Colorado State University

About: Colorado State University is a education organization based out in Fort Collins, Colorado, United States. It is known for research contribution in the topics: Population & Radar. The organization has 31430 authors who have published 69040 publications receiving 2724463 citations. The organization is also known as: CSU & Colorado Agricultural College.

Iterative near-term ecological forecasting: Needs, opportunities, and challenges

Abstract: Two foundational questions about sustainability are "How are ecosystems and the services they provide going to change in the future?" and "How do human decisions affect these trajectories?" Answering these questions requires an ability to forecast ecological processes Unfortunately, most ecological forecasts focus on centennial-scale climate responses, therefore neither meeting the needs of near-term (daily to decadal) environmental decision-making nor allowing comparison of specific, quantitative predictions to new observational data, one of the strongest tests of scientific theory Near-term forecasts provide the opportunity to iteratively cycle between performing analyses and updating predictions in light of new evidence This iterative process of gaining feedback, building experience, and correcting models and methods is critical for improving forecasts Iterative, near-term forecasting will accelerate ecological research, make it more relevant to society, and inform sustainable decision-making under high uncertainty and adaptive management Here, we identify the immediate scientific and societal needs, opportunities, and challenges for iterative near-term ecological forecasting Over the past decade, data volume, variety, and accessibility have greatly increased, but challenges remain in interoperability, latency, and uncertainty quantification Similarly, ecologists have made considerable advances in applying computational, informatic, and statistical methods, but opportunities exist for improving forecast-specific theory, methods, and cyberinfrastructure Effective forecasting will also require changes in scientific training, culture, and institutions The need to start forecasting is now; the time for making ecology more predictive is here, and learning by doing is the fastest route to drive the science forward

Glyphosate resistance: state of knowledge.

Abstract: Studies of mechanisms of resistance to glyphosate have increased current understanding of herbicide resistance mechanisms. Thus far, single-codon non-synonymous mutations of EPSPS (5-enolypyruvylshikimate-3-phosphate synthase) have been rare and, relative to other herbicide mode of action target-site mutations, unconventionally weak in magnitude for resistance to glyphosate. However, it is possible that weeds will emerge with non-synonymous mutations of two codons of EPSPS to produce an enzyme endowing greater resistance to glyphosate. Today, target-gene duplication is a common glyphosate resistance mechanism and could become a fundamental process for developing any resistance trait. Based on competition and substrate selectivity studies in several species, rapid vacuole sequestration of glyphosate occurs via a transporter mechanism. Conversely, as the chloroplast requires transporters for uptake of important metabolites, transporters associated with the two plastid membranes may separately, or together, successfully block glyphosate delivery. A model based on finite glyphosate dose and limiting time required for chloroplast loading sets the stage for understanding how uniquely different mechanisms can contribute to overall glyphosate resistance.

Second-order analysis of improper complex random vectors and processes

Abstract: We present a comprehensive treatment of the second-order theory of complex random vectors and wide-sense stationary (WSS) signals. The main focus is on the improper case, in which the complementary covariance does not vanish. Accounting for the information present in the complementary covariance requires the use of widely linear transformations. Based on these, we present the eigenanalysis of complex vectors and apply it to the problem of rank reduction through principal components. We also investigate joint properties of two complex vectors by introducing canonical correlations, which paves the way for a discussion of the Wiener filter and its rank-reduced version. We link the concepts of propriety and joint propriety to eigenanalysis and canonical correlation analysis, respectively. Our treatment is extended to WSS signals. In particular, we give a result on the asymptotic distribution of eigenvalues and examine the connection between WSS, proper, and analytic signals.

Recent advances in transition metal-catalyzed sp3 C–H amination adjacent to double bonds and carbonyl groups

Abstract: Transition metal-catalyzed C–H amination at positions adjacent to double bonds and carbonyl groups is discussed in this critical review. While the focus will center on the recent developments of α-oxidative amination, some historical developments and mutually beneficial reports in the broader field of C–H amination will be discussed. C–H amination has become a viable method for the efficient installation of nitrogen atoms en route to target molecules (89 references).

Simulations of the Atmospheric General Circulation Using a Cloud-Resolving Model as a Superparameterization of Physical Processes

Abstract: Traditionally, the effects of clouds in GCMs have been represented by semiempirical parameterizations. Recently, a cloud-resolving model (CRM) was embedded into each grid column of a realistic GCM, the NCAR Community Atmosphere Model (CAM), to serve as a superparameterization (SP) of clouds. Results of the standard CAM and the SP-CAM are contrasted, both using T42 resolution (2.8° 2.8° grid), 26 vertical levels, and up to a 500-day-long simulation. The SP was based on a two-dimensional (2D) CRM with 64 grid columns and 24 levels collocated with the 24 lowest levels of CAM. In terms of the mean state, the SP-CAM produces quite reasonable geographical distributions of precipitation, precipitable water, top-ofthe-atmosphere radiative fluxes, cloud radiative forcing, and high-cloud fraction for both December– January–February and June–July–August. The most notable and persistent precipitation bias in the western Pacific, during the Northern Hemisphere summer of all the SP-CAM runs with 2D SP, seems to go away through the use of a small-domain three-dimensional (3D) SP with the same number of grid columns as the 2D SP, but arranged in an 8 8 square with identical horizontal resolution of 4 km. Two runs with the 3D SP have been carried out, with and without explicit large-scale momentum transport by convection. Interestingly, the double ITCZ feature seems to go away in the run that includes momentum transport. The SP improves the diurnal variability of nondrizzle precipitation frequency over the standard model by precipitating most frequently during late afternoon hours over the land, as observed, while the standard model maximizes its precipitation frequency around local solar noon. Over the ocean, both models precipitate most frequently in the early morning hours as observed. The SP model also reproduces the observed global distribution of the percentage of days with nondrizzle precipitation rather well. In contrast, the standard model tends to precipitate more frequently, on average by about 20%–30%. The SP model seems to improve the convective intraseasonal variability over the standard model. Preliminary results suggest that the SP produces more realistic variability of such fields as 200-mb wind and OLR, relative to the control, including the often poorly simulated Madden–Julian oscillation (MJO).