ALBERT

Description: Tropical rainforests are recognized as one of the terrestrialtipping elements which could have profound impacts on the global cli-mate, once their vegetation has transitioned into savanna or grasslandstates. While several studies investigated the savannization of, e.g., theAmazon rainforest, few studies considered the influence of fire. Fire isexpected to potentially shift the savanna-forest boundary and henceimpact the dynamical equilibrium between these two possible vegeta-tion states under changing climate. To investigate the climate-inducedhysteresis in pan-tropical forests and the impact of fire under future cli-mate conditions, we employed the Earth system model CM2Mc, whichis biophysically coupled to the fire-enabled state-of-the-art dynamicglobal vegetation model LPJmL. We conducted several simulation ex-periments where atmospheric CO2concentrations increased (impactphase) and decreased from the new state (recovery phase), each withand without enabling wildfires. We find a hysteresis of the biomassand vegetation cover in tropical forest systems, with a strong regionalheterogeneity. After biomass loss along increasing atmospheric CO2concentrations and accompanied mean surface temperature increase ofabout 4°C (impact phase), the system does not recover completely intoits original state on its return path, even though atmospheric CO2concentrations return to their original state. While not detecting large-scale tipping points, our results show a climate-induced hysteresis intropical forest and lagged responses in forest recovery after the climatehas returned to its original state. Wildfires slightly widen the climate-induced hysteresis in tropical forests and lead to a lagged response inforest recovery by ca. 30 years.

Description: Global Water Models (GWMs), which include Global Hydrological, Land Surface, and Dynamic Global Vegetation Models, present valuable tools for quantifying climate change impacts on hydrological processes in the data scarce high latitudes. Here we performed a systematic model performance evaluation in six major Pan-Arctic watersheds for different hydrological indicators (monthly and seasonal discharge, extremes, trends (or lack of), and snow water equivalent (SWE)) via a novel Aggregated Performance Index (API) that is based on commonly used statistical evaluation metrics. The machine learning Boruta feature selection algorithm was used to evaluate the explanatory power of the API attributes. Our results show that the majority of the nine GWMs included in the study exhibit considerable difficulties in realistically representing Pan-Arctic hydrological processes. Average APIdischarge (monthly and seasonal discharge) over nine GWMs is 〉 50% only in the Kolyma basin (55%), as low as 30% in the Yukon basin and averaged over all watersheds APIdischarge is 43%. WATERGAP2 and MATSIRO present the highest (APIdischarge 〉 55%) while ORCHIDEE and JULES-W1 the lowest (APIdischarge ≤ 25%) performing GWMs over all watersheds. For the high and low flows, average APIextreme is 35% and 26%, respectively, and over six GWMs APISWE is 57%. The Boruta algorithm suggests that using different observation-based climate data sets does not influence the total score of the APIs in all watersheds. Ultimately, only satisfactory to good performing GWMs that effectively represent cold-region hydrological processes (including snow-related processes, permafrost) should be included in multi-model climate change impact assessments in Pan-Arctic watersheds.

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: The terrestrial biosphere is exposed to land-use and climate change, which not only affects vegetation dynamics, but also changes land-atmosphere feedbacks. Specifically, changes in land-cover affect biophysical feedbacks of water and energy, therefore contributing to climate change. In this study, we couple the well established and comprehensively validated Dynamic Global Vegetation Model LPJmL5 to the coupled climate model CM2Mc, which is based on the atmosphere model AM2 and the ocean model MOM5 (CM2Mc-LPJmL). In CM2Mc, we replace the simple land surface model LaD (where vegetation is static and prescribed) with LPJmL5 and fully couple the water and energy cycles using the Geophysical Fluid Dynamics Laboratory (GFDL) Flexible Modeling System (FMS). Several improvements to LPJmL5 were implemented to allow a fully functional biophysical coupling. These include a sub-daily cycle for calculating energy and water fluxes, a conductance of the soil evaporation and plant interception, a canopy-layer humidity, and the surface energy balance in order to calculate the surface and canopy layer temperature within LPJmL5. Exchanging LaD by LPJmL5, and therefore switching from a static and prescribed vegetation to a dynamic vegetation, allows us to model important biosphere processes, including fire, mortality, permafrost, hydrological cycling, and the impacts of managed land (crop growth and irrigation). Our results show that CM2Mc-LPJmL has similar temperature and precipitation biases as the original CM2Mc model with LaD. Performance of LPJmL5 in the coupled system compared to Earth observation data and to LPJmL offline simulation results is within acceptable error margins. The historic global mean temperature evolution of our model setup is within the range of CMIP5 models. The comparison of model runs with and without land-use change shows a partially warmer and drier climate state across the global land surface. CM2Mc-LPJmL opens new opportunities to investigate important biophysical vegetation-climate feedbacks with a state-of-the-art and process-based dynamic vegetation model.

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: In the 10 Must Knows from Biodiversity Science 45 scientists present facts about biodiversity in a well-founded and generally intelligible way. They analyse the complex systems of the earth by highlighting ten key areas, each of which, in turn, is inextricably linked to all the others. And they show ways to stop the continued loss of species diversity and ecosystems, and to promote biodiversity. The underlying aim is to provide policy-makers and society with scientifically validated assessments of the latest knowledge to facilitate improved policy decisions and action at local, regional, national and global levels, in order to conserve the diversity of life – biodiversity. These are the 10MustKnows 2022: 1. Achieving climate and biodiversity protection together 2. Strengthening planetary health 3. Considering hidden biodiversity 4. Promoting biocultural habitats 5. Using forests sustainably 6. Transforming agriculture 7. Protecting land and resources 8. Expanding transnational infrastructure and education for sustainability 9. Ensuring access and open use of research data 10. Setting biodiversity-friendly incentives

Description: Southeastern South America is subject to considerable precipitation variability on seasonal to decadal timescales and has undergone very heavy land-cover changes since the middle of the past century. The influence of local land-cover change and precipitation as drivers of regional evapotranspiration long-term trends and variability remains largely unknown in the region. Here, ensembles of stand-alone Dynamic Global Vegetation Models with different atmospheric forcings are used to disentangle the influence of those two drivers on austral summer evapotranspiration from 1950 to 2010. This paper examines the influence of both the ENSO and the dipole-like first-mode of southeastern South American precipitation variability (EOF1) on regional evapotranspiration. We found that in the lower La Plata Basin, evapotranspiration was driven by precipitation variability and showed a positive summer trend. Moreover, the region showed marked seasonal anomalies during El Niño and La Niña summers but mainly during EOF1 phases. On the contrary, in the upper La Plata Basin, land-cover changes forced the negative summer evapotranspiration trend and particularly reduced the summer anomalies of the late 1990s, a period of ENSO and EOF1-positive phases. In the South Atlantic Convergence Zone region, the high evapotranspiration uncertainty across ensemble members impeded finding robust results, which highlights the importance of using multiple DGVMs and atmospheric forcings instead of relying on single model/forcing results.

Description: Recent publications indicate that the Amazon may be acting more as a carbon source than a sink in some regions. Moreover, the Amazon is a source of moisture for other regions in the continent, and deforestation over the years may be reducing this function. In this work, we analyze the impacts of elevated CO2 (eCO2) and Land Use Change (LUC) on Gross Primary Productivity (GPP) and evaporation in the Southern Amazon (70S 140S, 660W 510W), which suffered strong anthropogenic influence in the period of 1981‒2010. We ran four Dynamic Global Vegetation Models (DGVMs), isolating historical CO2, constant CO2, LUC, and Potential Natural Vegetation (PNV) scenarios with three climate variable datasets: precipitation, temperature and shortwave radiation. We compared the outputs to five “observational” datasets obtained through eddy covariance, remote sensing, meteorological measurements, and machine learning. The results indicate that eCO2 may have offset deforestation, with GPP increasing by ∼13.5% and 9.3% (dry and rainy seasons, respectively). After isolating the LUC effect, a reduction in evaporation of ∼4% and ∼1.2% (dry and rainy seasons, respectively) was observed. The analysis of forcings in subregions under strong anthropogenic impact revealed a reduction in precipitation of ∼15 and 30 mm, and a temperature rise of 10 and 0.60 C (dry and rainy seasons, respectively). Differences in the implementation of plant physiology and Leaf area Index (LAI) in the DGVMs introduced some uncertainties in the interpretation of the results. Nevertheless, we consider that it was an important exercise given the relevance.

Description: This paper presents a review of concepts related to wildfire risk assessment, including the determination of fire ignition and propagation (fire danger), the extent to which fire may spatially overlap with valued assets (exposure), and the potential losses and resilience to those losses (vulnerability). This is followed by a brief discussion of how these concepts can be integrated and connected to mitigation and adaptation efforts. We then review operational fire risk systems in place in various parts of the world. Finally, we propose an integrated fire risk system being developed under the FirEUrisk European project, as an example of how the different risk components (including danger, exposure and vulnerability) can be generated and combined into synthetic risk indices to provide a more comprehensive wildfire risk assessment, but also to consider where and on what variables reduction efforts should be stressed and to envisage policies to be better adapted to future fire regimes. Climate and socio-economic changes entail that wildfires are becoming even more a critical environmental hazard; extreme fires are observed in many areas of the world that regularly experience fire, yet fire activity is also increasing in areas where wildfires were previously rare. To mitigate the negative impacts of fire, those responsible for managing risk must leverage the information available through the risk assessment process, along with an improved understanding on how the various components of risk can be targeted to improve and optimize the many strategies for mitigation and adaptation to an increasing fire risk.