Humans have altered the Earth’s land surface since the Paleolithic mainly by clearing woody vegetation first to improve hunting and gathering opportunities, and later to provide agricultural cropland. In the Holocene, agriculture was established on nearly all continents and led to widespread modification of terrestrial ecosystems. To quantify the role that humans played in the global carbon cycle over the Holocene, we developed a new, annually resolved inventory of anthropogenic land cover change from 8000 years ago to the beginning of large-scale industrialization (ad 1850). This inventory is based on a simple relationship between population and land use observed in several European countries over preindustrial time. Using this data set, and an alternative scenario based on the HYDE 3.1 land use data base, we forced the LPJ dynamic global vegetation model in a series of continuous simulations to evaluate the impacts of humans on terrestrial carbon storage during the preindustrial Holocene. Our model setup allowed us to quantify the importance of land degradation caused by repeated episodes of land use followed by abandonment. By 3 ka BP, cumulative carbon emissions caused by anthropogenic land cover change in our new scenario ranged between 84 and 102 Pg, translating to c. 7 ppm of atmospheric CO₂. By ad 1850, emissions were 325–357 Pg in the new scenario, in contrast to 137–189 Pg when driven by HYDE. Regional events that resulted in local emissions or uptake of carbon were often balanced by contrasting patterns in other parts of the world. While we cannot close the carbon budget in the current study, simulated cumulative anthropogenic emissions over the preindustrial Holocene are consistent with the ice core record of atmospheric δ¹³CO₂ and support the hypothesis that anthropogenic activities led to the stabilization of atmospheric CO₂ concentrations at a level that made the world substantially warmer than it otherwise would be.

The major objectives of this paper are: (1) to review the pros and cons of the scenarios of past anthropogenic land cover change (ALCC) developed during the last ten years, (2) to discuss issues related to pollen-based reconstruction of the past land-cover and introduce a new method, REVEALS (Regional Estimates of VEgetation Abundance from Large Sites), to infer long-term records of past land-cover from pollen data, (3) to present a new project (LANDCLIM: LAND cover – CLIMate interactions in NW Europe during the Holocene) currently underway, and show preliminary results of REVEALS reconstructions of the regional land-cover in the Czech Republic for five selected time windows of the Holocene, and (4) to discuss the implications and future directions in climate and vegetation/land-cover modeling, and in the assessment of the effects of human-induced changes in land-cover on the regional climate through altered feedbacks. The existing ALCC scenarios show large discrepancies between them, and few cover time periods older than AD 800. When these scenarios are used to assess the impact of human land-use on climate, contrasting results are obtained. It emphasizes the need for methods such as the REVEALS model-based land-cover reconstructions. They might help to fine-tune descriptions of past land-cover and lead to a better understanding of how long-term changes in ALCC might have influenced climate. The REVEALS model is demonstrated to provide better estimates of the regional vegetation/land-cover changes than the traditional use of pollen percentages. This will achieve a robust assessment of land cover at regional- to continental-spatial scale throughout the Holocene. We present maps of REVEALS estimates for the percentage cover of 10 plant functional types (PFTs) at 200 BP and 6000 BP, and of the two open-land PFTs "grassland" and "agricultural land" at five time-windows from 6000 BP to recent time. The LANDCLIM results are expected to provide crucial data to reassess ALCC estimates for a better understanding of the land suface-atmosphere interactions.

The unprecedented use of Earth's resources by humans, in combination with increasing natural variability in natural processes over the past century, is affecting the evolution of the Earth system. To better understand natural processes and their potential future trajectories requires improved integration with and quantification of human processes. Similarly, to mitigate risk and facilitate socio-economic development requires a better understanding of how the natural system (e.g. climate variability and change, extreme weather events, and processes affecting soil fertility) affects human processes. Our understanding of these interactions and feedback between human and natural systems has been formalized through a variety of modelling approaches. However, a common conceptual framework or set of guidelines to model human–natural-system feedbacks is lacking. The presented research lays out a conceptual framework that includes representing model coupling configuration in combination with the frequency of interaction and coordination of communication between coupled models. Four different approaches used to couple representations of the human and natural system are presented in relation to this framework, which vary in the processes represented and in the scale of their application. From the development and experience associated with the four models of coupled human–natural systems, the following eight lessons were identified that if taken into account by future coupled human–natural-systems model developments may increase their success: (1) leverage the power of sensitivity analysis with models, (2) remember modelling is an iterative process, (3) create a common language, (4) make code open-access, (5) ensure consistency, (6) reconcile spatio-temporal mismatch, (7) construct homogeneous units, and (8) incorporating feedback increases non-linearity and variability. Following a discussion of feedbacks, a way forward to expedite model coupling and increase the longevity and interoperability of models is given, which suggests the use of a wrapper container software, a standardized applications programming interface (API), the incorporation of standard names, the mitigation of sunk costs by creating interfaces to multiple coupling frameworks, and the adoption of reproducible workflow environments to wire the pieces together.

Marine litter is one of the most relevant pollution problems that our oceans are facing today. Marine litter in our oceans is a major threat to a sustainable planet. Here, we provide a comprehensive analysis of cutting-edge solutions developed globally to prevent, monitor and clean marine litter. Prevention in this research includes only innovative solutions to prevent litter entering oceans and seas rather than interventions such as waste reduction and recycling. On the basis of extensive search and data compilation, our analysis reveals that information is dispersed across platforms and is not easily accessible. In total, 177 solutions—the equivalent to <0.9% of the search hits—fulfilled our validation criteria and were evaluated. Most solutions (n = 106, 60%) primarily address monitoring and were developed during the past 3 years, with the scientific community being the key driver. Few solutions reached mature technical readiness and market availability, while none were validated for efficiency and environmental impact. Looking ahead, we elaborate on the limitations of the existing solutions, the challenges of developing new solutions, and provide recommendations for funding schemes and policy instruments to prevent, monitor and clean marine litter globally. In doing so, we encourage researchers, innovators and policy-makers worldwide to act towards achieving and sustaining a cleaner ocean for future generations.

Wildfire occurrence is influenced by climate, vegetation and human activities. A key challenge for understanding the risk of fires is quantifying the mediating effect of vegetation on fire regimes. Here, we explore the relative importance of Holocene land cover, land use, dominant functional forest type, and climate dynamics on biomass burning in temperate and boreo-nemoral regions of central and eastern Europe over the past 12 kyr. We used an extensive data set of Holocene pollen and sedimentary charcoal records, in combination with climate simulations and statistical modelling. Biomass burning was highest during the early Holocene and lowest during the mid-Holocene in all three ecoregions (Atlantic, continental and boreo-nemoral) but was more spatially variable over the past 3–4 kyr. Although climate explained a significant variance in biomass burning during the early Holocene, tree cover was consistently the highest predictor of past biomass burning over the past 8 kyr. In temperate forests, biomass burning was high at ∼45 % tree cover and decreased to a minimum at between 60 % and 70 % tree cover. In needleleaf-dominated forests, biomass burning was highest at ∼ 60 %–65 % tree cover and steeply declined at >65 % tree cover. Biomass burning also increased when arable lands and grasslands reached ∼ 15 %–20 %, although this relationship was variable depending on land use practice via ignition sources, fuel type and quantities. Higher tree cover reduced the amount of solar radiation reaching the forest floor and could provide moister, more wind-protected microclimates underneath canopies, thereby decreasing fuel flammability. Tree cover at which biomass burning increased appears to be driven by warmer and drier summer conditions during the early Holocene and by increasing human influence on land cover during the late Holocene. We suggest that long-term fire hazard may be effectively reduced through land cover management, given that land cover has controlled fire regimes under the dynamic climates of the Holocene.