature of biological & Park, 2011), analytical integrodifference equations (Caplat, Nathan, & invasions, with some exotic species spreading rapidly across the land- Buckley, 2012), or a combination of both (Travis, Harris, Park, & scape, whereas others advance more slowly (Pysek & Hulme, 2005). A Bullock, 2011), can be field parameterized for individual species and better understanding of species’ relative migration capacity would be a often produce accurate forecasts of migration rates. However, they are useful addition to efforts to predict the composition of future ecologi- usually restricted to one or a few species for which the extensive data cal communities and the success of biological invasions. needs are met (Urban et al., 2016). Species distribution models (SDMs) Theory shows that the highest spread velocities can be expected present an alternative approach and can make predictions with compa- for species combining far dispersal, high fecundity and a short time to rable methods for a variety of species. However, in SDMs future ranges maturity (Clark, 1998; Okubo & Levin, 1980; Skellam, 1951). However, are forecast based on climatic tolerances (Guisan & Thuiller, 2005), and empirical evidence suggests that these traits are correlated across spe- the predicted ability of species to fill that future range tends to be cies, which greatly complicates predictions of which species spread based on separate estimates of migration ability (e.g., Iverson, Schwartz, fastest. Trees, for example, often mature late (which slows spread), but & Prasad, 2004), rather than spatial population dynamics (but see J. disperse their seeds to greater distances than do most herbaceous life- Pagel & Schurr, 2012; Schurr et al., 2012). forms (Cain, Damman, & Muir, 1998; Svenning & Sandel, 2013), owing What is needed are modelling approaches that can be applied to greater height, well-developed dispersal structures (Venable & Levin, across a range of taxa, based on widely available data (Singer et al., 1983) and a lower seed terminal velocity (Endels et al., 2007). How- 2016), to provide a standardized measure of species’ spread capacity. ever, the vast majority of past studies have been based on categorical Such studies could forecast spread rates for a wider range of species plant life histories (life-forms such as herbs and trees) or proxies of dis- than possible with the complex demographic models requiring intensive persal ability (seed dispersal mode or terminal velocity) only, and an field parameterization (e.g., Jongejans et al., 2008), while still taking exact quantification of relationships between the traits controlling into account species-specific demographic and dispersal rates. Indeed, spread across species with different life histories is still lacking. If dis- Hemrova, Bullock, Hooftman, White, and Munzbergov€ a(2017)recently persal, fecundity and time to maturity are indeed correlated across taxa incorporated demographic data and estimates of wind dispersal into and life-forms, the key question becomes, which observed combination mathematical models of population spread to predict the invasion of these traits spreads the fastest? For example, will an annual plant velocity of 16 short-lived grassland herbs. Their finding that early matu- with early maturation, but moderate fecundity and dispersal advance ration was associated with faster spread merits exploration across the its range more rapidly (or slowly) than a later-maturing shrub with full range of plant life histories, including annuals, perennials, shrubs greater fecundity and dispersal? and trees. In principle, one can answer these questions with analyses of pub- Here, we ask: (a) whether the major life history traits determining lished spread velocities based on reconstructions of historical migra- population spread (age at maturity, dispersal and fecundity) are corre- tions, or with predicted spread velocities from models parameterized lated across species; (b) which observed association of these traits with contemporary demographic and dispersal information (Clark, leads to the fastest spread; and (c) whether these correlations cause Lewis, & Horvath, 2001; Lenoir et al., 2008; McLachlan, Clark, & different plant life-forms (annual herbs, perennial herbs, shrubs and Manos, 2005; Nathan, Horvitz, et al., 2011). However, as explained in trees) to spread at different rates. To address these questions, we the next two paragraphs, applying either approach to many species, as assessed the relationship between the three determinants of popula- required for comparative studies of spread capacity, is challenging tion spread for 80 plant species ranging widely in life-form, seed disper- because of the scarcity of relevant data. sal vector and geographical location, controlling for phylogenetic Palynological and molecular studies of post-glacial expansion typi- relatedness. We then incorporated these values into a stochastic model cally focus on temperate, wind-pollinated trees (Delcourt & Delcourt, of population spread to present a standardized estimate of spread 1987; McLachlan et al., 2005); much less is known about herbaceous velocity as a function of plant species life history.
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