1,721,016 research outputs found
CARDAMOM driving data and C-cycle model outputs to accompany "Scale-variance in the carbon dynamics of fragmented, mixed-use landscapes estimated using Model-Data Fusion"
Full text linkThis archive contains the driving data and selected model outputs to accompany the manuscript: Milodowski, D.T., Smallman, T.L., Williams, M. (in submission), "Scale-variance in the carbon dynamics of fragmented, mixed-use landscapes estimated using Model-Data Fusion", Biogeosciences Discussions. Many terrestrial landscapes are heterogeneous. Mixed land cover and land-use generate a complex mosaic of fragmented ecosystems at fine spatial resolutions with contrasting ecosystem stocks, traits and processes, each differently sensitive to environmental and human factors. Representing spatial complexity within terrestrial ecosystem models is a key challenge for understanding regional carbon dynamics, their sensitivity to environmental gradients, and their resilience in the face of climate change. Heterogeneity underpins this challenge due to the trade-off between the fidelity of ecosystem representation within modelling frameworks and the computational capacity required for fine-scale model calibration and simulation. We directly address this challenge by quantifying the sensitivity of simulated carbon fluxes in a mixed-use landscape in the UK to the spatial resolution of the model analysis.The archive contains two zip files containing: (i) the observations and driving data assimilated into CARDAMOM; and (ii) a selection of model output, including the carbon (C) stocks for each DALEC pool, and a compilation of key C fluxes. Data and model output are stored as netcdf files. The xarray package (https://docs.xarray.dev/en/stable/index.html) provides a convenient starting point for using netcdf files within python environments. More details are provided in the document "Milodowski_etal_dataset_description.pdf"
See also the document: "Milodowski_etal_dataset_description.pdf
SUPERSEDED - CARDAMOM driving data and C-cycle model outputs to accompany "Resolving scale-variance in the carbon dynamics of fragmented, mixed-use landscapes estimated using Model-Data Fusion"
No full text'## This item has been replaced by the one which can be found at https://datashare.ed.ac.uk/handle/10283/4849 - https://doi.org/10.7488/ds/3843 ##' This archive contains the driving data and selected model outputs to accompany the manuscript: "Resolving scale-variance in the carbon dynamics of fragmented, mixed-use landscapes estimated using Model-Data Fusion", submitted to Biogeosciences Discussions.
The archive contains two zip files containing: (i) the observations and driving data assimilated into CARDAMOM; and (ii) a selection of model output, including the carbon (C) stocks for each DALEC pool, and a compilation of key C fluxes. Data and model output are stored as netcdf files. The xarray package (https://docs.xarray.dev/en/stable/index.html) provides a convenient starting point for using netcdf files within python environments. More details are provided in the document "Milodowski_etal_dataset_description.pdf"The contents are described in the document: "Milodowski_etal_dataset_description.pdf
Systemic Carbon Cycle Analyses for the Southern African Woodlands ecoregion from 2006-2017
Full text linkThis dataset contains systemic carbon (C) cycle analyses for the Southern African Woodlands ecoregion from 2006-2017, mapped at 0.5 degree spatial resolution and monthly temporal resolution. There are five netcdf files: DRIVERS_OBS_2006_2017.nc : This file contains the environmental drivers, the assimilated observations, and their uncertainties; PARS_2006_2017.nc : This file contains maps of the parameter ensembles for the DALEC.4 ecosystem C cycle model, as retrieved by the Bayesian calibration; CFLUX_2006_2017.nc : This file contains the gross and net C fluxes for all C fluxes simulated by DALEC.4 at monthly temporal resolution; CSTOCK_2006_2017.nc : This file contains the C stocks in the live and dead organic matter pools simulated by DALEC.4 at monthly temporal resolution; NPP_MRT_2006_2017.nc : This file contains the monthly Net Primary Productivity (NPP), the monthly NPP allocation to different live C pools, the fractional NPP allocation to different live C pools, and the residence times for the live and dead organic matter C pools. We also include a readme file describing the datasets in more detail, alongside a set of python scripts used to generate the diagnostic analyses described in the manuscript. This dataset was produced using the CARDAMOM model-data fusion framework, and accompanies the manuscript: Williams, M., Milodowski, D. T., Smallman, T. L., Dexter, K. G., Hegerl, G. C., McNicol, I. M., O'Sullivan, M., Roesch, C. M., Ryan, C. M., Sitch, S., and Valade, A.: Precipitation–fire functional interactions control biomass stocks and carbon exchanges across the world's largest savanna, Biogeosciences, 22, 1597–1614,https://doi.org/10.5194/bg-22-1597-2025
A hybrid model for seasonal forecast of Indonesian fire risk
No full textDocumentation for the dataset is provided in the README file. List of files: 1. Readme.txt 2. A hybrid model code in the NCL language (seasonalforecasting.ncl.txt) 3. Equatorial Asian monthly total burned area (ba_eqa.data) 4. Sea Surface Temperature (SST) prediction data (model_aug_l1to3.data, model_sep_l1to3.data, model_oct_l1to3.data) 5. Sea Surface Temperature (SST) prediction data (model_aug_l1to3.txt, model_sep_l1to3.txt, model_oct_l1to3.txt)Kim, Jin-Soo; Milodowski, David; Williams, Mathew. (2020). A hybrid model for seasonal forecast of Indonesian fire risk , [dataset]. University of Edinburgh. https://doi.org/10.7488/ds/2781
CARDAMOM driving data and C-cycle model outputs to accompany "Resolving scale-variance in the carbon dynamics of fragmented, mixed-use landscapes estimated using Model-Data Fusion"
No full textThis archive contains the driving data and selected model outputs to accompany the manuscript: "Resolving scale-variance in the carbon dynamics of fragmented, mixed-use landscapes estimated using Model-Data Fusion", submitted to Biogeosciences Discussions. The archive contains two zip files containing: (i) the observations and driving data assimilated into CARDAMOM; and (ii) a selection of model output, including the carbon (C) stocks for each DALEC pool, and a compilation of key C fluxes. Data and model output are stored as netcdf files. The xarray package (https://docs.xarray.dev/en/stable/index.html) provides a convenient starting point for using netcdf files within python environments. More details are provided in the document "Milodowski_etal_dataset_description.pdf"Milodowski, David Thomas; Smallman, Thomas Luke; Williams, Mathew. (2022). CARDAMOM driving data and C-cycle model outputs to accompany "Resolving scale-variance in the carbon dynamics of fragmented, mixed-use landscapes estimated using Model-Data Fusion", 2014-2019 [dataset]. Global Change Institute. School of GeoSciences. University of Edinburgh. https://doi.org/10.7488/ds/3843
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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