6.1 Rate of invasive alien species establishment
2024-03-28 12:00:00 UTC
Headline indicator for Target 6:: Eliminate, minimize, reduce and or mitigate the impacts of invasive alien species on biodiversity and ecosystem services by identifying and managing pathways of the introduction of alien species, preventing the introduction and establishment of priority invasive alien species, reducing the rates of introduction and establishment of other known or potential invasive alien species by at least 50 per cent by 2030, and eradicating or controlling invasive alien species, especially in priority sites, such as islands.
The establishment of invasive alien species (IAS) is a main driver of biodiversity loss. Recent extensive analyses of biological invasions show that the documented numbers of IAS have continued to increase over recent decades (IPBES 2023). Multi-national agreements developed for the purposes of addressing the challenge and negative impacts of IAS require information on the status and trends of IAS establishment – within and across countries. Without a repeated data collection process and up-to-date evidence-base, progress to prevent and reduce the consequences of IAS is hindered, and neither the evaluation nor the achievement of policy targets is feasible.
This indicator links the management success of introduction pathways of IAS to the desired outcome to prevent new IAS country establishments. It directly supports Target 6 of the framework on managing pathways for the introduction of IAS and preventing and reducing their rate of introduction and establishment. It also informs the effectiveness of IAS management actions for the recovery and conservation of species and ecosystems.
Rate of invasive alien species establishment indicator: The number of invasive alien species that are expected to have established in a new region or country compared with the reference period, based on modelled trends in IAS observations.
The unit of measurement is the rate of invasive alien species establishments (number/year). From this we can estimate the trend in the rate of change for the reporting period.
Step 1
The indicator is calculated from compiled country checklists of introduced and invasive species, within the Global Register of Introduced and Invasive Species (GRIIS; Pagad et al. 2018; Pagad et al. 2022). GRIIS is maintained by the IUCN SSC Invasive Species Specialist Group (ISSG), published as open-access, interoperable checklist datasets through the Global Biodiversity Information Facility (GBIF), and available via ‘invasive alien species’ links from the country profile pages of the CBD global Clearing House Mechanism (CHM). The checklists are updatable through national expert author teams coordinated globally by GRIIS, and form the backbone of country monitoring frameworks for IAS. The information value of this indicator is dependent on availability of the most up to date data on new IAS established in the country, and ongoing updates to the GRIIS country checklists and the Alien Species First Record Database (Seebens et al. 2017; see e.g. 2023 update (v3) of the Alien Species First Record Database). It is also informed by ongoing collation of in-country evidence on which species have started to cause harm (have a negative impact) or continue to do so, and this information is fed back into the GRIIS country checklists.
Step 2
The indicator can be calculated for different species subsets: (1) Species known to have an impact (i.e., based on the subset of invasive alien species in GRIIS for which there is evidence of impact in at least one country, denoted as ‘Invasive’ in the ‘isInvasive’ field of the country checklists); (2) All alien (introduced) species in a country using GRIIS data or alternative sources; (3) All alien species introduced via a particular pathway of introduction.
Step 3
For the subset of ‘isInvasive’ species in the country (Pagad et al. 2022), the dates of introduction, estimated dates of introduction, or dates of ‘first record’ are required (Seebens 2023). These data can be collated from in-country sources, or obtained from the IAS First Record Database (Seebens 2023) or similar sources. Date information can be compiled on a taxon-by-taxon basis, starting with those taxa for which the data are most readily available and complete.
Step 4
Raw data trends can be compiled showing the known number of newly-established species per year.
Step 5
To estimate the ‘Rate of Establishment Indicator’, the above information is then modelled to estimate new species invasions per year, along with an estimate of uncertainty (McGeoch et al. 2023). The model is based on a time series that measures the number of observed species in each time period, and estimates the rate of introduction of new species from these IAS observations. The observed number of IAS is the product of the number of introductions and the observation probability of the introduced species (Figure. 1). See supporting information providing guidance to countries on constructing such indicators for guidance on this estimation procedure.
Step 6
Comparable use of this indicator by Parties relies on the use of the same baseline dataset and a consistent method for estimating the rate parameter. Further tools are currently being prepared by GEO BON to assist countries with this step.
Figure 1: The graph on the left show an example of a step change in the true number of introductions (black line). This is estimated from checklist data updated over time. We see that survey effort (coloured dotted line) affects our knowledge of change in the rate of IAS (number per year). The true number is estimated with a model as described by McGeoch et al. (2023). The graph on the right shows the change in the rate of establishment of IAS over a longer period. This trend is estimated as a linear trend (as estimated with a slope from a regression) through a time series of IAS per year.
Detailed methodology for compiling country checklists within the Global Register of Introduced and Invasive Species (GRIIS, see previous section) is described in Pagad et al. (2018), and included within the metadata associated with each checklist, available through GBIF and linked from the CHM country profile pages.
The methodology for compiling the IAS First Record Database is described in Seebens et al (2017).
The methodology for the indicator is described in McGeoch et al. (2023) and its national application is supported by GEO BON. As described in this paper governments and institutions responsible for assessing invasive alien species at the national level can follow four straightforward steps to build the data needed to estimate rates of invasive alien species (IAS) establishment (Figure 2),.
Parties can contribute to these efforts and to their own IAS establishment indicator by updating these data sources where necessary, and over time through ongoing observations of new species introductions and new evidence of IAS impacts within countries (Latombe et al. 2017).
GEO BON is producing additional material and tools to further support Parties in using this indicator, and will support a baseline indicator calculation that Parties can use in their reporting, or replace with their own calculation. Updates on this indicator will be made available at: https://geobon.org/ebvs/indicators/
Figure 2. Four steps for countries to build data required for this indicator (taken from McGeoch et al. 2023, Fig 3).
The indicator is available now. Indicator values can be produced for major taxonomic groups and countries with IAS checklists. The indicator can be updated annually, although annual updates rely on longer-term trends and interpreting change within the estimated uncertainty bounds.
Indicator will be available annually, from 1970 – present, although with highly variable levels of confidence depending on data availability at global and national levels.
Expert organizations, scientific societies, national and public repositories (e.g. IUCN ISSG, GRIIS, GBIF, CABI, GEO BON infrastructure)
GEO BON, IUCN ISSG, national and subnational agencies responsible for monitoring IAS.
Gaps in overall data availability are reflected in the large variability of the completeness of the GRIIS country checklists. The methods outlined above are designed to deliver useful information in the face of incomplete data. The IPBES Invasive Alien Species Assessment highlighted the issue of incomplete IAS inventories across realms, taxonomic groups and geographic regions, in particular highlighting marine, tropical and Arctic ecosystems; microorganisms and invertebrates; and Africa and Central Asia (IPBES 2023).
The indicator can be expressed for specific taxonomic groups only, for examples for plants and all vertebrates or subsets such as mammals, and other taxa (e.g. microbes) with inadequate data omitted. Species-poor taxonomic groups can also be aggregated by introduction pathways (e.g. release, escape, contaminant, stowaway, corridors, and unaided natural dispersal) for rate of establishment per pathway.
Scale of application:Global, Regional, National
Scale of data disaggregation/aggregation
Global/ regional scale indicator can be disaggregated to national level: Yes
National data is collated to form global indicator: Yes
This indicator can also be disaggregated to include within-country levels, in particular relating to islands.
This indicator is calculated based on data collected at the national level, supplemented by globally aggregated sources, see above.
Differences between country and international estimates may originate from limited data availability and the size and impact of IAS interventions and control measures. Filling species data gaps and confirming detections will reduce discrepancies. In countries where resources are limited, global analysis e.g. through literature synthesis, can supplement data available nationally. Because the rate of IAS establishment is estimated over several years, the impact of new national, regional, or global prevention and control interventions will take time to manifest as changes in index values at higher levels.
6d.1 Description of the methodology
The indicator is based on a model-estimated change in the number of new introductions per year, assuming a sampling effect (Belmaker et al. 2009, McGeoch et al. 2012, McGeoch et al. 2023).
6d.2 Additional methodological details
The compendium of country data to be used for global indicator production is available (Pagad et al. 2022).
6d.3 Description of the mechanism for collecting data from countries
Details available in Pagad et al. (2018).
An earlier version of this indicator was reported in the
It will be relevant to
No
Where the relevant data is available through GRIIS, this indicator can be disaggregated by species, taxon, region, country, sub-national unit (including islands), protected areas, pathways or type of impact.
As invasive species are a key driver of biodiversity loss, there is a clear link with goals A and B and its associated indicators (e.g. Red List Index, Red List of Ecosystems)
Group on Earth Observations Biodiversity Observation Network (GEO BON)
IUCN Invasive Species Specialist Group (ISSG)
Melodie McGeoch, Monash University/GEO BON(melodie.mcgeoch@monash.edu)
GEO BON Secretariat (info@geobon.org)
Shyama Pagad, IUCN ISSG (s.pagad@auckland.ac.nz)
IPBES (2023) Summary for Policymakers of the Thematic Assessment Report on Invasive Alien Species and their Control of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services. Roy, H. E., Pauchard, A., Stoett, P., Renard Truong, T., Bacher, S., Galil, B. S., Hulme, P. E., Ikeda, T., Sankaran, K. V., McGeoch, M. A., Meyerson, L. A., Nuñez, M. A., Ordonez, A., Rahlao, S. J., Schwindt, E., Seebens, H., Sheppard, A. W., and Vandvik, V. (eds.). IPBES secretariat, Bonn, Germany. https://doi.org/10.5281/zenodo.7430692
Latombe (2017). Latombe, G., P. Pysek, J. M. Jeschke et al. (2017). A vision for global monitoring of biological invasions. Biological Conservation 213:295-308. http://dx.doi.org/10.1016/j.biocon.2016.06.013
McGeoch et al. (2023). McGeoch, M. A., Buba, Y., Arlé, E., et al. (2023). Invasion trends: An interpretable measure of change is needed to support policy targets. Conservation Letters, 16, e12981. https://doi.org/10.1111/conl.12981
Pagad (2018) Pagad, S., Genovesi, P., Carnevali, L. et al. Introducing the Global Register of Introduced and Invasive Species. Sci Data 5, 170202 (2018). https://doi.org/10.1038/sdata.2017.202
Pagad et al. (2022)Pagad, S., Bisset, S., Genovesi, P. et al. Country Compendium of the Global Register of Introduced and Invasive Species. Sci Data 9, 391 (2022). https://doi.org/10.1038/s41597-022-01514-z
Seebens et al. (2017) Seebens, H., Blackburn, T., Dyer, E. et al. No saturation in the accumulation of alien species worldwide. Nat Commun 8, 14435 (2017). https://doi.org/10.1038/ncomms14435
Seebens (2023), Alien Species First Records Database (Version 3.1).Deposited 25 October 2023.Zenodo. https://zenodo.org/doi/10.5281/zenodo.3690741 .NB this link will always resolve to the latest version of this database.
6.1 Rate of invasive alien species establishment
2024-03-28 12:00:00 UTC
Headline indicator for Target 6:: Eliminate, minimize, reduce and or mitigate the impacts of invasive alien species on biodiversity and ecosystem services by identifying and managing pathways of the introduction of alien species, preventing the introduction and establishment of priority invasive alien species, reducing the rates of introduction and establishment of other known or potential invasive alien species by at least 50 per cent by 2030, and eradicating or controlling invasive alien species, especially in priority sites, such as islands.
The establishment of invasive alien species (IAS) is a main driver of biodiversity loss. Recent extensive analyses of biological invasions show that the documented numbers of IAS have continued to increase over recent decades (IPBES 2023). Multi-national agreements developed for the purposes of addressing the challenge and negative impacts of IAS require information on the status and trends of IAS establishment – within and across countries. Without a repeated data collection process and up-to-date evidence-base, progress to prevent and reduce the consequences of IAS is hindered, and neither the evaluation nor the achievement of policy targets is feasible.
This indicator links the management success of introduction pathways of IAS to the desired outcome to prevent new IAS country establishments. It directly supports Target 6 of the framework on managing pathways for the introduction of IAS and preventing and reducing their rate of introduction and establishment. It also informs the effectiveness of IAS management actions for the recovery and conservation of species and ecosystems.
Rate of invasive alien species establishment indicator: The number of invasive alien species that are expected to have established in a new region or country compared with the reference period, based on modelled trends in IAS observations.
The unit of measurement is the rate of invasive alien species establishments (number/year). From this we can estimate the trend in the rate of change for the reporting period.
Step 1
The indicator is calculated from compiled country checklists of introduced and invasive species, within the Global Register of Introduced and Invasive Species (GRIIS; Pagad et al. 2018; Pagad et al. 2022). GRIIS is maintained by the IUCN SSC Invasive Species Specialist Group (ISSG), published as open-access, interoperable checklist datasets through the Global Biodiversity Information Facility (GBIF), and available via ‘invasive alien species’ links from the country profile pages of the CBD global Clearing House Mechanism (CHM). The checklists are updatable through national expert author teams coordinated globally by GRIIS, and form the backbone of country monitoring frameworks for IAS. The information value of this indicator is dependent on availability of the most up to date data on new IAS established in the country, and ongoing updates to the GRIIS country checklists and the Alien Species First Record Database (Seebens et al. 2017; see e.g. 2023 update (v3) of the Alien Species First Record Database). It is also informed by ongoing collation of in-country evidence on which species have started to cause harm (have a negative impact) or continue to do so, and this information is fed back into the GRIIS country checklists.
Step 2
The indicator can be calculated for different species subsets: (1) Species known to have an impact (i.e., based on the subset of invasive alien species in GRIIS for which there is evidence of impact in at least one country, denoted as ‘Invasive’ in the ‘isInvasive’ field of the country checklists); (2) All alien (introduced) species in a country using GRIIS data or alternative sources; (3) All alien species introduced via a particular pathway of introduction.
Step 3
For the subset of ‘isInvasive’ species in the country (Pagad et al. 2022), the dates of introduction, estimated dates of introduction, or dates of ‘first record’ are required (Seebens 2023). These data can be collated from in-country sources, or obtained from the IAS First Record Database (Seebens 2023) or similar sources. Date information can be compiled on a taxon-by-taxon basis, starting with those taxa for which the data are most readily available and complete.
Step 4
Raw data trends can be compiled showing the known number of newly-established species per year.
Step 5
To estimate the ‘Rate of Establishment Indicator’, the above information is then modelled to estimate new species invasions per year, along with an estimate of uncertainty (McGeoch et al. 2023). The model is based on a time series that measures the number of observed species in each time period, and estimates the rate of introduction of new species from these IAS observations. The observed number of IAS is the product of the number of introductions and the observation probability of the introduced species (Figure. 1). See supporting information providing guidance to countries on constructing such indicators for guidance on this estimation procedure.
Step 6
Comparable use of this indicator by Parties relies on the use of the same baseline dataset and a consistent method for estimating the rate parameter. Further tools are currently being prepared by GEO BON to assist countries with this step.
Figure 1: The graph on the left show an example of a step change in the true number of introductions (black line). This is estimated from checklist data updated over time. We see that survey effort (coloured dotted line) affects our knowledge of change in the rate of IAS (number per year). The true number is estimated with a model as described by McGeoch et al. (2023). The graph on the right shows the change in the rate of establishment of IAS over a longer period. This trend is estimated as a linear trend (as estimated with a slope from a regression) through a time series of IAS per year.
Detailed methodology for compiling country checklists within the Global Register of Introduced and Invasive Species (GRIIS, see previous section) is described in Pagad et al. (2018), and included within the metadata associated with each checklist, available through GBIF and linked from the CHM country profile pages.
The methodology for compiling the IAS First Record Database is described in Seebens et al (2017).
The methodology for the indicator is described in McGeoch et al. (2023) and its national application is supported by GEO BON. As described in this paper governments and institutions responsible for assessing invasive alien species at the national level can follow four straightforward steps to build the data needed to estimate rates of invasive alien species (IAS) establishment (Figure 2),.
Parties can contribute to these efforts and to their own IAS establishment indicator by updating these data sources where necessary, and over time through ongoing observations of new species introductions and new evidence of IAS impacts within countries (Latombe et al. 2017).
GEO BON is producing additional material and tools to further support Parties in using this indicator, and will support a baseline indicator calculation that Parties can use in their reporting, or replace with their own calculation. Updates on this indicator will be made available at: https://geobon.org/ebvs/indicators/
Figure 2. Four steps for countries to build data required for this indicator (taken from McGeoch et al. 2023, Fig 3).
The indicator is available now. Indicator values can be produced for major taxonomic groups and countries with IAS checklists. The indicator can be updated annually, although annual updates rely on longer-term trends and interpreting change within the estimated uncertainty bounds.
Indicator will be available annually, from 1970 – present, although with highly variable levels of confidence depending on data availability at global and national levels.
Expert organizations, scientific societies, national and public repositories (e.g. IUCN ISSG, GRIIS, GBIF, CABI, GEO BON infrastructure)
GEO BON, IUCN ISSG, national and subnational agencies responsible for monitoring IAS.
Gaps in overall data availability are reflected in the large variability of the completeness of the GRIIS country checklists. The methods outlined above are designed to deliver useful information in the face of incomplete data. The IPBES Invasive Alien Species Assessment highlighted the issue of incomplete IAS inventories across realms, taxonomic groups and geographic regions, in particular highlighting marine, tropical and Arctic ecosystems; microorganisms and invertebrates; and Africa and Central Asia (IPBES 2023).
The indicator can be expressed for specific taxonomic groups only, for examples for plants and all vertebrates or subsets such as mammals, and other taxa (e.g. microbes) with inadequate data omitted. Species-poor taxonomic groups can also be aggregated by introduction pathways (e.g. release, escape, contaminant, stowaway, corridors, and unaided natural dispersal) for rate of establishment per pathway.
Scale of application:Global, Regional, National
Scale of data disaggregation/aggregation
Global/ regional scale indicator can be disaggregated to national level: Yes
National data is collated to form global indicator: Yes
This indicator can also be disaggregated to include within-country levels, in particular relating to islands.
This indicator is calculated based on data collected at the national level, supplemented by globally aggregated sources, see above.
Differences between country and international estimates may originate from limited data availability and the size and impact of IAS interventions and control measures. Filling species data gaps and confirming detections will reduce discrepancies. In countries where resources are limited, global analysis e.g. through literature synthesis, can supplement data available nationally. Because the rate of IAS establishment is estimated over several years, the impact of new national, regional, or global prevention and control interventions will take time to manifest as changes in index values at higher levels.
6d.1 Description of the methodology
The indicator is based on a model-estimated change in the number of new introductions per year, assuming a sampling effect (Belmaker et al. 2009, McGeoch et al. 2012, McGeoch et al. 2023).
6d.2 Additional methodological details
The compendium of country data to be used for global indicator production is available (Pagad et al. 2022).
6d.3 Description of the mechanism for collecting data from countries
Details available in Pagad et al. (2018).
An earlier version of this indicator was reported in the
It will be relevant to
No
Where the relevant data is available through GRIIS, this indicator can be disaggregated by species, taxon, region, country, sub-national unit (including islands), protected areas, pathways or type of impact.
As invasive species are a key driver of biodiversity loss, there is a clear link with goals A and B and its associated indicators (e.g. Red List Index, Red List of Ecosystems)
Group on Earth Observations Biodiversity Observation Network (GEO BON)
IUCN Invasive Species Specialist Group (ISSG)
Melodie McGeoch, Monash University/GEO BON(melodie.mcgeoch@monash.edu)
GEO BON Secretariat (info@geobon.org)
Shyama Pagad, IUCN ISSG (s.pagad@auckland.ac.nz)
IPBES (2023) Summary for Policymakers of the Thematic Assessment Report on Invasive Alien Species and their Control of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services. Roy, H. E., Pauchard, A., Stoett, P., Renard Truong, T., Bacher, S., Galil, B. S., Hulme, P. E., Ikeda, T., Sankaran, K. V., McGeoch, M. A., Meyerson, L. A., Nuñez, M. A., Ordonez, A., Rahlao, S. J., Schwindt, E., Seebens, H., Sheppard, A. W., and Vandvik, V. (eds.). IPBES secretariat, Bonn, Germany. https://doi.org/10.5281/zenodo.7430692
Latombe (2017). Latombe, G., P. Pysek, J. M. Jeschke et al. (2017). A vision for global monitoring of biological invasions. Biological Conservation 213:295-308. http://dx.doi.org/10.1016/j.biocon.2016.06.013
McGeoch et al. (2023). McGeoch, M. A., Buba, Y., Arlé, E., et al. (2023). Invasion trends: An interpretable measure of change is needed to support policy targets. Conservation Letters, 16, e12981. https://doi.org/10.1111/conl.12981
Pagad (2018) Pagad, S., Genovesi, P., Carnevali, L. et al. Introducing the Global Register of Introduced and Invasive Species. Sci Data 5, 170202 (2018). https://doi.org/10.1038/sdata.2017.202
Pagad et al. (2022)Pagad, S., Bisset, S., Genovesi, P. et al. Country Compendium of the Global Register of Introduced and Invasive Species. Sci Data 9, 391 (2022). https://doi.org/10.1038/s41597-022-01514-z
Seebens et al. (2017) Seebens, H., Blackburn, T., Dyer, E. et al. No saturation in the accumulation of alien species worldwide. Nat Commun 8, 14435 (2017). https://doi.org/10.1038/ncomms14435
Seebens (2023), Alien Species First Records Database (Version 3.1).Deposited 25 October 2023.Zenodo. https://zenodo.org/doi/10.5281/zenodo.3690741 .NB this link will always resolve to the latest version of this database.
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