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1. Impact of rainfall seasonality on intraspecific trait variation in a shrub from a Mediterranean climate

   https://doi.org/10.1111/1365-2435.13533  

   Moore, Timothy E. ; Jones, Cynthia S. ; Chong, Caroline ; Schlichting, Carl D. ; Seymour, ed., Colleen ( February 2020 , Functional Ecology)

   Selection pressures along climate gradients give rise to predictable variation in plant functional traits of individual species suggestive of local adaptation. Species whose ranges include winter rainfall, Mediterranean climates, or other strongly seasonal climates, may be exposed to divergent selection pressures at different ends of seasonality gradients.

   Here, we evaluate how rainfall seasonality in conjunction with other key climatic variables impacts patterns of trait variation inPelargonium scabrum, a woody shrub from the Greater Cape Floristic Region of South Africa. This biodiversity hotspot encompasses a Mediterranean climate (wet winters and hot, dry summers) and displays steep gradients in temperature and water availability.

   We used Bayesian regression models to evaluate leaf trait–trait and trait–climate relationships among 26 populations. Models included rainfall seasonality and its interaction with other climate variables (mean annual temperature, mean annual precipitation and potential evapotranspiration) as predictors to test for the impact of climate variation on three leaf traits: size, dissection and leaf mass per area (LMA). We evaluated model explanatory power by calculating BayesianR²values, and predictive power via leave‐one‐out cross‐validation.

   Trait–trait associations were modulated by rainfall seasonality, including a reversal in the relationship between leaf size and dissection depending on the proportion of rain received in winter. Trait–climate models were improved by including rainfall seasonality as a predictor for both explanatory and predictive power. For leaf dissection and LMA, we detected significant interactions between rainfall seasonality and other environmental variables, leading to reversals in the relationships between these traits and the three environmental variables depending on the proportion of winter rainfall.

   Differences in the timing of rainfall, coupled with strong differences in the covariation of climate variables, impose divergent selection pressures onP. scabrumpopulations resulting in divergence of trait values, trait integration and responses to climate gradients. These patterns are consistent with local adaptation ofP. scabrumpopulations mediated by the interactions between temperature and the amount and timing of rainfall. Species arrayed along broad climate gradients represent an excellent opportunity for investigating patterns of trait variation and abundances and distributions of species in relation to future changes in climate.

   A freePlain Language Summarycan be found within the Supporting Information of this article.

    

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2. Predicting intraspecific trait variation among California's grasses

   https://doi.org/10.1111/1365-2745.13673  

   Sandel, Brody ; Pavelka, Claire ; Hayashi, Thomas ; Charles, Lachlan ; Funk, Jennifer ; Halliday, Fletcher W. ; Kandlikar, Gaurav S. ; Kleinhesselink, Andrew R. ; Kraft, Nathan J. B. ; Larios, Loralee ; et al ( May 2021 , Journal of Ecology)

   Plant species can show considerable morphological and functional variation along environmental gradients. This intraspecific trait variation (ITV) can have important consequences for community assembly, biotic interactions, ecosystem functions and responses to global change. However, directly measuring ITV across many species and wide geographic areas is often infeasible. Thus, a method to predict spatial variation in a species’ functional traits could be valuable.

   We measured specific leaf area (SLA), height and leaf area (LA) of grasses across California, covering 59 species at 230 sampling locations. We asked how these traits change along climate gradients within each species and used machine learning to predict local trait values for any species at any location based on phylogenetic position, local climate and that species’ mean traits. We then examined how much these local predictions alter patterns of assemblage‐level trait variation across the state.

   Most species exhibited higher SLA and grew taller at higher temperatures and produced larger leaves in drier conditions. The random forests predicted spatial variation in functional traits very accurately, with correlations up to 0.97. Because trait records were spatially biased towards warmer areas, and these areas tend to have higher SLA individuals within each species, species means of SLA were upwardly biased. As a result, using species means over‐estimates SLA in the cooler regions of the state. Our results also suggest that height may be substantially under‐predicted in the warmest areas.

   Synthesis. Using only species mean traits to characterize the functional composition of communities risks introducing substantial error into trait‐based estimates of ecosystem properties including decomposition rates or NPP. The high performance of random forests in predicting local trait values provides a way forward for estimating high‐resolution patterns of ITV without a massive data collection effort.

    

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3. Adaptive trait syndromes along multiple economic spectra define cold and warm adapted ecotypes in a widely distributed foundation tree species

   https://doi.org/10.1111/1365-2745.13557  

   Blasini, Davis E. ; Koepke, Dan F. ; Grady, Kevin C. ; Allan, Gerard J. ; Gehring, Catherine A. ; Whitham, Thomas G. ; Cushman, Samuel A. ; Hultine, Kevin R. ; Battipaglia, ed., Giovanna ( December 2020 , Journal of Ecology)

   The coordination of traits from individual organs to whole plants is under strong selection because of environmental constraints on resource acquisition and use. However, the tight coordination of traits may provide underlying mechanisms of how locally adapted plant populations can become maladapted because of climate change.

   To better understand local adaptation in intraspecific trait coordination, we studied trait variability in the widely distributed foundation tree species,Populus fremontiiusing a common garden near the mid‐elevational point of this species distribution. We examined 28 traits encompassing four spectra: phenology, leaf economic spectrum (LES), whole‐tree architecture (Corner's Rule) and wood economic spectrum (WES).

   Based on adaptive syndrome theory, we hypothesized that trait expression would be coordinated among and within trait spectra, reflecting local adaptation to either exposure to freeze‐thaw conditions in genotypes sourced from high‐elevation populations or exposure to extreme thermal stress in genotypes sourced from low‐elevation populations.

   High‐elevation genotypes expressed traits within the phenology and WES that limit frost exposure and tissue damage. Specifically, genotypes sourced from high elevations had later mean budburst, earlier mean budset, higher wood densities, higher bark fractions and smaller xylem vessels than their low‐elevation counterparts. Conversely, genotypes sourced from low elevations expressed traits within the LES that prioritized hydraulic efficiency and canopy thermal regulation to cope with extreme heat exposure, including 40% smaller leaf areas, 67% higher stomatal densities and 34% higher mean theoretical maximum stomatal conductance. Low‐elevation genotypes also expressed a lower stomatal control over leaf water potentials that subsequently dropped to pressures that could induce hydraulic failure.

   Synthesis. Our results suggest thatPopulus fremontiiexpresses a high degree of coordination across multiple trait spectra to adapt to local climate constraints on photosynthetic gas exchange, growth and survival. These results, therefore, increase our mechanistic understanding of local adaptation and the potential effects of climate change that in turn, improves our capacity to identify genotypes that are best suited for future restoration efforts.

    

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4. Quantifying within‐species trait variation in space and time reveals limits to trait‐mediated drought response

   https://doi.org/10.1111/1365-2435.14112  

   Kerr, Kelly L. ; Anderegg, Leander D. L. ; Zenes, Nicole ; Anderegg, William R. L. ( June 2022 , Functional Ecology)

   Climate change is stressing many forests around the globe, yet some tree species may be able to persist through acclimation and adaptation to new environmental conditions. The ability of a tree to acclimate during its lifetime through changes in physiology and functional traits, defined here as its acclimation potential, is not well known.

   We investigated the acclimation potential of trembling aspenPopulus tremuloidesand ponderosa pinePinus ponderosatrees by examining within‐species variation in drought response functional traits across both space and time, and how trait variation influences drought‐induced tree mortality. We measured xylem tension, morphological traits and physiological traits on mature trees in southwestern Colorado, USA across a climate gradient that spanned the distribution limits of each species and 3 years with large differences in climate.

   Trembling aspen functional traits showed high within‐species variation, and osmotic adjustment and carbon isotope discrimination were key determinants for increased drought tolerance in dry sites and in dry years. However, trembling aspen trees at low elevation were pushed past their drought tolerance limit during the severe 2018 drought year, as elevated mortality occurred. Higher specific leaf area during drought was correlated with higher percentages of canopy dieback the following year. Ponderosa pine functional traits showed less within‐species variation, though osmotic adjustment was also a key mechanism for increased drought tolerance. Remarkably, almost all traits varied more year‐to‐year than across elevation in both species.

   Our results shed light on the scope and limits of intraspecific trait variation for mediating drought responses in key southwestern US tree species and will help improve our ability to model and predict forest responses to climate change.

   Read the freePlain Language Summaryfor this article on the Journal blog.

    

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5. Complex trait‒environment relationships underlie the structure of forest plant communities

   https://doi.org/10.1111/1365-2745.13757  

   Rolhauser, Andrés G. ; Waller, Donald M. ; Tucker, Caroline M. ( August 2021 , Journal of Ecology)

   Traits differentially adapt plant species to particular conditions generating compositional shifts along environmental gradients. As a result, community‐scale trait values show concomitant shifts, termed trait‒environment relationships. Trait‒environment relationships are often assessed by evaluating community‐weighted mean (CWM) traits observed along environmental gradients. Regression‐based approaches (CWMr) assume that local communities exhibit traits centred at a single optimum value and that traits do not covary meaningfully. Evidence suggests that the shape of trait‒abundance relationships can vary widely along environmental gradients—reflecting complex interactions—and traits are usually interrelated. We used a model that accounts for these factors to explore trait‒environment relationships in herbaceous forest plant communities in Wisconsin (USA).

   We built a generalized linear mixed model (GLMM) to analyse how abundances of 185 species distributed among 189 forested sites vary in response to four functional traits (vegetative height—VH, leaf size—LS, leaf mass per area—LMA and leaf carbon content), six environmental variables describing overstorey, soil and climate conditions, and their interactions. The GLMM allowed us to assess the nature and relative strength of the resulting 24 trait‒environment relationships. We also compared results between GLMM and CWMr to explore how conclusions differ between approaches.

   The GLMM identified five significant trait‒environment relationships that together explain ~40% of variation in species abundances across sites. Temperature appeared as a key environmental driver, with warmer and more seasonal sites favouring taller plants. Soil texture and temperature seasonality affected LS and LMA; seasonality effects on LS and LMA were nonlinear, declining at more seasonal sites. Although often assumed for CWMr, only some traits under certain conditions had centred optimum trait‒abundance relationships. CWMr more liberally identified (13) trait‒environment relationships as significant but failed to detect the temperature seasonality‒LMA relationship identified by the GLMM.

   Synthesis. Although GLMM represents a more methodologically complex approach than CWMr, it identified a reduced set of trait‒environment relationships still capable of accounting for the responses of forest understorey herbs to environmental gradients. It also identified separate effects of mean and seasonal temperature on LMA that appear important in these forests, generating useful insights and supporting broader application of GLMM approach to understand trait‒environment relationships.

    

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