Climate variability

Sensitivity of global terrestrial ecosystems to climate variability


  • 1

    Convention on Biological Diversity, Aichi Biodiversity Targets. http://www.cbd.int/sp/targets/default.shtml

  • 2

    Scheffer, M. et al. Early warning signals for critical transitions. Nature 461, 53-59 (2009)

    CASE
    ADS
    Item

    Google Scholar

  • 3

    Solano, R., Didan, K., Jacobson, A. & Huete, A. C5 MODIS Vegetation Index User Guide (MOD13 series). 1–42 http://vip.arizona.edu/documents/MODIS/MODIS_VI_UsersGuide_01_2012.pdf (2010)

  • 4

    Nemani, RR et al. Climate-induced increases in global land net primary production from 1982 to 1999. Science 300, 1560-1563 (2003)

    CASE
    ADS
    Item

    Google Scholar

  • 5

    De Keersmaecker, W. et al. A model quantifying the resistance and resilience of global vegetation to short-term climatic anomalies and their relationship to vegetation cover. Glob. School. Biogeogr. 24, 539-548 (2015)

    Item

    Google Scholar

  • 6

    Garcia, RA, Cabeza, M., Rahbek, C. & Araujo, MB Multiple dimensions of climate change and their implications for biodiversity. Science 344, 1247579 (2014)

    Item

    Google Scholar

  • 7

    Thomas, CD et al. Risk of extinction linked to climate change. Nature 427, 145-148 (2004)

    CASE
    ADS
    Item

    Google Scholar

  • 8

    Kharin, VV, Zwiers, FW, Zhang, X. & Hegerl, GC Changes in temperature and precipitation extremes across the IPCC set of global coupled model simulations. J. Clim. 20, 1419-1444 (2007)

    ADS
    Item

    Google Scholar

  • 9

    Holmgren, M., Hirota, M., Van Nes, EH & Scheffer, M. Effects of interannual climate variability on tropical tree cover. Nature Clim. Switch 3, 755-758 (2013)

    ADS
    Item

    Google Scholar

  • ten

    Pederson, N. et al. The legacy of episodic climatic events in the formation of temperate deciduous forests. School. Monogr. 84, 599-620 (2014)

    Item

    Google Scholar

  • 11

    Doughty, CE et al. Impact of drought on forest carbon dynamics and fluxes in the Amazon. Nature 519, 78-82 (2015)

    CASE
    ADS
    Item

    Google Scholar

  • 12

    Holling, CS Resilience and stability of ecological systems. Annu. Rev. School. Evol. Syst. 4, 1–23 (1973)

    Item

    Google Scholar

  • 13

    Dakos, V. et al. Slowdown as an early warning signal of abrupt climate change. Proc. Natl Acad. Sci. United States 105, 14308-14312 (2008)

    CASE
    ADS
    Item

    Google Scholar

  • 14

    Kerr, JT & Ostrovsky, M. From space to species: ecological applications for remote sensing. Trends Ecol. Evol. 18, 299–305 (2003)

    Item

    Google Scholar

  • 15

    Seeman, SW, Borbas, EE, Li, J., Menzel, WP & Gumley, Theoretical background document of the atmospheric profile recovery algorithm LE MODIS, version 6. http://modis-atmos.gsfc.nasa.gov/_docs/MOD07MYD07ATBDC005.pdf (2006).

  • 16

    Mu, Q., Zhao, M. & Running, SW Improvements to a MODIS global terrestrial evapotranspiration algorithm. Remote sensing Approx. 115, 1781-1800 (2011)

    ADS
    Item

    Google Scholar

  • 17

    Ackerman, S. et al. Distinguish the clear sky from the cloud with MODIS: Theoretical Basic Document of the Algorithm (MOD35), version 6.1. http://modisatmos.gsfc.nasa.gov/_docs/MOD35_ATBD_Collection6.pdf (2010).

  • 18

    Sala, OE, Gherardi, LA, Reichmann, L., Jobbgy, E. & Peters, D. Inheritance of rainfall fluctuations on primary production: theory and data synthesis. Phil. Trans. R. Soc. London. B 367, 3135–3144 (2012)

    Item

    Google Scholar

  • 19

    Richard, Y. & Poccard, I. A statistical study of the sensitivity of NDVI to seasonal and interannual variations in precipitation in southern Africa. Int. J. Remote sensing. 19, 2907-2920 (1998)

    Item

    Google Scholar

  • 20

    Intergovernmental Panel on Climate Change. Climate change 2013: the basis of physical science. (Cambridge Univ. Press, 2013)

  • 21

    Macias-Fauria, M., Forbes, BC, Zetterberg, P. & Kumpula, T. Greening of the Eurasian Arctic reveals teleconnections and the potential of structurally new ecosystems. Nature Clim. Switch 2, 613-618 (2012)

    ADS
    Item

    Google Scholar

  • 22

    Myers-Smith, IH et al. Expansion of shrubs in tundra ecosystems: dynamics, impacts and research priorities. About. Res. Lett. 6, 045509 (2011)

    ADS
    Item

    Google Scholar

  • 23

    Clark, DA, Piper, SC, Keeling, CD & Clark, DB Growth of tropical rainforest trees and atmospheric carbon dynamics related to interannual temperature variation between 1984 and 2000. Proc. Natl Acad. Sci. United States 100, 5852-5857 (2003)

    CASE
    ADS
    Item

    Google Scholar

  • 24

    Doughty, CE & Goulden, ML Are tropical forests near a high temperature threshold? J. Geophys. Res. 113, G00B07 (2008)

    ADS

    Google Scholar

  • 25

    Williams, JW, Jackson, ST & Kutzbach, JE Projected distributions of new and endangered climates by 2100 A D. Proc. Natl Acad. Sci. United States 104, 5738-5742 (2007)

    CASE
    ADS
    Item

    Google Scholar

  • 26

    Lenton, TM et al. Tipping elements in the Earth’s climate system. Proc. Natl Acad. Sci. United States 105, 1786-1793 (2008)

    CASE
    ADS
    Item

    Google Scholar

  • 27

    Barbosa, HA, Huete, AR & Baethgen, WE A 20 year study of NDVI variability in the northeast region of Brazil. J. Aride Environ. 67, 288-307 (2006)

    ADS
    Item

    Google Scholar

  • 28

    Harris, A., Carr, AS & Dash, J. Remote sensing of land cover dynamics and resilience in southern Africa. Int. J. Appl. Obs. of the Earth Géoinf. 28, 131-139 (2014)

    ADS
    Item

    Google Scholar

  • 29

    Hirota, M., Holmgren, M., Van Nes, EH & Scheffer, M. Global resilience of rainforest and savannah at critical transitions. Science 334, 232-235 (2011)

    CASE
    ADS
    Item

    Google Scholar

  • 30

    Lehner, B. & Döll, P. Development and validation of a global database of lakes, reservoirs and wetlands. J. Hydrol. (Amst.) 296, 1–22 (2004)

    ADS
    Item

    Google Scholar

  • 31

    Huete, A. et al. Overview of the radiometric and biophysical performances of MODIS vegetation indices. Remote sensing Approx. 83, 195-213 (2002)

    ADS
    Item

    Google Scholar

  • 32

    Cleugh, HA, Leuning, R., Mu, Q. & Running, SW Regional estimates of evaporation from flux tower and MODIS satellite data. Remote sensing Approx. 106, 285-304 (2007)

    ADS
    Item

    Google Scholar

  • 33

    Zuur, AF, Ieno, EN & Smith, GM Analysis of ecological data. (Springer, 2007)

  • 34

    Core team R. R: A language and an environment for statistical computation. http://www.R-project.org (2015).

  • 35

    Hijmans, RJ raster: analysis and modeling of geographic data. Package R version 2.4-20. http://CRAN.R-project.org/package=raster (2015).

  • 36

    Pinheiro, J., Bates, D., Debroy, S., Sarkar, D. & Team, ATRDC nlme: Linear and nonlinear mixed effects models. Package R version 3.1-122. http://CRAN.R-project.org/package=nlme (2013).

  • 37

    Pebesma, EJ Multivariable geostatistics in S: the gstat package. Calculation. Geosci. 30, 683-691 (2004)

    ADS
    Item

    Google Scholar

  • 38

    Bivand, R., Keitt, T. & Rowlingson, B. rgdal: Bindings for the Geospatial Data Abstraction Library. Package R version 0.9-3. http://CRAN.R-project.org/package=rgdal (2015).

  • 39

    Warnes, GR, Bolker, B. & Lumley, T. gtools: Various R. Package R programming tools version 3.5.0. http://CRAN.R-project.org/package=gtools (2015).

  • 40

    Hijmans, RJ, Cameron, SE, Parra, JL, Jones, PG & Jarvis, A. Very high resolution interpolated climatic surfaces for global land areas. Int. J. Climatol. 25, 1965-1978 (2005)

    Item

    Google Scholar

  • 41

    Pope, N. corHaversine function. http://stackoverflow.com/questions/18857443/specifying-a-correlation-structure-for-a-linear-mixed-model-using-the-ramps-pack (2013).


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