Introduction

2. Materials and Methods

2.2. Collection and Analyzing the Termite System’s Elements

The experiment was conducted at the Agriculture Research Station (ARS) of King Abdulaziz University located at Hada Al-Sham, northeast of Jeddah (21° 48′ 3′′ N, 39° 43′ 25′′ E), Saudi Arabia during the period extended from 01 October 2019-30 August 2020.

2.2.1. The Atmospheric Air Temperature

The dominant air temperature data of the study area were collected from the local meteorology station’s saved database that was measured at a constant level of two meters above ground level.

Moreover, within termite nests, the internal atmosphere measurements were limited to air temperature recording. For this task, continuous temperature measurements were taken, daily, at specified times in six hours intervals throughout the recording period (11 months) for each of the infected trunk of Zizyphus spina Christi (01 October 2019-31 August 2020). The starting record was 12 am on 1 October 2019. The measurements were recorded manually using digital thermometers with chromel-alumel thermocouple probes (type K with an error of ± 1 °C). Each thermometer’s probe was introduced deeply inside the termite nest passing through a naturally-holed tunnel spreading at the southwest direction. Since the pathways’ gallery of the nest are not straight, an electric drill with a long steel drill bit (size 0.25 “; maximum drilling depth 10 “) was used to engrave a straight pathway for entrance the thermometer probe into the nest. It is worth for mentioning that the artificial facial opening of the nest done by the drill was closed by a binding paste such as epoxy paste or honey bees wax to prevent changing the meteorological parameters within the nest as well as preventing predators to enter to the nest.

2.2.2. Soil

The soil properties in the open field were determined [83] as well as the minerals incorporated in the mortar that termites used them during constructing their nests.

In order to prevent any termite infestation, the reference soil sites were chosen to be at least 5 m away from termite nests and did not appear to have been influenced by termites. Each sampling location had three soil transects drilled from the site's center to its four cardinal points. For each transect, samples were collected at soil depths of 10, 30, and 60 cm at a constant width of 40 cm. The soil samples present at the horizon borders were avoided and the accurate samples were about 5 cm above or below the referred borders according to Rückamp et al [67].

For the soil analysis, four random soil samples from surface layer (0-30 cm depth) were collected just beneath each infected tree chosen for this study. The collected soil samples were air dried, sieved and analyzed for different physical and chemical properties.

I.

Electrical Conductivity (EC)

The EC is a measure of the amount of salts in soil (salinity of soil) that is an important indicator of soil health. The EC was measured in 1:1 soil suspension and extraction as described by Jackson [83].

II.

The pH

The pH was determined in 1:1 soil suspension and extraction as described by Jackson [83].

III.

Total Organic Matter Content (OMC) of Soil

The OMC present within the mortar collected from skeletons of the termite nests was done by applying loss on ignition (L_oI) method that is known to be one of the most widely used methods for this task [47,84-86]. The L_oI method was done at 450 °C during 5 h and at 600 °C during 6 h; and by the dry combustion method [85] using tube furnace (Carbolite). Since many factors may influence accuracy of this determination process such as furnace type, sample mass, duration and temperature of ignition and clay content of samples [47,84,85], all these factors were standardized for all the tests.

V.

Total Minerals Content in Soil (open field)

2.2.3. The Healthy Wood (W_h)

The most susceptible tree species to infection by Najdian termite, Microtermes najdensis located at Hada Al-Sham village, KSA were chosen from the enormous species habituating and cultivated in the KAU farm to study the termite infection as well as their susceptibility to the termite attack. These species were Tamarix aphylla (L.) H.Karst. (Family: Tamaricaceae Link), Pithecellobium dulce (Roxb.) Benth. (Famiy: Fabaceae Lindl.), Ziziphus spina-christi (L.) Desf. (Famiy: Rhamnaceae Juss.), Leucaena leucocephala (Lam.) de Wit (Famiy: Fabaceae Lindl.), Ficus infectoria Roxb. (Famiy: Moraceae Gaudich.), and Phoenix dactylifera L. (Arecaceae Bercht. & J.Presl). Three trees were selected from each species representing three replicates. Both the first and the latest genus (tamarix and Phoenix) are native to Saudi Arabia, while the other four genera were not.

After selecting the six tree species, wood samples was prepared for the healthy wood (W_h), and the termite nests’ skeleton (TNS) as illustrated in Figures S1a, and S1b, respectively.

A disc (approximately 30 cm thick) was sawn from each tree at a height of 0.6 m or so, and it was used to determine the wood's qualities. One bolt (approximately 1.8 cm tangentially and 30 cm long) was sliced longitudinally after the pith was isolated. Each inner- and outer-wood zone of each bolt had a diametric strip (nominal 1.8 cm tangentially and radially, and 30 cm longitudinally) removed. Accordingly, each bolt yielded two diametric strips. As a result, the removed strip was afterwards crosscut into four imperfection-free cubic samples according to Hindi [82].

The remaining volume of the wood disc, else inner or outer wood zones were separately converted into meal. Then, based on the standard methods for determining wood quality, wood meal was screened using various standard sieves and specified for the determinations of total extractives content (TEC), lignin content (KLC), holocelluloses content (HC) and ash content (AC) of the six lignocellulosic materials.

Three samples were randomly selected from each tree (a total of 9 samples of the three trees specified for each species) for each determination. For the six wood resources that were employed for each determination, 54 samples were accordingly specified.

Concerning to the characterization, the samples were prepared as indicated at Figures 1, and S1. The following wood properties were considered and their values were calculated as shown in Table 2:

I.

The Specific Gravity (SG) of the W_h

The SG of wood was determined by using Pycnometric displacement of water based on oven-dry weight and saturated volume.

Five defect-free samples (2.5 cm radially and tangentially and 2 cm longitudinally each) were used from each tree (15 samples of each species). Accordingly, 90 samples were specified for the six tree species used. The green samples assigned for this test were accurately re-saturated by water under vacuum and the saturated volume was measured by Pycnometric displacement of water. The SG was calculated based on oven-dry weight and saturated volume [87] as presented at Table 1.

II.

Total Extractives Content (TEC) of the W_h

The TEC of the healthy wood (W_h) was determined according to the ASTM [88]. Each sample assigned for extractive content determination was about one gram of an air-dried wood meal that has been' ground to pass through a No. 60 (250 urn) sieve and be retained on a No. 80 (180 um) sieve. The samples were extracted in a Soxhlet apparatus with ethanol-benzene mixture (in ta ratio of 1:2) for 4 hours, followed by extraction with 95 %ethanol for 4 hours, then extraction with a hot deionized water for 3 hours with changing of water every one hour . The extracted sample was oven-dried to a constant weight at 103 ± 2°C, and the TEC was calculated using the formula presented at Table 1.

III.

Holocelluloses Content (HC) of the W_h

The combination of hemicelluloses and alpha cellulose makes up the HC of wood [89]. According to the methodology outlined by Wise et al [90] and Hindi [12], it was determined as follows: A five weight percent fiber solution was made and combined with 0.75 g of sodium chlorite and 0.5 mL of glacial acetic acid. The temperature was held at 75 °C for one hour while the flask was top sealed to prevent the loss of gas generated during the reaction process. The chemical reagents were changed twice. The HC of wood was calculated as presented at Table 1.

IV.

Klason Lignin Content (KLC) of the W_h

The approach used by Hindi [68] and described by ASTM [91] and Jayme et al. [92] was used to determine the KLC. The diluted sulfuric acid solution (72%) was used to hydrolyze the extractives-free wood sample at 35°C. The sample was secondarily-hydrolyzed for 30 minutes after being primarily-hydrolyzed for an hour using 200 ml of distilled water. Whattman filter paper No. 44 was used to filter the material, which was then dried by air, oven, and weight. The KLC was determined as clear in Table 1.

V.

Ash Content (AC) of the W_h

The ASTM [84,87] was used to determine the AC of wood. The wood meal samples weighing about 2 g each that had been ground to pass through a No. 40 (425 um) sieve were gathered. Each sample was put into a porcelain crucible, dried in an oven at 103 ± 2 °C to a constant weight, and then weighed. In a tube furnace, the exposed crucible containing the sample was lit at 600 °C until all the carbon was burned off. It was then weighed after cooling in the desiccator. Up until the weight after cooling is constant to within 0.2 mg, the heating was repeated at 30 minute intervals. Based on the weight of the oven-dry wood meal, the proportion of residual containing ash was estimated (Table 1).

VI.

Gross Heat of Combustion (GHC) of the W_h

After preparing the GHC’s specimensas clear at Figure S1. the GHC of each of the healthy wood and the TNS was determined using an adiabatic oxygen bomb calorimeter, Parr 1341 in accordance with the ASTM [93] as well as the procedures stated by the Parr instruction manual as explained at Figure 1, Figure S1, and S3. The W_h samples were prepared according to the flowchart presented at Figure 1. Using a pellet press, model Parr 2811, each sample (0.8 g) designated for measuring GHC was formed into a pellet. The samples were dried in an oven and weighed. The calorimeter was calibrated using pellets of benzoic acid. Under carefully regulated circumstances, the sample was inserted in a metallic capsule and exploded within the oxygen bomb Parr 1108.

Using a mercurial thermometer (Parr 1603), temperature observations were recorded before, during, and after combustion. On a moisture-free basis, the heat generated by a sample’s combustion was estimated and converted into calories per grams. The estimates for the GHC included correction factors for the combustion of fusing wire and thermometer. On the other hand, because they are too minor to take into account, correction factors for the generation of nitric and sulfuric acids were not included in these calculations [94] and you can understand these calculations with their corrections through Table 1.

2.2.4. Sampling and Characterization of the Termite Nests Skeleton [TNS]

It was assumed that the majority of nests were built around mid of 2019/2020. In order to select the infested tree species and determining the termite nests’ locations within the trees, intensive monitoring of all lands within the ARS. The nests included numerous passageways and galleries with dense walls made primarily of organic residues arisen essential from the infested woody trees themselves as well as earth material transferred from beneath the infested trees-bearing the termite nests (Figure 3). Due to the majority of their apertures being on the western side, the nests appeared more wormer than the outer surrounding climate. For sampling, three replicates of each nest as well as reference soils were chosen according to Al-Ghamdi et al. [7] and Faragalla and Al Qhtani [8].

Termite nests were sampled at about 50 cm above the ground level. At each location, five 100 cm³-cores were used for the sampling process as explained at Figure S1b. Every sample was promptly air dried after collection. Regarding to physical and chemical characterization, the following properties were considered for the TNS:

2.2.4.1. Specific Gravity (SG) of the TNS

This SG, here, was determined in a dryness circumstance to keep the TNS’ construction to be intact as it is in the virgin termite nests without altering its SG.

Samples of the TNS were oven-dried to a constant weight at 103°±2 °C and weighed. Then, the oven-dry volume of each sample was determined by using Amsler volume meter filled with pure mercury. The SG of the TNS was calculated based on oven-dry weight and volume (Table 1).

2.2.4.2. Klason Lignin content (KLC) of the TNS

The KLC of the TNS was determined using the same KLC’s technique applied for the W_h samples, except for some modifications due to the difference between both materials (TNS and W_h) in their nature. Before determination of KLC of the TNS sample, its content of sand, ash and the organic matter other than lignin were discarded to get the pure KLC. For the sand particles, they were removed by saturation of the sample in a suitable amount of distilled water under fast stirring using and, after that the liquor was vacuum-filtered. The KLC of the TNS was calculated based on oven-dry weight (Table 1).

2.2.4.3. Total Organic Matter Content of the TNS

2.2.4.4. Total Minerals Content of the TNS

By thermal elimination of TOM, and we can estimate the minerals by subtraction. After sieving to ~2 mm and subsequent grinding with a ball mill, organic carbon (OC) was measured with an elemental analyzer (NA 2000, Fisons Instruments, Rodano, Milan, Italy). The minerals of some selected samples were characterized by X-ray diffraction (PW 1130, Philips, Almelo. The Netherlands).

2.2.4.5. Gross Heat of Combustion (GHC) of the TNS

The GHC of the TNS was determined using the same adiabatic oxygen bomb calorimeter used for the W_h. In addition, its samples’ preparation was applied according to Figure S1b, while its calculations with their corrections was illustrated at Table 1.

2.2.4.6. Mechanical Properties of the TNS

Specimens the TNS were used to examine strength of the TNS to best suggestion of using such TNS’ blend as a bioinspired composite materials in building sectors, especially at rural villages and tourist regions. Each TNS mass (see Figure 7, Figure S1) was sectioned into slices and samples were extracted from each slice according to Zachariah [95].

The stress–strain behaviors of the TNS collected from six infected tree species were measured using Instron universal testing machine, model 1193, Instron Co., Ltd., London, UK, with a 200 N-load cell according to the ASTM D–882 standard test, 1989. The device with two metallic grips was installed to hold the test sample at both ends. The starting grip separation for all samples was 50 mm, and the upper grip was extended at a constant rate of 50 mm per minute while the lower grip remained stationary. An automatic speed controller was fitted to the electrically powered machine to maintain the upper grip’s speed. The ambient temperature was used for all measurements. From the plot of stress–strain curves, the mechanical properties, namely, ultimate tensile strength (UCS) in MPa, modulus of elasticity (MoE) in MPa, and deformation at failure (EaF) as a percentage, were calculated (Table 1).

The ultimate compressive strength (UCS) of the TNS shows its maximum allowable compressive stress [-]. The UCS property was calculated by dividing the maximum load causing the failure of the TNS by the cross-sectional area of the specimen, as explained in Table 1.

The modulus of elasticity (MoE) is a reliable indicator of the TNS’ stiffness. The MoE was computed by dividing the stress at yield by length of the TNS’ specimen at yield, as expressed in Table 1.

Concerning to the deformation at failure (DaF) it was calculated by dividing the deformation at failure of the TNS’ specimen by the initial gauge length, as shown in Table 1.

Table 1. Calculation of different chemical and physical properties of the lignocellulosic resources used for construction of the termite nests found at Hada Al-Sham, Saudi Arabia.

Table 1. Calculation of different chemical and physical properties of the lignocellulosic resources used for construction of the termite nests found at Hada Al-Sham, Saudi Arabia.

Equation	Definitions
1 MChw, % = [(Wadhw − Wodhw) / Wodhw] × 100 2 MCtns, % = [(Wadtns − Wodtns) / WodTNS] × 100 3 SGw = Wodhw / Vshw 4 SGtnm = Wodtns / VodTNS 5 AC, % = (Wa / Wefhw) × 100 6 TEC, % = [(W1 - W2 )/W1 ] × 100 7 HC 8 KLC, % = (Wlr / Wefw) × 100 9 TOMS, % = 10 TOMN, % = 11 TMS, % = 12 TMN, % = 13 GHC, calories/g = [(t Ee) - e1 – e2 – e3] / Wodhw or WodTNS 14 t = tc - ta - r1 (b-a) - r2 (c-b) 15 e1 = = c1 if 0.0709N alkali was used for the titration. 16 e2 = (13.7×c2 )(Wodhw or WodTNS) 17 e3 = 2.3× c3  18 r1 = (Ta-Tb) / 5, calories/min. 19 r2 = (Td-Te) / 5}, calories/min.	Wadhw: Weight of air-dried healthy wood , g. Wodhw: Weight of oven-dried healthy wood, g. WadTNS: Weight of air-dried termite nest skeleton (TNS), g. WodTNS: Weight of oven-dried termite nest skeleton (TNS), g. Vshw = Volume of water-saturated healthy wood, cm3. VodTNS: Volume of oven-dried TNS, cm3. Wahw: Weight of ash matter of healthy wood. Wefhw = Weight of extractive-free oven-dried healthy wood meal, g. Wlr: Weight of lignin residues, g. WOMS: Weight of total organic matter in soil (open field), g. WOMN: Weight of total organic matter in TNS, g. WMS: Weight of minerals in soil (open field), g. WMN: Weight of minerals in nest, g. GHC: Gross heat of combustion, calorie/g. Ee = Energy equivalent of the calorimeter, determined under standardization e1: Thermochemical correction in calories for heat of formation of nitric acid (HNO3). e2: H2SO4. e3: Thermochemical correction in calories for heat of combustion of fuse wire. a: Time of combusting the sample. b: Time (to nearest 0.1 min.) when the temperature reaches 60 % of the total rise in temperature. c: Time at beginning of the post-period, whereby the rate of temperature change has become constant. c1: milliliters of standard alkali solution used in the acid titration c2: sulfur content in the sample, %. c3: centimeters of fuse wire consumed in firing. Ta: Temperature at time of combusting the sample Tb: Temperature at time of combusting the sample. Tc: Temperature at the point c (See the temperature rise curve, at the left side◦◦). Td: Initial temperature at the final period after combusting the sample. Te: Final temperature at the last period after combusting the sample. r1: rate (temperature units per minute) at which the temperature was rising during the 5-min. period before combusting the sample. r2: rate (temperature units per minute) at which the temperature was rising during the 5-min. period after time, where r1 and/or r2 = ‘+’ when the temperature is rising and ‘-‘when the temperature is falling.
20 Cs = Kλ/β1/2Cos θ 21 Ls = nλ / 2sinθ	K: The correction factor and usually taken to be 0.91 λ: The radiation wavelength of X-rays incident on the crystal (0.1542 nm). θ: The diffraction angle. β1/2: The corrected angular full width at FWHM. FWHM: The full width at half maximum of a XRD- peak. n: An ordinal number taking a value of “1” for diffractograms having the strongest intensity.
22 Compression strength = Ff/A 23 MoE = Stress/Strain at the PL = σ/ε 24 ε = [∆L/Lo] = [(Lf − Lo)/Lo] 25 EaF = ∆Lf = [(Lf − Lo)/Lo] × 100	Ff : Force at failure in Newton (N).
	A: Cross-section area (m2 ) of the Termite nest skeleton.
	σ: Compression stress (Pa).
	Lf : The length of the Termite nest skeleton at failure.
	Lo: The initial length of the Termite nest skeleton at failure.
26 d = WodTNS / VodTNS 27 P = 1 – (d/dp)	dp: Density of non-porous.

¹ Moisture content of healthy wood; ² Moisture content of termite nest skeleton; ³ Specific gravity of healthy wood; ⁴ Specific gravity of termite nest skeleton; ⁵ Ash content of healthy wood; ⁶ Total extractives content of healthy wood; ⁷ Holocelluloses content of healthy wood; ⁸ Klason lignin content of healthy wood; ⁹ Total organic matter in soil; ¹⁰ Total organic matter in TNS; ¹¹ Total minerals in soil; ¹² Total minerals in TNS; ¹³ Gross heat of combustion of healthy wood; ¹⁴ Temperature rise; ¹⁵ Correction for heat of formation of nitric acid; ¹⁶ Correction for heat of formation of sulfuric acid; ¹⁷ Correction for heat of formation of the nickel chromium-fuse wire; ¹⁸ Temperature rate for preperiod of combustion; ¹⁹ Temperature rate for post-period of combustion; ²⁰ Crystallite size, nm using Scherer equation with respect to the crystallographic plane (CP) of ‘002’; ²¹ Lattice spacing, nm using the Bragg’s equation at CP of 002; ²² Tensile strength (MPa), ²³ Modulus of elasticity (GPa), ²⁴ Tensile strain, ²⁵ Elongation at failure (%); ²⁶ Real density of the TNS; ²⁷ Porosity.

• The Micro- and Nanometric-Scaled Materials

Microcrystalline Cellulose (MCC) represents the micrometric-scaled polymeric materials in the termite nest skeleton (TNS), while nanocrystalline cellulose (NCC) is the famous nanoparticles assemblies the TNS that were discovered for the first time throughout humanity’s history.

• Characterization

MCCs and NCCs samples were assigned to XRD, FTIR, SEM and TEM investigations. For the XRD, FTIR, since their micrometric-scaled samples must be a fine powdered form, they were ground in a ball mill to passes through a 100 mesh and be retained on a 120 mesh. On the other hand, for each of the MCC and NCC samples specified for SEM and TEM spectroscopic studies, a thin film of each individual solution was required for each characterization. This solution was prepared from each powder type that was completely dissolved in an absolute ethanol by assistance of sonication.

I.

Scanning Electron Microscopy (SEM)

SEM study was used to study the surface morphology and types of anatomical features in the tangential plane samples of leaflet tissue as well as the SCNCs. The samples were placed on the double side carbon tape on Al-stub and dried in air. Before examination, all samples were sputtered with a 15 nm thick gold layer [JEOL JFC- 1600 Auto Fine Coater] in a vacuum chamber. The sample s were examined with a SEM Quanta FEG 450, FEI, Amsterdam, Netherland. The microscope was operated at an accelerating voltage ranged from 5-20 kV.

II.

Transmission Electron Microscopy (TEM)

This characterization was examined by TEM (JEM-1011 JEOL, Japan). The suspension was sampled by using a capillary pipet and dropped onto the copper grid. After being dried for 3 min at ambient condition, filter paper was used to remove the excess liquid on the copper grid. Afterwards, the dye liquor of phosphotungstic acid was dropped and dyed for 2 min. The dried sample was prepared for observed. The operated voltage was at 100 kV.

III.

Fourier Transform Infrared (FTIR) Spectroscopy

Chemical structure (functional groups) of the parent alpha as well as the cellulose-based products (MCC and NCC) were investigated by the FTIR using a Bruker Tensor 37 FTIR spectrophotometer. The samples were oven-dried at 100°C for 4-5 h, mixed with KBr in a ratio of 1:200 (w/w) and pressed under vacuum to form pellets. The FTIR-spectra of the samples were recorded in the transmittance mode in the range of 4000-500 cm^-1 [70,71].

IV.

The X-Ray Diffraction (XRD)

The X-ray powder diffraction spectra of the fibers were used to study the crystallinity of the using the XRD-D₂ Phaser Bruker (USA). The generator was operated at 30 KV and 30 mA. The samples were exposed for a period of 3000s using CuKa radiation with a wavelength of 0.15418 nm. All the experiments were performed in the reflection mode at a scan speed of 4° /min in steps of 0.05°. All samples were scanned in a 2θ=26° range varying from 4° to 30°. The crystallinity index individual crystalline peaks were first extracted by a curve-fitting process from the diffraction intensity profiles [70,71,97]. The CI was calculated by dividing the diffractogram area of crystalline cellulose by the total area of the original diffractogram. The area under the curve was estimated by summing of adjacent trapezoids using Excel (Microsoft, USA) as indicated by Hindi [70,71,93].

• Statistical Design and analysis

Differences between groups were examined with an analysis of variance (ANOVA), and the LSD0.05 test for comparisons of the mean values. The significance level was set at P < 0.05. The ANOVA was conducted with SPSS 14.0 (SPSS Inc., 2005, Chicago, USA) as illustrated by El-Nakhlawy [98].

3. Results and Discussion

3.1. Climate

3.1.1. Climate at Hada Al-Sham

Concerning to the most important parameters dominant at Hada Al-Sham region collected from the local meteorological station, their mean values were presented at Table 2. Since January was the coldest month throughout the investigation period (October 2019-August 2021) that stresses termites due to low temperatures, the meteorological data of this month are presented at Table 2.

Table 2. Climate at Hada Al-Sham: Air temperature (AT), soil temperature (ST), income and outcome radiation for each of shortwave and longwave, wind speed (WS), wind direction (WD), barometric pressure (BP) during January 2021.

Table 2. Climate at Hada Al-Sham: Air temperature (AT), soil temperature (ST), income and outcome radiation for each of shortwave and longwave, wind speed (WS), wind direction (WD), barometric pressure (BP) during January 2021.

Property	Height	Mean	Max	Min
Air temperature, ◦C at:	2 m	24.69	33.29	14.56
	5 m	24.75	32.7	15.85
	10 m	22.63	63.91	-0.683
Soil temperature at 50 cm, °C		28.79	31.37	27.93
Radiation wavelength	Income shortwave	33.79	143.3	-0.029
	Income longwave	6.26	41.76	-9.39
	Outcome shortwave	184.53	837	-6.451
	Outcome longwave	-42.579	-3.387	-84.1
Wind speed at 10 m, m/sec		2.38	11.66	0
Wind direction at 10 m, degrees		159.52	353.6	0.071
Barometric pressure, mbar		988.08	993	983

¹ N=1492.

3.1.2. Internal Temperature within the Termite Nests

Concerning to the conditioning status within the termite nest, the internal temperature (IT) of the nest and the outer temperature (OT) of the surrounding atmosphere were monitored, measured and plotted against time in six hours intervals during the period extended from October, 2018 up to the end of August 2020 as shown in Figure 2.

The eleven months included for the temperature measurements were October 2019, November 2019, December 2019, January 2020, February 2020, March 2020, April 2020, May 2020, June 2020, July 2020, and August 2020 as shown in Figure 2.

The obtained histograms matched the historical temperature data in which the minimal values of January is the coldest month, and the months from October to April are colder than the summer months. This thermal behavior adapted that resulted at Figure 3.

The IT was found to be milder than those for their analogous values for the outer environment, namely outer temperature (OT). For more simplifying, the IT was wormer than OT during cold durations, while it was colder than the hottest OT in hot days and vice versa [99,100]. Moreover, the IT wax exceeded more than its average level towered higher temperatures. This response is identical for all the eleven graphs representing the 11^th months of the measuring period. This common trend indicates that termites prefer wormer atmospheres other than the colder one, that is expected that coldest nest may affects termite members’ activity, especially their youngs.

Figure 3. Mean values of temperature measurements (T, °C) of the air about 2 m above the ground level, (—),the zigzag line and inside the termite nest, the slightly waved line (------) throughout eleven months (October-August) during 2019-2021 for the open atmosphere and within the termite nests engraved in the infected trunk of Zizyphus spina Christi grown at Hada Al-Sham village, Makkah Province, Saudi Arabia (each value is an average of two observations: The starting record is 12 am): (a) October 2019, (b) November 2019, (c) December 2019, (d) January 2020, (e) February 2020, (f) March 2020, (g) April 2020, (h) May 2020, (i) June 2020, (j) July 2020, (k) August 2020.

Figure 3. Mean values of temperature measurements (T, °C) of the air about 2 m above the ground level, (—),the zigzag line and inside the termite nest, the slightly waved line (------) throughout eleven months (October-August) during 2019-2021 for the open atmosphere and within the termite nests engraved in the infected trunk of Zizyphus spina Christi grown at Hada Al-Sham village, Makkah Province, Saudi Arabia (each value is an average of two observations: The starting record is 12 am): (a) October 2019, (b) November 2019, (c) December 2019, (d) January 2020, (e) February 2020, (f) March 2020, (g) April 2020, (h) May 2020, (i) June 2020, (j) July 2020, (k) August 2020.

3.2. Soil

3.2.1. Physical and chemical properties [101,102]

Clay, silt and sand contents, texture class, bulk density, air porosity, organic matter content (OMC), EC, and pH of the soil collected just beneath the six infected tree species are presented at Table 3.

3.2.2. Particle Size Distribution of the Parent Soil

It can be seen from Figure 4 that the parent soils collected outside the termite nests just beneath each tree of the six species have highest fractions of the coarse particles [˃ 425µ] for both Tamarix nilotica and Zizyphus spina Christ. On the other hand for the other four species sites, their major soil particles fractions are between 125-300 µ followed those higher than 425 µ. It was think that using coarser soil particles in the mortar blended with fine particles of organic materials, lignin and nanocellulose (MCC, NCC) allow to fabricate more permeable TNS featured by its high gas exchanging.

3.2.3. Electrical Conductivity (EC) of Soil

It can be seen from Figure 5 that EC of the soil particles used to construct the termite nest was found to be higher than that for the parent soil collected just beneath each of the six infected tree species.

3.2.4. Calcium Carbonate in the Parent Soil

CaCO₃ compound is found naturally in the soil composition, else that belonging to the open field close to the infected tree or those collected from the nest mortar used to blend the TNS. Since this chemical compound is well known by its binding behavior, termites extract it from soil using it to enhance the TNS’ rigidity without reducing the TNS’ porosity.

3.4. The Termite Nests

3.4.1. The Termite Colony

The small Najdian Termite, Microtermes najdensis [7,9,111,112] is shown in Figure 2.

Figure 7. The studied the Najdian Termite, Microtermes najdensis: (a) their life cycle; (b) the workers within a living infected trunk of Zizyphus spina christi.

Figure 7. The studied the Najdian Termite, Microtermes najdensis: (a) their life cycle; (b) the workers within a living infected trunk of Zizyphus spina christi.

Male and female winged shed Queen King Eggs Immature forms Queen Secondary

Queen King Developing winged forms Winged reproductive “alatase” Reproductive

Soldier Worker

3.4.2. The Termite Nest Skeleton (TNS)

Forty widely distributed species were surveyed in Hada Al-Sham and were found to be infected by this insect. The most dominant infected plants by this pest were Tamarix aphylla, Pithecellobium duce, Zizyphus spina christi, Leucaena leucocephala, Ficus infectoria, and Phoenix dactylifera.

The infection aspects of Zizyphus spina Christi’ s wood infected by the Najdian Termite, Microtermes najdensis are shown in Figure 8. It can be seen from Figure 8a that termite started to infect the sapwood, other than the heartwood of the infected log. This aspect is attributed to that heartwood is more enduring to the termites’ infestation due to its high content of the organic extractives comparing to the sapwood. In addition, bark of the infected Zizyphus tree was swollen and peeled easily due to prominent of the tunnelS shielded by a ceiling made up of a thick layer of the mortar. In addition, huge number of entryways noticed at the southwest direction. This direction was not selected by termites fortuitously, but they allowed their nests to have better aeration and more efficient gas exchange achievement.

3.4.2.1. Mineral Matter (MM) of the TNS

I. Particle size (PS)

It can be seen from Figure 9 that the parent soils collected outside the termite nests just beneath each tree of the six species have highest fractions of the coarse particles [˃ 425µ] for both Tamarix nilotica and Zizyphus spina Christ. On the other hand for the other four species sites, their major soil particles fractions are between 125-300 µ followed those higher than 425 µ

II. Organic Matter Content (OMC) M_iC of the TNS

The mineral content that was determined according to the related standard methods of the nest mortar ranged from 84.1 % for Phoenix dactylifera to 92.3 % for Pithecellobium duce (Figure 10). In addition, it can be seen that the minerals are considered as the most abundant constituent of the termite nest mortar. These results are in adaptance with those indicated by Ptáček et al. [47], and Rückamp et al. [66].

The OMC of the nest mortar was ranged from 7.7 % for Pithecellobium duce to 15.9 % for Phoenix dactylifera (Figure 10). There is no correlation relationship between the OMC and the lignin content of wood.

III. Lignin content in the nest mortar

Lignin, the organic macromolecule constituting about 20-30 % of the secondary cell wall of wood. It is worth for mentioning that termites feeding on wood use the easily degradable cellulose components rather than lignin as carbon and energy source. Since lignin resists degradation by most termite species, it could be a prominent tracer of the organic matter incorporated into termite nests and released into nest surroundings [66].

It can be seen from Figure 11 the allocation of both organic matter content (OMC) and the Klason lignin content (KLC) from old nests (KLC-O) and recent nests (KLC-R) skeletons within the trunks of the six infected tree species, namely Tamarix aphylla, Pithecellobium duce, Zizyphus spina Christi, Leucaena leucocephala, Ficus infectoria, and Phoenix dactylifera.

Higher values of the lignin contents within the recent built nests can be revealed to that lignin content of the nests is detereorated as they increased in age.

Both, OMC and KLS contents were higher in termite nests than those of the reference soil (Table 3 and Figure 11). The KLC was even more enriched than OMC in the termite nest mortar. This is due to termites use lignin as the main organic binding agent in the nest mortar.

The relationship between the KLC of each of W_h and TNS

3.5. Nanocelluloses Reinforcing the TNS

The nanometric-cellulosic materials (MCC, NCC) were surprised to be synthesized naturally by the act of hydrolyzing enzymes of the fungal communities and/or the termites’ digestion detected within the termites’ nest skeletons (TNS) within each of the six infected tree species.

The TNS’ samples were examined spectroscopically by SEM technique in order to speculate their surface morphology and types of anatomical features as presented at Figure 14 (for the MCC’s microparticles) and Figure 14 (for the NCC’s nanoparticles [70,71].

3.5.1. Microcrystalline cellulose (MCC)

Depending on Hindi [68,69], excess investigation of the six TNS specimens collected from the six tree species was achieved. In addition, SEM, FTIR, XRD examinations were performed to confirm presence of the MCC in the nest’s mortar as a secondary binder agent.

The obtained data of the MCC material were presented at Figure 14, Figure 16, and Figure 17 for SEM, FTIR, and XRD, respectively. All the above-mentioned analyses tools confirmed that the micrometric particles detected were MCCs.

Concerning to the SEM micrographs shown in Figure 14, all the six subfigures (a-f) are presented in a micrometric scale ranged gradually from 50 µm (Tamarix aphylla, Pithecellobium duce, and Leucaena leucocephala), 100 µm (Phoenix dactylifera), 200 µm (Zizyphus spina Christi), and 400 µm for Ficus infectoria. This difference in magnification between the subfigures can be attributed to our trial to reach the best resolution. Moreover, we think that the SEM’ dimensions for both MCC and NCC were less accurate to depend on comparing to the other tools (FTIR AND XRD). This difference in accuracy for the SEM’s image dimensions is attributed to the crystal growth phenomenon discovered previously by Hindi [70,71] for NCC

3.5.2. Nanocrystalline Cellulose (NCC)

This difference in accuracy for the SEM’s image dimensions is attributed to the crystal growth phenomenon discovered previously by Hindi [70,71] for NCC

It can be seen from Figure 15 that the scale bar of the six SEM’s images for the NCCs ranged from 100 nm to 500 nm [68-76,113]. For first scond, these dimensions are greater than those legally accepted according to Hindi [68] who reported that nanocellulose must have at least one dimension less than 100 nanometers in size. Really, we found that the NCC’s dimension always starting from about 5 nm, and after that the nanoparticle’s dimension increases through a self process termed as grystal growth [70,71]. This crystal development process from nano- to micrometric size demonstrated the NCCs' aptitude for self-organization, or so-called self-assembly. It was discovered that after about 30 minutes of spreading a drop of the hydrolysis supernant onto the sample’s stup of the SEM microscope, the NCCs spherulites were agglomerated into larger aggregates of colloidal state, which were then aligned straightly to form needle-shaped architectures.

The driving force for this crystal growth process can be limited to the following effects: a) electrostatic forces on the NCCs surfaces due to the grafted functional groups (protons, sulfate, and hydroxyl), b) the concentration gradient of the fungal communities' hydrolyzing enzymes and/or termite digestion, and c) the difference in surface tensions of solution, air, and glass. The net force produced at this interaction is thought to be the driving force behind the NCCs-crystal formation process. As a result, the needles were conceived to be created through electrostatic end-to-end attraction and subsequent self-welding of small NCC particles into larger ones [68,70-73]. However, it can be noticed from Figure 15 that there are a wide variation in particle size of the NCCs that confirms our theory of the NCC’s crystal grows.

Moreover, since the presence of the nanocelluloses incorporated within the TNS’ mortar was dicovered for the first time, it was expected that this phenomenon is one of the important reasons that strengthen the TNS that help them to endure different environment stresses.

Figure 15. TEM micrographs of the nanocrystalline cellulose (NCC) synthesized naturally by termites’ enzymatic hydrolysis of cellulose as detected in the termit nest skeleton (TNS) within the six infected tree species: (a) Tamarix aphylla, (b) Pithecellobium duce, (c) Zizyphus spina Christi, (d) Leucaena leucocephala, (e) Ficus infectoria, and (f) Phoenix dactylifera.

Figure 15. TEM micrographs of the nanocrystalline cellulose (NCC) synthesized naturally by termites’ enzymatic hydrolysis of cellulose as detected in the termit nest skeleton (TNS) within the six infected tree species: (a) Tamarix aphylla, (b) Pithecellobium duce, (c) Zizyphus spina Christi, (d) Leucaena leucocephala, (e) Ficus infectoria, and (f) Phoenix dactylifera.

FTIR

The FTIR’s spectrum of each alpha cellulose (C_α) and its nanocelluloses products, namely microcrystalline cellulose (MCC) and nanocrystalline cellulose (NCC) for the six tree species examined are presented at Figure 16. Moreover, the scientific illustration of arising these spectra were concluded at Table 5. showing the absorption bands of chemical (functional) groups featuring the examined cellulosic materials. Actually, all the samples exhibited two main absorbance regions detected ( 800–1800 cm⁻¹ and 2800–3500 cm⁻¹). The FTIR spectra of all samples have shown sharp bands around the wavenumbers [70,71] presented at Table 5.

Based on the FTIR’S spectral data for C, MCC and NCC materials arisen from each of the six tree species (Figure 16), it can be confirmed that the principle constituent of the three cellulosic materials (C_α, MCC, NCC) were similar to each others which means that the nanometric particles detected (MCC and NCC) were nanocelluloses.

Figure 16. Fourier transform infrared (FTIR) spectra of the alpha cellulose (C_α), microcrystalline cellulose (MCC), nanocrystalline cellulose (NCC) within the six infected tree species: (a) Tamarix aphylla, (b) Pithecellobium duce, (c) Zizyphus spina Christi, (d) Leucaena leucocephala, (e) Ficus infectoria, and (f) Phoenix dactylifera.

Figure 16. Fourier transform infrared (FTIR) spectra of the alpha cellulose (C_α), microcrystalline cellulose (MCC), nanocrystalline cellulose (NCC) within the six infected tree species: (a) Tamarix aphylla, (b) Pithecellobium duce, (c) Zizyphus spina Christi, (d) Leucaena leucocephala, (e) Ficus infectoria, and (f) Phoenix dactylifera.

The above mentioned explanation of the originality of both MCC and NCC from cellulose can be extended through studying their FTIR-bands (Figure 16) and reasons of their arrisen at certain wavenumbers (Table 5) as indicated by Hindi [69-71].

XRD

As clear in Figure 17 for the crystallographic findings, the crystallinity index was increased from crude wood passing through alpha cellulose, MCC and, finally ended by the NCC. This finding, also, confirms the presence of the nanocellulose in the six mortar blends as a result of enzymatic hydrolysis occuring by termits and/or fungi during their feeding and constructing their nests.

Figure 17. X-ray Diffractogram (XRD) of the healthy wood (W_h), alpha cellulose (C_α), microcrystalline cellulose (MCC), nanocrystalline cellulose (NCC) within the six infected tree species: (a) Tamarix aphylla, (b) Pithecellobium duce, (c) Zizyphus spina Christi, (d) Leucaena leucocephala, (e) Ficus infectoria, and (f) Phoenix dactylifera.

Figure 17. X-ray Diffractogram (XRD) of the healthy wood (W_h), alpha cellulose (C_α), microcrystalline cellulose (MCC), nanocrystalline cellulose (NCC) within the six infected tree species: (a) Tamarix aphylla, (b) Pithecellobium duce, (c) Zizyphus spina Christi, (d) Leucaena leucocephala, (e) Ficus infectoria, and (f) Phoenix dactylifera.

4. Conclusions and Future Perspectives

Nomenclature

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