Spatial Distribution of Plant Functional Types Along Stress Gradients – A Simulation Study Orientated Towards the Plant Succession on the Desiccating Aral Sea Floor

Spatial Distribution of Roots across Three Dryland Ecosystems and Plant Functional Types

Western North American Naturalist ◽

10.3398/064.079.0203 ◽

2019 ◽

Vol 79 (2) ◽

pp. 159 ◽

Cited By ~ 1

Author(s):

Jessica G. Swindon ◽

William K. Lauenroth ◽

Daniel R. Schlaepfer ◽

Ingrid C. Burke

Keyword(s):

Spatial Distribution ◽

Plant Functional Types ◽

Functional Types ◽

Dryland Ecosystems ◽

Distribution Of Roots

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Competition between plant functional types in the Canadian Terrestrial Ecosystem Model (CTEM) v. 2.0

Geoscientific Model Development ◽

10.5194/gmd-9-323-2016 ◽

2016 ◽

Vol 9 (1) ◽

pp. 323-361 ◽

Cited By ~ 52

Author(s):

J. R. Melton ◽

V. K. Arora

Keyword(s):

Spatial Distribution ◽

Large Scale ◽

Terrestrial Ecosystem ◽

Ecosystem Model ◽

Plant Functional Types ◽

Atmospheric Composition ◽

Climate Modelling ◽

Fractional Coverage ◽

Terrestrial Ecosystem Model ◽

Functional Types

Abstract. The Canadian Terrestrial Ecosystem Model (CTEM) is the interactive vegetation component in the Earth system model of the Canadian Centre for Climate Modelling and Analysis. CTEM models land–atmosphere exchange of CO2 through the response of carbon in living vegetation, and dead litter and soil pools, to changes in weather and climate at timescales of days to centuries. Version 1.0 of CTEM uses prescribed fractional coverage of plant functional types (PFTs) although, in reality, vegetation cover continually adapts to changes in climate, atmospheric composition and anthropogenic forcing. Changes in the spatial distribution of vegetation occur on timescales of years to centuries as vegetation distributions inherently have inertia. Here, we present version 2.0 of CTEM, which includes a representation of competition between PFTs based on a modified version of the Lotka–Volterra (L–V) predator–prey equations. Our approach is used to dynamically simulate the fractional coverage of CTEM's seven natural, non-crop PFTs, which are then compared with available observation-based estimates. Results from CTEM v. 2.0 show the model is able to represent the broad spatial distributions of its seven PFTs at the global scale. However, differences remain between modelled and observation-based fractional coverage of PFTs since representing the multitude of plant species globally, with just seven non-crop PFTs, only captures the large-scale climatic controls on PFT distributions. As expected, PFTs that exist in climate niches are difficult to represent either due to the coarse spatial resolution of the model, and the corresponding driving climate, or the limited number of PFTs used. We also simulate the fractional coverage of PFTs using unmodified L–V equations to illustrate its limitations. The geographic and zonal distributions of primary terrestrial carbon pools and fluxes from the versions of CTEM that use prescribed and dynamically simulated fractional coverage of PFTs compare reasonably well with each other and observation-based estimates. The parametrization of competition between PFTs in CTEM v. 2.0 based on the modified L–V equations behaves in a reasonably realistic manner and yields a tool with which to investigate the changes in spatial distribution of vegetation in response to future changes in climate.

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Spatial and temporal patterns of plant functional types under simulated fire regimes

International Journal of Wildland Fire ◽

10.1071/wf06109 ◽

2007 ◽

Vol 16 (4) ◽

pp. 484 ◽

Cited By ~ 33

Author(s):

Juli G. Pausas ◽

F. Lloret

Keyword(s):

Spatial Distribution ◽

Fire Regime ◽

Fire Regimes ◽

Plant Functional Types ◽

Spatial And Temporal Patterns ◽

Spatial And Temporal Scales ◽

Fire Recurrence ◽

Functional Types ◽

Mediterranean Countries ◽

Fire Scenarios

In spite of enormous fire suppression advances in Mediterranean countries, large high-intensity fires are still common. The effects on vegetation structure and composition of fire and fire regime changes at large spatial and temporal scales are poorly known, and landscape simulation models may throw some light in this regard. Thus, we studied how the abundance, richness, and spatial distribution of the different plant types are sensitive to the frequency, extent and spatial distribution of wildfires, using a landscape simulation model (FATELAND). We simulated the dynamics of 10 plant functional types (PFTs) defined as combinations of post-fire persistence strategies and life forms, under the following fire scenarios: No Fire, Suppressed (one large fire every 20 years), Prescribed (small fuel reductions every year), Unmanaged-1 (two small fires every year) and Unmanaged-2 (four small fires every year). The results suggest that the different fire regimes generate different spatial fire-recurrence patterns and changes in the proportion of the dominant species. For instance, with increasing fire recurrence, seeder shrubs (i.e. those recruiting new individuals after fire from persisting seed bank) with early reproduction increased and seeder trees decreased, while little variation was found for resprouters. Fire also increased the spatial aggregation of plants, while PFT richness decreased with increasing fire recurrence. The results suggest patterns of changes similar to those reported in field studies, and thus they provide consistent hypotheses on the possible vegetation changes due to different fire scenarios.

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Competition between plant functional types in the Canadian Terrestrial Ecosystem Model (CTEM) v. 2.0

Geoscientific Model Development Discussions ◽

10.5194/gmdd-8-4851-2015 ◽

2015 ◽

Vol 8 (6) ◽

pp. 4851-4948 ◽

Cited By ~ 2

Author(s):

J. R. Melton ◽

V. K. Arora

Keyword(s):

Spatial Distribution ◽

Large Scale ◽

Terrestrial Ecosystem ◽

Ecosystem Model ◽

Plant Functional Types ◽

Atmospheric Composition ◽

Climate Modelling ◽

Fractional Coverage ◽

Terrestrial Ecosystem Model ◽

Functional Types

Abstract. The Canadian Terrestrial Ecosystem Model (CTEM) is the interactive vegetation component in the Earth system model of the Canadian Centre for Climate Modelling and Analysis. CTEM models land–atmosphere exchange of CO2 through the response of carbon in living vegetation, and dead litter and soil pools, to changes in weather and climate at timescales of days to centuries. Version 1.0 of CTEM uses prescribed fractional coverage of plant functional types (PFTs) although, in reality, vegetation cover continually adapts to changes in climate, atmospheric composition, and anthropogenic forcing. Changes in the spatial distribution of vegetation occur on timescales of years to centuries as vegetation distributions inherently have inertia. Here, we present version 2.0 of CTEM which includes a representation of competition between PFTs based on a modified version of the Lotka–Volterra (L–V) predator–prey equations. Our approach is used to dynamically simulate the fractional coverage of CTEM's seven natural, non-crop PFTs which are then compared with available observation-based estimates. Results from CTEM v. 2.0 show the model is able to represent the broad spatial distributions of its seven PFTs at the global scale. However, differences remain between modelled and observation-based fractional coverages of PFTs since representing the multitude of plant species globally, with just seven non-crop PFTs, only captures the large scale climatic controls on PFT distributions. As expected, PFTs that exist in climate niches are difficult to represent either due to the coarse spatial resolution of the model, and the corresponding driving climate, or the limited number of PFTs used. We also simulate the fractional coverages of PFTs using unmodified L–V equations to illustrate its limitations. The geographic and zonal distributions of primary terrestrial carbon pools and fluxes from the versions of CTEM that use prescribed and dynamically simulated fractional coverage of PFTs compare reasonably well with each other and observation-based estimates. The parametrization of competition between PFTs in CTEM v. 2.0 based on the modified L–V equations behaves in a reasonably realistic manner and yields a tool with which to investigate the changes in spatial distribution of vegetation in response to future changes in climate.

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