ALBERT

Description: The progressive oxygenation of the Earth’s atmosphere was pivotal to the evolution of life, but the puzzle of when and how atmospheric oxygen (O2) first approached modern levels (∼21%) remains unresolved. Redox proxy data indicate the deep oceans were oxygenated during 435–392 Ma, and the appearance of fossil charcoal indicates O2 〉15–17% by 420–400 Ma. However, existing models have failed to predict oxygenation at this time. Here we show that the earliest plants, which colonized the land surface from ∼470 Ma onward, were responsible for this mid-Paleozoic oxygenation event, through greatly increasing global organic carbon burial—the net long-term source of O2. We use a trait-based ecophysiological model to predict that cryptogamic vegetation cover could have achieved ∼30% of today’s global terrestrial net primary productivity by ∼445 Ma. Data from modern bryophytes suggests this plentiful early plant material had a much higher molar C:P ratio (∼2,000) than marine biomass (∼100), such that a given weathering flux of phosphorus could support more organic carbon burial. Furthermore, recent experiments suggest that early plants selectively increased the flux of phosphorus (relative to alkalinity) weathered from rocks. Combining these effects in a model of long-term biogeochemical cycling, we reproduce a sustained +2‰ increase in the carbonate carbon isotope (δ13C) record by ∼445 Ma, and predict a corresponding rise in O2 to present levels by 420–400 Ma, consistent with geochemical data. This oxygen rise represents a permanent shift in regulatory regime to one where fire-mediated negative feedbacks stabilize high O2 levels.

Description: Nitrous oxide is a strong greenhouse gas and atmospheric ozone-depleting agent which is largely emitted by soils. Recently, lichens and bryophytes have also been shown to release significant amounts of nitrous oxide. This finding relies on ecosystem-scale estimates of net primary productivity of lichens and bryophytes, which are converted to nitrous oxide emissions by empirical relationships between productivity and respiration, as well as between respiration and nitrous oxide release. Here we obtain an alternative estimate of nitrous oxide emissions which is based on a global process-based non-vascular vegetation model of lichens and bryophytes. The model quantifies photosynthesis and respiration of lichens and bryophytes directly as a function of environmental conditions, such as light and temperature. Nitrous oxide emissions are then derived from simulated respiration assuming a fixed relationship between the two fluxes. This approach yields a global estimate of 0.27 (0.19–0.35) (Tg N2O) year−1 released by lichens and bryophytes. This is lower than previous estimates but corresponds to about 50 % of the atmospheric deposition of nitrous oxide into the oceans or 25 % of the atmospheric deposition on land. Uncertainty in our simulated estimate results from large variation in emission rates due to both physiological differences between species and spatial heterogeneity of climatic conditions. To constrain our predictions, combined online gas exchange measurements of respiration and nitrous oxide emissions may be helpful.

Description: The cycling of carbon (C) between the Earth surface and the atmosphere is controlled by biological and abiotic processes that regulate C storage in biogeochemical compartments and release to the atmosphere. This partitioning is quantified using various forms of C-use efficiency (CUE) – the ratio of C remaining in a system to C entering that system. Biological CUE is the fraction of C taken up allocated to biosynthesis. In soils and sediments, C storage depends also on abiotic processes, so the term C-storage efficiency (CSE) can be used. Here we first review and reconcile CUE and CSE definitions proposed for autotrophic and heterotrophic organisms and communities, food webs, whole ecosystems and watersheds, and soils and sediments using a common mathematical framework. Second, we identify general CUE patterns; for example, the actual CUE increases with improving growth conditions, and apparent CUE decreases with increasing turnover. We then synthesize 〉 5000 CUE estimates showing that CUE decreases with increasing biological and ecological organization – from unicellular to multicellular organisms and from individuals to ecosystems. We conclude that CUE is an emergent property of coupled biological–abiotic systems, and it should be regarded as a flexible and scale-dependent index of the capacity of a given system to effectively retain C.

Description: It is important that climate models can accurately simulate the terrestrial carbon cycle in the Arctic, due to the large and potentially labile carbon stocks found in permafrost-affected environments, which can lead to a positive climate feedback, along with the possibility of future carbon sinks from northward expansion of vegetation under climate warming. Here we evaluate the simulation of tundra carbon stocks and fluxes in three land surface schemes that each form part of major Earth System Models (JSBACH, Germany; JULES, UK and ORCHIDEE, France). We use a site-level approach where comprehensive, high-frequency datasets allow us to disentangle the importance of different processes. The models have improved physical permafrost processes and there is a reasonable correspondence between the simulated and measured physical variables, including soil temperature, soil moisture and snow. We show that if the models simulate the correct leaf area index (LAI), the standard C3 photosynthesis schemes produce the correct order of magnitude of carbon fluxes. Therefore, simulating the correct LAI is one of the first priorities. LAI depends quite strongly on climatic variables alone, as we see by the fact that the dynamic vegetation model can simulate most of the differences in LAI between sites, based almost entirely on climate inputs. However, we also identify an influence from nutrient limitation as the LAI becomes too large at some of the more nutrient-limited sites. We conclude that including moss as well as vascular plants is of primary importance to the carbon budget, as moss contributes a large fraction to the seasonal CO2 flux in nutrient-limited conditions. Moss photosynthetic activity can be strongly influenced by the moisture content of moss, and the carbon uptake can be significantly different from vascular plants with similar LAI. The soil carbon stocks depend strongly on the rate of input of carbon from the vegetation to the soil, and our analysis suggests that an improved simulation of photosynthesis would also lead to an improved simulation of soil carbon stocks. However, the stocks are also influenced by soil carbon burial (e.g. through cryoturbation) and the rate of heterotrophic respiration, which depends on the soil physical state. More detailed below-ground measurements are needed to fully evaluate soil biological and physical processes. Furthermore, even if these processes are well modelled, the soil carbon profiles cannot resemble peat layers as peat accumulation processes are not represented in the models. Thus we identify three priority areas for model development: 1. Dynamic vegetation including a. climate and b. nutrient limitation effects. 2. Adding moss as a plant functional type. 3. Improved vertical profile of soil carbon including peat processes.

Description: It is important that climate models can accurately simulate the terrestrial carbon cycle in the Arctic due to the large and potentially labile carbon stocks found in permafrost-affected environments, which can lead to a positive climate feedback, along with the possibility of future carbon sinks from northward expansion of vegetation under climate warming. Here we evaluate the simulation of tundra carbon stocks and fluxes in three land surface schemes that each form part of major Earth system models (JSBACH, Germany; JULES, UK; ORCHIDEE, France). We use a site-level approach in which comprehensive, high-frequency datasets allow us to disentangle the importance of different processes. The models have improved physical permafrost processes and there is a reasonable correspondence between the simulated and measured physical variables, including soil temperature, soil moisture and snow. We show that if the models simulate the correct leaf area index (LAI), the standard C3 photosynthesis schemes produce the correct order of magnitude of carbon fluxes. Therefore, simulating the correct LAI is one of the first priorities. LAI depends quite strongly on climatic variables alone, as we see by the fact that the dynamic vegetation model can simulate most of the differences in LAI between sites, based almost entirely on climate inputs. However, we also identify an influence from nutrient limitation as the LAI becomes too large at some of the more nutrient-limited sites. We conclude that including moss as well as vascular plants is of primary importance to the carbon budget, as moss contributes a large fraction to the seasonal CO2 flux in nutrient-limited conditions. Moss photosynthetic activity can be strongly influenced by the moisture content of moss, and the carbon uptake can be significantly different from vascular plants with a similar LAI. The soil carbon stocks depend strongly on the rate of input of carbon from the vegetation to the soil, and our analysis suggests that an improved simulation of photosynthesis would also lead to an improved simulation of soil carbon stocks. However, the stocks are also influenced by soil carbon burial (e.g. through cryoturbation) and the rate of heterotrophic respiration, which depends on the soil physical state. More detailed below-ground measurements are needed to fully evaluate biological and physical soil processes. Furthermore, even if these processes are well modelled, the soil carbon profiles cannot resemble peat layers as peat accumulation processes are not represented in the models. Thus, we identify three priority areas for model development: (1) dynamic vegetation including (a) climate and (b) nutrient limitation effects; (2) adding moss as a plant functional type; and an (3) improved vertical profile of soil carbon including peat processes.

Description: Bryophyte and lichen cover on the forest floor at high latitudes exerts an insulating effect on the ground. In this way, the cover decreases mean annual soil temperature and can protect permafrost soil. Climate change, however, may change bryophyte and lichen cover, with effects on the permafrost state and related carbon balance. It is, therefore, crucial to predict how the bryophyte and lichen cover will react to environmental change at the global scale. To date, current global land surface models contain only empirical representations of the bryophyte and lichen cover, which makes it impractical to predict the future state and function of bryophytes and lichens. For this reason, we integrate a process-based model of bryophyte and lichen growth into the global land surface model JSBACH (Jena Scheme for Biosphere–Atmosphere Coupling in Hamburg). The model simulates bryophyte and lichen cover on upland sites. Wetlands are not included. We take into account the dynamic nature of the thermal properties of the bryophyte and lichen cover and their relation to environmental factors. Subsequently, we compare simulations with and without bryophyte and lichen cover to quantify the insulating effect of the organisms on the soil. We find an average cooling effect of the bryophyte and lichen cover of 2.7 K on temperature in the topsoil for the region north of 50° N under the current climate. Locally, a cooling of up to 5.7 K may be reached. Moreover, we show that using a simple, empirical representation of the bryophyte and lichen cover without dynamic properties only results in an average cooling of around 0.5 K. This suggests that (a) bryophytes and lichens have a significant impact on soil temperature in high-latitude ecosystems and (b) a process-based description of their thermal properties is necessary for a realistic representation of the cooling effect. The advanced land surface scheme, including a dynamic bryophyte and lichen model, will be the basis for an improved future projection of land–atmosphere heat and carbon exchange.

Description: To clarify effects of the variability of meteorological measures and their extreme events on topsoil and subsoil temperature in permafrost regions, an artificially manipulated climate dataset has been used for process-oriented model experiments. Climate variability mainly impacts snow depth, and the cover and thermal diffusivity of lichens and bryophytes. The latter effect is of opposite direction in summer and winter. These impacts of climate variability on insulating layers together substantially alter the heat exchange between atmosphere and soil. As a result, soil temperature is up to 1 K higher when climate variability is reduced under conserved long-term mean meteorological measures. Climate models project warming of the Arctic region but also increasing climate variability and extreme events. Therefore, our results show that projected future increases in permafrost temperature and active-layer thickness will be less pronounced in response to climate change when considering dynamic snow and near-surface vegetation modules.

Description: Arboreal epiphytes (plants residing in forest canopies) are present across all major climate zones and play important roles in forest biogeochemistry. The substantial water storage capacity per unit area of the epiphyte “bucket” is a key attribute underlying their capability to influence forest hydrological processes and their related mass and energy flows. It is commonly assumed that the epiphyte bucket remains saturated, or near-saturated, most of the time; thus, epiphytes (particularly vascular epiphytes) can store little precipitation, limiting their impact on the forest canopy water budget. We present evidence that contradicts this common assumption from (i) an examination of past research; (ii) new datasets on vascular epiphyte and epi-soil water relations at a tropical montane cloud forest (Monteverde, Costa Rica); and (iii) a global evaluation of non-vascular epiphyte saturation state using a process-based vegetation model, LiBry. All analyses found that the external and internal water storage capacity of epiphyte communities is highly dynamic and frequently available to intercept precipitation. Globally, non-vascular epiphytes spend

Description: Non-vascular vegetation has been shown to capture considerable quantities of rainfall, which may affect the hydrological cycle and climate at continental scales. However, direct measurements of rainfall interception by non-vascular vegetation are confined to the local scale, which makes extrapolation to the global effects difficult. Here we use a process-based numerical simulation model to show that non-vascular vegetation contributes substantially to global rainfall interception. Inferred average global water storage capacity including non-vascular vegetation was 2.7 mm, which is consistent with field observations and markedly exceeds the values used in land surface models, which average around 0.4 mm. Consequently, we find that the total evaporation of free water from the forest canopy and soil surface increases by 61% when non-vascular vegetation is included, resulting in a global rainfall interception flux that is 22% of the terrestrial evaporative flux (compared with only 12% for simulations where interception excludes non-vascular vegetation). We thus conclude that non-vascular vegetation is likely to significantly influence global rainfall interception and evaporation with consequences for regional- to continental-scale hydrologic cycling and climate. © 2018, The Author(s).

Description: Effects of the short-term temporal variability of meteorological variables on soil temperature in northern high latitude regions have been investigated. For this, a process-oriented land surface model has been driven using an artificially manipulated climate dataset. Climate variability mainly impacts snow depth, and the thermal diffusivity of lichens and bryophytes. This latter effect is of opposite direction in summer and winter in most regions. These impacts of climate variability on insulating surface layers together substantially alter the heat exchange between atmosphere and soil. As a result, soil temperature is 0.1 to 0.8 °C higher when climate variability is reduced. Earth system models project warming of the Arctic region but also increasing variability of meteorological variables and more often extreme meteorological events. Therefore, our results show that projected future increases in permafrost temperature and active-layer thickness in response to climate change will be lower i) when taking into account future changes in short-term variability of meteorological variables, and ii) when representing dynamic snow and lichen and bryophyte functions in land surface models.