Ecology

1.Finnegan, S., Rasmussen, C. M. Ø. & Harper, D. A. T. Biogeographic and bathymetric determinants of brachiopod extinction and survival during the Late Ordovician mass extinction. Proc. Biol. Sci. 283, 1–9 (2016).
Google Scholar 
2.Penn, J. L., Deutsch, C., Payne, J. L. & Sperling, E. A. Temperature-dependent hypoxia explains biogeography and severity of end-Permian marine mass extinction. Science 362, eaat1327 (2018).ADS 
PubMed 

Google Scholar 
3.De Vleeschouwer, D. et al. The astronomical rhythm of Late-Devonian climate change (Kowala section, Holy Cross Mountains, Poland). Earth Planet. Sci. Lett. 365, 25–37 (2013).ADS 

Google Scholar 
4.De Vleeschouwer, D. et al. Timing and pacing of the Late Devonian mass extinction event regulated by eccentricity and obliquity. Nat. Commun. 8, 1–11 (2017).
Google Scholar 
5.Saupe, E. E. et al. Extinction intensity during Ordovician and Cenozoic glaciations explained by cooling and palaeogeography. Nat. Geosci. 13, 65–70 (2020).ADS 

Google Scholar 
6.Finnegan, S. et al. Paleontological baselines for evaluating extinction risk in the modern oceans. Science 348, 567–570 (2015).ADS 
CAS 
PubMed 

Google Scholar 
7.Carmichael, S. K., Waters, J. A., Suttner, T. J. & Kido, E. Paleogeography and paleoenvironments of the Late Devonian Kellwasser event: a review of its sedimentological and geochemical expression. Glob. Planet. Change 183, 102984 (2019).
Google Scholar 
8.Lash, G. G. A multiproxy analysis of the Frasnian–Famennian transition in western New York State, U.S.A.. Palaeogeogr. Palaeoclimatol. Palaeoecol. 473, 108–122 (2017).
Google Scholar 
9.Haddad, E. E. et al. Ichnofabrics and chemostratigraphy argue against persistent anoxia during the Upper Kellwasser Event in New York State. Palaeogeogr. Palaeoclimatol. Palaeoecol. 490, 178–190 (2018).
Google Scholar 
10.Joachimski, M. M. & Buggisch, W. Conodont apatite δ18O signatures indicate climatic cooling as a trigger of the Late Devonian mass extinction. Geology 30, 711–714 (2002).ADS 
CAS 

Google Scholar 
11.Joachimski, M. M. & Buggisch, W. Anoxic events in the Late Frasnian—Causes of the Frasnian–Famennian faunal crisis?. Geology 21, 675–678 (1993).ADS 
CAS 

Google Scholar 
12.McGhee, G. R. & Racki, G. Extinction: Late Devonian mass extinction. eLS 2, 1–12 (2021).
Google Scholar 
13.Racki, G. Toward understanding Late Devonian global events: few answers, many questions in Understanding Late Devonian and Permian-Triassic Biotic and Climatic Events: Towards an Integrated Approach (eds. Over, D. J., Morrow, J. R. & Wignall, P. B.), 5–36 (Elsevier, 2005).14.Hartenfels, S., Becker, R. T. & Aboussalam, Z. S. Givetian to Famennian stratigraphy, Kellwasser, Annulata and other events at Beringhauser Tunnel (Messinghausen Anticline, eastern Rhenish Massif). Münster. Forsch. Geol. Paläont. 108, 196–219 (2016).
Google Scholar 
15.Le Houedec, S., Girard, C. & Balter, V. Conodont Sr/Ca and δ18O record seawater changes at the Frasnian–Famennian boundary. Palaeogeogr. Palaeoclimatol. Palaeoecol. 376, 114–121 (2013).
Google Scholar 
16.McGhee, G. R., Sheehan, P. M., Bottjer, D. J. & Droser, M. L. Ecological ranking of Phanerozoic biodiversity crises: ecological and taxonomic severities are decoupled. Palaeogeogr. Palaeoclimatol. Palaeoecol. 211, 289–297 (2004).
Google Scholar 
17.Stigall, A. L. Speciation collapse and invasive species dynamics during the Late Devonian “Mass Extinction”. GSA Today 22, 4–9 (2012).
Google Scholar 
18.Beard, J. A., Bush, A. M., Fernandes, A. M., Getty, P. R. & Hren, M. T. Stratigraphy and paleoenvironmental analysis of the Frasnian–Famennian (Upper Devonian) boundary interval in Tioga, north-central Pennsylvania. Palaeogeogr. Palaeoclimatol. Palaeoecol. 478, 67–79 (2017).
Google Scholar 
19.Bush, A. M., Csonka, J. D., DiRenzo, G. V., Over, D. J. & Beard, J. A. Revised correlation of the Frasnian–Famennian boundary and Kellwasser Events (Upper Devonian) in shallow marine paleoenvironments of New York State. Palaeogeogr. Palaeoclimatol. Palaeoecol. 433, 233–246 (2015).
Google Scholar 
20.Day, J. Stratigraphy, Biostratigraphy, and Depositional History of the Givetian and Frasnian Strata in the San Andres and Sacramento Mountains of Southern New Mexico (University of Iowa, Iowa City, 1988).
Google Scholar 
21.Stanley, S. M. Thermal barriers and the fate of perched faunas. Geology 38, 31–34 (2010).ADS 

Google Scholar 
22.Copper, P. Frasnian/Famennian mass extinction and cold-water oceans. Geology 14, 835–839 (1986).ADS 

Google Scholar 
23.Reddin, C. J., Kocsis, Á. T. & Kiessling, W. Climate change and the latitudinal selectivity of ancient marine extinctions. Paleobiology 45, 70–84 (2019).
Google Scholar 
24.Copper, P. Evaluating the Frasnian–Famennian mass extinction: comparing brachiopod faunas. Acta Palaeontol. Pol. 43, 137–154 (1998).
Google Scholar 
25.Becker, R. T. & House, M. R. Kellwasser Events and goniatite successions in the Devonian of the Montagne Noire with comments on possible causations. Cour Forsch Senck 169, 45–77 (1994).
Google Scholar 
26.Bond, D., Wignall, P. B. & Racki, G. Extent and duration of marine anoxia during Frasnian–Famennian (Late Devonian) mass extinction in Poland, Germany, Austria, and France. Geol. Mag. 2, 173–193 (2004).ADS 

Google Scholar 
27.Buggisch, W. The global Frasnian–Famennian »Kellwasser Event«. Geol. Rundschau 80, 49–72 (1991).ADS 

Google Scholar 
28.Johnson, J. G., Klapper, G. & Sandberg, C. A. Devonian eustatic fluctuations in Euramerica. Geol. Soc. Am. Bull. 96, 567–587 (1985).ADS 

Google Scholar 
29.Mcghee, G. R. The Late Devonian extinction event: evidence for abrupt ecosystem collapse. Paleobiology 14, 250–257 (1988).
Google Scholar 
30.Sandberg, C. A., Morrow, J. R. & Ziegler, W. Late Devonian sea-level changes, catastrophic events, and mass extinctions. Geol. Soc. Am. Spec. Pap. 356, 473–487 (2002).
Google Scholar 
31.Mehta, C. R. & Patel, N. R. Exact logistic regression: theory and examples. Stat. Med. 14, 2143–2160 (1995).CAS 
PubMed 

Google Scholar 
32.Over, J. D. Conodont biostratigraphy of the Java Formation (Upper Devonian) and the Frasnian–Famennian boundary in western New York State. Geol. Soc. Am. Spec. Pap. 321, 161–177 (1997).
Google Scholar 
33.Boyer, D. L. et al. Living on the edge: the impact of protracted oxygen stress on life in the Late Devonian. Palaeogeogr. Palaeoclimatol. Palaeoecol. 566, 1–16 (2021).
Google Scholar 
34.Bush, A. M. & Brame, R. I. Multiple paleoecological controls on the composition of marine fossil assemblages from the Frasnian (Late Devonian) of Virginia, with a comparison of ordination methods. Paleobiology 26, 573–591 (2010).
Google Scholar 
35.Fasham, M. J. R. A comparison of nonmetric multidimensional scaling, principal components and reciprocal averaging for the ordination of simulated coenoclines, and coenoplanes. Ecology 58, 551–561 (1977).
Google Scholar 
36.Legendre, P. & Legendre, L. Numerical ecology (Elsevier, Amsterdam, 2012).MATH 

Google Scholar 
37.Holland, S. M. The stratigraphy of mass extinctions and recoveries. Annu. Rev. Earth Planet. Sci. https://doi.org/10.1146/annurev-earth-071719-054827 (2020).Article 

Google Scholar 
38.Kelly, A. A., Cohen, P. A. & Boyer, D. L. Tiny keys to unlocking the Kellwasser events: detailed characterization of organic walled microfossils associated with extinction in western New York State. Palaios 34, 96–104 (2019).ADS 

Google Scholar 
39.Boyer, D. L. & Droser, M. L. Palaeoecological patterns within the dysaerobic biofacies: examples from Devonian black shales of New York state. Palaeogeogr. Palaeoclimatol. Palaeoecol. 276, 206–216 (2009).
Google Scholar 
40.Day, J. & Witzke, B. J. Upper Devonian biostratigraphy, Event Stratigraphy, and Late Frasnian Kellwasser Extinction bioevents in the Iowa Basin: western Euramerica. In Stratigraphy & Timescales. 2, 243–332 (Elsevier, 2017).41.Day, J. & Copper, P. Revision of latest Givetian-Frasnian Atrypida (Brachiopoda) from central North America. Acta Palaeontol. Pol. 43, 155–204 (1998).
Google Scholar 
42.Day, J. Subtropical record of Upper Devonian (late Frasnian-early Famennian) sea level events and Kellwasser Extinction bioevents, southern Ouachita margin-western Laurussia (Arizona-New Mexico, central and northern Mexico) in Geological Society of America Abstracts with Programs Vol. 42, 89 (2010).43.Schindler, E. The late Frasnian (Upper Devonian) Kellwasser crisis. Lect. Notes Earth Sci. 30, 151–160 (1990).
Google Scholar 
44.Schindler, E. Event-stratigraphic markers within the Kellwasser crisis near the Frasnian/Famennian boundary (Upper Devonian) in Germany. Palaeogeogr. Palaeoclimatol. Palaeoecol. 104, 115–125 (1993).
Google Scholar 
45.Zapalski, M. et al. The palaeobiodiversity of stromatoporoids, tabulates and brachiopods in the Devonian of Ardennes-Changes through time. Bulletin de la Société Géologique de France. 178(5), 383–390. https://doi.org/10.2113/gssgfbull.178.5.383 (2007).Article 

Google Scholar 
46.Ma, X. P., Sun, Y. L., Hao, W. C. & Liao, W. H. Rugose corals and brachiopods across the Frasnian–Famennian boundary in central Hunan, South China. Acta Palaeontol. Pol. 47, 373–396 (2002).
Google Scholar 
47.Racki, G., Makowski, I., Miklas, J. & Gawlik, S. Brachiopod biofacies in the Frasnian reef-complexes: an example from the Holy Cross Mts, Poland. Geologia 12(13), 64–109 (1993).
Google Scholar 
48.Sokiran, E. V. Frasnian–Famennian extinction and recovery of rhynchonellid brachiopods from the East European Platform. Acta Palaeontol. Pol. 47, 339–354 (2002).
Google Scholar 
49.Brett, C. E., Hendy, A. J. W., Bartholomew, A. J., Bonelli, J. R. & Mclaughlin, P. I. Response of shallow marine biotas to sea-level fluctuations: a review of faunal replacement and the process of habitat tracking. Palaios https://doi.org/10.2110/palo.2005.p05-028r (2007).Article 

Google Scholar 
50.Rode, A. L. & Lieberman, B. S. Using GIS to unlock the interactions between biogeography, environment, and evolution in Middle and Late Devonian brachiopods and bivalves. Palaeogeogr. Palaeoclimatol. Palaeoecol. 211, 345–359 (2004).
Google Scholar 
51.Hall, J. Palaeontology: containing descriptions and figures of the fossil Brachiopoda of the upper Helderberg, Hamilton, Portage and Chemung Groups. Geological Survey of New York IV (1867).52.Cooper, G. A. & Dutro, J. T. Devonian brachiopods of New Mexico. Bull. Am. Paleontol. 82, 1–215 (1982).
Google Scholar 
53.Linsley, D. M. Devonian paleontology of New York. Paleontol. Res. Inst. Spec. Publ. 21, 472 (1994).
Google Scholar 
54.R: A Language and Environment for Statistical Computing. (2021).55.Holland, S. M., Miller, A. I., Meyer, D. L. & Dattilo, B. F. The detection and importance of subtle biofacies within a single lithofacies: the Upper Ordovician Kope Formation of the Cincinnati, Ohio region. Palaios 16, 205–217 (2001).ADS 

Google Scholar 
56.The Paleobiology Database. (2018). Available at: http://www.paleobiodb.org/.57.Mann, H. B. & Whitney, D. R. On a test of whether one of two random variables is stochastically larger than the other. Ann. Math. Stat. 18, 50–60 (1947).MathSciNet 
MATH 

Google Scholar 
58.Finney, D. J. The Fisher-Yates test of significance in 2 × 2 contingency tables. Biometrika 35, 156 (1948).MathSciNet 
MATH 

Google Scholar 
59.Scott, C. & Lyons, T. W. Contrasting molybdenum cycling and isotopic properties in euxinic versus non-euxinic sediments and sedimentary rocks: refining the paleoproxies. Chem. Geol. 324–325, 19–27 (2012).ADS 

Google Scholar 
60.Boyer, D. L., Owens, J. D., Lyons, T. W. & Droser, M. L. Joining forces: combined biological and geochemical proxies reveal a complex but refined high-resolution palaeo-oxygen history in Devonian epeiric seas. Palaeogeogr. Palaeoclimatol. Palaeoecol. 306, 134–146 (2011).
Google Scholar 
61.Boyer, D. L., Haddad, E. E. & Seeger, E. S. The last gasp: trace fossils track deoxygenation leading into the Frasnian–Famennian extinction event. Palaios 29, 646–651 (2014).ADS 

Google Scholar 
62.Rickard, L. V. & Fisher, D. W. Geologic map of New York: Finger Lakes sheet and Niagara sheet. (1970).63.Woodrow, D. L. Stratigraphy, structure, and sedimentary patterns in the Upper Devonian of Bradford County, Pennsylvania. Pennsylvania Geological Survey 1–78 (1968). More

RearingAll mosquitoes used in these experiments were derived from a laboratory-reared colony of An. stephensi is initially established (six generations) in University College Agriculture, University of Sargodha. Uninfected mosquitoes were maintained in the laboratory; in gauze-covered boxes (30 cm wide × 30 cm high × 50 cm deep) under control condition 27 ± 2 °C temperature and 75–80% relative humidity. Auto ON/OFF switches with the timer were used to break the scotophase (dark) period in the control conditions of the laboratory with the light: dark cycle set to 12:12 h48. A 10% fructose solution supplemented with 0.05% para-minobenzoic acid (PABA) was provided to mosquitoes. The adult mosquitoes were reared on blood provided via an in situ electronically derived artificial membrane feeder, set at 37 ± 1 °C, and offered twice a week, and offered twice a week given their need for another blood meal approximately 5–6 h after the first49. Multiple blood feeding is vital for Anopheline species as it has been demonstrated as influencing reproductive behavior50. Oviposition cups were provided two days following the second blood meal. The larvae were reared under laboratory conditions described above and provided a certified Laboratory Rodent Diet (LRD) Lab Diet 500151.Fecundity and fertilityTo determine differences in fecundity (number of eggs) and fertility (percentage of fertile eggs) in An. stephensi mosquitoes, cages of mosquitoes were provided ABO blood groups and control (distilled water) via artificial membrane feeders (as described above for mosquito rearing). The blood was obtained from the blood bank of DHQ (one batch of each blood group was used for each replication), Chakwal Punjab, Pakistan. A total of 10 replicate cages were used for each blood type and control, so 10 batches of each blood group (ABO) (just to reduce the potential individual to individual variation) were obtained from the DHQ. After each replication along with the new batch of each blood group, a new strain of mosquitoes was used just to reduce the learning behavior of mosquitoes. Feeding success was determined by calculating the percentage of fed mosquitoes, and also, the numbers of fully engorged female mosquitoes were recorded.To determine fecundity, females from each blood group were removed, killed, and dissected under a microscope, and the numbers of eggs per female were counted 60 h post-blood-feeding. Additionally, to determine oviposition and larval development, 40 fully fed female mosquitoes were caged in one of three replicate glass cages with gauze (25 cm wide × 25 cm high × 25 cm deep) and provided wet filter papers were placed for egg-laying. The total number of eggs was counted after every 12 h from 48 h until 96 h post-blood-feeding under a light microscope. The total numbers of eggs/40 females/box for each human blood group for 10 replicates were calculated.For fertility estimation, an additional 40 gravid An. stephensi from each treatment and replication, including the control group, the females were gently transferred to the cages with triangular Whatman filter paper No. 1 using the mouth aspirator. The egg laid in each experimental and control group was reared in plastic trays filled with distilled water. The numbers of hatched larvae were recorded for a fertility test. While the eggs that could not be hatched into larvae up to day 7 were considered as infertile. The number of fertile and infertile eggs was recorded from all experimental and control cages.The collected eggs from each experimental box were placed into the plastic trays (24 cm wide × 12 cm high × 7 cm deep) with water, and the development of mosquitoes was observed until adult mosquitoes had emerged from all pupae for each blood group. The water in these plastic trays was maintained at a constant level throughout immature mosquito rearing. The larvae were fed a certified Laboratory Rodent Diet (LRD) Lab Diet 500151. The rearing was done according to the standard mass rearing of Anopheles techniques52. Pupae were counted and removed from the tray and placed in cages according to each human blood group type fed to allow emergence, and the percent of male and female mosquitoes was recorded. Adult mosquitoes were maintained on a 10% fructose solution supplemented with 0.05% para-minobenzoic acid (PABA) but were not provided with a blood meal. The mortality of adult mosquitoes was recorded daily until total mortality reached 100%.Digestibility testsThe precipitin and benzidine tests were used to test the effect of human blood groups ABO (on the rate of digestion in mosquitoes). The experiment was conducted in controlled laboratory conditions where the temperature, humidity, and day and night periods were maintained as described above. Mosquitoes (10 mosquitoes were used for each blood group and the same experiment was repeated 10 times) that had not been fed previously on either a sugar solution or blood were used in experiments. Mosquitoes were provided one of four different human blood group types, as previously described. After feeding the female were kept in the same boxes without any further food and water, and boxes were placed in an incubator where the temperature and the relative humidity was at a constant level (28 ± 2 °C and 80 ± 5%). The engorged female adult mosquitoes were killed at 8 h intervals, rubbed over the filter paper53, and the filter papers were placed inside the refrigerator until the test could be conducted. Approximately 48 female mosquitoes were used in each boxed marked for each blood group. The rate of blood digestion in the engorged blood was classified according to the Sella scale, following Detinova et al.54.To perform the precipitin test, the physiological saline and the filter paper smears were extracted in a small capillary tube. The specific antiserum was also extracted in the same capillary tube at the end; the change in color, clumping, and cloudiness of the solution indicates the presence of human blood in the tissue smears55. The collected material was heated in a steam oven for 10–12 min to apply the benzidine test at 108–110 °C. The test was used to check the traces of iron porphyrins in the abdomen of mosquitoes.Effect of blood groups on oogenesisTo test the blood-specific effects on the development of the ovaries of An. stephensi, the ovaries of fully fed female mosquitoes were collected separately from the box of each blood group 36 h post engorgement. For scanning electron microscopy (SEM), the whole female mosquitoes were selected from each box of every blood group separately (10 females for each blood group ABO). In preparing specimens for the scanning electron microscope, the process is divided into two fixations, the primary and the secondary fixation. For the primary fixing process, the 2.5% glutaraldehyde in 0.1 M cacodylate buffer was used for the period of 2 h, followed by the three consecutive washing with the same buffer for the 30 min. While for the secondary fixation process, 1% osmium tetroxide was used for the 2 h. Then the samples were rinsed for the final time with the 0.1 M cacodylate buffer three times for 30 min.The ovaries were dehydrated by using the graded series of acetone (50%, 70%, 80%, 90%, and 100%). The dehydrated ovaries were then transferred to the critical point drying apparatus. The recommended quantity of acetone solution was also poured into the drying chamber to avoid over-drying. Liquid nitrogen was also added into the drying critical point drying chamber. The CO2 and acetone were allowed to be mixed freely; the same process was repeated eight times to confirm the drying of the specimen. The dried mosquito specimens were mounted over the stubs, and the specimens tubes were coated with a thin layer of silver. Gold-spotted SCD005 was used, and then the samples were photographed with SEM.Electroantennography (EAG)To measure the response of mosquitoes to each human blood group type, EAG recordings from one antenna of An. stephensi female mosquito was made. Unfed female mosquitoes were anesthetized by the use of CO2 and were permanently fixed with the reference electrode by the use of spectra 360 electrode gel. It was made sure that the mosquito was completely immobile except for the antennae. The tips of the antennae were pressed into the small drop of electrode gel on the recording electrode. Both of the electrodes are silver wires coated with silver chloride with a diameter of 0.2 mm. The experimental preparations were done in continuous airflow (600 mL/min, 1.5 m/s) by the Teflon tube of 0.7–0.8 cm diameter, containing about 100 mL/min dry air and the 600 mL/min moist air passed through the charcoal filter. At this stage, little modification was done in the structure of the electroantennogram, and an artificial blood feeder of mosquitoes with the membrane was attached to the system.The blood feeder was packed in a glass jar through which continuous airflow was passed, and this air flow ends as stimuli near the mounted mosquito. The diameter of the glass tube was 0.5 mm, and the flow of air was controlled by using an ON/OFF switch; three bursts of 0.5 s of air from the blood jar were provided as a stimulus to host-seeking mosquitoes. All the blood groups were tested systematically together with the control group. The amplifier amplified the generated signals while the well-known software decoded the recordings (EAG 2000, Syntech, Hilversum, and the Netherlands). All of the test blood groups were also dissolved separately in tetryl-butyl-methyl ether (MTBE), and about 30 uL of this test solution was applied onto a piece of filter paper (1.5–2 cm). About 20 min was given to the TMBE solution to evaporate from the filter paper leaving behind the blood; then, this piece of filter paper was placed into the Pasteur pipette. In the case of the control treatment, distilled water was used, and the same treatment was applied with the distilled water for the test compounds. The stimulus controller C5-01/b, Syntech, was used to inject the odor cues originating from the treated filter paper in the Pasteur pipette into the humidified and filtered air stream directed towards the antennae of immobilized mosquitoes. Olfactory stimuli were tested randomly against different mosquito specimens with a total of five specimens exposed to each of the human blood type groups and control.To minimize the chances of error and to test the electrophysiological activity of the stuck female mosquito, lactic acid, 1-octen-3-01, and isovaleric acid were used as known stimulants41,56. After that, each blood group was replicated three times to record the activity of the olfactory neurons of antennae. All the treatments of blood groups were tested randomly, and a regular interruption of control stimulus (0.1% lactic acid) was done. The regular interruption of the control stimulus was used to control the activity of the antennae. All the stimulants were expressed as a mean percent response to the control treatment. The response of different female mosquitoes to human blood groups was indicated as a mean percent response. The results were analyzed by the use of the Student’s t-test.Wind tunnel bioassaysWind tunnel bioassays were used to determine the response of An. stephensi to four human blood groups (A, B, AB, and O) and control stimuli (distilled water). Wind tunnel bioassays have been used to evaluate the response of Ae. aegypti, Cx. quinquefasciatus and Cx. nigripalpus towards the blood volatiles44. A dual choice wind tunnel was converted into a “five-choice” tunnel with all five glass tubes having glass jars at their end with openings to accommodate an artificial blood feeder. A continuous flow of warm water ensured the blood remained in liquid and produced its specific smell.A batch of approximately 100 female mosquitoes was released at the downwind end of the tunnel in the air stream coming from the five upwind end chambers. After 30 min, the numbers of mosquitoes in each of the five glass jars were counted. The mosquitoes were then sent back towards the downwind end of the wind tunnel, and the positions of odor cues were changed, including the control. Before the second time release, the fresh air was passed through the tunnel. Again the mosquitoes were released from the releasing box, and the response of the mosquitoes towards the new cues and the number of mosquitoes in each chamber at the upwind end was counted after 30 min; the same process was repeated, and for the third time with randomization. The same process was repeated 10 times with each blood group and with a new batch of mosquitoes each time.To test the response of female mosquitoes towards human-emitted olfactory cues, an olfactometer was used in previous studies41,43. The olfactometer test was conducted in the control room; the temperature was 27 ± 2 °C with 70–80% relative humidity. The optimum activity of the An. stephensi was observed late at night, so the experiment was conducted at 2–6 AM57.Steel balls rubbed in the hands of persons (ten volunteers per blood group) of having ABO blood groups along with the few drops of blood group-specific sweat were placed in the glass jars at the upwind end of the olfactometer. Approximately 100 female mosquitoes were released at the downwind end of the olfactometer from the releasing cage. After 30 min, the total number of mosquitoes in each box at the upwind end was counted, including the control. After that, the mosquitoes were returned to the releasing cage; then, the positions of steel balls at the upwind end of the glass jar of the olfactometer were changed randomly to decrease the biases from the data. To remove the smell of a sweat from the olfactory tube after cleaning, the fresh air was passed for about 10 min continuously. Mosquitoes were then again allowed to enter into the olfactometer, and after 30 min, the total number of mosquitoes was counted. The same process was repeated for the third time. The same experiment was repeated 10 times with different persons and mosquitoes to decrease the chances of error. A new batch of mosquitoes was selected for each replication.Statistical analysisThe mean number of eggs of An. stephensi were evaluated with the help of a linear model (ANOVA) and Tukey’s test on Minitab® software (12.2, version, Minitab). Before performing the ANOVA, with the help of angular transformation (arcsine √x), egg viability was also transformed58 for fertility. Data obtained were analyzed using R 3.2.2 software. The Shapiro–Wilk normality test was carried out, which showed that the data were not normally distributed. Hence, the Kruskal–Wallis Chi-square test was used to compare the averages of the responses of An. stephensi in relation to blood-group treatments.Ethics statementAll applicable international, national, and/or institutional guidelines for the care and use of animals were followed. More

EDITORIAL
21 December 2021

Sustainability at the crossroads

A look back at 2021 through the Sustainable Development Goals.

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A medical worker observes people with COVID-19 inside a makeshift care facility at the Commonwealth Games Village in New Delhi in May 2021.Credit: Getty

There were high hopes for 2021. The year promised progress on the push for sustainable development after months of pandemic-induced delays and uncertainty. We heard ambitious talk of a ‘green recovery’, and world leaders were due to gather for meetings of the United Nations conventions on biological diversity and on climate to set future agendas.How did the year’s sustainability debates evolve? We take a look through Nature’s science lens.2021: a year of multiple crisesAs 2021 draws to a close, the world is facing numerous crises. The COVID-19 pandemic is far from over. A year after the first vaccines began to clear regulatory hurdles, the emergence of the SARS-CoV-2 Omicron variant is challenging the fragile and unequal gains in bringing the virus under control. Progress is slow on mitigating and adapting to climate change, protecting biodiversity and ending hunger — parts of the Sustainable Development Goals (SDGs), the United Nations’ flagship plan to end poverty and promote a healthier planet by 2030. The plan, already off track before the pandemic, has been all but derailed by COVID-19.
More floods, fires and cyclones — plan for domino effects on sustainability goals
Nature has argued1 that the setback requires a more rapid response by the researchers who are writing the latest UN Global Sustainable Development Report — the scientific input to the SDGs, which runs on a four-year cycle. But attempts to feed science into policy have come up against strong barriers. Democracy and multilateralism are in retreat, undermining the commitment needed to make progress on sustainability goals. Still, this should not be a reason to disengage. On the contrary, researchers generally need to redouble their efforts.Fighting the climate crisisEarly November was marked by a momentous climate summit, the 26th UN Climate Change Conference of the Parties (COP26) in Glasgow, UK. For the first time, the final agreement included mention of a phase down of coal-fired power, although phase out was the original aim. It also called for the ending of some public subsidies for other fossil fuels — one of the biggest financial barriers to the shift to renewable energy. More than 100 countries pledged to cut methane emissions, flagged for their role in global warming in the latest report from the Intergovernmental Panel on Climate Change (IPCC)2. Richer nations committed to doubling their funding by 2025 to help low- and middle-income countries (LMICs) deal with the damage already caused by climate change, and they agreed to set up an office to research a long-proposed fund to compensate LMICs for that damage.But even if the pledges announced are implemented, temperatures are still projected to rise to a catastrophic 2.4 °C by 2100. And below the surface lay disagreements on definitions and the detail of implementation. And this is where research must continue to offer essential input. ‘Net-zero’ is one example. There is no agreed definition or measure of it, and without this, it’s impossible to know whether pledges will actually stop global warming. There is also no agreed definition of climate finance for LIMCs. This means that richer countries can make up their quotas with loans or official development aid that links to climate change only indirectly. Arguments have persisted for years over the funding promised more than a decade ago — what has been disbursed and who owes what — and this has undermined trust and has cast a shadow over negotiations, including those in the lead-up to the Glasgow meeting.

Protesters hold a ‘Biodiversity Emergency’ banner during the demonstration outside the Bank of England in London in November 2021.Credit: Vuk Valcic/SOPA Images/LightRocket/Getty

Elusive biodiversity protectionJust days before COP26, at a separate COP hosted by China in Kunming in Yunnan province, governments debated measures to protect the diversity and richness of plant and animal species. In the first sessions of a two-part UN summit on biological diversity, due to conclude in May 2022, discussions centred on a widely supported target to protect 30% of the world’s land and sea areas by 2030 — up from the previous ‘Aichi target’ of 17%. Among other targets under debate was the provision of greater financial support to low-income countries to preserve biodiversity.
The world’s species are playing musical chairs: how will it end?
Progress on biodiversity protection has proved elusive since the first ‘Earth Summit’ in Rio de Janeiro in 1992. The Kunming summit ended with a modest boost in funding for projects that help to preserve biodiversity — unlike climate change, funding for biodiversity comes mostly from the public sector. We argued that these contributions should be given as grants, rather than loans that saddle poor countries with debt3. This is now more important than ever, as the pandemic piles perilous debt on the developing world.Protecting biodiversity goes hand in hand with managing land and water resources sustainably, and in this way aligns with tackling climate change. And if nature continues to degrade, sooner or later economic output will suffer. This link is captured by debates over assigning monetary and other values to ecosystems, an idea no longer theoretical or controversial. In March, we welcomed a move by members of the UN Statistical Commission to finalize a set of principles that will help national statisticians record ecosystem health and work out payments for ecosystem services4.

Icebergs that calved from the Sermeq Kujalleq glacier in Greenland this year help mark one of Greenland’s biggest ice-melt years in recorded history.Credit: Mario Tama/Getty

Revamping food systemsLike biodiversity protection, the world’s food system needs fixing. One in ten people is undernourished and one in four is overweight. The number of people going hungry is rising fast, a trend fuelled by the pandemic. Nature’s coverage emphasizes the fact that science needs to guide the transformation of the food system. The task is challenging, because food spans many disciplines. We have yet to pin down what diets that are both healthy and sustainable should look like. And an IPCC-like system of scientific advice to inform policymaking has so far been missing from food and agriculture.
What humanity should eat to stay healthy and save the planet
That changed in September, when António Gutteres, the UN secretary-general, convened a controversial but historic Food Systems Summit. A group of scientists was tasked with ensuring that the science underpinning the summit was robust, broad and independent. Writing in Nature, this scientific group issued seven priorities for research, among them a greater focus on sustainable aquatic foods5. Soil-based agriculture tends to dominate discussions on food, with ‘blue foods’ — organisms such as fish, shellfish and seaweeds — rarely considered.Nature joined the scientific group’s call to argue that it’s time to change that (see go.nature.com/3e3ss6r). We published the Blue Food Assessment — the first systematic evaluation of how aquatic food contributes to food security — which explores how research can help transform the global food system. This work also shows some pitfalls of a greater reliance on blue foods without sustainable management, as a rapidly increasing demand for fish adds to risks for coastal ecosystems and the people of coastal communities.

Volunteers prepare meals for distribution in the Paraisopolis favela in São Paulo, Brazil, in March 2021Credit: Jonne Roriz/Bloomberg/Getty

Strong moves from the UN’s centreThe year 2021 also saw various arms of the UN consider how their own governance needs to respond and adapt to changing times. Guterres is set to appoint a new board of scientific advisers to his office, a decision that Nature welcomed6. The decision is part of the organization’s 25-year vision, laid out in the secretary-general’s report, Our Common Agenda (see go.nature.com/3egrudq), in September. Specialized agencies also needed to stocktake. Over the fifty years since its founding, the UN Environment Programme has pushed important initiatives that bring science into ‘green’ policy — co-founding the IPCC, for one — and we urged it to do more to bring together researchers from across environmental sciences to tackle interconnected challenges7. Nature also urged the International Monetary Fund’s shareholders to lend money to strengthen universities, so that science can better work towards global goals8.
The broken $100-billion promise of climate finance – and how to fix it
The right moves at the top echelons of global governance matter – but support for science and collaboration within and between countries matter just as much. In some ways, LMICs are leading the way. A 700-page report by the UN science and cultural organization UNESCO is a first attempt to understand the impact of the SDGs on research priorities9. It found that, unlike richer nations, lower-income countries’ share of research publications jumped in areas such as photovoltaics and climate-resilient crops. Individual countries need to do better to boost innovation, but collaboration will prove crucial. We need look no further than the pandemic for examples of how researchers working across borders, cultures and disciplines can benefit science and society.Collaboration and inclusionWe need — and can — do better on collaboration. Global problems need diverse teams to help navigate social and geopolitical challenges. Our COVID-19 coverage comes with a host of inspiring stories of scientists joining forces to tackle the crisis. It serves as a reminder of what can be done. But it’s not easy. Collaboration means spending less time achieving metrics of performance and more time nurturing relationships. Link-ups between science and industry suffer without rules around data ownership and intellectual property. And mounting geopolitical tensions, particularly between the United States and China, are limiting exchanges of people and knowledge10.
How the COVID pandemic is changing global science collaborations
The benefits of international research are worth the effort for both LIMCs and wealthy nations. But collaborations often come with concerns over equity and who benefits. Concerns over inclusion extend to policy forums too. At COP26, Nature found that researchers were frequently prevented by the organizers from accessing negotiations. Representatives from civil society and the global south also complained of exclusion. That experience must not be repeated. We’ve also argued that forums such as the G7 group of wealthy nations and the World Health Organization should regard emerging economies as equals. And UN bodies that solicit scientific input need to reach out beyond their usual expert networks to involve under-represented communities. The Food Systems Dialogues (see go.nature.com/3ykm2ye) could be a model: this initiative has engaged hundreds of participants across six continents since 2018, becoming an official mechanism to build international consensus at the UN food summit.An eye on the futureLooking ahead to 2022, we’re keeping our finger on the pulse. Nature will maintain a focus on climate, global health and sustainability. We expect more attention to the food crisis and climate-related migration, and more debate on solutions and trade-offs tied up with the energy transition.
Why fossil fuel subsidies are so hard to kill
The fallout from the pandemic will be a key focus. It includes the burden of disability from long COVID, lost ground in the fight against polio, malaria, tuberculosis and HIV, the lifelong impact of the loss of education for millions of children, and rising violence against women and girls. As economies struggle to get back on their feet, the financing of sustainability goals is an urgent issue that needs resolving. Researchers should also work towards resolving some of the long-standing tensions between climate, biodiversity conservation and food provision.The SDGs remain a holistic framework for guiding priorities for sustainable development. In the shorter term, we look to next year’s conclusion of the biodiversity summit, and the climate summit in Cairo. And we stand ready to support science as it responds to global challenges by engaging with policy and the public.

Nature 600, 569-570 (2021)
doi: https://doi.org/10.1038/d41586-021-03781-z

References1.Nature 589, 329–330 (2021).PubMed 
Article 

Google Scholar 
2.Intergovernmental Panel on Climate Change. Sixth Assessment Report — Climate Change 2021: The Physical Science Basis (IPCC, 2021).
Google Scholar 
3.Nature 598, 539–540 (2021).PubMed 
Article 

Google Scholar 
4.Nature 591, 178 (2021).PubMed 
Article 

Google Scholar 
5.von Braun, J., Afsana, K., Fresco, L. O. & Hassan, M. Nature 597, 28–30 (2021).PubMed 
Article 

Google Scholar 
6.Nature 600, 189-190 (2021).PubMed 
Article 

Google Scholar 
7.Nature 591, 8 (2021).PubMed 
Article 

Google Scholar 
8.Nature 592, 325–326 (2021).PubMed 
Article 

Google Scholar 
9.UNESCO. The Race Against Time for Smarter Development (UNESCO, 2021).
Google Scholar 
10.Nature 593, 477 (2021).PubMed 
Article 

Google Scholar 
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1.Dingemanse, N. J. & Wolf, M. Recent models for adaptive personality differences: A review. Phil. Trans. R. Soc. B 365, 3947–3958. https://doi.org/10.1098/rstb.2010.0221 (2010).Article 
PubMed 
PubMed Central 

Google Scholar 
2.Wolf, M., van Doorn, G., Leimar, O. & Weissing, F. J. Life-history trade-offs favour the evolution of animal personalities. Nature 447, 581–584. https://doi.org/10.1038/nature05835 (2007).ADS 
CAS 
Article 
PubMed 

Google Scholar 
3.Dingemanse, N. J., Both, C., Drent, P. J. & Tinbergen, J. M. Fitness consequences of avian personalities in a fluctuating environment. Proc. R. Soc. B. 271, 847–852. https://doi.org/10.1098/rspb.2004.2680 (2004).Article 
PubMed 
PubMed Central 

Google Scholar 
4.Sih, A. & Bell, A. M. Insights for behavioral ecology from behavioral syndromes. Adv. Study Behav. 38, 227–281. https://doi.org/10.1016/S0065-3454(08)00005-3 (2008).Article 
PubMed 
PubMed Central 

Google Scholar 
5.Sih, A., Bell, A. M. & Johnson, J. C. Behavioral syndromes: An ecological and evolutionary overview. Trends Ecol. Evol. 19, 372–378. https://doi.org/10.1016/j.tree.2004.04.009 (2004).Article 
PubMed 

Google Scholar 
6.Drent, P. J., van Oers, K. & van Noordwijk, A. J. Realized heritability of personalities in the great tit (Parus major). Proc. R. Soc. B. 270, 45–51. https://doi.org/10.1098/rspb.2002.2168 (2003).Article 
PubMed 
PubMed Central 

Google Scholar 
7.Sol, D., Griffin, A. S., Bartomeus, I. & Boyce, H. Exploring or avoiding novel food resources? The novelty conflict in an invasive bird. PLoS ONE 6, e19535. https://doi.org/10.1371/journal.pone.0019535 (2011).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
8.Dammhahn, M., Mazza, V., Schirmer, A., Göttsche, C. & Eccard, J. C. Of city and village mice: Behavioural adjustments of striped field mice to urban environments. Sci. Rep. 10, 13056. https://doi.org/10.1038/s41598-020-69998-6 (2020).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
9.Sih, A. & Del Giudice, M. Linking behavioural syndromes and cognition: A behavioural ecological perspective. Phil. Trans. R. Soc. B 367, 2762–2772. https://doi.org/10.1098/rstb.2012.0216 (2012).Article 
PubMed 
PubMed Central 

Google Scholar 
10.Stoewe, M. & Kotrschal, K. Behavioural phenotypes may determine whether social context facilitates or delays novel object exploration in ravens (Corvus corax). J. Ornithol. 148, S179–S184. https://doi.org/10.1007/s10336-007-0145-1 (2007).Article 

Google Scholar 
11.Guillette, L. M., Reddon, A. R., Hoeschele, M. & Sturdy, C. B. Sometimes slower is better: Slow-exploring birds are more sensitive to changes in a vocal discrimination task. Proc. R. Soc. B 278, 767–773. https://doi.org/10.1098/rspb.2010.1669 (2011).Article 
PubMed 

Google Scholar 
12.Dochtermann, N. A., Schwab, T. & Sih, A. The contribution of additive genetic variation to personality variation: Heritability of personality. Proc. R. Soc. B 282, 20142201. https://doi.org/10.1098/rspb.2014.2201 (2015).Article 
PubMed 
PubMed Central 

Google Scholar 
13.Van Oers, K., De Jong, G., Van Noordwijk, A. J., Kempenaers, B. & Drent, P. J. Contribution of genetics to the study of animal personalities: A review of case studies. Behaviour 142, 1185–1206. https://doi.org/10.1163/156853905774539364 (2005).Article 

Google Scholar 
14.Van Oers, K. & Mueller, J. C. Evolutionary genomics of animal personality. Phil. Trans. R. Soc. B 365, 3991–4000. https://doi.org/10.1098/rstb.2010.0178 (2010).Article 
PubMed 
PubMed Central 

Google Scholar 
15.Croston, R., Branch, C. L., Kozlovsky, D. Y., Dukas, R. & Pravosudov, V. V. Heritability and the evolution of cognitive traits. Behav. Ecol. 26, 1447–1459. https://doi.org/10.1093/beheco/arv088 (2015).Article 

Google Scholar 
16.Quinn, J. L., Cole, E. F., Reed, T. E. & Morand-Ferron, J. Environmental and genetic determinants of innovativeness in a natural population of birds. Phil. Trans. R. Soc. B 371, 20150184. https://doi.org/10.1098/rstb.2015.0184 (2016).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
17.Evans, J., Boudreau, K. & Hyman, J. Behavioural syndromes in urban and rural populations of song sparrows. Ethology 116, 588–595. https://doi.org/10.1111/j.1439-0310.2010.01771.x (2010).Article 

Google Scholar 
18.Bókony, V., Kulcsár, A., Tóth, Z. & Liker, A. Personality traits and behavioral syndromes in differently urbanized populations of house sparrows (Passer domesticus). PLoS ONE 7, 36639. https://doi.org/10.1371/journal.pone.0036639 (2007).ADS 
CAS 
Article 

Google Scholar 
19.Charmantier, A., Deyeyrier, V., Lambrechts, M., Perret, S. & Grégoire, A. Urbanization is associated with divergence in pace-of-life in great tits. Front. Ecol. Evol. https://doi.org/10.3389/fevo.2017.00053 (2017).Article 

Google Scholar 
20.Isaksson, C., Rodewald, A. D. & Gil, D. Editorial: Behavioural and ecological consequences of urban life in birds. Front. Ecol. Evol. https://doi.org/10.3389/fevo.2018.00050 (2018).Article 

Google Scholar 
21.Audet, J.-N., Ducatez, S. & Lefebvre, L. The town bird and the country bird: Problem solving and immunocompetence vary with urbanization. Behav. Ecol. 27, 637–644. https://doi.org/10.1093/beheco/arv201 (2016).Article 

Google Scholar 
22.Miranda, A. C., Schielzeth, H., Sonntag, T. & Partecke, J. Urbanization and its effects on personality traits: A result of microevolution or phenotypic plasticity. Glob. Change Biol. 19, 2634–2644. https://doi.org/10.1111/gcb.12258 (2013).ADS 
Article 

Google Scholar 
23.Riyahi, S., Björklund, M., Mateos-Gonzalez, F. & Senar, J. C. Personality and urbanization: Behavioural traits and DRD4 SNP830 polymorphisms in great tits in Barcelona city. J. Ethol. 35, 101–108. https://doi.org/10.1007/s10164-016-0496-2 (2017).Article 

Google Scholar 
24.Schinka, J. A., Letsch, E. A. & Crawford, F. C. DRD4 and novelty seeking: Results of meta-analyses. Am. J. Med. Genet. 114, 643–648. https://doi.org/10.1002/ajmg.10649 (2002).CAS 
Article 
PubMed 

Google Scholar 
25.Chen, C. S., Burton, M., Greenberger, E. & Dmitrieva, J. Population migration and the variation of Dopamine D4 Receptor (DRD4) allele frequencies around the globe. Evol. Hum. Behav. 20, 309–324. https://doi.org/10.1016/S1090-5138(99)00015-X (1999).Article 

Google Scholar 
26.Shimada, M. K. et al. Polymorphism in the second intron of dopamine receptor D4 gene in humans and apes. Biochem. Biophys. Res. Commun. 316, 1186–1190. https://doi.org/10.1016/j.bbrc.2004.03.006 (2004).CAS 
Article 
PubMed 

Google Scholar 
27.Fidler, A. E. et al. Drd4 gene polymorphisms are associated with personality variation in a passerine bird. Proc. R. Soc. B. 274, 1685–1691. https://doi.org/10.1098/rspb.2007.0337 (2007).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
28.Mueller, J. C. et al. Haplotype structure, adaptive history and associations with exploratory behaviour of the DRD4 gene region in four great tit (Parus major) populations. Mol. Ecol. 22, 2797–2809. https://doi.org/10.1111/mec.12282 (2013).CAS 
Article 
PubMed 

Google Scholar 
29.Korsten, P. et al. Association between DRD4 gene polymorphism and personality variation in great tits: A test across four wild populations. Mol. Ecol. 19, 832–843. https://doi.org/10.1111/j.1365-294X.2009.04518.x (2010).CAS 
Article 
PubMed 

Google Scholar 
30.Jiang, W., Shang, S. & Su, Y. Genetic influences on insight problem solving: The role of catechol-O-methyltransferase polymorphisms. Front. Psychol. 6, 1569. https://doi.org/10.3389/fpsyg.2015.01569 (2015).Article 
PubMed 
PubMed Central 

Google Scholar 
31.Hopkins, W. et al. Genetic influences on receptive joint attention in chimpanzees (Pan troglodytes). Sci. Rep. 4, 3774. https://doi.org/10.1038/srep03774 (2014).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
32.Fitzpatrick, M. J. et al. Candidate genes for behavioural ecology. Trends Ecol. Evol. 20, 96–104. https://doi.org/10.1016/j.tree.2004.11.017 (2005).Article 
PubMed 

Google Scholar 
33.Munafo, M. R., Brown, S. M. & Harkless, K. C. Serotonin transporter (5-HTTLPR) genotype and amygdala activation: A meta-analysis. Biol. Psychiatry 63, 852–857. https://doi.org/10.1016/j.biopsych.2007.08.016 (2008).CAS 
Article 
PubMed 

Google Scholar 
34.Staes, N. et al. Serotonin receptor 1A variation is associated with anxiety and agonistic behavior in chimpanzees. Mol. Biol. Evol. 36, 1418–1429. https://doi.org/10.1093/molbev/msz061 (2019).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
35.Mueller, J. C. et al. Behaviour-related DRD4 polymorphisms in invasive bird populations. Mol. Ecol. 23, 2876–2885. https://doi.org/10.1111/mec.12763 (2014).CAS 
Article 
PubMed 

Google Scholar 
36.Timm, K., Tilgar, V. & Saag, P. DRD4 gene polymorphism in great tits: Gender-specific association with behavioural variation in the wild. Behav. Ecol. Sociobiol. 69, 729–735. https://doi.org/10.1007/s00265-015-1887-z (2015).Article 

Google Scholar 
37.Riyahi, S., Sánchez-Delgado, M., Calafell, F., Monk, D. & Senar, J. C. Combined epigenetic and intraspecific variation of the DRD4 and SERT genes influence novelty seeking behaviour in great tit Parus major. Epigenetics 10, 516–525. https://doi.org/10.1080/15592294.2015.1046027 (2015).Article 
PubMed 
PubMed Central 

Google Scholar 
38.Holtmann, B. et al. Population differentiation and behavioural association of the two ‘personality’ genes DRD4 and SERT in dunnocks (Prunella modularis). Mol. Ecol. 25, 706–722. https://doi.org/10.1111/mec.13514 (2016).CAS 
Article 
PubMed 

Google Scholar 
39.Krause, E. T., Kjaer, J. B., Lüders, C. & van Phi, L. A polymorphism in the 5′-flanking region of the serotonin transporter (5-HTT) gene affects fear-related behaviors of adult domestic chickens. Behav. Brain Res. 14, 92–96. https://doi.org/10.1016/j.bbr.2017.04.051 (2017).CAS 
Article 

Google Scholar 
40.Timm, K., van Oers, K. & Tilgar, V. SERT gene polymorphisms are associated with risk-taking behaviour and breeding parameters in wild great tits. J. Exp. Biol. 221, jeb171595. https://doi.org/10.1242/jeb.171595 (2018).Article 
PubMed 

Google Scholar 
41.Timm, K., Koosa, K. & Tilgar, V. The serotonin transporter gene could play a role in anti-predator behaviour in a forest passerine. J. Ethol. 37, 221–227. https://doi.org/10.1007/s10164-019-00593-7 (2019).Article 

Google Scholar 
42.Berger, M., Gray, J. A. & Roth, B. L. The expanded biology of serotonin. Annu. Rev. Med. 60, 355–366. https://doi.org/10.1146/annurev.med.60.042307.110802 (2009).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
43.Lesch, K. P. & Merschdorf, U. Impulsivity, aggression, and serotonin: A molecular psychobiological perspective. Behav. Sci. Law 18, 581–604 (2000).CAS 
Article 

Google Scholar 
44.Duke, A. A., Bègue, L., Bell, R. & Eisenlohr-Moul, T. Revisiting the serotonin-aggression relation in humans: A meta-analysis. Psychol. Bull. 139, 1148–1172. https://doi.org/10.1037/a0031544 (2013).Article 
PubMed 
PubMed Central 

Google Scholar 
45.Ferrari, P. F., Palanza, P., Parmigiani, S., de Almeida, R. M. & Miczek, K. A. Serotonin and aggressive behavior in rodents and nonhuman primates: Predispositions and plasticity. Eur. J. Pharmacol. 526, 259–273. https://doi.org/10.1016/j.ejphar.2005.10.002 (2005).CAS 
Article 
PubMed 

Google Scholar 
46.Bacqué-Cazenave, J. et al. Serotonin in animal cognition and behavior. Int. J. Mol. Sci. 21, 1649. https://doi.org/10.3390/ijms21051649 (2020).CAS 
Article 
PubMed Central 

Google Scholar 
47.Walker, S. C. et al. Selective prefrontal serotonin depletion impairs acquisition of a detour-reaching task. Eur. J. Neurosci. 23, 3119–3123. https://doi.org/10.1111/j.1460-9568.2006.04826.x (2006).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
48.Cools, R., Roberts, A. C. & Robbins, T. W. Serotoninergic regulation of emotional and behavioural control processes. Trends Cogn. Sci. 12, 31–40. https://doi.org/10.1016/j.tics.2007.10.011 (2008).Article 
PubMed 

Google Scholar 
49.Rudnick, G. & Sandtner, W. Serotonin transport in the 21st century. J. Gen. Physiol. 151, 1248–1264. https://doi.org/10.1085/jgp.201812066 (2018).CAS 
Article 

Google Scholar 
50.Lesch, K. P. et al. Association of anxiety-related traits with a polymorphism in the serotonin transporter gene regulatory region. Science 274, 1527–1531. https://doi.org/10.1126/science.274.5292.1527 (1996).ADS 
CAS 
Article 
PubMed 

Google Scholar 
51.Sen, S., Burmeister, M. & Ghosh, D. Meta-analysis of the association between a serotonin transporter promoter polymorphism (5- HTTLPR) and anxiety-related personality traits. Am. J. Med. Genet. 127, 85–89. https://doi.org/10.1002/ajmg.b.20158 (2004).Article 

Google Scholar 
52.Karg, K., Burmeister, M., Shedden, K. & Sen, S. The serotonin transporter promoter variant (5-HTTLPR), stress, and depression meta-analysis revisited: Evidence of genetic moderation. Arch. Gen. Psychiatry 68, 444–454. https://doi.org/10.1001/archgenpsychiatry.2010.189 (2011).Article 
PubMed 
PubMed Central 

Google Scholar 
53.Beversdorf, D. Q. et al. Influence of serotonin transporter SLC6A4 genotype on the effect of psychosocial stress on cognitive performance: An exploratory pilot study. Cogn. Behav. Neurol. 31, 79–85. https://doi.org/10.1097/WNN.0000000000000153 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
54.Canli, T. & Lesch, P.-K. Long story short: The serotonin transporter in emotion regulation and social cognition. Nat. Neurosci. 10, 1103–1109. https://doi.org/10.1038/nn1964 (2007).CAS 
Article 
PubMed 

Google Scholar 
55.Jarrell, H. et al. Polymorphisms in the serotonin reuptake transporter gene modify the consequences of social status on metabolic health in female rhesus monkeys. Physiol. Behav. 93, 807–819. https://doi.org/10.1016/j.physbeh.2007.11.042 (2008).CAS 
Article 
PubMed 

Google Scholar 
56.Bennett, A. et al. Early experience and serotonin transporter gene variation interact to influence primate CNS function. Mol. Psychiatry 7, 118–122. https://doi.org/10.1038/sj.mp.4000949 (2002).CAS 
Article 
PubMed 

Google Scholar 
57.Golebiowska, J. et al. Serotonin transporter deficiency alters socioemotional ultrasonic communication in rats. Sci. Rep. 9, 20283. https://doi.org/10.1038/s41598-019-56629-y (2019).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
58.Thys, B. et al. The serotonin transporter gene and female personality variation in a free-living passerine. Sci. Rep. 11, 8577. https://doi.org/10.1038/s41598-021-88225-4 (2021).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
59.Audet, J.-N. et al. Divergence in problem-solving skills is associated with differential expression of glutamate receptors in wild finches. Sci. Adv. 4, eaao6369. https://doi.org/10.1126/sciadv.aao6369 (2018).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
60.Grunst, A. S., Grunst, M. L., Pinxten, R. & Eens, M. Personality and plasticity in neophobia levels vary with anthropogenic disturbance but not toxic metal exposure in urban great tits. Sci. Total Environ. 656, 997–1009. https://doi.org/10.1016/j.scitotenv.2018.11.383 (2019).ADS 
CAS 
Article 
PubMed 

Google Scholar 
61.Grunst, A. S., Grunst, M. L., Pinxten, R. & Eens, M. Sources of individual variation in problem-solving performance in urban great tits (Parus major): Exploring effects of metal pollution, urban disturbance and personality. Sci. Tot. Environ. 749, 141436. https://doi.org/10.1016/j.scitotenv.2020.141436 (2020).CAS 
Article 

Google Scholar 
62.Thys, B. et al. The female perspective of personality in a wild songbird: Repeatable aggressiveness relates to exploration behavior. Sci. Rep. 7, 7656. https://doi.org/10.1038/s41598-017-08001-1 (2017).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
63.Grunst, A. S. et al. An important personality trait varies with blood and plumage metal concentrations in a free-living songbird. Environ. Sci. Technol. 53, 10487–10496. https://doi.org/10.1021/acs.est.9b03548 (2019).ADS 
CAS 
Article 
PubMed 

Google Scholar 
64.Grunst, A. S. et al. Variation in personality traits across a metal pollution gradient in a free-living songbird. Sci. Total Environ. 630, 668–678. https://doi.org/10.1016/j.scitotenv.2018.02.19 (2018).ADS 
CAS 
Article 
PubMed 

Google Scholar 
65.Laucht, M. et al. Interaction between the 5-HTTLPR serotonin transporter polymorphism and environmental adversity for mood and anxiety psychopathology: Evidence from a high-risk community sample of young adults. Int. J. Neuropharmacol. 12, 737–747. https://doi.org/10.1017/S1461145708009875 (2009).CAS 
Article 

Google Scholar 
66.Wang, Z. et al. Genome-wide gene by lead exposure interaction analysis identifies UNC5D as a candidate gene for neurodevelopment. Environ. Health 16, 81. https://doi.org/10.1186/s12940-017-0288-3 (2017).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
67.Grunst, A. S., Grunst, M. L., Pinxten, R. & Eens, M. Proximity to roads, but not exposure to metal pollution, is associated with accelerated developmental telomere shortening in nestling great tits. Environ. Pollut. 256, 113373. https://doi.org/10.1016/j.envpol.2019.113373 (2019).CAS 
Article 
PubMed 

Google Scholar 
68.Dingemanse, N. J. et al. Repeatability and heritability of exploratory behaviour in great tits from the wild. Anim. Behav. 64, 929–937. https://doi.org/10.1006/anbe.2002.2006 (2002).Article 

Google Scholar 
69.Solé, X. et al. SNPStats: A web tool for the analysis of association studies. Bioinformatics 22, 1928–1929. https://doi.org/10.1093/bioinformatics/bti283 (2005).Article 

Google Scholar 
70.Hecht, M., Bromberg, Y. & Rost, B. Better prediction of functional effects for sequence variants from VarI-SIG 2014: Identification and annotation of genetic variants in the context of structure, function and disease. BMC Genom. 16, S1. https://doi.org/10.1186/1471-2164-16-S8-S1 (2015).CAS 
Article 

Google Scholar 
71.Choi, Y. & Chan, A. PROVEAN web server: A tool to predict the functional effect of amino acid substitutions and indels. Bioinformatics 31, 2745–2747. https://doi.org/10.1093/bioinformatics/btv195 (2015).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
72.Omasits, U., Ahrens, C. H., Müller, S. & Wollscheid, B. Protter: Interactive protein feature visualization and integration with experimental proteomic data. Bioinformatics 30(6), 884–886. https://doi.org/10.1093/bioinformatics/btt607 (2014).CAS 
Article 
PubMed 

Google Scholar 
73.R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria (2019). URL https://www.R-project.org/.74.Bates, D., Maechler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48. https://doi.org/10.18637/jss.v067.i01 (2014).Article 

Google Scholar 
75.Kuznetsova, A., Brockhoff, P. B. & Christensen, R. H. B. lmerTest Package: Tests in linear mixed effects models. J. Stat. Softw. 82, 1–26. https://doi.org/10.18637/jss.v082.i13 (2017).Article 

Google Scholar 
76.Stoffel, M. A., Nakagawa, S. & Schielzeth, H. rptR: repeatability estimation and variance decomposition by generalized linear mixed-effects models. Methods Ecol. Evol. 8, 1639–1644. https://doi.org/10.1111/2041-210X.12797 (2017).Article 

Google Scholar 
77.Harrison, X. A. Using observation-level random effects to model overdispersion in count data in ecology and evolution. PeerJ 2, e616. https://doi.org/10.7717/peerj.616 (2014).Article 
PubMed 
PubMed Central 

Google Scholar 
78.Lenth, R. emmeans: Estimated Marginal Means, aka Least-Squares Means. R package version 1.4.3.01 (2019). https://CRAN.R-project.org/package=emmeans.79.Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: A practical and powerful approach to multiple testing. J. R. Stat. Soc. B 57, 289–300. https://doi.org/10.2307/2346101 (1995).MathSciNet 
Article 
MATH 

Google Scholar 
80.Nakagawa, S. & Schielzeth, H. A general and simple method for obtaining R2 from generalized linear mixed-effects models. Methods Ecol. Evol. 4, 133–142. https://doi.org/10.1111/j.2041-210x.2012.00261.x (2013).Article 

Google Scholar 
81.Lüdecke, D., Makowski, D., Waggoner, P. & Patil, I. performance: Assessment of Regression Models Performance. R package version 0.4.6 (2020). https://CRAN.R-project.org/package=performance.82.Hartig, F. DHARMa: Residual Diagnostics for Hierarchical (Multi-Level/Mixed) Regression Models. R package version 0.2.6 (2019). https://CRAN.R-project.org/package=DHARMa.83.Mikros, E. & Diallinas, G. Tales of tails in transporters. Open Biol. 9, 190083. https://doi.org/10.1098/rsob.190083 (2019).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
84.Kern, C. et al. The N teminus specifies the switch between transporter modes of the human serotonin transporter. J. Biol. Chem. 292, 3603–3613. https://doi.org/10.1074/jbc.M116.771360 (2017).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
85.Visser, M. E., Van Noordwijk, A. J., Tinbergen, J. M. & Lessells, C. M. Warmer springs lead to mistimed reproduction in great tits (Parus major). Proc. R. Soc. B 265, 1867–1870. https://doi.org/10.1098/rspb.1998.0514 (1998).Article 
PubMed Central 

Google Scholar 
86.Hunt, R., Sauna, Z. E., Ambudkar, S. V., Gottesman, M. M. & Kimchi-Sarfaty, C. Silent (Synonymous) SNPs: Should we care about them? In Single Nucleotide Polymorphisms Methods in Molecular Biology (Methods and Protocols) Vol. 578 (ed. Komar, A.) (Humana Press, 2009). https://doi.org/10.1007/978-1-60327-411-1_2.Chapter 

Google Scholar 
87.Grunst, A.S., Grunst, M.L. & Staes, N., Bert, T., Pinxten, R., Eens, M. Data for: Serotonin Transporter (SERT) Polymorphisms, Personality and Problem-Solving in Urban Great Tits. (Dryad Digital Repository, 2021). More

1.Piao, S. et al. Glob. Change Biol. 25, 1922–1940 (2019).Article 

Google Scholar 
2.Richardson, A. D. et al. Nature 560, 368–371 (2018).CAS 
Article 

Google Scholar 
3.Ma, H. et al. Nat. Ecol. Evol. 5, 1110–1122 (2021).Article 

Google Scholar 
4.Mokany, K., Raison, R. J. & Prokushkin, A. S. Glob. Change Biol. 12, 84–96 (2006).Article 

Google Scholar 
5.Radville, L., McCormack, M. L., Post, E. & Eissenstat, D. M. J. Exp. Bot. 67, 3617–3628 (2016).CAS 
Article 

Google Scholar 
6.Liu, H. et al. Nat. Clim. Change https://doi.org/10.1038/s41558-021-01244-x (2021).7.Freschet, G. T. et al. New Phytol. 232, 1123–1158 (2021).Article 

Google Scholar 
8.Clemmensen, K. E. et al. Science 339, 1615–1618 (2013).CAS 
Article 

Google Scholar 
9.Sokol, N. W. & Bradford, M. A. Nat. Geosci. 12, 46–53 (2019).CAS 
Article 

Google Scholar 
10.Jones, D. L., Nguyen, C. & Finlay, R. D. Plant Soil 321, 5–33 (2009).CAS 
Article 

Google Scholar 
11.Abramoff, R. Z. & Finzi, A. C. New Phytol. 205, 1054–1061 (2015).Article 

Google Scholar 
12.Warren, J. M. et al. New Phytol. 205, 59–78 (2015).Article 

Google Scholar 
13.Blume-Werry, G., Wilson, S. D., Kreyling, J. & Milbau, A. New Phytol. 209, 978–986 (2016).CAS 
Article 

Google Scholar 
14.Sloan, V. L., Fletcher, B. J. & Phoenix, G. K. J. Ecol. 104, 239–248 (2016).CAS 
Article 

Google Scholar 
15.Fu, Y. H. et al. Nature 526, 104–107 (2015).CAS 
Article 

Google Scholar  More

1.Piao, S. et al. Characteristics, drivers and feedbacks of global greening. Nat. Rev. Earth Environ. 1, 14–27 (2020).
Google Scholar 
2.Forrest, J. & Miller-Rushing, A. Toward a synthetic understanding of the role of phenology in ecology and evolution. Philos. Trans. R. Soc. B 365, 3101–3112 (2010).
Google Scholar 
3.Lane, J. E., Kruuk, L., Charmantier, A., Murie, J. O. & Dobson, F. S. Delayed phenology and reduced fitness associated with climate change in a wild hibernator. Nature 489, 554–557 (2012).CAS 

Google Scholar 
4.Richardson, A. D. et al. Ecosystem warming extends vegetation activity but heightens vulnerability to cold temperatures. Nature 560, 368–371 (2018).CAS 

Google Scholar 
5.Abramoff, R. Z. & Finzi, A. C. Are above- and below-ground phenology in sync? New Phytol. 205, 1054–1061 (2015).
Google Scholar 
6.Piao, S. et al. Plant phenology and global climate change: current progresses and challenges. Glob. Change Biol. 25, 1922–1940 (2019).
Google Scholar 
7.Smithwick, E., Lucash, M. S., Mccormack, M. L. & Sivandran, G. Improving the representation of roots in terrestrial models. Ecol. Model. 291, 193–204 (2014).CAS 

Google Scholar 
8.Warren, J. M. et al. Root structural and functional dynamics in terrestrial biosphere models – evaluation and recommendations. New Phytol. 205, 59–78 (2015).
Google Scholar 
9.Ma, H., Mo, L., Crowther, T. W., Maynard, D. S. & Zohner, C. M. The global distribution and environmental drivers of aboveground versus belowground plant biomass. Nat. Ecol. Evol. 5, 1110–1122 (2021).
Google Scholar 
10.Neumann, R. B. & Cardon, Z. G. The magnitude of hydraulic redistribution by plant roots: a review and synthesis of empirical and modeling studies. New Phytol. 194, 337–352 (2012).
Google Scholar 
11.Lucas, M., Schlueter, S., Vogel, H.-J. & Vetterlein, D. Roots compact the surrounding soil depending on the structures they encounter. Sci. Rep. 9, 16236 (2019).
Google Scholar 
12.Oades, J. M. The role of biology in the formation, stabilization and degradation of soil structure. Geoderma 56, 377–400 (1993).
Google Scholar 
13.Thackeray, S. J. et al. Phenological sensitivity to climate across taxa and trophic levels. Nature 535, 241–245 (2016).CAS 

Google Scholar 
14.Roslin, T., Anto, L., Hllfors, M., Meyke, E. & Ovaskainen, O. Phenological shifts of abiotic events, producers and consumers across a continent. Nat. Clim. Change 11, 241–248 (2021).
Google Scholar 
15.Radville, L., McCormack, M. L., Post, E. & Eissenstat, D. M. Root phenology in a changing climate. J. Exp. Bot. 67, 3617–3628 (2016).CAS 

Google Scholar 
16.Blume-Werry, G., Jansson, R. & Milbau, A. Root phenology unresponsive to earlier snowmelt despite advanced above‐ground phenology in two subarctic plant communities. Funct. Ecol. 31, 1493–1502 (2017).
Google Scholar 
17.Wilson, J. B. A review of evidence on the control of shoot:root ratio, in relation to models. Ann. Bot. 61, 433–449 (1988).
Google Scholar 
18.Schwieger, S., Kreyling, J., Milbau, A. & Blume-Werry, G. Autumnal warming does not change root phenology in two contrasting vegetation types of subarctic tundra. Plant Soil 424, 145–156 (2018).CAS 

Google Scholar 
19.Liu, H., Lu, C., Wang, S., Ren, F. & Wang, H. Climate warming extends growing season but not reproductive phase of terrestrial plants. Glob. Ecol. Biogeogr. 30, 950–960 (2021).
Google Scholar 
20.Steinaker, D. F., Wilson, S. D. & Peltzer, D. A. Asynchronicity in root and shoot phenology in grasses and woody plants. Glob. Change Biol. 16, 2241–2251 (2010).
Google Scholar 
21.Keenan, T. F. et al. Net carbon uptake has increased through warming-induced changes in temperate forest phenology. Nat. Clim. Change 4, 598–604 (2014).CAS 

Google Scholar 
22.Thakur, M. P. Climate warming and trophic mismatches in terrestrial ecosystems: the green–brown imbalance hypothesis. Biol. Lett. 16, 20190770 (2020).
Google Scholar 
23.Wang, H. et al. Alpine grassland plants grow earlier and faster but biomass remains unchanged over 35 years of climate change. Ecol. Lett. 23, 701–710 (2020).
Google Scholar 
24.Chuine, I. A united model for budburst of trees. J. Theor. Biol. 2007, 337–347 (2000).
Google Scholar 
25.Lim, P. O., Kim, H. J. & Gil Nam, H. Leaf senescence. Annu. Rev. Plant Biol. 58, 115–136 (2007).CAS 

Google Scholar 
26.Reich, P. B., Walters, M. & Ellsworth, D. Leaf life-span in relation to leaf, plant, and stand characteristics among diverse ecosystems. Ecol. Monogr. 62, 365–392 (1992).
Google Scholar 
27.Körner, C. & Basler, D. Phenology under global warming. Science 327, 1461–1462 (2010).
Google Scholar 
28.Fu, Y. H. et al. Declining global warming effects on the phenology of spring leaf unfolding. Nature 526, 104–107 (2015).CAS 

Google Scholar 
29.Wolkovich, E. M. et al. Warming experiments underpredict plant phenological responses to climate change. Nature 485, 494–497 (2012).CAS 

Google Scholar 
30.López-Bucio, J., Cruz-Ramírez, A. & Herrera-Estrella, L. The role of nutrient availability in regulating root architecture. Curr. Opin. Plant Biol. 6, 280–287 (2003).
Google Scholar 
31.Friedl, M. A. et al. Global land cover mapping from MODIS: algorithms and early results. Remote Sens. Environ. 83, 287–302 (2002).
Google Scholar 
32.Lian, X. et al. Summer soil drying exacerbated by earlier spring greening of northern vegetation. Sci. Adv. 6, eaax0255 (2020).
Google Scholar 
33.Hollister, R. D., Webber, P. J. & Bay, C. Plant response to temperature in northern Alaska: implications for predicting vegetation change. Ecology 86, 1562–1570 (2005).
Google Scholar 
34.Song, J. et al. A meta-analysis of 1,119 manipulative experiments on terrestrial carbon-cycling responses to global change. Nat. Ecol. Evol. 3, 1309–1320 (2019).
Google Scholar 
35.Collins, C. G. et al. Experimental warming differentially affects vegetative and reproductive phenology of tundra plants. Nat. Commun. https://doi.org/10.1038/s41467-021-23841-2 (2021).36.Reyes-Fox, M. et al. Elevated CO2 further lengthens growing season under warming conditions. Nature 510, 259–267 (2014).CAS 

Google Scholar 
37.Richardson, A. D. et al. Influence of spring and autumn phenological transitions on forest ecosystem productivity. Philos. Trans. R. Soc. B 365, 3227–3246 (2010).
Google Scholar 
38.Wingler, A. & Hennessy, D. Limitation of grassland productivity by low temperature and seasonality of growth. Front. Plant Sci. 7, 1130 (2016).
Google Scholar 
39.Schenk, H. J. & Jackson, R. B. Rooting depths, lateral root spreads and below-ground/above-ground allometries of plants in water-limited ecosystems. J. Ecol. 90, 480–494 (2002).
Google Scholar 
40.Wang, P., Huang, K. & Hu, S. Distinct fine-root responses to precipitation changes in herbaceous and woody plants: a meta-analysis. New Phytol. 225, 1491–1499 (2020).
Google Scholar 
41.Arft, A. et al. Responses of tundra plants to experimental warming: meta-analysis of the international tundra experiment. Ecol. Monogr. 69, 491–511 (1999).
Google Scholar 
42.Fu, Y. S. et al. Variation in leaf flushing date influences autumnal senescence and next year’s flushing date in two temperate tree species. Proc. Natl Acad. Sci. USA 111, 7355–7360 (2014).CAS 

Google Scholar 
43.Seastedt, T. & Knapp, A. Consequences of nonequilibrium resource availability across multiple time scales: the transient maxima hypothesis. Am. Nat. 141, 621–633 (1993).CAS 

Google Scholar 
44.Bai, E. et al. A meta-analysis of experimental warming effects on terrestrial nitrogen pools and dynamics. New Phytol. 199, 441–451 (2013).
Google Scholar 
45.Sakai, A. & Larcher, W. Frost Survival of Plants: Responses and Adaptation to Freezing Stress (Springer‐Verlag, 1987).46.Zani, D., Crowther, T. W., Mo, L., Renner, S. S. & Zohner, C. M. Increased growing-season productivity drives earlier autumn leaf senescence in temperate trees. Science 370, 1066–1071 (2020).CAS 

Google Scholar 
47.Luo, Y. Terrestrial carbon-cycle feedback to climate warming. Annu. Rev. Ecol. Evol. Syst. 38, 683–712 (2007).
Google Scholar 
48.Hijmans, R. J., Ca Meron, S. E., Parra, J. L., Jones, P. G. & Jarvis, A. Very high resolution interpolated climate surfaces for global land areas. Int. J. Climatol. 25, 1965–1978 (2010).
Google Scholar 
49.Sloan, V. L., Fletcher, B. J. & Phoenix, G. K. Contrasting synchrony in root and leaf phenology across multiple sub‐Arctic plant communities. J. Ecol. 104, 239–248 (2016).CAS 

Google Scholar 
50.Kou, L. et al. Nitrogen deposition increases root production and turnover but slows root decomposition in Pinus elliottii plantations. New Phytol. 218, 1450–1461 (2018).
Google Scholar 
51.Adams, D. C., Gurevitch, J. & Rosenberg, M. S. Resampling tests for meta-analysis of ecological data. Ecology 78, 1277–1283 (1997).
Google Scholar 
52.Viechtbauer, W. Conducting meta-analyses in R with the metafor package. J. Stat. Soft. 36, 1–48 (2010).
Google Scholar 
53.Kattge, J. et al. TRY plant trait database-enhanced coverage and open access. Glob. Change Biol. 26, 119–188 (2020).
Google Scholar 
54.De Martonne, E. Une nouvelle fonction climatologique: l’indice d’aridité. La MétéOrol. 2, 449–458 (1926).
Google Scholar 
55.Breiman, L. Classification and Regression Trees (Routledge, 2017).56.Liaw, A. & Wiener, M. Classification and regression by randomForest. R News 2/3, 18–22 (2002).
Google Scholar 
57.Terrer, C. et al. Nitrogen and phosphorus constrain the CO2 fertilization of global plant biomass. Nat. Clim. Change 10, 696–697 (2020).
Google Scholar 
58.Wickham, H. ggplot2: Elegant Graphics for Data Analysis (Springer-Verlag, 2016).59.Liu, H. et al. Supporting data for ‘Phenological mismatches between above- and belowground plant responses to climate warming’. Figshare https://figshare.com/s/1f086364114021cd80d9 (2021). More

1.Yang, W. Y. et al. Soil properties and geography shape arbuscular mycorrhizal fungal communities in black land of China. Appl. Soil Ecol. 167, 104109. https://doi.org/10.1016/j.apsoil.2021.104109 (2021).Article 

Google Scholar 
2.Li, H. Y. et al. Effects of different slopes and fertilizer types on the grey water footprint of maize production in the black soil region of China. J. Clean. Prod. 246, 119077. https://doi.org/10.1016/j.jclepro.2019.119077 (2020).CAS 
Article 

Google Scholar 
3.Li, X. Y., Wang, D. Y., Ren, Y. X., Wang, Z. M. & Zhou, Y. H. Soil quality assessment of croplands in the black soil zone of Jilin Province, China: Establishing a minimum data set model. Ecol. Indic. 107, 105251. https://doi.org/10.1016/j.ecolind.2019.03.028 (2019).CAS 
Article 

Google Scholar 
4.Mao, L. G. et al. Flame soil disinfestation: A novel, promising, non-chemical method to control soilborne nematodes, fungal and bacterial pathogens in China. Crop. Prot. 83, 90–94. https://doi.org/10.1016/j.cropro.2016.02.002 (2016).ADS 
Article 

Google Scholar 
5.Rasool, M. et al. Role of biochar, compost and plant growth promoting rhizobacteria in the management of tomato early blight disease. Sci. Rep. 11, 6092. https://doi.org/10.1038/s41598-021-85633-4 (2021).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
6.Solorzano, C. D. & Malvick, D. K. Effects of fungicide seed treatments on germination, population, and yield of maize grown from seed infected with fungal pathogens. Field. Crop. Res. 122(3), 173–178. https://doi.org/10.1016/j.fcr.2011.02.011 (2011).Article 

Google Scholar 
7.An-le, H. E. et al. Soil application of Trichoderma asperellum GDFS1009 granules promotes growth and resistance to Fusarium graminearum in maize. J. Integr. Agric. 18(3), 599–606. https://doi.org/10.1016/S2095-3119(18)62089-1 (2019).Article 

Google Scholar 
8.Xu, X. G. et al. Isolation and characterization of Bacillus amyloliquefaciens MQ01, a bifunctional biocontrol bacterium with antagonistic activity against Fusarium graminearum and biodegradation capacity of zearalenone. Food Control 130, 108259. https://doi.org/10.1016/j.foodcont.2021.108259 (2021).CAS 
Article 

Google Scholar 
9.Bonanomi, G., Antignani, V. & Scala, C. P. Suppression of soilborne fungal diseases with organic amendments. J. Plant. Pathol. 89(3), 311–324 (2007).
Google Scholar 
10.Shafique, H. A., Sultana, V., Ehteshamul-Haque, S. & Athar, M. Management of soil-borne diseases of organic vegetables. J. Plan. Protect. Res. https://doi.org/10.1515/jppr-2016-0043 (2016).Article 

Google Scholar 
11.Li, H. et al. Evaluation on the production of food crop straw in China from 2006 to 2014. Bioenerg. Res. 10, 949–957. https://doi.org/10.1007/s12155-017-9845-4 (2017).Article 

Google Scholar 
12.Zhang, P., Wei, T., Jia, Z. K., Han, Q. F. & Ren, X. L. Soil aggregate and crop yield changes with different rates of straw incorporation in semiarid areas of northwest China. Geoderma 230–231, 41–49. https://doi.org/10.1016/j.geoderma.2014.04.007 (2014).ADS 
Article 

Google Scholar 
13.Yang, H. S. et al. The impacts of ditch-buried straw layers on the interface soil physicochemical and microbial properties in a rice-wheat rotation system. Soil. Till. Res. 202, 146656. https://doi.org/10.1016/j.still.2020.104656 (2020).Article 

Google Scholar 
14.Song, X. Y. et al. Stable isotopes reveal the formation diversity of humic substances derived from different cotton straw-based materials. Sci. Total. Environ. 740, 140202. https://doi.org/10.1016/j.scitotenv.2020.140202 (2020).ADS 
CAS 
Article 
PubMed 

Google Scholar 
15.Mi, Y. Z. et al. Changes in soil quality, bacterial community and anti-pepper Phytophthora disease ability after combined application of straw and multifunctional composite bacterial strains. Eur. J. Soil. Biol. 105, 103329. https://doi.org/10.1016/j.ejsobi.2021.103329 (2021).CAS 
Article 

Google Scholar 
16.Guo, X. X., Liu, H. T. & Wu, S. B. Humic substances developed during organic waste composting: Formation mechanisms, structural properties, and agronomic functions. Sci. Total. Environ. 662, 501–510. https://doi.org/10.1016/j.scitotenv.2019.01.137 (2019).ADS 
CAS 
Article 
PubMed 

Google Scholar 
17.Baldock, J. A. & Skjemstad, J. O. Role of the soil matrix and minerals in protecting natural organic materials against biological attack. Org. Geochem. 31(7–8), 697–710. https://doi.org/10.1016/S0146-6380(00)00049-8 (2000).CAS 
Article 

Google Scholar 
18.Chaparro, J. M. et al. Manipulating the soil microbiome to increase soil health and plant fertility. Biol. Fert. Soils. 48(5), 489–499. https://doi.org/10.1007/s00374-012-0691-4 (2012).Article 

Google Scholar 
19.Hu, Y. et al. Integrated biocontrol of tobacco bacterial wilt by antagonistic bacteria and marigold. Sci. Rep. 11, 16360. https://doi.org/10.1038/s41598-021-95741-w (2021).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
20.Hyder, S. et al. Characterization of native plant growth promoting rhizobacteria and their anti-oomycete potential against Phytophthora capsici affecting chilli pepper (Capsicum annum L.). Sci. Rep. 10, 13859. https://doi.org/10.1038/s41598-020-69410-3 (2020).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
21.Paterson, E., Sim, A., Osborne, S. & Murray, P. J. Long-term exclusion of plant-inputs to soil reduces the functional capacity of microbial communities to mineralise recalcitrant root-derived carbon sources. Soil. Biol. Biochem. 43(9), 1873–1880. https://doi.org/10.1016/j.soilbio.2011.05.006 (2011).CAS 
Article 

Google Scholar 
22.Wang, H., Guo, Q., Li, X., Li, X. & Zhang, C. Effects of long-term no-tillage with different straw mulching frequencies on soil microbial community and the abundances of two soil-borne pathogens. Appl. Soil. Ecol. 148, 103488. https://doi.org/10.1016/j.apsoil.2019.103488 (2020).Article 

Google Scholar 
23.Ndzelu, B. S., Dou, S. & Zhang, X. W. Changes in soil humus composition and humic acid structural characteristics under different corn straw returning modes. Soil. Res. 58, 452–460. https://doi.org/10.1071/SR20025 (2020).CAS 
Article 

Google Scholar 
24.De Corato, U. Agricultural waste recycling in horticultural intensive farming systems by on-farm composting and compost-based tea application improves soil quality and plant health: A review under the perspective of a circular economy. Sci. Total. Environ. 738, 139840. https://doi.org/10.1016/j.scitotenv.2020.139840 (2021).CAS 
Article 

Google Scholar 
25.Wong, M. & Swift, R. S. Role of organic matter in alleviating soil acidity. in Handbook of Soil Acidity. http://espace.library.uq.edu.au/view/UQ:191317 (2003).26.Xie, W. J. et al. Coastal saline soil aggregate formation and salt distribution are affected by straw and nitrogen application: A 4-year field study. Soil. Till. Res. 198, 104535. https://doi.org/10.1016/j.still.2019.104535 (2020).Article 

Google Scholar 
27.Cathal, N. et al. Soil aggregates formed in vitro by saprotrophic Trichocomaceae have transient water-stability. Soil. Biol. Biochem. 48, 151–161. https://doi.org/10.1016/j.soilbio.2012.01.010 (2012).CAS 
Article 

Google Scholar 
28.Lou, Y. L., Xu, M. G., Wang, W., Sun, X. L. & Zhao, K. Return rate of straw residue affects soil organic C sequestration by chemical fertilization. Soil. Till. Res. 113(1), 70–73. https://doi.org/10.1016/j.still.2011.01.007 (2011).Article 

Google Scholar 
29.Loffredo, E., Berloco, M. & Senesi, N. The role of humic fractions from soil and compost in controlling the growth in vitro of phytopathogenic and antagonistic soil-borne fungi. Ecotoxicol. Environ. Saf. 69(3), 350–357. https://doi.org/10.1016/j.ecoenv.2007.11.005 (2008).CAS 
Article 
PubMed 

Google Scholar 
30.Bhatia, A. et al. Diversity of bacterial isolates during full scale rotary drum composting. Waste Manag. 33(7), 1595–1601. https://doi.org/10.1016/j.wasman.2013.03.019 (2013).CAS 
Article 
PubMed 

Google Scholar 
31.Dou, S., Zhang, J. J. & Li, K. Effect of organic matter applications on 13C-NMR spectra of humic acids of soil. Eur. J. Soil. Sci. 59(3), 532–539. https://doi.org/10.1111/j.1365-2389.2007.01012.x (2008).CAS 
Article 

Google Scholar 
32.De, V. et al. Soil bacterial networks are less stable under drought than fungal networks. Nat. Commun. 9(1), 3033. https://doi.org/10.1038/s41467-018-05516-7 (2018).ADS 
CAS 
Article 

Google Scholar 
33.Sanaullah, M. et al. How do microbial communities in top and subsoil respond to root litter addition under field conditions?. Soil Biol. Biochem. 103, 28–38. https://doi.org/10.1016/j.soilbio.2016.07.017 (2016).CAS 
Article 

Google Scholar 
34.Song, Y. et al. Identification of the produced volatile organic compounds and the involved soil bacteria during decomposition of watermelon plant residues in a Fusarium-infested soil. Geoderma 315, 178–187. https://doi.org/10.1016/j.geoderma.2017.11.021 (2018).ADS 
CAS 
Article 

Google Scholar 
35.Vida, C., Cazorla, F. M. & Vicente, A. D. Characterization of biocontrol bacterial strains isolated from a suppressiveness-induced soil after amendment with composted almond shells. Res. Microbiol. 168(6), 583–593. https://doi.org/10.1016/j.resmic.2017.03.007 (2017).CAS 
Article 
PubMed 

Google Scholar 
36.Liu, J. G., Li, X. G., Jia, Z. J., Zhang, T. L. & Wang, X. X. Effect of benzoic acid on soil microbial communities associated with soilborne peanut diseases. Appl. Soil. Ecol. 110, 34–42. https://doi.org/10.1016/j.apsoil.2016.11.001 (2017).ADS 
Article 

Google Scholar 
37.Zhao, S. C. et al. Ciampitti dynamic of fungal community composition during maize residue decomposition process in north-central China. Appl. Soil Ecol. 167, 104057. https://doi.org/10.1016/j.apsoil.2021.104057 (2021).Article 

Google Scholar 
38.Zhang, J., Xu, Y., Liang, S., Ma, X. & Sun, F. Synergistic effect of klebsiella sp. fh-1 and arthrobacter sp. nj-1 on the growth of the microbiota in the black soil of northeast china. Ecotox. Environ. Safe 190, 110079. https://doi.org/10.1016/j.ecoenv.2019.110079 (2019).CAS 
Article 

Google Scholar 
39.Wang, X. W. et al. Diversity and taxonomy of Chaetomium and chaetomium-like fungi from indoor environments. Stud. Mycol. 84, 145–224. https://doi.org/10.1016/j.simyco.2016.11.005 (2016).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
40.Chen, W. H. et al. High-throughput sequencing analysis of endophytic fungal diversity in cynanchum sp.. S. Afr. J. Bot. 134, 349–358. https://doi.org/10.1016/j.sajb.2020.04.010 (2020).CAS 
Article 

Google Scholar 
41.Voriskova, J. & Baldrain, P. Fungal community on decomposing leaf litter undergoes rapid successional changes. ISME J. 7(3), 477–486. https://doi.org/10.1038/ismej.2012.116 (2013).CAS 
Article 
PubMed 

Google Scholar 
42.Kerdraon, L., Laval, V. & Suffert, F. Microbiomes and pathogen survival in crop residues, an ecotone between plant and soil. Phytobiomes J. 3, 246–255. https://doi.org/10.1094/pbiomes-02-19-0010-rvw (2019).Article 

Google Scholar 
43.Rahman, S. F. S. A. et al. Emerging microbial biocontrol strategies for plant pathogens. Plant Sci. 267, 102–111. https://doi.org/10.1016/j.plantsci.2017.11.012 (2018).CAS 
Article 

Google Scholar 
44.Wachowska, U., Irzykowski, W., Jedryczka, M., Stasiulewicz-Paluch, A. D. & Glowacka, K. Biological control of winter wheat pathogens with the use of antagonistic Sphingomonas bacteria under greenhouse conditions. Biocontrol. Sci. Technol. 23, 1110–1122. https://doi.org/10.1080/09583157.2013.812185 (2013).Article 

Google Scholar 
45.Liu, J. J. et al. Soil carbon content drives the biogeographical distribution of fungal communities in the black soil zone of northeast China. Soil Biol. Biochem. 83(0038–0017), 29–39. https://doi.org/10.1016/j.soilbio.2015.01.009 (2012).ADS 
CAS 
Article 

Google Scholar 
46.Xiong, W. et al. Distinct roles for soil fungal and bacterial communities associated with the suppression of vanilla Fusarium wilt disease. Soil Biol. Biochem. 107, 198–207. https://doi.org/10.1016/j.soilbio.2017.01.010 (2017).CAS 
Article 

Google Scholar 
47.Raaijmakers, J. M. & Mazzola, M. Diversity and natural functions of antibiotics produced by beneficial and plant pathogenic bacteria. Annu. Rev. Phytopathol. 50, 403–424. https://doi.org/10.1146/annurev-phyto-081211-172908 (2012).CAS 
Article 
PubMed 

Google Scholar 
48.Deng, X. H. et al. Rhizosphere bacteria assembly derived from fumigation and organic amendment triggers the direct and indirect suppression of tomato bacterial wilt disease. Appl. Soil Ecol. 147, 103364. https://doi.org/10.1016/j.apsoil.2019.103364 (2020).Article 

Google Scholar 
49.Li, C. N. et al. Microbial inoculation influences bacterial community succession and physicochemical characteristics during pig manure composting with corn straw. Bioresour. Technol. 289, 121653. https://doi.org/10.1016/j.biortech.2019.121653 (2019).CAS 
Article 
PubMed 

Google Scholar 
50.Lydia, S., Tymon, P. M., Gundersen, B. & Inglis, D. A. Potential of endophytic fungi collected from Cucurbita pepo roots grown under three different agricultural mulches as antagonistic endophytes to Verticillium dahliae in western Washington. Microbiol. Res. 240, 126535. https://doi.org/10.1016/j.micres.2020.126535 (2020).CAS 
Article 

Google Scholar 
51.Mehmood, M. A. et al. Sclerotia of a phytopathogenic fungus restrict microbial diversity and improve soil health by suppressing other pathogens and enriching beneficial microorganisms. J. Environ. Manag. 259, 109857. https://doi.org/10.1016/j.jenvman.2019.109857 (2020).Article 

Google Scholar 
52.Ding, J. L. et al. Influence of inorganic fertilizer and organic manure application on fungal communities in a long-term field experiment of Chinese Mollisols. Appl. Soil. Ecol. 111, 114–122. https://doi.org/10.1016/j.apsoil.2016.12.003 (2017).ADS 
Article 

Google Scholar 
53.Zhao, Y. Y. et al. Characterization of Lysobacter spp. strains and their potential use as biocontrol agents against pear anthracnose. Microbiol. Res. 242, 126624. https://doi.org/10.1016/j.micres.2020.126624 (2021).CAS 
Article 
PubMed 

Google Scholar 
54.Liu, X. S. et al. Organic amendment improves rhizosphere environment and shapes soil bacterial community in black and red soil under lead stress. J. Hazard. Mater. 416, 125805. https://doi.org/10.1016/j.jhazmat.2021.125805 (2021).CAS 
Article 
PubMed 

Google Scholar 
55.Qiao, J. Q., Tian, D. W., Huo, R., Wu, H. J. & Gao, X. W. Functional analysis and application of the cryptic plasmid pBSG3 harboring the RapQ–PhrQ system in Bacillus amyloliquefaciens B3. Plasmid 65(2), 141–149. https://doi.org/10.1016/j.plasmid.2010.11.008 (2011).CAS 
Article 
PubMed 

Google Scholar 
56.Coutte, F. et al. Effect of pps disruption and constitutive expression of srfa on surfactin productivity, spreading and antagonistic properties of Bacillus subtilis 168 derivatives. J. Appl. Microbiol. 109(2), 480–491. https://doi.org/10.1111/j.1365-2672.2010.04683.x (2010).CAS 
Article 
PubMed 

Google Scholar 
57.Leclere, V. et al. Mycosubtilin overproduction by Bacillus subtilis bbg100 enhances the organism’s antagonistic and biocontrol activities. Appl. Environ. Microb. 71(8), 4577. https://doi.org/10.1128/AEM.71.8.4577-4584.2005 (2005).ADS 
CAS 
Article 

Google Scholar 
58.Choi, S. K., Jeong, H., Kloepper, J. W. & Ryu, C. M. Genome sequence of Bacillus amyloliquefaciens GB03, an active ingredient of the first commercial biological control product. Genome Announc. 2(5), 1092–1106. https://doi.org/10.1128/genomeA.01092-14 (2014).Article 

Google Scholar 
59.Kim, S. Y., Lee, S. Y., Weon, H. Y., Sang, M. K. & Song, J. Complete genome sequence of Bacillus velezensis M75, a biocontrol agent against fungal plant pathogens, isolated from cotton waste. J. Biotechnol. 241, 112–115. https://doi.org/10.1016/j.jbiotec.2016.11.023 (2017).CAS 
Article 
PubMed 

Google Scholar 
60.Abbasi, S. et al. Streptomyces strains modulate dynamics of soil bacterial communities and their efficacy in disease suppression caused by Phytophthora capsici. Sci. Rep. 11, 9317. https://doi.org/10.1038/s41598-021-88495-y (2021).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
61.Saravanakumar, K. et al. Effect of Trichoderma harzianum on maize rhizosphere microbiome and biocontrol of Fusarium stalk rot. Sci. Rep. 7, 1771. https://doi.org/10.1038/s41598-017-01680-w (2017).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
62.Yan, F., Li, C., Ye, X., Lian, Y. & Wang, X. Antifungal activity of lipopeptides from Bacillus amyloliquefaciens mg3 against colletotrichum gloeosporioides in loquat fruits. Biol. Control 146, 104281. https://doi.org/10.1016/j.biocontrol.2020.104281 (2020).CAS 
Article 

Google Scholar 
63.Qi, Y., Liu, H., Wang, J. & Wang, Y. Effects of different straw biochar combined with microbial inoculants on soil environment of ginseng. Sci. Rep. 11, 14685. https://doi.org/10.21203/rs.3.rs-189319/v1 (2021).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
64.Wang, Y. et al. Evaluation and spatial variability of paddy soil fertility in typical county of northeast China. J. Plant Nutr. Fertil. 26(2), 256–266. https://doi.org/10.11674/zwyf.19128 (2020).CAS 
Article 

Google Scholar 
65.Cambardella, C. A. & Elliott, E. T. Carbon and nitrogen distribution in aggregates from cultivated and native grassland soils. Soil Sci. Soc. Am. J. 57(4), 1071–1076. https://doi.org/10.2136/sssaj1993.03615995005700040032x (1993).ADS 
CAS 
Article 

Google Scholar 
66.Zhang, X., Dou, S., Ndzelu, B. S., Guan, X. W. & Bai, Y. Effects of different corn straw amendments on humus composition and structural characteristics of humic acid in black soil. Commun. Soil. Sci. Plan. 51(1), 1–11. https://doi.org/10.1080/00103624.2019.1695827 (2019).CAS 
Article 

Google Scholar 
67.Edgar, R. C. Uparse: Highly accurate OTU sequences from microbial amplicon reads. Nat. Methods. 10(10), 996. https://doi.org/10.1038/NMETH.2604 (2021).Article 

Google Scholar 
68.Amato, K. R. et al. Habitat degradation impacts black howler monkey (Alouatta pigra) gastrointestinal microbiomes. ISME J. 7, 1344–1353. https://doi.org/10.1038/ismej (2013).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
69.Lourenço, K. S. et al. Resilience of the resident soil microbiome to organic and inorganic amendment disturbances and to temporary bacterial invasion. Microbiome 6, 142. https://doi.org/10.1186/s40168-018-0525-1 (2018).Article 
PubMed 
PubMed Central 

Google Scholar  More

Plant height (cm)Plant height of black cumin as affected by moringa leaf extract applied at various growth stages is reported in Table 1. Both concentrations of moringa leaf extract significantly affected plant height of black cumin. All growth stages also showed statistically significant results. Mean comparison of control vs treatments and water spray vs rest were also found significant for plant height (cm) of black cumin. Whereas, interaction of moringa leaf extract concentrations and growth stages remained non-significant. With increase in interval of spraying moringa leaf extract, plant height enhanced and thus taller plants (68.15 cm) were recorded when moringa leaf extract was sprayed at stage-7 (40 + 80 + 120 days after sowing), followed by (65.15 cm) stage-4 (40 + 80 days after sowing), while lower plants height (47.45 cm) was recorded in stage-3 (120 days after sowing). The use of moringa leaf extract during critical vegetative development phases increased the black cumin crop’s plant height. Similar results were recorded by Abbas et al.14 that moringa leaf extract enhanced plant height and improved fresh and dried weight of wheat root when compared to control. Taller (62.2 cm) plants were recorded in 20% moringa leaf extract sprayed plots followed by (55.8 cm) 10% moringa leaf extract. Spraying moringa leaf extract on a variety of field crops can boost plants and increase vegetative development15.Table 1 Plant height (cm), number of branches plant−1 fixed oil content (% vw−1) and essential oil content (% vw−1) of black cumin as affected by moringa leaf extract applied at various growth stages.Full size tableBranches plant−1
Branches plant−1 of black cumin were significantly influenced by moringa leaf extract concentrations, stage of application as well as their interaction (Table 1). The planned mean comparison of control vs rest and water spray vs rest were also found significant for branches plant−1. The unsprayed against sprayed treatments of moringa leaf extract showed that in unsprayed plots number of branches plant−1 (39) were less than plants sprayed with moringa leaf extract (61.19). Highest number of branches plant−1 (62.19) were observed 20% moringa leaf extract treated plots. These results are in agreement with Mahmood16 who found that foliar application of MLE contains an adequate amount of stimulating substances that promote cell division and enlargement at a faster rate. Zeatin, a growth hormone found in moringa leaf extract, encourages the growth of lateral buds, which leads to an increase in the number of branches. After pounding 100 g of Moringa leaves in 8 L of water, foliar spray of moringa leaf extract enhanced branches plant−1 in okra17. More number of branches plant−1 (70.66) were attained in plots sprayed with moringa leaf extract at growth stage 7 (40 + 80 + 120 days after sowing), followed by growth stage 4 (40 + 80 days after sowing). The effect of the application of MLE at the rate of 20% at 40 days’ interval increased the number of branches and this may be because of the abundant supply of macro and micronutrients and growth hormones. The result of yield parameters revealed that the yield increased as the frequency of moringa leaf extract increased. This is because hormone enhances formation and development of flowers and ripening of fruits. Hormones also enhance growth and yield by altering photosynthetic distributive pattern within the plants. The findings were also in line with that of Manzoor et al.18 who found that an aqueous extract of moringa significantly influence yield and yield components such as number of branches, number of fruits per plant and fruit weight of tomato. The significant interaction of MLE and growth stages is presented in Fig. 1. Applying moringa leaf extract @ 20% at all growth stages enhanced branches plant−1. Maximum branches plant−1 was observed when moringa leaf extract was sprayed @ 20% at growth stage 7 (40 + 80 + 120 days after sowing) whereas, minimum branches plant−1 was recorded in plants sprayed with 10% moringa leaf extract at growth stage-3 (120 days after sowing). Moringa leaf extract (MLE) increased number of branches. Similar results were recorded by Jain et al.19), who reported MLE positively enhanced plant growth attributes of wheat. He also stated that with increasing MLE concentration and application intervals, the growth parameters such as branches plant−1 were increased in arithmetic order. Plant growth regulators are essential for controlling growth and development of plants20. These plant growth regulators increased yield by changing the dry matter distribution pattern or controlling the growth characteristics in crop plants, depending on the dosage and time of application21. In comparison to control, foliar application of moringa leaf extract resulted in a markedly higher branches plant−1. The increased number of branches plant−1 might be due to Zeatin present in moringa leaf extract, which is very effective in delaying the abscission response10.Figure 1Number of branches plant−1 of black cumin as affected by moringa leaf extract applied at various growth stages.Full size imageFixed oil content (% vw−1)Data concerning fixed oil content (% vw−1) in response to moringa leaf extract applied at various growth stages is given in Table 1 and Fig. 2. Statistical analysis of data indicated that foliar application of various concentrations of moringa leaf extract, their stage of application and interaction of concentrations and growth stages had significantly affected fixed oil content (% vw−1) of black cumin crop. The planned mean comparison of control vs rest and water spray vs rest had significant effect on fixed oil content (% vw−1). Highest fixed oil percentage (35.39%) was recorded when moringa leaf extract was sprayed @ 20%, followed by (34.06%) 10% moringa leaf extract, whereas, control (31.48%) showed lowest fixed oil %. Sakr et al.22 indicated that foliar applications of MLE significantly improved the oil percentage and yield plant−1 and feddan of geranium plants. Application of MLE at growth stage-7 (40 + 80 + 120 days after sowing) showed maximum fixed oil content percentage (37.08%) as compared to all other growth stages. Minimum fixed oil percentage was recorded in growth stage-1 (40 days after sowing). Concerning the interaction of moringa leaf extract vs application stage, highest fix oil (37.45%) was observed when moringa leaf extract @ 20% was applied as foliar spray at growth stage-7 (40 + 80 + 120 days after sowing), followed by (36.71%) moringa leaf extract @ 10% applied at growth stage-7. Lowest fixed oil percentage (31.83%) was observed in plants sprayed with 10% moringa leaf extract at stage 1 (40 days after sowing). According to Rady et al.23, biosynthesis of cytokinins promotes the movement of stem reserves to new shoots, resulting in stable plant development, the prevention of premature leaf senescence, and the preservation of more leaf area for photosynthetic action.Figure 2Fixed oil content (%) of black cumin as affected by moringa leaf extract applied at various growth stages.Full size imageEssential oil content (% vw−1)Essential oil content (% vw−1) is a vital oil component of black cumin. Moringa leaf extract concentrations and stage of their application had significant effect on essential oil content of black cumin while the interaction remained non-significant (Table 1). Application of MLE at 20% resulted in higher essential oil yield (0.38%) followed by 10% moringa leaf extract (0.37) sprayed plots. Control plots resulted in lower essential oil (0.33%) content of black cumin. Many research ventures around the world are currently focusing on increasing the biomass yield and volatile oil output of aromatic plants. Moringa leaf extract has been discovered to be an excellent bio-stimulant for enhancing not only crop growth but also yield24,25. According to Aslam et al.26, Plant treated with MLE had major impacts, including an average rise in oil concentrations. Interestingly, MLE treatment not only increased the coriander fruit yield but also improved the fruits volatile oil suggesting that MLE could be a promise plant growth promoter that improved the content of volatile oil in coriander. MLE application also positively affected the volatile oil constituents (Table 2). Increasing the volatile oil in coriander by MLE could be due to the MLE components including amino acids, nutrient elements and phytohoromes that motivate the accumulation of secondary metabolites27. The phytohormones affect the pathway of terpenoids through motivating the responsible physiological and biochemical processes28. Concerning the application stages of moringa leaf extract, higher essential oil content % of black cumin (0.42%) was observed in growth stage-7 (40 + 80 + 120 days after sowing), followed by (0.39%) growth stage-4 (40 + 80 days after sowing), whereas, lower essential oil content % (0.36%) of black cumin was observed in growth stage-1 (40 days after sowing). Plant growth regulators are essential for controlling the amount, type, and direction of plant growth, development, and yield20. These plant growth regulators increased yield by changing the dry matter distribution pattern or controlling the growth characteristics in crop plants, depending on the dosage and time of application21. Exogenous application of MLE resulted in higher yield and quality29.Table 2 Peroxidase value (meq kg−1) and Iodine value (g of I2/100 g) of black cumin as affected by moringa leaf extract applied at various growth stages.Full size tablePeroxidase value (meq kg−1)The response of MLE and stage of MLE application recorded for peroxidase value is stated in Table 2. The data depicted that moringa leaf extract concentrations, stage of application and their interaction had significant (P ≤ 0.05) variation in peroxidase value of black cumin. Similarly, when means were compared, that of control vs treatments and water spray check vs treatments were found significant for peroxidase value (%). Mean value of data indicated that highest peroxidase value (6.32%) was recorded in 20% moringa leaf extract treated plots, followed by (6.03%) 10% moringa leaf extract. While in case of application stages, highest peroxidase value (6.42%) was recorded when moringa leaf extract was applied at stage-7 (40 + 80 + 120 days after sowing), followed by (6.39%) stage-6 (80 + 120 days after sowing). Whereas lowest peroxidase value (5.73%) was recorded in plots treated with moringa leaf extract at stage-3 (120 days after sowing). Interaction of moringa leaf extract concentrations and stage of application in Fig. 3 showed that increasing moringa leaf extract concentration from 10 to 20% applied at growth stage-7 increased peroxidase value of black cumin crop. However, application of moringa leaf extract @ 10% applied at growth stage-3 (120 days after sowing) showed lowest peroxidase value. The phytohormones affect the pathway of terpenoids through motivating the responsible physiological and biochemical processes28. Our results are in agreement with the reports of Ali et al.27 in geranium and Abdel-Rahman and Abdel-Kader30 in fennel who observed that MLE application improves both the volatile oil yield and its components. The fact that MLE application improved black cumin growth and quality characters suorts the study’s hypothesis that MLE is an important plant growth enhancer. In agreement with our results, Rady and Mohamed28 concluded that MLE is considered one of the important plant bio stimulants because it contains antioxidants, phenols, basic nutrients, ascorbates, and phytohormones. Furthermore, foliar application of moringa leaf extract may have a positive effect on endogenous phytohormone concentrations, resulting in improved plant growth and quality10,37.Figure 3Peroxidase value (meq kg−1) of black cumin as affected by moringa leaf extract applied at various growth stages.Full size imageIodine value (g of I2/100 g)Data concerning iodine value of black cumin oil in response to various concentrations of MLE applied at various growth stages is given in Table 2 and Fig. 4. Statistical analysis of data indicated that both the concentrations of moringa leaf extract, stage of application as well as their interaction had significant effect on iodine value of black cumin oil. The planned mean comparison of control vs rest and water spray vs rest treatments had significant effect on iodine value. Highest iodine value (85.3) was recorded with application of moringa leaf extract @ 20% whereas, lowest (78.28) was observed in control. Regarding the stage of application, highest iodine value (87.35) was observed in plots sprayed with moringa leaf extract at stage-7 (40 + 80 + 120 days after sowing), followed by (85.61) plots sprayed with moringa leaf extract at growth stage-6 (80 + 120 days after sowing). Concerning the interaction of MLE concentrations and stage of application of MLE, highest iodine value (6.49) was observed with 20% moringa leaf extract sprayed at stage-7 (40 + 80 + 120 days after sowing) whereas, lowest iodine value was observed in plants sprayed with moringa leaf extract @ 20% applied at stage-3 (120 days after sowing). The use of plant growth regulators is very specific and depends to achieve specific results like for example; enhanced plant growth, betterment in yield and yield related attributes, and to modify the fruit and plant bio-constituents. Several previous studies reveled that MLE are enriched with many phtyo-hormones especially zeatin31. In addition to that MLEs are embedded with many essential amino acids, vitamins (A, B1, B2, B3, C and E), minerals as well as several antioxidants like phenolic32,33. This unique biochemical composition of MLE showed that they can be utilized as bio stimulant which have the potential to promote crop growth, productivity as well as quality which in return depends on its application time34.Figure 4Iodine value (meq kg−1) of black cumin as affected by moringa leaf extract applied at various growth stages.Full size imageTotal free amino acidsThe data presented in Table 2 revealed that moringa leaf extract concentrations and application stages had significantly affected total free amino acid content of black cumin crop during rabi 2019-20 under agro-climatic conditions of Haripur whereas, their interaction remained non-significant. The planned mean comparison of control vs rest and water spray vs rest had significant effect on total free amino acids of black cumin. Highest amino acids (336.3) were observed with the application of moringa leaf extract @ 20%, followed by application of moringa leaf extract @ 10%. Regarding application stages, highest total free amino acids (364.2) were observed with the application of moringa leaf extract at 40 + 80 + 120 days after sowing, followed by (355.9) application of MLE at 40 + 80 days after sowing. Lowest total free amino acids (290.3) were recorded with moringa leaf extract sprayed at 40 days after sowing. Several investigations have demonstrated that MLE can alter both primary and secondary metabolism, resulting in an increase in antioxidant molecule concentrations35,36. The content of phenolic antioxidants, total soluble proteins, and total free amino acids increased in spinach plants treated with synthetic growth regulators and MLE26. MLE can also increase fruit quality metrics in ‘Kinnow’ mandarins, such as soluble solid contents, vitamin C, sugars, total antioxidant, phenolic contents, and superoxide dismutase and catalase enzyme activities, when treated at various growth stages37.Total phenolicPhenolic have acquired much importance because of their properties of disease preventing and health promoting. The effect of moringa leaf extract concentrations, stage of application and their interaction is presented in Table 2. Analysis of variance revealed that moringa leaf extract concentrations and stage of application of moringa leaf extract had significant effect on total phenolic content of black cumin while their interaction remained non-significant. Our results depict that all MLE levels enhanced the total phenolic content of black cumin leaves relative to the control. Highest phenolic content (71.59 mg g−1) was observed with application of moringa leaf extract at the rate of 20%, followed by (68.72 mg g−1) moringa leaf extract application at the rate of 10%. Regarding application stages, highest phenolic content (81.23 mg g−1) was observed with the application of moringa leaf extract at growth stage-7 (40 + 80 + 120 days after sowing), followed by (76.66 mg g−1) stage-6 (80 + 120 days after sowing), whereas, lowest phenolic content (55.25 mg g−1) was observed in crop sprayed with moringa leaf extract at stage-3 (120 days after sowing). In the medicinal, biological, and agricultural areas, phenolic and their derivatives gained scientists attention. Recent studies had focused on their potential as antioxidant-rich natural chemicals38. The increased content of phenolics, flavonoids, and phytohormones in moringa leaves, which may have contributed to the enhanced total phenolic content in black cumin leaves, can be linked to the higher content of phenolics, flavonoids, and phytohormones in MLE treated plants26. Furthermore, the proper concentrations of minerals, vitamins, and -carotene found in moringa leaves may have influenced metabolic processes in a way that increased the internal phenolic content in black cumin leaves, either directly or indirectly39. Therefore, these aspects assist MLE to serve as growth enhancer and natural antioxidant40. Our results supported by the previous report of Nasir et al.37 who revealed that the total phenolic content was enhanced as a result of MLE application at critical stages of plant growth. More