Global Biotic Interactions

Review of Species Interactions Available Through ChecklistBank

Mon, 20 Apr 2026 00:00:00 +0000

Figure 1. Screenshot of Afromoths.net as accessed on 2026-04-20. Afromoths "[...] provides an online database of the Afrotropical moth species (Lepidoptera), updated with the latest information obtained from 10,000+ published sources and our studies.[...]" [1] .

On Wed 22 October 2025, Rod Page gave a talk [1] in Bogotá, Columbia mentioning the “Afromoths” project by De Prins & De Prins [2] as an example. Afromoths is said to cover “all relevant information on every Afrotropical moth species” of Sub-Saharan Africa and includes descriptions of over 12k associated (plant) hosts (e.g., Daphnis nerii has host Nerium oleander L.) and over 500 parasites records (e.g., Agrionympha capensis has parasite Mesocomys pulchriceps Cameron) [3].

Facilitated by the Belgian Biodiversity Platform, Belspo, the Afromoth data is currently available through ChecklistBank in the Catalogue of Life Data Package (ColDP) format ([4], https://github.com/CatalogueOfLife/coldp). The ColDP format, developed by Markus Döring, Geoff Ower and colleagues, includes explicit support for species interactions, similar to how Darwin Core supports species interactions via their Resource Relationship Extension.

An example of the first record in a 2026 copy of their ColDP archive with sha256 and md5 fingerprints [5] hash://sha256/dd778e9038f87067815f9c7afdec1286db2e4cc08a298cbab27fe23dba2e1b44 and hash://md5/7e21ac93fb0e5e786f1254d6bd0a2341 respectively, was generated using the following bash script along with Preston v0.11.6 and miller:

preston cat \
 --algo md5 \
 --anchor hash://md5/a9aaa7113716ab2f87ede6f6b70297c8 \
 --remote https://zenodo.org \
 'line:zip:hash://md5/7e21ac93fb0e5e786f1254d6bd0a2341!/speciesinteractions.csv!/L1,L2' \
 | mlr --icsv --oxtab cat

producing:

taxonID                    S100010010
relatedTaxonID             
relatedTaxonScientificName Mesocomys pulchriceps Cameron
type                       has parasite
referenceID                6968
remarks                    

This record claims some reference with id 6968 that a taxon with id S100010010 has a parasite with a scientific name Mesocomys pulchriceps Cameron .

After extending Elton’s support to include Catalogue of Life Data Package, you can now access the record without having to join this records with their taxonomic and reference tables via an interpreted interaction record obtained via a published GloBI data review resource indexed-interactions.tsv.gz [3]:

preston cat \
 --remote https://zenodo.org \
 hash://md5/0c2373f08dc68ec2a44d18edb45d7139 \
| gunzip \
| mlr --itsvlite --oxtab \
 filter '$sourceTaxonId == "S100010010" && $targetTaxonName == "Mesocomys pulchriceps Cameron"'

or, by replaying the associated archived review process [2] and generating interpreted interaction records from the archived ChecklistBank dataset using Elton v0.16.10 via

preston ls \
 --algo md5 \
 --anchor hash://md5/a9aaa7113716ab2f87ede6f6b70297c8 \
 --remote https://zenodo.org \
 | elton stream \
 --algo md5 \
 --data-dir data \
 --prov-dir data \
 --anchor hash://md5/a9aaa7113716ab2f87ede6f6b70297c8 \
 --remote https://zenodo.org \
 | mlr --itsvlite --oxtab \
 filter '$sourceTaxonId == "S100010010" && $targetTaxonName == "Mesocomys pulchriceps Cameron"'

both of which are expected to produce a result including:

argumentTypeId                         https://en.wiktionary.org/wiki/support
[...]                  
sourceTaxonId                          S100010010
sourceTaxonName                        Agrionympha capensis
[...]
interactionTypeId                      http://purl.obolibrary.org/obo/RO_0002445
interactionTypeName                    hasParasite
[...]
targetTaxonName                        Mesocomys pulchriceps Cameron
[...]
referenceCitation                      Prinsloo G. L. & Uys V. M. (Eds.), 2015, Insects of cultivated plants and natural pastures in Southern Africa. vol  issue  pages i–xiv, 1–785
namespace                              urn:lsid:checklistbank.org:dataset:2017
archiveURI                             https://api.checklistbank.org/dataset/2017/archive.zip
lastSeenAt                             2026-03-31T15:23:43.269Z
contentHash                            dd778e9038f87067815f9c7afdec1286db2e4cc08a298cbab27fe23dba2e1b44
eltonVersion                           0.16.10

Discovery and Independent Review of ChecklistBank Associated Interaction Data

To help facilitate automated discovery of species interaction claims embedded in ChecklistBank Datasets, Elton, a GloBI commandline tool, is now able to list datasets with interaction claims using:

elton ls --online --registry checklistbank

On 2026-04-20, running the Elton command above produced the following list of datasets:

urn:lsid:checklistbank.org:dataset:1032
urn:lsid:checklistbank.org:dataset:1049
urn:lsid:checklistbank.org:dataset:1061
urn:lsid:checklistbank.org:dataset:1133
urn:lsid:checklistbank.org:dataset:1166
urn:lsid:checklistbank.org:dataset:1199
urn:lsid:checklistbank.org:dataset:2017
urn:lsid:checklistbank.org:dataset:2169
urn:lsid:checklistbank.org:dataset:2207
urn:lsid:checklistbank.org:dataset:2317
urn:lsid:checklistbank.org:dataset:2362
urn:lsid:checklistbank.org:dataset:124661
urn:lsid:checklistbank.org:dataset:265709

This suggests that a little over 10 datasets in ChecklistBank currently describe at least one species interaction claim. As expected, the Afromoth dataset (i.e., [2], urn:lsid:checklistbank.org:dataset:2017) is included in this list. Other examples include the Universal Chalcidoidea Database (i.e., [6], urn:lsid:checklistbank.org:dataset:124661) and the Catalogue of the Pterophoroidea of the World (i.e., [7], urn:lsid:checklistbank.org:dataset:1199).

This list of dataset identifiers can then be used to track associated datasets, and, if desired, generate interpreted species interaction records. For instance, for the Afromoths dataset with id urn:lsid:checklistbank.org:dataset:2017, a tab-seperated values table of their interpreted interaction data can be generated via:

elton track 'urn:lsid:checklistbank.org:dataset:2017'
elton interactions 'urn:lsid:checklistbank.org:dataset:2017' \
 > interactions.tsv

assuming that ChecklistBank Web API is reachable, the tool elton is available, and the Afromoths dataset has the CoLDP format. These assumptions are expected to no longer hold in the near future because websites come and go, software tool versions may no longer be available, and dataset formats change or become obsolete.

To have a more resilient approach to capturing the tracked dataset and the interpretation process, the associated resource can be captured in a so-called “Bill of Material” which includes the digital fingerprints (or signatures) of the resources needed for Elton to interpret the dataset. This approach is used in the GloBI review process, and can be summarized as follows:

elton track --algo md5 \
 --prov-mode \
 'urn:lsid:checklistbank.org:dataset:2017' \
 | elton tee --algo md5 \
 | preston append --algo md5 \
 |  elton stream --algo md5 --data-dir data --prov-dir data \
 | head -n2

in which the first line tells elton to generate the Data Bill of Materials (DataBOM) to document the versioned resources used to track, and interpret, the data associated with urn:lsid:checklistbank.org:dataset:2017 in rdf/nquads via the --prov-mode argument. Following, elton stores the associated resource in the data folders and the DataBOM is appended to a local Preston archive. In the second to last line (i.e., elton stream ...), elton is instructed to generate interaction records associated this DataBOM. Finally, in the last line, the first two lines in the resulting interaction record table are printed, resulting, at time of writing 2026-04-21, in the following record expressed in XTAB format:

The results in the data/ folder now contains all resources needed to reproduce this result, including the Data Bill of Materials outlining the process and versioned resources used. Because this DataBOM is a text file expressed in rdf/nquads, their digital fingerprint uniquely identifies the process and associated resources. Now, this DataBOM fingerprint (or signature) can be used to reproduce the process, provided that the referenced digital resource versions are available in data/ folder or elsewhere.

As part of the GloBI review process, such a DataBOM fingerprint (i.e., hash://md5/a9aaa7113716ab2f87ede6f6b70297c8) for the Afromoths dataset was published in [3] along with their referenced versioned resource. With this, you can re-generated the interpreted interaction records by running:

preston ls \
 --algo md5 \
 --remote https://zenodo.org \
 --anchor hash://md5/a9aaa7113716ab2f87ede6f6b70297c8 \
| elton stream \
 --algo md5 \
 --data-dir data \
 --prov-dir data \
 --anchor hash://md5/a9aaa7113716ab2f87ede6f6b70297c8 \
| head -n2

where the DataBOM fingerprint hash://md5/a9aaa7113716ab2f87ede6f6b70297c8 is used to define (or anchor) the resources needed to produced the interpreted interaction data records. With this, we established a way to reproduce the process to generate interaction records without having the assume that ChecklistBank data sevices remain available and produce expected results. Instead, we rely on an archived copy (e.g., [3]) of the process and the versioned resources used. And, because digital fingerprints [5] are location independent and storage media agnostic, this archived copy can be stored in whatever digital storage media may be available. In this case, we used Zenodo to store a copy of the Afromoths archive.

Figure 2. A search result on Global Biotic Interactions associated with dataset "Afromoths" discovered through ChecklistBank [2] as seen on 2026-04-20.

Additional reviews associated with the ChecklistBank datasets can be found via GloBI’s Zenodo Community or by clicking on the “archived review” badges on https://globalbioticinteractions.org/datasets or search results (see Figure 2.).

Discussion

Biodiversity data platforms such as ChecklistBank offer the ability to describe species interaction claims through registered datasets (e.g., [2], [6], [7]) using the Catalogue of Life Data Package (CoLDP) format. And, as of early 2026, GloBI helps discover these datasets via their search indexes, reviews and data products. This is yet another example how existing datasets in data infrastructures can be reused and integrated via review and data services associated with Global Biotic Interactions. With this, hopefully, these datasets can be more easily found just like their existing data cousins in the many other available data formats (e.g., DwC Associated Taxa, DwC Assocated Occurrences, DwC Resource Relations, or whatever other models happen to be in fashion).

A Note on CoLDP Schema Discovery and Dialects

On implementing GloBI’s support for extracting species interaction claims from ColDP formatted datasets, three distinct dialect were found. Because ColDP does not explicitly state the schema of the associated resources nor their location/name, elton implements ths following stategy to help interpret the available datasets:

Query ChecklistBank for datasets with species interaction records.

For each dataset, download their associated ColDP archive.

Inspect each archive and attempt to find the species interaction table by scanning the archive for variations of filenames like SpeciesInteractions.txt, SpeciesInteractions.csv, SpeciesInteractions.tsv, speciesinteractions.txt, …

Inspect the header of the species interaction table found, and attempt to detect one of three dialects used: (a) the TaxonWorks dialect (e.g., [6]) (b) the Belgium dialect (e.g., [2]) and (c) the Hobern dialect (e.g., [7]). See associated test cases and data package examples for more information.

Also, note that, unlike the relationshipOfResourceID of the DwC Resource Relationship Extension, the species interaction table in ColDP does not yet appear to support identifiers for the interaction type terms used. This is why a built-in translation table was introduced to map terms like “parasite of” to their RO equivalent http://purl.obolibrary.org/obo/RO_0002445 with label parasiteOf . Perhaps, a future version of the ColDP format will introduce support for species interaction type identifiers (e.g., typeID) to help more explicitly link the interaction type to their associated definition.

References

[1] Page, R.D.M. (2025). Using links from wikis to help discover content in the Biodiversity Heritage Library (BHL) Wikimedia and Biodiversity Data A Mutualistic Relationship in the Open Knowledge Ecosystem. Presented at Living Data/ Datos Vivos 2025 in Bogotá, Colombia on 2025-10-22. https://livingdata2025.com/program.html?abstract=7010913 https://youtu.be/wXaHJ85g88A?t=5814 .

[2] De Prins J., & De Prins W. (2006, October). Afromoths, online database of Afrotropical moth species (Lepidoptera). https://checklistbank.org/dataset/2017 https://doi.org/10.48580/d4fl.v124 https://www.afromoths.net/. Formerly published as a DwC archive through GBIF https://ipt.biodiversity.be/archive.do?r=afromoths https://www.gbif.org/dataset/65c9103f-2fbf-414b-9b0b-e47ca96c5df2 and https://doi.org/10.15468/s1kwuw .

[3] Elton, Nomer, & Preston. (2026). Versioned Archive and Review of Biotic Interactions and Taxon Names Found within urn:lsid:checklistbank.org:dataset:2017 hash://md5/a9aaa7113716ab2f87ede6f6b70297c8. Zenodo. https://doi.org/10.5281/zenodo.19389793.

[4] Döring, M., & Ower, G. (2019). The Catalogue of Life Data Package - A new format for exchanging nomenclatural and taxonomic information. Biodiversity Information Science and Standards, 3, e38771. https://doi.org/10.3897/biss.3.38771.

[5] Elliott M.J., Poelen, J.H. & Fortes, J.A.B. (2023) Signing data citations enables data verification and citation persistence. Sci Data. https://doi.org/10.1038/s41597-023-02230-y hash://sha256/f849c870565f608899f183ca261365dce9c9f1c5441b1c779e0db49df9c2a19d

[6] UCD Community. (2025). Universal Chalcidoidea Database curated in TaxonWorks (Apr 2025). https://doi.org/10.48580/d758p

[7] Hobern, D., & Gielis, C. (2025). Catalogue of the Pterophoroidea of the World (D. Hobern, Ed.; 1.1.25.304). Catalogue of Life, Amsterdam, Netherlands. https://doi.org/10.48580/d3gd.

A Way To Compile A European Atlas of Plant-Pollinator Associations

Thu, 22 Jan 2026 00:00:00 +0000

Figure 1. Density of flower visitation and pollination records found in a version of the GloBI Corpus of Reviewed Interaction Datasets [4]. Darker green indicates higher density of data, whereas lighter yellow color indicate lower data density. Created using OpenStreetMap, Eurostat/GISCO Geographical Data, DuckDB, and QGIS .

Many openly accessible datasets exist that describe how plants interact with their pollinators (e.g., bees, bats, birds). And, a EU Horizon project “Butterfly” [1] aims to use existing data, complemented by field observations, to establish EuroAPPA, a European Atlas of Plant Pollinator Associations.

There’s many ways to build such an atlas and the text below describes one of them. The method below demonstrates how to combine an existing GloBI Corpus of Review Data [4] and Eurostat/GISCO Geographical country data with DuckDB [2], a small but mighty database, and QGIS, an open source geographic information system tool to create maps to show the geographic distribution of existing flower visitation and pollination record claims.

Getting the Data

A Dec 2025 compilation of GloBI reviewed datasets is available through:

Poelen, J. H. (ed.), & Global Biotic Interactions Community. (2025). Global Biotic Interactions (GloBI) Review Dataset Corpus hash://md5/c326e584fb61f95d0075710c63dc2a33 [Data set]. Zenodo. https://doi.org/10.5281/zenodo.18064921

This compilation dataset includes a derived file that includes reviewed interaction records in a gzipped tab-separated format interactions.tsv.gz with digital fingerprint hash://md5/7c12420410e0fea43608308c387fa89c .

Also, a GeoPackage CNTR_RG_20M_2024_4326.gpkg with digital fingerprint hash://md5/8f345c975eb2ba6b1c92ea1ae27ec4cf was retrieved from https://ec.europa.eu/eurostat/web/gisco/geodata/administrative-units/countries on 2026-01-21 to help delineate current administrative boundaries of countries of interest.

Building A GeoPackage Using DuckDB

Using the GloBI data review corpus and downloaded Eurostat/GISCO geographical data, a GeoPackage euroappa.gpkg was created by selecting only georeferenced flower visitation and pollination claims within EU countries in addition to the United Kingdom, Norway, Switzerland and Ukraine.

More specifically, the GeoPackage euroappa.gpkg was generated by running using DuckDB v1.2.1 8e52ec4395 as follows:

cat generate-euroappa.sql | duckdb

with generate-euroappa.sql containing:

INSTALL spatial;
LOAD spatial;
  
CREATE TABLE IF NOT EXISTS interactions 
AS SELECT 
  ST_POINT(decimalLongitude,decimalLatitude) as location, 
  decimalLatitude,
  decimalLongitude,
  sourceTaxonName, 
  interactionTypeName,
  targetTaxonName, 
  "http://rs.tdwg.org/dwc/terms/eventDate" as eventDate,
  referenceCitation, 
  citation, 
  namespace, 
  lastSeenAt
FROM 
  'interactions.tsv.gz'
WHERE 
  interactionTypeName IN ('flowersVisitedBy','visitsFlowersOf', 'pollinates', 'pollinatedBy')
  AND
  ST_IsValid(location);


CREATE INDEX IF NOT EXISTS my_idx ON interactions USING RTREE (location);

COPY (
 SELECT interactions.*, countries.ISO3_CODE 
 FROM interactions
  JOIN (
    SELECT 
      geom AS country, 
      ISO3_CODE 
    FROM 
      'CNTR_RG_20M_2024_4326.gpkg' 
    WHERE 
      EU_STAT = 'T' 
      OR 
      ISO3_CODE IN ['GBR', 'NOR', 'CHE', 'UKR']
  ) AS countries
  ON ST_Within(interactions.location, countries.country)
) TO 'euroappa.gpkg'
WITH (FORMAT gdal, DRIVER 'GPKG', SRS 'EPSG:4326');

Clustering Data using DuckDB and H3

The resulting geopackage was clustered using h3 [3] on resolution level 4 (less granular) and 6 (more granular) to highlight the geographic distribution of flower visitation and pollination claims. These clustered data were packaged in data files euroappa-h3-level-4.gpkg and euroappa-h3-level-6.gpkg respectively and generated by:

cat generate-euroappa-h3-level-6.sql | duckdb

with generate-euroappa-h3-level-6.sql containing:

INSTALL spatial;
LOAD spatial;
INSTALL h3 FROM community;
LOAD h3;

COPY (
  SELECT 
    ST_GeomFromText(h3_cell_to_boundary_wkt(h3_cell)) AS cell_boundary, 
    number_of_records 
  FROM (
    SELECT 
      h3_latlng_to_cell(ST_Y(geom), ST_X(geom), 6) AS h3_cell,
      LOG(1+COUNT(*)) AS number_of_records
    FROM 
      'euroappa.gpkg'
    GROUP BY 
      h3_cell
  ) 
) TO 'euroappa-h3-level-6.gpkg'
WITH (FORMAT gdal, DRIVER 'GPKG', SRS 'EPSG:4326');

Visualizing Geospatial Maps Using QGIS

Figure 2. Density of flower visitation and pollination records found in a version of the GloBI Corpus of Reviewed Interaction Datasets [4]. Darker colors indicates higher density of data, whereas lighter colors indicate lower data density. Larger green/yellow hexagonals are of less granularity at h3 resolution level 4, and the smaller blue hexagonals are of higher granularity at h3 resolution level 6. Created using OpenStreetMap, Eurostat/GISCO Geographical Data, DuckDB, and QGIS .

After creating the geopackages, QGIS v3.34.4-Prizren was used to visualize the h3 geopackages and put them on a map of the world provided by OpenStreetMap. Figures 1., and 2. highlight geographic areas with higher (darker), lower (lighter), or no data coverage. The larger yellow/green hexagons are at h3 resolution level 4, whereas the smaller blue hexagons are a more granular scale, at h3 resolution level 6. All with © OpenStreetMap contributors and © EuroGeographics for the administrative boundaries .

Discussion

Our examples show that geographic maps indicating data availability of flower visitating and pollinator records can be generating using openly available datasets (e.g., GloBI data review corpus, Eurostat/GISCO geographical data) and open source data processing and visualization tools (e.g., DuckDB, QGIS).

References

[1] BUTTERFLY: Mainstreaming pollinator stewardship in view of cascading ecological, societal and economic impacts of pollinator decline. 2025. CORDIS / Horizon Europe doi:10.3030/101181930

[2] Mark Raasveldt and Hannes Mühleisen. 2019. DuckDB: an Embeddable Analytical Database. In Proceedings of the 2019 International Conference on Management of Data (SIGMOD ‘19). Association for Computing Machinery, New York, NY, USA, 1981–1984. https://doi.org/10.1145/3299869.3320212

[3] Brodsky, I., 2019: H3: Uber’s Hexagonal Hierarchical Spatial Index. Available online: https://eng.uber.com/h3/ Accessed January 22, 2026

[4] Poelen, J. H. (ed.), & Global Biotic Interactions Community. (2025). Global Biotic Interactions (GloBI) Review Dataset Corpus hash://md5/c326e584fb61f95d0075710c63dc2a33 [Data set]. Zenodo. https://doi.org/10.5281/zenodo.18064921

Contributing Datasets

The following datasets contributed to the data and maps in figures 1. and 2. For completeness, their associated data reviews are included also.

Groom, Q.J., Maarten De Groot, M. & Marčiulynienė, D. (2020) Species interation data manually extracted from literature for species . Associated data review: Elton, Nomer, & Preston. (2025). Versioned Archive and Review of Biotic Interactions and Taxon Names Found within AgentschapPlantentuinMeise/ashForestInteractions hash://md5/2273176929e38071b21a6438df74d484. Zenodo. https://doi.org/10.5281/zenodo.16416287

Pocock, Michael J. O.; Evans, Darren M.; Memmott, Jane (2012), Data from: The robustness and restoration of a network of ecological networks, Dryad, Dataset, https://doi.org/10.5061/dryad.3s36r118. For associated GloBI review see: Elton, Nomer, & Preston. (2025). Versioned Archive and Review of Biotic Interactions and Taxon Names Found within globalbioticinteractions/pocock2012 hash://md5/d8f6d8ddafbf5a4bbd6a7bf2cc798f69. Zenodo. https://doi.org/10.5281/zenodo.16416381

Web of Life. http://www.web-of-life.es . For associated GloBI review see Elton, Nomer, & Preston. (2025). Versioned Archive and Review of Biotic Interactions and Taxon Names Found within globalbioticinteractions/web-of-life hash://md5/df58ae253b9a759e387c7f78d05de592. Zenodo. https://doi.org/10.5281/zenodo.16416701

Cristina Preda and Quentin Groom. 2014. Species associations manually extracted from literature. For associated GloBI review see Elton, Nomer, & Preston. (2025). Versioned Archive and Review of Biotic Interactions and Taxon Names Found within qgroom/Vespa-velutina hash://md5/590d7f2941c8c31bfafb4afd4a3a4368. Zenodo. https://doi.org/10.5281/zenodo.16415902

http://iNaturalist.org is a place where you can record what you see in nature, meet other nature lovers, and learn about the natural world. For associated GloBI review see Elton, Nomer, & Preston. (2025). Versioned Archive and Review of Biotic Interactions and Taxon Names Found within globalbioticinteractions/inaturalist hash://md5/2865258bf6e685b25a42f471a2a45475. Zenodo. https://doi.org/10.5281/zenodo.16416416

Sarah E Miller. 6/19/2015. Species associations manually extracted from datasets https://www.nceas.ucsb.edu/interactionweb/resources.html. For associated GloBI review see Elton, Nomer, & Preston. (2025). Versioned Archive and Review of Biotic Interactions and Taxon Names Found within millerse/Plant-Pollinator-Web hash://md5/6d203140d0d7041ddb68493aa1afdd3c. Zenodo. https://doi.org/10.5281/zenodo.16415795

Allen-Perkins, Alfonso, Magrach, Ainhoa, Dainese, Matteo, Garibaldi, Lucas A., Kleijn, David, Rader, Romina, Reilly, James R., et al. 2022. “CropPol: A Dynamic, Open and Global Database on Crop Pollination.” Ecology 103(3): e3614. https://doi.org/10.1002/ecy.3614. For associated GloBI review see Elton, Nomer, & Preston. (2025). A Review of Biotic Interactions and Taxon Names Found in ibartomeus/OBservData hash://md5/35b1210f8b22088babe73b2b9012c15e. Zenodo. https://doi.org/10.5281/zenodo.15256406

Sarah E Miller. 5/30/2016. Interations from various papers. For associated GloBI review see: Elton, Nomer, & Preston. (2025). Versioned Archive and Review of Biotic Interactions and Taxon Names Found within millerse/Pollination-Collection hash://md5/45e01a3d185bebefe0c817999626e52e. Zenodo. https://doi.org/10.5281/zenodo.16415773

Jakovos Demetriou and Quentin Groom 2014. Species associations of Sceliphron manually extracted from literature. For associated GloBI review see Elton, Nomer, & Preston. (2025). Versioned Archive and Review of Biotic Interactions and Taxon Names Found within qgroom/Sceliphron hash://md5/8b608b17e34230c5b4697504e6ff98a5. Zenodo. https://doi.org/10.5281/zenodo.16415968

Balfour, N.J., Castellanos, M.C., Goulson, D., Philippides, A. and Johnson, C., 2022. DoPI: The Database of Pollinator Interactions. Ecology, 103, e3801. For associated GloBI review see Elton, Nomer, & Preston. (2025). Versioned Archive and Review of Biotic Interactions and Taxon Names Found within globalbioticinteractions/dopi hash://md5/5092adc224b66f397c752f6f2071ed53. Zenodo. https://doi.org/10.5281/zenodo.16416445

Lanuza et al. (2025), EuPPollNet: A European Database of Plant-Pollinator Networks. Global Ecol Biogeogr, 34: e70000. https://doi.org/10.1111/geb.70000. For associated GloBI review see Elton, Nomer, & Preston. (2025). Versioned Archive and Review of Biotic Interactions and Taxon Names Found within JoseBSL/EuPPollNet hash://md5/346321bf93ff80852d25f24efaafb18d. Zenodo. https://doi.org/10.5281/zenodo.16416096

Simone Lioy, Cristina Preda and Quentin Groom. 2022. Vespa velutina biotic interactions extracted from literature. For associated GloBI review see Elton, Nomer, & Preston. (2025). Versioned Archive and Review of Biotic Interactions and Taxon Names Found within SimoneLioy/Vespa-velutina-interactions hash://md5/b78cec2bb01456dd3f802601f30b9bd5. Zenodo. https://doi.org/10.5281/zenodo.16416070

The International Barcode of Life Consortium (2016). International Barcode of Life project (iBOL). Occurrence dataset https://doi.org/10.15468/inygc6. For associated GloBI review see Elton, Nomer, & Preston. (2025). Versioned Archive and Review of Biotic Interactions and Taxon Names Found within globalbioticinteractions/bold hash://md5/969227ee2bf361797a9508ba886bad24. Zenodo. https://doi.org/10.5281/zenodo.16416838

Menares, Esteban (2025): Literature-based, long-term interaction database for grasslands vascular plants and day-active (adult) Lepidoptera, region Brandenburg including Schorfheide-Chorin, 1960 to 2018. Version 4. Biodiversity Exploratories Information System. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/31736?version=4; Menares, Esteban (2025): Literature-based, long-term interaction database for grasslands vascular plants and day-active (adult) Lepidoptera, region Baden-Württemberg including Schwäbische Alb, 1975 to 2005. Version 9. Biodiversity Exploratories Information System. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/31734?version=9 . For associated GloBI review see Elton, Nomer, & Preston. (2025). Versioned Archive and Review of Biotic Interactions and Taxon Names Found within globalbioticinteractions/menares2025-flowervisitation hash://md5/833c72e7a4f443b8732431aca3c7ed36. Zenodo. https://doi.org/10.5281/zenodo.16898846

Bees Only Please: Selecting Hundreds of Thousands of Possible Bee Interactions Using a Laptop, Open Datasets, and Small (but Mighty) Commandline Tools.

Fri, 07 Jun 2024 00:00:00 +0000

Figure 1. A method for selecting interactions involving at least one bee using openly available data and tools.

As pollinators, bees play a major role in food production and ecosystems. Many datasets describing bee-plant interactions are becoming openly available. In their partnership, the Big Bee project [1] and Global Biotic Interactions (GloBI) [2] work together to facilitate access to these valuable bee interaction records. Here, we outline a method for accessing biotic interactions that involve Anthophila, commonly known as bees. These interactions include records of bees visiting flowers, parasites of bees as well as hosts of social parasitic bees. Using commonly available tools and known open resources, we show how to build an interaction dataset only involving Anthophila (bees).

Ingredients

GloBI’s verbatim interaction records [3]
DiscoverLife Bee Checklist as made available via Nomer [4], [5]
Lenovo T480s Laptop running Ubuntu 22.04.1 LTS
Familiarity with the Unix Shell [6], [7]
GloBI’s Interaction Data Review Report Framework

Selecting Bee Interactions

Figure 1. shows an approach to select biotic interactions involving bees in a verbatim interactions table from GloBI’s Interpreted Data Products.

First (Fig 1a), the taxonomic names are parsed using GBIF’s taxonomic name parser.

Next (Fig 1b), the parsed names are aligned with the DiscoverLife Bee Taxonomic Checklist as defined in Nomer’s Corpus of Taxonomic Resources.

Then (Fig 1c), interactions are only included when a known bee family name (i.e., Andrenidae, Apidae, Colletidae, Halictidae, Megachilidae, Melittidae, Stenotritidae) is mentioned.

Finally (Fig 1d), a review report is generated by re-using GloBI’s review script check-dataset.sh @09d2f68 with the subset of biotic interactions that mention at least one bee name per interaction.

This approach was implemented in a bash script select-bee-interactions.sh. This script combines openly available tools (e.g., GloBI’s Nomer [5], GNU’s Grep) to process openly available interaction data [3].

This script was run on two different interaction datasets (GloBI v0.6/v0.7) and the results can be found at https://github.com/Big-Bee-Network/select-bee-interactions.sh and in the table below.

output / version	GloBI Data v0.7	GloBI Data v0.6
input data	`verbatim-interactions.tsv` 13.9M records	`verbatim-interactions.tsv` 20.0M records
filtered interactions	`bees-only-interactions.tsv` 1.4M records (also here)	`bees-only-interactions.tsv` 1.1M records (also here)
review report	`bees-only-review.pdf` (also here)	`bees-only-review.pdf` (also here)

These results suggest that relatively complex and custom biodiversity data integrations with large datasets (>1M records) can be achieved on modest hardware with carefully selected tools, openly available datasets, using the nimble yet powerful Unix shell, and leveraging available data publication platforms.

The output from this work is currently being used by Big Bee to create a global dataset of bee interactions that includes taxon name alignment based on DiscoverLife. That dataset currently includes over half a million records of global bee species interacting with plants, parasites and other organisms [8].

Future Work

I suspect I’ll be reusing the select-bee-interactions.sh script in the future to create similar custom data processing workflows. . . and I am curious how others approach the challenge of integrating biodiversity data to answer a specific (research) question. So, I’ll close out by asking a question:

What other approach can you think of to get an extensive list of species interaction data involving bees compiled from known and open datasets?

References

[1] Seltmann, K., Allen, J., Brown, B. V, Carper, A., Engel, M. S, Franz, N., et al. (2021). Announcing Big-Bee: An initiative to promote understanding of bees through image and trait digitization. Biodiversity Information Science and Standards, 5(e74037). doi:10.3897/biss.5.74037 Retrieved from https://escholarship.org/uc/item/0937b5gp

[2] Jorrit H. Poelen, James D. Simons and Chris J. Mungall. (2014). Global Biotic Interactions: An open infrastructure to share and analyze species-interaction datasets. Ecological Informatics. https://doi.org/10.1016/j.ecoinf.2014.08.005.

[3] GloBI Community. (2024). Global Biotic Interactions: Interpreted Data Products hash://md5/946f7666667d60657dc89d9af8ffb909 hash://sha256/4e83d2daee05a4fa91819d58259ee58ffc5a29ec37aa7e84fd5ffbb2f92aa5b8 (0.7) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.11552565

[4] Ascher, J. S. and J. Pickering. 2024. Discover Life bee species guide and world checklist (Hymenoptera: Apoidea: Anthophila). http://www.discoverlife.org/mp/20q?guide=Apoidea_species.

[5] Poelen, J. H. (ed . ) . (2024). Nomer Corpus of Taxonomic Resources hash://sha256/83617875e84bb8ae7ac2a257ad50eb8e82d8935d975f465b8ee8f3a803f72b48 hash://md5/c639d7e3fcd5603f6c48e9d5e6c49672 (0.24) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.11105453

[6] Danielle Kane (Ed.), Anna Oates (Ed.), John Wright (Ed.), Nilani Ganeshwaran (Ed.), Tim Dennis (Ed.), Belinda Weaver (Ed.), James Baker, Christopher Erdmann, Dan Michael Heggø, Katrin Leinweber, hugolio, … Vikram Chhatre. (2019, July). LibraryCarpentry/lc-shell: Library Carpentry: The UNIX Shell, June 2019 (Version v2019.06.1). Zenodo. https://doi.org/10.5281/zenodo.3266085 Accessed at https://librarycarpentry.org/lc-shell/ on 2024-06-11 .

[7] Seltmann & Poelen. 2021. A Practical Exploration of Biotic Interaction Data Management and Information Retrieval through Terrestrial Parasite Tracker (TPT) and Global Biotic Interactions (GloBI) [Workshop]. Zenodo. doi:10.5281/zenodo.4759060 Access at https://www.globalbioticinteractions.org/interaction-data-workshop/03-ixodes-whole-dataset/ on 2024-06-11 .

[8] Katja C. Seltmann, & Global Biotic Interaction Community. (2024). Global Bee Interaction Data (v3.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.10552937

Field Museum and iNaturalist Adopt Darwin Core Resource Relationship Standard to Share Species Interaction Records

Fri, 03 Nov 2023 00:00:00 +0000

Life on earth is sustained by a complex interplay between organisms and their environment. Global Biotic Interactions (GloBI) helps to make records of these interactions easier to find by tracking and indexing digital datasets containing descriptions of how organisms interact. TDWG’s Darwin Core has long been used to exchange information about where organisms are seen. Recently, the Field Museum and iNaturalist switched to using the Darwin Core Resource Relationship extension to share how organisms interact.

The Field Museum holds millions of preserved specimens in their natural history collections. Some of these specimens are parasites that were found on their host. For instance, the Field Museum Insect Collection contains a preserved specimen of an adult male flea Trichopsylloides oregonensis Ewing, 1938 FMNH FMNHINS 0004 345 536 collected on 17 April 1971 by C. O. Maser in Tillamook, Oregon, USA at the Cascade Head Experimental Forest. And, according to their records this flea was found on a mountain beaver (Aplodontia rufa (Rafinesque, 1817) ).

Table 1. Top 5 most frequently reported interaction claims in Field Museum Collections are parasitic interactions between flies (Diptera) and bats (Chiroptera). Data was extracted from a data review report produced on 30 October 2023.
Primary Taxon	Interaction Type	Associated Taxon	Count
Trichobius joblingi Wenzel, 1966	ectoparasite of	Seba's short-tailed bat (Carollia perspicillata)	1377
Megistopoda proxima (Séguy, 1926)	ectoparasite of	Little yellow-shouldered bat (Sturnira lilium)	906
Megistopoda aranea (Coquillétt, 1899)	ectoparasite of	Jamaican fruit bat (Artibeus jamaicensis)	793
Trichobius parasiticus Gervais, 1844	ectoparasite of	Common vampire bat (Desmodus rotundus)	775
Strebla wiedemanni Kolenati, 1856	ectoparasite of	Common vampire bat (Desmodus rotundus)	697

iNaturalist is a popular community scientist platform used to help identify organisms in uploaded photos. They, similar to the Field Museum, also capture information about how the organism interacts with their environment. For instance, iNaturalist user lianaj took a picture of a Grey-headed Flying-fox (Pteropus poliocephalus) that fell prey to a Coastal Carpet Python (Morelia spilota) on 20 May 2020 in the Billinudgel Nature Reserve, Wooyung, NSW, Australia.

Figure 1.(c) Liana, some rights reserved (CC BY-NC) Grey-headed Flying-fox (Pteropus poliocephalus) being killed and eaten by a Coastal Carpet Python (Morelia spilota) on 20 May 2020 in the Billinudgel Nature Reserve, Wooyung, NSW, Australia.

I was able to find these records via GloBI because both the Field Museum and iNaturalist openly shared their interaction records using the Darwin Core Resource Relationship Extension. By using the Darwin Core Resource Extension, this kind of interaction can be expressed in a machine readable way. This machine-readability of interaction types gives the publishers a way to point to definitions of their interaction types. For the Field Museum flea specimen FMNH FMNHINS 0004 345 536 the relation http://purl.obolibrary.org/obo/RO_0002632 or “ectoparasite of” was used. In the iNaturalist photo of the bat being eaten by a python, the relation https://www.inaturalist.org/observation_fields/3133 or “Observation field: Interaction->Preyed upon by” was used.

💡 So, if you are looking for ways to share species interaction claims in a standardized way, please consider using the Darwin Core Resource Relationship extension. And, if you are looking for examples - the Field Museum and iNaturalist have hundreds of thousands of those records available for review.

Big thanks to Sharon Grant, Kate Webbink, Janeen Jones of the Field Museum and Patrick Leary and Ken-ichi Ueda of iNaturalist for their willingness to try new things, even though though they take years to complete. To get an impression of the amount of work and time required to introduce such standardization, please see Field Museum and iNaturalist related integration discussions.

Also, thanks to TDWG contributors like John Wieczorek, Peter Desmet, Quentin Groom, Steve Baskauf and many others for helping to review and approve an improvement to Resource Relationship extension that enabled machine readability of relationship types. If you’d like, you can review the history of the discussion threads related to this one seemingly small change to the Darwin Core standards at tdwg/dwc/issue#186 and tdwg/dwc/issue#283 - it takes a village to keep a standard alive!

Finally, this work was, in part, made possible with the financial support of NSF through projects like the Parasite Tracker Thematic Collections Network led by Jen Zaspel (PI) and Katja Seltmann (co-PI) via award numbers DBI:1901932 and DBI:1901926.

The (un)-hidden iguana puzzle

Wed, 16 Mar 2022 00:00:00 +0000

Green iguanas, Iguana iguana, are charismatic animals, but despite their ferocious appearance they are largely vegetarians and have become popular pets. They hatch from an egg as a tiny lizard, but can live for 20 years and grow to 1.5 meters and 9kg. For this reason they are often released from captivity when they outgrow their home, and in many places have become established and invasive. For example, in Grand Cayman the population has increased exponentially since their arrival through the pet trade and as a food source. The species was recorded occasionally in Grand Cayman in 1994 but has rapidly expanded since then. There are concerns that they might damage the endemic blue iguana Cyclura lewisi population, which is considered Endangered on the IUCN Red List, and is only just recovering from near extinction.

Figure 1. Iguana iguana, photographed by @laiet17 and posted to iNaturalist at https://www.inaturalist.org/observations/67779528

During a hackathon funded by Alien-CSI, an EU COST Action, held in Romania in March 2022, we sought to determine how green iguanas might impact blue iguanas and what the ecological impact of the introduction of green iguanas might be. Many of the impacts of invasive alien species are the result of species interactions, such as herbivory, hybridisation, predation, parasitism and competition. But what do iguanas eat, what parasites do they have, and do they compete for the same resources? We sought to answer these questions by building a dataset based on published records and then illustrating the result.

Figure 2. Cyclura lewisi, photographed by @marique and posted to iNaturalist at https://www.inaturalist.org/observations/17296991

As a first step to uncover the hidden interactions between blue and green iguanas, we collected data for iguanas and published it on the Global Biotic Interactions database to create a dataset describing the ecosystem of iguanas on Grand Cayman (Vlad, Peyton & Meeus 2022). We then built a visualization of the species interaction network so that we could examine the links between blue and green iguanas, but also the other organisms in the ecosystem. This revealed a complex pattern of interrelationships between the two species that can help us to understand the range of impacts of green iguana in Grand Cayman. Insights from this species interaction network may point to ways to manage green iguanas and how to protect blue iguanas and other vulnerable native species. They might also point to future and emerging issues, but also ways to head off problems.

Understanding the puzzle of interconnected species on Grand Cayman will take time, but visualizing it makes it easier to understand for a range of audiences and will help support an interdisciplinary response to green iguana management and blue iguana conservation.

Figure 3. The biotic interactions network of Green iguanas, (Iguana iguana) and Grand Cayman Blue Iguana (Cyclura lewisi). Created with Gephi. See: Bastian M., Heymann S., Jacomy M. (2009). Gephi: an open source software for exploring and manipulating networks. International AAAI Conference on Weblogs and Social Media.

GloBI and BDMY partnership - a symbiotic history

Thu, 21 Jan 2021 00:00:00 +0000

Figure 1. Yucatan Marine BioDiversity (BDMY, UNAM Faculty of Sciences, https://bdmy.org.mx and Global Biotic Interactions (GloBI) collaborate to help make existing species interaction datasets easier to find and access.

A brief story of a great collaboration

The GloBI and the Yucatan Marine BioDiversity (BDMY, UNAM Faculty of Sciences, https://bdmy.org.mx) project collaboration begins around 2016. At BDMY, we were looking for a way to standardize the data generation on marine invertebrates guest/host interactions. We began to generate a small dataset on associated crustaceans with coral reef sponges in the Gulf of Mexico and the Caribbean Sea. This interest led us to contact the Ph.D. James D. Simons, leader of the Gulf of Mexico Species Interactions (GoMexSI) project. James introduced us to Jorrit H. Poelen, a brilliant software and data engineer who shares a “crazy initiative” that he has: to compile the largest amount of information on species interactions at a global scale in a centralized site, in a standardized way and with public access, which he called “The GloBI.” This initiative makes all the sense to us, and it was perfectly adjusted to our needs. From that moment to the present day, GloBI and the BDMY team’s relationship has grown closer and closer - like a symbiosis! - with a common goal: “Make the species interactions more accessible to all the world.”

At this moment, we have three active data sets incorporated into GloBI:

Sponge-dwelling fauna from the Northwestern Atlantic Ocean: a bibliographic records database (v2.05)
Echino-Interactions (v3.0)
Paguroidea-Mollusca-Interactions (v1.0)

As a Latin-American working group, another concern is to make the exchange of information on ecological interactions more accessible for Spanish speakers. For this reason, BDMY has collaborated by creating an entirely Spanish tutorial on the GloBI operation and translating part of the GloBI website contents.

How was Marine Species Interactions born?

Derived from all this effort and work, BDMY: Marine Species Interactions arises, thanks to the initiative and commitment of the Ph.D. Nuno Simoes, MSc. Antar Pérez-Botello and D.Sc. Rosa Sotelo. Driven by the lack of consensus and the absence of standardized methodologies in analyzing interactions, the main objectives of Marine Species Interactions are to generate a species-interactions baseline in marine environments and propose tools that contribute to environmental protection and conservation initiatives.

Figure 2. A screenshot of the recently launched BDMY: Marine Species Interactions website at https://marinespeciesinteractions.org.

What is Marine Species Interactions?

“Marine Species Interactions” (https://marinespeciesinteractions.org) is a multidisciplinary project that involve ecology and taxonomy of marine invertebrates, data science, digital media, scientific illustration, and science communication, with a common goal, communicate and understand the symbiotic interactions between marine invertebrates importance and their influence on the ecological processes. We are currently concentrating our efforts on studying the Porifera, Echinoidea, Cnidaria, and Anomura phyla at the American Atlantic. Still, we are open to expanding research frontiers to as many geographies and taxa.

Why are symbiotic interactions crucial in the marine environment?

Symbiosis is a recurrent and prolonged phenomenon of two or more species where at least one obtains benefits that facilitate their survival. If we classify the types of symbiosis by the species benefit (+), harm (-), neutrality (0) during the association, we can distinguish three types: parasitism (+, -), commensalism (+, 0), and mutualism (+, +). At first sight, the symbiosis may seem an unusual phenomenon. In reality, its influence extends to all marine ecosystems and is crucial in the marine environment. For example, the majestic animal forest of hard corals is a well-known mutualistic association between an animal -the coral polyp-, and a photosynthetic microalgae.

For their part, sponges and echinoderms can facilitate the species establishment in the order of hundreds of species! Its associated fauna includes parasites and commensals that could not survive without their host (obligate symbionts), to species that, although they obtain a benefit by associating, can also survive on their own (opportunistic symbionts). An exceptional example of this diversity of associations is the Caribbean long-spined hedgehog, Diadema antillarum, which holds an incredible record of more than 30 symbiotic species documented in the scientific literature. The effect of symbiosis is decisive in ocean ecosystems’ ecological and co-evolutionary processes, and its study should become a priority if we want to propose biodiversity conservation and management strategies.

Figure 3. BDMY: Marine Species Interactions members involved in science outreach and ongoing training. For the X edition of the Ibero-American Forum of Marine Resources and Aquaculture (XFIRMA 2021), D.Sc. Rosa Sotelo will teach a specialized topic on echinoderm ecology, where ecological interactions and symbiosis clearly cannot be absent.

Our working group actively participates in scientific divulgation from all fronts and generates products for the scientific and non-scientific public, such as open-access databases, scientific articles, species infographics, and congresses’ participation. Likewise, we consider it of great importance that the new generations adhere to this type of ecological research line, for which we maintain active participation in teaching work and human capital formation.

We want to take advantage of this space to invite you to our next course, “Introduction to the ecological study of echinoderms in natural environments” (for Spanish-speaking colleagues), by D.Sc. Rosa Sotelo. This course will be part of the X Ibero-American Forum of Marine Resources and Aquaculture (XFIRMA online 2021) from February 2-4 of this year. We will take an exciting journey from the basic notions and ecological paradigms to the physiological particularities. These morphological and behavioral characteristics have made echinoderms an iconic edge of marine environments.

As you can see, BDMY and Marine Species Interactions still have many stories to tell, so we invite you to follow and visit our social medias and websites:

Links

https://www.facebook.com/BioDiversidadMarinaYucatan

https://bdmy.org.mx

https://marinespeciesinteractions.org

https://firmaonline.org/xfirma/cursos_ambiente.php

https://www.globalbioticinteractions.org/

References

Antar Mijail Perez-Botello, & Nuno Simões. (2021). Sponge-dwelling fauna from the Northwestern Atlantic Ocean: a bibliographic records database. (Version 2.04) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.4445331

Rosa Carmen Sotelo-Casas. (2020). BDMYRepository/Echino-Interactions-V3 (Version V3) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.3742346

Cervantes-Campero, Gabriel, & Simões, Nuno. (2020). BDMYRepository/Paguroidea-Mollusca-Interactions (Version 1.1) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.3901657

La asociación de GloBI y BDMY - Una historia de simbiosis

Thu, 21 Jan 2021 00:00:00 +0000

Una breve historia de una gran colaboración

La colaboración entre GloBI y el proyecto de BioDiversidad Marina de Yucatán (BDMY, https://bdmy.org.mx) de la Facultad de Ciencias de la UNAM, surge alrededor del año 2016. En BDMY nos encontrábamos buscando una manera de estandarizar la recolecta de información sobre interacciones huésped/hospedero en invertebrados marinos. En ese momento empezábamos a generar un pequeño juego de datos sobre Crustáceos asociados a esponjas arrecifales del golfo de México y el mar Caribe. Este interés nos llevó a ponernos en contacto con el Doctor James D. Simons, líder del proyecto Gulf of Mexico Species Interactions (GoMexSI, https://gomexsi.tamucc.edu), quien nos contactó con Jorrit H. Poelen, un brillante ingeniero en software y datos que nos habló de la “loca y aventurada iniciativa” que tiene: compilar la mayor cantidad de información de interacciones de especies a nivel global en un sitio centralizado, de manera estandarizada y de acceso público, a lo que llamó “el GloBI”.

Esta iniciativa nos pareció estupenda y se ajustó perfectamente a nuestras necesidades, por lo que a partir de ese momento la relación entre GloBI y el equipo de BDMY se ha ido estrechando cada vez más -¡como una simbiosis!-, con un objetivo en común: “Hacer que el estudio y acceso a la información sobre interacciones ecológicas sea cada vez más completo y llegue a más personas”.

De esa fecha al día de hoy BDMY tiene 3 juegos de datos en crecimiento incorporados a GloBI:

Sponge-dwelling fauna from the Northwestern Atlantic Ocean: a bibliographic records database (v2.05)
Echino-Interactions (v3.0)
Paguroidea-Mollusca-Interactions (v1.0)

Otra de nuestras inquietudes como un grupo de trabajo iberoamericano es hacer más accesible el intercambio de información sobre interacciones ecológicas para hispanohablantes. Para tal propósito BDMY ha colaborado creando un tutorial sobre le funcionamiento de GloBI totalmente en español, así como traduciendo parte de los contenidos de su sitio web.

¿Cómo nace Marine Species Interactions?

Derivado de todo este esfuerzo y trabajo, surge BDMY: Marine Species Interactions, gracias a la iniciativa y compromiso del doctor Nuno Simoes, el MSc. Antar Pérez-Botello y la Dra. Rosa Sotelo. Con los objetivos de combatir la falta de consenso y la ausencia de metodologías estandarizadas en el análisis de interacciones, generar una línea base en interacciones entre especies en ambientes marinos buscamos proponer herramientas que contribuyan a la toma informada de decisiones en materia de protección y conservación ambiental.

¿Qué es Marine Species Interactions?

“Marine Species Interactions” (https://marinespeciesinteractions.org) es un proyecto de colaboración multidisciplinaria entre especialistas en áreas como la ecología y taxonomía de invertebrados marinos, ciencia de datos, medios digitales, ilustración científica y difusión de la ciencia, con el objetivo de estudiar y dar a conocer la importancia de las interacciones simbióticas entre invertebrados marinos y su influencia en los procesos ecológicos del medio marino.

Actualmente concentramos nuestros esfuerzos en el estudio de los filos Porifera, Echinoidea, Cnidaria y Anomura y del Atlántico americano, pero estamos abiertos a ampliar esta línea de investigación hacia la mayor cantidad de geografías y taxa posibles con la intención de conformar una visión cada vez más completa sobre interacciones bióticas en el mundo marino.

¿Por qué son tan importantes las interacciones simbióticas en el ambiente marino?

La simbiosis es un fenómeno recurrente y prolongado de asociación entre dos o más especies dónde al menos uno de los miembros de la interacción obtiene beneficios que facilitan su supervivencia. Si clasificamos los tipos de simbiosis por el número de especies participantes que se benefician (+), perjudican (-), o no reciben afectación alguna (0) durante la asociación, podemos distinguir tres tipos: parasitismo (+, -), comensalismo (+,0) y mutualismo (+,+).

Aunque a primera vista la simbiosis pudiera parecer un fenómeno poco común, en realidad su influencia se extiende a todos los ecosistemas marinos, por ejemplo el majestuoso bosque animal de corales duros es en realidad la asociación mutualista entre un animal, -el pólipo de coral-, y una micro-alga que hace fotosíntesis. Estas dos especies al cooperar generan un excedente de energía que es invertido en la formación de los grandes esqueletos de carbonato de calcio que dan forma a los arrecifes tropicales del mundo.

Por su parte, grupos como las esponjas y los equinodermos albergan simbiontes en orden de ¡cientos de especies!, solamente contando las especies del Atlántico Tropical Americano. Su fauna asociada incluye desde parásitos y comensales que no podrían sobrevivir sin su anfitrión (simbiontes obligados), hasta especies que si bien obtienen un beneficio al asociarse también pueden sobrevivir por su cuenta (simbiontes oportunistas). Un ejemplo excepcional de esta diversidad de asociaciones es el erizo de espinas largas del Caribe, Diadema antillarum, quien ostenta un increíble récord de más de 30 especies simbiontes documentadas en literatura científica.

Como podemos ver el efecto de la simbiosis aunque subestimado en muchos casos, es determinante en los procesos ecológicos y co-evolutivos de de los ecosistemas oceánicos y su estudio debería tornarse prioritario si es que realmente queremos proponer estrategias de conservación y manejo efectivo para la biodiversidad de estos hábitats.

Un grupo activo y en constante crecimiento

Dado que las interacciones bióticas son realmente numerosas, sabemos que existe una necesidad constante de sumar manos al grupo de trabajo. También somos conscientes de la necesidad de que el conocimiento que se genere quede a disposición de la sociedad para su uso y aprovechamiento. Es por ello que nuestro grupo de trabajo participa activamente en labores de difusión de la ciencia desde todos los frentes y genera productos para público científico y no científico, tales como bases de datos de interacciones entre especies de acceso abierto, artículos científicos, participaciones en congresos y notas de divulgación científica.

Así mismo consideramos de gran importancia que las nuevas generaciones se adhieran a este tipo de líneas de investigación ecológica, por lo que mantenemos una participación activa en labores de docencia y formación de capital humano.

En este orden de ideas, queremos aprovechar este espacio para invitarlos a nuestro siguiente curso “Introducción al estudio ecológico de equinodermos en ambientes naturales” (para colegas de habla hispana), a cargo de la Dra. Rosa Sotelo, el cual se llevará a cabo en el marco del X Foro Iberoamericano de los Recursos Marinos y la Acuicultura (XFIRMA online 2021), del 2 al 4 de febrero del presente año, donde haremos un interesante recorrido desde las nociones y paradigmas básicos de la ecología, hasta las particularidades fisiológicas, morfológicas y de comportamiento que han convertido a los equinodermos en un filo icónico de los ambientes marinos.

Como pueden ver BDMY y Marine Species Interaccions tienen aún muchas historias que contar, por lo que los invitamos a seguirnos en redes sociales y visitar nuestros sitios web:

Links

https://www.facebook.com/BioDiversidadMarinaYucatan

https://bdmy.org.mx

https://marinespeciesinteractions.org

https://firmaonline.org/xfirma/cursos_ambiente.php

https://www.globalbioticinteractions.org/

Referencias

Rosa Carmen Sotelo-Casas. (2020). BDMYRepository/Echino-Interactions-V3 (Version V3) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.3742346

Cervantes-Campero, Gabriel, & Simões, Nuno. (2020). BDMYRepository/Paguroidea-Mollusca-Interactions (Version 1.1) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.3901657

Extracting Parasite Interaction Data from a Scientific Paper using Google Sheets

Tue, 25 Aug 2020 00:00:00 +0000

Figure 1. An example of the Google Sheets spreadsheet used for transcribing data. GloBI accessed the transcribed data set through open source scripts accessible on GitHub. Once every other day the data was indexed into GloBI data products.

During my senior year at Texas A&M University, I had the privilege of participating in a data transcription project. The goal of the project was to make parasite data generally more accessible to everyone. My task was to gather data from a host-parasite list from a scientific paper (Light et al. 2019) and prepare it for upload into GloBI by entering information into specific fields on a Google Sheet. Google Sheets was chosen because multiple people were working on this project and it was an efficient way to work simultaneously. I was transcribing the data of records of different ectoparasites (parasites found on the outside of the host body, such as fleas, ticks, mites, and lice) found on rodents across Mexico. For example, Amaradix euphorbia (flea), Otobius megnini (the spinose ear tick), Ameroseius bassolsae (mite), and Hoplopleura hirsuta (a sucking louse). Transcribing data was not a terribly difficult task. The challenge was how quickly I could transcribe the data points from the paper to the Google Sheet.

In my case, each data point consisted of the mammalian ectoparasite, its taxonomy, the host, the taxonomy of the host, the locality, and the natural history collection where the specimen is located (if that information was available). The Google Sheet spreadsheet also included cells that identified the proper taxonomic authorities such as the parasite authority, the host authority, and the association reference.

Figure 2. A spinose ear tick (Otobius megnini), one of the many mammalian parasites that were the subjects of this project. (Lindström, A. 2017).

My goal while transcribing this data was to be as efficient as possible. I did this by copying taxonomy and other information that was the same for multiple rows down about 10 or 20 cells and then hiding those columns so there was less cells I needed to fill in for each row. This process allowed the work to go by much quicker as I only needed to input the genus, species, locality and the home collection of each host-parasite association.

Another challenge I experienced was due to the monotony of the work. It was easy for my mind to slip and make simple mistakes. For example, when I attempted to hide a few columns I accidently erased them and did not realize it until I had already filled in another couple dozen data points. Anyone that has done a lot of work with spreadsheets has probably encountered a problem like this and it can be frustrating and worrisome. Fortunately, the Google Sheet restoration tools allowed me to repair my mistake and maintain the work I had done by copying it to another spreadsheet while restoring the original. To avoid making mistakes like that I worked in short hour-long bursts with breaks in between. This helped significantly by increasing my efficiency and accuracy.

The biggest lesson I learned from working on this project was the importance of giving your brain a break, especially with a monotonous task such as transcribing. I find that if I worked for too long, the mind will look to make shortcuts, which usually leads to mistakes. Taking some time to break apart the work helped keep my mind focused which in turn kept my work accurate. The experience was quite enjoyable. Even though the task was simple, I was satisfied by the work I had done. It was a wonderful privilege to assist in the congregation of demographic data for GloBI, and I am grateful for Dr. Light and her lab allowing me to work on this project.

References

Light, J.E. et al. 2020. Checklist of ectoparasites of cricetid and heteromyid rodents in México. Therya Volume 11 (1): 79-136. doi:10.12933/therya-20-785

Lindström, A., Lindström, J. . 2017. First report of spinose ear tick, Otobius megnini (Acari, Argasidae), in Sweden. Exp Appl Acarol 72, 179–181 . doi:10.1007/s10493-017-0139-5

Releasing Biological Data from COVID-19 Lockdown

Tue, 26 May 2020 00:00:00 +0000

Figure 1. An interaction visualization of Rousettus aegyptiacus bat species indexed by GloBI on 2020-05-26 and made available by Quentin Groom's manually transcribed literature references via https://doi.org/10.5281/zenodo.3782323. Please visit a full list of associated references and associated visualization .

Wouldn’t it have been better if we had known more about bats before the COVID-19 crisis? One in five of all mammals are bats; there are over 1400 living species (Simmons and Cirranello, 2020). Bats live on every continent except Antarctica, and in every imaginable habitat. Yet we know so little about most species. Where do they live? What do they eat? What other organisms do they interact with? How does this all relate to the transmission of viruses between bats, and between bats and other organisms?

During the current lockdown, the museum collection community established an international COVID-19 Task Force (https://cetaf.org/covid19-taf-communities-taking-action). COVID-19 research touches upon many aspects of science and data management. SARS-CoV-2, the virus that causes COVID-19, is likely to have originated from bats, and knowledge about bat ecology and interactions could be critical to avoiding crises like this in the future (Andersen et al., 2020).

Our team specifically looked at the availability of data on bats, viruses, and other coronavirus hosts. While there is a lack of basic knowledge, the problem is larger than that: much of the knowledge that we do have is not readily accessible. It is tucked away in undigitized museums, in undigitised literature, in closed access publications, or it is hard to find due to poor data management. Yet, we do have the tools and infrastructure to make this knowledge accessible. There are collection digitization programs, such as ADBC in the USA and DiSSCo in Europe. The publisher Pensoft is pioneering ways to make interaction data digitally accessible from publications. And repositories such as Zenodo, GloBI and TreatmentBank provide a place and methods to make access and publication of data easier. So, in a short space of time our small, eclectic team of scientists was able to mobilise a surprising large amount of data on the subject. Currently, we have added 17,123 new distinct taxonomic names and 85,493 interactions to GloBI (Poelen et al., 2020).

My small contribution was mobilising species interaction data to GloBI, which, to be perfectly honest, is not that difficult. After conducting a literature search for the interactions of the Egyptian fruit bat (Rousettus aegyptiacus), I cloned a template repository from GloBI and created my own dataset on GitHub (https://github.com/qgroom/batinterations). I then learned how to get this validated and harvested by GloBI and for an archive copy to be stored on Zenodo (https://doi.org/10.5281/zenodo.3782323. Now, not only are these standardized data available to me, they are for everyone else too.

Alexander Graham Bell said that “when one door closes, another opens; but we often look so long and so regretfully upon the closed door that we do not see the one which has opened for us”. For all of us the COVID-19 crisis has seen many doors close, but despite the physical restrictions of lockdown, data are still just as mobile. One of the doors that is opening is the one to more open data that can contribute to a better understanding of the natural world and the interactions between different species in it. Let’s give that door a nudge.

Figure 2. A visualization of all Rousettus aegyptiacus bat species interactions indexed by GloBI on 2020-05-26. Please visit a full list of associated references and associated visualization .

References

Andersen, K.G., Rambaut, A., Lipkin, W.I., et al. 2020. The proximal origin of SARS-CoV-2. Nat Med 26, 450–452 . doi:10.1038/s41591-020-0820-9.

Poelen, J.H., Upham, N.S., Agosti, D., et al. 2020. CETAF-DiSCCo/COVID19-TAF biodiversity-related knowledge hub working group: indexed biotic interactions and review summary (Version 0.2) [Data set]. Zenodo. doi:10.5281/zenodo.3839098 .

Simmons, N.B. and Cirranello, A.L. 2020. Bat Species of the World: A taxonomic and geographic database. https://batnames.org

Acknowledgements

Thanks to the Consortium of European Taxonomic Facilities (CETAF), the DiSSCo Infrastructure, iDigBio, Nancy Simmons (American Museum of Natural History), Donat Agosti of Plazi, whose goal it is to liberate biodiversity data from the dusty grave of, closed access and PDF-imprisoned literature, and by Jorrit Poelen who runs the Global Biotic Interactions database (GloBI).

Tracking Parasites

Thu, 05 Mar 2020 00:00:00 +0000

Figure 1. A parasite specimen and associated label from the Milwaukee Public Museum Invertebrate Zoology Collection (MPM-IZ) that was used in the group transcription exercise during the Terrestrial Parasite Tracker workshop on February 24-25, 2020 in the Field Museum, Chicago, IL. (A more specific specimen citation is pending as the specimen is still being processed)

After months of preparations, about fifty contributors to the NSF-sponsored (DBI:1901926, DBI:1901932) Terrestrial Parasite Tracker (TPT, https://parasitetracker.org, [1]) Thematic Collection Network gathered in the Field Museum in Chicago, IL for a workshop on February 24-25, 2020. The goals of the TPT workshop were to share ideas on how best to digitize parasitic arthropod specimens and make their associated digital records easily and openly accessible in order to build a better picture of how these little creatures (e.g., ticks, lice, mites) spread diseases and parasitize their hosts. The TPT project uses GloBI to find, index and review parasite-host associations captured in openly accessible digital collections shared by participating institutions.

Physical specimens in natural history collections are often accompanied with handwritten or printed labels (fig. 1). For parasite specimens, these labels often contain valuable information about the environment or organism from which they were collected. This information carries clues about what hosts these parasites may associate with. One highlight of the workshop was a transcription exercise: workshop participants were put into eight groups and were tasked first to individually transcribe (fig. 2) enlarged prints of specimen labels using a provided datasheet. Then, each of the groups discussed their transcription results and attempted to reach consensus on how to transcribe each of the provided photographed labels. After that, each of the groups presented their results and discussion followed. The main takeaways from the transcription results and lively discussions were that (a) labels should be transcribed verbatim and (b) interpretation of the verbatim terms should be done by experts using well-defined terms. So, when a label says, “pulled from Susan,” the transcription should say “pulled from Susan.” However, an interpretation of the transcription may say, “associated with: Homo sapiens,” or perhaps even “has host: Homo sapiens.” The group discussions made it clear that multiple interpretations of a single specimen label may exist. Some of these interpretations, or subjective claims, may even contradict each other.

Figure 2. Terrestrial Parasite Tracker workshop participants transcribing specimen labels as part of a group exercise on February 24, 2020 at the Field Museum, Chicago, IL.

To help keep track of the digitization efforts, a data paper was published [2] and a dedicated TPT web page was created at https://globalbioticinteractions.org/parasitetracker (see also [3]). The data paper contains a citable snapshot of the project, while the web page contains up-to-date information about TPT-affiliated collections and their associated data reviews, indexed interactions and data workflows (i.e., integration profiles). Also, the web page contains various examples of how to use Darwin Core archives to capture biotic association data. In addition, some pointers to biotic interaction term definitions are listed on the page as well as translation tables that detail how association terms provided by the collections (e.g.,”on:”, “ex:”) are interpreted by GloBI.

As the mutualistic partnership between TPT and GloBI matures in the years to come, the TPT-affiliated collections and GloBI will coevolve to improve access to, and use of, physical specimens of vectors and parasites in research, education, policy and management.

References

[1] Purdue University. (2019, August 13). Purdue leading effort to digitize North American parasite collections [Press release]. Retrieved from https://www.purdue.edu/newsroom/releases/2019/Q3/purdue-leading-effort-to-digitize-north-american-parasite-collections.html

[2] Poelen, Jorrit H., Seltmann, Katja C., & Campbell, Mariel. (2020). Terrestrial Parasite Tracker indexed biotic interactions and review summary (Version 0.1) [Data set]. Zenodo. doi:10.5281/zenodo.3685365

[3] Poelen, J. H. (2020, February 27). Global Biotic Interactions: On Keeping Track of Parasite-Host Specimen Records. doi:10.17605/OSF.IO/VK8WQ