Differentiable modelling to unify machine learning and physical models for geosciences

Nature Reviews Earth & Environment, Journal Year: 2023, Volume and Issue: 4(8), P. 552 - 567

Published: July 11, 2023

Language: Английский

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Artificial intelligence and automated monitoring for assisting conservation of marine ecosystems: A perspective

Frontiers in Marine Science, Journal Year: 2022, Volume and Issue: 9

Published: July 28, 2022

Conservation of marine ecosystems has been highlighted as a priority to ensure sustainable future. Effective management requires data collection over large spatio-temporal scales, readily accessible and integrated information from monitoring, tools support decision-making. However, there are many roadblocks achieving adequate timely on both the effectiveness, long-term success conservation efforts, including limited funding, inadequate sampling, processing bottlenecks. These factors can result in ineffective, or even detrimental, decisions already impacted ecosystems. An automated approach facilitated by artificial intelligence (AI) provides managers with toolkit that help alleviate number these issues reducing monitoring bottlenecks costs monitoring. Automating collection, transfer, access greater information, thereby facilitating effective management. Incorporating automation big availability into decision system user-friendly interface also enables adaptive We summarise current state techniques used science use examples other disciplines identify existing potentially transferable methods enable improve predictive modelling capabilities making. discuss emerging technologies likely be useful research computer associated continues develop become more accessible. Our perspective highlights potential AI analytics for supporting decision-making, but points important knowledge gaps multiple areas processes. challenges should prioritised move toward implementing informed understanding successful outcomes managers. conclude emphasis assisted several scientific may mean future is improved implementation automation.

Language: Английский

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Fire suppression makes wildfires more severe and accentuates impacts of climate change and fuel accumulation

Nature Communications, Journal Year: 2024, Volume and Issue: 15(1)

Published: March 25, 2024

Abstract Fire suppression is the primary management response to wildfires in many areas globally. By removing less-extreme wildfires, this approach ensures that remaining burn under more extreme conditions. Here, we term “suppression bias” and use a simulation model highlight how bias fundamentally impacts wildfire activity, independent of fuel accumulation climate change. We illustrate attempting suppress all necessarily means fires will with severe less diverse ecological impacts, burned area increasing at faster rates than expected from or Over human lifespan, modeled exceed those change alone, suggesting may exert significant underappreciated influence on patterns fire Managing safely low moderate conditions thus critical tool address growing crisis.

Language: Английский

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Refocusing multiple stressor research around the targets and scales of ecological impacts

Nature Ecology & Evolution, Journal Year: 2021, Volume and Issue: 5(11), P. 1478 - 1489

Published: Sept. 23, 2021

Language: Английский

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Spatially explicit models for decision‐making in animal conservation and restoration

Ecography, Journal Year: 2021, Volume and Issue: 2022(4)

Published: Oct. 8, 2021

Models are useful tools for understanding and predicting ecological patterns processes. Under ongoing climate biodiversity change, they can greatly facilitate decision‐making in conservation restoration help designing adequate management strategies an uncertain future. Here, we review the use of spatially explicit models decision support to identify key gaps current modelling restoration. Of 650 reviewed publications, 217 publications had a clear application were included our quantitative analyses. Overall, studies biased towards static (79%), species population level (80%) (rather than restoration) applications (71%). Correlative niche most widely used model type. Dynamic as well gene‐to‐individual community‐to‐ecosystem underrepresented, cost optimisation approaches only 10% studies. We present new typology selecting animal restoration, characterising types according organisational levels, biological processes interest desired applications. This will more closely link goals. Additionally, future efforts need overcome important challenges related data integration, integration decision‐making. conclude with five recommendations, suggesting that wider usage be achieved by 1) developing toolbox multiple, easier‐to‐use methods, 2) improving calibration validation dynamic 3) best‐practise guidelines applying these models. Further, robust 4) combining multiple assess uncertainty, 5) placing at core adaptive management. These must accompanied long‐term funding monitoring, improved communication between research practise ensure optimal outcomes.

Language: Английский

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It is past time to use ecosystem models tactically to support ecosystem‐based fisheries management: Case studies using Ecopath with Ecosim in an operational management context

Fish and Fisheries, Journal Year: 2023, Volume and Issue: 24(3), P. 381 - 406

Published: Feb. 27, 2023

Abstract The implementation of ecosystem management requires modelling within the context a natural resource process. Ecopath with Ecosim (EwE) is most widely used platform for investigating dynamics marine ecosystems, but has played limited role in fisheries and multi‐sector decision‐making. We review 10 case studies that demonstrate use EwE to support operational management. models are being inform tactical decision‐making other ocean sectors, as well identify key trade‐offs, develop appropriate policy objectives, reconcile conflicting legislative mandates variety ecosystems. suggest following criteria enhance management: (1) clear objective can be addressed through modelling; (2) an important trade‐off receptive amenable evaluation; (3) accessible well‐documented model follows best practices; (4) early iterative engagement among scientists, stakeholders, managers; (5) integration collaborative process; (6) multi‐model approach; (7) rigorous Our suggests existing frameworks much or more limitation than technical issues related data availability uncertainty. Ecosystem increasingly needed facilitate effective transparent assert requisite conditions currently exist enhanced strategic

Language: Английский

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Chemical Mixtures and Multiple Stressors: Same but Different?

Environmental Toxicology and Chemistry, Journal Year: 2023, Volume and Issue: 42(9), P. 1915 - 1936

Published: April 10, 2023

Ecosystems are strongly influenced by multiple anthropogenic stressors, including a wide range of chemicals and their mixtures. Studies on the effects stressors have largely focussed nonchemical whereas studies chemical mixtures ignored other stressors. However, both research areas face similar challenges require tools methods to predict joint or frameworks integrate missing. We provide an overview paradigms, tools, commonly used in stressor mixture discuss potential domains cross-fertilization challenges. First, we compare general paradigms ecotoxicology (applied) ecology explain historical divide. Subsequently, approaches for identification interactions, characterization, designing experiments. suggest that too focused interactions would benefit from integration regarding null model selection. Stressor characterization is typically more costly While comprehensive classification systems at suborganismal level been developed, recent account environmental context. Both suffer rather simplified experimental designs focus only limited number chemicals, treatments. concepts can guide realistic capturing spatiotemporal dynamics. process-based data-driven models particularly promising tackle challenge prediction (meta-)communities (meta-)food webs. propose framework assessment Environ Toxicol Chem 2023;42:1915-1936. © 2023 The Authors. Environmental Toxicology Chemistry published Wiley Periodicals LLC behalf SETAC.

Language: Английский

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Linking climate stressors to ecological processes in ecosystem models, with a case study from the Gulf of Alaska

ICES Journal of Marine Science, Journal Year: 2024, Volume and Issue: unknown

Published: Jan. 22, 2024

Abstract As climate stressors are impacting marine ecosystems and fisheries across the world, ecosystem models that incorporate environmental variables increasingly used to inform ecosystem-based management. The assumptions around mechanistic links between biological processes in these important, but implications for model outcomes of which captured how they affect modeled seldom explored. Using a whole-ecosystem (Atlantis) Gulf Alaska, we explore effects capturing physical (increased temperature) biogeochemical (decreased low trophic level productivity) stressors, disentangle each stressor on productivity forage fish, groundfish, fish-eating seabirds. We then test alternative specifications temperature-driven habitat determination bioenergetics. Increased temperature resulted increased weight-at-age higher natural mortality, while decreased mortality. Model specification dependence movement spawning influenced outcomes, decoupling from led overly optimistic biomass predictions. use management becomes more operational, illustrate ecological influence outcomes.

Language: Английский

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Fuzzy Machine Learning Applications in Environmental Engineering: Does the Ability to Deal with Uncertainty Really Matter?

Sustainability, Journal Year: 2024, Volume and Issue: 16(11), P. 4525 - 4525

Published: May 27, 2024

Statement of Problem: Environmental engineering confronts complex challenges characterized by significant uncertainties. Traditional modeling methods often fail to effectively address these As a promising direction, this study explores fuzzy machine learning (ML) as an underutilized alternative. Research Question: Although the potential logic is widely acknowledged, can its capabilities truly enhance environmental applications? Purpose: This research aims deepen understanding role and significance in managing uncertainty within applications. The objective contribute both theoretical insights practical implementations domain. Method: performs systematic review carried out alignment with PRISMA guidelines, encompassing 27 earlier studies that compare ML other across variety applications field engineering. Results: findings demonstrate how fuzzy-based models consistently outperform traditional scenarios marked uncertainty. originality lies comparison identification logic’s transparent, interpretable nature particularly suited for challenges. approach provides new perspective on integrating into engineering, emphasizing capability offer more adaptable resilient solutions. Conclusions: analysis reveals significantly excel compared methods. However, advocates case-by-case evaluation rather than blanket replacement models. encourages optimal selection based specific project needs. Practical Implications: Our actionable researchers engineers, highlighting transparent models, along their superior ability handle Such attributes position alternative Moreover, policymakers leverage reliability developing ML-aided sustainable policies, thereby enhancing decision-making processes management.

Language: Английский

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Linking Fire, Food Webs, and Fish in Stream Ecosystems

Ecosystems, Journal Year: 2025, Volume and Issue: 28(1)

Published: Jan. 3, 2025

As wildfire regimes shift, resource managers are concerned about potential threats to aquatic ecosystems and the species they support, especially fishes. However, predicting fish responses can be challenging because wildfires affect via multiple pathways. Application of whole-ecosystem approaches, such as food web modeling, act heuristic tools that offer valuable insights account for these different mechanisms. We applied a dynamic simulation model mechanistically linked stream trophic dynamics myriad effects have on riparian at local reach-scale. simulated how severity may influence short- (months years) long-term (years decades) periphyton, invertebrate, biomass in forested headwater streams western Pacific Northwest (USA). In many cases, increased modeled over both long-time periods. varied extensively their direction (that is, positive or negative), magnitude, duration depending fire severity, time since fire, level. The shapes response trajectories were sensitive predicted water temperature, canopy cover, shading, instream turbidity. Model simulations suggest single could result wide range ecosystem responses, watersheds with mixed burn severity. Our analysis highlights utility like improving our understanding mechanisms linking webs, identifying contexts where fires deleterious impacts

Language: Английский

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