Ecological Archives A025-127-A1

Volker C. Radeloff, John W. Williams, Brooke L. Bateman, Kevin D. Burke, Sarah K. Carter, Evan S. Childress, Kara J. Cromwell, Claudio Gratton, Andrew O. Hasley, Benjamin M. Kraemer, Alexander W. Latzka, Erika Marin-Spiotta, Curt D. Meine, Samuel E. Munoz, Thomas M. Neeson, Anna M. Pidgeon, Adena R. Rissman, Ricardo J. Rivera, Laura M. Szymanski, and Jacob Usinowicz. 2015. The rise of novelty in ecosystems. Ecological Applications 25:20512068.

Appendix A. Global assessment of novel environments: data and methods.

Human Demographics Data

The demographics data came from two sources: (1) Historic (AD 1900) and current (AD 2000) grids of population count from the History of the Global Environment (HYDE v. 3.1; Klein Goldewijk et al., 2011); (2) Projected (AD 2025) population counts from the Gridded Population of the World (GPW v.3) produced by the Columbia University center for International Earth Science Information Network (CIESIN) formed the basis of our AD 2050 population grid by adding the population growth projected by the United Nations (2013) under medium fertility conditions to cells with > 1 million inhabitants.

Biogeochemistry Data

The biogeochemistry data were accessed through the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC) for Biogeochemical Dynamics (F. J. Dentener, 2006). We used the data granules containing global coverage of N deposition for three time periods. The AD 1860 data were used for the AD 1900 baseline, the AD 1993 data for the AD 2000 time period, and the AD 2050 simulation for the future (AD 2050) projection.

The original data were available in 5.0 degree by 3.75 degree (x,y) spatial resolution, which we downscaled mean values to 0.5 by 0.5 degree (x,y) spatial resolution, and smoothed using a low-pass filter.

Climate Data

For the AD 1900 baseline climate data, we obtained global temperature and precipitation data for each month between AD 1900 and AD 2010 (0.5 degree resolution; ~50 km) from the University of Delaware Center for Climatic Research Global Climate Resource Pages ( Within each year, we calculated the mean of the monthly (January-December) average temperatures (°C; Willmott and Matsuura 2012a) and the sum of the monthly total precipitation (mm; Willmott and Matsuura 2012b) to obtain average temperature and total precipitation per year, respectively. We then calculated the long-term climate averages for annual temperature and precipitation for AD 1900 to AD 1930. We used these 30-year temperature and precipitation variables for the AD 1900 climate data. We completed all data processing in R version 2.15.1 (R 2012).

We created two versions of the current climate dataset, to ensure consistency within the current-to-historic and future-to-current novelty analyses. For the current-to-historic analyses, we used climate data from AD 1971 to AD 2000 from the University of Delaware, following the methods described above.

For the current-to-future analyses, we obtained global averages of annual temperature and precipitation (10 minute resolution) for the time periods of 1950–2000 (2000s) and 2041–2060 (2050) from the WorldClim global climate data, version 1.4 (; Hijmans et al. 2005). For temperature and precipitation we used the variables annual mean temperature (°C *10) and annual precipitation (mm), respectively, dividing the temperature data by 10 to rescale to °C. We obtained future climate data for the CMIP5 Representative Concentration Pathways 6.0 for 12 General Circulation Models (GCMs; BCC-CSM1-1, CCSM4, GFDL-ESM2G, GISS-E2-R, HadGEM2-AO, HadGEM2-ES, IPSL-CM5A-LR, MIROC-ESM-CHEM, MIROC-ESM, MIROC5, MRI-CGCM3, and NorESM1-M). We used the ensemble average of all 12 GCMs for the future (2050 AD) temperature and precipitation variables.

Spatial Processing

In ArcGIS version 10, we interpolated all data layers to a common 0.5 degree × 0.5 degree resolution and WGS84 projection. We removed continents that are uninhabited and ice covered (i.e., Antarctica), as well as world oceans.

Literature cited

Center for International Earth Science Information Network - CIESIN - Columbia University, United Nations Food and Agriculture Programme - FAO, and Centro Internacional de Agricultura Tropical - CIAT. 2005. Gridded Population of the World, Version 3 (GPWv3): Population Count Grid, Future Estimates. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC).

Dentener, F. J. 2006. Global Maps of Atmospheric Nitrogen Deposition, 1860, 1993, and 2050. Data set. Available on-line [] from Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee, U.S.A. doi:10.3334/ORNLDAAC/830

Hijmans, R. J., S. E. Cameron, J. L. Parra, P. G. Jones, and A. Jarvis. 2005. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25:1965–1978.

Klein Goldewijk, K. , A. Beusen, M. de Vos, and G. van Drecht. 2011. The HYDE 3.1 spatially explicit database of human induced land use change over the past 12,000 years, Global Ecology and Biogeography 20(1):73–86.

R. 2012. R: a language and environment for statistical computing. R Core Team; R Foundation for Statistical Computing, Vienna, Austria.

United Nations Department of Economic and Social Affairs, Population Division. 2013. World Population Prospects: The 2012 Revision, DVD Edition. URL:, accessed 9/2/2014

Williams J. W., S. T. Jackson, and J. E. Kutzbach. 2007. Projected distributions of novel and disappearing climates by 2100AD. Proceedings of the National Academy of Sciences 104:5738–5742.

Willmott, C. J., and K. Matsuura. 2012a. Terrestrial Air Temperature: 1900-2010 Gridded Monthly Time Series (Version 3.01)

Willmott, C. J., and K. Matsuura. 2012b. Terrestrial Precipitation: 1900-2010 Gridded Monthly Time Series (V 3.02)

[Back to A025-127]