Leaf functional trait variation in a humid temperate forest, and relationships with juvenile tree light requirements

Study site

The study was carried out in a humid temperate forest in the Lake Okataina Scenic Reserve (38.08°S, 176.42°E), in the North Island of New Zealand. Sampling was carried out in a 300 ha basin lying at about 400m a.s.l. within the reserve, infilled with tephras (mainly rhyolitic) derived from the Okataina Volcanic Centre (Pullar, Birrell & Heine, 1973). Climate data from GIS layers indicate a mean annual temperature of 11.7 °C, a frost-free period of 195 days, and mean annual precipitation of 1,659 mm (IIASA/FAO, 2012; Landcare Research 2011). Rainfall is evenly-distributed throughout the year. Although juvenile trees growing in clearings are exposed to large vapour pressure deficits (>1.5 kPa) during dry spells, deficits of that magnitude have not been recorded in the understorey and tree-fall gap environments where traits were measured in the present study (Lusk & Laughlin, 2017). A research permit to work at the site (66760-RES) was obtained from Department of Conservation.

The disturbance history of the basin has created a complex vegetation mosaic, including a wide range of light environments (Lusk & Laughlin, 2017). Most of the basin remains in tall forest with a canopy dominated by Beilschmiedia tawa (Lauraceae) up to 30 m tall and scattered emergent conifers up to 45 m, mainly Dacrydium cupressinum and Dacrycarpus dacrydioides (Podocarpaceae). Conifers occurred at higher densities before selective logging during the mid-20th century (Nicholls, 1991); this history of logging has left behind several clearings and a network of skidder tracks, some of which have been converted to walking tracks. At the north end of the basin is a stand of <2 ha with a canopy dominated by Weinmannia racemosa (Cunoniaceae), which admits more light to the understorey than the deep-crowned B. tawa that predominates elsewhere (Beveridge, 1973). As a result, seedlings and saplings of a wide range of species can be found in the understorey of this stand, which presumably owes its origin to a small fire or wind damage. All native tree and shrub species present in the basin are evergreen, except for Fuchsia excorticata (Onagraceae) and very occasional Plagianthus regius (Malvaceae)—McGlone et al. (2004) describe both as deciduous, but report that some northern populations of the former retain some leaves during winter.

Measurements of leaf traits

I measured a range of leaf traits that have variously been shown to correlate with species’ light requirements in other evergreen forests (Kitajima & Poorter, 2010; Lusk et al., 2010; Poorter & Bongers, 2006). Although leaf mass per area (LMA) is the structural trait included in the original leaf economic spectrum concept (Reich et al., 1991; Wright et al., 2004), it can be informative to partition this trait into leaf thickness and density—it has been reported that density correlates strongly with species’ shade tolerance in tropical humid tropical forests, whereas thickness does not (Kitajima & Poorter, 2010). Accordingly, leaf density and thickness were measured in addition to LMA. Leaf dry matter content is a widely used alternative to LMA, and has also been found to correlate with species’ light requirements in some humid forests (Lusk et al., 2010; Poorter, 2009).

Two ranges of light environments were defined as sources of sun- and shade-leaf traits (Tables 1, 2). Sun-leaf traits were measured on plants growing beneath tree-fall gaps, or besides roads or walking tracks. Shade-leaf traits were measured on juvenile trees growing mostly in the understorey of the W. racemosa-dominant stand at the north end of the basin. In each of these two light environments, five to six juveniles (50–200 cm tall) were selected haphazardly for leaf trait measurements. A Nikon Coolpix 4500 digital camera (Nikon, Tokyo, Japan) and an EC-08 fisheye adaptor were used to take a photo immediately above the apex of each of these selected juveniles (as described above), and Gap Light Analyzer (Frazer, Canham & Lertzman, 1999) was used to estimate % canopy openness from each photo. Light environments above plants sampled in gaps ranged from 12.0 to 27.8% canopy openness, compared to 1.2 to 3.0% in the understorey. There was no significant interspecific variation in mean canopy openness above plants sampled in either gaps (ANOVA, P = 0.97) or shade (P = 0.76). Juveniles of Coprosma robusta could not be found in understorey environments comparable with those of the other species, so C. robusta was sampled only in gap environments.

Leaf lifetimes were estimated by following survival of leaves over a 12-month period. The height of the principal axis of each juvenile was measured to the apex, and all fully-expanded leaves on this axis were counted. Twelve months later, each plant was revisited, its height remeasured, and survival of leaves recorded. Abscission scars were counted to determine mortality of new leaves initiated after the start of the study period; this was important for species that turn over most or all of their foliage in a single year, such as Aristotelia serrata.

Leaf lifetime (years) was estimated as: ${\displaystyle \frac{n^i}{\left(n^i-n^f\right)+m^n}}$

where n_i = initial number of leaves, n_f = final number surviving from n_i, and m_n = mortality of new leaves initiated since the first census (King, 1994; Lusk et al., 2008a). A few of the marked plants either suffered major damage by herbivores or disturbance during the study, or could not be relocated, and leaf lifespan estimates were eventually obtained from four to five plants of each species in each light environment.

After leaf lifespan measurements, leaves were taken from each of the same plants, for measurement of sun- and shade-leaf structural traits. Depending on leaf size, one to 10 of the youngest fully-expanded intact leaves were taken from each plant, avoiding leaves damaged by herbivores. Leaves were placed immediately in re-sealable plastic bags with moist tissue paper, and fresh weight determined within six hours of removal. Fresh leaves were photographed, and area calculated using ImageJ software (Schneider, Rasband & Eliceiri, 2012). Leaf volume was estimated using Archimedes’ principle. The leaf was immersed in a small container of water placed on an electronic balance, and displaced volume determined from the change in apparent weight. A small amount of detergent was added to the water to reduce hydrophobicity of leaf surfaces, and reduce bubble formation. Leaf thickness was later estimated dividing volume by area. Leaves were oven-dried at 60 °C for three days before measuring dry weight; drying was initiated within eight hours of leaf excision in all cases, minimizing the effect of dark respiration on non-structural carbohydrates, which can contribute up to 25% of leaf dry mass (Lusk & Piper, 2007). Leaf density was then calculated as dry mass / fresh volume. Leaf samples were pooled to obtain one estimate of total nitrogen content of each species in each light environment, using the Dumas combustion method.

Quantifying species light requirements

Distributions of juvenile trees 50–200 cm tall were quantified in relation to canopy openness determined from hemispherical photographs. Sampling was carried out on a series of transects run through old-growth stands, including tree-fall gaps of varied sizes and forest margins. Sets of parallel transects were run through forest stands, spaced at least 20 m apart, A total of 748 points were sampled at random intervals (10 to 15 m apart) along transects. Presence of juvenile trees and shrubs 50–200 cm tall was recorded in a circular plot of 1-m diameter, centred on the sample point. Although multiple juveniles of some species were often found in the same plot, only presence or absence data are used in the present analysis. A Nikon Coolpix 4500 digital camera (Nikon, Tokyo, Japan) and an EC-08 fisheye adaptor were used to take a photo at 1.5 m height at each sampling point. A spirit level fitted to the lens cap was used to level the camera, and photos were taken mostly while the solar disc was either obscured by clouds or below the horizon, to avoid errors caused by flaring and reflection. Gap Light Analyzer (Frazer, Canham & Lertzman, 1999) was used to estimate % canopy openness from each photo.

The 10th percentile of the distribution of each species in relation to canopy openness was used as an approximation of the lowest light levels tolerated by each species (Lusk et al., 2008a). This parameter is referred to hereafter as minimum light requirements (MLR). MLR represents an inversion of traditional shade tolerance ratings, i.e., shade-tolerant taxa have low MLRs, and light-demanders score high. Only species represented on at least 15 sampling plots were considered, yielding 18 species (Table 1).

Statistical analyses

One-way ANOVA was used to test for interspecific variation in the light environments in which leaf traits were measured. All trait data except leaf dry matter content were log10-transformed before analysis, in order to meet the assumption of additivity of effects (Quinn & Keough, 2002). The field sampling procedure meant light environments were effectively nested within species, as species were not all compared in common plots using a full factorial design. Nested ANOVA were therefore used to test for leaf trait differences between sun and shade leaves, and among species. In addition to cross-species correlations, relationships among leaf traits and species light requirements were also measured using phylogenetic least squares regression (PGLS: Symonds & Blomberg, 2014), to take into account the influence of phylogeny on trait relationships. COMPARE 4.6 (Martins, 2004) was used to carry out PGLS contrasts. A fully-resolved tree of the 19 species was obtained from the Angiosperm Phylogeny Group website (Stevens, 2001), although the lack of Coprosma robusta in the understorey meant only 18 species were included in the analysis of shade leaf traits. All other analyses were carried out in Statistica (Stat Soft. Inc., Tulsa, OK 74104, USA)

Inter- and intraspecific variation in leaf traits

ANOVA showed highly significant interspecific variation in all traits, as well as highly significant effects of light environment on all traits except for leaf density, which was only marginally affected by light (Table 3). ANOVA of leaf N data was not possible, due to the lack of replication resulting from pooling of leaf samples.

Interspecific variation of most traits was more marked in shade leaves than in sun leaves. This was especially true of leaf lifespan, which ranged 0.6 to 3.8 years in gaps, and 0.7 to 7.7 years in the understorey (Table 2). Other traits showed narrower ranges of values, spanning 2.4- to 3-fold variation in gaps, and 2.5- to 3.9-fold variation in the understorey.

Leaf lifespan was the trait that responded mostly strongly to light, shade leaves on average living about 70% longer than sun leaves of the same species (Table 2). LMA also responded strongly to light, leaves from plants growing in gaps on average having 58% more dry mass per area than shade leaves of the same species (Table 2); light environment explained just as much variation in LMA as species identity did (Table 3). Light environment had least effect on leaf density and leaf dry matter content, which respectively averaged only 10 and 11% higher in gap plants than in understorey conspecifics; variation in these two traits was therefore dominated by the effect of species (Table 3). Leaf N of most species was similar in the two light environments (Table 2).

Trait correlations with species’ minimum light requirements

The three traits included in the original leaf economic spectrum (LMA, leaf N, and leaf lifetimes) were tightly coordinated in both sun and shade leaves (Kendall’s coefficient of concordance = 0.78 and 0.76 respectively, P < .0001; Fig. 1A). They showed varied correlations with the other traits making up the dataset (Table 4).

Species’ minimum light requirements ranged from 0.8% (Beilschmiedia tawa) to 4.2% (Coprosma robusta) (Table 1). Species light requirements were strongly negatively correlated with leaf lifespans, especially those of shade leaves (Table 4; Fig. 1C); leaf lifespan was thus positively correlated with species’ shade tolerance. Light requirements were also negatively correlated with LMA (Fig. 1B), although this relationship was only marginally significant in gaps (P = 0.048) and non-significant according to PGLS (Table 4). Light requirements were not significantly correlated with any other structural trait or with leaf N, except for a marginally significant correlation with dry matter content of shade leaves under PGLS (Table 4).