ALBERT

Description: Climate change and land-use change are two major drivers of vegetation change causing habitat and biodiversity loss and posing a threat to the sustained provisioning of ecosystem goods and services. Following-up on the Millennium Ecosystem Assessment, the Sustainable Development Goals have been a fresh stimulus to the current interest in ecosystem services. Dynamic Global Vegetation Models (DGVMs) offer the possibility of integrating large amounts of geospatial data to quantify and project a large range of ecological variables important for ecosystem service provisioning under future scenarios. We outline how such model output could be used for projecting ecosystem service provisioning.

Description: Climate change and land‐use change are two major drivers of biome shifts causing habitat and biodiversity loss. What is missing is a continental‐scale future projection of the estimated relative impacts of both drivers on biome shifts over the course of this century. Here, we provide such a projection for the biodiverse region of Latin America under four socio‐economic development scenarios. We find that across all scenarios 5–6% of the total area will undergo biome shifts that can be attributed to climate change until 2099. The relative impact of climate change on biome shifts may overtake land‐use change even under an optimistic climate scenario, if land‐use expansion is halted by the mid‐century. We suggest that constraining land‐use change and preserving the remaining natural vegetation early during this century creates opportunities to mitigate climate‐change impacts during the second half of this century. Our results may guide the evaluation of socio‐economic scenarios in terms of their potential for biome conservation under global change.

Description: While deforestation represents an obvious ecosystem change, forest degradation is often more difficult to discern or quantify, but it impacts anumber of ecosystem functions which are vital for biodiversity and climate feedbacks. In the Brazilian Amazon, land-use changes increasefire occurrence, especially in fragmented forests close to managed land. We used remote sensing imagery to estimate the extent and impact of forest fires in degraded tropical rain-forest in the Brazilian Legal Amazon between 2007 and 2010and examinedland-use establishing in degraded areas. The trends in degraded area vs. burned area were different. Even though degradation increased one year after a high fire year, there wasnospatialoverlap, which pointsto other causes for degradation. Up to 11% of the degraded area was burned in the same year, playing escaping fires from managed and deforested lands a significant role in degradation by fire. Eighty-fourpercent of 2007s degraded area remained forest one year later, whereas the rest was identified as deforestation, secondary vegetation or pasture.Three years after degradation, 80% remained forest, the proportion of deforested area decreased and areas in regeneration after being deforested increased. Monitoring of forest degradation across tropical forests is critical for developing land management policies and for carbon stocks/emissions estimation.

Description: Fires are a fundamental part of the Earth System. In the last decades, they have been altering ecosystem structure, biogeochemical cycles and atmospheric composition with unprecedented rapidity. In this study, we implement a complex networks-based methodology to track individual fires over space and time. We focus on extreme fires—the 5% most intense fires—in the tropical forests of the Brazilian Legal Amazon over the period 2002–2019. We analyse the interannual variability in the number and spatial patterns of extreme forest fires in years with diverse climatic conditions and anthropogenic pressure to examine potential synergies between climate and anthropogenic drivers. We observe that major droughts, that increase forest flammability, co-occur with high extreme fire years but also that it is fundamental to consider anthropogenic activities to understand the distribution of extreme fires. Deforestation fires, fires escaping from managed lands, and other types of forest degradation and fragmentation provide the ignition sources for fires to ignite in the forests. We find that all extreme forest fires identified are located within a 0.5-km distance from forest edges, and up to 56% of them are within a 1-km distance from roads (which increases to 73% within 5 km), showing a strong correlation that defines spatial patterns of extreme fires.

Description: Humans profoundly alter fire regimes both directly, by introducing changes in fuel dynamics and ignitions, and indirectly by increasing the release of greenhouse gases and aerosols from fires, which can alter regional climate and, as a consequence, modify fuel moisture and availability. Interactions between vegetation dynamics, regional climate change, and anthropogenic pressure lead to high heterogeneity in the spatio-temporal fire distribution. We use the new FireTracks Scientific Dataset that tracks the spatio-temporal development of individual fires to analyse fire regimes in the Brazilian Legal Amazon over the period 2002-2020. We analyse fire size, duration, intensity, and rate of spread in six different land-cover classes. Particular combinations of fire features determine the dominant and characteristic fire regime in each of them. We find that fires in savannas and evergreen forests burn the largest areas and are the most long-lasting. Forest fires have the potential for burning at the highest intensities, whereas higher rates of spread are found in savannas. Woody savanna and grassland fires are usually affected by smaller, shorter, less-intense fires compared with fires in evergreen forest and savanna. However, fires in grasslands can burn at rates of spread as high as savanna fires as a result of the easily flammable fuel. We observe that fires in deciduous forests and croplands are generally small, short, and low-intense, although the latter can sustain high rates of spread due to the dry post-harvest residuals. The reconstructed fire regimes for each land cover can be used to improve the simulated fire characteristics by models, and thus, future projections.