Lineage-based functional types: characterising functional diversity to enhance the representation of ecological behaviour in Land Surface Models

Allometric relationships and trade-offs in 11 common Mediterranean-climate grasses

Biomass allocation in plants is the foundation for understanding dynamics in ecosystem carbon balance, species competition, and plant-environment interactions. However, existing work on plant allometry has mainly focused on trees, with fewer studies having developed allometric equations for grasses. Grasses with different life histories can vary in their carbon investment by prioritizing the growth of specific organs to survive, outcompete co-occurring plants, and ensure population persistence. Further, because grasses are important fuels for wildfire, the lack of grass allocation data adds uncertainty to process-based models that relate plant physiology to wildfire dynamics. To fill this gap, we conducted a greenhouse experiment with 11 common California grasses varying in photosynthetic pathway and growth form. We measured plant sizes and harvested above- and belowground biomass throughout the life cycle of annual species, while for the establishment stage of perennial grasses to quantify allometric relationships for leaf, stem, and root biomass, as well as plant height and canopy area. We used basal diameter as a reference measure of plant size. Overall, basal diameter is the best predictor for leaf and stem biomass, height, and canopy area. Including height as another predictor can improve model accuracy in predicting leaf and stem biomass and canopy area. Fine root biomass is a function of leaf biomass alone. Species vary in their allometric relationships, with most variation occurring for plant height, canopy area, and stem biomass. We further explored potential trade-offs in biomass allocation across species between leaf and fine root, leaf and stem, and allocation to reproduction. Consistent with our expectation, we found that fast-growing plants allocated a greater fraction to reproduction. Additionally, plant height and specific leaf area negatively influenced the leaf-to-stem ratio. However, contrary to our hypothesis, there were no differences in root-to-leaf ratio between perennial and annual or C4 and C3 plants. Our study provides species-specific and functional-type-specific allometry equations for both above- and belowground organs of 11 common California grass species, enabling nondestructive biomass assessment in California grasslands. These allometric relationships and trade-offs in carbon allocation across species can improve ecosystem model predictions of grassland species interactions and environmental responses through differences in morphology.

miR156-PvSPL2 controls culm development by transcriptional repression of switchgrass CYTOKININ OXIDASE/DEHYDROGENASE4

Culm development in grasses can be controlled by both miR156 and cytokinin. However, the crosstalk between the miR156-SPL module and the cytokinin metabolic pathway remains largely unknown. Here, we found CYTOKININ OXIDASE/DEHYDROGENASE4 (PvCKX4) plays a negative regulatory role in culm development of the bioenergy grass Panicum virgatum (switchgrass). Overexpression of PvCKX4 in switchgrass reduced the internode diameter and length without affecting tiller number. Interestingly, we also found that PvCKX4 was always upregulated in miR156 overexpressing (miR156OE) transgenic switchgrass lines. Additionally, upregulation of either miR156 or PvCKX4 in switchgrass reduced the content of isopentenyl adenine (iP) without affecting trans-zeatin (tZ) accumulation. It is consistent with the evidence that the recombinant PvCKX4 protein exhibited much higher catalytic activity against iP than tZ in vitro. Furthermore, our results showed that miR156-targeted SPL2 bound directly to the promoter of PvCKX4 to repress its expression. Thus, alleviating the SPL2-mediated transcriptional repression of PvCKX4 through miR156 overexpression resulted in a significant increase in cytokinin degradation and impaired culm development in switchgrass. On the contrary, suppressing PvCKX4 in miR156OE transgenic plants restored iP content, internode diameter, and length to wild-type levels. Most strikingly, the double transgenic lines retained the same increased tiller numbers as the miR156OE transgenic line, which yielded more biomass than the wild type. These findings indicate that the miR156-SPL module can control culm development through transcriptional repression of PvCKX4 in switchgrass, which provides a promising target for precise design of shoot architecture to yield more biomass from grasses.

Accounting for herbaceous communities in process-based models will advance our understanding of "grassy" ecosystems

Grassland and other herbaceous communities cover significant portions of Earth's terrestrial surface and provide many critical services, such as carbon sequestration, wildlife habitat, and food production. Forecasts of global change impacts on these services will require predictive tools, such as process-based dynamic vegetation models. Yet, model representation of herbaceous communities and ecosystems lags substantially behind that of tree communities and forests. The limited representation of herbaceous communities within models arises from two important knowledge gaps: first, our empirical understanding of the principles governing herbaceous vegetation dynamics is either incomplete or does not provide mechanistic information necessary to drive herbaceous community processes with models; second, current model structure and parameterization of grass and other herbaceous plant functional types limits the ability of models to predict outcomes of competition and growth for herbaceous vegetation. In this review, we provide direction for addressing these gaps by: (1) presenting a brief history of how vegetation dynamics have been developed and incorporated into earth system models, (2) reporting on a model simulation activity to evaluate current model capability to represent herbaceous vegetation dynamics and ecosystem function, and (3) detailing several ecological properties and phenomena that should be a focus for both empiricists and modelers to improve representation of herbaceous vegetation in models. Together, empiricists and modelers can improve representation of herbaceous ecosystem processes within models. In so doing, we will greatly enhance our ability to forecast future states of the earth system, which is of high importance given the rapid rate of environmental change on our planet.

Capturing patterns of evolutionary relatedness with reflectance spectra to model and monitor biodiversity

Biogeographic history can set initial conditions for vegetation community assemblages that determine their climate responses at broad extents that land surface models attempt to forecast. Numerous studies have indicated that evolutionarily conserved biochemical, structural, and other functional attributes of plant species are captured in visible-to-short wavelength infrared, 400 to 2,500 nm, reflectance properties of vegetation. Here, we present a remotely sensed phylogenetic clustering and an evolutionary framework to accommodate spectra, distributions, and traits. Spectral properties evolutionarily conserved in plants provide the opportunity to spatially aggregate species into lineages (interpreted as "lineage functional types" or LFT) with improved classification accuracy. In this study, we use Airborne Visible/Infrared Imaging Spectrometer data from the 2013 Hyperspectral Infrared Imager campaign over the southern Sierra Nevada, California flight box, to investigate the potential for incorporating evolutionary thinking into landcover classification. We link the airborne hyperspectral data with vegetation plot data from 1372 surveys and a phylogeny representing 1,572 species. Despite temporal and spatial differences in our training data, we classified plant lineages with moderate reliability (Kappa = 0.76) and overall classification accuracy of 80.9%. We present an assessment of classification error and detail study limitations to facilitate future LFT development. This work demonstrates that lineage-based methods may be a promising way to leverage the new-generation high-resolution and high return-interval hyperspectral data planned for the forthcoming satellite missions with sparsely sampled existing ground-based ecological data.

Optimal coordination and reorganization of photosynthetic properties in C4 grasses

Each of >20 independent evolutions of C₄ photosynthesis in grasses required reorganization of the Calvin-Benson-cycle (CB-cycle) within the leaf, along with coordination of C₄ -cycle enzymes with the CB-cycle to maximize CO₂ assimilation. Considering the vast amount of time over which C₄ evolved, we hypothesized (i) trait divergences exist within and across lineages with both C₄ and closely related C₃ grasses, (ii) trends in traits after C₄ evolution yield the optimization of C₄ through time, and (iii) the presence/absence of trends in coordination between the CB-cycle and C₄ -cycle provides information on the strength of selection. To address these hypotheses, we used a combination of optimality modelling, physiological measurements and phylogenetic-comparative-analysis. Photosynthesis was optimized after the evolution of C₄ causing diversification in maximal assimilation, electron transport, Rubisco carboxylation, phosphoenolpyruvate carboxylase and chlorophyll within C₄ lineages. Both theory and measurements indicated a higher light-reaction to CB-cycle ratio (J_atpmax /V_cmax ) in C₄ than C₃ . There were no evolutionary trends with photosynthetic coordination between the CB-cycle, light reactions and the C₄ -cycle, suggesting strong initial selection for coordination. The coordination of CB-C₄ -cycles (V_pmax /V_cmax ) was optimal for CO₂ of 200 ppm, not to current conditions. Our model indicated that a higher than optimal V_pmax /V_cmax affects assimilation minimally, thus lessening recent selection to decrease V_pmax /V_cmax .

Molecular, cellular, and developmental foundations of grass diversity

Humans have cultivated grasses for food, feed, beverages, and construction materials for millennia. Grasses also dominate the landscape in vast parts of the world, where they have adapted morphologically and physiologically, diversifying to form ~12,000 species. Sequences of hundreds of grass genomes show that they are essentially collinear; nonetheless, not all species have the same complement of genes. Here, we focus on the molecular, cellular, and developmental bases of grain yield and dispersal-traits that are essential for domestication. Distinct genes, networks, and pathways were selected in different crop species, reflecting underlying genomic diversity. With increasing genomic resources becoming available in nondomesticated species, we anticipate advances in coming years that illuminate the ecological and economic success of the grasses.

Genetic control of branching patterns in grass inflorescences

Inflorescence branching in the grasses controls the number of florets and hence the number of seeds. Recent data on the underlying genetics come primarily from rice and maize, although new data are accumulating in other systems as well. This review focuses on a window in developmental time from the production of primary branches by the inflorescence meristem through to the production of glumes, which indicate the transition to producing a spikelet. Several major developmental regulatory modules appear to be conserved among most or all grasses. Placement and development of primary branches are controlled by conserved auxin regulatory genes. Subtending bracts are repressed by a network including TASSELSHEATH4, and axillary branch meristems are regulated largely by signaling centers that are adjacent to but not within the meristems themselves. Gradients of SQUAMOSA-PROMOTER BINDING-like and APETALA2-like proteins and their microRNA regulators extend along the inflorescence axis and the branches, governing the transition from production of branches to production of spikelets. The relative speed of this transition determines the extent of secondary and higher order branching. This inflorescence regulatory network is modified within individual species, particularly as regards formation of secondary branches. Differences between species are caused both by modifications of gene expression and regulators and by presence or absence of critical genes. The unified networks described here may provide tools for investigating orphan crops and grasses other than the well-studied maize and rice.

Reimagine fire science for the anthropocene

Fire is an integral component of ecosystems globally and a tool that humans have harnessed for millennia. Altered fire regimes are a fundamental cause and consequence of global change, impacting people and the biophysical systems on which they depend. As part of the newly emerging Anthropocene, marked by human-caused climate change and radical changes to ecosystems, fire danger is increasing, and fires are having increasingly devastating impacts on human health, infrastructure, and ecosystem services. Increasing fire danger is a vexing problem that requires deep transdisciplinary, trans-sector, and inclusive partnerships to address. Here, we outline barriers and opportunities in the next generation of fire science and provide guidance for investment in future research. We synthesize insights needed to better address the long-standing challenges of innovation across disciplines to (i) promote coordinated research efforts; (ii) embrace different ways of knowing and knowledge generation; (iii) promote exploration of fundamental science; (iv) capitalize on the "firehose" of data for societal benefit; and (v) integrate human and natural systems into models across multiple scales. Fire science is thus at a critical transitional moment. We need to shift from observation and modeled representations of varying components of climate, people, vegetation, and fire to more integrative and predictive approaches that support pathways toward mitigating and adapting to our increasingly flammable world, including the utilization of fire for human safety and benefit. Only through overcoming institutional silos and accessing knowledge across diverse communities can we effectively undertake research that improves outcomes in our more fiery future.

Savanna fire regimes depend on grass trait diversity

Grasses fuel most fires on Earth and strongly influence local fire behaviour through traits that determine how flammable they are. Therefore, grass communities that differ in their species and trait compositions give rise to significant spatial variation in savanna fire regimes across the world, which cannot be otherwise explained. Likewise, fire regimes are continuously modified by alterations to savanna grass community traits, through species introductions and climatic changes. However, current representation of grassy fuels in global fire models misses important variation and therefore limits predictive power. The inclusion of grass trait diversity in models, using remotely sensed trait proxies, for example, will greatly improve our ability to understand and project savanna fires and their roles in the Earth system.

Two Dominant Herbaceous Species Have Different Plastic Responses to N Addition in a Desert Steppe

Nitrogen (N) deposition rates are increasing in the temperate steppe due to human activities. Understanding the plastic responses of plant dominant species to increased N deposition through the lens of multiple traits is crucial for species selection in the process of vegetation restoration. Here, we measured leaf morphological, physiological, and anatomical traits of two dominant species (Stipa glareosa and Peganum harmala) after 3-year N addition (0, 1, 3, and 6 g N m-2 year-1, designated N0, N1, N3, and N6, respectively) in desert steppe of Inner Mongolia. We separately calculated the phenotypic plasticity index (PI) of each trait under different N treatments and the mean phenotypic plasticity index (MPI) of per species. The results showed that N addition increased the leaf N content (LNC) in both species. N6 increased the contents of soluble protein and proline, and decreased the superoxide dismutase (SOD) and the peroxidase (POD) activities of S. glareosa, while increased POD and catalase (CAT) activities of P. harmala. N6 increased the palisade tissue thickness (PT), leaf thickness (LT), and palisade-spongy tissue ratio (PT/ST) and decreased the spongy tissue-leaf thickness ratio (ST/LT) of S. glareosa. Furthermore, we found higher physiological plasticity but lower morphological and anatomical plasticity in both species, with greater anatomical plasticity and MPI in S. glareosa than P. harmala. Overall, multi-traits comparison reveals that two dominant desert-steppe species differ in their plastic responses to N addition. The higher plasticity of S. glareosa provides some insight into why S. glareosa has a broad distribution in a desert steppe.

Representing plant diversity in land models: An evolutionary approach to make "Functional Types" more functional

Plants are critical mediators of terrestrial mass and energy fluxes, and their structural and functional traits have profound impacts on local and global climate, biogeochemistry, biodiversity, and hydrology. Yet, Earth System Models (ESMs), our most powerful tools for predicting the effects of humans on the coupled biosphere-atmosphere system, simplify the incredible diversity of land plants into a handful of coarse categories of "Plant Functional Types" (PFTs) that often fail to capture ecological dynamics such as biome distributions. The inclusion of more realistic functional diversity is a recognized goal for ESMs, yet there is currently no consistent, widely accepted way to add diversity to models, that is, to determine what new PFTs to add and with what data to constrain their parameters. We review approaches to representing plant diversity in ESMs and draw on recent ecological and evolutionary findings to present an evolution-based functional type approach for further disaggregating functional diversity. Specifically, the prevalence of niche conservatism, or the tendency of closely related taxa to retain similar ecological and functional attributes through evolutionary time, reveals that evolutionary relatedness is a powerful framework for summarizing functional similarities and differences among plant types. We advocate that Plant Functional Types based on dominant evolutionary lineages ("Lineage Functional Types") will provide an ecologically defensible, tractable, and scalable framework for representing plant diversity in next-generation ESMs, with the potential to improve parameterization, process representation, and model benchmarking. We highlight how the importance of evolutionary history for plant function can unify the work of disparate fields to improve predictive modeling of the Earth system.