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Biodiversity Informatics and
Related Developments
Keping MA
Institute of Botany, Chinese Academy of Sciences 2015-11-05
What is Biodiversity Informatics
History of the term "Biodiversity Informatics
According to correspondence reproduced by Walter
Berendsohn, the term "Biodiversity Informatics" was coined
by John Whiting in 1992 to cover the activities of an entity
known as the Canadian Biodiversity Informatics Consortium,
a group involved with fusing basic biodiversity information
with environmental economics and geospatial information in
the form of GPS and GIS. Subsequently it appears to have
lost any obligate connection with the GPS/GIS world and be
associated with the computerized management of any
aspects of biodiversity information.
Development of BiodivInform
Science,2000, Special feature: 5 papers
Philosophical Transactions of Royal
Society of London, Series B, Biological
Sciences, 2004. Taxonomy for the twenty-
first century:19 papers;
BMC:Bioinformatics,2009,
Biodiversity Informatics: the emergence of
a field:10 papers.
Key issues of BiodivInform
Global species names(CoL, GNA, IPNI, Ubio, GNI)
Digitization of baseline data(species, specimens, images,
literatures)
Standards/Protocols (Darwin Core, Dublin Core, ABCD, SDD,
TNC, SPM, TAPIR)
Data mining(GARP, MaxEnt, Random forest等)
Global Biodiversity Information Facility : GBIF
Catalogue of Life-Species2000: CoL
Biodiversity Heritage Library: BHL
EDIT: European Distributed Institute of Taxonomy
Tree of Life: TOL
Barcode of Life Data Systems :BOLD
Encyclopedia of Life: EOL
TROPICOS
Fishbase
ILDIS
GPI
The Plant list
DataONE
More than 600 projects on BI recorded by TDWG
Projects and organizations
11,106,374 NameBank Records
全球生物物种名录(CoL)
Catalogue of Life--China
Catalogue of
Life China
(2015)
includes
73,255
species and
10,035
infraspecific
taxa.
Species 2000 China Node (http://www.sp2000.cn/)
Species Catalogue of China
全球植物名录(TPL)
The International Plant Names
Index(IPNI)
Global Names
Key Issues of Multi hub Network
The contents of the system expanded from a
single taxonomic tree to multiple taxonomic trees.
Difference of concepts
and status of a name on
trees (if any), and
difference of tree’s
structures.
全球生物多样性信息网络(GBIF)
Basis of Record Record
s
Availabilit
y
Time
Cost
Examples GBIF(m)
Human
Observation
records
Millions
+
Easy if
online
Middle CFH, PPBC, Flickr,
interest groups,
iNaturalist, weibo
320 / 73.8
Specimen
records
Millions
+
Middle Long NSII, Herbarium
database
115 / 54.8
Observation
records
Millions
+
Middle Long Observatories, GEO BON,
CForBio, Protect area
97 / 30
Unknown
evidence records
34 / 8.5
Fossil records 4.8 / 0.7
Machine
Observation
records
Millions
+
Easy if
online
Short Automatic camera,
sensors,
1.4 / 0.34
Living Specimen
records
Millions
+
Easy if
online
Long Botanical Gardens, BGCI, 0.8 / 0.6
Literature Millions Easy Short or Web(BHL, IPNI, TPL), 0.46 /
GBIF Status(2015-7-31):
Animal:380.7million(66.3%), Plant:168.7million(29.4%)
Global Biodiversity Information Facility
GBIF-China
网络生命大百科
荷兰国家标本馆(Leiden)标本数字化流程示意图
荷兰国家标本馆(Leiden)标本数字化进展统计(3000万欧元)
2014-042010-2015
法国国家
自然历史
博物馆
600多万
份植物腊
叶标本全
部数字化
iDigBio--USA
ALA--Australia
All-in-one Design:
NSII(National Specimen Information Infrastructure)
Plant Rock
Protected Area
PolarAnimal
Education
Global
Regional
National
Thematic
Local
NSII
>12 million specimens, 100+ institutes & universities
Supporting
Database
DNA Barcode
Literature
Distribution
Ecology (Habitat)
User & Communities
国家标本资源共享平台(NSII)
Chinese Virtual Herbarium
(CVH)
生物多样性历史文献图书馆Biodiversity Heritage Library
生物多样性历史文献图书馆
Biodiversity Heritage Library
Flora of China
Botanical
Map of Life
MOL Status
http://mol.org/
1. Only 45 of 194 (23%) datasets are about plant data (2,565,659 records, about 0.7% of the total MOL)2. Only 5% dataset are point observation, and more are inventory, checklist, map and survey.
Big data VS. Small sources,
80% datasets are less than
10,000 records.
ABCDNet重点推动的项目
亚洲生物物种名录(Asia Species Checklist);
亚洲物种红色名录(Asia Species Red List);
亚洲植物制图(Mapping Asia Plants, MAP);
亚洲100种最受威胁物种 (100 most threatened
species);
东南亚生物多样性信息平台 (Southeast Asia
Biodiversity Information
Infrastructure, SEABio)
Existing Platforms in
Asia
Asia Biodiversity Information in
Global SyntheticSystems Asia
Biodiversity Information in
Global Thematic Database
亚洲生物多样性保护与信息网络
利用GBIF数据发表的论文
Maps of (a) collection density and (b) inventory incompleteness as indicators of
collecting effort for vascular plants in 2377 Chinese counties. (c) Relationship between
collection density and inventory incompleteness. (d) Map of absolute residuals from
ordinary least-squares regression in (c).
Mountainous areas are most
intensively collected in China, whereas
densely populated areas tend to be
neglected by plant collectors. This
sampling bias leads to woefully
incomplete inventories, particular in
urban and agricultural areas, and thus
to a pronounced ‘Wallacean shortfall’,
i.e. an incomplete documentation of
species ranges.
Distribution of Endemic Plants in China
Families: 193
Genera: 1513
Species: 15103
Maps of spatial turnover of Yunnan floristic assemblages in taxonomic
composition (a) and phylogenetic composition (b). Color scale depicts the
degree of taxonomic and phylogenetic turnover between the focal region
and all other regions. The maps were generated using DIVA-GIS 7.5.
A phylogenetically informed delineation of floristic
regions within a biodiversity hotspot in Yunnan, China
Rong Li, Nathan J. B. Kraft, Jie Yang & Yuhua Wang
Dendrogram (a) and map (b)
resulting from Ward
hierarchical clustering and
scatter plot (c) from non-metric
multidimensional scaling
(NMDS) two-dimensional
ordination for floristic
assemblages of Yunnan based
on phylogenetic beta diversity
distance matrices at the genus
level. The eight distinct floristic
regions are highlighted in the
dendrogram with large colored
rectangles and displayed in the
map in different colors. The
map was generated using
DIVA-GIS 7.5.
Spatiotemporal trends in crofton
weed ( Eupatorium adenophorum)
invasion in south-west China.
Geographical distribution of
training data was plotted on the
bottom x–y axis. Invasion history of
distribution points based on
recording dates was plotted on the
vertical axis. The black lines
represent the equal invasion time
and the grey arrows indicate the
direction of spread.
Geographic predictions for crofton weed (Eupatorium adenophorum) in China. Blue
triangles represent the 390 spots used to train the predicted models and where the
weed is known to occur, and white circles represent 51 extrinsic testing data used to
test the predicted geographic range.
Distribution of orchid
richness in China:
(a) all orchids,
(b) terrestrial orchids,
(c) epiphytic orchids,
(d) lithophytic orchids,
(e) orchids endemic to
China, and (f) orchids
non-endemic to China.
Regression between the
strength of phylogenetic
conservatism in flowering
phenology (Blomberg’s K) and
latitude, and the geographical
patterns of the K-values in
China estimated at the
province scale. Each point in
the regression represents a
province of China. The line is
the polynomial regression line
with a quadratic term.
Through analyses of 10,295 herbarium specimens of Himalayan
Rhododendron collected by plant hunters and botanists since 1884, we
were able to separate these responses into significant components.
However, over the full 125 y of collections, mean flowering time shows a
significant response to year-to-year changes in temperature, and this
response varies with season of warming. Mean flowering advances with
annual warming (2.27 d earlier per 1 °C warming), and also is delayed
with fall warming (2.54 d later per 1 °C warming). The lack of a directional
response suggests that contrasting phenological responses to temperature
changes may obscure temperature sensitivity in plants. By drawing on
large collections from multiple herbaria, made over more than a century, we
show how these data may inform studies even of remote localities, and we
highlight the increasing value of these and other natural history collections
in understanding long-term change.
The way forward
Biodiversity Mapping
LiteraturesSpecimens Plots & maps/RS Observations
Phylogenetic
dataTrait
data
Paleotological
data
On line
workflowsEcological
data
Thanks