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We present the results from a litter translocation experiment along a 2800-m elevation gradient in Peruvian tropical forests. The understanding of the environmental factors controlling litter decomposition is important in the description of the carbon and nutrient cycles of tropical ecosystems, and in predicting their response to long-term increases in temperature. Samples of litter from 15 species were transplanted across all five sites in the study, and decomposition was tracked over 448 d. Species' type had a large influence on the decomposition rate (k), most probably through its influence on leaf quality and morphology. When samples were pooled across species and elevations, soil temperature explained 95% of the variation in the decomposition rate, but no direct relationship was observed with either soil moisture or rainfall. The sensitivity of the decay rate to temperature (𝒦 T ) varied seven-fold across species, between 0.024 and 0.169°C⁻¹, with a mean value of 0.118 ± 0.009°C⁻¹ (SE). This is equivalent to a temperature sensitivity parameter (Q₁₀) for litter decay of 3.06 ± 0.28, higher than that frequently assumed for heterotrophic processes. Our results suggest that the warming of approx. 0.9°C experienced in the region in recent decades may have increased decomposition and nutrient mineralization rates by c. 10%.

Bolivia is located at the crossroad of the major climatic influences of Northern and Southern-South America, which turns this country into a natural laboratory to investigate the interactions between ocean-climate and fire variability. We chose two oceanic indices: MEI (multivariate ENSO Index) and AMO (Atlantic Multidecadal Oscillation) to select the three most representative years for four oceanic conditions: El Niño, La Niña, AMO, and standard years (understood as years with little ocean influences), for the period 1992–2012. We investigated how i) rainfall (dry vs wet seasons) and ii) fire responded in five Bolivian biomes (Tropical Moist Forests, Tropical Dry Forests, Tropical Grasslands, Tropical Montane, and Seasonally Flooded ecosystems) under these oceanic conditions. Bolivia showed a strong rainfall increase in El Niño years in both seasons (wet/dry), while AMO showed the strongest droughts in both seasons. La Niña showed a bipolar response with rainfall increases in the wet season and a very marked rainfall decrease in the dry season. Drought significantly increased fire numbers in AMO years, being the most significant fire condition and suggesting a larger fire influence of the Atlantic than the Pacific at the national level. Surprisingly, the amount of fire was very large under normal years (STD) and similar to fire levels under La Niña, suggesting generalized fire conditions in the country, except for El Niño years that bring rainfall excess and little fire. The most fire-affected biomes were the seasonally flooded and dry forests, followed by the grassland/savannah biome. Montane areas showed the least fire, but satellite fire omission is well known in the Andean region.

Understanding the global carbon (C) cycle is of crucial importance to map current and future climate dynamics relative to global environmental change. A full characterization of C cycling requires detailed information on spatiotemporal patterns of surface–atmosphere fluxes. However, relevant C cycle observations are highly variable in their coverage and reporting standards. Especially problematic is the lack of integration of the carbon dioxide (CO2) exchange of the ocean, inland freshwaters and the land surface with the atmosphere. Here we adopt a data-driven approach to synthesize a wide range of observation-based spatially explicit surface–atmosphere CO2 fluxes from 2001 to 2010, to identify the state of today's observational opportunities and data limitations. The considered fluxes include net exchange of open oceans, continental shelves, estuaries, rivers, and lakes, as well as CO2 fluxes related to net ecosystem productivity, fire emissions, loss of tropical aboveground C, harvested wood and crops, as well as fossil fuel and cement emissions. Spatially explicit CO2 fluxes are obtained through geostatistical and/or remote-sensing-based upscaling, thereby minimizing biophysical or biogeochemical assumptions encoded in process-based models. We estimate a bottom-up net C exchange (NCE) between the surface (land, ocean, and coastal areas) and the atmosphere. Though we provide also global estimates, the primary goal of this study is to identify key uncertainties and observational shortcomings that need to be prioritized in the expansion of in situ observatories. Uncertainties for NCE and its components are derived using resampling. In many regions, our NCE estimates agree well with independent estimates from other sources such as process-based models and atmospheric inversions. This holds for Europe (mean ± 1 SD: 0.8 ± 0.1 PgC yr−1, positive numbers are sources to the atmosphere), Russia (0.1 ± 0.4 PgC yr−1), East Asia (1.6 ± 0.3 PgC yr−1), South Asia (0.3 ± 0.1 PgC yr−1), Australia (0.2 ± 0.3 PgC yr−1), and most of the Ocean regions. Our NCE estimates give a likely too large CO2 sink in tropical areas such as the Amazon, Congo, and Indonesia. Overall, and because of the overestimated CO2 uptake in tropical lands, our global bottom-up NCE amounts to a net sink of −5.4 ± 2.0 PgC yr−1. By contrast, the accurately measured mean atmospheric growth rate of CO2 over 2001–2010 indicates that the true value of NCE is a net CO2 source of 4.3 ± 0.1 PgC yr−1. This mismatch of nearly 10 PgC yr−1 highlights observational gaps and limitations of data-driven models in tropical lands, but also in North America. Our uncertainty assessment provides the basis for setting priority regions where to increase carbon observations in the future. High on the priority list are tropical land regions, which suffer from a lack of in situ observations. Second, extensive pCO2 data are missing in the Southern Ocean. Third, we lack observations that could enable seasonal estimates of shelf, estuary, and inland water–atmosphere C exchange. Our consistent derivation of data uncertainties could serve as prior knowledge in multicriteria optimization such as the Carbon Cycle Data Assimilation System (CCDAS) and atmospheric inversions, without over- or under-stating bottom-up data credibility. In the future, NCE estimates of carbon sinks could be aggregated at national scale to compare with the official national inventories of CO2 fluxes in the land use, land use change, and forestry sector, upon which future emission reductions are proposed.

Schemes that reward developing countries for mitigating greenhouse-gas (GHG) emissions through forest preservation and restoration are becoming more common. However, efforts to reduce GHG emissions must also consider food production. This creates an apparent conflict, given that agricultural production - a key driver of GHG emissions as a consequence of forest clearance - will increase as human populations continue to grow. We propose that a mosaic of small patches of forest mixed with cropland enables sustainable intensification of agriculture by minimizing soil degradation. Economic analyses of this mixed land-use concept suggest an improvement of long-term economic performance of 19-25% relative to conventional industrial agriculture with large-scale monocropping. Adopting this approach requires farm management plans, landscape zoning, and new instruments to finance sustainable agriculture. We conclude that climate policy and food production can be reconciled through an integrative landscape concept that combines this more sustainable method of agricultural intensification with the reforestation of abandoned lands.

If tropical farmers cannot be provided with sustainable land‐use systems, which address their subsistence needs and keep them gainfully employed, tropical forests will continue to disappear. We looked at the ability of economic land‐use diversification – with reforestation of tropical “wastelands” as a key activity – to halt deforestation at the farm level. Our ecological–economic concept, based on land‐use data from the buffer area of the Podocarpus National Park in southern Ecuador, shows that stopping deforestation after 10 years is possible without violating subsistence demands. Tropical, farm‐level diversification may not only reduce total deforestation by 45%, but also increase farmers' profits by 65%, because the formerly unproductive wastelands have been returned to productive land use. We therefore conclude that a “win–win” scenario is possible: the subsistence needs of people can be reconciled with conservation objectives. However, inexpensive microcredits (at interest rates below 6%) and experience on alternative land‐use opportunities must be offered to farmers.

Warm-water coral reefs are facing unprecedented human-driven threats to their continued existence as biodiverse functional ecosystems upon which hundreds of millions of people rely. These impacts may drive coral ecosystems past critical thresholds, beyond which the system reorganises, often abruptly and potentially irreversibly; this is what the Intergovernmental Panel on Climate Change (IPCC, 2022) define as a tipping point. Determining tipping point thresholds for coral reef ecosystems requires a robust assessment of multiple stressors and their interactive effects. In this perspective piece, we draw upon the recent global tipping point revision initiative (Lenton et al., 2023a) and a literature search to identify and summarise the diverse range of interacting stressors that need to be considered for determining tipping point thresholds for warm-water coral reef ecosystems. Considering observed and projected stressor impacts, we endorse the global tipping point revision's conclusion of a global mean surface temperature (relative to pre-industrial) tipping point threshold of 1.2 °C (range 1–1.5 °C) and the long-term impacts of atmospheric CO2 concentrations above 350 ppm, while acknowledging that comprehensive assessment of stressors, including ocean warming response dynamics, overshoot, and cascading impacts, have yet to be sufficiently realised. These tipping point thresholds have already been exceeded, and therefore these systems are in an overshoot state and are reliant on policy actions to bring stressor levels back within tipping point limits. A fuller assessment of interacting stressors is likely to further lower the tipping point thresholds in most cases. Uncertainties around tipping points for such crucially important ecosystems underline the imperative of robust assessment and, in the case of knowledge gaps, employing a precautionary principle favouring lower-range tipping point values.

Tropical and subtropical areas present the vast majority of contemporary global fires. Despite the human origin of most of these fires, little is known of how environmental and socioeconomic variables contribute to the spatial patterns of fire incidence and burned areas. The tropical Mexican State of Chiapas represents a good case study to analyze these interactions, due to the availability of official data, and its similarities to other tropical countries, in terms of environmental and socioeconomic characteristics. This study evaluates the relative importance of human-related and environmental variables in determining the distribution of the number of fires and area burned in the tropical State of Chiapas in years of normal and extreme climatic conditions (non-El Niño vs. El Niño). We have searched for causal relationships among fire, environmental, and socioeconomic variables in Chiapas using path analysis. Results of this study show a major importance of environmental variables in non-El Niño years, suggesting that the status of the vegetation was the main cause determining fire ignition and fire spread in these years. Contrarily, the observed trends in the El Niño period indicate that fire trends were mainly determined by the presence of ignition agents. In these El Niño years, vegetation is so severely water stressed that, when fire starts, all vegetation types burn, regardless of their flammability properties. The main vegetation types affected by fire in non-El Niño years were the most flammable ones, such as pine-oak communities, while rainforests burned the most in El Niño years. Altitude, pine-oak communities, and poverty levels played major roles in the arboreal fire incidence in non-El Niño years, whereas the distribution of pastures appeared as an important variable determining arboreal fire incidence in El Niño years. When all fires were considered (affecting any vegetation layer), almost identical trends were observed, with the incorporation of a new variable influencing the area burned: density of infrastructure. The results of this study strengthen the importance of El Niño years in the conservation of rainforest ecosystems and suggest the existence of synergistic effects involving fires, fragmentation, and certain elements of the landscape, such as cattle pastures, in tropical areas.

According to the latest report of the Intergovernmental Panel on Climate Change (IPCC), emissions must be cut by 41–72 % below 2010 levels by 2050 for a likely chance of containing the global mean temperature increase to 2 °C. The AFOLU sector (Agriculture, Forestry and Other Land Use) contributes roughly a quarter ( ∼  10–12 Pg CO2e yr−1) of the net anthropogenic GHG emissions mainly from deforestation, fire, wood harvesting, and agricultural emissions including croplands, paddy rice, and livestock. In spite of the importance of this sector, it is unclear where the regions with hotspots of AFOLU emissions are and how uncertain these emissions are. Here we present a novel, spatially comparable dataset containing annual mean estimates of gross AFOLU emissions (CO2, CH4, N2O), associated uncertainties, and leading emission sources, in a spatially disaggregated manner (0.5°) for the tropics for the period 2000–2005. Our data highlight the following: (i) the existence of AFOLU emissions hotspots on all continents, with particular importance of evergreen rainforest deforestation in Central and South America, fire in dry forests in Africa, and both peatland emissions and agriculture in Asia; (ii) a predominant contribution of forests and CO2 to the total AFOLU emissions (69 %) and to their uncertainties (98 %); (iii) higher gross fluxes from forests, which coincide with higher uncertainties, making agricultural hotspots appealing for effective mitigation action; and (iv) a lower contribution of non-CO2 agricultural emissions to the total gross emissions (ca. 25 %), with livestock (15.5 %) and rice (7 %) leading the emissions. Gross AFOLU tropical emissions of 8.0 (5.5–12.2) were in the range of other databases (8.4 and 8.0 Pg CO2e yr−1 in FAOSTAT and the Emissions Database for Global Atmospheric Research (EDGAR) respectively), but we offer a spatially detailed benchmark for monitoring progress in reducing emissions from the land sector in the tropics. The location of the AFOLU hotspots of emissions and data on their associated uncertainties will assist national policy makers, investors, and other decision-makers who seek to understand the mitigation potential of the AFOLU sector.

The Agriculture, Forestry and Other Land Use (AFOLU) sector contributes with ca. 20–25 % of global anthropogenic emissions (2010), making it a key component of any climate change mitigation strategy. AFOLU estimates, however, remain highly uncertain, jeopardizing the mitigation effectiveness of this sector. Comparisons of global AFOLU emissions have shown divergences of up to 25 %, urging for improved understanding of the reasons behind these differences. Here we compare a variety of AFOLU emission datasets and estimates given in the Fifth Assessment Report for the tropics (2000–2005) to identify plausible explanations for the differences in (i) aggregated gross AFOLU emissions, and (ii) disaggregated emissions by sources and gases (CO2, CH4, N2O). We also aim to (iii) identify countries with low agreement among AFOLU datasets to navigate research efforts. The datasets are FAOSTAT (Food and Agriculture Organization of the United Nations, Statistics Division), EDGAR (Emissions Database for Global Atmospheric Research), the newly developed AFOLU “Hotspots”, “Houghton”, “Baccini”, and EPA (US Environmental Protection Agency) datasets. Aggregated gross emissions were similar for all databases for the AFOLU sector: 8.2 (5.5–12.2), 8.4, and 8.0 Pg CO2 eq. yr−1 (for Hotspots, FAOSTAT, and EDGAR respectively), forests reached 6.0 (3.8–10), 5.9, 5.9, and 5.4 Pg CO2 eq. yr−1 (Hotspots, FAOSTAT, EDGAR, and Houghton), and agricultural sectors were with 1.9 (1.5–2.5), 2.5, 2.1, and 2.0 Pg CO2 eq. yr−1 (Hotspots, FAOSTAT, EDGAR, and EPA). However, this agreement was lost when disaggregating the emissions by sources, continents, and gases, particularly for the forest sector, with fire leading the differences. Agricultural emissions were more homogeneous, especially from livestock, while those from croplands were the most diverse. CO2 showed the largest differences among the datasets. Cropland soils and enteric fermentation led to the smaller N2O and CH4 differences. Disagreements are explained by differences in conceptual frameworks (carbon-only vs. multi-gas assessments, definitions, land use vs. land cover, etc.), in methods (tiers, scales, compliance with Intergovernmental Panel on Climate Change (IPCC) guidelines, legacies, etc.) and in assumptions (carbon neutrality of certain emissions, instantaneous emissions release, etc.) which call for more complete and transparent documentation for all the available datasets. An enhanced dialogue between the carbon (CO2) and the AFOLU (multi-gas) communities is needed to reduce discrepancies of land use estimates.

The vast majority of the world's fires today occur in tropical and subtropical areas. The problem of fire in these countries reflects increased human and climatic pressures, which provoke interactions between fire and the transformed landscapes. Chiapas, a tropical state in the Mexican Republic, maintains a fire dataset, and it has similarities with other tropical areas. This study represents a descriptive approach to the problem in Chiapas, where fire is recognized as a major disturbance that degrades habitats and reduces ecosystem services. To date there has been little information about fire trends and contributing factors, but both frequency and intensity of fires appear to increase in El Niño years and to vary with landownership.