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Reconstructions of biomass burning from sediment charcoal records to improve data–model comparisons
(2015)
The location, timing, spatial extent, and frequency of wildfires are changing rapidly in many parts of the world, producing substantial impacts on ecosystems, people, and potentially climate. Paleofire records based on charcoal accumulation in sediments enable modern changes in biomass burning to be considered in their long-term context. Paleofire records also provide insights into the causes and impacts of past wildfires and emissions when analyzed in conjunction with other paleoenvironmental data and with fire models. Here we present new 1000-year and 22 000-year trends and gridded biomass burning reconstructions based on the Global Charcoal Database version 3 (GCDv3), which includes 736 charcoal records (57 more than in version 2). The new gridded reconstructions reveal the spatial patterns underlying the temporal trends in the data, allowing insights into likely controls on biomass burning at regional to global scales. In the most recent few decades, biomass burning has sharply increased in both hemispheres but especially in the north, where charcoal fluxes are now higher than at any other time during the past 22 000 years. We also discuss methodological issues relevant to data–model comparisons and identify areas for future research. Spatially gridded versions of the global data set from GCDv3 are provided to facilitate comparison with and validation of global fire simulations.
Reconstructions of biomass burning from sediment-charcoal records to improve data–model comparisons
(2016)
The location, timing, spatial extent, and frequency of wildfires are changing rapidly in many parts of the world, producing substantial impacts on ecosystems, people, and potentially climate. Paleofire records based on charcoal accumulation in sediments enable modern changes in biomass burning to be considered in their long-term context. Paleofire records also provide insights into the causes and impacts of past wildfires and emissions when analyzed in conjunction with other paleoenvironmental data and with fire models. Here we present new 1000-year and 22 000-year trends and gridded biomass burning reconstructions based on the Global Charcoal Database version 3 (GCDv3), which includes 736 charcoal records (57 more than in version 2). The new gridded reconstructions reveal the spatial patterns underlying the temporal trends in the data, allowing insights into likely controls on biomass burning at regional to global scales. In the most recent few decades, biomass burning has sharply increased in both hemispheres but especially in the north, where charcoal fluxes are now higher than at any other time during the past 22 000 years. We also discuss methodological issues relevant to data–model comparisons and identify areas for future research. Spatially gridded versions of the global data set from GCDv3 are provided to facilitate comparison with and validation of global fire simulations.
Investigators in the cognitive neurosciences have turned to Big Data to address persistent replication and reliability issues by increasing sample sizes, statistical power, and representativeness of data. While there is tremendous potential to advance science through open data sharing, these efforts unveil a host of new questions about how to integrate data arising from distinct sources and instruments. We focus on the most frequently assessed area of cognition - memory testing - and demonstrate a process for reliable data harmonization across three common measures. We aggregated raw data from 53 studies from around the world which measured at least one of three distinct verbal learning tasks, totaling N = 10,505 healthy and brain-injured individuals. A mega analysis was conducted using empirical bayes harmonization to isolate and remove site effects, followed by linear models which adjusted for common covariates. After corrections, a continuous item response theory (IRT) model estimated each individual subject’s latent verbal learning ability while accounting for item difficulties. Harmonization significantly reduced inter-site variance by 37% while preserving covariate effects. The effects of age, sex, and education on scores were found to be highly consistent across memory tests. IRT methods for equating scores across AVLTs agreed with held-out data of dually-administered tests, and these tools are made available for free online. This work demonstrates that large-scale data sharing and harmonization initiatives can offer opportunities to address reproducibility and integration challenges across the behavioral sciences.