Ecosystem approach to harvesting in the Arctic: Walking the tightrope between exploitation and conservation in the Barents Sea.
Ecosystem approach to harvesting in the Arctic: Walking the tightrope between exploitation and conservation in the Barents Sea.
复制标题
DOI：
10.1007/s13280-021-01616-9
复制
发表时间：
2022-03
期刊：
影响因子：
6.5
通讯作者：
Speirs DC
中科院分区：
文献类型：
--
作者：
Heath MR;Benkort D;Brierley AS;Daewel U;Laverick JH;Proud R;Speirs DC
由于生物和冰之间复杂的关系，预测变暖和海冰损失对北极海洋食物网和渔业的影响是具有挑战性的。我们使用了strthe2epolar，这是一个端到端（微生物到巨型动物）的食物网模型，结合对冰的依赖来模拟巴伦支海的气候-渔业相互作用。该模式由NEMO-MEDUSA地球系统模式输出驱动，假设RCP 8.5大气强迫。预计到21世纪40年代，巴伦支海全年无冰率将达到95%，而2010年代为50%，温度将升高约2°C。底栖鱼类（鳕鱼、黑线鳕）的渔业管理参考点（FMSY和BMSY）预计将增加约6%，表明生产率提高。然而，浮游鱼类（毛鳞鱼、鲱鱼）的参考点预计将减少15%，而高营养水平（鸟类、哺乳动物）对浮游鱼类的捕捞非常敏感。结果表明，在采伐和保护生态系统结构和功能之间，未来将面临艰难的权衡。在线版本包含补充材料，可在10.1007/s13280-021-01616-9获得。
Projecting the consequences of warming and sea-ice loss for Arctic marine food web and fisheries is challenging due to the intricate relationships between biology and ice. We used StrathE2EPolar, an end-to-end (microbes-to-megafauna) food web model incorporating ice-dependencies to simulate climate-fisheries interactions in the Barents Sea. The model was driven by output from the NEMO-MEDUSA earth system model, assuming RCP 8.5 atmospheric forcing. The Barents Sea was projected to be > 95% ice-free all year-round by the 2040s compared to > 50% in the 2010s, and approximately 2 °C warmer. Fisheries management reference points (FMSY and BMSY) for demersal fish (cod, haddock) were projected to increase by around 6%, indicating higher productivity. However, planktivorous fish (capelin, herring) reference points were projected to decrease by 15%, and upper trophic levels (birds, mammals) were strongly sensitive to planktivorous fish harvesting. The results indicate difficult trade-offs ahead, between harvesting and conservation of ecosystem structure and function. The online version contains supplementary material available at 10.1007/s13280-021-01616-9.
登录
查看更多内容
影响因子：
8.8
作者：
Heath MR;Speirs DC;Steele JH
通讯作者：
Steele JH
影响因子：
4.9
作者：
Gelaro, Ronald;McCarty, Will;Zhao, Bin
通讯作者：
Zhao, Bin
影响因子：
30.7
作者：
Fossheim, Maria;Primicerio, Raul;Dolgov, Andrey V.
通讯作者：
Dolgov, Andrey V.
影响因子：
4.8
作者：
Riahi, Keywan;Rao, Shilpa;Rafaj, Peter
通讯作者：
Rafaj, Peter
影响因子：
4.1
作者：
Eriksen, E.;Gjosaeter, H.;Sunnana, K.
通讯作者：
Sunnana, K.