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Miguel B. Araújo Lab

Predicting the effects of environmental change on biodiversity

You are here: Home / Projects / Former projects / ALARM / Outputs / Data

Data

Coordinates of European 50×50 grid cells including elevation and surface area information

europe50km.zip

When using these data please refer to:

Nogués-Bravo, D. & Araújo, M.B. 2006 Species richness, area and climate correlates. Global Ecology and Biogeography 15: 452–460.

Downscalled European maps of richness for plant, breeding bird, mammal, and herptile (reptile and amphibian) species

eu.sp.rich.txt

When using these data please refer to:

Araújo et al. 2005. Downscaling European species atlas distributions to a finer resolution: implications for conservation planning. Global Ecology and Biogeography 14: 17-30.

Ensembles of models of current and future (2050) distributions of amphibians and reptiles in Europe

InterpANNKap.seh.zip (present distributions)

InterpANNRoc.seh.zip (present distributions)

InterpCTAKap.seh.zip (present distributions)

InterpCTARoc.seh.zip (present distributions)

InterpGAMKap.seh.zip (present distributions)

InterpGAMRoc.seh.zip (present distributions)

InterpGLMKap.seh.zip (present distributions)

InterpGLMRoc.seh.zip (present distributions)

Pred2050.ANN.A1.Hadcm3.BinKap.zip (future distributions)

Pred2050.ANN.A1.Hadcm3.BinRoc.zip (future distributions)

Pred2050.ANN.A2.Csiro.BinKap.zip (future distributions)

Pred2050.ANN.A2.Csiro.BinRoc.zip (future distributions)

Pred2050.ANN.A2.Hadcm3.BinKap.zip (future distributions)

Pred2050.ANN.A2.Hadcm3.BinRoc.zip (future distributions)

Pred2050.ANN.B1.Hadcm3.BinKap.zip (future distributions)

Pred2050.ANN.B1.Hadcm3.BinRoc.zip (future distributions)

Pred2050.ANN.B2.Hadcm3.BinKap.zip (future distributions)

Pred2050.ANN.B2.Hadcm3.BinRoc.zip (future distributions)

Pred2050.CTA.A1.Hadcm3.BinKap.zip (future distributions)

Pred2050.CTA.A1.Hadcm3.BinRoc.zip (future distributions)

Pred2050.CTA.A2.Csiro.BinKap.zip (future distributions)

Pred2050.CTA.A2.Csiro.BinRoc.zip (future distributions)

Pred2050.CTA.A2.Hadcm3.BinKap.zip (future distributions)

Pred2050.CTA.A2.Hadcm3.BinRoc.zip (future distributions)

Pred2050.CTA.B1.Hadcm3.BinKap.zip (future distributions)

Pred2050.CTA.B1.Hadcm3.BinRoc.zip (future distributions)

Pred2050.CTA.B2.Hadcm3.BinKap.zip (future distributions)

Pred2050.CTA.B2.Hadcm3.BinRoc.zip (future distributions)

Pred2050.GAM.A1.Hadcm3.BinKap.seh.zip (future distributions)

Pred2050.GAM.A1.Hadcm3.BinRoc.zip (future distributions)

Pred2050.GAM.A2.Csiro.BinKap.seh.zip (future distributions)

Pred2050.GAM.A2.Csiro.BinRoc.zip (future distributions)

Pred2050.GAM.A2.Hadcm3.BinKap.zip (future distributions)

Pred2050.GAM.A2.Hadcm3.BinRoc.zip (future distributions)

Pred2050.GAM.B1.Hadcm3.BinKap.zip (future distributions)

Pred2050.GAM.B1.Hadcm3.BinRoc.zip (future distributions)

Pred2050.GAM.B2.Hadcm3.BinKap.zip (future distributions)

Pred2050.GAM.B2.Hadcm3.BinRoc.zip (future distributions)

Pred2050.GLM.A1.Hadcm3.BinKap.zip (future distributions)

Pred2050.GLM.A1.Hadcm3.BinRoc.zip (future distributions)

Pred2050.GLM.A2.Csiro.BinKap.zip (future distributions)

Pred2050.GLM.A2.Csiro.BinRoc.zip (future distributions)

Pred2050.GLM.A2.Hadcm3.BinKap.zip (future distributions)

Pred2050.GLM.A2.Hadcm3.BinRoc.zip (future distributions)

Pred2050.GLM.B1.Hadcm3.BinKap.zip (future distributions)

Pred2050.GLM.B1.Hadcm3.BinRoc.zip (future distributions)

Pred2050.GLM.B2.Hadcm3.BinKap.zip (future distributions)

Pred2050.GLM.B2.Hadcm3.BinRoc.zip (future distributions)

Key to understand the data:
  1. Interp (interpolation of current distributions from a 50×50 km atlas grid to 10’ [ca. 10-16 km] grid cells, using climate data for the period of 1961-1991)
  2. Pred (Prediction of future distributions based on original atlas data and “interp” models)
  3. 2050 (period of 2020-2050 in which predictions were made)
  4. ANN, CTA, GAM, GLM (Predictions made with: Artificial Neural Networks, Classification Tree Analysis, Generalized Additive Models, Generalized Linear Models)
  5. A1, A2, B1, B2 (Socioeconomic scenarios – See SRES in IPCC report)
  6. Hadcm3, CSIRO (The general circulation Models used; from Met Office of the Hadley Center and from Australian Commonwealth Scientific and Research Organization)
  7. Kap, Roc (Original species’ probability of occurrence data was transformed into presence and absence using max kappa statistic or the AUC [area under the curve] procedure)
Opening the files:

We provide data as standard text files. The first two collumns are lat long coordinates; the following collumns are species. Rows are grid cells. Values on the table are potential presences and absences of species in grid cells. You need a GIS to properly visualise the data, although software that is able to plot scatter diagrams (e.g. Excel) can allow you to visualise data.

Note from the authors:

Both current and future species distributions data CANNOT be interpreted as actual distributions. They represent species’ potential distributions or, to be more precise, the distributions of suitable climate space for species. Therefore it is possible to find predicted distributions in areas where the species do not exist, but where suitable climate conditions may be found.

We provide a relatively small ensemble of projections that enable users to measure the uncertainty of our forecasts. If users are not interested in measuring uncertainties we recommend using ANN projections, since these were shown to reflect the main consensus in the data.

When using these data please refer to:

Araújo, Thuiller & Pearson 2006. Climate warming and the decline of amphibians and reptiles in Europe. Journal of Biogeography 33: 1677-1688

Ensembles of models of current and future (2050 and 2080) distributions of plants in Europe

Plants_CGCM2_A1_2080

Plants_CGCM2_A2_2080

Plants_CSIRO2_A2_2050

Plants_CSIRO2_A2_2050

Plants_HadCM3_A1_2050

Plants_HadCM3_A1_2080

Plants_HadCM3_A2_2050

Plants_HadCM3_A2_2080

Plants_HadCM3_B1_2050

Plants_HadCM3_B1_2080

Plants_HadCM3_B2_2050

Plants_HadCM3_B2_2080

Names

Key to understand the files:
  1. All data interpolated from the original data at 50×50 km atlas grid to 10’ [ca. 10-16 km] grid cells, using climate data for the period of 1961-1991)
  2. 2050 and 2080 include projections made for 2020-2050 and 2050-2080
  3. Models used are ANN, CTA, GAM, GLM (Artificial Neural Networks, Classification Tree Analysis, Generalized Additive Models, Generalized Linear Models)
  4. A1, A2, B1, B2 are socioeconomic IPCC scenarios
  5. Hadcm3, CSIRO, and CGM2 are the AOGCM used (Met Office of the Hadley Center, Australian Commonwealth Scientific and Research Organization, and the Canadian Climate Centre)
  6. 2050 data are projections by the best models as evaluated with AUC/ROC procedure and were described by Thuiller (2004); 2080 data consensus projections and were described by Thuiller et al. (2005) – See below for full references and links
  7. Names file is a dfb table with the ids of the species and their corresponding names
Opening the files:

We provide data as standard text files. The first two collumns are lat long coordinates; the following collumns are species distributions data. Rows are grid cells. Values on the table are not standard presence and absence as for the amphibian and reptile data. Instead, data was coded as follows: (-2) currently suitable, projected to become unsuitable in the future; (-1) currently suitable, sprojected to remain suitable; (0) currently unsuitable, projected to remain unsuitable; (1) currently unsuitable, projected to become suitable. You need a GIS to properly visualise the data, although software that is able to plot scatter diagrams (e.g. Excel) can allow you to visualise data.

Note from the authors:

Both current and future species distributions data CANNOT be interpreted as actual distributions. They represent species’ potential distributions or, to be more precise, the distributions of suitable climate space for species. Therefore it is possible to find predicted distributions in areas where the species do not exist, but where suitable climate conditions may be found.

When using these data please refer to:

2050 data – Thuiller, W. (2004) Patterns and uncertainties of species’ range shifts under climate change. Global Change Biology 10, 2020-2027
2080 data – Thuiller, W., Lavorel, S., Araújo, M.B., Sykes, M. & Prentice, I.C. 2005. Climate change threats to plant diversity in Europe. Proceedings of the National Academy of Sciences, USA 102: 8245-8250

Provision of data was funded by the EC FP6 ALARM project

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News

  • Dangerous levels of subterranean water consumption
  • Welcome Nuria Galiana
  • Miguel Araújo identified as Highly Cited 2020
  • Biophilia Award to The Guardian
  • FBBVA Biodiversity Conservation Awards - 15th edition

Outreach

  • The future of coastlands in the era of mega hurricanes
  • What will 2021 bring for biodiversity and conservation?
  • Presentation of CORESCAM project
  • Discriminating climate, land‐cover and random effects on species range dynamics
  • Talk to representatives of ministries of CPLP

Opportunities

  • First call AQUACOSM-PLUS
  • La Caixa Foundation PhD studentship on climate change and protected areas
  • Two Post docs: Ecology & Conservation
  • Post-doc: Effects of climate change extremes on Caribbean biodiversity
  • Post doc - Modelling the effects of climate change extremes on Caribbean biodiversity

Research Highlights

The evolution of critical thermal limits of life on Earth

Climate shapes community trophic structures and humans simplify them

The marine fish food web is globally connected

Standards for data and models in biodiversity assessments

The effect of multiple biotic interaction types on species persistence

Books

Ecological Niches and Geographic Distributions

Ecological Niches and Geographic Distributions

Atlas of Biodiversity Risk

Atlas of Biodiversity Risk

Spatial Conservation Prioritization

Spatial Conservation Prioritization

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