1. ABOUT THE DATASET ------------ Title: Changes in climate trends and velocities, forest loss and population density between 2001-2018 in India's districts Creator(s): Alice Haughan[1,2], Dr Deepa Senapathi [1] Organisation(s): 1. University of Reading. 2. Institute of Zoology, Zoological Society of London Rights-holder(s): Alice Haughan and University of Reading Publication Year: 2022 Description: This dataset provides information on the average climate change and forest loss over time for 577 districts in India between 2001-2018. The dataset has numerous climate variables that provide information on how temporal trends and velocities of temperature and precipitation have changed over time. This climate data was created based on raw data from the Climate Research Unit (https://crudata.uea.ac.uk/cru/data/hrg/). The trends are shown for both annual and seasonal data. Further to this, there is data on the amount of forest loss between 2001-2018 derived from the Hansen Global Forest Change Dataset (https://storage.googleapis.com/earthenginepartners-hansen/GFC-2020-v1.8/download.html). Thirdly, there is data on the change in population density over time derived from SEDAC CIESIN data (https://sedac.ciesin.columbia.edu/data/collection/gpw-v4). This full dataset can be used to compare changes in climate and population density in India's districts with forest loss. Cite as: A. Haughan and D. Senapathi (2022): Changes in climate trends and velocities, forest loss and population density between 2001-2018 in India's districts. University of Reading. Dataset. https://doi.org/10.17864/1947.000364 Related publication: Haughan et al. (2022). Determining the role of climate change in India's past forest loss. Global Change Biology (Accepted). This dataset was created by Alice Haughan and Deepa Senapathi however some contributions to the format, and calculations of climate velocity, were provided by Dr Nathalie Pettorelli (Zoological Society of London) and Professor Simon Potts (University of Reading). 2. TERMS OF USE ----------------- Copyright 2022 Alice Haughan and University of Reading. This dataset is licensed under a Creative Commons Attribution 4.0 International Licence: https://creativecommons.org/licenses/by/4.0/ 3. PROJECT AND FUNDING INFORMATION ------------ Title: Determining the role of climate change in India's past forest loss Dates: September 2017 - March 2022 Funding organisation: This research was funded by NERC QMEE CDT studentship 1937679 4. CONTENTS ------------ File listing HaughanGCB2022.csv Original data sources: Climate data was collected from global raster datasets of total monthly precipitation (mm) and monthly mean temperature (oC) from the Climate Research Unit (CRU TS v. 4.03) were obtained at 0.5 x 0.5 degree resolution (~112km2) Forest data was collected from Hansen Global Forest Change v1.6 dataset (GFC) (Hansen et al., 2013) for the period 2001-2018 at a spatial resolution of ~30m, within the Google Earth Engine interface (Gorelick, et al., 2017) Population density (people per km²) for the years 2000 and 2020 was obtained from SEDAC’s GPWv4.11 dataset at a spatial resolution of 30 arc-seconds (~1km2 at the equator) The data from the original sources above was averaged to provide a value for each of the political districts in India using QGIS (version 3) and R (version 4.03) In addition, climate velocity variables were created from the CRU data. Gradient-based climate velocity was calculated in R using the gVoCC package and the integrated functions; SpatGrad and TempTrend following the methodology for local climate velocity outlined in Garcìa Molinos et al., (2019) and based off the original calculation by Loarie et al., (2009) - Garcìa Molinos, J. et al. (2019). VoCC: An r package for calculating the velocity of climate change and related climatic metrics. Methods in Ecology and Evolution, 10(12), pp, 2195-2202. doi: 10.1111/2041-210x.13295 - Gorelick, N. et al. (2017). Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote Sensing of Environment, 202, pp. 18-27 - Hansen, M. C. et al. (2013). High-resolution global maps of 21st-century forest cover change. Science, 342(6160), pp. 850–853. doi: 10.1126/science.1244693 - Loarie, S. R. et al. (2009). The velocity of climate change. Nature, 462(7276), pp. 1052–1055. doi: 10.1038/nature08649 The dataset contains: - 30 variables - 577 cases/rows Each row (data point) in this dataset is an average for the political boundary of 'district' (unless stated otherwise). There are 577 districts included in this dataset and hence 577 datapoints. This is a list of the variables included and an explanation of the data included in them: State: The political boundary of State that the subsequent data corresponds to District: The political boundary of District that the subsequent data corresponds to x: The central longitude point of the district y: The central latitude of the district Monsoon: The homogenous monsoon region that the data point belongs to out of six monsoon regions outlined by the Indian Institute of Tropical Meteorology (www.tropmet.res.in) coverkm: The total area of forest cover in km2 for that district in the year 2001 losskm: The total area of forest lost between 2001 and 2018, in km2 percentloss: The percentage of 2001 forest cover that was lost between 2001 and 2018 PDCNmean: The change in human population density between 2000 and 2015 (not used in the study), units are people per km2 _0020mean: The change in human population density between 2000 and 2020 (used in the study), units are people per km2 _pMovelmea: The mean precipitation velocity for the district during the Monsoon season (km/yr) _pPMOvelme: The mean precipitation velocity for the district during the Post Monsoon season (km/yr) _pPRMOvelm: The mean precipitation velocity for the district during the Pre Monsoon season (km/yr) _pWINvelme: The mean precipitation velocity for the district during the Winter season (km/yr) _pMOttmean: The mean precipitation temporal trend for the district during the Monsoon season (mm/yr) _pPMOttmea: The mean precipitation temporal trend for the district during the Post Monsoon season (mm/yr) _pPRMOttme: The mean precipitation temporal trend for the district during the Pre Monsoon season (mm/yr) _pWINttmea: The mean precipitation temporal trend for the district during the Winter season (mm/yr) _tMOvelmea: The mean temperature velocity for the district during the Monsoon season (km/yr) _tPMOvelme: The mean temperature velocity for the district during the Post Monsoon season (km/yr) _tPRMOvelm: The mean temperature velocity for the district during the Pre Monsoon season (km/yr) _tWINvelme: The mean temperature velocity for the district during the Winter season (km/yr) _tMOttmean: The mean temperature temporal trend for the district during the Monsoon season (degrees C/yr) _tPMOttmea: The mean temperature temporal trend for the district during the Post Monsoon season (degrees C/yr) _tPRMOttme: The mean temperature temporal trend for the district during the Pre Monsoon season (degrees C/yr) _tWINttmea: The mean temperature temporal trend for the district during the Winter season (degrees C/yr) tANvelmean: The mean temperature velocity for the district during the year (km/yr) pANNvelmea: The mean precipitation velocity for the district during the year (km/yr) tANttmean: The mean temperature temporal trend for the district during the year (degrees C/yr) pANttmean: The mean precipitation temporal trend for the district during the year (mm/yr)