The historic Kunming-Montreal Global Biodiversity Framework, which supports the achievement of the Sustainable Development Goals and builds on the Convention on Biological Diversity’s (CBD) previous Strategic Plans, sets out an ambitious pathway to reach the global vision of a world living in harmony with nature by 2050. Among the Framework’s key elements are 23 targets for 2030. In order to track the progress on the targets, a number of indicators were agreed upon for each target. The B3ALIEN software provides a technical solution to track Target 6: “Reduce the Introduction of Invasive Alien Species by 50% and Minimize Their Impact.” It mainly focusses on the headline indicator: rate of invasive alien species establishment, but can provide input to some of the complementary indicators.
Decision makers at local, regional, national and international levels need accurate and reliable information about status, trends, threats, and they need data presented in an actionable and understandable format, with measures of uncertainty. Furthermore, we need synthesized data products that can be combined with other environmental data, such as climate, soil chemistry, land use, altitude... B3ALIEN is built upon the concept of data cubes developed in the Horizon Europe Biodiversity Building Blocks for Policy project (b- cubed.eu). It uses the solid foundations of the GBIF infrastructure, where tools such as the GBIF Taxonomic Backbone and the Global Registry of Introduced and Invasive Species are available by default. Readily available occurrence data is used to determine and estimate accurately the rate of introduction of alien species..
from b3alien import b3cube
from b3alien import visualisation
from b3alien.utils.runtime import in_jupyter
from b3alien import griis
from b3alien import simulation
import matplotlib
matplotlib.use("TkAgg")cube = b3cube.OccurrenceCube("gs://b-cubed-eu/data_PT-30b.parquet", gproject='$GPROJECT-ID')print(cube.df) kingdom kingdomkey phylum phylumkey class \
0 Plantae 6 Charophyta 7819616 Charophyceae
1 Plantae 6 Tracheophyta 7707728 Polypodiopsida
2 Plantae 6 Tracheophyta 7707728 Polypodiopsida
3 Plantae 6 Tracheophyta 7707728 Polypodiopsida
4 Plantae 6 Tracheophyta 7707728 Polypodiopsida
... ... ... ... ... ...
52187 Plantae 6 Tracheophyta 7707728 Magnoliopsida
52188 Plantae 6 Tracheophyta 7707728 Magnoliopsida
52189 Plantae 6 Tracheophyta 7707728 Magnoliopsida
52190 Plantae 6 Marchantiophyta 9 Jungermanniopsida
52191 Plantae 6 Bryophyta 35 Bryopsida
classkey order orderkey family familykey ... \
0 328 Charales 626 Characeae 8782 ...
1 7228684 Salviniales 7229405 Salviniaceae 6629 ...
2 7228684 Polypodiales 392 Polypodiaceae 2368 ...
3 7228684 Polypodiales 392 Polypodiaceae 2368 ...
4 7228684 Polypodiales 392 Polypodiaceae 2368 ...
... ... ... ... ... ... ...
52187 220 Malpighiales 1414 Euphorbiaceae 4691 ...
52188 220 Malpighiales 1414 Euphorbiaceae 4691 ...
52189 220 Malpighiales 1414 Euphorbiaceae 4691 ...
52190 126 Jungermanniales 381 Calypogeiaceae 2289 ...
52191 327 Pottiales 621 Pottiaceae 4671 ...
classcount ordercount familycount genuscount distinctobservers \
0 1 1 1 1 1
1 11 1 1 1 1
2 1 1 1 1 1
3 1 1 1 1 1
4 6 6 1 1 1
... ... ... ... ... ...
52187 27 4 4 2 1
52188 27 4 4 2 1
52189 26 3 3 3 1
52190 2 2 1 1 1
52191 4 1 1 1 1
occurrences mintemporaluncertainty mincoordinateuncertaintyinmeters \
0 1 2678400 1000.0
1 1 60 23.0
2 1 86400 1000.0
3 1 2505600 1000.0
4 1 86400 1000.0
... ... ... ...
52187 1 1 16.0
52188 1 1 6.0
52189 3 86400 2400.0
52190 1 1 1000.0
52191 1 86400 30.0
cellCode geometry
0 W016N32ACAAA POLYGON ((-17 32.71875, -16.96875 32.71875, -1...
1 W016N32ACADB POLYGON ((-16.90625 32.65625, -16.875 32.65625...
2 W016N32AACCA POLYGON ((-17 32.78125, -16.96875 32.78125, -1...
3 W016N32AACCD POLYGON ((-16.96875 32.75, -16.9375 32.75, -16...
4 W016N32AACCD POLYGON ((-16.96875 32.75, -16.9375 32.75, -16...
... ... ...
52187 W017N32BDBCB POLYGON ((-17.09375 32.65625, -17.0625 32.6562...
52188 W017N32BDBCB POLYGON ((-17.09375 32.65625, -17.0625 32.6562...
52189 W017N32BDBDA POLYGON ((-17.0625 32.65625, -17.03125 32.6562...
52190 W016N32AACDB POLYGON ((-16.90625 32.78125, -16.875 32.78125...
52191 W017N32BBCAD POLYGON ((-17.21875 32.8125, -17.1875 32.8125,...
[52192 rows x 28 columns]
cube._species_richness()print(cube.richness) cell richness
0 W016N30DDDDA 3
1 W016N32AACAC 212
2 W016N32AACAD 152
3 W016N32AACBC 168
4 W016N32AACBD 225
.. ... ...
120 W017N32BDBCA 136
121 W017N32BDBCB 165
122 W017N32BDBDA 189
123 W017N32BDBDB 276
124 W017N32BDBDD 91
[125 rows x 2 columns]
b3cube.plot_richness(cube.richness, cube.df)
CL = griis.CheckList("$YOUR_DIRECTORY/merged_distr.txt")d_s, d_c = b3cube.cumulative_species(cube, CL.species)time, rate = b3cube.calculate_rate(d_c)C1 = simulation.simulate_solow_costello(time, rate, vis=True)Optimization terminated successfully.
Current function value: -263.092115
Iterations: 172
Function evaluations: 287
