Protecting Coastal Lagoons in the Southern Chukchi: Project Chariot Revisited 2018 Fieldwork Summary
Notice bibliographique
Résumé
The southeastern Chukchi Sea is a highly productive marine ecosystem. Nearshore habitats are heavily used by local people for commercial and subsistence harvest; they also provide important foraging habitat, proximity to shelter, and overwintering habitat for all life stages of many ecologically and locally/economically important fish species (Craig 1984; George et al. 2007; Johnson et al. 2007; Logerwell et al. 2015; Whiting et al. 2011). Coastal lagoons are a dominant landscape feature in this region, comprising over a third (37%) of the Arctic coastline between Wales and the Canadian border (Figure 1). These bodies of water provide critical habitat for migratory fish (e.g., salmon, whitefish) and other ecologically important forage fish (e.g., herring, smelt), as well as staging habitat for migratory shorebirds and waterfowl. Coastal community members are increasingly interested in documenting the ecology and importance of fish and invertebrates in these lagoons due to concerns about potential impacts from climate change, increased economic development, and the potential for coastal oil spill impacts (LGL 2011; Rand and Logerwell 2011). Our research efforts during summer 2018, included a focus on the coastal areas around Cape Thompson in the North Slope Borough of Alaska, addressing the need for baseline information on the structure and function of lagoons in the area. Three lagoons were visited within the boundary of the North Slope Borough: Kemegrak, Akoviknak and Atosik. We also sampled one additional lagoon just south of the boundary of the North Slope borough, Singoalik, which is in Northwest Arctic Borough. Previously, the most significant lagoon research efforts between Kivalina and Cape Thompson occurred in the 1950s as part of the Project Chariot Environmental Assessment (Johnson, 1961; Willimovsky and Wolfe, 1966; Tash and Armitage, 1967; Tash, 1971) and at Port Lagoon just to the south of Kivalina as part of the Environmental Assessment for the Red Dog Mine port facility. Apart from these research efforts, little research has been published about the presence and timing of habitat use by fishes in the coastal habitats of this area, despite their importance for food security and ecosystem health in the region. We collected data on physical water parameters including primary productivity, with samples at 4-7 individual sites per lagoon. These sites included: the marine edge, the terrestrial edge, fresh water inlets, the outlet of the lagoon to the marine environment, and three random sample sites based on established protocols developed as part of the National Park Service’s Arctic Lagoon Vital Sign (Jones and Apsens, 2017). We sampled fish community composition and abundance using a beach seine and experimental gill net, and performed zooplankton tows at each study site. We performed 3-5 tows per lagoon. We opportunistically recorded observations made by Point Hope community members who we encountered during sampling efforts. We spent one day sampling at each lagoon, with the exception of Akoviknak which we sampled over the course of two days. We traveled to Cape Thompson aboard the US Fish and Wildlife vessel the R/V Tiglax which we used as a base of operations. The Tiglax provided us with food and accommodations as well as a place to process and store samples. During the day we loaded sampling gear on to a larger inflatable boat and were taken to shore in the general vicinity of the target lagoon. Within each visited lagoon, we used a small inflatable boat equipped with a 9.9 horsepower outboard motor. Preliminary results from the 2018 field season reflect findings from 16 beach seine sets and 20 gill net sets, as well as point data on physiochemical water properties taken at each lagoon. These data on community composition and relative abundance will supplement laboratory analysis of zooplankton and fish samples in collaboration with the University of Alaska, Fairbanks, and other collaborators. Laboratory analysis will address several central research themes including genetic relationship between fish from closely separated study sites, mercury levels in fish from closely separated study sites, variation in stable isotope values in whitefish with geographic region, age, sex, and fork-length, and total mercury levels in relationship to trophic level. Lagoons varied in their physical water parameters. None of the lagoons sampled were open to the marine environment at the time of sampling. Temperature readings varied between lagoons, with the highest overall temperature occurring at Kemegrak Lagoon (16.35 ± 1.82°C) and the lowest at Mapsorak (8.86 ± 0.25°C). Salinity levels at all lagoons were relatively low, ranging from 0.60 ± 0.07 ppt at Mapsorak to 9.47 ± 0.45 ppt at Singoalik. Low salinity levels and higher temperature readings likely reflect the absence of recent influxes of colder saline water from the marine system. This exchange generally exists in lagoons around Cape Krusenstern (Smith et al., 2019), which are open to the marine environment at the beginning of the open water season, but gradually close as the summer progresses. Temperature readings recorded in the 1983 report by Dames and Moore, for instance, revealed lower overall temperatures at lagoons open to the marine environment particularly at sample stations directly inside the mouth of the lagoon, indicating that influx of colder water from the ocean has significant impact on the overall temperature in the main body of the lagoon. Primary production was highest at Kemegrak lagoon. We recorded seven species of fishes and one unidentified larval fish. Highest species diversity occurred at Singoalik Lagoon with six species captured. Fishes of the largest size class (100-199mm and 200+ mm) were found at Akoviknak, all of which were Least cisco. Sampling at both Atosik and Mapsorak did not catch any fish. Important forage species captured included ninespine stickleback, pond smelt and threespine stickleback. We conducted informal interviews with members of the local community through chance encounters on the beach during sampling events. Conversations with members of the Point Hope community indicate that the community is keen to see more scientific monitoring in the area.
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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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,004 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
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 ».