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(American Journal of Botany. 2002;89:88-94.)
© 2002 Botanical Society of America, Inc.

Ecology

Spectral reflectance and photosynthetic properties of Betula papyrifera (Betulaceae) leaves along an elevational gradient on Mt. Mansfield, Vermont, USA1

Andrew D. Richardson2 and Graeme P. Berlyn

Yale University, School of Forestry and Environmental Studies, 370 Prospect Street, New Haven, Connecticut 06511 USA

Received for publication February 22, 2001. Accepted for publication July 3, 2001.


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 LITERATURE CITED
 
We studied relationships between spectral reflectance and photosynthesis of mountain paper birch, Betula papyrifera var. cordifolia (Regel) Fern., leaves from three different elevations on Mt. Mansfield (summit elevation 1339 m above sea level) in the Green Mountains of Vermont, USA. The different reflectance indices we used all suggested progressively increasing stress with increasing elevation. The photochemical reflectance index (PRI) indicated lower photosynthetic radiation use efficiency at higher elevations, the red edge position ({lambda}RE) indicated lower chlorophyll concentrations at higher elevations, and the structure-independent pigment index (SIPI) indicated a higher carotenoid : chlorophyll a ratio at higher elevations. The rate of change in these indices with changes in elevation was much higher than we have observed in our studies of red spruce and balsam fir reflectance along a similar elevational gradient; we take this to be an indicator of the greater susceptibility of paper birch to elevation-related stressors compared to the very stress-tolerant conifers. At all light levels, photosynthesis decreased with increasing elevation; this pattern was most noticeable in the light-saturated rate of photosynthesis (Asat), which was nearly twice as high in low-elevation leaves (17.0 ± 1.0 µmol·m–2·s–1) than in high-elevation leaves. The quantum yield of photosynthesis ({Phi}) exhibited a similar trend. Furthermore, the highest elevation leaves showed a much sharper transition from the light-limited to the light-saturated part of the light response curve than did the lowest elevation leaves. The photochemical reflectance index was highly correlated with Asat (r2 = 0.99) and {Phi} (r2 = 0.96). In addition to contributing to our knowledge of the ecophysiology of paper birch along a steep environmental gradient, these results are further evidence of the usefulness of reflectance measures for the rapid and noninvasive detection of plant stress, especially when used in conjunction with direct measurements of photosynthesis.

Key Words: Betulaceae • Betula papyrifera • elevation • environmental gradient • leaf reflectance • light response curve • mountain paper birch • photosynthesis • stress physiology


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 LITERATURE CITED
 
When incident light strikes a leaf, some of the radiation is absorbed by the leaf tissue, some is transmitted through the leaf, and some is reflected back from the leaf surface. Spectral reflectance measures reflected light as a percentage of the incident light at different wavelengths across an entire spectrum. The spectrum often spans ultraviolet, visible (400–700 nm), and near infrared wavelengths. Reflectance is determined not only by the surface properties of the leaf, but also by the internal anatomical structure and biochemical content (Gamon and Surfus, 1999 ). Leaf pigments are important determinants of reflectance in the visible wavelengths, and since concentrations of different pigments can be directly related to stress physiology, the measurement of pigment concentrations in this manner provides important physiological information (Carter, 1993 ; Gitelson and Merzlyak, 1994 ; Peñuelas and Filella, 1998 ; Gamon and Surfus, 1999 ).

A central concern in ecophysiology is how organisms function in different environments. Leaf reflectance measurements can be used to gain deeper insights into environmental stress (Jackson, 1986 ; Filella and Peñuelas, 1999 ; Gamon and Qiu, 1999 ; Richardson, Berlyn, and Gregoire, 2001 ). The development of portable, narrow-band reflectometers has made such studies possible, both at remote field laboratories and in situ on live plants in the field (Gamon and Surfus, 1999 ). Unlike photosynthesis measurements, which are effectively instantaneous snapshots, reflectance measurements can be used to provide indicators of integrated leaf physiology across a wide range of conditions (Gamon and Surfus, 1999 ). Furthermore, leaf-level sampling can be integrated with remote sensing surveys using high-resolution or hyperspectral data to provide data about an entire watershed or ecosystem (Martin and Aber, 1997 ).

In a previous study (Richardson, Berlyn, and Gregoire, 2001 ) we investigated leaf reflectance properties of two co-occurring montane conifers, Picea rubens Sarg. (red spruce) and Abies balsamea (L.) Mill. (balsam fir), along two transects from 460 to 1460 m above sea level (asl) on Mt. Moosilauke, in the White Mountains of New Hampshire, USA. We documented elevation-related changes in a variety of commonly used reflectance indices, including the red edge position ({lambda}RE), the photochemical reflectance index (PRI), and the structure-independent pigment index (SIPI). The present study investigated Betula papyrifera var. cordifolia (Regel) Fern., mountain paper birch, on Mt. Mansfield, in the Green Mountains of Vermont, USA, ~100 km to the northwest of Mt. Moosilauke. We measured foliar reflectance of this temperate broadleaf species along an elevational gradient, and we interpret these reflectance measurements in relation to photosynthetic light response curves that we measured in the field. To our knowledge, only one previous study has reported changes in broadleaf reflectance associated with increasing elevation (Filella and Peñuelas, 1999 ), and that research was conducted in a Mediterranean environment.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 LITERATURE CITED
 
Study site
Sampling was conducted along a 610-m elevational gradient on Mt. Mansfield (44°33' N, 72°49' W), the highest peak in the Green Mountains of Vermont. The Green Mountains are an extension of the Appalachian Mountains that extend from Alabama and Georgia to the Gaspé Peninsula of Quebec, Canada; as such, they comprise some of the oldest rocks in eastern North America. The climate is best summarized as humid, temperate, and continental; Siccama (1974) describes the climate of the Green Mountains in greater detail.

From the 1339 m asl summit of Mt. Mansfield known as "the Chin," a broad ridge extends southwards for ~2.0 km to the 1238 m asl south summit, known as "the Nose" (Fig. 1). The Mt. Mansfield Toll Road runs up the southeast ridge of the mountain, intersecting the main north-south summit ridge immediately north of the Nose. Our study sites were located along this southeast ridge, at intervals of 305 m; the first was at 550 m asl (low elevation), the second at 855 m asl (mid-elevation), and the third at 1160 m asl (high elevation). The lowest site was situated in a typical northern hardwood forest; the highest site was dominated by red spruce and balsam fir. At each site, we collected branches for the leaf reflectance measurements from ~20–25 different small trees (≤2.0 m in height). Photosynthesis measurements were spread across several different days, and each site was visited three times for photosynthesis measurements. We used small trees so that photosynthesis could be measured without having to cut branches from the tree. Field work was completed during the first week of September, prior to the onset of autumn senescence. In the month leading up to our field work, the coldest temperatures occurred the nights of August 18 and August 20, when the daily minima reached 5.8°C at 853 m asl on the west slope of Mt. Mansfield (data provided by the Vermont Monitoring Cooperative with permission from Gerry Livingston, primary investigator for the Basic Meteorological Monitoring Project). Even if we assume a conservative lapse rate of –1.0°C/100 m elevation (Reiners, Hollinger, and Lang [1984] report a lapse rate of –0.64°C/100 m elevation in the White Mountains of New Hampshire, and Siccama [1974] reports a lapse rate of –0.60°C/100 m elevation at Camel's Hump, a nearby peak in the Green Mountains), the temperature at our 1160 m asl site likely did not drop below 2°–3°C.



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  		Fig. 1. Location of study sites on Mt. Mansfield, Vermont, USA (1339 m asl). Sites (550 m asl, 855 m asl, 1160 m asl) were located along the Mt. Mansfield Toll Road, which runs up the southeast ridge of the mountain to the minor south summit known as The Nose (1238 m asl)

 
Leaf reflectance
Spectral reflectance at wavelengths from 306 to 1138 nm was measured using a UniSpec Spectral Analysis System with a 1.5 mm diameter foreoptic and an internal 6.8-W halogen lamp (PP Systems, Haverhill, Massachusetts, USA). The instrument has a reported Raleigh resolution of <10 nm, and the 256 bands sampled by the detector are spaced at 3.3 nm intervals. Individual leaves were held in a black plastic polyvinyl chloride leaf clip at a 60° angle relative to the foreoptic. A Spectralon reflectance standard was scanned after every 20 leaves, and scans were corrected for the instrument's dark current. One hundred different leaves were scanned from each elevation. Each scan represented the average of six passes, and the instrument's integration time was set at 65 msec. Because certain spectral characteristics are known to change rapidly with irradiance (Gamon, Serrano, and Surfus, 1997 ), reflectance was measured on cut branches in a darkened room within 4 h of branch cutting in order to standardize the measurements across different field sampling days. We tested this methodology and found that reflectance indices changed very little in the 12 h following branch cutting. The reflectance spectrum for each leaf was calculated as R{lambda} = leaf radiance at wavelength {lambda}/reflectance standard radiance at wavelength {lambda}.

A variety of indices were used to characterize the complex spectra and make comparisons possible among different elevations. These indices have been derived by other authors based on knowledge of the reflectance properties of pigments and biochemical components.

A standard index in remote sensing work, the normalized difference vegetation index (NDVI) was calculated as (R750 – R675)/(R750 + R675) (Gamon and Qiu, 1999 ). A revised version of the NDVI, which is well correlated with and sensitive to a wide range of chlorophyll a concentrations, was calculated as Chl NDI = (R750 – R705)/(R750 + R705) (Gitelson and Merzlyak, 1994 ). We used this revised index because many of the other indices used for estimating chlorophyll a have been shown to saturate at moderate to high levels of chlorophyll. Saturation is thought not to occur with this index because even at high chlorophyll concentrations, R705 is still sensitive to chlorophyll content, unlike R675 (Gitelson and Merzlyak, 1994 ; Gitelson, Merzlyak, and Lichtenthaler, 1996 ).

Total chlorophyll content is correlated with the red edge position (Curran, Dungan, and Gholz, 1990 ), which is the wavelength {lambda} (in nanometers) of the maximum slope of the reflectance spectrum at wavelengths between 690 and 740 nm. Red edge {lambda} ({lambda}RE), measured in nanometers, was determined as the local maximum of the first-difference spectrum, calculated as (Rn – Rn – 1)/({lambda}n – {lambda}n – 1), over this range (where n is the band number, between 1 and 256). The first-difference spectrum measures how much reflectance changes from one wavelength to the next: it is an approximation of the slope, or first derivative, of the raw reflectance spectrum.

The structure-independent pigment index (SIPI), which is correlated with the carotenoid : chlorophyll a ratio (Peñuelas and Filella, 1998 ), was calculated as (R800 – R445)/(R800 – R680). Carotenoids exhibit a well-known absorption peak at 445 nm.

The photochemical reflectance index (PRI) was calculated as (R531 – R570)/(R531 + R570) (Gamon, Serrano, and Surfus, 1997 ). The PRI has been shown to be correlated with both the epoxidation state of xanthophyll cycle pigments (Gamon, Peñuelas, and Field, 1992 ; Filella et al., 1996 ) and photosynthetic radiation use efficiency (PRUE); PRUE = net photosynthesis/incident photosynthetically active radiation (PAR). Furthermore, parallel changes in PRI and the measured quantum yield of photosynthesis ({Phi}) have been noted under dark-light-dark transitions and simulated diurnal radiation (Gamon, Peñuelas, and Field, 1992 ; Peñuelas, Filella, and Gamon, 1995 ; Peñuelas and Filella, 1998 ).

Photosynthesis measurements
Photosynthetic light response curves were measured in the field on intact leaves using an LI-6400 Portable Photosynthesis System (LI-COR, Lincoln, Nebraska, USA). We used a standard broadleaf chamber with a built-in red + blue light-emitting diode light source (LI-COR 6400-02B). The CO2 level in the reference analyzer was held constant at 400 µmol CO2/mol air, and relative humidity in the sample chamber was held above 50%. Leaves were given 10 min in the chamber to reach equlibrium, which was assessed visually by graphing a strip chart of photosynthesis over time. Light curves were measured using the instrument's AutoProgram function. Measurements were taken at light levels of 2000, 1000, 500, 200, 100, 50, 20, and 0 µmol PAR·m–2·s–1. A minimum wait time of 90 sec was used at each light level, and measurements were logged automatically when the total coefficient of variation (CV) fell below 0.5%. Light response curves were measured on leaves from 12 different individual plants at each site.

Photosynthetic parameters were derived from the light response curve data as follows. Net photosynthesis under the highest light level (2000 µmol PAR·m–2·s–1) was taken to be Asat, the light-saturated rate of net photosynthesis. The maximum quantum yield of photosynthesis, {Phi}, was calculated as the slope of the light response curve across the three lowest light levels (0, 20, and 50 µmol PAR·m–2·s–1). The light compensation point IC was calculated as the corresponding x-intercept, again using just the three lowest light levels. For each elevation, a single modified hyperbolic curve (SigmaPlot 4.0, Jandel, San Rafael, California) was fit to the mean photosynthesis data to approximate the light response function. We used the highest stomatal conductance logged during the measurement of each light response curve as the maximal stomatal conductance (gmax).

Statistical analysis
With only one site studied at each elevation, our study cannot be considered a replicated experiment: the different leaves sampled within each elevation are subsamples and not true replicates. Hence, we have no knowledge of the variation between replicate treatments (independent sites at the same elevation) and no capability to test for differences between different treatments (i.e., different elevations). For this reason, we have chosen to avoid statistical analysis and statistical inference. We report our results as mean ± 1 SE, with the standard error of the mean calculated based on the number of individual leaves analyzed within each site (N = 100 leaves in the case of reflectance measurements, N = 12 leaves for photosynthesis measurements). The corresponding standard deviations are therefore roughly ten times the reported SE for the reflectance measures and 3.3 times the SE for photosynthetic measures. Two standard errors around each mean approximate a 95% confidence interval.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 LITERATURE CITED
 
Although not directly quantified, the foliar health of high-elevation leaves appeared to be considerably impaired relative to low-elevation leaves. Low-elevation leaves were generally darker green and without visible necrosis. On the other hand, high-elevation leaves, while still green, were often chlorotic and dry, with necrotic spots and blotches common. An exception to this was recently flushed high-elevation leaves, which were usually more healthy in appearance than older leaves on the same branch.

There were subtle differences between the average reflectance spectra from the three different study sites; these differences were most apparent between 400 and 700 nm (Fig. 2). At 445 nm, the high-elevation leaves reflected less than either the mid- or low-elevation leaves; this may be related to increased carotenoid absorption in the high-elevation leaves. The reflectance peak at 550 nm was narrowest and most sharply defined in the low-elevation leaves; the reflectance minimum at 680 nm was broadest and deepest in the low-elevation leaves. The mid-elevation leaves were most similar to the low-elevation leaves in the range 400–560 nm, but most similar to the high-elevation leaves in the range 600–690 nm.



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  		Fig. 2. Reflectance spectra (400–700 nm) of birch leaves collected at three elevations on Mt. Mansfield. Each spectrum represents the mean of N = 100 leaves scanned from each elevation

 
The first difference spectra help to elucidate some of the fine differences among spectra of leaves from different elevations (Fig. 3A, B). In particular, slight changes in the curvature of the original spectra around 525 and 575 nm become clear when looking at the first-difference spectra (Fig. 3A). This suggests differences in xanthophyll cycle pigmentation (normally detected by reflectance at 531 and 570 nm wavelengths) between the low- and high-elevation leaves.



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  		Fig. 3. First-difference reflectance spectra ({Delta}R/{Delta}{lambda}, in percent per nanometer) of birch leaves collected at three elevations on Mt. Mansfield. Each spectrum represents the mean of N = 100 leaves scanned from each elevation. First-difference spectra calculated as described in MATERIALS AND METHODS section. (A) Wavelengths 500–600 nm illustrate subtle changes in xanthophyll cycle pigmentation; (B) wavelengths 650–750 nm illustrate changes in the red edge inflection point ({lambda}RE) associated with varying chlorophyll levels

 
Differences among leaves from different elevations could be most clearly seen using a variety of reflectance indices. Four common indices, NDVI, SIPI, PRI, and {lambda}RE, all showed steady trends with regard to elevation (Fig. 4A–D). Decreases in both NDVI (from 0.825 ± 0.004 to 0.781 ± 0.009, mean ± 1 SE, Fig. 4A) and {lambda}RE (from 706.0 ± 0.4 nm to 702.0 ± 0.3 nm) with increasing elevation indicated lower chlorophyll concentrations in the high-elevation leaves. The changes in {lambda}RE are obvious in the first-difference spectra shown in Fig. 3B. Not only did the first-difference maximum shift to a shorter wavelength at higher elevations (also seen in Fig. 4B), but the magnitude of the peak was somewhat reduced in leaves from the higher elevations. Note, however, that the differences between leaves from the low- and mid-elevation sites were negligible. Similar to {lambda}RE, Chl NDI (data not illustrated), another chlorophyll-based index, indicated little change between 550 m asl (0.403 ± 0.008) and 855 m asl (0.388 ± 0.007), but showed a sharp drop in chlorophyll between 855 m asl and 1160 m asl (0.321 ± 0.008).



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  		Fig. 4. Changes in various reflectance indices with elevation (in meters above sea level). Each point represents the mean of N = 100 birch leaves scanned from each elevation. Error bars indicate ±1 SE. (A) Normalized difference vegetation index, NDVI = (R750 – R675)/(R750 + R675). (B) Red edge position ({lambda}RE) is the wavelength {lambda} (in nanometers) of the maximum slope of the reflectance spectrum at wavelengths between 690 and 740 nm. (C) Structure-independent pigment index, SIPI = (R800 – R445)/(R800 – R680). (D) Photochemical reflectance index, PRI = (R531 – R570)/(R531 + R570)

 
Increases in SIPI with increasing elevation indicated corresponding increases in the carotenoid : chlorophyll a ratio (Fig. 4C). However, this may be due either to the apparent decrease in chlorophyll concentration or actual increases in carotenoid concentrations. The PRI steadily decreased with increasing elevation (Fig. 4D), indicating changes in xanthophyll cycle pigmentation. The decline in PRI also suggests that the photosynthetic efficiency of high-elevation leaves was dramatically reduced relative to low-elevation leaves.

Photosynthetic parameters derived from the light response curves (Fig. 5) showed several trends that appeared closely coupled with elevation. Even when the full data set of 36 light response curves was reduced to the 21 light response curves measured only on leaves displaying little or no necrosis, the same patterns were still exhibited. At all light levels, photosynthesis of low-elevation leaves was greater than that of high-elevation leaves. This effect was most pronounced at saturating light levels (e.g., 2000 µmol·m–2·s–1): Asat of low-elevation leaves (17.0 ± 1.0 µmol·m–2·s–1) was almost twice that of high-elevation leaves (9.1 ± 0.8 µmol·m–2·s–1). However, there were also differences among elevations with regard to the shapes of the light response curves. The highest-elevation leaves showed a much sharper transition from the linear (light-limited) part of the light response curve to the light-saturated part of the curve. Even at comparatively low light levels, the light response curve for high-elevation leaves appeared to have reached a plateau and was close to flat, whereas it was still sloping upwards for low- and middle-elevation leaves. While the high-elevation leaves had reached >90% of Asat at 25% full sunlight (i.e., 500 µmol·m–2·s–1), low- and middle-elevation leaves had reached only 80% of Asat at the same light level. The quantum yield of photosynthesis, {Phi}, showed a steady decrease from 0.069 ± 0.002 µmol CO2/µmol PAR in low-elevation leaves to 0.055 ± 0.002 µmol CO2/µmol PAR in high-elevation leaves; mid-elevation leaves were intermediate. On the other hand, the light compensation point, IC, although somewhat higher in high-elevation leaves (16.7 ± 2.5 µmol·m–2·s–1) than low-elevation leaves (11.8 ± 1.2 µmol·m–2·s–1), was actually highest in the mid-elevation leaves (20.9 ± 1.7 µmol·m–2·s–1). The maximum stomatal conductance, gmax, was much higher in the low- (0.56 ± 0.05 mol H2O·m–2·s–1) and mid-elevation leaves (0.53 ± 0.05 mol H2O·m–2·s–1) than in the high-elevation (0.37 ± 0.05 mol H2O·m–2·s–1) leaves analyzed.



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  		Fig. 5. Photosynthetic light response curves for birch leaves sampled at three elevations on Mt. Mansfield. Each point represents the mean of N = 12 leaves sampled at each elevation and error bars indicate ±1 SE. Best-fit curves are modified hyperbolas fit to the mean values for each elevation

 
The PRI was tightly correlated with both the light-saturated rate of photosynthesis, Asat (r2 = 0.99), and the quantum yield of photosynthesis, {Phi} (r2 = 0.96) (Fig. 6).



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  		Fig. 6. Correlations between the photochemical reflectance index (PRI), light saturated rate of photosynthesis (Asat), and quantum yield of photosynthesis ({Phi}). The PRI values represent the mean calculated from N = 100 leaves for each point; photosynthetic parameters calculated from N = 12 photosynthetic light response curves, as described in MATERIALS AND METHODS

 

   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
LITERATURE CITED
 
Reflectance indices
In our previous study (Richardson, Berlyn, and Gregoire, 2001 ) of spruce and fir, SIPI values were generally higher and PRI values were generally lower than we report in the present study. The red edge was located at approximately similar wavelengths in both studies. Because the two studies were conducted in different years, at different times of the year, and on different mountains, it is not possible to draw any solid conclusions regarding absolute differences in spectral reflectance indices among species. However, we can compare the elevation-related patterns exhibited by the different species. The indices used in the present paper all indicate generally increasing levels of plant stress with increasing elevation. This is fully in agreement with the results of our previous study over the range from 460 m asl (deciduous northern hardwood forest) to 1370 m asl (treeline on Mt. Moosilauke). What is different between the two studies is the rate of change in these indices with regard to elevation. We fitted a linear regression line (not shown in Fig. 4) through the data from both studies to arrive at a rate of change in index units (dimensionless except for {lambda}RE, which is measured in nanometers) per 1000 m of elevation. For example, {lambda}RE decreased at a rate of 4.2 nm/km in mature spruce needles and 6.1 nm/km in mature fir needles, but at 7.0 nm/km in birch leaves. The rate of decrease in Chl NDI was more than twice as great in birch (–0.135/km) than either spruce (–0.066/km) or fir (–0.049/km). The apparent decline in photosynthetic efficiency as measured by the PRI was also twice as rapid in birch (–0.063/km) as compared to mature spruce (–0.030/km) or fir (–0.031/km) needles.

There are two possible (and not mutually exclusive) interpretations of these data. One is that this is further evidence of the plasticity of birch. Betula papyrifera, an early successional, shade-intolerant species, is known to exhibit highly plastic leaf anatomy, morphology, and physiology in response to abiotic environmental conditions (Ashton et al., 1998 ), and ecophysiological differences among populations of B. papyrifera are also known to occur (Li, Berlyn, and Ashton, 1996 ). On the other hand, shade-tolerant species, of which P. rubens and A. balsamea are two examples, are thought to be much less plastic in response to abiotic environmental conditions (Jackson, 1967 ). This is supported by the fact that red spruce and balsam fir do not live in as wide a variety of habitats as paper birch. Spruce and fir are better adapted to the habitats they do live in, although their niche breadth and plastic range are narrower than birch.

The second interpretation is that these differences are not only the product of an adaptive plastic response by high-elevation plants, but also the result of impaired physiological performance that is a consequence of growth in a stressful mountaintop climate. Chlorophyll degradation is generally related to stress (Curran, Dungan, and Gholz, 1990 ). Studies on Pinus, Picea, and Alnus by Benecke (cited in Tranquillini, 1979 ) showed that there were steady declines in total chlorophyll content over an elevational range from 650 m asl to 1950 m asl. In contrast to this, Oleksyn et al. (1998) found that high-elevation provenances of Norway spruce, Picea abies (L.) Karst., had higher chlorophyll concentrations than low-elevation provenances when different provenances were grown in a common garden. The fact that our field studies (as well as Benecke's) showed the reverse of Oleksyn's common-garden experiments tends to suggest that the pattern we observed may be a by-product of elevation-related stress, in spite of potential adaptations by high-elevation ecotypes to accumulate more chlorophyll.

We hypothesize that the environment on Mt. Mansfield, especially at the highest site, has demands that marginally exceed the plastic ability of paper birch. At their range limit, these birch can survive, but they are unable to adapt enough to grow without showing signs of severe stress. The two conifers both have foliage that is well-adapted to reduce water stress and mechanical damage (in particular, thick waxy cuticles, a low external surface area : volume ratio, and heavily lignified tissue), whereas the broadleaf birch, although having almost as wide a geographic range as that of balsam fir (and occupying a wider range of habitats), does not have such adaptations. Birch cannot adapt to these high-elevation sites as well as spruce or fir because it is constrained in part by the structure and function of its leaves. Hence, we might expect birch leaves to be more susceptible to environmental stresses associated with increasing elevation. From an ecological perspective, this may indicate a reduction in the competitive ability of paper birch. Thus these patterns may help to explain the ability of fir to out-compete birch at higher-elevation sites (above 1200 m), whereas birch outcompetes fir at lower-elevation sites (below 800 m).

Photosynthesis
The shapes of the photosynthetic light response curves merit discussion. Tranquillini (1979) concluded that there was little evidence in the literature that high-elevation trees were better adapted to taking advantage of high light intensities than low-elevation trees. In our study, leaves from the high-elevation site featured a sharper transition from the linear phase of light-limited photosynthesis to light-saturated photosynthesis, and a comparatively low Asat. These are characteristics commonly associated with shade leaves, whereas the low-elevation leaves had characteristics associated with sun leaves (Jones, 1992 ). Although solar radiation flux increases with elevation when the sky is clear, the proportion of days with heavy cloud cover usually also increases. Consequently, in many humid areas, the total solar radiation received during the growing season at high elevation may be only a fraction of that at low elevation (Körner, 1999 ). Our analysis of climate data from the nearby Burlington, Vermont airport (data source: daily surface data from the National Climatic Data Center [2000] ) indicates that during the years 1950–1996, the cloud ceiling was at or below 1220 m asl for a total of 18.2% of the time between May and September; at 610 m asl the corresponding figure was only 5.9%. These figures do not, however, take into account the very localized clouds that tend to develop around the area's highest summits even on otherwise cloudless days (Siccama, 1974 ), which tend to further accentuate the differences between our high- and low-elevation sites. It is possible that some of the differences in photosynthetic performance between high- and low-elevation leaves can be partially attributed to differences in light environment resulting from high-elevation trees being engulfed in clouds more often than low-elevation trees.

Reports of reduced photosynthetic rates in high-elevation trees are common in the literature for a variety of genera (Tranquillini, 1979 ) and are thought to be a factor in determining treeline (Grace, 1989 ). However, two common-garden experiments provided contradictory results. Fryer and Ledig (1972) found that high-elevation balsam fir provenances had lower rates of photosynthesis than low-elevation provenances. On the other hand, Oleksyn et al.'s (1998) experiments documented the reverse in Norway spruce. These experiments nevertheless suggest that differences in photosynthetic performance with regard to elevation may have a genetic as well as an environmental component. The cause of low Asat in the high-elevation birches we studied can probably be attributed mostly to stress, since the reflectance indices {lambda}RE and Chl NDI indicated lower chlorophyll concentrations in high-elevation leaves. The concentration of xanthophyll cycle carotenoids relative to chlorophylls is known to increase under environmental stress (Demmig-Adams and Adams, 1996 ), and PRI indicated a higher proportion of xanthophyll-cycle pigments in the photoprotective zeaxanthin state (Filella et al., 1996 ; Filella and Peñuelas, 1999 ) in the high-elevation leaves. These reflectance indices help to explain the patterns we observed in the photosynthesis measurements. When xanthophyll cycle pigments are in the zeaxanthin state, they have an energy level below that of chlorophyll a and hence they provide a sink for excess excitation energy. However, radiation that is dissipated by the xanthophyll cycle is not available for photosynthesis, and hence photosynthetic efficiency is low when PRI is low (Demmig-Adams and Adams, 1996 ). Reflectance measurements can therefore be seen as complementing, rather than replacing, photosynthesis measurements: they help the ecophysiologist to interpret changes in photosynthetic parameters.

The reduced rates of photosynthesis in high-elevation leaves are particularly important because the number of growing degree-days decreases with increasing elevation (Reiners, Hollinger, and Lang, 1984 ). Consequently, the lower maximal rates of photosynthesis, combined with the shorter and cooler growing season, act as a significant constraint on the annual carbon fixation at higher elevations. Tranquillini (1979) considers this to be a significant factor in determining the upper limit of montane forests.

Summary
These results give further evidence that the effects of environmental stress on plant physiology can be detected using rapid and noninvasive measurements of leaf reflectance at 300–1100 nm wavelengths. Furthermore, reflectance-based measures of stress can be directly related to the effects of stress on photosynthetic efficiency and capacity. This is of fundamental importance, as quantification of photosynthesis represents the most basic measure of productivity. Unfortunately, it is still impossible to isolate the primary effects of a stress factor (e.g., drought or extreme temperature) from the subsequent secondary effects (e.g., photoinhibition) (Jackson, 1986 ; Carter, 1993 ). A better understanding of leaf reflectance in relation to stress may eventually make such distinctions possible.


   FOOTNOTES
 
1 The authors thank Spencer Meyer for help with the field work; the University of Vermont and the Vermont Agency of Natural Resources for permission to conduct research on Mt. Mansfield; the Mt. Mansfield Corporation for toll road access and logistical assistance; the Andrew W. Mellon Foundation for generous funding; and Ellen Denny for helpful comments on the manuscript. Back

2 Author for reprint requests (tel.: 203-432-5153, FAX: 203-432-3929, andrew.richardson{at}yale.edu ). Back


   LITERATURE CITED
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
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