Biology subjects

Groom, Q.

Publications and source records attributed to Groom, Q..

5 recordsLinked to original sources

bioRxiv2026

Can data mining from various internet platforms systematically accelerate detection of alien species invasions across the EU?

Invasive alien species (IAS) expansions are increasingly impacting the biodiversity and economy of Europe. To more effectively allocate the limited resources available for their management, it is pertinent to accelerate detection of IAS spread and distribution. One largely untapped secondary data source showing much potential lies in the automated tracking of internet activity such as IAS search intensity or mentions across different internet platforms. In this study, we tested if internet activity increases systematically when IAS expand into new EU countries utilizing the combined data of 88 invasive species from various internet platforms. In total, 14 internet platforms were screened and evaluated based on their database accessibility, mined data quality and utility for systematic IAS expansion tracking. We found that the procedure to obtain researcher access to minimal data required for IAS tracking (i.e., information about location, time and place) varies widely across platforms, and is particularly difficult without incurring significant costs for many of the larger ones (X, Google and Tiktok). From the explored species, more charismatic species (i.e., mammals) overall gained more online traction than more cryptic ones (i.e., plants), though online activity of the first proved a worse representation of real-world occurrence patterns. Moreover, while the final five selected internet platforms showed increased activity surrounding the year of invasion in many of the explored invasion scenarios (particularly Wikipedia and Facebook), inconsistencies between species groups, trends per platform and the large variability in data quality currently still hampers systematic integration of such data into existing databases. We conclude that combining IAS activity data from various internet platforms shows potential to accelerate IAS expansion detection across the EU (especially for fish, crustaceans, reptiles, birds and plants). However, incorporation in automated early warning systems is currently hampered by variable data quality, limited researcher access to online data and the few open, accurate and generalizable species classification algorithms with API access.

ecology↗

bioRxiv2024

Capacity building needed to reap the benefits of access to biodiversity collections

SummaryO_LIThis research examines biodiversity specimens from two areas of the Caribbean to understand patterns of collection and the roles of the people involved. Using open data from the Global Biodiversity Information Facility (GBIF) and Wikidata, we aimed to uncover geographic and historical trends in specimen use. This study aims to provide concrete evidence to guide collaboration between collection-holding institutions and the communities that need their resources most. C_LIO_LIWe analysed biodiversity specimens from Montserrat and the Cayman Islands in three steps. First, we extracted specimen data from GBIF, disambiguated collector names, and linked them to unique biographical entries. Next, we connected collectors to their publications and specimens. Finally, we analysed the modern use of these specimens through citation data, mapping author affiliations and research themes. C_LIO_LISpecimens are predominantly housed in the Global North and were initially used by their collectors, whose focus was largely on taxonomy and biogeography. With digitisation, use of these collections remains concentrated in the Global North and covers a broader range of subjects, although Brazil and China stand out as significant users of digital collection data compared to other similar countries. C_LIO_LIThe availability of open digital data from collections in the Global North has led to a substantial increase in the reuse of these data across biodiversity science. Nonetheless, most research using these data is still conducted in the Global North. For the non-monetary benefits of digitisation to extend to the countries of origin, capacity building in the Global South is crucial, Open Data alone are insufficient. C_LI Societal Impact StatementDigital biodiversity data from herbaria and museums hold significant potential for nature conservation in the Global South, yet many regions, like Montserrat and the Cayman Islands in the Caribbean, are, for multiple reasons, unable to fully leverage this information. This lack of skills and resources limits local conservation efforts, showing the need for more investment in training, facilities, and expertise. Although past funding has helped improve coordination and build skills, our findings show that more work is needed to make sure conservation in these biodiverse areas can continue in the long term.

scientific communication and education↗

bioRxiv2022

The Global Register of Introduced and Invasive Species: Country Compendium

The Country Compendium of the Global Register of Introduced and Invasive Species (GRIIS) is a collation of data across 196 individual country checklists of alienspecies, along with a designation of those species with evidence of impact at a country level. The Compendium provides a baseline for monitoring the distribution and invasion status of all major taxonomic groups, and can be used for the purpose of global analyses of Introduced (alien, non-native, exotic) and Invasive species (invasive alien species), including regional, single and multi-species taxon assessments and comparisons. It enables exploration of gaps and inferred absences of species for countries, and provides a means for short to medium term refinement of GRIIS Checklists. The Country Compendium is, for example, instrumental, along with data on first records of introduction, for assessing and reporting on invasive alien species targets, including for the Convention on Biological Diversity and Sustainable Development Goals. The GRIIS Country Compendium provides a baseline and mechanism for tracking the spread of introduced and invasive alien species across countries globally. O_TBL View this table: org.highwire.dtl.DTLVardef@eb30fdorg.highwire.dtl.DTLVardef@dd338aorg.highwire.dtl.DTLVardef@62b8daorg.highwire.dtl.DTLVardef@1561763org.highwire.dtl.DTLVardef@119988e_HPS_FORMAT_FIGEXP M_TBL C_TBL

ecology↗

bioRxiv2021

Policy-relevant indicators for invasive alien species assessment and reporting

Invasive alien species are repeatedly shown to be amongst the top threats to biodiversity globally. Robust indicators for measuring the status and trends of biological invasions are lacking, but essential for monitoring biological invasions and the effectiveness of interventions. Here, we formulate and demonstrate three such indicators that capture the key dimensions of species invasions, each a significant and necessary advance to inform invasive alien species policy targets: 1) Rate of Invasive Alien Species Spread, which provides modelled rates of ongoing introductions of species based on invasion discovery and reporting. 2) Impact Risk, that estimates invasive alien species impacts on the environment in space and time and provides a basis for nationally targeted prioritization of where best to invest in management efforts. 3) Status Information on invasive alien species, that tracks improvement in the essential dimensions of information needed to guide relevant policy and data collection and in support of assessing invasive alien species spread and impact. We show how proximal, model-informed status and trend indicators on invasive alien species can provide more effective global (and national) reporting on biological invasions, and how countries can contribute to supporting these indicators.

ecology↗

bioRxiv2020

Occurrence cubes: a new paradigm for aggregating species occurrence data

In this paper we describe a method of aggregating species occurrence data into what we coined "occurrence cubes". The aggregated data can be perceived as a cube with three dimensions - taxonomic, temporal and geographic - and takes into account the spatial uncertainty of each occurrence. The aggregation level of each of the three dimensions can be adapted to the scope. Built on Open Science principles, the method is easily automated and reproducible, and can be used for species trend indicators, maps and distribution models. We are using the method to aggregate species occurrence data for Europe per taxon, year and 1km2 European reference grid, to feed indicators and risk mapping/modelling for the Tracking Invasive Alien Species (TrIAS) project.

ecology↗