Evidence map›Paper›PMID 40991430›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2025

Developing new technologies to protect ecosystems: Planning with adaptive management.

Luz Valerie Pascal, Iadine Chadès, Matthew P Adams, Kate J Helmstedt

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Choosing structure over complexity: POMDPs for emerging diseases and invasive species.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Luz Valerie PascalSchool of Mathematical Sciences and Centre for Data Science, Faculty of Science, Queensland University of Technology, Brisbane, QLD 4000, Australia.ORCID 0000-0002-5389-4461
Iadine ChadèsEnvironment Research Unit, Commonwealth Scientific and Industrial Research Organisation, Dutton Park, Brisbane, QLD 4102, Australia.ORCID 0000-0002-7442-2850
Matthew P AdamsSchool of Mathematical Sciences and Centre for Data Science, Faculty of Science, Queensland University of Technology, Brisbane, QLD 4000, Australia.ORCID 0000-0003-4875-0225
Kate J HelmstedtSchool of Mathematical Sciences and Centre for Data Science, Faculty of Science, Queensland University of Technology, Brisbane, QLD 4000, Australia.ORCID 0000-0003-0201-5348

Funding

Department of Education and Training | Australian Research Council (ARC) DE200100683Department of Education and Training | Australian Research Council (ARC) DE200101791Department of Education and Training | Australian Research Council (ARC) SR200100005
6 · The paper itself

Abstract

Technology development is an essential investment for policymakers to address contemporary global crises, including climate change, biodiversity loss, the energy transition, and emergent infectious diseases. However, investing limited resources in the development of new technologies is risky. The research and development process is unpredictable, with unknown timelines and outcomes. In addition, even after successful development, the effects of deploying a new technology remain uncertain. When confronted with these uncertainties, policymakers must determine how long they should allocate resources to developing new technologies. Informed decisions require anticipating possible successes and failures of both technology development and deployment, which is a challenging optimization task when managing dynamic systems, such as threatened ecological systems. Using an adaptive management approach from AI, we find a time limit new technologies should be developed for, which balances costs, benefits, and uncertainties during development and deployment. We extract clear and transparent general rules for investing in new technologies, building on an analytical approximation. Using Australia's Great Barrier Reef as a case study, we demonstrate that the development time limit ranges between 0 to 45 y before surrendering. We also show how characteristics of an ecological system influence the optimal investment strategy. Our approach can inform the development of new technologies in multiple domains including biodiversity conservation, public health, energy production, and the technology industry more broadly.

Indexed as

Conservation of Natural ResourcesEcosystemAustraliaBiodiversityClimate ChangeCoral Reefsadaptive managementGreat Barrier ReefPOMDPstechnology development

Identifiers

PMID40991430
PMCPMC12501129

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.