Notice bibliographique
Résumé
Without nitrogen (N) and phosphorus (P) there would be no life – no me, no you, no rainbow trout, no Atlantic cod, no Antarctic krill. But like anything in excess, too much N and P leads to a series of negative consequences. For example, in aquatic systems, high nutrient levels can lead to harmful algal blooms, low dissolved oxygen events, and decreases in biodiversity. Despite these well-known adverse impacts, no US states to date have implemented Environmental Protection Agency-approved N and P criteria for all water bodies within their respective borders (although Hawaii, it should be noted, has N and P standards for all water bodies except wetlands). Citing concerns on the part of stakeholders (citizens, industry, and lobbying groups), many state lawmakers are hesitant to adopt numeric nutrient criteria to regulate N and P, despite the 40-year-old charge in the US Clean Water Act. In some proactive US states, natural resource managers informed by the scientific literature – most notably the whole-system experimental manipulations in Canadian lakes – established P management strategies that resulted in water-quality goals being met. However, because P is likely not the limiting nutrient in most marine systems, P mitigation strategies did little to improve downstream coastal water quality. Many ecosystem ecologists therefore argue for reductions in both N and P. Nevertheless, the contention exists in the regulation community that the evidence for dual nutrient reduction is simply not compelling enough and that the cost is too high to justify. So how do we continue a rigorous scientific debate while also providing an unambiguous, action-oriented message to non-scientist stakeholders? First, researchers can undertake due diligence by clearly presenting to stakeholders and policy makers the basic and staggering effects that humans have had on N and P cycling. Most people are well aware of the impact of anthropogenic increases in carbon dioxide, yet humans have arguably done more to influence N and P cycling globally. For example, since the beginning of the 20th century, human activities have doubled the amount of N cycling through the biosphere and tripled the amount of P mobilized on Earth. In doing so, we have fundamentally altered terrestrial and aquatic ecosystem functioning. Now, with more than 50% and 90% of the world's population living within 3 km and 10 km of freshwater sources, respectively, human impacts on aquatic resources worldwide are enormous and growing. Second, given the longstanding and vigorous debate among policy makers over whether to manage N or P or both, scientists can advocate for a holistic, watershed-level, dual-nutrient approach. Unfortunately, in some instances, researchers inadvertently confuse the issue with academic debates over whether N or P is the nutrient limiting growth in a given terrestrial or aquatic system. Although intellectually important, these debates – outside of academia – sometimes obfuscate the need for dual-nutrient policy and provide policy makers with a justification to limit either N or P but not both. Worse yet, as we have seen recently in the climate-change debate, the lack of clear public communication of the state of the science has led to instances of researchers appearing “unsure” of their findings and, as a result, efforts to establish relevant policy have been abandoned. Third – and borrowing from Voltaire – remember that perfect is the enemy of good. In the case of water-quality standards, it is safe to say that the arsenal of scientific literature and sentiment strongly supports criteria for both N and P, a refrain that should be repeated often. Even if it does have criteria for both N and P, the final policy, while not perfect, will serve the greater good in protecting waters both locally and downstream. “Primum non nocere”, or “first, do no harm”, is one of the central ethical principles taught to medical students, and one that scientists and policy makers alike should embrace. In this context, to do no harm, we argue that a systems-wide, holistic approach to N and P control is essential. When developing nutrient criteria for a given river or estuary, it is imperative for policy makers to remember that actions in one watershed will affect a neighboring or downstream ecosystem. Since the passage of the Clean Water Act 40 years ago, the road to comprehensive nutrient pollution policy has been slow and sporadic. Yet the need for action has never been greater, and the impact that scientists can make on policy should not be underestimated.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,010 | 0,044 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,005 | 0,015 |
| Communication savante | 0,012 | 0,015 |
| Science ouverte | 0,002 | 0,007 |
| Intégrité de la recherche | 0,013 | 0,015 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,083 | 0,059 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».