Showing papers on "Vegetation (pathology) published in 2007"

Theory of quantitative reconstruction of vegetation I: pollen from large sites REVEALS regional vegetation composition:

Abstract: Quantitative reconstruction of past vegetation is one of the primary goals in Quaternary palynology and palaeoecology but still remains difficult. This paper proposes a model, REVEALS, that estimates regional vegetation composition using pollen from ‘large lakes’ that have small site-to-site variations of pollen assemblages even if vegetation is highly heterogeneous. Once these data have been used to quantify regional vegetation composition within 104 -105 km2, background pollen, one of the parameters crucial for vegetation reconstruction, can be estimated for smaller-sized sites, and incorporated into the Landscape Reconstruction Algorithm (LRA), a multistep framework for quantitative reconstruction of vegetation in smaller areas (≤ 104 ha). Simulations using the POLLSCAPE modelling show that REVEALS can provide accurate estimates of regional vegetation composition in various landscapes and under different atmospheric conditions. If pollen assemblages from lakes that are much smaller than ‘large lakes’ a...

Sensitivity of the Enhanced Vegetation Index (EVI) and Normalized Difference Vegetation Index (NDVI) to Topographic Effects: A Case Study in High-Density Cypress Forest

Abstract: Vegetation indices play an important role in monitoring variations in vegetation.The Enhanced Vegetation Index (EVI) proposed by the MODIS Land Discipline Groupand the Normalized Difference Vegetation Index (NDVI) are both global-based vegetationindices aimed at providing consistent spatial and temporal information regarding globalvegetation. However, many environmental factors such as atmospheric conditions and soilbackground may produce errors in these indices. The topographic effect is another veryimportant factor, especially when the indices are used in areas of rough terrain. In thispaper, we theoretically analyzed differences in the topographic effect on the EVI and theNDVI based on a non-Lambertian model and two airborne-based images acquired from amountainous area covered by high-density Japanese cypress plantation were used as a casestudy. The results indicate that the soil adjustment factor "L" in the EVI makes it moresensitive to topographic conditions than is the NDVI. Based on these results, we stronglyrecommend that the topographic effect should be removed in the reflectance data beforethe EVI was calculated-as well as from other vegetation indices that similarly include a term without a band ratio format (e.g., the PVI and SAVI)-when these indices are used in the area of rough terrain, where the topographic effect on the vegetation indices having only a band ratio format (e.g., the NDVI) can usually be ignored.

Theory of quantitative reconstruction of vegetation II: all you need is LOVE

Abstract: This paper describes the LOVE (LOcal Vegetation Estimates) model for estimating local vegetation composition within the relevant source area of pollen. This model quantifies and then subtracts background pollen (ie, pollen coming from beyond the relevant source area) in order to arrive at a quantitative reconstruction of local vegetation. Parameters required for LOVE applications are pollen counts from target sites, the relevant source area of pollen of these sites, pollen productivity estimates and regional vegetation composition within 104 -105 km2. Regional vegetation composition is obtained using fossil pollen from large sites (≥102 ha) with the REVEALS (Regional Estimates of VEgetation Abundance from Large Sites) model, the first step of the Landscape Reconstruction Algorithm (LRA) specifically designed for LOVE applications. POLLSCAPE simulations demonstrate that (1) regional vegetation composition can be used to predict background pollen at and beyond the relevant source area of pollen for given-si...

Vegetation causes channel erosion in a tidal landscape

Abstract: Vegetation is traditionally regarded to reduce the erosion of channels in both fl uvial and tidal landscapes. We present a coupled hydrodynamic, morphodynamic, and plant growth model that simulates plant colonization and channel formation on an initially bare, fl at substrate, and apply this model to a tidal landscape. The simulated landscape evolution is compared with aerial photos. Our results show that reduction of erosion by vegetation is only the local, on-site effect operating within static vegetation. Dynamic vegetation patches, which can expand or shrink, have a contrasting larger scale, off-site effect: they obstruct the fl ow, leading to flconcentration and channel erosion between laterally expanding vegetation patches. In contrast with traditional insights, our fi ndings imply that in tidal landscapes, which are colonized by denser vegetation, channels are formed with a higher channel drainage density. Hence this study demonstrates that feedbacks between vegetation, fl ow, and landform have an important control on landscape evolution.

Unexpected impacts of climate change on alpine vegetation

Abstract: The vegetation in a high alpine site of the European Alps experienced changes in area between 1953 and 2003 as a result of climate change. Shrubs showed rapid expansion rates of 5.6% per decade at altitudes between 2400 m and 2500 m. Above 2500 m, vegetation coverage exhibited unexpected patterns of regression associated with increased precipitation and permafrost degradation. As these changes follow a sharp increase in both summer and annual temperatures after 1980, we suggest that vegetation of the alpine (2400–2800 m) and nival (above 2800 m) belts respond in a fast and flexible way, contradicting previous hypotheses that alpine and nival species appear to have a natural inertia and are able to tolerate an increase of 1–2°C in mean air temperature.

Diverse responses of vegetation phenology to a warming climate

Abstract: [1] Warming climates have been widely recognized to advance spring vegetation phenology. However, the delayed responses of vegetation phenology to rising temperature and their mechanisms are poorly understood. Using satellite and climate data from 1982 to 2005, we reveal a latitude transition zone of greenup onset in vegetation communities that has diversely responded to warming temperature in North America. From 40°N northwards, a winter chilling requirement for vegetation dormancy release is far exceeded and the decrease in chilling days by warming winter temperature has little impact on thermal-time requirements for greenup onset. Thus, warming spring temperature has constantly advanced greenup onset by 0.32 days/year. However, from 40°N southward, the shortened winter chilling days are insufficient for fulfilling vegetation chilling requirement, so that the thermal-time requirement for greenup onset during spring increases gradually. Consequently, vegetation greenup onset changes progressively from an early trend (north region) to a later trend (south region) along the latitude transition zone from 40–31°N, where the switch occurs around 35°N. The greenup onset is delayed by 0.15 days/year below 31°N.

Early onset of vegetation growth vs. rapid green-up: impacts on juvenile mountain ungulates

Abstract: Seasonal patterns of climate and vegetation growth are expected to be altered by global warming. In alpine environments, the reproduction of birds and mammals is tightly linked to seasonality; therefore such alterations may have strong repercussions on recruitment. We used the normalized difference vegetation index (NDVI), a satellite-based measurement that correlates strongly with aboveground net primary productivity, to explore how annual variations in the timing of vegetation onset and in the rate of change in primary production during green-up affected juvenile growth and survival of bighorn sheep (Ovis canadensis), Alpine ibex (Capra ibex), and mountain goats (Oreamnos americanus) in four different populations in two continents. We indexed timing of onset of vegetation growth by the integrated NDVI (INDVI) in May. The rate of change in primary production during green-up (early May to early July) was estimated as (1) the maximal slope between any two successive bimonthly NDVI values during this period and (2) the slope in NDVI between early May and early July. The maximal slope in NDVI was negatively correlated with lamb growth and survival in both populations of bighorn sheep, growth of mountain goat kids, and survival of Alpine ibex kids, but not with survival of mountain goat kids. There was no effect of INDVI in May and of the slope in NDVI between early May and early July on juvenile growth and survival for any species. Although rapid changes in NDVI during the green-up period could translate into higher plant productivity, they may also lead to a shorter period of availability of high-quality forage over a large spatial scale, decreasing the opportunity for mountain ungulates to exploit high-quality forage. Our results suggest that attempts to forecast how warmer winters and springs will affect animal population dynamics and life histories in alpine environments should consider factors influencing the rate of changes in primary production during green-up and the timing of vegetation onset.

Note on the NDVI-LST relationship and the use of temperature-related drought indices over North America

Abstract: [1] A comprehensive evaluation of the relationship between vegetation and Land Surface Temperature (LST) over the North America is presented. It is found that the correlations between LST and Normalized Difference Vegetation Index (NDVI) depend on the season-of-year and time-of-day. For winter, the correlation between NDVI and LST is positive. The strong negative correlations between LST and NDVI are only found during the warm seasons. Thus temperature-related drought indices may only be used in the warm seasons from May to October, and should be used with caution during cold seasons in North America. The cooling effect of vegetation on LST is stronger during daytime than nighttime. Moreover, the negative correlations between NDVI and LST are much stronger than those between NDVI and the brightness temperature. Therefore using daytime LST for drought monitoring should be more reasonable than using brightness temperature or nighttime LST.

Significance of the riparian vegetation dynamics on meandering river morphodynamics

Abstract: [1] A river and its surrounding riparian vegetation are two dynamical systems that interact through several hydrological, geomorphological, and ecological processes. This work focuses on the role played by vegetation on meandering river morphodynamics: River planform evolution forces the riparian vegetation dynamics, which, in turn, affect the mechanical characteristics of the river banks and influence the meandering dynamics of the river itself. It follows that despite the fact that a traditional engineering approach considers vegetation as a static element the study of river morphodynamics should be coupled with the riparian vegetation evolution. To this end, a fluid dynamic model of meandering rivers is here coupled with a process-based model for the riparian biomass dynamics. The feedback of vegetation on river morphology is provided by a relation that links the biomass density to the bank erodibility. The numerical results highlight (1) the remarkable effects of the vegetation dynamics on meander evolution and (2) the role of the temporal scales of vegetation growth and decay in relation to typical morphodynamic scales. In particular, the differences with respect to the constant erodibility case can be of the order of tens or hundreds of meters (10–20% of the meander wavelength), and peculiar meander shapes that do not show the usual marked upstream skewness emerge.

Functional convergence in regulation of net CO2 flux in heterogeneous tundra landscapes in Alaska and Sweden

Abstract: 1. Arctic landscapes are characterized by extreme vegetation patchiness, often with sharply defined borders between very different vegetation types. This patchiness makes it difficult to predict landscape-level C balance and its change in response to environment. 2. Here we develop a model of net CO2 flux by arctic landscapes that is independent of vegetation composition, using instead a measure of leaf area derived from NDVI (normalized-difference vegetation index). 3. Using the light response of CO2 flux (net ecosystem exchange, NEE) measured in a wide range of vegetation in arctic Alaska and Sweden, we exercise the model using various data subsets for parameter estimation and tests of predictions. 4. Overall, the model consistently explains similar to 80% of the variance in NEE knowing only the estimated leaf area index (LAI), photosynthetically active photon flux density (PPFD) and air temperature. 5. Model parameters derived from measurements made in one site or vegetation type can be used to predict NEE in other sites or vegetation types with acceptable accuracy and precision. Further improvements in model prediction may come from incorporating an estimate of moss area in addition to LAI, and from using vegetation-specific estimates of LAI. 6. The success of this model at predicting NEE independent of any information on species composition indicates a high level of convergence in canopy structure and function in the arctic landscape.

Object-Based Classification of Ikonos Imagery for Mapping Large-Scale Vegetation Communities in Urban Areas

Abstract: Effective assessment of biodiversity in cities requires detailed vegetation maps.To date, most remote sensing of urban vegetation has focused on thematically coarse landcover products. Detailed habitat maps are created by manual interpretation of aerialphotographs, but this is time consuming and costly at large scale. To address this issue, wetested the effectiveness of object-based classifications that use automated imagesegmentation to extract meaningful ground features from imagery. We applied thesetechniques to very high resolution multispectral Ikonos images to produce vegetationcommunity maps in Dunedin City, New Zealand. An Ikonos image was orthorectified and amulti-scale segmentation algorithm used to produce a hierarchical network of image objects.The upper level included four coarse strata: industrial/commercial (commercial buildings),residential (houses and backyard private gardens), vegetation (vegetation patches larger than0.8/1ha), and water. We focused on the vegetation stratum that was segmented at moredetailed level to extract and classify fifteen classes of vegetation communities. The firstclassification yielded a moderate overall classification accuracy (64%, κ = 0.52), which ledus to consider a simplified classification with ten vegetation classes. The overallclassification accuracy from the simplified classification was 77% with a κ value close tothe excellent range (κ = 0.74). These results compared favourably with similar studies inother environments. We conclude that this approach does not provide maps as detailed as those produced by manually interpreting aerial photographs, but it can still extract ecologically significant classes. It is an efficient way to generate accurate and detailed maps in significantly shorter time. The final map accuracy could be improved by integrating segmentation, automated and manual classification in the mapping process, especially when considering important vegetation classes with limited spectral contrast.

TIMESAT - a Program for Analyzing Time-Series of Satellite Sensor Data Users Guide for TIMESAT 2.3

Abstract: Time-series of vegetation index derived from satellite spectral measurements can be used to gain information on seasonal vegetation development. This information aids analyzes of the functional and ...

Global change shifts vegetation and plant–parasite interactions in a boreal mire

Abstract: The aim of this study was to detect vegetation change and to examine trophic interactions in a Sphagnum-dominated mire in response to raised temperature and nitrogen (N) addition. A long-term globa ...

A review of vegetation—atmosphere interactions and their influences on mesoscale phenomena

Abstract: Vegetation strongly influences exchanges of energy and moisture between land and atmosphere through (1) the vegetation's response to incoming radiation and its emission of longwave radiation (2) the vegetation's physical presence, and (3) the plant's transpiration. These processes affect the diurnal temperature range, processes in the atmospheric boundary layer, cloud cover, rainfall, differential heating, and atmospheric circulations. This paper overviews how vegetation interacts with surface energy and moisture budgets and reviews both observational and modelling studies that examine how vegetation affects weather and climate on the mesoscale (ie, phenomena 10s to 100s of kilometres in horizontal size).

Riparian hydroecology: A coupled model of the observed interactions between groundwater flow and meadow vegetation patterning

Abstract: [1] Stream incision is altering the hydroecology of riparian areas worldwide. In the Last Chance watershed in the northern Sierra Nevada, California, logging, overgrazing, and road/railroad construction have caused stream incision, which resulted in drainage of riparian meadow sediments and a succession from native wet meadow vegetation to sagebrush and dryland grasses. Restoration efforts have been initiated to reestablish the ecosystem function of these systems. Original field data including stream stage records, water table hydrographs, sediment hydraulic properties, topographic transects, and aerial imagery of vegetation patterning were used to develop a model of an archetype meadow. Hydrologic behavior was simulated with a finite element model of variably saturated groundwater flow. This model was coupled to an empirical, time-dependent, vegetation threshold relationship between vegetation type and depth to the water table. This was a two-way coupling requiring an iterative approach because water table depth is a determinant of vegetation type, yet the vegetation regime influences water table depth through evapotranspiration. The hydrology and vegetation patterns were analyzed under pristine, degraded (incised), and restored conditions. For the case of deep streambed incision, our hydroecological model predicts the observed shift from mesic (wetter) to xeric (drier) vegetation communities and reproduces their imaged longitudinal zonation. This patterning is explained as a response to groundwater drainage to the stream, which creates dry zones with xeric vegetation adjacent to the stream, while preserving sufficient moisture at the margins of the meadow to support holdout populations of mesic vegetation. The model further predicts the reestablishment of meadow vegetation when the incised channel is filled and a new shallow channel is restored. The coupling of a near-surface hydrologic model to a vegetation response model may be used to design stream restoration projects by predicting vegetation patterning.

Assessment of Vegetation Stress Using Reflectance or Fluorescence Measurements

Abstract: Current methods for large-scale vegetation monitoring rely on multispectral remote sensing, which has serious limitation for the detection of vegetation stress. To contribute to the establishment of a generalized spectral approach for vegetation stress detection, this study compares the ability of high-spectral-resolution reflectance (R) and fluorescence (F) foliar measurements to detect vegetation changes associated with common environmental factors affecting plant growth and productivity. To obtain a spectral dataset from a broad range of species and stress conditions, plant material from three experiments was examined, including (i) corn, nitrogen (N) deficiency/excess; (ii) soybean, elevated carbon dioxide, and ozone levels; and (iii) red maple, augmented ultraviolet irradiation. Fluorescence and R spectra (400-800 nm) were measured on the same foliar samples in conjunction with photosynthetic pigments, carbon, and N content. For separation of a wide range of treatment levels, hyperspectral (5-10 nm) R indices were superior compared with F or broadband R indices, with the derivative parameters providing optimal results. For the detection of changes in vegetation physiology, hyperspectral indices can provide a significant improvement over broadband indices. The relationship of treatment levels to R was linear, whereas that to F was curvilinear. Using reflectance measurements, it was not possible to identify the unstressed vegetation condition, which was accomplished in all three experiments using F indices. Large-scale monitoring of vegetation condition and the detection of vegetation stress could be improved by using hyperspectral R and F information, a possible strategy for future remote sensing missions.

Classification of floodplain vegetation by data fusion of spectral (CASI) and LiDAR data

Abstract: To safeguard the goals of flood protection and nature development, a river manager requires detailed and up-to-date information on vegetation structures in floodplains. In this study, remote-sensing data on the vegetation of a semi-natural floodplain along the river Waal in the Netherlands were gathered by means of a Compact Airborne Spectrographic Imager (CASI; spectral information) and LiDAR (structural information). These data were used to classify the floodplain vegetation into eight and five different vegetation classes, respectively. The main objective was to fuse the CASI and LiDAR-derived datasets on a pixel level and to compare the classification results of the fused dataset with those of the non-fused datasets. The performance of the classification results was evaluated against vegetation data recorded in the field. The LiDAR data alone provided insufficient information for accurate classification. The overall accuracy amounted to 41% in the five-class set. Using CASI data only, the overall accuracy was 74% (five-class set). The combination produced the best results, raising the overall accuracy to 81% (five-class set). It is concluded that fusion of CASI and LiDAR data can improve the classification of floodplain vegetation, especially for those vegetation classes which are important to predict hydraulic roughness, i.e. bush and forest. A novel measure, the balance index, is introduced to assess the accuracy of error matrices describing an ordered sequence of classes such as vegetation structure classes that range from bare soil to forest.