Colorado Native Plant Society Newsletter, Vol. 2 No. 4, July-August 1978

The Colorado Native Plant Society Newsletter will be published on a bimonthly basis. The contents will consist primarily of a calendar of events, notes of interest, editorials, listings of new members and conservation news. Until there is a Society journal, the Newsletter will include short articles also. The deadline for the Newsletter is one month prior to its release.https://epublications.regis.edu/aquilegia/1009/thumbnail.jp

Simulating the Biogeochemical and Biogeophysical Impacts of Transient Land Cover Change and Wood Harvest in the Community Climate System Model (CCSM4) from 1850 to 2100

This is the publisher's version, also available electronically from http://journals.ametsoc.org/doi/abs/10.1175/JCLI-D-11-00256.1.To assess the climate impacts of historical and projected land cover change in the Community Climate System Model, version 4 (CCSM4), new time series of transient Community Land Model, version 4 (CLM4) plant functional type (PFT) and wood harvest parameters have been developed. The new parameters capture the dynamics of the Coupled Model Intercomparison Project phase 5 (CMIP5) land cover change and wood harvest trajectories for the historical period from 1850 to 2005 and for the four representative concentration pathway (RCP) scenarios from 2006 to 2100. Analysis of the biogeochemical impacts of land cover change in CCSM4 reveals that the model produced a historical cumulative land use flux of 127.7 PgC from 1850 to 2005, which is in general agreement with other global estimates of 156 PgC for the same period. The biogeophysical impacts of the transient land cover change parameters were cooling of the near-surface atmosphere over land by −0.1°C, through increased surface albedo and reduced shortwave radiation absorption. When combined with other transient climate forcings, the higher albedo from land cover change was counteracted by decreasing snow albedo from black carbon deposition and high-latitude warming. The future CCSM4 RCP simulations showed that the CLM4 transient PFT parameters can be used to represent a wide range of land cover change scenarios. In the reforestation scenario of RCP 4.5, CCSM4 simulated a drawdown of 67.3 PgC from the atmosphere into the terrestrial ecosystem and product pools. By contrast the RCP 8.5 scenario with deforestation and high wood harvest resulted in the release of 30.3 PgC currently stored in the ecosystem

Fire dynamics during the 20th century simulated by the Community Land Model

Fire is an integral Earth System process that interacts with climate in multiple ways. Here we assessed the parametrization of fires in the Community Land Model (CLM-CN) and improved the ability of the model to reproduce contemporary global patterns of burned areas and fire emissions. In addition to wildfires we extended CLM-CN to account for fires related to deforestation. We compared contemporary fire carbon emissions predicted by the model to satellite-based estimates in terms of magnitude and spatial extent as well as interannual and seasonal variability. Long-term trends during the 20th century were compared with historical estimates. Overall we found the best agreement between simulation and observations for the fire parametrization based on the work by Arora and Boer (2005). We obtained substantial improvement when we explicitly considered human caused ignition and fire suppression as a function of population density. Simulated fire carbon emissions ranged between 2.0 and 2.4 Pg C/year for the period 1997–2004. Regionally the simulations had a low bias over Africa and a high bias over South America when compared to satellite-based products. The net terrestrial carbon source due to land use change for the 1990s was 1.2 Pg C/year with 11% stemming from deforestation fires. During 2000–2004 this flux decreased to 0.85 Pg C/year with a similar relative contribution from deforestation fires. Between 1900 and 1960 we predicted a slight downward trend in global fire emissions caused by reduced fuels as a consequence of wood harvesting and also by increases in fire suppression. The model predicted an upward trend during the last three decades of the 20th century as a result of climate variations and large burning events associated with ENSO-induced drought conditions

Carbon-nitrogen interactions regulate climate-carbon cycle feedbacks : results from an atmosphere-ocean general circulation model

© 2009 The Authors. This article is distributed under the terms of the Creative Commons Attribution 3.0 License. The definitive version was published in Biogeosciences 6 (2009): 2099-2120, doi:10.5194/bg-6-2099-2009Inclusion of fundamental ecological interactions between carbon and nitrogen cycles in the land component of an atmosphere-ocean general circulation model (AOGCM) leads to decreased carbon uptake associated with CO2 fertilization, and increased carbon uptake associated with warming of the climate system. The balance of these two opposing effects is to reduce the fraction of anthropogenic CO2 predicted to be sequestered in land ecosystems. The primary mechanism responsible for increased land carbon storage under radiatively forced climate change is shown to be fertilization of plant growth by increased mineralization of nitrogen directly associated with increased decomposition of soil organic matter under a warming climate, which in this particular model results in a negative gain for the climate-carbon feedback. Estimates for the land and ocean sink fractions of recent anthropogenic emissions are individually within the range of observational estimates, but the combined land plus ocean sink fractions produce an airborne fraction which is too high compared to observations. This bias is likely due in part to an underestimation of the ocean sink fraction. Our results show a significant growth in the airborne fraction of anthropogenic CO2 emissions over the coming century, attributable in part to a steady decline in the ocean sink fraction. Comparison to experimental studies on the fate of radio-labeled nitrogen tracers in temperate forests indicates that the model representation of competition between plants and microbes for new mineral nitrogen resources is reasonable. Our results suggest a weaker dependence of net land carbon flux on soil moisture changes in tropical regions, and a stronger positive growth response to warming in those regions, than predicted by a similar AOGCM implemented without land carbon-nitrogen interactions. We expect that the between-model uncertainty in predictions of future atmospheric CO2 concentration and associated anthropogenic climate change will be reduced as additional climate models introduce carbon-nitrogen cycle interactions in their land components.This work was supported in part by NASA Earth Science Enterprise, Terrestrial Ecology Program, grant #W19,953 to P. E. Thornton. Support was provided by the National Center for Atmospheric Research (NCAR) through the NCAR Community Climate System Modeling program, and through the NCAR Biogeosciences program. Additional support was provided by the US Department of Energy, Office of Science, Office of Biological and Environmental Research. I. Fung, S. Doney, N. Mahowald, and J. Randerson acknowledge support from National Science Foundation, Atmospheric Sciences Division, through the Carbon and Water Initiative

Federated Benchmarking of Medical Artificial Intelligence With MedPerf

Medical artificial intelligence (AI) has tremendous potential to advance healthcare by supporting and contributing to the evidence-based practice of medicine, personalizing patient treatment, reducing costs, and improving both healthcare provider and patient experience. Unlocking this potential requires systematic, quantitative evaluation of the performance of medical AI models on large-scale, heterogeneous data capturing diverse patient populations. Here, to meet this need, we introduce MedPerf, an open platform for benchmarking AI models in the medical domain. MedPerf focuses on enabling federated evaluation of AI models, by securely distributing them to different facilities, such as healthcare organizations. This process of bringing the model to the data empowers each facility to assess and verify the performance of AI models in an efficient and human-supervised process, while prioritizing privacy. We describe the current challenges healthcare and AI communities face, the need for an open platform, the design philosophy of MedPerf, its current implementation status and real-world deployment, our roadmap and, importantly, the use of MedPerf with multiple international institutions within cloud-based technology and on-premises scenarios. Finally, we welcome new contributions by researchers and organizations to further strengthen MedPerf as an open benchmarking platform

MedPerf : Open Benchmarking Platform for Medical Artificial Intelligence using Federated Evaluation

Medical AI has tremendous potential to advance healthcare by supporting the evidence-based practice of medicine, personalizing patient treatment, reducing costs, and improving provider and patient experience. We argue that unlocking this potential requires a systematic way to measure the performance of medical AI models on large-scale heterogeneous data. To meet this need, we are building MedPerf, an open framework for benchmarking machine learning in the medical domain. MedPerf will enable federated evaluation in which models are securely distributed to different facilities for evaluation, thereby empowering healthcare organizations to assess and verify the performance of AI models in an efficient and human-supervised process, while prioritizing privacy. We describe the current challenges healthcare and AI communities face, the need for an open platform, the design philosophy of MedPerf, its current implementation status, and our roadmap. We call for researchers and organizations to join us in creating the MedPerf open benchmarking platform

Identification of Novel Genetic Loci Associated with Thyroid Peroxidase Antibodies and Clinical Thyroid Disease

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