scholarly journals Impacts of trait variation through observed trait-climate relationships on performance of a representative Earth System model: a conceptual analysis

2012 ◽  
Vol 9 (12) ◽  
pp. 18907-18950 ◽  
Author(s):  
L. M. Verheijen ◽  
V. Brovkin ◽  
R. Aerts ◽  
G. Bönisch ◽  
J. H. C. Cornelissen ◽  
...  
Keyword(s):  
Plant Traits ◽  
Environmental Gradients ◽  
Environmental Filtering ◽  
Natural Vegetation ◽  
Earth System ◽  
Terrestrial Vegetation ◽  
Trait Variation ◽  
Vegetation Models ◽  
Mean Differences ◽  
Global Vegetation

Abstract. In current dynamic global vegetation models (DGVMs), including those incorporated into Earth System Models (ESMs), terrestrial vegetation is represented by a small number of plant functional types (PFTs), each with fixed properties irrespective of their predicted occurrence. This contrasts with natural vegetation, in which many plant traits vary systematically along geographic and environmental gradients. In the JSBACH DGVM, which is part of the MPI-ESM, we allowed three traits (specific leaf area (SLA), maximum carboxylation rate at 25 °C (Vcmax25) and maximum electron transport rate (Jmax25)) to vary within PFTs via trait-climate relationships based on a large trait database. For all three traits, the means of observed natural trait values strongly deviated from values used in the default model, with mean differences of 32.3% for Vcmax25, 26.8% for Jmax25 and 17.3% for SLA. Compared to the default simulation, allowing trait variation within PFTs resulted in GPP differences up to 50% in the tropics, in > 35% different dominant vegetation cover, and a closer match with a natural vegetation map. The discrepancy between default trait values and natural trait variation, combined with the substantial changes in simulated vegetation properties, together emphasize that incorporating observational data based on the ecological concepts of environmental filtering will improve the modeling of vegetation behavior in DGVMs and as such will enable more reliable projections in unknown climates.

scholarly journals Impacts of trait variation through observed trait–climate relationships on performance of an Earth system model: a conceptual analysis

2013 ◽  
Vol 10 (8) ◽  
pp. 5497-5515 ◽  
Author(s):  
L. M. Verheijen ◽  
V. Brovkin ◽  
R. Aerts ◽  
G. Bönisch ◽  
J. H. C. Cornelissen ◽  
...  
Keyword(s):  
Plant Traits ◽  
Environmental Gradients ◽  
Natural Vegetation ◽  
Earth System ◽  
Terrestrial Vegetation ◽  
Trait Variation ◽  
Ecological Concepts ◽  
Vegetation Models ◽  
Global Vegetation ◽  
The Tropics

Abstract. In many current dynamic global vegetation models (DGVMs), including those incorporated into Earth system models (ESMs), terrestrial vegetation is represented by a small number of plant functional types (PFTs), each with fixed properties irrespective of their predicted occurrence. This contrasts with natural vegetation, in which many plant traits vary systematically along geographic and environmental gradients. In the JSBACH DGVM, which is part of the MPI-ESM, we allowed three traits (specific leaf area (SLA), maximum carboxylation rate at 25 °C (Vcmax25) and maximum electron transport rate at 25 °C (Jmax25)) to vary within PFTs via trait–climate relationships based on a large trait database. The R2adjusted of these relationships were up to 0.83 and 0.71 for Vcmax25 and Jmax25, respectively. For SLA, more variance remained unexplained, with a maximum R2adjusted of 0.40. Compared to the default simulation, allowing trait variation within PFTs resulted in gross primary productivity differences of up to 50% in the tropics, in > 35% different dominant vegetation cover, and a closer match with a natural vegetation map. The discrepancy between default trait values and natural trait variation, combined with the substantial changes in simulated vegetation properties, together emphasize that incorporating climate-driven trait variation, calibrated on observational data and based on ecological concepts, allows more variation in vegetation responses in DGVMs and as such is likely to enable more reliable projections in unknown climates.

scholarly journals Harmonising plant functional type distributions for evaluating Earth system models

2019 ◽  
Vol 15 (1) ◽  
pp. 335-366 ◽  
Author(s):  
Anne Dallmeyer ◽  
Martin Claussen ◽  
Victor Brovkin
Keyword(s):  
Classical Method ◽  
New Method ◽  
Earth System ◽  
System Models ◽  
Warm Temperate Forest ◽  
Simulated Climate ◽  
Vegetation Models ◽  
Global Vegetation ◽  
Warm Temperate ◽  
Earth System Models

Abstract. Dynamic vegetation models simulate global vegetation in terms of fractional coverage of a few plant functional types (PFTs). Although these models often share the same concept, they differ with respect to the number and kind of PFTs, complicating the comparability of simulated vegetation distributions. Pollen-based vegetation reconstructions are initially only available in the form of time series of individual taxa that are not distinguished in the models. Thus, to evaluate simulated vegetation distributions, the modelling results and pollen-based vegetation reconstructions have to be converted into a comparable format. The classical approach is the method of biomisation, but hitherto PFT-based biomisation methods were only available for individual models. We introduce and evaluate a simple, universally applicable technique to harmonise PFT distributions by assigning them into nine mega-biomes, using only assumptions on the minimum PFT cover fractions and few bioclimatic constraints (based on the 2 m temperature). These constraints mainly follow the limitation rules used in the classical biome models (here BIOME4). We test the method for six state-of-the-art dynamic vegetation models that are included in Earth system models based on pre-industrial, mid-Holocene and Last Glacial Maximum simulations. The method works well, independent of the spatial resolution or the complexity of the models. Large biome belts (such as tropical forest) are generally better represented than regionally confined biomes (warm–temperate forest, savanna). The comparison with biome distributions inferred via the classical biomisation approach of forcing biome models (here BIOME1) with the simulated climate states shows that the PFT-based biomisation is even able to keep up with the classical method. However, as the new method considers the PFT distributions actually calculated by the Earth system models, it allows for a direct comparison and evaluation of simulated vegetation distributions which the classical method cannot do. Thereby, the new method provides a powerful tool for the evaluation of Earth system models in general.

scholarly journals Periodic Relations between Terrestrial Vegetation and Climate Factors across the Globe

2020 ◽  
Vol 12 (11) ◽  
pp. 1805
Author(s):  
Boyi Liang ◽  
Hongyan Liu ◽  
Xiaoqiu Chen ◽  
Xinrong Zhu ◽  
Elizabeth L. Cressey ◽  
...  
Keyword(s):  
Time Lag ◽  
Climate Factors ◽  
Vegetation Types ◽  
Terrestrial Vegetation ◽  
Area Index ◽  
Vegetation Growth ◽  
Annual Cycles ◽  
Vegetation Models ◽  
Global Vegetation ◽  
The Impact

In this paper, cross-spectrum analysis was used to verify the agreement of periodicity between the global LAI (leaf area index) and climate factors. The results demonstrated that the LAI of deciduous forests and permanent wetlands have high agreement with temperature, rainfall and radiation over annual cycles. A low agreement between the LAI and seasonal climate variables was observed for some of the temperate and tropical vegetation types including shrublands and evergreen broadleaf forests, possibly due to the diversity of vegetation and human activities. Across all vegetation types, the LAI demonstrated a large time lag following variation in radiation (>1 month), whereas relatively short lag periods were observed between the LAI and annual temperature (around 2 weeks)/rainfall patterns (less than 10 days), suggesting that the impact of radiation on global vegetation growth is relatively slow, which is in accord with the results of previous studies. This work can provide a benchmark of the phenological drivers in global vegetation, from the perspective of periodicity, as well as helping to parameterize and refine the DGVMs (Dynamic Global Vegetation Models) for different vegetation types.

scholarly journals Leaf trait variation in species-rich tropical Andean forests

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jürgen Homeier ◽  
Tabea Seeler ◽  
Kerstin Pierick ◽  
Christoph Leuschner
Keyword(s):  
Environmental Gradients ◽  
Elevation Gradient ◽  
Environmental Filtering ◽  
Leaf Thickness ◽  
Community Level ◽  
Plant Performance ◽  
Small Scale ◽  
Trait Variation ◽  
Leaf Trait ◽  
Foliar N

AbstractScreening species-rich communities for the variation in functional traits along environmental gradients may help understanding the abiotic drivers of plant performance in a mechanistic way. We investigated tree leaf trait variation along an elevation gradient (1000–3000 m) in highly diverse neotropical montane forests to test the hypothesis that elevational trait change reflects a trend toward more conservative resource use strategies at higher elevations, with interspecific trait variation decreasing and trait integration increasing due to environmental filtering. Analysis of trait variance partitioning across the 52 tree species revealed for most traits a dominant influence of phylogeny, except for SLA, leaf thickness and foliar Ca, where elevation was most influential. The community-level means of SLA, foliar N and Ca, and foliar N/P ratio decreased with elevation, while leaf thickness and toughness increased. The contribution of intraspecific variation was substantial at the community level in most traits, yet smaller than the interspecific component. Both within-species and between-species trait variation did not change systematically with elevation. High phylogenetic diversity, together with small-scale edaphic heterogeneity, cause large interspecific leaf trait variation in these hyper-diverse Andean forests. Trait network analysis revealed increasing leaf trait integration with elevation, suggesting stronger environmental filtering at colder and nutrient-poorer sites.

scholarly journals Lineage Functional Types (LFTs): Characterizing functional diversity to enhance the representation of ecological behavior in Earth System Models

2020 ◽  
Author(s):  
Daniel M. Griffith ◽  
Colin Osborne ◽  
Erika J. Edwards ◽  
Seton Bachle ◽  
David J. Beerling ◽  
...  
Keyword(s):  
Functional Diversity ◽  
Species Level ◽  
Earth System ◽  
Trait Variation ◽  
System Models ◽  
Biogeographic History ◽  
Functional Types ◽  
Wide Range ◽  
Vegetation Models ◽  
Earth System Models

SummaryProcess-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 harbor large functional diversity, yet most Earth System Models (ESMs) summarize grasses into two generic PFTs based primarily on differences between temperate C3 grasses and (sub)tropical C4 grasses. 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 ESMs. Using reported measurements, we developed grass functional trait values (physiological, structural, biochemical, anatomical, phenological, and disturbance-related) of dominant lineages to improve ESM 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.

Exploring the influence of plant trait diversity on climate using the plant trait diversity model JeDi-BACH in an Earth system model

2021 ◽  
Author(s):  
Pin-hsin Hu ◽  
Christian H. Reick ◽  
Axel Kleidon ◽  
Martin Claussen
Keyword(s):  
Plant Growth ◽  
Environmental Filtering ◽  
Earth System Model ◽  
System Model ◽  
Earth System ◽  
New Model ◽  
Plant Trait ◽  
Trait Diversity ◽  
Global Vegetation ◽  
Selection Of

<p>To understand the interaction between vegetation and the climate, Dynamic Global Vegetation Models (DGVMs) have been coupled with Earth system models (ESMs). In DGVMs, global vegetation is commonly empirically categorized into a few discrete plant functional types (PFTs) by differentiating their phenological, morphophysiological, and bioclimatic properties. Although the PFT-approach is useful to capture the large-scale general features of plants, growing evidence from the ecology community has challenged the use of the plant-type specific parametrization in models and the omission of the intra-variation of PFTs. Modelling studies have also shown that the local climate is highly sensitive to the selection and combination of PFTs. Therefore, a less parameter-dependent approach, of which the results should be robust to the empirical selection of parameters, is critical to address vegetation-climate interaction in climate models.</p><p>Based on a process-based plant functioning trade-off scheme developed by Kleidon and Mooney (2000), we have set up a new vegetation model JeDi-BACH and have implemented the new model into the land component of the ICON-Earth System Model (ICON-ESM). The advantage of this new model is to obtain plant distribution as a result of environmental filtering. Plants are represented based on several well-known fundamental functional trade-offs that link the plant functions to abiotic and biotic attributes. For example, plants which partition more biomass to roots could improve their soil-water uptake and thereby reduce the stress from water shortage. Each plant functional aspect is defined by a set of plant-trait parameters that is randomly generated for each plant species. Hence, every parameter set realizes a plant growth strategy with different functional capabilities. Using a large number of randomly generated plant growth strategies, plants are allowed to ‘grow’ everywhere; but the environment will select the survivors. In such a way, plants dynamically adjust to the changing environment and meanwhile influence climate. We have done several simulations of present-day climate with JeDi-BACH and coupled to the atmosphere component of the ICON-ESM to investigate how such an adaptive ecosystem interacts with regional and global climate. Future investigations will focus on non-analogue climates (eg. Eocene with tropical vegetation at high latitudes) where in contrast to PFT-based DGVMs the new model allows vegetation to adjust consistently with climate because of its dynamic selection of plant traits by environmental filtering.</p><p>Kleidon, A. and Mooney, H. A.: A global distribution of biodiversity inferred from climatic constraints: Results from a process-based modelling study, Glob. Chang. Biol., 6(5), 507–523, doi:10.1046/j.1365-2486.2000.00332.x, 2000.</p><p> </p>

scholarly journals Implementing spatially explicit seed and pollen dispersal in the individual-based larch simulation model: LAVESI-WIND 1.0

2018 ◽  
Author(s):  
Stefan Kruse ◽  
Alexander Gerdes ◽  
Nadja J. Kath ◽  
Ulrike Herzschuh
Keyword(s):  
Simulation Model ◽  
Genetic Information ◽  
Plant Traits ◽  
Pollen Dispersal ◽  
Spatially Explicit ◽  
Arctic Ecosystems ◽  
Major Interest ◽  
Vegetation Models ◽  
Global Vegetation ◽  
The Impact

Abstract. It is of major interest to estimate the feedback of arctic ecosystems to the global warming we expect in upcoming decades. The speed of this response is driven by the potential of species to migrate, tracking their climate optimum. For this, sessile plants have to produce and disperse seeds to newly available habitats, and pollination is needed for the seeds to be viable. These two processes are also the vectors that pass genetic information through a population. A restricted exchange among subpopulations might lead to a maladapted population due to diversity losses. Hence, a realistic implementation of these dispersal processes into a simulation model would allow an assessment of the importance of diversity for the migration of plant species in various environments worldwide. To date, dynamic global vegetation models have been optimised for a global application and overestimate the migration of biome shifts in currently warming temperatures. We hypothesise that this is caused by neglecting important fine-scale processes, which are necessary to estimate realistic vegetation trajectories. Recently, we built and parameterised a simulation model LAVESI for larches that dominate the latitudinal treelines in the northernmost areas of Siberia. In this study, we updated the vegetation model by including seed and pollen dispersal driven by wind speed and direction. The seed dispersal is modelled as a ballistic flight, and for the pollination of seeds produced, we implemented a wind-determined and distance-dependent probability distribution function using a von Mises distribution to select the potential pollen donor. This individual-based and spatially explicit implementation of both dispersal processes makes it easily feasible to inherit plant traits and genetic information to assess the impact of migration processes on the genetics. The final model can substantially help in unveiling the important drivers of migration dynamics and, with this, guide the improvement of recent global vegetation models.

Scale-Dependent Performance of CMIP5 Earth System Models in Simulating Terrestrial Vegetation Carbon*

2015 ◽  
Vol 28 (13) ◽  
pp. 5217-5232 ◽  
Author(s):  
Lifen Jiang ◽  
Yaner Yan ◽  
Oleksandra Hararuk ◽  
Nathaniel Mikle ◽  
Jianyang Xia ◽  
...  
Keyword(s):  
Residence Time ◽  
Goodness Of Fit ◽  
Spatial Scales ◽  
Carbon Stocks ◽  
Earth System ◽  
Terrestrial Vegetation ◽  
System Models ◽  
Vegetation Carbon ◽  
Global Vegetation ◽  
Earth System Models

Abstract Model intercomparisons and evaluations against observations are essential for better understanding of models’ performance and for identifying the sources of uncertainty in their output. The terrestrial vegetation carbon simulated by 11 Earth system models (ESMs) involved in phase 5 of the Coupled Model Intercomparison Project (CMIP5) was evaluated in this study. The simulated vegetation carbon was compared at three distinct spatial scales (grid, biome, and global) among models and against the observations (an updated database from Olson et al.’s “Major World Ecosystem Complexes Ranked by Carbon in Live Vegetation: A Database”). Moreover, the underlying causes of the differences in the models’ predictions were explored. Model–data fit at the grid scale was poor but greatly improved at the biome scale. Large intermodel variability was pronounced in the tropical and boreal regions, where total vegetation carbon stocks were high. While 8 out of 11 ESMs reproduced the global vegetation carbon to within 20% uncertainty of the observational estimate (560 ± 112 Pg C), the simulated global totals varied nearly threefold between the models. The goodness of fit of ESMs in simulating vegetation carbon depended strongly on the spatial scales. Sixty-three percent of the variability in contemporary global vegetation carbon stocks across ESMs could be explained by differences in vegetation carbon residence time across ESMs (P < 0.01). The analysis indicated that ESMs’ performance of vegetation carbon predictions can be substantially improved through better representation of plant longevity (i.e., carbon residence time) and its respective spatial distributions.

scholarly journals Harmonizing plant functional type distributions for evaluating Earth System Models

2018 ◽  
Author(s):  
Anne Dallmeyer ◽  
Martin Claussen ◽  
Victor Brovkin
Keyword(s):  
State Of The Art ◽  
Mixed Forest ◽  
New Method ◽  
Earth System ◽  
Functional Type ◽  
System Models ◽  
Vegetation Models ◽  
Global Vegetation ◽  
Background Climate ◽  
Earth System Models

Abstract. Dynamic vegetation models simulate global vegetation in terms of fractional coverages of a few plant functional types (PFTs). Although these models often share the same concept, they differ with respect to the number and kind of PFTs, complicating the comparability of simulated vegetation distributions. Pollen-based reconstructions are initially only available in form of time-series of individual taxa that are not distinguished in the models. Thus, to evaluate simulated vegetation distributions, the modelling results and pollen-based reconstructions have to be converted into a comparable format. The classical approach is the method of biomisation, but hitherto, PFT-based biomisation methods were only available for individual models. We introduce and evaluate a simple, universally applicable technique to harmonize PFT-distributions by assigning them into nine mega-biomes that follow the definitions commonly used for vegetation reconstructions. The method works well for all state-of the art dynamic vegetation models, independent of the spatial resolution or the complexity of the models. Large biome belts (such as tropical forest) are well represented, but regionally confined biomes (warm-mixed forest, Savanna) are only partly captured. Overall, the PFT-based biomisation is able to keep up with the conventional biomisation approach of forcing biome models (here: BIOME1) with the background climate states. The new method has, however, the advantage that it allows a more direct comparison and evaluation of the vegetation distributions simulated by Earth System Models. Thereby, the new method provides a powerful tool for the evaluation of Earth System Models in general.

scholarly journals Implementing spatially explicit wind-driven seed and pollen dispersal in the individual-based larch simulation model: LAVESI-WIND 1.0

2018 ◽  
Vol 11 (11) ◽  
pp. 4451-4467 ◽  
Author(s):  
Stefan Kruse ◽  
Alexander Gerdes ◽  
Nadja J. Kath ◽  
Ulrike Herzschuh
Keyword(s):  
Seed Dispersal ◽  
Simulation Model ◽  
Genetic Information ◽  
Plant Traits ◽  
Pollen Dispersal ◽  
Spatially Explicit ◽  
Major Interest ◽  
Vegetation Models ◽  
Global Vegetation ◽  
The Impact

Abstract. It is of major interest to estimate the feedback of arctic ecosystems to the global warming we expect in upcoming decades. The speed of this response is driven by the potential of species to migrate, tracking their climate optimum. For this, sessile plants have to produce and disperse seeds to newly available habitats, and pollination of ovules is needed for the seeds to be viable. These two processes are also the vectors that pass genetic information through a population. A restricted exchange among subpopulations might lead to a maladapted population due to diversity losses. Hence, a realistic implementation of these dispersal processes into a simulation model would allow an assessment of the importance of diversity for the migration of plant species in various environments worldwide. To date, dynamic global vegetation models have been optimized for a global application and overestimate the migration of biome shifts in currently warming temperatures. We hypothesize that this is caused by neglecting important fine-scale processes, which are necessary to estimate realistic vegetation trajectories. Recently, we built and parameterized a simulation model LAVESI for larches that dominate the latitudinal treelines in the northernmost areas of Siberia. In this study, we updated the vegetation model by including seed and pollen dispersal driven by wind speed and direction. The seed dispersal is modelled as a ballistic flight, and for the pollination of ovules of seeds produced, we implemented a wind-determined and distance-dependent probability distribution function using a von Mises distribution to select the pollen donor. A local sensitivity analysis of both processes supported the robustness of the model's results to the parameterization, although it highlighted the importance of recruitment and seed dispersal traits for migration rates. This individual-based and spatially explicit implementation of both dispersal processes makes it easily feasible to inherit plant traits and genetic information to assess the impact of migration processes on the genetics. Finally, we suggest how the final model can be applied to substantially help in unveiling the important drivers of migration dynamics and, with this, guide the improvement of recent global vegetation models.

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