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Mapping global bird distributions
NCEAS working group meeting 16-20 July 2001
Walter Jetz
Dept Zoology
Oxford
Benefits
Why a free, public global vertebrate distribution database
would be valuable
• Large-scale conservation priority setting (refining
the hotspot approach with species distributions)
• Rapid assessment of diversity in regions under
threat
• Coarse-resolution basis for deductive modelling of
species’ fine-scale distributions
• Scrutiny of hypothesis in large-scale ecology
Mapping Global Vertebrate Distributions
Walter Jetz, University of Oxford
Beneficiaries
General GOs and NGOs
Conservation NGOs
• prioritise conservation efforts
• taxonomically: range size as
measure of extinction risk
• geographically: refining
hotspots using species data
• tool for resource and land
management
Museums
• identify holes in distribution and
gaps of specimen records
• prioritise areas for fieldwork
• link morphological data and
biogeographic perspective
General Public
Private Sector Land-use
• custom species lists for home
region or eco-tourism
destinations
• information tool for land
development projects, impact
assessments
Academia
• identify determinants of patterns in
species richness
• detect mechanisms and environmental
correlates of speciation
• understand environmental
determinants of biological patterns
Mapping Global Vertebrate Distributions
Walter Jetz, University of Oxford
Joint Effort
Conservation NGOs
Museums
• ground network of expertise
• source and gap identification
• facilitation of digitisation and
gap filling
• taxonomic expertise
• source identification and selection
• specimen records
Working Group
meetings at (and funded by)
National Centre for Ecological Analysis and
Synthesis, University of Santa Barbara
Academia
• methodological expertise
• source selection and prioritisation
• GIS tools
Mapping Global Vertebrate Distributions
Walter Jetz, University of Oxford
Diversity of Terrestrial Vertebrates
• Birds (Sibley)
– Passerines (Passeriformes): 5879
– Nonpasserines (Non-Passeriformes): 4075
9954
• Mammals (Wilson & Reeder 1993)
– Platypus, Echidnas (Monotremata): 3
– Oppossums, Kangaroos etc. (Marsupalia): 273
– Placental Mammals (Eutheria): 4353-78 (whales)
4275
• Amphibians (Duellman & Trueb 1986)
– Frogs and Toads (Salientia): 3438
– Salamanders and Newts (Caudata): 352
– Caecilians (Gymnophiona): 162
3952
• Reptiles (Uetz)
–
–
–
–
–
–
Lizards (Sauria): 4582
Snakes (Serpentes): 2910
Turtles (Testudines): 296
Crocodiles (Crocodylia): 23
Amphisbaenians (Amphisbaenia): 158
Tuataras (Rhynchocephalia): 2
7971
-------26152
Mapping Global Vertebrate Distributions
Walter Jetz, University of Oxford
Birds
regional databases
9954 species
in 176 families
State of country- and continent-wide mapping efforts for
bird distributions. Dark green: advanced, light green: weak
Mapping Global Vertebrate Distributions
Walter Jetz, University of Oxford
Sources
Regional atlas projects
Meta-data collections
Congo Peacock
Identify
key sources
Regional species lists
Species accounts
Museum specimen
Square-tailed Kite
Experts’ opinion
Mapping Global Vertebrate Distributions
Walter Jetz, University of Oxford
Birds
the knowledge base
I. Major regional atlases
II. Major monographs
(proportion of 9954 bird species)
(proportion of 176 bird families)
Australia
Nonpasserines
not covered
Passerines
not covered
Europe &
Africa
Gridded
databases
Not
covered
Other
Monographs
America
Handbook of
the Birds of the
World
Mapping Global Vertebrate Distributions
Walter Jetz, University of Oxford
Inter-relationship of Source Types
Gaps
Taxonomically
organised sources
• Monographs
• Specimen Collections
• etc. ...
Distributions
source
overlap
Sources organised
by extinction risk
• IUCN Red List data
• Conservation NGO data and
distribution maps
Geographically
organised sources
• Atlases
• Regional databases
• Regional monographs
• Regional specimen collections
• etc. ...
Example: Bird Distributions in Asia
Gaps
Taxonomically
organised sources
• HBW - Nonpasserines
• Thrushes of the World
• Finches and Sparrows of the World
• Old World Warblers
• etc. ...
Distributions
source
overlap
Sources organised
by extinction risk
• Threatened Birds of the World
• Regional threatened species databases
Geographically
organised sources
•
•
•
•
The Birds of China
Birds of the Indian Subcontinent
Birds of Japan
etc. ...
Birds: 9,954 species
Taxonomically
organised sources
Geographically
organised sources
I.
Handbook of the Birds of the World
full ranges for 3,666 species
Full Distributions
I. 8,200 species
III.
Various family monographs
II. 9,450 species
III. 9,954 species
Sources organised
by extinction risk
I.
Birdlife: Threatened Birds of the World
full ranges for 1,189 species
I.
• ABI-CABS Birds of the Americas
Database
partial ranges for ca. 3,680 species
• Atlas of Birds of Australia
partial ranges for ca. 1,030 species
• Atlas of Birds of Europe
partial ranges for ca. 430 species
• Birds of Oceanic islands, from WWF
eco-regions and other sources
partial ranges for ca. 450 species
II.
• Birds of the Western Palearctic
full ranges for ca. 520 species
• Birds of China
• Keith et al: Birds of Africa, Atlases
from Southern Africa, Tanzania,
Kenia, Somalia, Liberia, etc. …
partial ranges for ca. 2000 species
III.
III.
• Various regional sources and species
Birdlife: Endemic Bird Areas
lists.
for Orientalis, Wallacea
* listed are potential sources pending agreement with authors/publishers
How to map a species’ range from a variety of sources?
Overlaying disparate sources
Source 3
Regional Atlas
Gridded,
fixed resolution
Source 4
Point Data
Hierarchical
Decision Rule
S4 > S3 > S2 > S1
Source 1
HBW
Source 2
Regional Monograph
• Climate and vegetation
layers, remotely sensed
• Species habitat
preference information
Concatenated,
original resolution
confirmed fine scale presence and absence,
extent of occurrence maps for biogeographic validation
Modelled (inductive and deductive) species distribution
General Methodology
Evaluate sources for
quality, accessibility
and complementarity
Identify
available
sources
Range of
potential
sources
Selected
sources
Identify most
efficient method of
digitisation
Digitise
Multitude of
regional and
taxonomic
databases of
different
resolution and
quality
Queried database
Devise
hierarchical
algorithm for
query where
sources overlap
Mapping Global Vertebrate Distributions
Walter Jetz, University of Oxford
Taxonomies
Data Reality
• Taxonomies will always differ somehow by expert and region
• Various initiatives: ISIS, Species2000…. BCIS
Master Taxonomies ?
• Herps: Master Taxonomies?
• Mammals: Wilson & Reeder
• Birds: Sibley & Ahlquist
Solution …?
• Create database of all potential taxonomies (or ask data provider to provide)
• Link all taxonomies to master taxonomy
Source Types - Problems
Extent of occurrence maps
• poor temporal and spatial resolution
• wide coverage
• Frame/size of maps printed in books does not scale with extent of range
• potentially high spatial error
• size of error should be directly related to map scale, can perhaps be
incorporated in modelling
• inter- and extrapolated in unstandardised way, false presences
• great resource for range modelling together with point data
Atlas Data
• good temporal resolution
• geographically limited
• differences in observer effort, holes in distribution, false absences
Point Data: specimen, community studies, observations
• perfect temporal and spatial resolution
• coverage scattered, patchy, biased
• great basis for ranges modelling using remotely sensed data and extent of
occurrence maps for biogeographic component
Towards a standardised source database
Source types:
• Published or expert-based extent of occurrence maps, atlas data,
gridded databases, regional or local community studies, point
localities (observations and specimen)
Fields to include:
•
•
•
•
Usual reference information (author, year, title, journal/publisher)
Extent: temporal, taxonomic, geographic (description), spatial object
Procedural information: processes undertaken, dates, people behind
Evaluation:
–
–
–
–
spatial resolution
quality: correct species identification
quality: spatial error data
quality: spatial error digitisation
• Notes: Similar sources
Time Efficient Data Entry
Streamlining
the
digitisation
process
Square-tailed Kite
White-collared Kite
Mapping Global Vertebrate Distributions
Walter Jetz, University of Oxford
Global Patterns of Diversity in Diurnal Raptors
Ranges of year-round residents, min=1 to max=70 species
Data from Handbook of the Birds of the World, resampled to 200km grid
Mapping Global Vertebrate Distributions
Walter Jetz, University of Oxford
New World Passerines
Species Richness
Geom. Mean of Range Sizes
natural breaks, min=1, max=332
natural breaks, min=12990km2,
max=13642403km2
Collaboration with Lisa Manne and Stuart Pimm.
Mapping Global Vertebrate Distributions
Walter Jetz, University of Oxford
Determinants of species richness
- Hypotheses Plethora of hypotheses
Lessons so far
•
•
•
•
• one single factor ???
• many studies to date:
– limited to one specific
hypothesis/variable
– limited to small region,
taxonomic sub-sample
– limited to one dimension
(e.g. latitude)
– excluding the tropics
Energy availability
Habitat Heterogeneity
Evolutionary Time
Biome area
• Geometric constraints
Species richness pattern
All species (n=1902), continental Africa
Natural breaks classification, 2-615 species per quadrat
Collaboration with Carsten Rahbek.
Productivity & Habitat Heterogeneity
NDVI mean of all ten-day images (1982-99)
• remotely sensed from AVHHR
satellites at 7.6km resolution
• NDVI (normalised difference
vegetation index) is measure
of greenness of vegetation,
often used for vegetation
classification
• NDVI is synthesis of climatic
condition that regulate
productivity
Productivity & Habitat Heterogeneity
spatial pattern, observed vs. predicted
observed
predicted
(NPP, NPP2, HabHet)
Natural breaks classification, left 3-558 species per quadrat, right 28-371
Productivity & Habitat Heterogeneity
spatial pattern of residuals
cyan: white: 0
red: +
Residual from model NPP+NPP2+HabHet
Standard deviation classification, <-3 to >+3s.d.; left -8.962 to 8.612 ; right -214 to 262
A signature of history?
• Past climate events and their potential regional significance
difficult to reconcile
• Species data as proxy
• Assumption: Regions with restricted range species
(Centers of Endemism) have distinct evolutionary history
• Prediction: species richness in such defined regions with
distinct evolutionary history is
– likely to be higher than in surrounding regions
– much less well predicted from contemporary environmental
variables
The signature of history
observed and predicted species richness
in and outside Centers of Endemism (CoE)
Observed species richness
Residual from model NPP+NPP2+HabHet
Centers of endemism:
quadrats with species
that have <= 10
quadrats range size
Natural breaks classification
3-558 species per quadrat
Standard deviation classification
<-3 to >+3s.d., -214 to 262 species
The signature of history
observed and predicted species richness
in and outside Centers of Endemism (CoE)
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Phylogeography
Environmental change and rates of evolution: the phylogeographic
pattern within the hartebeest complex as related to climatic variation
Flagstad et al. Proc. R. Soc Lond. B (2001) 268, 667-677
Mapping Global Vertebrate Distributions
Walter Jetz, University of Oxford
The ‘End’ Product?
Source, species, lat, lon
17,1245,45,42
17, 1245,45,43
17, 1245,45,41
17, 1245,44,43
17, 1245,43,43
17, 1245,43,42
17, 1246,02,22
17, 1246,02,22
17, 1246,03,20
17, 1246,03,19
………………
One-off database,
downloadable from the
internet
Continuously updated, peer supervised
internet based database embedded in a
multi-level access, graphical webportal with facilities for down- and
uploading data etc. ...
Mapping Global Vertebrate Distributions
Walter Jetz, University of Oxford
Mapping Global Vertebrate Distributions
Walter Jetz, University of Oxford