Process‐based vegetation models attempt to represent the wide range of trait variation in biomes by grouping ecologically similar species into plant functional types (PFTs). This approach has been successful in representing many aspects of plant physiology and biophysics but struggles to capture biogeographic history and ecological dynamics that determine biome boundaries and plant distributions. Grass‐dominated ecosystems are broadly distributed across all vegetated continents and harbour large functional diversity, yet most Land Surface Models (LSMs) summarise grasses into two generic PFTs based primarily on differences between temperate C3grasses and (sub)tropical C4grasses. Incorporation of species‐level trait variation is an active area of research to enhance the ecological realism of PFTs, which form the basis for vegetation processes and dynamics in LSMs. Using reported measurements, we developed grass functional trait values (physiological, structural, biochemical, anatomical, phenological, and disturbance‐related) of dominant lineages to improve LSM representations. Our method is fundamentally different from previous efforts, as it uses phylogenetic relatedness to create lineage‐based functional types (LFTs), situated between species‐level trait data and PFT‐level abstractions, thus providing a realistic representation of functional diversity and opening the door to the development of new vegetation models.
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.
more » « less- NSF-PAR ID:
- 10364074
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Global Change Biology
- Volume:
- 28
- Issue:
- 8
- ISSN:
- 1354-1013
- Page Range / eLocation ID:
- p. 2541-2554
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Simulations of the land surface carbon cycle typically compress functional diversity into a small set of plant functional types (PFT), with parameters defined by the average value of measurements of functional traits. In most earth system models, all wild plant life is represented by between five and 14 PFTs and a typical grid cell (≈100 × 100 km) may contain a single PFT. Model logic applied to this coarse representation of ecological functional diversity provides a reasonable proxy for the carbon cycle, but does not capture the non‐linear influence of functional traits on productivity. Here we show through simulations using the Energy Exascale Land Surface Model in 15 diverse terrestrial landscapes, that better accounting for functional diversity markedly alters predicted total carbon uptake. The shift in carbon uptake is as great as 30% and 10% in boreal and tropical regions, respectively, when compared to a single PFT parameterized with the trait means. The traits that best predict gross primary production vary based on vegetation phenology, which broadly determines where traits fall within the global distribution. Carbon uptake is more closely associated with specific leaf area for evergreen PFTs and the leaf carbon to nitrogen ratio in deciduous PFTs.
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Abstract Aim C4grasses are distinct from C3grasses, because C4grasses respond in a different manner to light, temperature, CO2and nitrogen and often have higher resource‐use efficiencies. C3and C4grasses are typically represented in earth system models (ESMs) by different plant functional types (PFTs). The ability of ESMs to capture C4grass biogeography and ecology across differing time periods is important to assess, given the crucial role they play in ecosystems and their divergent responses to global change.
Location North America.
Time periods Last Glacial Maximum (LGM), historical modern period (
ca . 1850) and end of this century.Major taxa studied C4grasses.
Methods Proxy data representing relative cover and productivity of C4grasses were collated, including carbon isotope ratios of soil carbon and animal grazer tissue, and vegetation plot data in undisturbed grasslands. We selected available model predictions of C4PFT percentage cover. Models were compared against one another and assessed against proxy data at key time points: the LGM, the historical modern period before widespread grassland conversion to agriculture, and the end of this century.
Results We highlight large differences among model predictions of percentage C4grass cover across North America: all pairwise combinations have correlations < .5, and most are < .2. Models also do not capture spatial patterns of the percentage C4grass cover from proxy data, during either the LGM or the historical modern period. Models generally under‐predict percentage C4grass cover, particularly during the historical modern period.
Main conclusions Earth system models do not accurately represent the biogeography of C4grasses across a range of time‐scales, and their outputs do not agree with one another. We suggest model improvements to represent this crucial functional type better, including more collection and greater integration of C3and C4grass trait data, explicit representations of tree–grass competition for water, and a greater focus on disturbance ecology.
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Abstract Tropical forests are a key determinant of the functioning of the Earth system, but remain a major source of uncertainty in carbon cycle models and climate change projections. In this study, we present an updated land model (LM3PPA‐TV) to improve the representation of tropical forest structure and dynamics in Earth system models (ESMs). The development and parameterization of LM3PPA‐TV drew on extensive datasets on tropical tree traits and long‐term field censuses from Barro Colorado Island (BCI), Panama. The model defines a new plant functional type (PFT) based on the characteristics of shade‐tolerant, tropical tree species, implements a new growth allocation scheme based on realistic tree allometries, incorporates hydraulic constraints on biomass accumulation, and features a new compartment for tree branches and branch fall dynamics. Simulation experiments reproduced observed diurnal and seasonal patterns in stand‐level carbon and water fluxes, as well as mean canopy and understory tree growth rates, tree size distributions, and stand‐level biomass on BCI. Simulations at multiple sites captured considerable variation in biomass and size structure across the tropical forest biome, including observed responses to precipitation and temperature. Model experiments suggested a major role of water limitation in controlling geographic variation forest biomass and structure. However, the failure to simulate tropical forests under extreme conditions and the systematic underestimation of forest biomass in Paleotropical locations highlighted the need to incorporate variation in hydraulic traits and multiple PFTs that capture the distinct floristic composition across tropical domains. The continued pressure on tropical forests from global change demands models which are able to simulate alternative successional pathways and their pace to recovery. LM3PPA‐TV provides a tool to investigate geographic variation in tropical forests and a benchmark to continue improving the representation of tropical forests dynamics and their carbon storage potential in ESMs.
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Summary Evolutionary history plays a key role driving patterns of trait variation across plant species. For scaling and modeling purposes, grass species are typically organized into C3vs C4plant functional types (PFTs). Plant functional type groupings may obscure important functional differences among species. Rather, grouping grasses by evolutionary lineage may better represent grass functional diversity.
We measured 11 structural and physiological traits
in situ from 75 grass species within the North American tallgrass prairie. We tested whether traits differed significantly among photosynthetic pathways or lineages (tribe) in annual and perennial grass species.Critically, we found evidence that grass traits varied among lineages, including independent origins of C4photosynthesis. Using a rigorous model selection approach, tribe was included in the top models for five of nine traits for perennial species. Tribes were separable in a multivariate and phylogenetically controlled analysis of traits, owing to coordination of important structural and ecophysiological characteristics.
Our findings suggest grouping grass species by photosynthetic pathway overlooks variation in several functional traits, particularly for C4species. These results indicate that further assessment of lineage‐based differences at other sites and across other grass species distributions may improve representation of C4species in trait comparison analyses and modeling investigations.
