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The North Atlantic Basin (NAB) is seeing a significant increase in the frequency and intensity of tropical cyclones since the 1980s, with record-breaking seasons such as 2017 and 2020. However, little is known about how coastal ecosystems, particularly mangroves in the Gulf of Mexico and the Caribbean, are responding to these new “climate normals” at regional and subregional scales. Wind speed, rainfall, pre-cyclone forest structure, and hydro-geomorphology are known to influence mangrove damage and recovery following cyclones in the NAB. However, these studies have focused on site-specific responses and individual cyclonic events. Here, we analyze 25 years (1996-2020) of mangrove vulnerability (damage after a cyclone) and short-term resilience (recovery after damage) for the entire NAB and its subregions, using multi-annual, remote sensing-derived databases. We applied machine learning to characterize the influence of 22 potential drivers that include previously researched variables and new ones such as human development and long-term climate trends. The characteristics of the cyclones mainly drive vulnerability at the regional level, while resilience is largely driven by site-specific conditions. These include long-term climate conditions, such as air temperature and drought trends, pre-cyclone habitat conditions, such as canopy cover and height and soil organic carbon stock, and human interventions on the land. Rates and drivers of mangrove vulnerability and resilience vary across subregions in the NAB, and hotspots for restoration and conservation actions are highlighted within subregions. The impacts of increasing cyclone activity need to be framed in the context of climate change compound effects and heavy human influences in the region. There is an urgent need to value the restoration and conservation of mangroves as fundamental Nature-based Solutions against cyclone impacts in the NAB.

The BlueFlux field campaign is supported by NASA’s Carbon Monitoring System (CMS) and will develop prototype blue carbon products to inform coastal carbon management. Blue carbon is included in carbon-dioxide removal actions proposed to reduce atmospheric CO2 concentrations to mitigate climate change. Due to their high productivity and carbon storage, combined with historic losses and a wide-range of beneficial ecosystem services, the restoration and conservation of mangrove ecosystems features prominently in blue-carbon planning. The goal of BlueFlux is to carry out multi-scale measurements of CO2 and CH4 fluxes using chambers, flux towers, and aircraft and scale these to gridded products using space-based observations of forest structure and surface reflectance. The measurements cover gradients in disturbance, mainly from the history of hurricanes in the region that drive the dieback of mangroves and the formation of ‘ghost forests’. The fluxes of CH4 emissions will be contrasted with CO2 uptake to provide a more complete budget of radiative forcing and to understand the net climate benefits of blue carbon. BlueFlux demonstrates that quantifying the removals of CO2 and emissions of CH4 using a multi-scale approach can provide increased confidence in regional greenhouse-gas accounting, contribute to process-understanding, and help inform restoration and conservation efforts in the context of climate mitigation.

To know the quantity of fine root biomass is crucial to understanding ecosystem structure and function. Soil characteristics and fertility are mainly determined by fine root dynamics, the turnover of this material is a major contribution of organic matter to soil structure and mineral nutrient cycles, and also the main source of carbon storage. Many studies of forests are mainly estimates of above-ground biomass. Here we report on differential patterns of fine root biomass allocation in Peruvian forests. Peru is divided into three large sub-regions, Amazon, Andean, and coast. These different ecosystems have also around 84 of the 103 ecosystems types and 28 of the 32 climates on the planet. A field study was conducted installing one-hectare permanent plots in each sub-region, this research was part of an intensive monitoring effort of the carbon cycle and functional traits in primary and secondary forests. To evaluate fine root biomass, 1 m2 cross-section pits were set up in the plots where soil samples were collected every 10 cm up to 1 m depth and every 25 cm up to 2 m depth. Roots were retrieved and sorted into different diameter categories ≤0.5, 0.5 - 2.5, 2.5 - 5, and> 5 cm. Samples were rinsed with tap water over a 500-um sieve to loosen the soil and facilitate root sorting and to ensure that the sieve was fine enough to retain the finer roots. The roots after sorting were weighed fresh and then dried at 80°C for 48 hours, weighed to the nearest 0.0001 g, and stored in plastic vials for chemical analysis.Total root biomass measurements displayed strong regional differences. Coastal dry forest at 370 to 422 m in elevation, where a one ha plot can support 651-681 stems (> 10 cm dbh) had root biomass values ranging from 7960 kg ha-1 to 8130 kg/ha-1. Andean forest plots at 1780 m.a.s.l., with 586 stems contained 17020 kg ha-1 and Amazonian forest at 415 m.a.s.l., with 689 stems, had 33410 kg ha-1 fine root biomass. Our results support the hypothesis that large root biomass in tropical forests is related to ecosystem type, climatic variables (temperature and moisture), and nutrients. The low bulk density and fine root biomass in tropical forests are inversely related to temperature and moisture. Fine-root turnover decreased with soil depth, which can also have important implications for the soil carbon stock and C cycling.

Managing forests for climate change mitigation requires action by diverse stakeholders undertaking different activities with overlapping objectives and spatial impacts. To date, several forest carbon monitoring systems have been developed for different regions using various data, methods and assumptions, making it difficult to evaluate mitigation performance consistently across scales. Here, we integrate ground and Earth observation data to map annual forest-related greenhouse gas emissions and removals globally at a spatial resolution of 30 m over the years 2001–2019. We estimate that global forests were a net carbon sink of −7.6 ± 49 GtCO2e yr−1, reflecting a balance between gross carbon removals (−15.6 ± 49 GtCO2e yr−1) and gross emissions from deforestation and other disturbances (8.1 ± 2.5 GtCO2e yr−1). The geospatial monitoring framework introduced here supports climate policy development by promoting alignment and transparency in setting priorities and tracking collective progress towards forest-specific climate mitigation goals with both local detail and global consistency.

Andean tropical montane forests (TMF) are hotspots of biodiversity that provide fundamental hydrological services as well as carbon sequestration and storage. Agroforestry systems occupy large areas in the Andes but climatic pressures, market volatility and diseases may result inagroforest abandonment, promoting secondary succession. Secondary forests are well-adapted and efficient carbon sinks whose conservation is vital to mitigate and adapt to climate change and to support biodiversity. Little is known, however, about how secondary TMF recover their aboveground biomass (AGB) and composition after abandonment. We established a 1.5 ha plot at 1780 masl on a 30-year old abandoned agroforest and compared it against two control forest plots at similar elevations. Agroforestry legacies influenced AGB leading to far lower stocks (42.3 +/- 5.4-59.6 +/- 7.9 Mg ha(-1) using allometric equations) than those expected after 30 years (106 +/- 33 Mg ha(-1)) based on IPCC standard growth rates for secondary montane forests. This suggests a regional overestimation of mitigation potentials when using IPCC standards. Satellite-derived AGB largely overestimated our plot values (179 +/- 27.3 Mg ha(-1)). Secondary growth rates (1.41-2.0 Mg ha(-1) yr(-1) for DBH >= 10 cm) indicate recovery times of ca. 69 to 97 years to reach average control AGB values (137 +/- 12.3 Mg ha(-1)). This is 26 years above the average residence time of montane forests at our elevation (71 +/- 1.91 years) suggesting a non-recovery or far slower recovery to control AGB values. Three variables appear to define this outcome compared to the control plots: lower DBH (15.8 +/- 5.9 cm vs 19.8 +/- 11.0 cm), lower basal area (12.67 +/- 0.7 vs 28.03 +/- 1.5 m(2) ha(-1)) and higher abundance of lighter-wood tree genera (0.46 +/- 0.10 vs 0.57 +/- 0.11 gr cm(3)) such as Inga, a common shade-tree in Andean agroforests. With 3.2 million hectares committed to restoration, Peru needs to target currently neglected TMF recovery schemes to support biodiversity, water and carbon storage and fulfill its international commitments. This work was supported by a CONCYTEC (Peru) -World Bank grant (Contract 011-2019-FONDECYT-BM-INC-INV). In Huayopata we thank the Cuba and Povea families for their hospitality and help during field work.

Defining the most important factors related with forest carbon (C) stocks in different forest types is still a controversial topic. In this study we used data from 10,500 plots from The National Forest Inventory of Mexico encompassing the six main forest types in Mexico (conifer, broadleaf, mixed, evergreen and semi-deciduous, dry and semiarid forests) in order to identify the main factors related to the spatial pattern of C stocks, including climate (temperature and rainfall), forest diversity (structural and species richness), topographic and soil characteristics (soil depth, slope and land tenure) and disturbance factors (fires, pests and tree felling). We built two different types of models, one taking all plots into account (global model, R2 = 0.54, P

Voluntary markets transacted over $66 million USD of forest carbon offsets in 2016, according to Forest Trends, and over 99% of those offset projects were audited to a standard, primarily the Verified Carbon Standard (VCS). We provide a table characterizing all 70 validated and verified forest carbon projects employing the VCS version 3.0 currently-in-use (December 2011–July 2017). We also examine two separate aspects of the audit process––impact and thoroughness––to assess the effectiveness of the costly audit process, which can consume up to one-third of offset revenue. Audit impact we measure in terms of reduction in the number of offsets from ex ante estimated to ex post approved. Audit thoroughness we measure both directly in terms of the number of auditor hours worked per project and also indirectly in terms of the total number of Corrective Action Requests (CARs)/Non-Conformity Reports (NCRs) auditors prescribe. In terms of impact, we find that Afforestation/Reforestation/Restoration (A/R/R) and Improved Forest Management (IFM) projects, though only constituting 5% of total verified offsets, demonstrate significant (p ex ante estimated to ex post approved offsets, likely because auditors can easily scrutinize carbon stocks/emission factors for the commercial tree species involved in these project types. In terms of thoroughness, we find that higher ex ante estimates correlate with more total auditor hours worked and total CARs/NCRs prescribed for three of four project activity types, likely because auditors perceive larger ex ante projects as higher risk. We conclude with recommendations for the VCS to empower auditors to scrutinize carbon stocks/emissions factors from avoided deforestation projects, and also to continue to flag high ex ante projects as higher risk.

Naturally isolated montane forests in East Africa are hotspots of biodiversity, often characterised by high species endemism, and are fundamental contributors to water services. However, they are located in areas highly suitable for agriculture, making them a prime target for agricultural activities. The Eastern Arc Mountains (EAM) in Eastern Tanzania are within the target regions for agricultural development under the Southern Agricultural Growth Corridor of Tanzania (SAGCOT). However, forest monitoring initiatives that track long-term forest dynamics and the ecological impact of current agricultural development policies on forests, are lacking. Here, we use the STEF (Space-Time Extremes and Features) algorithm and Landsat time series to track forest disturbances (deforestation and degradation) and forest gains (regeneration) as spatio-temporal events over seventeen years (2001–2017) in the montane forests of the Mvomero District in Tanzania. We found that 27 % (∼ 20 487 ha) of montane forests were disturbed between 2001 and 2017, mainly led by deforestation (70 %). Small-scale crop farms with maize, banana, and cassava crops, were the most planted on deforested areas. Most disturbances occurred at lower elevation (lowland montane), but there was an increasing shift to higher elevations in recent years (2011–2017). Forest disturbances exclusively occurred at small spatial scales, a pattern similar to other forest montane landscapes in Africa, which lowers detection capabilities in global forest loss products. Our locally calibrated and validated deforestation map (Producer's accuracy = 80 %; User’s accuracy = 78 %) shows a gross underestimation of forest cover loss (>10 000 ha) by global forest loss products in these mountainous forest landscapes. Overall, we found few areas undergoing forest regeneration, with only 9 % of the disturbed forest regenerating over 17 years. Long-term conversion to cropland prevented regeneration in the lowlands, with regeneration mainly happening at higher elevations. However, the shift of deforestation and forest degradation to higher elevations may challenge high elevation regeneration trends, leaving the remaining blocks of montane forest in the Mvomero District at a risk of degradation and disappearance. Without effective forest conservation measures, market-driven agricultural development is likely to trigger an expansion of cropland at the expense of forests to meet the increased demand for the agricultural products promoted, with negative impact on biodiversity, carbon sequestration and water services.

Land degradation is a globally recognized problem and restoration of degraded land is currently high on the international agenda. Forest landscape restoration and other restorative ecosystem management activities are important measures that contribute towards reaching the objectives of the Bonn Challenge, which aims to restore 350 million hectares by 2030. In this context, many restoration projects are being planned and implemented in Latin America and the Caribbean (LAC). We present an overview of the location, goals and activities, and an estimated climate change mitigation potential of 154 recent, ongoing and planned restoration projects in LAC. Our analysis suggests that most projects are located in the humid tropics and less attention is paid to drylands. Increasing vegetation cover, biodiversity recovery and recovery of ecological processes are the most common goals. Restorative activities to fulfil these goals were diverse and were related to the type and source of funding that projects receive. For example, projects implemented through the Forest Investment Program (FIP) and the Global Environment Facility (GEF) generally rely on natural or assisted regeneration over large areas (&gt, 20,000 ha), whereas Clean Development Mechanism (CDM) projects establish forest plantations, often including exotic monocultures, in smaller project areas (&lt, 5000 ha). Projects that are specifically implemented within the scope of Initiative 20 &times, 20 and other local initiatives that target the local environmental problems, are more varied and rely on a wider portfolio of restorative activities, such as erosion control, exclusion of grazing and mixed plantations. These projects are usually implemented in smaller project areas (&lt, 5000 ha). All projects had the potential to contribute to climate change mitigation by storing additional forest aboveground biomass through natural regeneration, assisted regeneration or establishing a plantation. Further analysis of the implemented activities is an important next step to investigate their effectiveness in terms of goals achieved under Initiative 20 &times, 20 and the Bonn Challenge. This would provide information for future restoration projects and upscaling of restorative activities in a wider area.

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.

Comprised of 17 named tropical storms, 6 of which were major hurricanes, the 2017 Atlantic hurricane season ranked as one of the most damaging and costly hurricane seasons on record. In addition to socio-economic impacts, many previous studies have shown that important coastal ecosystems like mangroves are shaped by severe storms. However, little is known about how the cumulative effects of storms over entire hurricane seasons affect mangroves across large regions. We used satellite imagery from the entire Caribbean and Gulf of Mexico region to show that 2017 resulted in disproportionate mangrove damage compared to baseline responses over the previous 8 years. Specifically, we observed 30 times more mangrove damage, via a reduction in the normalized difference vegetation index (NDVI), during 2017 compared to any of the eight previous hurricane seasons, and most (72%) of this damage persisted throughout the 7 month post-hurricane season period as indicated by no NDVI recovery. Furthermore, wind speed, rainfall, and canopy height data showed that mangrove damage primarily resulted from high maximum wind speeds, but flooding (cumulative rainfall), previous storm history, and mangrove structure (canopy height) were also important predictors of damage. While mangroves are known to be resilient to hurricane impacts, our results suggest that increasingly frequent mega-hurricane seasons in the Caribbean region will dramatically alter mangrove disturbance dynamics.

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 (CO$_{2}$, CH$_{4}$, N$_{2}$O). 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 PgCO$_{2}$ eq. yr$^{-1}$ (for Hotspots, FAOSTAT, and EDGAR respectively), forests reached 6.0 (3.8–10), 5.9, 5.9, and 5.4 PgCO$_{2}$ 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 PgCO$_{2}$ eq. yr$^{-1}$ (Hotspots, FAOSTAT, Published by Copernicus Publications on behalf of the European Geosciences Union. 5800 R. M. Roman-Cuesta et al.: AFOLU dataset comparisons 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. CO$_{2}$ showed the largest differences among the datasets. Cropland soils and enteric fermentation led to the smaller N$_{2}$O and CH$_{4}$ 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 (CO$_{2}$/ and the AFOLU (multi-gas) communities is needed to reduce discrepancies of land use estimates.

Tropical montane cloud forests (TMCFs) harbour high levels of biodiversity and large carbon stocks. Their location at high elevations make them especially sensitive to climate change, because a warming climate is enhancing upslope species migration, but human disturbance (especially fire) may in many cases be pushing the treeline downslope. TMCFs are increasingly being affected by fire, and the long-term effects of fire are still unknown. Here we present a 28-years chronosequence to assess the effects of fire and recovery pathways of burned TMCFs, with a detailed analysis of carbon stocks, forest structure and diversity. We assessed rates of change of carbon (C) stock pools, forest structure, and tree size distribution pathways and tested several hypotheses regarding metabolic scaling theory (MST), C recovery and biodiversity. We found four different C stock recovery pathways depending on the selected C pool and time since last fire, with a recovery of total C stocks but not of aboveground C stocks. In terms of forest structure, there was an increase in the number of small stems in the burned forests up to 5-9 years after fire because of regeneration patterns, but no differences on larger trees between burned and unburned plots in the long term. In support of MST, after fire, forest structure appears to approximate steady state size distribution in less than 30 years. However, our results also provide new evidence that the species recovery of TMCF after fire is idiosyncratic and follows multiple pathways. While fire increased species richness it also enhanced species dissimilarity with geographical distance. This is the first study to report a long-term chronosequence of recovery pathways to fire suggesting faster recovery rates than previously reported, but at the expense of biodiversity and aboveground C stocks. This article is protected by copyright. All rights reserved.

Global climate models suggest enhanced warming of the tropical mid and upper troposphere, with larger temperature rise rates at higher elevations. Changes in fire activity are amongst the most significant ecological consequences of rising temperatures and changing hydrological properties in mountainous ecosystems, and there is a global evidence of increased fire activity with elevation. Whilst fire research has become popular in the tropical lowlands, much less is known of the tropical high Andean region (2000 masl, from Colombia to Bolivia). This study examines fire trends in the high Andes for three ecosystems, the Puna, the Paramo and the Yungas, for the period 1982-2006. We pose three questions: (i) is there an increased fire response with elevation? (ii) does the El Niño- Southern Oscillation control fire activity in this region? (iii) are the observed fire trends human driven (e.g., human practices and their effects on fuel build-up) or climate driven? We did not find evidence of increased fire activity with elevation but, instead, a quasicyclic and synchronous fire response in Ecuador, Peru and Bolivia, suggesting the influence of high-frequency climate forcing on fire responses on a subcontinental scale, in the high Andes. ENSO variability did not show a significant relation to fire activity for these three countries, partly because ENSO variability did not significantly relate to precipitation extremes, although it strongly did to temperature extremes. Whilst ENSO did not individually lead the observed regional fire trends, our results suggest a climate influence on fire activity, mainly through a sawtooth pattern of precipitation (increased rainfall before fire-peak seasons (t-1) followed by drought spells and unusual low temperatures (t0), which is particularly common where fire is carried by low fuel loads (e.g., grasslands and fine fuel). This climatic sawtooth appeared as the main driver of fire trends, above local human influences and fuel build-up cyclicity.

Key messagesA new global wetlands map, which uses a multisource approach (satellite, climatic and topographic data) and is underpinned by an expert system model with high spatial detail (232 x 232 m2), is now available. The map suggests that much more peat exists in the tropics than was previously reported.Unprecedented areas and volumes of peatlands, three times the size of previous estimates, are identified in the tropics, mainly outside Asia.Brazil emerges to be the main host of peat areas and volumes, closely followed by Indonesia.Tropical and sub-tropical peatland-hosting countries in all continents can use the map to direct, locate and prioritize conservation and management of wetlands and peatlands in the context of climate change mitigation and adaptation.Scientific engagement should be continued through intensive field campaigns to validate these new peat hotspots; the interactive map will facilitate this process.

Background Human-caused disturbance to tropical rainforests—such as logging and fire—causes substantial losses of carbon stocks. This is a critical issue to be addressed in the context of policy discussions to implement REDD+. This work reviews current scientific knowledge about the temporal dynamics of degradation-induced carbon emissions to describe common patterns of emissions from logging and fire across tropical forest regions. Using best available information, we: (i) develop short-term emissions factors (per area) for logging and fire degradation scenarios in tropical forests; and (ii) describe the temporal pattern of degradation emissions and recovery trajectory post logging and fire disturbance. Results Average emissions from aboveground biomass were 19.9 MgC/ha for logging and 46.0 MgC/ha for fire disturbance, with an average period of study of 3.22 and 2.15 years post-disturbance, respectively. Longer-term studies of post-logging forest recovery suggest that biomass accumulates to pre-disturbance levels within a few decades. Very few studies exist on longer-term (>10 years) effects of fire disturbance in tropical rainforests, and recovery patterns over time are unknown. Conclusions This review will aid in understanding whether degradation emissions are a substantial component of country-level emissions portfolios, or whether these emissions would be offset by forest recovery and regeneration.

Peat landscapes will be in focus at the upcoming ‘Global Landscapes Forum: Peatlands Matter’ event, taking place in Jakarta on 18 May 2017. Find out more here.Wetlands are important providers of ecosystem services and key regulators of climate change. They positively contribute to global warming through their greenhouse gas emissions, and negatively through the accumulation of organic material in histosols, particularly in peatlands. Our understanding of wetlands' services is currently constrained by limited knowledge on their distribution, extent, volume, inter-annual flood variability, and disturbance levels. We present an expert system approach to estimate wetland and peatland areas, depths and volumes, which relies on three biophysical indices related to wetland and peat formation: 1. Long-term water supply exceeding atmospheric water demand; 2. Annually or seasonally water-logged soils; 3. A geomorphological position where water is supplied and retained. Tropical and subtropical wetlands estimates reach 4.7 million km2. In line with current understanding, the American continent is the major contributor (45%) and Brazil, with its Amazonian inter-fluvial region, contains the largest tropical wetland area (800,720 km2). Our model suggests, however, unprecedented extents and volumes of peatland in the tropics (1.7 million km2 and 7,268 (6,076-7,368) km3), which more than three-fold current estimates. Unlike current understanding, our estimates suggest that South America and not Asia contributes the most to tropical peatland area and volume (ca. 44% for both) partly related to some yet unaccounted extended deep deposits but mainly to extended but shallow peat in the Amazon Basin. Brazil leads the peatland area and volume contribution. Asia hosts 38% of both tropical peat area and volume with Indonesia as the main regional contributor and still the holder of the deepest and most extended peat areas in the tropics. Africa hosts more peat than previously reported but climatic and topographic contexts leave it as the least peat forming continent. Our results suggest large biases in our current understanding of the distribution, area, and volumes of tropical peat and their continental contributions.

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 vertical oceanic, inland freshwaters and terrestrial carbon dioxide (CO2) exchange. Here we adopt a data-driven approach to synthesize a wide range of observation-based spatially explicit surface-atmosphere CO2 fluxes from 2001 and 2010, to identify the state of today’s observational opportunities and data limitation. The considered fluxes include vertical net exchange of open oceans, continental shelves, estuaries, rivers, and lakes, as well as CO2 fluxes related to gross primary productivity, terrestrial ecosystem respiration, 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; minimizing biophysical or biogeochemical assumptions encoded in process-based models. We estimate a global bottom-up net C exchange (NCE) between the surface (land, ocean, and coastal areas) and the atmosphere. Uncertainties for NCE and its components are derived using resampling. In most continental regions our NCE estimates agree well with independent estimates from other sources. This holds for Europe (mean ±1 SD: 0.80 ± 0.16 PgC/yr, positive numbers are sources to the atmosphere), Russia (−0.02 ± 0.49 PgC/yr), East Asia (1.76 ± 0.38 PgC/yr), South Asia (0.25 ± 0.16 PgC/yr), and Australia (0.22 ± 0.47 PgC/yr). Our NCE estimates also suggest large C sink in tropical areas. The global NCE estimate is −6.07 ± 3.38 PgC/yr. This global bottom-up value is the opposite direction of what is expected from the atmospheric growth rate of CO2, and would require an offsetting surface C source of 4.27±0.10 PgC/yr. This mismatch highlights large knowledge and observational gaps in tropical areas, particularly in South America, Africa, and Southeast Asia, but also in North America. Our uncertainty assessment provides the basis for designing new observation campaigns. In particular, we lack seasonal monitoring of shelf, estuary and inland water-atmosphere C exchange. Also, extensive pCO2 measurements are missing in the Southern Ocean. Most importantly, tropical land C fluxes suffer from a lack of in-situ observations. The consistent derivation of data uncertainties could serve as prior knowledge in multi-criteria optimization such as the Carbon Cycle Data Assimilation System (CCDAS) without overstating data credibility. Furthermore, the spatially explicit flux estimates may be used as a starting point to assess the validity of countries’ claims of reducing net C emissions in climate change negotiations.

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 remain, however, highly uncertain, jeopardizing the mitigation effectiveness of this sector. Global comparisons of AFOLU emissions have shown divergences of up to 25 %, urging for improved understanding on the reasons behind these differences. Here we compare a diversity of AFOLU emission datasets (e.g. FAOSTAT, EDGAR, the newly developed AFOLU "Hotspots", "Houghton", "Baccini", and EPA) 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 by gases (CO2, CH4, N2O). We also aim to iii) identify countries with low agreement among AFOLU datasets, to navigate research efforts. Aggregated gross emissions were similar for all databases for the AFOLU: 8.2 (5.5–12.2), 8.4 and 8.0 Pg CO2e. yr−1 (Hotspots, FAOSTAT and EDGAR respectively), Forests: 6.0 (3.8–10), 5.9, 5.9 and 5.4 Pg CO2e. yr−1 (Hotspots, FAOSTAT, EDGAR, and Houghton), and Agricultural sectors: 1.9 (1.5–2.5), 2.0, 2.1, and 2.0 Pg CO2e. yr−1 (Hotspots, FAOSTAT, EDGAR, and EPA). However, this agreement was lost when disaggregating by sources, continents, and gases, particularly for the forest sector (fire leading the differences). Agricultural emissions were more homogeneous, especially livestock, while croplands were the most diverse. CO2 showed the largest differences among datasets. Cropland soils and enteric fermentation led the smaller N2O and CH4 differences. Disagreements are explained by differences in conceptual frameworks (e.g. carbon-only vs multi-gas assessments, definitions, land use versus land cover, etc), in methods (Tiers, scales, compliance with Intergovernmental Panel on Climate Change (IPCC) guidelines, legacies, etc) and in assumptions (e.g. carbon neutrality of certain emissions, instantaneous emissions release, etc) that call for more complete and transparent documentation for all the available datasets. Enhanced dialogue between the carbon (CO2) and the AFOLU (multi-gas) communities is needed to reduce discrepancies of land use estimates.

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) roughly contributes with a quarter (~ 10–12 PgCO2e.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 are the regions in the planet with AFOLU emissions hotspots, 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: 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 (75 %) and to their uncertainties (98 %), iii) higher gross fluxes from forests coincide with higher uncertainties, making agricultural hotspots more appealing for effective mitigation action, and iv) a lower contribution of non-CO2 agricultural emissions to the total gross budget (ca. 25 %) with livestock (15.5 %) and rice (7 %) leading the emissions. Gross AFOLU tropical emissions 8.2 (5.5–12.2) were in the range of other databases 8.4 and 8.0 PgCO2e.yr−1 (FAOSTAT and EDGAR respectively), but we offer a spatially detailed benchmark for monitoring progress on 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 UNFCCC mechanism for Reducing Emissions from Deforestation and Degradation in developing countries (REDD+) represents an unprecedented opportunity for the conservation of forest biodiversity. Nevertheless, there are widespread concerns surrounding the possibility of negative environmental outcomes if biodiversity is not given adequate consideration throughout the REDD+ process. We propose a general framework for incorporating biodiversity concerns into national REDD+ programmes based on well-established ecological principles and experiences. First, we identify how biodiversity distribution and threat data, together with data on biodiversity responses to forest change and management, can be readily incorporated into the strategic planning process for REDD+ in order to identify priority areas and activities for investment that will deliver returns for both carbon and biodiversity. Second, we propose that assessments of changes in biodiversity following REDD+ implementation could be greatly facilitated by paralleling, where possible, the existing IPCC architecture for assessing carbon emissions. A three-tiered approach is proposed for biodiversity assessment, where lower tiers can provide a realistic starting point for countries with fewer data and lower technical capacities. Planning and assessment of biodiversity safeguards for REDD+ need not overburden an already encumbered UNFCCC process. Immediate progress is already possible for a large number of developing countries, and a gradual, phased approach to implementation would minimise risks and facilitate the protection of additional biodiversity benefits from REDD+ activities. Greater levels of coordination between the UNFCCC and CBD, as well as other agencies and stakeholder groups interested in forest conservation are needed if biodiversity safeguards are to be fully adopted and implemented.

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 th...

Burnt area maps based on satellite observations are frequently used in calculations related to fire regime, such as those of carbon dioxide emissions. Nevertheless, burnt area estimates between products vary widely, and validation against independent data is scarce, especially for Europe. Here we compare two active fire maps the ATSR World Fire Atlas and the Moderate Resolution Imaging Spectroradiometer MODIS Active Fire Product and two fire scars maps the L3JRC and the MODIS Burned Area Product to independent national statistics taken from 22 European countries between 1997 and 2008. We also tested the coincidence between satellite products derived by calculation of the fraction of active fires that were confirmed by a subsequent drop in reflectance. As a large proportion of fire pixels between 40% and 66%, depending on the product is located on urban land or crop fields, filtering out fires located on these land uses greatly improves the agreement between satellite-based burnt area estimates and national statistics and it also improves the coincidence between satellite products. The MODIS Active Fire Product appears to be most suitable for use as a proxy for burnt area patterns, showing a high correlation to national statistics R2 = 0.9, relatively low spatial and temporal heterogeneity and only a slight underestimation of the total burnt area 19 000 ha year–1. Unfiltered products show cases of substantial wildfire overestimation in all products, mainly attributable to anthropogenic activity, in the case of active fire products, and drought-induced vegetation dieback, in that of fire scar maps. Thus, filtering out fires on anthropogenic land uses seems to be essential when analysing patterns of forest fires from satellite observations. However, if agricultural fires are to be included, a combination of MODIS Active Fire and MODIS Burned Area products is recommended. We obtained that such combination shows low temporal and spatial heterogeneity and the highest coincidence between satellite products 25%, although the correlation to national statistics is not very high R2 = 0.67 and clearly underestimates the total burnt area 187 000 ha year–1.

Fire in tropical montane cloud forests (TMCFs) is not as rare as once believed. Andean TMCFs sit immediately below highly flammable, high-altitude grasslands (Puna/Paramo) that suffer from recurrent anthropogenic fire. This treeline is a zone of climatic tension where substantial future warming is likely to force upward tree migrations, while increased fire presence and fire impacts are likely to force it downwards. TMCFs contain large carbon stocks in their peat soils and their loss through fire is a currently unaccounted for regional source of CO2. This study, conducted in the southern Peruvian Andes (>2800 m), documents differences in live tree biomass, fine root biomass, fallen and standing dead wood, and soil organic carbon in 4 paired-sample plots (burned versus control) following the severe ground fires that occurred during the 2005 Andean drought. Peat soils contributed the most to biomass burning emissions, with lower values corresponding to an 89% mean stock difference compared to the controls (mean ± SE) (54.1 ± 22.3 vs. 5.8 ± 5.3 MgC ha−1). Contrastingly, carbon stocks from live standing trees differed by a non-significant 37% lower value in the burned plots compared to the controls, largely compensated by vigorous resprouting (45.5 ± 17.4 vs. 69.2 ± 13.4 MgC ha−1). Both standing dead trees and fallen dead wood were significantly higher in the burned plots with a three-fold difference from the controls: dead Trees 45.2 ± 9.4 vs. 16.4 ± 4.4 MgC ha−1, and ca. a 2 fold difference for the fallen dead wood: 11.2 ± 5 vs. 6.7 ± 3.2 MgC ha−1 for the burned plots versus their controls. A preliminary estimate of the regional contribution of biomass burning emissions from Andean TMCFs for the period 2000–2008, resulted in mean carbon emission rates of 1.3 TgC yr−1 (max-min: 1.8–0.8 TgC yr−1). This value is in the same order of magnitude than South American annual fire emissions (300 TgC yr−1) suggesting the need for further research on Andean forest fires. On-going projects on the region are working on the promotion of landowner participation in TMCFs conservation through REDD+ mechanism. The heart of the proposed initiative is reforestation of degraded lands with green fire breaks enriched with economically valuable Andean plant species. The cultivation of these species may contribute to reduce deforestation pressure on the Amazonian cloud forest by providing an alternative income to local communities, at the same time that they prevent the spread of fire into Manu National Park and adjacent community-held forests, protecting forest and reducing CO2 emissions.

Analyses were carried out on financial compensation to avoid loss of tropical forests and related carbon (C) emissions when marginal financial yield declined for land-use options with extended areas, and when a risk-averting perspective (modeled according to financial theory around the capital asset pricing model) is assumed. The approach in this study was to consider natural forest, forest plantation, pasture, and cropland simultaneously to investigate how an optimized land-use distribution may reduce the amount of compensation necessary to avoid C emissions from forest loss. The financial compensations derived were as high as US$ 176 per hectare per year when comparing natural forests only with the most profitable alternative (croplands). However, compensation decreased to US$ 124 for risk-neutral decision-makers, who would strive for optimized land-use allocation, and to only US$ 47 per hectare per year for risk-avoiders, who would look to maximize the reward-to-variability ratio. Sensitivity analyses indicated that the compensation under risk-aversion increased much less than under risk-ignoring when increased productivity of agricultural land-use or growing demand for agricultural products was simulated. It was concluded that considering appropriate diversification strategies and the well documented human behavior to avoid risks is an important step in developing cost-effective compensation policies.

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 experi...

Large forest fires have recently increased in frequency and severity in many ecosystems. Due to the heterogeneity in fuels, weather and topography, these large fires tend to form unburned islands of vegetation. This study focuses on a large forest fire that occurred in north-eastern Spain in 1998, which left large areas of unburned vegetation within its perimeter. Based on a satellite post-fire severity map we searched for the relative influence of biotic and abiotic factors leading to unburned island formation. We divided the area of the fire into individual units we called “slopes” which were meant to separate the differential microclimatic effects of contrasted aspects. The number of unburned islands and their areas were related to 12 variables that influence their formation (i.e. land cover composition, aspect, steepness, forest structure, two landscape indices and weather variables). We hypothesized that unburned vegetation islands would concentrate on northern aspects, in less flammable forests (i.e. broadleaf species) and higher fragmentation to interrupt the advance of fire. While north and western aspects did have a higher presence of unburned vegetation islands, our study suggests greater presence of islands in slopes that are larger (i.e. more continuous areas with relatively homogeneous aspect), with greater proportions of forest cover, with higher wood volumes and with lower proportions of broadleaf species. Climate also played a role, with relative humidity and wind speed positively and negatively correlated to island formation, respectively. Unburned vegetation was more frequent on slopes with lower diversity of land covers and higher dominance of one land cover in the slope. Since slopes with only one land cover (i.e. forests) had more islands than slopes with multiple cover types, we infer that under severe meteorological conditions, fragmented forests can be more affected by wind and by water stress, thus burning more readily than forests that are protected from this edge phenomenon. These results would reinforce forest management strategies that avoid linear features (fire-lines and fire-breaks), to enhance fuel treatments that focus on areas and minimize fragmentation.

The human use of the land is one of the critical links between people and the Earth system, with changes in land use contributing to the significant modification of hydrology, ecology, geomorphology, climate and biogeochemical cycles. Over the past decade there have been several major research efforts (e.g. IGBP-IHDP LUCC, ESSP) to link the social and natural sciences through the study of land-use and land-cover change, with particular attention being paid to the potential of linking remote sensing with socioeconomic data, local case studies with larger scale modelling efforts, and scientific research with the needs of stakeholders. This paper evaluates the extent to which such land-use-change studies can provide reliable data, explanation and projections of future land use. It assesses how such studies might address major theoretical questions in social and natural science such as those concerning the role of population or of institutions in land-use dynamics, or the detailed attribution of hazards to physical or social processes. In general, and using examples of research conducted in Mexico, the paper concludes that progress has been limited, because of factors that include the difficulties in gathering socio-economic information at global and regional scales, linking social data to satellite imagery, and forecasting human activities and policies. For interactions between the social and earth sciences to succeed, a certain level of tolerance and mutual understanding will be needed so that social scientists understand the earth science aspiration for quantitative socio-economic scenarios and predictions, and earth scientists understand the variations in how social scientists explain human behaviour and institutions and accept the clear limits to predicting human activities and decisions. Copyright © 2008 John Wiley & Sons, Ltd.

Extensive plot studies across Amazonia have demonstrated that there are large regional gradients in forest productivity and that the dynamics of the forests seem to have accelerated substantially in recent decades, with ensuing impacts on forest structure. Most of these sites are, however, one hectare plots nested within a heterogeneous landscape, and a clear need exists to understand the landscape and regional context of these studies. Remote sensing offers the potential to scale up from plot to higher landscape levels but it has proven complex to evaluate forest structure, and therefore biomass patterns in tropical areas, due to saturation, signal noises, and unclear relationships between reflectance values and structural properties, both for optical and radar systems. In this study, we explore the potential of a textural approach to detect landscape and regional variations in the structure of tropical forest canopies, as viewed from high resolution IKONOS satellite imagery. We used lacunarity analysis and a derived variable, the index of translational homogeneity (ITH), as a tool to search for structural and dynamic forest properties within and among different Amazonian landscapes. The main goals of this research were: (1) to examine the sensitivity and robustness of ITH analysis to details of the analysis procedure; (2) to explore the intra- and inter-regional textural properties of a variety of tropical forest canopies [Caxiuana, Manaus, Sinop, Santarem (Brazil), and Tambopata (Peru)], and (3) to relate textural properties derived from lacunarity to structural properties of the forest canopy, mainly crown size. Our results show how ITH and lacunarity analyses offer insights into the spatial distribution of structural properties of forest canopies, easily differentiating between terra firme forests and swamp forests. The studied forest canopies are self-similar on length-scales of 5–11 m, and show translational invariance on scales above 20 m (central and western Amazonia) and 30 m (eastern Amazonia) For a restricted range of solar elevation angles, the ITH appears to be determined mainly by the mean size of tree crowns, and by the fraction of large (shadowgenerating) trees.

More than 100 countries pledged to reduce agricultural greenhouse gas (GHG) emissions in the 2015 Paris Agreement of the United Nations Framework Convention on Climate Change. Yet technical information about how much mitigation is needed in the sector vs. how much is feasible remains poor. We identify a preliminary global target for reducing emissions from agriculture of ~1 GtCO2e yr−1 by 2030 to limit warming in 2100 to 2 °C above pre-industrial levels. Yet plausible agricultural development pathways with mitigation cobenefits deliver only 21–40% of needed mitigation. The target indicates that more transformative technical and policy options will be needed, such as methane inhibitors and finance for new practices. A more comprehensive target for the 2 °C limit should be developed to include soil carbon and agriculture-related mitigation options. Excluding agricultural emissions from mitigation targets and plans will increase the cost of mitigation in other sectors or reduce the feasibility of meeting the 2 °C limit.

Since the severe 1982-1983 El Nino drought, recurrent burning has been reported inside tropical protected areas (TPAs). Despite the key role of fire in habitat degradation, little is known about the effectiveness of TPAs in mitigating fire incidence and burned areas. We used a GPS fire database (1995-2005) (n=3590 forest fires) obtained from the National Forest Commission to compare fire incidence (number of fires) and burned areas inside TPAs and their surrounding adjacent buffer areas in Southern Mexico (Chiapas). Burned areas inside parks ranged from 2% (Palenque) to 45% (Lagunas de Montebello) of a park's area, and the amount burned was influenced by two severe El Nino events (1998 and 2003). These two years together resulted in 67% and 46% of the total area burned in TPAs and buffers, respectively during the period under analysis. Larger burned areas in TPAs than in their buffers were exclusively related to the extent of natural habitats (flammable area excluding agrarian and pasture lands). Higher fuel loads together with access and extinction difficulties were likely behind this trend. A higher incidence of fire in TPAs than in their buffers was exclusively related to anthropogenic factors such as higher road densities and agrarian extensions. Our results suggest that TPAs are failing to mitigate fire impacts, with both fire incidence and total burned areas being significantly higher in the reserves than in adjacent buffer areas. Management plans should consider those factors that facilitate fires in TPAs: anthropogenic origin of fires, sensitivity of TPAs to El Ninio-droughts, large fuel loads and fuel continuity inside parks, and limited financial resources. Consideration of these factors favors lines of action such as alternatives to the use of fire (e.g., mucuna-maize system), climatic prediction to follow the evolution of El Nino, fuel management strategies that favor extinction practices, and the strengthening of local communities and ecotourism. Language: en

Environmental agencies frequently require tools for quick assessments of areas affected by large fires. Remote sensing techniques have been reported as efficient tools to evaluate the effects of fire. However, there exist few quantitative comparisons about the performance of the diverse methods. This study quantitatively evaluated the accuracy of five different techniques, a field survey and four satellite‐based techniques, in order to quickly classify a large forest fire that occurred in 1998 in Solsones (north‐east Spain) by means of an IRS LISS‐III image. Three pure classes were determined: burned area, unburned vegetation, and bare soil; along with a non‐pure class that we called mixed area. These selected techniques were included into a tree classifier to investigate their partial contribution to the final classification. The most accurate methods when focusing on pure classes were those directly related to the spectral characteristics of the pixel: Reflectance Data and Spectral Unmixing (82% of over...

Measuring forest degradation and related forest carbon stock changes is more challenging than measuring deforestation since degradation implies changes in the structure of the forest and does not entail a change in land use, making it less easily detectable through remote sensing. Although we anticipate the use of the IPCC guidance under the United Framework Convention on Climate Change (UNFCCC), there is no one single method for monitoring forest degradation for the case of REDD+ policy. In this review paper we highlight that the choice depends upon a number of factors including the type of degradation, available historical data, capacities and resources, and the potentials and limitations of various measurement and monitoring approaches. Current degradation rates can be measured through field data (i.e. multi-date national forest inventories and permanent sample plot data, commercial forestry data sets, proxy data from domestic markets) and/or remote sensing data (i.e. direct mapping of canopy and forest structural changes or indirect mapping through modelling approaches), with the combination of techniques providing the best options. Developing countries frequently lack consistent historical field data for assessing past forest degradation, and so must rely more on remote sensing approaches mixed with current field assessments of carbon stock changes. Historical degradation estimates will have larger uncertainties as it will be difficult to determine their accuracy. However improving monitoring capacities for systematic forest degradation estimates today will help reduce uncertainties even for historical estimates.

Vegetation burning in tropical countries is a threat to the environment, causing not only local ecological, economic and social impacts, but also large-scale implications for global change. The burning is usually a result of interacting factors, such as climate, land-use and vegetation type. Satellite-derived monthly time series datasets of rainfall, burned area and active fire detections between December 2000 and 2009 were used in this study. A map of vegetation types was also used to determine these factors' spatial and temporal variability and interactions with the total amount of burned area and active fires detected in Colombia. Grasslands represented the vegetation most affected by fires every year in terms of burned area (standardised by their total area), followed by secondary vegetation, pasture and forests. Grasslands were also most affected by active fires, but followed closely by pasture, agricultural areas, secondary vegetation and forests. The results indicated strong climate and fire seasonality and marked regional difference, partly explained by climatic differences amongst regions and vegetation types, especially in the Orinoco and Caribbean regions. The incidence of fire in the Amazon and Andes was less influenced by climate in terms of burned area impacted, but the strength of the ENSO phenomenon affected the Orinoco and the Andes more in terms of burned area. Many of the active fires detected occurred in areas of transition between the submontane and lowland Andes and the Amazon, where extensive conversion to pasture is occurring. The possible high impact of small fires on the tropical rainforest present in this transition area and the Amazonian rainforest deserves more attention in Colombia due to its previous lack of attention to its contribution to global change. © 2010 Elsevier B.V.