Mapping global bird distributions

1
Mapping global bird distributions
NCEAS working group meeting 16-20 July 2001
Walter Jetz Dept Zoology Oxford
2
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
3
Beneficiaries

• Conservation NGOs
• prioritise conservation efforts
• taxonomically range size as measure of
  extinction risk
• geographically refining hotspots using species
  data

• Museums
• identify holes in distribution and gaps of
  specimen records
• prioritise areas for fieldwork
• link morphological data and biogeographic
  perspective

• 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
4
Joint Effort
Working Group meetings at (and funded
by) National Centre for Ecological Analysis and
Synthesis, University of Santa Barbara
Mapping Global Vertebrate Distributions Walter
Jetz, University of Oxford
5
Diversity of Terrestrial Vertebrates

• Birds (Sibley)
• Passerines (Passeriformes) 5879
• Nonpasserines (Non-Passeriformes) 4075
• Mammals (Wilson Reeder 1993)
• Platypus, Echidnas (Monotremata) 3
• Oppossums, Kangaroos etc. (Marsupalia) 273
• Placental Mammals (Eutheria) 4353-78 (whales)
• Amphibians (Duellman Trueb 1986)
• Frogs and Toads (Salientia) 3438
• Salamanders and Newts (Caudata) 352
• Caecilians (Gymnophiona) 162
• Reptiles (Uetz)
• Lizards (Sauria) 4582
• Snakes (Serpentes) 2910
• Turtles (Testudines) 296
• Crocodiles (Crocodylia) 23
• Amphisbaenians (Amphisbaenia) 158
• Tuataras (Rhynchocephalia) 2

9954 4275 3952 7971 -------- 26152
Mapping Global Vertebrate Distributions Walter
Jetz, University of Oxford
6
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
7
(No Transcript)
8
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
9
Birds the knowledge base
I. Major regional atlases (proportion of 9954
bird species)
II. Major monographs (proportion of 176 bird
families)
Mapping Global Vertebrate Distributions Walter
Jetz, University of Oxford
10
Inter-relationship of Source Types
Gaps
Geographically organised sources
Taxonomically organised sources
Distributions

• Atlases
• Regional databases
• Regional monographs
• Regional specimen collections
• etc. ...

• Monographs
• Specimen Collections
• etc. ...

source overlap
Sources organised by extinction risk

• IUCN Red List data
• Conservation NGO data and distribution maps

11
Example Bird Distributions in Asia
Gaps
Geographically organised sources
Taxonomically organised sources
Distributions

• HBW - Nonpasserines
• Thrushes of the World
• Finches and Sparrows of the World
• Old World Warblers
• etc. ...

• The Birds of China
• Birds of the Indian Subcontinent
• Birds of Japan
• etc. ...

source overlap
Sources organised by extinction risk

• Threatened Birds of the World
• Regional threatened species databases

12
Birds 9,954 species
Taxonomically organised sources
Geographically organised sources

• I.
• ABI-CABS Birds of the Americas Databasepartial
  ranges for ca. 3,680 species
• Atlas of Birds of Australiapartial ranges for
  ca. 1,030 species
• Atlas of Birds of Europepartial ranges for ca.
  430 species
• Birds of Oceanic islands, from WWF eco-regions
  and other sourcespartial ranges for ca. 450
  species

• I.
• Handbook of the Birds of the World
• full ranges for 3,666 species

Full Distributions
I. 8,200 species
II. 9,450 species
III. Various family monographs
III. 9,954 species

• II.
• Birds of the Western Palearcticfull 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

Sources organised by extinction risk
I. Birdlife Threatened Birds of the World full
ranges for 1,189 species

• III.
• Various regional sources and species lists.

III. Birdlife Endemic Bird Areas for Orientalis,
Wallacea
listed are potential sources pending agreement
with authors/publishers
13
How to map a species range from a variety of
sources? Overlaying disparate sources
Source 3 Regional Atlas
Source 4 Point Data
Source 1 HBW
Source 2 Regional Monograph
14
General Methodology

• Range of potential sources

Mapping Global Vertebrate Distributions Walter
Jetz, University of Oxford
15
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

16
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

17
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

18
Time Efficient Data Entry
Streamlining the digitisation process
Square-tailed Kite
White-collared Kite
Mapping Global Vertebrate Distributions Walter
Jetz, University of Oxford
19
Global Patterns of Diversity in Diurnal Raptors
Ranges of year-round residents, min1 to max70
species Data from Handbook of the Birds of the
World, resampled to 200km grid
Mapping Global Vertebrate Distributions Walter
Jetz, University of Oxford
20
New World Passerines
Species Richness natural breaks, min1, max332
Geom. Mean of Range Sizes natural breaks,
min12990km2, max13642403km2
Collaboration with Lisa Manne and Stuart Pimm.
Mapping Global Vertebrate Distributions Walter
Jetz, University of Oxford
21
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

22
Species richness pattern All species (n1902),
continental Africa
Natural breaks classification, 2-615 species per
quadrat
Collaboration with Carsten Rahbek.
23
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

24
Productivity Habitat Heterogeneityspatial
pattern, observed vs. predicted
observed
predicted (NPP, NPP2, HabHet)
Natural breaks classification, left 3-558 species
per quadrat, right 28-371
25
Productivity Habitat Heterogeneityspatial
pattern of residuals
cyan - white 0 red
Residual from model NPPNPP2HabHet Standard
deviation classification, lt-3 to gt3s.d. left
-8.962 to 8.612 right -214 to 262
26
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

27
The signature of historyobserved and predicted
species richness in and outside Centers of
Endemism (CoE)
Observed species richness
Residual from model NPPNPP2HabHet
Centers of endemism quadrats with species that
have lt 10 quadrats range size
Natural breaks classification 3-558 species per
quadrat
Standard deviation classification lt-3 to gt3s.d.,
-214 to 262 species
28
The signature of historyobserved and predicted
species richness in and outside Centers of
Endemism (CoE)
29
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
30
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

• Continuously updated, peer supervised internet
  based database embedded in a multi-level access,
  graphical web-portal with facilities for down-
  and uploading data etc. ...

• One-off database, downloadable from the internet

Mapping Global Vertebrate Distributions Walter
Jetz, University of Oxford
31
Mapping Global Vertebrate Distributions Walter
Jetz, University of Oxford