Effects of Increased Drought in Amazon Forests Under Climate Change: Separating the Roles of Canopy Responses and Soil Moisture

The Amazon forests are one of the largest ecosystem carbon pools on Earth. Although more frequent and prolonged future droughts have been predicted, the impacts have remained largely uncertain, as most land surface models (LSMs) fail to capture the vegetation drought responses. In this study, the ability of the LSM JSBACH to simulate the drought responses of leaf area index (LAI) and leaf litter production in the Amazon forests is evaluated against artificial drought experiments. Based on the evaluation, improvements are implemented, including a dependency of leaf growth on leaf carbon allocation and a better representation of drought-dependent leaf shedding. The modified JSBACH is shown to capture the drought responses at two sites and across different regions of the basin. It is then coupled with an atmospheric model to simulate the carbon and biogeophysical feedbacks of drought under future climate. We separate the drought impacts into (a) the direct effect, resulting from drier soil and stomatal closure, which does not involve a change in canopy structure, and (b) the LAI effect, resulting from leaf shedding and involving canopy response. We show that the latter accounts for 35% of reduced land carbon uptake (9 ± 10 vs. 26 ± 7 g/m2/yr; mean ± 1 sd) and 12% of surface warming (0.09 ± 0.03 vs. 0.7 ± 0.07 K) during the late 21st century. A north-south dipole of precipitation change is found, which is largely attributable to the direct effect. The results highlight the importance of incorporating drought deciduousness of tropical rainforests in LSMs to better simulate land-atmosphere interactions in the future

A vertically discretised canopy description for ORCHIDEE (SVN r2290) and the modifications to the energy, water and carbon fluxes

Since 70% of global forests are managed and forests impact the global carbon cycle and the energy exchange with the overlying atmosphere, forest management has the potential to mitigate climate change. Yet, none of the land surface models used in Earth system models, and therefore none of today’s predictions of future climate, account for the interactions between climate and forest management. We addressed this gap in modelling capability by developing and parametrizing a version of the land surface model ORCHIDEE to simulate the biogeochemical and biophysical effects of forest management. The most significant changes between the new branch called ORCHIDEE-CAN (SVN r2290) and the trunk version of ORCHIDEE (SVN r2243) are the allometric-based allocation of carbon to leaf, root, wood, fruit and reserve pools; the transmittance, absorbance and reflectance of radiation within the canopy; and the vertical discretisation of the energy budget calculations. In addition, conceptual changes were introduced towards a better process representation for the interaction of radiation with snow, the hydraulic architecture of plants, the representation of forest management and a numerical solution for the photosynthesis formalism of Farquhar, von Caemmerer and Berry. For consistency reasons, these changes were extensively linked throughout the code. Parametrization was revisited after introducing twelve new parameter sets that represent specific tree species or genera rather than a group of often distantly related or even unrelated species, as is the case in widely used plant functional types. Performance of the new model was compared against the trunk and validated against independent spatially explicit data for basal area, tree height, canopy strucure, GPP, albedo and evapotranspiration over Europe. For all tested variables ORCHIDEE-CAN outperformed the trunk regarding its ability to reproduce large-scale spatial patterns as well as their inter-annual variability over Europe. Depending on the data stream, ORCHIDEE-CAN had a 67% to 92% chance to reproduce the spatial and temporal variability of the validation data.JRC.H.5-Land Resources Managemen

How does management affect soil C sequestration and greenhouse gas fluxes in boreal and temperate forests? : A review

Acknowledgements This review has been supported by the grant Holistic management practices, modelling and monitoring for European forest soils – HoliSoils (EU Horizon 2020 Grant Agreement No 101000289) and the Academy of Finland Fellow project (330136, B. Adamczyk). In addition to the HoliSoils consortium partners, Dr. Abramoff contributed on this study and her work was supported by the United States Department of Energy, Office of Science, Office of Biological and Environmental Research. Oak Ridge National Laboratory is managed by UT-Battelle, LLC, for the United States Department of Energy under contract DE-AC05-00OR22725.Peer reviewedPublisher PD

Generalized information theory meets human cognition: Introducing a unified framework to model uncertainty and information search

Searching for information is critical in many situations. In medicine, for instance, careful choice of a diagnostic test can help narrow down the range of plausible diseases that the patient might have. In a probabilistic framework, test selection is often modeled by assuming that people’s goal is to reduce uncertainty about possible states of the world. In cognitive science, psychology, and medical decision making, Shannon entropy is the most prominent and most widely used model to formalize probabilistic uncertainty and the reduction thereof. However, a variety of alternative entropy metrics (Hartley, Quadratic, Tsallis, Rényi, and more) are popular in the social and the natural sciences, computer science, and philosophy of science. Particular entropy measures have been predominant in particular research areas, and it is often an open issue whether these divergences emerge from different theoretical and practical goals or are merely due to historical accident. Cutting across disciplinary boundaries, we show that several entropy and entropy reduction measures arise as special cases in a unified formalism, the Sharma-Mittal framework. Using mathematical results, computer simulations, and analyses of published behavioral data, we discuss four key questions: How do various entropy models relate to each other? What insights can be obtained by considering diverse entropy models within a unified framework? What is the psychological plausibility of different entropy models? What new questions and insights for research on human information acquisition follow? Our work provides several new pathways for theoretical and empirical research, reconciling apparently conflicting approaches and empirical findings within a comprehensive and unified information-theoretic formalism

Evaluating the performance of land surface model ORCHIDEE-CAN v1.0 on water and energy flux estimation with a single- and multi-layer energy budget scheme

Canopy structure is one of the most important vegetation characteristics for land-atmosphere interactions, as it determines the energy and scalar exchanges between the land surface and the overlying air mass. In this study we evaluated the performance of a newly developed multilayer energy budget in the ORCHIDEE-CAN v1.0 land surface model (Organising Carbon and Hydrology In Dynamic Ecosystems - CANopy), which simulates canopy structure and can be coupled to an atmospheric model using an implicit coupling procedure. We aim to provide a set of accept-able parameter values for a range of forest types. Top-canopy and sub-canopy flux observations from eight sites were collected in order to conduct this evaluation. The sites crossed climate zones from temperate to boreal and the vegetation types included deciduous, evergreen broad-leaved and evergreen needle-leaved forest with a maximum leaf area index (LAI; all-sided) ranging from 3.5 to 7.0. The parametrization approach proposed in this study was based on three selected physical processes - namely the diffusion, advection, and turbulent mixing within the canopy. Short-term sub-canopy observations and long-term surface fluxes were used to calibrate the parameters in the sub-canopy radiation, turbulence, and resistance modules with an automatic tuning process. The multi-layer model was found to capture the dynamics of sub-canopy turbulence, temperature, and energy fluxes. The performance of the new multi-layer model was further compared against the existing single-layer model. Although the multi-layer model simulation results showed few or no improvements to both the nighttime energy balance and energy partitioning during winter compared with a single-layer model simulation, the increased model complexity does provide a more detailed description of the canopy micrometeorology of various forest types. The multi-layer model links to potential future environmental and ecological studies such as the assessment of in-canopy species vulnerability to climate change, the climate effects of disturbance intensities and frequencies, and the consequences of biogenic volatile organic compound (BVOC) emissions from the terrestrial ecosystem.Peer reviewe

The ‘affect tagging and consolidation’ (ATaC) model of depression vulnerability

Since the 1960’s polysomnographic sleep research has demonstrated that depressive episodes are associated with REM sleep alterations. Some of these alterations, such as increased REM sleep density, have also been observed in first-degree relatives of patients and remitted patients, suggesting that they may be vulnerability markers of major depressive disorder (MDD), rather than mere epiphenomena of the disorder. Neuroimaging studies have revealed that depression is also associated with heightened amygdala reactivity to negative emotional stimuli, which may also be a vulnerability marker for MDD. Several models have been developed to explain the respective roles of REM sleep alterations and negatively-biased amygdala activity in the pathology of MDD, however the possible interaction between these two potential risk-factors remains uncharted. This paper reviews the roles of the amygdala and REM sleep in the encoding and consolidation of negative emotional memories, respectively. We present our ‘affect tagging and consolidation’ (ATaC) model, which argues that increased REM sleep density and negatively-biased amygdala activity are two separate, genetically influenced risk-factors for depression which interact to promote the development of negative memory bias – a well-known cognitive vulnerability marker for depression. Predictions of the ATaC model may motivate research aimed at improving our understanding of sleep dependent memory consolidation in depression aetiology

Drought resistance increases from the individual to the ecosystem level in highly diverse Neotropical rainforest:A meta-analysis of leaf, tree and ecosystem responses to drought

The effects of future warming and drying on tropical forest functioning remain largely unresolved. Here, we conduct a meta-analysis of observed drought responses in Neotropical humid forests, focusing on carbon and water exchange. Measures of leaf-, tree- A nd ecosystem-scale performance were retrieved from 145 published studies conducted across 232 sites in Neotropical forests. Differentiating between seasonal and episodic drought, we find that (1) during seasonal drought the increase in atmospheric evaporative demand and a decrease in soil matric potential result in a decline in leaf water potential, stomatal conductance, leaf photosynthesis and stem diameter growth while leaf litterfall and leaf flushing increase. (2) During episodic drought, we observe a further decline in stomatal conductance, photosynthesis, stem growth and, in contrast to seasonal drought, a decline also in daily tree transpiration. Responses of ecosystem-scale processes, productivity and evapotranspiration are of a smaller magnitude and often not significant. Furthermore, we find that the magnitude and direction of a drought-induced change in photosynthesis, stomatal conductance and transpiration reported in a study is correlated to study-averaged wood density. Although wood density is often not functionally related to plant hydraulic properties, we find that it is a good proxy for hydraulic behaviour and can be used to predict leaf- A nd tree-scale responses to drought. We present new insights into the functioning of tropical forest in response to drought and present novel relationships between wood density and tropical-tree responses to drought

Does the stress tolerance of mixed grassland communities change in a future climate? A test with heavy metal stress (zinc pollution)

Will species that are sensitive/tolerant to Zn pollution still have the same sensitivity/tolerance in a future climate? To answer this question we analysed the response of constructed grassland communities to five levels of zinc (Zn) supply, ranging from 0 to 354 mg Zn kg(-1) dry soil, under a current climate and a future climate (elevated CO(2) and warming). Zn concentrations increased in roots and shoots with Zn addition but this increase did not differ between climates. Light-saturated net CO(2) assimilation rate (A(sat)) of the species, on the other hand, responded differently to Zn addition depending on climate. Still, current and future climate communities have comparable biomass responses to Zn, i.e., no change in root biomass and a 13% decrease of above-ground biomass. Provided that the different response of A(sat) in a future climate will not compromise productivity and survival on the long term, sensitivity is not altered by climate change. (C) 2011 Elsevier Ltd. All rights reserved