256 research outputs found
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Divergent drivers of leaf trait variation within species, among species, and among functional groups.
Understanding variation in leaf functional traits-including rates of photosynthesis and respiration and concentrations of nitrogen and phosphorus-is a fundamental challenge in plant ecophysiology. When expressed per unit leaf area, these traits typically increase with leaf mass per area (LMA) within species but are roughly independent of LMA across the global flora. LMA is determined by mass components with different biological functions, including photosynthetic mass that largely determines metabolic rates and contains most nitrogen and phosphorus, and structural mass that affects toughness and leaf lifespan (LL). A possible explanation for the contrasting trait relationships is that most LMA variation within species is associated with variation in photosynthetic mass, whereas most LMA variation across the global flora is associated with variation in structural mass. This hypothesis leads to the predictions that (i) gas exchange rates and nutrient concentrations per unit leaf area should increase strongly with LMA across species assemblages with low LL variance but should increase weakly with LMA across species assemblages with high LL variance and that (ii) controlling for LL variation should increase the strength of the above LMA relationships. We present analyses of intra- and interspecific trait variation from three tropical forest sites and interspecific analyses within functional groups in a global dataset that are consistent with the above predictions. Our analysis suggests that the qualitatively different trait relationships exhibited by different leaf assemblages can be understood by considering the degree to which photosynthetic and structural mass components contribute to LMA variation in a given assemblage
Divergent drivers of leaf trait variation within species, among species, and among functional groups
Understanding variation in leaf functional traitsâincluding rates of photosynthesis and respiration and concentrations of nitrogen and phosphorusâis a fundamental challenge in plant ecophysiology. When expressed per unit leaf area, these traits typically increase with leaf mass per area (LMA) within species but are roughly independent of LMA across the global flora. LMA is determined by mass components with different biological functions, including photosynthetic mass that largely determines metabolic rates and contains most nitrogen and phosphorus, and structural mass that affects toughness and leaf lifespan (LL). A possible explanation for the contrasting trait relationships is that most LMA variation within species is associated with variation in photosynthetic mass, whereas most LMA variation across the global flora is associated with variation in structural mass. This hypothesis leads to the predictions that (i) gas exchange rates and nutrient concentrations per unit leaf area should increase strongly with LMA across species assemblages with low LL variance but should increase weakly with LMA across species assemblages with high LL variance and that (ii) controlling for LL variation should increase the strength of the above LMA relationships. We present analyses of intra- and interspecific trait variation from three tropical forest sites and interspecific analyses within functional groups in a global dataset that are consistent with the above predictions. Our analysis suggests that the qualitatively different trait relationships exhibited by different leaf assemblages can be understood by considering the degree to which photosynthetic and structural mass components contribute to LMA variation in a given assemblage
Tropical tree height and crown allometries for the Barro Colorado Nature Monument, Panama: a comparison of alternative hierarchical models incorporating interspecific variation in relation to life history traits
Tree allometric relationships are widely employed for estimating forest biomass
and production and are basic building blocks of dynamic vegetation models.
In tropical forests, allometric relationships are often modeled by fitting
scale-invariant power functions to pooled data from multiple species, an
approach that fails to capture changes in scaling during ontogeny and
physical limits to maximum tree size and that ignores interspecific
differences in allometry. Here, we analyzed allometric relationships of tree
height (9884 individuals) and crown area (2425) with trunk diameter for 162
species from the Barro Colorado Nature Monument, Panama. We fit
nonlinear, hierarchical models informed by species traits â
wood density, mean sapling growth, or sapling mortality â and assessed the
performance of three alternative functional forms: the scale-invariant power
function and the saturating Weibull and generalized MichaelisâMenten (gMM)
functions. The relationship of tree height with trunk diameter was best fit
by a saturating gMM model in which variation in allometric parameters was
related to interspecific differences in sapling growth rates, a measure of
regeneration light demand. Light-demanding species attained taller heights at
comparatively smaller diameters as juveniles and had shorter asymptotic
heights at larger diameters as adults. The relationship of crown area with
trunk diameter was best fit by a power function model incorporating a weak
positive relationship between crown area and species-specific wood density.
The use of saturating functional forms and the incorporation of functional
traits in tree allometric models is a promising approach for improving estimates
of forest biomass and productivity. Our results provide an improved basis for
parameterizing tropical plant functional types in vegetation models.</p
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A fire model with distinct crop, pasture, and non-agricultural burning: Use of new data and a model-fitting algorithm for FINAL.1
This study describes and evaluates the Fire
Including Natural & Agricultural Lands model (FINAL)
which, for the first time, explicitly simulates cropland and
pasture management fires separately from non-agricultural
fires. The non-agricultural fire module uses empirical relationships
to simulate burned area in a quasi-mechanistic
framework, similar to past fire modeling efforts, but with
a novel optimization method that improves the fidelity
of simulated fire patterns to new observational estimates
of non-agricultural burning. The agricultural fire components
are forced with estimates of cropland and pasture
fire seasonality and frequency derived from observational
land cover and satellite fire datasets. FINAL accurately
simulates the amount, distribution, and seasonal
timing of burned cropland and pasture over 2001â2009
(global totals: 0:434 x 10^6 and 2:02 x 10^6 km^2 yr-1 modeled,
0:454 x 10^6 and 2:04 x 10^6 km2 yr-1 observed), but carbon
emissions for cropland and pasture fire are overestimated
(global totals: 0.295 and 0.706 PgCyr-1 modeled, 0.194 and
0.538 PgCyr-1 observed). The non-agricultural fire module
underestimates global burned area (1:91 x 10^6 km2 yr-1 modeled,
2:44 x 10^6 km^2 yr-1 observed) and carbon emissions
(1.14 PgCyr-1 modeled, 1.84 PgCyr-1 observed). The spatial
pattern of total burned area and carbon emissions is generally
well reproduced across much of sub-Saharan Africa,
Brazil, Central Asia, and Australia, whereas the boreal zone
sees underestimates. FINAL represents an important step in the development of global fire models, and offers a strategy
for fire models to consider human-driven fire regimes on cultivated
lands. At the regional scale, simulations would benefit
from refinements in the parameterizations and improved
optimization datasets. We include an in-depth discussion of
the lessons learned from using the LevenbergâMarquardt algorithm
in an interactive optimization for a dynamic global
vegetation model
Constraining Fossil Fuel CO2 Emissions From Urban Area Using OCOâ2 Observations of Total Column CO2
Satellite observations of the total column dryâair CO2 (XCO2) are expected to support the quantification and monitoring of fossil fuel CO2 (ffCO2) emissions from urban areas. We evaluate the utility of the Orbiting Carbon Observatory 2 (OCOâ2) XCO2 retrievals to optimize wholeâcity emissions, using a Bayesian inversion system and highâresolution transport modeling. The uncertainties of constrained emissions related to transport model, satellite measurements, and local biospheric fluxes are quantified. For the first two uncertainty sources, we examine cities of different landscapes: âplume cityâ located in relatively flat terrain, represented by Riyadh and Cairo; and âbasin cityâ located in basin terrain, represented by Los Angeles (LA). The retrieved scaling factors of emissions and their uncertainties show prominent variabilities from track to track, due to the varying meteorological conditions and relative locations of the tracks transecting plumes. To explore the performance of multiple tracks in retrieving emissions, pseudo data experiments are carried out. The estimated least numbers of tracks required to constrain the total emissions for Riyadh (<10% uncertainty), Cairo (<10%), and LA (<5%) are 8, 5, and 7, respectively. Additionally, to evaluate the impact of biospheric fluxes on derivation of the ffXCO2 enhancements, we conduct simulations for Pearl River Delta metropolitan area. Significant fractions of local XCO2 enhancements associated with local biospheric XCO2 variations are shown, which potentially lead to biased estimates of ffCO2 emissions. We demonstrate that satellite measurements can be used to improve urban ffCO2 emissions with a sufficient amount of measurements and appropriate representations of the uncertainty components.Key PointsInversion method is utilized to constrain wholeâcity fossil fuel emissions with measurement and transport model errors consideredPotential of incorporating multiple tracks to obtain regular emission estimates is evaluated by pseudo data experimentsSignificant contribution of the biospheric fluxes variability to local XCO2 variation is demonstratedPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154979/1/jgrd56150_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154979/2/jgrd56150.pd
Convergence of bark investment according to fire and climate structures ecosystem vulnerability to future change
Fire regimes in savannas and forests are changing over much of the world. Anticipating the impact of these changes requires understanding how plants are adapted to fire. Here we test whether fire imposes a broad selective force on a key fire-tolerance trait, bark thickness, across 572 tree species distributed worldwide. We show that investment in thick bark is a pervasive adaptation in frequently burned areas across savannas and forests in both temperate and tropical regions where surface fires occur. Geographic variability in bark thickness is largely explained by annual burned area and precipitation seasonality. Combining environmental and species distribution data allowed us to assess the vulnerability to future climate and fire conditions: tropical rainforests are especially vulnerable, whereas seasonal forests and savannas are more robust. The strong link between fire and bark thickness provides an avenue for assessing the vulnerability of tree communities to fire and demands inclusion in global models
North American carbon dioxide sources and sinks: magnitude, attribution, and uncertainty
North America is both a source and sink of atmospheric carbon dioxide (CO2). Continental sources - such as fossil-fuel combustion in the US and deforestation in Mexico - and sinks - including most ecosystems, and particularly secondary forests - add and remove CO2 from the atmosphere, respectively. Photosynthesis converts CO2 into carbon as biomass, which is stored in vegetation, soils, and wood products. However, ecosystem sinks compensate for only similar to 35% of the continent's fossil-fuel-based CO2 emissions; North America therefore represents a net CO2 source. Estimating the magnitude of ecosystem sinks, even though the calculation is confounded by uncertainty as a result of individual inventory- and model-based alternatives, has improved through the use of a combined approach. Front Ecol Environ 2012; 10(10): 512-519, doi:10.1890/12006
A new evaluation of the uncertainty associated with CDIAC estimates of fossil fuel carbon dioxide emission
Three uncertainty assessments associated with the global total of carbon dioxide emitted from fossil fuel use and cement production are presented. Each assessment has its own strengths and weaknesses and none give a full uncertainty assessment of the emission estimates. This approach grew out of the lack of independent measurements at the spatial and temporal scales of interest. Issues of dependent and independent data are considered as well as the temporal and spatial relationships of the data. The result is a multifaceted examination of the uncertainty associated with fossil fuel carbon dioxide emission estimates. The three assessments collectively give a range that spans from 1.0 to 13% (2 Ï). Greatly simplifying the assessments give a global fossil fuel carbon dioxide uncertainty value of 8.4% (2 Ï). In the largest context presented, the determination of fossil fuel emission uncertainty is important for a better understanding of the global carbon cycle and its implications for the physical, economic and political world
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