Spring photosynthetic onset and net CO 2 uptake in Alaska triggered by landscape thawing - Nicholas C. Parazoo; Almut Arneth; Thomas A. M. Pugh; Ben Smith; Nicholas Steiner; Kristina Luus; Roisin Commane; Josh Benmergui; Eric Stofferahn; Junjie Liu; Christian Rödenbeck; Randy Kawa; et al. (Global Change Biology, 2018)
The springtime transition to regional‐scale onset of photosynthesis and net ecosystem carbon uptake in boreal and tundra ecosystems are linked to the soil freeze–thaw state. We present evidence from diagnostic and inversion models constrained by satellite fluorescence and airborne CO 2 from 2012 to 2014 indicating the timing and magnitude of spring carbon uptake in Alaska correlates with landscape thaw and ecoregion. Landscape thaw in boreal forests typically occurs in late April ( DOY 111 ± 7) with a 29 ± 6 day lag until photosynthetic onset. North Slope tundra thaws 3 weeks later ( DOY 133 ± 5) but experiences only a 20 ± 5 day lag until photosynthetic onset. These time lag differences reflect efficient cold season adaptation in tundra shrub and the longer dehardening period for boreal evergreens. Despite the short transition from thaw to photosynthetic onset in tundra, synchrony of tundra respiration with snow melt and landscape thaw delays the transition from net carbon loss (at photosynthetic onset) to net uptake by 13 ± 7 days, thus reducing the tundra net carbon uptake period. Two global CO 2 inversions using a CASA ‐ GFED model prior estimate earlier northern high latitude net carbon uptake compared to our regional inversion, which we attribute to (i) early photosynthetic‐onset model prior bias, (ii) inverse method (scaling factor + optimization window), and (iii) sparsity of available Alaskan CO 2 observations. Another global inversion with zero prior estimates the same timing for net carbon uptake as the regional model but smaller seasonal amplitude. The analysis of Alaskan eddy covariance observations confirms regional scale findings for tundra, but indicates that photosynthesis and net carbon uptake occur up to 1 month earlier in evergreens than captured by models or CO 2 inversions, with better correlation to above‐freezing air temperature than date of primary thaw. Further collection and analysis of boreal evergreen species over multiple years and at additional subarctic flux towers are critically needed.

Adaptation of global land use and management intensity to changes in climate and atmospheric carbon dioxide - Peter Alexander; Sam Rabin; Peter Anthoni; Roslyn Henry; Thomas A. M. Pugh; Mark D. A. Rounsevell; Almut Arneth (Global Change Biology, 2018)
Land use contributes to environmental change, but is also influenced by such changes. Climate and atmospheric carbon dioxide ( CO 2 ) levels’ changes alter agricultural crop productivity, plant water requirements and irrigation water availability. The global food system needs to respond and adapt to these changes, for example, by altering agricultural practices, including the crop types or intensity of management, or shifting cultivated areas within and between countries. As impacts and associated adaptation responses are spatially specific, understanding the land use adaptation to environmental changes requires crop productivity representations that capture spatial variations. The impact of variation in management practices, including fertiliser and irrigation rates, also needs to be considered. To date, models of global land use have selected agricultural expansion or intensification levels using relatively aggregate spatial representations, typically at a regional level, that are not able to characterise the details of these spatially differentiated responses. Here, we show results from a novel global modelling approach using more detailed biophysically derived yield responses to inputs with greater spatial specificity than previously possible. The approach couples a dynamic global vegetative model ( LPJ ‐ GUESS ) with a new land use and food system model ( PLUM v2), with results benchmarked against historical land use change from 1970. Land use outcomes to 2100 were explored, suggesting that increased intensity of climate forcing reduces the inputs required for food production, due to the fertilisation and enhanced water use efficiency effects of elevated atmospheric CO 2 concentrations, but requiring substantial shifts in the global and local patterns of production. The results suggest that adaptation in the global agriculture and food system has substantial capacity to diminish the negative impacts and gain greater benefits from positive outcomes of climate change. Consequently, agricultural expansion and intensification may be lower than found in previous studies where spatial details and processes consideration were more constrained.

Large uncertainty in carbon uptake potential of land‐based climate‐change mitigation efforts - Andreas Krause; Thomas A. M. Pugh; Anita D. Bayer; Wei Li; Felix Leung; Alberte Bondeau; Jonathan C. Doelman; Florian Humpenöder; Peter Anthoni; Benjamin L. Bodirsky; Philippe Ciais; Christoph Müller; et al. (Global Change Biology, 2018)
Most climate mitigation scenarios involve negative emissions, especially those that aim to limit global temperature increase to 2°C or less. However, the carbon uptake potential in land‐based climate change mitigation efforts is highly uncertain. Here, we address this uncertainty by using two land‐based mitigation scenarios from two land‐use models ( IMAGE and MA g PIE ) as input to four dynamic global vegetation models ( DGVM s; LPJ ‐ GUESS , ORCHIDEE , JULES , LPJ mL). Each of the four combinations of land‐use models and mitigation scenarios aimed for a cumulative carbon uptake of ~130 GtC by the end of the century, achieved either via the cultivation of bioenergy crops combined with carbon capture and storage ( BECCS ) or avoided deforestation and afforestation ( ADAFF ). Results suggest large uncertainty in simulated future land demand and carbon uptake rates, depending on the assumptions related to land use and land management in the models. Total cumulative carbon uptake in the DGVM s is highly variable across mitigation scenarios, ranging between 19 and 130 GtC by year 2099. Only one out of the 16 combinations of mitigation scenarios and DGVM s achieves an equivalent or higher carbon uptake than achieved in the land‐use models. The large differences in carbon uptake between the DGVM s and their discrepancy against the carbon uptake in IMAGE and MA g PIE are mainly due to different model assumptions regarding bioenergy crop yields and due to the simulation of soil carbon response to land‐use change. Differences between land‐use models and DGVM s regarding forest biomass and the rate of forest regrowth also have an impact, albeit smaller, on the results. Given the low confidence in simulated carbon uptake for a given land‐based mitigation scenario, and that negative emissions simulated by the DGVM s are typically lower than assumed in scenarios consistent with the 2°C target, relying on negative emissions to mitigate climate change is a highly uncertain strategy.

Simulating the recent impacts of multiple biotic disturbances on forest carbon cycling across the United States - Markus Kautz; Peter Anthoni; Arjan J. H. Meddens; Thomas A. M. Pugh; Almut Arneth (Global Change Biology, 2018)
Biotic disturbances ( BD s, for example, insects, pathogens, and wildlife herbivory) substantially affect boreal and temperate forest ecosystems globally. However, accurate impact assessments comprising larger spatial scales are lacking to date although these are critically needed given the expected disturbance intensification under a warming climate. Hence, our quantitative knowledge on current and future BD impacts, for example, on forest carbon (C) cycling, is strongly limited. We extended a dynamic global vegetation model to simulate ecosystem response to prescribed tree mortality and defoliation due to multiple biotic agents across United States forests during the period 1997–2015, and quantified the BD ‐induced vegetation C loss, that is, C fluxes from live vegetation to dead organic matter pools. Annual disturbance fractions separated by BD type (tree mortality and defoliation) and agent (bark beetles, defoliator insects, other insects, pathogens, and other biotic agents) were calculated at 0.5° resolution from aerial‐surveyed data and applied within the model. Simulated BD ‐induced C fluxes totaled 251.6 Mt C (annual mean: 13.2 Mt C year −1 , SD ±7.3 Mt C year −1 between years) across the study domain, to which tree mortality contributed 95% and defoliation 5%. Among BD agents, bark beetles caused most C fluxes (61%), and total insect‐induced C fluxes were about five times larger compared to non‐insect agents, for example, pathogens and wildlife. Our findings further demonstrate that BD ‐induced C cycle impacts (i) displayed high spatio‐temporal variability, (ii) were dominated by different agents across BD types and regions, and (iii) were comparable in magnitude to fire‐induced impacts. This study provides the first ecosystem model‐based assessment of BD ‐induced impacts on forest C cycling at the continental scale and going beyond single agent‐host systems, thus allowing for comparisons across regions, BD types, and agents. Ultimately, a perspective on the potential and limitations of a more process‐based incorporation of multiple BD s in ecosystem models is offered.