Microsoft Research Ltd.
Cambridge, 16-17/2012
Visualising the future of our planet – Can we do better than heat maps?
Museo Nacional de Ciencias Naturales (CSIC), Spain
http://jhortal.com/; jhortal@mncn.csic.es / jqhortal@gmail.com
Joaquín Hortal
Biodiversity information
Quality (and quantity) of data: Wallacean
Shortfall
Mapping unknown species distributions
Mapping ignorance
biodiversity and biogeography
Imagine a magnificent and omniscient
GIS for all the Earth’s living species, with
the capacity to display any level of the
Linnaean hierarchy on any spatial scale,
for any season of the year.
Colwell & Coddington Phil Trans Roy Soc B 1994
gathering biodiversity information
digitize available distributional information:
 Natural History collections
▪ Institutional (Museums, Herbaria)
▪ Private collections
gathering biodiversity information
digitize available distributional information:
 Natural History collections
▪ Institutional (Museum, Herbaria)
▪ Private collections
 Literature
gathering biodiversity information
digitize available distributional information:
 Natural History collections
▪ Institutional (Museums, Herbaria)
▪ Private collections
 Literature
 ad hoc surveys
biodiversity databases
integrate all information on the distribution of
biodiversity
Map of Life
http://www.gbif.org/ ; http://www.mappinglife.org/ ; http://splink.cria.org.br/
Wallacean shortfall
Adequate distribution data is lacking for many of the
known species and higher taxa (Lomolino 2004)
Whittaker et al. Div Distr 2005; Hortal et al. Conserv Biol 2007
Wallacean shortfall
Adequate distribution data is lacking for many of the
known species and higher taxa (Lomolino 2004)
Tenerife seed plants
1,131 species
1,084,971 records
960 records/species
128 records/grid cell
Whittaker et al. Div Distr 2005; Hortal et al. Conserv Biol 2007
Wallacean shortfall
Adequate distribution data is lacking for many of the
known species and higher taxa (Lomolino 2004)
Tenerife seed plants
Records
Whittaker et al. Div Distr 2005; Hortal et al. Conserv Biol 2007
Observed
Richness
taxonomic error
Lozier et al J Biogeogr 2009
taxonomic error
Lozier et al J Biogeogr 2009
taxonomic bias
Baselga et al Biodiv Conserv 2007
spatial bias
recorder’s home range
hotspots
Dennis & Thomas J Insect Conserv 2000
spatial bias
accessibility: ‘roadside bias’
Kadmon et al Ecol Appl 2003; Hurlbert & Jetz PNAS 2007
spatial bias
bias differs between
groups
butterflies
Hortal et al Biod Conserv 2001; Hortal et al Ecography 2004
scarab dung beetles
temporal bias
Onthophagus fracticornis
Lobo et al. Div Distr 2007
quality of distributional data
Historical survey process has
been incomplete and biased:
 Taxonomic bias
 Temporal bias
 Spatial bias
Pineda & Lobo J Anim Ecol 2009
quality of distributional data
Historical survey process has
been incomplete and biased:
 Taxonomic bias
 Temporal bias
 Spatial bias
Current biodiversity picture depends on the survey process
Pineda & Lobo J Anim Ecol 2009
quality of distributional data
Historical survey process has
been incomplete and biased:
 Taxonomic bias
 Temporal bias
 Spatial bias
Current biodiversity picture depends on the survey process
Current knowledge on species distribution patterns may
depend on survey unevenness rather than on their actual
distributions
Pineda & Lobo J Anim Ecol 2009
mapping species distributions
fill in the gaps
Carabus granulatus
expert opinion
predictive models
Copris hispanus
Hortal J Biogeogr 2008; Penev et al The genus Carabus in Europe 2007; Chefaoui et al Biol Conserv 2005
inconsistencies with atlas data
neither the species are present everywhere within their
range maps, nor all their known occurrences are within
these range maps
Hurlbert & White Ecol Lett 2005
inconsistencies with atlas data
these mismatches are scale dependent
Hurlbert & Jetz PNAS 2007
the actual responses of the
species to the environment
are unknown
probability of presence
limited knowledge on the predictors
environmental gradient
land classes
data incompleteness
the descriptions of the environmental responses of most
species are incomplete and biased
100
All species
100
90
23 First recorded species
60
60
40
40
20
20
0
Number of species
Total
80
80
0
1900
1935
1970
1998
1900
1935
1970
100%
90%
100
80
Niche coverage
70
75%
50%
60
50
40
30
1998
20
10
0
1900
Hortal et al Oikos 2008
1935
1970
1998
uncertainty in predictions
expert-drawn
predictive models
observed plots
hybrid approach
different techniques predict different distribution patterns
fine
whorl snail
Vertigo mouninsiana
GLM
southern damselfly
Coenagrion mercuriale
coarse
Chefaoui et al Anim Biodiv Conserv 2011
GAM
NNET
uncertainty in future projections
Araújo & Rahbek Science 2006; Lawler et al Global Change Biol 2006
other determinants of the distribution
historical effects
Spanish moon moth
Graellsia isabelae
e.g.,
Lobo&etLobo
al. Div
DistrMan
200620º7
Chefaoui
J Wildl
dealing with uncertainty?
ensemble forecasting
Araújo & New Tree 2006
maps of ignorance
a region is an “area of ignorance” if the total library
resources of the outside world do not cover it (Boggs 1949)
Boggs Proc Am Phil Soc 1949
maps of ignorance
a region is an “area of ignorance” if the total library
resources of the outside world do not cover it (Boggs 1949)
Boggs Proc Am Phil Soc 1949
accuracy of knowledge
Kp = f ( [K0·C] , Lt , Ls )
Kp = accuracy of the knowledge about a given taxon or
community at area p
K0 = knowledge about such taxon or community at each
area in the moment of the survey
C = degree of completeness of the survey
Lt = loss of knowledge across time
Ls = loss of knowledge across space
Hortal, Ladle et al in prep.
quality of initial knowledge
– Taxonomic accuracy
– Detectability (crypsis, phenology)
– Adequacy of sampling method and dates
– Interactions
– Size of focal unit
– Habitat heterogeneity
– Sampling effort and success
100
80
Sobs
60
40
20
0
0
200
400
600
em
Hortal, Ladle et al in prep.
800
1000
1200
Magersfontein battlefield, South Africa
temporal loss of knowledge
Temporal decay of similarity:
1899
- Changes in taxonomy
- Turnover of species (mobility,
phenotypic traits)
- Area of unit (small  higher
turnover)
2005
- Range shifts (climate change)
- Local extinctions (land use changes,
biological invasions)
Magersfontein battlefield, South Africa
(from Moustakas et al Front Biogeogr 2010)
Hortal, Ladle et al in prep.
Magersfontein
battlefield, Southstructure
Africa / habitat specificity (niche width) / changes in climatic scenopoetic conditions
•Species: metacommunity
spatial loss of knowledge
Distance decay of similarity:
- Taxon specific
- Biogeographical changes
- Environmental gradients
- Metacommunity structure
- Habitat specificity (niche width)
(from Green et al Nature 2004)
Hortal, Ladle et al in prep.
looking forward
1. develop tools to map ignorance
- how to measure taxonomic uncertainty
- how to assess uncertainty in observations
- how to map the degree of reliability of species
distribution models in each point of space
- how to determine when distribution is being extrapolated
- how…
2. attach maps of ignorance as metadata for any
distributional map
suggestions are welcome!
looking forward
1. develop tools to map ignorance
- how to measure taxonomic uncertainty
- how to assess uncertainty in observations
- how to map the degree of reliability of species
distribution models in each point of space
- how to determine when distribution is being extrapolated
- how…
2. attach maps of ignorance as metadata for any
distributional map
suggestions are welcome!
Richard J. Ladle
Jorge M. Lobo
Duccio Rocchini
Geiziane Tessarolo
and many others...
Museo Nacional de Ciencias Naturales (CSIC), Spain
http://jhortal.com/ ; jhortal@mncn.csic.es , jqhortal@gmail.com
Joaquín Hortal