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Record W4411099411 · doi:10.1111/gwat.13495

Collaborative Science for Groundwater Biodiversity Conservation

2025· editorial· en· W4411099411 on OpenAlexaff
Mattia Saccò, Xander Huggins, Alejandro Martínez, Robert Reinecke

Bibliographic record

VenueGround Water · 2025
Typeeditorial
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsUniversity of British Columbia
FundersCurtin University of Technology
KeywordsBiodiversityGroundwaterBiodiversity conservationEnvironmental scienceHydrology (agriculture)Environmental planningEnvironmental resource managementWater resource managementGeographyGeologyEcologyGeotechnical engineeringBiology

Abstract

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Lost in the alarm and broader narrative on global trends of biodiversity collapse, an ecosystem is silently vanishing under our feet: groundwater. “Out-of-sight, out-of-mind” describes not only groundwater the resource, but to even greater effect, groundwater the ecosystem. That is, while groundwater is generally recognized as an invisible resource, it is rarely acknowledged or celebrated as an invisible habitat. Depletion and quality degradation of groundwater ecosystems trigger impacts on diverse, highly specialized, and often locally endemic biota, ranging from microbes to cavefish. The extent to which groundwater ecosystems are threatened is alarming: underground biological extinction is already happening (Humphreys 2022). The full breadth of this challenge is unknown, yet the large-scale and widespread depletion and quality degradation of groundwater would suggest that groundwater ecosystem collapse may be extensive and with concerning implications. First, all the essential services linked to the maintenance of a well-functioning groundwater ecosystem, such as contaminant degradation, oxygenation, and carbon turnover regulation, would be lost. Without those, groundwater quality is bound to degrade, leading to the potential proliferation of harmful viruses and bacteria. Furthermore, this impoverishment could cause detrimental cascade effects on the myriad of ecosystems that depend on groundwater, for example, rivers, lakes, grasslands, and forests. As climate change and aridification intensify, the reliance of these ecosystems on groundwater will inevitably increase, reinforcing the need for sustainable groundwater management policies and strategies (Gleeson et al. 2020). Multiple exciting recent developments have enabled a better understanding of groundwater ecosystems. The number of species documented in subterranean groundwater-dependent ecosystems is now almost 50,000 (Martinez et al. 2018), a number that far exceeds that of fish globally. These species deliver innumerable provisioning, regulation, and cultural ecosystem services below and above ground (Griebler and Avramov 2015). Simultaneously, the marked emergence of continental to global groundwater modeling in recent decades presents a particular opportunity to link groundwater dynamics and patterns of biodiversity with land use, climate, socioeconomic, and political change across broad contexts. In continuity with the concept of “ecohydrogeology” (Cantonati et al. 2020), we perceive a grand opportunity to better link the groundwater biology and hydrology communities and raise here the critical need to leverage such collaborations to enhance and empower groundwater ecosystem conservation and management. A handful of efforts to map terrestrial and aquatic groundwater-dependent ecosystems have emerged over recent years (Link et al. 2023; Huggins et al. 2023a; Rohde et al. 2024; Saccò et al. 2024), yet acknowledgement of groundwater biota in hydrogeological studies remains rare, and aquifer management impacts continue to be unquantified. Likewise, thorough representation of hydrological processes is equally sparse in groundwater biology studies. Both fields have blind spots that mutual collaboration can address. Groundwater is increasingly recognized as a resource embedded in a diverse network of systems (Huggins et al. 2023b), which include social, economic, cultural, ecological, biological, hydrological, and geological components. Broadening the “tent” of groundwater science to include the various systems and disciplinary forms of expertise that relate to groundwater could enable a more fruitful environment for this needed interdisciplinarity. Indeed, there is great potential for groundwater hydrogeologists and biologists to lead the way on this, and we pinpoint three priority areas, each followed by an actionable initiative. (1) Collaborative research—organize dedicated workshops, conference sessions, and special issues focused to nurture and facilitate collaboration between hydrologists, biologists, and conservation scientists. (2) Conservation policies—incentivize the collection of empirical subterranean ecological data to support informed, and field-verified conservation and management actions. (3) Social awareness—establish international days to promote groundwater biodiversity issues, which could include the establishment of a World Groundwater Day, in line with existing days dedicated to rivers and lakes, or through advocating a subterranean or groundwater theme for an upcoming World Biodiversity Day. Overall, these actions could meaningfully raise the profile of groundwater ecosystems. Advancing these actions, however, will not be trivial, and deepening the integration of hydrogeology with biology will face challenges relating to the fuzzy definition and concept of groundwater-dependent ecosystems, the acquisition of geographically extensive data in subterranean ecosystems, and the feasibility of incorporating biological components into hydrological modeling frameworks. Yet, in a world dominated by the language and discourse of crisis, we remind ourselves and readers of the fundamentally optimistic orientation of the scientific enterprise (Paskins 2020). To protect groundwater biodiversity worldwide, now is the time to be bold and think outside of the (subterranean) blue box. The authors warmly thank colleagues, friends, and partners for insightful and constructive feedback. M.S. acknowledges support from the School of Molecular and Life Sciences at Curtin University, and the BHP-Curtin alliance within the framework of the “eDNA for Global Environment Studies (eDGES)” programme. A.M. was supported by P.R.I.N. 2022 project “ANCHIALOS” (2022LLNF3N), funded by the Ministry of Universities and Research (Italy). Data sharing is not applicable to this article as no new data were created or analyzed in this study.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.351
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.230
Teacher spread0.223 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEditorial

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations3
Published2025
Admission routes1
Has abstractyes

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