Influência das condições ambientais no verdor da vegetação da caatinga frente às mudanças climáticas

The Caatinga biome, a semi-arid climate ecosystem found in northeast Brazil, presents low rainfall regime and strong seasonality. It has the most alarming climate change projections within the country, with air temperature rising and rainfall reduction with stronger trends than the global average predictions. Climate change can present detrimental results in this biome, reducing vegetation cover and changing its distribution, as well as altering all ecosystem functioning and finally influencing species diversity. In this context, the purpose of this study is to model the environmental conditions (rainfall and temperature) that influence the Caatinga biome productivity and to predict the consequences of environmental conditions in the vegetation dynamics under future climate change scenarios. Enhanced Vegetation Index (EVI) was used to estimate vegetation greenness (presence and density) in the area. Considering the strong spatial and temporal autocorrelation as well as the heterogeneity of the data, various GLS models were developed and compared to obtain the best model that would reflect rainfall and temperature influence on vegetation greenness. Applying new climate change scenarios in the model, environmental determinants modification, rainfall and temperature, negatively influenced vegetation greenness in the Caatinga biome. This model was used to create potential vegetation maps for current and future of Caatinga cover considering 20% decrease in precipitation and 1 °C increase in temperature until 2040, 35% decrease in precipitation and 2.5 °C increase in temperature in the period 2041-2070 and 50% decrease in precipitation and 4.5 °C increase in temperature in the period 2071-2100. The results suggest that the ecosystem functioning will be affected on the future scenario of climate change with a decrease of 5.9% of the vegetation greenness until 2040, 14.2% until 2070 and 24.3% by the end of the century. The Caatinga vegetation in lower altitude areas (most of the biome) will be more affected by climatic changes.

Sensitivity of the Amazon biome to high resolution climate change projections

ABSTRACT: Despite the reduction in deforestation rate in recent years, the impact of global warming by itself can cause changes in vegetation cover. The objective of this work was to investigate the possible changes on the major Brazilian biome, the Amazon Rainforest, under different climate change scenarios. The dynamic vegetation models may simulate changes in vegetation distribution and the biogeochemical processes due to climate change. Initially, the Inland dynamic vegetation model was forced with initial and boundary conditions provided by CFSR and the Eta regional climate model driven by the historical simulation of HadGEM2-ES. These simulations were validated using the Santarém tower data. In the second part, we assess the impact of a future climate change on the Amazon biome by applying the Inland model forced with regional climate change projections. The projections show that some areas of rainforest in the Amazon region are replaced by deciduous forest type and grassland in RCP4.5 scenario and only by grassland in RCP8.5 scenario at the end of this century. The model indicates a reduction of approximately 9% in the area of tropical forest in RCP4.5 scenario and a further reduction in the RCP8.5 scenario of about 50% in the eastern region of Amazon. Although the increase of CO2 atmospheric concentration may favour the growth of trees, the projections of Eta-HadGEM2-ES show increase of temperature and reduction of rainfall in the Amazon region, which caused the forest degradation in these simulations.

INFLUENTIAL FACTORS IN SURFACE WATER QUALITY IN CATCHMENTS WITHIN THE PAMPA BIOME WITH DIFFERENT LAND USE1

The aim of this study was to identify, by multivariate statistical technique, the physic, chemical and biological variables that best characterize the quality of surface waters in two small rural catchments with different land uses (eucalyptus silviculture (SC) vs. pasture and extensive livestock (LC)) located in Rosário do Sul, RS - Brazil. Monitoring was conducted during the months of August 2011 to August 2012 and the following parameters were analyzed: Ca2+, Mg2+, K+, SO42-, Cl-, pH, electrical conductivity, turbidity, alkalinity, suspended and dissolved solids, biochemical oxygen demand , total coliforms, Escherichia coli and temperature, flow and rainfall. Through the use of FA/PCA, it was found that the model best fit to express water quality of in LC that was composed of five factors which account for 83.5% of the total variance, while for SC, four factors accounted for 85.12% of the variance. In LC, the five main factors were, respectively, soluble salts, diffuse pollution, solid, and both anthropogenic and organic factors. In SC, the four factors were namely: soluble salts, mineral, nutritional and diffuse pollution factors. The results of this study showed that by replacing the traditional soil usage (pasture and livestock) with planted forest, diffuse pollution was attenuated but, however, it did not result in major changes in the physical-chemical and biological characteristics of the water. Another point to note is that factorial analysis did not result in a large reduction in the number of variables, once the best model fit occurred with the addition of 15 of 18 analyzed variables (LC) and 17 of 18 analyzed variables (SC).

Climate and CO2 controls on global vegetation distribution at the last glacial maximum: analysis based on palaeovegetation data, biome modelling and palaeoclimate simulations.

The global vegetation response to climate and atmospheric CO2 changes between the last glacial maximum and recent times is examined using an equilibrium vegetation model (BIOME4), driven by output from 17 climate simulations from the Palaeoclimate Modelling Intercomparison Project. Features common to all of the simulations include expansion of treeless vegetation in high northern latitudes; southward displacement and fragmentation of boreal and temperate forests; and expansion of drought-tolerant biomes in the tropics. These features are broadly consistent with pollen-based reconstructions of vegetation distribution at the last glacial maximum. Glacial vegetation in high latitudes reflects cold and dry conditions due to the low CO2 concentration and the presence of large continental ice sheets. The extent of drought-tolerant vegetation in tropical and subtropical latitudes reflects a generally drier low-latitude climate. Comparisons of the observations with BIOME4 simulations, with and without consideration of the direct physiological effect of CO2 concentration on C3 photosynthesis, suggest an important additional role of low CO2 concentration in restricting the extent of forests, especially in the tropics. Global forest cover was overestimated by all models when climate change alone was used to drive BIOME4, and estimated more accurately when physiological effects of CO2 concentration were included. This result suggests that both CO2 effects and climate effects were important in determining glacial-interglacial changes in vegetation. More realistic simulations of glacial vegetation and climate will need to take into account the feedback effects of these structural and physiological changes on the climate.

The climate and biomes of Europe at 6000 yr BP: comparison of model simulations and pollen-based reconstructions

14C-dated pollen and lake-level data from Europe are used to assess the spatial patterns of climate change between 6000 yr BP and present, as simulated by the NCAR CCM1 (National Center for Atmospheric Research, Community Climate Model, version 1) in response to the change in the Earth’s orbital parameters during this perod. First, reconstructed 6000 yr BP values of bioclimate variables obtained from pollen and lake-level data with the constrained-analogue technique are compared with simulated values. Then a 6000 yr BP biome map obtained from pollen data with an objective biome reconstruction (biomization) technique is compared with BIOME model results derived from the same simulation. Data and simulations agree in some features: warmer-than-present growing seasons in N and C Europe allowed forests to extend further north and to higher elevations than today, and warmer winters in C and E Europe prevented boreal conifers from spreading west. More generally, however, the agreement is poor. Predominantly deciduous forest types in Fennoscandia imply warmer winters than the model allows. The model fails to simulate winters cold enough, or summers wet enough, to allow temperate deciduous forests their former extended distribution in S Europe, and it incorrectly simulates a much expanded area of steppe vegetation in SE Europe. Similar errors have also been noted in numerous 6000 yr BP simulations with prescribed modern sea surface temperatures. These errors are evidently not resolved by the inclusion of interactive sea-surface conditions in the CCM1. Accurate representation of mid-Holocene climates in Europe may require the inclusion of dynamical ocean–atmosphere and/or vegetation–atmosphere interactions that most palaeoclimate model simulations have so far disregarded.

Climate and biome simulations for the past 21,000 years

This paper reports on a set of paleoclimate simulations for 21, 16, 14, 11 and 6 ka (thousands of years ago) carried out with the Community Climate Model, Version 1 (CCM1) of the National Center for Atmospheric Research (NCAR). This climate model uses four interactive components that were not available in our previous simulations with the NCAR CCM0 (COHMAP, 1988Science, 241, 1043–1052; Wright et al., 1993Global Climate Since the Last Glocial Maximum, University of Minnesota Press, MN): soil moisture, snow hydrology, sea-ice, and mixed-layer ocean temperature. The new simulations also use new estimates of ice sheet height and size from ( Peltier 1994, Science, 265, 195–201), and synchronize the astronomically dated orbital forcing with the ice sheet and atmospheric CO2 levels corrected from radiocarbon years to calendar years. The CCM1 simulations agree with the previous simulations in their most general characteristics. The 21 ka climate is cold and dry, in response to the presence of the ice sheets and lowered CO2 levels. The period 14–6 ka has strengthened northern summer monsoons and warm mid-latitude continental interiors in response to orbital changes. Regional differences between the CCM1 and CCM0 simulations can be traced to the effects of either the new interactive model components or the new boundary conditions. CCM1 simulates climate processes more realistically, but has additional degrees of freedom that can allow the model to ‘drift’ toward less realistic solutions in some instances. The CCM1 simulations are expressed in terms of equilibrium vegetation using BIOME 1, and indicate large shifts in biomes. Northern tundra and forest biomes are displaced southward at glacial maximum and subtropical deserts contract in the mid-Holocene when monsoons strengthen. These vegetation changes could, if simulated interactively, introduce additional climate feedbacks. The total area of vegetated land remains nearly constant through time because the exposure of continental shelves with lowered sea level largely compensates for the land covered by the expanded ice sheets.

Comparing projections of future changes in runoff from hydrological and biome models in ISI-MIP

Future changes in runoff can have important implications for water resources and flooding. In this study, runoff projections from ISI-MIP (Inter-sectoral Impact Model Inter-comparison Project) simulations forced with HadGEM2-ES bias-corrected climate data under the Representative Concentration Pathway 8.5 have been analysed for differences between impact models. Projections of change from a baseline period (1981-2010) to the future (2070-2099) from 12 impacts models which contributed to the hydrological and biomes sectors of ISI-MIP were studied. The biome models differed from the hydrological models by the inclusion of CO2 impacts and most also included a dynamic vegetation distribution. The biome and hydrological models agreed on the sign of runoff change for most regions of the world. However, in West Africa, the hydrological models projected drying, and the biome models a moistening. The biome models tended to produce larger increases and smaller decreases in regionally averaged runoff than the hydrological models, although there is large inter-model spread. The timing of runoff change was similar, but there were differences in magnitude, particularly at peak runoff. The impact of vegetation distribution change was much smaller than the projected change over time, while elevated CO2 had an effect as large as the magnitude of change over time projected by some models in some regions. The effect of CO2 on runoff was not consistent across the models, with two models showing increases and two decreases. There was also more spread in projections from the runs with elevated CO2 than with constant CO2. The biome models which gave increased runoff from elevated CO2 were also those which differed most from the hydrological models. Spatially, regions with most difference between model types tended to be projected to have most effect from elevated CO2, and seasonal differences were also similar, so elevated CO2 can partly explain the differences between hydrological and biome model runoff change projections. Therefore, this shows that a range of impact models should be considered to give the full range of uncertainty in impacts studies.

SIMULATION OF USE AND MANAGEMENT EFFECTS ON THE SOIL ORGANIC MATTER POOLS OF THE ATLANTIC FOREST BIOME, BRAZIL

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Microcharcoal concentration and elongation, and age model of sediment core MD96-2098

Although grassland and savanna occupy only a quarter of the world's vegetation, burning in these ecosystems accounts for roughly half the global carbon emissions from fire. However, the processes that govern changes in grassland burning are poorly understood, particularly on time scales beyond satellite records. We analyzed microcharcoal, sediments, and geochemistry in a high-resolution marine sediment core off Namibia to identify the processes that have controlled biomass burning in southern African grassland ecosystems under large, multimillennial-scale climate changes. Six fire cycles occurred during the past 170,000 y in southern Africa that correspond both in timing and magnitude to the precessional forcing of north-south shifts in the Intertropical Convergence Zone. Contrary to the conventional expectation that fire increases with higher temperatures and increased drought, we found that wetter and cooler climates cause increased burning in the study region, owing to a shift in rainfall amount and seasonality (and thus vegetation flammability). We also show that charcoal morphology (i.e., the particle's length-to-width ratio) can be used to reconstruct changes in fire activity as well as biome shifts over time. Our results provide essential context for understanding current and future grassland-fire dynamics and their associated carbon emissions.

Global LAI uncertainty and relative uncertainty datasets derived from a Triple Collocation Error Model (TCEM)

Uncertainty information for global leaf area index (LAI) products is important for global modeling studies but usually difficult to systematically obtain at a global scale. Here, we present a new method that cross-validates existing global LAI products and produces consistent uncertainty information. The method is based on a triple collocation error model (TCEM) that assumes errors among LAI products are not correlated. Global monthly absolute and relative uncertainties, in 0.05° spatial resolutions, were generated for MODIS, CYCLOPES, and GLOBCARBON LAI products, with reasonable agreement in terms of spatial patterns and biome types. CYCLOPES shows the lowest absolute and relative uncertainties, followed by GLOBCARBON and MODIS. Grasses, crops, shrubs, and savannas usually have lower uncertainties than forests in association with the relatively larger forest LAI. With their densely vegetated canopies, tropical regions exhibit the highest absolute uncertainties but the lowest relative uncertainties, the latter of which tend to increase with higher latitudes. The estimated uncertainties of CYCLOPES generally meet the quality requirements (± 0.5) proposed by the Global Climate Observing System (GCOS), whereas for MODIS and GLOBCARBON only non-forest biome types have met the requirement. Nevertheless, none of the products seems to be within a relative uncertainty requirements of 20%. Further independent validation and comparative studies are expected to provide a fair assessment of uncertainties derived from TCEM. Overall, the proposed TCEM is straightforward and could be automated for the systematic processing of real time remote sensing observations to provide theoretical uncertainty information for a wider range of land products.

Tropical climate and vegetation simulations during the Heinrich event 1 using an Earth System Model of Intermediate Complexity (EMIC) - the University of Victoria Earth System-Climate Model (UVic ESCM)

Abrupt climate changes from 18 to 15 thousand years before present (kyr BP) associated with Heinrich Event 1 (HE1) had a strong impact on vegetation patterns not only at high latitudes of the Northern Hemisphere, but also in the tropical regions around the Atlantic Ocean. To gain a better understanding of the linkage between high and low latitudes, we used the University of Victoria (UVic) Earth System-Climate Model (ESCM) with dynamical vegetation and land surface components to simulate four scenarios of climate-vegetation interaction: the pre-industrial era, the Last Glacial Maximum (LGM), and a Heinrich-like event with two different climate backgrounds (interglacial and glacial). We calculated mega-biomes from the plant-functional types (PFTs) generated by the model to allow for a direct comparison between model results and palynological vegetation reconstructions. Our calculated mega-biomes for the pre-industrial period and the LGM corresponded well with biome reconstructions of the modern and LGM time slices, respectively, except that our pre-industrial simulation predicted the dominance of grassland in southern Europe and our LGM simulation resulted in more forest cover in tropical and sub-tropical South America. The HE1-like simulation with a glacial climate background produced sea-surface temperature patterns and enhanced inter-hemispheric thermal gradients in accordance with the "bipolar seesaw" hypothesis. We found that the cooling of the Northern Hemisphere caused a southward shift of those PFTs that are indicative of an increased desertification and a retreat of broadleaf forests in West Africa and northern South America. The mega-biomes from our HE1 simulation agreed well with paleovegetation data from tropical Africa and northern South America. Thus, according to our model-data comparison, the reconstructed vegetation changes for the tropical regions around the Atlantic Ocean were physically consistent with the remote effects of a Heinrich event under a glacial climate background.

Results of Heinrich event 1 simulation from the University of Victoria Earth System-Climate Model (UVic ESCM) and the Community Climate System Model (CCSM3)

We investigated changes in tropical climate and vegetation cover associated with abrupt climate change during Heinrich Event 1 (HE1, ca. 17.5 ka BP) using two different global climate models: the University of Victoria Earth System-Climate Model (UVic ESCM) and the Community Climate System Model version 3 (CCSM3). Tropical South American and African pollen records suggest that the cooling of the North Atlantic Ocean during HE1 influenced the tropics through a southward shift of the rain belt. In this study, we simulated the HE1 by applying a freshwater perturbation to the North Atlantic Ocean. The resulting slowdown of the Atlantic Meridional Overturning Circulation was followed by a temperature seesaw between the Northern and Southern Hemispheres, as well as a southward shift of the tropical rain belt. The shift and the response pattern of the tropical vegetation around the Atlantic Ocean were more pronounced in the CCSM3 than in the UVic ESCM simulation. For tropical South America, opposite changes in tree and grass cover were modeled around 10° S in the CCSM3 but not in the UVic ESCM. In tropical Africa, the grass cover increased and the tree cover decreased around 15° N in the UVic ESCM and around 10° N in the CCSM3. In the CCSM3 model, the tree and grass cover in tropical Southeast Asia responded to the abrupt climate change during the HE1, which could not be found in the UVic ESCM. The biome distributions derived from both models corroborate findings from pollen records in southwestern and equatorial western Africa as well as northeastern Brazil.

Predicting the Dispersal Potential of an Invasive Polychaete Pest along a Complex Coastal Biome

Boccardia proboscidea is a recently introduced polychaete in South Africa where it is a notorious pest of commercially reared abalone. Populations were originally restricted to abalone farms but a recent exodus into the wild at some localities has raised conservation concerns due to the species’ invasive status in other parts of the world. Here, we assessed the dispersal potential of B. proboscidea by using a population genetic and oceanographic modeling approach. Since the worm is in its incipient stages of a potential invasion, we used the closely related Polydora hoplura as a proxy due its similar reproductive strategy and its status as a pest of commercially reared oysters in the country. Populations of P. hoplura were sampled from seven different localities and a section of the mtDNA gene, Cyt b and the intron ATPSa was amplified. A high resolution model of the coastal waters around southern Africa was constructed using the Regional Ocean Modeling System. Larvae were represented by passive drifters that were deployed at specific points along the coast and dispersal was quantified after a 12-month integration period. Our results showed discordance between the genetic and modeling data. There was low genetic structure (Φ = 0.04 for both markers) and no geographic patterning of mtDNA and nDNA haplotypes. However, the dispersal model found limited connectivity around Cape Point—a major phylogeographic barrier on the southern African coast. This discordance was attributed to anthropogenic movement of larvae and adult worms due to vectors such as aquaculture and shipping. As such, we hypothesized that cryptic dispersal could be overestimating genetic connectivity. Though wild populations of B. proboscidea could become isolated due to the Cape Point barrier, anthropogenic movement may play the critical role in facilitating the dispersal and spread of this species on the southern African coast.

Predicting the Dispersal Potential of an Invasive Polychaete Pest along a Complex Coastal Biome

Boccardia proboscidea is a recently introduced polychaete in South Africa where it is a notorious pest of commercially reared abalone. Populations were originally restricted to abalone farms but a recent exodus into the wild at some localities has raised conservation concerns due to the species’ invasive status in other parts of the world. Here, we assessed the dispersal potential of B. proboscidea by using a population genetic and oceanographic modeling approach. Since the worm is in its incipient stages of a potential invasion, we used the closely related Polydora hoplura as a proxy due its similar reproductive strategy and its status as a pest of commercially reared oysters in the country. Populations of P. hoplura were sampled from seven different localities and a section of the mtDNA gene, Cyt b and the intron ATPSa was amplified. A high resolution model of the coastal waters around southern Africa was constructed using the Regional Ocean Modeling System. Larvae were represented by passive drifters that were deployed at specific points along the coast and dispersal was quantified after a 12-month integration period. Our results showed discordance between the genetic and modeling data. There was low genetic structure (Φ = 0.04 for both markers) and no geographic patterning of mtDNA and nDNA haplotypes. However, the dispersal model found limited connectivity around Cape Point—a major phylogeographic barrier on the southern African coast. This discordance was attributed to anthropogenic movement of larvae and adult worms due to vectors such as aquaculture and shipping. As such, we hypothesized that cryptic dispersal could be overestimating genetic connectivity. Though wild populations of B. proboscidea could become isolated due to the Cape Point barrier, anthropogenic movement may play the critical role in facilitating the dispersal and spread of this species on the southern African coast.

Integrated Proteomics Identified Up-regulated Focal Adhesion-mediated Proteins In Human Squamous Cell Carcinoma In An Orthotopic Murine Model.

Understanding the molecular mechanisms of oral carcinogenesis will yield important advances in diagnostics, prognostics, effective treatment, and outcome of oral cancer. Hence, in this study we have investigated the proteomic and peptidomic profiles by combining an orthotopic murine model of oral squamous cell carcinoma (OSCC), mass spectrometry-based proteomics and biological network analysis. Our results indicated the up-regulation of proteins involved in actin cytoskeleton organization and cell-cell junction assembly events and their expression was validated in human OSCC tissues. In addition, the functional relevance of talin-1 in OSCC adhesion, migration and invasion was demonstrated. Taken together, this study identified specific processes deregulated in oral cancer and provided novel refined OSCC-targeting molecules.