Land use has generally been considered a local environmental issue, but it is becoming a force of global importance. Worldwide changes to forests, farmlands, waterways, and air are being driven by the need to provide food, fiber, water, and shelter to more than six billion people. Global croplands, pastures, plantations, and urban areas have expanded in recent decades, accompanied by large increases in energy, water, and fertilizer consumption, along with considerable losses of biodiversity. Such changes in land use have enabled humans to appropriate an increasing share of the planet's resources, but they also potentially undermine the capacity of ecosystems to sustain food production, maintain freshwater and forest resources, regulate climate and air quality, and ameliorate infectious diseases. We face the challenge of managing trade-offs between immediate human needs and maintaining the capacity of the biosphere to provide goods and services in the long term.

Roughly 53% of Brazil's native vegetation occurs on private properties. Native forests and savannahs on these lands store 105 ± 21 GtCO₂e (billion tons of CO₂ equivalents) and play a vital role in maintaining a broad range of ecosystem services (1). Sound management of these private landscapes is critical if global efforts to mitigate climate change are to succeed. Recent approval of controversial revisions to Brazil's Forest Code (FC)—the central piece of legislation regulating land use and management on private properties—may therefore have global consequences. Here, we quantify changes resulting from the FC revisions in terms of environmental obligations and rights granted to land-owners. We then discuss conservation opportunities arising from new policy mechanisms in the FC and challenges for its implementation.

Interactions between climate and land-use change may drive widespread degradation of Amazonian forests. High-intensity fires associated with extreme weather events could accelerate this degradation by abruptly increasing tree mortality, but this process remains poorly understood. Here we present, to our knowledge, the first field-based evidence of a tipping point in Amazon forests due to altered fire regimes. Based on results of a large-scale, long-term experiment with annual and triennial burn regimes (B1yr and B3yr, respectively) in the Amazon, we found abrupt increases in fire-induced tree mortality (226 and 462%) during a severe drought event, when fuel loads and air temperatures were substantially higher and relative humidity was lower than long-term averages. This threshold mortality response had a cascading effect, causing sharp declines in canopy cover (23 and 31%) and aboveground live biomass (12 and 30%) and favoring widespread invasion by flammable grasses across the forest edge area (80 and 63%), where fires were most intense (e.g., 220 and 820 kW⋅m⁻¹). During the droughts of 2007 and 2010, regional forest fires burned 12 and 5% of southeastern Amazon forests, respectively, compared with <1% in nondrought years. These results show that a few extreme drought events, coupled with forest fragmentation and anthropogenic ignition sources, are already causing widespread fire-induced tree mortality and forest degradation across southeastern Amazon forests. Future projections of vegetation responses to climate change across drier portions of the Amazon require more than simulation of global climate forcing alone and must also include interactions of extreme weather events, fire, and land-use change. Significance Climate change alone is unlikely to drive severe tropical forest degradation in the next few decades, but an alternative process associated with severe weather and forest fires is already operating in southeastern Amazonia. Recent droughts caused greatly elevated fire-induced tree mortality in a fire experiment and widespread regional forest fires that burned 5–12% of southeastern Amazon forests. These results suggest that feedbacks between fires and extreme climatic conditions could increase the likelihood of an Amazon forest “dieback” in the near-term. To secure the integrity of seasonally dry Amazon forests, efforts to end deforestation must be accompanied by initiatives that reduce the accidental spread of land management fires into neighboring forest reserves and effectively suppress forest fires when they start.

While a new class of Dynamic Global Ecosystem Models (DGEMs) has emerged in the past few years as an important tool for describing global biogeochemical cycles and atmosphere‐biosphere interactions, these models are still largely untested. Here we analyze the behavior of a new DGEM and compare the results to global‐scale observations of water balance, carbon balance, and vegetation structure. In this study, we use version 2 of the Integrated Biosphere Simulator (IBIS), which includes several major improvements and additions to the prototype model developed by Foley et al. [1996]. IBIS is designed to be a comprehensive model of the terrestrial biosphere; the model represents a wide range of processes, including land surface physics, canopy physiology, plant phenology, vegetation dynamics and competition, and carbon and nutrient cycling. The model generates global simulations of the surface water balance (e.g., runoff), the terrestrial carbon balance (e.g., net primary production, net ecosystem exchange, soil carbon, aboveground and belowground litter, and soil CO₂ fluxes), and vegetation structure (e.g., biomass, leaf area index, and vegetation composition). In order to test the performance of the model, we have assembled a wide range of continental and global‐scale data, including measurements of river discharge, net primary production, vegetation structure, root biomass, soil carbon, litter carbon, and soil CO₂ flux. Using these field data and model results for the contemporary biosphere (1965–1994), our evaluation shows that simulated patterns of runoff, NPP, biomass, leaf area index, soil carbon, and total soil CO₂ flux agree reasonably well with measurements that have been compiled from numerous ecosystems. These results also compare favorably to other global model results.