Philippa Kaur

We analyse weekly reported counts of suspected and confirmed human cases and deaths attributed to LF (as defined in Supplementary Table 1), between 1 January 2012 and 30 December 2019, from across the entire of Nigeria. The weekly counts were reported from 774 LGAs in 36 Federal states and the Federal Capital Territory, under Integrated Disease Surveillance and Response (IDSR) protocols, and collated by the NCDC. All suspected cases, confirmed cases and deaths from notifiable infectious diseases (including viral haemorrhagic fevers; VHFs) are reported weekly to the LGA Disease Surveillance and Notification Officer (DSNO) and State Epidemiologist (SE). IDSR routine data on priority diseases are collected from inpatient and outpatient registers in health facilities, and forwarded to each LGA’s DSNO using SMS or paper form. Subsequently, individual LGA DSNOs collate and forward the data to their respective SE, also by SMS and paper form, for weekly and monthly reporting respectively to NCDC. From mid-2017 onwards, data entry in 18 states has been conducted using a mobile phone-based electronic reporting system called mSERS, with the data entered using a customised Excel spreadsheet that is used to manually key into NCDC-compatible spreadsheets. Data from this surveillance regime (WERs) were collated by epidemiologists at NCDC throughout the period 2012 to March 2018 (Supplementary Fig. 1).Throughout the study period, within-country LF surveillance and response has been strengthened under NCDC coordination2,20,33. LGAs are now required to notify immediately any suspected case to the state-level, which in turn reports to NCDC within 24 h, and also sends a cumulative weekly report of all reported cases. A dedicated, multi-sectoral NCDC LF TWG was set up in 2016 with the responsibility of coordinating all LF preparedness and response activities across states. Further capacity building occurred in 2017 to 2019, with the opening of three additional LF diagnostic laboratories in Abuja (Federal Capital Territory), Abakaliki (Ebonyi state) and Owo (Ondo state) (to a total of five; Fig. 2) and the rollout of intensive country-wide training on surveillance, clinical case management and diagnosis. We note that, due to the rapid expansion in a test capacity, the definition of a suspected case in our data has subtly changed over the surveillance period: from 2012 to 2016, suspected cases include probable cases that were not lab-tested, whereas from 2017 to 2019, all suspected cases were tested and confirmed to be negative.In addition to the WERs data, since 2017 LF case reporting data has also been collated by the LF TWG and used to inform the weekly NCDC LF Situation Reports (SitRep data; https://ncdc.gov.ng/diseases/sitreps). This regime includes post hoc follow-ups to ensure more accurate case counts, so our analyses use WER-derived case data from 2012 to 2016, and SitRep-derived case data from 2017 to 2019 (see Fig. 1 for full time series). A visual comparison of the data from each separate time series, including the overlap period (2017 to March 2018) is provided in Supplementary Fig. 1, and all statistical models considered random intercepts for the different surveillance regimes. Where other studies of recent Nigeria LF incidence have been more spatially and temporally restricted34,35, the extended monitoring period and fine spatial granularity of these data provide the opportunity for a detailed empirical perspective on the local drivers of LF at a country-wide scale and their relationship to changes in reporting effort.Recent trends in LF surveillance in NigeriaWe visualised temporal and seasonal trends in suspected and confirmed LF cases within and between years, for both surveillance datasets. Weekly case counts were aggregated to country-level and visualised as both annual case accumulation curves, and aggregated weekly case totals (Fig. 1 and Supplementary Fig. 1). We also mapped annual counts of suspected and confirmed cases across Nigeria at the LGA-level to examine spatial changes in reporting over the surveillance period (Fig. 2). State and LGA shapefiles used for modelling and mapping were obtained from Humanitarian Data Exchange under a CC-BY-IGO license (https://data.humdata.org/dataset/nga-administrative-boundaries).Analyses of aggregated district data are sensitive to differences in scale and shape of aggregation (the modifiable areal unit problem; MAUP36), and LGA geographical areas in Nigeria are highly skewed and vary over >3 orders of magnitude (median 713 km2, mean 1175 km2, range 4–11,255 km2). We therefore also aggregated all LGAs across Nigeria into 130 composite districts with a more even distribution of geographical areas, using distance-based hierarchical clustering on LGA centroids (implemented using hclust in R), with the constraint that each new cluster must contain only LGAs from within the same state (to preserve potentially important state-level differences in surveillance regime). Weekly and annual suspected and confirmed LF case totals were then calculated for each aggregated district. We used these spatially aggregated districts to test for the effects of scale on spatial drivers of LF occurrence and incidence.Statistical analysisWe analysed the full case time series (Fig. 1) to characterise the spatiotemporal incidence and drivers of LF in Nigeria, while controlling for year-on-year increases and expansions of surveillance effort. We firstly modelled annual LF occurrence and incidence at a country-wide scale, to identify the spatial, climatic and socio-ecological correlates of disease risk across Nigeria. Secondly, we modelled seasonal and temporal trends in weekly LF incidence within hyperendemic areas in the north and south of Nigeria, to identify the seasonal climatic conditions associated with LF risk dynamics and evaluate the scope for forecasting. All data processing and modelling was conducted in R v.3.4.1 with the packages R-INLA v.20.03.1737, raster v.3.4.1338 and velox v0.2.039. Statistical modelling was conducted using hierarchical regression in a Bayesian inference framework (integrated nested Laplace approximation (INLA)), which provides fast, stable and accurate posterior approximation for complex, spatially and temporally-structured regression models37,40, and has been shown to outperform alternative methods for modelling environmental phenomena with evidence of spatially biased reporting41.Processing climatic and socio-ecological covariatesWe collated geospatial data on socio-ecological and climatic factors that are hypothesised to influence either M. natalensis distribution and population ecology (rainfall, temperature and vegetation patterns), frequency and mode of human–rodent contact (poverty and improved housing prevalence), both of the above (agricultural and urban land cover) or likelihood of LF reporting (travel time to nearest laboratory with LF diagnostic capacity and travel time to nearest hospital). For each LGA we extracted the mean value for each covariate across the LGA polygon. The full suite of covariates tested across all analyses, data sources and associated hypotheses are described in Supplementary Table 5.We collated climate data spanning the full monitoring period and up until the date of analysis (July 2011 to January 2021). We obtained daily precipitation rasters for Africa42 from the Climate Hazards Infrared Precipitation with Stations (CHIRPS) project; this dataset is based on combining sparse weather station data with satellite observations and interpolation techniques, and is designed to support hydrologic forecasts in areas with poor weather station coverage (such as tropical West Africa)42. A recent study ground-truthing against weather station data showed that CHIRPS provides greater overall accuracy than other gridded precipitation products in Nigeria43. Air temperature daily minimum and maximum rasters were obtained from NOAA and were also averaged to calculate daily mean temperature. EVI, a measure of vegetation quality, was obtained from processing 16-day composite layers from NASA (National Aeronautics and Space Administration) (excluding all grid cells with unreliable observations due to cloud cover and linearly interpolating between observations to give daily values; Supplementary Table 5).We derived several spatial bioclimatic variables to capture conditions across the full monitoring period (Jan 2012 to Dec 2019): mean precipitation of the driest annual month, mean precipitation of the wettest annual month, precipitation seasonality (coefficient of variation), annual mean air temperature, air temperature seasonality, annual mean EVI and EVI seasonality. We also calculated monthly total precipitation, 3-month SPI44, average daily mean (Tmean), minimum (Tmin) and maximum (Tmax) temperature and EVI variables at sequential time lags prior to reporting week for seasonal modelling (described below in Temporal drivers). SPI is a standardised measure of drought or wetness conditions relative to the historical average conditions for a given period of the year. SPI was calculated within a rolling 3-month window across the full 40-year historical CHIRPS rainfall time series (1981–2020) using the R package SPEI v.1.744.We accessed annual human population rasters at 100 m resolution from WorldPop. We accessed the proportion of the population living in poverty in 2010 ( More

Our measure of interest was whether females ate more of the flake items (i.e., cheated less quickly) when the male had perceptual access than when he did not. Consistent with our predictions, females ate fewer flake items in the male not visible condition (Mean = 3.6 items, SD = 3.2) than in the male visible condition (Mean = 4.5, SD = 3.1; Fig. 2A; for flake items eaten by pairs see Supplementary Fig. S1). Additionally, females tended to cheat less over rounds (Supplementary Fig. S2). Indeed, the number of flake items eaten was predicted by both conditions (LRT, X21 = 8.13, p = 0.004; Fig. 2A; Supplementary Table S1) and round (LRT, X21 = 12.46, p  More

In banana, bract opening behavior depends on the time of the day, the position of the bract, and sex of the flowers enclosed by the bract. Bract opening is a continuous process especially in the first bracts subtending female flowers of some genotypes; it starts in the evening and continues through the night (Table 1). In cases where bracts did not fully open, the process was halted early morning and resumed in the evening. It is therefore not obvious to judge whether such bracts have opened or not. However, opening is permanent as opposed to some plant species which open and close their flowers at specific times. Ssebuliba et al.16 considered East African Highland bananas ready for pollination when bracts were half way open with stigmas having a creamy white appearance. According to observations made in the current study, it can be said that bract lifting is indicative of flower opening thus pollination can start.Bract lift and bract roll seemed to be a response of a certain light quality6, the response time and speed are genotype dependent. Finger curling also seems to be triggered by the same factors that lead to bract opening. Bract opening and finger curling are likely to be a response of changes in turgor pressures in cells that lead to tissues being pushed in a given direction17. This was evident with upward movement of the inflorescence from the horizontal-pendent toward the horizontal position in the evening and downward movement towards the pendent position by mid-morning. These movements were genotype dependent and small, maximum oscillation was about 10˚. A similar pattern was observed for leaf folding to influence relative canopy cover18.Generally, bracts subtending female flower lifted and started rolling earlier than those subtending male flowers. However, male flowers ended opening before female flowers, resulting in faster bract opening for male flowers (Table 1 and t-test). This might be due to the smaller bract size of male flowers (Fig. 1) or an adaption for female flowers to find male flowers open with ready pollen. Consequently, the strategy ensures maximum pollination success and survival of the Musa spp. Studies have revealed that pollen viability reduces with time after flower opening1. This is in agreement that controlled pollination should be done between 07:00 and 10:00 h7. In comparison to lilies, some flowers were observed also to open starting at 17:00 h while others open during day. Both nocturnal and diurnal pollinators were found to be active flower visitors19. This implies that pollination in banana can start in the evening as long as bracts for parents in the cross of interest lift in time.In Musa itinerans, two nectar production peaks were found, that is between 08:00 to 12:00 h and 20:00 to 24:00 h20. This maybe a close depiction of what happens in edible bananas thus emphasizing the potential importance of diurnal and nocturnal pollinators. Bats, bees, and birds were found to be among the most important pollinators of bananas at Onne, Nigeria10. However, natural pollinators were not the main focus of the study though they are good indicators of when stigmas might be highly receptive. Since nectar quality and quantity varies between different agro-ecologies and seasons21, flower visitations and seed set are also expected to vary accordingly. Different agro-ecologies are also expected to experience variable BOTs due to variable solar radiation. Likewise the different growing seasons (rainy and dry) might also affect BOTs and therefore seed set22. However, a comparison of time from sunrise to beginning of bract lift of Musa AAA Cavendish cultivars in a glasshouse and M. basjoo in the garden in Belgium revealed no significant difference6. But comparison of bract curling time in Mchare in Arusha with short days and Cavendish cultivars in a glasshouse in Belgium with long days in summer, there was early curling in the glasshouse. However, bract lift time may be a better event to use for comparison than bract curling or rolling time.Bracts of both female and male flowers of different genotypes completed opening at different times and this may be partly the reason for variable pollen viability and stigma receptivity (Table 1). Female flowers that finish opening much earlier may set less seed compared to those that finish opening closer to the routine time of hand pollination between 07:00 and 10:00 h. Conversely, male flowers that are ready shortly before the time of hand pollination are expected to have higher pollen viability. This probably explains the high fertility of ‘Calcutta 4’ as it finished opening at 06:30 h. Some male flowers like those of Matooke finished opening as early as 21:54 h (Table 1) and are expected to have pollen with low viability at the time it is measured the next day.All observed inflorescences opened one female bract on the first day, increasing to multiple bracts opening on subsequent days (Fig. 2). One to three bracts subtending female flowers were observed to open per day from the second bract position of the inflorescence. The pattern of opening took on a hyperbolic shape with up to four bracts opening on the fourth day in the midsection of the inflorescence. For hand pollination, more clusters are therefore expected to be pollinated per day during bract opening in the mid-section of the inflorescence. The different clusters of female flowers that open on the same day are likely to have stigmas with varying receptivity. The darker appearance of stigmas of former clusters compared to creamy stigmas in latter clusters reflects higher receptivity in the latter2. This may explain why some clusters set more seed especially in the mid-section of a seemingly fertile inflorescence.Upon complete opening of female and transitional bracts, inflorescences went into a pause period before male flowers opened (Table 2). In additional to spatial separation of flowers, this is temporal separation to promote cross pollination in banana. However, temporal separation of male and female flowers is not very effective for genotypes that had less than 24 h of separation. With aid of crawling insects, self-pollination may happen between the last female cluster and the first male cluster as stigmas are likely to be receptive for more than one day. Once male flowers started opening, one bract opened per day and occasionally two bracts were observed to open on the same day. For highly fertile genotypes like ‘Calcutta 4’, ample pollen is produced to pollinate many female flowers. Male flowers are also produced throughout the inflorescence growth period which ensures constant supply of pollen especially for controlled hand pollination. Averages of bracts subtending male flowers opening per day could not be calculated as there were two to three observed bracts subtending male flowers for most genotypes.It appears that proximal bracts subtending female flowers are less stimulated to lift and roll compared to distal bracts subtending female flowers and all bracts subtending male flowers. This was revealed by low vigour of bract lift and the small angle of lift at 08:00 h especially in the first female flower cluster (Figs. 2, 3). The bract angle of lift increases from proximal to distal end and this has been linked to reduced fertility in proximal clusters2. But it may not be the case since highly female (in all clusters) and male fertile ‘Calcutta 4’ showed the same pattern as edible bananas. The high R2 for female bract roll scores compared to bracts subtending male flowers was a result of more bracts used to calculate averages for bracts subtending female flowers compared to bracts subtending male flowers (Fig. 3). For bracts subtending male flowers, two to three bracts were observed for most genotypes thus the first three data points were close to the trend line. Since the number of female clusters varies, reducing number of data points were used to calculate average bract lift angles in the distal end or larger inflorescences. Besides, bract lift angles of some clusters could not be measured because of obscurity or being in awkward positions. This led to the last two points being far off the trend line for angle of lift and hence a low R2.Flower opening time is said to be genetically and environmentally controlled, results from this study are in agreement since light had considerable influence on bract opening events (Tables 1, 3). Significant effects of temperature, solar radiation, and vapor pressure deficit on flower opening time have been observed in rice11. For Musa spp., only light has a significant relationship with BOT. However, there was early curling under long summer days in the glasshouse in Belgium compared to short days in Arusha field conditions6. This suggested a particular light signal for BOT in Musa spp. It is unclear why high light intensity led to early lift of bracts subtending male flowers and this calls for farther investigation. Since bracts subtending male flowers instinctively open later than bracts subtending female flowers, light intensity had less effect on the former bracts. The small sample size could have also had an impact on the results in the study, the light flush from the camera could have also affected the results. The extent of weather effects on BOT in banana need to be studied in field conditions of locations with significantly different day length for a more reliable conclusion. More

1.Hairston, N. G., Smith, F. E. & Lawrence, B. S. Community structure, population control, and competition. Am. Nat. 94, 421–425 (1960).Article 

Google Scholar 
2.Gross, P. Insect behavioral and morphological defenses against parasitoid. Annu. Rev. Entomol. 38, 251–273 (1993).Article 

Google Scholar 
3.Tylikinais, J. M., Tscharntke, T. & Klein, A. M. Diversity, ecosystem function and stability of parasitoid—host interactions across a tropical habitat gradient. Ecology 87, 3047–3057 (2006).Article 

Google Scholar 
4.Strand, M. R. & Obrycki, J. J. Host specificity of insect parasitoids and predators. Bioscience 46, 422–429 (1996).Article 

Google Scholar 
5.Dawkins, R. & Krebs, J. R. Arms races between and within species. Proc. R. Soc. Lond. B. 205, 489–511 (1979).ADS 
CAS 
PubMed 
Article 

Google Scholar 
6.Kraaijeveld, A. R., van Alphen, J. J. M. & Godfray, H. C. J. The coevolution of host resistance and parasitoid virulence. Parasitology 116, 29–45 (1998).Article 

Google Scholar 
7.Jeffries, M. J. & Lawton, J. H. Enemy free space and the structure of ecological communities. Biol. J. Linn. Soc. 23, 269–286 (1984).Article 

Google Scholar 
8.Grosman, A. H. et al. No adaptation of a herbivore to a novel host but loss of adaptation to its native host. Sci. Rep.-UK 5, 16211 (2015).ADS 
CAS 
Article 

Google Scholar 
9.Diamond, S. E. & Kingsolver, J. G. Fitness consequences of host plant choice: A field experiment. Oikos 119, 542–550 (2010).Article 

Google Scholar 
10.Meijer, K., Schilthuizen, M., Beukeboom, L. & Smit, C. A review and meta-analysis of the enemy release hypothesis in plant–herbivorous insect systems. PeerJ 4, e2778 (2016).PubMed 
PubMed Central 
Article 

Google Scholar 
11.Forbes, A. A., Powell, T. H., Stelinski, L. L., Smith, J. J. & Feder, J. L. Sequential sympatric speciation across trophic levels. Science 323, 776–779 (2009).ADS 
CAS 
PubMed 
Article 

Google Scholar 
12.Grosman, A. H., Holtz, A. M., Pallini, A., Sabelis, M. W. & Janssen, A. Parasitoids follow herbivorous insects to a novel host plant, generalist predators less so. Entomol. Exp. Appl. 162, 261–271 (2017).Article 

Google Scholar 
13.Soler, R., Bezemer, T. M., Van Der Putten, W. H., Vet, L. E. & Harvey, J. A. Root herbivore effects on above-ground herbivore, parasitoid and hyperparasitoid performance via changes in plant quality. J. Anim. Ecol. 74, 1121–1130 (2005).Article 

Google Scholar 
14.Ode, P. J. Plant chemistry and natural enemy fitness: Effects on herbivore and natural enemy interactions. Annu. Rev. Entomol. 51, 163–185 (2006).CAS 
PubMed 
Article 

Google Scholar 
15.Thompson, J. N. Trade-offs in larval performance on normal and novel hosts. Entomol. Exp. Appl. 80, 133–139 (1996).Article 

Google Scholar 
16.Lucas, É., Coderre, D. & Brodeur, J. Intraguild predation among aphid predators: Characterization and influence of extraguild prey density. Ecology 79, 1084–1092 (1998).Article 

Google Scholar 
17.Henry, L. M., May, N., Acheampong, S., Gillespie, D. R. & Roitberg, B. D. Host-adapted parasitoids in biological control: Does source matter?. Ecol. Appl. 20, 242–250 (2010).PubMed 
Article 

Google Scholar 
18.Mackauer, M. Sexual size dimorphism in solitary parasitoid wasps: influence of host quality. Oikos 76, 265–272 (1996).Article 

Google Scholar 
19.Bezemer, T. M. & Mills, N. J. Clutch size decisions of a gregarious parasitoid under laboratory and feld conditions. Anim. Behav. 66, 1119–1128 (2003).Article 

Google Scholar 
20.Samková, A., Hadrava, J., Skuhrovec, J. & Janšta, P. Host population density and presence of predators as key factors influencing the number of gregarious parasitoid Anaphes flavipes offspring. Sci. Rep.-UK 9, 6081 (2019).ADS 
Article 
CAS 

Google Scholar 
21.Schmidt, J. M. & Smith, J. J. B. Correlations between body angles and substrate curvature in the parasitoid wasp Trichogramma minutum: a possible mechanism of host radius measurement. J. Exp. Biol. 125, 271–285 (1986).Article 

Google Scholar 
22.Boivin, G. & Baaren, J. The role of larval aggression and mobility in the transition between solitary and gregarious development in parasitoid wasps. Ecol. Lett. 3, 469–474 (2000).Article 

Google Scholar 
23.Mayhew, P. J. The evolution of gregariousness in parasitoid wasps. P. Roy. Soc. Lond. B. Bio. 265, 383–389 (1998).Article 

Google Scholar 
24.Pexton, J. J. & Mayhew, P. J. Competitive interactions between parasitoid larvae and the evolution of gregarious development. Oecologia 141, 179–190 (2004).ADS 
PubMed 
Article 

Google Scholar 
25.Harvey, P. H. & Partridge, L. Murderous mandibles and black holes in hymenopteran wasps. Nature 326, 128–129 (1987).ADS 
Article 

Google Scholar 
26.Godfray, H. C. J. The evolution of clutch size in parasitic wasps. Am. Nat. 129, 221–233 (1987).Article 

Google Scholar 
27.Rosenheim, J. A. Single-sex broods and the evolution of nonsiblicidal parasitoid wasps. Am. Nat. 141, 90–104 (1993).Article 

Google Scholar 
28.Mayhew, P. J. & van Alphen, J. J. Gregarious development in alysiine parasitoids evolved through a reduction in larval aggression. Anim. Behav. 58, 131–141 (1999).CAS 
PubMed 
Article 

Google Scholar 
29.Pexton, J. J. & Mayhew, P. J. Immobility: The key to family harmony?. Trends. Ecol. Evol. 16, 7–9 (2001).CAS 
PubMed 
Article 

Google Scholar 
30.Hamilton, W. D. Extraordinary sex ratios. Science 156, 477–488 (1967).ADS 
CAS 
PubMed 
Article 

Google Scholar 
31.Mayhew, P. J. & Hardy, I. C. Nonsiblicidal behavior and the evolution of clutch size in bethylid wasps. Am. Nat. 151, 409–424 (1998).ADS 
CAS 
PubMed 
Article 

Google Scholar 
32.Zaviezo, T. & Mills, N. Factors influencing the evolution of clutch size in a gregarious insect parasitoid. J. Anim. Ecol. 69, 1047–1057 (2000).Article 

Google Scholar 
33.Koppik, M., Tiel, A. & Hofmeister, T. S. Adaptive decision making or diferential mortality: What causes ofspring emergence in a gregarious parasitoid?. Entomol. Exp. Appl. 150, 208–216 (2014).Article 

Google Scholar 
34.Visser, M. E., Van Alphen, J. J. & Hemerik, L. Adaptive superparasitism and patch time allocation in solitary parasitoids: An ESS model. J. Anim. Ecol. 61, 93–101 (1992).Article 

Google Scholar 
35.Waage, J. K. & Ming, N. S. The reproductive strategy of a parasitic wasp: I. optimal progeny and sex allocation in Trichogramma evanescens. J. An. Ecol. 53, 401–415 (1984).Article 

Google Scholar 
36.Harvey, J. A., Poelman, E. H. & Tanaka, T. Intrinsic inter-and intraspecific competition in parasitoid wasps. Ann. Rev. Entomol. 58, 333–351 (2013).CAS 
Article 

Google Scholar 
37.Harvey, J. A., Bezemer, T. M., Gols, R., Nakamatsu, Y. & Tanaka, T. Comparing the physiological effects and function of larval feeding in closely-related endoparasitoids (Braconidae: Microgastrinae). Physiol. Entomol. 33, 217–225 (2008).Article 

Google Scholar 
38.Cloutier, C., Duperron, J., Tertuliano, M. & McNeil, J. N. Host instar, body size and fitness in the koinobiotic parasitoid Aphidius nigripes. Entomol. Exp. Appl. 97, 29–40 (2000).Article 

Google Scholar 
39.Bai, B., Luck, R. F., Forster, L., Stephens, B. & Janssen, J. M. The effect of host size on quality attributes of the egg parasitoid Trichogramma pretiosum. Entomol. Exp. Appl. 64, 37–48 (1992).Article 

Google Scholar 
40.Kazmer, D. J. & Luck, R. F. Field tests of the size-fitness hypothesis in the egg parasitoid Trichogramma Pretiosum. Ecology 76, 412–425 (1995).Article 

Google Scholar 
41.Samková, A., Hadrava, J., Skuhrovec, J. & Janšta, P. Reproductive strategy as a major factor determining female body size and fertility of a gregarious parasitoid. J. Appl. Entomol. 143, 441–450 (2019).Article 

Google Scholar 
42.Wei, K., Tang, Y. L., Wang, X. Y., Cao, L. M. & Yang, Z. Q. The developmental strategies and related profitability of an idiobiont ectoparasitoid Sclerodermus pupariae vary with host size. Ecol. Entomol. 39, 101–108 (2014).Article 

Google Scholar 
43.May, R. M., Hassell, M. P., Anderson, M. R. & Tonkyn, D. V. Density dependence in host-parasitoid models. J. Anim. Ecol. 50, 855–865 (1981).MathSciNet 
Article 

Google Scholar 
44.Hoddle, M. S., Van Driesche, R. G., Elkinton, J. S. & Sanderson, J. P. Discovery and utilization of Bemisia argentifolii patches by Eretmocerus eremicus and Encarsia formosa (Beltsville strain) in greenhouses. Entomol. Exp. Appl. 87, 15–28 (1998).Article 

Google Scholar 
45.Samková, A., Raska, J., Hadrava, J. & Skuhrovec, J. An intergenerational approach for prediction of parasitoid population dynamics. BioRxiv. https://doi.org/10.1101/2021.02.22.432341 (2021).Article 

Google Scholar 
46.Anderson, R. C. & Paschke, J. D. The biology and ecology of Anaphes flavipes (Hymenoptera: Mymaridae), an exotic egg parasite of the cereal leaf beetle. Ann. Entomol. Soc. Am. 61, 1–5 (1968).Article 

Google Scholar 
47.Klomp, H. & Teerink, B. J. The significance of oviposition rates in the egg parasite Trichogramma embryophagum Htg. Arch. Neerl. Zool. 17, 350–375 (1967).Article 

Google Scholar 
48.Waage, J. K. & Lane, J. A. The reproductive strategy of a parasitic wasp: II. Sex allocation and local mate competition in Trichogramma evanescens. J. Anim. Ecol. 53, 417–426 (1984).Article 

Google Scholar 
49.Dysart, R. J., Maltby, H. L. & Brunson, M. H. Larval parasites of Oulema melanopus in Europe and their colonization in the United States. Entomophaga 18, 133–167 (1973).Article 

Google Scholar 
50.Skuhrovec, J. et al. Insecticidal activity of two formulations of essential oils against the cereal leaf beetle. Acta Agr. Scand. 68, 489–495 (2018).CAS 

Google Scholar 
51.Jervis, M. A., Ellers, J. & Harvey, J. A. Resource acquisition, allocation, and utilization in parasitoid reproductive strategies. Annu. Rev. Entomol. 53, 361–385 (2008).CAS 
PubMed 
Article 

Google Scholar 
52.Vinson, S. B. & Iwantsch, G. F. Host suitability for insect parasitoids. Ann. Rev. Entomol. 25, 397–419 (1980).Article 

Google Scholar 
53.Mackauer, M., Sequeira, R. & Otto, M. Growth and development in parasitoid wasps adaptation to variable host resources. In Vertical Food Web Interactions 191–203 (Springer, 1997).Chapter 

Google Scholar 
54.Ode, P. J. Plant toxins and parasitoid trophic ecology. Curr. Opin. Insect sci. 32, 118–123 (2019).PubMed 
Article 

Google Scholar 
55.Cronin, J. T. & Abrahamson, W. G. Do parasitoids diversify in response to host-plant shifts by herbivorous insects?. Ecol. Entomol. 26, 347–355 (2001).Article 

Google Scholar 
56.Sarfraz, M., Dosdall, L. M. & Keddie, B. A. Host plant nutritional quality affects the performance of the parasitoid Diadegma insulare. Biol. Control. 51, 34–41 (2009).CAS 
Article 

Google Scholar 
57.Harvey, J. A. Factors affecting the evolution of development strategies in parasitoid wasps: The importance of functional constraints and incorporating complexity. Entomol. Exp. Appl. 117, 1–13 (2005).Article 

Google Scholar 
58.Cortesero, A. M. & Monge, J. P. Influence of pre-emergence experience on response to host and host plant odours in the larval parasitoid Eupelmus vuilleti. Entomol. Exp. Appl. 72, 281–288 (1994).Article 

Google Scholar 
59.Gandolfi, M., Mattiacci, L. & Dorn, S. Preimaginal learning determines adult response to chemical stimuli in a parasitic wasp. Proc. Roy. Soc. Lon. Series. B-Biol. Scien. 270, 2623–2629 (2003).Article 

Google Scholar 
60.Kester, K. M. & Barbosa, P. Postemergence learning in the insect parasitoid, Cotesia congregata (Say) (Hymenoptera: Braconidae). J. Insect Behav. 4, 727–742 (1991).Article 

Google Scholar 
61.Vet, L. E. & Groenewold, A. W. Semiochemicals and learning in parasitoids. J. Chem. Ecol. 16, 3119–3135 (1990).CAS 
PubMed 
Article 

Google Scholar 
62.Samková, A., Hadrava, J., Skuhrovec, J. & Janšta, P. Effect of adult feeding and timing of host exposure on the fertility and longevity of the parasitoid Anaphes flavipes. Entomol. Exp. Appl. 167, 932–938 (2019).Article 

Google Scholar 
63.Jervis, M. A., Heimpel, G. E., Ferns, P. N., Harvey, J. A. & Kidd, N. A. Life-history strategies in parasitoid wasps: A comparative analysis of ‘ovigeny’. J. Anim. Ecol. 70, 442–458 (2001).Article 

Google Scholar 
64.Bjorksten, T. A. & Hoffmann, A. A. Persistence of experience effects in the parasitoid Trichogramma nr. brassicae. Ecol. Entomol. 23, 110–117 (1998).Article 

Google Scholar 
65.Lentz, A. J. & Kester, K. M. Postemergence experience affects sex ratio allocation in a gregarious insect parasitoid. J. Insect. Behav. 21, 34–45 (2008).Article 

Google Scholar 
66.Nishida, R. Sequestration of defensive substances from plants by Lepidoptera. Annu. Rev. Entomol. 47, 57–92 (2002).CAS 
PubMed 
Article 

Google Scholar 
67.Zvereva, E. L. & Rank, N. E. Fly parasitoid Megaselia opacicornis uses defensive secretions of the leaf beetle Chrysomela lapponica to locate its host. Oecologia 140, 516–522 (2004).ADS 
CAS 
PubMed 
Article 

Google Scholar 
68.Roy, H. E., Handley, L. J. L., Schönrogge, K., Poland, R. L. & Purse, B. V. Can the enemy release hypothesis explain the success of invasive alien predators and parasitoids?. Biocontrol 56, 451–468 (2011).Article 

Google Scholar 
69.Snyder, W. E. & Ives, A. R. Interactions between specialist and generalist natural enemies: Parasitoids, predators, and pea aphid biocontrol. Ecology 84, 91–107 (2003).Article 

Google Scholar 
70.Polis, G. A., Myers, C. A. & Holt, R. D. The ecology and evolution of intraguild predation: Potential competitors that eat each other. Annu. Rev. Ecol. Syst. 20, 297–330 (1989).Article 

Google Scholar 
71.Nakashima, Y. & Senoo, N. Avoidance of ladybird trails by an aphid parasitoid Aphidius ervi: active period and efects of prior oviposition experience. Entomol. Exp. Appl. 109, 163–166 (2003).Article 

Google Scholar 
72.Samková, A., Raška, J., Hadrava, J., Skuhrovec, J. & Janšta, P. Female manipulation of offspring sex ratio in the gregarious parasitoid Anaphes flavipes from a new two-generation approach. BioRxiv https://doi.org/10.1101/2021.02.22.432331 (2021).Article 

Google Scholar 
73.Visser, M. E. The importance of being large: the relationship between size and fitness in females of the parasitoid Aphaereta minuta (Hymenoptera: Braconidae). J. Anim. Ecol. 63, 963–978 (1994).Article 

Google Scholar 
74.Banks, M. & Thomson, D. J. Lifetime mating success in the damselfly Coenagrion puella. Anim. Behav. 33, 1175–1183 (1985).Article 

Google Scholar 
75.Ellers, J. & Jervis, M. Body size and the timing of egg production in parasitoid wasps. Oikos 102, 164–172 (2003).Article 

Google Scholar 
76.Anderson, R. C. & Paschke, J. D. Additional Observations on the Biology of Anaphes flavipes (Hymenoptera: Mymaridae), with Special Reference to the Efects of Temperature and Superparasitism on Development. Ann. Entomol. Soc. Am. 62, 1316–1321 (1969).Article 

Google Scholar 
77.Bezděk, J. & Baselga, A. Revision of western Palaearctic species of the Oulema melanopus group, with description of two new species from Europe (Coleoptera: Chrysomelidae: Criocerinae). Acta. Ent. Mus. Nat. Pra. 55, 273–304 (2015).
Google Scholar 
78.R. Core Team R. A language and environment for statistical computing. R Foundation for Statistical Computing (R Core Team, 2020).
Google Scholar 
79.Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting Linear Mixed-Effects Models Using lme4. J. Stat. Softw 67, 1–48. (2015) URL: https://CRAN.R-project.org/package=Hmisc.80.Harrell, F. E. Jr, Dupont, C., et mult. al. (2020) Hmisc: Harrell Miscellaneous. R package version 4.4–2. URL: https://CRAN.R-project.org/package=Hmisc.81.Signorell et mult. al. (2021). DescTools: Tools for descriptive statistics. R package version 0.99.40. URL: https://cran.r-project.org/package=DescTools. More

1.Zanne, A. E. et al. Three keys to the radiation of angiosperms into freezing environments. Nature 506, 89 (2014).ADS 
CAS 
PubMed 
Article 

Google Scholar 
2.Cornwell, W. K. et al. Functional distinctiveness of major plant lineages. J. Ecol. 102, 345–356 (2014).Article 

Google Scholar 
3.Díaz, S. et al. The global spectrum of plant form and function. Nature 529, 167 (2016).ADS 
PubMed 
Article 
CAS 

Google Scholar 
4.Kunstler, G. et al. Plant functional traits have globally consistent effects on competition. Nature 529, 204 (2016).ADS 
CAS 
PubMed 
Article 

Google Scholar 
5.Chapin, F. S. III, Autumn, K. & Pugnaire, F. Evolution of suites of traits in response to environmental stress. Am. Nat. 142, S78–S92 (1993).Article 

Google Scholar 
6.Adler, P. B. et al. Functional traits explain variation in plant life history strategies. Proc. Natl. Acad. Sci. USA 111, 740–745 (2014).ADS 
CAS 
PubMed 
Article 

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

Google Scholar 
8.Violle, C. et al. Let the concept of trait be functional! Oikos 116, 882–892 (2007).Article 

Google Scholar 
9.Westoby, M. A leaf-height-seed (LHS) plant ecol. Strategy scheme. Plant Soil 199, 213–227 (1998).CAS 
Article 

Google Scholar 
10.Funk, J. L. et al. Revisiting the holy grail: Using plant functional traits to understand ecological processes. Biol. Rev. 92, 1156–1173 (2017).PubMed 
Article 
PubMed Central 

Google Scholar 
11.Kattge, J. et al. TRY a global database of plant traits. Glob. Chang. Biol. 17, 2905–2935 (2011).ADS 
PubMed Central 
Article 

Google Scholar 
12.Kattge, J. et al. TRY plant trait database enhanced coverage and open access. Glob. Chang. Biol. 26, 119–188 (2020).ADS 
PubMed 
Article 
PubMed Central 

Google Scholar 
13.CHAH. Australian Plant Census, Centre of Australian National Biodiversity Research. https://id.biodiversity.org.au/tree/51354547 (2020).14.Kissling, W. D. et al. Towards global data products of Essential Biodiversity Variables on species traits. Nat. Ecol. Evol. 2, 1531–1540 (2018).PubMed 
Article 
PubMed Central 

Google Scholar 
15.Gallagher, R. V. et al. Open Science principles for accelerating trait-based science across the Tree of Life. Nat. Ecol. Evol. 4, 294–303 (2020).PubMed 
Article 
PubMed Central 

Google Scholar 
16.Chapman, A. D. et al. Numbers of living species in Australia and the world. (Australian Government, 2009).17.Hopper, S. D. & Gioia, P. The Southwest Australian Floristic Region: Evolution and conservation of a global hot spot of biodiversity. Annual Review of Ecology, Evolution, and Systematics 35, 623–650 (2004).Article 

Google Scholar 
18.Madin, J. et al. An ontology for describing and synthesizing ecological observation data. Ecol. Inform. 2, 279–296 (2007).Article 

Google Scholar 
19.Garnier, E. et al. Towards a thesaurus of plant characteristics: An ecological contribution. J. Ecol. 105, 298–309 (2017).Article 

Google Scholar 
20.Adams, M. A. M, P. & Attiwill. Role of Acacia spp. in nutrient balance and cycling in regenerating Eucalyptus regnans F. Muell. forests. I. Temporal changes in biomass and nutrient content. Aust. J. Bot. 32, 205–215 (1984).CAS 

Google Scholar 
21.Ahrens, C. W. et al. Plant functional traits differ in adaptability and are predicted to be differentially affected by climate change. Ecol. Evo. 10, 232–248 (2019).Article 

Google Scholar 
22.Australian National Botanic Gardens. The National Seed Bank. http://www.anbg.gov.au/gardens/living/seedbank/ (2018).23.Angevin, T. Species richness and functional trait diversity response to land use in a temperate eucalypt woodland community. (La Trobe University, 2011).24.Apgaua, D. M. G. et al. Functional traits and water transport strategies in lowland tropical rainforest trees. PLoS One 10, e0130799 (2015).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
25.Apgaua, D. M. G. et al. Plant functional groups within a tropical forest exhibit different wood functional anatomy. Funct. Ecol. 31, 582–591 (2017).Article 

Google Scholar 
26.Ashton, D. H. Studies of litter in Eucalyptus regnans forests. Aust. J. Bot. 23, 413–433 (1975).CAS 
Article 

Google Scholar 
27.Ashton, D. H. Phosphorus in forest ecosystems at Beenak, Victoria. The J. Ecol. 64, 171–186 (1976).CAS 

Google Scholar 
28.Attiwill, P. M. Nutrient cycling in a Eucalyptus obliqua (L’Herit.) forest IV: Nutrient uptake and nutrient return. Aust. J. Bot. 28, 199–222 (1980).CAS 
Article 

Google Scholar 
29.Barlow, B. A., Clifford, H. T., George, A. S. & McCusker, A. K. A. Flora of Australia. http://www.environment.gov.au/biodiversity/abrs/online-resources/flora/main/ (1981).30.Bean, A. R. A revision of Baeckea (Myrtaceae) in eastern Australia, Malesia and south-east Asia. Telopea 7, 245–268 (1997).Article 

Google Scholar 
31.Bell, L.C. Nutrient requirements for the establishment of native flora at Weipa. (Comalco Aluminium Ltd., 1985).32.Bennett, L. T. & Attiwill, P. M. The nutritional status of healthy and declining stands of Banksia integrifolia on the Yanakie Isthmus, Victoria. Aust. J. Bot. 45, 15–30 (1997).Article 

Google Scholar 
33.Bevege, D. I. Biomass and nutrient distribution in indigenous forest ecosystems. vol. 6 20 (Queensland Department of Forestry, 1978).34.Birk, E. M. & Turner, J. Response of flooded gum (E. grandis) to intensive cultural treatments: biomass and nutrient content of eucalypt plantations and native forests. For. Ecol. Manage. 47, 1–28 (1992).Article 

Google Scholar 
35.Blackman, C. J., Brodribb, T. J. & Jordan, G. J. Leaf hydraulic vulnerability is related to conduit dimensions and drought resistance across a diverse range of woody angiosperms. New Phytol. 188, 1113–1123 (2010).PubMed 
Article 

Google Scholar 
36.Blackman, C. J. et al. Leaf hydraulic vulnerability to drought is linked to site water availability across a broad range of species and climates. Ann. Bot. 114, 435–440 (2014).PubMed 
PubMed Central 
Article 

Google Scholar 
37.Blackman, C. J. et al. The links between leaf hydraulic vulnerability to drought and key aspects of leaf venation and xylem anatomy among 26 Australian woody angiosperms from contrasting climates. Ann. Bot. 122, 59–67 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
38.Bloomfield, K. J. et al. A continental-scale assessment of variability in leaf traits: Within species, across sites and between seasons. Funct. Ecol. 32, 1492–1506 (2018).Article 

Google Scholar 
39.Bolza, E. Properties and uses of 175 timber species from Papua New Guinea and West Irian. (Victoria (Australia) CSIRO, Div. of Building Research, 1975).40.Bragg, J. G. & Westoby, M. Leaf size and foraging for light in a sclerophyll woodland. Funct. Ecol. 16, 633–639 (2002).Article 

Google Scholar 
41.Brisbane Rainforest Action and Information Network. Trait measurements for Australian rainforest species. http://www.brisrain.org.au/ (2016).42.Briggs, A. L. & Morgan, J. W. Seed characteristics and soil surface patch type interact to affect germination of semi-arid woodland species. Plant Ecol. 212, 91–103 (2010).Article 

Google Scholar 
43.Brock, J. & Dunlop, A. Native plants of northern Australia. (Reed New Holland, 1993).44.Brodribb, T. J. & Cochard, H. Hydraulic failure defines the recovery and point of death in water-stressed conifers. Plant Physiol. 149, 575–584 (2009).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
45.Buckton, G. et al. Functional traits of lianas in an Australian lowland rainforest align with post-disturbance rather than dry season advantage. Austral Ecol. 44, 983–994 (2019).Article 

Google Scholar 
46.Burgess, S. S. O. & Dawson, T. E. Predicting the limits to tree height using statistical regressions of leaf traits. New Phytol. 174, 626–636 (2007).CAS 
PubMed 
Article 

Google Scholar 
47.Burrows, G. E. Comparative anatomy of the photosynthetic organs of 39 xeromorphic species from subhumid New South Wales, Australia. Int. J. Plant Sci. 162, 411–430 (2001).Article 

Google Scholar 
48.Butler, D. W., Gleason, S. M., Davidson, I., Onoda, Y. & Westoby, M. Safety and streamlining of woody shoots in wind: an empirical study across 39 species in tropical Australia. New Phytol. 193, 137–149 (2011).PubMed 
Article 

Google Scholar 
49.CAB International. Forestry Compendium. http://www.cabi.org/fc/ (2009).50.Caldwell, E., Read, J. & Sanson, G. D. Which leaf mechanical traits correlate with insect herbivory among feeding guilds? Ann. Bot. 117, 349–361 (2015).PubMed 
PubMed Central 

Google Scholar 
51.Canham, C. A., Froend, R. H. & Stock, W. D. Water stress vulnerability of four Banksia species in contrasting ecohydrological habitats on the Gnangara Mound. Western Australia. Plant Cell Envrion. 32, 64–72 (2009).Article 

Google Scholar 
52.Carpenter, R. J. Cuticular morphology and aspects of the ecology and fossil history of North Queensland rainforest Proteaceae. Bot. J. Linn. Soc. 116, 249–303 (1994).Article 

Google Scholar 
53.Carpenter, R. J., Hill, R. S. & Jordan, G. J. Leaf Cuticular Morphology Links Platanaceae and Proteaceae. Int. J. Plant Sci. 166, 843–855 (2005).Article 

Google Scholar 
54.Catford, J. A., Downes, B. J., Gippel, C. J. & Vesk, P. A. Flow regulation reduces native plant cover and facilitates exotic invasion in riparian wetlands. J. Appl. Ecol. 48, 432–442 (2011).Article 

Google Scholar 
55.Catford, J. A., Morris, W. K., Vesk, P. A., Gippel, C. J. & Downes, B. J. Species and environmental characteristics point to flow regulation and drought as drivers of riparian plant invasion. Divers. Distrib. 20, 1084–1096 (2014).Article 

Google Scholar 
56.Cernusak, L. A., Hutley, L. B., Beringer, J. & Tapper, N. J. Stem and leaf gas exchange and their responses to fire in a north Australian tropical savanna. Plant Cell Envrion. 29, 632–646 (2006).Article 

Google Scholar 
57.Cernusak, L. A., Hutley, L. B., Beringer, J., Holtum, J. A. M. & Turner, B. L. Photosynthetic physiology of eucalypts along a sub-continental rainfall gradient in northern Australia. Agric. For. Meteorol. 151, 1462–1470 (2011).ADS 
Article 

Google Scholar 
58.Chandler, G. T., Crisp, M. D., Cayzer, L. W. & Bayer, R. J. Monograph of Gastrolobium (Fabaceae: Mirbelieae). Aust. Syst. Bot. 15, 619–739 (2002).Article 

Google Scholar 
59.Chave, J. et al. Towards a worldwide wood economics spectrum. Ecol. Lett. 12, 351–366 (2009).PubMed 
Article 

Google Scholar 
60.Cheal, D. Growth stages and tolerable fire intervals for Victoria’s native vegetation data sets. (Victorian Government Department of Sustainability; Environment Melbourne, 2010).61.Cheesman, A. W., Duff, H., Hill, K., Cernusak, L. A. & McInerney, F. A. Isotopic and morphologic proxies for reconstructing light environment and leaf function of fossil leaves: A modern calibration in the Daintree Rainforest, Australia. Am. J. Bot. 107, 1165–1176 (2020).CAS 
PubMed 
Article 

Google Scholar 
62.Chen et al. Plants show more flesh in the tropics: Variation in fruit type along latitudinal and climatic gradients. Ecography 40, 531–538 (2017).Article 

Google Scholar 
63.Chinnock, R. J. Eremophila and allied genera: A monograph of the plant family Myoporaceae. (Rosenberg, 2007).64.Choat, B., Ball, M. C., Luly, J. G. & Holtum, J. A. M. Hydraulic architecture of deciduous and evergreen dry rainforest tree species from north-eastern Australia. Trees 19, 305–311 (2005).Article 

Google Scholar 
65.Choat, B., Ball, M. C., Luly, J. G., Donnelly, C. F. & Holtum, J. A. M. Seasonal patterns of leaf gas exchange and water relations in dry rain forest trees of contrasting leaf phenology. Tree Physiol. 26, 657–664 (2006).PubMed 
Article 

Google Scholar 
66.Choat, B. et al. Global convergence in the vulnerability of forests to drought. Nature 491, 752–755 (2012).ADS 
CAS 
PubMed 
Article 

Google Scholar 
67.Chudnoff, M. Tropical timbers of the world. 472 (US Department of Agriculture, Forest Service, 1984).68.The French agricultural research and international cooperation organization (CIRAD). Wood density data. http://www.cirad.fr/ (2009).69.Clarke, P. J. et al. A synthesis of postfire recovery traits of woody plants in Australian ecosystems. Sci. Total Environ. 534, 31–42 (2015).ADS 
CAS 
PubMed 
Article 

Google Scholar 
70.Cooper, W. & Cooper, W. T. Fruits of the Australian tropical rainforest. (Nokomis Editions, 2004).71.Cooper, W. & Cooper, W. T. Australian rainforest fruits. 272 (CSIRO Publishing, 2013).72.Cornwell, W. K. Causes and consequences of functional trait diversity: plant community assembly and leaf decomposition. (Stanford University, California, 2006).73.Centre for Plant Biodiversity Research. EUCLID 2.0: Eucalypts of Australia. http://apps.lucidcentral.org/euclid/text/intro/index.html (2002).74.Craven, L. A., A taxonomic revision of Calytrix Labill. (Myrtaceae). Brunonia 10, 1–138 (1987).Article 

Google Scholar 
75.Craven, L. A., Lepschi, B. J. & Cowley, K. J. Melaleuca (Myrtaceae) of Western Australia: Five new species, three new combinations, one new name and a new state record. Nuytsia 20, 27–36 (2010).
Google Scholar 
76.Crisp, M. D., Cayzer, L., Chandler, G. T. & Cook, L. G. A monograph of Daviesia (Mirbelieae, Faboideae, Fabaceae). Phytotaxa 300, 1–308 (2017).Article 

Google Scholar 
77.Cromer, R. N., Raupach, M., Clarke, A. R. P. & Cameron, J. N. Eucalypt plantations in Australia – the potential for intensive production and utilization. Appita J. 29, 165–173 (1975).
Google Scholar 
78.Cross, E. The characteristics of natives and invaders: A trait-based investigation into the theory of limiting similarity. (La Trobe University, 2009).79.Crous, K. Y. et al. Photosynthesis of temperate Eucalyptus globulus trees outside their native range has limited adjustment to elevated CO2 and climate warming. Glob. Chang. Biol. 19, 3790–3807 (2013).ADS 
PubMed 
Article 

Google Scholar 
80.Crous, K. Y., Wujeska-Klause, A., Jiang, M., Medlyn, B. E. & Ellsworth, D. S. Nitrogen and phosphorus retranslocation of leaves and stemwood in a mature Eucalyptus forest exposed to 5 years of elevated CO2. Front. Plant. Sci. 10, art664 (2019).Article 

Google Scholar 
81.Cunningham, S. A., Summerhayes, B. & Westoby, M. Evolutionary divergences in leaf structure and chemistry, comparing rainfall and soil nutrient gradients. Ecol. Monogr. 69, 569–588 (1999).Article 

Google Scholar 
82.Curran, T. J., Clarke, P. J. & Warwick, N. W. M. Water relations of woody plants on contrasting soils during drought: does edaphic compensation account for dry rainforest distribution? Aust. J. Bot. 57, 629–639 (2009).Article 

Google Scholar 
83.Curtis, E. M., Leigh, A. & Rayburg, S. Relationships among leaf traits of Australian arid zone plants: alternative modes of thermal protection. Aust. J. Bot. 60, 471–483 (2012).Article 

Google Scholar 
84.Denton, M. D., Veneklaas, E. J., Freimoser, F. M. & Lambers, H. Banksia species (Proteaceae) from severely phosphorus-impoverished soils exhibit extreme efficiency in the use and re-mobilization of phosphorus. Plant Cell Envrion. 30, 1557–1565 (2007).CAS 
Article 

Google Scholar 
85.Desch, H. E. & Dinwoodie, J. M. Timber structure, properties, conversion and use. (Palgrave Macmillan, 1996).86.de Tombeur, F. et al. A shift from phenol to silica-based leaf defenses during long-term soil and ecosystem development. Ecol. Lett. 24, 984–995 (2021).PubMed 
Article 

Google Scholar 
87.Dong, N. et al. Leaf nitrogen from first principles: field evidence for adaptive variation with climate. Biogeosciences 14, 481–495 (2017).ADS 
CAS 
Article 

Google Scholar 
88.Dong, N. et al. Components of leaf-trait variation along environmental gradients. New Phytol. 228, 82–94 (2020).CAS 
PubMed 
Article 

Google Scholar 
89.Du, P., Arndt, S. K. & Farrell, C. Relationships between plant drought response, traits, and climate of origin for green roof plant selection. Ecol. Appl. 28, 1752–1761 (2018).PubMed 
Article 

Google Scholar 
90.Du, P., Arndt, S. K. & Farrell, C. Can the turgor loss point be used to assess drought response to select plants for green roofs in hot and dry climates? Plant Soil 441, 399–408 (2019).CAS 
Article 

Google Scholar 
91.Duan, H. et al. Drought responses of two gymnosperm species with contrasting stomatal regulation strategies under elevated [CO2] and temperature. Tree Physiol. 35, 756–770 (2015).CAS 
PubMed 
Article 

Google Scholar 
92.Duncan, R. P. et al. Plant traits and extinction in urban areas: a meta-analysis of 11 cities. Glob. Ecol. Biog. 20, 509–519 (2011).Article 

Google Scholar 
93.Dwyer, J. M. & Laughlin, D. C. Constraints on trait combinations explain climatic drivers of biodiversity: The importance of trait covariance in community assembly. Ecol. Lett. 20, 872–882 (2017).PubMed 
Article 

Google Scholar 
94.Dwyer, J. M. & Mason, R. Plant community responses to thinning in densely regenerating Acacia harpophylla forest. Restor. Ecol. 26, 97–105 (2018).Article 

Google Scholar 
95.Eamus, D. & Prichard, H. A cost-benefit analysis of leaves of four Australian savanna species. Tree Physiol. 18, 537–545 (1998).PubMed 
Article 

Google Scholar 
96.Eamus, D., Myers, B., Duff, G. & Williams, D. Seasonal changes in photosynthesis of eight savanna tree species. Tree Physiol. 19, 665–671 (1999).PubMed 
Article 

Google Scholar 
97.Myers, B., E., D. & Duff, G. A cost-benefit analysis of leaves of eight Australian savanna tree species of differing life-span. Photosynthetica 36, 575–586 (1999).Article 

Google Scholar 
98.Edwards, C., Read, J. & Sanson, G. D. Characterising sclerophylly: some mechanical properties of leaves from heath and forest. Oecologia 123, 158–167 (2000).ADS 
CAS 
PubMed 
Article 

Google Scholar 
99.Edwards, C., Sanson, G. D., Aranwela, N. & Read, J. Relationships between sclerophylly, leaf biomechanical properties and leaf anatomy in some Australian heath and forest species. Plant Biosyst. 134, 261–277 (2000).Article 

Google Scholar 
100.Schöenenberger, J. et al. Phylogenetic analysis of fossil flowers using an angiosperm-wide data set: proof-of-concept and challenges ahead. Am. J. Bot. 107, 1433–1448 (2020).Article 

Google Scholar 
101.Esperon-Rodriguez, M. et al. Functional adaptations and trait plasticity of urban trees along a climatic gradient. Urban For. Urban Green. 54, art126771 (2020).Article 

Google Scholar 
102.Everingham, S. E., Offord, C. A., Sabot, M. E. B. & Moles, A. T. Time travelling seeds reveal that plant regeneration and growth traits are responding to climate change. Ecology 102, e03272 (2020).
Google Scholar 
103.Falster, D. S. & Westoby, M. Leaf size and angle vary widely across species: what consequences for light interception? New Phytol. 158, 509–525 (2003).Article 

Google Scholar 
104.Falster, D. S. & Westoby, M. Alternative height strategies among 45 dicot rain forest species from tropical Queensland, Australia. J. Ecol. 93, 521–535 (2005).Article 

Google Scholar 
105.Falster, D. S. & Westoby, M. Tradeoffs between height growth rate, stem persistence and maximum height among plant species in a post-fire succession. Oikos 111, 57–66 (2005).Article 

Google Scholar 
106.Farrell, C., Mitchell, R. E., Szota, C., Rayner, J. P. & Williams, N. S. G. Green roofs for hot and dry climates: Interacting effects of plant water use, succulence and substrate. Ecol. Eng. 49, 270–276 (2012).Article 

Google Scholar 
107.Farrell, C., Szota, C., Williams, N. S. G. & Arndt, S. K. High water users can be drought tolerant: using physiological traits for green roof plant selection. Plant Soil 372, 177–193 (2013).CAS 
Article 

Google Scholar 
108.Farrell, C., Szota, C. & Arndt, S. K. Does the turgor loss point characterize drought response in dryland plants? Plant Cell Envrion. 40, 1500–1511 (2017).CAS 
Article 

Google Scholar 
109.Feller, M. C. Biomass and nutrient distribution in two eucalypt forest ecosystems. Austral Ecol. 5, 309–333 (1980).Article 

Google Scholar 
110.Firn, J. et al. Leaf nutrients, not specific leaf area, are consistent indicators of elevated nutrient inputs. Nature Ecol. Evo. 3, 400–406 (2019).Article 

Google Scholar 
111.Flynn, J. H. & Holder, C. D. A guide to useful woods of the world. (Forest Products Society, 2001).112.Fonseca, C. R., Overton, J. M. C., Collins, B. & Westoby, M. Shifts in trait-combinations along rainfall and phosphorus gradients. J. Ecol. 88, 964–977 (2000).Article 

Google Scholar 
113.McDonald, P. G., Fonseca, C. R., Overton, J. M. C. & Westoby, M. Leaf-size divergence along rainfall and soil-nutrient gradients: is the method of size reduction common among clades? Funct. Ecol. 17, 50–57 (2003).Article 

Google Scholar 
114.Forster, P. I. A taxonomic revision of Alyxia (Apocynaceae) in Australia. Aust. Syst. Bot. 5, 547–580 (1992).Article 

Google Scholar 
115.Forster, P. I. New names and combinations in Marsdenia (Asclepiadaceae: Marsdenieae) from Asia and Malesia (excluding Papusia). Aust. Syst. Bot. 8, 691–701 (1995).Article 

Google Scholar 
116.French, B. J., Prior, L. D., Williamson, G. J. & Bowman, D. M. J. S. Cause and effects of a megafire in sedge-heathland in the Tasmanian temperate wilderness. Aust. J. Bot. 64, 513–525 (2016).Article 

Google Scholar 
117.Froend, R. H. & Drake, P. L. Defining phreatophyte response to reduced water availability: preliminary investigations on the use of xylem cavitation vulnerability in Banksia woodland species. Aust. J. Bot. 54, 173–179 (2006).Article 

Google Scholar 
118.Funk, J. L., Standish, R. J., Stock, W. D. & Valladares, F. Plant functional traits of dominant native and invasive species in mediterranean-climate ecosystems. Ecology 97, 75–83 (2016).PubMed 
Article 
PubMed Central 

Google Scholar 
119.Gallagher, R. V. et al. Invasiveness in introduced Australian acacias: The role of species traits and genome size. Divers. Distrib. 17, 884–897 (2011).Article 

Google Scholar 
120.Gallagher, R. V. & Leishman, M. R. A global analysis of trait variation and evolution in climbing plants. J. Biogeogr. 39, 1757–1771 (2012).Article 

Google Scholar 
121.Gardiner, R., Shoo, L. P. & Dwyer John. M. Look to seedling heights, rather than functional traits, to explain survival during extreme heat stress in the early stages of subtropical rainforest restoration. J. Appl. Ecol. 56, 2687–2697 (2019).Article 

Google Scholar 
122.Geange, S. R. et al. Phenotypic plasticity and water availability: responses of alpine herb species along an elevation gradient. Clim. Change Responses 4, 1–12 (2017).Article 

Google Scholar 
123.Geange, S. R., Holloway-Phillips, M.-M., Briceno, V. F. & Nicotra, A. B. Aciphylla glacialis mortality, growth and frost resistance: a field warming experiment. Aust. J. Bot. 67, 599–609 (2020).Article 

Google Scholar 
124.Ghannoum, O. et al. Exposure to preindustrial, current and future atmospheric CO2 and temperature differentially affects growth and photosynthesis in Eucalyptus. Glob. Chang. Biol. 16, 303–319 (2010).ADS 
Article 

Google Scholar 
125.Gleason, S. M., Butler, D. W., Zieminska, K., Waryszak, P. & Westoby, M. Stem xylem conductivity is key to plant water balance across Australian angiosperm species. Funct. Ecol. 26, 343–352 (2012).Article 

Google Scholar 
126.Gleason, S. M., Butler, D. W. & Waryszak, P. Shifts in leaf and stem hydraulic traits across aridity gradients in eastern Australia. Int. J. Plant Sci. 174, 1292–1301 (2013).Article 

Google Scholar 
127.Gleason, S. M., Blackman, C. J., Cook, A. M., Laws, C. A. & Westoby, M. Whole-plant capacitance, embolism resistance and slow transpiration rates all contribute to longer desiccation times in woody angiosperms from arid and wet habitats. Tree Physiol. 34, 275–284 (2014).PubMed 
Article 
PubMed Central 

Google Scholar 
128.Gleason, S. M. et al. Vessel scaling in evergreen angiosperm leaves conforms with Murray’s law and area-filling assumptions: implications for plant size, leaf size and cold tolerance. New Phytol. 218, 1360–1370 (2018).PubMed 
Article 
PubMed Central 

Google Scholar 
129.Goble-Garratt, E., Bell, D. & Loneragan, W. Floristic and leaf structure patterns along a shallow elevational gradient. Aust. J. Bot. 29, 329–347 (1981).Article 

Google Scholar 
130.Gosper, C. R. Fruit characteristics of invasive bitou bush, Chrysanthemoides monilifera (Asteraceae), and a comparison with co-occurring native plant species. Aust. J. Bot. 52, 223–230 (2004).Article 

Google Scholar 
131.Gosper, C. R., Yates, C. J. & Prober, S. M. Changes in plant species and functional composition with time since fire in two mediterranean climate plant communities. J. Veg. Sci. 23, 1071–1081 (2012).Article 

Google Scholar 
132.Gosper, C. R., Prober, S. M. & Yates, C. J. Estimating fire interval bounds using vital attributes: implications of uncertainty and among-population variability. Ecol. Appl. 23, 924–935 (2013).PubMed 
Article 
PubMed Central 

Google Scholar 
133.Gosper, C. R., Yates, C. J. & Prober, S. M. Floristic diversity in fire-sensitive eucalypt woodlands shows a “U”-shaped relationship with time since fire. J. Appl. Ecol. 50, 1187–1196 (2013).Article 

Google Scholar 
134.Gosper, C. R. et al. A conceptual model of vegetation dynamics for the unique obligate-seeder eucalypt woodlands of south-western Australia. Austral Ecol. 43, 681–695 (2018).Article 

Google Scholar 
135.Clayton, W. D., Vorontsova, M. S., Harman, K. T. & Williamson, H. GrassBase – The online world grass flora. http://www.kew.org/data/grasses-db.html (2006).136.Gray, E. F. et al. Leaf:wood allometry and functional traits together explain substantial growth rate variation in rainforest trees. AoB Plants 11, 1–11 (2019).Article 

Google Scholar 
137.Groom, P. K. & Lamont, B. B. Reproductive ecology of non-sprouting and re-sprouting Hakea species (Proteaceae) in southwestern Australia. In Gondwanan heritage (eds. S.D. Hopper M. Harvey, J. C. & George, A. S.) (Surrey Beatty, Chipping Norton, 1996).138.Groom, P. K. & Lamont, B. B. Fruit-seed relations in Hakea: serotinous species invest more dry matter in predispersal seed protection. Austral Ecol. 22, 352–355 (1997).Article 

Google Scholar 
139.Groom, P. K. & Lamont, B. B. Phosphorus accumulation in Proteaceae seeds: A synthesis. Plant Soil 334, 61–72 (2010).CAS 
Article 

Google Scholar 
140.Grootemaat, S., Wright, I. J., van Bodegom, P. M., Cornelissen, J. H. C. & Cornwell, W. K. Burn or rot: leaf traits explain why flammability and decomposability are decoupled across species. Funct. Ecol. 29, 1486–1497 (2015).Article 

Google Scholar 
141.Grootemaat, S., Wright, I. J., van Bodegom, P. M., Cornelissen, J. H. C. & Shaw, V. Bark traits, decomposition and flammability of Australian forest trees. Aust. J. Bot. 65, 327 (2017).Article 

Google Scholar 
142.Grootemaat, S., Wright, I. J., van Bodegom, P. M. & Cornelissen, J. H. C. Scaling up flammability from individual leaves to fuel beds. Oikos 126, 1428–1438 (2017).Article 

Google Scholar 
143.Gross, C. L. The reproductive ecology of Canavalia rosea (Fabaceae) on Anak Krakatau. Indonesia. Aust. J. Bot. 41, 591–599 (1993).Article 

Google Scholar 
144.Gross, C. L. A comparison of the sexual systems in the trees from the Australian tropics with other tropical biomes–more monoecy but why? Am. J. Bot. 92, 907–919 (2005).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
145.Grubb, P. J. & Metcalfe, D. J. Adaptation and inertia in the Australian tropical lowland rain-forest flora: Contradictory trends in intergeneric and intrageneric comparisons of seed size in relation to light demand. Funct. Ecol. 10, 512–520 (1996).Article 

Google Scholar 
146.Grubb, P. J. et al. Monocot leaves are eaten less than dicot leaves in tropical lowland rain forests: Correlations with toughness and leaf presentation. Ann. Bot. 101, 1379–1389 (2008).PubMed 
PubMed Central 
Article 

Google Scholar 
147.Guilherme Pereira, C., Clode, P. L., Oliveira, R. S. & Lambers, H. Eudicots from severely phosphorus-impoverished environments preferentially allocate phosphorus to their mesophyll. New Phytol. 218, 959–973 (2018).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
148.Guilherme Pereira, C. et al. Trait convergence in photosynthetic nutrient-use efficiency along a 2-million year dune chronosequence in a global biodiversity hotspot.  J. Ecol. 107, 2006–2023 (2019).CAS 
Article 

Google Scholar 
149.Hacke, U. G. et al. Water transport in vesselless Angiosperms: Conducting efficiency and cavitation safety. Int. J. Plant Sci. 168, 1113–1126 (2007).Article 

Google Scholar 
150.Hall, T. J. The nitrogen and phosphorus concentrations of some pasture species in the Dichanthium-Eulalia Grasslands of North-West Queensland. Rangeland J. 3, 67–73 (1981).Article 

Google Scholar 
151.Harrison, M. T., Edwards, E. J., Farquhar, G. D., Nicotra, A. B. & Evans, J. R. Nitrogen in cell walls of sclerophyllous leaves accounts for little of the variation in photosynthetic nitrogen-use efficiency. Plant Cell Envrion. 32, 259–270 (2009).CAS 
Article 

Google Scholar 
152.Hassiotou, F., Evans, J. R., Ludwig, M. & Veneklaas, E. J. Stomatal crypts may facilitate diffusion of CO2 to adaxial mesophyll cells in thick sclerophylls. Plant Cell Envrion. 32, 1596–1611 (2009).CAS 
Article 

Google Scholar 
153.Hatch, A. B. Influence of plant litter on the Jarrah forest soils of the Dwellingup region. West. Aust. For. Timber Bur. Leaflet 18 (1955).154.Hayes, P., Turner, B. L., Lambers, H. & Laliberte, E. Foliar nutrient concentrations and resorption efficiency in plants of contrasting nutrient-acquisition strategies along a 2-million-year dune chronosequence. J. Ecol. 102, 396–410 (2013).Article 
CAS 

Google Scholar 
155.Hayes, P. E., Clode, P. L., Oliveira, R. S. & Lambers, H. Proteaceae from phosphorus-impoverished habitats preferentially allocate phosphorus to photosynthetic cells: an adaptation improving phosphorus-use efficiency. Plant Cell Envrion. 41, 605–619 (2018).CAS 
Article 

Google Scholar 
156.Henery, M. L. & Westoby, M. Seed mass and seed nutrient content as predictors of seed output variation between species. Oikos 92, 479–490 (2001).Article 

Google Scholar 
157.Hocking, P. J. The nutrition of fruits of two proteaceous shrubs, Grevillea wilsonii and Hakea undulata, from south-western Australia. Aust. J. Bot. 30, 219–230 (1982).CAS 
Article 

Google Scholar 
158.Hocking, P. J. Mineral nutrient composition of leaves and fruits of selected species of Grevillea from southwestern Australia, with special reference to Grevillea leucopteris Meissn. Aust. J. Bot. 34, 155–164 (1986).CAS 
Article 

Google Scholar 
159.Hong, L. T. et al. Plant resources of south east Asia: Timber trees. World biodiversity Database CD rom series (Springer-Verlag Berlin; Heidelberg GmbH; Co. KG, 1999).160.Hopmans, P., Stewart, H. T. L. & Flinn, D. W. Impacts of harvesting on nutrients in a eucalypt ecosystem in southeastern Australia. For. Ecol. Manage. 59, 29–51 (1993).Article 

Google Scholar 
161.Huang, G., Rymer, P. D., Duan, H., Smith, R. A. & Tissue, D. T. Elevated temperature is more effective than elevated CO2 in exposing genotypic variation in Telopea speciosissima growth plasticity: implications for woody plant populations under climate change. Glob. Chang. Biol. 21, 3800–3813 (2015).ADS 
PubMed 
Article 
PubMed Central 

Google Scholar 
162.Hyland, B. P. M., Whiffin, T., Christophel, D., Gray, B. & Elick, R. W. Australian tropical rain forest plants trees, shrubs and vines. (CSIRO Publishing, 2003).163.World Agroforestry Centre (ICRAF). The wood density database. http://www.worldagroforestry.org/output/wood-density-database (2009).164.Ilic, J., Boland, D., McDonald, M., G., D. & Blakemore, P. Woody density phase 1 – State of knowledge. National Carbon Accounting System. Technical Report 18. (Australian Greenhouse Office, Canberra, Australia, 2000).165.Islam, M., Turner, D. W. & Adams, M. A. Phosphorus availability and the growth, mineral composition and nutritive value of ephemeral forbs and associated perennials from the Pilbara, Western Australia. Aust. J. Exp. Agric. 39, 149–159 (1999).Article 

Google Scholar 
166.Islam, M. & Adams, M. A. Mineral content and nutritive value of native grasses and the response to added phosphorus in a Pilbara rangeland. Trop. Grassl. 33, 193–200 (1999).
Google Scholar 
167.Jordan, G. J. An investigation of long-distance dispersal based on species native to both Tasmania and New Zealand. Aust. J. Bot. 49, 333–340 (2001).Article 

Google Scholar 
168.Jordan, G. J., Weston, P. H., Carpenter, R. J., Dillon, R. A. & Brodribb, T. J. The evolutionary relations of sunken, covered, and encrypted stomata to dry habitats in Proteaceae. Am. J. Bot. 95, 521–530 (2008).PubMed 
Article 
PubMed Central 

Google Scholar 
169.Jordan, G. J., Carpenter, R. J., Koutoulis, A., Price, A. & Brodribb, T. J. Environmental adaptation in stomatal size independent of the effects of genome size. New Phytol. 205, 608–617 (2015).PubMed 
Article 
PubMed Central 

Google Scholar 
170.Jordan, G. J. et al. Links between environment and stomatal size through evolutionary time in Proteaceae. Proc. R. Soc. Lond. B Biol. Sci. 287, 20192876 (2020).CAS 

Google Scholar 
171.Jurado, E. Diaspore weight, dispersal, growth form and perenniality of central Australian plants. J. Ecol. 79, 811–828 (1991).Article 

Google Scholar 
172.Jurado, E. & Westoby, M. Germination biology of selected central Australian plants. Austral Ecol. 17, 341–348 (1992).Article 

Google Scholar 
173.Kanowski, J. Ecological determinants of the distribution and abundance of the folivorous marsupials endemic to the rainforests of the Atherton uplands, north Queensland. (James Cook University, Townsville, 1999).174.Keighery, G. Taxonomy of the Calytrix ecalycata complex (Myrtaceae). Nuytsia 15, 261–268 (2004).
Google Scholar 
175.Royal Botanic Gardens Kew. Seed Information Database (SID) and Seed Bank Database. http://data.kew.org/sid/ (2019).176.Royal Botanic Gardens Kew. Seed protein data from Seed Information Database (SID) and Seed Bank Database. http://data.kew.org/sid/ (2019).177.Royal Botanic Gardens Kew. Oil content data from Seed Information Database (SID) and Seed Bank Database. http://data.kew.org/sid/ (2019).178.Royal Botanic Gardens Kew. Seed dispersal data from the Seed Information Database (SID) and Seed Bank Database. http://data.kew.org/sid/ (2019).179.Royal Botanic Gardens Kew. Germination data from the Seed Information Database (SID) and Seed Bank Database. http://data.kew.org/sid/ (2019).180.Knox, K. J. E. & Clarke, P. J. Fire severity and nutrient availability do not constrain resprouting in forest shrubs. Plant Ecol. 212, 1967–1978 (2011).Article 

Google Scholar 
181.Körner, C. & Cochrane, P. M. Stomatal responses and water relations of Eucalyptus pauciflora in summer along an elevational gradient. Oecologia 66, 443–455 (1985).ADS 
PubMed 
Article 

Google Scholar 
182.Kooyman, R., Rossetto, M., Cornwell, W. & Westoby, M. Phylogenetic tests of community assembly across regional to continental scales in tropical and subtropical rain forests. Glob. Ecol. Biog. 20, 707–716 (2011).Article 

Google Scholar 
183.Kotowska, M. M., Wright, I. J. & Westoby, M. Parenchyma abundance in wood of evergreen trees varies independently of nutrients. Front. Plant. Sci. 11, art86 (2020).Article 

Google Scholar 
184.Kuo, J., Hocking, P. & Pate, J. Nutrient reserves in seeds of selected Proteaceous species from South-western Australia. Aust. J. Bot. 30, 231–249 (1982).CAS 
Article 

Google Scholar 
185.Laliberté, E. et al. Experimental assessment of nutrient limitation along a 2-million-year dune chronosequence in the south-western Australia biodiversity hotspot. J. Ecol. 100, 631–642 (2012).Article 
CAS 

Google Scholar 
186.Lambert, M. J. Sulphur relationships of native and exotic tree species. (Macquarie University, Sydney, 1979).187.Lamont, B. B., Groom, P. K. & Cowling, R. M. High leaf mass per area of related species assemblages may reflect low rainfall and carbon isotope discrimination rather than low phosphorus and nitrogen concentrations. Funct. Ecol. 16, 403–412 (2002).Article 

Google Scholar 
188.Lamont, B. B., Groom, P. K., Williams, M. & He, T. LMA, density and thickness: recognizing different leaf shapes and correcting for their nonlaminarity. New Phytol. 207, 942–947 (2015).PubMed 
Article 

Google Scholar 
189.Landsberg, J. Dieback of rural eucalypts: response of foliar dietary quality and herbivory to defoliation. Austral Ecol. 15, 89–96 (1990).Article 

Google Scholar 
190.Landsberg, J. & Gillieson, D. S. Regional and local variation in insect herbivory, vegetation and soils of eucalypt associations in contrasted landscape positions along a climatic gradient. Aust. J. Ecol. 20, 299–315 (1995).Article 

Google Scholar 
191.Lawes, M. J., Adie, H., Russell-Smith, J., Murphy, B. & Midgley, J. J. How do small savanna trees avoid stem mortality by fire? The roles of stem diameter, height and bark thickness. Ecosphere 2, 1–13 (2011).Article 

Google Scholar 
192.Lawes, M. J., Richards, A., Dathe, J. & Midgley, J. J. Bark thickness determines fire resistance of selected tree species from fire-prone tropical savanna in north Australia. Plant Ecol. 212, 2057–2069 (2011).Article 

Google Scholar 
193.Lawes, M. J., Midgley, J. J. & Clarke, P. J. Costs and benefits of relative bark thickness in relation to fire damage: A savanna/forest contrast. J. Ecol. 101, 517–524 (2012).Article 

Google Scholar 
194.Lawson, J. R., Fryirs, K. A. & Leishman, M. R. Data from: Hydrological conditions explain wood density in riparian plants of south-eastern Australia. Dryad Digital Repository https://doi.org/10.5061/dryad.72h45 (2015).195.Laxton, E. Relationship between leaf traits, insect communities and resource availability. (Macquarie University, 2005).196.Lee, M. R. et al. Good neighbors aplenty: fungal endophytes rarely exhibit competitive exclusion patterns across a span of woody habitats. Ecology 100, e02790 (2019).PubMed 
Article 

Google Scholar 
197.Leigh, A. & Nicotra, A. B. Sexual dimorphism in reproductive allocation and water use efficiency in Maireana pyramidata (Chenopodiaceae), a dioecious, semi-arid shrub. Aust. J. Bot. 51, 509–514 (2003).Article 

Google Scholar 
198.Leigh, A., Cosgrove, M. J. & Nicotra, A. B. Reproductive allocation in a gender dimorphic shrub: anomalous female investment in Gynatrix pulchella? J. Ecol. 94, 1261–1271 (2006).Article 

Google Scholar 
199.Leishman, M. R. & Westoby, M. Classifying plants into groups on the basis of associations of individual traits–Evidence from Australian semi-arid woodlands. J. Ecol. 80, 417–424 (1992).Article 

Google Scholar 
200.Leishman, M. R., Westoby, M. & Jurado, E. Correlates of seed size variation: A comparison among five temperate floras. J. Ecol. 83, 517–529 (1995).Article 

Google Scholar 
201.Leishman, M. R., Haslehurst, T., Ares, A. & Baruch, Z. Leaf trait relationships of native and invasive plants: community- and global-scale comparisons. New Phytol. 176, 635–643 (2007).CAS 
PubMed 
Article 

Google Scholar 
202.Lemmens, R. H. M. J. & Soerjanegara, I. Prosea, Volume 5/1: Timber Trees – Major Commercial Timbers. (Pudoc/Prosea, 1993).203.Lenz, T. I., Wright, I. J. & Westoby, M. Interrelations among pressure-volume curve traits across species and water availability gradients. Physiol. Plant. 127, 423–433 (2006).CAS 
Article 

Google Scholar 
204.Leuning, R., Cromer, R. N. & Rance, S. Spatial distributions of foliar nitrogen and phosphorus in crowns of Eucalyptus grandis. Oecologia 88, 504–510 (1991).ADS 
CAS 
PubMed 
Article 

Google Scholar 
205.Lewis, J. D. et al. Rising temperature may negate the stimulatory effect of rising CO2 on growth and physiology of Wollemi pine (Wollemia nobilis). Funct. Plant. Bio. 42, 836–850 (2015).CAS 
Article 

Google Scholar 
206.Lim, F. K. S., Pollock, L. J. & Vesk, P. A. The role of plant functional traits in shrub distribution around alpine frost hollows. J. Veg. Sci. 28, 585–594 (2017).Article 

Google Scholar 
207.Lord, J. et al. Larger seeds in tropical floras: Consistent patterns independent of growth form and dispersal mode. J. Biogeogr. 24, 205–211 (1997).Article 

Google Scholar 
208.Lusk, C. H., Onoda, Y., Kooyman, R. & Gutiurrez-Giron, A. Reconciling species-level vs plastic responses of evergreen leaf structure to light gradients: shade leaves punch above their weight. New Phytol. 186, 429–438 (2010).PubMed 
Article 

Google Scholar 
209.Lusk, C. H., Kelly, J. W. G. & Gleason, S. M. Light requirements of Australian tropical vs. cool-temperate rainforest tree species show different relationships with seedling growth and functional traits. Ann. Bot. 111, 479–488 (2012).PubMed 
PubMed Central 
Article 

Google Scholar 
210.Lusk, C. H., Sendall, K. M. & Clarke, P. J. Seedling growth rates and light requirements of subtropical rainforest trees associated with basaltic and rhyolitic soils. Aust. J. Bot. 62, 48–55 (2014).Article 

Google Scholar 
211.Macinnis-Ng, C., McClenahan, K. & Eamus, D. Convergence in hydraulic architecture, water relations and primary productivity amongst habitats and across seasons in Sydney. Funct. Plant. Bio. 31, 429–439 (2004).Article 

Google Scholar 
212.Macinnis-Ng, C. M. O., Zeppel, M. J. B., Palmer, A. R. & Eamus, D. Seasonal variations in tree water use and physiology correlate with soil salinity and soil water content in remnant woodlands on saline soils. J. Arid Environ. 129, 102–110 (2016).ADS 
Article 

Google Scholar 
213.Marsh, N. R. & Adams, M. A. Decline of Eucalyptus tereticornis near Bairnsdale, Victoria: insect herbivory and nitrogen fractions in sap and foliage. Aust. J. Bot. 43, 39–49 (1995).Article 

Google Scholar 
214.Maslin, B. WATTLE, Interactive Identification of Australian Acacia. Version 2. (Australian Biological Resources Study, Canberra, 2014).215.McCarthy, J. K., Dwyer, J. M. & Mokany, K. A regional-scale assessment of using metabolic scaling theory to predict ecosystem properties. Proc. R. Soc. Lond. B Biol. Sci. 286, 20192221 (2019).
Google Scholar 
216.McClenahan, K., Macinnis-Ng, C. & Eamus, D. Hydraulic architecture and water relations of several species at diverse sites around Sydney. Aust. J. Bot. 52, 509–518 (2004).Article 

Google Scholar 
217.McGlone, M. S., Richardson, S. J. & Jordan, G. J. Comparative biogeography of New Zealand trees: Species richness, height, leaf traits and range sizes. New Zealand J. Ecol. 34, 137–151 (2010).
Google Scholar 
218.McGlone, M. S., Richardson, S. J., Jordan, G. J. & Perry, G. L. W. Is there a “suboptimal” woody species height? A response to Scheffer et al. Trends in Ecol. Evo. 30, 4–5 (2015).Article 

Google Scholar 
219.McIntyre, S., Lavorel, S. & Tremont, R. M. Plant life-history attributes: Their relationship to disturbance response in herbaceous vegetation. The J. Ecol. 83, 31–44 (1995).Article 

Google Scholar 
220.Meers, T. Role of plant functional traits in determining the response of vegetation to land use change on the Delatite Peninsula, Victoria. (University of Melbourne, 2007).221.Meers, T. L., Bell, T. L., Enright, N. J. & Kasel, S. Role of plant functional traits in determining vegetation composition of abandoned grazing land in north-eastern Victoria, Australia. J. Veg. Sci. 19, 515–524 (2008).Article 

Google Scholar 
222.Meers, T. L., Bell, T. L., Enright, N. J. & Kasel, S. Do generalisations of global trade-offs in plant design apply to an Australian sclerophyllous flora? Aust. J. Bot. 58, 257–270 (2010).Article 

Google Scholar 
223.Meers, T. L., Kasel, S., Bell, T. L. & Enright, N. J. Conversion of native forest to exotic Pinus radiata plantation: response of understorey plant composition using a plant functional trait approach. For. Ecol. Manage. 259, 399–409 (2010).Article 

Google Scholar 
224.Meier, E. The wood database. http://www.wood-database.com/ (2007).225.Laliberté, E. et al. Land-use intensification reduces functional redundancy and response diversity in plant communities. Ecol. Lett. 13, 76–86 (2010).PubMed 
Article 
PubMed Central 

Google Scholar 
226.Milberg, P. & Lamont, B. B. Seed/cotyledon size and nutrient content play a major role in early performance of species on nutrient-poor soils. New Phytol. 137, 665–672 (1997).Article 

Google Scholar 
227.Milberg, P., Pérez-Fernández, M. A. & Lamont, B. B. Seedling growth response to added nutrients depends on seed size in three woody genera. J. Ecol. 86, 624–632 (1998).Article 

Google Scholar 
228.Mokany, K. & Ash, J. Are traits measured on pot grown plants representative of those in natural communities? J. Veg. Sci. 19, 119–126 (2008).Article 

Google Scholar 
229.Mokany, K., Thomson, J. J., Lynch, A. J. J., Jordan, G. J. & Ferrier, S. Linking changes in community composition and function under climate change. Ecol. Appl. 25, 2132–2141 (2015).PubMed 
Article 
PubMed Central 

Google Scholar 
230.Moles, A. T. & Westoby, M. Do small leaves expand faster than large leaves, and do shorter expansion times reduce herbivore damage? Oikos 90, 517–524 (2000).Article 

Google Scholar 
231.Moles, A. T., Warton, D. I. & Westoby, M. Seed size and survival in the soil in arid Australia. Austral Ecol. 28, 575–585 (2003).Article 

Google Scholar 
232.Moles, A. T. et al. Putting plant resistance traits on the map: A test of the idea that plants are better defended at lower latitudes. New Phytol. 191, 777–788 (2011).PubMed 
Article 
PubMed Central 

Google Scholar 
233.Mooney, H. A., Ferrar, P. J. & Slatyer, R. O. Photosynthetic capacity and carbon allocation patterns in diverse growth forms of Eucalyptus. Oecologia 36, 103–111 (1978).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
234.Moore, A. W., Russell, J. S. & Coaldrake, J. E. Dry matter and nutrient content of a subtropical semiarid forest of Acacia harpophylla F. Muell. (Brigalow). Aust. J. Bot. 15, 11–24 (1967).Article 

Google Scholar 
235.Moore, N. A., Camac, J. S. & Morgan, J. W. Effects of drought and fire on resprouting capacity of 52 temperate Australian perennial native grasses. New Phytol. 221, 1424–1433 (2018).PubMed 
Article 
PubMed Central 

Google Scholar 
236.Morgan, H. Root system architecture, water use and rainfall responses of perennial species. (Macquarie University, 2005).237.Muir, A. M., Vesk, P. A. & Hepworth, G. Reproductive trajectories over decadal time-spans after fire for eight obligate-seeder shrub species in south-eastern Australia. Aust. J. Bot. 62, 369–379 (2014).Article 

Google Scholar 
238.Munroe, S. E. M. et al. The photosynthetic pathways of plant species surveyed in Australia’s national terrestrial monitoring network. Scientific Data 8, 97 (2021).PubMed 
PubMed Central 
Article 

Google Scholar 
239.National Herbarium of NSW. Trait measurements for NSW rainforest species from PLantNET. http://plantnet.rbgsyd.nsw.gov.au/ (2016).240.Nicholson, A., Prior, L. D., Perry, G. L. W. & Bowman, D. M. J. S. High post-fire mortality of resprouting woody plants in Tasmanian Mediterranean-type vegetation. Int. J. Wildland Fire 26, 532–537 (2017).Article 

Google Scholar 
241.Nicolle, D. A classification and census of regenerative strategies in the eucalypts (Angophora, Corymbia and Eucalyptus – Myrtaceae), with special reference to the obligate seeders. Aust. J. Bot. 54, 391–407 (2006).Article 

Google Scholar 
242.Nicolle, D. Classification of the Eucalypts (Angophora, Corymbia and Eucalyptus) Version 3. (Currency Creek Arboretum Eucalypt Research, 2018).243.Niinemets, U., Wright, I. J. & Evans, J. R. Leaf mesophyll diffusion conductance in 35 Australian sclerophylls covering a broad range of foliage structural and physiological variation. J. Exp. Bot. 60, 2433–2449 (2009).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
244.Kenny, B., Orscheg, C., Tasker, E., Gill, M. A. & Bradstock, R. NSW Flora Fire Response Database, v2.1. (NSW Department of Planning Industry; Environment, 2014).245.Northern Territory Herbarium. Flora of the Darwin Region Online. http://www.lrm.nt.gov.au/plants-and-animals/herbarium/darwin_flora_online (2014).246.Onoda, Y., Richards, A. E. & Westoby, M. The relationship between stem biomechanics and wood density is modified by rainfall in 32 Australian woody plant species. New Phytol. 185, 493–501 (2009).PubMed 
Article 
PubMed Central 

Google Scholar 
247.O’Reilly-Nugent, A. et al. Measuring competitive impact: Joint‐species modelling of invaded plant communities. J. Ecol. 108, 449–459 (2018).Article 

Google Scholar 
248.Osborne, C. P. et al. A global database of C4 photosynthesis in grasses. New Phytol. 204, 441–446 (2014).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
249.Paczkowska G. & Chapman, A.R. The Western Australian flora: A descriptive catalogue. 652 (CALM, Kings Park; Botanic Gardens; Wildflower Society of Western Australia, 2000).250.Palma, E. et al. Functional trait changes in the floras of 11 cities across the globe in response to urbanization. Ecography 40, 875–886 (2017).Article 

Google Scholar 
251.Pate, J. S., Rasins, E., Rullo, J. & Kuo, J. Seed nutrient reserves of Proteaceae with special reference to protein bodies and their inclusions. Ann. Bot. 57, 747–770 (1986).CAS 
Article 

Google Scholar 
252.Pearcy, R. W. Photosynthetic gas exchange responses of Australian tropical forest trees in canopy, gap and understory micro-environments. Funct. Ecol. 1, 169–178 (1987).Article 

Google Scholar 
253.Peeters, P. J. Correlations between leaf structural traits and the densities of herbivorous insect guilds. Biol. J. Linn. Soc. 77, 43–65 (2002).Article 

Google Scholar 
254.Pekin, B. K., Wittkuhn, R. S., Boer, M. M., Macfarlane, C. & Grierson, P. F. Plant functional traits along environmental gradients in seasonally dry and fire-prone ecosystem. J. Veg. Sci. 22, 1009–1020 (2011).Article 

Google Scholar 
255.Pickering, C., Green, K., Barros, A. A. & Venn, S. A resurvey of late-lying snowpatches reveals changes in both species and functional composition across snowmelt zones. Alp. Bot. 124, 93–103 (2014).Article 

Google Scholar 
256.Pickup, M., Westoby, M. & Basden, A. Dry mass costs of deploying leaf area in relation to leaf size. Funct. Ecol. 19, 88–97 (2005).Article 

Google Scholar 
257.Pollock, L. J., Morris, W. K. & Vesk, P. A. The role of functional traits in species distributions revealed through a hierarchical model. Ecography 35, 716–725 (2011).Article 

Google Scholar 
258.Pollock, L. J. et al. Combining functional traits, the environment and multiple surveys to understand semi-arid tree distributions. J. Veg. Sci. 29, 967–977 (2018).Article 

Google Scholar 
259.Prior, L. D., Eamus, D. & Bowman, D. M. J. S. Leaf attributes in the seasonally dry tropics: A comparison of four habitats in northern Australia. Funct. Ecol. 17, 504–515 (2003).Article 

Google Scholar 
260.Prior, L. D., Bowman, D. M. J. S. & Eamus, D. Seasonal differences in leaf attributes in Australian tropical tree species: family and habitat comparisons. Funct. Ecol. 18, 707–718 (2004).Article 

Google Scholar 
261.Prior, L. D., Williamson, G. J. & Bowman, D. M. J. S. Impact of high-severity fire in a Tasmainian dry eucalypt forest. Aust. J. Bot. 64, 193–205 (2016).Article 

Google Scholar 
262.Oxford Forestry Institute. Prospect: The wood database. http://dps.plants.ox.ac.uk/ofi/prospect/index.htm (2009).263.Royal Botanic Gardens Kew. Seed Information Database (SID). http://data.kew.org/sid/ (2014).264.Royal Botanic Gardens Sydney. PLantNET. http://plantnet.rbgsyd.nsw.gov.au/search/simple.htm (2014).265.Royal Botanic Gardens Sydney. PLantNET: NSW flora online. http://plantnet.rbgsyd.nsw.gov.au/ (2014).266.Read, J. & Sanson, G. D. Characterizing sclerophylly: the mechanical properties of a diverse range of leaf types. New Phytol. 160, 81–99 (2003).PubMed 
Article 
PubMed Central 

Google Scholar 
267.Read, J., Sanson, G. D. & Lamont, B. B. Leaf mechanical properties in sclerophyll woodland and shrubland on contrasting soils. Plant Soil 276, 95–113 (2005).CAS 
Article 

Google Scholar 
268.Reid, J. B., Hill, R., Brown, M. & and M. Hovenden. Vegetation of Tasmania. 456 (1999).269.Reynolds, V. A., Anderegg, L. D. L., Loy, X., HilleRisLambers, J. & Mayfield, M. M. Unexpected drought resistance strategies in seedlings of four Brachychiton species. Tree Physiol. 38, 664–677 (2017).Article 
CAS 

Google Scholar 
270.Rice, K. J., Matzner, S. L., Byer, W. & Brown, J. R. Patterns of tree dieback in Queensland, Australia: The importance of drought stress and the role of resistance to cavitation. Oecologia 139, 190–198 (2004).ADS 
PubMed 
Article 
PubMed Central 

Google Scholar 
271.Richards, A. E. et al. Physiological profiles of restricted endemic plants and their widespread congenors in the North Queensland wet tropics, Australia. Biol. Conserv. 111, 41–52 (2003).Article 

Google Scholar 
272.Roderick, M. L., Berry, S. L. & Noble, I. R. The relationship between leaf composition and morphology at elevated CO2 concentrations. New Phytol. 143, 63–72 (1999).Article 

Google Scholar 
273.Roderick, M. L. & Cochrane, M. J. On the conservative nature of the leaf mass-area relationship. Ann. Bot. 89, 537–542 (2002).PubMed 
PubMed Central 
Article 

Google Scholar 
274.Rosell, J. A., Gleason, S., Mendez-Alonzo, R., Chang, Y. & Westoby, M. Bark functional ecology: Evidence for tradeoffs, functional coordination, and environment producing bark diversity. New Phytol. 201, 486–497 (2014).PubMed 
Article 
PubMed Central 

Google Scholar 
275.Rye, B. L. A revision of south-western Australian species of Micromyrtus (Myrtaceae) with five antisepalous ribs on the hypanthium. Nuytsia 15, 101–122 (2002).
Google Scholar 
276.Rye, B. L. A partial revision of the south-western Australian species of Micromyrtus (Myrtaceae: Chamelaucieae). Nuytsia 16, 117–147 (2006).
Google Scholar 
277.Rye, B. L. Reinstatement of the Western Australian genus Oxymyrrhine (Myrtaceae: Chamelaucieae) with three new species. Nuytsia 19, 149–165 (2009).
Google Scholar 
278.Rye, B. L. A revision of the Micromyrtus racemosa complex (Myrtaceae: Chamelaucieae) of south-western Australia. Nuytsia 20, 37–56 (2010).
Google Scholar 
279.Rye, B. L., Wilson, P. G. & Keighery, G. J. A revision of the species of Hypocalymma (Myrtaceae: Chamelaucieae) with smooth or colliculate seeds. Nuytsia 23, 283–312 (2013).
Google Scholar 
280.Rye, B. L. An update to the taxonomy of some western Australian genera of Myrtaceae tribe Chamelaucieae. 1. Calytrix. Nuytsia 23, 483–501 (2013).
Google Scholar 
281.Rye, B. L. A revision of the south-western Australian genus Babingtonia (Myrtaceae: Chamelaucieae). Nuytsia 25, 219–250 (2015).
Google Scholar 
282.Jessop, J. P. & Toelken, H. R. Flora of South Australia, 4th edition, 4 vols. (Government Printer, Adelaide, 1986).283.Sams, M. A. et al. Landscape context explains changes in the functional diversity of regenerating forests better than climate or species richness. Glob. Ecol. Biog. 26, 1165–1176 (2017).Article 

Google Scholar 
284.Sauquet, H. et al. The ancestral flower of angiosperms and its early diversification. Nat. Commun. 8, 1–10 (2017).Article 
CAS 

Google Scholar 
285.Schmidt, S. & Stewart, G. R. Waterlogging and fire impacts on nitrogen availability and utilization in a subtropical wet heathland (wallum). Plant Cell Envrion. 20, 1231–1241 (1997).Article 

Google Scholar 
286.Schmidt, S. & Stewart, G. R. d15N values of tropical savanna and monsoon forest species reflect root specialisations and soil nitrogen status. Oecologia 134, 569–577 (2003).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
287.Schmidt, S., Lamble, R. E., Fensham, R. J. & Siddique, I. Effect of woody vegetation clearing on nutrient and carbon relations of semi-arid dystrophic savanna. Plant Soil 331, 79–90 (2009).Article 
CAS 

Google Scholar 
288.Schulze, E., Kelliher, F. M., Körner, C., Lloyd, J. & Leuning, R. Relationships among maximum stomatal conductance, ecosystem surface conductance, carbon assimilation rate, and plant nitrogen nutrition: A global ecology scaling exercise. Annu. Rev. Ecol. Syst. 25, 629–662 (1994).Article 

Google Scholar 
289.Schulze, E.-D. et al. Carbon and nitrogen isotope discrimination and nitrogen nutrition of trees along a rainfall gradient in northern Australia. Aust. J. Plant. Physiol. 25, 413–425 (1998).
Google Scholar 
290.Schulze, E.-D., Turner, N. C., Nicolle, D. & Schumacher, J. Species differences in carbon isotope ratios, specific leaf area and nitrogen concentrations in leaves of Eucalyptus growing in a common garden compared with along an aridity gradient. Physiol. Plant. 127, 434–444 (2006).CAS 
Article 

Google Scholar 
291.Schulze, E.-D., Turner, N. C., Nicolle, D. & Schumacher, J. Leaf and wood carbon isotope ratios, specific leaf areas and wood growth of Eucalyptus species across a rainfall gradient in Australia. Tree Physiol. 26, 479–492 (2006).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
292.Turner, N. C., Schulze, E.-D., Nicolle, D., Schumacher, J. & Kuhlmann, I. Annual rainfall does not directly determine the carbon isotope ratio of leaves of Eucalyptus species. Physiol. Plant. 132, 440–445 (2008).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
293.Schulze, E. D. et al. Stable carbon and nitrogen isotope ratios of Eucalyptus and Acacia species along a seasonal rainfall gradient in Western Australia. Trees 28, 1125–1135 (2014).CAS 
Article 

Google Scholar 
294.Scott, A. J. Vegetation recovery and recruitment processes in south-eastern Australian semi-arid old fields. (La Trobe University, 2010).295.Sendall, K. M., Lusk, C. H. & Reich, P. B. Trade-offs in juvenile growth potential vs. shade tolerance among subtropical rain forest trees on soils of contrasting fertility. Funct. Ecol. 30, 845–855 (2015).Article 

Google Scholar 
296.Seng, O. D. Specific gravity of Indonesian Woods and its significance for practical use. (FPRDC Forestry Department, Bogor, Indonesia, 1951).297.Sjöström, A. & Gross, C. L. Life-history characters and phylogeny are correlated with extinction risk in the Australian angiosperms. J. Biogeogr. 33, 271–290 (2006).Article 

Google Scholar 
298.Smith, B. Community-level Convergence and Community Structure of temperate Nothofagus forests. (University of Otago, Dunedin, New Zealand, 1996).299.Smith, R. A., Lewis, J. D., Ghannoum, O. & Tissue, D. T. Leaf structural responses to pre-industrial, current and elevated atmospheric CO2 and temperature affect leaf function in Eucalyptus sideroxylon. Funct. Plant. Bio. 39, 285–296 (2012).CAS 
Article 

Google Scholar 
300.Soliveres, S., Eldridge, D. J., Hemmings, F. & Maestre, F. T. Nurse plant effects on plant species richness in drylands: The role of grazing, rainfall and species specificity. Perspect. Plant Ecol. Evol. Systs. 14, 402–410 (2012).Article 

Google Scholar 
301.Soper, F. M. et al. Natural abundance (delta15N) indicates shifts in nitrogen relations of woody taxa along a savanna-woodland continental rainfall gradient. Oecologia 178, 297–308 (2014).ADS 
PubMed 
Article 

Google Scholar 
302.Specht, R. L. et al. Mediterranean-type ecosystems: A data source book. 248 (Springer, 1988).303.Specht, R. L. & Rundel, P. W. Sclerophylly and foliar nutrient status of Mediterranean-climate plant communities in southern Australia. Aust. J. Bot. 38, 459–474 (1990).Article 

Google Scholar 
304.Sperry, J. S., Hacke, U. G., Feild, T. S., Sano, Y. & Sikkema, E. H. Hydraulic consequences of vessel evolution in Angiosperms. Int. J. Plant Sci. 168, 1127–1139 (2007).Article 

Google Scholar 
305.Staples, T., Dwyer, J. M., England, J. R. & Mayfield, M. M. Productivity does not correlate with species and functional diversity in Australian reforestation plantings across a wide climate gradient. Glob. Ecol. Biog. 28, 1417–1429 (2019).Article 

Google Scholar 
306.Stewart, G., Turnbull, M., Schmidt, S. & Erskine, P. 13C natural abundance in plant communities along a rainfall gradient: a biological integrator of water availability. Funct. Plant. Bio. 22, 51–55 (1995).Article 

Google Scholar 
307.Stock, W. D., Pate, J. S. & Rasins, E. Seed developmental patterns in Banksia attenuata R. Br. and B. laricina C. Gardner in relation to mechanical defence costs. New Phytol. 117, 109–114 (1991).CAS 
Article 

Google Scholar 
308.Tait, C. J., Daniels, C. B. & Hill, R. S. Changes in species assemblages within the Adelaide metropolitan area, Australia, 1836–2002. Ecol. Appl. 15, 346–359 (2005).Article 

Google Scholar 
309.Taseski, G., Keith, D. A., Dalrymple, R. L. & Cornwell, W. K. Shifts in fine root traits within and among species along a small-scale hydrological gradient. (University of New South Wales, 2017).310.Taylor, D. & Eamus, D. Coordinating leaf functional traits with branch hydraulic conductivity: Resource substitution and implications for carbon gain. Tree Physiol. 28, 1169–1177 (2008).PubMed 
Article 

Google Scholar 
311.Thomas, F. M. & Vesk, P. A. Growth races in The Mallee: Height growth in woody plants examined with a trait-based model. Austral Ecol. 42, 790–800 (2017).Article 

Google Scholar 
312.Thomas, F. M. & Vesk, P. A. Are trait-growth models transferable? Predicting multi-species growth trajectories between ecosystems using plant functional traits. PLoS One 12, e0176959 (2017).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
313.Thompson, I. R. Morphometric analysis and revision of eastern Australian Hovea (Brongniartieae-Fabaceae). Aust. Syst. Bot. 14, 1–99 (2001).Article 

Google Scholar 
314.Tasmanian Herbarium. Flora of Tasmania Online. http://www.tmag.tas.gov.au/floratasmania (2009).315.Tng, D. Y. P., Jordan, G. J. & Bowman, D. M. J. S. Plant traits demonstrate that temperate and tropical giant Eucalypt forests are ecologically convergent with rainforest not savanna. PLoS One 8, e84378 (2013).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
316.Toelken, H. R. A revision of the genus Kunzea (Myrtaceae) I. The western Australian section Zeanuk. J. Adel. Bot. Gard. 17, 29–106 (1996).
Google Scholar 
317.Tomlinson, K. W. et al. Biomass partitioning and root morphology of savanna trees across a water gradient. J. Ecol. 100, 1113–1121 (2012).Article 

Google Scholar 
318.Tomlinson, K. W. et al. Leaf adaptations of evergreen and deciduous trees of semi-arid and humid savannas on three continents. J. Ecol. 101, 430–440 (2013).Article 

Google Scholar 
319.Tomlinson, K. W. et al. Seedling growth of savanna tree species from three continents under grass competition and nutrient limitation in a greenhouse experiment. J. Ecol. 107, 1051–1066 (2019).Article 

Google Scholar 
320.Tremont, R. M. Life-history attributes of plants in grazed and ungrazed grasslands on the Northern Tablelands of New South Wales. Aust. J. Bot. 42, 511–530 (1994).Article 

Google Scholar 
321.Trudgen, M. E. & Rye, B. L. Astus, a new western Australian genus of Myrtaceae with heterocarpidic fruits. Nuytsia 14, 495–512 (2005).
Google Scholar 
322.Trudgen, M. E. & Rye, B. L. An update to the taxonomy of some western Australian genera of Myrtaceae tribe Chamelaucieae. 2. Cyathostemon. Nuytsia 24, 7–16 (2014).
Google Scholar 
323.Turner, J. & Lambert, M. J. Nutrient cycling within a 27-year-old Eucalyptus grandis plantation in New South Wales. For. Ecol. Manage. 6, 155–168 (1983).CAS 
Article 

Google Scholar 
324.Turner, N. C., Schulze, E.-D., Nicolle, D. & Kuhlmann, I. Growth in two common gardens reveals species by environment interaction in carbon isotope discrimination of Eucalyptus. Tree Physiol. 30, 741–747 (2010).CAS 
PubMed 
Article 

Google Scholar 
325.Veneklaas, E. J. & Poot, P. Seasonal patterns in water use and leaf turnover of different plant functional types in a species-rich woodland, south-western Australia. Plant Soil 257, 295–304 (2003).CAS 
Article 

Google Scholar 
326.Venn, S. E., Green, K., Pickering, C. M. & Morgan, J. W. Using plant functional traits to explain community composition across a strong environmental filter in Australian alpine snowpatches. Plant Ecol. 212, 1491–1499 (2011).Article 

Google Scholar 
327.Venn, S., Pickering, C. & Green, K. Spatial and temporal functional changes in alpine summit vegetation are driven by increases in shrubs and graminoids. AoB Plants 6, plu008 (2014).PubMed 
PubMed Central 
Article 

Google Scholar 
328.Vesk, P. A., Leishman, M. R. & Westoby, M. Simple traits do not predict grazing response in Australian dry shrublands and woodlands. J. Appl. Ecol. 41, 22–31 (2004).Article 

Google Scholar 
329.Vesk, P. A. & Yen, J. D. L. Plant resprouting: How many sprouts and how deep? Flexible modelling of multispecies experimental disturbances. Perspect. Plant Ecol. Evol. Systs. 41, 125497 (2019).Article 

Google Scholar 
330.Vlasveld, C., O’Leary, B., Udovicic, F. & Burd, M. Leaf heteroblasty in eucalypts: biogeographic evidence of ecological function. Aust. J. Bot. 66, 191–201 (2018).Article 

Google Scholar 
331.Western Australian Herbarium. FloraBase: The Western Australian flora. http://florabase.dpaw.wa.gov.au (1998).332.Western Australian Herbarium. FloraBase: The Western Australian flora. http://florabase.dpaw.wa.gov.au/ (2016).333.Warren, C. R., Tausz, M. & Adams, M. A. Does rainfall explain variation in leaf morphology and physiology among populations of red ironbark (Eucalyptus sideroxylon subsp. tricarpa) grown in a common garden? Tree Physiol. 25, 1369–1378 (2005).PubMed 
Article 
PubMed Central 

Google Scholar 
334.Warren, C. R., Dreyer, E., Tausz, M. & Adams, M. A. Ecotype adaptation and acclimation of leaf traits to rainfall in 29 species of 16-year-old Eucalyptus at two common gardens. Funct. Ecol. 20, 929–940 (2006).Article 

Google Scholar 
335.Weerasinghe, L. K. et al. Canopy position affects the relationships between leaf respiration and associated traits in a tropical rainforest in Far North Queensland. Tree Physiol. 34, 564–584 (2014).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
336.Wells, J. A. Phylogeny and inter-relations of ecological traits and seed dispersal in rainforest plants: Exploring aspects of functional diversity in primary and secondary rainforests in Australia’s Wet Tropics. (University of Queensland, 2012).337.Westman, W. E. & Roggers, R. V. Nutrient stocks in a subtropical eucalypt forest, North Stradbroke Island. Austral Ecol. 2, 447–460 (1977).Article 

Google Scholar 
338.Westoby, M. et al. Seed size and plant growth form as factors in dispersal spectra. Ecology 71, 1307–1315 (1990).Article 

Google Scholar 
339.Westoby, M. & Wright, I. J. The leaf size – twig size spectrum and its relationship to other important spectra of variation among species. Oecologia 135, 621–628 (2003).ADS 
PubMed 
Article 
PubMed Central 

Google Scholar 
340.Wheeler, J. R., Marchant, N. G. & Lewington, M. Flora of the south west: Bunbury, Augusta, Denmark. (Australian Biological Resources Study; University of Western Australia Press, 2002).341.White, M., Sinclair, S. & Frood, D. Victorian Vital Attributes Database. (Department of Environment, Land, Water; Planning, Victoria, 2020).342.Williams, N. S. G., Morgan, J. W., McDonnell, M. J. & McCarthy, M. A. Plant traits and local extinctions in natural grasslands along an urban-rural gradient. J. Ecol. 93, 1203–1213 (2005).Article 

Google Scholar 
343.Wills, J. et al. Tree leaf trade-offs are stronger for sub-canopy trees: leaf traits reveal little about growth rates in canopy trees. Ecol. Appl. 28, 1116–1125 (2018).PubMed 
Article 
PubMed Central 

Google Scholar 
344.Wilson, P. G. & Rowe, R. A revision of the Indigofereae (Fabaceae) in Australia. 2. Indigofera species with trifoliolate and alternately pinnate leaves. Telopea 12, 293–307 (2008).Article 

Google Scholar 
345.Wright, I. J. et al. A survey of seed and seedling characters in 1744 Australian dicotyledon species: Cross-species trait correlations and correlated trait-shifts within evolutionary lineages. Biol. J. Linn. Soc. 69, 521–547 (2000).Article 

Google Scholar 
346.Wright, I. J., Reich, P. B. & Westoby, M. Strategy shifts in leaf physiology, structure and nutrient content between species of high- and low-rainfall and high- and low-nutrient habitats. Funct. Ecol. 15, 423–434 (2001).Article 

Google Scholar 
347.Wright, I. J. & Westoby, M. Leaves at low versus high rainfall: Coordination of structure, lifespan and physiology. New Phytol. 155, 403–416 (2002).PubMed 
Article 
PubMed Central 

Google Scholar 
348.Wright, I. J., Westoby, M. & Reich, P. B. Convergence towards higher leaf mass per area in dry and nutrient-poor habitats has different consequences for leaf life span. J. Ecol. 90, 534–543 (2002).Article 

Google Scholar 
349.Wright, I. J., Falster, D. S., Pickup, M. & Westoby, M. Cross-species patterns in the coordination between leaf and stem traits, and their implications for plant hydraulics. Physiol. Plant. 127, 445–456 (2006).CAS 
Article 

Google Scholar 
350.Wright, I. J. et al. Stem diameter growth rates in a fire-prone savanna correlate with photosynthetic rate and branch-scale biomass allocation, but not specific leaf area. Austral Ecol. 44, 339–350 (2018).Article 

Google Scholar 
351.Yates, C. J. et al. Mallee woodlands and shrublands: the mallee, muruk/muert and maalok vegetation of Southern Australia. in Australian Vegetation (Cambridge University Press, 2017).352.Zanne, A. E. et al. Data from: Towards a worldwide wood economics spectrum. Dryad https://doi.org/10.5061/dryad.234 (2009).353.Zieminska, K., Butler, D. W., Gleason, S. M., Wright, I. J. & Westoby, M. Fibre wall and lumen fractions drive wood density variation across 24 Australian angiosperms. AoB Plants 5, plt046 (2013).PubMed Central 
Article 
CAS 

Google Scholar 
354.Zieminska, K., Westoby, M. & Wright, I. J. Broad anatomical variation within a narrow wood density range – A study of twig wood across 69 Australian Angiosperms. PLoS One 10, e0124892 (2015).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
355.R Core Team. R: A language and environment for statistical computing. (R Foundation for Statistical Computing, 2020).356.Wickham, H. et al. Welcome to the tidyverse. Journal of Open Source Software 4, 1686 (2019).ADS 
Article 

Google Scholar 
357.Stephens, J. Yaml: Methods to convert r data to YAML and back (r package version 2.1. 13). (2014).358.FitzJohn, R. Remake: Make-like build management. R package version 0.2.0. (2016).359.Xie, Y. Dynamic documents with R and Knitr. (2015).360.Allaire, J. et al. Rmarkdown: Dynamic documents for R. R package version 0.5.1. (2015).361.CHAH. Australian Plant Name Index (continuously updated), Centre of Australian National Biodiversity Research. (https://www.biodiversity.org.au/nsl/services/apni (14/05/2020), 2020).362.Chamberlain, S. A. & Szöcs, E. Taxize: Taxonomic search and retrieval in R. F1000Res. 2, 191 (2013).PubMed 
PubMed Central 
Article 

Google Scholar 
363.Falster, D. et al. AusTraits: a curated plant trait database for the Australian flora. Zenodo https://doi.org/10.5281/zenodo.3568417 (2021).364.Wilkinson, M. D. et al. The FAIR guiding principles for scientific data management and stewardship. Sci. Data 3 (2016).365.Falster, D. S., FitzJohn, R. G., Pennell, M. W. & Cornwell, W. K. Datastorr: A workflow and package for delivering successive versions of ‘evolving data’ directly into R. GigaScience 8, giz035 (2019).PubMed 
PubMed Central 
Article 

Google Scholar 
366.Smith, S. A. & Brown, J. W. Constructing a broadly inclusive seed plant phylogeny. Am. J. Bot. 105, 302–314 (2018).PubMed 
Article 
PubMed Central 

Google Scholar 
367.Jin, Y. V.PhyloMaker: Make phylogenetic hypotheses for vascular plants, etc.. R package version 0.1.0. (2020).368.Yu, G., Smith, D. K., Zhu, H., Guan, Y. & Lam, T. T.-Y. Gtree: An r package for visualization and annotation of phylogenetic trees with their covariates and other associated data. Methods in Ecol. Evo. 8, 28–36 (2017).Article 

Google Scholar 
369.Stefan, V. & Levin, S. Plotbiomes: Plot Whittaker biomes with ggplot2. R package version 0.0.0.9001. (2020).370.Whittaker, R. H. Communities and ecosystems. (MacMillan Publishers, 1975).371.Fick, S. E. & Hijmans, R. J. WorldClim 2: New 1-km spatial resolution climate surfaces for global land areas. Int. J. Climatol. 37, 4302–4315 (2017).Article 

Google Scholar  More

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1.Leach JE, Tringe SG. Plant–microbiome interactions: from community assembly to plant health. Nat Rev Microbiol. 2020;18:607–21.PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
2.Pii Y, Mimmo T, Tomasi N, Terzano R, Cesco S, Crecchio C. Microbial interactions in the rhizosphere: beneficial influences of plant growth-promoting rhizobacteria on nutrient acquisition process. A Rev Biol Fertil Soils. 2015;51:403–21.CAS 
Article 

Google Scholar 
3.Backer R, Rokem JS, Ilangumaran G, Lamont J, Praslickova D, Ricci E, et al. Plant growth-promoting rhizobacteria: context, mechanisms of action, and roadmap to commercialization of biostimulants for sustainable agriculture. Front Plant Sci. 2018;871:1473–89.Article 

Google Scholar 
4.Lugtenberg B, Kamilova F. Plant-growth-promoting rhizobacteria. Annu Rev Microbiol. 2009;63:541–56.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
5.Bhattacharyya PN, Jha DK. Plant growth-promoting rhizobacteria (PGPR): emergence in agriculture. World J Microbiol Biotechnol. 2012;28:1327–50.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
6.Leach JE, Triplett LR, Argueso CT, Trivedi P. Communication in the phytobiome. Cell. 2017;169:587–96.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
7.Vorholt JA, Vogel C, Carlström CI, Müller DB. Establishing causality: opportunities of synthetic communities for plant microbiome research. Cell Host Microbe. 2017;22:142–55.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
8.Douglas AE. The microbial exometabolome: ecological resource and architect of microbial communities. PTRBAE. 2020;375:20190250.CAS 
PubMed 
PubMed Central 

Google Scholar 
9.Turroni F, Milani C, Duranti S, Mahony J, van Sinderen D, Ventura M. Glycan utilization and cross-feeding activities by Bifidobacteria. Trends Microbiol. 2018;26:339–50.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
10.Evans CR, Kempes CP, Price-Whelan A, Dietrich LEP. Metabolic heterogeneity and cross-feeding in bacterial multicellular systems. Trends Microbiol. 2020;28:732–43.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
11.Smith NW, Shorten PR, Altermann E, Roy NC, McNabb WC. The classification and evolution of bacterial cross-feeding. Front Ecol Evol. 2019;7:153.Article 

Google Scholar 
12.Santoyo G, del Orozco-Mosqueda MC, Govindappa M. Mechanisms of biocontrol and plant growth-promoting activity in soil bacterial species of Bacillus and Pseudomonas: a review. Biocontrol Sci Technol. 2012;22:855–72.Article 

Google Scholar 
13.Borriss R. Use of plant-associated Bacillus strains as biofertilizers and biocontrol agents in agriculture. Bacteria in agrobiology: plant growth responses. Springer: Berlin; 2011. 41–76.14.Xiong W, Guo S, Jousset A, Zhao Q, Wu H, Li R, et al. Bio-fertilizer application induces soil suppressiveness against Fusarium wilt disease by reshaping the soil microbiome. Soil Biol Biochem. 2017;114:238–47.CAS 
Article 

Google Scholar 
15.Qin Y, Shang Q, Zhang Y, Li P, Chai Y. Bacillus amyloliquefaciens L-S60 reforms the rhizosphere bacterial community and improves growth conditions in cucumber plug seedling. Front Microbiol. 2017;8:2620.PubMed 
PubMed Central 
Article 

Google Scholar 
16.Compant S, Samad A, Faist H, Sessitsch A. A review on the plant microbiome: ecology, functions, and emerging trends in microbial application. J Adv Res. 2019;19:29–37.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
17.Cao Y, Zhang Z, Ling N, Yuan Y, Zheng X, Shen B, et al. Bacillus subtilis SQR9 can control Fusarium wilt in cucumber by colonizing plant roots. Biol Fertil Soils. 2011;47:495–506.CAS 
Article 

Google Scholar 
18.Xu Z, Shao J, Li B, Yan X, Shen Q, Zhang R. Contribution of bacillomycin D in Bacillus amyloliquefaciens SQR9 to antifungal activity and biofilm formation. Appl Environ Microbiol. 2013;79:808–15.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
19.Chen L, Liu Y, Wu G, Veronican Njeri K, Shen Q, Zhang N, et al. Induced maize salt tolerance by rhizosphere inoculation of Bacillus amyloliquefaciens SQR9. Physiol plant. 2016;158:34–44.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
20.Blake C, Nordgaard Christensen M, Kovács ÁT. Molecular aspects of plant growth promotion and protection by Bacillus subtilis. Mol Plant Microbe Interact. 2020;34:15–25.PubMed 
Article 
PubMed Central 

Google Scholar 
21.Al-Ali A, Deravel J, Krier F, Béchet M, Ongena M, Jacques P. Biofilm formation is determinant in tomato rhizosphere colonization by Bacillus velezensis FZB42. Environ Sci Pollut Res. 2018;25:29910–20.CAS 
Article 

Google Scholar 
22.Xu Z, Mandic-Mulec I, Zhang H, Liu Y, Sun X, Feng H, et al. Antibiotic bacillomycin D affects iron acquisition and biofilm formation in Bacillus velezensis through a Btr-mediated FeuABC-dependent pathway. Cel Rep. 2019;29:1192–202.CAS 
Article 

Google Scholar 
23.Murashige T, Skoog F. A revised medium for rapid growth and bioassays with tobacco tissue cultures. Physiol Plant. 1962;15:473–97.CAS 
Article 

Google Scholar 
24.Bai Y, Müller DB, Srinivas G, Garrido-Oter R, Potthoff E, Rott M, et al. Functional overlap of the Arabidopsis leaf and root microbiota. Nature. 2015;528:364–9.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
25.Zhou C, Shi L, Ye B, Feng H, Zhang J, Zhang R, et al. pheS *, an effective host-genotype-independent counter-selectable marker for marker-free chromosome deletion in Bacillus amyloliquefaciens. Appl Microbiol Biotechnol. 2017;101:217–27.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
26.Feng H, Zhang N, Fu R, Liu Y, Krell T, Du W, et al. Recognition of dominant attractants by key chemoreceptors mediates recruitment of plant growth-promoting rhizobacteria. Environ Microbiol. 2019;21:402–15.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
27.Lambertsen L, Sternberg C, Molin S. Mini-Tn7 transposons for site-specific tagging of bacteria with fluorescent proteins. Environ Microbiol. 2004;6:726–32.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
28.Seemann T. Prokka: rapid prokaryotic genome annotation. Bioinformatics. 2014;30:2068–9.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
29.Machado D, Andrejev S, Tramontano M, Patil KR. Fast automated reconstruction of genome-scale metabolic models for microbial species and communities. Nucleic Acids Res. 2018;46:7542–53.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
30.Lieven C, Beber ME, Olivier BG, Bergmann FT, Ataman M, Babaei P, et al. MEMOTE for standardized genome-scale metabolic model testing. Nat Biotechnol. 2020;38:272–6.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
31.Zelezniak A, Andrejev S, Ponomarova O, Mende DR, Bork P, Patil KR. Metabolic dependencies drive species co-occurrence in diverse microbial communities. Proc Natl Acad Sci USA. 2015;112:6449–54.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
32.Edgar RC. UPARSE: highly accurate OTU sequences from microbial amplicon reads. Nat Methods. 2013;10:996–8.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
33.Parks DH, Tyson GW, Hugenholtz P, Beiko RG. STAMP: statistical analysis of taxonomic and functional profiles. Bioinformatics. 2014;30:3123–4.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
34.Branda SS, González-Pastor JE, Ben-Yehuda S, Losick R, Kolter R. Fruiting body formation by Bacillus subtilis. Proc Natl Acad Sci USA. 2001;98:11621–6.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
35.Page AJ, Cummins CA, Hunt M, Wong VK, Reuter S, Holden MTG, et al. Roary: rapid large-scale prokaryote pan genome analysis. Bioinformatics. 2015;31:3691–3.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
36.Langdon WB. Performance of genetic programming optimised Bowtie2 on genome comparison and analytic testing (GCAT) benchmarks. BioData Min. 2015;8:1–7.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
37.Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15:1–21.Article 
CAS 

Google Scholar 
38.Huerta-Cepas J, Forslund K, Coelho LP, Szklarczyk D, Jensen LJ, von Mering C, et al. Fast genome-wide functional annotation through orthology assignment by eggNOG-mapper. Mol Biol Evol. 2017;34:2115–22.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
39.Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2-ΔΔ C(T) method. Methods. 2001;25:402–8.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
40.Ling N, Raza W, Ma J, Huang Q, Shen Q. Identification and role of organic acids in watermelon root exudates for recruiting Paenibacillus polymyxa SQR-21 in the rhizosphere. Eur J Soil Biol. 2011;47:374–9.CAS 
Article 

Google Scholar 
41.Gordillo F, Chávez FP, Jerez CA. Motility and chemotaxis of Pseudomonas sp. B4 towards polychlorobiphenyls and chlorobenzoates. FEMS Microbiol Ecol. 2007;60:322–8.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
42.Dragoš A, Kiesewalter H, Martin M, Hsu CY, Hartmann R, Wechsler T, et al. Division of labor during biofilm matrix production. Curr Biol. 2018;28:1903–.e5.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
43.Ahmad F, Ahmad I, Khan MS. Screening of free-living rhizospheric bacteria for their multiple plant growth promoting activities. Microbiol Res. 2008;163:173–81.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
44.Lynne AM, Haarmann D, Louden BC. Use of blue agar CAS assay for siderophore detection. J Microbiol Biol Educ. 2011;12:51–53.PubMed 
PubMed Central 
Article 

Google Scholar 
45.Nautiyal CS. An efficient microbiological growth medium for screening phosphate solubilizing microorganisms. FEMS Microbiol Lett. 1999;170:265–70.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
46.Ansari FA, Ahmad I. Fluorescent Pseudomonas -FAP2 and Bacillus licheniformis interact positively in biofilm mode enhancing plant growth and photosynthetic attributes. Sci Rep. 2019;9:1–12.
Google Scholar 
47.Santhanam R, Menezes RC, Grabe V, Li D, Baldwin IT, Groten K. A suite of complementary biocontrol traits allows a native consortium of root‐associated bacteria to protect their host plant from a fungal sudden‐wilt disease. Mol Ecol. 2019;28:1154–69.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
48.Santhanam R, Luu VT, Weinhold A, Goldberg J, Oh Y, Baldwin IT. Native root-associated bacteria rescue a plant from a sudden-wilt disease that emerged during continuous cropping. Proc Natl Acad Sci USA. 2015;112:E5013–E5120.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
49.Berendsen RL, Vismans G, Yu K, Song Y, de Jonge R, Burgman WP, et al. Disease-induced assemblage of a plant-beneficial bacterial consortium. ISME J. 2018;12:1496–507.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
50.Ren D, Madsen JS, Sørensen SJ, Burmølle M. High prevalence of biofilm synergy among bacterial soil isolates in cocultures indicates bacterial interspecific cooperation. ISME J. 2015;9:81–89.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
51.Oliveira NM, Martinez-Garcia E, Xavier J, Durham WM, Kolter R, Kim W, et al. Biofilm formation as a response to ecological competition. PLoS Biol. 2015;13:1–23.
Google Scholar 
52.Gallegos-Monterrosa R, Mhatre E, Kovács ÁT. Specific Bacillus subtilis 168 variants form biofilms on nutrient-rich medium. Microbiology. 2016;162:1922–32.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
53.Shao J, Xu Z, Zhang N, Shen Q, Zhang R. Contribution of indole-3-acetic acid in the plant growth promotion by the rhizospheric strain Bacillus amyloliquefaciens SQR9. Biol Fertil Soils. 2015;51:321–30.CAS 
Article 

Google Scholar 
54.Stopnisek N, Shade A. Persistent microbiome members in the common bean rhizosphere: an integrated analysis of space, time, and plant genotype. ISME J. 2021;15:2708–22.PubMed 
PubMed Central 
Article 

Google Scholar 
55.Sivasakthi S, Usharani G, Saranraj P. Biocontrol potentiality of plant growth promoting bacteria (PGPR)—Pseudomonas fluorescens and Bacillus subtilis: a review. Afr J Agric Res. 2014;9:1265–77.
Google Scholar 
56.Dardanelli MS, Manyani H, González-Barroso S, Rodríguez-Carvajal MA, Gil-Serrano AM, Espuny MR, et al. Effect of the presence of the plant growth promoting rhizobacterium (PGPR) Chryseobacterium balustinum Aur9 and salt stress in the pattern of flavonoids exuded by soybean roots. Plant Soil. 2010;328:483–93.CAS 
Article 

Google Scholar 
57.Gómez Expósito R, Postma J, Raaijmakers JM, de Bruijn I. Diversity and activity of Lysobacter species from disease suppressive soils. Front Microbiol. 2015;6:1243.PubMed 
PubMed Central 
Article 

Google Scholar 
58.Han Q, Ma Q, Chen Y, Tian B, Xu L, Bai Y, et al. Variation in rhizosphere microbial communities and its association with the symbiotic efficiency of rhizobia in soybean. ISME J. 2020;14:1915–28.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
59.Peterson SB, Dunn AK, Klimowicz AK, Handelsman J. Peptidoglycan from Bacillus cereus mediates commensalism with rhizosphere bacteria from the Cytophaga-Flavobacterium group. Appl Environ Microbiol. 2006;72:5421–7.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
60.Tao C, Li R, Xiong W, Shen Z, Liu S, Wang B, et al. Bio-organic fertilizers stimulate indigenous soil Pseudomonas populations to enhance plant disease suppression. Microbiome. 2020;8:137.PubMed 
PubMed Central 
Article 

Google Scholar 
61.Kumar A, Singh J. Biofilms forming microbes: diversity and potential application in plant-microbe interaction and plant growth. Springer: Cham; 2020. 173−97.62.Tabassum B, Khan A, Tariq M, Ramzan M, Iqbal Khan MS, Shahid N, et al. Bottlenecks in commercialisation and future prospects of PGPR. Appl Soil Ecol. 2017;121:102–17.Article 

Google Scholar 
63.Madsen JS, Røder HL, Russel J, Sørensen H, Burmølle M, Sørensen SJ. Coexistence facilitates interspecific biofilm formation in complex microbial communities. Environ Microbiol. 2016;18:2565–74.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
64.Burmølle M, Webb JS, Rao D, Hansen LH, Sørensen SJ, Kjelleberg S. Enhanced biofilm formation and increased resistance to antimicrobial agents and bacterial invasion are caused by synergistic interactions in multispecies biofilms. Appl Environ Microbiol. 2006;72:3916–23.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
65.Lee KWK, Periasamy S, Mukherjee M, Xie C, Kjelleberg S, Rice SA. Biofilm development and enhanced stress resistance of a model, mixed-species community biofilm. ISME J. 2014;8:894–907.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
66.Yannarell SM, Grandchamp GM, Chen SY, Daniels KE, Shank EA. A dual-species biofilm with emergent mechanical and protective properties. J Bacteriol. 2019;201:e00670–18.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
67.Preussger D, Giri S, Muhsal LK, Oña L, Kost C. Reciprocal fitness feedbacks promote the evolution of mutualistic cooperation. Curr Biol. 2020;30:1–11.Article 
CAS 

Google Scholar 
68.Nadell CD, Drescher K, Foster KR. Spatial structure, cooperation, and competition in biofilms. Nat Rev Microbiol. 2016;14:589–600.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
69.Estrela S, Sanchez-Gorostiaga A, Vila JCC, Sanchez A. Nutrient dominance governs the assembly of microbial communities in mixed nutrient environments. eLife. 2021;10:e65948.PubMed 
PubMed Central 
Article 

Google Scholar 
70.Molina-Santiago C, Pearson JR, Navarro Y, Berlanga-Clavero MV, Caraballo-Rodriguez AM, Petras D, et al. The extracellular matrix protects Bacillus subtilis colonies from Pseudomonas invasion and modulates plant co-colonization. Nat Commun. 2019;10:1919.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
71.Yan Q, Lopes LD, Shaffer BT, Kidarsa TA, Vining O, Philmus B, et al. Secondary metabolism and interspecific competition affect accumulation of spontaneous mutants in the GacS-GacA regulatory system in Pseudomonas protegens. mBio. 2018;9:e01845–17.CAS 
PubMed 
PubMed Central 

Google Scholar 
72.Mee MT, Collins JJ, Church GM, Wang HH. Syntrophic exchange in synthetic microbial communities. Proc Natl Acad Sci USA. 2014;111:E2149–E2156.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
73.D’Souza G, Shitut S, Preussger D, Yousif G, Waschina S, Kost C. Ecology and evolution of metabolic cross-feeding interactions in bacteria. Nat Prod Rep. 2018;35:455–88.PubMed 
Article 
PubMed Central 

Google Scholar 
74.Goldford JE, Lu N, Bajić D, Estrela S, Tikhonov M, Sanchez-Gorostiaga A, et al. Emergent simplicity in microbial community assembly. Science. 2018;361:469–74.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
75.Lawrence D, Fiegna F, Behrends V, Bundy JG, Phillimore AB, Bell T, et al. Species interactions alter evolutionary responses to a novel environment. PLoS Biol. 2012;10:e1001330.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
76.Evans R, Beckerman AP, Wright RCT, McQueen-Mason S, Bruce NC, Brockhurst MA. Eco-evolutionary dynamics set the tempo and trajectory of metabolic evolution in multispecies communities. Curr Biol. 2020;30:1–5.Article 
CAS 

Google Scholar 
77.Gamez RM, Ramirez S, Montes M, Cardinale M. Complementary dynamics of banana root colonization by the plant growth-promoting rhizobacteria Bacillus amyloliquefaciens Bs006 and Pseudomonas palleroniana Ps006 at spatial and temporal scales. Micro Ecol. 2020;80:656–68.CAS 
Article 

Google Scholar 
78.Feng H, Zhang N, Fu R, Liu Y, Krell T, Du W, et al. Recognition of dominant attractants by key chemoreceptors mediates recruitment of plant growth-promoting rhizobacteria. Environ Microbiol. 2019;21:402–15.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
79.Feng H, Zhang N, Du W, Zhang H, Liu Y, Fu R, et al. Identification of chemotaxis compounds in root exudates and their sensing chemoreceptors in plant-growth-promoting rhizobacteria Bacillus amyloliquefaciens SQR9. Mol Plant Microbe interact. 2018;31:995–1005.CAS 
PubMed 
Article 

Google Scholar 
80.Xu Z, Xie J, Zhang H, Wang D, Shen Q, Zhang R. Enhanced control of plant wilt disease by a xylose-inducible degQ gene engineered into Bacillus velezensis strain SQR9XYQ. Phytopathology. 2019;109:36–43.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar  More

1.Kang CS, Liang X, Dershwitz P, Gu W, Schepers A, Flatley A, et al. Evidence for methanobactin “theft” and novel chalkophore production in methanotrophs: impact on methanotrophic-mediated methylmercury degradation. ISME J. 2021;https://doi.org/10.1038/s41396-021-01062-1.2.Semrau JD, DiSpirito AA, Obulisamy PK, Kang-Yun CS. Methanobactin from methanotrophs: genetics, structure, function and potential applications. FEMS Microbiol Lett. 2020;367:fnaa045.CAS 
Article 

Google Scholar 
3.Kim HJ, Graham DW, DiSpiito AA, Alterman MA, Galeva N, Larive CK, et al. Methanobactin: a copper-acquisition compound from methane-oxidizing bacteria. Science. 2004;305:1612–5.CAS 
Article 

Google Scholar 
4.Lu X, Gu W, Zhao L, Farhan Ul Haque M, DiSpirito AA, Semrau JD, et al. Methylmercury uptake and degradation by methanotrophs. Sci Adv. 2017;3:e1700041.Article 

Google Scholar 
5.Ve T, Mathisen K, Helland R, Karlsen OA, Fjellbirkeland A, Røhr ÅK, et al. The Methylococcus capsulatus (Bath) secreted protein, MopE*, binds both reduced and oxidized copper. PLoS ONE. 2012;7:e43146.CAS 
Article 

Google Scholar 
6.DiSpirito AA, Semrau JD, Murrell JC, Gallagher WH, Dennison C, Vuilleumier S. Methanobactin and the link between copper and bacterial methane oxidation. Microbiol Mol Biol Rev. 2016;80:387–409.CAS 
Article 

Google Scholar 
7.Kenney GE, Rosenzweig AC. Genome mining for methanobactins. BMC Biol. 2013;11:17.CAS 
Article 

Google Scholar 
8.Yu Z, Zheng Y, Huang J, Chistoserdova L. Systems biology meets enzymology: recent insights into communal metabolism of methane and the role of lanthanides. Curr Issues Mol Biol. 2019;33:183–96.Article 

Google Scholar 
9.Gwak J-H, Jung M-Y, Hong HY, Kim J-G, Quan Z-X, Reinfelder JR, et al. Archaeal nitrification is constrained by copper complexation with organic matter in municipal wastewater treatment plants. ISME J. 2020;14:335–46.CAS 
Article 

Google Scholar 
10.Chang J, Kim DD, Semrau JD, Lee J, Heo H, Gu W, et al. Enhancement of nitrous oxide emissions in soil microbial consortia via copper competition between proteobacterial methanotrophs and denitrifiers. Appl Environ Microbiol. 2020;87:e02301–20.
Google Scholar  More