Berliner Boersenzeitung - Half of species not assessed for endangered list risk extinction: study

EUR -
AED 4.291906
AFN 74.188104
ALL 95.612363
AMD 433.156007
ANG 2.091768
AOA 1072.830672
ARS 1638.484029
AUD 1.630045
AWG 2.106512
AZN 2.010972
BAM 1.956061
BBD 2.354674
BDT 143.446706
BGN 1.949446
BHD 0.442057
BIF 3479.049841
BMD 1.168661
BND 1.492893
BOB 8.078044
BRL 5.785104
BSD 1.169136
BTN 111.336396
BWP 15.888054
BYN 3.309685
BYR 22905.757712
BZD 2.351274
CAD 1.590986
CDF 2706.619162
CHF 0.916447
CLF 0.027048
CLP 1064.499798
CNY 7.982247
CNH 7.98296
COP 4357.294507
CRC 531.861943
CUC 1.168661
CUP 30.969519
CVE 110.279259
CZK 24.381188
DJF 208.186919
DKK 7.472927
DOP 69.658113
DZD 154.76695
EGP 62.802792
ERN 17.529917
ETB 183.829569
FJD 2.568011
FKP 0.863475
GBP 0.863413
GEL 3.137805
GGP 0.863475
GHS 13.105695
GIP 0.863475
GMD 85.904498
GNF 10260.194951
GTQ 8.924039
GYD 244.591626
HKD 9.158166
HNL 31.077151
HRK 7.535554
HTG 153.00782
HUF 362.844148
IDR 20396.642314
ILS 3.43906
IMP 0.863475
INR 111.23761
IQD 1531.478363
IRR 1536789.356921
ISK 143.406371
JEP 0.863475
JMD 183.973001
JOD 0.828547
JPY 184.397214
KES 150.956306
KGS 102.16494
KHR 4689.606366
KMF 491.427992
KPW 1051.798729
KRW 1721.507961
KWD 0.360123
KYD 0.974226
KZT 543.250242
LAK 25673.319558
LBP 104693.036799
LKR 374.113571
LRD 214.527738
LSL 19.565079
LTL 3.450752
LVL 0.706912
LYD 7.416927
MAD 10.805343
MDL 20.178609
MGA 4869.629643
MKD 61.597109
MMK 2453.84549
MNT 4182.178877
MOP 9.43682
MRU 46.681437
MUR 54.868938
MVR 18.061679
MWK 2027.262125
MXN 20.373444
MYR 4.630822
MZN 74.689153
NAD 19.565414
NGN 1599.452824
NIO 43.025011
NOK 10.801864
NPR 178.138795
NZD 1.987606
OMR 0.449355
PAB 1.169151
PEN 4.098677
PGK 5.083679
PHP 72.064337
PKR 325.795044
PLN 4.2543
PYG 7083.91595
QAR 4.273153
RON 5.219126
RSD 117.37212
RUB 88.235831
RWF 1709.421028
SAR 4.385311
SBD 9.37952
SCR 15.61227
SDG 701.753321
SEK 10.839335
SGD 1.492357
SHP 0.872524
SLE 28.807603
SLL 24506.234619
SOS 668.186396
SRD 43.773389
STD 24188.925413
STN 24.502854
SVC 10.229191
SYP 129.17296
SZL 19.561613
THB 38.141008
TJS 10.931113
TMT 4.096157
TND 3.408455
TOP 2.813856
TRY 52.845214
TTD 7.924923
TWD 36.940799
TZS 3041.441932
UAH 51.378143
UGX 4413.514019
USD 1.168661
UYU 47.076288
UZS 14069.638616
VES 571.408376
VND 30762.66634
VUV 138.515007
WST 3.174003
XAF 656.041826
XAG 0.015872
XAU 0.000256
XCD 3.158365
XCG 2.106972
XDR 0.815298
XOF 656.041826
XPF 119.331742
YER 278.871774
ZAR 19.503961
ZMK 10519.353599
ZMW 22.066853
ZWL 376.3084
  • RYCEF

    0.3500

    16.35

    +2.14%

  • RBGPF

    1.6000

    64.7

    +2.47%

  • GSK

    -0.6600

    50.24

    -1.31%

  • CMSC

    -0.0727

    22.7974

    -0.32%

  • RELX

    -0.2250

    36.135

    -0.62%

  • BTI

    0.3000

    58.65

    +0.51%

  • BCE

    0.0600

    23.99

    +0.25%

  • CMSD

    -0.0300

    23.22

    -0.13%

  • BCC

    1.0700

    75.4

    +1.42%

  • NGG

    -0.5000

    87

    -0.57%

  • VOD

    -0.3250

    15.725

    -2.07%

  • AZN

    -2.3700

    181.09

    -1.31%

  • JRI

    0.0350

    12.965

    +0.27%

  • BP

    -0.8850

    46.055

    -1.92%

  • RIO

    1.1500

    99.78

    +1.15%

Half of species not assessed for endangered list risk extinction: study
Half of species not assessed for endangered list risk extinction: study / Photo: Juni Kriswanto - AFP/File

Half of species not assessed for endangered list risk extinction: study

More than half of species whose endangered status cannot be assessed due to a lack of data are predicted to face the risk of extinction, according to a machine-learning analysis published Thursday.

Text size:

The International Union for the Conservation of Nature (IUCN) currently has nearly 150,000 entries on its Red List for threatened species, including some 41,000 species threatened with extinction.

These include 41 percent of amphibians, 38 percent of sharks and rays, 33 percent of reef building corals, 27 percent of mammals and 13 percent of birds.

But there are thousands of species that the IUCN has been unable to categorise as they are "data insufficient" and are not on the Red List even though they live in the same regions and face similar threats to those species that have so far been assessed.

Researchers from the Norwegian University of Science and Technology used a machine learning technique to predict the likelihood of 7,699 data deficient species being at risk of extinction.

They trained the algorithm on a list of more than 26,000 species that the IUCN has been able to categorise, incorporating data on the regions where species live and other factors known to influence biodiversity to determine whether it predicted their extinction risk status.

"These could include climatic conditions, land use conditions or land use changes, pesticide use, threats from invasive species or really a range of different stressors," lead author Jan Borgelt, from the university's Industrial Ecology Programme, told AFP.

After comparing the algorithm's results with the IUCN's lists, the team then applied it to predict the data deficient species' extinction risk.

Writing in the journal Communications Biology, they found that 4,336 species -- or 56 percent of those sampled -- were likely threatened with extinction, including 85 percent of amphibians and 61 percent of mammals.

This compares to the 28 percent of species assessed by the IUCN Red List.

"We see that across most land areas and coastal areas around the world that the average extinction risk would be higher if we included data deficient species," said Borgelt.

A global United Nations biodiversity assessment in 2019 warned that as many as a million species were threatened with extinction due to a number of factors including habitat loss, invasive species and climate change.

Borgelt said the analysis revealed some hotspots for data-deficient species risk, including Madagascar and southern India. He said he hoped the study could help the IUCN develop its strategy for underreported species, adding that the team had reached out to the union.

"With these predictions from machine learning we can get really sort of pre-assessments or we could use those as predictions to prioritise which species have to be looked at by the IUCN," he said.

Head of the IUCN's Red List Craig Hilton-Taylor said the organisation was continuously harnessing new technology with a view to reduce the number of data deficient species.

"We also understand that a proportion of data deficient species are at risk of extinction, and include this in our calculations when we estimate the proportion of threatened species in a group," he told AFP.

(A.Berg--BBZ)