Global monthly averaged CO 2 fluxes recovered using a geostatistical inverse modeling approach: 1. Results using atmospheric measurements

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/94622/1/jgrd14633.pd

The utility of continuous atmospheric measurements for identifying biospheric CO 2 flux variability

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95026/1/jgrd16859.pd

Global monthly averaged CO 2 fluxes recovered using a geostatistical inverse modeling approach: 2. Results including auxiliary environmental data

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/94853/1/jgrd14632.pd

Data from: An assessment of wheat yield sensitivity and breeding gains in hot environments

Genetic improvements in heat tolerance of wheat provide a potential adaptation response to long-term warming trends, and may also boost yields in wheat-growing areas already subject to heat stress. Yet there have been few assessments of recent progress in breeding wheat for hot environments. Here, data from 25 years of wheat trials in 76 countries from the International Maize and Wheat Improvement Center (CIMMYT) are used to empirically model the response of wheat to environmental variation and assess the genetic gains over time in different environments and for different breeding strategies. Wheat yields exhibited the most sensitivity to warming during the grain-filling stage, typically the hottest part of the season. Sites with high vapour pressure deficit (VPD) exhibited a less negative response to temperatures during this period, probably associated with increased transpirational cooling. Genetic improvements were assessed by using the empirical model to correct observed yield growth for changes in environmental conditions and management over time. These ‘climate-corrected’ yield trends showed that most of the genetic gains in the high-yield-potential Elite Spring Wheat Yield Trial (ESWYT) were made at cooler temperatures, close to the physiological optimum, with no evidence for genetic gains at the hottest temperatures. In contrast, the Semi-Arid Wheat Yield Trial (SAWYT), a lower-yielding nursery targeted at maintaining yields under stressed conditions, showed the strongest genetic gains at the hottest temperatures. These results imply that targeted breeding efforts help us to ensure progress in building heat tolerance, and that intensified (and possibly new) approaches are needed to improve the yield potential of wheat in hot environments in order to maintain global food security in a warmer climate

regression.dat_nurseries_ADW2.Rdat

This R data frame contains 1353 rows corresponding to the international trials in the CIMMYT database used in this study. The column names should be self-descriptive, and contain all the predictors used for this regression analysis

Sustainable Development Opportunities at the Climate, Land, Energy and Water Nexus in Nicaragua

There are strong interconnections between the practices needed to sustainably manage land, energy, and water resources, which become even more pronounced when the many implications of climate change are taken into consideration. An exploration of these resource sectors in Nicaragua, a country at high risk from climate change, shows how their linkages directly impact the opportunities for development available to a rapidly growing economy. In particular, these linkages may shape solutions for sustainably managing agriculture,confronting water scarcity, and promoting local energy resources, which together can provide independence from global market volatility. Here we synthesize the state of climate, land,energy, and water issues in Nicaragua and highlight the potential for integrated resource planning in the country. We focus on three ongoing, sustainable development initiatives as case studies: rain-water harvesting in the Pacific Mountain Corridor, community-scale breadfruit processing in the Caribbean Coast region, and national bioenergy production using sugarcane bagasse.Fil: Gourdji, Sharon. University of Stanford; Estados UnidosFil: Craig, Mathias. Blue Energy; Estados UnidosFil: Shirley, Rebekah. University of California at Berkeley; Estados UnidosFil: Ponce de Leon Barido, Diego. University of California at Berkeley; Estados UnidosFil: Campos, Eleonora. Instituto Nacional de Tecnología Agropecuaria; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Giraldo, Mauricio. Universidad Pontificia Bolivariana; ColombiaFil: Lopez, Mauricio. Pontificia Universidad Católica de Chile; ChileFil: Pereira de Lucena, Andre F.. Universidade Federal do Rio de Janeiro; BrasilFil: Luger, Martina. Horizont3000; NicaraguaFil: Kammen, Daniel M.. University of California at Berkeley; Estados Unido

A Modified vegetation photosynthesis and respiration model (VPRM) for the Eastern USA and Canada, evaluated with comparison to atmospheric observations and other biospheric models

Atmospheric CO2 measurements from a dense surface network can help to evaluate terrestrial biosphere model (TBM) simulations of Net Ecosystem Exchange (NEE) with two key benefits. First, gridded CO2 flux estimates can be evaluated over regional scales, not possible using flux tower observations at discrete locations for model evaluation. Second, TBM ability to explain atmospheric CO2 fluctuations due to the biosphere can be directly tested, an important objective for anthropogenic emissions monitoring using atmospheric observations. Here, we customize the Vegetation Photosynthesis and Respiration Model (VPRM) for an eastern North American domain with strong biological activity upwind of urban areas. Parameters are optimized using flux tower observations from a historical database with sites in (and near) the domain. In addition, the respiration model (originally a linear function of temperature) is modified to account for impacts of changing foliage, non-linear temperature, and water stress. Flux estimates from VPRM, the Carnegie-Ames-Stanford Approach (CASA) model and the Simple Biosphere Model v4 (SiB4), are convolved with footprints from atmospheric transport models for evaluation with CO2 observations at 21 towers in the domain, with roughly half of the towers used here for the first time. Results show that the new respiration model in VPRM helps to correct a growing season sink bias in the atmosphere associated with underestimated summertime respiration using the original model with annual parameters. The new VPRM also better explains fine-scale atmospheric CO2 variability compared to other TBMs, due to higher resolution diagnostic phenology, the new respiration model, domain-specific parameters, and high-quality input data sets

The Impact of COVID‐19 on CO 2

Responses to COVID‐19 have resulted in unintended reductions of city‐scale carbon dioxide (CO(2)) emissions. Here, we detect and estimate decreases in CO(2) emissions in Los Angeles and Washington DC/Baltimore during March and April 2020. We present three lines of evidence using methods that have increasing model dependency, including an inverse model to estimate relative emissions changes in 2020 compared to 2018 and 2019. The March decrease (25%) in Washington DC/Baltimore is largely supported by a drop in natural gas consumption associated with a warm spring whereas the decrease in April (33%) correlates with changes in gasoline fuel sales. In contrast, only a fraction of the March (17%) and April (34%) reduction in Los Angeles is explained by traffic declines. Methods and measurements used herein highlight the advantages of atmospheric CO(2) observations for providing timely insights into rapidly changing emissions patterns that can empower cities to course‐correct CO(2) reduction activities efficiently