The status and challenge of global fire modelling

This is the discussion paper version of the article. The final published version was published in Biogeosciences Vol. 13 (1), pp. 3359-3375 and is in ORE at http://hdl.handle.net/10871/22886Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, either using well-founded empirical relationships or process-based models with good predictive skill. A large variety of models exist today and it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central question underpinning the creation of the Fire Model Intercomparison Project - FireMIP, an international project to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we summarise the current state-of-the-art in fire regime modelling and model evaluation, and outline what lessons may be learned from FireMIP.Stijn Hantson and Almut Arneth acknowledge support by the EU FP7 projects BACCHUS (grant agreement no. 603445) and LUC4C (grant agreement no. 603542). This work was supported, in part, by the German Federal Ministry of Education and Research (BMBF), through the Helmholtz Association and its research programme ATMO, and the HGF Impulse and Networking fund. The MC-FIRE model development was supported by the global change research programmes of the Biological Resources Division of the US Geological Survey (CA 12681901,112-), the US Department of Energy (LWT6212306509), the US Forest Service (PNW96–5I0 9 -2-CA), and funds from the Joint Fire Science Program. I. Colin Prentice is supported by the AXA Research Fund under the Chair Programme in Biosphere and Climate Impacts, part of the Imperial College initiative Grand Challenges in Ecosystems and the Environment. Fang Li was funded by the National Natural Science Foundation (grant agreement no. 41475099 and no. 2010CB951801). Jed O. Kaplan was supported by the European Research Council (COEVOLVE 313797). Sam S. Rabin was funded by the National Science Foundation Graduate Research Fellowship, as well as by the Carbon Mitigation Initiative. Allan Spessa acknowledges funding support provided by the Open University Research Investment Fellowship scheme. FireMIP is a non-funded community initiative and participation is open to all

Conditional Knockout of NMDA Receptors in Dopamine Neurons Prevents Nicotine-Conditioned Place Preference

Nicotine from smoking tobacco produces one of the most common forms of addictive behavior and has major societal and health consequences. It is known that nicotine triggers tobacco addiction by activating nicotine acetylcholine receptors (nAChRs) in the midbrain dopaminergic reward system, primarily via the ventral tegmental area. Heterogeneity of cell populations in the region has made it difficult for pharmacology-based analyses to precisely assess the functional significance of glutamatergic inputs to dopamine neurons in nicotine addiction. By generating dopamine neuron-specific NR1 knockout mice using cre/loxP-mediated method, we demonstrate that genetic inactivation of the NMDA receptors in ventral tegmental area dopamine neurons selectively prevents nicotine-conditioned place preference. Interestingly, the mutant mice exhibit normal performances in the conditioned place aversion induced by aversive air puffs. Therefore, this selective effect on addictive drug-induced reinforcement behavior suggests that NMDA receptors in the dopamine neurons are critical for the development of nicotine addiction

Analysis of Thyroid Response Element Activity during Retinal Development

Thyroid hormone (TH) signaling components are expressed during retinal development in dynamic spatial and temporal patterns. To probe the competence of retinal cells to mount a transcriptional response to TH, reporters that included thyroid response elements (TREs) were introduced into developing retinal tissue. The TREs were placed upstream of a minimal TATA-box and two reporter genes, green fluorescent protein (GFP) and human placental alkaline phosphatase (PLAP). Six of the seven tested TREs were first tested in vitro where they were shown to drive TH-dependent expression. However, when introduced into the developing retina, the TREs reported in different cell types in both a TH-dependent and TH-independent manner, as well as revealed specific spatial patterns in their expression. The role of the known thyroid receptors (TR), TRα and TRβ, was probed using shRNAs, which were co-electroporated into the retina with the TREs. Some TREs were positively activated by TR+TH in the developing outer nuclear layer (ONL), where photoreceptors reside, as well as in the outer neuroblastic layer (ONBL) where cycling progenitor cells are located. Other TREs were actively repressed by TR+TH in cells of the ONBL. These data demonstrate that non-TRs can activate some TREs in a spatially regulated manner, whereas other TREs respond only to the known TRs, which also read out activity in a spatially regulated manner. The transcriptional response to even simple TREs provides a starting point for understanding the regulation of genes by TH, and highlights the complexity of transcriptional regulation within developing tissue

Model outputs: Quantitative assessment of fire and vegetation properties in historical simulations with fire-enabled vegetation models from the Fire Model Intercomparison Project

This dataset contains the fire model outputs of various variables used in the initial FireMIP benchmarking paper.This dataset contains the fire model outputs of various variables used in the initial FireMIP benchmarking paper.