The southeastern Amazon has been transformed by widespread land use and climate changes, altering the hydrologic cycle. In this seasonally dry tropical forest, the soil water reservoir plays a strong role in mediating the water balance by buffering forests during dry seasons and moderate droughts, as well as modulating runoff to streams. Few studies have examined the response of soil water reservoirs to large-scale forest loss in headwater regions, much less how these changes may influence catchment water balances during droughts. This study compares the water balance of forested and cropland watersheds in the headwaters of the Xingu River basin (Mato Grosso, Brazil). We combined measurements of stream discharge and soil moisture (from 0.3 to 8 m depth) from the 2014-2018 water years, along with remotely sensed precipitation and evapotranspiration (ET) data, comparing normal precipitation years to an extreme drought year. Streams within agricultural catchments had four times higher discharge (29% of total precipitation) than in forested catchments (8%). During normal years, this difference was balanced by differences in ET. We found that groundwater outflow-water that bypasses a catchment without reaching the stream-is a significant water export term under both landcovers (19% in forest; 26% in croplands). However, during drought years, this outflow disappears in forested catchments and decreases in agricultural catchments, suggesting enhanced groundwater uptake by vegetation that diminishes contributions to rivers downstream. Multiyear droughts projected under future climate changes could threaten the soil water reservoir, leaving forests without a critical resource and downstream communities vulnerable to streamflow loss.

Amazon forests are undergoing rapid transformations driven by deforestation, climate change, fire, and other anthropogenic pressures, leading to the hypothesis that they may be nearing a catastrophic tipping point—beyond which ecosystems could shift to a permanently altered state. This review revisits the concept of an Amazon tipping point and assesses the risk of forest collapse from an ecological perspective. We synthesize evidence showing that environmental stressors can drive critical ecosystem transitions, either gradually through incremental loss of resilience or abruptly via synergistic feedbacks. The interplay between climate and land-use change amplifies risks to biodiversity, ecosystem services, and livelihoods. Yet, there is limited evidence for a single, system-wide tipping point. Instead, the Amazon's resilience—although not unlimited—offers meaningful pathways for recovery. The most immediate and effective strategies to support this resilience include slowing forest loss, mitigating climate change, reducing fire activity, curbing defaunation, and restoring degraded ecosystems. Without decisive action to address direct threats, the Amazon system may be pushed beyond safe ecological-climatological operating limits—even in the absence of sharply defined thresholds—due to the scale and persistence of anthropogenic pressures. Preserving the Amazon's ecological integrity and its vital role in regulating the global climate requires urgent, sustained conservation efforts in collaboration with local and Indigenous communities.

Soil moisture is a crucial variable mediating soil-vegetation-atmosphere water exchange. As climate and land use change, the increased frequency and intensity of extreme weather events and disturbances will likely alter feedbacks between ecosystem functions and soil moisture. In this study, we evaluated how extreme drought (2015/2016) and postfire vegetation regrowth affected the seasonality of soil water content (0-8 m depth) in a transitional forest in southeastern Amazonia. The experiment included three treatment plots: an unburned Control, an area burned every three years (B3yr), and an area burned annually (B1yr) between 2004 and 2010. We hypothesized that (a) soil moisture at B1yr and B3yr would be higher than the Control in the first years postfire due to lower transpiration rates, but differences between burned plots would decrease as postfire vegetation regrew; (b) during drought years, the soil water deficit in the dry season would be significantly greater in all plots as plants responded to greater evaporative demand; and (c) postfire recovery in the burned plots would cause an increase in evapotranspiration over time, especially in the topsoil. Contrary to the first expectation, the burned plots had lower volumetric water content than the Control plot. However, we found that droughts significantly reduced soil moisture in all plots compared to non-drought years (15.6%), and this effect was amplified in the burned plots (19%). Our results indicate that, while compounding disturbances such as wildfires and extreme droughts alter forest dynamics, deep soil moisture is an essential water source for vegetation recovery. As extreme droughts and wildfires have become more common in southeastern Amazonia, they could alter soil moisture availability, but the intensity of these compounding effects still needs to be understood. This study investigates the impact of the extreme drought of 2015/2016, postfire vegetation recovery, the return of water to the atmosphere, and their interacting effects on water distribution across the soil profile in three treatment plots: an unburned Control, an area burned every three years, and an area burned annually from 2004 to 2010. Contrary to expectations, we found that soil moisture in the burned plots decreased in the years following the last experimental fire (2010), even as the vegetation recovered. Drought events significantly reduced soil moisture across all plots, but this effect was amplified in the burned plots. As land use changes increase and climate change intensifies, such drought-induced soil drying may become more common, exacerbating the impacts of wildfires on ecosystem resilience and forest health across much of the region. During the driest months of the year, burned forests showed significant reductions in soil moisture compared with unburned forests The drought event of 2015/2016 caused greater reductions in soil moisture in the burned forest than in the unburned forest Both burned and unburned forests increased water use throughout the 8-m soil column from 2011 to 2018

Brazil emerged as an agricultural powerhouse in the last four decades, producing 33% of the world’s soybeans and 14% of its beef. Historically, much of that growth has come at the expense of its native ecosystems. A growing body of work suggests this paradigm is outdated and brings negative social and environmental outcomes. Here, we provide an integrated analysis of an alternate pathway to solve this puzzle based on a scenario of land-use allocation governance. We compare it with a business-as-usual scenario through the lens of cost, revenues, and impact. The path forward is based on four fronts that can reduce deforestation while increasing production and social well-being. First, allocate undesignated public forests as protected areas and improve the management of new and existing ones. This first strategy would generate a positive return, and foster recognition of human rights, cultural preservation, and improved livelihoods. Second, prevent legal deforestation on private lands and promote compliance with Brazil's Native Vegetation Protection Law (Brasil, 2012) through restoration, also generating positive returns and directing the region towards a zero-deforestation future. Third, promote sustainable intensification of medium and large farms. It would allow Brazil to achieve its agricultural production targets while freeing land up for soy expansion and restoration. Fourth, improve technical assistance and increase market access and income of smallholders while reducing deforestation pressure on family farms. Implementing these fronts requires a coordinated effort between public and private institutions. Still, it would reestablish Brazil`s global leadership in managing natural resources and mitigating climate change.

Deforestation not only contributes to global warming but also induces changes in the regional climates that impact agriculture. Here, we analyse the effects of deforestation-induced climate change on the soy–maize double cropping of the Cerrado biome. Since the 1980s, there has been an average delay of 36 days in the start of the agricultural rainy season, a 36.7

Tropical ecosystems store over half of the world’s aboveground live carbon as biomass, and water availability plays a key role in its distribution. Although precipitation and temperature are shifting across the tropics, their effect on biomass and carbon storage remains uncertain. Here we use empirical relationships between climate and aboveground biomass content to show that the contraction of humid regions, and expansion of those with intense dry periods, results in substantial carbon loss from the neotropics. Under a low emission scenario (Representative Concentration Pathway 4.5) this could cause a net reduction of aboveground live carbon of ~14.4–23.9 PgC (6.8–12%) from 1950–2100. Under a high emissions scenario (Representative Concentration Pathway 8.5) net carbon losses could double across the tropics, to ~28.2–39.7 PgC (13.3–20.1%). The contraction of humid regions in South America accounts for ~40% of this change. Climate mitigation strategies could prevent half of the carbon losses and help maintain the natural tropical net carbon sink.

Increasing harvest and overexploitation of wild plants for non‐timber forest products can significantly affect population dynamics of harvested populations. While the most common approach to assess the effect of harvest and perturbation of vital rates is focused on the long‐term population growth rate, most management strategies are planned and implemented over the short‐term. We developed an integral projection model to investigate the effects of harvest on the demography and the short‐ and long‐term population dynamics of Banisteriopsis caapi in the Peruvian Amazon rainforest. Harvest had no significant effect on the size‐dependent growth of lianas, but survival rates increased with size. Harvest had a significant negative effect on size‐dependent survival where larger lianas experienced greater mortality rates under high harvest pressure than smaller lianas. In the populations under high harvest pressure, survival of smaller lianas was greater than that of populations with low harvest pressure. Harvest had no significant effect on clonal or sexual reproduction, but fertility was size‐dependent. The long‐term population growth rates of B. caapi populations under high harvest pressure were projected to decline at a rate of 1.3% whereas populations with low harvest pressure are expected to increase at 3.2%. However, before reaching equilibrium, over the short‐term, all B. caapi populations were in decline by 26% (high harvested population) and (low harvested population) 20.4% per year. Elasticity patterns were dominated by survival of larger lianas irrespective of harvest treatments. Life table response experiment analyses indicated that high harvest caused the 6% reduction in population growth rates by significantly reducing the survival of large lianas and increasing the survival‐growth of smaller lianas including vegetative reproductive individuals. Synthesis and applications . This study emphasizes how important it is for management strategies for B. caapi lianas experiencing anthropogenic harvest to prioritize the survival of larger size lianas and vegetative reproducing individuals, particularly in increased harvested systems often prone to multiple stressors. From an applied conservation perspective, our findings illustrate the importance of both prospective and retrospective perturbation analyses in population growth rates in understanding the population dynamics of lianas in general in response to human‐induced disturbance.

The Amazon biome is being pushed by unsustainable economic drivers towards an ecological tipping point where restoration to its previous state may no longer be possible. This degradation is the result of self-reinforcing interactions between deforestation, climate change and fire. We assess the economic, natural capital and ecosystem services impacts and trade-offs of scenarios representing movement towards an Amazon tipping point and strategies to avert one using the Integrated Economic-Environmental Modeling (IEEM) Platform linked with spatial land use-land cover change and ecosystem services modeling (IEEM + ESM). Our approach provides the first approximation of the economic, natural capital and ecosystem services impacts of a tipping point, and evidence to build the economic case for strategies to avert it. For the five Amazon focal countries, namely, Brazil, Peru, Colombia, Bolivia and Ecuador, we find that a tipping point would create economic losses of US$256.6 billion in cumulative gross domestic product by 2050. Policies that would contribute to averting a tipping point, including strongly reducing deforestation, investing in intensifying agriculture in cleared lands, climate-adapted agriculture and improving fire management, would generate approximately US$339.3 billion in additional wealth and a return on investment of US$29.5 billion. Quantifying the costs, benefits and trade-offs of policies to avert a tipping point in a transparent and replicable manner can support the design of regional development strategies for the Amazon biome, build the business case for action and catalyze global cooperation and financing to enable policy implementation.

The Brazilian Cerrado is one of the most biodiverse savannas in the world, yet 46% of its original cover has been cleared to make way for crops and pastures. These extensive land-use transitions (LUTs) are expected to influence regional climate by reducing evapotranspiration (ET), increasing land surface temperature (LST), and ultimately reducing precipitation. Here, we quantify the impacts of LUTs on ET and LST in the Cerrado by combining MODIS satellite data with annual land use and land cover maps from 2006 to 2019. We performed regression analyses to quantify the effects of six common LUTs on ET and LST across the entire gradient of Cerrado landscapes, Results indicate that clearing forests for cropland or pasture increased average LST by similar to 3.5 degrees C and reduced mean annual ET by 44% and 39%, respectively. Transitions from woody savannas to cropland or pasture increased average LST by 1.9 degrees C and reduced mean annual ET by 27% and 21%, respectively. Converting native grasslands to cropland or pasture increased average LST by 0.9 and 0.6 degrees C, respectively. Conversely, grasslandto-pasture transitions increased mean annual ET by 15%. To date, land changes have caused a 10% reduction in water recycled to the atmosphere annually and a 0.9 degrees C increase in average LST across the biome, compared to the historic baseline under native vegetation. Global climate changes from increased atmospheric greenhouse gas concentrations will only exacerbate these effects. Considering potential future scenarios, we found that abandoning deforestation control policies or allowing legal deforestation to continue (at least 28.4 Mha) would further reduce yearly ET (by -9% and -3%, respectively) and increase average LST (by +0.7 and +0.3 degrees C, respectively) by 2050. In contrast, policies encouraging zero deforestation and restoration of the 5.2 Mha of illegally deforested areas would partially offset the warming and drying impacts of land-use change.

Este capítulo discutirá los impactos observados y pronosticados del cambio climático en los ecosistemas terrestres y acuáticos amazónicos. Nos centraremos en los impactos sobre la biodiversidad, los servicios ecosistémicos, el ciclo del carbono, la pesca y las emisiones de quema de biomasa.

The Amazon River basin harbors some of the world's largest wetland complexes, which are of major importance for biodiversity, the water cycle and climate, and human activities. Accurate estimates of inundation extent and its variations across spatial and temporal scales are therefore fundamental to understand and manage the basin's resources. More than fifty inundation estimates have been generated for this region, yet major differences exist among the datasets, and a comprehensive assessment of them is lacking. Here we present an intercomparison of 29 inundation datasets for the Amazon basin, based on remote sensing only, hydrological modeling, or multi-source datasets, with 18 covering the lowland Amazon basin (elevation <500 m, which includes most Amazon wetlands), and 11 covering individual wetland complexes (subregional datasets). Spatial resolutions range from 12.5 m to 25 km, and temporal resolution from static to monthly, spanning up to a few decades. Overall, 31% of the lowland basin is estimated as subject to inundation by at least one dataset. The long-term maximum inundated area across the lowland basin is estimated at 599,700 ± 81,800 km2 if considering the three higher quality SAR-based datasets, and 490,300 ± 204,800 km2 if considering all 18 datasets. However, even the highest resolution SAR-based dataset underestimates the maximum values for individual wetland complexes, suggesting a basin-scale underestimation of ~10%. The minimum inundation extent shows greater disagreements among datasets than the maximum extent: 139,300 ± 127,800 km2 for SAR-based ones and 112,392 ± 79,300 km2 for all datasets. Discrepancies arise from differences among sensors, time periods, dates of acquisition, spatial resolution, and data processing algorithms. The median total area subject to inundation in medium to large river floodplains (drainage area > 1000 km2) is 323,700 km2. The highest spatial agreement is observed for floodplains dominated by open water such as along the lower Amazon River, whereas intermediate agreement is found along major vegetated floodplains fringing larger rivers (e.g., Amazon mainstem floodplain). Especially large disagreements exist among estimates for interfluvial wetlands (Llanos de Moxos, Pacaya-Samiria, Negro, Roraima), where inundation tends to be shallower and more variable in time. Our data intercomparison helps identify the current major knowledge gaps regarding inundation mapping in the Amazon and their implications for multiple applications. In the context of forthcoming hydrology-oriented satellite missions, we make recommendations for future developments of inundation estimates in the Amazon and present a WebGIS application (https://amazon-inundation.herokuapp.com/) we developed to provide user-friendly visualization and data acquisition of current Amazon inundation datasets.

Climate policy has thus far focused solely on carbon stocks and sequestration to evaluate the potential of forests to mitigate global warming. These factors are used to assess the impacts of different drivers of deforestation and forest degradation as well as alternative forest management. However, when forest cover, structure and composition change, shifts in biophysical processes (the water and energy balances) may enhance or diminish the climate effects of carbon released from forest aboveground biomass. The net climate impact of carbon effects and biophysical effects determines outcomes for forest and agricultural species as well as the humans who depend on them. Evaluating the net impact is complicated by the disparate spatio-temporal scales at which they operate. Here we review the biophysical mechanisms by which forests influence climate and synthesize recent work on the biophysical climate forcing of forests across latitudes. We then combine published data on the biophysical effects of deforestation on climate by latitude with a new analysis of the climate impact of the CO 2 in forest aboveground biomass by latitude to quantitatively assess how these processes combine to shape local and global climate. We find that tropical deforestation leads to strong net global warming as a result of both CO 2 and biophysical effects. From the tropics to a point between 30°N and 40°N, biophysical cooling by standing forests is both local and global, adding to the global cooling effect of CO 2 sequestered by forests. In the mid-latitudes up to 50°N, deforestation leads to modest net global warming as warming from released forest carbon outweighs a small opposing biophysical cooling. Beyond 50°N large scale deforestation leads to a net global cooling due to the dominance of biophysical processes (particularly increased albedo) over warming from CO 2 released. Locally at all latitudes, forest biophysical impacts far outweigh CO 2 effects, promoting local climate stability by reducing extreme temperatures in all seasons and times of day. The importance of forests for both global climate change mitigation and local adaptation by human and non-human species is not adequately captured by current carbon-centric metrics, particularly in the context of future climate warming.

The Caspian Sea (CS) is the largest inland lake in the world. Large variations in sea level and surface area occurred in the past and are projected for the future. The potential impacts on regional and large-scale hydroclimate are not well understood. Here, we examine the impact of CS area on climate within its catchment and across the northern hemisphere, for the first time with a fully coupled climate model. The Community Earth System Model (CESM1.2.2) is used to simulate the climate of four scenarios: (a) larger than present CS area, (b) current area, (c) smaller than present area, and (d) no-CS scenario. The results reveal large changes in the regional atmospheric water budget. Evaporation (e) over the sea increases with increasing area, while precipitation (P) increases over the south-west CS with increasing area. P-E over the CS catchment decreases as CS surface area increases, indicating a dominant negative lake-evaporation feedback. A larger CS reduces summer surface air temperatures and increases winter temperatures. The impacts extend eastwards, where summer precipitation is enhanced over central Asia and the north-western Pacific experiences warming with reduced winter sea ice. Our results also indicate weakening of the 500-hPa troughs over the northern Pacific with larger CS area. We find a thermal response triggers a southward shift of the upper troposphere jet stream during summer. Our findings establish that changing CS area results in climate impacts of such scope that CS area variations should be incorporated into climate model simulations, including palaeo and future scenarios.

Brazil’s leadership in soybean and maize production depends on predictable rainfall in the Amazon-Cerrado agricultural frontier. Here we assess whether agricultural expansion and intensification in the region are approaching a climatic limit to rainfed production. We show that yields decline in years with unusually low rainfall or high aridity during the early stages of crop development—a pattern observed in rainfed and irrigated areas alike. Although agricultural expansion and intensification have increased over time, dry–hot weather during drought events has slowed their rate of growth. Recent regional warming and drying already have pushed 28% of current agricultural lands out of their optimum climate space. We project that 51% of the region’s agriculture will move out of that climate space by 2030 and 74% by 2060. Although agronomic adaptation strategies may relieve some of these impacts, maintaining native vegetation is a critical part of the solution for stabilizing the regional climate. Soybean and maize yields in the Amazon-Cerrado region of Brazil are dependent on water from rain. Warming and drying will make the climate less suitable for agricultural production; changes have already moved 28% of croplands out of their optimum climate space.

Carbon losses from forest degradation and disturbances are significant and growing sources of emissions in the Brazilian Amazon. Between 2003 and 2019, degradation and disturbance accounted for 44% of forest carbon losses in the region, compared with 56% from deforestation (forest clearing). We found that land tenure played a decisive role in explaining these carbon losses, with Undesignated Public Forests and Other Lands (e.g., private properties) accounting for the majority (82%) of losses during the study period. Illegal deforestation and land grabbing in Undesignated Public Forests widespread and increasingly are important drivers of forest carbon emissions from the region. In contrast, indigenous Territories and Protected Natural Areas had the lowest emissions, demonstrating their effectiveness in preventing deforestation and maintaining carbon stocks. These trends underscore the urgent need to develop reliable systems for monitoring and reporting on carbon losses from forest degradation and disturbance. Together with improved governance, such actions will be crucial for Brazil to reduce pressure on standing forests; strengthen Indigenous land rights; and design effective climate mitigation strategies needed to achieve its national and international climate commitments.

The amplitude, duration, frequency, and predictability of runoff and inundation of aquatic habitats are key hydrological characteristics linked to aquatic ecosystem functioning and biodiversity, but they are seldom integrated into analyses of Amazon floodplain ecology. Remote sensing approaches, measurements and modelling of floodplain hydrology provide a basis for this integration. Effective legislation to protect floodplains and other wetlands depends on operational definitions that require application of hydrological data. Extent and changes of flooded areas are linked to fish diversity and to presence and growth of flooded forests and floating plants. Dam construction reduces river system connectivity and modifies the flood pulse, with major negative implications for floodplain ecosystems adapted to and dependent on a natural flood regime. Trends and variability in climate plus deforestation are altering the Amazon's hydrological cycle, causing changes in discharge and flooded area with concomitant ecological impacts.

The Amazon biome, despite its resilience, is being pushed by unsustainable economic drivers towards an ecological tipping point where restoration to its previous state may no longer possible. This is the result of self-reinforcing interactions between deforestation, climate change and fire. In this paper, we develop scenarios that represent movement towards an Amazon tipping point and strategies to avert one. We assess the economic, natural capital and ecosystem services impacts of these scenarios using the Integrated Economic-Environmental Modeling (IEEM) Platform linked with high resolution spatial land use land cover change and ecosystem services modeling (IEEMESM). This papers main contributions are developing: (i) a framework for evaluating strategies to avert an Amazon tipping point based on their relative costs, benefits and trade-offs, and; (ii) a first approximation of the economic, natural capital and ecosystem services impacts of movement towards an Amazon tipping point, and evidence to build the economic case for strategies to avert it. We find that a conservative estimate of the cumulative regional cost through 2050 of an Amazon tipping point would be US$256.6 billion in Gross Domestic Product. Policies that would contribute to averting a tipping point, including strongly reducing deforestation, investing in climate-adapted agriculture, and improving fire management, would generate approximately US$339.3 billion in additional wealth. From a public investment perspective, the returns to implementing strategies for averting a tipping point would be US$29.5 billion. Quantifying the costs, benefits and trade-offs of policies to avert a tipping point in a transparent and replicable manner can pave the way for evidence-based approaches to support policy action focusing on the design of regional strategies for the Amazon biome and catalyze global cooperation and financing to enable their implementation.

Nitrogen (N) fertilizer use is rapidly intensifying on tropical croplands and has the potential to increase emissions of the greenhouse gas, nitrous oxide (N2O). Since about 2005 Mato Grosso (MT), Brazil has shifted from single-cropped soybeans to double-cropping soybeans with maize, and now produces 1.5% of the world's maize. This production shift required an increase in N fertilization, but the effects on N2O emissions are poorly known. We calibrated the process-oriented biogeochemical DeNitrification-DeComposition (DNDC) model to simulate N2O emissions and crop production from soybean and soybean-maize cropping systems in MT. After model validation with field measurements and adjustments for hydrological properties of tropical soils, regional simulations suggested N2O emissions from soybean-maize cropland increased almost fourfold during 2001–2010, from 1.1 ± 1.1 to 4.1 ± 3.2 Gg 1014 N-N2O. Model sensitivity tests showed that emissions were spatially and seasonably variable and especially sensitive to soil bulk density and carbon content. Meeting future demand for maize using current soybean area in MT might require either (a) intensifying 3.0 million ha of existing single soybean to soybean-maize or (b) increasing N fertilization to ~180 kg N ha−1 on existing 2.3 million ha of soybean-maize area. The latter strategy would release ~35% more N2O than the first. Our modifications of the DNDC model will improve estimates of N2O emissions from agricultural production in MT and other tropical areas, but narrowing model uncertainty will depend on more detailed field measurements and spatial data on soil and cropping management.

Abstract Understanding which factors influence medicinal plant species selection and harvest or use pressure can provide valuable insights for sustainable management of natural resources and conservation efforts. The utilitarian redundancy model, a theoretical framework in ethnobotany, suggests that species that are therapeutically redundant or fulfil similar therapeutic functions within traditional ethnomedicine are less likely to be under greater use pressure. However, species' evolutionary relatedness and the preference of certain species over others to treat a given illness can directly affect how use pressure is diffused across several groups of species. These factors may alter the strength of the therapeutic redundancy–use pressure relationship. Medicinal plant species that fulfil the same therapeutic functions may experience greater use pressure despite their level of therapeutic redundancy because they are preferred, where most people select these species preferably over other species that are equally available for a given treatment. Furthermore, species that are closely related evolutionarily may be more likely to be harvested not because they are therapeutically unique but because they share evolutionary traits such as secondary chemistry with other medicinally important species which may make them more prone to being harvested. We investigate the effects of species therapeutic redundancy, use value, preference and evolutionary relatedness on species use pressure in the Shipibo‐Konibo community of Paoyhan in the Peruvian Amazon region. We used phylogenetic generalized least squares models to identify significant predictors of species use pressure for 62 medicinal plant species cited by 30 participants and fulfilling 31 therapeutic functions in Shipibo‐Konibo ethnomedicine. Our model controlling for species' shared evolutionary history indicated that therapeutically redundant medicinal plants experienced greater levels of use pressure. However, as preference increased, the effect of therapeutic redundancy on species use pressure became less positive. Contrary to predictions, species preference by local people alone did not predict use pressure. Furthermore, when we control for species' shared evolutionary history, the effect of preference on species use pressure was dependent on therapeutic redundancy. Our study illustrates the importance of controlling for evolutionary relatedness between species in studying plant–human interactions and the complexity involved in employing the utilitarian redundancy model to inform management and conservation efforts. A free plain language summary can be found within the Supporting Information of this article.

This chapter presents observed and predicted impacts of climate change on Amazonian ecosystems, focusing on biodiversity, ecosystem services, carbon cycling, fisheries, and emissions from biomass burning. It also considers climate and land-use change feedbacks and highlights knowledge gaps to better understand these complex interactions.