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Climate change increases fire-favorable weather in forests, but fire trends are also affected by multiple other controlling factors that are difficult to untangle. We use machine learning to systematically group forest ecoregions into 12 global forest pyromes, with each showing distinct sensitivities to climatic, human, and vegetation controls. This delineation revealed that rapidly increasing forest fire emissions in extratropical pyromes, linked to climate change, offset declining emissions in tropical pyromes during 2001 to 2023. Annual emissions tripled in one extratropical pyrome due to increases in fire-favorable weather, compounded by increased forest cover and productivity. This contributed to a 60% increase in forest fire carbon emissions from forest ecoregions globally. Our results highlight the increasing vulnerability of forests and their carbon stocks to fire disturbance under climate change. 

Abstract Changing wildfire regimes in the western US and other fire-prone regions pose considerable risks to human health and ecosystem function. However, our understanding of wildfire behavior is still limited by a lack of data products that systematically quantify fire spread, behavior and impacts. Here we develop a novel object-based system for tracking the progression of individual fires using 375 m Visible Infrared Imaging Radiometer Suite active fire detections. At each half-daily time step, fire pixels are clustered according to their spatial proximity, and are either appended to an existing active fire object or are assigned to a new object. This automatic system allows us to update the attributes of each fire event, delineate the fire perimeter, and identify the active fire front shortly after satellite data acquisition. Using this system, we mapped the history of California fires during 2012–2020. Our approach and data stream may be useful for calibration and evaluation of fire spread models, estimation of near-real-time wildfire emissions, and as means for prescribing initial conditions in fire forecast models. 

BACKGROUND Madagascar is one of the world’s foremost biodiversity hotspots. Its unique assemblage of plants, animals, and fungi—the majority of which evolved on the island and occur nowhere else—is both diverse and threatened. After human arrival, the island’s entire megafauna became extinct, and large portions of the current flora and fauna may be on track for a similar fate. Conditions for the long-term survival of many Malagasy species are not currently met because of multiple anthropogenic threats. ADVANCES We review the extinction risk and threats to biodiversity in Madagascar, using available international assessment data as well as a machine learning analysis to predict the extinction risks and threats to plant species lacking assessments. Our compilation of global International Union for Conservation of Nature (IUCN) Red List assessments shows that overexploitation alongside unsustainable agricultural practices affect 62.1 and 56.8% of vertebrate species, respectively, and each affects nearly 90% of all plant species. Other threats have a relatively minor effect today but are expected to increase in coming decades. Because only one-third (4652) of all Malagasy plant species have been formally assessed, we carried out a neural network analysis to predict the putative status and threats for 5887 unassessed species and to evaluate biases in current assessments. The percentage of plant species currently assessed as under threat is probably representative of actual numbers, except in the case of the ferns and lycophytes, where significantly more species are estimated to be threatened. We find that Madagascar is home to a disproportionately high number of Evolutionarily Distinct and Globally Endangered (EDGE) species. This further highlights the urgency for evidence-based and effective in situ and ex situ conservation. Despite these alarming statistics and trends, we find that 10.4% of Madagascar’s land area is protected and that the network of protected areas (PAs) covers at least part of the range of 97.1% of terrestrial and freshwater vertebrates with known distributions (amphibians, freshwater fishes, reptiles, birds, and mammal species combined) and 67.7% of plant species (for threatened species, the percentages are 97.7% for vertebrates and 79.6% for plants). Complementary to this, ex situ collections hold 18% of vertebrate species and 23% of plant species. Nonetheless, there are still many threatened species that do not occur within PAs and are absent from ex situ collections, including one amphibian, three mammals, and seven reptiles, as well as 559 plants and more yet to be assessed. Based on our updated vegetation map, we find that the current PA network provides good coverage of the major habitats, particularly mangroves, spiny forest, humid forest, and tapia, but subhumid forest and grassland-woodland mosaic have very low areas under protection (5.7 and 1.8% respectively). OUTLOOK Madagascar is among the world’s poorest countries, and its biodiversity is a key resource for the sustainable future and well-being of its citizens. Current threats to Madagascar’s biodiversity are deeply rooted in historical and present social contexts, including widespread inequalities. We therefore propose five opportunities for action to further conservation in a just and equitable way. First, investment in conservation and restoration must be based on evidence and effectiveness and be tailored to meet future challenges through inclusive solutions. Second, expanded biodiversity monitoring, including increased dataset production and availability, is key. Third, improving the effectiveness of existing PAs—for example through community engagement, training, and income opportunities—is more important than creating new ones. Fourth, conservation and restoration should not focus solely on the PA network but should also include the surrounding landscapes and communities. And finally, conservation actions must address the root causes of biodiversity loss, including poverty and food insecurity. In the eyes of much of the world, Madagascar’s biodiversity is a unique global asset that needs saving; in the daily lives of many of the Malagasy people, it is a rapidly diminishing source of the most basic needs for subsistence. Protecting Madagascar’s biodiversity while promoting social development for its people is a matter of the utmost urgency Visual representation of five key opportunities for conserving and restoring Madagascar’s rapidly declining biodiversity identified in this Review. The dashed lines point to representative vegetation types where these recommendations could have tangible effects, but the opportunities are applicable across Madagascar. ILLUSTRATION: INESSA VOET 

BACKGROUND The Republic of Madagascar is home to a unique assemblage of taxa and a diverse set of ecosystems. These high levels of diversity have arisen over millions of years through complex processes of speciation and extinction. Understanding this extraordinary diversity is crucial for highlighting its global importance and guiding urgent conservation efforts. However, despite the detailed knowledge that exists on some taxonomic groups, there are large knowledge gaps that remain to be filled. ADVANCES Our comprehensive analysis of major taxonomic groups in Madagascar summarizes information on the origin and evolution of terrestrial and freshwater biota, current species richness and endemism, and the utilization of this biodiversity by humans. The depth and breadth of Madagascar’s biodiversity—the product of millions of years of evolution in relative isolation —is still being uncovered. We report a recent acceleration in the scientific description of species but many remain relatively unknown, particularly fungi and most invertebrates. DIGITIZATION Digitization efforts are already increasing the resolution of species richness patterns and we highlight the crucial role of field- and collections-based research for advancing biodiversity knowledge in Madagascar. Phylogenetic diversity patterns mirror that of species richness and endemism in most of the analyzed groups. Among the new data presented, our update on plant numbers estimates 11,516 described vascular plant species native to Madagascar, of which 82% are endemic, in addition to 1215 bryophyte species, of which 28% are endemic. Humid forests are highlighted as centers of diversity because of their role as refugia and centers of recent and rapid radiations, but the distinct endemism of other areas such as the grassland-woodland mosaic of the Central Highlands and the spiny forest of the southwest is also important despite lower species richness. Endemism in Malagasy fungi remains poorly known given the lack of data on the total diversity and global distribution of species. However, our analysis has shown that ~75% of the fungal species detected by environmental sequencing have not been reported as occurring outside of Madagascar. Among the 1314 species of native terrestrial and freshwater vertebrates, levels of endemism are extremely high (90% overall)—all native nonflying terrestrial mammals and native amphibians are found nowhere else on Earth; further, 56% of the island’s birds, 81% of freshwater fishes, 95% of mammals, and 98% of reptile species are endemic. Little is known about endemism in insects, but data from the few well-studied groups on the island suggest that it is similarly high. The uses of Malagasy species are many, with much potential for the uncovering of useful traits for food, medicine, and climate mitigation. OUTLOOK Considerable work remains to be done to fully characterize Madagascar’s biodiversity and evolutionary history. The multitudes of known and potential uses of Malagasy species reported here, in conjunction with the inherent value of this unique and biodiverse region, reinforce the importance of conserving this unique biota in the face of major threats such as habitat loss and overexploitation. The gathering and analysis of data on Madagascar’s remarkable biota must continue and accelerate if we are to safeguard this unique and highly threatened subset of Earth’s biodiversity. Emergence and composition of Madagascar’s extraordinary biodiversity. Madagascar’s biota is the result of over 160 million years of evolution, mostly in geographic isolation, combined with sporadic long distance immigration events and local extinctions. (Left) We show the age of the oldest endemic Malagasy clade for major groups (from bottom to top): arthropods, bony fishes, reptiles, flatworms, birds, amphibians, flowering plants, mammals, non-flowering vascular plants, and mollusks). Humans arrived recently, some 10,000 to 2000 years (top right) and have directly or indirectly caused multiple extinctions (including hippopotamus, elephant birds, giant tortoises, and giant lemurs) and introduced many new species (such as dogs, zebu, rats, African bushpigs, goats, sheep, rice). Endemism is extremely high and unevenly distributed across the island (the heat map depicts Malagasy palm diversity, a group characteristic of the diverse humid forest). Human use of biodiversity is widespread, including 1916 plant species with reported uses. The scientific description of Malagasy biodiversity has accelerated greatly in recent years (bottom right), yet the diversity and evolution of many groups remain practically unknown, and many discoveries await. 

Abstract Fire emissions of gases and aerosols alter atmospheric composition and have substantial impacts on climate, ecosystem function, and human health. Warming climate and human expansion in fire‐prone landscapes exacerbate fire impacts and call for more effective management tools. Here we developed a global fire forecasting system that predicts monthly emissions using past fire data and climate variables for lead times of 1 to 6 months. Using monthly fire emissions from the Global Fire Emissions Database (GFED) as the prediction target, we fit a statistical time series model, the Autoregressive Integrated Moving Average model with eXogenous variables (ARIMAX), in over 1,300 different fire regions. Optimized parameters were then used to forecast future emissions. The forecast system took into account information about region‐specific seasonality, long‐term trends, recent fire observations, and climate drivers representing both large‐scale climate variability and local fire weather. We cross‐validated the forecast skill of the system with different combinations of predictors and forecast lead times. The reference model, which combined endogenous and exogenous predictors with a 1 month forecast lead time, explained 52% of the variability in the global fire emissions anomaly, considerably exceeding the performance of a reference model that assumed persistent emissions during the forecast period. The system also successfully resolved detailed spatial patterns of fire emissions anomalies in regions with significant fire activity. This study bridges the gap between the efforts of near‐real‐time fire forecasts and seasonal fire outlooks and represents a step toward establishing an operational global fire, smoke, and carbon cycle forecasting system.