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Phylogenetic analysesA total of 21 sequences were newly generated and deposited in GenBank (Supplementary Table 1). The concatenated sequence alignment of the three loci comprised 100 sequences (38 for ITS, 30 for rpb2 and 32 for mtSSU) from 43 collections (Supplementary Table 1). The alignment was 2,004 characters long, including gaps. Multi-locus trees generated from ML and BI analyses showed similar topologies without any supported topological conflict. The multi-locus phylogeny (Fig. 1) confirmed placement of all Thai collections within the well-supported R. subsect. Amoeninae (ML = 99, BI = 1.0). Five collections from northeastern Thailand and two collections from northern Thailand form two strongly supported clades and are described below as the new species R. bellissima sp. nov. and R. luteonana sp. nov. The new species are not resolved as sister. The first species, R. bellissima, is strongly supported as sister to a clade of Australian sequestrate species that includes R. variispora T. Lebel and an undescribed Russula sp. labeled as Macowanites sp. The Indian species R. intervenosa S. Paloi, A.K. Dutta & K. Acharya is placed as sister to them with bootstrap support of 77. The second species, R. luteonana, is placed with moderate support as sister to the sequestrate European species R. andaluciana T.F. Elliott & Trappe.Figure 1ML phylogenetic tree inferred from the three-gene dataset (ITS, rpb2, mtSSU) of Russula subsection Amoeninae species, using ML and BI analyses. Three members of R. subg. Heterophyllidiae are used as outgroup. Species in boldface are new species in this study. Bootstrap support values (BS ≥ 50%) and posterior probabilities (PP ≥ 0.90) are shown at the supported branches.Full size imageThe ITS tree (Fig. 2) shows a similar topology and relationships for the studied specimens. In addition, R. intervenosa received good support (ML = 84, BI = 0.99) as sister to the clade of R. bellissima and R. variispora. Five additional ITS sequences that are grouped with strong support within R. bellissima species clade were recovered, three from Thailand, one from Laos, and one from Singapore. We did not recover any other Amoeninae ITS sequences from Thailand.Figure 2ML phylogenetic tree inferred from the ITS region of Russula subsection Amoeninae species and allied groups, using ML and BI methods. Samples in boldface are new species in this study. Bootstrap support values (BS ≥ 50%) and posterior probabilities (PP ≥ 0.90) are shown at the supported branches.Full size imageTaxonomy
Russula bellissima Manz & F. Hampe sp. nov.
Mycobank: MB 840549Holotype THAILAND, Theong district, Chiang Rai, 19°36′45”N 100°4′00”E, alt. 500 m, dry dipterocarpus forest in small groups on loamy soil, 12 July 2012, F. Hampe (Holotype: GENT FH 12-127; Isotype: MFLU12-0619).Etymology ’bellus’ = latin for beautiful, pretty, lovely; ’bellissima’ = the most beautiful. Resembling the species Russula bella which is also belonging to Russula subsection Amoeninae.Diagnosis Pileus small to medium-sized; cuticle dry, smooth, matt and pruinose, red; stipe white or with a red flush; spore ornamentation of moderately distant to dense amyloid spines or warts, frequently fused into short crests or even long wings; suprahilar spot inamyloid; hymenial cystidia and pileocystidia absent.Pileus (Fig. 3) small to medium sized, 10–50 mm diam., young hemispherical or convex, becoming plane and depressed at the centre; margin first even, when old distinctly tuberculate-striate up to 10 mm from the margin, often radially cracking; cuticle hardly peeling, radially disrupted into small patches, pruinose when young, later dry, smooth, matt and pruinose in the centre, colour near the margin when young varnish red (9C8), later red to coral red (9B6-7); near the centre deep red, blood red, dark red (10C7-8), raspberry red (10D7), strawberry red (10D8) or purple brown (10E-F8). Lamellae: 3–5 mm deep, thin, moderately dense, 6–8 at 1 cm near the pileus margin, adnexed, white, slightly anastomosing at the base; lamellulae absent, occasionally forked near the stipe; edges concolorous, entire but pruinose under lens. Stipe: 10–30 × 3–7 mm, usually narrowed towards the base, sometimes cylindrical, surface smooth, white and mainly with a distinct pastel red to red flush, occasionally completely white or sometimes also almost completely red, interior stuffed. Context: white, fragile, unchanging when damaged, reaction with guaiac after 5 s negative on both stipe and lamellae surfaces, reaction to FeSO4 and sulfovanillin negative; taste mild; odour inconspicuous. Spore print: not observed.Figure 3Basidiomata of Russula bellissima. (A) FH12-127 (Holotype). (B) FH12-158. Scale bar = 1 cm. Photos by Felix Hampe.Full size imageSpores (Figs. 4, 5) (6.9–)7.3–7.8–8.3(–8.9) × (6.1–)6.8–7.2–7.6(–8.4) µm, subglobose to broadly ellipsoid, Q = 1.01–1.1–1.2(–1.29); ornamentation of moderately distant [(4–)5–6(–7) in a 3 µm diam. circle] amyloid spines or warts, (1.1–)1.2–1.4–1.6(–1.7) µm high, fused or connected by fine line connections into often long crests or wings, [(0–)1–3(–4) fusions and the same number of line connections in a 3 µm diam. circle], crests and wings frequently branched and occasionally form closed loops, isolated elements dispersed, edge of crests and wings irregularly wavy; suprahilar spot moderately large, inamyloid. Basidia: (30.5–)34.5–44.1–53.5(–65.0) × (10.5–)11.5–12.6–14.0(–16.0) µm, broadly clavate or obpyriform, 4-spored; basidiola cylindrical, ellipsoid or broadly clavate, ca. 5–10 µm wide. Hymenial cystidia on lamellae sides: absent. Lamellae edges: covered by densely arranged or fasciculate marginal cells. Marginal cells: (27.0–)38.5–46.4–54.5(–61.0) × (5.0–)5.5–6.7–7.5(–9.0) µm; subulate or narrowly lageniform, apically attenuated and constricted to ca. 1–2 µm, sometimes slightly moniliform or flexuous. Pileipellis: (Fig. 6) orthochromatic in Cresyl Blue, gradually passing to the underlying context, 200–300 µm deep; suprapellis 60–130 µm deep, composed of erect or ascending hyphal terminations forming a dry trichoderm, well delimited from 140 to 210 µm deep subpellis composed of horizontally oriented, strongly gelatinized narrow hyphae. Subpellis not well delimited from the underlying context, elongate hyphae gradually changing to sphaerocytes. Acid- resistant incrustations: absent. Hyphal terminations near the pileus margin: composed of long apically attenuated terminal cell and a chain of 1–4 ovoid to barrel shaped, short unbranched cells with one distinctly longer apical cell; constricted on septa, usually not flexuous, oriented towards the pileus surface, usually thin-walled, sometimes slightly thick-walled (up to 1 µm thick); terminal cells mainly subulate or lageniform, apically attenuated and acute, measuring (19–)27.5–38.3–49.0(–66.5) × (3.3–)4.5–5.8–7.0(–9.0) µm, rarely with a forked apex, mixed with dispersed, cylindrical or ellipsoid, distinctly shorter, obtuse terminal cells measuring (7.5–)11.5–17.8–29.5(–42.5) × (3.0–)4.0–4.5–5.0 µm; subterminal cells measuring (4.5–)5.5–8.3–11.5(–16.0) × 4.5–5.3–6.0(–7.0) µm. Hyphal terminations near the pileus centre: similar in shape and also with a mixture of long acute and short obtuse terminal cells, acute ones measuring (12.0–)22.0–35.2–48.5(–79.0) × (2.5–)3.5–4.9–6.5(–8.0) µm, obtuse ones more frequent, measuring (6.5–)8.5–12.0–15.5(–22.0) × (3.5–)4.0–4.9–6.0(–7.5) µm. Primordial hyphae or pileocystidia: absent. Cystidioid hyphae and oleipherous hyphae not observed.Figure 4Hymenial elements of Russula bellissima (holotype, FH 12-127). (A) Basidia and basidiolae. (B) Marginal cells. (C) Spores as seen in Melzer’s reagent. Scale bar = 10 µm, but only 5 µm for spores.Full size imageFigure 5Scanning electron microscope photo of spore ornamentation. Russula bellissima (holotype, FH 12-127). Scale bar = 2 μm.Full size imageFigure 6Elements of the pileipellis of Russula bellissima (holotype, FH 12-127). (A) Hyphal terminations near the pileus margin. (B) Hyphal terminations near the pileus centre. Scale bar = 10 μm.Full size imageAdditional material studied THAILAND, Chiang Mai Province, Mae On District, about 3 km from Tharnthong lodges, 18° 51′ 55″ N 99° 17′ 23″ E, alt. 725 m, Dipterocarpaceae dominated forest with the presence of some Castanopsis trees, in small groups on loamy soil, 17 July 2012, F. Hampe (GENT FH 12-158, duplicate: MFLU12-0648).Note Russula bellissima is a small species with a bright red pileus and pink colour on the stipe. This colour is distinctive and resembles North American R. mariae, Indian R. intervenosa and Asian R. bella. It is very unlikely that the distribution of any European or North American species is overlapping with the Thai species. However, little is known about the distributional ranges and the ecological niches of other Asian Russula species. Therefore discussing the morphological distinguishing characters between Asian species and R. bellissima is more relevant. Russula bellissima is not closely related to R. bella and it differs from this species by larger spores with a more prominent spore ornamentation, absence of hymenial cystidia on lamellae sides, and subterminally short, ellipsoid cells in the suprapellis arranged in unbranched chains of up to four7. The Thai species resembles and is closely related to the Indian R. intervenosa, but it has a more prominent spore ornamentation, hymenial cystidia (on lamellae sides) are absent, and hyphal terminations in the pileipellis are wider22.
Russula luteonana M. Pobkwamsuk & K. Wisitrassameewong sp. nov.
Mycobank: MB 840550Holotype: THAILAND, Amnat Charoen province, Hua Taphan district, Junction near Watbochaneng , dry dipterocarp forest, alt. 145 m, 15° 41′ 28″ N 104° 31′ 41″ E, 13 July 2016, Thitiya Boonpratuang, Rattaket Choeyklin, Prapapan Sawhasan, Maneerat Pobkwamsuk, Pattrachai Juthamas, Nattawut Wiriyathanawudhiwong, Patcharee Patangwesa (BBH41120).Etymology ‘Luteolus’ = yellow colour, ‘Nanus’ = small. Refer to pileus color and size of the species.Diagnosis Pileus medium-sized, dry, usually yellow, spores with subreticulate amyloid ornamentation and inamyloid suprahilar spot, hymenial cystidia on lamellae sides large, lamellae edges with combination of subulate, clavate and pyriform marginal cells.Pileus (Fig. 7) medium-sized, 28‒53 mm diam., plano-convex with depressed centre, infundibuliform when mature; margin striated and radially cracking in dry condition; cuticle dry, peeling to almost ½ of radius, smooth to minutely wrinkled, dull in dry condition, color very variable, some collections pale cream and with darker pale brownish-yellow centre, other yellow brownish and with darker orange-brown centre, sometimes also bright red-brown and with discolored centre, always with rusty-brown spots especially when near the centre. Lamellae: 3‒5 mm deep, moderately distant, intervenose, forking near the stipe, white to cream, edges even, concolorous. Stipe: 26‒40 × 6‒9 mm, cylindrical or narrowed at the base, surface dry, longitudinally wrinkled, white, turning brown when bruised. Context: 2‒4 mm in at the half pileus radius, soft, solid, becoming partially hollow when mature, white, unchanging when cut. Taste mild; odour rather strong, fishy. Spore print: not observed.Figure 7Basidiomata of Russula luteonana. (A) BBH41120 (Holotype). (B) BBH41121. (C) BBH41122. (D) BBH42510. Scale bar = 1 cm. Photos by Thitiya Boonpratuang.Full size imageSpores (Figs. 8, 9) (7.4‒)8.1‒8.6‒9(‒10.1) × (6.1‒)7.4‒7.5‒7.9(‒9.1) μm, subglobose to broadly ellipsoid, Q = (1.03‒)1.09‒1.15‒1.20(‒1.30), ornamentation of moderately distant, obtuse, (0.7‒)1.1‒1.3‒1.5(‒1.9) μm high spines, connected by abundant line connections [(0‒)3‒6(‒8) in in a 3 µm diam. circle], branched, forming an incomplete reticulum, crest irregularly wavy and occasionally fused [(0‒)1‒2(‒5) fusions in the circle], isolated elements rare; suprahilar spot inamyloid. Basidia: (29‒)34.5‒39.1‒44(‒51.5) × (10‒)12‒13.2‒14.5(‒16.5) μm, clavate, 4-spored, rarely 2-spored, basidiola subcylindrical to subclavate, (25.5‒)30‒35.4‒41(‒47) × (9‒)11‒12.2‒14 (‒16) μm. Hymenial cystidia on lamellae sides: usually protruding over other elements of hymenium, widely dispersed ( More

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Site descriptionWarra Supersite, (Lat: 43° 5′ 42ʺ S; Long: 146° 39′ 16ʺ E) is located on a floodplain of the Huon River within the Warra Long Term Ecological Research site (https://warra.com/) 60 km southwest of Hobart, Tasmania. The forest at the Supersite is a Eucalyptus obliqua tall forest with a canopy height of 50–55 m, overtopping a 15–40 m tall secondary layer of rainforest and wet sclerophyll tree species. Ferns dominate the ground layer. The forest is very productive with an aboveground biomass of 790 tonnes/ha16 and a leaf area index of 5.7 m2/m247.The Supersite is within the Tasmanian Wilderness World Heritage Area (TWWHA). That part of the TWWHA experiences infrequent, but sometimes intense, wildfire. Except for a small proportion of mature ( > 250 years-old) E. obliqua trees, the current forest resulted from seedling regeneration following the last major wildfire in that part of the landscape in 1898. No timber harvesting has ever been done in the forest at the Supersite.The climate at Warra is classified as temperate, with no dry season and a mild summer48. Mean annual rainfall measured at the nearby Warra Climate Station (Bureau of Meteorology Station 097024) is 1736 mm and the mean daily temperature is 14 °C and 5.6 °C in January and July, respectively. The soil at the site is a Kurosolic Redoxic Hydrosol16.Analysis of historical heatwaves in southern TasmaniaDaily maximum temperature records from the Bureau of Meteorology station at Cape Bruny Lighthouse (station number 94010) were extracted from the Bureau of Meteorology’s online climate data portal (http://www.bom.gov.au/climate/data). Cape Bruny Lighthouse is one of the 112 stations in the ACORN-SAT network of Australia’s reference sites for monitoring climate change49. The station provides a record of daily maximum temperature measurements commencing in 1923 and spanning almost a century. It is the southern-most station in the ACORN-SAT network; is 59 km south-east of the Warra Flux Site; and bounds the south-eastern extent of E. obliqua tall forest in Tasmania.Missing temperature measurements represented less than 0.6% of the 35,795 records collected at Cape Bruny Lighthouse between January 1st 1923 and December 31st 2020. The missing measurements were gap-filled using predicted values calculated from linear regression models constructed from measurements made at nearby Bureau of Meteorology stations (listed in order of proximity to Cape Bruny Lighthouse and priority for gap-filling)—Cape Bruny Automatic Weather Station (1997-present), Hastings Chalet (1947–1987) and Hobart-Ellerslie Road (1892-present).Average, standard deviation and 90th percentiles of daily maximum temperature were calculated for each calendar day of the year. Further analysis of heatwaves was restricted to the period between the beginning of August and the end of February. This period bounds the growing season of the forest at the Warra Supersite when there is normally a net carbon gain by the forest (Wardlaw unpublished data). Heatwaves were identified as three or more consecutive days with maximum temperatures that met or exceeded the 90th percentile value sensu Perkins and Alexander9. For each heatwave event that was identified, the following three statistics were calculated: (1) average daily maximum temperature during the heatwave; (2) summed departures (as standard deviations) from average daily maximum temperature during the heatwave; (3) summed departures (as standard deviations) from average daily maximum temperature of the 21 day period centred on the middle day of the heatwave. The November 2017 heatwave, as described by these three statistics, was ranked against all the other heatwave events identified between 1923 and 2020 at Cape Bruny Lighthouse. In addition, the z-score was calculated to measure the magnitude of the departure of the average daily maximum temperatures during the November 2017 heatwave from the long-term average of this 21-day period. Those statistics were also calculated for the same period in 2016.Weather conditions at Warra Supersite during the 2017 warm spellFour attributes of weather were used to describe the November 2017 warm spell—air temperature, vapor pressure deficit (calculated from temperature and relative humidity), incoming shortwave radiation and soil moisture. Air temperature and relative humidity were measured using an HMP155A probe (Vaisala, Finland) and incoming shortwave radiation was measured using a CNR4 radiometer (Kipp and Zonen, The Netherlands). Both instruments were mounted 80-m above ground level at the top of the Warra Flux tower. Data was processed to 30-min averages and logged onto a CR3000 datalogger (Campbell Scientific, Logan, USA).Soil moisture was measured by time-domain reflectometry using two CS616 soil moisture probes (Campbell Scientific, Logan, USA) each installed at a depth of 20 cm. These probes were installed in two pits approximately 40 m west of the tower. Soil moisture data were processed to 30-min averages and logged onto a CR1000 datalogger (Campbell Scientific, Logan USA).Turbulent fluxes at Warra Supersite during the November 2017 warm spellMeasurement of turbulent fluxes (carbon, water and energy) were done by eddy covariance (EC) using a closed-path infra-red gas analyser (Model EC155, Campbell Scientific Inc., Logan, USA) to measure CO2 and H2O concentrations and a 3-D sonic anemometer (Model CSAT3A, Campbell Scientific Inc, Logan, USA) to measure turbulent wind vectors and virtual air temperature. The sonic anemometer and infra-red gas analyser were mounted at 80-m above the ground at the top of the Warra Flux tower. Storage of CO2 and H2O beneath the forest canopy was measured by a profile system (Model AP200, Campbell Scientific Inc, Logan, USA ), with sampling heights of 2, 4, 8, 16, 30, 42, 54, 70 m. Temperature sensors in aspirated shields (Model 110-ST, Apogee Instruments, Logan, USA) were co-located with the CO2/H2O sample inlets of the profile system. High frequency (10 Hz) measurements of turbulent fluxes were processed to 30-min averages in a datalogger (Model CR3000, Campbell Scientific, Logan USA). High frequency (2 Hz) of CO2 and water concentration measurements were processed to 15-s averages sequentially for each profile sample height in a datalogger (Model CR1000, Campbell Scientific, Logan, USA). Thus, each inlet was sampled for a 15 s interval every 2 min. The rate at which sub-canopy storage of CO2 changed was calculated from changes in the quasi-instantaneous (2-min) vertical profile concentrations beneath the tower at the beginning and end of each 30-min flux averaging period using the method of McHugh50.Soil heat flux (SHF) was measured to enable calculation of energy balance that was needed to partition energy fluxes into latent and sensible heat. SHF was measured using five SHF plates (Model HFP01SC, Hukseflux, Delft, The Netherlands) inserted in the soil at depth 8 cm adjacent to the two pits in which the soil moisture probes were installed. Each of the five SHF plates were allocated to one of the two soil pits in a 2–3 split. Changes in soil temperature was measured by an averaging thermocouple (Model TCAV, Campbell Scientific Inc, Logan, USA) inserted into the soil above each SHF plate at depths of 2 and 6 cm. Soil moisture measurements at 20 cm depth were as described previously. Heat flux, soil temperature and soil moisture data were processed to 30-min averages on a datalogger (Model CR1000, Campbell Scientific Inc, Logan, USA).Raw 30-min flux, CO2 storage and climate data were processed by the standard OzFlux QA/QC processing stream51 using PyFluxPro Version 1.0.2 software. Fluxes (carbon and energy) adjusted for storage were computed at the mid-stage (level 3). At the final stage of data processing (level 6), gap-filled net ecosystem exchange (NEE) data were partitioned into gross primary productivity (GPP) and ecosystem respiration (ER) using the u*-filtered night-time CO2 flux records to calculate ER with the SOLO artificial neural network algorithm as described in51. The standard conventions of the global flux network were adopted in partitioning NEE as described in52.The full period between 10 and 30th November 2017 was defined as the November 2017 warm spell. The climate and fluxes measured during this period were compared with measurements of those made during the same calendar days of the preceding year, 2016. The carbon fluxes measured in the 10 weeks before (1 September–9 November) and the month after (1–31 December) the 2017 warm spell period were also compared with the same periods in 2016. This was done to ascertain whether changes in carbon fluxes during the 2017 warm spell we not due to differences in antecedent weather conditions and, whether or not differences in carbon fluxes arising from the warm spell persisted after the warm spell.Data analysisFor each day of the 10–30 November period, daily sums were calculated for measurements of carbon fluxes and incoming shortwave radiation (Fsd), while daily averages were calculated for air temperature, VPD and soil moisture. Quantile plots, done for Ta and VPD, used 30-min data during daytime hours (when Fsd  > 0). The significance of differences in measurements during the 10–30 November period among the two years of each variable were tested by analysis of variance. Tests were first done to confirm the data for each variable were normally distributed and between-group variances were homoscedastic. Log-transformation was used to correct skewness in the VPD data. Soil moisture data were strongly skewed, and transformation was unable to correct. For this variable, the Kruskal–Wallis method was used to test the significance of differences in medians among the two years. These analyses were repeated for the 10 weeks (1st September–9th November) leading up to the warm spell and the 4 weeks (1st–31st December) following the warm spell to examine antecedent conditions and subsequent recovery from the warm spell, respectively.The energy fluxes were examined for evidence of coupling between GPP, transpiration and canopy conductance. Closure of the energy balance was first determined for the two periods to ensure comparability of the energy fluxes for the 2017 warm spell period and the corresponding period in 2016. This was done by firstly resampling the 30-min data and calculating 2-hourly averages of latent heat flux (Fe), sensible heat flux (Fh), net radiation (Fn) and ground heat flux (Fg), then fitting linear regressions of Fe + Fh against Fn–Fg for dates encompassing the warm spell in each of two years. Peak energy storage of the biomass, Fb, in the forest at Warra was estimated as 40 W m−2 using the method described in17. That estimate used the value of LAI of 5.72 based on the average of periodic measurements of LAI at Warra reported in47 and the value of 22.0 for the quadratic mean radius at breast height (1.3 m) calculated from tree measurements in a 1-ha plot adjacent to the Warra Flux tower (detailed in47). The ratio of energy storage in the biomass and ground heat flux at their respective daily maxima was calculated, assuming their respective diurnal peaks coincided. This ratio was then applied to each 2-h average of ground heat flux measured in the warm spell period in 2017 and the corresponding period in 2016. Available energy was recalculated using the formula Fn–(Fg + Fb). Analysis of variance was used to test the significance of differences between the 2017 warm spell and the corresponding period in 2016 of each component energy fluxes (Fn, Fe, Fh and Fg) for each of the twelve, 2-h periods, in the day. Kruskal–Wallis rank test was used if a variable had a non-normal distribution or exhibited heteroscedasticity. The Bowen ratio, which is the ratio between Fh and Fe, was calculated for each 2-h period during daytime hours. The 2-h average data were non-normal and heteroscedastic so testing the significance of differences in daytime Bowen ratio between the warm spell and comparison period was done using 2-sample t-test with unequal variance.Latent heat flux was converted to evapotranspiration by dividing the measured latent heat flux by the latent heat of vaporisation of water. Evapotranspiration was used as a proxy of transpiration on the assumption that evaporation was a minor component of evapotranspiration in the tall E. obliqua forest at Warra based on measurements of soil and litter evaporation in similar forests by23. An estimate of total canopy conductance of sunlit leaves, Gt, was calculated from transpiration (E) and vapor pressure deficit, VPD, using the Skelton et al.53 adaptation of the method developed by Hogg and Hurdle54, whereby:$${text{G}}_{{text{t}}} = (upalpha /1000){text{E}}/{text{VPD}}$$The atmospheric pressure of water vapor, α, is equivalent to ρwGvTk, where ρw is the density of water (c 1000 kg m−3), Gv is the universal gas constant for water vapor (0.462 m3 kPa kg−1 K−1) and Tk is air temperature (in K = Ta + 273.15). Gt (in mmol m−2 s−1) was calculated for each 2-h period during the 2017 warm spell and the same calendar days in 2016 using each period’s corresponding values of E, VPD and Ta. Records were excluded if rain fell during the 2-h period. The significance of differences in daytime canopy conductance between the 2017 warm spell and the 2016 comparison period was tested using a two-sample t-test as the data were strongly skewed.The diurnal patterns of GPP, ER and canopy conductance were compared with incoming shortwave radiation, air temperature and vapour pressure deficit. Each 30-min record of the six variables was recoded to its corresponding 2-h time interval. Analysis of variance was used to test for significance of differences between the warm spell and comparison period for each of the twelve 2-h diurnal periods of the six variables. Kruskal–Wallis rank test was used in the data were non-normal or heteroscedastic. Time series plots of diurnal 2-hourly averages for each of the six variables were plotted and visually compared. More