222
Qiao H, Soberón J, Peterson AT (2015) No silver bullets in correlative ecological niche modelling:
insights from testing among many potential algorithms for niche estimation. Methods Ecol
Evol 6(10):1126–1136. https://doi.org/10.1111/2041-210x.12397
R Core Team (2018) R: a language and environment for statistical computing. R Foundation for
Statistical Computing, Vienna, Austria. https://www.R-project.org/
Radeloff VC, Dubinin M, Coops NC et al (2019) The dynamic habitat indices (DHIs) from
MODIS and global biodiversity. Remote Sens Environ 222:204–214. https://doi.org/10.1016/j.
rse.2018.12.009
Randin CF, Ashcroft MB, Bolliger J et al. (2020) Monitoring biodiversity in the Anthropocene
using remote sensing in species distribution models. Remote Sens Environ 239:111626 https://
doi.org/10.1016/j.rse.2019.111626
Smith AB, Godsoe W, Rodríguez-Sánchez F et al (2018) Niche estimation above and below the
species level. Trends Ecol Evol 34:260. https://doi.org/10.1016/j.tree.2018.10.012
Saatchi S, Buermann W, ter Steege H et al (2008) Modeling distribution of Amazonian tree species
and diversity using remote sensing measurements. Remote Sens Environ 112(5):2000–2017.
https://doi.org/10.1016/j.rse.2008.01.008
Sanín C, Anderson RP (2018) A framework for simultaneous tests of abiotic, biotic, and historical
drivers of species distributions: empirical tests for north American Wood warblers based on
climate and pollen. Am Nat 192(2):E48–E61. https://doi.org/10.1086/697537
Serbin SP, Singh A, Desai AR et al (2015) Remotely estimating photosynthetic capacity, and its
response to temperature, in vegetation canopies using imaging spectroscopy. Remote Sens
Environ 167:78–87. https://doi.org/10.1016/j.rse.2015.05.024
Simões MVP, Peterson AT (2018) Importance of biotic predictors in estimation of potential invasive areas: the example of the tortoise beetle Eurypedus nigrosignatus, in Hispaniola. PeerJ
6:e6052. https://doi.org/10.7717/peerj.6052
Soberón J (2007) Grinnellian and Eltonian niches and geographic distributions of species. Ecol
Lett 10(12):1115–1123. https://doi.org/10.1111/j.1461-0248.2007.01107.x
Soberón J, Nakamura M (2009) Niches and distributional areas: concepts, methods, and assumptions. Proc Natl Acad Sci U S A 106(Supplement_2):19644–19650. https://doi.org/10.1073/
pnas.0901637106
Soberón J, Peterson AT (2005) Interpretation of models of fundamental ecological niches and
species’ distributional areas. Biodivers Inform 2. https://doi.org/10.17161/bi.v2i0.4
Soberón J, Osorio-Olvera L, Peterson AT (2017) Diferencias conceptuales entre modelación de
nichos y modelación de áreas de distribución. Rev Mex Biodivers 88(2):437–441. https://doi.
org/10.1016/j.rmb.2017.03.011
Sokal RR, Rohlf FJ (1995) Biometry: the principles and practice of statistics in biological research,
3rd edn. W. H. Freeman and Co., New York
Soria-Auza RW, Kessler M, Bach K et al (2010) Impact of the quality of climate models for modelling species occurrences in countries with poor climatic documentation: a case study from
Bolivia. Ecol Model 221(8):1221–1229. https://doi.org/10.1016/j.ecolmodel.2010.01.004
Schweiger AK, Cavender-Bares J, Townsend PA et al (2018) Plant spectral diversity integrates
functional and phylogenetic components of biodiversity and predicts ecosystem function. Nat
Ecol Evol 2(6):976–982. https://doi.org/10.1038/s41559-018-0551-1
Thuiller W (2004) Patterns and uncertainties of species’ range shifts under climate change. Glob
Chang Biol 10(12):2020–2027. https://doi.org/10.1111/j.1365-2486.2004.00859.x
Tilman D (1997) The influence of functional diversity and composition on ecosystem processes.
Science 277(5330):1300–1302. https://doi.org/10.1126/science.277.5330.1300
Turner W (2014) Sensing biodiversity. Science 346(6207):301–302. https://doi.org/10.1126/
science.1256014
Turner W, Spector S, Gardiner N et al (2003) Remote sensing for biodiversity science and conservation. Trends Ecol Evol 18(6):306–314. https://doi.org/10.1016/s0169-5347(03)00070-3
Tylianakis JM, Didham RK, Bascompte J et al (2008) Global change and species interactions in terrestrial ecosystems. Ecol Lett 11(12):1351–1363. https://doi.
org/10.1111/j.1461-0248.2008.01250.x
J. N. Pinto-Ledezma and J. Cavender-Bares
Qiao H, Soberón J, Peterson AT (2015) No silver bullets in correlative ecological niche modelling:
insights from testing among many potential algorithms for niche estimation. Methods Ecol
Evol 6(10):1126–1136. https://doi.org/10.1111/2041-210x.12397
R Core Team (2018) R: a language and environment for statistical computing. R Foundation for
Statistical Computing, Vienna, Austria. https://www.R-project.org/
Radeloff VC, Dubinin M, Coops NC et al (2019) The dynamic habitat indices (DHIs) from
MODIS and global biodiversity. Remote Sens Environ 222:204–214. https://doi.org/10.1016/j.
rse.2018.12.009
Randin CF, Ashcroft MB, Bolliger J et al. (2020) Monitoring biodiversity in the Anthropocene
using remote sensing in species distribution models. Remote Sens Environ 239:111626 https://
doi.org/10.1016/j.rse.2019.111626
Smith AB, Godsoe W, Rodríguez-Sánchez F et al (2018) Niche estimation above and below the
species level. Trends Ecol Evol 34:260. https://doi.org/10.1016/j.tree.2018.10.012
Saatchi S, Buermann W, ter Steege H et al (2008) Modeling distribution of Amazonian tree species
and diversity using remote sensing measurements. Remote Sens Environ 112(5):2000–2017.
https://doi.org/10.1016/j.rse.2008.01.008
Sanín C, Anderson RP (2018) A framework for simultaneous tests of abiotic, biotic, and historical
drivers of species distributions: empirical tests for north American Wood warblers based on
climate and pollen. Am Nat 192(2):E48–E61. https://doi.org/10.1086/697537
Serbin SP, Singh A, Desai AR et al (2015) Remotely estimating photosynthetic capacity, and its
response to temperature, in vegetation canopies using imaging spectroscopy. Remote Sens
Environ 167:78–87. https://doi.org/10.1016/j.rse.2015.05.024
Simões MVP, Peterson AT (2018) Importance of biotic predictors in estimation of potential invasive areas: the example of the tortoise beetle Eurypedus nigrosignatus, in Hispaniola. PeerJ
6:e6052. https://doi.org/10.7717/peerj.6052
Soberón J (2007) Grinnellian and Eltonian niches and geographic distributions of species. Ecol
Lett 10(12):1115–1123. https://doi.org/10.1111/j.1461-0248.2007.01107.x
Soberón J, Nakamura M (2009) Niches and distributional areas: concepts, methods, and assumptions. Proc Natl Acad Sci U S A 106(Supplement_2):19644–19650. https://doi.org/10.1073/
pnas.0901637106
Soberón J, Peterson AT (2005) Interpretation of models of fundamental ecological niches and
species’ distributional areas. Biodivers Inform 2. https://doi.org/10.17161/bi.v2i0.4
Soberón J, Osorio-Olvera L, Peterson AT (2017) Diferencias conceptuales entre modelación de
nichos y modelación de áreas de distribución. Rev Mex Biodivers 88(2):437–441. https://doi.
org/10.1016/j.rmb.2017.03.011
Sokal RR, Rohlf FJ (1995) Biometry: the principles and practice of statistics in biological research,
3rd edn. W. H. Freeman and Co., New York
Soria-Auza RW, Kessler M, Bach K et al (2010) Impact of the quality of climate models for modelling species occurrences in countries with poor climatic documentation: a case study from
Bolivia. Ecol Model 221(8):1221–1229. https://doi.org/10.1016/j.ecolmodel.2010.01.004
Schweiger AK, Cavender-Bares J, Townsend PA et al (2018) Plant spectral diversity integrates
functional and phylogenetic components of biodiversity and predicts ecosystem function. Nat
Ecol Evol 2(6):976–982. https://doi.org/10.1038/s41559-018-0551-1
Thuiller W (2004) Patterns and uncertainties of species’ range shifts under climate change. Glob
Chang Biol 10(12):2020–2027. https://doi.org/10.1111/j.1365-2486.2004.00859.x
Tilman D (1997) The influence of functional diversity and composition on ecosystem processes.
Science 277(5330):1300–1302. https://doi.org/10.1126/science.277.5330.1300
Turner W (2014) Sensing biodiversity. Science 346(6207):301–302. https://doi.org/10.1126/
science.1256014
Turner W, Spector S, Gardiner N et al (2003) Remote sensing for biodiversity science and conservation. Trends Ecol Evol 18(6):306–314. https://doi.org/10.1016/s0169-5347(03)00070-3
Tylianakis JM, Didham RK, Bascompte J et al (2008) Global change and species interactions in terrestrial ecosystems. Ecol Lett 11(12):1351–1363. https://doi.
org/10.1111/j.1461-0248.2008.01250.x
J. N. Pinto-Ledezma and J. Cavender-Bares