Sap Flux Density Radial Profiles Explained.
Introduction.
One of the fundamental concepts in sap flow research is the radial profile of sap flow, which refers to the variation of water transport within the tree’s sapwood from the cambium (bark) to the inner xylem or heartwood (Figure 1). This profile plays a significant role in determining the overall water use of a tree and is essential for accurate measurements of sap flux density. The radial profile is particularly significant for trees growing in Europe, North America, and Asian regions such as Japan and South Korea.
Figure 1. A diagram of the radial profile from a cross section of a tree. The radial profile starts at the outside of the bark (cambium) and ends in the middle of the tree, typically in the heartwood.
Importance of radial sap flux density variation.
The xylem tissue responsible for water transport in trees is not uniform in function across the sapwood radius. Instead, different zones contribute differently to sap flow, depending on factors such as tree species, age, environmental conditions, and xylem anatomy. Understanding radial profiles is crucial for:
- Improving Accuracy in Sap Flow Measurements: Many sap flow measurement techniques, such as heat ratio methods or thermal dissipation probes, rely on a single- or two-point measurement sensor. Only sampling a sub-section, or small portion, of the radial profile can lead to significant errors in estimating whole-tree water use.
- Assessing Tree Hydraulics and Water Use Strategies: Some trees exhibit high sap flow activity near the bark and reduced flow toward the heartwood, while others show a more uniform or even inverse profile. For example, trees in California may have a different radial profile to trees growing in Germany, South Korea or Japan. These variations provide insights into tree physiology, coping with drought and stress, and phenological and genotypic adaptation to different environments.
- Enhancing Hydrological and Ecophysiological Models: Many large-scale hydrological and climate models rely on accurate tree water use estimates. Understanding radial variation allows for better parameterization of such models, leading to improved predictions of forest responses to climate change.
In practical applications, foresters and ecologists can use radial flow data to:
- Identify drought-resistant species based on their ability to maintain water transport efficiency.
- Improve irrigation strategies by understanding water distribution within the tree.
- Assess forest health by detecting anomalies in sap flow profiles that may indicate disease or environmental stress across regions in Europe, North America, Japan, and South Korea.
Typical radial sap flux patterns in trees.
While each species exhibits unique characteristics, a commonly observed pattern is a peak sap flow in the outer sapwood and a decline in sap flow to the heartwood (Figure 2). Sap flow in the heartwood is zero because, by definition, heartwood is an area of non-conducting xylem.
Figure 2. An idealised schematic (not to scale) showing the sap flux density radial profile at midday under conditions of optimal temperature and soil moisture. The data show a convex pattern of peak sap flow towards the outer region of sapwood. In the heartwood, sap flow is zero because this is a region of non-conducting xylem.
However, other radial profiles have been observed in different wood types such as diffuse porous and ring porous trees. Common patterns of sap flow radial profiles include (Figure 3):
- Convex Profile: Highest sap flux near the cambium, gradually decreasing toward the center (common in diffuse-porous species like poplar and beech).
- Concave Profile: Higher sap flux at intermediate depths with lower flow near the cambium and center (observed in some conifers).
- Steep Decline Profile: Sharp drop in sap flux with depth, typical in ring-porous species (e.g., oak).
- Uniform Profile: Nearly constant sap flow across the sapwood, often found in younger trees or species with homogeneous xylem structure.
Figure 3. Idealised schematics (not to scale) showing different types of sap flux density radial profiles. (A) Convex profile. (B) Concave profile. (C) Steep profile. (D) Uniform profile.
Factors influencing sap flux density radial profiles.
Several biological and environmental factors determine the shape of a tree’s sap flow radial profile:
1. Xylem Anatomy and Age
Xylem vessels near the cambium are typically younger and more conductive compared to the inner sapwood. In diffuse-porous species (e.g., maple, birch), xylem vessels are relatively uniform in size, leading to more even radial profiles. In contrast, ring-porous species (e.g., oak, ash) have large earlywood vessels near the cambium and a steep decline in conductivity toward the center, leading to a more pronounced profile.
2. Tree Size and Growth Patterns
Larger trees often exhibit a more complex radial distribution due to the need for extensive hydraulic support. Fast-growing species may maintain high water transport efficiency throughout the sapwood, whereas slow-growing species often concentrate flow near the outer sapwood.
3. Environmental Conditions
Soil moisture, temperature, and atmospheric demand influence sap flow profiles. Under drought stress, trees may exhibit more uniform radial flow as inner xylem conduits are recruited to compensate for reduced outer xylem functionality. Alternatively, in well-watered conditions, the flow may be concentrated near the cambium where newly formed vessels are most efficient.
4. Wounding and Xylem Dysfunction
Tree wounds, decay, and embolism (air bubble formation) can significantly alter radial sap flow patterns. Older xylem may become nonfunctional due to air entry or pathogen attack, reducing water transport in the inner layers.
How to measure the radial profile.
Three primary methods exist for measuring the radial profile of sap flow: the IX-SF60 Implexx Sap Flow Sensor, Granier (thermal dissipation, TDP) probes, and heat field deformation (HFD) sensors.
TDP probes, also known as Granier probes, are widely used but are not well-suited for accurately capturing the radial profile of sap flow. Due to inherent methodological limitations, TDP sensors can introduce errors exceeding 60% (Steppe et al., 2010). Furthermore, TDP probes measure sap flux at a single point, requiring multiple sensors positioned circumferentially or across different trees to infer a radial profile. Consequently, data obtained from Granier probes represent a combination of radial and azimuthal (circumferential) measurements rather than a true radial profile at a single location.
HFD sensors offer an improvement over TDP by enabling the measurement of a true radial profile from a single installation point. However, HFD sensors are among the most expensive sap flow measurement tools, with costs ranging from a whopping 400% to 2000% higher than alternative sensor technologies. The high cost restricts sample sizes and replication, which can negatively impact statistical robustness and the overall quality of research findings.
The IX-SF60 Implexx Sap Flow Sensor (Figure 4) provides a cost-effective solution for measuring the true radial profile at a single location. Moreover, it is the only sensor capable of simultaneously measuring the radial profile of stem water content. Additional advantages of the IX-SF60 include:
- The ability to measure sap flux density under zero, slow, extremely fast, and negative flow conditions.
- The capacity to quantify stem water content across the radial profile.
- The ability to record stem temperature across the radial profile.
- A cost-effective, digital design compatible with a wide range of data loggers and IoT platforms.
This combination of capabilities makes the IX-SF60 an efficient and versatile tool for sap flow research.
Figure 4. The different types of sap flow sensors available from Implexx. The IX-SF60 Implexx Sap Flow Sensor is ideally suited for sap flux density radial profile measurements.
Example sap flux density radial profile data.
An IX-SF60 Implexx Sap Flow Sensor was installed on an apple tree (Malus domestica 'Pink Lady') to assess the radial profile of sap flow. Figure 5 presents the radial sap flux density profile from a representative summer day, during which ambient air temperature reached approximately 28 °C and soil moisture was at field capacity. To simplify data visualization, measurements from three key time points—predawn (4:00 AM), mid-morning (10:00 AM), and peak flow period (1:00 PM)—are shown. The data exhibit a concave radial profile, with maximum sap flux density occurring near the mid-point of the sapwood.
Figure 5. Examples of a radial sap flux density profile from an apple tree as measured with an IX-SF60 Implexx Sap Flow Sensor. Three representative periods are displayed: 4am (blue), 10am (purple), and 1pm (brown). The radial distance of 0 is the cambium (bark) and xylem interface. P1, P2, P3, P4 and P5 are the sensor measurement positions from the IX-SF60 Implexx Sap Flow Sensor.
Figure 6 displays sap flux density data recorded over three consecutive days, reinforcing the radial profile pattern observed in Figure 5. Peak sap flow consistently occurred at sensor position P3, located approximately 2.5 cm beneath the cambium. This pattern remained stable throughout the measurement period, indicating a persistent trend in sap flux distribution across the sapwood.
Figure 6. Three consecutive days of sap flux density radial profile as measured on an apple tree with the IX-SF60 Implexx Sap Flow Sensor.
Conclusion.
Sap flow radial profiles provide essential insights into tree water transport dynamics and hydraulic function. Characterising the radial profile is important in regions including North America, California, South Korea and Japan. Understanding these profiles is crucial for improving the accuracy of sap flow measurements and for broader ecological and hydrological applications. By integrating advanced measurement techniques and considering species-specific flow patterns, researchers can enhance our understanding of forest water use and tree physiology, ultimately contributing to better forest management and climate adaptation strategies.
Further Reading.
Berdanier et al., 2016. Tree Physiology
Forster, 2020. Tree Physiology
Forster et al., 2022. Agricultural and Forest Meteorology
Steppe et al., 2010. Agricultural and Forest Meteorology
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