Including the sub-grid scale plume rise of vegetation fires in low resolution atmospheric transport models

We describe and begin to evaluate a parameterization to include the vertical transport of hot gases and particles emitted from biomass burning in low resolution atmospheric-chemistry transport models. This sub-grid transport mechanism is simulated by embedding a 1-D cloud-resolving model with appropriate lower boundary conditions in each column of the 3-D host model. Through assimilation of remote sensing fire products, we recognize which columns have fires. Using a land use dataset appropriate fire properties are selected. The host model provides the environmental conditions, allowing the plume rise to be simulated explicitly. The derived height of the plume is then used in the source emission field of the host model to determine the effective injection height, releasing the material emitted during the flaming phase at this height. Model results are compared with CO aircraft profiles from an Amazon basin field campaign and with satellite data, showing the huge impact that this mechanism has on model performance. We also show the relative role of each main vertical transport mechanisms, shallow and deep moist convection and the pyro-convection (dry or moist) induced by vegetation fires, on the distribution of biomass burning CO emissions in the troposphere.

Signal classification of submerged aquatic vegetation based on the hemispherical-conical reflectance factor spectrum shape in the yellow and red regions

The water column overlying the submerged aquatic vegetation (SAV) canopy presents difficulties when using remote sensing images for mapping such vegetation. Inherent and apparent water optical properties and its optically active components, which are commonly present in natural waters, in addition to the water column height over the canopy, and plant characteristics are some of the factors that affect the signal from SAV mainly due to its strong energy absorption in the near-infrared. By considering these interferences, a hypothesis was developed that the vegetation signal is better conserved and less absorbed by the water column in certain intervals of the visible region of the spectrum; as a consequence, it is possible to distinguish the SAV signal. To distinguish the signal from SAV, two types of classification approaches were selected. Both of these methods consider the hemispherical-conical reflectance factor (HCRF) spectrum shape, although one type was supervised and the other one was not. The first method adopts cluster analysis and uses the parameters of the band (absorption, asymmetry, height and width) obtained by continuum removal as the input of the classification. The spectral angle mapper (SAM) was adopted as the supervised classification approach. Both approaches tested different wavelength intervals in the visible and near-infrared spectra. It was demonstrated that the 585 to 685-nm interval, corresponding to the green, yellow and red wavelength bands, offered the best results in both classification approaches. However, SAM classification showed better results relative to cluster analysis and correctly separated all spectral curves with or without SAV. Based on this research, it can be concluded that it is possible to discriminate areas with and without SAV using remote sensing. © 2013 by the authors; licensee MDPI, Basel, Switzerland.

Disturbances, elevation, topography and spatial proximity drive vegetation patterns along an altitudinal gradient of a top biodiversity hotspot

The correlation between vegetation patterns (species distribution and richness) and altitudinal variation has been widely reported for tropical forests, thereby providing theoretical basis for biodiversity conservation. However, this relationship may have been oversimplified, as many other factors may influence vegetation patterns, such as disturbances, topography and geographic distance. Considering these other factors, our primary question was: is there a vegetation pattern associated with substantial altitudinal variation (10-1,093 m a.s.l.) in the Atlantic Rainforest-a top hotspot for biodiversity conservation-and, if so, what are the main factors driving this pattern? We addressed this question by sampling 11 1-ha plots, applying multivariate methods, correlations and variance partitioning. The Restinga (forest on sandbanks along the coastal plains of Brazil) and a lowland area that was selectively logged 40 years ago were floristically isolated from the other plots. The maximum species richness (>200 spp. per hectare) occurred at approximately 350 m a.s.l. (submontane forest). Gaps, multiple stemmed trees, average elevation and the standard deviation of the slope significantly affected the vegetation pattern. Spatial proximity also influenced the vegetation pattern as a structuring environmental variable or via dispersal constraints. Our results clarify, for the first time, the key variables that drive species distribution and richness across a large altitudinal range within the Atlantic Rainforest. © 2013 Springer Science+Business Media Dordrecht.

Connectivity processes and riparian vegetation of the upper Paraná River, Brazil

In fluvial systems, the relationship between a dominant variable (e.g. flood pulse) and its dependent ones (e.g. riparian vegetation) is called connectivity. This paper analyzes the connectivity elements and processes controlling riparian vegetation for a reach of the upper Paraná River (Brazil) and estimates the future changes in channel-vegetation relationship as a consequence of the managing of a large dam. The studied reach is situated 30km downstream from the Porto Primavera Dam (construction finished in 1999). Through aerial photography (1:25,000, 1996), RGB-CBERS satellite imagery and a previous field botany survey it was possible to elaborate a map with the five major morpho-vegetation units: 1) Tree-dominated natural levee, 2) Shrubby upper floodplain, 3) Shrub-herbaceous mid floodplain, 4) Grass-herbaceous lower floodplain and 5) Shrub-herbaceous flood runoff channel units. By use of a detailed topographic survey and statistical tools each morpho-vegetation type was analyzed according to its connectivity parameters (frequency, recurrence, permanence, seasonality, potamophase, limnophase and FCQ index) in the pre- and post-dam closure periods of the historical series. Data showed that most of the morpho-vegetation units were predicted to present changes in connectivity parameters values after dam closing and the new regime could affect, in different intensity, the river ecology and particularly the riparian vegetation. The methods used in this study can be useful for dam impact studies in other South American tropical rivers. © 2012 Elsevier Ltd.

Hydromorphic Soil, Topographic Depression and Vegetation Development History by Using 13c and 14c In Rondônia State (sw Brazilian Amazon)

13C e 14C obtidos da matéria orgânica do solo foram usados para diferenciar fases de flutuação da vegetação em transição floresta-savana. A região apresenta baixos platôs com depressões topográficas imperfeitamente drenadas na superfície. Na topossequência estudada foram analisados solos de cinco perfis localizados sob floresta (F), transição floresta-savana (S1), borda da depressão sob savana (S2) e centro da depressão sob savana (S3). Os valores de 13C e idades evidenciam que a ~ 200cm de profundidade, com idades entre ~ 12.000 e 10.000 A.P., valores de -27‰ a -27,7‰ indicam vegetação de floresta (C3) em todos os perfis. Na profundidade de 100 cm, com idades entre ~ 6.000 e 5.000 A.P., houve enriquecimento de – 20,2‰ a -22,3‰, indicando regressão da floresta e expansão da savana. Valores entre -15,9 e -18,7‰ a 50-60 cm, estimado entre ~ 4.700 a 3.800 A.P., sugere máxima expansão da vegetação C4 em resposta às condições climáticas mais secas, exceto no perfil S3 com valores mais empobrecidos (-20,9‰), sugerindo que na depressão, o desenvolvimento da hidromorfia possibilitou a presença de espécies de gramíneas C3 e C4 da savana em resposta as mudanças das condições ambientais.

The role of native vegetation on infection rates of Calacarus heveae (Acari: Eriophyidae) by Hirsutella thompsonii (Ascomycota: Ophiocordycipitaceae)

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Mites from Cerrado fragments and adjacent soybean crops: does the native vegetation help or harm the plantation?

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Cerrado vegetation and global change: the role of functional types, resource availability and disturbance in regulating plant community responses to rising CO2 levels and climate warming

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Feedbacks between vegetation and disturbance processes promote long-term persistence of forest-grassland mosaics in south Brazil

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A multisensor, multitemporal approach for monitoring herbaceous vegetation growth in the Amazon floodplain

The Amazon River floodplain is an important source of atmospheric CO2 and CH4. Aquatic herbaceous vegetation (macrophytes) have been shown to contribute significantly to floodplain net primary productivity (NPP) and methane emission in the region. Their fast growth rates under both flooded and dry conditions make herbaceous vegetation the most variable element in the Amazon floodplain NPP budget, and the most susceptible to environmental changes. The present study combines multitemporal Radarsat-1 and MODIS images to monitor spatial and temporal changes in herbaceous vegetation cover in the Amazon floodplain. Radarsat-1 images were acquired from Dec/2003 to Oct/2005, and MODIS daily surface reflectance products were acquired for the two cloud-free dates closest to each Radarsat-1 acquisition. An object-based, hierarchical algorithm was developed using the temporal SAR information to discriminate Permanent Open Water (OW), Floodplain (FP) and Upland (UL) classes at Level 1, and then subdivide the FP class into Woody Vegetation (WV) and Possible Macrophytes (PM) at Level 2. At Level 3, optical and SAR information were combined to discriminate actual herbaceous cover at each date. The resulting maps had accuracies ranging from 80% to 90% for Level 1 and 2 classifications, and from 60% to 70% for Level 3 classifications, with kappa values ranging between 0.7 and 0.9 for Levels 1 and 2 and between 0.5 and 0.6 for Level 3. All study sites had noticeable variations in the extent of herbaceous cover throughout the hydrological year, with maximum areas up to four times larger than minimum areas. The proposed classification method was able to capture the spatial pattern of macrophyte growth and development in the studied area, and the multitemporal information was essential for both separating vegetation cover types and assessing monthly variation in herbaceous cover extent.

Estimation of Submerged Aquatic Vegetation Height and Distribution in Nova Avanhandava Reservoir (São Paulo State, Brazil) Using Bio-Optical Modeling

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Deriving vegetation indices for phenology analysis using genetic programming

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

NDVI and vegetation phenology dynamics under the influence of sunshine duration on the Tibetan plateau

Climate change has significantly influenced vegetation dynamics on the Tibetan Plateau (TP). Past research mainly focused on vegetation responses to temperature variation and water stress, but the influence of sunshine duration on NDVI and vegetation phenology on the TP is not well understood. In this study, NDVI time series from 1982-2008 were used to retrieve spatiotemporal vegetation dynamics on the TP. Empirical orthogonal function (EOF) analysis was conducted to understand the spatiotemporal variations of NDVI. The Start of Season (SOS) was estimated from NDVI time series with a local threshold method. The first EOF, accounting for 35.1% of NDVI variations on the TP, indicates that NDVI variations are larger in areas with shorter sunshine duration. The needle-leaved forest and shrub in the southeastern TP are more sensitive to sunshine duration anomalies (p < 0.01) than broad-leaved forest, steppe, and meadow due to spatial and altitudinal distribution of sunshine duration and vegetation types. The decrease in sunshine duration for the growing season on the TP has resulted in a decreased NDVI trend in some areas of southeastern TP (p ranging from 0.32-0.05 with threshold ranging from 0.05 to 0.25) in spite of the overall NDVI increase. SOS dynamics in most parts of the TP were mainly related to temperature variability, with precipitation and sunshine duration playing a role in a few regions. This study enhances our understanding of vegetation responses to climatic change on the TP.

Combining ALOS/PALSAR derived vegetation structure and inundation patterns to characterize major vegetation types in the Mamiraua Sustainable Development Reserve, Central Amazon floodplain, Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)