B42A-01 10:20h
Mesoscale Drivers of Major Tributary Chemistry: a Quasi-Inverse Modeling Approach
The biogeochemical signal (the composite hydrological and chemical distributions of C, N, O, and P species) at the downstream end of a major tributary can nominally be used to identify different drainage basin source regions, reaches or stages, and can be tied to landscape-related processes such as chemical weathering and nutrient retention by local vegetation. Indeed, the central premise of a large river basin model is that the constituents of river water provide a continuous, integrated record of upstream processes. But because of potential scaling issues and alternative pathways, the problem is not that "simple." Here we examine the composite chemical signals in the lower reaches of the Madeira, Purus, Jurua, Ica, Japura, and Negro rivers in terms of their respective upstream hydrological cycles and basin properties. Essentially, we use an inverse model to see how far we can explain the observed signals.
B42A-02 10:35h
Modeling surface hydrology across the Amazon Basin using a Variable Infiltration Capacity approach
The large amount of vital field information gathered by the Large Scale Atmosphere-Biosphere Experiment in Amazonia has significantly improved our knowledge of the Amazon ecosystem dynamics. Due to the extent of the amazon basin, models have become key tools to synthesize this knowledge and to improve the understanding of the basin wide ecosystem functioning. Therefore, to be able to predict the basin hydrology and river biogeochemistry, we are calibrating the Variable Infiltration Capacity model for the Amazon basin. First, we have developed a series of regional GIS libraries and input data sets for the area compiled at 0.1deg from different sources, including remote sensing, maps and observational data gathered at the field.. Soil texture, leaf area index and albedo were the main targets. Our results, reveal good temporal and spatial distribution of evapotranspiration and discharge (R2 = 0.775). For both parameters, modeled values were in the same range of those measured at the field. Soil texture and land use/cover effects on the water cycle are clearly shown. While pasture areas present lower values of ET, the forest maintains higher levels of ET during the dry season.
B42A-03 10:50h
$^{14}$C and $^{13}$C Constraints on CO$_{2}$ Cycling in Pristine and Deforested Lowland Amazonian Rivers
"Lowland" rivers in the Amazon are those that, unlike the Amazon mainstem, do not drain the Andean cordillera and are not directly influenced by sediments recently eroded from the Andes. The Brazilian Amazon is predominantly drained by lowland watersheds. We examined the sources and fate of CO2 and Dissolved Inorganic Carbon (DIC) in a range of small to large lowland rivers across the region. In particular, we focused on the Ji-Parana basin, which spans the deforestation arc in the state of Rondonia. Carbonate weathering appears to be a strong source of DIC in the western lowland basins (Jurua and Purus); however, carbonate-derived DIC in these systems is completely flushed out downstream through outgassing and mixing with contemporary respiratory CO2 inputs and carbonate-free tributaries. DIC exported from carbonate-free lowland soils appers to be predominantly contemporary, but some regions in the Ji-Parana headwaters export CO2 with a mean age of several decades. In that system, replacement of C3 forests with C4 pastures appears to exert a strong influence on riverine carbon cycling from small to large rivers. Inputs from riparian grasses may play a disproportionately important role. Finally, we found tentative evidence that anoxic conditions in wetlands may result in mineralization of previously protected, aged organic matter, leading to significant aging in riverine DIC.
B42A-04 11:05h
Biogeochemistry of the Amazon River Basin: the role of aquatic ecosystems in the Amazon functioning
In this study we present the results of an integrated analysis of physical and anthropogenic controls of river biogeochemistry in Amazonia. At the meso-scale level, our results show that both soil properties and land use are the main drivers of river biogeochemistry and metabolism, with pasture cover and soil exchange cation capacity explaining 99% (p < 0.01) of the variability observed in surface water ions and nutrients concentrations. In small rivers, forest clearing can increase cations, P and C inputs. P and light are the main PPL limiting factors in forested streams, while in pasture streams N becomes limiting. P export to streams may increase or remain nearly undetectable after forest-to-pasture conversion, depending on soil type. Pasture streams on Oxisols have very low P export, while on Ultisols P export is increased. Conversions of forest to pasture leads to extensive growth of in channel Paspalum resulting in higher DOC concentrations and respiration rates. Pasture streams have higher DOC fluxes when compared to the forest ones. In pasture areas the soil are compacted, there is less infiltration and higher surface run off, leaching soil superficial layers and caring more DOC to the streams. In forest areas infiltration is deeper into the soils and canopy interaction is higher. Mineralogy and soil properties are key factors determining exports of nutrients to streams. Therefore, land use change effects on nutrient export from terrestrial to aquatic ecosystems and the atmosphere must be understood within the context of varying soil properties across the Amazon Basin.
B42A-05 11:20h
Effects of Roads on Deforestation in the Brazilian Amazon: new evidence using census-tract data and addressing endogeneity
Regional landscape projections constitute a valuable tool for identifying policies that can address the development needs of Amazonian populations while minimizing loss of ecosystem integrity. Changes in transport costs in particular are expected to affect both livelihoods and deforestation, and there are significant planned policies which would involve investments to lower such costs. Recent work has advanced the literature in terms of both its questions and its empirical approach. Specifically, more has been learned about the development gains attendant to loss in forest area. Also more "dynamic" and more appropriate approaches have been taken to infer factors' effects. One particular result of interest from this work has been that roads' effect depend on the setting. Most controversially, it suggests that more roads could lower deforestation rate in cleared areas. In reconsidering that idea, this paper addresses the greatest limitation upon the previous research. Specifically, the use of census-tract-level data over time provides over 20 times the observations. This permits much greater control for unobservables that could easily drive any previous results. Further, it permits separate regressions for different settings to directly address effects of roads. The results suggest that setting does indeed matter and that roads' effects may fall with clearing. However, it does not appear that lowering the cost of transport ever lowers rates of deforestation. While to this point we have results only for our first time period, this is a strong important result. The second part of the paper considers the possibility that the effects of roads are overestimated. The reason for this is endogeneity of roads, i.e. they are not randomly but purposefully located. Should their location be driven by factors that would themselves lead to greater forest clearing, empirical results appearing to indicate effects of roads could be showing effects of those factors. Project team members have been studying what lead to the creation of parts of the road network, and we examine empirically what land-use settings are the most likely to give rise to new roads. We then use this result to set up cleaner comparisons of locations with and without new roads, controlling for other factors by comparing locations that are similar in terms of those factors. Early results find that this lowers estimated effects of roads but they remain quite significant.
B42A-06 11:35h
Changing Dynamics of Forest Clearing in Mato Grosso: Implications for Ecosystem Processes
The state of Mato Grosso has experienced consistently high rates of deforestation over the past ten years. Recent land use transitions in the state have been influenced by a growing grain-based agricultural sector. Clearings for mechanized agriculture have altered the size and timing of deforestation activities. We explore the changing dynamics of forest clearing in Mato Grosso between 2000 and 2004 with field-validated estimates of deforestation based on Moderate Resolution Spectroradiometer (MODIS) data at 250m resolution. Subsequently, we classify areas of new deforestation based on the phenological signature of post-clearing land use as pasture or mechanized agriculture. The combination of these datasets permits the quantification of relative increases in mean clearing size and definition of the timing of new clearing, stratified by post-clearing land cover. In addition, the classification of deforested areas as pasture or mechanized agriculture provides critical insight regarding climate feedbacks from changing land use in the region. Using an offline version of the Simple Biosphere Model (SiB2) modified for tropical land cover types, we evaluate the sensitivity of water and surface energy balances and temperature to transitions from forest to pasture, forest to mechanized agriculture, and pasture to mechanized agriculture. The results illustrate the important influence of land use changes that alter the photosynthetic pathway (C3 or C4) of the vegetation. Characterizing the changing dynamics of forest clearing at the agricultural/forest frontier is a critical step towards quantifying the impacts of land use change on ecosystem processes.
B42A-07 11:50h
Classifying fire type based on MODIS vegetation time-series signal
The importance of fire in tropical ecosystems is growing as both direct and indirect consequences of land use. Throughout the 80s and early 90s, constantly increasing human forcing and climate anomalies made forest fires in the Amazon Basin a major environmental issue. However, not all fires are equal. Some fires result in a major conversion of the landscape. While in other locations, fires are necessary to maintain the landscape. As land management and carbon science efforts continue to focus on the role of fire, it will be important to "filter" fire maps to differentiate between conversion and maintenance fires. To develop such a filter, we explore the MODIS vegetation signal before and after fires to establish the time series signal associated with different types of fire. In this work we present the time series signal for a set of prescribed burns, including recently deforested areas and grasslands managed for grazing. Results show that fires and land cover dynamics do influence the MODIS signal, but there is significant noise. To resolve complicated time series signatures, it is critical to utilize longer time series profiles and the MODIS quality assessment (QA) flags for proper interpretation of the data.
B42A-08 12:05h
Remote Sensing of Forest Disturbance and Selective Logging Throughout the Brazilian Amazon
Selective logging is one of the most difficult forms of land-cover change to detect with remote sensing. Variation in the biophysical attributes of selective logging challenge traditional methods. LBA has supported the development of improved remote sensing approaches for detecting the location of selective logging, for quantifying forest canopy damage associated with timber harvest, and for monitoring rates of forest canopy closure following disturbance. Different methods have now been compared, and the strengths and weaknesses have been documented. In addition, remotely observed changes in forest canopy cover following timber harvest are now being linked to a range of ecological and biogeochemical processes in the field. This presentation will provide a detailed summary of the overall progress towards understanding how selective logging affects Amazonian forest ecosystems at the regional scale.