The forest biome of Amazonia is one of Earth's greatest biological treasures, and a major component of the Earth system. This century, it faces the dual threats of deforestation and stress from climate change. In this review, we summarize some of the latest findings and thinking on these threats, explore the consequences for the forest ecosystem and its human residents, and outline options for the future of Amazonia. We also discuss the implications of new proposals to finance preservation of Amazonian forests.

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Atmospheric general circulation models used for climate simulation and weather forecasting require the fluxes of radiation, heat, water vapor, and momentum across the land-atmosphere interface to be specified. These fluxes are calculated by submodels called land surface parameterizations. Over the last 20 years, these parameterizations have evolved from simple, unrealistic schemes into credible representations of the global soil-vegetation-atmosphere transfer system as advances in plant physiological and hydrological research, advances in satellite data interpretation, and the results of largescale field experiments have been exploited. Some modern schemes incorporate biogeochemical and ecological knowledge and, when coupled with advanced climate and ocean models, will be capable of modeling the biological and physical responses of the Earth system to global change, for example, increasing atmospheric carbon dioxide.Until the early 1980s, global atmospheric general circulation models (AGCMs) incorporated very simple land surface parameterizations (LSPs) to estimate the exchanges of energy, heat, and momentum between the land surface and the atmosphere. These have since evolved into a family of schemes that can realistically describe a comprehensive range of land-atmosphere interactions. These advanced schemes will be needed to understand the response of the biosphere and the climate system to global change, for example, increasing atmospheric CO 2 (1-3).Three generations of models have taken us from the early LSPs to where we stand now. The first, developed in the late 1960s and 1970s, was based on simple aerodynamic bulk transfer formulas and often uniform prescriptions of surface parameters (albedo, aerodynamic roughness, and soil moisture availability) over the continents (4). In the early 1980s, a second generation of models explicitly recognized the effects of vegetation in the calculation of the surface energy balance (5, 6). At the same time, global, spatially varying data of land surface properties were assembled from ecological and geographical surveys published in the scientific literature (7). The latest (third generation) models use modern theories relating photosynthesis and plant water relations to provide a consistent description of energy exchange, evapotranspiration, and carbon exchange by plants (8-10). Some are beginning to incorporate treatments of nutrient dynamics and biogeography, so that vegetation systems can move in response to climate shifts. A series of largescale field experiments have been executed to validate the process models and scaling assumptions involved in land-atmosphere schemes (3). These experiments have also accelerated the development of methods for translating satellite data into global surface parameter sets for the models. Theoretical Background and the First-Generation ModelsIt has been understood for nearly 200 years that the continents and the atmosphere exchange energy, water, and carbon with each other. However, it was not until the late 1960s with the construct...

In 2005, large sections of southwestern Amazonia experienced one of the most intense droughts of the last hundred years. The drought severely affected human population along the main channel of the Amazon River and its western and southwestern tributaries, the Solimões (also known as the Amazon River in the other Amazon countries) and the Madeira Rivers, respectively. The river levels fell to historic low levels and navigation along these rivers had to be suspended. The drought did not affect central or eastern Amazonia, a pattern different from the El Niño-related droughts in 1926, 1983, and 1998. The choice of rainfall data used influenced the detection of the drought. While most datasets (station or gridded data) showed negative departures from mean rainfall, one dataset exhibited above-normal rainfall in western Amazonia.The causes of the drought were not related to El Niño but to (i) the anomalously warm tropical North Atlantic, (ii) the reduced intensity in northeast trade wind moisture transport into southern Amazonia during the peak summertime season, and (iii) the weakened upward motion over this section of Amazonia, resulting in reduced convective development and rainfall. The drought conditions were intensified during the dry season into September 2005 when humidity was lower than normal and air temperatures were 3°-5°C warmer than normal. Because of the extended dry season in the region, forest fires affected part of southwestern Amazonia.

The distribution of sources and sinks of carbon among the world's ecosystems is uncertain. Some analyses show northern mid-latitude lands to be a large sink, whereas the tropics are a net source; other analyses show the tropics to be nearly neutral, whereas northern mid-latitudes are a small sink. Here we show that the annual flux of carbon from deforestation and abandonment of agricultural lands in the Brazilian Amazon was a source of about 0.2 Pg Cyr(-1) over the period 1989-1998 (1 Pg is 10(15) g). This estimate is based on annual rates of deforestation and spatially detailed estimates of deforestation, regrowing forests and biomass. Logging may add another 5-10% to this estimate, and fires may double the magnitude of the source in years following a drought. The annual source of carbon from land-use change and fire approximately offsets the sink calculated for natural ecosystems in the region. Thus this large area of tropical forest is nearly balanced with respect to carbon, but has an interannual variability of +/- 0.2 PgC yr(-1).

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For half a century, the process of economic integration of the Amazon has been based on intensive use of renewable and nonrenewable natural resources, which has brought significant basin-wide environmental alterations. The rural development in the Amazonia pushed the agricultural frontier swiftly, resulting in widespread land-cover change, but agriculture in the Amazon has been of low productivity and unsustainable. The loss of biodiversity and continued deforestation will lead to high risks of irreversible change of its tropical forests. It has been established by modeling studies that the Amazon may have two "tipping points," namely, temperature increase of 4°C or deforestation exceeding 40% of the forest area. If transgressed, large-scale "savannization" of mostly southern and eastern Amazon may take place. The region has warmed about 1°C over the last 60 y, and total deforestation is reaching 20% of the forested area. The recent significant reductions in deforestation-80% reduction in the Brazilian Amazon in the last decade-opens up opportunities for a novel sustainable development paradigm for the future of the Amazon. We argue for a new development paradigm-away from only attempting to reconcile maximizing conservation versus intensification of traditional agriculture and expansion of hydropower capacity-in which we research, develop, and scale a high-tech innovation approach that sees the Amazon as a global public good of biological assets that can enable the creation of innovative high-value products, services, and platforms through combining advanced digital, biological, and material technologies of the Fourth Industrial Revolution in progress.Amazon tropical forests | Amazon sustainability | Amazon land use | Amazon savannization | climate change impacts

A coupled numerical model of the global atmosphere and biosphere has been used to assess the effects of Amazon deforestation on the regional and global climate. When the tropical forests in the model were replaced by degraded grass (pasture), there was a significant increase in surface temperature and a decrease in evapotranspiration and precipitation over Amazonia. In the simulation, the length of the dry season also increased; such an increase could make reestablishment of the tropical forests after massive deforestation particularly difficult.The distribution of global vegetation was traditionally thought to be determined by local climate factors, especially precipitation and radiation. This view has been modified because controlled numerical experiments with complex models of the atmosphere showed that the presence or absence of vegetation can influence the regional climate (1-3). One implication of these results is that the current climate and vegetation may coexist in a dynamic equilibrium that could be altered by large perturbations in either of the two components. The high rate of deforestation in the Brazilian portion of Amazonia, from 25,000 to 50,000 km2 per year (4-7), might thus be expected to have an effect on the regional climate. If deforestation were to continue at this rate, most of the Amazonian tropical forests would disappear in 50 to 100 years.Removal of the Amazonian forest would also have tremendous effects on species diversity and atmospheric chemistry (8). The Amazon basin is host to roughly half of the world's species, and the intensity and complexity of plant-animal interactions (9) and the rapid nutrient cycling in the soils (10) make the region vulnerable to external disturbances. The Amazon is also an important natural sink for ozone and plays an important role in global tropospheric chemistry. The present study is mainly confined to the assessment of the effects of deforestation on the physical climate system.Quantitatively estimating the effects that large changes in terrestrial ecosystems can have on temperature, circulation, and rainfall has been difficult because the equilibrium climate is determined by complex interactions among the dynamical processes in the atmosphere and thermodynamic processes at the earth-atmosphere interface. Realistic models of the biosphere that can be coupled with realistic models of the global atmosphere have only recently been