Land use intensification increasingly drives the spatiotemporal patterns of the global human appropriation of net primary production in the last century.

Land use has greatly transformed Earth's surface. While spatial reconstructions of how the extent of land cover and land-use types have changed during the last century are available, much less information exists about changes in land-use intensity. In particular, global reconstructions that consistently cover land-use intensity across land-use types and ecosystems are missing. We, therefore, lack understanding of how changes in land-use intensity interfere with the natural processes in land systems. To address this research gap, we map land-cover and land-use intensity changes between 1910 and 2010 for 9 points in time. We rely on the indicator framework of human appropriation of net primary production (HANPP) to quantify and map land-use-induced alterations of the carbon flows in ecosystems. We find that, while at the global aggregate level HANPP growth slowed down during the century, the spatial dynamics of changes in HANPP were increasing, with the highest change rates observed in the most recent past. Across all biomes, the importance of changes in land-use areas has declined, with the exception of the tropical biomes. In contrast, increases in land-use intensity became the most important driver of HANPP across all biomes and settings. We conducted uncertainty analyses by modulating input data and assumptions, which indicate that the spatial patterns of land use and potential net primary production are the most critical factors, while spatial allocation rules and uncertainties in overall harvest values play a smaller role. Highlighting the increasing role of land-use intensity compared to changes in the areal extent of land uses, our study supports calls for better integration of the intensity dimension into global analyses and models. On top of that, we provide important empirical input for further analyses of the sustainability of the global land system.

Forest responses to last-millennium hydroclimate variability are governed by spatial variations in ecosystem sensitivity.

Forecasts of future forest change are governed by ecosystem sensitivity to climate change, but ecosystem model projections are under-constrained by data at multidecadal and longer timescales. Here, we quantify ecosystem sensitivity to centennial-scale hydroclimate variability, by comparing dendroclimatic and pollen-inferred reconstructions of drought, forest composition and biomass for the last millennium with five ecosystem model simulations. In both observations and models, spatial patterns in ecosystem responses to hydroclimate variability are strongly governed by ecosystem sensitivity rather than climate exposure. Ecosystem sensitivity was higher in models than observations and highest in simpler models. Model-data comparisons suggest that interactions among biodiversity, demography and ecophysiology processes dampen the sensitivity of forest composition and biomass to climate variability and change. Integrating ecosystem models with observations from timescales extending beyond the instrumental record can better understand and forecast the mechanisms regulating forest sensitivity to climate variability in a complex and changing world.

State-of-the-art global models underestimate impacts from climate extremes.

Global impact models represent process-level understanding of how natural and human systems may be affected by climate change. Their projections are used in integrated assessments of climate change. Here we test, for the first time, systematically across many important systems, how well such impact models capture the impacts of extreme climate conditions. Using the 2003 European heat wave and drought as a historical analogue for comparable events in the future, we find that a majority of models underestimate the extremeness of impacts in important sectors such as agriculture, terrestrial ecosystems, and heat-related human mortality, while impacts on water resources and hydropower are overestimated in some river basins; and the spread across models is often large. This has important implications for economic assessments of climate change impacts that rely on these models. It also means that societal risks from future extreme events may be greater than previously thought.

Tree mortality submodels drive simulated long-term forest dynamics: assessing 15 models from the stand to global scale.

Models are pivotal for assessing future forest dynamics under the impacts of changing climate and management practices, incorporating representations of tree growth, mortality, and regeneration. Quantitative studies on the importance of mortality submodels are scarce. We evaluated 15 dynamic vegetation models (DVMs) regarding their sensitivity to different formulations of tree mortality under different degrees of climate change. The set of models comprised eight DVMs at the stand scale, three at the landscape scale, and four typically applied at the continental to global scale. Some incorporate empirically derived mortality models, and others are based on experimental data, whereas still others are based on theoretical reasoning. Each DVM was run with at least two alternative mortality submodels. Model behavior was evaluated against empirical time series data, and then, the models were subjected to different scenarios of climate change. Most DVMs matched empirical data quite well, irrespective of the mortality submodel that was used. However, mortality submodels that performed in a very similar manner against past data often led to sharply different trajectories of forest dynamics under future climate change. Most DVMs featured high sensitivity to the mortality submodel, with deviations of basal area and stem numbers on the order of 10-40% per century under current climate and 20-170% under climate change. The sensitivity of a given DVM to scenarios of climate change, however, was typically lower by a factor of two to three. We conclude that (1) mortality is one of the most uncertain processes when it comes to assessing forest response to climate change, and (2) more data and a better process understanding of tree mortality are needed to improve the robustness of simulated future forest dynamics. Our study highlights that comparing several alternative mortality formulations in DVMs provides valuable insights into the effects of process uncertainties on simulated future forest dynamics.

Nitrous oxide effluxes from plants as a potentially important source to the atmosphere.

The global budget for nitrous oxide (N2 O), an important greenhouse gas and probably dominant ozone-depleting substance emitted in the 21st century, is far from being fully understood. Cycling of N2 O in terrestrial ecosystems has traditionally exclusively focused on gas exchange between the soil surface (nitrification-denitrification processes) and the atmosphere. Terrestrial vegetation has not been considered in the global budget so far, even though plants are known to release N2 O. Here, we report the N2 O emission rates of 32 plant species from 22 different families measured under controlled laboratory conditions. Furthermore, the first isotopocule values (δ15 N, δ18 O and δ15 Nsp ) of N2 O emitted from plants were determined. A robust relationship established between N2 O emission and CO2 respiration rates, which did not alter significantly over a broad range of changing environmental conditions, was used to quantify plant-derived emissions on an ecosystem scale. Stable isotope measurements (δ15 N, δ18 O and δ15 Nsp ) of N2 O emitted by plants clearly show that the dual isotopocule fingerprint of plant-derived N2 O differs from that of currently known microbial or chemical processes. Our work suggests that vegetation is a natural source of N2 O in the environment with a large fraction released by a hitherto unrecognized process.

Emergent climate and CO2 sensitivities of net primary productivity in ecosystem models do not agree with empirical data in temperate forests of eastern North America.

Ecosystem models show divergent responses of the terrestrial carbon cycle to global change over the next century. Individual model evaluation and multimodel comparisons with data have largely focused on individual processes at subannual to decadal scales. Thus far, data-based evaluations of emergent ecosystem responses to climate and CO2 at multidecadal and centennial timescales have been rare. We compared the sensitivity of net primary productivity (NPP) to temperature, precipitation, and CO2 in ten ecosystem models with the sensitivities found in tree-ring reconstructions of NPP and raw ring-width series at six temperate forest sites. These model-data comparisons were evaluated at three temporal extents to determine whether the rapid, directional changes in temperature and CO2 in the recent past skew our observed responses to multiple drivers of change. All models tested here were more sensitive to low growing season precipitation than tree-ring NPP and ring widths in the past 30 years, although some model precipitation responses were more consistent with tree rings when evaluated over a full century. Similarly, all models had negative or no response to warm-growing season temperatures, while tree-ring data showed consistently positive effects of temperature. Although precipitation responses were least consistent among models, differences among models to CO2 drive divergence and ensemble uncertainty in relative change in NPP over the past century. Changes in forest composition within models had no effect on climate or CO2 sensitivity. Fire in model simulations reduced model sensitivity to climate and CO2 , but only over the course of multiple centuries. Formal evaluation of emergent model behavior at multidecadal and multicentennial timescales is essential to reconciling model projections with observed ecosystem responses to past climate change. Future evaluation should focus on improved representation of disturbance and biomass change as well as the feedbacks with moisture balance and CO2 in individual models.

Biological soil crusts accelerate the nitrogen cycle through large NO and HONO emissions in drylands.

Reactive nitrogen species have a strong influence on atmospheric chemistry and climate, tightly coupling the Earth's nitrogen cycle with microbial activity in the biosphere. Their sources, however, are not well constrained, especially in dryland regions accounting for a major fraction of the global land surface. Here, we show that biological soil crusts (biocrusts) are emitters of nitric oxide (NO) and nitrous acid (HONO). Largest fluxes are obtained by dark cyanobacteria-dominated biocrusts, being ∼20 times higher than those of neighboring uncrusted soils. Based on laboratory, field, and satellite measurement data, we obtain a best estimate of ∼1.7 Tg per year for the global emission of reactive nitrogen from biocrusts (1.1 Tg a(-1) of NO-N and 0.6 Tg a(-1) of HONO-N), corresponding to ∼20% of global nitrogen oxide emissions from soils under natural vegetation. On continental scales, emissions are highest in Africa and South America and lowest in Europe. Our results suggest that dryland emissions of reactive nitrogen are largely driven by biocrusts rather than the underlying soil. They help to explain enigmatic discrepancies between measurement and modeling approaches of global reactive nitrogen emissions. As the emissions of biocrusts strongly depend on precipitation events, climate change affecting the distribution and frequency of precipitation may have a strong impact on terrestrial emissions of reactive nitrogen and related climate feedback effects. Because biocrusts also account for a large fraction of global terrestrial biological nitrogen fixation, their impacts should be further quantified and included in regional and global models of air chemistry, biogeochemistry, and climate.

Nitrous oxide and methane emissions from cryptogamic covers.

Cryptogamic covers, which comprise some of the oldest forms of terrestrial life on Earth (Lenton & Huntingford, ), have recently been found to fix large amounts of nitrogen and carbon dioxide from the atmosphere (Elbert et al., ). Here we show that they are also greenhouse gas sources with large nitrous oxide (N2 O) and small methane (CH4 ) emissions. Whilst N2 O emission rates varied with temperature, humidity, and N deposition, an almost constant ratio with respect to respiratory CO2 emissions was observed for numerous lichens and bryophytes. We employed this ratio together with respiration data to calculate global and regional N2 O emissions. If our laboratory measurements are typical for lichens and bryophytes living on ground and plant surfaces and scaled on a global basis, we estimate a N2 O source strength of 0.32-0.59 Tg year(-1) for the global N2 O emissions from cryptogamic covers. Thus, our emission estimate might account for 4-9% of the global N2 O budget from natural terrestrial sources. In a wide range of arid and forested regions, cryptogamic covers appear to be the dominant source of N2 O. We suggest that greenhouse gas emissions associated with this source might increase in the course of global change due to higher temperatures and enhanced nitrogen deposition.