Ecology

1.
Faostat, F. Available online, http://www.fao.org/faostat/en/#data.QC. Accessed Jan 2018.
2.
MAL, R. Ministry of Agricultural and Land Reclamation. Economic Affairs Sector, study of statistics for animal, poultry and fish wealth. Egypt. Minist. Agric. Land Reclam., 18, 145–159 (2008).

3.
Al-Keraby, F. Egypt country report. Global Agenda for, 73 (2000).

4.
El-Beltagy, A. & Abo-Hadeed, A. The Main Pillars of the National Program for maximizing the Water-Use Efficiency in the Old Land (The Research and Development Council, Ministry of Agriculture and Land Reclamation (MOALR), Giza, Egypt, 2008).
Google Scholar 

5.
Kandil, E. E., Abdelsalam, N. R., Mansour, M. A., Ali, H. M. & Siddiqui, M. H. Potentials of organic manure and potassium forms on maize (Zea mays L.) growth and production. Sci. Rep. 10, 1–11 (2020).
Article  CAS  Google Scholar 

6.
Mohamed, A. E. & Makki, E. K. Wheat response to irrigation scheduling. Univ. Khartoum J. Agric. Sci. (Sudan) 13(1) (2019).

7.
Change, I. P. O. C. Climate change 2007: impacts, adaptation and vulnerability. Genebra, Suíça (2001).

8.
Lobell, D. B. & Field, C. B. Global scale climate–crop yield relationships and the impacts of recent warming. Environ. Res. Lett. 2, 014002 (2007).
ADS  Article  Google Scholar 

9.
Tezara, W., Mitchell, V., Driscoll, S. & Lawlor, D. Water stress inhibits plant photosynthesis by decreasing coupling factor and ATP. Nature 401, 914–917 (1999).
ADS  CAS  Article  Google Scholar 

10.
Du, N., Guo, W., Zhang, X. & Wang, R. Morphological and physiological responses of Vitex negundo L. var. heterophylla (Franch.) Rehd. to drought stress. Acta Physiol. Plant. 32, 839–848 (2010).
Article  Google Scholar 

11.
Gholami, R. & Zahedi, S. M. Identifying superior drought-tolerant olive genotypes and their biochemical and some physiological responses to various irrigation levels. J. Plant Nutr. 42, 2057–2069 (2019).
CAS  Article  Google Scholar 

12.
Zahedi, S. M., Moharrami, F., Sarikhani, S. & Padervand, M. Selenium and silica nanostructure-based recovery of strawberry plants subjected to drought stress. Sci. Rep. 10, 1–18 (2020).
Article  CAS  Google Scholar 

13.
Cakir, R. Effect of water stress at different development stages on vegetative and reproductive growth of corn. Field Crops Res. 89, 1–16 (2004).
Article  Google Scholar 

14.
Igbadun, H. E., Tarimo, A. K., Salim, B. A. & Mahoo, H. F. Evaluation of selected crop water production functions for an irrigated maize crop. Agric. Water Manag. 94, 1–10 (2007).
Article  Google Scholar 

15.
Tariq, J. & Usman, K. Regulated deficit irrigation scheduling of maize crop. 2009. Sarhad J. Agric. 25, 441–450 (2009).
Google Scholar 

16.
Singh, L. et al. Efficient techniques to increase water use efficiency under rainfed eco-systems. J. AgriSearch 1, 193–200 (2014).
Google Scholar 

17.
Al-Mansor, A., El-Gindy, A., Hegazi, M., El-Bagoury, K. & Abd El-Hady, S. Effect of surface and subsurface trickle irrigation on yield and water use efficiency of tomato crop under deficit irrigation conditions. Misr J. Agric. Eng. 32, 1021–1040 (2015).
Article  Google Scholar 

18.
Schmidt, R., Zhang, X. & Chalmers, D. Response of photosynthesis and superoxide dismutase to silica applied to creeping bentgrass grown under two fertility levels. J. Plant Nutr. 22, 1763–1773 (1999).
CAS  Article  Google Scholar 

19.
Kandil, E. E., Abdelsalam, N. R., Aziz, A. A. A. E., Ali, H. M. & Siddiqui, M. H. Efficacy of nanofertilizer, fulvic acid and boron fertilizer on sugar beet (Beta vulgaris L.) yield and quality. SUGAR TECH 22, 782–791 (2020).
CAS  Article  Google Scholar 

20.
Liang, Y., Sun, W., Si, J. & Römheld, V. Effects of foliar-and root-applied silicon on the enhancement of induced resistance to powdery mildew in Cucumis sativus. Plant. Pathol. 54, 678–685 (2005).
CAS  Article  Google Scholar 

21.
Hattori, T. et al. Application of silicon enhanced drought tolerance in Sorghum bicolor. Physiol. Plant. 123, 459–466 (2005).
CAS  Article  Google Scholar 

22.
Liang, Y., Sun, W., Zhu, Y.-G. & Christie, P. Mechanisms of silicon-mediated alleviation of abiotic stresses in higher plants: a review. Environ. Pollut. 147, 422–428 (2007).
CAS  PubMed  Article  PubMed Central  Google Scholar 

23.
Maghsoudi, K., Emam, Y. & Ashraf, M. Influence of foliar application of silicon on chlorophyll fluorescence, photosynthetic pigments, and growth in water-stressed wheat cultivars differing in drought tolerance. Turk. J. Bot. 39, 625–634 (2015).
CAS  Google Scholar 

24.
Ibrahim, H. I., Sallam, A. M. & Shaban, K. A. Impact of irrigation rates and potassium silicate fertilizer on seed production and quality of Fahl Egyptian clover and soil properties under saline conditions. Am.-Eurasian J. Agric. Environ. Sci. 15, 1245–1255 (2015).
Google Scholar 

25.
El-Naggar, M. E. et al. Soil application of nano silica on maize yield and its insecticidal activity against some stored insects after the post-harvest. Nanomaterials 10, 739 (2020).
CAS  PubMed Central  Article  Google Scholar 

26.
Romero-Aranda, M. R., Jurado, O. & Cuartero, J. Silicon alleviates the deleterious salt effect on tomato plant growth by improving plant water status. J. Plant Physiol. 163, 847–855 (2006).
CAS  PubMed  Article  PubMed Central  Google Scholar 

27.
Eneji, A. E. et al. Growth and nutrient use in four grasses under drought stress as mediated by silicon fertilizers. J. Plant Nutr. 31, 355–365 (2008).
CAS  Article  Google Scholar 

28.
Liu, J., Han, C., Sheng, X., Liu, S. & Qi, X. in Oral Presentation at 5th International Conference on Si Agriculature. 13–18.

29.
Ali, A. M., Ibrahim, S. M. & Abou-Amer, I. Water deficit stress mitigation by foliar application of potassium silicate for sugar beet grown in a saline calcareous soil. Egypt. J. Soil Sci. 59, 15–23 (2019).
Google Scholar 

30.
Mosa, W. F., Ali, H. M. & Abdelsalam, N. R. The utilization of tryptophan and glycine amino acids as safe alternatives to chemical fertilizers in apple orchards. Environ. Sci. Pollut. Res., 1–9. https://doi.org/10.1007/s11356-020-10658-7 (2020).

31.
Fouda, M. M. et al. Impact of high throughput green synthesized silver nanoparticles on agronomic traits of onion. Int. J. Biol. Macromol. 149, 1304–1317 (2020).
CAS  PubMed  Article  PubMed Central  Google Scholar 

32.
Abdelsalam, N. R. et al. Assessment of silver nanoparticles decorated starch and commercial zinc nanoparticles with respect to their genotoxicity on onion. Int. J. Biol. Macromol. 133, 1008–1018 (2019).
CAS  PubMed  Article  PubMed Central  Google Scholar 

33.
Janislampi, K. W. Effect of silicon on plant growth and drought stress tolerance (2012).

34.
Balakhnina, T. & Borkowska, A. Effects of silicon on plant resistance to environmental stresses. Int. Agrophys. 27, 225–232 (2013).
CAS  Article  Google Scholar 

35.
Gao, L. et al. Nitrogen fertilizer management and maize straw return modulate yield and nitrogen balance in sweet corn. Agronomy 10, 362 (2020).
CAS  Article  Google Scholar 

36.
Page, A., Miller, R. & Keeney, D. Methods of Soil Analysis. Part 2: Chemical and Microbiological Properties (American Society of Agronomy, Soil Science Society of America, Madison, 1982).
Google Scholar 

37.
Israelsen, D. & Hansen, V. Flow of water into and through soils. In Irrigation Principles and Practices 3rd edn (Willey, New York, 1962). https://doi.org/10.2136/sssaj1963.03615995002700020010x

38.
Kjeldahl, C. A new method for the determination of nitrogen in organic matter. Z. Anal. Chem. 22, 366 (1883).
Article  Google Scholar 

39.
AOAC. Official Methods of Analysis (Association of Official Analytical Chemists, Rockville, 1990).
Google Scholar 

40.
Steel, R. G. Pinciples and procedures of statistics a biometrical approach. Report No. 0070610282 (1997).

41.
CoStat, V. Cohort software798 light house Ave. PMB320, Monterey, CA93940, and USA. email: info@ cohort. com and Website: http://www.cohort.com. DownloadCoStatPart2. html (2005).

42.
Elgamaal, A. A. & Maswada, H. F. Response of three yellow maize hybrids to exogenous salicylic acid under two irrigation intervals. Asian J. Crop Sci. 5, 264–274 (2013).
Article  Google Scholar 

43.
Shi, Q., Zeng, X., Li, M., Tan, X. & Xu, F. Effects of different water management practices on rice growth. Water-Wise Rice Prod. 1, 3–14 (2002).
Google Scholar 

44.
Comas, L. H., Trout, T. J., DeJonge, K. C., Zhang, H. & Gleason, S. M. Water productivity under strategic growth stage-based deficit irrigation in maize. Agric. Water Manag. 212, 433–440 (2019).
Article  Google Scholar 

45.
Song, L., Jin, J. & He, J. Effects of severe water stress on maize growth processes in the field. Sustainability 11, 5086 (2019).
Article  Google Scholar 

46.
Zhang, H. et al. Response of maize yield components to growth stage-based deficit irrigation. Agron. J. 111, 3244–3252 (2019).
Article  Google Scholar 

47.
Shedeed, S. I. Assessing effect of potassium silicate consecutive application on forage maize plants (Zea mays L.). J. Innov. Pharm. Biol. Sci. 5, 119–127 (2018).
CAS  Article  Google Scholar 

48.
Mikhael, B., Awad-Allah, M. & Gewaily, E. Effect of irrigation intervals and silicon sources on the productivity of broadcast-seeded Sakha 107 rice cultivar. J. Plant Prod. 9, 1055–1062 (2018).
Article  Google Scholar 

49.
Ren, J., Guo, J., Xing, X., Qi, G. & Yuan, Z. Preliminary study on yield increase effects and yield increase mechanism of silicate fertilizer on maize. J. Maize Sci. 10, 86–87 (2002).
Google Scholar 

50.
Ahmad, A., Afzal, M., Ahmad, A. & Tahir, M. Effect of foliar application of silicon on yield and quality of rice (Oryza Sativa L). Cercet. Agron. Mold. 46, 21–28 (2013).
Article  Google Scholar 

51.
Pilon, C., Soratto, R. P. & Moreno, L. A. Effects of soil and foliar application of soluble silicon on mineral nutrition, gas exchange, and growth of potato plants. Crop Sci. 53, 1605–1614 (2013).
Article  Google Scholar 

52.
Abdeen, S. & Mancy, A. A melioration of water stress effect on sorghum plant growth and water use efficiency by application of potassium silicate and salicylic acid. Bull. Fac. Agric. Cairo Univ. 69, 43–52 (2018)
Google Scholar 

53.
Sepaskhah, A. R. & Khajehabdollahi, M. H. Alternate furrow irrigation with different irrigation intervals for maize (Zea mays L.). Plant Prod. Sci. 8, 592–600 (2005).
Article  Google Scholar 

54.
Artyszak, A. Effect of silicon fertilization on crop yield quantity and quality—a literature review in Europe. Plants 7, 54 (2018).
CAS  PubMed Central  Article  Google Scholar 

55.
Zahedi, S. M., Karimi, M. & Teixeira da Silva, J. A. The use of nanotechnology to increase quality and yield of fruit crops. J. Sci. Food Agric. 100, 25–31 (2020).
CAS  PubMed  Article  PubMed Central  Google Scholar 

56.
Hasanuzzaman, M., Alam, M. M., Nahar, K., Ahamed, K. U. & Fujita, M. Exogenous salicylic acid alleviates salt stress-induced oxidative damage in Brassica napus by enhancing the antioxidant defense and glyoxalase systems. Aust. J. Crop Sci. 8, 631 (2014).
CAS  Google Scholar  More

1.
Normile, D. Reinventing rice to feed the world. Science 321, 330–333 (2008).
MathSciNet  CAS  PubMed  Article  PubMed Central  Google Scholar 
2.
Marschner, P. Marschner’s Mineral Nutrition of Higher Plants (Academic Press, London, 2012).
Google Scholar 

3.
Vigani, G., Tarantino, D. & Murgia, I. Mitochondrial ferritin is a functional iron-storage protein in cucumber (Cucumis sativus) roots. Front. Plant Sci. 4, 316 (2013).
PubMed  PubMed Central  Google Scholar 

4.
Violante, A., Barberis, E., Pigna, M. & Boero, V. Factors affecting the formation, nature, and properties of iron precipitation products at the soil-root interface. J. Plant Nutr. 26, 1889–1908 (2003).
CAS  Article  Google Scholar 

5.
Pradhan, S. K. et al. Genetic regulation of homeostasis, uptake, bio-fortification and efficiency enhancement of iron in rice. Environ. Exp. Bot. 177, 104066 (2020).
CAS  Article  Google Scholar 

6.
Kilcoyne, S. H., Bentley, P. M., Thongbai, P., Gordon, D. C. & Goodman, B. A. The application of 57Fe Mössbauer spectroscopy in the investigation of iron uptake and translocation in plants. Nucl. Instrum. Meth B 160, 157–166 (2000).
ADS  CAS  Article  Google Scholar 

7.
Zhang, A. et al. Effect of biochar amendment on yield and methane and nitrous oxide emissions from a rice paddy from Tai Lake plain, China. Agric. Ecosyst. Environ. 139, 469–475 (2010).
CAS  Article  Google Scholar 

8.
Huang, M., Yang, L., Qin, H., Jiang, L. & Zou, Y. Quantifying the effect of biochar amendment on soil quality and crop productivity in Chinese rice paddies. Field Crops Res. 154, 172–177 (2013).
Article  Google Scholar 

9.
Zhang, A. et al. Effects of biochar amendment on soil quality, crop yield and greenhouse gas emission in a Chinese rice paddy: A field study of 2 consecutive rice growing cycles. Field Crops Res. 127, 153–160 (2012).
Article  Google Scholar 

10.
Kim, S. & Dale, B. E. Global potential bioethanol production from wasted crops and crop residues. Biomass Bioenerg. 26, 361–375 (2004).
Article  Google Scholar 

11.
Wang, Y., Xiao, X., Xu, Y. & Chen, B. Environmental effects of silicon within Biochar (Sichar) and carbon–silicon coupling mechanisms: A critical review. Environ. Sci. Technol. 53, 13570–13582 (2019).
ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

12.
Chan, K. Y., Van Zwieten, L., Meszaros, I., Downie, A. & Joseph, S. Agronomic values of greenwaste biochar as a soil amendment. Soil Res. 45, 629 (2007).
CAS  Article  Google Scholar 

13.
Van Zwieten, L. et al. Effects of biochar from slow pyrolysis of papermill waste on agronomic performance and soil fertility. Plant Soil 327, 235–246 (2009).
Article  CAS  Google Scholar 

14.
Joseph, S. et al. Shifting paradigms: Development of high-efficiency biochar fertilizers based on nano-structures and soluble components. Carbon Manag. 4, 323–343 (2013).
CAS  Article  Google Scholar 

15.
Chew, J. et al. Biochar-based fertilizer: Supercharging root membrane potential and biomass yield of rice. Sci. Total Environ. 713, 136431 (2020).
ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

16.
Irshad, M. K. et al. Goethite-modified biochar ameliorates the growth of rice (Oryza sativa L.) plants by suppressing Cd and As-induced oxidative stress in Cd and As co-contaminated paddy soil. Sci. Total Environ. 717, 137086 (2020).
ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

17.
Zhang, J.-Y. et al. Effects of nano-Fe3O4-modified biochar on iron plaque formation and Cd accumulation in rice (Oryza sativa L.). Environ. Pollut. 260, 113970 (2020).
CAS  PubMed  Article  PubMed Central  Google Scholar 

18.
Chen, Z. et al. Mitigation of Cd accumulation in paddy rice (Oryza sativa L.) by Fe fertilization. Environ. Pollut. 231, 549–559 (2017).
CAS  PubMed  Article  PubMed Central  Google Scholar 

19.
Küpper, H., Zhao, F. J. & McGrath, S. P. Cellular compartmentation of zinc in leaves of the hyperaccumulator Thlaspi caerulescens. Plant Physiol. 119, 305–312 (1999).
PubMed Central  Article  Google Scholar 

20.
Blackwell, P. et al. Influences of biochar and biochar-mineral complex on mycorrhizal colonisation and nutrition of wheat and sorghum. Pedosphere 25, 686–695 (2015).
CAS  Article  Google Scholar 

21.
Rodriguez, N., Menendez, N., Tornero, J., Amils, R. & de la Fuente, V. Internal iron biomineralization in Imperata cylindrica, a perennial grass: Chemical composition, speciation and plant localization. New Phytol. 165, 781–789 (2005).
CAS  PubMed  Article  Google Scholar 

22.
Neumann, D., Nieden, U. Z., Lichtenberger, O. & Leopold, I. How does Armeria maritima tolerate high heavy metal concentrations?. J. Plant Physiol. 146, 704–717 (1995).
CAS  Article  Google Scholar 

23.
Liu, D. H., Adler, K. & Stephan, U. W. Iron-containing particles accumulate in organelles and vacuoles of leaf and root cells in the nicotianamine-free tomato mutantchloronerva. Protoplasma 201, 213–220 (1998).
CAS  Article  Google Scholar 

24.
Alkhatib, R., Alkhatib, B., Abdo, N., Al-Eitan, L. & Creamer, R. Physio-biochemical and ultrastructural impact of (Fe3O4) nanoparticles on tobacco. BMC Plant Biol. 19, 253 (2019).
PubMed  PubMed Central  Article  CAS  Google Scholar 

25.
Fuente, V. et al. Formation of biomineral iron oxides compounds in a Fe hyperaccumulator plant: Imperata cylindrica (L.) P. Beauv. J. Struct. Biol. 193, 23–32 (2016).
CAS  PubMed  Article  Google Scholar 

26.
Graham, U. M. et al. Tissue specific fate of nanomaterials by advanced analytical imaging techniques—A review. Chem. Res. Toxicol. 33, 1145–1162 (2020).
CAS  PubMed  PubMed Central  Article  Google Scholar 

27.
Aoki, D. et al. Distribution of coniferin in freeze-fixed stem of Ginkgo biloba L. by cryo-TOF-SIMS/SEM. Sci. Rep. 6, 31525 (2016).
ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

28.
Martin, R. R. et al. Time of flight secondary ion mass spectrometry studies of the distribution of metals between the soil, rhizosphere and roots of Populus tremuloides Minchx growing in forest soil. Chemosphere 54, 1121–1125 (2004).
ADS  CAS  PubMed  Article  Google Scholar 

29.
Saito, K. et al. Aluminum localization in the cell walls of the mature xylem of maple tree detected by elemental imaging using time-of-flight secondary ion mass spectrometry (TOF-SIMS). Holzforschung 68, 85–92 (2014).
CAS  Article  Google Scholar 

30.
Hanć, A., Piechalak, A., Tomaszewska, B. & Barałkiewicz, D. Laser ablation inductively coupled plasma mass spectrometry in quantitative analysis and imaging of plant’s thin sections. Int. J. Mass spectrom. 363, 16–22 (2014).
Article  CAS  Google Scholar 

31.
Shi, J., Gras, M. A. & Silk, W. K. Laser ablation ICP-MS reveals patterns of copper differing from zinc in growth zones of cucumber roots. Planta 229, 945–954 (2009).
CAS  PubMed  Article  PubMed Central  Google Scholar 

32.
Guizani, C., Haddad, K., Limousy, L. & Jeguirim, M. New insights on the structural evolution of biomass char upon pyrolysis as revealed by the Raman spectroscopy and elemental analysis. Carbon 119, 519–521 (2017).
CAS  Article  Google Scholar 

33.
Joseph, S. et al. An investigation into the reactions of biochar in soil. Soil Res. 48, 501–515 (2010).
CAS  Article  Google Scholar 

34.
Prendergast-Miller, M. T., Duvall, M. & Sohi, S. P. Biochar-root interactions are mediated by biochar nutrient content and impacts on soil nutrient availability. Eur. J. Soil Sci. 65, 173–185 (2014).
CAS  Article  Google Scholar 

35.
Nielsen, S. et al. Comparative analysis of the microbial communities in agricultural soil amended with enhanced biochars or traditional fertilisers. Agric. Ecosyst. Environ. 191, 73–82 (2014).
Article  Google Scholar 

36.
Hansel, C. M., Fendorf, S., Sutton, S. & Newville, M. Characterization of Fe plaque and associated metals on the roots of mine-waste impacted aquatic plants. Environ. Sci. Technol. 35, 3863–3868 (2001).
ADS  CAS  PubMed  Article  Google Scholar 

37.
Gloter, A., Zbinden, M., Guyot, F., Gaill, F. & Colliex, C. TEM-EELS study of natural ferrihydrite from geological–biological interactions in hydrothermal systems. Earth Planet. Sci. Lett. 222, 947–957 (2004).
ADS  CAS  Article  Google Scholar 

38.
Rajendran, M. et al. Effect of sulfur and sulfur-iron modified biochar on cadmium availability and transfer in the soil-rice system. Chemosphere 222, 314–322 (2019).
ADS  CAS  PubMed  Article  Google Scholar 

39.
Wu, C. et al. The effect of silicon on iron plaque formation and arsenic accumulation in rice genotypes with different radial oxygen loss (ROL). Environ. Pollut. 212, 27–33 (2016).
CAS  PubMed  Article  PubMed Central  Google Scholar 

40.
Linke, R., Schreiner, M., Demortier, G. & Alram, M. Determination of the provenance of medieval silver coins: potential and limitations of X-ray analysis using photons, electrons or protons. X-ray Spectrom. 32, 373–380 (2003).
ADS  CAS  Article  Google Scholar 

41.
Haynes, R. J. A contemporary overview of silicon availability in agricultural soils. J. Plant Nutr. Soil Sci. 177, 831–844 (2014).
CAS  Article  Google Scholar 

42.
Kostic, L. et al. Liming of anthropogenically acidified soil promotes phosphorus acquisition in the rhizosphere of wheat. Biol. Fertility Soils 51, 289–298 (2014).
Article  CAS  Google Scholar 

43.
Acosta-Martinez, V. & Tabatabai, M. Enzyme activities in a limed agricultural soil. Biol. Fertility Soils 31, 85–91 (2000).
CAS  Article  Google Scholar 

44.
Chan, K., Van Zwieten, L., Meszaros, I., Downie, A. & Joseph, S. Using poultry litter biochars as soil amendments. Soil Res. 46, 437–444 (2008).
Article  Google Scholar 

45.
Khan, N. et al. Root iron plaque on wetland plants as a dynamic pool of nutrients and contaminants. Adv. Agron. 138, 1–96 (2016).
Article  Google Scholar 

46.
Kuzyakov, Y. & Blagodatskaya, E. Microbial hotspots and hot moments in soil: Concept and review. Soil Biol. Biochem. 83, 184–199 (2015).
CAS  Article  Google Scholar 

47.
Ma, J., Cai, H., He, C., Zhang, W. & Wang, L. A hemicellulose-bound form of silicon inhibits cadmium ion uptake in rice (Oryza sativa) cells. New Phytol. 206, 1063–1074 (2015).
CAS  PubMed  Article  PubMed Central  Google Scholar 

48.
Wang, Y., Stass, A. & Horst, W. J. Apoplastic binding of aluminum is involved in silicon-induced amelioration of aluminum toxicity in maize. Plant Physiol. 136, 3762–3770 (2004).
CAS  PubMed  PubMed Central  Article  Google Scholar 

49.
Wang, P., Lombi, E., Zhao, F.-J. & Kopittke, P. M. Nanotechnology: A new opportunity in plant sciences. Trends Plant Sci. 21, 699–712 (2016).
CAS  PubMed  Article  PubMed Central  Google Scholar 

50.
Garvie, L. A. & Buseck, P. R. Ratios of ferrous to ferric iron from nanometre-sized areas in minerals. Nature 396, 667–670 (1998).
ADS  CAS  Article  Google Scholar 

51.
Goya, G. F., Berquó, T. S., Fonseca, F. C. & Morales, M. P. Static and dynamic magnetic properties of spherical magnetite nanoparticles. J. Appl. Phys. 94, 3520–3528 (2003).
ADS  CAS  Article  Google Scholar 

52.
Yao, C. et al. Developing more effective enhanced biochar fertilisers for improvement of pepper yield and quality. Pedosphere 25, 703–712 (2015).
CAS  Article  Google Scholar 

53.
Rawal, A. et al. Mineral-biochar composites: Molecular structure and porosity. Environ. Sci. Technol. 50, 7706–7714 (2016).
ADS  CAS  PubMed  Article  Google Scholar 

54.
Mitchell, D. R. Contamination mitigation strategies for scanning transmission electron microscopy. Micron 73, 36–46 (2015).
CAS  PubMed  Article  PubMed Central  Google Scholar  More

1.
FAO. The State of World Fisheries and Aquaculture 2018. (Food and Agriculture Organization of the United Nations, 2018).
2.
Zuo, Z.-H., Shang, B.-J., Shao, Y.-C., Li, W.-Y. & Sun, J.-S. Screening of intestinal probiotics and the effects of feeding probiotics on the growth, immune, digestive enzyme activity and intestinal flora of Litopenaeus vannamei. Fish Shellfish Immunol. 86, 160–168. https://doi.org/10.1016/j.fsi.2018.11.003 (2019).
CAS  Article  PubMed  Google Scholar 

3.
Hoseinifar, S. H., Sun, Y., Wang, A. & Zhou, Z. Probiotics as means of diseases control in aquaculture, a review of current knowledge and future perspectives. Front. Microbiol. 9, 2429. https://doi.org/10.3389/fmicb.2018.02429 (2018).
Article  PubMed  PubMed Central  Google Scholar 

4.
Reverter, M., Bontemps, N., Lecchini, D., Banaigs, B. & Sasal, P. Use of plant extracts in fish aquaculture as an alternative to chemotherapy: Current status and future perspectives. Aquaculture 433, 50–61. https://doi.org/10.1016/j.aquaculture.2014.05.048 (2014).
Article  Google Scholar 

5.
Lieke, T. et al. Sustainable aquaculture requires environmental-friendly treatment strategies for fish diseases. Rev. Aquac. 12, 943–965. https://doi.org/10.1111/raq.12365 (2019).
Article  Google Scholar 

6.
Noga, E. J. Fish Disease: Diagnosis and Treatment. Vol. 2nd Edn 143–148 (Wiley, 2011).

7.
Haugarvoll, E., Bjerkås, I., Nowak, B. F., Hordvik, I. & Koppang, E. O. Identification and characterization of a novel intraepithelial lymphoid tissue in the gills of Atlantic salmon. J. Anat. 213, 202–209. https://doi.org/10.1111/j.1469-7580.2008.00943.x (2008).
Article  PubMed  PubMed Central  Google Scholar 

8.
Zhang, Z., Swain, T., Bøgwald, J., Dalmo, R. A. & Kumari, J. Bath immunostimulation of rainbow trout (Oncorhynchus mykiss) fry induces enhancement of inflammatory cytokine transcripts, while repeated bath induce no changes. Fish Shellfish Immunol. 26, 677–684. https://doi.org/10.1016/j.fsi.2009.02.014 (2009).
CAS  Article  PubMed  Google Scholar 

9.
Jeney, G. & Anderson, D. P. Enhanced immune response and protection in rainbow trout to Aeromonas salmonicida bacterin following prior immersion in immunostimulants. Fish Shellfish Immunol. 3, 51–58. https://doi.org/10.1006/fsim.1993.1005 (1993).
Article  Google Scholar 

10.
Steinberg, C. E. W. Ecology of Humic Substances in Freshwaters: Determinants from Geochemistry to Ecological Niches. Vol. 1 (Springer, 2003).

11.
Haitzer, M., Höss, S., Traunspurger, W. & Steinberg, C. E. W. Effects of dissolved organic matter (DOM) on the bioconcentration of organic chemicals in aquatic organisms—A review. Chemosphere 37, 1335–1362. https://doi.org/10.1016/S0045-6535(98)00117-9 (1998).
ADS  CAS  Article  PubMed  Google Scholar 

12.
Thurman, E. M. Organic Geochemistry of Natural Waters. Vol. 1 (Nijhoff, M./Junk, W. Publishers, 1985).

13.
IHSS. What are Humic Substances? http://humic-substances.org .

14.
Meinelt, T. et al. Reduction in vegetative growth of the water mold Saprolegnia parasitica (Coker) by humic substance of different qualities. Aquat. Toxicol. 83, 93–103. https://doi.org/10.1016/j.aquatox.2007.03.013 (2007).
CAS  Article  PubMed  Google Scholar 

15.
Yamin, G. et al. The protective effect of humic substances and water and sludge from a recirculating aquaculture system on Aeromonas salmonicida infection in common carp (Cyprinus carpio). J. Fish Dis. 40, 1783–1790. https://doi.org/10.1111/jfd.12645 (2017).
CAS  Article  PubMed  Google Scholar 

16.
Kodama, H., Denso & Nakagawa, T. Protection against atypical Aeromonas salmonicida infection in carp (Cyprinus carpio L.) by oral administration of humus extract. J. Vet. Med. Sci. 69, 405–408, https://doi.org/10.1292/jvms.69.405 (2007).

17.
Fierro-Coronado, J. A. et al. Dietary fulvic acid effects on survival and expression of immune-related genes in Litopenaeus vannamei challenged with Vibrio parahaemolyticus. Aquac. Res. 49, 3218–3227. https://doi.org/10.1111/are.13789 (2018).
CAS  Article  Google Scholar 

18.
Gao, Y. et al. Effects of fulvic acid on growth performance and intestinal health of juvenile loach Paramisgurnus dabryanus (Sauvage). Fish Shellfish Immunol. 62, 47–56. https://doi.org/10.1016/j.fsi.2017.01.008 (2017).
CAS  Article  PubMed  Google Scholar 

19.
Saebelfeld, M., Minguez, L., Griebel, J., Gessner, M. O. & Wolinska, J. Humic dissolved organic carbon drives oxidative stress and severe fitness impairments in Daphnia. Aquat. Toxicol. 182, 31–38. https://doi.org/10.1016/j.aquatox.2016.11.006 (2017).
CAS  Article  PubMed  Google Scholar 

20.
Steinberg, C. E. W. et al. Stress by poor food quality and exposure to humic substances: Daphnia magna responds with oxidative stress, lifespan extension, but reduced offspring numbers. Hydrobiologia 652, 223–236 (2010).
CAS  Article  Google Scholar 

21.
Hseu, Y.-C. et al. Humic acid induced genotoxicity in human peripheral blood lymphocytes using comet and sister chromatid exchange assay. J. Hazard. Mater. 153, 784–791. https://doi.org/10.1016/j.jhazmat.2007.09.024 (2008).
CAS  Article  PubMed  Google Scholar 

22.
Savy, D. et al. Quantitative structure-activity relationship of humic-like biostimulants derived from agro-industrial by products and energy crops. Front. Plant Sci. 11, 581. https://doi.org/10.3389/fpls.2020.00581 (2020).
Article  PubMed  PubMed Central  Google Scholar 

23.
Pörs, Y. & Steinberg, C. E. Humic substances delay aging of the photosynthetic apparatus of Chara hispida. J. Phycol. 48, 1522–1529. https://doi.org/10.1111/jpy.12012 (2012).
CAS  Article  PubMed  Google Scholar 

24.
Muscolo, A., Sidari, M., Francioso, O., Tugnoli, V. & Nardi, S. The auxin-like activity of humic substances is related to membrane interactions in carrot cell cultures. J. Chem. Ecol. 33, 115–129. https://doi.org/10.1007/s10886-006-9206-9 (2007).
CAS  Article  PubMed  Google Scholar 

25.
Gilbert, M., Bährs, H., Steinberg, C. E. W. & Wilhelm, C. The artificial humic substance HS1500 does not inhibit photosynthesis of the green alga Desmodesmus armatus in vivo but interacts with the photosynthetic apparatus of isolated spinach thylakoids in vitro. Photosynth. Res. https://doi.org/10.1007/s11120-018-0513-0 (2018).
Article  PubMed  Google Scholar 

26.
Perdue, E. M. in Encyclopedia of Inland Waters (ed Gene E. Likens) 806–819 (Academic Press, 2009).

27.
Chen, J., Gu, B., LeBoeuf, E. J., Pan, H. & Dai, S. Spectroscopic characterization of the structural and functional properties of natural organic matter fractions. Chemosphere 48, 59–68. https://doi.org/10.1016/S0045-6535(02)00041-3 (2002).
ADS  CAS  Article  PubMed  Google Scholar 

28.
Lieke, T., Zhang, X., Steinberg, C. E. & Pan, B. Overlooked risks of biochars: Persistent free radicals trigger neurotoxicity in Caenorhabditis elegans. Environ. Sci. Technol. 52, 7981–7987. https://doi.org/10.1021/acs.est.8b01338 (2018).
ADS  CAS  Article  PubMed  Google Scholar 

29.
Liao, S., Pan, B., Li, H., Zhang, D. & Xing, B. Detecting free radicals in biochars and determining their ability to inhibit the germination and growth of corn, wheat and rice seedlings. Environ. Sci. Technol. 48, 8581–8587. https://doi.org/10.1021/es404250a (2014).
ADS  CAS  Article  PubMed  Google Scholar 

30.
Yuan, Y. et al. Electron transfer capacity as a rapid and simple maturity index for compost. Biores. Technol. 116, 428–434. https://doi.org/10.1016/j.biortech.2012.03.114 (2012).
CAS  Article  Google Scholar 

31.
Scott, D. T., McKnight, D. M., Blunt-Harris, E. L., Kolesar, S. E. & Lovley, D. R. Quinone moieties act as electron acceptors in the reduction of humic substances by humics-reducing microorganisms. Environ. Sci. Technol. 32, 2984–2989. https://doi.org/10.1021/es980272q (1998).
ADS  CAS  Article  Google Scholar 

32.
Abdel-Tawwab, M., Abdel-Rahman, A. M. & Ismael, N. E. M. Evaluation of commercial live bakers’ yeast, Saccharomyces cerevisiae as a growth and immunity promoter for Fry Nile tilapia, Oreochromis niloticus (L.) challenged in situ with Aeromonas hydrophila. Aquaculture 280, 185–189, https://doi.org/10.1016/j.aquaculture.2008.03.055 (2008).

33.
Sanmanee, N. & Areekijseree, M. The effects of fulvic acid on copper bioavailability to porcine oviductal epithelial cells. Biol. Trace Elem. Res. 135, 162–173. https://doi.org/10.1007/s12011-009-8508-5 (2010).
CAS  Article  PubMed  Google Scholar 

34.
Hasan, M. & Soto, D. Improving Feed Conversion Ratio and Its Impact on Reducing Greenhouse Gas Emissions in Aquaculture. (FAO, 2017).

35.
Besson, M. et al. Environmental impacts of genetic improvement of growth rate and feed conversion ratio in fish farming under rearing density and nitrogen output limitations. J. Clean. Prod. 116, 100–109 (2016).
Article  Google Scholar 

36.
Tort, L. Stress and immune modulation in fish. Dev. Comp. Immunol. 35, 1366–1375. https://doi.org/10.1016/j.dci.2011.07.002 (2011).
CAS  Article  PubMed  Google Scholar 

37.
Mommsen, T. P., Vijayan, M. M. & Moon, T. W. Cortisol in teleosts: Dynamics, mechanisms of action, and metabolic regulation. Rev. Fish Biol. Fisheries 9, 211–268. https://doi.org/10.1023/A:1008924418720 (1999).
Article  Google Scholar 

38.
Meinelt, T. et al. Humic substances affect physiological condition and sex ratio of swordtail (Xiphophorus helleri Heckel). Aquat. Sci. 66, 239–245. https://doi.org/10.1007/s00027-004-0706-9 (2004).
Article  Google Scholar 

39.
Bly, J. E., Quiniou, S. M. & Clem, L. W. Environmental effects on fish immune mechanisms. Dev. Biol. Stand. 90, 33–43 (1997).
CAS  PubMed  Google Scholar 

40.
Conde-Sieira, M., Chivite, M., Míguez, J. M. & Soengas, J. L. Stress effects on the mechanisms regulating appetite in teleost fish. Front. Endocrinol. 9, https://doi.org/10.3389/fendo.2018.00631 (2018).

41.
Kalamarz-Kubiak, H. in Corticosteroids (ed Ali Gamal Al-Kaf) Chap. 7, 183–155 (InTechOpen, 2018).

42.
Timofeyev, M. A. et al. Natural organic matter (NOM) induces oxidative stress in freshwater amphipods Gammarus lacustris Sars and Gammarus tigrinus (Sexton). Sci. Total Environ. 366, 673–681. https://doi.org/10.1016/j.scitotenv.2006.02.003 (2006).
ADS  CAS  Article  PubMed  Google Scholar 

43.
Xin, Z. et al. Species sensitivity analysis of heavy metals to freshwater organisms. Ecotoxicology 24, 1621–1631. https://doi.org/10.1007/s10646-015-1500-2 (2015).
CAS  Article  PubMed  Google Scholar 

44.
Demers, N. E. & Bayne, C. J. The immediate effects of stress on hormones and plasma lysozyme in rainbow trout. Dev. Comp. Immunol. 21, 363–373. https://doi.org/10.1016/S0145-305X(97)00009-8 (1997).
CAS  Article  PubMed  Google Scholar 

45.
Dupré-Crochet, S., Erard, M. & Nüβe, O. ROS production in phagocytes: why, when, and where?. J. Leukoc. Biol. 94, 657–670. https://doi.org/10.1189/jlb.1012544 (2013).
CAS  Article  PubMed  Google Scholar 

46.
Geng, X. et al. Effects of dietary chitosan and Bacillus subtilis on the growth performance, non-specific immunity and disease resistance of cobia, Rachycentron canadum. Fish Shellfish Immunol. 31, 400–406. https://doi.org/10.1016/j.fsi.2011.06.006 (2011).
CAS  Article  PubMed  Google Scholar 

47.
Fries, C. & Tripp, M. Depression of phagocytosis in Mercenaria following chemical stress. Dev. Comp. Immunol. 4, 233–244. https://doi.org/10.1016/S0145-305X(80)80027-9 (1980).
CAS  Article  PubMed  Google Scholar 

48.
Sesti-Costa, R., Baccan, G. C., Chedraoui-Silva, S. & Mantovani, B. Effects of acute cold stress on phagocytosis of apoptotic cells: The role of corticosterone. NeuroImmunoModulation 17, 79–87. https://doi.org/10.1159/000258690 (2010).
CAS  Article  PubMed  Google Scholar 

49.
Narnaware, Y. K., Baker, B. I. & Tomlinson, M. G. The effect of various stresses, corticosteroids and adrenergic agents on phagocytosis in the rainbow trout Oncorhynchus mykiss. Fish Physiol. Biochem. 13, 31–40. https://doi.org/10.1007/BF00004117 (1994).
CAS  Article  PubMed  Google Scholar 

50.
Dhabhar, F. S. & McEwen, B. S. Acute stress enhances while chronic stress suppresses cell-mediated immunity in vivo: A potential role for leukocyte trafficking. Brain Behav. Immun. 11, 286–306 (1997).
CAS  Article  Google Scholar 

51.
Adel, M., Abedian Amiri, A., Zorriehzahra, J., Nematolahi, A. & Esteban, M. Á. Effects of dietary peppermint (Mentha piperita) on growth performance, chemical body composition and hematological and immune parameters of fry Caspian white fish (Rutilus frisii kutum). Fish Shellfish Immunol. 45, 841–847, https://doi.org/10.1016/j.fsi.2015.06.010 (2015).

52.
Christybapita, D., Divyagnaneswari, M. & Michael, R. D. Oral administration of Eclipta alba leaf aqueous extract enhances the non-specific immune responses and disease resistance of Oreochromis mossambicus. Fish Shellfish Immunol. 23, 840–852. https://doi.org/10.1016/j.fsi.2007.03.010 (2007).
CAS  Article  PubMed  Google Scholar 

53.
Ragland, S. A. & Criss, A. K. From bacterial killing to immune modulation: Recent insights into the functions of lysozyme. PLoS Pathog. 13, https://doi.org/10.1371/journal.ppat.1006512 (2017).

54.
Ansorg, R. & Rochus, W. Studies on the antimicrobial effect of natural and synthetic humic acids (author’s transl). Arzneimittelforschung 28, 2195–2198 (1978).
CAS  PubMed  Google Scholar 

55.
Hertkorn, N. et al. Comparative analysis of partial structures of a peat humic and fulvic acid using one-and two-dimensional nuclear magnetic resonance spectroscopy. J. Environ. Qual. 31, 375–387. https://doi.org/10.2134/jeq2002.3750 (2002).
CAS  Article  PubMed  Google Scholar 

56.
Zheng, X. et al. Comparing electron donating/accepting capacities (EDC/EAC) between crop residue-derived dissolved black carbon and standard humic substances. Sci. Total Environ. 673, 29–35. https://doi.org/10.1016/j.scitotenv.2019.04.022 (2019).
ADS  CAS  Article  PubMed  Google Scholar 

57.
Weil, J. A. & Bolton, J. R. Electron Paramagnetic Resonance: Elementary Theory and Practical Applications. Vol. 2 (Wiley, 2007).

58.
Hopkins, K. D. Reporting fish growth: A review of the basics 1. J. World Aquac. Soc. 23, 173–179. https://doi.org/10.1111/j.1749-7345.1992.tb00766.x (1992).
Article  Google Scholar 

59.
Fulton, T. W. The Rate of Growth of Fishes. 141–241 (Scotland, 1904).

60.
Barnham, C. A. & Baxter, A. F. Condition Factor, K, for Salmonid Fish. (Department of Primary Industries, 2003).

61.
Secombes, C. J. in Techniques in Fish Immunology Vol. 1 (eds J. S. Stolen et al.) 137–154 (SOS Publications, 1990).

62.
Chettri, J. K., Holten-Andersen, L. & Buchmann, K. Factors influencing in vitro respiratory burst assays with head kidney leucocytes from rainbow trout, Oncorhynchus mykiss (Walbaum). J. Fish Dis. 33, 593–602. https://doi.org/10.1111/j.1365-2761.2010.01160.x (2010).
CAS  Article  PubMed  Google Scholar 

63.
Crampe, M., Farley, S. R., Langston, A. & Pulsford, A. L. in Methodology in Fish Diseases Research (eds A.C. Barnes, G.A. Davidson, M. P. Hiney, & D. McIntosh) 81–91 (Fisheries Research Services, 1998).

64.
Begemann, H. & Rastetter, J. Atlas of Clinical Haematology 9–21 (Springer, Berlin, 1972).
Google Scholar 

65.
Sitja-Bobadilla, A., Palenzuela, O. & Alvarez-Pellitero, P. Immune response of turbot, Psetta maxima (L.) (Pisces: Teleostei), to formalin-killed scuticociliates (Ciliophora) and adjuvanted formulations. Fish Shellfish Immunol. 24, 1–10, https://doi.org/10.1016/j.fsi.2007.06.007 (2008).

66.
Siwicki, A. in Fish Diseases Diagnosis and Preventions Methods Vol. 1 (eds A.K. Siwicki, D.P. Anderson, & J. Waluga) 105–111 (Wydawnictwo Instytutu Rybactwa Strodladowego, 1993).

67.
Bradford, M. M. A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding. Anal. Biochem. 72, 248–254. https://doi.org/10.1016/0003-2697(76)90527-3 (1976).
CAS  Article  Google Scholar 

68.
Amado, L. L. et al. A method to measure total antioxidant capacity against peroxyl radicals in aquatic organisms: Application to evaluate microcystins toxicity. Sci. Total Environ. 407, 2115–2123. https://doi.org/10.1016/j.scitotenv.2008.11.038 (2009).
ADS  CAS  Article  PubMed  Google Scholar 

69.
Hollander, M. & Wolfe, D. A. Nonparametric Statistical Methods. Vol. 3 115–120 (Wiley, 2015).

70.
Dunn, O. J. Multiple comparisons using rank sums. Technometrics 6, 241–252. https://doi.org/10.2307/1266041 (1964).
Article  Google Scholar 

71.
Siegal, S. & Castellan Jr., N. J. Nonparametric Statistics for the Behavioral Sciences. (McGraw-Hill, 1988).

72.
Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: A practical and powerful approach to multiple testing. J. R. Stat. Soc. Ser. B (Methodological) 57, 289–300 (1995). More

1.
Dong, F. et al. Ice age unfrozen: severe effect of the last interglacial, not glacial, climate change on East Asian avifauna. BMC Evol. Biol. 17, 244 (2017).
PubMed  PubMed Central  Article  Google Scholar 
2.
Hewitt, G. M. Genetic consequences of climatic oscillations in the quaternary. Philo. Trans. R. Soc. Lond. Ser. B Biol. Sci. 359, 183–195 (2004).
CAS  Article  Google Scholar 

3.
Zheng, B., Xu, Q. & Shen, Y. The relationship between climate change and quaternary glacial cycles on the Qinghai-Tibetan Plateau: review and speculation. Quat. Int. 97, 93–101 (2002).
Article  Google Scholar 

4.
Wei, Z., Zhijiu, C. & Yonghua, L. Review of the timing and extent of glaciers during the last glacial cycle in the bordering mountains of Tibet and in East Asia. Quat. Int. 154, 32–43 (2006).
Article  Google Scholar 

5.
Zhou, S., Wang, X., Wang, J. & Xu, L. A preliminary study on timing of the oldest Pleistocene glaciation in Qinghai-Tibetan Plateau. Quat. Int. 154, 44–51 (2006).
Article  Google Scholar 

6.
Ma, J., Wang, Y., Jin, C., Hu, Y. & Bocherens, H. Ecological flexibility and differential survival of Pleistocene Stegodon orientalis and Elephas maximus in mainland southeast Asia revealed by stable isotope (C, O) analysis. Quat. Sci. Rev. 212, 33–44 (2019).
ADS  Article  Google Scholar 

7.
Avise, J. C. Phylogeography: The History and Formation of Species (Harvard University Press, Cambridge, 2000).
Google Scholar 

8.
Hewitt, G. The genetic legacy of the Quaternary ice ages. Nature 405, 907–913 (2000).
ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

9.
Wiens, J. J. Speciation and ecology revisited: phylogenetic niche conservatism and the origin of species. Evolution 58, 193–197 (2004).
PubMed  Article  Google Scholar 

10.
Srinivasan, U., Tamma, K. & Ramakrishnan, U. Past climate and species ecology drive nested species richness patterns along an east-west axis in the Himalaya. Glob. Ecol. Biogeogr. 23, 52–60 (2014).
Article  Google Scholar 

11.
Carstens, B. C. & Knowles, L. L. Shifting distributions and speciation: species divergence during rapid climate change. Mol. Ecol. 16, 619–627 (2007).
PubMed  Article  Google Scholar 

12.
Yang, S., Dong, H. & Lei, F. Phylogeography of regional fauna on the Tibetan Plateau: a review. Prog. Nat. Sci. 19, 789–799 (2009).
CAS  Article  Google Scholar 

13.
Qu, Y., Lei, F., Zhang, R. & Lu, X. Comparative phylogeography of five avian species: implications for Pleistocene evolutionary history in the Qinghai-Tibetan plateau. Mol. Ecol. 19, 338–351 (2010).
CAS  PubMed  Article  Google Scholar 

14.
Zhao, N. et al. Pleistocene climate changes shaped the divergence and demography of Asian populations of the great tit Parus major: evidence from phylogeographic analysis and ecological niche models. J. Avian Biol. 43, 297–310 (2012).
Article  Google Scholar 

15.
Lei, F., Qu, Y. & Song, G. Species diversification and phylogeographical patterns of birds in response to the uplift of the Qinghai-Tibet Plateau and Quaternary glaciations. Curr. Zool. 60, 149–161 (2014).
Article  Google Scholar 

16.
McKinney, M. L. Extinction vulnerability and selectivity: combining ecological and paleontological views. Annu. Rev. Ecol. System. 28, 495–516 (1997).
Article  Google Scholar 

17.
Biesmeijer, J. C. et al. Parallel declines in pollinators and insect-pollinated plants in Britain and the Netherlands. Science 313, 351–354 (2006).
ADS  CAS  PubMed  Article  Google Scholar 

18.
Colles, A., Liow, L. H. & Prinzing, A. Are specialists at risk under environmental change? Neoecological, paleoecological and phylogenetic approaches. Ecol. Lett. 12, 849–863 (2009).
PubMed  PubMed Central  Article  Google Scholar 

19.
Glatston, A., Wei, F., Zaw, T. & Sherpa, A. Ailurus fulgens. The IUCN Red. List of Threatened Species. (2015).

20.
Choudhury, A. An overview of the status and conservation of the red panda Ailurus fulgens in India, with reference to its global status. Oryx 35, 250–259 (2001).
Article  Google Scholar 

21.
Thapa, A. et al. Predicting the potential distribution of the endangered red panda across its entire range using MaxEnt modeling. Ecol. Evol. 8, 10542–10554 (2018).
PubMed  PubMed Central  Article  Google Scholar 

22.
Wei, F., Feng, Z., Wang, Z., Zhou, A. & Hu, J. Use of the nutrients in bamboo by the red panda (Ailurus fulgens). J. Zool. 248, 535–541 (1999).
Article  Google Scholar 

23.
Roberts, M. S. & Gittleman, J. L. Ailurus fulgens repository.si.edu. Mamm. Species Acc. 222, 1–8 (1984).
Google Scholar 

24.
Su, B., Fu, Y., Wang, Y., Jin, L. & Chakraborty, R. Genetic diversity and population history of the red panda (Ailurus fulgens) as inferred from mitochondrial DNA sequence variations. Mol. Biol. Evol. 18, 1070–1076 (2001).
CAS  PubMed  Article  Google Scholar 

25.
Li, M. et al. Mitochondrial phylogeography and subspecific variation in the red panda (Ailurus fulgens): implications for conservation. Mol. Phylogenet. Evol. 36, 78–89 (2005).
CAS  PubMed  Article  Google Scholar 

26.
Hu, Y. et al. Genetic structuring and recent demographic history of red pandas (Ailurus fulgens) inferred from microsatellite and mitochondrial DNA. Mol. Ecol. 20, 2662–2675 (2011).
PubMed  Article  Google Scholar 

27.
Hu, Y. et al. Genomic evidence for two phylogenetic species and long-term population bottlenecks in red pandas. Sci. Adv. 6, eaax5751 (2020).
ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

28.
Dalui, S. et al. Fine-scale landscape genetics unveiling contemporary asymmetric movement of red panda (Ailurus fulgens) in Kangchenjunga landscape, India. Sci. Rep. 10, 1–12 (2020).
Article  Google Scholar 

29.
Liu, Z. F. et al. Variations ofδ18O in precipitation of the Yarlung Zangbo River Basin. Acta Geograph. Sin. (Chin.) 17, 317–326 (2007).
Google Scholar 

30.
Wang, X. D. et al. Regional assessment of environmental vulnerability in the Tibetan Plateau: development and application of a new method. J. Arid Environ. 721, 929–939 (2008).
Google Scholar 

31.
Zeng, C. et al. Improving sediment load estimations: The case of the Yarlung Zangbo River (the upper Brahmaputra, Tibet Plateau). CATENA 160, 210–211 (2018).
Article  Google Scholar 

32.
Du, Z. et al. Mountain Geoecology and Sustainable Development of the Tibetan Plateau 312 (Kluwer, Riverwoods, 2000).
Google Scholar 

33.
Choudhury, A. Primates in northeast India: an overview of their distribution and conservation status. ENVIS Bull. Wildl. Prot. Areas 1, 92–101 (2001).
Google Scholar 

34.
Meijaard, E. & Groves, C. P. The geography of mammals and rivers in mainland Southeast Asia. In Primate Biogeography (eds Lehman, S. M. & Fleagle, J. G.) 305–329 (Springer, Boston, 2006).
Google Scholar 

35.
Fordham, G., Shanee, S. & Peck, M. Effect of river size on Amazonian primate community structure: a biogeographic analysis using updated taxonomic assessments. Am. J. Primatol. 82, e23136 (2020).
PubMed  Article  Google Scholar 

36.
Bazin, E. et al. Population size does not influence mitochondrial genetic diversity in animals. Science 312, 570 (2006).
ADS  CAS  PubMed  Article  Google Scholar 

37.
Heller, R., Chikhi, L. & Siegismund, H. R. The confounding effect of population structure on Bayesian skyline plot inferences of demographic history. PLoS ONE 8(5), e62992 (2013).
ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

38.
Hu, Y., Qi, D., Wang, H. & Wei, F. Genetic evidence of recent population contraction in the southernmost population of giant pandas. Genetica 138, 1297–1306 (2010).
PubMed  Article  Google Scholar 

39.
Chung, S.-L. et al. Diachronous uplift of the Tibetan plateau starting 40? Myr ago. Nature 394, 769–773 (1998).
ADS  CAS  Article  Google Scholar 

40.
Tapponnier, P. et al. Oblique stepwise rise and growth of the Tibet Plateau. Science 294, 1671–1677 (2001).
ADS  CAS  PubMed  Article  Google Scholar 

41.
Royden, L. H., Burchfiel, B. C. & van der Hilst, R. D. The geological evolution of the Tibetan Plateau. Science 321, 1054–1058 (2008).
ADS  CAS  PubMed  Article  Google Scholar 

42.
Kapp, P., DeCelles, P. G., Gehrels, G. E., Heizler, M. & Ding, L. Geological records of the Lhasa-Qiangtang and Indo-Asian collisions in the Nima area of central Tibet. Geol. Soc. Am. Bull. 119, 917–933 (2007).
ADS  Article  Google Scholar 

43.
Schmidt, F., Franke, F. A., Shirley, M. H., Vliet, K. A. & Villanova, V. L. The importance of genetic research in zoo breeding programmes for threatened species: the African dwarf crocodiles (genus Osteolaemus) as a case study. Int. Zoo Yearb. 49, 125–136 (2015).
Article  Google Scholar 

44.
Gippoliti, S., Cotterill, F. P., Zinner, D. & Groves, C. P. Impacts of taxonomic inertia for the conservation of African ungulate diversity: an overview. Biol. Rev. 93, 115–130 (2018).
PubMed  Article  Google Scholar 

45.
McClenachan, L., Ferretti, F. & Baum, J. K. From archives to conservation: why historical data are needed to set baselines for marine animals and ecosystems. Conserv. Lett. 5, 349–359 (2012).
Article  Google Scholar 

46.
Grace, M. et al. Using historical and palaeoecological data to inform ambitious species recovery targets. Philos. Trans. R. Soc. Lond. B 374, 20190297 (2019).
Article  Google Scholar 

47.
Rozas, J. et al. DnaSP 6: DNA sequence polymorphism analysis of large data sets. Mol. Biol. Evol. 34, 3299–3302 (2017).
CAS  Article  Google Scholar 

48.
Bouckaert, R. et al. BEAST 2: a software platform for Bayesian evolutionary analysis. PLoS Comput. Biol. 10, e1003537 (2014).
PubMed  PubMed Central  Article  Google Scholar 

49.
Nylander, J. A. A. MrModeltest ver. 2. 2004: Evolutionary Biology Centre (Uppsala University, Sweden, 2004).
Google Scholar 

50.
Sato, J. J. et al. Deciphering and dating the red panda’s ancestry and early adaptive radiation of Musteloidea. Mol. Phylogenet. Evol. 53, 907–922 (2009).
CAS  PubMed  Article  Google Scholar 

51.
Rambaut, A. & Drummond, A. J. Tracer version 1.5 [computer program]. (2009).

52.
Rambaut, A. FigTree version 1.4. 0. Available at http://tree.bio.ed.ac.uk/software/figtree. Accessed October (2016).

53.
Bandelt, H.-J., Forster, P. & Röhl, A. Median-joining networks for inferring intraspecific phylogenies. Mol. Biol. Evol. 16, 37–48 (1999).
CAS  PubMed  Article  Google Scholar 

54.
Corander, J. & Marttinen, P. Bayesian identification of admixture events using multilocus molecular markers. Mol. Ecol. 15, 2833–2843 (2006).
PubMed  Article  Google Scholar 

55.
Corander, J., Marttinen, P., Sirén, J. & Tang, J. Enhanced Bayesian modelling in BAPS software for learning genetic structures of populations. BMC Bioinform. 9, 539 (2008).
Article  Google Scholar 

56.
Dupanloup, I., Schneider, S. & Excoffier, L. A simulated annealing approach to define the genetic structure of populations. Mol. Ecol. 11, 2571–2581 (2002).
CAS  PubMed  Article  Google Scholar 

57.
Rogers, A. R. & Harpending, H. Population growth makes waves in the distribution of pairwise genetic differences. Mol. Biol. Evol. 9, 552–569 (1992).
CAS  PubMed  Google Scholar 

58.
Tajima, F. Statistical method for testing the neutral mutation hypothesis by DNA polymorphism. Genetics 123, 585–595 (1989).
CAS  PubMed  PubMed Central  Google Scholar 

59.
Fu, Y.-X. Statistical tests of neutrality of mutations against population growth, hitchhiking and background selection. Genetics 147, 915–925 (1997).
CAS  PubMed  PubMed Central  Google Scholar 

60.
Excoffier, L. & Lischer, H. E. Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows. Mol. Ecol. Resour. 10, 564–567 (2010).
PubMed  Article  Google Scholar  More

1.
Grueter, C. C., Qi, X., Li, B. & Li, M. Multilevel societies. Curr. Biol. 27, 984–986 (2017).
Article  CAS  Google Scholar 
2.
Grueter, C. C., Matsuda, I., Zhang, P. & Zinner, D. Multilevel societies in primates and other mammals: Introduction to the special issue. Int. J. Primatol. 33, 993–1001 (2012).
PubMed  PubMed Central  Article  Google Scholar 

3.
Matsuda, I. et al. Comparisons of intraunit relationships in nonhuman primates living in multilevel social systems. Int. J. Primatol. 33, 1038–1053 (2012).
Article  Google Scholar 

4.
Papageorgiou, D. et al. The multilevel society of a small-brained bird. Curr. Biol. 29, R1120–R1121 (2019).
CAS  PubMed  Article  Google Scholar 

5.
Grueter, C. C. et al. Multilevel Organisation of Animal Sociality. Trends Ecol. Evol. https://doi.org/10.1016/j.tree.2020.05.003 (2020).
Article  PubMed  Google Scholar 

6.
Schreier, A. L. & Swedell, L. The fourth level of social structure in a multi-level society: ecological and social functions of clans in Hamadryas Baboons. Am. J. Primatol. 71, 948–955 (2009).
PubMed  Article  Google Scholar 

7.
Snyder-Mackler, N., Beehner, J. C. & Bergman, T. J. Defining higher levels in the multilevel societies of Geladas (Theropithecus gelada). Int. J. Primatol. 33, 1054–1068 (2012).
Article  Google Scholar 

8.
Whitehead, H. et al. Multilevel societies of female sperm whales (Physeter macrocephalus) in the Atlantic and Pacific: Why are they so different?. Int. J. Primatol. 33, 1142–1164 (2012).
Article  Google Scholar 

9.
Tong, W., Shapiro, B. & Rubenstein, D. I. Genetic relatedness in two-tiered plains zebra societies suggests that females choose to associate with kin. Behaviour 152, 2059–2078 (2015).
Article  Google Scholar 

10.
Rubenstein, D. I. & Hack, M. Ecology and social structure of the Gobi khulan Equus hemionus subsp. in the Gobi B National Park, Mongolia. In Sexual Selection in Primates: New and Comparative Perspectives 266–279 (2004). https://doi.org/10.1017/CBO9780511542459.017.

11.
Ozogany, K. & Vicsek, T. Modeling leadership hierarchy in multilevel animal societies. Cornell Univ. Libr. Phys. arXiv:1403.0260 (2014).

12.
Swedell, L. & Plummer, T. A papionin multilevel society as a model for hominin social evolution. Int. J. Primatol. 33, 1165–1193 (2012).
Article  Google Scholar 

13.
Linklater, W. L. Adaptive explanation in socio-ecology: Lessons from the equidae. Biol. Rev. 75, 1–20 (2000).
CAS  PubMed  Article  Google Scholar 

14.
Forcina, G. et al. From groups to communities in western lowland gorillas. Proc. R. Soc. B Biol. Sci. https://doi.org/10.1098/rspb.2018.2019 (2019).
Article  Google Scholar 

15.
Zhang, P., Li, B., Qi, X., MacIntosh, A. J. J. & Watanabe, K. A proximity-based social network of a group of Sichuan snub-nosed monkeys (Rhinopithecus roxellana). Int. J. Primatol. 33, 1081–1095 (2012).
CAS  Article  Google Scholar 

16.
de Silva, S., Schmid, V. & Wittemyer, G. Fission–fusion processes weaken dominance networks of female Asian elephants in a productive habitat. Behav. Ecol. 28, 243–252 (2016).
Article  Google Scholar 

17.
Wittemyer, G., Douglas-Hamilton, I. & Getz, W. M. The socioecology of elephants: Analysis of the processes creating multitiered social structures. Anim. Behav. 69, 1357–1371 (2005).
Article  Google Scholar 

18.
Qi, X. G. et al. Satellite telemetry and social modeling offer new insights into the origin of primate multilevel societies. Nat. Commun. https://doi.org/10.1038/ncomms6296 (2014).
Article  PubMed  PubMed Central  Google Scholar 

19.
Stead, S. M. & Teichroeb, J. A. A multi-level society comprised of one-male and multi-male core units in an African colobine (Colobus angolensis ruwenzorii). PLoS ONE 14, e0217666 (2019).
CAS  PubMed  PubMed Central  Article  Google Scholar 

20.
Ward, A. & Webster, M. Attraction, Alignment and repulsion: how groups form and how they function. In Sociality: The Behaviour of Group-Living Animals 29–54 (Springer, Cham, 2016). https://doi.org/10.1007/978-3-319-28585-6_3.

21.
Aureli, F., Schaffner, C. M., Asensio, N. & Lusseau, D. What is a subgroup? How socioecological factors influence interindividual distance. Behav. Ecol. 23, 1308–1315 (2012).
Article  Google Scholar 

22.
Maciej, P., Patzelt, A., Ndao, I., Hammerschmidt, K. & Fischer, J. Social monitoring in a multilevel society: A playback study with male Guinea baboons. Behav. Ecol. Sociobiol. 67, 61–68 (2013).
PubMed  Article  Google Scholar 

23.
Bergman, T. J. Experimental evidence for limited vocal recognition in a wild primate: Implications for the social complexity hypothesis. In Proceedings of the Royal Society B: Biological Sciences 277, 3045–3053 (Royal Society, London, 2010).

24.
Bowler, M., Knogge, C., Heymann, E. W. & Zinner, D. Multilevel societies in new world primates? Flexibility may characterize the organization of Peruvian red uakaris (Cacajao calvus ucayalii). Int. J. Primatol. 33, 1110–1124 (2012).
PubMed  PubMed Central  Article  Google Scholar 

25.
Farine, D. R. & Whitehead, H. Constructing, conducting and interpreting animal social network analysis. J. Anim. Ecol. 84, 1144–1163 (2015).
PubMed  PubMed Central  Article  Google Scholar 

26.
Hemelrijk, C. K. Towards the integration of social dominance and spatial structure. Anim. Behav. 59, 1035–1048 (2000).
CAS  PubMed  Article  Google Scholar 

27.
Miller, R. Seasonal movements and home ranges of feral horse bands in Wyoming’s Red Desert. J. Range Manag. 36, 199 (1983).
Article  Google Scholar 

28.
Miller, R. & Dennisto, R. H. I. Interband dominance in feral horses. Z. Tierpsychol. 51, 41–47 (1979).
Article  Google Scholar 

29.
Feh, C. Relationships and communication in socially natural horse herds. In The Domestic Horse: The Origins, Development and Management of its Behaviour (eds Mills, D. S. & McDonnell, S. M.) 83–93 (Cambridge University Press, Cambridge, 2005).
Google Scholar 

30.
Boyd, L., Scorolli, A., Nowzari, H. & Bouskila, A. Social organization of wild equids. In Wild Equids: Ecology, Management, and Conservation (eds Ransom, J. I. & Kaczensky, P.) 7–22 (Johns Hopkins University Press, Baltimore, 2016).
Google Scholar 

31.
Ringhofer, M. et al. Comparison of the social systems of primates and feral horses: Data from a newly established horse research site on Serra D’Arga, northern Portugal. Primates 58, 479–484 (2017).
PubMed  Article  Google Scholar 

32.
Inoue, S. et al. Spatial positioning of individuals in a group of feral horses: A case study using drone technology. Mammal Res. 64, 249–259 (2019).
Article  Google Scholar 

33.
Inoue, S., Yamamoto, S., Ringhofer, M., Mendonça, R. S. & Hirata, S. Lateral position preference in grazing feral horses. Ethology 00, 1–9 (2019).
Google Scholar 

34.
Ringhofer, M. et al. Herding mechanisms to maintain the cohesion of a harem group: two interaction phases during herding. J. Ethol. 38, 71–77. https://doi.org/10.1007/s10164-019-00622-5 (2019).
Article  Google Scholar 

35.
Go, C. K. et al. A mathematical model of herding in horse-harem group. J. Ethol. https://doi.org/10.1007/s10164-020-00656-0 (2020).
Article  Google Scholar 

36.
Young, D. et al. Package ‘Mixtools’ Title Tools for Analyzing Finite Mixture Models. J Stat Software. 32(6), 1–29. https://doi.org/10.18637/jss.v032.i06 (2009).

37.
Fieberg, J. & Kochanny, C. O. Quantifying home-range overlap: The importance of the utilization distribution. J. Wildl. Manag. 69, 1346–1359 (2005).
Article  Google Scholar 

38.
Torney, C. J. et al. Inferring the rules of social interaction in migrating caribou. Philos. Trans. R. Soc. B Biol. Sci. 373, 20170385 (2018).
Article  Google Scholar 

39.
Pun, A., Birch, S. A. J. & Baron, A. S. Infants use relative numerical group size to infer social dominance. Proc. Natl. Acad. Sci. 113, 2376–2381 (2016).
CAS  PubMed  Article  ADS  Google Scholar 

40.
Berger, J. Organizational systems and dominance in feral horses in the Grand Canyon. Behav. Ecol. Sociobiol. 2, 131–146 (1977).
Article  Google Scholar 

41.
de Silva, S. & Wittemyer, G. A comparison of social organization in Asian elephants and African savannah elephants. Int. J. Primatol. 33, 1125–1141 (2012).
Article  Google Scholar 

42.
Zhang, P., Watanabe, K., Li, B. & Qi, X. Dominance relationships among one-male units in a provisioned free-ranging band of the Sichuan snub-nosed monkeys (Rhinopithecus roxellana) in the Qinling Mountains, China. Am. J. Primatol. 70, 634–641 (2008).
PubMed  Article  Google Scholar 

43.
Grueter, C. & Zinner, D. Nested societies. Convergent adaptations of baboons and snub-nosed monkeys? Primate Rep. 70, 1–98 (2004).

44.
Rubenstein, D. I. & Hack, M. Natural and sexual selection and the evolution of multi-level societies: Insights from zebras with comparisons to primates. In Sexual Selection in Primates: New and Comparative Perspectives 266–279 (2004). https://doi.org/10.1017/CBO9780511542459.017.

45.
Grueter, C. C. & Van Schaik, C. P. Evolutionary determinants of modular societies in colobines. Behav. Ecol. 21, 63–71 (2010).
Article  Google Scholar 

46.
Gray, M. E. An infanticide attempt by a free-roaming feral stallion (Equus caballus). Biol. Lett. 5, 23–25 (2009).
PubMed  Article  Google Scholar 

47.
Boyd, L. & Keiper, R. Behavioural ecology of feral horses. In The Domestic Horse: The Origins, Development and Management of its Behaviour (eds Mills, D. S. & McDonnell, S. M.) 55–82 (Cambridge University Press, Cambridge, 2005).
Google Scholar 

48.
Christensen, J. W., Ladewig, J., Søndergaard, E. & Malmkvist, J. Effects of individual versus group stabling on social behaviour in domestic stallions. Appl. Anim. Behav. Sci. 75, 233–248 (2002).
Article  Google Scholar 

49.
R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, Vienna, 2019).
Google Scholar 

50.
Hoppitt, W. J. E. & Farine, D. R. Association indices for quantifying social relationships: How to deal with missing observations of individuals or groups. Anim. Behav. 136, 227–238 (2018).
Article  Google Scholar 

51.
Calenge, C. & Fortmann-Roe, S. Package ‘ adehabitatHR ’ v0.4.18. R CRAN Repos. (2020).

52.
Couzin, I. D., Krause, J., James, R., Ruxton, G. D. & Franks, N. R. Collective memory and spatial sorting in animal groups. J. Theor. Biol. 218, 1–11 (2002).
MathSciNet  PubMed  Article  Google Scholar 

53.
Hinde, R. A. Interactions, relationships and social structure. Man New Ser. 11, 1–17 (1976).
Google Scholar 

54.
King, A. J., Sueur, C., Huchard, E. & Cowlishaw, G. A rule-of-thumb based on social affiliation explains collective movements in desert baboons. Anim. Behav. 82, 1337–1345 (2011).
Article  Google Scholar 

55.
Cairns, S. J. & Schwager, S. J. A comparison of association indices. Anim. Behav. 35, 1454–1469 (1987).
Article  Google Scholar 

56.
Dray, S. & Dufour, A. B. The ade4 package: Implementing the duality diagram for ecologists. J Stat Software https://doi.org/10.18637/jss.v022.i0 (2007).
Article  Google Scholar 

57.
Croft, D. P., Madden, J. R., Franks, D. W. & James, R. Hypothesis testing in animal social networks. Trends Ecol. Evol. 26, 502–507 (2011).
PubMed  Article  Google Scholar 

58.
Franks, D. W., Weiss, M. N., Silk, M. J., Perryman, R. J. Y. & Croft, D. P. Calculating effect sizes in animal social network analysis. Methods Ecol. Evol. https://doi.org/10.1111/2041-210X.13429 (2020).
Article  Google Scholar 

59.
Weiss, M. N. et al. Common permutations of animal social network data are not appropriate for hypothesis testing using linear models. bioRxiv 1–26 (2020). https://doi.org/10.1101/2020.04.29.068056.

60.
Sosa, S. et al. A multilevel statistical toolkit to study animal social networks: Animal Network Toolkit ( ANT ) R package. bioRxiv 347005 (2018). https://doi.org/10.1101/347005

61.
Sosa, S. Social network analysis. In International Encyclopedia of the Social & Behavioral Sciences 2nd Edn, 1–18 (eds Vonk, J. & Shackleford, T. K.) (Springer, Berlin, 2018). https://doi.org/10.1016/B978-0-08-097086-8.10563-X.
Google Scholar 

62.
Damien Farine. Animal Social Network Inference and Permutations for Ecologists in R using asnipe. Methods in Ecology and Evolution. 4(12), 1187–1194. https://doi.org/10.1111/2041-210X.12121 (2014).

63.
Bastian, M., Heymann, S. & Jacomy, M. Gephi: An open source software for exploring and manipulating networks. In International AAAI Conference on Weblogs and Social Media 361–362 (2009). More

1.
Vitousek PM, Porder S, Houlton BZ, Oliver A, Vitousek PM, Porder S, et al. Terrestrial phosphorus limitation: mechanisms, implications, and nitrogen–phosphorus interactions. Ecol Appl. 2010;20:5–15.
PubMed  Article  Google Scholar 
2.
Lundstrom US, Van Breemen N, Bain D. The podzolization process. A review. Geoderma. 2000;94:91–107.
CAS  Article  Google Scholar 

3.
Crowley KF, Mcneil BE, Lovett GM, Canham CD, Driscoll CT, Rustad LE, et al. Do nutrient limitation patterns shift from nitrogen toward phosphorus with increasing nitrogen deposition across the northeastern United States? Ecosystems. 2012;15:940–57.
CAS  Article  Google Scholar 

4.
Jonard M, Fürst A, Verstraeten A, Thimonier A, Timmermann V, Potočić N, et al. Tree mineral nutrition is deteriorating in Europe. Glob Change Biol. 2015;21:418–30.
Article  Google Scholar 

5.
Hayward J, Horton TR, Nu MA. Ectomycorrhizal fungal communities coinvading with Pinaceae host plants in Argentina: Gringos bajo el bosque. N Phytol. 2015;208:497–506.
Article  Google Scholar 

6.
Köhler J, Yang N, Pena R, Raghavan V, Polle A, Meier IC. Ectomycorrhizal fungal diversity increases phosphorus uptake efficiency of European beech. N Phytol. 2018;220:1200–10.
Article  Google Scholar 

7.
Kranabetter JM, Harman-Denhoed R, Hawkins BJ. Saprotrophic and ectomycorrhizal fungal sporocarp stoichiometry (C: N: P) across temperate rainforests as evidence of shared nutrient constraints among symbionts. N Phytol. 2019;221:482–92.
CAS  Article  Google Scholar 

8.
Ning C, Xiang W, Mueller GM. Differences in ectomycorrhizal community assembly between native and exotic pines are reflected in their enzymatic functional capacities. Plant Soil. 2019;446:179–93.
Article  CAS  Google Scholar 

9.
Courty PE, Buée M, Diedhiou AG, Frey-Klett P, Le Tacon F, Rineau F, et al. The role of ectomycorrhizal communities in forest ecosystem processes: new perspectives and emerging concepts. Soil Biol Biochem. 2010;42:679–98.
CAS  Article  Google Scholar 

10.
Cairney JWG. Ectomycorrhizal fungi: the symbiotic route to the root for phosphorus in forest soils. Plant Soil. 2011;344:51–71.
CAS  Article  Google Scholar 

11.
Hodge A. Accessibility of inorganic and organic nutrients for mycorrhizas. In: Johnson NC, Gehring CA, Jansa J, editors. Mycorrhizal mediation of soil: fertility, structure, and carbon storage. Amsterdam: Elsevier; 2017. p. 129–48.

12.
Plassard C, Louche J, Ali MA, Duchemin M, Legname E, Cloutier-Hurteau B. Diversity in phosphorus mobilisation and uptake in ectomycorrhizal fungi. Ann Sci. 2011;68:33–43.
Article  Google Scholar 

13.
Becquer A, Trap J, Irshad U, Ali MA, Claude P. From soil to plant, the journey of P through trophic relationships and ectomycorrhizal association. Front Plant Sci. 2014;5:1–7.
Article  Google Scholar 

14.
Tunlid A, Floudas D, Koide RT, Rineau F. Soil organic matter decomposition mechanisms in ectomycorrhizal fungi. In: Martin FM, editor. Molecular mycorrhizal symbiosis. 1st ed. Hoboken, New Jersey, USA: John Wiley & Sons, Inc; 2017. p. 257–75.

15.
Nannipieri P, Giagnoni L, Landi L, Renella G. Role of phosphatase enzymes in soil. In: Bunemann et al., editors. Phosphorus in action. Berlin, Heidelberg: Springer Verlag; 2011. p. 215–43.

16.
Jarosch KA, Kandeler E, Frossard E, Bünemann EK. Is the enzymatic hydrolysis of soil organic phosphorus compounds limited by enzyme or substrate availability? Soil Biol Biochem. 2019;139:1–11.
Article  CAS  Google Scholar 

17.
Bending GD, Read DJ. The structure and function of the vegetative mycelium of ectomycorrhizal plants: VI. Activities of nutrient mobilizing enzymes in birch litter colonized by Paxillus involutus (Fr.) Fr. N Phytol. 1995;130:411–7.
CAS  Article  Google Scholar 

18.
Liu X, Feng F, He X, Song F. The effect of ectomycorrhizal fungi on litter decomposition and phosphorus availability to Pinus koraiensis. Int J Agric Biol. 2017;19:1019–24.
CAS  Article  Google Scholar 

19.
Read DJ, Perez-Moreno J. Mycorrhizas and nutrient cycling in ecosystems—a journey towards relevance? N Phytol. 2003;157:475–92.
Article  Google Scholar 

20.
Jones MD, Twieg BD, Ward V, Barker JS, Durall DM, Simard SW. Functional complementarity of Douglas-fir ectomycorrhizas for extracellular enzyme activity after wildfire or clearcut logging. Funct Ecol. 2010;24:1139–51.
Article  Google Scholar 

21.
Alvarez M, Huygens D, Díaz LM, Villanueva CA, Heyser W, Boeckx P. The spatial distribution of acid phosphatase activity in ectomycorrhizal tissues depends on soil fertility and morphotype, and relates to host plant phosphorus uptake. Plant, Cell Environ. 2012;35:126–35.
CAS  Article  Google Scholar 

22.
Walker JKM, Cohen H, Higgins LM, Kennedy PG. Testing the link between community structure and function for ectomycorrhizal fungi involved in a global tripartite symbiosis. N Phytol. 2014;202:287–96.
CAS  Article  Google Scholar 

23.
Zavišić A, Nassal P, Yang N, Heuck C, Spohn M, Marhan S, et al. Phosphorus availabilities in beech (Fagus sylvatica L.) forests impose habitat filtering on ectomycorrhizal communities and impact tree nutrition. Soil Biol Biochem. 2016;98:127–37.
Article  CAS  Google Scholar 

24.
Patterson A, Flores-renter L, Whipple A, Whitham T, Gehring C. Common garden experiments disentangle plant genetic and environmental contributions to ectomycorrhizal fungal community structure. N Phytol. 2019;221:493–502.
CAS  Article  Google Scholar 

25.
Koide RT, Fernandez C, Petprakob K. General principles in the community ecology of ectomycorrhizal fungi. Ann Sci. 2011;68:45–55.
Article  Google Scholar 

26.
Bahram M, Kohout P, Anslan S, Harend H, Abarenkov K. Stochastic distribution of small soil eukaryotes resulting from high dispersal and drift in a local environment. ISME J. 2016;10:885–96.
PubMed  Article  Google Scholar 

27.
Courty P-E, Munoz F, Selosse M-A, Duchemin M, Criquet S, Ziarelli F, et al. Into the functional ecology of ectomycorrhizal communities: environmental filtering of enzymatic activities. J Ecol. 2016;104:1585–98.
Article  Google Scholar 

28.
Walker JKM, Ward V, Jones MD. Ectomycorrhizal fungal exoenzyme activity differs on spruce seedlings planted in forests versus clearcuts. Trees – Struct Funct. 2016;30:497–508.
CAS  Article  Google Scholar 

29.
Kyaschenko J, Clemmensen KE, Karltun E, Lindahl BD. Below-ground organic matter accumulation along a boreal forest fertility gradient relates to guild interaction within fungal communities. Ecol Lett. 2017;20:1546–55.
PubMed  Article  Google Scholar 

30.
Kranabetter JM, Hawkins BJ, Jones MD, Robbins S, Dyer T, Li T. Species turnover (beta-diversity) in ectomycorrhizal fungi linked to NH4 (+) uptake capacity. Mol Ecol. 2015;24:5992–6005.
CAS  PubMed  Article  PubMed Central  Google Scholar 

31.
Johnson NC, Wilson GWT, Bowker MA, Wilson JA, Miller RM. Resource limitation is a driver of local adaptation in mycorrhizal symbioses. Proc Natl Acad Sci. 2010;107:2093–8.
CAS  PubMed  Article  PubMed Central  Google Scholar 

32.
Pickles BJ, Twieg BD, Neill GAO, Mohn WW, Simard SW. Local adaptation in migrated interior Douglas-fir seedlings is mediated by ectomycorrhizas and other soil factors. N Phytol. 2015;207:858–71.
Article  Google Scholar 

33.
Kranabetter JM, Stoehr M, O’Neill GA. Ectomycorrhizal fungal maladaptation and growth reductions associated with assisted migration of Douglas-fir. N Phytol. 2015;206:1135–44.
CAS  Article  Google Scholar 

34.
Mooshammer M, Wanek W, Zechmeister-boltenstern S, Richter A. Stoichiometric imbalances between terrestrial decomposer communities and their resources: mechanisms and implications of microbial adaptations to their resources. Front Microbiol. 2014;5:1–11.
Article  Google Scholar 

35.
Treseder KK, Vitousek PM. Effects of soil nutrient availablity on investment in acquisition of N and P in Hawaiian rain forests. Ecology. 2001;82:946–54.
Article  Google Scholar 

36.
Revillini D, Gehring CA, Johnson NC. The role of locally adapted mycorrhizas and rhizobacteria in plant–soil feedback systems. Funct Ecol. 2016;30:1086–98.
Article  Google Scholar 

37.
Marklein AR, Houlton BZ. Nitrogen inputs accelerate phosphorus cycling rates across a wide variety of terrestrial ecosystems. N Phytol. 2011;193:696–704.
Article  CAS  Google Scholar 

38.
Zechmeister-Boltenstern S, Keiblinger KM, Mooshammer M, Peñuelas J, Richter A, Sardans J, et al. The application of ecological stoichiometry to plant-microbial-soil organic matter transformations. Ecol Monogr. 2015;85:133–55.
Article  Google Scholar 

39.
Carter MR, Gregorich E. Soil sampling and methods of analysis. 2nd ed. Boca Raton, Florida: CRC Press; 2008. p. 823.

40.
Green RN, Trowbridge RL, Klinka K. Towards a taxonomic classification of humus forms. Sci Monogr. 1993;29:1–48.
Google Scholar 

41.
Cade-Menun BJ. Improved peak identification in 31 P-NMR spectra of environmental samples with a standardized method and peak library. Geoderma. 2015;257–258:102–14.
Article  CAS  Google Scholar 

42.
Pritsch K, Courty PE, Churin JL, Cloutier-Hurteau B, Ali MA, Damon C, et al. Optimized assay and storage conditions for enzyme activity profiling of ectomycorrhizae. Mycorrhiza. 2011;21:589–600.
CAS  PubMed  Article  Google Scholar 

43.
Eivazi F, Tabatabai M. Phosphatases in soils. Soil Biol Biochem. 1977;9:167–72.
CAS  Article  Google Scholar 

44.
Pritsch K, Garbaye J. Enzyme secretion by ECM fungi and exploitation of mineral nutrients from soil organic matter. Ann Sci. 2011;68:25–32.
Article  Google Scholar 

45.
Courty PE, Pritsch K, Schloter M, Hartmann A, Garbaye J. Activity profiling of ectomycorrhiza communities in two forest soils using multiple enzymatic tests. N Phytol. 2005;167:309–19.
CAS  Article  Google Scholar 

46.
Kõljalg U, Nilsson RH, Abarenkov K, Tedersoo L, Taylor AFS, Bahram M, et al. Towards a unified paradigm for sequence-based identification of fungi. Mol Ecol. 2013;22:5271–7.
Article  CAS  PubMed  Google Scholar 

47.
Team RC. R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2017.
Google Scholar 

48.
Gerz M, Guillermo Bueno C, Ozinga WA, Zobel M, Moora M. Niche differentiation and expansion of plant species are associated with mycorrhizal symbiosis. J Ecol. 2018;106:254–64.
CAS  Article  Google Scholar 

49.
Carrara JE, Walter CA, William JSH, Brzostek ER, Averill TPC. Interactions among plants, bacteria, and fungi reduce extracellular enzyme activities under long-term N fertilization. Glob Change Biol. 2018;24:2721–34.
Article  Google Scholar 

50.
Bartlett EM, Lewis DH. Surface phosphatase activity of mycorrhizal roots of Beech. Soil Biol Biochem. 1973;5:249–57.
CAS  Article  Google Scholar 

51.
Allison SD, Vitousek PM. Responses of extracell enzymes to simple and complex nutrient inputs. Soil Biol Biochem. 2005;37:937–44.

52.
Alexander IJ, Hardy K. Surface phosphatase activity of Sitka spruce mycorrhizas from a serpentine site. Soil Biol Biochem. 1981;13:301–5.
CAS  Article  Google Scholar 

53.
Ali MA, Louche J, Legname E, Duchemin M, Plassard C. Pinus pinaster seedlings and their fungal symbionts show high plasticity in phosphorus acquisition in acidic soils. Tree Physiol. 2009;29:1587–97.
CAS  PubMed  Article  Google Scholar 

54.
Antibus RK, Sinsabaugh RL, Linkins AE. Phosphatase activities and phosphorus uptake from inositol phosphate by ectomycorrhizal fungi. Can J Bot. 1992;70:794–801.
CAS  Article  Google Scholar 

55.
Tibbett M, Sanders FE, Cairney JWG. The effect of temperature and inorganic phosphorus supply on growth and acid phosphatase production in arctic and temperate strains of ectomycorrhizal Hebeloma spp. in axenic culture. Mycol Res. 1998;102:129–35.
CAS  Article  Google Scholar 

56.
van Aarle IM, Plassard C. Spatial distribution of phosphatase activity associated with ectomycorrhizal plants is related to soil type. Soil Biol Biochem. 2010;42:324–30.
Article  CAS  Google Scholar 

57.
Kroehler J, Linkins E. The effects of organic and inorganic phosphorus concentration on the acid phosphatase activity of ectomycorrhizal fungi. Can J Bot. 1987;66:750–6.
Article  Google Scholar 

58.
Horsman GP, Zechel DL. Phosphonate biochemistry. Chem Rev. 2017;117:5704–83.
CAS  PubMed  Article  Google Scholar 

59.
Turner BL. Inositol phosphates in soil: amounts, forms and significance of the phosphorylated inositol stereoisomers. In: Turner BL, Richardson AE, Mullaney EJ, editors. Inositol phosphates: linking agriculture and the environment. Wallingford, UK: CAB International; 2007. p. 186–207.

60.
Colpaert JV, Van Laere A, Van Tichelen KK, Van, Assche JA. The use of inositol hexaphosphate as a phosphorus as a phosphorus source by mycorrhizal and non-mycorrhizal Scots Pine (Pinus sylvestris). Funct Ecol. 1997;11:407–15.
Article  Google Scholar 

61.
Leake JR, Miles W. Phosphodiesters as mycorrhizal P sources I. Phosphodiesterase production and the utilization of DNA as a phosphorus source by the ericoid mycorrhizal fungus Hymenoseyphus ericae. N Phytol. 1996;132:435–43.
CAS  Article  Google Scholar 

62.
Lang F, Krüger J, Amelung W, Willbold S, Frossard E, Bünemann EK, et al. Soil phosphorus supply controls P nutrition strategies of beech forest ecosystems in Central Europe. Biogeochemistry. 2017;136:5–29.
CAS  Article  Google Scholar 

63.
Criquet S, Ferre E, Farnet AM, Le Petit J. Annual dynamics of phosphatase activities in an evergreen oak litter: Influence of biotic and abiotic factors. Soil Biol Biochem. 2004;36:1111–8.
CAS  Article  Google Scholar 

64.
Antibus RK, Bower D, Dighton J. Root surface phosphatase activities and uptake of 32P-labelled inositol phosphate in field-collected gray birch and red maple roots. Mycorrhiza. 1997;7:39–46.
CAS  Article  Google Scholar 

65.
Steidinger BS, Turner BL, Corrales A, Dalling JW. Variability in potential to exploit different soil organic phosphorus compounds among tropical montane tree species. Funct Ecol. 2015;29:121–30.
Article  Google Scholar 

66.
Tate KR, Newman RH. Phosphorus fractions of a climosequence of soils in New Zealand tussock grasslands. Soil Biol Biochem. 1981;191:191–6.
Google Scholar 

67.
Stewart JWB, Tiessen H. Dynamics of soil organic phosphorus. Biogeochemistry. 1987;4:41–60.
CAS  Article  Google Scholar 

68.
Turner BL, Haygarth PM. Phosphatase activity in temperate pasture soils: potential regulation of labile organic phosphorus turnover by phosphodiesterase activity. Sci Total Environ. 2005;344:27–36.
CAS  PubMed  Article  Google Scholar 

69.
Reich PB, Oleksyn J. Global patterns of plant leaf N and P in relation to temperature and latitude. PNAS. 2004;101:11001–6.
CAS  PubMed  Article  Google Scholar 

70.
Vandenkoornhuyse P, Quaiser A, Duhamel M, Le Van A, Dufresne A. The importance of the microbiome of the plant holobiont. N Phytol. 2015;206:1196–206.
Article  Google Scholar 

71.
Zhang H, Wang J, Wang J, Guo Z, Geo G, Zeng D. Tree stoichiometry and nutrient resorption along a chronosequence of Metasequoia glyptostroboides forests in coastal China. Ecol Manag. 2018;430:445–50.
Article  Google Scholar 

72.
Duquesnay A, Dupouey JL, Clement A, Ulrich E, Tacon FLE. Spatial and temporal variability of foliar mineral concentration in beech (Fagus sylvatica) stands in northeastern France. Tree Physiol. 2000;20:13–22.
CAS  PubMed  Article  PubMed Central  Google Scholar 

73.
Kranabetter JM, Berch S, MacKinnon J, Ceska O, Dunn D, Ott P. Species–area curve and distance–decay relationships indicate habitat thresholds of ectomycorrhizal fungi in an old-growth Pseudotsuga menziesii landscape. Divers Distrib. 2018;24:755–64.
Article  Google Scholar 

74.
Zavisic A, Yang N, Marhan S, Kandeler E, Polle A. Forest soil phosphorus resources and fertilization affect ectomycorrhizal community composition, Beech P uptake efficiency, and photosynthesis. Front Plant Sci. 2018;9:1–13.
Article  Google Scholar 

75.
Bogar L, Peay KG, Kornfeld A, Huggins J, Hortal S, Anderson I, et al. Plant-mediated partner discrimination in ectomycorrhizal mutualisms. Mycorrhiza. 2019;29:97–111.
CAS  PubMed  Article  PubMed Central  Google Scholar 

76.
Hortal S, Plett KL, Plett JM, Cresswell T, Johansen M, Pendall E, et al. Role of plant–fungal nutrient trading and host control in determining the competitive success of ectomycorrhizal fungi. ISME J. 2017;11:2666–76.
CAS  PubMed  PubMed Central  Article  Google Scholar 

77.
Vellend M. Conceptual synthesis in community ecology. Q Rev Biol. 2010;85:183–206.
PubMed  Article  PubMed Central  Google Scholar 

78.
Nicholson BA, Jones MD. Early-successional ectomycorrhizal fungi effectively support extracellular enzyme activities and seedling nitrogen accumulation in mature forests. Mycorrhiza. 2017;27:247–60.
CAS  PubMed  Article  PubMed Central  Google Scholar 

79.
Marupakula S, Mahmood S, Jernberg J, Nallanchakravarthula S, Fahad ZA, Finlay RD. Bacterial microbiomes of individual ectomycorrhizal Pinus sylvestris roots are shaped by soil horizon and differentially sensitive to nitrogen addition. Environ Microbiol. 2017;19:4736–53.
CAS  PubMed  Article  PubMed Central  Google Scholar 

80.
Cullings K, Ishkhanova G, Henson J. Defoliation effects on enzyme activities of the ectomycorrhizal fungus Suillus granulatus in a Pinus contorta (lodgepole pine) stand in Yellowstone National Park. Oecologia. 2008;158:77–83.
PubMed  Article  Google Scholar 

81.
Jones MD, Phillips LA, Treu R, Ward V, Berch SM. Functional responses of ectomycorrhizal fungal communities to long-term fertilization of lodgepole pine (Pinus contorta Dougl. ex Loud. var. latifolia Engelm.) stands in central British Columbia. Appl Soil Ecol. 2012;60:29–40.
Article  Google Scholar  More

1.
Lüthi, D. et al. High-resolution carbon dioxide concentration record 650,000–800,000 years before present. Nature 453, 379–382. https://doi.org/10.1038/nature06949 (2008).
CAS  Article  PubMed  ADS  Google Scholar 
2.
NASA. Global Vital Signs: Vital Signs of the Planet https://climate.nasa.gov/ (2019).

3.
Pachauri, R. K. et al. Climate Change 2014: synthesis report. Fifth Assessment Report on the Intergovernmental Panel on Climate Change 151. Geneva, Switzerland. (2014)

4.
Bale, J. S. et al. Herbivory in global climate change research: direct effects of rising temperature on insect herbivores. Glob. Change Biol. 8, 1–16. https://doi.org/10.1046/j.1365-2486.2002.00451.x (2002).
Article  ADS  Google Scholar 

5.
Forrest, J. R. K. Complex responses of insect phenology to climate change. Curr. Opin. Insect Sci. 17, 49–54. https://doi.org/10.1016/j.cois.2016.07.002 (2016).
Article  PubMed  Google Scholar 

6.
Food and Agriculture Organisation of the United Nations. FAOSTAT Crops http://www.fao.org/faostat/en/#home (2019).

7.
Lobell, D. B., Schlenker, W. & Costa-Roberts, J. Climate trends and global crop production since 1980. Science 333, 616–620. https://doi.org/10.1126/science.1204531 (2011).
CAS  Article  PubMed  ADS  Google Scholar 

8.
Ray, D. K. et al. Climate change has likely already affected global food production. PLoS ONE 14, e0217148. https://doi.org/10.1371/journal.pone.0217148 (2019).
CAS  Article  PubMed  PubMed Central  Google Scholar 

9.
Ali, M. P. et al. Will climate change affect outbreak patterns of planthoppers in Bangladesh?. PLoS ONE https://doi.org/10.1371/journal.pone.0091678 (2014).
Article  PubMed  PubMed Central  Google Scholar 

10.
Ali, M. P. et al. Increased temperature induces leaffolder outbreak in rice field. J. Appl. Entomol. 143, 867–874. https://doi.org/10.1111/jen.12652 (2019).
Article  Google Scholar 

11.
Hu, G. et al. Outbreaks of the brown planthopper Nilaparvata lugens (Stål) in the Yangtze River Delta: immigration or local reproduction? PLoS ONE 9, e88973 (2014).

12.
Yukawa, J. et al. Northward range expansion by Nezara viridula (Hemiptera: Pentatomidae) in Shikoku and Chugoku Districts, Japan, possibly due to global warming. Appl. Entomol. Zool. 44, 429–437 (2009).
Article  Google Scholar 

13.
Horgan, F. G. Integrating gene deployment and crop management for improved rice resistance to Asian planthoppers. Crop Prot. 110, 21–33 (2018).
CAS  Article  Google Scholar 

14.
Ali, M. P. et al. Establishing next-generation pest control services in rice fields: eco-agriculture. Sci. Rep. 9, 1–9 (2019).
Article  Google Scholar 

15.
Horgan, F. G. et al. Effects of vegetation strips, fertilizer levels and varietal resistance on the integrated management of arthropod biodiversity in a tropical rice ecosystem. Insects 10, 328 (2019).
Article  Google Scholar 

16.
Horgan, F. G. Potential for an impact of global climate change on insect herbivory in cereal crops. In Crop Protection Under Climate Change (eds Jabran, K. et al.) 101–144 (Springer, Berlin, 2020).
Google Scholar 

17.
Fujita, D., Kohli, A. & Horgan, F. G. Rice resistance to planthoppers and leafhoppers. Crit. Rev. Plant Sci. 32, 162–191 (2013).
CAS  Article  Google Scholar 

18.
Horgan, F. G. et al. Virulence of brown planthopper (Nilaparvata lugens) populations from South and South East Asia against resistant rice varieties. Crop Prot. 78, 222–231 (2015).
Article  Google Scholar 

19.
Khush, G. S. & Virk, P. S. IR Varieties and Their Impact (International Rice Research Institute, Los Baños, Philippines, 2005).
Google Scholar 

20.
Ren, J. et al. Bph32, a novel gene encoding an unknown SCR domain-containing protein, confers resistance against the brown planthopper in rice. Sci. Rep. 6, 37645 (2016).
CAS  Article  ADS  Google Scholar 

21.
Horgan, F. G. & Ferrater, J. B. Benefits and potential trade-offs associated with yeast-like symbionts during virulence adaptation in a phloem-feeding planthopper. Entomol. Exp. Appl. 163, 112–125 (2017).
Article  Google Scholar 

22.
Horgan, F. G., Garcia, C. P. F., Haverkort, F., de Jong, P. W. & Ferrater, J. B. Changes in insecticide resistance and host range performance of planthoppers artificially selected to feed on resistant rice. Crop Prot. 127, 104963. https://doi.org/10.1016/j.cropro.2019.104963 (2020).
CAS  Article  PubMed  PubMed Central  Google Scholar 

23.
Ferreter, J. B. et al. Varied responses by yeast-like symbionts during virulence adaptation in a monophagous phloem-feeding insect. Arthropod-Plant Interact. 9, 215–224 (2015).
Article  Google Scholar 

24.
Ferrater, J. B., de Jong, P. W., Dicke, M., Chen, Y. H. & Horgan, F. G. Symbiont-mediated adaptation by planthoppers and leafhoppers to resistant rice varieties. Arthropod-Plant Interact. 7, 591–605. https://doi.org/10.1007/s11829-013-9277-9 (2013).
Article  Google Scholar 

25.
Lee, Y. H. & Hou, R. F. Physiological roles of a yeast-like symbiote in reproduction and embryonic development of the brown planthopper, Nilaparvata lugensStål. J. Insect Physiol. 33, 851–860 (1987).
Article  Google Scholar 

26.
Hongoh, Y. & Ishikawa, H. Uric acid as a nitrogen resource for the brown planthopper, Nilaparvata lugens: studies with synthetic diets and aposymbiotic insects. Zool. Sci. 14, 581–586 (1997).
CAS  Article  Google Scholar 

27.
Pan, Y. et al. Identification of brown planthopper resistance gene Bph32 in the progeny of a rice dominant genic male sterile recurrent population using genome-wide association study and RNA-seq analysis. Mol. Breed. 39, 72 (2019).
Article  Google Scholar 

28.
Stevenson, P. C., Kimmins, F. M., Grayer, R. J. & Raveendranath, S. Schaftosides from rice phloem as feeding inhibitors and resistance factors to brown planthopper, Nilaparvata lugens. Entomol. Exp. Appl. 80, 246–249 (1996).
Article  Google Scholar 

29.
Uawisetwathana, U. et al. Global metabolite profiles of rice brown planthopper-resistant traits reveal potential secondary metabolites for both constitutive and inducible defenses. Metabolomics 15, 151. https://doi.org/10.1007/s11306-019-1616-0 (2019).
CAS  Article  PubMed  Google Scholar 

30.
Saxena, R. C. & Okech, S. H. Role of plant volatiles in resistance of selected rice varieties to brown planthopper, Nilaparvata lugens (Stål)(Homoptera; Delphacidae). J. Chem. Ecol. 11, 1601–1616 (1985).
CAS  Article  Google Scholar 

31.
Kamolsukyeunyong, W. et al. Identification of spontaneous mutation for broad-spectrum brown planthopper resistance in a large, long-term fast neutron mutagenized rice population. Rice 12, 16 (2019).
Article  Google Scholar 

32
Nguyen, C. D. et al. The development and characterization of near-isogenic and pyramided lines carrying resistance genes to brown planthopper with the genetic background of japonica rice (Oryza sativa L.). Plants 8, 498 (2019).
CAS  Article  Google Scholar 

33.
Salim, M. & Saxena, R. C. Temperature stress and varietal resistance in rice: effects on whitebackedplanthopper. Crop Sci. 31, 1620–1625. https://doi.org/10.2135/cropsci1991.0011183X003100060048x (1991).
Article  Google Scholar 

34.
Wang, B.-J., Xu, H.-X., Zheng, X.-S., Fu, Q. & Lu, Z.-X. High temperature modifies resistance performances of rice varieties to brown planthopper, Nilaparvata lugens (Stål). Rice Sci. 17, 334–338. https://doi.org/10.1016/S1672-6308(09)60036-6 (2010).
CAS  Article  Google Scholar 

35.
Havko, N. E., Kapali, G., Das, M. R. & Howe, G. A. Stimulation of insect herbivory by elevated temperature outweighs protection by the jasmonate pathway. Plants 9, 172 (2020).
Article  Google Scholar 

36.
Yuan, J. S., Himanen, S. J., Holopainen, J. K., Chen, F. & Stewart, C. N. Jr. Smelling global climate change: mitigation of function from plant volatile organic compounds. Trends Ecol. Evol. 24, 323–331 (2009).
Article  Google Scholar 

37.
Horgan, F. G., Arida, A., Ardestani, G. & Almazan, M. L. P. Temperature-dependent oviposition and nymph performance reveal distinct thermal niches of coexisting planthoppers with similar thresholds for development. PLoS ONE 15, e0235506 (2020).
CAS  Article  Google Scholar 

38.
Srinivas, M., Devi, R. S., Varmaand, N. R. G. & Jagadeeshwar, R. Interactive effect of temperature and CO2 on resistance of rice genotypes to brown planthopper, Nilaparvata lugens (Stål.). J. Entomol. Zool. Stud. 8, 600–602 (2020).
Google Scholar 

39.
Zhang, L., Wu, J. & Chen, B. Influence of temperature and light on expression of resistance in rice to the brown planthopper, Nilaparvata lugens (Homoptera: Delphacidae). J. South China Agric. Univ. 11, 64–70 (1990).
Google Scholar 

40.
Romena, S. & Saxena, R. Screening for resistance to whitebacked planthopper, Sogatella furcifera (Horvath): effect of temperature on seedling damage (Pest Control Council of the Philippines, Cebu City (Philippines), 1988).
Google Scholar 

41.
Horgan, F. G. et al. Resistance and tolerance to the brown planthopper, Nilaparvata lugens (Stål), in rice infested at different growth stages across a gradient of nitrogen applications. Field Crops Res. 217, 53–65. https://doi.org/10.1016/j.fcr.2017.12.008 (2018).
Article  PubMed  PubMed Central  Google Scholar 

42.
Neven, L. G. Physiological responses of insects to heat. Postharvest Biol. Technol. 21, 103–111 (2000).
CAS  Article  Google Scholar 

43.
Bühler, A., Lanzrein, B. & Wille, H. Influence of temperature and carbon dioxide concentration on juvenile hormone titre and dependent parameters of adult worker honey bees (Apis mellifera L). J. Insect Physiol. 29, 885–893 (1983).
Article  Google Scholar 

44.
Foissac, X., Edwards, M., Du, J., Gatehouse, A. & Gatehouse, J. Putative protein digestion in a sap-sucking homopteran plant pest (rice brown plant hopper; Nilaparvata lugens: Delphacidae)—identification of trypsin-like and cathepsin B-like proteases. Insect Biochem. Mol. Biol. 32, 967–978 (2002).
CAS  Article  Google Scholar 

45.
MacMillan, H. A. & Sinclair, B. J. Mechanisms underlying insect chill-coma. J. Insect Physiol. 57, 12–20 (2011).
CAS  Article  Google Scholar 

46.
Vailla, S., Muthusamy, S., Konijeti, C., Shanker, C. & Vattikuti, J. L. Effects of elevated carbon dioxide and temperature on rice brown planthopper, Nilaparvata lugens (Stål) populations in India. Curr. Sci. 116, 988 (2019).
CAS  Article  Google Scholar 

47.
Wang, B., Xu, H., Zheng, X., Fu, Q. & Lu, X. Effect of temperature on resistance of rice to brown planthopper, Nilaparvata lugens. Chin. J. Rice Sci. 24, 443–446 (2010).
Google Scholar 

48.
Ji, R. et al. A salivary endo-β-1, 4-glucanase acts as an effector that enables the brown planthopper to feed on rice. Plant Physiol. 173, 1920–1932 (2017).
CAS  Article  Google Scholar 

49.
Venkatesh, J. & Kang, B.-C. Current views on temperature-modulated R gene-mediated plant defense responses and tradeoffs between plant growth and immunity. Curr. Opin. Plant Biol. 50, 9–17 (2019).
CAS  Article  Google Scholar 

50.
Murai, M. & Kiritani, K. Influence of parental age upon the offspring in the green rice leafhopper, Nephotettix cincticeps Uhler (Hemiptera: Deltocephalidae). Appl. Entomol. Zool. 5, 189–201 (1970).
Article  Google Scholar 

51.
Lu, K. et al. Nutritional signaling regulates vitellogenin synthesis and egg development through juvenile hormone in Nilaparvata lugens (Stål). Int. J. Mol. Sci. 17, 269 (2016).
Article  Google Scholar 

52.
Thoeun, H. C. Observed and projected changes in temperature and rainfall in Cambodia. Weather Clim. Extremes 7, 61–71 (2015).
Article  Google Scholar 

53.
PAGASA. Observed Climate Trends and Projected Climate Change in the Philippines. (Philippine Athmospheric, Geophysical and Astronomical Services Administration (PAGASA), Philippines, (2018).

54.
Yu Media Group. Weather Atlas: weather around the world – list of countries. http://www.weather-atlas.com/en/countries (2020).

55
You, L. L. et al. Driving pest insect populations: agricultural chemicals lead to an adaptive syndrome in Nilaparvata Lugens Stål (Hemiptera: Delphacidae). Sci. Rep. https://doi.org/10.1038/srep37430 (2016).
Article  PubMed  PubMed Central  Google Scholar 

56.
Ge, L. Q. et al. Molecular basis for insecticide-enhanced thermotolerance in the brown planthopper Nilaparvata lugens Stål (Hemiptera: Delphacidae). Mol. Ecol. 22, 5624–5634. https://doi.org/10.1111/mec.12502 (2013).
CAS  Article  PubMed  Google Scholar  More

1.
Chen, I.-C., Hill, J. K., Ohlemüller, R., Roy, D. B. & Thomas, C. D. Rapid range shifts of species associated with high levels of climate warming. Science (80-). 333, 1024–1026 (2011).
ADS  CAS  Article  Google Scholar 
2.
Beniston, M. Climatic change in mountain regions: A review of possible impacts. Clim. Chang. 5, 5–31 (2003).
Article  Google Scholar 

3.
Bishop, T. R., Robertson, M. P., van Rensburg, B. J. & Parr, C. L. Coping with the cold: Minimum temperatures and thermal tolerances dominate the ecology of mountain ants. Ecol. Entomol. 42, 105–114 (2017).
Article  Google Scholar 

4.
Bentley, L. K., Robertson, M. P. & Barker, N. P. Range contraction to a higher elevation: The likely future of the montane vegetation in South Africa and Lesotho. Biodivers. Conserv. 28, 131–153 (2019).
Article  Google Scholar 

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

6.
Peters, R. L. & Darling, J. D. S. The greenhouse effect and nature reserves. Bioscience 35, 707–717 (1985).
Article  Google Scholar 

7.
MacArthur, R. & Wilson, E. The Theory of Island Biogeography (Princeton University Press, Princeton, 1967).
Google Scholar 

8.
Soliveres, S., DeSoto, L., Maestre, F. T. & Olano, J. M. Spatio-temporal heterogeneity in abiotic factors modulate multiple ontogenetic shifts between competition and facilitation. Perspect. Plant Ecol. Evol. Syst. 12, 227–234 (2010).
Article  Google Scholar 

9.
Suggitt, A. J. et al. Habitat microclimates drive fine-scale variation in extreme temperatures. Oikos 120, 1–8 (2011).
Article  Google Scholar 

10.
Thomas, J. A., Rose, R. J., Clarke, R. T., Thomas, C. D. & Webb, N. R. Intraspecific variation in habitat availability among ectothermic animals near their climatic limits and their centres of range. Funct. Ecol. 13, 55–64 (1999).
CAS  Article  Google Scholar 

11.
Porter, W. P. & Gates, D. M. Thermodynamic equilibria of animals with environment. Ecol. Monogr. 39, 227–244 (1969).
Article  Google Scholar 

12.
Del Toro, I., Ribbons, R. R. & Pelini, S. L. The little things that run the world revisited: A review of ant-mediated ecosystem services and disservices (Hymenoptera: Formicidae). Myrmecol. News 17, 133–146 (2012).
Google Scholar 

13.
Wilson, E. The little things that run the world (the importance and conservation of invertebrates). Conserv. Biol. 1, 344–346 (1987).
Article  Google Scholar 

14.
Folgarait, P. J. Ant biodiversity and its relationship to ecosystem functioning: A review. Biodivers. Conserv. 7, 1221–1244 (1998).
Article  Google Scholar 

15.
Seymour, C. & Joseph, G. Ecology of Smaller Animals Associated with Savanna Woody Plants. in Savanna Woody Plants And Large Herbivores (eds. Scogings, P. & Sankaran, M.) 183–212 (2019).

16.
Palmer, T. M. et al. Breakdown of an ant-plant mutualism follows the loss of large herbivores from an African savanna. Science (80-). 319, 192–195 (2008).
ADS  CAS  Article  Google Scholar 

17.
Hölldobler, B. & Wilson, E. The Ants (Harvard University Press, Cambridge, 1990).
Google Scholar 

18.
Munyai, T. C. & Foord, S. H. Temporal patterns of ant diversity across a mountain with climatically contrasting aspects in the tropics of Africa. PLoS ONE 10, 1–16 (2015).
Article  CAS  Google Scholar 

19.
Dunn, R. R., Parker, C. R. & Sanders, N. J. Temporal patterns of diversity: Assessing the biotic and abiotic controls on ant assemblages. Biol. J. Linn. Soc. 91, 191–201 (2007).
Article  Google Scholar 

20.
Urban, M. C., Tewksbury, J. J. & Sheldon, K. S. On a collision course: Competition and dispersal differences create no-analogue communities and cause extinctions during climate change. Proc. R. Soc. B Biol. Sci. 279, 2072–2080 (2012).
Article  Google Scholar 

21.
Warren, R. J. & Chick, L. Upward ant distribution shift corresponds with minimum, not maximum, temperature tolerance. Glob. Chang. Biol. 19, 2082–2088 (2013).
ADS  PubMed  Article  Google Scholar 

22.
Suggitt, A. J. et al. Extinction risk from climate change is reduced by microclimatic buffering. Nat. Clim. Change 8, 2 (2018).
Article  Google Scholar 

23.
Joseph, G. S. et al. Microclimates mitigate against hot temperatures in dryland ecosystems: termite mounds as an example. Ecosphere Article e01509 (2016).

24.
Baudier, K. M., Mudd, A. E., Erickson, S. C. & O’Donnell, S. Microhabitat and body size effects on heat tolerance: Implications for responses to climate change (army ants: Formicidae, Ecitoninae). J. Anim. Ecol. 84, 1322–1330 (2015).
PubMed  Article  Google Scholar 

25.
Zellweger, F., Roth, T., Bugmann, H. & Bollmann, K. Beta diversity of plants, birds and butterflies is closely associated with climate and habitat structure. Glob. Ecol. Biogeogr. 26, 898–906 (2017).
Article  Google Scholar 

26.
Mauda, E. V., Joseph, G. S., Seymour, C. L., Munyai, T. C. & Foord, S. H. Changes in landuse alter ant diversity, assemblage composition and dominant functional groups in African savannas. Biodivers. Conserv. 27, 947–965 (2018).
Article  Google Scholar 

27.
Andrew, N. R., Miller, C., Hall, G., Hemmings, Z. & Oliver, I. Aridity and land use negatively influence a dominant species’ upper critical thermal limits. PeerJ 2019, 1–20 (2019).
Google Scholar 

28.
Oliver, I., Dorrough, J., Doherty, H. & Andrew, N. R. Additive and synergistic effects of land cover, land use and climate on insect biodiversity. Landsc. Ecol. 31, 2415–2431 (2016).
Article  Google Scholar 

29.
Hahn, N. Floristic diversity of the Soutpansberg, Limpopo Province, South Africa (University of Pretoria, Pretoria, 2006).
Google Scholar 

30.
Davis, C. & Vincent, K. Climate Risk and Vulnerability: A Handbook for Southern Africa. (2017).

31.
Joseph, G. S. et al. Stability of Afromontane ant diversity decreases across an elevation gradient. Glob. Ecol. Conserv. 17, e00596 (2019).
Article  Google Scholar 

32.
Longino, J. T. & Colwell, R. K. Density compensation, species composition, and richness of ants on a neotropical elevational gradient. Ecosphere 2, 1–20 (2011).
Article  Google Scholar 

33.
Bishop, T. R., Robertson, M. P., van Rensburg, B. J. & Parr, C. L. Contrasting species and functional beta diversity in montane ant assemblages. J. Biogeogr. 42, 1776–1786 (2015).
PubMed  PubMed Central  Article  Google Scholar 

34.
Tilman, D. Functional Diversity. In Encyclopedia of Biodiversity Vol. 3 (ed. Levin, S. A.) 109–121 (Academic Press, New York, 2001).
Google Scholar 

35.
Díaz, S. & Cabido, M. Vive la différence: Plant functional diversity matters to ecosystem processes. Trends Ecol. Evol. 16, 646–655 (2001).
Article  Google Scholar 

36.
Seymour, C. L., Simmons, R. E., Joseph, G. S. & Slingsby, J. A. On bird functional diversity: Species richness and functional differentiation show contrasting responses to rainfall and vegetation structure in an arid landscape. Ecosystems 18, 971–984 (2015).
Article  Google Scholar 

37.
Joseph, G. S. et al. Termite mounds mitigate against 50 years of herbivore-induced reduction of functional diversity of savanna woody plants. Landsc. Ecol. 30, 2161–2174 (2015).
Article  Google Scholar 

38.
Díaz, S., Cabido, M. & Casanoves, F. Plant functional traits and environmental filters at a regional scale. J. Veg. Sci. 9, 113–122 (1998).
Article  Google Scholar 

39.
Modiba, R. V., Joseph, G. S., Seymour, C. L., Fouché, P. & Foord, S. H. Restoration of riparian systems through clearing of invasive plant species improves functional diversity of Odonate assemblages. Biol. Conserv. 214, 46–54 (2017).
Article  Google Scholar 

40.
Van Wyk, A. & Smith, G. Regions of Floristic Endemism in Southern Africa: A Review with Emphasis on Succulents (Umdaus press, Umdaus, 2001).
Google Scholar 

41.
Mostert, T., Bredenkamp, G., Klopper, H. & Al, E. Major vegetation types of the Soutpansberg conservancy and the Blouberg nature reserve, South Africa. Koedoe 50, 32–48 (2008).
Article  Google Scholar 

42.
Mucina, L. & Rutherford, M. C. The vegetation of South Africa, Lesotho and Swaziland. (2011).

43.
McKillup, S. Statistics Explained: An Introductory Guide for Life Scientists (Cambridge University Press, Cambridge, 2011).
Google Scholar 

44.
Yates, M., Andrew, N., Binns, M. & Gibb, H. Morphological traits: predictable responses to macrohabitats across a 300 km scale. PeerJ 2, e271 (2014).
PubMed  PubMed Central  Article  Google Scholar 

45.
Schofield, S. F., Bishop, T. R. & Parr, C. L. Morphological characteristics of ant assemblages (Hymenoptera: Formicidae) differ among contrasting biomes. Myrmecol. News 23, 129–137 (2016).
Google Scholar 

46.
Colwell, R. K. EstimateS: Statistical estimation of species richness and shared species from samples. (2006).

47.
Baselga, A. Partitioning the turnover and nestedness components of beta diversity. Glob. Ecol. Biogeogr. 19, 134–143 (2010).
Article  Google Scholar 

48.
Baselga, A. & Orme, C. D. L. Betapart: An R package for the study of beta diversity. Methods Ecol. Evol. 3, 808–812 (2012).
Article  Google Scholar 

49.
Wang, Y., Naumann, U., Eddelbuettel, D. & Warton, D. mvabund: statistical methods for analysing multivariate abundance data. R package version 3.13.1. (2018).

50.
Warton, D. I., Foster, S. D., Death, G., Stoklosa, J. & Dunstan, P. K. Model-based thinking for community ecology. Plant Ecol. 216, 669–682 (2015).
Article  Google Scholar 

51.
Warton, D. I., Thibaut, L. & Wang, Y. A. The PIT-trap—A “model-free” bootstrap procedure for inference about regression models with discrete, multivariate responses. PLoS ONE 12, 1–19 (2017).
Article  CAS  Google Scholar 

52.
Hui, F. boral: Bayesian Ordination and Regression AnaLysis. R package version 1.6.1. (2018).

53.
Petchey, O. L. & Gaston, K. J. Functional diversity: Back to basics and looking forward. Ecol. Lett. 9, 741–758 (2006).
PubMed  Article  Google Scholar 

54.
Weber, N. The biology of the fungus-growing ants. Part IV. Additional new forms. Rev. Entomol. 9, 154–206 (1938).
Google Scholar 

55.
Laliberté, E. & Shipley, B. FD: measuring functional diversity from multiple traits, and other tools for functional ecology. R package 1.0–11. (2011).

56.
Petchey, O. L. & Gaston, K. J. Extinction and the loss of functional diversity. Proc. Biol. Sci. 269, 1721–1727 (2002).
PubMed  PubMed Central  Article  Google Scholar 

57.
Kembel, S. et al. Picante: R tools for integrating phylogenies and ecology. Bioinformatics 26, 1463–1464 (2010).
CAS  Google Scholar 

58.
Gotelli, N. J. & Rohde, K. Co-occurrence of ectoparasites of marine fishes: a null model analysis. Ecol. Lett. 5, 86–94 (2002).
Article  Google Scholar 

59.
Pinheiro, J., Bates, D., DebRoy, S., Sarkar, D. & R Core Team, . nlme: Linear and Nonlinear Mixed Effects Models. (2016).

60.
Kamil Barton. MuMIn: Multi-Model Inference. R package version 1.43.17. (2020).

61.
Burnham, K. P. & Anderson, D. R. Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach (2nd ed). Ecological Modelling vol. 172 (2002).

62.
Nakagawa, S. & Schielzeth, H. A general and simple method for obtaining R2 from generalized linear mixed-effects models. Methods Ecol. Evol. 4, 133–142 (2013).
Article  Google Scholar 

63.
Didham, R., Kapos, V. & Ewers, R. Rethinking the conceptual foundations of habitat fragmentation research. Oikos 121, 161–170 (2012).
Article  Google Scholar 

64.
Niu, K. et al. Fertilization decreases species diversity but increases functional diversity: A three-year experiment in a Tibetan alpine meadow. Agric. Ecosyst. Environ. 182, 106–112 (2014).
Article  Google Scholar 

65.
Joseph, G. S. et al. Elephants, termites and mound thermoregulation in a progressively warmer world. Landsc. Ecol. 33, 731–742 (2018).
Article  Google Scholar 

66.
Bishop, T. R. et al. Thermoregulatory traits combine with range shifts to alter the future of montane ant assemblages. Glob. Chang. Biol. 25, 2162–2173 (2019).
ADS  PubMed  Article  Google Scholar 

67.
Prentice, I. C. et al. Dynamic global vegetation modeling: Quantifying terrestrial ecosystem responses to large-scale environmental change. Terrest. Ecosyst. Chang. World https://doi.org/10.1007/978-3-540-32730-1_15 (2007).
Article  Google Scholar 

68.
Pfeiffer, M., Kumar, D., Martens, C. & Scheiter, S. Climate change will cause non-analogue vegetation states in Africa and commit vegetation to long-term change. Biogeosci. Discuss. https://doi.org/10.5194/bg-2020-179 (2020).
Article  Google Scholar 

69.
Potter, K. A., Woods, H. A. & Pincebourde, S. Microclimatic challenges in global change biology. Glob. Chang. Biol. 19, 2932–2939 (2013).
ADS  PubMed  Article  Google Scholar 

70.
Scheffers, B. R., Edwards, D. P., Diesmos, A., Williams, S. E. & Evans, T. A. Microhabitats reduce animal’s exposure to climate extremes. Glob. Chang. Biol. 20, 495–503 (2014).
ADS  PubMed  Article  Google Scholar 

71.
Bonachela, J. A. et al. Termite mounds can increase the robustness of dryland ecosystems to climatic change. Science (80-). 347, 651–655 (2015).
ADS  CAS  Article  Google Scholar 

72.
Joseph, G. S. et al. Landuse change in savannas disproportionately reduces functional diversity of invertebrate predators at the highest trophic levels: Spiders as an example. Ecosystems 21, 930–942 (2018).
Article  Google Scholar 

73.
Hoerling, M. & Kumar, A. The perfect ocean for drought. Science (80-). 299, 691–694 (2003).
ADS  CAS  Article  Google Scholar 

74.
Diffenbaugh, N. S. & Field, B. S. Changes in ecologically critical terrestrial climate conditions. Science (80-). 341, 486–493 (2013).
ADS  CAS  Article  Google Scholar 

75.
Colwell, R. K., Brehm, G., Cardelús, C. L., Gilman, A. C. & Longino, J. T. Global warming, elevational range shifts, and lowland biotic attrition in the wet tropics. Science (80-). 322, 258–261 (2008).
ADS  CAS  Article  Google Scholar 

76.
Fowler, H., Forti, L., Brandão, C. & et al. Ecologia nutricional de formigas. in Ecologia Nutricional de Insetos E Suas Implicações No Manejo de Pragas 131–223 (1991).

77.
Davidson, D., Cook, S. & Snelling, R. Liquid-feeding performances of ants (Formicidae): Ecological and evolutionary implications. Oecologia 139, 255–266 (2004).
ADS  PubMed  Article  Google Scholar 

78.
Sarty, M., Abbott, K. & Lester, P. Habitat complexity facilitates coexistence in a tropical ant community. Oecologia 149, 465–473 (2006).
ADS  CAS  PubMed  Article  Google Scholar 

79.
Kaspari, M. Body size and microclimate use in Neotropical granivorous ants. Oecologia 96, 500–507 (1993).
ADS  PubMed  Article  Google Scholar 

80.
Weiser, M. & Kaspari, M. Ecological morphospace of New World ants. Ecol. Entomol. 31, 131–142 (2006).
Article  Google Scholar 

81.
Gibb, H. et al. Does morphology predict trophic position and habitat use of ant species and assemblages?. Oecologia 177, 519–531 (2015).
ADS  CAS  PubMed  Article  Google Scholar 

82.
Gibb, H. & Cl, P. Does structural complexity determine the morphology of assemblages? An experimental test on three continents. PLoS ONE 8, e64005 (2013).
ADS  CAS  PubMed  PubMed Central  Article  Google Scholar  More