Detecting general plant functional type responses in fragmented landscapes using spatially-explicit simulations

2008 ◽  
Vol 210 (3) ◽  
pp. 287-300 ◽  
Author(s):  
Katrin Körner ◽  
Florian Jeltsch
Keyword(s):  
Plant Functional Type ◽  
Spatially Explicit ◽  
Functional Type ◽  
Fragmented Landscapes

scholarly journals Evaluating and improving the Community Land Model's sensitivity to land cover

2018 ◽  
Vol 15 (15) ◽  
pp. 4731-4757 ◽  
Author(s):  
Ronny Meier ◽  
Edouard L. Davin ◽  
Quentin Lejeune ◽  
Mathias Hauser ◽  
Yan Li ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Land Surface ◽  
Soil Column ◽  
Plant Functional Type ◽  
Model Parameters ◽  
Functional Type ◽  
Land Surface Models ◽  
Surface Models ◽  
Open Land

Abstract. Modeling studies have shown the importance of biogeophysical effects of deforestation on local climate conditions but have also highlighted the lack of agreement across different models. Recently, remote-sensing observations have been used to assess the contrast in albedo, evapotranspiration (ET), and land surface temperature (LST) between forest and nearby open land on a global scale. These observations provide an unprecedented opportunity to evaluate the ability of land surface models to simulate the biogeophysical effects of forests. Here, we evaluate the representation of the difference of forest minus open land (i.e., grassland and cropland) in albedo, ET, and LST in the Community Land Model version 4.5 (CLM4.5) using various remote-sensing and in situ data sources. To extract the local sensitivity to land cover, we analyze plant functional type level output from global CLM4.5 simulations, using a model configuration that attributes a separate soil column to each plant functional type. Using the separated soil column configuration, CLM4.5 is able to realistically reproduce the biogeophysical contrast between forest and open land in terms of albedo, daily mean LST, and daily maximum LST, while the effect on daily minimum LST is not well captured by the model. Furthermore, we identify that the ET contrast between forests and open land is underestimated in CLM4.5 compared to observation-based products and even reversed in sign for some regions, even when considering uncertainties in these products. We then show that these biases can be partly alleviated by modifying several model parameters, such as the root distribution, the formulation of plant water uptake, the light limitation of photosynthesis, and the maximum rate of carboxylation. Furthermore, the ET contrast between forest and open land needs to be better constrained by observations to foster convergence amongst different land surface models on the biogeophysical effects of forests. Overall, this study demonstrates the potential of comparing subgrid model output to local observations to improve current land surface models' ability to simulate land cover change effects, which is a promising approach to reduce uncertainties in future assessments of land use impacts on climate.

scholarly journals Plant functional type mapping for earth system models

2011 ◽  
Vol 4 (3) ◽  
pp. 2081-2121 ◽  
Author(s):  
B. Poulter ◽  
P. Ciais ◽  
E. Hodson ◽  
H. Lischke ◽  
F. Maignan ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Climate Variability ◽  
Forest Cover ◽  
Plant Functional Type ◽  
Earth System ◽  
Functional Type ◽  
System Models ◽  
Satellite Sensors ◽  
Earth System Models

Abstract. The sensitivity of global carbon and water cycling to climate variability is coupled directly to land cover and the distribution of vegetation. To investigate biogeochemistry-climate interactions, earth system models require a representation of vegetation distributions that are either prescribed from remote sensing data or simulated via biogeography models. However, the abstraction of earth system state variables in models means that data products derived from remote sensing need to be post-processed for model-data assimilation. Dynamic global vegetation models (DGVM) rely on the concept of plant functional types (PFT) to group shared traits of thousands of plant species into just several classes. Available databases of observed PFT distributions must be relevant to existing satellite sensors and their derived products, and to the present day distribution of managed lands. Here, we develop four PFT datasets based on land-cover information from three satellite sensors (EOS-MODIS 1 km and 0.5 km, SPOT4-VEGETATION 1 km, and ENVISAT-MERIS 0.3 km spatial resolution) that are merged with spatially-consistent Köppen-Geiger climate zones. Using a beta (β) diversity metric to assess reclassification similarity, we find that the greatest uncertainty in PFT classifications occur most frequently between cropland and grassland categories, and in dryland systems between shrubland, grassland and forest categories because of differences in the minimum threshold required for forest cover. The biogeography-biogeochemistry DGVM, LPJmL, is used in diagnostic mode with the four PFT datasets prescribed to quantify the effect of land-cover uncertainty on climatic sensitivity of gross primary productivity (GPP) and transpiration fluxes. Our results show that land-cover uncertainty has large effects in arid regions, contributing up to 30 % (20 %) uncertainty in the sensitivity of GPP (transpiration) to precipitation. The availability of plant functional type datasets that are consistent with current satellite products and adapted for earth system models is an important component for reducing the uncertainty of terrestrial biogeochemistry to climate variability.

Incorporating behavior-based indices of connectivity into spatially explicit population models

2012 ◽  
Vol 90 (2) ◽  
pp. 222-236 ◽  
Author(s):  
C.E. Rizkalla ◽  
R.K. Swihart
Keyword(s):  
Population Models ◽  
Spatially Explicit ◽  
Patch Occupancy ◽  
Ecological Processes ◽  
Forest Patch ◽  
Fragmented Landscapes ◽  
Direct Observations ◽  
Behavior Based ◽  
Potential Methods ◽  
Parameter Values

Measuring connectivity in fragmented landscapes remains a central problem in ecology. Connectivity metrics range from descriptors of landscape structure to direct observations of a species’ ability to move to and colonize a forest patch. We constructed individual-based spatially explicit population models for a guild of forest rodents in Indiana to test the ability of structural and actual, or behavioral, measures of connectivity to predict patch and landscape occupancy and abundance. Model accuracy was assessed using comparisons with data from trapping studies. Predicted abundances within patches correlated with empirical data for five out of six species, but predicted patterns of patch occupancy corresponded with observations for only one species. Discrepancies may be due to inaccurate parameter values or the absence from the models of ecological processes such as conspecific attraction and competition. Nonetheless, the models demonstrated the utility of patch immigration as a measure of connectivity in explaining population abundance in fragmented landscapes. We discuss potential methods of collecting these behavior-based data.

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

1996 ◽  
Vol 7 (3) ◽  
pp. 381-390 ◽  
Author(s):  
Martín R. Aguiar ◽  
José M. Paruelo ◽  
Osvaldo E. Sala ◽  
William K. Lauenroth
Keyword(s):  
Plant Functional Type ◽  
Functional Type ◽  
Ecosystem Responses ◽  
Patagonian Steppe ◽  
Type Composition

scholarly journals Modeling forest carbon cycle response to tree mortality: Effects of plant functional type and disturbance intensity

2015 ◽  
Vol 120 (11) ◽  
pp. 2178-2193 ◽  
Author(s):  
Renato Prata de Moraes Frasson ◽  
Gil Bohrer ◽  
David Medvigy ◽  
Ashley M. Matheny ◽  
Timothy H. Morin ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Tree Mortality ◽  
Forest Carbon ◽  
Plant Functional Type ◽  
Functional Type ◽  
Disturbance Intensity

scholarly journals A STUDY ON PRODUCING HIGHLY RELIABILE REFERENCE DATA SETS FOR GLOBAL LAND COVER VALIDATION

2016 ◽  
Vol XLI-B8 ◽  
pp. 1207-1211
Author(s):  
N. Soyama ◽  
K. Muramatsu ◽  
M. Daigo ◽  
F. Ochiai ◽  
N. Fujiwara
Keyword(s):  
Land Cover ◽  
Reference Data ◽  
Ground Truth ◽  
Plant Functional Type ◽  
Data Sets ◽  
Functional Type ◽  
Reference Dataset ◽  
Ground Truth Data ◽  
Global Land Cover ◽  
Global Land

Validating the accuracy of land cover products using a reliable reference dataset is an important task. A reliable reference dataset is produced with information derived from ground truth data. Recently, the amount of ground truth data derived from information collected by volunteers has been increasing globally. The acquisition of volunteer-based reference data demonstrates great potential. However information given by volunteers is limited useful vegetation information to produce a complete reference dataset based on the plant functional type (PFT) with five specialized forest classes. In this study, we examined the availability and applicability of FLUXNET information to produce reference data with higher levels of reliability. FLUXNET information was useful especially for forest classes for interpretation in comparison with the reference dataset using information given by volunteers.

scholarly journals Phenology and plant functional type dominance drive CO2 exchange in seminatural grasslands in the Pyrenees

2020 ◽  
Vol 158 (1-2) ◽  
pp. 3-14 ◽  
Author(s):  
M. Ibañez ◽  
N. Altimir ◽  
A. Ribas ◽  
W. Eugster ◽  
M.-T. Sebastià
Keyword(s):  
Environmental Variables ◽  
Biomass Productivity ◽  
Light Response ◽  
Co2 Exchange ◽  
Plant Functional Type ◽  
Functional Type ◽  
Relative Contribution ◽  
Peak Biomass ◽  
Mountain Grasslands ◽  
Seminatural Grasslands

AbstractUnderstanding the mechanisms underlying net ecosystem CO2 exchange (NEE) in mountain grasslands is important to quantify their relevance in the global carbon budget. However, complex interactions between environmental variables and vegetation on NEE remain unclear; and there is a lack of empirical data, especially from the high elevations and the Mediterranean region. A chamber-based survey of CO2 exchange measurements was carried out in two climatically contrasted grasslands (montane v. subalpine) of the Pyrenees; assessing the relative contribution of phenology and environmental variables on CO2 exchange at the seasonal scale, and the influence of plant functional type dominance (grasses, forbs and legumes) on the NEE light response. Results show that phenology plays a crucial role as a CO2 exchange driver, suggesting a differential behaviour of the vegetation community depending on the environment. The subalpine grassland had a more delayed phenology compared to the montane, being more temperature than water constrained. However, temperature increased net CO2 uptake at a higher rate in the subalpine than in the montane grassland. During the peak biomass, productivity (+74%) and net CO2 uptake (NEE +48%) were higher in the subalpine grassland than in the montane grassland. The delayed phenology at the subalpine grassland reduced vegetation's sensitivity to summer dryness, and CO2 exchange fluxes were less constrained by low soil water content. The NEE light response suggested that legume dominated plots had higher net CO2 uptake per unit of biomass than grasses. Detailed information on phenology and vegetation composition is essential to understand elevation and climatic differences in CO2 exchange.

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