167,845 research outputs found

    Dynamics of Tipping Cascades on Complex Networks

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    Tipping points occur in diverse systems in various disciplines such as ecology, climate science, economy or engineering. Tipping points are critical thresholds in system parameters or state variables at which a tiny perturbation can lead to a qualitative change of the system. Many systems with tipping points can be modeled as networks of coupled multistable subsystems, e.g. coupled patches of vegetation, connected lakes, interacting climate tipping elements or multiscale infrastructure systems. In such networks, tipping events in one subsystem are able to induce tipping cascades via domino effects. Here, we investigate the effects of network topology on the occurrence of such cascades. Numerical cascade simulations with a conceptual dynamical model for tipping points are conducted on Erd\H{o}s-R\'enyi, Watts-Strogatz and Barab\'asi-Albert networks. Additionally, we generate more realistic networks using data from moisture-recycling simulations of the Amazon rainforest and compare the results to those obtained for the model networks. We furthermore use a directed configuration model and a stochastic block model which preserve certain topological properties of the Amazon network to understand which of these properties are responsible for its increased vulnerability. We find that clustering and spatial organization increase the vulnerability of networks and can lead to tipping of the whole network. These results could be useful to evaluate which systems are vulnerable or robust due to their network topology and might help to design or manage systems accordingly.Comment: 22 pages, 12 figure

    Agronomic evaluation of biofortified beans in Antioquia producers’ farms

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    The objective of this research was to evaluate genotypes of iron- and zinc-enriched common beans during breeding in producers’ farms. Yield, disease reaction, and commercial grain characteristics were evaluated to achieve this objective. In three locations of Antioquia (Rionegro, Jardín, and Betulia), seven bush beans and eight climbing bean genotypes were planted. A randomized complete block design with four replications was used in each location. There were significant differences between the bush and climbing bean genotypes that were evaluated. The highest yields, in all locations, were for the biofortified bean NUA 45 and the control variety Uribe Rosado, followed by the CAL 96 and AFR 612 genotypes. For the climbing beans, the highest yields were found in the G2333 genotypes, being this treatment equal to the MAC 27, a bean that is adapted to mid-climate and altitudes. The MAC 27 material is presented as a promising variety because of its high yields and tolerance to diseases, mainly anthracnose

    Recommendations of Alternative System Plans and Transmission Corridors for the Dickey/Lincoln School Hydroelectric Project

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    The regional scope of this study (a three state area of approximately 33,000 square miles) necessitated an initial investigation to determine what data was available. Known and potential sources of data were identified through the use of the Environmental Data Reconnaissance Report* prepared by Comitta Frederick Associates for the United States Depart-ment of the Interior in March 1976. The collected data was then analyzed for its accuracy, reliability, mappability and compatibility with the scope of this study

    Signal detection in global mean temperatures after "Paris": An uncertainty and sensitivity analysis

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    In December 2015, 195 countries agreed in Paris to hold the increase in global mean surface temperature (GMST) well below 2.0 °C above pre-industrial levels and to pursue efforts to limit the temperature increase to 1.5 °C. Since large financial flows will be needed to keep GMSTs below these targets, it is important to know how GMST has progressed since pre-industrial times. However, the Paris Agreement is not conclusive as regards methods to calculate it. Should trend progression be deduced from GCM simulations or from instrumental records by (statistical) trend methods? Which simulations or GMST datasets should be chosen, and which trend models? What is pre-industrial and, finally, are the Paris targets formulated for total warming, originating from both natural and anthropogenic forcing, or do they refer to anthropogenic warming only? To find answers to these questions we performed an uncertainty and sensitivity analysis where datasets and model choices have been varied. For all cases we evaluated trend progression along with uncertainty information. To do so, we analysed four trend approaches and applied these to the five leading observational GMST products. We find GMST progression to be largely independent of various trend model approaches. However, GMST progression is significantly influenced by the choice of GMST datasets. Uncertainties due to natural variability are largest in size. As a parallel path, we calculated GMST progression from an ensemble of 42 GCM simulations. Mean progression derived from GCM-based GMSTs appears to lie in the range of trend–dataset combinations. A difference between both approaches appears to be the width of uncertainty bands: GCM simulations show a much wider spread. Finally, we discuss various choices for pre-industrial baselines and the role of warming definitions. Based on these findings we propose an estimate for signal progression in GMSTs since pre-industrial

    Growing South Dakota (Summer 2023)

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    3 SDSU Little International Celebrates 100 years of Tradition7 2023 CAFES Celebration of Faculty Excellence11 South Dakota Agricultural Experiment Station Locations and Research Initiatives15 Every Acre Counts16 Undergraduate Research19 Tanner Sloan: South Dakota State Wrestler & Animal Science Student Takes Home NCAA Division I & U23 World Silver Medals21 2023 CAFES Outstanding Seniors23 Robert Streeter: International Advocate for Wildlife Conservation25 Collegiate Cattlemen\u27s Club27 Jim and Melody Mielke: Lifelong Donors Contribute to Agriculture in More Ways than One29 Jackrabbits Now and Thenhttps://openprairie.sdstate.edu/growingsd/1034/thumbnail.jp

    Growing South Dakota (Spring 2021)

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    This issue contains the 2020 SDSU Extension Annual Report and 2020 South Dakota Agricultural Experiment Station Annual Report.[Page] 3 COVID-19 Impacts[Page] 9 Precision Agriculture: What\u27s New[Page] 13 Featured Research[Page] 19 SDSU Extension 2020 Annual Report[Page] 45 South Dakota Agricultural Experiment Station 2020 Annual Report[Page] 55 CAFES News and Updates[Page] 67 Alumni News[Page] 75 Alumni Gone Down in History[Page] 81 Jackrabbits Now and Then: A Current Student and Alumni Q&Ahttps://openprairie.sdstate.edu/growingsd/1031/thumbnail.jp

    AS-685-09 Resolution on Proposal to Establish College of Agriculture, Food and Environmental Sciences (CAFES) Center for Sustainability

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    Endorses the proposal to establish a CAFES Center for Sustainability