Advertisement

Plant and Soil

, Volume 424, Issue 1–2, pp 103–122 | Cite as

Linking above- and belowground phenology of hybrid walnut growing along a climatic gradient in temperate agroforestry systems

  • Awaz Mohamed
  • Alexia Stokes
  • Zhun Mao
  • Christophe Jourdan
  • Sylvie Sabatier
  • François Pailler
  • Stephane Fourtier
  • Lydie Dufour
  • Yogan Monnier
Regular Article

Abstract

Background and aims

Plant phenology is a sensitive indicator of plant response to climate change. Observations of phenological events belowground for most ecosystems are difficult to obtain and very little is known about the relationship between tree shoot and root phenology. We examined the influence of environmental factors on fine root production and mortality in relation with shoot phenology in hybrid walnut trees (Juglans sp.) growing in three different climates (oceanic, continental and Mediterranean) along a latitudinal gradient in France.

Methods

Eight rhizotrons were installed at each site for 21 months to monitor tree root dynamics. Root elongation rate (RER), root initiation quantity (RIQ) and root mortality quantity (RMQ) were recorded frequently using a scanner and time-lapse camera. Leaf phenology and stem radial growth were also measured. Fine roots were classified by topological order and 0–1 mm, 1–2 mm and 2–5 mm diameter classes and fine root longevity and risk of mortality were calculated during different periods over the year.

Results

Root growth was not synchronous with leaf phenology in any climate or either year, but was synchronous with stem growth during the late growing season. A distinct bimodal pattern of root growth was observed during the aerial growing season. Mean RER was driven by soil temperature measured in the month preceding root growth in the oceanic climate site only. However, mean RER was significantly correlated with mean soil water potential measured in the month preceding root growth at both Mediterranean (positive relationship) and oceanic (negative relationship) sites. Mean RIQ was significantly higher at both continental and Mediterranean sites compared to the oceanic site. Soil temperature was a driver of mean RIQ during the late growing season at continental and Mediterranean sites only. Mean RMQ increased significantly with decreasing soil water potential during the late aerial growing season at the continental site only. Mean root longevity at the continental site was significantly greater than for roots at the oceanic and Mediterranean sites. Roots in the 0–1 mm and 1–2 mm diameter classes lived for significantly shorter periods compared to those in the 2–5 mm diameter class. First order roots (i.e. the primary or parents roots) lived longer than lateral branch roots at the Mediterranean site only and first order roots in the 0–1 mm diameter class had 44.5% less risk of mortality than that of lateral roots for the same class of diameter.

Conclusions

We conclude that factors driving root RER were not the same between climates. Soil temperature was the best predictor of root initiation at continental and Mediterranean sites only, but drivers of root mortality remained largely undetermined.

Keywords

Agroforestry Rhizotron Root elongation Initiation Mortality Longevity 

Abbreviations

ψ

Soil water potential

DS

Dormant season

EGS

Early growing season

LGS

Late growing season

RER

Root elongation rate

RIQ

Root initiation quantity

RMQ

Root mortality quantity

Introduction

Climate models predict that an increase in precipitation and temperature could affect many biological phenomena and changes in plant phenology are considered a very sensitive indicator of plant response to climate change (Steinaker et al. 2010; Morin et al. 2010). The timing of above and belowground phenological events is important to assess ecosystem function and plant productivity (Fridley 2012; Richardson et al. 2006). Aboveground phenological events include bud burst, leaf expansion and leaf fall, all of which have attracted attention because of the role they play in determining species’ responses to climate change (Diez et al. 2012). However, observations of phenological events belowground, including timing of root initiation, peak growth, survivorship and cessation of growth, are more difficult to obtain for most ecosystems and hence are less well characterized, especially in natural conditions.

Fine root demographic processes play an essential role in ecosystem nutrient cycling and the global carbon budget (C) cycle (Vogt et al. 1995, 1998; Gill and Jackson 2000). Quantifying root demography includes estimations of elongation rate (Germon et al. 2016; Jourdan et al. 2008), production and mortality (Hendrick and Pregitzer 1993b; Mao et al. 2013a; McCormack et al. 2014), turnover (Anderson et al. 2003), survivorship (Anderson et al. 2003; Kern et al. 2004) and senescence (Huck et al. 1987). Fine root phenology can be influenced by different factors throughout the year, and these factors will alter patterns of root growth and longevity. Several studies found strong effects of abiotic factors on root elongation, such as soil temperature (Kuhns et al. 1985; Wan et al. 2002; Tanner et al. 2006; Steinaker and Wilson 2008; Steinaker et al. 2010; Coll et al. 2012), soil water content (Green et al. 2005; Metcalfe et al. 2008; Misson et al. 2006; Block et al. 2006) or air temperature (M’bou et al. 2008; Tierney and Fahey 2002; Fukuzawa et al. 2013). For example, Germon et al. (2016) studying walnut (Juglans nigra × regia L.) trees in a Mediterranean climate found that RER was positively and significantly correlated with mean daily soil temperature. In contrast, other studies have found no correlations with abiotic factors (Hendrick and Pregitzer 1993a, b; Hendrick and Pregitzer 1996a; Joslin and Wolfe 1998; Joslin et al. 2000) and suggest that endogenous factors, such as growth regulators (McAdam et al. 2016), photoassimilate transport and photosynthate availability (Sloan et al. 2016; Tierney and Fahey 2002; Joslin et al. 2000) are the main drivers of growth. Abramoff and Finzi (2015) also suggested that endogenous cuing and allocation of stored carbohydrates were dominant drivers of root growth in Mediterranean trees.

Although air temperature may be the most important environmental factor controlling the timing of aboveground growth, as reported by a number of studies (Menzel 2003; Radville et al. 2016a; Wielgolaski 1999), the drivers of belowground phenology are less clear. We also have a poor understanding of the relationship between root growth and leaf phenology (Reich et al. 1980; Pregitzer et al. 2000; McCormack et al. 2015; Abramoff and Finzi 2015) and how this relationship is affected by abiotic factors. It is commonly assumed that root and shoot growth are asynchronous (Steinaker et al. 2010; Abramoff and Finzi 2015; Sloan et al. 2016) with a peak of root growth in the early and late spring (Contador et al. 2015; Germon et al. 2016) or in the summer (Psarras et al. 2000). However, several studies have shown that root growth can occur in a single flush but often occurs in multiple flushes throughout the growing season (Reich et al. 1980; Harris et al. 1995; Steinaker et al. 2010) depending on resource availability either during a single seasonal pulse or multiple periods of favorable environmental conditions (McCormack et al. 2014). In temperate forests, leaf growth occurs several weeks before root growth (Steinaker and Wilson 2008; Abramoff and Finzi 2015; Harris et al. 1995). However, Radville et al. (2016b) in an arctic climate, and Abramoff and Finzi (2015) reviewing data from a subtropical climate, showed that root growth can precede shoot growth by several weeks to several months (Radville et al. 2016b; Broschat 1998). Therefore, climate is an important factor driving root phenology, with major consequences for biogeochemical cycles and other plant processes such as root longevity.

Fine root lifespan is considered an important root trait (Wang et al. 2016), because it determines the quantity of root organic matter transferred to soil (Guo et al. 2008) as well as exerting an indirect control on nutrient and water uptake efficiency (McCormack et al. 2012). Root turnover varies widely within and among species and across ecosystems (Majdi et al. 2005; McCormack and Guo 2014), but a fundamental understanding of the mechanisms that control fine root life span among different climates is poorly understood. Most published studies have related root lifespan either to endogenous factors such as root diameter and branch order (Guo et al. 2008; Wang et al. 2016), seasons of initiation, nitrogen (N) concentration (McCormack et al. 2012), root depth (Baddeley and Watson 2005) or to climatic factors such as temperature, water and nutrient availability (Chen and Brassard 2013; Green et al. 2005). However, knowledge of the influence of environmental factors on fine root life span remains limited.

In this study, we examined root elongation, initiation, mortality and survivorship of walnut trees (Juglans sp.) growing in agroforest systems along a climatic gradient in France. We aimed at determining which factor most drives root growth over different phenological periods. We also characterized the relationship between root and shoot phenology, particularly in response to both temperature and precipitation. We hypothesized that (i) shoot and root phenology are asynchronous regardless of the climate, (ii) the drivers of root growth and mortality are not the same between climates, (iii) root diameter is linked to elongation rate and is altered over phenological periods and between climates, and (iv) root longevity is altered among climates.

Materials and methods

Study sites

Root and shoot phenology of hybrid walnut (Juglans sp., Table S1) were studied in three agroforestry systems along a climatic gradient in France (Fig. 1). Trees were intercropped with pasture or crops (Fig. S1). The most northern site was located at Pas de Calais, France where climate was oceanic with a mean annual temperature of 11.8 °C and a mean annual rainfall of 777.9 mm (Météo France, see “Climatic data” section), thus the site is hereafter termed ‘oceanic’ (Table S1). The soil is silt loam (Table 1; Fig. S2) and at least 2.5 m deep, with the presence of the water table at this depth in June. The mean diameter at breast height (DBH) of walnut trees at the site was 0.30 ± 0.03 m and mean height was 14.75 ± 3.50 m.
Fig. 1

Geographic location of each site along the latitudinal gradient in France. Map of France courtesy of TomKr, Wikimedia Commons, (2008)

Table 1

Soil physical and chemical characteristics at each site. Data are means ± standard deviation (S.D.). “C” is Carbon, “N” is Nitrogen, “P” is Phosphorus and “K” is Potassium

Soil properties

Site

Chemical

Texture (%)

pH

N (g/Kg)

C/N

P (g/Kg)

K (g/100 g)

Clay

Silt

Sand

Mean

Mean

S.D.

Mean

S.D.

Mean

S.D.

Mean

S.D.

Mean

Mean

Mean

Oceanic

6.9

0.17

0.1

9.19

1.5

0.15

0.1

1.5

0.1

17.6

66.3

16.1

Continental

4.7

0.22

0.1

9.76

1.4

0.04

0

2.82

0.2

15.1

22.6

62.3

Mediterranean

8.4

0.9

0.1

10.7

0.7

25.0

60.0

15.0

The second agroforest was located at Cantal, France. Climate was continental with a mean annual temperature of 10.3 °C and a mean annual rainfall of 1174 mm (Météo France, this site is hereafter termed ‘continental’, Table S1). The soil is sandy, acidic, and attained an average maximum depth of 110 cm (Table 1, Fig. S2). Mean DBH of all walnut cultivars at the site was 0.20 ± 0.02 m and mean height was 12.09 ± 1.30 m.

The third agroforest was located at the Restinclières experimental site, 15 km north of Montpellier, Department Hérault, France. The climate is sub-humid Mediterranean with a mean annual temperature of 14.7 °C and a mean annual rainfall of 873 mm (this site is henceforth termed ‘Mediterranean’, Table S1). The soil is a silty clay deep alluvial soil (25% clay and 60% silt) with a depth > 4 m (Mulia and Dupraz 2006). Mean DBH of all walnut trees at the site was 0.24 ± 0.13 m and mean height was 11.09 ± 2.50 m.

Climatic data

Precipitation data for the three sites were obtained from Météo-France. Weather stations were located at Le Touquet, (oceanic: 50°30′48″N, 1°37′18″E, elevation 5 m a.s.l.), Station Naves (continental:, 45°19′12″N, 1°46′18″E, elevation 450 m a.s.l.) and Restinclières (Mediterranean: 43°42′15.53″N 3°51′38.66″E, elevation 100 m a.s.l.). Air temperatures were measured in the shade at a height of 1.5 m at each site and soil temperatures were measured in two soil layers (10 and 60 cm) per site, using Thermochron iButtons (DS1921G) (Hubbart et al. 2005). All sensors were programmed to measure the temperature twice a day (2 a.m. and 2 p.m). Soil water potential (noted ψ hereafter) was measured using Irrometers (WaterMark, IRROMETER Company, Inc. USA) installed at each site at depths of 10 and 60 cm and measured water potential every 12 h.

Rhizotron installation

To measure tree root elongation rate (RER) and mortality, we installed rhizotrons, also called root windows, in pits at each field site (Fig. S3). Rhizotrons comprised transparent polyvinylchloride (PVC) sheets placed against the soil profile, through which root growth dynamics can be observed (Reich et al. 1980; Misra 1999; Mao et al. 2013a, b; Mohamed et al. 2017). In the oceanic site, four trenches (2 m long × 1 m wide × 2 m deep) were dug in one row of trees. One rhizotron was installed on each opposing face of the trench (n = 8 rhizotrons in total).

In the continental agroforest (Madic), we dug eight (1 m long × 1 m wide × 1 m depth) trenches in three rows of trees. Eight rhizotrons (50 cm long × 50 cm wide × 0.5 cm thick), were installed. Each trench was at a distance of 2 m from the nearest tree trunk.

At the Mediterranean site, one pit (5 m long × 1.5 m wide × 4 m depth) was dug in March 2012 between two walnut trees on the same tree row (Fig. S4) (Cardinael et al. 2015). In June 2014, two rhizotrons (100 cm long × 80 cm wide × 0.5 cm thick) were installed, as well as eight smaller windows (65 cm long × 30 cm wide × 0.5 cm thick) at depths of 20, 115, 220 and 320 cm.

Where the rhizotrons were to be placed on the soil wall, we gently removed the soil to make a flat surface and cut all roots on the profile with secateurs. The soil removed during the digging of the trenches was kept aside, and then sieved through a 5 mm sieve and air-dried for several hours. The sieved and air-dried soil was then poured into the space between the window and the soil profile and slowly compacted using a wooden plank. Each rhizotron was covered with foil-backed felt insulation and black plastic sheeting to protect roots from light and temperature variations. All pits were then covered with wooden boards and corrugated plastic or a metallic roof to avoid damage from passing animals and to prevent direct rainfall and sunlight on the rhizotrons. In the first three months after installation, no root growth was recorded because soil disturbance during rhizotron installation causes overestimations of root growth (Strand et al. 2008; Mohamed et al. 2017).

Measurements of root growth

To measure fine root growth dynamics, we either scanned rhizotrons or used a time-lapse camera to automatically take pictures (Mohamed et al. 2017). Roots were measured from the upper 10 cm to 60 cm of soil in the three sites. In the continental and Mediterranean sites, a scan of each rhizotron (between two and four images per window depending on the size of the window) was taken at monthly intervals over the observation period (21 months) using an Epson Perfection V370 flatbed scanner with a high optical resolution of 4800 dpi (Fig. S5).

At the oceanic site, which was more difficult to access frequently, a time-lapse camera (Cuddeback Attack, U.S.A.) was placed on a wooden cleat in front of each rhizotron at a distance of 90 cm from the rhizotron (Fig. S5). RER measurements from time-lapse cameras do not differ from those measured with a scanner (Mohamed et al. 2017). Photographs were taken daily at 2 a.m. and 2 p.m. over the observation period (21 months). The time-lapse cameras ran automatically for several months at a time using alkaline batteries. However, in September 2014, the trench at the Mediterranean site was flooded due to exceptionally strong rainfall; therefore all rhizotrons were reinstalled in March 2015. No data were recorded from September 2014 to March 2015, and data were recorded from March to June 2015 but not used in the statistical analysis. Similarly, at the oceanic site, nearly all trenches were flooded due to strong rainfall in January 2015 and the proximity of the water table, and half the cameras were damaged. In March 2015, all cameras were replaced and no data were recorded from January 2015 to March 2015. To avoid the same problem the following year, we removed cameras from November 2015 to March 2016, therefore, data are missing for this period also.

Monthly measurements of root emergence, mortality and elongation were carried out immediately after roots were observed in each rhizotron (and after the first three months had passed) until October 2014. Roots were classified into three diameter classes: (0–1) mm, (1–2) mm, and (2–5) mm. However for measurements from the camera method, because of an overestimation of diameters (Mohamed et al. 2017), we corrected the value of root diameter using the following equation:
$$ y=0.43\times $$
Where y represents the value corrected root diameter, x represents the real value of the diameter taken by the camera. 0.43 is the relative value corresponding to the mean difference between the scanner measurement and camera measurement. We also classified root topology into two orders: ‘parent’ or ‘child or lateral branch root’ (SmartRoot software). The effect of root topological orders at the oceanic site was excluded from the analysis because a negligible number of lateral roots emerged.

In previous studies, root mortality was assumed to occur when the root became darker in color (West et al. 2004) or when it disappeared (Baddeley and Watson 2005). In some studies, both criteria were applied (Wells and Eissenstat 2001; Anderson et al. 2003). In our study, color was the only criterion applied (Mao et al. 2013a), as root death can occur before its disappearance (Hooker et al. 1995). We declared the root dead when it turned black and displayed no growth for two or more successive sessions.

Image analysis

Once images of root growth had been acquired, we conducted analysed images using the semi-automated SmartRoot software (Lobet et al. 2011). SmartRoot is an operating system, independent freeware based on ImageJ and using cross-platform standards (RSML, SQL, and Java) for communication with data analysis softwares (Lobet et al. 2011; Mathieu et al. 2015). Before analyzing roots, when necessary, images need “stitching” together (e.g. with Adobe Photoshop CS3 software), if several have been taken for the same rhizotron (when the rhizotron surface area was greater than the field of the scanner). SmartRoot only processes grayscale (8-bit) images, then all images should be converted to grayscale and the current implementation assumes alive roots have lower pixel (darker) values than the background. In the case of this study, we transformed all images to 8 bit gray scale and then inverted them using ImageJ software so that roots were darker than the background of the image. The length and diameter of each root produced during one interval time (i.e. one month) were calculated for each rhizotron (Mohamed et al. 2017). Before analyzing a new sequence of images, SmartRoot provides the user with an icon to import the traces of the same roots from the previous image data file to superimpose them on this new image, which helps the estimation of the evolution of root length. This preceding image also helps determine whether the root is live (walnut roots are usually cream in color) or dead (turning black) (Huck and Taylor 1982; Mao et al. 2013a).

Aboveground phenology and radial growth

We assessed the timing of shoot production through changes in the phenological phases of leaves throughout the year. We divided the year into three phenological periods, early growing season (from budburst to 100% leafing out of early green leaves), late growing season (100% leafing out to leaf-fall) and dormancy (leaf-fall to budburst, Fig. S6). Shoot phenological periods were recorded using a time-lapse camera (Wingscapes TimelapseCam8.0) at a resolution of 5 megapixels in the oceanic and continental agroforests. One camera per site was placed on the trunk of one tree facing a line of trees. Photographs were taken daily at 12 a.m. and 12 p.m. At the Mediterranean site, shoot phenological periods were recorded visually using binoculars. During the bud-burst period, visual measurements were made daily.

We also measured the radial growth of tree trunks by installing dendrometers (Increment Sensor DB20) on eight trees per site. The dendrometers are girth bands, comprising a steel band, spring and nonius scale. Bands were placed on the stem; at a height of 1.3 m. Measured values are read at the nonius scale with 0.1 mm precision. Readings were made monthly at both continental and Mediterranean sites. However, readings were made only every three months at the oceanic site because of difficulties with site access. Tree height was recorded annually after leaf shedding using a hypsometer Vertex (Quebec, Canada).

Root growth and mortality dynamics

We used the following methods to estimate RER, initiation and mortality:
  1. (i)

    Individual root growth was evaluated by calculating the difference between root length at t −1 and at t. To determine daily RER, the mean of all individual root lengths produced between time t and t −1 was divided by the duration of the corresponding period:

     
$$ {RER}_{t-1,t}=\frac{len{.}_t\hbox{--} len{.}_{t-1}}{Pt_{-1,t}} $$
where, RER t −1 , t is the daily root elongation rate (in mm/day) from inventory time t-1 to t; len t−1 and len t are the lengths of the root n at inventory time t −1 and t, respectively; p t−1 , t is the period in days between inventory time t −1 and t.
  1. (ii)

    Monthly mean root initiation quantity (RIQ) was calculated as the mean number of new roots initiated between time t and t -1.

     
  2. (iii)

    Monthly mean root mortality quantity (RMQ) was calculated as the mean number of dead roots between t and t −1 only when live roots were present.

     

Statistical analysis

All indicators of root dynamics, including mean RER (for growing roots only), mean RIQ and mean RMQ (when the total number of alive roots was >0) were calculated using R software Version 2.15.3 (R Development Core Team 2013). A Shapiro-Wilk test was performed before each test to determine if data followed a normal distribution and homogeneity of variances was checked. For data not normally distributed, analyses were performed by a Kruskal-Wallis test. Effects of season, site, diameter classes and topological orders (i.e. the primary or parent roots and the lateral branch root) were tested on each variable. A post-hoc analysis was performed when the Kruskal-Wallis result was significant, using a Nemenyi test of Kruskal Wallis at p < 0.05 to determine which levels of the independent variable differed from each other level. Spearman’s rank correlations were performed to determine the relationship between the climatic variables (mean soil and air temperatures and mean ψ) of the month preceding the growth measurement, and mean RER, RIQ and RMQ.

A Cox Proportional Hazard Model was used to analyze the effects of different varying factors on root mortality and to calculate root longevity and risk of mortality. Factors used as variables included sites, phenological period, diameter classes and topology orders. Different Cox Hazard Models were performed for two topological orders: parent and child order (SmartRoot software). We performed the statistical test only when the sample size was >20 for each category (topology order, diameter classes, sites, time periods). During the observation period, every root was accounted for, i.e., the months of initiation and mortality were known for all roots. Roots that were alive at the end of the observation period were considered as censored data and were included in the analysis. All analyses were performed using R software, Version 2.15.3 (R Development Core Team 2013) at a significance level of <0.05.

Results

Latitudinal gradient of meteorological and soil hydrological data

Mean annual temperature over the two year period was 11.7 °C (oceanic), 12.4 °C (continental) and 14.8 °C (Mediterranean). Mean monthly air temperature over the same period was lowest in December at all field sites (ranging from 3.1 °C to 7.6 °C; Fig. 2), and highest in July at the oceanic (17.8 °C), continental (20.6 °C) and Mediterranean sites (24.3 °C) (Fig. 2).
Fig. 2

Soil (yellow line) and air (red line; measured at a height of 1.5 m above rhizotrons) temperatures, daily precipitation (blue bars) and soil water potential, ψ, (light blue line) at oceanic, continental and Mediterranean field sites from September 2014 to June 2016. Different background colors correspond to different phenological periods: “LGS” is late growing season (green) “EGS” is early growing season (light green), “DS” is dormant season (gray)

Average annual precipitation over 2014 and 2015 was 910 mm (oceanic), 1056 mm (continental) and 938 mm (Mediterranean) (Fig. 2). Rainfall at the Mediterranean site was highly variable between the two years, with 1264 mm in 2014 and only 613 mm in 2015 (Fig. 2). A negative and significant (p < 0.001, ρ = −0.40) correlation was found between total annual rainfall and ψ.

Mean annual soil water potential was significantly higher at the Mediterranean site than those of continental and oceanic sites (p < 0.001) and the oceanic site had a significantly higher ψ than the continental site (p < 0.001, Table S1).

Mean annual soil and air temperatures at the Mediterranean site were both significantly higher than those at the continental and oceanic sites (p < 0.001) and the oceanic site had a significantly greater mean soil temperature compared to the continental site (p < 0.001). However, no significant differences were found in mean air temperature between oceanic and continental sites (p = 0.07, Table S1).

Leaf phenology

The date of budburst differed among sites: the Mediterranean trees in 2015 had an earlier budburst (18 April 2015) than the continental and oceanic climates by 15 days and 27 days, respectively. In 2016, this difference increased to 21 and 28 days, respectively (Table 2). The Mediterranean trees had an earlier leaf unfolding date (2 June 2015) than the continental and oceanic climates by 3 and 16 days, respectively. Mediterranean trees had later leaf fall (18 November 2014 and 12 November 2015) than the continental (6 days in 2014 and 15 days in 2015) and oceanic sites (10 days in 2014 and 9 days in 2015).
Table 2

The length (in days) of different phases of the growing season for both shoots and roots in the three climates

Phenological growth periods

Early growing season

Late growing season

Dormant season

Total growing season

Shoot

 Year

2015

2016

2015

2014–2015

2015–2016

2015

Oceanic

 Date

15 May

12 May

18 Jun

08 Nov

03 Nov

 

 Length

34

138

188

191

172

Continental

 Date

3 May

5 May

05 Jun

12 Nov

28 Oct

 

 Length

33

36

145

172

190

178

Mediterranean

 Date

18 Apr

14 Apr

02 Jun

18 Nov

12 Nov

 

 Length

45

163

151

154

208

Root

 Oceanic

210

100

154

210

 Continental

240

118

124

240

 Mediterranean

216

126

216

— no observation recorded

Stem phenology

The timing of root growth was synchronous with that of stem growth during the late growing season (from June to November) in both study sites (Fig. 3). Stem radial growth started when trees had 100% of leaf unfolding (the onset of late growing season). Root and stem growth had an antagonistic growth pattern (Fig. 3), i.e. peaks of root growth occurred inversely to those of stem growth. Stem growth then dropped sharply with leaf fall. The length of the radial growing season was shorter than that of roots by 86 days and 73 days at both continental and Mediterranean sites, respectively.
Fig. 3

Mean root elongation rate (RER, blue line) and trunk radial growth (red line) at oceanic, continental and Mediterranean field sites from September 2014 to June 2016. Different background colours correspond to different phenological periods: “LGS” is late growing season (green) “EGS” is early growing season (light green), “DS” is dormant season (gray). Missing data/ flood damage is shown with a dotted line over the dashed curves. Vertical bars represent standard errors (not shown when smaller than the symbol size)

Root elongation rate (RER)

Mean RER for growing roots at all sites was influenced significantly by season, with a bimodal distinct flush of root growth observed during the aerial growing season (Fig. 3), and negligible growth during the rest of the year. Peaks of mean RER always lagged behind those for budburst. In 2015, mean RER was initiated before budburst in both oceanic (28 days) and continental (26 days) climates. However at the Mediterranean site, budburst preceded root elongation by 28 days in 2015. Mean RER peaked in June (Mediterranean) or July (oceanic and continental; Fig. 3), before decreasing and then peaking to a lesser extent in August for the Mediterranean site, and September for the oceanic and continental sites (Fig. 3). When mean RER (during all observation periods) and between all sites was compared, mean RER was significantly higher (P = 0.01) at the oceanic site compared to the continental site only.

No significant relationships were found between RER and root diameter classes. No significant differences were found in RER of any roots between the early and dormant seasons.

When all root data were combined, mean RER was positively and significantly correlated with the mean air and soil temperatures of the month preceding the RER measurement at the oceanic (P < 0.001, ρ = 0.55) and continental (P < 0.001, ρ = 0.48) sites only (Fig. 4a, b, Table 3). Mean RER was correlated with mean ψ at the oceanic site only (Fig. 4c, P < 0.001, ρ = 0.55). However, when mean RER of roots growing during the aerial growing season was examined, positive and significant correlations were found between mean RER and soil temperature (Fig. 5a, P = 0.002, ρ = 0.61) and mean RER and air temperature (Fig. 5b, P = 0.004, ρ = 0.48) of the month preceding growth at the oceanic site only. The mean RER was significantly correlated with mean ψ in both oceanic (negatively) (Fig. 5c, P = 0.004, ρ = −0.48) and Mediterranean (positively) (Fig. 5c, P = 0.05, ρ = 0.50) sites only.
Fig. 4

Spearman rank’s correlations (ρ) (for all periods combined together) between mean root elongation rate (RER) and (a) mean soil temperature, (b) mean air temperature and c) mean soil water potential at the oceanic (open triangles), continental (closed circles) and Mediterranean (open diamonds) sites. Where: * is P < 0.05, ** is P < 0.01 and *** is P < 0.001

Table 3

Probability (P) and correlation coefficients (ρ) from correlations between mean soil and air temperatures, mean soil water potential of the preceding month and root elongation rate (RER), root initiation quantity (RIQ) and root mortality quantity (RMQ) at the three sites during the late growing season

 

Variable

oceanic

continental

Mediterranean

ρ

P

ρ

P

ρ

P

Soil temperature

RER

0.61

<0.001***

0.28

n.s.

−0.12

n.s.

RIQ

0.06

n.s.

−0.28

<0.001***

−0.54

<0.001***

RMQ

0.19

n.s.

0.21

0.02*

0.10

n.s.

Air temperature

RER

0.48

0.005**

0.28

n.s.

0.06

n.s.

RIQ

0.14

0.04*

−0.12

n.s.

−0.37

<0.001***

RMQ

0.17

0.11

0.16

n.s.

0.12

n.s.

Soil water potential ψ

RER

−0.48

0.005**

0.21

n.s.

0.50

0.05*

RIQ

0.08

n.s.

0.13

n.s.

−0.01

n.s.

RMQ

−0.16

n.s.

−0.66

<0.001***

0.06

n.s.

Where: n.s. is non-significant, * is P < 0.05, ** is P < 0.01 and *** is P < 0.001

Fig. 5

Spearman rank’s correlations (ρ) (for late growing season only) between mean root elongation rate (RER) and (a) mean soil temperature, (b) mean air temperature and (c) mean soil water potential at the oceanic (open triangles), continental (closed circles) and Mediterranean (open diamonds) sites. Where: * is P < 0.05, ** is P < 0.01 and *** is P < 0.001

Comparing above and belowground phenology

Phenological periods of growth differed between sites. In 2015, the Mediterranean climate had a longer aerial growing season (208 days) than continental and oceanic climates by 30 days and 36 days, respectively. In 2014, the dormant season was shorter at the Mediterranean site (151 days) compared to continental (172 days) and oceanic sites (188 days). However, in 2015, the length of the growing season was similar in oceanic and Mediterranean climates but the dormant season was longer by 36 days at the continental site (Table 2). The duration of the growing season of roots was longer than that for leaves for the oceanic (38 days), continental (62 days) and Mediterranean (8 days) sites (Table 2). Root growth was not synchronous with leaf phenology in any climate or either year. However, root elongation was synchronous with trunk growth in the three climates (Fig. 3).

Mean monthly root initiation and mortality quantities

Mean RIQ was always highest during the late growing season compared to the other seasons. The first peak of root appearance at each site was 3 months after rhizotron installation (October 2014 at both the oceanic and continental sites and in June 2015 at the Mediterranean site). In 2015, peaks of mean RIQ were found in June at the oceanic site (1.17 ± 2.32 roots), in July at the continental site (3.6 ± 6.02 roots) and in October at Mediterranean site (1.71 ± 3.29 roots; Fig. 6). Each peak of mRIQ was followed immediately by a peak of mRMQ in all climates during the late growing season (Fig. 6). A significantly lower number of roots was initiated (P = 0.02) at the oceanic site (0.66 ± 1.87 roots) compared to both continental (2.6 ± 5.3 roots) and Mediterranean climates (1.9 ± 4.9 roots). No significant differences in mean RIQ were found between continental and Mediterranean sites.
Fig. 6

Mean root initiation quantity (RIQ, blue line) and mean root mortality quantity (RMQ, red line) between time t and t−1, per 0.25 m−2 rhizotron (red line) at oceanic, continental and Mediterranean field sites from September 2014 to June 2016. Different background colors correspond to different phenological periods: “LGS” is late growing season (green) “EGS” is early growing season (light green), “DS” is dormant season (gray). Missing data/ flood damage is shown with a dotted line over the dashed curves. Vertical bars represent standard errors (not shown when smaller than the symbol size)

No significant differences in mean RMQ were found between climates between early and late growing seasons. Mean RMQ was significantly higher in the late growing season compared to the dormant season (P = 0.009).

During the late growing season, mean RIQ was not correlated with mean ψ in any of the three climates. Significant negative correlations were found between mean RIQ and mean soil temperature of the preceding month at the continental (P < 0.001, ρ = −0.28) and Mediterranean (P < 0.001, ρ = −0.54) sites only (Fig. 7). Mean air temperature of the preceding month was negatively correlated (P = 0.002, ρ = −0.37) with mean RIQ in the Mediterranean climate only (Fig. 7). Mean RMQ increased rapidly with the increase of mean soil temperature and mean ψ and peaked when ψ was maximal at the continental site only (Fig. 8). However, mean RMQ was not correlated with mean soil or air temperatures or mean ψ in either oceanic or Mediterranean sites (Fig. 8). When all factors were considered together, mean RIQ and mean RMQ of first order roots (parents) was significantly greater than that of the lateral (children) roots at the continental site only (P < 0.001).
Fig. 7

Spearman rank’s correlations (ρ) (for late growing season only) between mean root initiation (RIQ) and (a) mean soil temperature and (b) mean air temperature at the oceanic (open triangles), continental (closed circles) and Mediterranean (open diamonds) sites. Where: * is P < 0.05, ** is P < 0.01 and *** is P < 0.001

Fig. 8

Spearman rank’s correlations (ρ) (for late growing season only) between mean root mortality (RMQ) and (a) mean soil temperature, (b) mean soil water potential at the oceanic (open triangles), continental (closed circles) and Mediterranean (open diamonds) sites Where: * is P < 0.05, ** is P < 0.01 and *** is P < 0.001

Root longevity and risk of mortality

Cox’s proportional hazards regressions showed that when all root diameter classes were grouped together, mean root longevity at the continental site was significantly greater than for roots at the oceanic (z = 7.7, P < 0.001) and Mediterranean (z = 14.2, P < 0.001) sites. The longevity of roots at the Mediterranean site was significantly shorter than at the oceanic site (Fig. 9a). Compared to the continental climate, the risk of mortality was 2.7 times greater for roots from the Mediterranean site and 2.1 times greater for roots from the oceanic site. The phenological period had an important effect on root longevity at the continental site but not at oceanic and Mediterranean sites during the observation period. At the continental site, compared to the dormant season, the risk of mortality was 1.8 times more during the early growing season and 1.7 times more during the late growing season (Fig. 9b). No significant differences in longevity were found between growing seasons at the other two sites. Root diameter classes had the largest effect on root longevity compared with other factors. When lateral roots were excluded from the analysis (for all growth periods combined), roots in the 0.1 mm diameter class lived for significantly shorter periods compared to those in the 2–5 mm diameter class at continental (z = −1.65, P = 0.006) and Mediterranean (z = −3.36, P < 0.001) sites only. However, no significant differences in longevity were found between roots from the 0–1 mm and 1–2 mm diameter classes (Fig. 9c). At the continental site, roots in the 2–5 mm diameter class had 38% less risk of mortality than roots in the 0–1 mm diameter class. At the Mediterranean site, roots in the 2–5 mm diameter class had 61% less risk of mortality than those from 0 to 1 diameter class. When all factors were considered together, except for topological order, first order roots lived longer than lateral roots at the Mediterranean site (z = −3, P = 0.005) but not at the continental site. At the Mediterranean site, first order roots in the 0–1 mm diameter class had 44.5% less risk of mortality (z = −3.04, P = 0.002) than that of lateral roots for the same class of diameter, but no differences in longevity were found at the continental site. First order roots in the 1–2 mm diameter class had significantly longer longevity (z = −2.7, P = 0.005) than lateral roots of the same class of diameter at the Mediterranean climate, but not at the continental site (Fig. 9d).
Fig. 9

Cox’s hazard regression relationships for estimating root longevity and risk of mortality in relation to (a) climate (oceanic - circles, continental - triangles and Mediterranean - diamonds), (b) phenological periods (early growing season, late growing season and dormant season), (c) root diameter classes (0–1) mm, (1–2) mm and (2–5) mm and (d) root topological order (first and second order roots) over the observation period from October 2014 to June 2016. Different shades represent the interval confidence of each curve corresponding to the color of that curve

Discussion

We did not find any significant differences between climates with regard to the phenology of root dynamics throughout the year. Walnut hybrids had a distinct bimodal pattern of root growth during the aerial growing season in all three climates, with much less root growth during the aerial dormant season.

Temperature and soil water potential effects on root growth dynamics

Mean RER of walnut trees was positively correlated with both mean soil and air temperatures at the oceanic and continental sites only. It is surprising that we did not find any relationships between mean RER and temperature at the Mediterranean site, as Germon et al. (2016) found a highly significant and positive correlation between RER and soil temperature for the same stand of walnut cultivars. However, mean RER was significantly and positively correlated with mean air and soil temperatures during the late growing season, where the highest peaks of root growth were found at the oceanic site only. Mean RER at the oceanic site was also significantly and negatively correlated with mean soil ψ of the preceding month, similar to results found by Joslin et al. (2001) for oak sp. (Quercus prinus L., Q. alba L.) growing in a subtropical climate. However, mean RER at the Mediterranean site was significantly but positively correlated with mean soil ψ, as found in Abies balsamea L. (Olesinski et al. 2011) and Q. alba L. seedlings (Reich et al. 1980). At the continental site, the absence of correlations of RER with any climatic factors is in conflict with other studies which indicate that air and soil temperatures are the prominent factors driving RER (Misra 1999; Hendricks et al. 2006; Mao et al. 2013a; McCormack and Guo 2014; Germon et al. 2016; Gill and Jackson 2000). In our study, for all climates, soil temperature never reached <3 °C or >21 °C during the entire study period. Most root elongation occurred when the soil temperature was within the range 9–17 °C, and we found that the highest rate of elongation occurred when temperatures were between 14 and 17 °C. At the oceanic site, soil temperature varied little throughout the year, with few extreme values, whereas the continental site had large seasonal differences in soil temperature. Mean soil ψ at the Mediterranean site was significantly lower than at the oceanic and continental sites. Soil ψ can limit root elongation by either excessive water resulting in anaerobic conditions or inadequate water to support growth (Joslin et al. 2001). Previous studies have shown that walnut seedlings have a low resistance to water stress and are sensitive to waterlogging both between and within cultivars (Mapelli et al. 1995–1996), a phenomenon that we encountered (waterlogging occurred in the oceanic site and water stress in occurred in the Mediterranean site).

Our results demonstrated a decline in RER with the decrease of mean soil ψ at the Mediterranean site, showing that soil water is limiting for root growth in the superficial layers, as found for other broadleaf species (e.g. Wan et al. 2002). However, at the oceanic site, we showed that RER augmented with the decrease of mean soil ψ and declined with the increase of mean air and soil temperatures, as also found by Joslin et al. (2001) in Q. prinus L. At the oceanic site, soil temperature played a major role in driving root elongation, as found by e.g., Germon et al. (2016), Mao et al. (2013a), but soil ψ played an indirect role. As both factors co-vary during the late growing season, it is difficult to disentangle their distinct effects on root growth. Nevertheless, we suggest that once soil temperature is favorable for root growth and if there are no extreme occurrences of temperature throughout the year, then other limiting factors will drive root growth.

Surprisingly, and contrary to the observations of previous authors (e.g. Germon et al. 2016, working on walnut cultivars, Mao et al. (2013a) studying Picea abies and Abies alba and Kern et al. (2004) studying Populus deltoides Bartr), mean RER was not related to root diameter. While trees growing at the continental site produced many short-lived lateral roots, no lateral root initiation occurred at the Mediterranean and oceanic sites. Soil conditions could have played a role because soil acidity has been shown to increase heavy metal solubility and hinder the development of lateral roots (Kahle 1993). The lower phosphorus content at the continental site would also influence root architecture and lateral root development, as roots increase their exploration and scavenging of the soil (Niu et al. 2013).

Mean RIQ and mean RMQ were related to annual variations in soil temperature, except for the first peak of root initiation which occurred three months after rhizotron installation at the three sites regardless of the phenological period (Johnson 2001; Baddeley and Watson 2005). We consider this result as an artefact of the rhizotron method, which led to an overestimation of the fine root production (Hendrick and Pregitzer 1996a; Majdi 1996; Majdi et al. 2005; Green et al. 2005; Metcalfe et al. 2008). The second peak of mean RIQ was found during the late growing season, regardless of climate, and was followed immediately by a peak in mean RMQ. Therefore, the major pulse of hybrid walnut root production is inherently programmed to occur during the late growing season (June–November) with significantly less production in the aerial dormant season, as also found in many deciduous tree species in temperate zones (e.g., Joslin et al. 2000; Hendrick and Pregitzer 1996a, b; Joslin et al. 2000).

In our study, mean RIQ was significantly higher at the continental site compared to the two other sites during the late growing season, possibly because soil/air temperatures and ψ were optimal for growth at this period. Mean RIQ was correlated with mean soil temperature at the Mediterranean and continental sites only, as was expected (Comas et al. 2005; Mao et al. 2013a), but the lack of significant relationships at the oceanic site is not understood. However, air temperature at the three sites was correlated with mean RIQ during the late growing season. These results are consistent with the observations of Radville et al. (2016a), Fukuzawa et al. (2013) and Steinaker et al. (2010), who demonstrated that soil temperature was a main driver of root initiation in temperate environments. Tierney and Fahey (2002) also showed that mean fine root production of Acer saccharum Marsh. was strongly associated with mean air temperature but not soil moisture or nutrient availability.

We found that mean RMQ did not differ significantly between sites and was highest during the late growing season. These results are contrary to those of Kern et al. (2004) working on P. deltoides in a continental climate, who found that mortality was greatest after the end of the growing season. Mean RMQ was correlated with both mean soil temperature and mean ψ at the continental climate only, as found by Harris et al. (1995) studying A. saccharum in a moderate continental climate, who showed that root mortality increased in warmer soil temperatures. We suggest that the peak of mortality could be a consequence of a trade-off between competing plant sinks to balance carbohydrate availability. Therefore, if other factors are equal (e.g. endogenous factors such as non-structural carbohydrates (NSC) and hormone levels or soil nutrient levels), the growth of new roots and the death of existing roots are accelerated with the increase of soil temperature.

Above and belowground phenological relationships

The timing of root growth was asynchronous with that of budburst at all sites, and the spring roots flush occurred several weeks after budburst. As both budburst and root emergence are very sensitive to local temperatures (Du and Fang 2014; Tierney and Fahey 2002), a rapid increase in air temperature in April/May would stimulate budburst quickly. Soil is buffered against rapid changes in air temperature, therefore the subsequent cambial activity in roots would take longer to occur, and root flushes will usually occur after bud burst (Pregitzer et al. 2000). Maximal root and radial stem growth both took place during the late growing season. Peaks of stem and root radial growth at the Mediterranean site occurred later in the season (September) than at both other sites (July), possibly linked to precipitation events after the hot, dry summer.

Our results suggest a trade-off between competing plant sinks (Radville et al. 2016a). For example, fine root growth was likely fueled by NSC stored before the onset of the aerial growing season, as shown by Gaudinski et al. (2009) and Najar et al. (2014). The decrease in fine root elongation observed in August (oceanic and continental sites) and July (Mediterranean site), may be due to NSC being used for radial growth and fruit production. NSC production from photosynthesis would then increase during the summer, fueling a second root flush, before leaf senescence in November. The decrease in photosynthetic rates at the end of the growing season would result in less NSC being available for radial growth, which decreases rapidly in September – October (Radville et al. 2016a; Du and Fang 2014; Abramoff and Finzi 2015). Minor root elongation can occur during aerial dormancy at all sites, using local NSC stocks as energy for growth (Y. Wang et al., Linking conifer root growth and production to soil temperature and carbon supply in temperate forests, unpublished).

Root longevity and risk of mortality

We showed that root longevity differed significantly between climates and roots lived longest at the continental site, where fine roots were significantly thicker possibly due to the lack of resource investment into lateral root initiation or stonier soil conditions reducing penetration and elongation. Fine root diameter was correlated to longevity, as also shown by e.g., Anderson et al. (2003) and Wells and Eissenstat (2001). Roots in the 0–1 mm and 1–2 mm diameter classes lived for significantly shorter periods compared to those in the 2–5 mm diameter class at continental and Mediterranean sites only. Thicker roots have lower N concentration, lower surface area and higher C content than finer roots and thus longevity is increased because of a decrease in metabolic activity (McCormack et al. 2012; Guo et al. 2004, 2008; Baddeley and Watson 2005).

As root traits may be prominent drivers of ecosystem processes (McCormack et al. 2015), and as topological order can influence traits, considering branching order when studying root survivorship is considered fundamental (Guo et al. 2008). In our study, first order roots lived longer than lateral roots at the Mediterranean site only and first order roots in the both 0–1 mm and 1–2 mm diameter classes had 44% less risk of mortality than that of lateral roots for the same class of diameter). Guo et al. (2008) also showed in longleaf pine (Pinus palustris. Mill.) that higher order roots had 46% greater longevity than roots one order lower. We suppose that first order roots live longer than lateral roots because of the greater resource investment in their construction. Ephemeral lateral roots cost less to construct, and so can grow quickly when needed for soil exploration and resource capture.

The risk of root mortality at the continental site was significantly greater during the growing season compared to the aerial dormant season, as also found in apple (Malus sylvestris. L) (Psarras et al. 2000). However, our results are contrary to those of Wang et al. (2016) who found that the mortality hazard ratio of P. abies and A. alba initiated in the late growing season was reduced by 27% compared to roots that emerged in the early growing season. Root longevity usually decreases with increasing temperature (King et al. 1999; Majdi et al. 2005) therefore, as temperature fluctuations were more extreme at the continental site, roots may die more quickly as summer temperatures increase rapidly. As root density was higher during growing season at the continental site, soil herbivores and pathogens may also be more active (Guo et al. 2008).

Conclusion

In conclusion, although root studies have increased significantly in recent years, it is still difficult to draw any firm conclusions about how variations in climate will affect root dynamics and in turn how changes in dynamics might affect plant production or carbon cycling in soil. The main reason may be the difficulty to generalize this impact in the face of broad variability in responses among plant species, biomes and climates, as well as the variability introduced by methodology (Norby and Jackson 2000). Our results highlight that abiotic factors drive fine root production when they are limiting (e.g. soil water potential at Mediterranean site in our study and soil temperatures at both continental and oceanic site) and if they are not limiting, endogenous factors such as NSC and hormones may play major roles in driving root production. We showed clear differences between shoot and root phenology. Root and leaf phenology was asynchronous at the three climates with the major pulse of root production during the late growing season, regardless of length of both aerial (6.0–7.5 months) and belowground (7.5–8.5 months) growing seasons, suggesting that hybrid walnut root production is inherently programmed to occur during the late growing season with significantly less production in the aerial dormant season in the three climates. Through a multi-covariate analysis of root survivorship, the effects of site and root diameter were the strongest predictors to root survivorship among these factors.

Our results call for further analyses on the role of site conditions (e.g. soil, altitude, topography and plant genotype) in determining tree responses to climate variability. An interesting next step would be to focus on better understanding how edaphic and climatic factors interact in natural environments to influence the fine root phenology of plants at various temporal and spatial scales. In addition, the seasonal phenology of trees is a main driver of C allocation from shoots to roots, thus further research is also required to evaluate more precisely the relationship between the internal dynamics of tree C and nutrient resources and root phenology.

Notes

Acknowledgements

Thanks are due to Jérôme Nespoulous, Luis Merino Martin and Merlin Ramel (INRA) for technical assistance, to Camille Béral (Agroof, France) for help finding field sites and to the farmers M. Queuille and M. Becue for letting us work in their agroforests.

Funding

Funding for a Ph.D. bursary was provided by Campus France and the Kurdish Institute, France (AM), la Fondation de France (YM) and fieldwork was funded by the FOARDAPT project, INRA metaprogram AAFCC (Adaptation of Agriculture and Forests to Climate Change), France.

Compliance with ethical standards

Competing interest

The authors declare that they have no competing interests.

Availability of data and materials

The datasets about root survivorship generated and/or analyzed during the current study are available in the [Zenodo] repository, “https://zenodo.org/record/842737#.WbrdOrJJaCj” . The other datasets generated and/or analyzed during the current study are available from the corresponding author on request.

Supplementary material

11104_2017_3417_MOESM1_ESM.docx (8.5 mb)
ESM 1 (DOCX 8678 kb)
11104_2017_3417_MOESM2_ESM.docx (39 kb)
ESM 2 (DOCX 39 kb)

References

  1. Abramoff RZ, Finzi AC (2015) Are above- and below-ground phenology in sync? New Phytol 205:1054–1061CrossRefPubMedGoogle Scholar
  2. Anderson L, Comas L, Lakso A, Eissenstat D (2003) Multiple risk factors in root survivorship: a 4- year study in concord grape. New Phytol 158:489–501CrossRefGoogle Scholar
  3. Baddeley JA, Watson CA (2005) Influences of root diameter, tree age, soil depth and season on fine root survivorship in Prunus Avium. Plant Soil 276:15–22CrossRefGoogle Scholar
  4. Block RMA, Rees KCJ, Knight JD (2006) A review of fine root dynamics in Populus plantations. Agrofor Syst 67:73–84CrossRefGoogle Scholar
  5. Broschat TK (1998) Root and shoot growth patterns in four palm species and their relationships with air and soil temperatures. Hortscience 33:995–998Google Scholar
  6. Cardinael R, Mao Z, Prieto I, Stokes A, Dupraz C et al (2015) Competition with winter crops induces deeper rooting of walnut trees in a Mediterranean alley cropping agroforestry system. Plant Soil 391:219–235CrossRefGoogle Scholar
  7. Chen HY, Brassard BW (2013) Intrinsic and extrinsic controls of fine root life span. Crit Rev Plant Sci 32:151–161CrossRefGoogle Scholar
  8. Coll L, Camarero AJJ, Aragón JMD (2012) Fine root seasonal dynamics, plasticity, and Mycorrhization in 2 coexisting Mediterranean oaks with contrasting aboveground phenology. Ecoscience 19:238–245CrossRefGoogle Scholar
  9. Comas LH, Anderson L, Dunst R, Lakso A, Eissenstat D (2005) Canopy and environmental control of root dynamics in a long‐term study of Concord grape. New Phytol 167:829–40Google Scholar
  10. Contador ML, Comas LH, Metcalf SG, Stewart WL, Porris Gomez I et al (2015) Root growth dynamics linked to above-ground growth in walnut (Juglans Regia). Ann Bot-London 116:49–60CrossRefGoogle Scholar
  11. Diez JM, Ibáñez I, Miller-Rushing AJ, Mazer SJ, Crimmins TM et al (2012) Forecasting phenology: from species variability to community patterns. Ecol Lett 15:545–553CrossRefPubMedGoogle Scholar
  12. Du E, Fang J (2014) Linking belowground and aboveground phenology in two boreal forests in Northeast China. Oecologia 176:883–892CrossRefPubMedGoogle Scholar
  13. Fridley JD (2012) Extended leaf phenology and the autumn niche in deciduous forest invasions. Nature 485:359–362CrossRefPubMedGoogle Scholar
  14. Fukuzawa K, Shibata H, Takagi K, Satoh F, Koike T, Sasa K (2013) Temporal variation in fine-root biomass, production and mortality in a cool temperate forest covered with dense understory vegetation in northern Japan. For Ecol Manag 310:700–710CrossRefGoogle Scholar
  15. Gaudinski JB, Torn MS, Riley W, Swanston C, Trumbore SE, et al (2009) Use of stored carbon reserves in growth of temperate tree roots and leaf buds: analyses using radiocarbon measurements and modeling. Glob Chang Biol 15:992–1014Google Scholar
  16. Germon A, Cardinael R, Prieto I, Mao Z, Kim J et al (2016) Unexpected phenology and lifespan of shallow and deep fine roots of walnut trees grown in a silvoarable Mediterranean agroforestry system. Plant Soil 401:409–426CrossRefGoogle Scholar
  17. Gill RA, Jackson RB (2000) Global patterns of root turnover for terrestrial ecosystems. New Phytol 147:13–31CrossRefGoogle Scholar
  18. Green IJ, Dawson LA, Proctor J, Duff EI, Elston DA (2005) Fine root dynamics in a tropical rain forest is influenced by rainfall. Plant Soil 276:23–32CrossRefGoogle Scholar
  19. Guo DL, Mitchell RJ, Hendricks JJ (2004) Fine root branch orders respond differentially to carbon source-sink manipulations in a longleaf pine forest. Oecologia 140:450–457CrossRefPubMedGoogle Scholar
  20. Guo D, Mitchell RJ, Withington JM, Fan P-P, Hendricks JJ (2008) Endogenous and exogenous controls of root life span, mortality and nitrogen flux in a longleaf pine forest: root branch order predominates. J Ecol 96:737–745CrossRefGoogle Scholar
  21. Harris JR, Bassuk NL, Zobel RW, Whitlow TH (1995) Root and shoot growth periodicity of green ash, scarlet oak, turkish hazelnut, and tree lilac. J Am Soc Hortic Sci 120:211–216Google Scholar
  22. Hendrick RL, Pregitzer KS (1993a) The dynamics of fine root length, biomass, and nitrogen content in two northern hardwood ecosystems. Can J For Res 23:2507–2520CrossRefGoogle Scholar
  23. Hendrick RL, Pregitzer KS (1993b) Patterns of fine root mortality in 2 sugar maple forests. Nature 361:59–61CrossRefGoogle Scholar
  24. Hendrick RL, Pregitzer KS (1996a) Applications of minirhizotrons to understand root function in forests and other natural ecosystems. Plant Soil 185:293–304CrossRefGoogle Scholar
  25. Hendrick RL, Pregitzer KS (1996b) Temporal and depth-related patterns of fine root dynamics in northern hardwood forests. J Ecol 84:167–176CrossRefGoogle Scholar
  26. Hendricks JJ, Hendrick RL, Wilson CA, Mitchell RJ, Pecot SD, Guo D (2006) Assessing the patterns and controls of fine root dynamics: an empirical test and methodological review. J Ecol 94:40–57CrossRefGoogle Scholar
  27. Hooker JE, Black KE, Perry RL, Atkinson D (1995) Arbuscular mycorrhizal fungi induced alteration to root longevity in poplar. Plant Soil 172:327–329Google Scholar
  28. Hubbart J, Link T, Campbell C, Cobos D (2005) Evaluation of a low- cost temperature measurement system for environmental applications. Hydrol Process 19:1517–1523CrossRefGoogle Scholar
  29. Huck MG, Taylor HM (1982) The rhizotron as a tool for root research. In: Brady NC (ed) Advances in agronomy. Academic Press, Cambridge, pp 1–35Google Scholar
  30. Huck M, Hoogenboom G, Peterson CM (1987) Soybean root senescence under drought stress. In: Taylor HM (ed) Minirhizotron observation tubes: Methods and applications for measuring rhizosphere dynamics. ASA Special Publication No. 50. ASA, CSSA, SSSA, Madison, pp 109–121Google Scholar
  31. Johnson MG (2001) Advancing fine root research with minirhizotrons. Environ Exp Bot 45:263–289CrossRefPubMedGoogle Scholar
  32. Joslin JD, Wolfe M (1998) Impacts of water input manipulations on fine root production and mortality in a mature hardwood Forest. Plant Soil 204:165–174CrossRefGoogle Scholar
  33. Joslin JD, Wolfe MH, Hanson PJ (2000) Effects of altered water regimes on forest root systems. New Phytol 147:117–129CrossRefGoogle Scholar
  34. Joslin JD, Wolfe MH, Hanson PJ (2001) Factors controlling the timing of root elongation intensity in a mature upland oak stand. Plant Soil 228:201–212CrossRefGoogle Scholar
  35. Jourdan C, Silva EV, Goncalves JLM, Ranger J, Moreira RM, Laclau JP (2008) Fine root production and turnover in Brazilian eucalyptus plantations under contrasting nitrogen fertilization regimes. For Ecol Manag 256:396–404CrossRefGoogle Scholar
  36. Kahle H (1993) Response of roots of trees to heavy metals. Environ Exp Bot 33:99–119CrossRefGoogle Scholar
  37. Kern CC, Friend AL, Johnson JM-F, Coleman MD (2004) Fine root dynamics in a developing Populus deltoides plantation. Tree Physiol 24:651–660CrossRefPubMedGoogle Scholar
  38. King J, Pregitzer K, Zak D (1999) Clonal variation in above- and below-ground growth responses of Populus tremuloides Michaux: influence of soil warming and nutrient availability. Plant Soil 217:119–130CrossRefGoogle Scholar
  39. Kuhns MR, Garrett HE, Teskey RO, Hinckley TM (1985) Root-growth of black walnut trees related to soil-temperature, soil-water potential, and leaf water potential. For Sci 31:617–629Google Scholar
  40. Lobet G, Pagès L, Draye X (2011) A novel image-analysis toolbox enabling quantitative analysis of root system architecture. Plant Physiol 157:29–39CrossRefPubMedPubMedCentralGoogle Scholar
  41. Majdi H (1996) Root sampling methods - applications and limitations of the minirhizotron technique. Plant Soil 185:255–258CrossRefGoogle Scholar
  42. Majdi H, Pregitzer K, Morén A-S, Nylund J-E, I. Ågren G. (2005) Measuring fine root turnover in Forest ecosystems. Plant Soil 276:1–8CrossRefGoogle Scholar
  43. Mao Z, Bonis M-L, Rey H, Saint-André L, Stokes A, Jourdan C (2013a) Which processes drive fine root elongation in a natural mountain forest ecosystem? Plant Ecolog Divers 6:231–243CrossRefGoogle Scholar
  44. Mao Z, Jourdan C, Bonis M-L, Pailler F, Rey H et al (2013b) Modelling root demography in heterogeneous mountain forests and applications for slope stability analysis. Plant Soil 363:357–382CrossRefGoogle Scholar
  45. Mapelli S, Lombardi L, Brambilla I, Iulini A, Bertani A. (1995–1996) III International Walnut Congress 4421995:129–36Google Scholar
  46. Mathieu L, Lobet G, Tocquin P, Périlleux C (2015) “Rhizoponics”: a novel hydroponic rhizotron for root system analyses on mature Arabidopsis thaliana plants. Plant Methods 11:1–8CrossRefGoogle Scholar
  47. M’bou AT, Jourdan C, Deleporte P, Nouvellon Y, Saint-André L, et al (2008) Root elongation in tropical Eucalyptus plantations: effect of soil water content. Ann For Sci 65:609–09Google Scholar
  48. McAdam SAM, Brodribb TJ, Ross JJ (2016) Shoot-derived abscisic acid promotes root growth. Plant Cell Environ 39:652–659CrossRefPubMedGoogle Scholar
  49. McCormack ML, Guo D (2014) Impacts of environmental factors on fine root lifespan. Front Plant Sci 5:205CrossRefPubMedPubMedCentralGoogle Scholar
  50. McCormack M, Adams TS, Smithwick EAH, Eissenstat DM (2012) Predicting fine root lifespan from plant functional traits in temperate trees. New Phytol 195:823–831CrossRefGoogle Scholar
  51. McCormack ML, Adams TS, Smithwick EAH, Eissenstat DM (2014) Variability in root production, phenology, and turnover rate among 12 temperate tree species. Ecology 95:2224–2235CrossRefPubMedGoogle Scholar
  52. McCormack ML, Gaines K, Pastore M, Eissensat DM (2015) Early season fine root and leaf phenology in six diverse temperate tree species. Plant Soil 389:121–129CrossRefGoogle Scholar
  53. Menzel A (2003) Plant Phenological anomalies in Germany and their relation to air temperature and NAO. Clim Chang 57:243–263CrossRefGoogle Scholar
  54. Metcalfe DB, Meir P, Aragão LEO, da Costa AC, Braga AP et al (2008) The effects of water availability on root growth and morphology in an Amazon rainforest. Plant Soil 311:189–199CrossRefGoogle Scholar
  55. Misra RK (1999) Root and shoot elongation of rhizotron-grown seedlings of Eucalyptus nitens and Eucalyptus globulus in relation to temperature. Plant Soil 206:37–46CrossRefGoogle Scholar
  56. Misson L, Gershenson A, Tang J, McKay M, Cheng W, Goldstein A (2006) Influences of canopy photosynthesis and summer rain pulses on root dynamics and soil respiration in a young ponderosa pine forest. Tree Physiol 26:833–844CrossRefPubMedGoogle Scholar
  57. Mohamed A, Monnier Y, Mao Z, Lobet G, Maeght J-L et al (2017) An evaluation of inexpensive methods for root image acquisition when using rhizotrons. Plant Methods 13:11CrossRefPubMedPubMedCentralGoogle Scholar
  58. Morin X, Roy J, Sonié L, Chuine I (2010) Changes in leaf phenology of three European oak species in response to experimental climate change. New Phytol 186:900–910CrossRefPubMedGoogle Scholar
  59. Mulia R, Dupraz C (2006) Unusual fine root distributions of two deciduous tree species in southern France: what consequences for modelling of tree root dynamics? Plant Soil 281:71–85CrossRefGoogle Scholar
  60. Najar A, Landhäusser SM, Whitehill JG, Bonello P, Erbilgin N (2014) Reserves accumulated in nonphotosynthetic organs during the previous growing season drive plant defenses and growth in aspen in the subsequent growing season. J Chem Ecol 40:21–30Google Scholar
  61. Niu YF, Chai RS, Jin GL, Wang H, Tang CX, Zhang YS (2013) Responses of root architecture development to low phosphorus availability: a review. Ann Bot 112:391–408Google Scholar
  62. Norby RJ, Jackson RB (2000) Root dynamics and global change: seeking an ecosystem perspective. New Phytol 147:3–12Google Scholar
  63. Olesinski J, Lavigne MB, Krasowski MJ (2011) Effects of soil moisture manipulations on fine root dynamics in a mature balsam fir (Abies balsamea L. Mill.) forest. Tree Physiol 31:339–48Google Scholar
  64. Pregitzer KS, King JS, Burton AJ, Brown SE (2000) Responses of tree fine roots to temperature. New Phytol 147:105–115CrossRefGoogle Scholar
  65. Psarras G, Merwin IA, Lakso AN, Ray JA (2000) Root growth phenology, root longevity, and Rhizosphere respiration of field grown Mutsu' apple trees on Malling rootstock. J Am Soc Hortic Sci 125:596–602Google Scholar
  66. R Development Core Team (2013) R: a language and environment for statistical computing. R Foundation for Statistical Computing, ViennaGoogle Scholar
  67. Radville L, McCormack ML, Post E, Eissenstat DM (2016a) Root phenology in a changing climate. J Exp Bot 67(12):3617–3628CrossRefPubMedGoogle Scholar
  68. Radville L, Post E, Eissenstat DM (2016b) Root phenology in an Arctic shrub-graminoid community: the effects of long-term warming and herbivore exclusion. Clim Chang Res 3:1–9CrossRefGoogle Scholar
  69. Reich P, Teskey R, Johnson P, Hinckley T (1980) Periodic root and shoot growth in oak. For Sci 26:590–598Google Scholar
  70. Richardson AD, Bailey AS, Denny EG, Martin CW, O'Keefe J (2006) Phenology of a northern hardwood forest canopy. Glob Chang Biol 12:1174–1188CrossRefGoogle Scholar
  71. Sloan VL, Fletcher BJ, Phoenix GK (2016) Contrasting synchrony in root and leaf phenology across multiple sub-Arctic plant communities. J Ecol 104:239–248CrossRefGoogle Scholar
  72. Steinaker DF, Wilson SD (2008) Phenology of fine roots and leaves in forest and grassland. J Ecol 96:1222–1229CrossRefGoogle Scholar
  73. Steinaker DF, Wilson SD, Peltzer DA (2010) Asynchronicity in root and shoot phenology in grasses and woody plants. Glob Chang Biol 16:2241–2251CrossRefGoogle Scholar
  74. Strand AE, Pritchard SG, McCormack ML, Davis MA, Oren R (2008) Irreconcilable differences: fineroot life spans and soil carbon persistence. Science 319Google Scholar
  75. Tanner SC, Reighard GL, Wells CE (2006) Soil treatments differentially affect peach tree root development and demography in a replant site. In: Infante R (ed) Proceedings of the VIth international peach symposium, Acta, pp 381–387Google Scholar
  76. Tierney GL, Fahey TJ (2002) Fine root turnover in a northern hardwood forest: a direct comparison of the radiocarbon and minirhizotron methods. Can J For Res 32:1692–1697CrossRefGoogle Scholar
  77. Vogt K, Vogt D, Palmiotto P, Boon P, O'Hara J, Asbjornsen H (1995) Review of root dynamics in forest ecosystems grouped by climate, climatic forest type and species. Plant Soil 187:159–219CrossRefGoogle Scholar
  78. Vogt KA, Vogt DJ, Bloomfield J (1998) Analysis of some direct and indirect methods for estimating root biomass and production of forests at an ecosystem level. In: Box J Jr (ed) Root demographics and their efficiencies in sustainable agriculture, grasslands and forest ecosystems. Springer Netherlands, Berlin, pp 687–720CrossRefGoogle Scholar
  79. Wan CG, Yilmaz I, Sosebee RE (2002) Seasonal soil-water availability influences snakeweed, root dynamics. J Arid Environ 51:255–264CrossRefGoogle Scholar
  80. Wang Z, Ding L, Wang J, Zuo X, Yao S, Feng J (2016) Effects of root diameter, branch order, root depth, season and warming on root longevity in an alpine meadow. Ecol Res 31:739–747CrossRefGoogle Scholar
  81. Wells CE, Eissenstat DM (2001) Marked differences in survivorship among apple roots of different diameters. Ecology 82:882–892CrossRefGoogle Scholar
  82. West JB, Espeleta JF, Donovan LA (2004) Fine root production and turnover across a complex edaphic gradient of a Pinus palustris–Aristida stricta savanna ecosystem. For Ecol Manag 189:397–406CrossRefGoogle Scholar
  83. Wielgolaski F-E (1999) Starting dates and basic temperatures in phenological observations of plants. Int J Biometeorol 42:158–168CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.AMAP, INRA, CNRS, IRD, CIRADUniversity of MontpellierMontpellierFrance
  2. 2.Eco&Sols, CIRAD, INRA, IRD, Montpellier SupAgroUniversity of MontpellierMontpellierFrance
  3. 3.UMR System, INRAMontpellier cedex 2France

Personalised recommendations