Dominant Plant Functional Types Research Articles

Comparing the ability of a genetic algorithm based clustering analysis and a physically based dynamic vegetation model to predict vegetation distribution

This study explores the applicability of data‐driven clustering analysis in predicting vegetation distribution over two continents where water is an important controlling factor for vegetation growth, South America and Africa, and compares the ability of clustering analysis with that of a physically based dynamic vegetation model to predict vegetation distribution. A clustering analysis algorithm based on the genetic‐algorithm‐based K‐means is tested, with the number of clusters determined a priori according to the primary plant functional types observed to exist in the study domain. The most important variables upon which the clustering analysis is based include available water, its seasonality, and evaporative demand. The dynamic vegetation model used is the Community Land Model version 3 coupled with a Dynamic Global Vegetation Model (CLM3‐DGVM) with modifications targeted to address some known biases of the model. Results from both the clustering analysis and the modified CLM3‐DGVM are compared against observations derived from the Moderate Resolution Imaging Spectroradiometer (MODIS). Both methods reasonably reproduced the general pattern of dominant plant functional type distribution. There is no clear winner between the two methods, as the DGVM outperforms the clustering analysis approach in some aspects and is outperformed in others. It is therefore suggested that clustering analysis can be a useful tool in biogeography estimation, although it cannot be used in mechanistic studies as the process‐based DGVMs are.

Potential future changes of the terrestrial ecosystem based on climate projections by eight general circulation models

A number of previous modeling studies have assessed the implications of projected CO2‐induced climate change for future terrestrial ecosystems. However, although current understanding of possible long‐term response of vegetation to elevated CO2 and CO2‐induced climate change in some geographical areas (e.g., the high‐latitude regions) has been strengthened by dint of accumulating evidence from these past studies, it is still weak in others. This study examines the responses of global potential natural vegetation distribution, net primary production (NPP), and fire emissions to future changes in atmospheric CO2 concentration and climate using the National Center for Atmospheric Research Community Land Model's dynamic global vegetation model. The model is run to vegetative equilibrium (i.e., with respect to leaf area index (LAI) and vegetation coverage) driven with preindustrial climate and future climate near 2100, respectively, simulated by eight general circulation models (GCMs). The simulated potential vegetation under the preindustrial control mean climate (CO2 concentration held at 275 ppm) is compared with that under the SRESA1B 2100 mean climate (CO2 concentration stabilizes at 720 ppm beyond 2100). Simulated vegetation response ranges from mild changes of the fractional coverage of different plant functional types to the rather dramatic changes of dominant plant functional types. Although such response differs significantly across different GCM climate projections, a quite consistent spatial pattern emerges, characterized by a considerable poleward spread or shift of temperate and boreal forests in the Northern Hemisphere high latitudes, and a substantial degradation of vegetation type in the tropics (e.g., increase of drought deciduous trees coverage at the expense of evergreen trees) especially in portions of West and southern Africa and South America. Despite the widespread degradation of vegetation type in the tropics, NPP, and growing season LAI are predicted to increase under most GCM scenarios over most of the globe. Carbon fluxes to the atmosphere due to fire generally increase too across the globe. Such responses of NPP and fire occurrence result from the synergistic effects of CO2 concentration changes, climate changes, and vegetation changes. In the HadCM‐driven simulation, however, extreme responses are shown in some regions: Deciduous forest is replaced by grasses in large areas in the middle latitudes, and substantial areas in northern South America and southern Africa predominantly covered by evergreen forest are replaced with grasses while NPP and fire emissions reduce drastically (by more than 100%). A future paper will examine how the biosphere response documented here influences the impact of climate change on surface hydrological conditions.

Calibrating a forest landscape model to simulate frequent fire in Mediterranean-type shrublands

In Mediterranean-type ecosystems (MTEs), fire disturbance influences the distribution of most plant communities, and altered fire regimes may be more important than climate factors in shaping future MTE vegetation dynamics. Models that simulate the high-frequency fire and post-fire response strategies characteristic of these regions will be important tools for evaluating potential landscape change scenarios. However, few existing models have been designed to simulate these properties over long time frames and broad spatial scales. We refined a landscape disturbance and succession (LANDIS) model to operate on an annual time step and to simulate altered fire regimes in a southern California Mediterranean landscape. After developing a comprehensive set of spatial and non-spatial variables and parameters, we calibrated the model to simulate very high fire frequencies and evaluated the simulations under several parameter scenarios representing hypotheses about system dynamics. The goal was to ensure that observed model behavior would simulate the specified fire regime parameters, and that the predictions were reasonable based on current understanding of community dynamics in the region. After calibration, the two dominant plant functional types responded realistically to different fire regime scenarios. Therefore, this model offers a new alternative for simulating altered fire regimes in MTE landscapes.

SIMULATING THE EFFECTS OF FREQUENT FIRE ON SOUTHERN CALIFORNIA COASTAL SHRUBLANDS

Fire disturbance is a primary agent of change in the mediterranean-climate chaparral shrublands of southern California, USA. However, fire frequency has been steadily increasing in coastal regions due to ignitions at the growing wildland-urban interface. Although chaparral is resilient to a range of fire frequencies, successively short intervals between fires can threaten the persistence of some species, and the effects may differ according to plant functional type. California shrublands support high levels of biological diversity, including many endangered and endemic species. Therefore, it is important to understand the long-term effects of altered fire regimes on these communities. A spatially explicit simulation model of landscape disturbance and succession (LANDIS) was used to predict the effects of frequent fire on the distribution of dominant plant functional types in a study area administered by the National Park Service. Shrubs dependent on fire-cued seed germination were most sensitive to frequent fire and lost substantial cover to other functional types, including drought-deciduous subshrubs that typify coastal sage scrub and nonnative annual grasses. Shrubs that resprout were favored by higher fire frequencies and gained in extent under these treatments. Due to this potential for vegetation change, caution is advised against the widespread use of prescribed fire in the region.

A biome classification of China based on plant functional types and the BIOME3 model

A biome classification for China was established based on plant functional types (PFTs) using the BIOME3 model to include 16 biomes. In the eastern part of China, the PFTs of trees determine mostly the physiognomy of landscape. Biomes range from boreal deciduous coniferous forest/woodland, boreal mixed forest/woodland, temperate mixed forest, temperate broad-leaved deciduous forest, warm-temperate broad-leaved evergreen/mixed forest, warm-temperate/cool-temperate evergreen coniferous forest, xeric woodland/scrub, to tropical seasonal and rain forest, and tropical deciduous forest from north to south. In the northern and western part of China, grass is the dominant PFT. From northeast to west and southwest the biomes range from moist savannas, tall grassland, short grassland, dry savannas, arid shrubland/steppe, desert, to alpine tundra/ice/polar desert. Comparisons between the classification introduced here and the four classifications which were established over the past two decades, i.e. the vegetation classification, the vegetation division, the physical ecoregion, and the initial biome classification have showed that the different aims of biome classifications have resulted in different biome schemes each with its own unique characteristics and disadvantages for global change study. The new biome classification relies not only on climatic variables, but also on soil factor, vegetation functional variables, ecophysiological parameters and competition among the PFTs. It is a comprehensive classification that using multivariables better expresses the vegetation distribution and can be compared with world biome classifications. It can be easily used in the response study of Chinese biomes to global change, regionally and globally.

Hierarchical subdivision of Arctic tundra based on vegetation response to climate, parent material and topography.

Current land-cover classifications used for global modelling portray Arctic tundra as one or two classes. This is insufficient for analysis of climate-vegetation interactions. This paper presents a simple three-level vegetation-map legend system useful for modelling at global, regional, and landscape scales. At the highest level (global scale: 107 -108 km2 ) the Tundra Zone is divided into four subzones based on vegetation response to temperature along the latitudinal temperature gradient from north to south: (1) Cushion-forb, (2) Prostrate Dwarf-shrub, (3) Erect Dwarf-shrub, and (4) Low Shrub subzones. The boundaries follow a modification of Yurtsev's phytogeographic subzones. Parent material and topography are also major considerations at global, regional, and landscape scales. Soil pH is a key variable for many ecosystem responses, and a division into acidic (pH 5.5 or less) and nonacidic soils is used. A conceptual mesotopographic gradient is used to characterize the influence of soil-moisture and snow regimes. The example legend framework focuses on the Northern Alaska floristic subprovince, and could be expanded to other floristic provinces using local expert knowledge and available literature. Dominant plant functional types within each habitat type within the four subzones are also presented. Modellers could include or ignore different levels of resolution depending on the purpose of the model. The approach resolves conflicts in terminology that have previously been encountered between the Russian, North American, and Fennoscandian approaches to Arctic zonation.

Grazing effects on patchy dryland vegetation in northern Patagonia

In this study the spatial patterns and dynamics of vegetation patches along a grazing gradient in the steppe ofLarrea divaricataandStipaspp. in NE Patagonia (Argentina) are described. A general effect of grazing is the reduction of total plant cover resulting from the decrease in cover of perennial grasses (Stipa speciosa, Poa ligularis, Stipa tenuis) and some tall shrubs (Chuquiraga hystrix, Bougainvillea spinosa, Lycium chilense). Dwarf shrubs (Nassauvia fueguianaandJunellia seriphioides) increase their cover under medium and/or high grazing pressures. Plant species are spatially grouped into patches which alternate with areas of bare soil. Eleven types of vegetation patch differing in the dominant plant functional type or species, floristic richness and size were identified with different relative frequency along the grazing gradient. Based on these results, it is postulated that grazing forces the replacement of large patches dominated by tall shrubs with high species richness, byLarrea divaricatapatches or small dwarf shrub patches with low species richness and the extinction of grass patches. This results from: (1) disruption of local balances of species deletions and additions; (2) fragmentation of large patches; and (3) formation of new vegetation patches. These changes lead to differing plant spatial organization and heterogeneity along the grazing gradient which may be described by characteristic arrays of vegetation patches.

BIOME3: An equilibrium terrestrial biosphere model based on ecophysiological constraints, resource availability, and competition among plant functional types

The equilibrium terrestrial biosphere model BIOME3 simulates vegetation distribution and biogeochemistry, and couples vegetation distribution directly to biogeochemistry. Model inputs consist of latitude, soil texture class, and monthly climate (temperature, precipitation, and sunshine) data on a 0.5° grid. Ecophysiological constraints determine which plant functional types (PFTs) may potentially occur. A coupled carbon and water flux model is then used to calculate, for each PFT, the leaf area index (LAI) that maximizes net primary production (NPP), subject to the constraint that NPP must be sufficient to maintain this LAI. Competition between PFTs is simulated by using the optimal NPP of each PFT as an index of competitiveness, with additional rules to approximate the dynamic equilibrium between natural disturbance and succession driven by light competition. Model output consists of a quantitative vegetation state description in terms of the dominant PFT, secondary PFTs present, and the total LAI and NPP for the ecosystem. Canopy conductance is treated as a function of the calculated optimal photosynthetic rate and water stress. Regional evapotranspiration is calculated as a function of canopy conductance, equilibrium evapotranspiration rate, and soil moisture using a simple planetary boundary layer parameterization. This scheme results in a two‐way coupling of the carbon and water fluxes through canopy conductance, allowing simulation of the response of photosynthesis, stomatal conductance, and leaf area to environmental factors including atmospheric CO2. Comparison with the mapped distribution of global vegetation shows that the model successfully reproduces the broad‐scale patterns in potential natural vegetation distribution. Comparison with NPP measurements, and with an FPAR (fractional absorbed photosynthetically active radiation) climatology based on remotely sensed greenness measurements, provides further checks on the model's internal logic. The model is envisaged as a tool for integrated analysis of the impacts of changes in climate and CO2 on ecosystem structure and function.

Ecosystem responses to changes in plant functional type composition: An example from the Patagonian steppe

Abstract. Grass cover along a grazing intensity gradient in Patagonia decreases, whereas bare soil and shrub cover increases. Our objective was to study the effect of a change in the dominant plant functional type on soil water balance, primary production, herbivore biomass, roughness, and albedo. Using a soil water balance model, we found increases in evaporation and deep drainage, and a decrease in total transpiration along the grazing intensity gradient. Above‐ground primary production, estimated from transpiration, decreased along the grazing intensity gradient because shrubs did not fully compensate for the decrease in grass production. Using a statistical model, we calculated herbivore biomass from estimates of above‐ground primary production. Estimated herbivore biomass was lowest in the shrub‐dominated extreme of the grazing gradient. Roughness increased from the grass‐dominated to the shrub‐dominated community. Albedo had a maximum at an intermediate position along the gradient.Our results suggest that changes in plant functional type composition, independent of changes in biomass, affect ecosystem functioning and the exchange of energy and material with the atmosphere. Grasses and shrubs proved to be appropriate plant functional types to link structure and function of ecosystems.