The planetary commons: A new paradigm for safeguarding Earth-regulating systems in the Anthropocene.

The Anthropocene signifies the start of a no-analogue trajectory of the Earth system that is fundamentally different from the Holocene. This new trajectory is characterized by rising risks of triggering irreversible and unmanageable shifts in Earth system functioning. We urgently need a new global approach to safeguard critical Earth system regulating functions more effectively and comprehensively. The global commons framework is the closest example of an existing approach with the aim of governing biophysical systems on Earth upon which the world collectively depends. Derived during stable Holocene conditions, the global commons framework must now evolve in the light of new Anthropocene dynamics. This requires a fundamental shift from a focus only on governing shared resources beyond national jurisdiction, to one that secures critical functions of the Earth system irrespective of national boundaries. We propose a new framework-the planetary commons-which differs from the global commons framework by including not only globally shared geographic regions but also critical biophysical systems that regulate the resilience and state, and therefore livability, on Earth. The new planetary commons should articulate and create comprehensive stewardship obligations through Earth system governance aimed at restoring and strengthening planetary resilience and justice.

Earth beyond six of nine planetary boundaries.

This planetary boundaries framework update finds that six of the nine boundaries are transgressed, suggesting that Earth is now well outside of the safe operating space for humanity. Ocean acidification is close to being breached, while aerosol loading regionally exceeds the boundary. Stratospheric ozone levels have slightly recovered. The transgression level has increased for all boundaries earlier identified as overstepped. As primary production drives Earth system biosphere functions, human appropriation of net primary production is proposed as a control variable for functional biosphere integrity. This boundary is also transgressed. Earth system modeling of different levels of the transgression of the climate and land system change boundaries illustrates that these anthropogenic impacts on Earth system must be considered in a systemic context.

Irrigation of biomass plantations may globally increase water stress more than climate change.

Bioenergy with carbon capture and storage (BECCS) is considered an important negative emissions (NEs) technology, but might involve substantial irrigation on biomass plantations. Potential water stress resulting from the additional withdrawals warrants evaluation against the avoided climate change impact. Here we quantitatively assess potential side effects of BECCS with respect to water stress by disentangling the associated drivers (irrigated biomass plantations, climate, land use patterns) using comprehensive global model simulations. By considering a widespread use of irrigated biomass plantations, global warming by the end of the 21st century could be limited to 1.5 °C compared to a climate change scenario with 3 °C. However, our results suggest that both the global area and population living under severe water stress in the BECCS scenario would double compared to today and even exceed the impact of climate change. Such side effects of achieving substantial NEs would come as an extra pressure in an already water-stressed world and could only be avoided if sustainable water management were implemented globally.

Social tipping dynamics for stabilizing Earth's climate by 2050.

Safely achieving the goals of the Paris Climate Agreement requires a worldwide transformation to carbon-neutral societies within the next 30 y. Accelerated technological progress and policy implementations are required to deliver emissions reductions at rates sufficiently fast to avoid crossing dangerous tipping points in the Earth's climate system. Here, we discuss and evaluate the potential of social tipping interventions (STIs) that can activate contagious processes of rapidly spreading technologies, behaviors, social norms, and structural reorganization within their functional domains that we refer to as social tipping elements (STEs). STEs are subdomains of the planetary socioeconomic system where the required disruptive change may take place and lead to a sufficiently fast reduction in anthropogenic greenhouse gas emissions. The results are based on online expert elicitation, a subsequent expert workshop, and a literature review. The STIs that could trigger the tipping of STE subsystems include 1) removing fossil-fuel subsidies and incentivizing decentralized energy generation (STE1, energy production and storage systems), 2) building carbon-neutral cities (STE2, human settlements), 3) divesting from assets linked to fossil fuels (STE3, financial markets), 4) revealing the moral implications of fossil fuels (STE4, norms and value systems), 5) strengthening climate education and engagement (STE5, education system), and 6) disclosing information on greenhouse gas emissions (STE6, information feedbacks). Our research reveals important areas of focus for larger-scale empirical and modeling efforts to better understand the potentials of harnessing social tipping dynamics for climate change mitigation.

Europe's renewable energy directive poised to harm global forests.

This comment raises concerns regarding the way in which a new European directive, aimed at reaching higher renewable energy targets, treats wood harvested directly for bioenergy use as a carbon-free fuel. The result could consume quantities of wood equal to all Europe's wood harvests, greatly increase carbon in the air for decades, and set a dangerous global example.

Trade-offs for food production, nature conservation and climate limit the terrestrial carbon dioxide removal potential.

Large-scale biomass plantations (BPs) are a common factor in climate mitigation scenarios as they promise double benefits: extracting carbon from the atmosphere and providing a renewable energy source. However, their terrestrial carbon dioxide removal (tCDR) potentials depend on important factors such as land availability, efficiency of capturing biomass-derived carbon and the timing of operation. Land availability is restricted by the demands of future food production depending on yield increases and population growth, by requirements for nature conservation and, with respect to climate mitigation, avoiding unfavourable albedo changes. We integrate these factors in one spatially explicit biogeochemical simulation framework to explore the tCDR opportunity space on land available after these constraints are taken into account, starting either in 2020 or 2050, and lasting until 2100. We find that assumed future needs for nature protection and food production strongly limit tCDR potentials. BPs on abandoned crop and pasture areas (~1,300 Mha in scenarios of either 8.0 billion people and yield gap reductions of 25% until 2020 or 9.5 billion people and yield gap reductions of 50% until 2050) could, theoretically, sequester ~100 GtC in land carbon stocks and biomass harvest by 2100. However, this potential would be ~80% lower if only cropland was available or ~50% lower if albedo decreases were considered as a factor restricting land availability. Converting instead natural forest, shrubland or grassland into BPs could result in much larger tCDR potentials ̶ but at high environmental costs (e.g. biodiversity loss). The most promising avenue for effective tCDR seems to be improvement of efficient carbon utilization pathways, changes in dietary trends or the restoration of marginal lands for the implementation of tCDR.

Macroscopic description of complex adaptive networks coevolving with dynamic node states.

In many real-world complex systems, the time evolution of the network's structure and the dynamic state of its nodes are closely entangled. Here we study opinion formation and imitation on an adaptive complex network which is dependent on the individual dynamic state of each node and vice versa to model the coevolution of renewable resources with the dynamics of harvesting agents on a social network. The adaptive voter model is coupled to a set of identical logistic growth models and we mainly find that, in such systems, the rate of interactions between nodes as well as the adaptive rewiring probability are crucial parameters for controlling the sustainability of the system's equilibrium state. We derive a macroscopic description of the system in terms of ordinary differential equations which provides a general framework to model and quantify the influence of single node dynamics on the macroscopic state of the network. The thus obtained framework is applicable to many fields of study, such as epidemic spreading, opinion formation, or socioecological modeling.

A high-resolution approach to estimating ecosystem respiration at continental scales using operational satellite data.

A better understanding of the local variability in land-atmosphere carbon fluxes is crucial to improving the accuracy of global carbon budgets. Operational satellite data backed by ground measurements at Fluxnet sites proved valuable in monitoring local variability of gross primary production at highly resolved spatio-temporal resolutions. Yet, we lack similar operational estimates of ecosystem respiration (Re) to calculate net carbon fluxes. If successful, carbon fluxes from such a remote sensing approach would form an independent and sought after measure to complement widely used dynamic global vegetation models (DGVMs). Here, we establish an operational semi-empirical Re model, based only on data from the Moderate Resolution Imaging Spectroradiometer (MODIS) with a resolution of 1 km and 8 days. Fluxnet measurements between 2000 and 2009 from 100 sites across North America and Europe are used for parameterization and validation. Our analysis shows that Re is closely tied to temperature and plant productivity. By separating temporal and intersite variation, we find that MODIS land surface temperature (LST) and enhanced vegetation index (EVI) are sufficient to explain observed Re across most major biomes with a negligible bias [R² = 0.62, RMSE = 1.32 (g C m(-2) d(-1)), MBE = 0.05 (g C m(-2) d(-1))]. A comparison of such satellite-derived Re with those simulated by the DGVM LPJmL reveals similar spatial patterns. However, LPJmL shows higher temperature sensitivities and consistently simulates higher Re values, in high-latitude and subtropical regions. These differences remain difficult to explain and they are likely associated either with LPJmL parameterization or with systematic errors in the Fluxnet sampling technique. While uncertainties remain with Re estimates, the model formulated in this study provides an operational, cross-validated and unbiased approach to scale Fluxnet Re to the continental scale and advances knowledge of spatio-temporal Re variability.

Carbon residence time dominates uncertainty in terrestrial vegetation responses to future climate and atmospheric CO2.

Future climate change and increasing atmospheric CO2 are expected to cause major changes in vegetation structure and function over large fractions of the global land surface. Seven global vegetation models are used to analyze possible responses to future climate simulated by a range of general circulation models run under all four representative concentration pathway scenarios of changing concentrations of greenhouse gases. All 110 simulations predict an increase in global vegetation carbon to 2100, but with substantial variation between vegetation models. For example, at 4 °C of global land surface warming (510-758 ppm of CO2), vegetation carbon increases by 52-477 Pg C (224 Pg C mean), mainly due to CO2 fertilization of photosynthesis. Simulations agree on large regional increases across much of the boreal forest, western Amazonia, central Africa, western China, and southeast Asia, with reductions across southwestern North America, central South America, southern Mediterranean areas, southwestern Africa, and southwestern Australia. Four vegetation models display discontinuities across 4 °C of warming, indicating global thresholds in the balance of positive and negative influences on productivity and biomass. In contrast to previous global vegetation model studies, we emphasize the importance of uncertainties in projected changes in carbon residence times. We find, when all seven models are considered for one representative concentration pathway × general circulation model combination, such uncertainties explain 30% more variation in modeled vegetation carbon change than responses of net primary productivity alone, increasing to 151% for non-HYBRID4 models. A change in research priorities away from production and toward structural dynamics and demographic processes is recommended.

Development of probability density functions for future South American rainfall.

*We estimate probability density functions (PDFs) for future rainfall in five regions of South America, by weighting the predictions of the 24 Coupled Model Intercomparison Archive Project 3 (CMIP3) General Circulation Models (GCMs). The models are rated according to their relative abilities to reproduce the inter-annual variability in seasonal rainfall. *The relative weighting of the climate models is updated sequentially according to Bayes' theorem, based on the biases in the mean of the predicted time-series and the distributional fit of the bias-corrected time-series. *Depending on the season and the region, we find very different rankings of the GCMs, with no single model doing well in all cases. However, in some regions and seasons, differential weighting of the models leads to significant shifts in the derived rainfall PDFs. *Using a combination of the relative model weightings for each season we have also derived a set of overall model weightings for each region that can be used to produce PDFs of forest biomass from the simulations of the Lund-Potsdam-Jena Dynamic Global Vegetation Model for managed land (LPJmL).

Estimating the risk of Amazonian forest dieback.

*Climate change will very likely affect most forests in Amazonia during the course of the 21st century, but the direction and intensity of the change are uncertain, in part because of differences in rainfall projections. In order to constrain this uncertainty, we estimate the probability for biomass change in Amazonia on the basis of rainfall projections that are weighted by climate model performance for current conditions. *We estimate the risk of forest dieback by using weighted rainfall projections from 24 general circulation models (GCMs) to create probability density functions (PDFs) for future forest biomass changes simulated by a dynamic vegetation model (LPJmL). *Our probabilistic assessment of biomass change suggests a likely shift towards increasing biomass compared with nonweighted results. Biomass estimates range between a gain of 6.2 and a loss of 2.7 kg carbon m(-2) for the Amazon region, depending on the strength of CO(2) fertilization. *The uncertainty associated with the long-term effect of CO(2) is much larger than that associated with precipitation change. This underlines the importance of reducing uncertainties in the direct effects of CO(2) on tropical ecosystems.

Tipping elements in the Earth's climate system.

The term "tipping point" commonly refers to a critical threshold at which a tiny perturbation can qualitatively alter the state or development of a system. Here we introduce the term "tipping element" to describe large-scale components of the Earth system that may pass a tipping point. We critically evaluate potential policy-relevant tipping elements in the climate system under anthropogenic forcing, drawing on the pertinent literature and a recent international workshop to compile a short list, and we assess where their tipping points lie. An expert elicitation is used to help rank their sensitivity to global warming and the uncertainty about the underlying physical mechanisms. Then we explain how, in principle, early warning systems could be established to detect the proximity of some tipping points.

Quantifying and mapping the human appropriation of net primary production in earth's terrestrial ecosystems.

Human appropriation of net primary production (HANPP), the aggregate impact of land use on biomass available each year in ecosystems, is a prominent measure of the human domination of the biosphere. We present a comprehensive assessment of global HANPP based on vegetation modeling, agricultural and forestry statistics, and geographical information systems data on land use, land cover, and soil degradation that localizes human impact on ecosystems. We found an aggregate global HANPP value of 15.6 Pg C/yr or 23.8% of potential net primary productivity, of which 53% was contributed by harvest, 40% by land-use-induced productivity changes, and 7% by human-induced fires. This is a remarkable impact on the biosphere caused by just one species. We present maps quantifying human-induced changes in trophic energy flows in ecosystems that illustrate spatial patterns in the human domination of ecosystems, thus emphasizing land use as a pervasive factor of global importance. Land use transforms earth's terrestrial surface, resulting in changes in biogeochemical cycles and in the ability of ecosystems to deliver services critical to human well being. The results suggest that large-scale schemes to substitute biomass for fossil fuels should be viewed cautiously because massive additional pressures on ecosystems might result from increased biomass harvest.

Terrestrial vegetation redistribution and carbon balance under climate change.

BACKGROUND: Dynamic Global Vegetation Models (DGVMs) compute the terrestrial carbon balance as well as the transient spatial distribution of vegetation. We study two scenarios of moderate and strong climate change (2.9 K and 5.3 K temperature increase over present) to investigate the spatial redistribution of major vegetation types and their carbon balance in the year 2100. RESULTS: The world's land vegetation will be more deciduous than at present, and contain about 125 billion tons of additional carbon. While a recession of the boreal forest is simulated in some areas, along with a general expansion to the north, we do not observe a reported collapse of the central Amazonian rain forest. Rather, a decrease of biomass and a change of vegetation type occurs in its northeastern part. The ability of the terrestrial biosphere to sequester carbon from the atmosphere declines strongly in the second half of the 21st century. CONCLUSION: Climate change will cause widespread shifts in the distribution of major vegetation functional types on all continents by the year 2100.

Impacts of large-scale climatic disturbances on the terrestrial carbon cycle.

BACKGROUND: The amount of carbon dioxide in the atmosphere steadily increases as a consequence of anthropogenic emissions but with large interannual variability caused by the terrestrial biosphere. These variations in the CO2 growth rate are caused by large-scale climate anomalies but the relative contributions of vegetation growth and soil decomposition is uncertain. We use a biogeochemical model of the terrestrial biosphere to differentiate the effects of temperature and precipitation on net primary production (NPP) and heterotrophic respiration (Rh) during the two largest anomalies in atmospheric CO2 increase during the last 25 years. One of these, the smallest atmospheric year-to-year increase (largest land carbon uptake) in that period, was caused by global cooling in 1992/93 after the Pinatubo volcanic eruption. The other, the largest atmospheric increase on record (largest land carbon release), was caused by the strong El Niño event of 1997/98. RESULTS: We find that the LPJ model correctly simulates the magnitude of terrestrial modulation of atmospheric carbon anomalies for these two extreme disturbances. The response of soil respiration to changes in temperature and precipitation explains most of the modelled anomalous CO2 flux. CONCLUSION: Observed and modelled NEE anomalies are in good agreement, therefore we suggest that the temporal variability of heterotrophic respiration produced by our model is reasonably realistic. We therefore conclude that during the last 25 years the two largest disturbances of the global carbon cycle were strongly controlled by soil processes rather then the response of vegetation to these large-scale climatic events.

Tropical forests and the global carbon cycle: impacts of atmospheric carbon dioxide, climate change and rate of deforestation.

The remaining carbon stocks in wet tropical forests are currently at risk because of anthropogenic deforestation, but also because of the possibility of release driven by climate change. To identify the relative roles of CO2 increase, changing temperature and rainfall, and deforestation in the future, and the magnitude of their impact on atmospheric CO2 concentrations, we have applied a dynamic global vegetation model, using multiple scenarios of tropical deforestation (extrapolated from two estimates of current rates) and multiple scenarios of changing climate (derived from four independent offline general circulation model simulations). Results show that deforestation will probably produce large losses of carbon, despite the uncertainty about the deforestation rates. Some climate models produce additional large fluxes due to increased drought stress caused by rising temperature and decreasing rainfall. One climate model, however, produces an additional carbon sink. Taken together, our estimates of additional carbon emissions during the twenty-first century, for all climate and deforestation scenarios, range from 101 to 367 Gt C, resulting in CO2 concentration increases above background values between 29 and 129 p.p.m. An evaluation of the method indicates that better estimates of tropical carbon sources and sinks require improved assessments of current and future deforestation, and more consistent precipitation scenarios from climate models. Notwithstanding the uncertainties, continued tropical deforestation will most certainly play a very large role in the build-up of future greenhouse gas concentrations.

Climatic control of the high-latitude vegetation greening trend and Pinatubo effect.

A biogeochemical model of vegetation using observed climate data predicts the high northern latitude greening trend over the past two decades observed by satellites and a marked setback in this trend after the Mount Pinatubo volcano eruption in 1991. The observed trend toward earlier spring budburst and increased maximum leaf area is produced by the model as a consequence of biogeochemical vegetation responses mainly to changes in temperature. The post-Pinatubo decline in vegetation in 1992-1993 is apparent as the effect of temporary cooling caused by the eruption. High-latitude CO(2) uptake during these years is predicted as a consequence of the differential response of heterotrophic respiration and net primary production.