221
Kissling WD, Dormann CF, Groeneveld J et al (2012) Towards novel approaches to modelling
biotic interactions in multispecies assemblages at large spatial extents. J Biogeogr 39(12):
2163–2178. https://doi.org/10.1111/j.1365-2699.2011.02663.x
Koehler K, Center A, Cavender-Bares J (2011) Evidence for a freezing tolerance-growth rate
trade-off in the live oaks (Quercus series Virentes) across the tropical-temperate divide. New
Phytol 193(3):730–744. https://doi.org/10.1111/j.1469-8137.2011.03992.x
Liaw A, Wiener M (2002) Classification and regression by randomForest. R News 2:18–22
Lin LH, Wiens JJ (2017) Comparing macroecological patterns across continents: evolution of
climatic niche breadth in varanid lizards. Ecography 40(8):960–970. https://doi.org/10.1111/
ecog.02343
Lobo JM, Jiménez-Valverde A, Hortal J (2010) The uncertain nature of absences and their
importance in species distribution modelling. Ecography 33(1):103–114. https://doi.
org/10.1111/j.1600-0587.2009.06039.x
Manzoor SA, Griffiths G, Lukac M (2018) Species distribution model transferability and model
grain size – finer may not always be better. Sci Rep 8(1):7168. https://doi.org/10.1038/
s41598-018-25437-1
Mateo RG, Mokany K, Guisan A (2017) Biodiversity models: what if unsaturation is the rule?
Trends Ecol Evol 32(8):556–566. https://doi.org/10.1016/j.tree.2017.05.003
Milborrow S (2016) Earth: multivariate adaptive regression splines. R package version 4.4.4.
Retrieved from https://CRAN.R-project.org/package=earth.
Myneni R, Hoffman S, Knyazikhin Y et al (2002) Global products of vegetation leaf area and
fraction absorbed PAR from year one of MODIS data. Remote Sens Environ 83(1–2):214–231.
https://doi.org/10.1016/s0034-4257(02)00074-3
Nix HA (1986) A biogeographic analysis of Australian elapid snakes. In: Longmore R (ed) Atlas
of elapid snakes of Australia: Australian Flora and Fauna Series, vol 7. Bureau of Flora and
Fauna, Canberra, pp 4–15
Ovaskainen O, Tikhonov G, Norberg A et al (2017) How to make more out of community data? A
conceptual framework and its implementation as models and software. Ecol Lett 20(5):561–
576. https://doi.org/10.1111/ele.12757
Pearson RG, Dawson TP, Liu C (2004) Modelling species distributions in Britain: a hierarchical integration of climate and land-cover data. Ecography 27(3):285–298. https://doi.
org/10.1111/j.0906-7590.2004.03740.x
Peterson AT, Martínez-Meyer E, Soberón J et al (2011) Ecological niches and geographic distributions. Monographs in population biology, vol 49. Princeton University Press, Princeton
Peterson AT, Nakazawa Y (2008) Environmental data sets matter in ecological niche modelling: an
example with Solenopsis invicta and Solenopsis richteri. Glob Ecol Biogeogr 17(1):135–144.
https://doi.org/10.1111/j.1466-8238.2007.00347.x
Pettorelli N, Safi K, Turner W (2014a) Satellite remote sensing, biodiversity research and conservation of the future. Philos Trans R Soc Lond Ser B Biol Sci 369(1643):20130190–20130190.
https://doi.org/10.1098/rstb.2013.0190
Pettorelli N, Laurance WF, O’Brien TG et al (2014b) Satellite remote sensing for applied
ecologists: opportunities and challenges. J Appl Ecol 51(4):839–848. https://doi.
org/10.1111/1365-2664.12261
Phillips LB, Hansen AJ, Flather CH (2008) Evaluating the species energy relationship with the
newest measures of ecosystem energy: NDVI versus MODIS primary production. Remote
Sens Environ 112(9):3538–3549. https://doi.org/10.1016/j.rse.2008.04.012
Pigot AL, Tobias JA, Jetz W (2016) Energetic constraints on species coexistence in birds. PLoS
Biol 14(3):e1002407. https://doi.org/10.1371/journal.pbio.1002407
Pinto-Ledezma JN, Rivero ML (2014) Temporal patterns of deforestation and fragmentation
in lowland Bolivia: implications for climate change. Clim Chang 127(1):43–54. https://doi.
org/10.1007/s10584-013-0817-1
Pradervand JN, Dubuis A, Pellissier L et al (2013) Very high resolution environmental predictors in species distribution models. Prog Phys Geogr 38(1):79–96. https://doi.
org/10.1177/0309133313512667
9 Using Remote Sensing for Modeling and Monitoring Species Distributions
Kissling WD, Dormann CF, Groeneveld J et al (2012) Towards novel approaches to modelling
biotic interactions in multispecies assemblages at large spatial extents. J Biogeogr 39(12):
2163–2178. https://doi.org/10.1111/j.1365-2699.2011.02663.x
Koehler K, Center A, Cavender-Bares J (2011) Evidence for a freezing tolerance-growth rate
trade-off in the live oaks (Quercus series Virentes) across the tropical-temperate divide. New
Phytol 193(3):730–744. https://doi.org/10.1111/j.1469-8137.2011.03992.x
Liaw A, Wiener M (2002) Classification and regression by randomForest. R News 2:18–22
Lin LH, Wiens JJ (2017) Comparing macroecological patterns across continents: evolution of
climatic niche breadth in varanid lizards. Ecography 40(8):960–970. https://doi.org/10.1111/
ecog.02343
Lobo JM, Jiménez-Valverde A, Hortal J (2010) The uncertain nature of absences and their
importance in species distribution modelling. Ecography 33(1):103–114. https://doi.
org/10.1111/j.1600-0587.2009.06039.x
Manzoor SA, Griffiths G, Lukac M (2018) Species distribution model transferability and model
grain size – finer may not always be better. Sci Rep 8(1):7168. https://doi.org/10.1038/
s41598-018-25437-1
Mateo RG, Mokany K, Guisan A (2017) Biodiversity models: what if unsaturation is the rule?
Trends Ecol Evol 32(8):556–566. https://doi.org/10.1016/j.tree.2017.05.003
Milborrow S (2016) Earth: multivariate adaptive regression splines. R package version 4.4.4.
Retrieved from https://CRAN.R-project.org/package=earth.
Myneni R, Hoffman S, Knyazikhin Y et al (2002) Global products of vegetation leaf area and
fraction absorbed PAR from year one of MODIS data. Remote Sens Environ 83(1–2):214–231.
https://doi.org/10.1016/s0034-4257(02)00074-3
Nix HA (1986) A biogeographic analysis of Australian elapid snakes. In: Longmore R (ed) Atlas
of elapid snakes of Australia: Australian Flora and Fauna Series, vol 7. Bureau of Flora and
Fauna, Canberra, pp 4–15
Ovaskainen O, Tikhonov G, Norberg A et al (2017) How to make more out of community data? A
conceptual framework and its implementation as models and software. Ecol Lett 20(5):561–
576. https://doi.org/10.1111/ele.12757
Pearson RG, Dawson TP, Liu C (2004) Modelling species distributions in Britain: a hierarchical integration of climate and land-cover data. Ecography 27(3):285–298. https://doi.
org/10.1111/j.0906-7590.2004.03740.x
Peterson AT, Martínez-Meyer E, Soberón J et al (2011) Ecological niches and geographic distributions. Monographs in population biology, vol 49. Princeton University Press, Princeton
Peterson AT, Nakazawa Y (2008) Environmental data sets matter in ecological niche modelling: an
example with Solenopsis invicta and Solenopsis richteri. Glob Ecol Biogeogr 17(1):135–144.
https://doi.org/10.1111/j.1466-8238.2007.00347.x
Pettorelli N, Safi K, Turner W (2014a) Satellite remote sensing, biodiversity research and conservation of the future. Philos Trans R Soc Lond Ser B Biol Sci 369(1643):20130190–20130190.
https://doi.org/10.1098/rstb.2013.0190
Pettorelli N, Laurance WF, O’Brien TG et al (2014b) Satellite remote sensing for applied
ecologists: opportunities and challenges. J Appl Ecol 51(4):839–848. https://doi.
org/10.1111/1365-2664.12261
Phillips LB, Hansen AJ, Flather CH (2008) Evaluating the species energy relationship with the
newest measures of ecosystem energy: NDVI versus MODIS primary production. Remote
Sens Environ 112(9):3538–3549. https://doi.org/10.1016/j.rse.2008.04.012
Pigot AL, Tobias JA, Jetz W (2016) Energetic constraints on species coexistence in birds. PLoS
Biol 14(3):e1002407. https://doi.org/10.1371/journal.pbio.1002407
Pinto-Ledezma JN, Rivero ML (2014) Temporal patterns of deforestation and fragmentation
in lowland Bolivia: implications for climate change. Clim Chang 127(1):43–54. https://doi.
org/10.1007/s10584-013-0817-1
Pradervand JN, Dubuis A, Pellissier L et al (2013) Very high resolution environmental predictors in species distribution models. Prog Phys Geogr 38(1):79–96. https://doi.
org/10.1177/0309133313512667
9 Using Remote Sensing for Modeling and Monitoring Species Distributions