Using a Bottom-Up Approach to Scale Leaf Photosynthetic Traits of Oil Palm, Rubber, and Two Coexisting Tropical Woody Species

Abstract

Rainforest conversion to woody croplands impacts the carbon cycle via ecophysiological processes such as photosynthesis and autotrophic respiration. Changes in the carbon cycle associated with land-use change can be estimated through Land Surface Models (LSMs). The accuracy of carbon flux estimation in carbon fluxes associated with land-use change has been attributed to uncertainties in the model parameters affecting photosynthetic activity, which is a function of both carboxylation capacity (V_cmax) and electron transport capacity (J_max). In order to reduce such uncertainties for common tropical woody crops and trees, in this study we measured V_cmax25 (V_cmax standardized to 25 °C), J_max25 (J_max standardized to 25 °C) and light-saturated photosynthetic capacity (A_max) of Elaeis guineensis Jacq. (oil palm), Hevea brasiliensis (rubber tree), and two native tree species, Eusideroxylon zwageri and Alstonia scholaris, in a converted landscape in Jambi province (Sumatra, Indonesia) at smallholder plantations. We considered three plantations; a monoculture rubber, a monoculture oil palm, and an agroforestry system (jungle rubber plantation), where rubber trees coexist with some native trees. We performed measurements on leaves at the lower part of the canopy, and used a scaling method based on exponential function to scale up photosynthetic capacity related traits to the top of the canopy. At the lower part of the canopy, we found (i) high V_cmax25 values for H. brasiliensis from monoculture rubber plantation and jungle rubber plantation that was linked to a high area-based leaf nitrogen content, and (ii) low value of A_max for E. guineensis from oil palm plantation that was due to a low value of V_cmax25 and a high value of dark respiration. At the top of the canopy, A_max varied much more than V_cmax25 among different land-use types. We found that photosynthetic capacity declined fastest from the top to the lower part of the canopy in oil palm plantations. We demonstrate that photosynthetic capacity related traits measured at the lower part of the canopy can be successfully scaled up to the top of the canopy. We thus provide helpful new data that can be used to constrain LSMs that simulate land-use change related to rubber and oil palm expansion.

1. Introduction

Tropical forest conversions to different land use significantly impact water and carbon cycle dynamics by modifying carbon sequestration and carbon emission rates [1,2]. In Southeast Asia, Indonesia has one of the highest annual losses of rainforests worldwide [3], where forests have been deforested and converted to woody croplands, namely oil palm and rubber plantations [4]. One of the hotspots of land-use change in Indonesia has been Jambi’s province in Sumatra Island, where the area of rubber plantations increased by 19%, and that of oil palm plantations by 85%, from 2000 to 2010 [5]. Land-use change (LUC) from native forest vegetation to rubber and oil palm plantations has increased the income of farmers of Jambi [4,6,7] while at the same time leading to significant ecological costs: decreases in above-ground and below-ground carbon stocks [8,9,10], reduction in soil nitrogen availability [11] and increases in soil N₂O emissions following N fertilization [12]. Partly because of a lack of field data, it is still unclear to what extent these changes will impact water and carbon transfer between land surface and atmosphere. In consequence, and despite their importance for biogeochemical cycles, the impacts of LUC in the tropics are not well represented in Land Surface Models (LSMs).

In LSMs, the exchange of gases between plants and the atmosphere is represented at the leaf and canopy levels. One common method used to calculate fluxes of carbon and water vapor is the coupling of a mechanistic C₃ model of assimilation FvCB [13] to a stomatal conductance model (gs; Ball, Woodrow & Berry 1987 [14]). In the FvCB model, net leaf photosynthesis (A_n) of C₃ plants is simulated with the assumption that A_n is equal to the lowest rate of three limiting biochemical processes: (1) the ribulose 1.5-bisphosphate (RuBP) saturation rate under low intercellular CO₂ concentrations (C_i), where the rate of A_n is predicted by the properties of the Rubisco enzyme (V_cmax); (2) the rate of regeneration of RuBP at high C_i, driven by light harvesting and electron transport (J_max); or (3) triose phosphate use limitation (TPU) [15]. Recent studies have shown that TPU rarely limits net photosynthesis [16,17]. To our knowledge, many LSMs do not consider TPU limitation or represent it non-mechanistically [18,19], as the evidence for the occurrence of TPU limitation in mature plants from natural ecosystems is scarce (Ellsworth et al. 2015 [20]).

Thus, photosynthetic capacity in LSMs is mainly represented by V_cmax and J_max, whose values are estimated from A_n/C_i curves. These parameters are often coupled, allowing J_max to be estimated from V_cmax [21,22]. V_cmax and J_max values in LSMs are frequently treated as fixed per plant functional type or linearly related to leaf nitrogen [23,24]. While V_cmax and J_max have been shown to have a substantial impact on global projections of the carbon cycle [25,26], the natural variability of these parameters is still not known for many plants or ecosystem types.

Since photosynthetic capacity is commonly expressed as the light-saturated photosynthetic rate (A_max) [27,28,29,30], we measured light response curves in addition to CO₂ response curves. Although we are aware that recently there has been standardization in the format of leaf gas exchange parameters [31], in this study we refer to A_max as the typical maximum photosynthetic rate under optimal conditions in the field [30,32,33,34], so that we can compare our estimates with the literature. We estimated A_max, V_cmax25 and J_max25 (J_max standardized to 25 °C) of rubber trees (H. brasiliensis) and oil palms (E. guineensis) in smallholder farmers monoculture plantations, as well as from a jungle rubber plantation [35], where rubber trees coexist with native trees [35,36]. In our study region, the tree species A. scholaris and E. zwageri are commonly found to coexist with rubber trees [9,29,37]. A. scholaris is considered to be a light-demanding species, and is principally grown for timber production [29], while E. zwageri is a mid-canopy species [37] and grows relatively slowly [38,39].

In this study, our aim is to determine the photosynthetic capacity and foliar traits of oil palm, rubber and two coexisting woody species growing in tropics. We limited our field measurements at the lower part of the canopy due to logistic constraints. Since estimates of V_cmax25 and J_max25 at the lower part of the canopy are not directly useful to the LSMs, we used a scaling method based on exponential function to scale up photosynthetic capacity-related traits to the top of the canopy [25,40,41]. The scaling method assumes that photosynthetic capacity at the canopy top is scaled with depth, such that photosynthetic capacity at the canopy top decreases exponentially with cumulative leaf area index [25]. The main objectives of our study were: (i) to estimate key physiological parameters (V_cmax25, J_max25, A_max) and leaf traits (LMA, leaf N), in two tropical tree crops (rubber and oil palm) and two native tree species at the lower part of the canopy; and (ii) to scale up photosynthetic capacity-related traits measured at the lower part of the canopy to the top of the canopy using a ‘bottom-up’ approach.

2. Methods

2.1. Experimental Sites

We conducted our measurements in Jambi Province of the island of Sumatera, Indonesia. The region’s climate is tropical maritime, and the rainy season goes from October through April, with the rest of the year being relatively dry [42,43,44]. The average monthly rainfall in the drier season (161 mm month⁻¹) is 38% lower than in the rainy season (261 mm month⁻¹). The mean annual temperature and mean annual precipitation measured at Jambi airport are 26.7 ± 0.2 °C and 2235 ± 381 mm, respectively [42,45]. Measurements were conducted in three land-use types on loam Acrisol soils: a monoculture oil palm plantation (S 01°54′34.6′′ E 103°15′58.3′′), a monoculture rubber plantation (S 01°54′39.5′′ E 103°16′00.1′′), and a jungle rubber plantation, where rubber trees are planted within secondary forests (S 01°55′40.0′′ E 103°15′33.8′′) [9]. All study sites were owned by local smallholders. The oil palm plantation was 16 years old at sampling, with an average height of 12 meters [9]. The oil palm plantation received fertilization rates of 68-30-99 kg N, P, K ha⁻¹ year⁻¹ [46].

The rubber trees in the monoculture rubber plantation and jungle rubber were of similar age (about 14 years old), with an average height of 13 meters, and the monoculture rubber plantation, jungle rubber plantation and oil palm stem density were about 440 ha⁻¹ and 525 ha⁻¹ and 140 ha⁻¹, respectively [9]. Rubber cultivars differ in clone types [47]. In Sumatra, the most widely planted clone is PB 260 [48], which is characterized by a high production potential and strength against wind disturbances [49]. It is also one of the latex-producing clones recommended for their high yield characteristic [50]. In contrast, there is no single oil palm cultivar used in Jambi. Based on local farmers’ communication, the oil palm cultivars are DP Marihat, DP Bah Jambi, DP Sucfindo LaMe, DP Dolok Sinumbah and DP LAVROS.

In the jungle rubber plantation, two native trees, E. zwageri (EZ) and A. scholaris (AS), coexisted with the rubber trees. In this study, we use the term “native trees or forests” to refer to these two native tree species together. The native trees were about 20 meters tall, with a stem density of 525 ha⁻¹. Based on their Latin names, we use ‘HBm’ and ‘HBj’ to refer to rubber from the monoculture rubber plantation and jungle rubber plantation, respectively, while we use ‘EG’ to refer to oil palm. The trees E. zwageri and A. scholaris are referred to as EZ and AS, respectively. We also use ‘OPP’ and ‘RP’ to refer to oil palm plantation and rubber plantation, respectively, while we use ‘JRP’ to refer to jungle rubber plantation.

2.2. Sampling Procedure and Gas Exchange Measurements

We performed measurements on two trees or two palms that occurred close to the center of the 50 m × 50 m plot from 8th to 29th May 2017. The measurements were conducted between 8:00 am and 2:00 pm local time. In the case of rubber and native trees, we selected a branch from the lower part of every tree and used a 5-meter ladder to access the branch. We assumed that at the lower part of the canopy, canopy bottoms are shade-prone, and thus all leaves are at least temporarily shaded. Two fully expanded matured leaves were identified per branch. Matured leaves were identified based on visual assessment of leaf color and size—this method has been used by Albert et al. [51].

CO₂ and H₂O gas exchanges were measured using a portable photosynthesis system (LI-6800; LiCor Biosciences, Lincoln, NE, USA) with a 3 × 3 cm² leaf chamber. The LI-6800 is an open gas exchange system, whereby the measurements of photosynthesis and transpiration are based on the differences in CO₂ and H₂O in an air stream that is entering (reference) and exiting the leaf (sample). The air stream flows through both the reference and sample gas analyzers and splits in the sensor head rather than the console, meaning that the conditioned air does not flow through two different tubes until the head. The head has a valve system that partitions the flow between the reference and sample gas analyzers. The valves also vent chamber air when matching the gas analyzers. It took about 20 minutes for the leaf to reach steady state conditions. Then, a light response curve was generated to determine the light saturation point (1500–1600 μmol photon m⁻² s⁻¹). After the completion of the light response curve, we again allowed about 20 minutes for the same leaf to reach steady state conditions. Next, a CO₂ response curve on the same leaf was generated. Response curves of net photosynthesis (gross photosynthesis minus respiration, A_net) versus C_i (A_net/C_i), where C_i is the CO₂ concentration inside the leaf, and net photosynthesis versus photosynthetically active radiation (Q_in) (A_net/Q_in), was determined on four leaves from the same branch during each measurement period. For the A_net/C_i curves, leaves were acclimated in the chamber for about 10 minutes until A_net did not change over time. The A_net/C_i curves measurements were performed at a leaf temperature of 25 °C, a relative humidity of 70% and a photosynthetically active radiation of 1500 μmol photon m⁻² s⁻¹ in all cases. The CO₂ response curve (A_net/C_i) was then initiated with eight levels of CO₂ (400, 200, 0, 400, 600, 800, 1000 and 1200 μmol CO₂ mol⁻¹ air). After completing the A_net/C_i curve, CO₂ concentration was kept constant at 400 μmol mol⁻¹ air, and Q_in was sequentially lowered from 1500 to 1300, 1100, 900, 700, 500, 300, 100 and 0 μmol photon m⁻² s⁻¹. We completed all of the CO₂ response curves and then performed the light response curves. Because photosynthesis has diurnal patterns e.g., [52], we ensured that am and pm measurements were equally represented.

In the case of oil palm, we selected a matured frond from the lower part of every palm and like in the case of trees, we used a 5-meter ladder to access the frond. Two fully matured leaf-lets from the center of the frond were identified per frond. As for trees, it took about 20 minutes for a leaf-let to reach steady state conditions. Next, a light response curve was generated to determine the light saturation point (1500–1600 μmol photon m⁻² s⁻¹). After the completion of the light response curve, we allowed 20 minutes for the same leaf to reach steady state conditions. Finally, a CO₂ response curve on the same leaf-let was generated. We completed all of the CO₂ response curves and then performed the light response curves by following the similar protocol as for trees. Like for trees, we ensured that am and pm measurements for oil palms were equally represented. We also performed measurements on juvenile (young) trees/palms of all species. However, these young trees/palms were ‘parasiting’ under the planted canopy, instead of being planted on clearings left by missing adult trees, and therefore we did not consider comparing those data-sets with those used in the present study.

2.3. Response Curve Analyses

The estimates of V_cmax25, J_max25, and R_d were generated for the A/C_i curves by fitting the FvCB model [13,53] using the Plantecophys R package [54]. The general form of FvCB model used is expressed as

$$A_{\mathrm{net}}=\min \left(A_{\mathrm{c}},A_{\mathrm{j}}\right)-R_{\mathrm{d}},$$

(1)

where A_net is the net rate of CO₂ assimilation, A_c is the gross photosynthesis rate when Rubisco activity is limiting, A_j when RuBP-regeneration is limiting and R_d the rate of dark respiration. A_c and A_j are non-linear functions of the chloroplastic CO₂ concentration (C_c), both of the form k₁ (C_cΓ*)/(k₂+C_c), where Γ* is the CO₂ compensation point without R_d, and k₁ and k₂ are different parameter combinations for A_c and A_j. For a detailed description of these functions and the various parameters’ temperature dependence, readers are referred to Medlyn et al. [55]. We used the default settings of the fitaci function from the Plantecophys package but provided the values of CO₂ concentration in the cuvette (CO₂S), C_i, leaf temperature, net photosynthesis, photosynthetically active radiation as an input. The fitaci function fits the FvCB model using the hyperbolic minimum of A_c and A_j, yielding estimates of V_cmax, J_max, and R_d and their standard errors. The hyperbolic minimum of A_c and A_j is described by:

$$A_{\mathrm{m}}=\frac{A_{\mathrm{c}}+A_{\mathrm{j}}-\sqrt{{\left(A_{\mathrm{c}}+A_{\mathrm{j}}\right)}^2-4\theta A_{\mathrm{c}}{A}_{\mathrm{j}}}}{2\theta }-R_{\mathrm{d}},$$

(2)

where θ is a shape parameter, set to 0.99, and A_m is the hyperbolic minimum of A_c and A_j.

The response of A_net to Q_in was fitted to the non-rectangular hyperbolic function [56] described as

$$\theta {\left(A_{\mathrm{net}}+R_{\mathrm{d}}\right)}^2-\left(\epsilon Q_{\mathrm{in}}+A_{\max }\right)\left(A_{\mathrm{net}}+R_{\mathrm{d}}\right) + \epsilon Q_{\mathrm{in}}{A}_{\max }=0,$$

(3)

from which A_net is calculated as

$$A_{\mathrm{net}}=\frac{\epsilon Q_{\mathrm{in}}+A_{\max }-\sqrt{{\left(\epsilon Q_{\mathrm{in}}+A_{\max }\right)}^2-4\theta \epsilon Q_{\mathrm{in}}{A}_{\max }}}{2\theta }+R_{\mathrm{d}},$$

(4)

where A_max is the maximum rate of photosynthesis at saturating irradiance, R_d is the rate of respiration in the dark, θ defines the convexity of the response curve, and ε, the initial slope of the curve, is the photosynthetic light-use efficiency.

2.4. Leaf Nutrient Status and Specific Leaf Area

Following the gas exchange measurements, the same leaves were taken as samples in a dry paper envelope. The specific leaf area (SLA) was measured by cutting a disk with a size of 11.34 cm², then using a ratio of cut-area dry weight to total dry weight from the laboratory—a method that we adopted from Norby et al. [57]. This study refers to the inverse of SLA as the leaf mass per area ratio (LMA). The sampled leaves were dried for 72 h at 60 °C in an oven. The leaf carbon and nitrogen concentrations were analyzed using a CN analyzer (Vario EL Cube; Elementar Analysis Systems GmbH, Hanau, Germany). Leaf phosphorus, potassium and other element concentrations (e.g., Sulphur, Calcium, etc.) were determined by pressure digestion with concentrated HNO₃, and the digests were analyzed using inductively coupled plasma atomic emission spectrometry (iCAP 6300 Duo VIEW ICP Spectrometer, Thermo Fischer Scientific GmbH, Dreieich, Germany).

To keep it simple, in this study we followed Norby et al.’s [57] approach in determining the leaf nutrient contents. Norby et al. [57] also performed measurements in a tropical setting. We acknowledge that measurements on leaf chlorophyll or chlorophyll ratios might have provided further insights. These measurements could be a valuable direction for future research—where we compare and contrast strengths and weaknesses of the various methods used to derive leaf contents.

2.5. Theory for Within-Canopy Gradients in Photosynthetic Capacity

Generally, plant canopies have vertical gradients in physiological processes that relates to maximum carboxylation rates (V_cmax25), maximum light-saturated photosynthetic rates (A_max), area-based leaf nitrogen content (N_a) and LMA [58,59]. Canopy models often decrease leaf photosynthetic capacity with depth in the canopy using an exponential profile of leaf nitrogen content [25,40,41]. In land surface models (e.g., CLM4) [25], V_cmax25 is specified at the canopy top and is scaled with depth using the function

$$V_{cmax}\left(LAI\right)=V_{cmax25\_top}exp\left(-K_{n}LAI\right),$$

(5)

where LAI is the cumulative leaf area index and K_n is the extinction coefficient for V_cmax. A relatively high K_n value indicates a more rapid extinction of solar radiation than a relatively low K_n value, and implies a steeper decline in photosynthetic capacity through the canopy with respect to the leaf area index (LAI) [25]. This exponential saturation model does not consider some of the processes that could improve the scaled up estimate. First, it does not consider variations in leaf lifetimes [60], leaf angles and size [61,62] along the vertical canopy profile. Second, the method does not consider individual tree heights [63,64] and within- and between-species variations in nutrient concentrations [65]. Third, it does not include effects of direct versus diffuse radiation [66]. Finally, although the decline in photosynthetically critical elements such as nitrogen and phosphorus with increasing depth in plant canopies can be considerable, this decline may be never to the same extent that it matches the reduction in radiation with canopy depth [67,68]. However, the scaling up algorithm has been successfully applied in a number of studies [65,69,70,71], so by combining ‘isolated dataset for only one stratum’ from this study with ‘K_n’ estimates from previous studies, we are able to present a model that is more conceptual rather than quantitative, and can be used for the parameterization of the gas exchange when developing models for CO₂ exchange in tropical settings. The maximum electron transport rate (J_{max_top}), leaf respiration rate (R_{d_top}), and other photosynthetic parameters (A_{max_top}, LMA_{_top}, N_{a_top}) at the top of the canopy are similarly scaled with canopy depth. Using previous studies, we estimate K_n values for our oil palm plantation, rubber plantation and jungle rubber plantation canopies (see in Appendix A for details).

2.6. Measured Data-Sets

LAI measurements were performed in May until mid-June 2018 at five locations in five subplots (a total of 25 measurements per land-use type (or per plantation plot)) in a 50 m × 50 m plot using the LAI-2200 plant canopy analyzer (LiCOR, Biosciences, Lincoln, NE, USA). We placed the LAI-2200 plant canopy analyzer in different positions so as to capture the spatial heterogeneity, and these 25 measurements were representative of the plant community. The measurements were conducted in oil palm plantation, rubber plantation, jungle rubber plantation and forests on sunny days (see in Appendix B for further details). To compare our up-scaled estimate of leaf mass per area and leaf nitrogen content at the top of the canopy with measurements, we obtained measured data from Kotowska et al. [43], which was measured at the same site and on a similar plant age.

2.7. Scaling Up Photosynthetic Capacity and Data Availability

After ‘K_n’ values were estimated for every land-use type, we use ‘inversion technique’ to estimate the photosynthetic capacity at the top of the canopy. Basically, we inverted Equation (5), wherein

$$V_{cmax25\_top}=V_{cmax}\left(LAI\right)/exp\left(-K_{n}LAI\right),$$

(6)

The maximum electron transport rate (J_{max_top}), leaf respiration rate (R_{d_top}) and other photosynthetic parameters (A_{max_top}, LMA_{_top}, N_{a_top}) at the top of the canopy are similarly scaled with canopy depth (see in Appendix C for further details). All of the original data set related to photosynthetic capacity is publicly available through https://github.com/ashehad/Photosynthetic_capacity_tropics/ (access on 16 February 2021).

A summarized version of the data can be also found in the same repository. To show what the scaling of photosynthetic capacity means to the land surface models (e.g., CLM5) [72,73], as an example, we obtained the baseline (default) values of maximum carboxylation rate (V_{cmax_top}) and N_{a_top} from CLM5 for tropical evergreen forests and compared it with the values of maximum carboxylation rate (V_{cmax_top}) and N_{a_top} using the scaling method applied in this study for a potential tropical evergreen forest.

3. Results

3.1. Variation of Photosynthetic Capacity at the Lower Part of the Canopy

Values of V_cmax25 ranged from 5.7 to 47 μmol CO₂ m⁻² s⁻¹ among all species (Figure 1a) at the lower part of the canopy. HBm and HBi species exhibited the highest values of V_cmax25 (Figure 1a), while EZ species had the lowest values (Figure 1a)—a similar trend was noted for J_max25 (Figure 1b). Values of J_max25 ranged from 16 to 10.7 μmol electron m⁻² s⁻¹ among all species (Figure 1b) at the lower part of the canopy. No considerable difference in leaf nitrogen content (N_a) values was found among EG, HBm and HBj species (Figure 1c). EZ species had the lowest N_a values (Figure 1c). N_a values ranged from 0.74 to 1.49 g N m⁻² among all species (Figure 1c).

AS species had the highest values of A_max (Figure 2a). Overall, species’ means of A_max varied more than four-fold (from 3.2 to 13.3 μmol CO₂ m⁻² s⁻¹) (Figure 2a). Within species, R_d varied much more than A_max (Figure 1a,b). The species’ R_d values ranged from 0.2 to 1.31 μmol CO₂ m⁻² s⁻¹ (Figure 2b) at the lower part of the canopy. EZ species had the least R_d and LMA values (Figure 2b,c). Among species, low- and high-LMA values were 29 and 61.5 g m⁻², respectively (Figure 2c).

3.2. Extinction of Light in the Canopy Profile

Oil palm plantation (OPP) had the highest K_n value (0.32 m² m⁻²; Figure 3a), while rubber and jungle plantation had similar K_n values (~0.2 m² m⁻²; Figure 3a). The jungle rubber plantation had the highest LAI value (LAI = 5.3 m² m⁻²; Figure 3b) while oil palm plantation exhibited moderate LAI value (LAI = 2.8 m² m⁻²; Figure 3b). The rubber monoculture plantation had the least LAI value (LAI = 2.3 m² m⁻²; Figure 3b).

3.3. Variation of Photosynthetic Capacity at the Top of the Canopy

OPP, RP and JRP exhibited similar V_cmax25 values at the top of the canopy (~69.4 μmol CO₂ m⁻² s⁻¹; Figure 4a)), while values of J_max25 at the top of canopy ranged from 142 to 183 μmol electron m⁻² s⁻¹ among these three plantations (Figure 4b). At the top of the canopy, the J_max25: V_cmax25 ratio ranged from 2.1 to 2.7 μmol electron μmol⁻¹ CO₂ among all the three plantations (Figure 4a,b), wherein both OPP and RP had a lower J_max25: V_cmax25 ratio than the JRP (Figure 4a,b).

At the top of the canopy, A_max varied considerably among different plantations (10.3 to 24.1 μmol CO₂ m⁻² s⁻¹; Figure 4c), JRP had the highest values of A_max (24.1 μmol CO₂ m⁻² s⁻¹; Figure 4c) and the OPP had the lowest values (10.3 μmol CO₂ m⁻² s⁻¹; Figure 4c)—a similar trend was observed for J_max25 at the top of the canopy (Figure 4b). Like in the case of V_cmax25, there were similar R_d values at the top of the canopy (~2.3 μmol CO₂ m⁻² s⁻¹; Figure 4d)).

3.4. Area-Based Leaf Nitrogen Content and Leaf Mass Per Area

At the top of the canopy, the scaling method used in this study estimated the largest N_a value for the OPP, while it estimated the least for the RP and JRP (3.6 versus ~2.6 g N m⁻²; Figure 5a). For the OPP, the estimated N_a value at the top of the canopy via the scaling method was underestimated compared to the field measurements (3.6 versus 5.6 g N m⁻²; Figure 5a). However, there were little differences in N_a values at the top of the canopy between the scaling method and measurements for RP and JRP (Figure 5a).

In line with the field measurements, the scaling method used in this study estimated the highest value of LMA at the top of the canopy for the OPP (133.5 g m⁻²; Figure 5a). There was a considerable difference in LMA values at the top of the canopy between the scaling method and measurements for JRP (117 versus 94 g m⁻²; Figure 5b).

From the lower part of the canopy to the top, N_a values increased from 1.5 to 3.7 g N m⁻² in OPP, whereas N_a values increased from 1.43 to 2.36 g N m⁻² in RB (Figure 1c, Figure 5a). In the case of LMA, from the lower part of the canopy to the top, its values increased from 54.5 to 133.5 g m⁻², whereas LMA values increased from 45.9 to 75.8 g m⁻² in RB (Figure 2c, Figure 5b).

3.5. Within-Canopy Gradients for Forest Ecosystems

Forests had the lowest K_n value (0.15 m² m⁻²) compared to oil palm plantations, rubber plantations and jungle rubber plantations (Figure 3a). On the contrary, forests had the highest leaf area index value (6 m² m⁻²) compared to oil palm plantations, rubber plantations and jungle rubber plantations (Figure 3b). The N_a: V_{cmax25_top} ratio using the scaling method is higher than the default CLM5 model (0.064 versus 0.05 g N s/μmol CO₂).

4. Discussion

4.1. Interspecific Variability in Photosynthetic Traits at the Bottom of the Canopy

In our study, the high V_cmax25 values for H. brasiliensis from monoculture rubber plantation or jungle rubber plantation can be due to a high area-based leaf nitrogen content (Figure 1c). It is worth noting that for the H. brasiliensis from monoculture rubber plantation or jungle rubber plantation, our measured value of V_cmax25 (~45 µmol CO₂ m⁻² s⁻¹) is higher than the value reported by Kumagai et al. [74], who observed V_cmax25 values of 30 µmol CO₂ m⁻² s⁻¹ at the bottom of the canopy. The difference in V_cmax25 can be linked to differences in LAI, where our studied rubber plantation had much lower LAI than that of Kumagai et al. [74] (2.3 m² m⁻² versus 3.89 m² m ⁻²). A low LAI could mean a high canopy openness, more light penetration, and thus a high V_cmax25 at the lower part of the canopy. The relatively low value of A_max (4.2 µmol CO₂ m⁻² s⁻¹) for E. guineensis from oil palm plantation at the bottom of the canopy is due to a lower value of V_cmax25 and J_max25 (Figure 1a,b) and a relatively high R_d value (Figure 2b).

4.2. Light Extinction in the Canopy Profile

The high K_n value in oil palm plantation suggests that a relatively large amount of light is extinct in the oil palm plantation compared to monoculture rubber plantation or jungle rubber plantation. Subsequently, from the top to the lower part of the canopy, photosynthetic capacity declines faster in oil palm plantation than monoculture rubber plantation or jungle rubber plantation. Our estimate of K_n for forests (0.15 m² m⁻²) is in agreement with the values from Kattge et al. [24] that showed variations from 0.13 to 0.23. The K_n value for forests in this study is also closer to Bonan et al. [25] (0.11 m² m⁻²), who derived it from observations.

In general, the light extinction approach is more valid for spatially uniform plant canopy than non-uniform plant canopy, as non-uniform plant canopy is usually characterized by a mosaic solar radiation pattern [75,76]. Therefore, for non-uniform plant canopies, we posit that there could be uncertainties associated with estimating the photosynthesis parameters at the top of the canopy using the up-scaling procedure used in this study.

4.3. Photosynthetic Trait Variability at the Top of the Canopy

The value of V_cmax25 estimated by the scaling method for E. guineensis at the top of the canopy (V_cmax25 = 69 µmol CO₂ m⁻² s⁻¹) is similar to those reported by Rival [77] (V_cmax25 = 74 µmol CO₂ m⁻² s⁻¹). For the monoculture rubber plantation, our estimate of V_cmax25 at the top of the canopy (V_cmax25 = 73 ± µmol CO₂ m⁻² s⁻¹) is closer to the value reported by Kumagai et al. [74], who observed V_cmax25 values of 70 µmol CO₂ m⁻² s⁻¹. Our estimate of V_cmax25 at the top of the canopy for a potential forest ecosystem that consist of the two native tree species (V_cmax25 = 36 µmol CO₂ m⁻² s⁻¹) is comparable with values reported from other tropical forest sites [28,78,79]. Overall, the higher V_cmax25 and J_max25 of rubber trees and oil palms compared to the forest ecosystem that consist of the two native tree species were in line with the findings of Leuning et al. [80], who reported that these photosynthetic capacity parameters are more commonly higher in agricultural than non-agricultural species.

In our study, the estimate of A_max of H. brasiliensis in the monoculture rubber plantation at the top of the canopy was 16.8 µmol CO₂ m⁻² s⁻¹—this value is slightly higher than the value (A_max = 13.1 µmol CO₂ m⁻² s⁻¹) reported on two-year-old rubber seedlings grown in the field [81]. In the case of E. guineensis, the estimate of A_max at the top of the canopy was 10.3 µmol CO₂ m⁻² s⁻¹, which is slightly lower than Corley [82] (A_max = 14 µmol CO₂ m⁻² s⁻¹).

The scaling method estimated the highest value of A_max (24.1 µmol CO₂ m⁻² s⁻¹) in the jungle rubber plantation at the top of the canopy. The reason for this is due to a relatively high leaf nitrogen content (Figure 5a); this reason is also supported by the measurements from the top of the canopy (Figure 5a) [43].

4.4. Limitations and Implications of Scaling Method Used in This Study

In this study, we did not perform diurnal integrative assessments of the light environment. This is important especially for studying diurnal patterns of photosynthesis, looking at diurnal shading patterns and investigating the inhibition of photosynthesis, e.g., [83]. Our up-scaled values of photosynthetic capacity related traits from the lower part of the canopy to the top of the canopy suffer from a couple of shortcomings. First, we used the leaf area index estimates from the similar month, but from a subsequent year. Second, we have studied only two native tree species from the jungle rubber plantation.

Our up-scaled values of photosynthetic capacity-related traits from the lower part of the canopy to the top of the canopy matched reasonably well with the previous measurements from our studied sites, e.g., [43] as well as from the literature [74,77]. This indicates that our data can be integrated with the land surface models (e.g., CLM5) [72,73]. As an example, for a potential tropical evergreen forest ecosystem, our estimated N_a: V_{cmax25_top} ratio using the scaling method was higher than the default CLM5 [72,73] model because mainly the area-based leaf nitrogen content at the top of the canopy was 30% higher, as a result of the scaling method than the default CLM5. It is worth noting that measurements at our study sites indicate a 2-fold area-based leaf nitrogen content at the top of the canopy compared to the default CLM5. The high N_a: V_{cmax25_top} ratio suggests that if CLM5 is parameterized with our estimates from the scaling method, the transpiration estimate of CLM5 will have greater sensitivity than the default CLM5. We do acknowledge, however, that the transpiration estimate of CLM5 is also sensitive to other parameters, such as the stomatal slope that relates stomatal conductance to photosynthesis [73].

5. Conclusions

We can conclude that the photosynthetic capacity-related traits measured at the lower part of the canopy can be successfully scaled up to the top of the canopy, especially for closed and uniform plant canopies. Future measurement efforts for species studied in this study should focus on upper canopy locations, so that our study’s data-sets can be combined and the variability of leaf traits in the vertical canopy profile can be investigated.