Ecology

Taco-Taype, N. & Zúñiga-Dávila, D. Efecto de la inoculación de plantas de Tarwi con cepas de Bradyrhizobium spp. aisladas de un lupino silvestre, en condiciones de invernadero. Revista peruana de biología. 27, 35–42 (2022).Article 

Google Scholar 
Atchison, G. W. et al. Lost crops of the Incas: Origins of domestication of the Andean pulse crop tarwi Lupinus mutabilis. Am. J. Bot. 103, 1592–1606 (2016).CAS 
Article 

Google Scholar 
Peru Origins. Tarwi (Lupinus Mutabilis). https://peruorigins.com/tarwi/ (2022).Guilengue, N., Alves, S., Talhinhas, P. & Neves-Martins, J. Genetic and genomic diversity in a tarwi (Lupinus mutabilis Sweet) germplasm collection and adaptability to Mediterranean climate conditions. Agronomy 10, 21 (2020).Article 

Google Scholar 
Repo-Carrasco-Valencia, R., Basilio-Atencio, J., Luna-Mercado, G. I., Pilco-Quesada, S. & VidaurreRuiz, J. Andean ancient grains: Nutritional value and novel uses. Biol. Life Sci. Forum. https://doi.org/10.3390/blsf2021008015 (2022).Article 

Google Scholar 
Gulisano, A., Alves, S., Martins, J. N. & Trindade, L. M. Genetics and breeding of Lupinus mutabilis: An emerging protein crop. Front. Plant Sci. https://doi.org/10.3389/fpls.2019.01385 (2019).Article 

Google Scholar 
Chen, Y., She, Y., Zhang, R., Wang, J. & Zhang, X. Use of starch-based fat replacers in foods as a strategy to reduce dietary intake of fat and risk of metabolic diseases. Food Sci. Nutr. 8, 16–22 (2020).CAS 
Article 

Google Scholar 
Frick, K. M., Kamphuis, L. G., Siddique, K. H. M., Singh, K. B. & Foley, R. C. Quinolizidine alkaloid biosynthesis in lupins and prospects for grain quality improvement. Front. Plant Sci. https://doi.org/10.3389/fpls.2017.00087 (2017).Article 

Google Scholar 
Chirinos-Arias, M. C. Andean Lupin (Lupinus mutabilis Sweet) a plant with nutraceutical and medicinal potential. Revista Bio. Ciencias. 3, 163–172 (2015).
Google Scholar 
Wink, M. Chemical defense of leguminosae. Are quinolizidine alkaloids part of the antimicrobial defense system of lupins?. Zeitschrift für Naturforschung C. 39, 548–552 (1984).Article 

Google Scholar 
Hidalgo, M. et al. Evaluation of in vitro suceptibility to spartein in four strain of Mycobacterium tuberculosis. Rev. Peru Med Exp Salud Publica. 39, 77–82 (2022).Article 

Google Scholar 
Muñoz, E. B., Luna-Vital, D. A., Fornasini, M., Baldeón, M. E. & Gonzalez de Mejia, E. Gamma-conglutin peptides from Andean lupin legume (Lupinus mutabilis Sweet) enhanced glucose uptake and reduced gluconeogenesis in vitro. J. Funct. 45, 339–347 (2018).Article 

Google Scholar 
Bryant, L., Rangan, A. & Grafenauer, S. Lupins and health outcomes: A systematic literature review. Nutrients 14, 327 (2022).CAS 
Article 

Google Scholar 
Jacobsen, S. & Mujica, A. Geographical distribution of the Andean lupin (Lupinus mutabilis Sweet). Plant Genet. Resour. Newslett. 155, 1–8 (2008).
Google Scholar 
Antunez de Mayolo, S. Nutricion en el antiguo Peru. Banco Central de la Republica. Lima, Peru. 127 (1981).FAO. Perfiles nutricionales por paises: Peru. (ed. FAO) 36 p. (2000).UNICEF. Estado Mundial de la Infancia 2019 incluye a Perú entre las experiencias exitosas de lucha contra la desnutrición crónica infantile. https://www.unicef.org/peru/nota-de-prensa/estado-mundial-infancia-nutricion-alimentos-derechos-peru-experiencias-exitosas-desnutricion-cronica-infantil-reporte (2022).MINSA (Ministry of health – Peru). Situacion actual de la anemia. https://anemia.ins.gob.pe/situacion-actual-de-la-anemia-c1 (2022).WHO. Anemia. https://www.who.int/es/health-topics/anaemia#tab=tab_1 (2022).Galani, Y. J. H., Orfila, C. & Gong, Y. Y. A review of micronutrient deficiencies and analysis of maize contribution to nutrient requirements of women and children in Eastern and Southern Africa. Crit. Rev. Food Sci. Nutr. 62, 1568–1591 (2022).CAS 
Article 

Google Scholar 
White, P. J. & Martin, R. B. Biofortifying crops with essential mineral elements. Trends Plant Sci. 10, 586–593 (2005).Article 

Google Scholar 
White, P. J. & Martin, R. B. Biofortification of crops with seven mineral elements often lacking in human diets-iron, zinc, copper, calcium, magnesium, selenium and iodine. New Phytol. 182, 49–84 (2009).CAS 
Article 

Google Scholar 
Waters, B. M. & Sankaran, R. P. Moving micronutrients from the soil to the seeds: genes and physiological processes from a biofortification perspective. Plant Sciences. 180, 562–574 (2011).CAS 
Article 

Google Scholar 
Brooker, R. W. et al. Improving intercropping: A synthesis of research in agronomy, plant physiology and ecology. New Phytol. 206, 107–117 (2015).Article 

Google Scholar 
Ducsay, L. et al. Possibility of selenium biofortification of winter wheat grain. Plant Soil Environ. 62, 379–383 (2016).CAS 
Article 

Google Scholar 
Kumar, S. & Pandey, G. Biofortification of pulses and legumes to enhance nutrition. Heliyon. https://doi.org/10.1016/j.heliyon.2020.e03682 (2020).Article 

Google Scholar 
Diehn, T. A. et al. Boron demanding tissues of Brassica napus express specific sets of functional Nodulin26-like Intrinsic Proteins and BOR 1 transporters. Plant J. 100, 68–82 (2019).CAS 
Article 

Google Scholar 
Jayalakshmi, V. A., Reddy, T. & Nagamadhuri, K. V. Genetic diversity and variability for protein and micro nutrients in advance breeding lines and chickpea varieties grown in Andhra Pradesh.”. Legume Res. Int. J. 42, 768–772 (2019).
Google Scholar 
Bouis, H. & Saltzman, A. Improving nutrition through biofortification: A review of evidence from HarvestPlus, 2003 through 2016. Glob Food Sec. 12, 49–58 (2017).Article 

Google Scholar 
Sanca, D. Composición nutricional de diez genotipos de lupino (L. mutabilis y L. albus) desamargados por proceso acuoso. Thesis. Universidad Nacional Agraria La Molina. (2015).Rodríguez, A. Evaluación “in vitro” de la actividad antibacteriana de los alcaloides del agua de desamargado del chocho (Lupinus mutrabilis Sweet). Thesis. Escuela Superior Politécnica de Chimborazo, Ecuador (2009).Villacres, E. et al. Germination, an effective process to in-crease the nutritional value and reduce non-nutritive factors of lupine grain (Lupinus mutabilis Sweet). Int. J. Food Sci. Nutr. Eng. 5, 163–168 (2015).
Google Scholar 
Villacres, E., Rubio, A., Egas, L., Segovia, G. Usos alternativos del chocho: Chocho (Lupinus mutabilis Sweet) alimento andino redescubierto. IOP publishing: repositorio. https://repositorio.iniap.gob.ec/handle/41000/298 (2006).Ortega-David, E. A., Rodríguez, A. D. & Burbano, A. Z. Caracterización de semillas de lupino (Lupinus mutabilis) sembrado en los Andes de Colombia. Acta Agronómica. 59, 111–118 (2010).
Google Scholar 
White, P. J. & Broadley, M. R. Physiological limits to zinc biofortification of edible crops. Front Plant Sci. 80, 1–11 (2011).
Google Scholar 
Zhao, F., Su, Y. H., Dunham, S. J. & Rakszegiet, M. Variation in mineral micronutrient concentrations in grain of wheat lines of diverse origin. J. Cereal Sci. 49, 290–295 (2009).CAS 
Article 

Google Scholar 
Uauy, C., Distelfeld, A., Fahima, T., Blechl, A. & Dubcovsky, J. A NAC Gene regulating senescence improves grain protein, zinc, and iron content in wheat. Science 24, 1298–1301 (2006).ADS 
Article 

Google Scholar 
Shorrocks, V. M. The occurrence and correction of boron deficiency. Plant Soil 193, 121–148 (1997).CAS 
Article 

Google Scholar 
D’Imperio, M. et al. Boron biofortification of Portulaca oleracea L. through soilless cultivation for a new tailored crop. Agronomy. 10, 999–1013 (2020).Article 

Google Scholar 
Boyacioglu, O., Orenay-Boyacioglu, S., Yildirim, H. & Korkmaz, M. Boron intake, osteocalcin polymorphism and serum level in postmenopausal osteoporosis. J. Trace Elem. Med. Biol. 48, 52–56 (2018).CAS 
Article 

Google Scholar 
Oliveira Araújo, E., Ferreira Dos Santos, E. & Camacho Oliveira, M. A. Boron-zinc interaction in the absorption of micronutrients by cotton. Agronomía Colombiana. 36, 51–57 (2018).Article 

Google Scholar 
Squitti, R., Siotto, M. & Polimanti, R. Low-copper diet as a preventive strategy for Alzheimer’s disease. Neurobiol. Aging 2, 40–50 (2014).Article 

Google Scholar 
Schilsky, M.L. Management of Wilson Disease (A Pocket Guide), 1st ed.; Publisher: Humana Press, Farmington, CT, USA. 154–196 (2018).Martins, A. C. et al. Manganese in the diet: Bioaccessibility, adequate intake, and neurotoxicological effects. J. Agric. Food Chem. 46, 12893–12903 (2020).Article 

Google Scholar 
Falah, S. A. & Saja, N. M. Essential trace elements and their vital roles in human body. Indian J. Adv. Chem. Sci. 3, 127–136 (2017).
Google Scholar 
National institutes of health. Manganese. Fact Sheet for Health Professionals. IOP Publishing ods.od.nih.gov. https://ods.od.nih.gov/factsheets/Manganese-HealthProfessional/. (2021).Savadi, S. Molecular regulation of seed development and strategies for engineering seed size in crop plants. Plant Growth Regul. 84, 401–422 (2018).CAS 
Article 

Google Scholar 
Ge, L. et al. (2016) Increasing seed size and quality by manipulating BIG SEEDS1 in legume species. Proc Natl Acad Sci. 113, 12414–12419 (2016).CAS 
Article 

Google Scholar 
Zou, L. Effects of gradual and sudden heat stress on seed quality of Andean lupin, Lupinus mutabilis. Thesis. University of Helsinki. https://helda.helsinki.fi/handle/10138/16501 (2009).Buircell, B.J., Cowling, A.W. Genetic Resources in Lupins (eds. Gladstones, J.S., Atkins, C.A., Hamblin, J.) (United Kingdom: CAB International, 1998).Aguilar-Angulo, L. A. Evaluación del rendimiento de grano y capacidad simbiótica de once accesiones de tarwi (Lupinus mutabilis Sweet), bajo condiciones de Otuzco-La Libertad (Universidad Nacional Agraria La Molina, 2015).
Google Scholar 
De La Cruz, N. Caracterización fenotípica y de rendimiento preliminar de ecotipos de tarwi (Lupinus mutabilis sweet), bajo condiciones del Callejón de Huaylas – Ancash (Universidad Nacional Agraria la Molina, 2018).
Google Scholar 
Huisa, J. Evaluación del comportamiento agronómico de catorce accesiones del ensayo nacional de tarwi (Lupinus mutabilis sweet.) en el CIP Camacani Puno – Perú”. Thesis. Universidad Nacional Agraria la Moina (2018).Cayo, B. Evaluación del comportamiento agronómico de ocho genotipos selectos de tarwi (Lupinus mutabilis sweet) bajo condiciones del CIP. CAMACANI – UNA – PUNO. Thesis. Universidad Nacional del Altiplano (2020).Buircell, B.J., Cowling, A.W. Lupin. Lupinus spp. Promoting the conservation and use of underutilized and ne-glected crops (eds. Gladstones, J.S., Atkins, C.A., Hamblin, J.) (United Kingdom: CAB International, 1998).Plata, J. Comportamiento Agronómico de dos Variedades de tarwi (Lupinus mutabilis Sweet), bajo tres densidades de siembra en la comunidad Marka Hilata Carabuco (Universidad San Andres, 2016).
Google Scholar 
Mendoza, C. Rendimiento de ecotipos regionales y variedades de tarwi (Lupínus mutabilis Sweet.) en el valle del Mantaro, Jauja, Junín. Thesis. Universidad Nacional Agraria la Moina (2020).Aguilar, S. Sistemas de producción de Lupinus mutabilis Sweet ‘chocho’ en terrazas y laderas con fertilización fosfatada en Cajamarca. Dissertation. La Molina National Agrarian University (2011).Aquino, S. Sustentabilidad del cultivo de tarwi (Lupinus mutabilis sweet) en la zona altoandina del Valle del Mantaro (Universidad Nacional Agraria la Molina, 2018).
Google Scholar 
Barda, M. S., Chatzigeorgiou, T., Papadopoulos, G. K. & Bebeli, P. J. Agro-morphological evaluation of Lupinus mutabilis in two locations in greece and association with insect pollinators. Agriculture https://doi.org/10.3390/agriculture11030236 (2021).Article 

Google Scholar 
Herniter, I. A., Jia, Z. & Kusi, F. Market preferences for cowpea (Vigna unguiculata [L.] Walp) dry grain in Ghana. African J Ag Res. 14, 928–934 (2019).Article 

Google Scholar 
Dordas, C. Foliar boron application affects lint and seed yield and improves seed quality of cotton grown on calcareous soils. Nutr. Cycl. Agroecosyst. 76, 19–28 (2006).CAS 
Article 

Google Scholar 
Kristek, S. et al. Effect of various rates of boron on yield and quality of high-grade sugar beet varieties. Listy Cukrovarnické a Řepařské. 4, 146–150 (2018).
Google Scholar 
Thomas, C. L. et al. Root morphology and seed and leaf ionomic traits in a Brassica napus L. diversity panel show wide phenotypic variation and are characteristic of crop habit. BMC Plant Biol. 16, 214–232 (2016).CAS 
Article 

Google Scholar 
Dursun, A. et al. Effects of boron fertilizer on tomato, pepper and cucumber yields and chemical composition. Commun Soil Sci Plant Anal. 1, 1576–1593 (2010).Article 

Google Scholar 
Sotiropoulos, T. E., Therios, T. N., Dimassi, K. N., Bosabalidis, A. & Kofidis, G. Nutritional status, growth, CO2 assimilation, and leaf anatomical responses in two kiwifruit species under boron toxicity. J Plant Nutr. 25, 1249–1261 (2002).CAS 
Article 

Google Scholar 
Muccifora, S. & Bellani, L. Effects of copper on germination and reserve mobilization in Vicia sativa L. seeds. Environ. Pollut. 179, 68–74 (2013).CAS 
Article 

Google Scholar 
Kobraee, S. Effect of foliar fertilization with zinc and manganese sulfate on yield, dry matter accumulation, and zinc and manganese contents in leaf and seed of chickpea (Cicer arietinum). J. Appl. Biol. Biotechnol. 7, 20–28 (2019).CAS 

Google Scholar 
IBPGR (1981) Lupin descriptors. https://www.bioversityinternational.org/fileadmin/bioversity/publications/Web_version/103/ (1981).Zasoski, R. J. & Burau, R. G. A rapid nitric-perchloric acid digestion method for multi-element tissue analysis. Commun. Soil Sci. Plant Anal. 8, 425–436 (1997).Article 

Google Scholar 
Pereira, T., Coelho, C. M. M., Bogo, A., Guidolin, A. F. & Miquelluti, D. J. Diversity in common bean landraces from south Brazil. Acta Bot. Croat. 1, 79–92 (2009).
Google Scholar 
Pujar, M., Govindaraj, M., Gangaprasad, S., Kanatti, A. & Shivade, H. Genetic variation and diversity for grain iron, zinc, protein and agronomic traits in advanced breeding lines of pearl millet [Pennisetum glaucum (L.) R Br] for biofortification breeding. Genet. Resour. Crop Evol. 67, 2009–2022 (2020).CAS 
Article 

Google Scholar 
Lira, J. P. E. et al. Safflower genetic diversity based on agronomic characteristics in Mato Grosso state, Brazil, for a crop improvement program. Genet. Mol. Res. 1, 1–12 (2021).
Google Scholar 
de Sá, S. F. et al. Genetic diversity via REML-BLUP of ex situ conserved macauba [Acrocomia aculeata (Jacq.) Lodd. ex Mart.] ecotypes. Genet. Resour. Crop Evol. 68, 3193–3204 (2021).Article 

Google Scholar 
Kuru, R., Yilmaz, S., Tasli, P. N., Yarat, A. & Sahin, F. Boron content of some foods consumed in Istanbul, Turkey. Biol. Trace Elem. Res. 187, 1–8 (2019).CAS 
Article 

Google Scholar 
Shokunbi, O., Adepoju, O., Mojapelo, P., Ramaite, I. & Akinyele, I. Copper, manganese, iron and zinc contents of Nigerian foods and estimates of adult dietary intakes. J. Food Compos. Anal. 82, 103–245 (2019).Article 

Google Scholar 
Norwegian scientific committee for food and environment. Assessment of dietary intake of manganese in rela-tion to tolerable upper intake. IOP Publishing wkm. www.vkm.no. (2018).Gil, V., Guzmán, L. & Quintero, E. Caracterización de la variabilidad morfológica de un “genotipo local” de maíz y dos de sus selecciones. Centro Agrícola. 4, 79–83 (2004).
Google Scholar  More

Chaigneau, A., Gizolme, A. & Grados, C. Mesoscale eddies off Peru in altimeter records: identification algorithms and eddy spatio-temporal patterns. Prog. Oceanogr. 79, 106–119 (2008).ADS 
Article 

Google Scholar 
McGillicuddy, D. J. Jr et al. Influence of mesoscale eddies on new production in the Sargasso Sea. Nature 394, 263–266 (1998).ADS 
CAS 
Article 

Google Scholar 
Dufois, F. et al. Anticyclonic eddies are more productive than cyclonic eddies in subtropical gyres because of winter mixing. Sci. Adv. 2, 1–7 (2016).Article 

Google Scholar 
Godø, O. R. et al. Mesoscale eddies are oases for higher trophic marine life. PLoS ONE 7, e30161 (2012).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Chelton, D. B., Gaube, P., Schlax, M. G., Early, J. J. & Samelson, R. M. The influence of nonlinear mesoscale eddies on near-surface oceanic chlorophyll. Science 334, 328–333 (2011).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Sarmiento, J. L. et al. Response of ocean ecosystems to climate warming. Global Biogeochem. Cycles 18, GB3003 (2004).ADS 
Article 
CAS 

Google Scholar 
Bell, J. D. et al. Diversifying the use of tuna to improve food security and public health in Pacific Island countries and territories. Mar. Policy 51, 584–591 (2015).Article 

Google Scholar 
Della Penna, A. & Gaube, P. Mesoscale eddies structure mesopelagic communities. Front. Mar. Sci. 7, 454 (2020).ADS 
Article 

Google Scholar 
Braun, C. D. et al. The functional and ecological significance of deep diving by large marine predators. Ann. Rev. Mar. Sci. 14, 129–159 (2022).PubMed 
Article 

Google Scholar 
McGillicuddy, D. J. Jr Mechanisms of physical-biological-biogeochemical interaction at the oceanic mesoscale. Ann. Rev. Mar. Sci. 8, 125–159 (2016).PubMed 
Article 

Google Scholar 
Fennell, S. & Rose, G. Oceanographic influences on deep scattering layers across the North Atlantic. Deep-Sea Res. Part I Oceanogr. Res. Pap. 105, 132–141 (2015).ADS 
Article 

Google Scholar 
Duffy, L. M. et al. Global trophic ecology of yellowfin, bigeye, and albacore tunas: understanding predation on micronekton communities at ocean-basin scales. Deep-Sea Res. Part II Topical Stud. Oceanogr. 140, 55–73 (2017).ADS 
Article 

Google Scholar 
Gaube, P. et al. Mesoscale eddies influence the movements of mature female white sharks in the Gulf Stream and Sargasso Sea. Sci. Rep. 8, 7363 (2018).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Braun, C. D., Gaube, P., Sinclair-Taylor, T. H., Skomal, G. B. & Thorrold, S. R. Mesoscale eddies release pelagic sharks from thermal constraints to foraging in the ocean twilight zone. Proc. Natl Acad. Sci. USA 116, 17187–17192 (2019).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Doyle, T. K. et al. Leatherback turtles satellite-tagged in European waters. Endanger. Species Res. 4, 23–31 (2008).Article 

Google Scholar 
Pauly, D. & Christensen, V. Primary production required to sustain global fisheries. Nature 374, 255–257 (1995).ADS 
CAS 
Article 

Google Scholar 
Lynham, J., Nikolaev, A., Raynor, J., Vilela, T. & Villaseñor-Derbez, J. C. Impact of two of the world’s largest protected areas on longline fishery catch rates. Nat. Commun. 11, 979 (2020).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Polovina, J. J., Abecassis, M., Howell, E. A. & Woodworth, P. Increases in the relative abundance of mid-trophic level fishes concurrent with declines in apex predators in the subtropical North Pacific, 1996-2006. Fish. Bull. 107, 523–531 (2009).
Google Scholar 
Royer, T. C. Ocean eddies generated by seamounts in the North Pacific. Science 199, 1063–1064 (1978).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Liu, Y. et al. Eddy analysis in the subtropical zonal band of the North Pacific Ocean. Deep-Sea Res. Part I Oceanogr. Res. Pap. 68, 54–67 (2012).ADS 
Article 

Google Scholar 
Bernstein, R. L. & White, W. B. Time and length scales of baroclinic eddies in the central North Pacific Ocean. J. Phys. Oceanogr. 4, 613–624 (1974).ADS 
Article 

Google Scholar 
Maunder, M. N. & Punt, A. E. Standardizing catch and effort data: a review of recent approaches. Fish. Res. 70, 141–159 (2004).Article 

Google Scholar 
Woodworth, P. A. et al. Eddies as offshore foraging grounds for melon-headed whales (Peponocephala electra). Mar. Mammal Sci. 28, 638–647 (2012).Article 

Google Scholar 
Gaube, P. et al. The use of mesoscale eddies by juvenile loggerhead sea turtles (Caretta caretta) in the southwestern Atlantic. PLoS ONE 12, e0172839 (2017).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Chambault, P. et al. Swirling in the ocean: immature loggerhead turtles seasonally target old anticyclonic eddies at the fringe of the North Atlantic Gyre. Prog. Oceanogr. 175, 345–358 (2019).ADS 
Article 

Google Scholar 
Gaube, P., McGillicuddy Jr, D., Chelton, D., Behrenfeld, M. & Strutton, P. Regional variations in the influence of mesoscale eddies on near-surface chlorophyll. J. Geophys. Res. Oceans 119, 8195–8220 (2014).Waga, H., Kirawake, T. & Ueno, H. Impacts of mesoscale eddies on phytoplankton size structure. Geophys. Res. Lett. 46, 13191–13198 (2019).ADS 
Article 

Google Scholar 
Irigoien, X. et al. Large mesopelagic fishes biomass and trophic efficiency in the open ocean. Nat. Commun. 5, 3271 (2014).ADS 
PubMed 
Article 
CAS 

Google Scholar 
Chen, Y.-lL. et al. Biologically active warm-core anticyclonic eddies in the marginal seas of the western Pacific Ocean. Deep Sea Res. Part I 106, 68–84 (2015).CAS 
Article 

Google Scholar 
Harke, M. J. et al. Microbial community transcriptional patterns vary in response to mesoscale forcing in the North Pacific Subtropical Gyre. Environ. Microbiol. 23, 4807–4822 (2021).CAS 
PubMed 
Article 

Google Scholar 
Hawco, N. J. et al. Iron depletion in the deep chlorophyll maximum: mesoscale eddies as natural iron fertilization experiments. Global Biogeochem. Cycles 35, e2021GB007112 (2021).ADS 
CAS 
Article 

Google Scholar 
Klevjer, T. A. et al. Large scale patterns in vertical distribution and behaviour of mesopelagic scattering layers. Sci. Rep. 6, 19873 (2016).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Behrenfeld, M. J. et al. Global satellite-observed daily vertical migrations of ocean animals. Nature 576, 257–261 (2019).CAS 
PubMed 
Article 

Google Scholar 
Madigan, D. J. et al. Water column structure defines vertical habitat of twelve pelagic predators in the South Atlantic. ICES J. Mar. Sci. 78, 867–883 (2021).Article 

Google Scholar 
Arostegui, M., Gaube, P. & Braun, C. Movement ecology and stenothermy of satellite-tagged shortbill spearfish (Tetrapturus angustirostris). Fish. Res. 215, 21–26 (2019).Article 

Google Scholar 
Lehodey, P., Senina, I. & Murtugudde, R. A spatial ecosystem and populations dynamics model (SEAPODYM)—modeling of tuna and tuna-like populations. Prog. Oceanogr. 78, 304–318 (2008).ADS 
Article 

Google Scholar 
Varghese, S. P., Somvanshi, V. S. & Dalvi, R. S. Diet composition, feeding niche partitioning and trophic organisation of large pelagic predatory fishes in the eastern Arabian Sea. Hydrobiologia 736, 99–114 (2014).CAS 
Article 

Google Scholar 
Ward, P. & Myers, R. A. Inferring the depth distribution of catchability for pelagic fishes and correcting for variations in the depth of longline fishing gear. Can. J. Fish. Aquat.Sci. 62, 1130–1142 (2005).Article 

Google Scholar 
Kai, E. T. et al. Top marine predators track Lagrangian coherent structures. Proc. Natl Acad. Sci. USA 106, 8245–8250 (2009).ADS 
CAS 
Article 

Google Scholar 
Lima, I. D., Olson, D. B. & Doney, S. C. Biological response to frontal dynamics and mesoscale variability in oligotrophic environments: biological production and community structure. J. Geophys. Res. Oceans 107, 25-1–25-21 (2002).Article 

Google Scholar 
Spall, S. A. & Richards, K. J. A numerical model of mesoscale frontal instabilities and plankton dynamics—I. model formulation and initial experiments. Deep-Sea Res. Part I Oceanogr. Res. Pap. 47, 1261–1301 (2000).ADS 
Article 

Google Scholar 
Siegelman, L., O’Toole, M., Flexas, M., Rivière, P. & Klein, P. Submesoscale ocean fronts act as biological hotspot for southern elephant seal. Sci. Rep. 9, 5588 (2019).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Lévy, M., Ferrari, R., Franks, P. J., Martin, A. P. & Rivière, P. Bringing physics to life at the submesoscale. Geophys. Res. Lett. https://doi.org/10.1029/2012GL052756 (2012).Article 

Google Scholar 
Guidi, L. et al. Does eddy-eddy interaction control surface phytoplankton distribution and carbon export in the North Pacific Subtropical Gyre? J. Geophys. Res. Biogeosciences https://doi.org/10.1029/2012JG001984 (2012).Article 

Google Scholar 
Chow, C. H., Cheah, W., Tai, J. H. & Liu, S. F. Anomalous wind triggered the largest phytoplankton bloom in the oligotrophic North Pacific Subtropical Gyre. Sci. Rep. 9, 15550 (2019).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Guo, M., Xiu, P., Chai, F. & Xue, H. Mesoscale and submesoscale contributions to high sea surface chlorophyll in subtropical gyres. Geophys. Res. Lett. 46, 13217–13226 (2019).ADS 
Article 

Google Scholar 
Klein, P. et al. Ocean-scale interactions from space. Earth Space Sci. 6, 795–817 (2019).ADS 
Article 

Google Scholar 
Martin, A. et al. The oceans’ twilight zone must be studied now, before it is too late. Nature 580, 26–28 (2020).ADS 
CAS 
PubMed 
Article 

Google Scholar 
St. John, M. A. et al. A dark hole in our understanding of marine ecosystems and their services: perspectives from the mesopelagic community. Front. Marine Sci. 3, 31 (2016).
Google Scholar 
Bigelow, K., Musyl, M. K., Poisson, F. & Kleiber, P. Pelagic longline gear depth and shoaling. Fish. Res. 77, 173–183 (2006).Article 

Google Scholar 
Brodziak, J. & Walsh, W. A. Model selection and multimodel inference for standardizing catch rates of bycatch species: a case study of oceanic whitetip shark in the Hawaii-based longline fishery. Can. J. Fish. Aquat.Sci. 70, 1723–1740 (2013).Article 

Google Scholar 
Woodworth-Jefcoats, P. A., Polovina, J. & Drazen, J. Synergy among oceanographic variability, fishery expansion, and longline catch composition in the central North Pacific Ocean. Fish. Bull. 116, 228–239 (2018).Article 

Google Scholar 
Boggs, C. H. Depth, capture time, and hooked longevity of longline-caught pelagic fish: timing bites of fish with chips. Fish. Bull. 90, 642–658 (1992).
Google Scholar 
Walsh, W. A. & Brodziak, J. Applications of Hawaii longline fishery observer and logbook data for stock assessment and fishery research. NOAA Tech. Memo. 57, 62 (2016).
Google Scholar 
Walsh, W. A. & Brodziak, J. Billfish CPUE standardization in the Hawaii longline fishery: model selection and multimodel inference. Fish. Res. 166, 151–162 (2015).Article 

Google Scholar 
Gilman, E., Chaloupka, M., Fitchett, M., Cantrell, D. L. & Merrifield, M. Ecological responses to blue water MPAs. PLoS ONE 15, e0235129 (2020).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Portner, E. J., Polovina, J. J. & Choy, C. A. Patterns in micronekton diversity across the North Pacific Subtropical Gyre observed from the diet of longnose lancetfish (Alepisaurus ferox). Deep-Sea Research Part I 125, 40–51 (2017).ADS 
Article 

Google Scholar 
Brooks, M. E. et al. glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. R J. 9, 378–400 (2017).Article 

Google Scholar 
Hartig, F. DHARMa: Residual diagnostics for hierarchical (multi-level/mixed) regression models. R package version 0.3.3.0 http://florianhartig.github.io/DHARMa/ (2020).Jackson, C. H. Multi-state models for panel data: the msm package for R. J. Stat. Softw. https://doi.org/10.18637/jss.v038.i08 (2011).Article 

Google Scholar 
Bates, D. et al. lme4: Linear mixed-effects models using ’Eigen’ and S4. R package version 1.1-25 https://github.com/lme4/lme4/ (2020).Lenth, R. et al. emmeans: Estimated marginal means, aka least-squares mean. R package version 1.7.2 https://github.com/rvlenth/emmeans (2022).R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2020); http://www.r-project.org/ More

In line with the results of present study, we suggest that the exploitation of forage resources by agro-pastoralists occurs in a non-random manner. The use of forage resources is guided by a series of functional characters related to palatability and nutritional value, which determine preferential use due to the better quality of resource. At the same time, we understand that forage uses are complex and multifactorial in nature, and regulated in a substantial way by seasonality and ecological factors (Fig. 5), such as the availability of plant resources and local diversity.Figure 5Diagrammatic representation for the effects of vegetation cover and seasonality on forage resource selection in Dry Forests. Image created with Microsoft Office 2019 PowerPoint (www.office.com).Full size imageThe differences of plant species cited between areas reveal the positive effect of vegetation cover on the use and knowledge of plants by agro-pastoralists. Our findings reveal that the greater number of plant species mentioned by agro-pastoralists in Area II is directly associated with greater availability of resources in this area, as long as we consider vegetation cover as availability of resources, which allows different species to be used throughout the year. On the other hand, in regions with low vegetation cover (Area I), the low availability of resources limits the use and knowledge of plants by residents, which can lead to greater pressure on a small set of available species. Such findings reinforce the importance of vegetation cover for ecosystem provision of goods and services to human populations that depend directly or indirectly on these services.The most represented families found in the present study have also been reported in several other ethnobotanical studies6,16,17,29, with emphasis on Fabaceae and Poaceae, which are recognized for their high forage potential, which derives, above all, from high palatability and nutritional value30. Simultaneously, citations mostly for native species reflect the importance and potential of Caatinga resources as important components of the ruminant diet11, both for the woody and herbaceous strata, corroborating the estimate in the literature that 70% of vegetation has potential use as forage31.The characteristic seasonality of vegetation, on the other hand, represents a limiting factor for forage productivity, culminating in high fluctuations in quality and availability, as well as changes in the dominance of different strata and composition of forage species throughout the seasons11,32. The seasonal distribution of species explains the similarity of seasons between areas, with a higher similarity percentage for the dry seasons, since there is less availability of resources to be exploited compared to the rainy season. In this context, the potentially used species are commonly accessible woody species in both areas. However, during the rainy season, the high availability of herbaceous plants regulates different uses (Fig. 4), but even so, they also exhibit relatively similar patterns, mainly due to the woody component that denotes the common demand by ruminants at the beginning of this season.The effect of climatic variables on vegetation use patterns was documented by16,17, both of which showed greater richness in the use of herbaceous forage during the rainy season, a finding that reflects the seasonal distribution—restriction to that season—and decrease in the qualitative character of annual species33. At the same time, it also reflects the greater number of unique species for the rainy season. However, when compared to woody strata, significant differences in terms of richness are not found because although the diversity of herbaceous species in the Caatinga is greater24, it is much less known than that of the tree-shrub stratum11.Agro-pastoralists even characterize animal preferences for herbaceous stratum, but as its diversity is immense and ephemeral, they claim to have limited ability to identify the species. The high abundance of resources in the rainy season also reduces the concern with forage use, which implies less attention to the species that are consumed. In contrast, woody species, due to multiple uses and greater availability over time, tend to be better known10,34, with a different effect in the dry season making the optimal foraging pattern in this period inherent to the knowledge of agro-pastoralists35.In addition, according to the ecological appearance hypothesis, there is a general tendency for less apparent species to be neglected by populations36. Some studies have corroborated the hypothesis within the context of forage use, with woody species being cited more and having more uses6,15. In addition, people tend to focus on resources whose supply is given continuously10, which may explain why woody species are well represented in both seasons.Security in the provisioning of ecosystem services is an essential component for local populations, and thus woody species are highly valued because they reflect predictability of use15,35. This can be a particularly influential criterion because perennial or late leaf deciduous species, such as Cynophalla flexuosa and Myracrodruon urundeva, had significant amounts of citations and perceptions employing high valuation, as represented by some statements by some interviewees: “É um refrigero na seca” (it is savage in the dry season), “É uma ração boa na seca” (it is a good food in the dry season).In turn, differences in richness of the species cited by the two areas corroborate our first hypothesis that populations inserted in environments with greater vegetation cover tend to cite more species. In line with these findings, considerable floristic dissimilarity was also found between the two areas, given the exclusivity of species. Such dissimilarity may suggest particularities in the vegetation attributes of each area, such as greater floristic diversity7,37,38.Since anthropic processes are irregularly distributed in space, variation in the provisioning of ecosystem services by vegetation also occurs, and influences different collection profiles39. On the other hand, areas with greater species richness have been shown to have greater use patterns6,7. The larger number of species cited as woody and native for Area II is, therefore, associated with greater general richness, as well as herbaceous species present in the rainy season. In contrast, common species are reflected in trends of similar foraging patterns, as well as the presence of common species between areas38. In addition to different levels of disturbance, differences in floristic composition between areas may also be due to edaphic variation40.Our second hypothesis was refuted because the difference in the richness of exotic species between the areas. Plausible explanations for this finding are that, in general, exotic herbaceous species are commonly used for forage in the semi-arid region of Brazil41. Herbaceous species comprise the primary component of the ruminant diet. However, in the midst of their occurrence restricted to the short rainy period, exotic species, mainly of Fabaceae and Poaceae, have been introduced to increase the forage availability, which currently represents an important attribute of forage resources in the Caatinga41,42,43. At the same time, and to also increase the availability of forage resources, the cultivation of species by agro-pastoralists may be common in their properties44, mainly exotics, such as Prosopis juliflora, that have high adaptive potential and governmental incentives45.Regarding use patterns, according to the data presented here it is possible to state that agro-pastoralists ’ experiences with herding activities provide an accumulation of a vast knowledge about forage resources15. This knowledge allows forage resources to be characterized by their potential according to a variety of criteria associated with seasonal variation and qualitative attributes, as commonly found by other studies14,15,16,17,37. Such criteria are often revealed by qualitative approaches that define the valuation perception of resources. Thus, nutritional value and palatability can be implicitly associated with the definitions of “É uma ração boa” (it is a good food), “o bicho gosta muito” (the animals like it very much) and “Rico em proteínas” (rich in protein).It should be added that the establishment of intrinsic relationships with resources allows a particular understanding at a high level of detail15,35, such as changes in palatability throughout development with descriptions including chemical17 and structural changes. Studies confirm that some Caatinga species vary in their chemical composition during leaf maturation, which influences nutritional quality17,46.In addition to revealing the domain of information, this body of knowledge allows maximizing forage use based on nutritional properties weighted by availability14,37. Nunes37 confirmed that the forage species selected by informants and the criteria they adopted coincided with nutritional values measured by the literature, and that, as also found in the present study, younger plants were recognized as highly appreciated by animals. This appreciation is due to the greater palatability of plant organs at this stage47. This is a matter of concern for the sustainability of the Caatinga, since direct or indirect grazing has compromised the regeneration process12 since younger individuals are clearly more sensitive to damage48.Also, considering the potential of Caatinga, we suggest that investment through government actions encourage the cultivation of native species to ensure the production of forage and, consequently, guarantee the sustainability of livestock activity and the ecosystem in question. More

Effects of Se and K-humate on nitrogen concentrationsThe N concentration in the soil varied in availability and total content in oat straw and seeds after the foliar application of Se and K-humate. Se alone increased the availability of N in the soil in the following order: Se3  > Se2  > Se1  > control. Thus, Se was found to increase the available N-soil in an application-rate-dependent manner (Table 2). The availability of N-soil after Se application was improved via the simultaneous application of K-humate with the same rate-dependence as observed with Se alone. Comparable results were found using the sum of means for analysis. The insignificant difference found between the sum of means for control and treatment at an Se concentration of 12 × 10−3 mM Se may reflect the relatively low concentration of Se used.Table 2 Effect of selenium and K-humate on nitrogen content.Full size tableThe total N-straw content increased as a result of an increased content of N-plant (Table 2). Differences were found to be insignificant between Se concentrations of 12 × 10−3 mM, 63 × 10−3 mM, and controls. Likewise, the simultaneous application of K-humate showed insignificant differences between Se concentrations of 63 × 10−3 mM and 88 × 10−3 mM. Insignificant differences were noted between the control and Se concentration of 12 × 10−3 mM and the Se concentration of 63 × 10−3 and 88 × 10−3 mM using the sum of means. The total N-seeds content increased for application rates of 12 × 10−3–88 × 10−3 mM, and the simultaneous application of K-humate augmented this increase. The application rate dependency of the effects of Se and K-humate application was identical to that observed in N-soil and N-straw. No significant differences among Se and K-humate applications were observed. An insignificant difference was observed among the sum of means for Se and K-humate applications at concentrations of 63 × 10−3 and 88 × 10−3 mM.The application of Se caused proportional increases in N-soil, N-straw, and N-seeds, and the simultaneous application of K-humate improved this effect. Previously, the application of Se resulted in an increase in the accumulation of NPK which altered N and K distribution. However, the distribution of P was not affected19. Furthermore, the application of Se ultimately resulted in an increase in the accumulation of N, calcium (Ca), K, and Mn20. A significant increase in concentrations of N and S in the rice grain plants grown under N-limiting conditions was also observed while the Ca that have been treated with Se regardless of N supply21. Thus, a synergistic interaction between Se and N in total grain proteins was reported21.Effects of Se and K-humate on PThe effect of applications of different Se concentrations without K-humate on the available P-soil showed a reduction in the following order: Se3  > Se2  > Se1  > control (Table 3). Thus, the foliar application rate of Se caused a rate-dependent increase in the available P-soil. Simultaneous application of K-humate further increased P-soil availability. A rate dependency similar to Se alone was also observed with simultaneous Se and K-humate application. A similar result was observed using the sum of means for data analysis. Significant differences were observed among all treatments.Table 3 Effect of selenium and K-humate on phosphorous content.Full size tableFoliar application of Se increased total P-straw. An insignificant difference was found between the control and Se concentrations of 12 × 10−3 and 63 × 10−3 mM, which was similar to findings observed after the application of K-humate. Moreover, insignificant differences were observed between the applications of Se and Se + K-humate. An insignificant effect was found between control and Se concentrations of (12 × 10−3 and 63 × 10−3 mM), and K-humate application using the sum of means.The application of Se having concentrations ranging from 12 × 10−3 to 88 × 10−3 mM resulted in increased P-seeds and the addition of K-humate augmented this effect (Table 3). The effect of Se and K-humate applications showed a decrease in the following order: Se3  > Se2  > Se1  > control. Insignificant differences between values were observed when Se was applied without K-humate at concentrations of 12 × 10−3 and 63 × 10−3 mM, and for the sum of means for Se and K-humate applications at concentrations of 12 × 10−3 and 63 × 10−3 mM. Thus, the application rate of Se caused a proportional increase in P-soil, P-straw, and P-seeds. Furthermore, the simultaneous application of K-humate augmented this effect.Consistently, concentrations of P and Ca increased in response to the application of selenite-Se (Na2SeO3⋅5H2O) to maize seedlings22, and the application of Se led to an increase in the accumulation of NPK, with alteration of N and K distribution. However, the distribution of P was not influenced19.Effects of the foliar application of Se and K-humate on KDifferent application rates of Se without humate increased K-soil and this effect showed a decrease in the following order: Se3  > Se2  > Se1 = control (Table 4). Again, the foliar application rate of Se causes a proportional increase, in this case, in K-soil. The application of K-humate with Se augmented this effect. A similar rate dependency was also observed with simultaneous application and when the sum of means was used. An insignificant difference was observed between the sum of means for controls and Se concentrations of 12 × 10−3 mM.Table 4 Effect of selenium and K-humate on potassium content.Full size tableThe foliar application of Se led to a slight increase in the total K-straw content (Table 4). An insignificant change was observed for Se concentrations from 12 × 10−3 to 88 × 10−3 mM, and similar results were found with the additional application of K-humate.The application of Se at concentrations from 12 × 10−3 to 88 × 10−3 mM resulted in a slight increase in K-seeds, and the additional application of K-humate only slightly increased the accumulation of K (Table 4). An insignificant difference was observed between Se alone and with K-humate. Similar findings were noted when the sum of means was used for analysis. Se application rates thus produce a proportional increase in K-soil but not in K-straw or K-seeds. Comparable data were noted after K-humate addition. Concentrations of K previously decreased in response to selenite-Se (Na2SeO3⋅5H2O) application to maize seedlings; however, magnesium (Mg) concentrations did not change22. Moreover, the application of Se led to the accumulation of NPK and altered N and K distribution without affecting the P distribution19. Consistently, the application of Se ultimately resulted in increasing K accumulation20.Effects of Se and K-humate application on oat growthApplication of Se improved the yield, which was assessed as kg × 10−3/feddan (Table 5). Higher concentrations of Se produced a higher yield of oat. The effect of Se showed a reduction in the following order: Se3  > Se2  > Se1  > control. The simultaneous application of K-humate increased the yield only slightly, resulting in insignificant differences. Similar findings were also observed when the sum of means was used. In contrast, seed production was not significantly affected, and plant length (m × 10–2) did not show a significant response. In contrast, Se application to potato plants enhanced tuber yield, plant growth, and quality compared with controls. Moreover, Se application along with different N additions ultimately increased potato productivity compared with Se or N alone23. Similarly, the grain yield increased when Se was applied; this application was significant at low levels24.Table 5 Effect of Se and K-humate application on oat growth.Full size tableEffects of Se and K-humate applications on OMS (%) and non-enzymatic antioxidants and total phenols in oat plantsThe total OMS content increased with increasing Se concentrations, perhaps due to stimulation of root growth or microbial biomass. This effect showed a decrease in the following order: Se3  > Se2  > Se1  > control. The addition of K-humate by foliar application significantly augmented the OMS content (%) (Table 6). Application of Se also increased the non-enzymatic antioxidant content; however, the increases were insignificant at Se concentrations of 12 × 10−3 and 63 × 10−3 mM. The highest values for non-enzymatic antioxidants were observed at Se concentrations of 88 × 10−3 mM. The application of K-humate along with Se did not significantly augment the effects observed after the application of Se alone. Analyses using the sum of means were completely consistent with these findings.Table 6 Effect of selenium and K-humate application on organic matter in soil (OMS), non-enzymatic antioxidant, and total phenols in oats.Full size tableSe positively enhanced the total phenol content with effects decreasing in the following order: Se3  > Se2  > Se1  > control. Furthermore, this effect was significantly amplified with the simultaneous application of K-humate. Analysis using the sum of means gave comparable results. Se enhances the ability of plants to cope with stress by stimulating plant cell antioxidant capacity though the upregulating of antioxidant enzymes, such as CAT, SOD, and GSH-Px. Se also increases the synthesis of PCs, GSH, proline, ascorbate, alkaloids, flavonoids, and carotenoids. Se may also induce the spontaneous dismutation of the superoxide radical into H2O2. Elevated antioxidant capacity can reduce lipid peroxidation by lowering ROS accumulation under metal-induced oxidative stress conditions25. Application of Se using foliar spray also induced an increase in the concentration of rosmarinic acid20.Effects of Se and K-humate applications on Se contentAfter the application of Se, Se-soil concentrations increased. The effects of Se concentrations decreased in the following order: Se3  > Se2  > Se1  > control. The additional application of K-humate significantly amplified these effects (Table 7). The treatment of K-humate that increased Se content in the soil may be owing to experimental errors, however, increasing Se content in either straw or seeds may be owing to the increased stimulating movement from soil to different parts of the plant. Se-straw content increased with increasing the Se foliar application; this effect decreased in the following order: Se3  > Se2  > Se1  > control. The simultaneous application of K-humate augmented the effects observed after the application of Se alone. Total Se concentration also increased Se-seeds like Se-straw for Se alone, Se with K-humate, and using the sum of means for analysis.Table 7 Effects of Se and K-humate applications on Se content.Full size tableEffects of Se and K-humate application on Cr contentThe highest concentrations of Cr were observed in control plants followed by Se2  > Se3  > Se1. In response to Se application, the Cr-straw content decreased (Table 8). The difference between Se2 and Se3 was insignificant. K-humate addition induced a notable increase in Cr-straw in the following order: control  > Se3  > Se2  > Se1. This may be owing to the increased stimulating movement of Cr from soil to different parts of the plant. Results obtained from Se treatments varied depending on the presence of K-humate. Cr-seeds decreased in the following order: Se2  > Se3  > Se2  > control. The addition of K-humate increased the Cr-seed content compared with Se alone; however, the difference between Se2 and Se3 was insignificant. Analysis using the sum of means did not produce significant differences.Table 8 Effects of Se and K-humate application on Cr content.Full size tableEffects of Se and K-humate applications on Fe contentVariable effects were produced using different application rates of Se on Fe-straw, and this effect was observed in the following order: Se3  > Se1  > control  > Se2 (Table 9). Differences were insignificant among control, Se1, and Se2. K-humate caused concentrations of Fe-straw to significantly increase in the following order: control  > Se3  > Se2  > Se1. Differences between control and Se3 as well as Se1 and Se2 were insignificant. Analysis using the sum of means was similar. Neither Se nor Se with K-humate applications produced significant changes in Fe-seeds. Analysis using the sum of means was similar. Low concentration of Se application may enhance plant productivity and encourage phytoremediation by improving plant tolerance to stress and enhancing photosynthesis25. Further, a significant increase was observed in concentrations of Fe and S in rice grain grown in N-limiting conditions while Ca that have been treated with Se regardless of N supply21.Table 9 Effects of Se and K-humate applications on Fe content.Full size tableEffects of Se and K-humate application on Mn contentApplication of Se reduced the Mn-straw content, and this effect was observed in the following order: control  > Se2  > Se1  > Se3. No significant difference was found between control and Se1 (Table 10). In contrast, K-humate addition further reduced Mn-straw concentrations in the following order: control  > Se1  > Se3  > Se2. The control and Se1 were not significantly different when using the sum of means for analysis. Likewise, no significant difference was seen between Se1 and Se3. Accumulation of Mn in seeds varied among treatments in the following order: control  > Se2  > Se3  > Se1. K-humate addition altered this order to be in the following order: control  > Se2  > Se1  > Se3. No significant differences were observed between Se2 and Se3 when the sum of means for analysis was used. Previously, the application of Se increased the concentrations of Mg and molybdenum in grains grown in 16 and 24 mM N compared with N-limited plants21.Table 10 Effects of Se and K-humate application on Mn content.Full size tableEffect of Se and K-humate applications on Zn content in oat plantsApplication of Se2—the middle concentration of Se—resulted in highest accumulation in Zn-straw, and this effect was observed in the following order: Se2  > Se1  > control  > Se3 (Table 11). The application of K-humate with Se resulted in some insignificant variations compared with the application of Se alone. Control, Se1, and Se3 were insignificantly different when the sum of means was used for the analysis. Concentrations of Zn in seeds were reduced after Se application. K-humate with Se foliar application altered the concentration of Zn in seeds with impacts in the following order: control  > Se3  > Se1  > Se2. The difference between Se1 and Se3 was insignificant. Additionally, insignificant differences in Zn concentrations after application of Se1, Se2, and Se3 were found when the sum of means was used for analysis. Low concentrations of Se possibly enhance plant productivity and phytoremediation capacity by improving the ability of plants to tolerate stress and enhancing photosynthesis25.Table 11 Effect of Se and K-humate applications on Zn containing oat plant.Full size tableEffects of Se and K-humate application on Cu contentIncreasing concentrations of Se from 12 × 10−3 to 88 × 10−3 mM increased the concentration of Cu-seed, and this effect was observed in the following order: Se1  > control  > Se2  > Se3 as it shown in Table 12. Application of Se with K-humate showed significant changes in the Cu-straw content in the following order: Se1  > Se2  > control  > Se3. No significant differences were observed using the sum of means for analyses. In contrast, the foliar application of Se resulted in increases in Cu-seed at concentrations of Se1 and Se3; however, at 63 × 10−3 mM (Se2), a reduction in Cu-seed was observed. K-humate with Se simultaneously resulted in increased Cu-seed content with impacts decreasing in the following order: Se3  > Se1  > control  > Se2. The sum of means analysis showed no significant variation between control and Se2. Previously, the application of Se led to a decrease in the concentrations of Cu in grains grown in 16 and 24 mm N compared with N-limited plants21.
Table 12 Effects of Se and K-humate application on Cu content.Full size table More

Murray, N. J. et al. The global distribution and trajectory of tidal flats. Nature 565, 222–225, https://doi.org/10.1038/s41586-018-0805-8 (2019).CAS 
Article 
PubMed 

Google Scholar 
Bishop, M. J., Murray, N. J., Swearer, S. & Keith, D. A. In The IUCN Global Ecosystem Typology 2.0: Descriptive profiles for biomes and ecosystem functional groups (eds D. A. Keith, J. R. Ferrer-Paris, E. Nicholson, & R. T. Kingsford) (IUCN, 2020).Keith, D. A. et al. Earth’s ecosystems: a function-based typology for conservation and sustainability. Nature (In review).Murray, N. J., Phinn, S. R., Clemens, R. S., Roelfsema, C. M. & Fuller, R. A. Continental scale mapping of tidal flats across East Asia using the Landsat Archive. Remote Sensing 4, 3417–3426, https://doi.org/10.3390/Rs4113417 (2012).Article 

Google Scholar 
Murray, N. J., Clemens, R. S., Phinn, S. R., Possingham, H. P. & Fuller, R. A. Tracking the rapid loss of tidal wetlands in the Yellow Sea. Fron. Ecol. Environ. 12, 267–272, https://doi.org/10.1890/130260 (2014).Article 

Google Scholar 
Murray, N. J., Ma, Z. & Fuller, R. A. Tidal flats of the Yellow Sea: A review of ecosystem status and anthropogenic threats. Austral Ecol. 40, 472–481, https://doi.org/10.1111/aec.12211 (2015).Article 

Google Scholar 
Dhanjal-Adams, K. et al. Distribution and protection of intertidal habitats in Australia. Emu 116, 208–214 (2015).Article 

Google Scholar 
Murray, N. J. et al. High-resolution mapping of losses and gains of Earth’s tidal wetlands. Science 376, 744–749, https://doi.org/10.1126/science.abm9583 (2022).CAS 
Article 
PubMed 

Google Scholar 
Gong, P. et al. Finer resolution observation and monitoring of global land cover: first mapping results with Landsat TM and ETM+ data. Int. J. Remote Sens. 34, 2607–2654 (2013).Article 

Google Scholar 
Gorelick, N. et al. Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote Sens. Environ. 202, 18–27, https://doi.org/10.1016/j.rse.2017.06.031 (2017).Article 

Google Scholar 
Turner, W. et al. Free and open-access satellite data are key to biodiversity conservation. Biol. Conserv. 182, 173–176 (2015).Article 

Google Scholar 
Murray, N. J. et al. The role of satellite remote sensing in structured ecosystem risk assessments. Sci Total Environ 619–620, 249–257, https://doi.org/10.1016/j.scitotenv.2017.11.034 (2018).CAS 
Article 
PubMed 

Google Scholar 
Ying, Q. et al. Global bare ground gain from 2000 to 2012 using Landsat imagery. Remote Sens. Environ. 194, 161–176, https://doi.org/10.1016/j.rse.2017.03.022 (2017).Article 

Google Scholar 
Song, X.-P. et al. Global land change from 1982 to 2016. Nature 560, 639–643, https://doi.org/10.1038/s41586-018-0411-9 (2018).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Noble, S. et al. A new 30 meter resolution global shoreline vector and associated global islands database for the development of standardized ecological coastal units AU – Sayre, Roger. Journal of Operational Oceanography, 1–10, https://doi.org/10.1080/1755876X.2018.1529714 (2018).Sayre, R. et al. A global ecological classification of coastal segment units to complement marine biodiversity observation network assessments. Oceanography 34, 120–129 (2021).Article 

Google Scholar 
Hansen, M. C. et al. High-resolution global maps of 21st-century forest cover change. Science 342, 850–853, https://doi.org/10.1126/science.1244693 (2013).CAS 
Article 
PubMed 

Google Scholar 
Margono, B. A., Potapov, P. V., Turubanova, S., Stolle, F. & Hansen, M. C. Primary forest cover loss in Indonesia over 2000–2012. Nature Climate Change 4, 730–735, https://doi.org/10.1038/nclimate2277 (2014).Article 

Google Scholar 
Curtis, P. G., Slay, C. M., Harris, N. L., Tyukavina, A. & Hansen, M. C. Classifying drivers of global forest loss. Science 361, 1108–1111, https://doi.org/10.1126/science.aau3445 (2018).CAS 
Article 
PubMed 

Google Scholar 
Pekel, J. F., Cottam, A., Gorelick, N. & Belward, A. S. High-resolution mapping of global surface water and its long-term changes. Nature 540, 418–422, https://doi.org/10.1038/nature20584 (2016).CAS 
Article 
PubMed 

Google Scholar 
Pickens, A. H. et al. Mapping and sampling to characterize global inland water dynamics from 1999 to 2018 with full Landsat time-series. Remote Sens. Environ. 243, 111792, https://doi.org/10.1016/j.rse.2020.111792 (2020).Article 

Google Scholar 
Yamazaki, D., Trigg, M. A. & Ikeshima, D. Development of a global ~ 90 m water body map using multi-temporal Landsat images. Remote Sens. Environ. 171, 337–351, https://doi.org/10.1016/j.rse.2015.10.014 (2015).Article 

Google Scholar 
Fluet-Chouinard, E., Lehner, B., Rebelo, L.-M., Papa, F. & Hamilton, S. K. Development of a global inundation map at high spatial resolution from topographic downscaling of coarse-scale remote sensing data. Remote Sens. Environ. 158, 348–361, https://doi.org/10.1016/j.rse.2014.10.015 (2015).Article 

Google Scholar 
Bunting, P. et al. The Global Mangrove Watch—A new 2010 global baseline of mangrove extent. Remote Sensing 10, 1669 (2018).Article 

Google Scholar 
Worthington, T. A. et al. Harnessing Big Data to Support the Conservation and Rehabilitation of Mangrove Forests Globally. One Earth 2, 429–443, https://doi.org/10.1016/j.oneear.2020.04.018 (2020).Article 

Google Scholar 
Worthington, T. A. et al. A global typology of mangroves and its relevance for ecosystem services and deforestation. Scientific reports (2020).Thomas, N. et al. Distribution and drivers of global mangrove forest change, 1996–2010. PLOS ONE 12, e0179302, https://doi.org/10.1371/journal.pone.0179302 (2017).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Simard, M. et al. Mangrove canopy height globally related to precipitation, temperature and cyclone frequency. Nature Geoscience 12, 40–45, https://doi.org/10.1038/s41561-018-0279-1 (2019).CAS 
Article 

Google Scholar 
Allen, G. H. & Pavelsky, T. M. Global extent of rivers and streams. Science 361, 585–588, https://doi.org/10.1126/science.aat0636 (2018).MathSciNet 
CAS 
Article 
PubMed 
MATH 

Google Scholar 
Lyons, M. et al. Mapping the world’s coral reefs using a global multiscale earth observation framework. Remote Sensing in Ecology and Conservation (2020).Li, J. et al. A global coral reef probability map generated using convolutional neural networks. Coral Reefs https://doi.org/10.1007/s00338-020-02005-6 (2020).Article 

Google Scholar 
Yang, X., Pavelsky, T. M. & Allen, G. H. The past and future of global river ice. Nature 577, 69–73, https://doi.org/10.1038/s41586-019-1848-1 (2020).CAS 
Article 
PubMed 

Google Scholar 
Newbold, T. et al. Has land use pushed terrestrial biodiversity beyond the planetary boundary? A global assessment. Science 353, 288–291, https://doi.org/10.1126/science.aaf2201 (2016).CAS 
Article 
PubMed 

Google Scholar 
Tittensor, D. P. et al. A mid-term analysis of progress toward international biodiversity targets. Science 346, 241–244, https://doi.org/10.1126/science.1257484 (2014).CAS 
Article 
PubMed 

Google Scholar 
Lee, C. K. F., Nicholson, E., Duncan, C. & Murray, N. J. Estimating changes and trends in ecosystem extent with dense time-series satellite remote sensing. Conserv Biol 35, 325–335, https://doi.org/10.1111/cobi.13520 (2021).Article 
PubMed 

Google Scholar 
Deegan, L. A. et al. Coastal eutrophication as a driver of salt marsh loss. Nature 490, 388–392 (2012).CAS 
Article 

Google Scholar 
Goldberg, L., Lagomasino, D., Thomas, N. & Fatoyinbo, T. Global declines in human-driven mangrove loss. Glob Chang Biol 26, 5844–5855, https://doi.org/10.1111/gcb.15275 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Brown, A. C. & McLachlan, A. Sandy shore ecosystems and the threats facing them: some predictions for the year 2025. Environ. Conserv. 29, 62–77, https://doi.org/10.1017/s037689290200005x (2002).Article 

Google Scholar 
Krumhansl, K. A. et al. Global patterns of kelp forest change over the past half-century. Proc. Natl. Acad. Sci. USA 113, 13785–13790, https://doi.org/10.1073/pnas.1606102113 (2016).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Hill, N. K., Woodworth, B. K., Phinn, S. R., Murray, N. J. & Fuller, R. A. Global protected-area coverage and human pressure on tidal flats. Conserv Biol, https://doi.org/10.1111/cobi.13638 (2021).Murray, N. J. et al. Myanmar’s terrestrial ecosystems: Status, threats and conservation opportunities. Biol. Conserv. 252, 108834, https://doi.org/10.1016/j.biocon.2020.108834 (2020).Article 

Google Scholar 
Jackson, M. V. et al. Dual threat of tidal flat loss and invasive Spartina alterniflora endanger important shorebird habitat in coastal mainland China. J Environ Manage 278, 111549, https://doi.org/10.1016/j.jenvman.2020.111549 (2021).Article 
PubMed 

Google Scholar 
Davidson, N. C. & Finlayson, C. M. Updating global coastal wetland areas presented in Davidson and Finlayson (2018). Marine and Freshwater Research 70, 1195–1200, https://doi.org/10.1071/MF19010 (2019).Article 

Google Scholar 
Duan, H. et al. Identifying new sites of significance to waterbirds conservation and their habitat modification in the Yellow and Bohai Seas in China. Global Ecology and Conservation, e01031 (2020).Jung, M. et al. A global map of terrestrial habitat types. Scientific Data 7, 256, https://doi.org/10.1038/s41597-020-00599-8 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Keith, D. et al. The IUCN Global Ecosystem Typology v2.0: Descriptive profiles for Biomes and Ecosystem Functional Groups. (The International Union for the Conservation of Nature (IUCN), Gland, 2020).Fink, D. et al. Modeling avian full annual cycle distribution and population trends with citizen science data. Ecol. Appl. 30, e02056, https://doi.org/10.1002/eap.2056 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Convention on Biological Diversity. Indicators for the post-2020 Global Biodiversity Framework. (Convention on Biological Diversity, 2021).Murray, NJ. et al. High-resolution global maps of tidal flat ecosystems from 1984 to 2019, Figshare, https://doi.org/10.6084/m9.figshare.c.5884598.v1 (2022).Amante, C. & Eakins, B. W. ETOPO1 1 arc-minute global relief model: procedures, data sources and analysis. (US Department of Commerce, National Oceanic and Atmospheric Administration, National Environmental Satellite, Data, and Information Service, National Geophysical Data Center, Marine Geology and Geophysics Division, 2009).Farr, T. G. et al. The shuttle radar topography mission. Rev. Geophys. 45, Rg200410.1029/2005rg000183 (2007).Article 

Google Scholar 
Mcowen, C. et al. A global map of saltmarshes. Biodiversity Data Journal 5, https://doi.org/10.3897/BDJ.5.e11764 (2017).Giri, C. et al. Status and distribution of mangrove forests of the world using earth observation satellite data. Global Ecology and Biogeography 20, 154–159, https://doi.org/10.1111/j.1466-8238.2010.00584.x (2011).Article 

Google Scholar 
US Geological Survey. Product Guide: Landsat 4–7 Surface Reflectance (LEDAPS) Product (2018).US Geological Survey. Product Guide: Landsat 8 Surface Reflectance Code (LASRC) Product (2018).Foga, S. et al. Cloud detection algorithm comparison and validation for operational Landsat data products. Remote Sens. Environ. 194, 379–390 (2017).Article 

Google Scholar 
Breiman, L. Random forests. Machine learning 45, 5–32 (2001).Article 

Google Scholar 
Murray, N. J. et al. Code and data supplement to “High-resolution global maps of tidal flat ecosystems from 1984 to 2019”. Zenodo https://doi.org/10.5281/zenodo.6332960 (2020).Congalton, R. G. & Green, K. Assessing the Accuracy of Remotely Sensed Data: Principles and Practices. (CRC press, 2008).Lyons, M. B., Keith, D. A., Phinn, S. R., Mason, T. J. & Elith, J. A comparison of resampling methods for remote sensing classification and accuracy assessment. Remote Sens. Environ. 208, 145–153, https://doi.org/10.1016/j.rse.2018.02.026 (2018).Article 

Google Scholar 
Sagar, S., Roberts, D., Bala, B. & Lymburner, L. Extracting the intertidal extent and topography of the Australian coastline from a 28 year time series of Landsat observations. Remote Sens. Environ. 195, 153–169, https://doi.org/10.1016/j.rse.2017.04.009 (2017).Article 

Google Scholar 
Lee, J. et al. The first national scale evaluation of organic carbon stocks and sequestration rates of coastal sediments along the West Sea, South Sea, and East Sea of South Korea. Sci Total Environ 793, 148568, https://doi.org/10.1016/j.scitotenv.2021.148568 (2021).CAS 
Article 
PubMed 

Google Scholar 
Zhang, Z., Xu, N., Li, Y. & Li, Y. Sub-continental-scale mapping of tidal wetland composition for East Asia: A novel algorithm integrating satellite tide-level and phenological features. Remote Sens. Environ. 269, 112799, https://doi.org/10.1016/j.rse.2021.112799 (2022).Article 

Google Scholar 
Hooijer, A. & Vernimmen, R. Global LiDAR land elevation data reveal greatest sea-level rise vulnerability in the tropics. Nat. Commun. 12, 1–7 (2021).Article 

Google Scholar 
Rodríguez, J. P. et al. A practical guide to the application of the IUCN Red List of Ecosystems criteria. Philos. Trans. R. Soc. B-Biol. Sci. 370, 20140003, https://doi.org/10.1098/rstb.2014.0003 (2015).Article 

Google Scholar 
Keith, D. A. et al. The IUCN Red List of Ecosystems: Motivations, Challenges, and Applications. Conservation Letters 8, 214–226, https://doi.org/10.1111/conl.12167 (2015).Article 

Google Scholar 
Spencer, T. et al. Global coastal wetland change under sea-level rise and related stresses: The DIVA Wetland Change Model. Global and Planetary Change 139, 15–30 (2016).Article 

Google Scholar 
Bunting, P., Rosenqvist, A., Hilarides, L., Lucas, R. M. & Thomas, N. Global Mangrove Watch: Updated 2010 Mangrove Forest Extent (v2.5). Remote Sensing 14, 1034 (2022).Article 

Google Scholar 
US Geological Survey. Landsat 4–7 Collection 1 (C1) Surface Reflectance (LEDAPS) Product Guide. Version 3.0. (USGS, 2020).Xu, C. & Liu, W. Mapping and analyzing the annual dynamics of tidal flats in the conterminous United States from 1984 to 2020 using Google Earth Engine. Environmental Advances 7, 100147, https://doi.org/10.1016/j.envadv.2021.100147 (2022).Article 

Google Scholar 
Wang, X. X. et al. Rebound in China’s coastal wetlands following conservation and restoration. Nature Sustainability 4, 1076-+, https://doi.org/10.1038/s41893-021-00793-5 (2021).Article 

Google Scholar 
Fitton, J. M., Rennie, A. F., Hansom, J. D. & Muir, F. M. E. Remotely sensed mapping of the intertidal zone: a Sentinel-2 and Google Earth Engine methodology. Remote Sensing Applications: Society and Environment, 100499, https://doi.org/10.1016/j.rsase.2021.100499 (2021).Murray, N. J., Kennedy, E., Álvarez-Romero, J. G. & Lyons, M. B. Data freshness in ecology and conservation. Trends in Ecology and Evolution 36, 485–487, https://doi.org/10.1016/j.tree.2021.03.005 (2021).Article 
PubMed 

Google Scholar  More

Zaneveld, J. R., McMinds, R. & Thurber, R. V. Stress and stability: Applying the Anna Karenina principle to animal microbiomes. Nat. Microbiol. 2, 1–8 (2017).Article 
CAS 

Google Scholar 
Trevelline, B. K., Fontaine, S. S., Hartup, B. K. & Kohl, K. D. Conservation biology needs a microbial renaissance: A call for the consideration of host-associated microbiota in wildlife management practices. Proc. R. Soc. B 286, 2018–2448 (2019).Article 

Google Scholar 
Bennett, A. G. On the occurrence of diatoms on the skin of whales. Proc. R. Soc. Lond. B 91, 352–357 (1920).ADS 
Article 

Google Scholar 
Denys, L. Morphology and taxonomy of epizoic diatoms (Epiphalaina and Tursiocola) on a sperm whale (Physeter macrocephalus) stranded on the coast of Belgium. Diatom. Res. 12, 1–18 (1997).Article 

Google Scholar 
Majewska, R. Tursiocola neliana sp. nov (Bacillariophyceae) epizoic on South African leatherback sea turtles (Dermochelys coriacea) and new observations on the genus Tursiocola. Phytotaxa 453, 1–15 (2020).Article 

Google Scholar 
Majewska, R. et al. Chelonicola and Poulinea, two new gomphonemoid genera living on marine turtles from Costa Rica. Phytotaxa 233, 236–250 (2015).Article 

Google Scholar 
Majewska, R. et al. Shared epizoic taxa and differences in diatom community structure between green turtles (Chelonia mydas) from distant habitats. Microb Ecol. 74, 969–978 (2017).PubMed 
Article 

Google Scholar 
Majewska, R. et al. Two new epizoic Achnanthes species (Bacillariophyta) living on marine turtles from Costa Rica. Bot. Mar. 60, 303–318 (2017).Article 

Google Scholar 
Majewska, R., De Stefano, M. & Van de Vijver, B. Labellicula lecohuiana, a new epizoic diatom species living on green turtles in Costa Rica. Nova Hedwig Beih. 146, 23–31 (2018).Article 

Google Scholar 
Majewska, R. et al. Craspedostauros alatus sp. nov., a new diatom (Bacillariophyta) species found on museum sea turtle specimens. Diatom Res. 33, 229–240 (2018).Article 

Google Scholar 
Majewska, R. et al. Six new epibiotic Proschkinia (Bacillariophyta) species and new insights into the genus phylogeny. Eur. J. Phycol. 54, 609–631 (2019).Article 

Google Scholar 
Majewska, R., Robert, K., Van de Vijver, B. & Nel, R. A new species of Lucanicum (Cyclophorales, Bacillariophyta) associated with loggerhead sea turtles from South Africa. Bot. Lett. 167, 7–14 (2020).Article 

Google Scholar 
Frankovich, T. A., Sullivan, M. J. & Stacy, N. I. Tursiocola denysii sp. Nov. (Bacillariophyta) from the neck skin of Loggerhead sea turtles (Caretta caretta). Phytotaxa 234, 227–236 (2015).Article 

Google Scholar 
Frankovich, T. A., Ashworth, M. P., Sullivan, M. J., Vesela, J. & Stacy, N. I. Medlinella amphoroidea gen. et sp. Nov. (Bacillariophyta) from the neck skin of Loggerhead sea turtles (Caretta caretta). Phytotaxa 272, 101–114 (2016).Article 

Google Scholar 
Riaux-Gobin, C. et al. New epizoic diatom (Bacillariophyta) species from sea turtles in the Eastern Caribbean and South Pacific. Diatom Res. 32, 109–125 (2017).Article 

Google Scholar 
Riaux-Gobin, C., Witkowski, A., Chevallier, D. & Daniszewska-Kowalczyk, G. Two new Tursiocola species (Bacillariophyta) epizoic on green turtles (Chelonia mydas) in French Guiana and Eastern Caribbean. Fottea Olomouc 17, 150–163 (2017).Article 

Google Scholar 
Riaux-Gobin, C., Witkowski, A., Kociolek, J. P. & Chevallier, D. Navicula dermochelycola sp. Nov., presumably an exclusively epizoic diatom on sea turtles Dermochelys coriacea and Lepidochelys olivacea from French Guiana. Oceanol. Hydrobiol. Stud. 49, 132–139 (2020).CAS 
Article 

Google Scholar 
Robert, K., Bosak, S. & Van de Vijver, B. Catenula exigua sp. nov., a new marine diatom (Bacillariophyta) species from the Adriatic Sea. Phytotaxa 414, 113–118 (2019).Article 

Google Scholar 
Van de Vijver, B. & Bosak, S. Planothidium kaetherobertianum, a new marine diatom (Bacillariophyta) species from the Adriatic Sea. Phytotaxa 425, 105–112 (2019).Article 

Google Scholar 
Robinson, N. J. et al. Epibiotic diatoms are universally present on all sea turtle species. PLoS ONE 11, e0157011 (2016).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Van de Vijver, B. et al. Diversity of diatom communities (Bacillariophyta) associated with loggerhead sea turtles. PLoS ONE 15, e0236513 (2020).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Van de Vijver, B., Robert, K., Witkowski, A. & Bosak, S. Majewskaea gen. nov. (Bacillariophyta), a new marine benthic diatom genus from the Adriatic Sea. Fottea 20, 112–120 (2020).Article 

Google Scholar 
Majewska, R. Nagumoea hydrophicola sp. Nov. (Bacillariophyta), the first diatom species described from sea snakes. Diatom Res. 36, 49–59 (2021).Article 

Google Scholar 
Frankovich, T. A., Sullivan, M. J. & Stacey, N. I. Three new species of Tursiocola (Bacillariophyta) from the skin of the West Indian manatee (Trichechus manatus). Phytotaxa 204, 33–48 (2015).Article 

Google Scholar 
Frankovich, T. A., Ashworth, M. P., Sullivan, M. J., Theriot, E. C. & Stacy, N. I. Epizoic and apochlorotic Tursiocola species (Bacillariophyta) from the skin of Florida manatees (Trichechus manatus latirostris). Protist 169, 539–568 (2018).PubMed 
Article 

Google Scholar 
Azari, M. et al. Diatoms on sea turtles and floating debris in the Persian Gulf (Western Asia). Phycologia 59, 292–304 (2020).Article 

Google Scholar 
Majewska, R. & Goosen, W. E. For better, for worse: Manatee-associated Tursiocola (Bacillariophyta) remain faithful to their host. J. Phycol. 56, 1019–1027 (2020).CAS 
PubMed 
Article 

Google Scholar 
Smol, J. P. & Stoermer, E. F. The Diatoms: Applications for the Environmental and Earth Sciences (Cambridge University Press, 2010).Book 

Google Scholar 
Rivera, S. F. et al. DNA metabarcoding and microscopic analyses of sea turtles biofilms: Complementary to understand turtle behavior. PLoS ONE 13, e0195770 (2018).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Majewska, R. et al. On sea turtle-associated Craspedostauros with description of three novel species. J Phycol. 57, 199–208 (2021).CAS 
PubMed 
Article 

Google Scholar 
Holmes, R. W. The morphology of diatoms epizoic on cetaceans and their transfer from Cocconeis to two new genera, Bennettella and Epipellis. Br. Phycol. J. 20, 43–57 (1985).Article 

Google Scholar 
Woodworth, K. A., Frankovich, T. A. & Freshwater, D. W. Melanothamnus maniticola (Ceramiales, Rhodophyta): An epizoic species evolved for life on the West Indian Manatee. J. Phycol. 55, 1239–1245 (2019).CAS 
PubMed 
Article 

Google Scholar 
Vitt, L. J. & Caldwell, J. P. Herpetology: An Introductory Biology of Amphibians and Reptiles (Academic Press, 2013).
Google Scholar 
Pitman, L. R. et al. Skin in the game: Epidermal molt as a driver of long-distance migration in whales. Mar. Mamm. Sci. 36, 565–594 (2020).Article 

Google Scholar 
Pope, D. H. & Berger, L. R. Algal photosynthesis at increased hydrostatic pressure and constant pO2. Arch. Microbiol. 89, 321–325 (1973).CAS 

Google Scholar 
Calcagno, V., Jarne, P., Loreau, M., Mouquet, N. & David, P. Diversity spurs diversification in ecological communities. Nat. Commun. 8, 15810 (2017).ADS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Robinson, N. J. & Pfaller, J. B. Sea turtle epibiosis: Global patterns and knowledge gaps. Trends Evol. Ecol. 10, 844021 (2021).
Google Scholar 
Conant, T. A., Dutton, P. H., Eguchi, T., Epperly, S. P., Fahy, C. C., Godfrey, M. H., MacPherson, S. L., Possardt, E. E., Schroeder, B. A., Seminoff, J. A., Snover, M. L. Loggerhead sea turtle (Caretta caretta) 2009 status review under the US Endangered Species Act. In Report of the loggerhead biological review Team to the National Marine Fisheries Service. 222, 1–230 (2009).Evans, K. M., Wortley, A. H. & Mann, D. G. An assessment of potential diatom ‘“barcode”’ genes (cox1, rbcL, 18S and ITS rDNA) and their effectiveness in determining relationships in Sellaphora (Bacillariophyta). Protist 158, 349–364 (2007).CAS 
PubMed 
Article 

Google Scholar 
Hamsher, S. E., Evans, K. M., Mann, D. G., Poulíčková, A. & Saunders, G. W. Barcoding diatoms: Exploring alternatives to COI-5P. Protist 162, 405–422 (2011).CAS 
PubMed 
Article 

Google Scholar 
Bowen, B. W. & Karl, S. A. Population genetics and phylogeography of sea turtles. Mol Ecol. 16, 4886–4907 (2007).CAS 
PubMed 
Article 

Google Scholar 
Shanker, K., Ramadevi, J., Choudhury, B. C., Singh, L. & Aggarwal, R. K. Phylogeography of olive ridley turtles (Lepidochelys olivacea) on the east coast of India: implications for conservation theory. Mol. Ecol. 13, 1899–1909 (2004).CAS 
PubMed 
Article 

Google Scholar 
Pinou, T. et al. Standardizing sea turtle epibiont sampling: Outcomes of the epibiont workshop at the 37th International Sea Turtle Symposium. Mar. Turt. Newsl. 157, 22–32 (2019).
Google Scholar 
Ehrhert L., Ogren L. H. Studies in foraging habitats: capturing and handling turtles. In Research and management techniques for the conservation of sea turtles (eds. Eckert, K. L., Bjorndal, K. A., Abreu-Grobois, F. A., Donnelly, M.). IUCN/SSC Marine Turtle Specialist Group. Publication No. 4. (1999).Guillard, R. R. Culture of phytoplankton for feeding marine invertebrates. In Culture of Marine Invertebrate Animals 29–60 (Springer, 1975).Theriot, E. C., Ashworth, M. P., Nakov, T., Ruck, E. & Jansen, R. K. Dissecting signal and noise in diatom chloroplast protein encoding genes with phylogenetic information profiling. Mol. Phylogenet. Evol. 89, 28–36 (2015).CAS 
PubMed 
Article 

Google Scholar 
Lobban, C. S., Ashworth, M. P., Calaor, J. J. & Theriot, E. C. Extreme diversity in fine-grained morphology reveals fourteen new species of conopeate Nitzschia (Bacillariophyta: Bacillariales). Phytotaxa. 401, 199–238 (2019).Article 

Google Scholar 
Lanfear, R., Frandsen, P. B., Wright, A. M., Senfeld, T. & Calcott, B. PartitionFinder 2: New methods for selecting partitioned models of evolution for molecular and morphological phylogenetic analyses. Mol. Biol. Evol. 34, 772–773 (2017).CAS 
PubMed 

Google Scholar 
Lanfear, R., Calcott, B., Kainer, D., Mayer, C. & Stamatakis, A. Selecting optimal partitioning schemes for phylogenomic datasets. BMC Evol. Biol. 14, 1–14 (2014).Article 

Google Scholar 
Stamatakis, A. RAxML version 8: A tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 30, 1312–1313 (2014).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Nguyen, L.-T., Schmidt, H. A., von Haeseler, A. & Minh, B. Q. IQ-TREE: A fast and effective stochastic algorithm for estimating maximum likelihood phylogenies. Mol. Biol. Evol. 32, 268–274 (2015).CAS 
PubMed 
Article 

Google Scholar 
Chernomor, O., Von Haeseler, A. & Minh, B. Q. Terrace aware data structure for phylogenomic inference from supermatrices. Syst. Biol. 65, 997–1008 (2016).PubMed 
PubMed Central 
Article 

Google Scholar 
Aberer, A. J., Kobert, K. & Stamatakis, A. ExaBayes: Massively parallel bayesian tree inference for the whole-genome Era. Mol. Biol. Evol. 31, 2553–2556 (2014).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar  More

Editorial Committee of Vegetation Map China. Vegetation Map of China (1:1000 000) (Geology Press, 2007).Fu, B. et al. Current condition and protection strategies of Qinghai–Tibet Plateau ecological security barrier. Bull. Chin. Acad. Sci. 36, 1298–1306 (2021).
Google Scholar 
Zhang, Y. et al. Spatial and temporal variability in the net primary production (NPP) of alpine grassland on Tibetan Plateau from 1982 to 2009. Acta Geogr. Sin. 68, 1197–1211 (2013).
Google Scholar 
Bao, C. & Liu, R. Spatiotemporal evolution of the urban system in the Tibetan Plateau. J. Geoinf. Sci. 21, 1330–1340 (2019).
Google Scholar 
Miehe, G. et al. The Kobresia pygmaea ecosystem of the Tibetan highlands — origin, functioning and degradation of the world’s largest pastoral alpine ecosystem: Kobresia pastures of Tibet. Sci. Total Environ. 648, 754–771 (2019). This work describes features of K. pygmaea grassland and reveals that overstocking has caused pasture degradation and soil deterioration.Article 

Google Scholar 
Liu, Y. et al. Grassland dynamics in responses to climate variation and human activities in China from 2000 to 2013. Sci. Total Environ. 690, 27–39 (2019).Article 

Google Scholar 
Cao, J. et al. Grassland degradation on the Qinghai–Tibetan Plateau: reevaluation of causative factors. Rangel. Ecol. Manag. 72, 988–995 (2019).Article 

Google Scholar 
Zhao, X. Restoration and Sustainable Management of Degradaded Grassland in the Three Rivers Headwater (Science Press, 2011).Gao, Q. Exploration and Study on Eoclogical Revelization Fuatures in Qiangtang Plateau (China Agriculture Press, 2015).Gu, X. et al. Soil extractable organic C and N contents, methanotrophic activity under warming and degradation in a Tibetan alpine meadow. Agric. Ecosyst. Environ. 278, 6–14 (2019).Article 

Google Scholar 
Li, Y. et al. Changes of soil microbial community under different degraded gradients of alpine meadow. Agric. Ecosyst. Environ. 222, 213–222 (2016).Article 

Google Scholar 
Wang, W., Wang, Q. & Wang, H. The effect of land management on plant community composition, species diversity, and productivity of alpine Kobersia steppe meadow. Ecol. Res. 21, 181–187 (2005).Article 

Google Scholar 
Xu, H., Wang, X. & Zhang, X. Alpine grasslands response to climatic factors and anthropogenic activities on the Tibetan Plateau from 2000 to 2012. Ecol. Eng. 92, 251–259 (2016).Article 

Google Scholar 
Yu, L., Tang, L., Wei, D., Mei, M. & Zhou, H. Characteristics and causes of changes of alpine grassland productivity in the source region of Yellow River. Int. Conf. Geoinformatics https://doi.org/10.1109/GEOINFORMATICS.2010.5567879 (2010).Article 

Google Scholar 
Yang, Y. et al. Responses of the functional structure of soil microbial community to livestock grazing in the Tibetan alpine grassland. Glob. Chang. Biol. 19, 637–648 (2013). This work shows that soil microbial community functional structure is very sensitive to livestock grazing.Article 

Google Scholar 
Gao, Y. Z. et al. Belowground net primary productivity and biomass allocation of a grassland in Inner Mongolia is affected by grazing intensity. Plant Soil 307, 41–50 (2008).Article 

Google Scholar 
Dlamini, A. P. et al. Controlling factors of sheet erosion under degraded grasslands in the sloping lands of KwaZulu-Natal, South Africa. Agric. Water Manag. 98, 1711–1718 (2011).Article 

Google Scholar 
Niemandt, C. & Greve, M. Fragmentation metric proxies provide insights into historical biodiversity loss in critically endangered grassland. Agric. Ecosyst. Environ. 235, 172–181 (2016).Article 

Google Scholar 
Kang, S. C. et al. Review of climate and cryospheric change in the Tibetan Plateau. Environ. Res. Lett. 5, 15101–15101 (2010).Article 

Google Scholar 
Shen, H. et al. Effects of simulated N deposition on photosynthesis and productivity of key plants from different functional groups of alpine meadow on Qinghai–Tibetan Plateau. Environ. Pollut. 251, 731–737 (2019).Article 

Google Scholar 
Yu, G. R. et al. Stabilization of atmospheric nitrogen deposition in China over the past decade. Nat. Geosci. 12, 424 (2019).Article 

Google Scholar 
Lu, C. & Tian, H. Spatial and temporal patterns of nitrogen deposition in China: synthesis of observational data. J. Geophys. Res. 112, D22S05 (2007).
Google Scholar 
National Bureau of Statistics of China. China Statistics Yearbook (China Statistics Press, 2020).Mo, X. Sustainable livestock carring capacity and overgrazing rate of grassland over Qinghai–Tibet plateau since 1980. Natl Tibetan Plateau Data Center https://doi.org/10.11888/Socioeco.tpdc.270347 (2020).Article 

Google Scholar 
Tian, Y. Y., Jiang, G. H., Zhou, D. Y. & Li, G. Y. Systematically addressing the heterogeneity in the response of ecosystem services to agricultural modernization, industrialization and urbanization in the Qinghai–Tibetan Plateau from 2000 to 2018. J. Clean. Prod. https://doi.org/10.1016/j.jclepro.2020.125323 (2021).Article 

Google Scholar 
Yao, Y. et al. Spatiotemporal pattern of gross primary productivity and its covariation with climate in China over the last thirty years. Glob. Chang. Biol. 24, 184–196 (2018).Article 

Google Scholar 
Li, L. et al. Current challenges in distinguishing climatic and anthropogenic contributions to alpine grassland variation on the Tibetan Plateau. Ecol. Evol. 8, 5949–5963 (2018). This work finds that large inconsistencies exist in distinguishing the respective contribution of climatic and anthropogenic forces to grassland dynamics.Article 

Google Scholar 
Zhong, L., Ma, Y. M., Xue, Y. K. & Piao, S. L. Climate change trends and impacts on vegetation greening over the Tibetan Plateau. J. Geophys. Res. Atmos. 124, 7540–7552 (2019). This work demonstrates that the general increasing trends in vegetation density and greening of the QTP are mainly caused by climate factors, using satellite-derived climate and vegetation data from 1999 to 2014.Article 

Google Scholar 
Yang, K. & He, J. China meteorological forcing dataset (1979–2018). Natl Tibetan Plateau Data Center https://doi.org/10.11888/AtmosphericPhysics.tpe.249369.file (2019).Article 

Google Scholar 
Xiong, Q. et al. Monitoring the impact of climate change and human activities on grassland vegetation dynamics in the northeastern Qinghai–Tibet Plateau of China during 2000–2015. J. Arid. Land 11, 637–651 (2019).Article 

Google Scholar 
Pan, T., Zou, X. T., Liu, Y. J., Wu, S. H. & He, G. M. Contributions of climatic and non-climatic drivers to grassland variations on the Tibetan Plateau. Ecol. Eng. 108, 307–317 (2017).Article 

Google Scholar 
Hou, X. 1:1 Million vegetation map of China (National Tibetan Plateau Data Center, 2019).Peng, S. S. et al. Recent change of vegetation growth trend in China. Environ. Res. Lett. 6, 044027 (2011).Article 

Google Scholar 
Yuan, W. et al. Increased atmospheric vapor pressure deficit reduces global vegetation growth. Sci. Adv. 5, eaax1396 (2019).Article 

Google Scholar 
Zhu, Z. C. et al. Greening of the earth and its drivers. Nat. Clim. Chang. 6, 791 (2016).Article 

Google Scholar 
Vermote, E. et al. NOAA climate data record (CDR) of normalized difference vegetation index (NDVI), version 4. NOAA Natl Cent. Environ. Inf. https://doi.org/10.7289/V5PZ56R6 (2014).Article 

Google Scholar 
Chen, H. et al. Attribution analyses of changes in alpine grasslands on the Qinghai–Tibetan Plateau. Chin. Sci. Bull. 65, 2406–2418 (2020). This work demonstrates that human activities play an increasingly important role in the restoration of degraded grasslands.Article 

Google Scholar 
Shen, M. et al. Evaporative cooling over the Tibetan Plateau induced by vegetation growth. Proc. Natl Acad. Sci. USA 112, 9299–9304 (2015).Article 

Google Scholar 
Cai, D. et al. Vegetation dynamics on the Tibetan Plateau (1982–2006): an attribution by ecohydrological diagnostics. J. Clim. 28, 4576–4584 (2015).Article 

Google Scholar 
Zhou, W. et al. Grassland degradation remote sensing monitoring and driving factors quantitative assessment in China from 1982 to 2010. Ecol. Indic. 83, 303–313 (2017).Article 

Google Scholar 
Liu, Z. et al. Patterns of plant species diversity along an altitudinal gradient and its effect on above-ground biomass in alpine meadows in Qinghai–Tibet Plateau. Biodivers. Sci. 23, 451–462 (2015).Article 

Google Scholar 
Harris, R. B. Rangeland degradation on the Qinghai–Tibetan Plateau: a review of the evidence of its magnitude and causes. J. Arid. Environ. 74, 1–12 (2010).Article 

Google Scholar 
Lu, S. et al. Basic characteristics of Stipa sareptana var. krylovii communities in China. Chin. J. Plant. Ecol. 44, 1087–1094 (2020).Article 

Google Scholar 
Qiao, X. et al. Distribution, community characteristics and classification of Stipa tianschanica var. klemenzii steppe in China. Chin. J. Plant. Ecol. 41, 231–237 (2017).Article 

Google Scholar 
Qiao, X., Guo, K., Zhao, L., Yang, Y. & Zhao, H. Distribution, community characteristics and classification of Stipa basiplumosa steppe on Tibetan Plateau. Geogr. Res. 36, 2432–2440 (2017).
Google Scholar 
Qiao, X., Guo, K., Zhao, L., Wang, Z. & Liu, C. Community characteristics of Stipa bungeana alliance in China. Chin. J. Plant Ecol. 44, 986–994 (2020).Article 

Google Scholar 
Zhu, Y., Qiao, X., Guo, K., Xu, R. & Zhao, L. Distribution, community characteristics and classification of Stipa tianschanica var. gobica steppe in China. Chin. J. Plant Ecol. 42, 785–792 (2018).Article 

Google Scholar 
Li, X. R., Jia, X. H. & Dong, G. R. Influence of desertification on vegetation pattern variations in the cold semi-arid grasslands of Qinghai–Tibet plateau, north-west China. J. Arid. Environ. 64, 505–522 (2006).Article 

Google Scholar 
Tang, L. et al. Changes in vegetation composition and plant diversity with rangeland degradation in the alpine region of Qinghai–Tibet Plateau. Rangel. J. 37, 107–115 (2015).Article 

Google Scholar 
Zhou, X. Chinese Kobresia Meadow (Science Press, 2001).Wang, B. Z. et al. Potential distribution patterns of Stipa bungeana in China and the major factors influencing distribution. Acta Prataculturae Sinica 28, 3–13 (2019).
Google Scholar 
Sun, H., Li, W., Zhang, M. & Han, Y. A comprehensive scientific expedition to the Qinghai–Tibet Plateau. Resour. Sci. 8, 22–30 (1986).
Google Scholar 
Zhu, F. X. et al. Spatiotemporal variations of annual shallow soil temperature on the Tibetan Plateau during 1983–2013. Clim. Dyn. 51, 2209–2227 (2018).Article 

Google Scholar 
Chen, L. T. et al. Changes of carbon stocks in alpine grassland soils from 2002 to 2011 on the Tibetan Plateau and their climatic causes. Geoderma 288, 166–174 (2017).Article 

Google Scholar 
Ding, J. et al. Decadal soil carbon accumulation across Tibetan permafrost regions. Nat. Geosci. 10, 420–424 (2017).Article 

Google Scholar 
Tian, L. M. et al. Variations in soil nutrient availability across Tibetan grassland from the 1980s to 2010s. Geoderma 338, 197–205 (2019).Article 

Google Scholar 
Pepin, N. et al. Elevation-dependent warming in mountain regions of the world. Nat. Clim. Chang. 5, 424–430 (2015).Article 

Google Scholar 
Chen, H. et al. The impacts of climate change and human activities on biogeochemical cycles on the Qinghai–Tibetan Plateau. Glob. Chang. Biol. 19, 2940–2955 (2013). This work suggests that warming enhanced NPP and soil respiration but many uncertainties remain.Article 

Google Scholar 
Shen, M. G. et al. Plant phenological responses to climate change on the Tibetan Plateau: research status and challenges. Natl Sci. Rev. 2, 454–467 (2015).Article 

Google Scholar 
Liu, X. D., Yin, Z. Y., Shao, X. M. & Qin, N. S. Temporal trends and variability of daily maximum and minimum, extreme temperature events, and growing season length over the eastern and central Tibetan Plateau during 1961–2003. J. Geophys. Res. Atmos. https://doi.org/10.1029/2005jd006915 (2006).Article 

Google Scholar 
Yang, K. et al. Recent climate changes over the Tibetan Plateau and their impacts on energy and water cycle: a review. Glob. Planet. Change 112, 79–91 (2014). This work reviews the main spatio-temporal characteristics of climate change on the QTP.Article 

Google Scholar 
Klein, J. A., Harte, J. & Zhao, X. Q. Experimental warming, not grazing, decreases rangeland quality on the Tibetan Plateau. Ecol. Appl. 17, 541–557 (2007).Article 

Google Scholar 
Li, C. et al. Productivity and quality of alpine grassland vary with soil water availability under experimental warming. Front. Plant. Sci. 9, 1790 (2018).Article 

Google Scholar 
Peng, A. H. et al. Plant community responses to warming modified by soil moisture in the Tibetan Plateau. Arct. Antarct. Alp. Res. 52, 60–69 (2020).Article 

Google Scholar 
Li, F. et al. Leaf area rather than photosynthetic rate determines the response of ecosystem productivity to experimental warming in an alpine steppe. J. Geophys. Res. Biogeosci. 124, 2277–2287 (2019).Article 

Google Scholar 
Zong, N. et al. Responses of ecosystem CO2 fluxes to short-term experimental warming and nitrogen enrichment in an alpine meadow, northern Tibet Plateau. Sci. World J. 2013, 415318 (2013).Article 

Google Scholar 
Chen, Q., Niu, B., Hu, Y., Luo, T. & Zhang, G. Warming and increased precipitation indirectly affect the composition and turnover of labile-fraction soil organic matter by directly affecting vegetation and microorganisms. Sci. Total Environ. 714, 136787 (2020).Article 

Google Scholar 
Wang, X. X. et al. Effects of short-term and long-term warming on soil nutrients, microbial biomass and enzyme activities in an alpine meadow on the Qinghai–Tibet Plateau of China. Soil. Biol. Biochem. 76, 140–142 (2014).Article 

Google Scholar 
Jiang, L. L. et al. Plant organic N uptake maintains species dominance under long-term warming. Plant Soil 433, 243–255 (2018).Article 

Google Scholar 
Li, N. et al. Short-term effects of temperature enhancement on community structure and biomass of alpine meadow in the Qinghai–Tibet Plateau. Acta Ecol. Sin. 31, 895–905 (2011).
Google Scholar 
Jiang, Y., Fan, M. & Zhang, Y. Effect of short-term warming on plant community features of alpine meadow in northern Tibet. Chin. J. Ecol. 36, 616–622 (2017).
Google Scholar 
Wang, S. et al. Effects of warming and grazing on soil N availability, species composition, and ANPP in an alpine meadow. Ecology 93, 2365–2376 (2012). This work shows the effects of asymmetric warming and moderate grazing on plant composition, diversity, productivity and their relationships.Article 

Google Scholar 
Liu, P. et al. Ambient climate determines the directional trend of community stability under warming and grazing. Glob. Change Biol. 27, 5198–5210 (2021). This work finds that the negative effect of warming on plant diversity disappears with experimental duration, and ambient climate modulates the effects of warming and grazing on productivity stability.Article 

Google Scholar 
Zhang, B. et al. Responses of soil microbial communities to experimental warming in alpine grasslands on the Qinghai–Tibet Plateau. PLoS ONE 9, e103859 (2014).Article 

Google Scholar 
Chen, X. et al. Effects of warming and nitrogen fertilization on GHG flux in the permafrost region of an alpine meadow. Atmos. Environ. 157, 111–124 (2017).Article 

Google Scholar 
Zhang, Y. et al. Effects of grazing and climate warming on plant diversity, productivity and living state in the alpine rangelands and cultivated grasslands of the Qinghai–Tibetan Plateau. Rangel. J. 37, 57–65 (2015).Article 

Google Scholar 
Quan, Q. et al. High-level rather than low-level warming destabilizes plant community biomass production. J. Ecol. 109, 1607–1617 (2021).Article 

Google Scholar 
Wang, X. et al. Response of greenhouse gases emission fluxes to long-term warming in alpine meadow of northern Tibet. Chin. J. Agrometeorol. 39, 152–161 (2018).
Google Scholar 
Klein, J. A., Harte, J. & Zhao, X. Q. Experimental warming causes large and rapid species loss, dampened by simulated grazing, on the Tibetan Plateau. Ecol. Lett. 7, 1170–1179 (2004).Article 

Google Scholar 
Zhang, C. H. et al. Recovery of plant species diversity during long-term experimental warming of a species-rich alpine meadow community on the Qinghai–Tibet Plateau. Biol. Conserv. 213, 218–224 (2017).Article 

Google Scholar 
Li, X. et al. Responses of biotic interactions of dominant and subordinate species to decadal warming and simulated rotational grazing in Tibetan alpine meadow. Sci. China Life Sci. 61, 849–859 (2018).Article 

Google Scholar 
Klein, J. A., Harte, J. & Zhao, X. Q. Dynamic and complex microclimate responses to warming and grazing manipulations. Glob. Chang. Biol. 11, 1440–1451 (2005).Article 

Google Scholar 
Chen, J. et al. Warming effects on ecosystem carbon fluxes are modulated by plant functional types. Ecosystems 20, 515–526 (2017).Article 

Google Scholar 
Zhang, Y. Q. & Welker, J. M. Tibetan alpine tundra responses to simulated changes in climate: aboveground biomass and community responses. Arct. Alp. Res. 28, 203–209 (1996).Article 

Google Scholar 
Liu, H. et al. Shifting plant species composition in response to climate change stabilizes grassland primary production. Proc. Natl Acad. Sci. USA 115, 4051–4056 (2018). This work demonstrates that shifting plant species composition in response to climate change may have stabilized primary production in this high-elevation ecosystem, but also causes a shift from above-ground to below-ground productivity.Article 

Google Scholar 
Ganjurjav, H. et al. Differential response of alpine steppe and alpine meadow to climate warming in the central Qinghai–Tibetan Plateau. Agric. For. Meteorol. 223, 233–240 (2016).Article 

Google Scholar 
Jiang, F., Wei, X., Kang, B. & Shao, X. Effects of warming on alpine meadow diversity and primary productivity. Acta Agrestia Sin. 27, 298–305 (2019).
Google Scholar 
Zong, N. et al. Responses of plant community structure and species composition to warming and N addition in an alpine meadow, northern Tibetan Plateau, China. Chin. J. Appl. Ecol. 27, 3739–3748 (2016).
Google Scholar 
Peng, F. et al. Warming-induced shift towards forbs and grasses and its relation to the carbon sequestration in an alpine meadow. Environ. Res. Lett. https://doi.org/10.1088/1748-9326/aa6508 (2017).Article 

Google Scholar 
Dorji, T. et al. Grazing and spring snow counteract the effects of warming on an alpine plant community in Tibet through effects on the dominant species. Agric. For. Meteorol. 263, 188–197 (2018).Article 

Google Scholar 
Xue, X., Peng, F., You, Q., Xu, M. & Dong, S. Belowground carbon responses to experimental warming regulated by soil moisture change in an alpine ecosystem of the Qinghai–Tibet Plateau. Ecol. Evol. 5, 4063–4078 (2015).Article 

Google Scholar 
Jing, X. et al. No temperature acclimation of soil extracellular enzymes to experimental warming in an alpine grassland ecosystem on the Tibetan Plateau. Biogeochemistry 117, 39–54 (2014).Article 

Google Scholar 
Yu, C. Q., Shen, Z. X., Zhang, X. Z., Sun, W. & Fu, G. Response of soil C and N, dissolved organic C and N, and inorganic N to short-term experimental warming in an alpine meadow on the Tibetan Plateau. Sci. World J. 2014, 152576 (2014).
Google Scholar 
Zhang, Y. et al. Simulated warming enhances the responses of microbial N transformations to reactive N input in a Tibetan alpine meadow. Environ. Int. 141, 105795 (2020).Article 

Google Scholar 
Jia, J. et al. Climate warming alters subsoil but not topsoil carbon dynamics in alpine grassland. Glob. Chang. Biol. 25, 4383–4393 (2019).Article 

Google Scholar 
Ding, X. L. et al. Warming increases microbial residue contribution to soil organic carbon in an alpine meadow. Soil. Biol. Biochem. 135, 13–19 (2019).Article 

Google Scholar 
Guan, S. et al. Climate warming impacts on soil organic carbon fractions and aggregate stability in a Tibetan alpine meadow. Soil. Biol. Biochem. 116, 224–236 (2018).Article 

Google Scholar 
Rui, Y. C. et al. Warming and grazing affect soil labile carbon and nitrogen pools differently in an alpine meadow of the Qinghai–Tibet Plateau in China. J. Soils Sediment. 11, 903–914 (2011).Article 

Google Scholar 
Heng, T., Wu, J., Xie, S. & Wu, M. The responses of soil C and N, microbial biomass C or N under alpine meadow of Qinghai–Tibet Plateau to the change of temperature and precipitation. Chin. Agric. Sci. Bull. 27, 425–430 (2011).
Google Scholar 
Li, N., Wang, G., Yang, Y., Gao, Y. & Liu, G. Plant production, and carbon and nitrogen source pools, are strongly intensified by experimental warming in alpine ecosystems in the Qinghai–Tibet Plateau. Soil. Biol. Biochem. 43, 942–953 (2011).Article 

Google Scholar 
Zhao, J. X. et al. Increased precipitation offsets the negative effect of warming on plant biomass and ecosystem respiration in a Tibetan alpine steppe. Agric. For. Meteorol. https://doi.org/10.1016/j.agrformet.2019.107761 (2019). This work shows that increased precipitation offsets the negative effect of warming on plant biomass and ecosystem respiration in a Tibetan alpine steppe.Article 

Google Scholar 
Wu, H. et al. Effects of increased precipitation combined with nitrogen addition and increased temperature on methane fluxes in alpine meadows of the Tibetan Plateau. Sci. Total Environ. 705, 135818 (2020).Article 

Google Scholar 
Shi, F. S., Chen, H., Chen, H. F., Wu, Y. & Wu, N. The combined effects of warming and drying suppress CO2 and N2O emission rates in an alpine meadow of the eastern Tibetan Plateau. Ecol. Res. 27, 725–733 (2012).Article 

Google Scholar 
Fu, G., Zhang, H. R. & Sun, W. Response of plant production to growing/non-growing season asymmetric warming in an alpine meadow of the northern Tibetan Plateau. Sci. Total Environ. 650, 2666–2673 (2019).Article 

Google Scholar 
Xiong, Q. L. et al. Warming and nitrogen deposition are interactive in shaping surface soil microbial communities near the alpine timberline zone on the eastern Qinghai–Tibet Plateau, southwestern China. Appl. Soil. Ecol. 101, 72–83 (2016).Article 

Google Scholar 
Wang, C. et al. Responses of plant leaf traits to simulated rainfall changes in alpine region. Acta Ecol. Sin. 41, 1–13 (2021).Article 

Google Scholar 
Zhang, K. et al. Effects of short-term warming and altered precipitation on soil microbial communities in alpine grassland of the Tibetan Plateau. Front. Microbiol. 7, 1032 (2016).
Google Scholar 
Evans, R. D. & Ehleringer, J. R. Water and nitrogen dynamics in an arid woodland. Oecologia 99, 233–242 (1994).Article 

Google Scholar 
Swap, R. J., Aranibar, J. N., Dowty, P. R., Gilhooly, W. P. III & Macko, S. A. Natural abundance of 13C and 15N in C3 and C4 vegetation of southern Africa: patterns and implications. Glob. Chang. Biol. 10, 350–358 (2004).Article 

Google Scholar 
Jia, Y. et al. Spatial and decadal variations in inorganic nitrogen wet deposition in China induced by human activity. Sci. Rep. 4, 3763–3763 (2014).Article 

Google Scholar 
Liu, Y. W., Xu, R., Wang, Y. S., Pan, Y. P. & Piao, S. L. Wet deposition of atmospheric inorganic nitrogen at five remote sites in the Tibetan Plateau. Atmos. Chem. Phys. 15, 11683–11700 (2015).Article 

Google Scholar 
Wang, W. et al. Atmospheric nitrogen deposition to a southeast Tibetan forest ecosystem. Atmosphere https://doi.org/10.3390/atmos11121331 (2020).Article 

Google Scholar 
Zou, X. et al. Ice-core based assessment of nitrogen deposition in the central Tibetan Plateau over the last millennium. Sci. Total Environ. https://doi.org/10.1016/j.scitotenv.2021.152692 (2022).Article 

Google Scholar 
Aerts, R., Wallen, B. & Malmer, N. Growth-limiting nutrients in sphagnum-dominated bogs subject to low and high amospheric nitrogen supply. J. Ecol. 80, 131–140 (1992).Article 

Google Scholar 
Bai, Y. F. et al. Tradeoffs and thresholds in the effects of nitrogen addition on biodiversity and ecosystem functioning: evidence from Inner Mongolia grasslands. Glob. Chang. Biol. 16, 358–372 (2010).Article 

Google Scholar 
Du, Y. Population statistics of Qinghai–Tibet Plateau (1952–2016) (National Tibetan Plateau Data Center, 2019).Zhang, Y. J., Zhang, X. Q., Wang, X. Y., Liu, N. & Kan, H. M. Establishing the carrying capacity of the grasslands of China: a review. Rangel. J. 36, 1–9 (2014).Article 

Google Scholar 
Bardgett, R. D. et al. Combatting global grassland degradation. Nat. Rev. Earth Environ. 2, 720–735 (2021). This work shows that socio-ecological solutions are needed to combat degradation and promote restoration.Article 

Google Scholar 
Liu, M. et al. Effects of rotational and continuous overgrazing on newly assimilated C allocation. Biol. Fertil. Soils 57, 193–202 (2021).Article 

Google Scholar 
Yang, X. X. et al. Different responses of soil element contents and their stoichiometry (C:N:P) to yak grazing and Tibetan sheep grazing in an alpine grassland on the eastern Qinghai–Tibetan Plateau. Agric. Ecosyst. Environ. https://doi.org/10.1016/j.agee.2019.106628 (2019).Article 

Google Scholar 
Lin, B., Zhao, X. R., Zheng, Y., Qi, S. & Liu, X. Z. Effect of grazing intensity on protozoan community, microbial biomass, and enzyme activity in an alpine meadow on the Tibetan Plateau. J. Soils Sediment. 17, 2752–2762 (2017).Article 

Google Scholar 
Ma, W. M., Ding, K. Y. & Li, Z. W. Comparison of soil carbon and nitrogen stocks at grazing-excluded and yak grazed alpine meadow sites in Qinghai–Tibetan Plateau, China. Ecol. Eng. 87, 203–211 (2016).Article 

Google Scholar 
Li, W. et al. Effects of grazing regime on vegetation structure, productivity, soil quality, carbon and nitrogen storage of alpine meadow on the Qinghai–Tibetan Plateau. Ecol. Eng. 98, 123–133 (2017).Article 

Google Scholar 
Sun, J. et al. Effects of grazing regimes on plant traits and soil nutrients in an alpine steppe, northern Tibetan Plateau. PLoS ONE 9, e108821 (2014).Article 

Google Scholar 
Niu, K. C., He, J. S. & Lechowicz, M. J. Grazing-induced shifts in community functional composition and soil nutrient availability in Tibetan alpine meadows. J. Appl. Ecol. 53, 1554–1564 (2016).Article 

Google Scholar 
Luan, J. W. et al. Different grazing removal exclosures effects on soil C stocks among alpine ecosystems in east Qinghai–Tibet Plateau. Ecol. Eng. 64, 262–268 (2014).Article 

Google Scholar 
Wei, D. et al. Responses of CO2, CH4 and N2O fluxes to livestock exclosure in an alpine steppe on the Tibetan Plateau, China. Plant Soil 359, 45–55 (2012).Article 

Google Scholar 
Shen, H. et al. Grazing enhances plant photosynthetic capacity by altering soil nitrogen in alpine grasslands on the Qinghai–Tibetan Plateau. Agric. Ecosyst. Environ. 280, 161–168 (2019).Article 

Google Scholar 
Jiang, L. et al. Grazing modifies inorganic and organic nitrogen uptake by coexisting plant species in alpine grassland. Biol. Fertil. Soils 52, 211–221 (2016).Article 

Google Scholar 
Sun, Y., Schleuss, P. M., Pausch, J., Xu, X. L. & Kuzyakov, Y. Nitrogen pools and cycles in Tibetan Kobresia pastures depending on grazing. Biol. Fertil. Soils 54, 569–581 (2018).Article 

Google Scholar 
Chen, B. et al. The impact of climate change and anthropogenic activities on alpine grassland over the Qinghai–Tibet Plateau. Agric. For. Meteorol. 189-190, 11–18 (2014).Article 

Google Scholar 
Wang, Z. Q. et al. Quantitative assess the driving forces on the grassland degradation in the Qinghai–Tibet Plateau, in China. Ecol. Inform. 33, 32–44 (2016).Article 

Google Scholar 
Huang, K. et al. The influences of climate change and human activities on vegetation dynamics in the Qinghai–Tibet Plateau. Remote Sens. 8, 876 (2016).Article 

Google Scholar 
Li, L. et al. Increasing sensitivity of alpine grasslands to climate variability along an elevational gradient on the Qinghai–Tibet Plateau. Sci. Total Environ. 678, 21–29 (2019).Article 

Google Scholar 
Wang, Z. et al. Vegetation expansion on the Tibetan Plateau and its relationship with climate change. Remote. Sens. https://doi.org/10.3390/rs12244150 (2020).Article 

Google Scholar 
Wu, J. et al. Disentangling climatic and anthropogenic contributions to nonlinear dynamics of alpine grassland productivity on the Qinghai–Tibetan Plateau. J. Environ. Manag. 281, 111875 (2021).Article 

Google Scholar 
Fu, G., Shen, Z. X. & Zhang, X. Z. Increased precipitation has stronger effects on plant production of an alpine meadow than does experimental warming in the northern Tibetan Plateau. Agric. For. Meteorol. 249, 11–21 (2018).Article 

Google Scholar 
Hu, Y. et al. Effect of increasing precipitation and warming on microbial community in Tibetan alpine steppe. Environ. Res. 189, 109917 (2020).Article 

Google Scholar 
Ma, Z. et al. Climate warming reduces the temporal stability of plant community biomass production. Nat. Commun. 8, 15378 (2017).Article 

Google Scholar 
Bai, W., Xi, J. & Wang, G. Effects of short-term warming and nitrogen addition on CO2 emission during growing season in an alpine swamp meadow ecosystem of Qinghai–Tibetan Plateau. Chin. J. Ecol. 38, 927–936 (2019).
Google Scholar 
Bai, W., Wang, G. X., Xi, J. Y., Liu, Y. W. & Yin, P. S. Short-term responses of ecosystem respiration to warming and nitrogen addition in an alpine swamp meadow. Eur. J. Soil Biol. 92, 16–23 (2019).Article 

Google Scholar 
Ge, Y. et al. Effects of warming and nitrogen addition on plant community structure and species diversity of alpine meadow in northern Tibet. Ecol. Environ. Sci. 28, 2185–2191 (2019).
Google Scholar 
Zong, N. et al. Effects of warming and nitrogen addition on community production and biomass allocation in an alpine meadow. Chin. J. Appl. Ecol. 29, 59–67 (2018).
Google Scholar 
Zhu, X. X. et al. Effects of warming, grazing/cutting and nitrogen fertilization on greenhouse gas fluxes during growing seasons in an alpine meadow on the Tibetan Plateau. Agric. For. Meteorol. 214, 506–514 (2015).Article 

Google Scholar 
Fu, G. et al. Clipping alters the response of biomass production to experimental warming: a case study in an alpine meadow on the Tibetan Plateau, China. J. Mt. Sci. 12, 935–942 (2015).Article 

Google Scholar 
Chen, S. P. et al. Plant diversity enhances productivity and soil carbon storage. Proc. Natl Acad. Sci. USA. 115, 4027–4032 (2018).Article 

Google Scholar 
Wu, J. S. et al. Effects of livestock exclusion and climate change on aboveground biomass accumulation in alpine pastures across the northern Tibetan Plateau. Chin. Sci. Bull. 59, 4332–4340 (2014).Article 

Google Scholar 
Sun, J., Cheng, G. W., Li, W. P., Sha, Y. K. & Yang, Y. C. On the variation of NDVI with the principal climatic elements in the Tibetan Plateau. Remote Sens. 5, 1894–1911 (2013).Article 

Google Scholar 
Sun, J. et al. Reconsidering the efficiency of grazing exclusion using fences on the Tibetan Plateau. Sci. Bull. 65, 1405–1414 (2020). This work finds that fencing enclosures lead to some negative impacts, such as hindering wildlife movement.Article 

Google Scholar 
Yu, C. et al. Grazing exclusion to recover degraded alpine pastures needs scientific assessments across the northern Tibetan Plateau. Sustainability https://doi.org/10.3390/su8111162 (2016).Article 

Google Scholar 
Wu, J. & Wang, X. Effect of enclosure ages on community characters and biomas of the degraded alpine steppe at the northern Tibet. Acta Agrestia Sin. 25, 261–266 (2017).
Google Scholar 
Zhao, J. X., Luo, T. X., Li, R. C., Li, X. & Tian, L. H. Grazing effect on growing season ecosystem respiration and its temperature sensitivity in alpine grasslands along a large altitudinal gradient on the central Tibetan Plateau. Agric. For. Meteorol. 218, 114–121 (2016).Article 

Google Scholar 
Deng, L., Sweeney, S. & Shangguan, Z. P. Grassland responses to grazing disturbance: plant diversity changes with grazing intensity in a desert steppe. Grass Forage Sci. 69, 524–533 (2014).Article 

Google Scholar 
Yuan, Z., Epstein, H. & Li, G. Grazing exclusion did not affect soil properties in alpine meadows in the Tibetan permafrost region. Ecol. Eng. https://doi.org/10.1016/j.ecoleng.2019.105657 (2020).Article 

Google Scholar 
Zhang, W. et al. Effects of banning grazing and delaying grazing on species diversity and biomass of alpine meadow in northern Tibet. J. Agric. Sci. Technol. 15, 143–149 (2013).
Google Scholar 
Miao, F., Guo, Y., Miao, P., Guo, Z. & Shen, Y. The northeast edge of Qinghai–Tibet Plateau area of alpine meadow community characteristics respond to nurture. Acta Prataculture Sin. 21, 11–16 (2012).
Google Scholar 
Lu, X. et al. Short-term grazing exclusion has no impact on soil properties and nutrients of degraded alpine grassland in Tibet, China. Solid Earth 6, 1195–1205 (2015).Article 

Google Scholar 
Gao, Y. H., Zeng, X. Y., Schumann, M. & Chen, H. Effectiveness of exclosures on restoration of degraded alpine meadow in the eastern Tibetan Plateau. Arid. Land. Res. Manag. 25, 164–175 (2011).Article 

Google Scholar 
Yao, X. X. et al. Effects of long term fencing on biomass, coverage, density, biodiversity and nutritional values of vegetation community in an alpine meadow of the Qinghai–Tibet Plateau. Ecol. Eng. 130, 80–93 (2019).Article 

Google Scholar 
Chen, W., Chang, H. & Liu, R. Fractal features of soil particle size distributions and their implications for indicating enclosure management in a semiarid grassland ecosystem. Pol. J. Ecol. 68, 132–144 (2020).
Google Scholar 
Smith, D., King, R. & Allen, B. L. Impacts of exclusion fencing on target and non-target fauna: a global review. Biol. Rev. 95, 1590–1606 (2020).Article 

Google Scholar 
Zhang, Y. et al. Assessment of effectiveness of nature reserves on the Tibetan Plateau based on net primary production and the large sample comparison method. J. Geogr. Sci. 26, 27–44 (2016).Article 

Google Scholar 
Hu, J. Research on the status quo and problems of natural reserve construction in Qinghai–Tibet Plateau. Environ. Dev. 32, 204–206 (2020).
Google Scholar 
Shao, Q., Fan, J., Liu, J., Cao, W. & Liu, L. Target-based assessment on effects of first-stage ecological conservation and restoration project in three-river source region, China and policy recommendations. Bull. Chin. Acad. Sci. 32, 35–44 (2017).
Google Scholar 
Liu, F. & Zeng, Y. N. Spatial–temporal change in vegetation net primary productivity and its response to climate and human activities in Qinghai Plateau in the past 16 years. Acta Ecol. Sin. 39, 1528–1540 (2019).
Google Scholar 
Zhang, Y., Wu, X., Qi, W., Li, S. & Bai, W. Characteristics and protection effectiveness of nature reserves on the Tibetan Plateau, China. Resources. Science 37, 1455–1464 (2015).
Google Scholar 
Buckley, M. C. & Crone, E. E. Negative off-site impacts of ecological restoration: understanding and addressing the conflict. Conserv. Biol. 22, 1118–1124 (2008).Article 

Google Scholar 
Cao, S. X. & Zhang, J. Political risks arising from the impacts of large-scale afforestation on water resources of the Tibetan Plateau. Gondwana Res. 28, 898–903 (2015).Article 

Google Scholar 
Li, Y. & Li, W. Why “Balance of Forage and Livestock” system failed to reach sustainable grassland utilization. China Agric. Univ. J. Soc. Sci. Ed. 29, 124–131 (2012).
Google Scholar 
Du, S. A Study on the Satisfaction Degree of Herdsmen’s Income and Grassland Ecological Compensation Policy. Master thesis, Lanzhou Univ. (2019).Yu, H., Wang, G., Yang, Y. & Lü, Y. Concept of grassland green carrying capacity and its application framework in national park. Acta Ecol. Sin. 40, 7248–7254 (2020).
Google Scholar 
Deng, Y. & Li, C. The investigation and research about the Farmland Retirement and Environment Project in the Yangtze River headwaters area. Ecol. Econ. 2, 77–80 (2006).
Google Scholar 
Zhou, Q. et al. Analysis on the relationship between grassland area and forage-livestock balance in Qinghai–Tibet Plateau. Chin. J. Grassl. 41, 110–117 (2019).
Google Scholar 
Li, Y. et al. Awareness and reaction of herdsmen to the policy of returning grazing land to grasslands in the Changtang Plateau,Tibet. Pratacultural Sci. 30, 788–794 (2013).
Google Scholar 
Fan, J. et al. Third pole national park group construction is scientific choice for implementing strategy of major function zoning and green development in Tibet, China. Bull. Chin. Acad. Sci. 32, 932–944 (2017).
Google Scholar 
Xu, Z., Cheng, S. & Gao, L. Impacts of herders sedentarization on regional spatial heterogeneity and grassland ecosystem change in pastoral area. J. Arid. Land. Resour. Environ. 31, 8–13 (2017).
Google Scholar 
Ptackova, J. Sedentarisation of Tibetan nomads in China: implementation of the Nomadic settlement project in the Tibetan Amdo area; Qinghai and Sichuan Provinces. Pastoralism https://doi.org/10.1186/2041-7136-1-4 (2011).Article 

Google Scholar 
Weber, K. T. & Horst, S. Desertification and livestock grazing: the roles of sedentarization, mobility and rest. Pastoralism https://doi.org/10.1186/2041-7136-1-19 (2011).Article 

Google Scholar 
Zhang, J. et al. Ecological consequence of nomad settlement policy in the pasture area of Qinghai–Tibetan Plateau: from plant and soil perspectives. J. Environ. Manage. https://doi.org/10.1016/j.jenvman.2020.110114 (2020).Article 

Google Scholar 
Li, C. X., de Jong, R., Schmid, B., Wulf, H. & Schaepman, M. E. Spatial variation of human influences on grassland biomass on the Qinghai–Tibetan Plateau. Sci. Total Environ. 665, 678–689 (2019).Article 

Google Scholar 
Kuang, W. Dataset of Urban Distribution, Urban Population and Built-up Area in Tibetan Plateau (2000–2015) (National Tibetan Plateau Data Center, 2021).Tian, L. & Chen, J. Urban expansion inferenced by ecosystem production on the Qinghai–Tibet plateau. Environ. Res. Lett. https://doi.org/10.1088/1748-9326/ac3178 (2022).Article 

Google Scholar 
Liu, Y. & Lu, C. Quantifying grass coverage trends to identify the hot plots of grassland degradation in the Tibetan Plateau during 2000–2019. Int. J. Environ. Res. Public Health https://doi.org/10.3390/ijerph18020416 (2021).Article 

Google Scholar 
Tang, L. et al. Warming counteracts grazing effects on the functional structure of the soil microbial community in a Tibetan grassland. Soil. Biol. Biochem. 134, 113–121 (2019).Article 

Google Scholar 
Zhong, L. Tourism Planning Case in Tibetan Plateau (China Tourism Press, 2018).La, M. Discussion of the coordinated development of tourism development and ecological Environment Protection in Tibetan. Soc. Sci. Res. 6, 118–120, (2013).
Google Scholar 
Zhuang, M. et al. Opportunities for household energy on the Qinghai–Tibet Plateau in line with United Nations’ Sustainable Development Goals. Renew. Sustain. Energy Rev. https://doi.org/10.1016/j.rser.2021.110982 (2021).Article 

Google Scholar 
Ruess, R. W. & Mcnaughton, S. J. Grazing and the dynamics of nutrient and energy regulated microbial processes in the serengeti grasslands. Oikos 49, 101–110 (1987).Article 

Google Scholar 
Li, M. et al. Changes in plant species richness distribution in Tibetan alpine grasslands under different precipitation scenarios. Glob. Ecol. Conserv. 21, 13 (2020).
Google Scholar 
Wang, Z. et al. Quantitative assess the driving forces on the grassland degradation in the Qinghai–Tibet Plateau, in China. Ecol. Inform. 33, 32–44 (2016).Article 

Google Scholar 
Muñoz Sabater, J. ERA5-Land monthly averaged data from 1981 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS), https://doi.org/10.24381/cds.68d2bb30 (2019).Abatzoglou, J. T., Dobrowski, S. Z., Parks, S. A. & Hegewisch, K. C. Terraclimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958–2015. Sci. Data 5, 170191 (2018).Article 

Google Scholar  More

Metcalf, C. J. & Pavard, S. Why evolutionary biologists should be demographers. Trends Ecol. Evol. 22, 205–212 (2007).PubMed 
Article 

Google Scholar 
French, J. C., Riris, P., Fernandez-Lopez de Pablo, J., Lozano, S. & Silva, F. A manifesto for palaeodemography in the twenty-first century. Philos. Trans. R. Soc. Lond. B Biol. Sci. 376, 20190707 (2021).PubMed 
Article 

Google Scholar 
French, J. C. Demography and the Palaeolithic archaeological record. J. Archaeol. Method Th. 23, 150–199 (2016).Article 

Google Scholar 
Henrich, J. Demography and cultural evolution: how adaptive cultural processes can produce maladaptive losses – The Tasmanian case. Am. Antiquity 69, 197–214 (2004).Article 

Google Scholar 
Powell, A., Shennan, S. & Thomas, M. G. Late Pleistocene demography and the appearance of modern human behavior. Science 324, 1298–1301 (2009).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Shennan, S. Demography and cultural innovation: a model and its implications for the emergence of modern human culture. Camb. Archaeol. J. 11, 5–16 (2001).Article 

Google Scholar 
Jorgensen, E. K. The palaeodemographic and environmental dynamics of prehistoric Arctic Norway: an overview of human-climate covariation. Quat. Int. 549, 36–51 (2020).Article 

Google Scholar 
Jorgensen, E. K. & Riede, F. Convergent catastrophes and the termination of the Arctic Norwegian Stone Age: a multi-proxy assessment of the demographic and adaptive responses of mid-Holocene collectors to biophysical forcing. Holocene 29, 1782–1800 (2019).ADS 
Article 

Google Scholar 
Riede, F. Lateglacial and Postglacial Pioneers in Northern Europe (Archaeopress, 2014).Tallavaara, M. & Seppä, H. Did the mid-Holocene environmental changes cause the boom and bust of hunter-gatherer population size in eastern Fennoscandia? Holocene 22, 215–225 (2011).ADS 
Article 

Google Scholar 
Kavanagh, P. H. et al. Hindcasting global population densities reveals forces enabling the origin of agriculture. Nat. Hum. Behav. 2, 478–484 (2018).PubMed 
Article 

Google Scholar 
Tallavaara, M., Luoto, M., Korhonen, N., Jarvinen, H. & Seppa, H. Human population dynamics in Europe over the Last Glacial Maximum. Proc. Natl Acad. Sci. USA 112, 8232–8237 (2015).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Bliege Bird, R. & Codding, B. F. Promise and peril of ecological and evolutionary modelling using cross-cultural datasets. Nat. Ecol. Evol. 6, 1–3 (2021).Hamilton, M. J. & Tallavaara, M. Statistical inference, scale and noise in comparative anthropology. Nat. Ecol. Evol. 6, 122 (2022).PubMed 
Article 

Google Scholar 
Gurven, M. D. & Davison, R. J. Periodic catastrophes over human evolutionary history are necessary to explain the forager population paradox. Proc. Natl Acad. Sci. USA 116, 12758–12766 (2019).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Tallavaara, M. & Jorgensen, E. K. Why are population growth rate estimates of past and present hunter-gatherers so different? Philos. T R Soc. B 376, 20190708 (2021).Blackman, F. F. Optima and limiting factors. With two diagrams in the text. Ann. Bot. Lond. 19, 281–296 (1905).Article 

Google Scholar 
Maier, A. et al. Cultural evolution and environmental change in Central Europe between 40 and 15 ka. Quat. Int. 581-582, 225–240 (2021).Article 

Google Scholar 
Zhu, D., Galbraith, E. D., Reyes-Garcia, V. & Ciais, P. Global hunter-gatherer population densities constrained by influence of seasonality on diet composition. Nat. Ecol. Evol. 5, 1536 (2021).PubMed 
PubMed Central 
Article 

Google Scholar 
Binford, L. R. Archaeology as anthropology. Am. Antiquity 28, 217–225 (1962).Article 

Google Scholar 
Lowe, J. J. et al. Synchronisation of palaeoenvironmental events in the North Atlantic region during the Last Termination: a revised protocol recommended by the INTIMATE group. Quat. Sci. Rev. 27, 6–17 (2008).ADS 
Article 

Google Scholar 
Bocquet-Appel, J. P., Demars, P. Y., Noiret, L. & Dobrowsky, D. Estimates of upper Palaeolithic meta-population size in Europe from archaeological data. J. Archaeol. Sci. 32, 1656–1668 (2005).Article 

Google Scholar 
Fort, J., Pujol, T. & Cavalli-Sforza, L. L. Palaeolithic populations and waves of advance (Human range expansions). Camb. Archaeol. J. 14, 53–61 (2004).Article 

Google Scholar 
Schmidt, I. et al. Approaching prehistoric demography: proxies, scales and scope of the Cologne Protocol in European contexts. Philos. Trans. R. Soc. Lond. B Biol. Sci. 376, 20190714 (2021).PubMed 
Article 

Google Scholar 
de Pablo, J. F. L. et al. Palaeodemographic modelling supports a population bottleneck during the Pleistocene-Holocene transition in Iberia. Nat. Commun. 10, 1872 (2019).Binford, L. R. Constructing Frames of Reference: An Analytical Method for Archaeological Theory Building Using Ethnographic and Environmental Data Sets. (Univ. California Press, 2019).Johnson, A. L. Exploring adaptive variation among hunter-gatherers with Binford’s frames of reference. J. Archaeol. Res. 22, 1–42 (2014).Article 

Google Scholar 
Graham, M. H. Confronting multicollinearity in ecological multiple regression. Ecology 84, 2809–2815 (2003).Article 

Google Scholar 
Tallavaara, M., Eronen, J. T. & Luoto, M. Productivity, biodiversity, and pathogens influence the global hunter-gatherer population density. Proc. Natl Acad. Sci. USA 115, 1232–1237 (2018).CAS 
PubMed 
Article 

Google Scholar 
Cade, B. S. & Noon, B. R. A gentle introduction to quantile regression for ecologists. Front Ecol. Environ. 1, 412–420 (2003).Article 

Google Scholar 
Cade, B. S., Terrell, J. W. & Schroeder, R. L. Estimating effects of limiting factors with regression quantiles. Ecology 80, 311–323 (1999).Article 

Google Scholar 
Burman, P., Chow, E. & Nolan, D. A cross-validatory method for dependent data. Biometrika 81, 351–358 (1994).MathSciNet 
MATH 
Article 

Google Scholar 
Burke, K. D. et al. Differing climatic mechanisms control transient and accumulated vegetation novelty in Europe and eastern North America. Philos. Trans. R. Soc. Lond. B Biol. Sci. 374, 20190218 (2019).PubMed 
PubMed Central 
Article 

Google Scholar 
Currie, D. J. Energy and large-scale patterns of animal-species and plant-species richness. Am. Nat. 137, 27–49 (1991).Article 

Google Scholar 
Franklin, J. Mapping Species Distributions: Spatial Inference and Prediction (Cambridge Univ. Press, 2010).Harcourt, A. Human Biogeography (Univ. California Press, 2012).Marlowe, F. W. Hunter-gatherers and human evolution. Evol. Anthropol. 14, 54–67 (2005).Article 

Google Scholar 
Belovsky, G. E. An optimal foraging-based model of hunter-gatherer population-dynamics. J. Anthropol. Archaeol. 7, 329–372 (1988).Article 

Google Scholar 
Williams, J. W. & Jackson, S. T. Novel climates, no-analog communities, and ecological surprises. Front. Ecol. Environ. 5, 475–482 (2007).Article 

Google Scholar 
Ohlemuller, R. Climate. Running out of climate space. Science 334, 613–614 (2011).ADS 
PubMed 
Article 

Google Scholar 
Williams, J. W., Jackson, S. T. & Kutzbach, J. E. Projected distributions of novel and disappearing climates by 2100 AD. Proc. Natl Acad. Sci. USA 104, 5738–5742 (2007).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Warren, D. L., Glor, R. E. & Turelli, M. Environmental niche equivalency versus conservatism: quantitative approaches to niche evolution. Evolution 62, 2868–2883 (2008).PubMed 
Article 

Google Scholar 
Broennimann, O. et al. Measuring ecological niche overlap from occurrence and spatial environmental data. Glob. Ecol. Biogeogr. 21, 481–497 (2012).Article 

Google Scholar 
Warren, D. L., Cardillo, M., Rosauer, D. F. & Bolnick, D. I. Mistaking geography for biology: inferring processes from species distributions. Trends Ecol. Evol. 29, 572–580 (2014).PubMed 
Article 

Google Scholar 
Wobst, H. M. The archaeo-ethnology of hunter-gatherers or the tyranny of the ethnographic record in archaeology. Am Antiquity 43, 303–309 (1978).Maier, A. et al. Demographic estimates of hunter-gatherers during the Last Glacial Maximum in Europe against the background of palaeoenvironmental data. Quat. Int. 425, 49–61 (2016).Article 

Google Scholar 
Riede, F. Oxford Handbook of the Archaeology and Anthropology of Hunter-Gatherers (Oxford Univ. Press, 2014).Jochim, M., Herhahn, C. & Starr, H. The Magdalenian colonization of southern Germany. Am. Anthropol. 101, 129–142 (1999).Article 

Google Scholar 
Arts, N. & Deeben, J. On the Northwestern Border of Late Magdalenian Territory: Ecology and Archaeology of Early Late Glacial Band Societies in Northwestern Europe. In Late Glacial in Central Europe. Culture and Environment. (eds Burdukiewicz, J. M. & Kobusiewicz, M.) (Polska Akademia Nauk, Warszawa 1987).Maier, A. Population and settlement dynamics from the Gravettian to the Magdalenian. Mitteilungen der Ges. f.ür. Urgesch. 26, 83–101 (2017).
Google Scholar 
Maier, A., Liebermann, C. & Pfeifer, S. J. Beyond the Alps and Tatra Mountains-the 20-14 ka repopulation of the northern mid-latitudes as inferred from palimpsests deciphered with keys from Western and Central Europe. J. Paleolit. Archaeol. 3, 398–452 (2020).Article 

Google Scholar 
Gamble, C., Davies, W., Pettitt, P. & Richards, M., Climate change. and evolving human diversity in Europe during the last glacial. Philos. Trans. R. Soc. Lond. B Biol. Sci. 359, 243–253 (2004).PubMed 
PubMed Central 
Article 

Google Scholar 
Housley, R. A., Gamble, C. S., Street, M. & Pettitt, P. Proceedings of the Prehistoric Society. (Cambridge Univ. Press).Bellwood, P. S. First Farmers: the Origins of Agricultural Societies. (Blackwell, Oxford 2005).d’Errico, F. et al. The origin and evolution of sewing technologies in Eurasia and North America. J. Hum. Evol. 125, 71–86 (2018).PubMed 
Article 

Google Scholar 
Moseler, F. Brandstrukturen im späten Magdalénien: Betrieb, Nutzung und Funktion (Verlag des Römisch-Germanischen Zentralmuseums, 2020).Simova, I. & Storch, D. The enigma of terrestrial primary productivity: measurements, models, scales and the diversity-productivity relationship. Ecography 40, 239–252 (2017).Rosenzweig, M. L. Net primary productivity of terrestrial communities – prediction from climatological data. Am. Nat. 102, 67 (1968).Article 

Google Scholar 
Jensen, H. J. & Møberg, T. Et røgeri fra ældre stenalder ved Bølling Sø? Midtjyske Fortaellinger 2007, 51–62 (2008).Holst, D. Hazelnut economy of early Holocene hunter-gatherers: a case study from Mesolithic Duvensee, northern Germany. J. Archaeol. Sci. 37, 2871–2880 (2010).Article 

Google Scholar 
Boethius, A. Something rotten in Scandinavia: the world’s earliest evidence of fermentation. J. Archaeol. Sci. 66, 169–180 (2016).Article 

Google Scholar 
Dyson‐Hudson, R. & Smith, E. A. Human territoriality: an ecological reassessment. Am. Anthropol. 80, 21–41 (1978).Article 

Google Scholar 
Finlayson, C. The water optimisation hypothesis and the human occupation of the mid-latitude belt in the Pleistocene. Quat. Int 300, 22–31 (2013).Article 

Google Scholar 
Laland, K. N. & Brown, G. R. Niche construction, human behavior, and the adaptive-lag hypothesis. Evol. Anthropol. 15, 95–104 (2006).Article 

Google Scholar 
Laland, K. N. & O’Brien, M. J. Niche construction theory and archaeology. J. Archaeol. Method Th. 17, 303–322 (2010).Article 

Google Scholar 
Riede, F. Handbook of Evolutionary Research in Archaeology (Springer, 2019).Jöris, O. & Terberger, T. Zur Rekonstruktion eines Zeltes mit Trapezförmigem Grundriss am Magdalénien-Fundplatz Gönnersdorf/Mittelrhein: Eine» Quadratur des Kreises «? Arch.äologisches Korrespondenzblatt 31, 163–172 (2001).
Google Scholar 
Salomon, H., Vignaud, C., Lahlil, S. & Menguy, N. Solutrean and Magdalenian ferruginous rocks heat-treatment: accidental and/or deliberate action? J. Archaeol. Sci. 55, 100–112 (2015).CAS 
Article 

Google Scholar 
Nakazawa, Y., Straus, L. G., Gonzalez-Morales, M. R., Solana, D. C. & Saiz, J. C. On stone-boiling technology in the Upper Paleolithic: behavioral implications from an Early Magdalenian hearth in El Miron Cave, Cantabria, Spain. J. Archaeol. Sci. 36, 684–693 (2009).Article 

Google Scholar 
Pedersen, J., Maier, A. & Riede, F. A punctuated model for the colonisation of the Late Glacial margins of northern Europe by Hamburgian hunter-gatherers. Quart.är. 65, 85–104 (2018).
Google Scholar 
Whallon, R. Social networks and information: non-“utilitarian” mobility among hunter-gatherers. J. Anthropol. Archaeol. 25, 259–270 (2006).Article 

Google Scholar 
Leal Filho, W. et al. Impacts of climate change to African indigenous communities and examples of adaptation responses. Nat. Commun. 12, 6224 (2021).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Heitz, C. F., Hinz, M., Laabs, J. & Hafner, A. Mobility as resilience capacity in northern Alpine Neolithic settlement communities. Archaeol. Rev. Camb. 36, 75–106 (2021).
Google Scholar 
Riede, F., Oetelaar, G. A. & VanderHoek, R. From crisis to collapse in hunter-gatherer societies. A comparative investigation of the cultural impacts of three large volcanic eruptions on past hunter-gatherers. Crisis to Collapse–The Archaeology of Social Breakdown. Louvain-la-Neuve: UCL Presses Universitaires De Louvian 23–39 (2017).Halstead, P., O’Shea, J. & O’Shea, J. M. Bad Year Economics: Cultural Responses to Risk and Uncertainty. (Cambridge Univ. Press, 2004).Brovkin, V. et al. Past abrupt changes, tipping points and cascading impacts in the Earth system. Nat. Geosci. 14, 550–558 (2021).ADS 
CAS 
Article 

Google Scholar 
Burke, A. et al. The archaeology of climate change: the case for cultural diversity. Proc Natl Acad Sci USA 118, e2108537118 (2021).Binford, L. R. Willow smoke and dogs tails – Hunter-gatherer settlement systems and archaeological site formation. Am. Antiquity 45, 4–20 (1980).Article 

Google Scholar 
Birdsell, J. B. Some environmental and cultural factors influencing the structuring of Australian aboriginal populations. Am. Nat. 87, 171–207 (1953).Article 

Google Scholar 
Kelly, R. L. The Lifeways of Hunter-Gatherers: The Foraging Spectrum (Cambridge Univ. Press, 2013).Penington, R. Hunter-gatherer demography. In Hunter-Gatherers: An Interdisciplinary Perspective. (eds. Panter-Brick, C., Layton, R. H. & Rowley-Conwy, P.) (Cambridge University Press, Cambridge, 2001).Wobst, H. M. Locational relationships in Paleolithic society. J. Hum. Evol. 5, 49–58 (1976).Article 

Google Scholar 
Richards, M. P., Pettitt, P. B., Stiner, M. C. & Trinkaus, E. Stable isotope evidence for increasing dietary breadth in the European mid-Upper Paleolithic. Proc. Natl Acad. Sci. USA 98, 6528–6532 (2001).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Drucker, D. & Bocherens, H. Carbon and nitrogen stable isotopes as tracers of change in diet breadth during Middle and Upper Palaeolithic in Europe. Int J. Osteoarchaeol. 14, 162–177 (2004).Article 

Google Scholar 
Kretschmer, I. Demographische Untersuchungen zu Bevölkerungsdichten, Mobilität und Landnutzungsmustern im späten Jungpaläolithikum (Verlag Marie Leidorf GmbH, 2015).Langley, M. C. & Street, M. Long range inland-coastal networks during the Late Magdalenian: evidence for individual acquisition of marine resources at Andernach-Martinsberg, German Central Rhineland. J. Hum. Evol. 64, 457–465 (2013).PubMed 
Article 

Google Scholar 
Lanczont, M. et al. Late Glacial environment and human settlement of the Central Western Carpathians: a case study of the Nowa Biala 1 open-air site (Podhale Region, southern Poland). Quat. Int 512, 113–132 (2019).Article 

Google Scholar 
Cziesla, E. Robbenjagd in Brandenburg? Gedanken zur Verwendung großer Widerhakenspitzen. Ethnographisch-archaologische Z. 48, 1–48 (2007).
Google Scholar 
Fick, S. E. & Hijmans, R. J. WorldClim 2: new 1‐km spatial resolution climate surfaces for global land areas. Int. J. Climatol. 37, 4302–4315 (2017).Article 

Google Scholar 
Le Cook, B. & Manning, W. G. Thinking beyond the mean: a practical guide for using quantile regression methods for health services research. Shanghai Arch. Psychiatry 25, 55 (2013).PubMed 
PubMed Central 

Google Scholar 
Yee, T. W. & Mitchell, N. D. Generalized additive-models in plant ecology. J. Veg. Sci. 2, 587–602 (1991).Article 

Google Scholar 
Guisan, A., Edwards, T. C. & Hastie, T. Generalized linear and generalized additive models in studies of species distributions: setting the scene. Ecol. Model 157, 89–100 (2002).Article 

Google Scholar 
Fewster, R. M., Buckland, S. T., Siriwardena, G. M., Baillie, S. R. & Wilson, J. D. Analysis of population trends for farmland birds using generalized additive models. Ecology 81, 1970–1984 (2000).Article 

Google Scholar 
Drexler, M. & Ainsworth, C. H. Generalized additive models used to predict species abundance in the Gulf of Mexico: an ecosystem modeling tool. PLos ONE 8, e64458 (2013).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Moisen, G. G. & Frescino, T. S. Comparing five modelling techniques for predicting forest characteristics. Ecol. Model 157, 209–225 (2002).Article 

Google Scholar 
Wood, S. N. Generalized Additive Models: An Introduction with R (CRC Press, 2006).Zuur, A. F. A Beginner’s Guide to Generalized Additive Models with R (Highland Statistics Limited, 2012).Team, R. C. R: a language and environment for statistical computing. (2013).Wood, S. N. Generalized Additive Models: An Introduction with R (CRC Press, 2017).Fasiolo, M., Wood, S. N., Zaffran, M., Nedellec, R. & Goude, Y. Fast calibrated additive quantile regression. J. Am. Stat. Assoc. 116, 1402–1412 (2021).MathSciNet 
CAS 
Article 

Google Scholar 
AlejoOrdonez/PaleoPopDen: (Version NatCommV0) [Computer software]. Zenodo. https://doi.org/10.5281/ZENODO.6962693 (2022).Liu, Z. et al. Transient simulation of last deglaciation with a new mechanism for Bolling-Allerod warming. Science 325, 310–314 (2009).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Lorenz, D. J., Nieto-Lugilde, D., Blois, J. L., Fitzpatrick, M. C. & Williams, J. W. Downscaled and debiased climate simulations for North America from 21,000 years ago to 2100AD. Sci. Data 3, 160048 (2016).PubMed 
PubMed Central 
Article 

Google Scholar 
Peltier, W. R., Argus, D. & Drummond, R. Space geodesy constrains ice age terminal deglaciation: the global ICE‐6G_C (VM5a) model. J. Geophys. Res. Solid Earth 120, 450–487 (2015).ADS 
Article 

Google Scholar 
Vermeersch, P. M. European population changes during the Marine Isotope Stages 2 and 3. Quat. Int 137, 77–85 (2005).Article 

Google Scholar 
Gamble, C., Davies, W., Pettitt, P., Hazelwood, L. & Richards, M. The archaeological and genetic foundations of the European population during the late glacial: Implications for ‘agricultural thinking’. Camb. Archaeol. J. 15, 193–223 (2005).Article 

Google Scholar 
Steele, J. Radiocarbon dates as data: quantitative strategies for estimating colonization front speeds and event densities. J. Archaeol. Sci. 37, 2017–2030 (2010).Article 

Google Scholar 
Shennan, S. et al. Regional population collapse followed initial agriculture booms in mid-Holocene Europe. Nat. Commun. 4, 2486 (2013).ADS 
PubMed 
Article 
CAS 

Google Scholar 
Surovell, T. A., Finley, J. B., Smith, G. M., Brantingham, P. J. & Kelly, R. Correcting temporal frequency distributions for taphonomic bias. J. Archaeol. Sci. 36, 1715–1724 (2009).Article 

Google Scholar 
Williams, A. N. The use of summed radiocarbon probability distributions in archaeology: a review of methods. J. Archaeol. Sci. 39, 578–589 (2012).Article 

Google Scholar 
Kelly, R. L., Surovell, T. A., Shuman, B. N. & Smith, G. M. A continuous climatic impact on Holocene human population in the Rocky Mountains. Proc. Natl Acad. Sci. USA 110, 443–447 (2013).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Hijmans, R. J. et al. Package ‘raster’. R package 734, (2015).Lewin-Koh, N. J. et al. Package ‘maptools’. Internet: http://cran.r-project.org/web/packages/maptools/maptools.pdf (2012).Thornthwaite, C. W. An approach toward a rational classification of climate. Geogr. Rev. 38, 55–94 (1948).Article 

Google Scholar 
Lieth, H.Primary Productivity of the Biosphere (Springer, 1975). More