Using Changes in Biomass and Productivity to Discern Anthropogenic Impacts in Aquatic Ecosystems
Notice bibliographique
Résumé
The purpose of these studies was to monitor changes in two aquatic ecosystems that represent end members along a continuum of human impacts. St. Andrew Bay in Panama City, Florida, USA, has been impacted by humans since it formed about 5,000 years ago; however these impacts have accelerated in the last 150 years as industrialization took place. In contrast, the peatlands north of High Level, Alberta, Canada, are located in a region where human population and development are minimal, yet these remote areas do not appear to be immune to the global climate change that resulted from the industrial revolution. This work describes the effects of water quality on seagrass distribution and epiphyte growth in St. Andrew Bay and it shows how climate change affects peat deposits north of High Level. Water quality has been monitored in St. Andrew Bay since 1990 and these data were coupled with seagrass monitoring data collected since 2000 and five aerial photos taken since 1953 to better determine the extent of seagrass losses in the bay system. The St. Andrew Bay system is composed of four smaller bays: West Bay, North Bay, St. Andrew Bay, and East Bay, and although there has been no systemic decline in seagrass coverage in North Bay, St. Andrew Bay, and East Bay, approximately half of the seagrasses in West Bay have been destroyed or degraded since 1953. Comparisons among these smaller bays show higher turbidities, higher chlorophyll a concentrations, and increased epiphyte growth rates in West Bay which result in shallower seagrass depths. Although the initial cause of seagrass loss in West Bay is unknown, the present eutrophication of this area will make it harder for seagrasses to recover. Furthermore, the future development of over 30,000 acres within West Bay's watershed surrounding a new international airport and industrial complex does not bode well for this stressed ecosystem. Although the peatlands of Canada are located in an area where human impacts are minimal, these ecosystems are still at risk from indirect stressors such a global climate change. Peatlands formed approximately 7,000 years ago as shallow lakes filled in with vegetation; eventually the accumulating vegetation insulated the ground allowing permafrost to form. Over the past 60 years however, global temperatures have increased, the direct result of increased carbon dioxide levels that started to climb after the industrial revolution. This warmer climate decreases the ability of peat to sufficiently insulate the ground allowing the permafrost to melt. Relatively small, shallow collapse scar bogs have now formed within the permafrost plateau and this creates wet depressions where primary productivity increases. Peat cores were removed from several bogs north of High Level, Alberta, and the age of the successive layers in the peat were determined using isotopes of 210Pb and the Constant Rate of Supply (CRS) model. Ages derived from the activity of 137Cs in two cores were used to corroborate these results. Peat accumulation rates were determined for each layer in the core based on peat age and cumulative mass depth of the layer. In general, peat accumulation was greatest in bogs 60 miles north of High Level and lowest in bogs 120 miles away. Furthermore, when peat accumulation rates were compared among neighboring cores, changes in peat accumulation rates occurred at similar time intervals. This indicates that local climate factors influence the rate of peat accumulation once these collapse scar bogs form; however, global changes in climate appear to be responsible for the initial formation of these bogs.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».