Ecology

Pan, Y. et al. A large and persistent carbon sink in the world’s forests. Science 333, 988–993 (2011).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Tarnocai, C. et al. Soil organic carbon pools in the northern circumpolar permafrost region. Glob. Biogeochem. Cycles 23, 1–11 (2009).Article 
CAS 

Google Scholar 
Davidson, E. A. & Janssens, I. A. Temperature sensitivity of soil carbon decomposition and feedbacks to climate change. Nature 440, 165–173 (2006).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Wardle, D. A., Nilsson, M. C., Zackrisson, O. & Gallet, C. Determinants of litter mixing effects in a Swedish boreal forest. Soil Biol. Biochem. 35, 827–835 (2003).CAS 
Article 

Google Scholar 
Moen, J., Cairns, D. M. & Lafon, C. W. Factors structuring the treeline ecotone in Fennoscandia. Plant Ecol. Divers. 1, 77–87 (2008).Article 

Google Scholar 
Sjögersten, S. & Wookey, P. A. Climatic and resource quality controls on soil respiration across a forest-tundra ecotone in Swedish Lapland. Soil Biol. Biochem. 34, 1633–1646 (2002).Article 

Google Scholar 
Sjögersten, S., Turner, B. L., Mahieu, N., Condron, L. M. & Wookey, P. A. Soil organic matter biochemistry and potential susceptibility to climatic change across the forest-tundra ecotone in the Fennoscandian mountains. Glob. Change Biol. 9, 759–772 (2003).ADS 
Article 

Google Scholar 
IPCC. IPCC report global warming of 1.5 °C. Ipcc Sr15. 2, 17–20 (2018).
Google Scholar 
Hobbie, S. E., Nadelhoffer, K. J. & Högberg, P. A synthesis: The role of nutrients as constraints on carbon balances in boreal and arctic regions. Plant Soil 242, 163–170 (2002).CAS 
Article 

Google Scholar 
DeLuca, T. H. & Boisvenue, C. Boreal forest soil carbon: Distribution, function and modelling. Forestry 85, 161–184 (2012).Article 

Google Scholar 
Hansson, A., Dargusch, P. & Shulmeister, J. A review of modern treeline migration, the factors controlling it and the implications for carbon storage. J. Mt. Sci. 18, 291–306 (2021).Article 

Google Scholar 
Sjögersten, S. & Wookey, P. A. The impact of climate change on ecosystem carbon dynamics at the Scandinavian mountain birch forest-tundra heath ecotone. Ambio 38, 2–10 (2009).PubMed 
Article 

Google Scholar 
Rustad, L. E. et al. A meta-analysis of the response of soil respiration, net nitrogen mineralization, and aboveground plant growth to experimental ecosystem warming. Oecologia 126, 543–562 (2001).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Kullman, L. Rapid recent range-margin rise of tree and shrub species in the Swedish Scandes. J. Ecol. 90, 68–77 (2002).Article 

Google Scholar 
Lloyd, A. H. & Fastie, C. L. Recent changes in treeline forest distribution and structure in interior Alaska. Ecoscience 10, 176–185 (2003).Article 

Google Scholar 
Truong, C., Palmé, A. E. & Felber, F. Recent invasion of the mountain birch Betula pubescens ssp. tortuosa above the treeline due to climate change: Genetic and ecological study in northern Sweden. J. Evol. Biol. 20, 369–380 (2007).CAS 
PubMed 
Article 

Google Scholar 
Danby, R. K. & Hik, D. S. Variability, contingency and rapid change in recent subarctic alpine tree line dynamics. J. Ecol. 95, 352–363 (2007).Article 

Google Scholar 
Harsch, M. A., Hulme, P. E., McGlone, M. S. & Duncan, R. P. Are treelines advancing? A global meta-analysis of treeline response to climate warming. Ecol. Lett. 12, 1040–1049 (2009).PubMed 
Article 

Google Scholar 
Tingstad, L., Olsen, S. L., Klanderud, K., Vandvik, V. & Ohlson, M. Temperature, precipitation and biotic interactions as determinants of tree seedling recruitment across the tree line ecotone. Oecologia 179, 599–608 (2015).ADS 
PubMed 
Article 

Google Scholar 
Hofgaard, A. Inter-Relationships between treeline position, species diversity, land use and climate change in the Central Scandes Mountains of Norway. Annika Hofgaard Source Glob. Ecol. Biogeogr. Lett. 6(6), 419–429 (1997).Article 

Google Scholar 
Olsson, E. G. A., Austrheim, G. & Grenne, S. N. Landscape change patterns in mountains, land use and environmental diversity, Mid-Norway 1960–1993. Landsc. Ecol. 15, 155–170 (2000).Article 

Google Scholar 
Weintraub, M. N. & Schimel, J. P. Interactions between carbon and nitrogen mineralization and soil organic matter chemistry in arctic tundra soils. Ecosystems 6, 129–143 (2003).CAS 
Article 

Google Scholar 
Melillo, J. M. et al. Soil warming and carbon-cycle feedbacks to the climate system. Science 298, 2173–2176 (2002).Kammer, A. et al. Treeline shifts in the Ural mountains affect soil organic matter dynamics. Glob. Change Biol. 15, 1570–1583 (2009).ADS 
Article 

Google Scholar 
Parker, T. C., Subke, J. A. & Wookey, P. A. Rapid carbon turnover beneath shrub and tree vegetation is associated with low soil carbon stocks at a subarctic treeline. Glob. Change Biol. 21, 2070–2081 (2015).ADS 
Article 

Google Scholar 
Speed, J. D. M. et al. Continuous and discontinuous variation in ecosystem carbon stocks with elevation across a treeline ecotone. Biogeosciences 12, 1615–1627 (2015).ADS 
Article 

Google Scholar 
Hartley, I. P. et al. A potential loss of carbon associated with greater plant growth in the European Arctic. Nat. Clim. Chang. 2, 875–879 (2012).ADS 
CAS 
Article 

Google Scholar 
Yoo, K., Amundson, R., Heimsath, A. M. & Dietrich, W. E. Spatial patterns of soil organic carbon on hillslopes: Integrating geomorphic processes and the biological C cycle. Geoderma 130, 47–65 (2006).ADS 
CAS 
Article 

Google Scholar 
Zhu, M. et al. Soil organic carbon as functions of slope aspects and soil depths in a semiarid alpine region of Northwest China. CATENA 152, 94–102 (2017).CAS 
Article 

Google Scholar 
Hilli, S., Stark, S. & Derome, J. Litter decomposition rates in relation to litter stocks in boreal coniferous forests along climatic and soil fertility gradients. Appl. Soil Ecol. 46, 200–208 (2010).Article 

Google Scholar 
Parker, T. C. et al. Exploring drivers of litter decomposition in a greening Arctic: Results from a transplant experiment across a treeline. Ecology 99, 2284–2294 (2018).PubMed 
Article 

Google Scholar 
Strand, L. T., Callesen, I., Dalsgaard, L. & de Wit, H. A. Carbon and nitrogen stocks in Norwegian forest soils—The importance of soil formation, climate, and vegetation type for organic matter accumulation. Can. J. For. Res. 46, 1459–1473 (2016).CAS 
Article 

Google Scholar 
Thieme, N., Bollandsås, O. M., Gobakken, T. & Næsset, E. Detection of small single trees in the forest-tundra ecotone using height values from airborne laser scanning. Can. J. Remote Sens. 37, 264–274 (2011).ADS 
Article 

Google Scholar 
Mienna, I. M., Klanderud, K., Ørka, H. O., Bryn, A. & Bollandsås, O. M. Land cover classification of treeline ecotones along a 1100 km latitudinal transect using spectral- and three-dimensional information from UAV -based aerial imagery. Remote Sens. Ecol. Conserv. https://doi.org/10.1002/rse2.260 (2022).Article 

Google Scholar 
Tveito, O. E., Bjørdal, I., Skjelvåg, A. O. & Aune, B. A GIS-based agro-ecological decision system based on gridded climatology. Meteorol. Appl. 12, 57–68 (2005).ADS 
Article 

Google Scholar 
Carter, T. R. Changes in the thermal growing season in Nordic countries during the past century and prospects for the future. Agric. Food Sci. Finl. 7, 161–179 (1998).Article 

Google Scholar 
Abdi, H. Partial least square regression PLS-regression. Encyclopedia Res. Methods Social Sci. 792.295 (2003).Wold, S., Sjöström, M. & Eriksson, L. PLS-regression: A basic tool of chemometrics. Chemom. Intell. Lab. Syst. 58, 109–130 (2001).CAS 
Article 

Google Scholar 
Liland, K. H., Mevik, B.-H., Wehrens, R. & Hiemstra, P. Package ‘ pls ’. (2021).Mevik, B.-H. & Wehrens, R. Introduction to the pls Package. Help Sect. ‘pls’ Packag. RStudio Softw. 1–23 (2015).Huang, X. et al. Soil moisture dynamics within soil profiles and associated environmental controls. CATENA 136, 189–196 (2016).Article 

Google Scholar 
Trap, J., Hättenschwiler, S., Gattin, I. & Aubert, M. Forest ageing: An unexpected driver of beech leaf litter quality variability in European forests with strong consequences on soil processes. For. Ecol. Manage. 302, 338–345 (2013).Article 

Google Scholar 
Sørensen, M. V. et al. Draining the pool? Carbon storage and fluxes in three alpine plant communities. Ecosystems 21, 316–330 (2018).Article 
CAS 

Google Scholar 
Qian, H., Joseph, R. & Zeng, N. Enhanced terrestrial carbon uptake in the Northern High Latitudes in the 21st century from the Coupled Carbon Cycle Climate Model Intercomparison Project model projections. Glob. Chang. Biol. 16, 641–656 (2010).ADS 
Article 

Google Scholar 
Sturm, M. et al. Snow—Shrub interactions in Arctic Tundra : A hypothesis with climatic implications. J. Clim. 14, 336–344 (2001).ADS 
Article 

Google Scholar 
Grogan, P. & Jonasse, S. Ecosystem CO2 production during winter in a Swedish subarctic region: The relative importance of climate and vegetation type. Glob. Change Biol. 12, 1479–1495 (2006).ADS 
Article 

Google Scholar 
Sistla, S. A. et al. Long-term warming restructures Arctic tundra without changing net soil carbon storage. Nature 497, 615–617 (2013).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Wiesmeier, M. et al. Soil organic carbon storage as a key function of soils—A review of drivers and indicators at various scales. Geoderma 333, 149–162 (2019).ADS 
CAS 
Article 

Google Scholar 
Brooks, P. D. & Williams, M. W. Snowpack controls on nitrogen cycling and export in seasonally snow-covered catchments. Hydrological processes 13, 2177–2190 (1999).Broll, G. et al. Landscape mosaic in the treeline ecotone on Mt. Rodjanoaivi, Subarctic Finland. Fenn. J. Geogr. 185, 89–105 (2007).
Google Scholar 
Turetsky, M. R. The role of bryophytes in carbon and nitrogen cycling. Bryologist 106, 395–409 (2003).Article 

Google Scholar  More

Hu, S., Niu, Z., Chen, Y., Li, L. & Zhang, H. Global wetlands: Potential distribution, wetland loss, and status. Sci. Total Environ. 586, 319–327 (2017).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Guo, M., Li, J., Sheng, C., Xu, J. & Wu, L. A review of wetland remote sensing. Sensors 17, 777 (2017).ADS 
PubMed Central 
Article 

Google Scholar 
Mingwu, Z., Haijiang, J., Desuo, C. & Chunbo, J. The comparative study on the ecological sensitivity analysis in Huixian karst wetland, China. Procedia Environ. Sci. 2, 386–398 (2010).Article 

Google Scholar 
Li, Z., Jin, Z. & Li, Q. Changes in Land Use and their Effectson Soil Properties in Huixian KarstWetland System. Pol. J. Environ. Stud. 26, 699–707 (2017).Article 

Google Scholar 
Jiang, X., Xiong, Z., Liu, H., Liu, G. & Liu, W. Distribution, source identification, and ecological risk assessment of heavy metals in wetland soils of a river–reservoir system. Environ. Sci. Pollut. Res. 24, 436–444 (2016).Article 
CAS 

Google Scholar 
Fu, B. et al. Comparison of optimized object-based RF-DT algorithm and SegNet algorithm for classifying Karst wetland vegetation communities using ultra-high spatial resolution UAV data. Int. J. Appl. Earth Obs. Geoinf. 104, 102553 (2021).
Google Scholar 
Xu, D. et al. Distribution, speciation, environmental risk, and source identification of heavy metals in surface sediments from the karst aquatic environment of the Lijiang River, Southwest China. Environ. Sci. Pollut. Res. 23, 9122–9133 (2016).CAS 
Article 

Google Scholar 
Gao, P. et al. Spatial and temporal changes of P and Ca distribution and fractionation in soil and sediment in a karst farmland-wetland system. Chemosphere 220, 644–650 (2019).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Gil-Márquez, J. M., Barberá, J. A., Andreo, B. & Mudarra, M. Hydrological and geochemical processes constraining groundwater salinity in wetland areas related to evaporitic (karst) systems. A case study from Southern Spain. J. Hydrol. 544, 538–554 (2017).Chamberlin, C. A. et al. Mass balance implies Holocene development of a low-relief karst patterned landscape. Chem. Geol. 527, 118782 (2019).ADS 
CAS 
Article 

Google Scholar 
Watts, A. C. et al. Evidence of biogeomorphic patterning in a low-relief karst landscape. Earth Surf. Proc. Land. 39, 2027–2037 (2014).ADS 
Article 

Google Scholar 
Fan, Z., Li, J., Yue, T., Zhou, X. & Lan, A. Scenarios of land cover in Karst area of Southwestern China. Environ. Earth Sci. 74, 6407–6420 (2015).Article 

Google Scholar 
Wang, S., Zhang, L., Zhang, H., Han, X. & Zhang, L. Spatial-temporal wetland landcover changes of poyang lake derived from landsat and HJ-1A/B data in the dry season from 1973–2019. Remote Sens. 12, 1595 (2020).ADS 
Article 

Google Scholar 
Szabó, L., Deák, B., Bíró, T., Dyke, G. J. & Szabó, S. NDVI as a proxy for estimating sedimentation and vegetation spread in artificial lakes—monitoring of spatial and temporal changes by using satellite images overarching three decades. Remote Sens. 12, 1468 (2020).ADS 
Article 

Google Scholar 
Malekmohammadi, B. & Rahimi Blouchi, L. Ecological risk assessment of wetland ecosystems using multi criteria decision making and geographic information system. Ecol. Indic. 41, 133–144 (2014).Article 

Google Scholar 
Tian, Y. et al. Monitoring invasion process of spartina alterniflora by seasonal sentinel-2 imagery and an object-based random forest classification. Remote Sens. 12, 1383 (2020).ADS 
Article 

Google Scholar 
Lane, C. et al. Improved wetland classification using eight-band high resolution satellite imagery and a hybrid approach. Remote Sens. 6, 12187–12216 (2014).ADS 
Article 

Google Scholar 
Betbeder, J., Rapinel, S., Corgne, S., Pottier, E. & Hubert-Moy, L. TerraSAR-X dual-pol time-series for mapping of wetland vegetation. ISPRS J. Photogramm. Remote. Sens. 107, 90–98 (2015).ADS 
Article 

Google Scholar 
Franklin, S. E., Skeries, E. M., Stefanuk, M. A. & Ahmed, O. S. Wetland classification using Radarsat-2 SAR quad-polarization and Landsat-8 OLI spectral response data: A case study in the Hudson Bay Lowlands Ecoregion. Int. J. Remote Sens. 39, 1615–1627 (2017).Article 

Google Scholar 
Cao, J. et al. Object-based mangrove species classification using unmanned aerial vehicle hyperspectral images and digital surface models. Remote Sens. 10, 89 (2018).ADS 
Article 

Google Scholar 
Liu, T. & Abd-Elrahman, A. Multi-view object-based classification of wetland land covers using unmanned aircraft system images. Remote Sens. Environ. 216, 122–138 (2018).ADS 
Article 

Google Scholar 
Churches, C. E., Wampler, P. J., Sun, W. & Smith, A. J. Evaluation of forest cover estimates for Haiti using supervised classification of Landsat data. Int. J. Appl. Earth Obs. Geoinf. 30, 203–216 (2014).ADS 

Google Scholar 
Gerke, M. & Xiao, J. Fusion of airborne laserscanning point clouds and images for supervised and unsupervised scene classification. ISPRS J. Photogramm. Remote. Sens. 87, 78–92 (2014).ADS 
Article 

Google Scholar 
Maulik, U. & Chakraborty, D. Learning with transductive SVM for semisupervised pixel classification of remote sensing imagery. ISPRS J. Photogramm. Remote. Sens. 77, 66–78 (2013).ADS 
Article 

Google Scholar 
Crasto, N. et al. A LiDAR-based decision-tree classification of open water surfaces in an Arctic delta. Remote Sens. Environ. 164, 90–102 (2015).ADS 
Article 

Google Scholar 
O’Neil, G. L., Goodall, J. L. & Watson, L. T. Evaluating the potential for site-specific modification of LiDAR DEM derivatives to improve environmental planning-scale wetland identification using Random Forest classification. J. Hydrol. 559, 192–208 (2018).ADS 
Article 

Google Scholar 
Howard, A. G. Some improvements on deep convolutional neural network based image classification. arXiv.org https://doi.org/10.48550/arXiv.1805.07836 (2013).Yao, X. et al. Land use classification of the deep convolutional neural network method reducing the loss of spatial features. Sensors 19, 2792 (2019).ADS 
PubMed Central 
Article 

Google Scholar 
Chen, Y., Fan, R., Yang, X., Wang, J. & Latif, A. Extraction of urban water bodies from high-resolution remote-sensing imagery using deep learning. Water 10, 585 (2018).Article 

Google Scholar 
Gu, J. et al. Recent advances in convolutional neural networks. Pattern Recogn. 77, 354–377 (2018).ADS 
Article 

Google Scholar 
Srinivas, S., Subramanya, A. & Babu, R. V. Training Sparse Neural Networks. in 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) (IEEE, 2017).Liang, S., Lan, Y., Jiang, S., Li, Y. & Lu, Z. The activities of microbial communities in Huixian Wetland sediments under the interactive toxicity of Cu(II) and pentachloronitrobenzene. Acta Ecol. Sin. 37, 379–391 (2017).Article 

Google Scholar 
Feng, W. Fish diversity in huixian wetland in guangxi. Wetland Science 44, (2017).Breiman, L. Random forests. Mach. Learn. 45, 5–32 (2001).MATH 
Article 

Google Scholar 
Mutanga, O., Adam, E. & Cho, M. A. High density biomass estimation for wetland vegetation using WorldView-2 imagery and random forest regression algorithm. Int. J. Appl. Earth Obs. Geoinf. 18, 399–406 (2012).ADS 

Google Scholar 
van Beijma, S., Comber, A. & Lamb, A. Random forest classification of salt marsh vegetation habitats using quad-polarimetric airborne SAR, elevation and optical RS data. Remote Sens. Environ. 149, 118–129 (2014).ADS 
Article 

Google Scholar 
Badrinarayanan, V., Kendall, A. & Cipolla, R. SegNet: A deep convolutional encoder-decoder architecture for image segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 39, 2481–2495 (2017).PubMed 
Article 

Google Scholar 
Ioffe, S. & Szegedy, C. Batch normalization: Accelerating deep network training by reducing internal covariate shift. Int. Conf. Mach. Learn. 37, 448–456 (2015).
Google Scholar 
Long, J., Shelhamer, E. & Darrell, T. Fully convolutional networks for semantic segmentation. in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 3431–3440 (IEEE, 2015).Chen, L.-C., Barron, J. T., Papandreou, G., Murphy, K. & Yuille, A. L. semantic image segmentation with task-specific edge detection using CNNs and a discriminatively trained domain transform. in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 4545–4546 (IEEE, 2016).Eigen, D. & Fergus, R. Predicting depth, surface normals and semantic labels with a common multi-scale convolutional architecture. in 2015 IEEE International Conference on Computer Vision (ICCV) (IEEE, 2015).Hu, Y. et al. Deep learning classification of coastal wetland hyperspectral image combined spectra and texture features: A case study of Huanghe (Yellow) River Estuary wetland. Acta Oceanol. Sin. 38, 142–150 (2019).Article 

Google Scholar 
Liu, F. & Fang, M. Semantic segmentation of underwater images based on improved Deeplab. J. Marine Sci. Eng. 8, 188 (2020).Article 

Google Scholar 
Dronova, I. Object-based image analysis in wetland research: A review. Remote Sens. 7, 6380–6413 (2015).ADS 
Article 

Google Scholar 
Zhang, Z. & Sabuncu, M. R. Generalized cross entropy loss for training deep neural networks with noisy labels. arXiv.org https://arxiv.org/abs/1805.07836 (2018).Ruder, S. An overview of gradient descent optimization algorithms. arXiv.org https://arxiv.org/abs/1609.04747 (2016).Song, S. et al. Intelligent object recognition of urban water bodies based on deep learning for multi-source and multi-temporal high spatial resolution remote sensing imagery. Sensors 20, 397 (2020).ADS 
CAS 
PubMed Central 
Article 

Google Scholar 
Sun, G. et al. Fusion of multiscale convolutional neural networks for building extraction in very high-resolution images. Remote Sens. 11, 227 (2019).ADS 
Article 

Google Scholar 
Al-Najjar, H. A. H. et al. Land cover classification from fused DSM and UAV images using convolutional neural networks. Remote Sens. 11, 1461 (2019).ADS 
Article 

Google Scholar 
Villoslada, M. et al. Fine scale plant community assessment in coastal meadows using UAV based multispectral data. Ecol. Ind. 111, 105979 (2020).Article 

Google Scholar 
Zhao, H. & Liu, H. Multiple classifiers fusion and CNN feature extraction for handwritten digits recognition. Granul. Comput. 5, 411–418 (2019).Article 

Google Scholar 
Hu, K., Zhang, S. & Zhao, X. Context-based conditional random fields as recurrent neural networks for image labeling. Multimedia Tools Appl. 79, 17135–17145 (2019).Article 

Google Scholar 
Wang, M. et al. Assessing texture features to classify coastal wetland vegetation from high spatial resolution imagery using completed local binary patterns (CLBP). Remote Sens. 10, 778 (2018).ADS 
Article 

Google Scholar 
Szantoi, Z., Escobedo, F., Abd-Elrahman, A., Smith, S. & Pearlstine, L. Analyzing fine-scale wetland composition using high resolution imagery and texture features. Int. J. Appl. Earth Obs. Geoinf. 23, 204–212 (2013).ADS 

Google Scholar 
Bhatnagar, S., Gill, L., Regan, S., Waldren, S. & Ghosh, B. A nested drone-satellite approach to monitoring the ecological conditions of wetlands. ISPRS J. Photogramm. Remote. Sens. 174, 151–165 (2021).ADS 
Article 

Google Scholar  More

Trivers, R. L. Parent-offspring conflict. Am. Zool. 14, 249–264 (1974).Article 

Google Scholar 
Gittleman, J. L. & Thompson, S. D. Energy allocation in mammalian reproduction. Am. Zool. 28, 863–875 (1988).Article 

Google Scholar 
Kerby, J. & Post, E. Capital and income breeding traits differentiate trophic match-mismatch dynamics in large herbivores. Philos. Trans. R. Soc. B Biol. Sci. 368, 20120484 (2013).Article 

Google Scholar 
Costa, D. P. Reproductive and foraging energetics of pinnipeds: Implications for life history patterns. In The Behaviour of Pinnipeds (ed. D. Renouf) 300–344 (Springer, Netherlands, 1991).Costa, D. P., Boeuf, B. J. L., Huntley, A. C. & Ortiz, C. L. The energetics of lactation in the Northern elephant seal, Mirounga angustirostris. J. Zool. 209, 21–33 (1986).Article 

Google Scholar 
Crocker, D. E., Williams, J. D., Costa, D. P. & Le Boeuf, B. J. Maternal traits and reproductive effort in northern elephant seals. Ecology 82, 3541–3555 (2001).Article 

Google Scholar 
Shero, M. R., Krotz, R. T., Costa, D. P., Avery, J. P. & Burns, J. M. How do overwinter changes in body condition and hormone profiles influence Weddell seal reproductive success? Funct. Ecol. 29, 1278–1291 (2015).Article 

Google Scholar 
Lönnerdal, B. Bioactive proteins in human milk—potential benefits for preterm infants. Clin. Perinatol. 44, 179–191 (2017).PubMed 
Article 

Google Scholar 
Fields, D. A. et al. Associations between human breast milk hormones and adipocytokines and infant growth and body composition in the first 6 months of life. Pediatr. Obes. 12, 78–85 (2017).PubMed 
PubMed Central 
Article 

Google Scholar 
Klein, L. D. et al. Concentrations of trace elements in human milk: comparisons among women in Argentina, Namibia, Poland, and the United States. PLoS ONE 12, e0183367 (2017).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Burns, J. M. & Hammill, M. O. Does iron availability limit oxygen store development in seal pups? In 4th CPB Meeting in Africa: Mara 2008. “Molecules to migration: The pressures of life” International Proceedings 417–428 (Medimond Publishing Co., 2008).Burns, J. M., Lestyk, K., Folkow, L. P., Hammill, M. O. & Blix, A. S. Size and distribution of oxygen stores in harp and hooded seals from birth to maturity. J. Comp. Physiol. B 177, 687–700 (2007).CAS 
PubMed 
Article 

Google Scholar 
Kooyman, G. L. Diverse divers: Physiology and behavior. (Springer-Verlag, 1989).Butler, P. J. & Jones, D. R. Physiology of diving of birds and mammals. Physiol. Rev. 77, 837–899 (1997).CAS 
PubMed 
Article 

Google Scholar 
Kanatous, S. B., DiMichele, L. V., Cowan, D. F. & Davis, R. W. High aerobic capacities in skeletal muscles of pinnipeds: adaptations to diving hypoxia. J. Appl. Physiol. 86, 1247–1256 (1999).CAS 
PubMed 
Article 

Google Scholar 
Shero, M. R., Andrews, R. D., Lestyk, K. C. & Burns, J. M. Development of the aerobic dive limit and muscular efficiency in northern fur seals (Callorhinus ursinus). J. Comp. Physiol. B 182, 425–436 (2012).CAS 
PubMed 
Article 

Google Scholar 
Shero, M. R., Costa, D. P. & Burns, J. M. Scaling matters: Incorporating body composition into Weddell seal seasonal oxygen store comparisons reveals maintenance of aerobic capacities. J. Comp. Physiol. B 185, 811–824 (2015).CAS 
PubMed 
Article 

Google Scholar 
Shero, M. R., Reiser, P. J., Simonitis, L. & Burns, J. M. Links between muscle phenotype and life history: differentiation of myosin heavy chain composition and muscle biochemistry in precocial and altricial pinniped pups. J. Compar. Physiol. B, https://doi.org/10.1007/s00360-019-01240-w (2019).Burns, J. M., Lestyk, K., Freistroffer, D. & Hammill, M. O. Preparing muscles for diving: age-related changes in muscle metabolic profiles in Harp (Pagophilus groenlandicus) and hooded (Cystophora cristata) seals. Physiol. Biochem. Zool. 88, 167–182 (2015).CAS 
PubMed 
Article 

Google Scholar 
Kooyman, G. L., Wahrenbrock, E. A., Castellini, M. A., Davis, R. W. & Sinnett, E. E. Aerobic and anaerobic metabolism during voluntary diving in Weddell seals: evidence of preferred pathways from blood chemistry and behavior. J. Comp. Physiol. 138, 335–346 (1980).CAS 
Article 

Google Scholar 
Wallace, D. F. The regulation of iron absorption and homeostasis. Clin. biochemist. Rev. 37, 51–62 (2016).
Google Scholar 
Juan, S.-H. & Aust, S. D. Studies on the interaction between ferritin and ceruloplasmin. Arch. Biochem. Biophys. 355, 56–62 (1998).CAS 
PubMed 
Article 

Google Scholar 
Hagler, L. et al. Influence of dietary iron deficiency on hemoglobin, myoglobin, their respective reductases, and skeletal muscle mitochondrial respiration. Am. J. Clin. Nutr. 34, 2169–2177 (1981).CAS 
PubMed 
Article 

Google Scholar 
Kooyman, G. L. Weddell seal: Consummate Diver. (Cambridge University Press, 1981).Heerah, K. et al. Ecology of Weddell seals during winter: Influence of environmental parameters on their foraging behaviour. Deep Sea Res. Part II: Topical Stud. Oceanogr. 88–89, 23–33 (2013).ADS 
Article 

Google Scholar 
Hindell, M. A., Harcourt, R., Waas, J. R. & Thompson, D. Fine-scale three-dimensional spatial use by diving, lactating female Weddell seals Leptonychotes weddellii. Mar. Ecol. Prog. Ser. 242, 275–284 (2002).ADS 
Article 

Google Scholar 
Sato, K. et al. Deep foraging dives in relation to the energy depletion of Weddell seal (Leptonychotes weddellii) mothers during lactation. Polar Biol. 25, 696–702 (2002).Article 

Google Scholar 
Wheatley, K. E., Bradshaw, C. J., Davis, L. S., Harcourt, R. G. & Hindell, M. A. Influence of maternal mass and condition on energy transfer in Weddell seals. J. Anim. Ecol. 75, 724–733 (2006).PubMed 
Article 

Google Scholar 
Walcott, S. M. Evaluating the dynamics of physiological, environmental and behavioral parameters to the cost of the annual pelage molt in a polar pinniped: the Weddell seal (Leptonychotes weddellii) MSc thesis, University of Alaska Anchorage, (2019).Beltran, R. S. et al. Seasonal resource pulses and the foraging depth of a Southern Ocean top predator. Proc. R. Soc. B: Biol. Sci. 288, 20202817 (2021).CAS 
Article 

Google Scholar 
Shero, M. R., Goetz, K. T., Costa, D. P. & Burns, J. M. Temporal changes in Weddell seal dive behavior over winter: Are females increasing foraging effort to support gestation? Ecol. Evol. 8, 11857–11874 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
Looker, A. C. & Johnson, C. L. Prevalence of elevated serum transferrin saturation in adults in the United States. Ann. Intern. Med. 129, 940–945 (1998).CAS 
PubMed 
Article 

Google Scholar 
Eleftheriadis, T., Liakopoulos, V., Antoniadi, G. & Stefanidis, I. Which is the best way for estimating transferrin saturation. Ren. Fail. 32, 1022–1023 (2010).PubMed 
Article 

Google Scholar 
McLaren, C. E. et al. Distribution of transferrin saturation in an Australian population: relevance to the early diagnosis of hemochromatosis. Gastroenterology 114, 543–549 (1998).CAS 
PubMed 
Article 

Google Scholar 
Emmett, B. & Hochachka, P. W. Scaling of oxidative and glycolytic enzymes in mammals. Respir. Physiol. 45, 261–272 (1981).CAS 
PubMed 
Article 

Google Scholar 
Clark, C. A., Burns, J. M., Schreer, J. F. & Hammill, M. O. Erythropoietin concentration in developing harbor seals (Phoca vitulina). Gen. Comp. Endocrinol. 147, 262–267 (2006).CAS 
PubMed 
Article 

Google Scholar 
Richmond, J. P., Burns, J. M., Rea, L. D. & Mashburn, K. L. Postnatal ontogeny of erythropoietin and hematology in free-ranging Steller sea lions (Eumetopias jubatus). Gen. Comp. Endocrinol. 141, 240–247 (2005).CAS 
PubMed 
Article 

Google Scholar 
Hadley, G. L., Rotella, J. J. & Garrott, R. A. Influence of maternal characteristics and oceanographic conditions on survival and recruitment probabilities of Weddell seals. Oikos 116, 601–613 (2006).Article 

Google Scholar 
Hall, A. C., McConnell, B. J. & Barker, R. J. Factors affecting first-year survival in grey seals and their implications for life history strategies. J. Anim. Ecol. 70, 138–149 (2001).
Google Scholar 
Proffitt, K. M., Garrott, R. A. & Rotella, J. J. Long-term evaluation of body mass at weaning and postweaning survival rates of Weddell seals in Erebus Bay, Antarctica. Mar. Mamm. Sci. 24, 677–689 (2008).Article 

Google Scholar 
Burns, J. M. & Castellini, M. A. Physiological and behavioral determinants of the aerobic dive limit in Weddell seal (Leptonychotes weddellii) pups. J. Comp. Physiol. B 166, 473–483 (1996).Article 

Google Scholar 
Costa, D. P., Kuhn, C. E., Weise, M. J., Shaffer, S. A. & Arnould, J. P. Y. When does physiology limit the foraging behaviour of freely diving mammals? Int. Congr. Ser. 1275, 359–366 (2004).Article 

Google Scholar 
Hadley, G. L., Rotella, J. J. & Garrott, R. A. Evaluation of reproductive costs for Weddell seals in Erebus Bay, Antarctica. J. Anim. Ecol. 76, 448–458 (2007).PubMed 
Article 

Google Scholar 
Young, S. P., Fahmy, M. & Golding, S. Ceruloplasmin, transferrin and apotransferrin facilitate iron release from human liver cells. FEBS Lett. 411, 93–96 (1997).CAS 
PubMed 
Article 

Google Scholar 
Mazzaro, L. M., Dunn, J. L., St. Aubin, D. J., Andrews, G. A. & Chavey, P. S. Serum indices of body stores of iron in northern fur seals (Callorhinus ursinus) and their relationship to hemochromatosis. Zoo. Biol. 23, 205–218 (2004).Article 

Google Scholar 
Yalçn, S. S., Baykan, A., Yurdakök, K., Yalçn, S. & Gücüs, A. I. The factors that affect milk-to-serum ratio for iron during early lactation. J. Pediatr. Hematol. Oncol. 31, 85–90 (2009).Article 

Google Scholar 
Geiseler, S. J., Blix, A. S., Burns, J. M. & Folkow, L. P. Rapid postnatal development of myoglobin from large liver iron stores in hooded seals. J. Exp. Biol. 216, 1793–1798 (2013).CAS 
PubMed 

Google Scholar 
Samokyszyn, V. M., Miller, D. M., Reif, D. W. & Aust, S. D. Inhibition of superoxide and ferritin-dependent lipid peroxidation by ceruloplasmin. J. Biol. Chem. 264, 21–26 (1989).CAS 
PubMed 
Article 

Google Scholar 
Kohgo, Y., Ikuta, K., Ohtake, T., Torimoto, Y. & Kato, J. Body iron metabolism and pathophysiology of iron overload. Int. J. Hematol. 88, 7–15 (2008).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Zhang, P. et al. The effect of serum iron concentration on iron secretion into mouse milk. J. Physiol. 522(Pt 3), 479–491 (2000).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Erdogan, S., Celik, S. & Erdogan, Z. Seasonal and locational effects on serum, milk, liver and kidney chromium, manganese, copper, zinc, and iron concentrations of dairy cows. Biol. Trace Elem. Res. 98, 51–61 (2004).CAS 
PubMed 
Article 

Google Scholar 
Kaldor, I. & Morgan, E. H. Iron metabolism during lactation and suckling in a marsupial, the quokka (Setonix brachyurus). Comp. Biochem. Physiol. Part A: Physiol. 84, 691–694 (1986).CAS 
Article 

Google Scholar 
Tedman, R. A. & Green, B. Water and sodium fluxes in suckling pups of Weddell seals (Leptonychotes weddelli). J. Zool. 212, 29–42 (1987).Article 

Google Scholar 
National Institutes of Health, Supplements, O. o. D. Iron Fact Sheet for Consumers, https://ods.od.nih.gov/factsheets/Iron-Consumer/ (2021).Saarinen, U. M., Siimes, M. A. & Dallman, P. R. Iron absorption in infants: high bioavailability ofbreast milk iron as indicated by the extrinsic tag method of iron absorption and by the concentration of serum ferritin. J. Pediatrics 91, 36–39 (1977).CAS 
Article 

Google Scholar 
Loh, T.-T. Iron metabolism of the lactating mouse. Proc. Soc. Exp. Biol. Med. 137, 962–965 (1971).CAS 
PubMed 
Article 

Google Scholar 
Folkow, L. P., Nordoy, E. S. & Blix, A. S. Distribution and diving behavior of harp seals (Pagophilus groenlandica) from the Greenland Sea stock. Polar Biol. 27, 281–298 (2004).Article 

Google Scholar 
Beck, C. A., Bowen, W. D. & Iverson, S. J. Seasonal changes in buoyancy and diving behaviour of adult grey seals. J. Exp. Biol. 203, 2323–2330 (2000).CAS 
PubMed 
Article 

Google Scholar 
Gentry, R. L. & Kooyman, G. L. Fur seals: maternal strategies on land and at sea. (Princeton University Press, 1986).McDonald, B. I. & Ponganis, P. J. Insights from venous oxygen profiles: oxygen utilization and management in diving California sea lions. J. Exp. Biol. 216, 3332–3341 (2013).CAS 
PubMed 
Article 

Google Scholar 
Noren, S. R., Iverson, S. J. & Boness, D. J. Development of the blood and muscle oxygen stores in gray seals (Halichoerus grypus): Implications for juvenile diving capacity and the necessity of a terrestrial postweaning fast. Physiol. Biochem. Zool. 78, 482–490 (2005).PubMed 
Article 

Google Scholar 
Weise, M. J. & Costa, D. P. Total body oxygen stores and physiological diving capacity of California sea lions as a function of sex and age. J. Exp. Biol. 210, 278–289 (2007).PubMed 
Article 

Google Scholar 
Burns, J. M., Hindell, M. A., Bradshaw, C. J. A. & Costa, D. P. Fine-scale habitat selection by crabeater seals as determined by diving behavior. Deep Sea Res. II 55, 500–514 (2008).ADS 
Article 

Google Scholar 
Burns, J. Crabeater seal oxygen stores. U.S. Antarctic Program (USAP) Data Center. https://doi.org/10.15784/601583 (2022).Nicol, S. et al. Southern Ocean iron fertilization by baleen whales and Antarctic krill. Fish. Fish. 11, 203–209 (2010).Article 

Google Scholar 
Williams, T. M. The cost of foraging by a marine predator, the Weddell seal Leptonychotes weddellii: pricing by the stroke. J. Exp. Biol. 207, 973–982 (2004).PubMed 
Article 

Google Scholar 
Wheatley, K. E., Bradshaw, C. J. A., Harcourt, R. G. & Hindell, M. A. Feast or famine: evidence for mixed capital–income breeding strategies in Weddell seals. Oecologia 155, 11–20 (2008).ADS 
PubMed 
Article 

Google Scholar 
Honda, K., Sahrul, M., Hidaka, H. & Tatsukawa, R. Organ and tissue distribution of heavy metals, and their growth-related changes in Antarctic Fish, Pagothenia borchgrevinki. Agric. Biol. Chem. 47, 2521–2532 (1983).CAS 

Google Scholar 
Galbraith, E. D., Le Mézo, P., Solanes Hernandez, G., Bianchi, D. & Kroodsma, D. Growth limitation of marine fish by low iron availability in the open ocean. Front. Marine Sci. 6, https://doi.org/10.3389/fmars.2019.00509 (2019).Pollycove, M. & Mortimer, R. The quantitative determination of iron kinetics and hemoglobin synthesis in human subjects. J. Clin. Invest. 40, 753–782 (1961).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Åkeson, Å., Ehrenstein, G. V., Hevesy, G. & Theorell, H. Life span of myoglobin. Arch. Biochem. Biophys. 91, 310–318 (1960).PubMed 
Article 

Google Scholar 
Tift, M. S. et al. Adaptive potential of the heme oxygenase/carbon monoxide pathway during hypoxia. Front. Physiol. 11, https://doi.org/10.3389/fphys.2020.00886 (2020).Tift, M. S., Ponganis, P. J. & Crocker, D. E. Elevated carboxyhemoglobin in a marine mammal, the northern elephant seal. J. Exp. Biol. 217, 1752–1757 (2014).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Ma, Y.-J. et al. A modified carbon monoxide breath test for measuring erythrocyte lifespan in small animals. BioMed. Res. Int. 2016, 7173156 (2016).PubMed 
PubMed Central 

Google Scholar 
Zhang, H.-D. et al. Human erythrocyte lifespan measured by Levitt’s CO breath test with newly developed automatic instrument. J. Breath. Res. 12, 036003 (2018).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Hochachka, P. W. & Somero, G. N. Biochemical adaptation. (Oxford University Press, 2002).De Miranda, M. A., Schlater, A. E., Green, T. L. & Kanatous, S. B. In the face of hypoxia: myoglobin increases in response to hypoxic conditions and lipid supplementation in cultured Weddell seal skeletal muscle cells. J. Exp. Biol. 215, 806–813 (2012).PubMed 
Article 
CAS 

Google Scholar 
Kanatous, S. B. & Mammen, P. P. Regulation of myoglobin expression. J. Exp. Biol. 213, 2741–2747 (2010).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Halvorsen, S. & Bechensteen, A. G. Physiology of erythropoietin during mammalian development. Acta Paediatr. Suppl. 438, 17–26 (2002).Article 

Google Scholar 
Hochachka, P. W. Mechanism and evolution of hypoxia-tolerance in humans. J. Exp. Biol. 201, 1243–1254 (1998).CAS 
PubMed 
Article 

Google Scholar 
Klopfleisch, R. & Olias, P. The pathology of comparative animal models of human haemochromatosis. J. Comp. Pathol. 147, 460–478 (2012).CAS 
PubMed 
Article 

Google Scholar 
Henriksson, J. & Reitman, J. S. Time course of changes in human skeletal muscle succinate dehydrogenase and cytochrome oxidase activities and maximal oxygen uptake with physical activity and inactivity. Acta Physiol. Scand. 99, 91–97 (1977).CAS 
PubMed 
Article 

Google Scholar 
Goetz, K. T. Movement, habitat, and foraging behavior of Weddell seals (Leptonychotes weddellii) in the western Ross Sea, Antarctica, University of California Santa Cruz, (2015).Cisewski, B., Strass, V. H., Rhein, M. & Krägefsky, S. Seasonal variation of diel vertical migration of zooplankton from ADCP backscatter time series data in the Lazarev Sea, Antarctica. Deep Sea Res. Part I: Oceanographic Res. Pap. 57, 78–94 (2010).ADS 
CAS 
Article 

Google Scholar 
Jones, R. M. & Smith, W. O. The influence of short-term events on the hydrographic and biological structure of the southwestern Ross Sea. J. Mar. Syst. 166, 184–195 (2017).Article 

Google Scholar 
Smith, W. O. & Nelson, D. M. Importance of ice edge phytoplankton production in the Southern Ocean. Bioscience 36, 251–257 (1986).CAS 
Article 

Google Scholar 
Rivkin, R. B. Seasonal patterns of planktonic production in McMurdo Sound, Antarctica. Am. Zool. 31, 5–16 (2015).Article 

Google Scholar 
Proffitt, K. M., Rotella, J. J. & Garrott, R. A. Effects of pup age, maternal age, and birth date on pre-weaning survival rates of Weddell seals in Erebus Bay, Antarctica. Oikos 119, 1255–1264 (2010).Article 

Google Scholar 
Beltran, R. S., Kirkham, A. L., Breed, G. A., Testa, J. W. & Burns, J. M. Reproductive success delays moult phenology in a polar mammal. Sci. Rep. 9, 5221 (2019).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Mellish, J.-A. E., Tuomi, P. A., Hindle, A. G. & Horning, M. Chemical immobilization of Weddell seals (Leptonychotes weddellii) by ketamine/midazolam combination. Vet. Anaesth. Analg. 37, 123–131 (2010).CAS 
PubMed 
Article 

Google Scholar 
Shero, M. R., Pearson, L. E., Costa, D. P. & Burns, J. M. Improving the precision of our ecosystem calipers: a modified morphometric technique for estimating marine mammal mass and body composition. PLoS ONE 9, e91233 (2014).ADS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Foldager, N. & Blomqvist, C. G. Repeated plasma volume determination with the Evans blue dye dilution technique: the method and the computer program. Comput. Biol. Med. 21, 35–41 (1991).CAS 
PubMed 
Article 

Google Scholar 
El-Sayed, H., Goodall, S. R. & Hainsworth, F. R. Re-evaluation of Evans blue dye dilution method of plasma volume measurement. Clin. Lab. Haem. 17, 189–194 (1995).CAS 

Google Scholar 
Reynafarje, B. Simplified method for the determination of myoglobin. J. Lab. Clin. Med. 61, 138–145 (1963).CAS 
PubMed 

Google Scholar 
Prewitt, J. S., Freistroffer, D. V., Schreer, J. F., Hammill, M. O. & Burns, J. M. Postnatal development of muscle biochemistry in nursing harbor seal (Phoca vitulina) pups: Limitations to diving behavior? J. Comp. Physiol. B 180, 757–766 (2010).CAS 
PubMed 
Article 

Google Scholar 
Polasek, L., Dickson, K. A. & Davis, R. W. Metabolic indicators in the skeletal muscles of harbor seals (Phoca vitulina). Am. J. Physiol. Regul. Integr. Comp. Physiol. 290, R1720–R1727 (2006).CAS 
PubMed 
Article 

Google Scholar 
Kooyman, G. L., Castellini, M. A., Davis, R. W. & Maue, R. A. Aerobic diving limits of immature Weddell seals. J. Comp. Physiol. 151, 171–174 (1983).Article 

Google Scholar 
Davis, R. W. & Kanatous, S. B. Convective oxygen transport and tissue oxygen consumption in Weddell seals during aerobic dives. J. Exp. Biol. 202, 1091–1113 (1999).CAS 
PubMed 
Article 

Google Scholar 
Lenfant, C., Johansen, K. & Torrance, J. D. Gas transport and oxygen storage capacity in some pinnipeds and the sea otter. Respir. Physiol. 9, 277–286 (1970).CAS 
PubMed 
Article 

Google Scholar 
Kleiber, M. The fire of life: an introduction to animal energetics. (R.E. Krieger Pub. Co., 1975).Sato, K., Mitani, Y., Cameron, M. F., Siniff, D. B. & Naito, Y. Factors affecting stroking patterns and body angle in diving Weddell seals under natural conditions. J. Exp. Biol. 206, 1461–1470 (2003).PubMed 
Article 

Google Scholar 
Zuur, A. F., Hilbe, J. M. & Ieno, E. N. A Beginner’s Guide to GLM and GLMM with R: A Frequentist and Bayesian Perspective for Ecologists. (Highland Statistics Newburgh, 2013).Shero, M. Weddell seal iron dynamics and oxygen stores across lactation. U.S. Antarctic Program (USAP) Data Center. https://doi.org/10.15784/601575. (2022).Anderson, R. S. et al. Zinc, copper, iron and calcium concentrations in bitch milk. J. Nutr. 121, S81–S82 (1991).CAS 
PubMed 
Article 

Google Scholar 
Griffiths, M., Green, B., MC Leckie, R., Messer, M. & Newgrain, K. Constituents of platypus and echidna milk, with particular reference to the fatty acid complement of the triglycerides. Aust. J. Biol. Sci. 37, 323–330 (1984).CAS 
Article 

Google Scholar 
Peddemors, V. M., de Muelenaere, H. J. H. & Devchand, K. Comparative milk composition of the bottlenosed dolphin (Tursiops truncatus), humpback dolphin (Sousa plumbea) and common dolphin (Delphinus delphis) from southern African waters. Comp. Biochem. Physiol. Part A Physiol. 94, 639–641 (1989).CAS 
Article 

Google Scholar 
Ullrey, D. E. et al. Blue-green color and composition of Stejneger’s beaked whale (Mesoplodon stejnegeri) milk. Comp. Biochem. Physiol. B Comp. Biochem. 79, 349–352 (1984).CAS 
Article 

Google Scholar 
Dosako, S. I. et al. Milk of Northern fur seal: composition, especially carbohydrate and protein. J. Dairy Sci. 66, 2076–2083 (1983).CAS 
PubMed 
Article 

Google Scholar 
Oftedal, O. T., Boness, D. J. & Tedman, R. The Behavior, Physiology, and Anatomy of Lactation in the Pinnipedia. (Genoyways, H. H. eds) (Current Mammalogy. Springer, Boston, MA, 1987).Habran, S., Pomeroy, P. P., Debier, C. & Das, K. Changes in trace elements during lactation in a marine top predator, the grey seal. Aquat. Toxicol. 126, 455–466 (2013).CAS 
PubMed 
Article 

Google Scholar 
Seal, U. S., Erickson, A. W., Siniff, D. B. & Cline, D. R. Blood chemistry and protein polymorphisms in three species of Antarctic seals (Lobodon carcinophagus, Leptonychootes weddellii, and Mirounga leonina) In Antarctic Pinnipedia 181–192 (1971).Green, B., Fogerty, A., Libke, J., Newgrain, K. & Shaughnessy, P. Aspects of lactation in the crab-eater seal (Lobodon-Carcinophagus). Aust. J. Zool. 41, 203–213 (1993).Article 

Google Scholar 
Casey, C. E., Smith, A. & Zhang, P. Microminerals in human and animal milks, In Handbook of milk composition 622–674 (ed. R. G. Jensen) (Academic Press, 1995). More

Wirtz, K., Smith, S. L., Mathis, M. & Taucher, J. Nat. Clim. Change https://doi.org/10.1038/s41558-022-01430-5 (2022).Article 

Google Scholar 
Watanabe, M., Kohata, K. & Kimura, T. Limnol. Oceanogr. 36, 593–602 (1991).Article 

Google Scholar 
Villareal, T. A. et al. Nature 397, 423–425 (1999).CAS 
Article 

Google Scholar 
Krumhardt, K. M., Lovenduski, N. S., Iglesias-Rodriguez, M. D. & Kleypas, J. A. Prog. Oceanogr. 159, 276–295 (2017).Article 

Google Scholar 
Alldredge, A. L. & Silver, M. W. Prog. Oceanogr. 20, 41–82 (1988).Article 

Google Scholar 
White, A. E., Spitz, Y. H. & Letelier, R. M. Mar. Ecol. Prog. Ser. 323, 35–45 (2006).Article 

Google Scholar 
Kwiatkowski, L. et al. Biogeosciences 17, 3439–3470 (2020).CAS 
Article 

Google Scholar 
Tittensor, D. P. et al. Nat. Clim. Change 11, 973–981 (2021).Article 

Google Scholar 
Giorgetta, M. A. et al. J. Adv. Model. Earth Syst. 5, 572–597 (2013).Article 

Google Scholar 
McGillicuddy, D. J. et al. Nature 394, 263–266 (1998).CAS 
Article 

Google Scholar 
Lévy, M., Franks, P. J. & Smith, K. S. Nat. Commun. 9, 4758 (2018).Article 

Google Scholar 
Durham, W. M. & Stocker, R. Annu. Rev. Mar. Sci. 4, 177–207 (2012).Article 

Google Scholar 
Cullen, J. J. Annu. Rev. Mar. Sci. 7, 207–239 (2015).Article 

Google Scholar 
Moeller, H. V., Laufkötter, C., Sweeney, E. M. & Johnson, M. D. Nat. Commun. 10, 1978 (2019).Article 

Google Scholar 
Fawcett, S. E., Johnson, K. S., Riser, S. C., Van Oostende, N. & Sigman, D. M. Mar. Chem. 207, 108–123 (2018).CAS 
Article 

Google Scholar  More

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Zangoueinejad, R. & Alebrahim, M. T. Use of conventional and innovative organic materials as alternatives to black plastic mulch to suppress weeds in tomato production. Biol. Agric. Hortic. 37, 267–284. https://doi.org/10.1080/01448765.2021.1947377 (2021).Article 

Google Scholar 
Biswas, S. K., Akanda, A. R., Rahman, M. S. & Hossain, M. A. Effect of drip irrigation and mulching on yield, water-use efficiency and economics of tomato. Plant Soil Environ. 61, 97–102. https://doi.org/10.17221/804/2014-PSE (2015).Article 

Google Scholar 
Haapala, T., Palonen, P., Tamminen, A. & Ahokas, J. Effects of different paper mulches on soil temperature and yield of cucumber (Cucumis sativus L.) in the temperate zone. Agric. Food Sci. 24, 52–58. https://doi.org/10.23986/afsci.47220 (2015).CAS 
Article 

Google Scholar 
Shiukhy, S., Raeini-Sarjaz, M. & Chalavi, V. Colored plastic mulch microclimates affect strawberry fruit yield and quality. Int. J. Biometeorol. 59, 1061–1066. https://doi.org/10.1007/s00484-014-0919-0 (2015).ADS 
Article 
PubMed 

Google Scholar 
Sideman, R. G. Performance of sweetpotato cultivars grown using biodegradable black plastic mulch in New Hampshire. HortTechnology 25, 412–416. https://doi.org/10.21273/HORTTECH.25.3.412 (2015).Article 

Google Scholar 
Ferdous, Z., Datta, A. & Anwar, M. Plastic mulch and indigenous microorganism effects on yield and yield components of cauliflower and tomato in inland and coastal regions of Bangladesh. J. Crop Improv. 31, 261–279. https://doi.org/10.1080/15427528.2017.1293578 (2017).Article 

Google Scholar 
Lament, W. J. Jr. Plastic mulches for the production of vegetable crops. HortTechnology 3, 35–39. https://doi.org/10.21273/HORTTECH.3.1.35 (1993).Article 

Google Scholar 
Abdul-Baki, A. A., Teasdale, J. R., Goth, R. W. & Haynes, K. G. Marketable yields of fresh-market tomatoes grown in plastic and hairy vetch mulches. HortScience 37, 878–881. https://doi.org/10.21273/HORTSCI.37.6.878 (2002).Article 

Google Scholar 
Chalker-Scott, L. Impact of mulches on landscape plants and the environment—A review. J. Environ. Hortic. 25, 239–249. https://doi.org/10.24266/0738-2898-25.4.239 (2007).Article 

Google Scholar 
Kasirajan, S. & Ngouajio, M. Polyethylene and biodegradable mulches for agricultural applications: A review. Agron. Sustain. Dev. 32, 501–529. https://doi.org/10.1007/s13593-011-0068-3 (2012).CAS 
Article 

Google Scholar 
Iqbal, R. et al. Potential agricultural and environmental benefit of mulches—A review. Bull. Natl. Res. Cent. 44, 752020. https://doi.org/10.1186/s42269-020-00290-3 (2020).Article 

Google Scholar 
Travlos, I. et al. Efficacy of different herbicides on Echinocholoa colona (L.) Link control and the first case of its glyphosate resistance in Greece. Agronomy 10, 1056. https://doi.org/10.3390/agronomy10071056 (2000).CAS 
Article 

Google Scholar 
Travlos, I. S. & Chachalis, D. Glyphsate-resistant hairy fleabane (Conyza bonariensis) is reported in Greece. Weed Technol. 24, 569–573. https://doi.org/10.1614/WT-D-09-00080.1 (2010).CAS 
Article 

Google Scholar 
Tahmasebi, B. K. et al. Effectiveness of alternative herbicides on three Conyza species from Europe with and without glyphosate resistance. Crop Prot. 112, 350–355. https://doi.org/10.1016/j.cropro.2018.06.021 (2018).CAS 
Article 

Google Scholar 
Kanatas, P., Anthonopoulos, N., Gazoulis, I. & Travlos, I. S. Screening glyphosate-alternative weed control options in important perennial crops. Weed Sci. 69, 704–718. https://doi.org/10.1017/wsc.2021.55 (2021).Article 

Google Scholar 
Anthonopoulos, N. et al. Hot foam: Evaluation of a new, non-chemical weed control option in perennial crops. Smart Agric. Technol. 3, 1000063. https://doi.org/10.1016/j.atech.2022.100063 (2023).Article 

Google Scholar 
Espí, E., Salmerón, A., Fontecha, A., García, Y. & Real, A. I. Plastic films for agricultural applications. J. Plast. Film Sheeting 22, 85–102. https://doi.org/10.1177/8756087906064220 (2006).CAS 
Article 

Google Scholar 
Li, C. et al. Effects of biodegradable mulch on soil quality. Appl. Soil Ecol. 79, 59–69. https://doi.org/10.1016/j.apsoil.2014.02.012 (2014).ADS 
Article 

Google Scholar 
van Sebille, E. A global inventory of small floating plastic debris. Environ. Res. Lett. 10, 124006. https://doi.org/10.1088/1748-9326/10/12/124006 (2015).ADS 
Article 

Google Scholar 
Moreno, M. M., Cirujeda, A., Aibar, J. & Moreno, C. Soil thermal and productive responses of biodegradable mulch materials in a processing tomato (Lycopersicon esculentum Mill.). Crop. Soil Res. 54, 207–215. https://doi.org/10.1071/SR15065 (2016).Article 

Google Scholar 
Barnes, D. K. A., Galgani, F., Thompson, R. C. & Barlaz, M. Accumulation and fragmentation of plastic debris in global environments. Philos Trans. R. Soc. Lond. B Biol. Sci. 364, 1985–1998. https://doi.org/10.1098/rstb.2008.0205 (2009).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Moore, C. J. Synthetic polymers in the marine environment: A rapidly increasing, long-term threat. Environ. Res. 108, 131–139. https://doi.org/10.1016/j.envres.2008.07.025 (2008).CAS 
Article 
PubMed 

Google Scholar 
Lim, X. Microplastics are everywhere—But are they harmful?. Nature 593, 22–25. https://doi.org/10.1038/d41586-021-01143-3 (2021).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Cardinael, Ŕ, Cadisch, G., Gosme, M., Oelbermann, M. & van Noordwik, M. Climate change mitigation and adaptation agriculture: Why agroforestry should be part of the solution. Agric. Ecosyst. Environ. 319, 107555. https://doi.org/10.1016/j.agee.2021.107555 (2021).Article 

Google Scholar 
Ji, S. & Unger, P. W. Soil water accumulation under different precipitation, potential evaporation, and straw mulch conditions. Soil Sci. Soc. Am. J. 65, 442–448. https://doi.org/10.2136/sssaj2001.652442x (2001).ADS 
CAS 
Article 

Google Scholar 
Schmithals, A. & Kühn, N. To mulch or not to mulch? Effects of gravel mulch toppings on plant establishment and development in ornamental prairie plantings. PLoS ONE 12, e0171533. https://doi.org/10.1371/journal.pone.0171533 (2017).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Pinamonti, F. Compost mulch effects on soil fertility, nutritional status and performance of grapevine. Nutr. Cycl. Agroecosyst. 51, 239–248. https://doi.org/10.1023/A:1009701323580 (1998).Article 

Google Scholar 
Cline, G. R. & Silvernail, A. F. Residual nitrogen and kill date effects on winter cover crop growth and nitrogen content in a vegetable production system. HortTechnology 11, 219–225. https://doi.org/10.21273/HORTTECH.11.2.219 (2001).CAS 
Article 

Google Scholar 
Cherr, C. M., Scholberg, J. M. S. & McSorley, R. Green manure approaches to crop production: A synthesis. Agron. J. 98, 302–319. https://doi.org/10.2134/agronj2005.0035 (2006).Article 

Google Scholar 
Nguyen, L. T. T., Ortner, K. A., Tiemann, L. K., Renner, K. A. & Kravchenko, A. N. Soil properties after one year of interseeded cover cropping in topographically diverse agricultural landscape. Agric. Ecosyst. Environ. 326, 107803. https://doi.org/10.1016/j.agee.2021.107803 (2021).CAS 
Article 

Google Scholar 
Breton, V., Crosaz, Y. & Rey, F. Effects of wood chip amendments on the revegetation performance of plant species on eroded marly terrains in a Mediterranean mountainous climate (Southern Alps, France). Solid Earth 7, 599–610. https://doi.org/10.5194/se-2016-11 (2016).ADS 
Article 

Google Scholar 
Wang, L., Gruber, S. & Claupein, W. Effects of woodchip mulch and barley intercropping on weeds in lentil crops. Weed Res. 52, 161–168. https://doi.org/10.1111/j.1365-3180.2012.00905.x (2012).Article 

Google Scholar 
Jabran, K. Use of mulches for managing field bindweed and purple nutsedge, and weed control in spinach. Int. J. Agric. Biol. 23, 1114–1120. https://doi.org/10.17957/IJAB/15.1394 (2020).CAS 
Article 

Google Scholar 
Keeley, J. E., Morton, B. A., Pedrosa, A. & Trotter, P. Role of allelopathy, heat and charred wood in the germination of chaparral herbs and suffrutescents. J. Ecol. 73, 445–458. https://doi.org/10.2307/2260486 (1985).Article 

Google Scholar 
Schumann, A. W., Little, K. M. & Eccles, N. S. Suppression of seed germination and early seedling growth by plantation harvest residues. S. Afr. J. Plant Soil 12, 170–172. https://doi.org/10.1080/02571862.1995.10634359 (1995).Article 

Google Scholar 
Rathinasabapathi, B., Ferguson, J. & Gal, M. Evaluation of allelopathic potential of wood chips for weed suppression in horticultural production systems. HortScience 40, 711–713. https://doi.org/10.21273/HORTSCI.40.3.711 (2005).Article 

Google Scholar 
Wezel, A. et al. Agroecological practices for sustainable agriculture. A review. Agron. Sustain. Dev. 34, 1–20. https://doi.org/10.1142/q0088 (2014).Article 

Google Scholar 
Rahmathulla, V. K. Management of climatic factors for successful silkworm (Bombyx mori L.) crop and higher silk production: A review. Psyche J. Entomol. 2012, 121234. https://doi.org/10.1155/2012/121234 (2012).Article 

Google Scholar 
Guttikunda, S. K. & Kopakka, R. V. Source emissions and health impacts of urban air pollution in Hyderadad, India. Air Qual. Atmos. Health 7, 195–207. https://doi.org/10.1007/s11869-013-0221-z (2014).CAS 
Article 

Google Scholar 
Dhaka, S. K. et al. PM2.5 diminution and haze events over Delhi during the COVID-19 lockdown period: An interplay between the baseline pollution and meteorology. Sci. Rep. 10, 13442. https://doi.org/10.1038/s41598-020-70179-8 (2020).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Ehret, D. L., Helmer, T. & Hall, J. W. Cuticle cracking in tomato fruit. J. Hortic. Sci. 68, 195–201. https://doi.org/10.1080/00221589.1993.11516343 (1993).Article 

Google Scholar 
Peet, M. M. & Willits, D. H. Role of excess water in tomato fruit cracking. Hortic. Sci. 30, 65–68. https://doi.org/10.21273/HORTSCI.30.1.65 (1995).Article 

Google Scholar 
Ikeda, T., Sakamoto, Y., Watanabe, S. & Okano, K. Water relations in fruit cracking of single-truss tomato plants. Environ. Control Biol. 37, 153–158. https://doi.org/10.2525/ecb1963.37.153 (1999).Article 

Google Scholar 
Uetani, M., Fujitani, S. & Kimura, M. Mitigation techniques on fruit cracking in tomato cultivation under rain shelter in summer and autumn. Bull. Oita Pref Agr. For. Fish. Res. Cent. 4, 11–25 (2014) (in Japanese with English summary).
Google Scholar 
Kuhns, L. J. Efficacy and phytotoxicity of three landscape herbicides with and without a light mulch. Proc. Northeast. Weed Sci. Soc. 46, 85–89 (1992).
Google Scholar 
Petrikovszki, R., Zalai, M., Bogdányi, F. T. & Tóth, F. The effect of organic mulching and irrigation on the weed species composition and the soil weed seed bank of tomato. Plants 9, 66. https://doi.org/10.3390/plants9010066 (2020).Article 
PubMed Central 

Google Scholar 
Egley, G. H. Weed seed and seedling reductions by soil solarization with transparent polyethylene sheets. Weed Sci. 31, 404–409. https://doi.org/10.1017/S0043174500069253 (1983).Article 

Google Scholar 
Ashworth, S. & Harrison, H. Evaluation of mulches for use in the home garden. HortScience 18, 180–182 (1983).
Google Scholar 
Chakrabory, R. C. & Sadhu, M. K. Effect of mulch type and colour on growth and yield of tomato (Lycopersicon esculentum). Indian J. Agric. Sci. 64, 608–612 (1994).
Google Scholar 
Bhella, H. S. Tomato response to trickle irrigation and black polyethylene mulch. J. Am. Soc. Hortic. Sci. 113, 543–546 (1988).
Google Scholar 
Garnaud, J. C. The Intensification of Horticultural Crop Production in the Mediterranean Basin by Protected Cultivation (FAO of the United Nations, 1974).
Google Scholar 
Ahmad, S. et al. Significance of partial root zone drying and mulches for water saving and weed suppression in wheat. J. Anim. Plant Sci. 30, 154–162. https://doi.org/10.36899/japs.2020.1.0018 (2020).Article 

Google Scholar 
Ahmad, S. et al. Mulching strategies for weeds control and water conservation in cotton. ARPN J. Agric. Biol. Sci. 10, 299–306 (2015).
Google Scholar 
Hartwing, N. L. & Ammon, H. U. Cover crops and living mulches. Weed Sci. 50, 688–699. https://doi.org/10.1614/0043-1745(2002)050[0688:AIACCA]2.0.CO;2 (2002).Article 

Google Scholar 
Samedani, B., Ranjbar, M., Rahimian, H. & Jahansoz, M. R. Utilization of rye and hairy vetch cover crops for weed control in transplanted tomato. Pak. J. Biol. Sci. 9, 2323–2327. https://doi.org/10.3923/pjbs.2006.2323.2327 (2006).Article 

Google Scholar 
Pickering, J. S. & Shepherd, A. Evaluation of organic landscape mulches: composition and nutrient releases characteristics. Arboric J. 24, 175–187. https://doi.org/10.1080/03071375.2000.9747271 (2000).Article 

Google Scholar 
Marí, A. I., Pardo, G., Aibar, J. & Cirujeda, A. Purple nutsedge (Cyperus rotundus L.) control with biodegradable mulches and its effect on fresh pepper production. Sci. Hortic. 263, 109111. https://doi.org/10.1016/j.scienta.2019.109111 (2020).CAS 
Article 

Google Scholar 
R Development Core Team. R: A Language and Environment of Statistical Computing (R Foundation for Statistical Computing, 2019).
Google Scholar 
Kanda, Y. Investigation of the freely available easy-to-use software ‘EZR’ for medical statistics. Bone Marrow Transplant. 48, 452–458. https://doi.org/10.1038/bmt.2012.244 (2013).CAS 
Article 
PubMed 

Google Scholar  More

Westberry, T., Behrenfeld, M., Siegel, D. & Boss, E. Carbon-based primary productivity modeling with vertically resolved photoacclimation. Glob. Biogeochem. Cycles 22 (2008).Richardson, K. & Bendtsen, J. Vertical distribution of phytoplankton and primary production in relation to nutricline depth in the open ocean. Mar. Ecol. Prog. Ser. 620, 33–46 (2019).CAS 

Google Scholar 
Oschlies, A. in Ocean Modeling in an Eddying Regime (eds Hecht, M. W. & Hasumi, H.) 115–130 (AGU, 2008).Letscher, R. T., Primeau, F. & Moore, J. K. Nutrient budgets in the subtropical ocean gyres dominated by lateral transport. Nat. Geosci. 9, 815–819 (2016).CAS 

Google Scholar 
Johnson, K. S., Riser, S. C. & Karl, D. M. Nitrate supply from deep to near-surface waters of the North Pacific subtropical gyre. Nature 465, 1062–1065 (2010).CAS 

Google Scholar 
Fawcett, S. E., Lomas, M. W., Casey, J. R., Ward, B. B. & Sigman, D. M. Assimilation of upwelled nitrate by small eukaryotes in the Sargasso Sea. Nat. Geosci. 4, 717–722 (2011).CAS 

Google Scholar 
Knapp, A. N., Casciotti, K. L., Berelson, W. M., Prokopenko, M. G. & Capone, D. G. Low rates of nitrogen fixation in eastern tropical South Pacific surface waters. Proc. Natl Acad. Sci. USA 113, 4398–4403 (2016).CAS 

Google Scholar 
Böttjer, D. et al. Temporal variability of nitrogen fixation and particulate nitrogen export at station ALOHA. Limnol. Oceanogr. 62, 200–216 (2017).
Google Scholar 
Gruber, N., Keeling, C. D. & Stocker, T. F. Carbon-13 constraints on the seasonal inorganic carbon budget at the BATS site in the northwestern Sargasso Sea. Deep Sea Res. 1 45, 673–717 (1998).CAS 

Google Scholar 
Doney, S. C., Glover, D. M. & Najjar, R. G. A new coupled, one-dimensional biological–physical model for the upper ocean: applications to the JGOFS Bermuda Atlantic Time-series Study (BATS) site. Deep Sea Res. 2 43, 591–624 (1996).CAS 

Google Scholar 
Ascani, F. et al. Physical and biological controls of nitrate concentrations in the upper subtropical North Pacific Ocean. Deep Sea Res 2 93, 119–134 (2013).CAS 

Google Scholar 
Gran, H. H. in Rapport Vol. 56, 1–112 (Bureau du Conseil permanent international pour l’exploration de la mer, 1929).Hasle, G. R. Phototactic vertical migration in marine dinoflagellates. Oikos 2, 162–175 (1950).
Google Scholar 
Villareal, T. A. et al. Upward transport of oceanic nitrate by migrating diatom mats. Nature 397, 423–425 (1999).CAS 

Google Scholar 
Villareal, T. & Carpenter, E. Buoyancy regulation and the potential for vertical migration in the oceanic cyanobacterium Trichodesmium. Microb. Ecol. 45, 1–10 (2003).CAS 

Google Scholar 
Wirtz, K. & Smith, S. L. Vertical migration by bulk phytoplankton sustains biodiversity and nutrient input to the surface ocean. Sci. Rep. 10, 1142 (2020).CAS 

Google Scholar 
Silsbe, G. M., Behrenfeld, M. J., Halsey, K. H., Milligan, A. J. & Westberry, T. K. The CAFE model: a net production model for global ocean phytoplankton. Glob. Biogeochem. Cycles 30, 1756–1777 (2016).CAS 

Google Scholar 
Wang, W.-L., Moore, J. K., Martiny, A. C. & Primeau, F. W. Convergent estimates of marine nitrogen fixation. Nature 566, 205–211 (2019).CAS 

Google Scholar 
Karl, D. M., Letelier, R., Hebel, D. V., Bird, D. F. & Winn, C. D. in Marine Pelagic Cyanobacteria: Trichodesmium and Other Diazotrophs (eds Carpenter, E. J. et al.) 219–237 (Springer, 1992).Cullen, J. J. Subsurface chlorophyll maximum layers: enduring enigma or mystery solved? Ann. Rev. Mar. Sci. 7, 207–239 (2015).
Google Scholar 
Masuda, Y. et al. Photoacclimation by phytoplankton determines the distribution of global subsurface chlorophyll maxima in the ocean. Commun. Earth Environ. 2, 1–8 (2021).
Google Scholar 
Anugerahanti, P., Kerimoglu, O. & Smith, S. L. Enhancing ocean biogeochemical models with phytoplankton variable composition. Front. Mar. Sci. 8, 675428 (2021).
Google Scholar 
Pérez, V., Fernández, E., Marañón, E., Morán, X. A. G. & Zubkov, M. V. Vertical distribution of phytoplankton biomass, production and growth in the Atlantic subtropical gyres. Deep Sea Res. 1 53, 1616–1634 (2006).
Google Scholar 
Cornec, M. et al. Deep chlorophyll maxima in the global ocean: occurrences, drivers and characteristics. Glob. Biogeochem. Cycles 35, e2020GB006759 (2021).CAS 

Google Scholar 
Li, Q. P., Wang, Y., Dong, Y. & Gan, J. Modeling long-term change of planktonic ecosystems in the northern South China Sea and the upstream Kuroshio Current. J. Geophys. Res. 120, 3913–3936 (2015).
Google Scholar 
Latif, S., Ayub, Z. & Siddiqui, G. Seasonal variability of phytoplankton in a coastal lagoon and adjacent open sea in Pakistan. Turk. J. Botany 37, 398–410 (2013).CAS 

Google Scholar 
Liang, Y. et al. Nutrient-limitation induced diatom–dinoflagellate shift of spring phytoplankton community in an offshore shellfish farming area. Mar. Pollut. Bull. 141, 1–8 (2019).CAS 

Google Scholar 
Rahlff, J. et al. Short-term responses to ocean acidification: effects on relative abundance of eukaryotic plankton from the tropical Timor Sea. Mar. Ecol. Prog. Ser. 658, 59–74 (2021).CAS 

Google Scholar 
Kahru, M., Savchuk, O. & Elmgren, R. Satellite measurements of cyanobacterial bloom frequency in the Baltic Sea: interannual and spatial variability. Mar. Ecol. Prog. Ser. 343, 15–23 (2007).
Google Scholar 
Klais, R., Tamminen, T., Kremp, A., Spilling, K. & Olli, K. Decadal-scale changes of dinoflagellates and diatoms in the anomalous Baltic Sea spring bloom. PLoS ONE 6, e21567 (2011).CAS 

Google Scholar 
Klais, R., Norros, V., Lehtinen, S., Tamminen, T. & Olli, K. Community assembly and drivers of phytoplankton functional structure. Funct. Ecol. 31, 760–767 (2017).
Google Scholar 
Villareal, T. A., Pilskaln, C. H., Montoya, J. P. & Dennett, M. Upward nitrate transport by phytoplankton in oceanic waters: balancing nutrient budgets in oligotrophic seas. PeerJ 2, e302 (2014).
Google Scholar 
Mignot, A. et al. Understanding the seasonal dynamics of phytoplankton biomass and the deep chlorophyll maximum in oligotrophic environments: a bio-argo float investigation. Glob. Biogeochem. Cycles 28, 856–876 (2014).CAS 

Google Scholar 
Chen, B., Smith, S. L. & Wirtz, K. W. Effect of phytoplankton size diversity on primary productivity in the North Pacific: trait distributions under environmental variability. Ecol. Lett. 22, 56–66 (2019).
Google Scholar 
Cabré, A., Marinov, I. & Leung, S. Consistent global responses of marine ecosystems to future climate change across the IPCC AR5 Earth system models. Clim. Dyn. 45, 1253–1280 (2015).
Google Scholar 
Giorgetta, M. A. et al. Climate and carbon cycle changes from 1850 to 2100 in MPI-ESM simulations for the Coupled Model Intercomparison Project phase 5. J. Adv. Mod. Earth Sys. 5, 572–597 (2013).
Google Scholar 
Bopp, L. et al. Multiple stressors of ocean ecosystems in the 21st century: projections with CMIP5 models. Biogeosciences 10, 6225–6245 (2013).
Google Scholar 
Fu, W., Randerson, J. T. & Moore, J. K. Climate change impacts on net primary production (NPP) and export production (EP) regulated by increasing stratification and phytoplankton community structure in the CMIP5 models. Biogeosciences 13, 5151–5170 (2016).
Google Scholar 
Gliwicz, M. Z. Predation and the evolution of vertical migration in zooplankton. Nature 320, 746–748 (1986).
Google Scholar 
Huettel, M., Forster, S., Kloser, S. & Fossing, H. Vertical migration in the sediment-dwelling sulfur bacteria Thioploca spp. in overcoming diffusion limitations. Appl. Environ. Microbiol. 62, 1863–1872 (1996).CAS 

Google Scholar 
Waterbury, J. B., Willey, J. M., Franks, D. G., Valois, F. W. & Watson, S. W. A cyanobacterium capable of swimming motility. Science 230, 74–76 (1985).CAS 

Google Scholar 
McCarren, J. et al. Inactivation of swmA results in the loss of an outer cell layer in a swimming Synechococcus strain. J. Bacteriol. 187, 224–230 (2005).CAS 

Google Scholar 
Eppley, R. W., Holm-Hansen, O. & Strickland, J. D. Some observations on the vertical migration of dinoflagellates. J. Phycol. 4, 333–340 (1968).CAS 

Google Scholar 
Sengupta, A., Carrara, F. & Stocker, R. Phytoplankton can actively diversify their migration strategy in response to turbulent cues. Nature 543, 555–558 (2017).CAS 

Google Scholar 
Waite, A., Fisher, A., Thompson, P. & Harrison, P. Sinking rate verses cell volume relationships illuminate sinking rate control mechanisms in marine diatoms. Mar. Ecol. Prog. Ser. 157, 97–108 (1997).
Google Scholar 
Throndsen, J. Motility in some marine nanoplankton flagellates. Nor. J. Zool. 21, 193–200 (1973).
Google Scholar 
Gittleson, S. M., Hotchkiss, S. K. & Valencia, F. G. Locomotion in the marine dinoflagellate Amphidinium carterae (Hulburt). Trans. Am. Microsc. Soc. 93, 101–105 (1974).Barsanti, L. et al. Swimming patterns of the quadriflagellate Tetraflagellochloris mauritanica (Chlamydomonadales, Chlorophyceae). J. Phycol. 52, 209–218 (2016).
Google Scholar 
Schuech, R. & Menden-Deuer, S. Going ballistic in the plankton: anisotropic swimming behavior of marine protists. Limnol. Oceanogr. Fluids Environ. 4, 1–16 (2014).
Google Scholar 
Eppley, R. W., Holmes, R. W. & Strickland, J. D. Sinking rates of marine phytoplankton measured with a fluorometer. J. Exp. Mar. Biol. Ecol. 1, 191–208 (1967).
Google Scholar 
Bienfang, P. Phytoplankton sinking rates in oligotrophic waters off Hawaii, USA. Mar. Biol. 61, 69–77 (1980).
Google Scholar 
Lisicki, M., Rodrigues, M. F. V., Goldstein, R. E. & Lauga, E. Swimming eukaryotic microorganisms exhibit a universal speed distribution. Elife 8, e44907 (2019).CAS 

Google Scholar 
Moore, J. & Villareal, T. Buoyancy and growth characteristics of three positively buoyant marine diatoms. Mar. Ecol. Prog. Ser. 132 (1996).Hawaii Ocean Time-series (HOT) (School of Ocean and Earth Science and Technology at the University of Hawai’i, 2020); http://hahana.soest.hawaii.edu/hot/hot-dogsBermuda Atlantic Time-Series (BATS) (Bermuda Institure of Ocean Sciences, 2020); http://bats.bios.eduThe Japanese 55-Year Reanalysis (JRA-55) (Japan Meteorological Agency, 2020); http://jra.kishou.go.jp/JRA-55Ridgway, K., Dunn, J. & Wilkin, J. Ocean interpolation by four-dimensional weighted least squares—application to the waters around Australasia. J. Atmos. Ocean. Technol. 19, 1357–1375 (2002).
Google Scholar 
CSIRO Atlas of Regional Seas (CARS) (CSIRO, 2009); http://www.marine.csiro.au/~dunn/cars2009Ocean Colour (ESA-CCI, 2020); http://www.esa-oceancolour-cci.orgCloud (ESA-CCI, 2020); http://www.esa-cloud-cci.orgSea Surface Temperature (ESA-CCI, 2020); http://www.esa-sst-cci.orgRosati, A. & Miyakoda, K. A general circulation model for upper ocean simulation. J. Phys. Oceanogr. 18, 1601–1626 (1988).
Google Scholar 
Ralston, D. K., McGillicuddy, D. J. & Townsend, D. W. Asynchronous vertical migration and bimodal distribution of motile phytoplankton. J. Plankton Res. 29, 803–821 (2007).
Google Scholar 
Kamykowski, D. & Yamazaki, H. A study of metabolism-influenced orientation in the diel vertical migration of marine dinoflagellates. Limnol. Oceanogr. 42, 1189–1202 (1997).
Google Scholar 
Richardson, T. L., Cullen, J. J., Kelley, D. E. & Lewis, M. R. Potential contributions of vertically migrating Rhizosolenia to nutrient cycling and new production in the open ocean. J. Plankton Res. 20, 219–241 (1998).
Google Scholar 
Ross, O. N. & Sharples, J. Phytoplankton motility and the competition for nutrients in the thermocline. Mar. Ecol. Prog. Ser. 347, 21–38 (2007).CAS 

Google Scholar 
Chavez, F. P., Messié, M. & Pennington, J. T. Marine primary production in relation to climate variability and change. Ann. Rev. Mar. Sci. 3, 227–260 (2011).
Google Scholar 
Saba, V. et al. An evaluation of ocean color model estimates of marine primary productivity in coastal and pelagic regions across the globe. Biogeosciences 8, 489–503 (2011).CAS 

Google Scholar 
Bhattathiri, P., Devassy, V. & Radhakrishna, K. Primary production in the Bay of Bengal during southwest monsoon of 1978. Mahasagar Bull. Natl Inst. Oceanogr. 13, 315–323 (1980).
Google Scholar 
Sarupria, J. & Bhargava, R. Seasonal primary production in different sectors of the EEZ of India. Mahasagar Bull. Natl Inst. Oceanogr. 26, 139–147 (1993).
Google Scholar 
Jyothibabu, R. et al. Differential response of winter cooling on biological production in the northeastern Arabian Sea and northwestern Bay of Bengal. Curr. Sci. 87, 783–791 (2004).
Google Scholar 
Kumar, S. P. et al. Is the biological productivity in the Bay of Bengal light limited? Curr. Sci. 98, 1331–1339 (2010).CAS 

Google Scholar 
Kumar, S. P. et al. Seasonal cycle of physical forcing and biological response in the Bay of Bengal. Ind. J. Mar. Sci. 39, 388–405 (2010).CAS 

Google Scholar 
Buitenhuis, E. T., Hashioka, T. & Quéré, C. L. Combined constraints on global ocean primary production using observations and models. Glob. Biogeochem. Cycles 27, 847–858 (2013).CAS 

Google Scholar  More

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