Relating Water Use to Tree Vitality of Populus Euphratica Oliv. in the Lower Tarim River, NW China

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Article Relating Water Use to Tree Vitality of Populus euphratica Oliv. in the Lower Tarim River, NW China

Maierdang Keyimu 1, Ümüt Halik 1,2,* and Aihemaitijiang Rouzi 1

1 Key Laboratory of Oasis Ecology, College of Resources and Environmental Science, Xinjiang University, Shengli Road, No. 666, Urumqi 830046, China; [email protected] (M.K.); [email protected] (A.R.) 2 Faculty of Mathematics and Geography, Catholic University of Eichstaett-Ingolstadt, Osten str. 14, 85072 Eichstaett, Germany * Correspondence: [email protected] or [email protected]; Tel.: +86-991-858-1102

Received: 4 June 2017; Accepted: 17 August 2017; Published: 19 August 2017

Abstract: This study aimed to compare the hydraulic characteristics of different vitalities of Populus euphratica to reveal the differences in their water use strategies and water consumption to provide useful data to scale water use of riparian poplar forests in the lower reaches of the Tarim River, Northwestern China. Our results showed that the sapwood area of P. euphratica could be estimated based on its correlation with tree biometric parameters. The sapwood area of vital poplars tended to be larger than the senesced poplar despite both having the same diameter at breast height. This indicates that poplar vitality should be taken into account when estimating its sapwood area. Therefore, we established two different sapwood area estimation models for vital and senesced poplar (sapwood area = 1.452 × DBH1.553, R2 = 0.891; sapwood area = 0.915 × DBH1.618, R2 = 0.718; DBH: diameter at breast height). The sap flow process of vital and senesced poplar had certain differences and similarities; the average diurnal sap flow velocity and water consumption of vital poplar were 15.85 cm/h and 45.95 L, respectively; for the senesced poplar, it was 9.64 cm/h and 18.17 L, respectively, which were smaller than that of vital poplars. The influence of environmental factors on the sap flow velocity of two different P. euphratica was similar; the sap flow of both vital and senesced poplar had positive correlation with air temperature (R2 = 0.800 and 0.851), solar radiation (R2 = 0.732 and 0.778), vapor pressure deficit (R2 = 0.508 and 0.643) and groundwater depth (R2 = 0.301 and 0.171), while negative correlation with air humidity (R2 = −0.313 and −0.478).

Keywords: Populus euphratica; tree vitality; sapwood area; water consumption; environmental factors

1. Introduction Heterogeneous environmental conditions influence the hydraulic characteristics of vegetation. Water availability is one of the most important factors influencing the growth and development of plants [1]. Related studies have indicated that the structure of the plant hydraulic system has the potential to limit water flow through its body, thus restricting its water balance, and eventually its growth [2]. Therefore, studying the differences in the hydraulic characteristics of plants of different vitality may help us understand the influence of water availability on tree growth. The Tarim River, located along the northern rim of the Taklamakan Desert in the Xinjiang Uighur Autonomous Region, Northwestern China. It is one of the longest inland water ways in the world along with the Volga, Syr Darya, Amu Darya, and the Ural [3–6]. The riparian forests at the Tarim are an important ecosystem which plays a key role in maintaining the structure, function and stability of the arid ecosystem [7,8].

Water 2017, 9, 622; doi:10.3390/w9080622 www.mdpi.com/journal/water Water 2017, 9, 622 2 of 14

Populus euphratica Oliv. is a rare, ancient, and endangered tree species which forms the floodplain forest ecosystem in inland river basins in central Asian arid regions [9,10]. Given its high capacity against environmental stressors, e.g., saline, high temperature, drought and sand storms, it plays an irreplaceable function in these areas [11–14]. However, due to the irrational water allocation along the upper and middle reaches of the Tarim River, the lower reaches (ca. 320 km) has been cut off since 1970. This has resulted in a decrease in the groundwater level along the lower Tarim [4,15,16], and the eventual degradation of the riparian ecosystem [6,12,17,18]. Since 2000, the Ecological Water Diversion to the lower Tarim River was started to restore the degraded ecosystem of this region, and a number of studies have shown that the riparian forest has demonstrated a positive response to the water diversion [12,13,19,20]. However, in terms of water shortage in this region, the insurance of long-term water transferring and the virtuous cycle of ecological environment depends on the rational and efficient usage of limited water resources, which includes the scientific allocation of water for irrigated agriculture, nature and ecosystem conservation, as well as for industry, oasis settlements and human well-being [4,21–24]. Therefore, it is important to estimate the water use of riparian forests in the lower Tarim River for providing scientific reference to the water management authorities. Different upscaling methods have been reported for estimating the water use of poplar forests [25–27]; however, these methods did not consider the vitality of poplar trees. The objectives of this study were to assess and compare the hydraulic characteristics of Populus euphratica of different vitalities by monitoring the diurnal changes of its sap flow during hot sunny days, measuring and estimating the area of water conducting tissue, as well as analyzing the correlation between sap flow velocity and environmental factors. These experiments were carried out on poplar trees of different vitalities growing at two sites with different groundwater conditions. There is evidence from the literature that the sapwood area of the poplar tree can be estimated based on the correlation between the sapwood area and tree biometric parameters [25,27]; furthermore, the water consumption of poplar trees at stand level could be obtained by upscaling methods based on the sap flow measurement of sample trees [26,28], but little information is available regarding the water consumption of poplar trees at different vitalities. This knowledge is of particular importance when estimating whole tree water usage in this region more accurately.

2. Materials and Methods

2.1. Study Area The study area was located at the lower reaches of the Tarim River (Arghan, 40◦08050” N, 88◦21028” E), between the Taklamakan and Kuruktagh Deserts in the southern part of the Xinjiang Uighur Autonomous Region, Northwestern China (Figure1). The region is within an extremely arid warm temperate zone, with an annual precipitation from 17 to 42 mm and a potential evaporation of approximately 2500–3000 mm [4,11,17], rendering this area one of the most hyper arid places in the world [10,27,29]. The average groundwater depth beside the riverbank is low, thus can only support vegetation types with a higher drought resistance [29,30]. Therefore, desert riparian vegetation has a relatively simple structure along the river. The main tree species are Populus euphratica Oliv., Elaeagnus angustifolia L; and the main shrubs are Tamarix hispida Willd., Tamarix elongata Ledeb., Tamarix ramosissima Ledeb., Halimodendron halodendron (Pall.) Voss., Lycium ruthenicum Murr., Karelinia caspica (Pall.) Less., Hexinia polydichotoma (Ostent.) H.L., Inula salsoloides (Turcz.) Ostrnf., Phragmites communis, Poacynum hendersonii (Hook. F.) Woodson., Halostachys caspica (M.B.) C.A. Mey., Alhagi sparsifolia (B.Keller et Shap.) Shap. and Glycyrrhiza inﬂate Bat. [10–12,16]. Water 2017, 9, 622 3 of 14 Water 2017, 9, 622 3 of 14

Figure 1. The lower reaches of the Tarim River and the study area Arghan [10]. Figure 1. The lower reaches of the Tarim River and the study area Arghan [10]. 2.2. Sample Selection and Measurement 2.2. Sample Selection and Measurement Based on the vitality classification criteria of Halik et al. [12] and Aishan et al. [20], Populus Basedeuphratica on of different the vitality vitality classiﬁcation status were chosen criteria. Vital ofpoplar Halik sample et trees al. [ were12] andlocated Aishan at 40°08 et′44″ al.N, [20], Populus88°20 euphratica′59″ E; senescedof different poplar vitalitytrees were status located were at 40°08 chosen.′07″ VitalN, 88°21′ poplar44″ E. sample Three sample trees were trees locatedwere at 40◦08selected044” N, from 88◦20 each059” plot E; senesced to run sap poplar flow measurement trees were locateds. Sapwood at 40 samples◦08007” were N, 88 taken◦21044” from E. 91 Three vital sampleP. euphratica and 78 senesced P. euphratica using an increment borer, in addition, their biometric trees were selected from each plot to run sap ﬂow measurements. Sapwood samples were taken from parameters (DBH: Diameter at breast height, CD: Crown diameter and TH: Tree height) were 91 vital P. euphratica and 78 senesced P. euphratica using an increment borer, in addition, their biometric measured to run modeling analysis for estimating the sapwood area and model validation. Table 1 parametersshows a (DBH: summary Diameter of the statistics at breast of height, the poplar CD: trees Crown used diameter for sapwood and TH:sampling. Tree height) were measured to run modeling analysis for estimating the sapwood area and model validation. Table1 shows a summary of the statisticsTable 1. Summary of the poplar statistics trees of poplar used trees for with sapwood vital and sampling. senesced growth status. Tree Parameters DBH (cm) TH (m) CD (m) Sapwood Area (cm2) VitalityTable Status 1. SummaryVital statisticsSenesced of poplarVital treesSenesced with vitalVital and senescedSenesced growth Vital status. Senesced Number of samples 91 78 91 78 91 78 91 78 Tree ParametersAverage 21.5 DBH (cm)21.2 8.3 TH (m)6.5 4.9 CD (m)4.4 175.6Sapwood Area130.8 (cm 2) VitalityMax Status Vital53.1 Senesced35.4 Vital13.0 Senesced10.0 Vital8.5 Senesced7.2 822.5 Vital 332.6 Senesced Min 7.4 9.0 2.6 2.9 2.0 1.8 18.4 18.2 Number of samples 91 78 91 78 91 78 91 78 AverageNote: DBH 21.5 = diameter 21.2 at breast 8.3 height, TH 6.5 = tree height, 4.9 CD = crown 4.4 diameter. 175.6 130.8 Max 53.1 35.4 13.0 10.0 8.5 7.2 822.5 332.6 Min 7.4 9.0 2.6 2.9 2.0 1.8 18.4 18.2 Note: DBH = diameter at breast height, TH = tree height, CD = crown diameter. Water 2017, 9, 622 4 of 14 Water 2017, 9, 622 4 of 14 To calculate the sapwood area of the poplar stem, we assumed that the tree stem was circular, that theTo calculatesapwoodthe and sapwood the inner area wood of theareas poplar were stem, in the we shape assumed of concentric that the treecircles, stem and was the circular, outer circlethat the represented sapwood andthe sapwood the inner woodarea (Figure areas were 2a). inThe the sapwood shape of of concentric P. euphratica circles, is easy and to the differentiate outer circle fromrepresented the inner the wood sapwood when area the (Figure sample2a). is Thefresh sapwood (Figure 2b of),P. and euphratica can usuallyis easy be to observed differentiate with from the nakedthe inner eye wood. when the sample is fresh (Figure2b), and can usually be observed with the naked eye.

(a)

(b)

Figure 2. Sapwood and and inner inner wood wood of of the the tree tree stem stem where where ( (aa)) t thehe blue blue colored colored part part is is the the sapwood, sapwood, and the green colored part part is is the inner wood wood;; ( (b)) the the white white area area on the left is is the sapwood, the the dark dark area on the right is inner wood of P. euphraticaeuphratica..

The following equation is for calculating the sapwood area: The following equation is for calculating the sapwood area: 2 d d 2 sapwood area = π ×d 2 − π × (d − sapwood depth) 2 (1) sapwood area = π × 2 − π × ( 2 − sapwood depth) (1) 2 2 where π is the mathematical constant (3.14), and d is the diameter of tree at breast height. where π is the mathematical constant (3.14), and d is the diameter of tree at breast height. 2.3. Sap Flow Measurement 2.3. Sap Flow Measurement A SFM1 sap flow meter (ICT, Armidale, NSW, Australia) that utilized the heat ratio method (HRM)A SFM1was used sapﬂow to record meter heat (ICT, pulse Armidale, velocity NSW, (Vh Australia)) at 15 min that intervals utilized thefor heatthe period ratio method from 1 (HRM) to 10 Septemberwas used to 2015 record. The heat installation pulse velocity and (Vh sensor) at 15 design min intervals were identical for the period to descriptions from 1 to 10 provided September in Pfautsch2015. The et installation al. [31] and and Keyimu sensor et design al. [32] were. identical to descriptions provided in Pfautsch et al. [31] and Keyimu et al. [32]. 2.4. Meteorological Data 2.4. Meteorological Data Meteorological parameters, such as Rs (solar radiation), Ta (air temperature), RH (air humidity) Meteorological parameters, such as R (solar radiation), T (air temperature), RH (air humidity) were collected from the corresponding sensorss (Watchdog 2000a , Spectrum Co. Ltd., Selmer, TN, were collected from the corresponding sensors (Watchdog 2000, Spectrum Co. Ltd., Selmer, TN, USA). USA). The parameters were recorded at 1 h intervals; data read out was completed using Spec ware The parameters were recorded at 1 h intervals; data read out was completed using Spec ware software. software. Vapor pressure deficit (VPD) was calculated using the following equation [33]: Vapor pressure deﬁcit (VPD) was calculated using the following equation [33]: 푅퐻 푉푃퐷 = (1 − ) × 푒푎∗ (2) 100RH VPD = 1 − × ea∗ (2) where RH is air humidity, ea* is vapor pressure. ea* is100 obtained using the following equation [34]: 푇푎 where RH is air humidity, ea* is vapor pressure. ea* is( obtained푏 × ) using the following equation [34]: 푒푎∗ = 푎 × 퐸푋푃 푇푎 + 푐 (3)

∗ (b× Ta ) ea = a × EXP Ta+c (3)

Water 2017, 9, 622 5 of 14 where Ta is air temperature, and the values of parameters a, b, and c are 0.611 kPa, 17.502, and 237.3Water◦C, 2017 respectively., 9, 622 5 of 14

2.5.where Groundwater Ta is airData temperature, and the values of parameters a, b, and c are 0.611 kPa, 17.502, and 237.3 °C , respectively. The groundwater depth (GWD) measurement was carried out simultaneously with sap flow measurement2.5. Groundwater using Data aDiver data logger (Schlumberger Limited, Paris, France) at two different sites. LoggerThe groundwater installation, depth sensor (GWD design) measurement and measurement was carried principles out simultaneously were provided with sap in detail flow in Keilholzmeasurement et al. [24 using,35]. a Diver data logger (Schlumberger Limited, Paris, France) at two different sites. Logger installation, sensor design and measurement principles were provided in detail in Keilholz 2.6.et Data al. [24,3 Processing5]. A sap flow tool (ICT International, Armidale, NSW, Australia) was utilized to process the raw 2.6. Data Processing sap flow data, calculate the sap flow velocity, and water consumption. The number of trees and their biometricA parameterssap flow tool data (ICT as International, well as sapwood Armidale area, calculation NSW, Australia were) processedwas utilized by to Microsoft process the Excel raw 2015 software.sap flow Sapwood data, calculate area estimation the sap flow models velocity, for and both water vital consumption. and senesced TheP. number euphratica of treeswere and created their by selectingbiometric the sapwoodparameters area data as as a dependentwell as sapwood variable, area andcalculation DBH, crown were processed diameter, by and Microsoft tree height Excel as the independent2015 software variables.. Sapwood Regression area estimation models models between for both sap vital flow and and senesced meteorological P. euphratica parameters were created were by selecting the sapwood area as a dependent variable, and DBH, crown diameter, and tree height as established by selecting the VPD, RH, Ta, Rs, and GWD as the independent variables and sap flow rate the independent variables. Regression models between sap flow and meteorological parameters were as the dependent variable. Modeling analysis was carried out using the SPSS statistical tool 20.0 (IBM, established by selecting the VPD, RH, Ta, Rs, and GWD as the independent variables and sap flow Armonk,rate as NY, the USA).dependent Paired variable.t-test wasModeling conducted analysis for was validating carried out the using sapwood the SPSS area statistical estimation tool model 20.0 at p ≤ (0.05IBM, significance Armonk, NY, level. USA All). Paired plotting t-test was was carried conducted out onfor Microsoft validating Excelthe sapwood 2015. area estimation model at p ≤ 0.05 significance level. All plotting was carried out on Microsoft Excel 2015. 3. Results 3. Results 3.1. Sapwood Area of P. euphratica with Different Vitality 3.1.In Sapwood the first A plot,rea of theP. euphratica results showed with Different that DBHVitality and sapwood area could be modeled at higher 2 2 R whenIn compared the first plot, to otherthe results biometric showed parameters that DBH and (Figure sapwood3), R area= could 0.901, ben modeled= 48. In at the higher meantime, R2 the sapwoodwhen compared area of to the other rest biometric of the trees parameters was measured. (Figure 3), The R2 =t-test 0.901, result n = 48. showed In the thatmeantime, there wasthe no significantsapwood difference area of the between rest of the treesmodel’s was estimated measured. value The t- andtest result the measured showed that value there (n = was 43) no of the sapwoodsignificant area difference (p > 0.05) between (Figure the4). model’s Therefore, estimated the estimation value and value the measured of power value function (n = 43) model of the was reliable,sapwood and couldarea (p be > used0.05) (Figure for estimating 4). Therefore, the sapwood the estimation area. value of power function model was reliable,However, and the could performance be used for result estimating of the the first sapwood model (whicharea. was established based on the biometric However, the performance result of the first model (which was established based on the parameters of vital poplars) was not reliable when it was used to estimate the sapwood area of senesced biometric parameters of vital poplars) was not reliable when it was used to estimate the sapwood poplars (Figure5). As the estimated sapwood area tended to be larger than the measured sapwood area of senesced poplars (Figure 5). As the estimated sapwood area tended to be larger than the area, the mean value of the model based estimated sapwood area and measured sapwood area were measured sapwood area, the mean value of the model based estimated sapwood area and measured 2 2 166.04sapwood cm and area 134.05were 166.04 cm , cm respectively.2 and 134.05 cm Therefore,2, respectively. another Therefore, model another was established model was established using similar 2 growthusing parameters similar growth of senesced parameters poplars of senesced(Figure6 ), poplarsR = 0.718, (Figure (n =6), 40), R2 the= 0.718, model (n validation= 40), the resultmodel was reliablevalidation (p > 0.05) result (Figure was reliable7)( n = (p 38). > 0.05) (Figure 7) (n = 38).

900 800 y = 1.452x1.553

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Water 2017 9 Water 2017,,, 9,,, 6 62222 66 of of 14 14 Water 2017, 9, 622 6 of 14

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350 350 y = 0.915x1.618 300 y = 0.915x1.618 R² = 0.718 300 y R=² 0.= 910.7185x1.618 R² = 0.718 250

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0 5 10 15 20 25 30 35 40 0 5 10 15 20 25 30 35 40 DBH (cm) 5 10 15 20DBH (cm) 25 30 35 40 DBH (cm) FigureFigure 6 6.. SenescedSenesced poplar poplar sapwood sapwood area area estimation estimation model model.. Figure 6. Senesced poplar sapwood area estimation model.

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3.2.3.2. Sap Sap Flow Flow Characteristics Characteristics ofof P.P. euphratica euphraticaeuphratica withwith DifferentDifferent Vitality VitalityVitality ThereThere were were certain certain similaritiessimilarities of sap flow flow variationvariation between between between poplar poplar poplar trees trees trees of of ofdifferent different different vitality. vitality. vitality. BothBoth vital vital vital and and and senesced senesced senesced poplars poplars poplars showed showed showed a pronounced a pronounced pronounced diurnal diurnal diurnal sap flow sap sap process,flow flow process, process, all had all peak all had had variation peak peak featuresvariationvariation (Figure features features8); (Figure and(Figure during 8 8);); andand the duringduring night the the sap nightnight flow thethe remained sap sap flow flow remained active,remained but active, active, at lower but but at rate. atlower lower rate. rate. However,However, heterogeneousheterogeneous heterogeneous characteristicscharacteristicscharacteristics of of sap sap flow flowflow variation variation also also existed existed between between the the vital vital and and senescedsenesced poplars. poplars. This ThisThis was was manifested manifested from from aspectsaspects ofof of average average sap sap flow flow flow velocity, velocity, daily dailydaily consumed consumedconsumed waterwater amount, amount, and and increasing increasing andand decreasingdecreasing time time points points of of sap sap flow. flow. flow. The The average average sap sap flow flow flow velocity velocity ofof vital vital poplarspoplars poplars throughoutthroughout throughout the thethe wholewholewhole measurementmeasurement period periodperiod was waswas 15.85 15.8515.85 cm/h, cm/h,cm/h, which which was was higher higher than than thethe averageaverage average sapsap sap flowflow flow velocityvelocity velocity ofofof senescedsenescedsenesced poplarpoplar atat 9.649.64 cm/h. cm/h. The The average average daily daily consumed consumed water water amountsamounts of of vital vital and and senesced senesced poplarspoplars were 45.95 45.95 L L and and 18.17 18.17 L, L, respectively respectivelyrespectively (Figure (Figure 9).9 9).Sap). SapSap flow flowflow velocity of both vital and senesced poplars started to rise from 7:00 a.m., whereas the sap flow of velocity of both vital and senesced poplars started to rise from 7:00 a.m.,a.m., whereaswhereas the sap flowflow of senesced poplars reached its higher value of 13.69 cm/h at 10:00 a.m. and vital poplars reached its senesced poplars reached its higherhigher valuevalue ofof 13.6913.69 cm/hcm/h at 10:00 a a.m..m. and vital poplars reached its higher sap flow 25.68 cm/h at 12:00 p.m., after the midday depression appeared. From 17:00 p.m. higher sap flowflow 25.6825.68 cm/hcm/h at at 12:00 p p.m.,.m., after the midday depression appeared. From From 17:00 17:00 p p.m..m. onwards, the sap flow velocity of senesced poplars began to decrease, which was 2 h earlier than vital onwards, the the sap sap flow flow velocity velocity of of senesced senesced poplars poplars began began to decrease, to decrease, which which was was 2 h earlier 2 h earlier than thanvital poplars. vitalpoplars. poplars.

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0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 FigureFigure 8. 8.Diurnal Diurnal sap ﬂowflow variation of of TiP.P.m euphratica euphraticae (h) withinwithin different different vitalities. vitalities.

Figure 8. Diurnal sap flow variation of P. euphratica within different vitalities.

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0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 2 2 2 2 Time (h) Figure 9. Accumulated sap flow of vital and senesced poplar trees. Figure 9. Accumulated sap flow of vital and senesced poplar trees. 3.3. Relationship between Sap Flow of Different Vitality P. euphratica and Meteorological Factor 3.3. Relationship between Sap Flow of Different Vitality P. euphratica and Meteorological Factor The sap flow variation feature of vegetation was closely related to changing environmental factors The sap flow variation feature of vegetation was closely related to changing environmental during the measurement period [36]. While conducting sap flow measurements on the sample trees, factors during the measurement period [36]. While conducting sap flow measurements on the sample environmental factors were recorded simultaneously (Figure 10). The result of the non-parametric trees, environmental factors were recorded simultaneously (Figure 10). The result of the non-parametric Spearman correlation analysis between sap flow velocity and environmental factors showed that the Spearman correlation analysis between sap flow velocity and environmental factors showed that the diurnal variation of sap flow velocity of both vital and senesced poplar was significantly related to diurnal variation of sap flow velocity of both vital and senesced poplar was significantly related to VPD, Ta, RH, Rs and groundwater depth. It was negatively related to RH, and positively related to VPD, Ta, RH, Rs and groundwater depth. It was negatively related to RH, and positively related to other meteorological factors (Table2). The influence of meteorological factors on the sap flow rate of other meteorological factors (Table 2). The influence of meteorological factors on the sap flow rate of vital poplars was in the order of: Ta (0.800) > Rs (0.732) > VPD (0.508) > RH (−0.313) > GWD (0.301). vital poplars was in the order of: Ta (0.800) > Rs (0.732) > VPD (0.508) > RH (−0.313) > GWD (0.301). For For the senesced poplars, it was in the same order of: Ta (0.851) > Rs (0.778) > VPD (0.643) > RH the senesced poplars, it was in the same order of: Ta (0.851) > Rs (0.778) > VPD (0.643) >RH (−0.478) > (−0.478) > GWD (0.171). GWD (0.171).

Table 2. Spearman correlation between sap ﬂow velocity and environmental factors. Table 2. Spearman correlation between sap flow velocity and environmental factors.

Environmental Factors T (◦C) R (w/m2) RH (%) VPD GWD (m) Environmental Factors Ta (°Ca ) Rss (w/m2) RH (%) VPD GWD (m) Sap flow velocity of vital poplar 0.800 ** 0.732 ** −0.313 ** 0.508 ** 0.301 ** Sap flow velocity of vital poplar 0.800 ** 0.732 ** −0.313 ** 0.508 ** 0.301 ** p-value <0.01 <0.01 <0.01 <0.01 <0.01 Sap flowp-value velocity of senesced poplar<0.0 0.8511 ** 0.778<0.01 ** –0.478<0.0 **1 0.643 **<0.01 0.171 ** <0.01 p-value <0.01 <0.01 <0.01 <0.01 <0.01 Sap flow velocity of senesced poplar 0.851 ** 0.778 ** –0.478 ** 0.643 ** 0.171 ** Note: ** Significant at 0.05 level. p-value <0.01 <0.01 <0.01 <0.01 <0.01 Note: ** Significant at 0.05 level. The multiple regression equations showed that the main influencing factors on the sap flow rate of vital andThe senescedmultiple poplarsregression were equations almost similar showed in that the order the main of Ta influencing, Rs, and GWD factors(Table on3 ).the The sap regression flow rate coefficientsof vital and of senesced the equations poplars were were tested, almost and thesimilar significant in the errororder probability of Ta, Rs, ofand the GWD respective (Table variables 3). The wasregression <0.01, indicating coefficients that of our the regression equations equation were tested, revealed and the the interrelation significant error between probability environmental of the factorsrespective and variable sap flows rate. was <0.01, indicating that our regression equation revealed the interrelation between environmental factors and sap flow rate. Table 3. Relationship models between sap flow velocity and environmental factors. Table 3. Relationship models between sap flow velocity and environmental factors. Sap Flow Velocity Regression Model Validation Results Sap Flow Velocity Regression Model 2 Validation Results Sap flow velocity of vital poplar Fv = −50.903 + 1.960 Ta + 0.011 Rs − 2.759 VPD + 5.377 GWD R = 0.720, F = 150.995, n = 240 Sap flow velocity of vital Sap flow velocity of 2 Fv = −50.903Fv + 1.960= −2.853 Ta + + 0.011 0.746 TaRs +− 0.0052.759 RVPD+ 0.992 + 5.377GWD GWD RR2 == 0.720, 0.770, F = 263.218,150.995,n n= = 240 240 senescedpoplar poplar s Sap flow velocity of Fv = −2.853 + 0.746 Ta + 0.005 Rs + 0.992 GWD R2 = 0.770, F = 263.218, n = 240 senesced poplar

Water 2017, 9, 622 9 of 14 Water 2017, 9, 622 9 of 14

33 30 Vital poplar Senesced poplar B A 31

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4.5 0 E GWD (vital poplar site) F 4.0 -1 GWD (senesced poplar site) 3.5 -2 3.0 -3 2.5 -4 VPD 2.0 1.5 -5

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Figure 10.10.Diurnal Diurnal variation variation of sap of flowsap velocityflow velocity of P. euphratica of P. euphraticawith different with vitality different and environmentalvitality and factors.environmental(A): Diurnal factors variation. (A): Diurnal of sap variation flow velocity of sap of flow different velocity vitality of different poplars, vitality (B): Diurnal poplars variation, (B): ofDiurnal air temperature, variation of (aCir): temperature Diurnal variation, (C): Diurnal of solar variation radiation, of solar (D): Diurnalradiation variation, (D): Diurnal of air variation humidity, (ofE ): air Diurnal humidity variation, (E): Diurnalof vapor variation pressure deficit of vapor (VPD), pressure (F): Diurnal deficit variation(VPD), (F of): Diurnalgroundwater variation depth. of groundwater depth. 4. Discussion 4. Discussion A comparison analysis of the hydraulic characteristics of different plant species, the different individualA comparison of the sameanalysis species of the (athydraulic different characteristics vitality), and of different the same plant species species, in heterogeneousthe different environmentalindividual of the conditions same species should (at be different based on vitality), their simultaneous and the same observation species in and heterogeneous measurement; otherwiseenvironmental it does conditions not make should sense. be based on their simultaneous observation and measurement; otherwiseSapwood it does is not the make water-conducting sense. tissue [37–39], and direct correlation manifested between the sapwoodSapwood area is the and water water-conducting consumption tissue of [3 trees7–39], [ 27and,40 direct,41]. Estimationcorrelation ofmanifested the sapwood between area the of a treesapwood stand area is commonly and water achievedconsumption based of ontrees the [27, correlation40,41]. Estimation between of growth the sapwood parameters area ofof thea tree tree stand is commonly achieved based on the correlation between growth parameters of the tree (e.g., (e.g., diameter at breast height, crown size, biomass, leaf area index) and the sapwood area. Hatton diameter at breast height, crown size, biomass, leaf area index) and the sapwood area. Hatton and and Vertessy’s study showed that the area of xylem conducting tissue, DBH, and tree basal area were Vertessy’s study showed that the area of xylem conducting tissue, DBH, and tree basal area were efficient upscaling parameters [42,43]. However, there are differences of sapwood width and sapwood efficient upscaling parameters [42,43]. However, there are differences of sapwood width and area among different tree species, even among different individuals of the same tree species, which sapwood area among different tree species, even among different individuals of the same tree species, is influenced by the tree growth status [44,45], site condition [46,47], and tree genetic traits [48,49]. which is influenced by the tree growth status [44,45], site condition [46,47], and tree genetic traits Therefore, heterogeneous environmental conditions and the growth status of trees require different [48,49]. Therefore, heterogeneous environmental conditions and the growth status of trees require sapwood area estimation models, this support the findings in our study. different sapwood area estimation models, this support the findings in our study. The diurnal sap flow variation feature of vital and senesced poplars in this study was similar The diurnal sap flow variation feature of vital and senesced poplars in this study was similar as as both showed obvious circadian rhythms; however, there were differences in the increasing and both showed obvious circadian rhythms; however, there were differences in the increasing and decreasing time points, as well as the average, maximum, and minimum value of sap flow. Average decreasing time points, as well as the average, maximum, and minimum value of sap flow. Average sap flow velocity of vital poplars was almost twice that of the senesced poplar. Sap flow of vital poplar sap flow velocity of vital poplars was almost twice that of the senesced poplar. Sap flow of vital started to decrease from 19:00 p.m., which was 2 h later than the senesced poplar, which may have been poplar started to decrease from 19:00 p.m., which was 2 h later than the senesced poplar, which may decidedhave been by decided the physiological by the physiological and morphological and morphological status of the status tree itself. of the Hörtensteiner’s tree itself. Hört studyensteiner’s showed thatstudy chlorophyll showed that content chlorophyll in tree leavescontent decreased in tree leaves when decreased the tree leaves when were the tree senesced leaves [ 50were]; furthermore, senesced Christ[50]; furthermore, et al. found Christ that water et al. shortage found that also water induced shortage decreasing also induced chlorophyll decreasing in tree leaveschlorophyll [51], however,in tree leaves [51], however, the lower chlorophyll content in tree leaves weakened the photosynthetic activity

Water 2017, 9, 622 10 of 14 the lower chlorophyll content in tree leaves weakened the photosynthetic activity of tree leaves, which eventually reduced transpiration. Bucci et al. and Chave et al. presented studies that showed that lower water availability increased the density of sapwood and lowered the water transport capacity in trees [52,53]. The average sap flow velocity during the day was higher than at night. Although the sap flow process was weaker at night, it remained active. This was probably to refill the water loss during the day to keep its water balance [54], which corresponded to the research results of Zhang et al. [55,56], Si et al. [57], and Yu et al. [58]. Water is the most influencing factor to the survival, distribution and development of vegetation in hyper arid regions [59]. The root system is the main organ of the plant to absorb water from the ground, therefore, its morphology and distribution impacts the growth of vegetation. Feng et al. showed that P. euphratica had a highly developed root system, and its root density decreased with increasing distance from the ground [60], therefore, when the groundwater table was lower, the plant water uptake through its root would be restricted to some degree, and the amount of water transported by vegetation decreased. In contrast, a higher groundwater table enabled vegetation to uptake more water. Our findings on the difference of sap flow velocity and diurnal water consumption between two different measurement sites with heterogeneous groundwater depth corresponded with the research results of Ma et al. [61], Zhao et al. [62], and Shen et al. [63]. As demonstrated in our study, the groundwater depth was positively related to the sap flow velocity of both vital (R2 = 0.301) and senesced (R2 = 0.171) poplars. When the sap flow velocity increased, the groundwater depth also increased, which was due to the water uptake by poplar trees. The correlation of sap flow velocity and groundwater depth in the vital poplars distributed plot was larger than that of the senesced poplar plot, which indicates that the groundwater availability strengthened the influence on the water uptake of poplars. Many studies have shown that Rs, RH, Ta, and GWD are the most influencing external factors on the water consumption of trees [40–42,56,64]. Solar radiation affects the photosynthetic and transpiration activities of vegetation; it is the energy required to activate photosynthesis. Air temperature rises with the strengthening of solar radiation. When the leaf temperature is higher, plants decrease its temperature through increasing its transpiration rate. Leaf stomatal resistance increases when the air temperature reaches 32 ◦C, next, the stomata conductance and water potential decreases, which reduces the transpiration rate [65]. Air humidity changes the VPD between the plant, leaf, and atmosphere. When the air humidity is low, the difference in vapor pressure between the leaf and atmosphere is higher, which accelerates the transpiration rate. In contrast, when the air humidity is higher, the transpiration rate is lower.

5. Conclusions As reported in the relevant literature, the results of our study further showed that DBH and the sapwood area of poplars were closely related to each other; therefore, DBH could be used to estimate the sapwood area by establishing statistical models. However, the sapwood area of vital poplars tended to be larger than the senesced poplars, therefore, the vitality of the poplars should be taken into account when estimating the sapwood area. There were certain similarities and differences between the sap flow processes of vital and senesced poplars; sap flow velocity and diurnal water consumption of vital poplars was larger than that of the senesced poplars. However, the influence of environmental factors on sap flow was similar; sap flow of both vital and senesced poplars had a positive correlation with air temperature, solar radiation, vapor pressure deficit, groundwater depth, and negative correlation with air humidity. Our results demonstrated that the hydraulic characteristics of two different vitalities of poplar were not the same, and that when analyzing the water usage strategy and estimating the water consumption of poplar forests, these two kinds of trees should be treated differently.

Acknowledgments: This research work was supported by the German Volkswagen Foundation within the framework of EcoCAR project (Az.: 88497), National Natural Science Foundation of China (Grant No: 31360200), Water 2017, 9, 622 11 of 14 and “Sino-German interdisciplinary joint training of innovative talents for ecological restoration of floodplain” funded by China Scholarship Council (Grant No. 201505990312). We thank the Forestry Department of Qarkilik (Ruoqiang), especially Askar and Sadik from Arghan Forestry Station for their support during our field work. We also would like to express our gratitude to Zhang Ximing (CAS), Atawulla Muyibul for supervising and supporting our sap flow equipment installation, and to our team memmbers Gulipiya Wumaier, Kailibinuer Nuermaimaiti and Maidina Muhetaer (Xinjiang University) for their assistance during the field work. Finally, we thank the editors and anonymous reviewers who helped to improve the manuscript. Author Contributions: The manuscript was mainly written by Maierdang Keyimu with support from Ümüt Halik. Ümüt Halik and Maierdang Keyimu conceived of and designed the overall concept for the research; Ümüt Halik and Aihemaitijiang Rouzi are responsible for manuscript modification. Data were collected and sorted by Maierdang Keyimu, Aihemaitijiang Rouzi. Conflicts of Interest: The authors declare that they have no conflict of interest.

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