499 research outputs found
Leaf area distribution and radiative transfer in open-canopy forests: implications for mass and energy exchange
No full textLeaf area and its spatial distribution are key canopy parameters needed to model the radiation regime within a forest and to compute the mass and energy exchange between a forest and the atmosphere. A much larger proportion of available net radiation is received at the forest floor in open-canopy
forests than in closed-canopy forests. The proportion of ecosystem water vapor exchange (ëE) and sensible heat exchange from the forest floor is therefore expected to be larger in opencanopy forests than in closed-canopy forests. We used a combination of optical and canopy geometry measurements, and robust one- and three-dimensional models
to evaluate the influence of canopy architecture and radiative transfer on estimates of carbon, water and energy exchange of a ponderosa pine (Pinus ponderosa Dougl. ex Laws.) forest. Three-dimensional model simulations showed that the average probability of diffuse and direct radiation transmittance to the forest floor was greater than if a random distribution of foliage had been assumed. Direct and diffuse radiation transmittance
to the forest floor was 28 and 39%, respectively, in the three-dimensional model simulations versus 23 and 31%, respectively,
in the one-dimensional model simulations. The assumption of randomly distributed foliage versus inclusion of clumping factors in a one-dimensional, multi-layer biosphereatmosphere gas exchange model (CANVEG) had the greatest effect on simulated annual net ecosystem exchange (NEE) and soil evaporation. Assuming random distribution, NEE was 41% lower, net photosynthesis 3% lower, total ëE 10% lower,
and soil evaporation 40% lower. The same comparisons at LAI 5 showed a similar effect on annual NEE estimates (37%) and ëE (12%), but a much larger effect on net photosynthesis (20%), suggesting that, at low LAI, canopies are mostly sunlit, so that redistribution of light has little effect on net photosynthesis, whereas the effect on net photosynthesis is much greater at high LAI
Estimation of leaf area index in open-canopy ponderosa pine forests at different successional stages and management regimes in Oregon
No full textLeaf area and its spatial distribution are key parameters in describing canopy characteristics. They determine radiation
regimes and influence mass and energy exchange with the atmosphere. The evaluation of leaf area in conifer stands is
particularly challenging due to their open nature and clumping on the needle, shoot and tree scale. The overall objective of our
study was to characterize leaf area index (LAI) (Lh, m2 half-surface area foliage m-2 ground) in the vicinity of our old-growth
and 14-year-old ponderosa pine (Pinus ponderosa, var. Laws) eddy covariance flux sites, with future plans to scale from
the flux sites to the pine region using ecosystem models and remote sensing. From the combination of optical and canopy
geometry measurements, sapwood and litter-fall measurements, and one- and three-dimensional (3-D) models, we evaluated
the variation in estimates of Lh in a mixed-age stand at the old-growth flux site. We also compared sapwood area estimates from a local allometric equation with LAI-2000 estimates that have been corrected for clumping and the interception of light
by stems and branches (Lhc, m2 half-surface area m-2 ground) across a range of age classes and stand densities of ponderosa
pine forests along a 15 km swath in Central Oregon that encompassed the flux sites. In the old-growth stand, the litter-fall and
sapwood estimates tended to be higher than the optical and 3-D radiative transfer model estimates. Across the 15 km east–west
gradient from the crest of the Cascade Mountains, Lhc was typically lower than the sapwood estimates (Lhsw; slope 0.38). The
Lhc data, as well as aboveground production estimates for the 17 pine plots will be useful for scaling flux measurements to the
region using ecosystem models that have been validated with these dat
A fuel dryness index for grassland fire danger assessment”
No full textAbstract
The assessment of fuel moisture content on a large spatial scale requires several observations and estimates and is often time consuming and costly due to labour and transportation expenses. Therefore, various models based on empirical functions of weather variables have been developed and applied to determine the amount of moisture in fuel. In this paper, a fuel dryness index (F-d) based on biophysical principles associated with energy exchange is presented and applied to monitor fuel moisture content for annual grasslands. Daily values of F-d were determined as the ratio of sensible heat flux density to the available energy using high-frequency temperature data and the surface renewal (SR) method in combination with net radiation and soil heat flux values. The SR method was evaluated by comparing with sensible and latent heat flux densities from eddy covariance data measured in a fire-vulnerable annual grassland. The F-d values and trends were compared with three well-known slow response fire-danger indices including the Keetch-Byram drought index, two modified versions of the drought factor in the McArthur forest fire-danger meter, and the fast response fine fuel moisture code of the Canadian fire weather index. Moreover, Fd index was compared with the McArthur grassland fire-danger meter. The Fd index was more responsive to daily changes than most of the other indices, providing accurate information on fuel dryness condition of a live vegetation grassland. In addition, it can potentially eliminate the need for calibrated empirical weather models and fuel stick measurements. (c) 2006 Elsevier B.V. All rights reserved
Convergence of potential net ecosystem production among contrasting C3 grasslands
No full textPrevious synthesis studies concluded that net ecosystem production (NEP) differs among contrasting C3 grasslands. However, it has not yet been investigated whether differences in ecosystem traits, environment and management alter the intrinsic potential NEP (NEPPOT) and thereby explain some of the range in annual apparent NEP. We estimated NEPPOT for nine C3 grasslands under contrasting climate and management regimes using multi-year eddy-covariance data. NEPPOT converged within a narrow range suggesting no differences in the net CO2 uptake capacity across C3 grasslands. Our results indicate a unique feature of C3 grasslands compared to other terrestrial ecosystems and suggest a state of stability in NEP based on coupled production and respiration processes during non-limiting conditions. Consequently, the annual CO2 sink-source strength of C3 grasslands is primarily a function of seasonal and short-term environmental and management constraints, and therefore especially susceptible to changes in future climate patterns and associated adaptation of management practices
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Complexity in Climatic Controls on Plant Species Distribution: Satellite Data Reveal Unique Climate for Giant Sequoia in the California Sierra Nevada
No full textA better understanding of the environmental controls on current plant species distribution is essential if the impacts of such diverse challenges as invasive species, changing fire regimes, and global climate change are to be predicted and important diversity conserved. Climate, soil, hydrology, various biotic factors fire, history, and chance can all play a role, but disentangling these factors is a daunting task. Increasingly sophisticated statistical models relying on existing distributions and mapped climatic variables, among others, have been developed to try to answer these questions. Any failure to explain pattern with existing mapped climatic variables is often taken as a referendum on climate as a whole, rather than on the limitations of the particular maps or models. Every location has a unique and constantly changing climate so that any distribution could be explained by some aspect of climate. Chapter 1 of this dissertation reviews some of the major flaws in species distribution modeling and addresses concerns that climate may therefore not be predictive of, or even relevant to, species distributions. Despite problems with climate-based models, climate and climate-derived variables still have substantial merit for explaining species distribution patterns. Additional generation of relevant climate variables and improvements in other climate and climate-derived variables are still needed to demonstrate this more effectively. Satellite data have a long history of being used for vegetation mapping and even species distribution mapping. They have great potential for being used for additional climatic information, and for improved mapping of other climate and climate-derived variables. Improving the characterization of cloud cover frequency with satellite data is one way in which the mapping of important climate and climate-derived variables can be improved. An important input to water balance models, solar radiation maps could be vastly improved with a better mapping of spatial and temporal patterns in cloud cover. Chapter 2 of this dissertation describes the generation of custom daily cloud cover maps from Advanced Very High Resolution Radiometer (AVHRR) satellite data from 1981-1999 at ~5 km resolution and Moderate Resolution Imagine Spectroradiomter (MODIS) satellite reflectance data at ~500 meter resolution for much of the western U.S., from 2000 to 2012. Intensive comparisons of reflectance spectra from a variety of cloud and snow-covered scenes from the southwestern United States allowed the generation of new rules for the classification of clouds and snow in both the AVHRR and MODIS data. The resulting products avoid many of the problems that plague other cloud mapping efforts, such as the tendency for snow cover and bright desert soils to be mapped as cloud. This consistency in classification across cover types is critically important for any distribution modeling of a plant species that might be dependent on cloud cover. In Chapter 3, monthly cloud frequencies derived from the daily classifications were used directly in species distribution models for giant sequoia and were found to be the strongest predictors of giant sequoia distribution. A high frequency of cloud cover, especially in the spring, differentiated the climate of the west slope of the southern Sierra Nevada, where giant sequoia are prolific, from central and northern parts of the range, where the tree is rare and generally absent. Other mapped cloud products, contaminated by confusion with high elevation snow, would likely not have found this important result. The result illustrates the importance of accuracy in mapping as well as the importance of previously overlooked aspects of climate for species distribution modeling. But it also raises new questions about why the clouds form where they do and whether they might be associated with other aspects of climate important to giant sequoia distribution. What are the exact climatic mechanisms governing the distribution? Detailed aspects of the local climate warranted more investigation. Chapter 4 investigates the climate associated with the frequent cloud formation over the western slopes of the southern Sierra Nevada: the "sequoia belt". This region is climatically distinct in a number of ways, all of which could be factors in influencing the distribution of giant sequoia and other species. Satellite and micrometeorological flux tower data reveal characteristics of the sequoia belt that were not evident with surface climate measurements and maps derived from them. Results have implications for species distributions everywhere, but especially in rugged mountains, where climates are complex and poorly mapped. Chapter 5 summarizes some of the main conclusions from the work and suggests directions for related future research. (Abstract shortened by UMI.
Quantitative remote sensing of vegetation properties and functioning under normal and dry conditions
No full textThe main idea of this research is to exploit multiple observations including time-series of optical, thermal (TIR) and soil moisture data for remote sensing of vegetation properties and functioning under normal and dry conditions. It is significant to investigate the information content of such observations and quantify the impact of their synergistic use to explain drought effects on vegetation functioning. Therefore, understanding how much information one can get from different sensors (e.g., optical, TIR and soil moisture) to see vegetation (here for annual C3 grasses) properties and functioning (notably canopy photosynthesis [gross primary production (GPP)] and evapotranspiration (ET)) variations during a drought episode and whether combined use of this information can enhance vegetation functioning estimations is of great interest. This study describes the importance of plant functioning, drought effects, application of remote sensing and in-situ observations, methods for plant functioning assessment, the proposed coupled modeling approach. For more information, the reader is refereed to the digital version of the thesis here:
https://library.itc.utwente.nl/papers_2018/phd/bayat.pd
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Near-surface remote sensing of canopy architecture and land-atmosphere interactions in an oak savanna ecosystem
No full textCanopy architecture plays fundamental roles in the land-atmosphere interactions, yet quantification of canopy architecture using optical sensors in an open canopy remains a challenge. Savannas are spatially heterogeneous, open ecosystems, thus efforts to quantify canopy structure with methods developed for homogeneous, closed canopies are prone to failure. I employed a multi-model and multi-instrument approach to quantify leaf area index in an oak savanna ecosystem of California. I found that the effective area index should be calculated by taking the logarithm of average gap fraction. Contrary to boreal and temperate forests, the savanna ecosystem was highly clumped at the ecosystem scale (clumping index=0.49). Thus quantification of clumping effects at the ecosystem scale, which has been overlooked in most leaf area index products, is crucial to obtain the correct leaf area index. To investigate how evaporation in the annual grassland of the savanna ecosystem is modulated by biological/environmental factors, I investigated the 6 year evaporation data measured with a eddy covariance system. The annual evaporation ranged between 266 mm to 391 mm despite a two-fold range in precipitation. I found that the pronounced energy-limited and water-limited periods occurred within the same year. In the water-limited period, monthly integrated evaporation scaled negatively with solar radiation and was restrained by precipitation. In the energy-limited period, on the other hand, the majority of evaporation scaled positively with solar radiation and was confined by potential evaporation. Evaporation was most sensitive to the availability of soil moisture during the transition to the senescence period rather than the onset of the greenness period, causing annual evaporation to be strongly modulated by the length of growing season.To bridge canopy structure, function and metabolism, I tested the use of light emitting diodes (LEDs) to monitor the vegetation reflectance in narrow spectral bands. LEDs are appealing because they are inexpensive, small and reliable light sources that used in reverse mode, can measure spectrally selective radiation. To test the efficacy of this approach, I measured the spectral reflectance with LEDs in red and near-infrared wavebands, which are used to calculate the normalized difference vegetation index over the grassland over 3.5 years. The LED-spectrometer captured daily to inter-annual variation of the spectral reflectance at the two bands with reliable and stable performance. The spectral reflectance in the two bands and NDVI proved to be useful to identify the leaf-on and leaf-off dates (mean bias errors of 5.3 and 4.2 days, respectively) and to estimate the canopy photosynthesis (r2=0.91). I suggest that this novel instrument can monitor other structural and functional (e.g. leaf area index, leaf nitrogen) variables by employing the LEDs that have other specific wavelengths bands. Considering that off-the-shelf LEDs cover a wide range of wavebands from the ultraviolet to near-infrared regions, I believe that the research community could explore a range of similar instruments across a range of bands for a variety of ecological applications.The regular monitoring of evaporation from satellites has been limited because of discontinuous temporal coverage. Here, I found a strong linear relationship between mean hourly λE (i.e., 1000-1100hh; 1100-1200hh; 1200-1300hh; 1300-1400hh) and 8-day means of λE at 26 eddy covariance flux towers across seven plant functional types from boreal to tropical climatic zones. Hourly time steps of evaporation were selected to correspond with potential overpass times of the MODIS Terra and Aqua satellites. The mean slope of the linear relationship between mean hourly means of evaporation and 8-day, 24-h evaporation means showed no significant differences among sites and for each of the four mid-day hours. The results suggest a factor of 0.370 (95% CI: 0.354, 0.385) can be used to temporally upscale instantaneous evaporation measurements averaged over 8-day periods to an 8-day mean evaporation
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