Nonstructural carbohydrate dynamics' relationship to leaf development under varying environments.

Leaf-out in temperate forests is a critical transition point each spring and advancing with global change. The mechanism linking phenological variation to external cues is poorly understood. Nonstructural carbohydrate (NSC) availability may be key. Here, we use branch cuttings from northern red oak (Quercus rubra) and measure NSCs throughout bud development in branch tissue. Given genes and environment influence phenology, we placed branches in an arrayed factorial experiment (three temperatures × two photoperiods, eight genotypes) to examine their impact on variation in leaf-out timing and corresponding NSCs. Despite significant differences in leaf-out timing between treatments, NSC patterns were much more consistent, with all treatments and genotypes displaying similar NSC concentrations across phenophases. Notably, the moderate and hot temperature treatments reached the same NSC concentrations and phenophases at the same growing degree days (GDD), but 20 calendar days apart, while the cold treatment achieved only half the GDD of the other two. Our results suggest that NSCs are coordinated with leaf-out and could act as a molecular clock, signaling to cells the passage of time and triggering leaf development to begin. This link between NSCs and budburst is critical for improving predictions of phenological timing.

The drivers of intraspecific trait variation and their implications for future tree productivity and survival.

Forests are facing unprecedented levels of stress from pest and disease outbreaks, disturbance, fragmentation, development, and a changing climate. These selective agents act to alter forest composition from regional to cellular levels. Thus, a central challenge for understanding how forests will be impacted by future change is how to integrate across scales of biology. Phenotype, or an observable trait, is the product of an individual's genes (G) and the environment in which an organism lives (E). To date, researchers have detailed how environment drives variation in tree phenotypes over long time periods (e.g., long-term ecological research sites [LTERs]) and across large spatial scales (e.g., flux network). In parallel, researchers have discovered the genes and pathways that govern phenotypes, finding high degrees of genetic control and signatures of local adaptation in many plant traits. However, the research in these two areas remain largely independent of each other, hindering our ability to generate accurate predictions of plant response to environment, an increasingly urgent need given threats to forest systems. I present the importance of both genes and environment in determining tree responses to climate stress. I highlight why the difference between G versus E in driving variation is critical for our understanding of climate responses, then propose means of accelerating research that examines G and E simultaneously by leveraging existing long-term, large-scale phenotypic data sets from ecological networks and adding newly affordable sequence (-omics) data to both drill down to find the genes and alleles influencing phenotypes and scale up to find how patterns of demography and local adaptation may influence future response to change.

Global variation in nonstructural carbohydrate stores in response to climate.

Woody plant species store nonstructural carbohydrates (NSCs) for many functions. While known to buffer against fluctuations in photosynthetic supply, such as at night, NSC stores are also thought to buffer against environmental extremes, such as drought or freezing temperatures by serving as either back-up energy reserves or osmolytes. However, a clear picture of how NSCs are shaped by climate is still lacking. Here, we update and leverage a unique global database of seasonal NSC storage measurements to examine whether maximum total NSC stores and the amount of soluble sugars are associated with clinal patterns in low temperatures or aridity, indicating they may confer a benefit under freezing or drought conditions. We examine patterns using the average climate at each study site and the unique climatic conditions at the time and place in which the sample was taken. Altogether, our results support the idea that NSC stores act as critical osmolytes. Soluble Sugars increase with both colder and drier conditions in aboveground tissues, indicating they can plastically increase a plants' tolerance of cold or arid conditions. However, maximum total NSCs increased, rather than decreased, with average site temperature and had no relationship to average site aridity. This result suggests that the total amount of NSC a plant stores may be more strongly determined by its capacity to assimilate carbon than by environmental stress. Thus, NSCs are unlikely to serve as reservoir of energy. This study is the most comprehensive synthesis to date of global NSC variation in relation to climate and supports the idea that NSC stores likely serve as buffers against environmental stress. By clarifying their role in cold and drought tolerance, we improve our ability to predict plant response to environment.

Plant carbohydrate storage: intra- and inter-specific trade-offs reveal a major life history trait.

Trade-offs among carbon sinks constrain how trees physiologically, ecologically, and evolutionarily respond to their environments. These trade-offs typically fall along a productive growth to conservative, bet-hedging continuum. How nonstructural carbohydrates (NSCs) stored in living tree cells (known as carbon stores) fit in this trade-off framework is not well understood. We examined relationships between growth and storage using both within species genetic variation from a common garden, and across species phenotypic variation from a global database. We demonstrate that storage is actively accumulated, as part of a conservative, bet-hedging life history strategy. Storage accumulates at the expense of growth both within and across species. Within the species Populus trichocarpa, genetic trade-offs show that for each additional unit of wood area growth (in cm2 yr-1 ) that genotypes invest in, they lose 1.2 to 1.7 units (mg g-1 NSC) of storage. Across species, for each additional unit of area growth (in cm2 yr-1 ), trees, on average, reduce their storage by 9.5% in stems and 10.4% in roots. Our findings impact our understanding of basic plant biology, fit storage into a widely used growth-survival trade-off spectrum describing life history strategy, and challenges the assumptions of passive storage made in ecosystem models today.

Adaptive variation and plasticity in non-structural carbohydrate storage in a temperate tree species.

Trees' total amount of non-structural carbohydrate (NSC) stores and the proportion of these stores residing as insoluble starch are vital traits for individuals living in variable environments. However, our understanding of how stores vary in response to environmental stress is poorly understood as the genetic component of storage is rarely accounted for in studies. Here, we quantified variation in NSC traits in branch samples taken from over 600 clonally transplanted black cottonwood (Populus trichocarpa) trees grown in two common gardens. We found heritable variation in both total NSC stores and the proportion of stores in starch (H2TNC  = 0.19, H2PropStarch  = 0.31), indicating a substantial genetic component of variation. In addition, we found high amounts of plasticity in both traits in response to cold temperatures and significant genotype-by-environment (GxE) interactions in the total amount of NSC stored (54% of P is GxE). This finding of high GxE indicates extensive variation across trees in their response to environment, which may explain why previous studies of carbohydrate stores' responses to stress have failed to converge on a consistent pattern. Overall, we found high amounts of environmental and genetic variation in NSC storage concentrations, which may bolster species against future climate change.

A multidimensional selective landscape drives adaptive divergence between and within closely related Phlox species.

Selection causes local adaptation across populations within species and simultaneously divergence between species. However, it is unclear if either the force of or the response to selection is similar across these scales. We show that natural selection drives divergence between closely related species in a pattern that is distinct from local adaptation within species. We use reciprocal transplant experiments across three species of Phlox wildflowers to characterize widespread adaptive divergence. Using provenance trials, we also find strong local adaptation between populations within a species. Comparing divergence and selection between these two scales of diversity we discover that one suite of traits predicts fitness differences between species and that an independent suite of traits predicts fitness variation within species. Selection drives divergence between species, contributing to speciation, while simultaneously favoring extensive diversity that is maintained across populations within a species. Our work demonstrates how the selection landscape is complex and multidimensional.

The value of long-term ecological research for evolutionary insights.

Scientists must have an integrative understanding of ecology and evolution across spatial and temporal scales to predict how species will respond to global change. Although comprehensively investigating these processes in nature is challenging, the infrastructure and data from long-term ecological research networks can support cross-disciplinary investigations. We propose using these networks to advance our understanding of fundamental evolutionary processes and responses to global change. For ecologists, we outline how long-term ecological experiments can be expanded for evolutionary inquiry, and for evolutionary biologists, we illustrate how observed long-term ecological patterns may motivate new evolutionary questions. We advocate for collaborative, multi-site investigations and discuss barriers to conducting evolutionary work at network sites. Ultimately, these networks offer valuable information and opportunities to improve predictions of species' responses to global change.

Evidence of nutrient translocation in response to smoke exposure by the East African ant acacia, Vachellia drepanolobium.

Fire is a major selective force on arid grassland communities, favoring traits such as the smoke-induced seed germination response seen in a wide variety of plant species. However, little is known about the relevance of smoke as a cue for plants beyond the seedling stage.We exposed a fire-adapted savanna tree, Vachellia (=Acacia) drepanolobium, to smoke and compared nutrient concentrations in leaf and root tissues to unexposed controls. Experiments were performed on three age cohorts: 2-year-old, 9-month-old, and 3-month-old plants.For the 2-year-old plants exposed to smoke, carbon and nitrogen concentrations were lower in the leaves and higher in the roots than controls. Less pronounced trends were found for boron and magnesium.In contrast, smoke-exposed 3-month-old plants had lower root nitrogen concentrations than controls. No significant differences were found in the 9-month-old plants, and no significant shifts in other nutrient concentrations were observed between plant tissues for any of the three age cohorts. Synthesis: Our findings are consistent with smoke-induced translocation of nutrients from leaves to roots in 2-year-old V. drepanolobium. This could represent a novel form of fire adaptation, with variation over the course of plant development. The translocation differences between age cohorts highlight the need to investigate smoke response in older plants of other species. Accounting for this adaptation could better inform our understanding of savanna community structure and nutrient flows under fire regimes altered by anthropogenic land use and climate change.

Protocol for Projecting Allele Frequency Change under Future Climate Change at Adaptive-Associated Loci.

We describe how to predict population-level allele frequency change at loci associated with locally adapted traits under future climate conditions. Our method can identify populations that are at higher risk of local extinction and those that might be prime targets for conservation intervention. We draw on previously developed community ecology statistical methods and apply them in novel ways to plant genomes. While a powerful diagnostic tool, our method requires a wealth of genomic data for use. For complete details on the use and execution of this protocol, please refer to Blumstein et al. (2020).

A New Perspective on Ecological Prediction Reveals Limits to Climate Adaptation in a Temperate Tree Species.

Forests absorb a large fraction of anthropogenic CO2 emission, but their ability to continue to act as a sink under climate change depends in part on plant species undergoing rapid adaptation. Yet models of forest response to climate change currently ignore local adaptation as a response mechanism. Thus, considering the evolution of intraspecific trait variation is necessary for reliable, long-term species and climate projections. Here, we combine ecophysiology and predictive climate modeling with analyses of genomic variation to determine whether sugar and starch storage, energy reserves for trees under extreme conditions, have the heritable variation and genetic diversity necessary to evolve in response to climate change within populations of black cottonwood (Populus trichocarpa). Despite current patterns of local adaptation and extensive range-wide heritable variation in storage, we demonstrate that adaptive evolution in response to climate change will be limited by a lack of heritable variation within northern populations and by a need for extreme genetic changes in southern populations. Our method can help design more targeted species management interventions and highlights the power of using genomic tools in ecological prediction to scale from molecular to regional processes to determine the ability of a species to respond to future climates.