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Leaf mass per area (LMA), which is the leaf dried weight divided by its fresh area is one of the most widely researched plant trait, and because it indexes so much information of ecological importance it is of high interest for plant ecologists and ecophysiologists (Lusk et al. 2008). LMA is seen as a key trait in plant growth (Lambers & Poorter 1992) and an important indicator of plant strategies (Grime, 2001; Westoby et al., 2002). It is also widely used in plant ecology, agronomy and forestry (Poorter et al. 2009). Globally, across species LMA is positively correlated with leaf life span (Williams et al. 1989; Campanella & Bertiller 2009) and negatively correlated with transpiration and respiration rate (Givnish 1988) which in turn is associated with lower photosynthetic capacity (Lusk et al. 2008). Further research show that high LMA leaves, which have more mesophylls per area are better in photosynthesise in the abundance of sunlight, whereas low LMA leaves do better where sunlight is scarcer .
Wright et al. (2002) sampled perennial species from nutrient poor and nutrient rich areas from Western Australia and found that species growing on dry and infertile soil converge towards higher LMA, and those high LMA leaves also had a higher life span than species growing on more productive environments.
Vertical and horizontal variation in environmental conditions
Variation in environmental conditions is observed across a whole range of spatial conditions. For example, globally, a strong variation in environmental conditions is observed across a latitudinal gradient , as we move away from the equator, sunlight and consequently temperature tends to decrease and, alongside this change in environment, plant traits also change to match the environment. For example, species growing closer to the equator (15o) have a greater mean maximum height 29 times greater than those growing between 60-75o and 31 times greater than those growing 45-60o (Moles et al. 2009). It has been also suggested that along a latitudinal gradient, plants also display different strategies in nutrient conservation which can be an indicator for P limitation in the tropics and selective pressure shaping the evolution of plant traits (Yuan & Chen 2009).
Altitude has also a strong effect in plant traits. (Craine & Lee 2003) while studying grass species along an altitudinal gradient in New Zealand found that plants in higher altitudes generally have thicker leaves and roots compared to those at lower altitudes. There is also a negative correlation between altitude and plant height(Totland & Birks 1996). These changes in plant traits along an altitudinal gradient are an adaptation to the environmental conditions which change with altitude, the most conspicuous being perhaps the negative correlation between altitude and temperature (Totland 2001).
Environmental conditions are also vary to a smaller extent, such as vertically (distance from forest floor to canopy) and horizontally within a forest. Alongside this environmental variation plant traits are also expected to co vary. Similarly to what (Burns 2004) found when studying plants in a bog area, where plants closed to the centre of the bog, where sunlight is more abundant had higher SLA.
Environmental filtering and convergence of traits
Much study in community ecology focuses in how environmental conditions can affect individuals within a community. The relationship between environment and plant form has played a central role in plant ecology and convergent evolution (Ackerly et al. 2002). There are two main ways in which organisms can be influenced by the environment. The first termed to be described is know as co-gradient variation (sometimes termed convergence of traits) which is the similarity of plastic and evolutionary responses to an environmental gradient; such that environmental effects on phenotypic expression reinforce genetically determined differences between populations or species (Lusk et al. 2008). For example, it has been found that leaf lifespan is often longer in shaded individuals than in those growing in brighter light (Ackerly & Bazzaz 1995; Reich et al. 2004), leaves have a genetic predisposition to last longer in shade, as it is more cost expensive to create a new leave rather than maintaining an existing one, and this genetic predisposition is reinforced in the shade. Photosynthetic capacity and respiration rates are also usually lower in plants growing in the shade compared to those growing in higher light (Walters & Reich 1999) as plant metabolism is lowered down in the absence of sun, again, a genetic imprint that is reinforced by the environment. Another pattern found in relation to plant traits and environment is termed counter-gradient variation, where environmental effects on phenotypic expression masks genetically determined differences between populations or species (Lusk et al. 2008).
Resource utilization is of great importance for plant physiology, however, how are resources divided in an environment to minimize competition? Perhaps, the niche theory can answer this question. The ecological niche theory (Hutchinson 1958) describes how an organism or population responds to the distribution of resources and competitors (e.g., by growing when resources are abundant, and when predators, parasites and pathogens are scarce) and how it in turn alters those same factors (e.g., limiting access to resources by other organisms, acting as a food source for predators and a consumer of prey). For example, individual plant species have a set of physiological traits which allow them to survive and thrive in a given environment. Perhaps, in the case of LMA, only species with high LMA are able to thrive in a certain type of environment, in the same manner Darwin finches can coexist by feeding on the same food source, by exploiting different fruit size. Or it could be the case that no such relationship exists, and a whole range of LMA is observed utilizing the same environmental conditions.
Niche is divided into two different categories, the fundamental and the realized niche. The fundamental niche of a species includes the total range of environmental conditions that are suitable for existence without the influence of interspecific competition or predation from other species, it is the "minimum" requirement of a species for survival. (Scherzinger, 2009) found that distribution of Capercaillie stretches from eastern Siberia to Western Europe. Within this area habitats are characterized by coniferous trees, dwarf shrubs like heather and bilberries, diverse flowers, leafs, and herbs for nutrition, whereby the birds choose the best combination of these resources in each location, so, the best combination of these resources is Capercaillie fundamental niche.The realized niche describes that part of the fundamental niche actually occupied by the species, in the same study, (Scherzinger 2009) found that within this area Capercaillie have certain preferences in the quality of their habitat, and tend to occupy certain areas over others (realized niche). The main difference between the fundamental and realized niche is the effect that competition and predation has on species.
The aim of this research is to test if there are relationships between plant traits (LMA) and environmental conditions (vertically and horizontally) in a New Zealand forest.
Otari-Wilton's Bush (41Â°14â€² S, 174Â°45â€² E) is located just within Wellington city limits at the southern tip of the North IsÂland of New Zealand, and encompasses approximately 100 hectares of native forest. The reserve is situated 70-280 meters above sea level and the soil is comprised of stoney colluvium of greyÂwacke parent material. Average annual rainfall totals 1,240 millimetres and average daily temperatures range from 20Â°C in summer to 7Â°C in winter (Council 2007). The vegetation is classified as coastal conifer-broadleaved forest, whose vertical structure is highly complex and similar to most tropical forests (Dawson & Lucas 2000) .It has a fairly continuous canopy, which is frequently interrupted by canopy gaps and canopy emergent tree species. A dense comÂmunity of shrubs and tree ferns occurs beneath the canopy (Blick et al. 2008) .Lianas and epiphytes are also abundant (Burns and Dawson, 2005) . Dysoxylum spectabile is the dominant canopy-forming species, alongside Melicytus ramiflorus, Corynocarpus laevigatus and Eleaocarpus dentatus. Macropiper excelsum and Geniostoma rupestre are the most common subcanopy shrubs. Emergent trees include Dacrydium cupressinum, Beilschmedia tawa and Knightia excelsa. Burns (2007) gives a detailed inventory of the woody plant community.
Data collection I - Plots
Thirty 30m x 30m plots were surveyed within the reserve (following (Marjot 1992). The plots encompassed a whole range of environmental conditions which were decided upon before data collection started as it was desired to cover plots facing different aspects (N, S, E and W). Once the locations were chosen plots were randomly selected within the location. A random number was generated using a calculator, if the number generated was even, plot would be placed on the right side of the track, if odd, plot would be placed on the left side of the track. After that, another random number was generated in order to decide how many steps would be walked in the chosen direction, were the centre of the plot would be placed. A compass was also used to assure that I walked in a straight line from the track to the desired location of the plot in order to avoid sampling bias. However, some restrictions were applied regarding the location of the plots, mainly due to safety reasons. Therefore, locations with slope >40 degrees were avoided of sampling.
In each plot abundance of sexually mature vascular species was recorded. Sexually mature individuals are defined in this study as those capable of reproducing. Clues such as presence of fruit and/or flowers or evidence of such were used in deciding whether or not to include an individual in the research.
Data collection II - Individual species
Once the abundance of mature individuals was recorded, the second step was to collected information on individual plants. Plant species present in 5 or more of the plots were re sampled, only those found in at least 5 of the plots were used in order to provide more robust comparisons. Emergent species (Beilschmedia tawa and Knightia excelsa) and Podocarps were also not surveyed due to restriction in collection of leaves from these individuals.
In each plot, the tallest two individuals of each species had their height measured. Height was measured with the use of a hypsometer (Nikon Forestry 550), and was taken from the base to the uppermost branch of the tree. Once height was measured, each individual had six leaves collected, except Dysoxilum spectabile which has large compound leaves, and for that species leaflets were collected since they are likely to be functionally equivalent to leaves (Bongers & Popma 1990). Only leaves fully exposed to sunlight from the outer part of the branch were collected for trees, for shrubs, leaves on the top of the plant were collected as those leaves are not exposed to direct sunlight. Leaves were collected with, placed into a paper bag, and taken to the lab for further measurements.
Data collection III - physical aspects of plots
Information physical aspect of each plot was also collected. Information on plot aspect was collected using a compass; slope was collected using a hypsometer (Nikon Forestry 550). A soil tester with 30 cm probes was used to measure ph and soil moisture in the upper layer (< 30cm) of the forest floor, measurement on soil moisture was given on a scale between 1 and 10, with 1 being the driest and 10 the wettest. Ph was given on a scale between 3.5 (acidic) to 8 (alkaline). Moisture and ph were measured
Sunlight was measured using a light meter and given in lux. Measurement was given on a scale between 0 (dark) to 2000 (light). Data on sunlight was collected on a sunny day of clear sky and each plot was surveyed twice on the same day (one measurement in the morning and another in the afternoon). Sunlight was collected at a height of 1.5m above the floor, therefore, reflecting the amount of sun received by shrub species. Sunlight was measured at the corners and centre of each plot and an average was taken for each plot. Averages for morning and afternoon for each plot were calculated for statistical analysis.
Each measurement (sunlight, moisture and ph) was taken at 5 different areas of the plot (4 corners and centre) and average value was then used in each plot for statistical analysis. Slope was taken from one end to another end of the plot in the direction the plot was facing; therefore, slope was measured in an area of 30 m.
Data collection IV - Lab
The fresh leaves collected from individual plants had their area in cm2 measured using an area meter scanner. Fresh leaf area was recorded to an accuracy of 2 decimal points, and once measurements on area were made, leaves were dried for 48 hours at a temperature of 65o (following (Wright et al. 2002)and dried weight was taken using an electronic scale. Weight was measured in mg to an accuracy of 3 decimal points. With those measurements, leaf mass per area (LMA) in g/m2 was calculated and an average was given for each individual plant, based on the six collected leaves.
35 different species belonging to 33 different genera were found. Out of 35 species 13 were found in 5 or more of the plots. B. tawa and K. excelsa are emergent species, therefore leaves were not collected due to restrictions. Podocarps were also not sampled. Thus, 9 species were used for further data collection and analysis. For each of the nine specie, in each plot two plants had their height measured and in each plant six leaves were collected for further analyses. Total number of plant with height measured was 288. In each of the 288 plants, six leaves were collected resulting in a total of 1728 leaves.
Data was analysed using PASW statistics 18. LMA diversity within species was investigated by obtaining the PC1 value of the environmental condition. Environmental conditions used to create the PC1 axis were sunlight, moisture, slope and soil Ph.
A factorial analysis was used in order to reduce different components (in this case environmental) into on axis. PCA seeks a linear combination of variables such that the maximum variance is extracted from the variables. It then removes this variance and seeks a second linear combination which explains the maximum proportion of the remaining variance, and so on. This is called the principal axis method and results in uncorrelated factors.
The main applications of factor analytic techniques are: (1) to reduce the number of variables and (2) to detect structure in the relationships between variables, that is to classify variables. Therefore, factor analysis is applied as a data reduction or structure detection method (the term factor analysis was first introduced by Thurstone, 1931).
By using PCA analysis it was possible to reduce four measured environmental variables (sunlight, slope, aspect and pH) into one axis. PCA1 was then plotted against LMA average for each species for all the plots. A linear regression model was also used to analyze the data. LMA was used as the dependent variable and PCA1 was used as an independent variable.
Another statistical test used was a multiple regression analysis, by applying the following formula:
Y = a + b1X1 + b2X2 + ... + bpXp
Where Y is the value of the Dependent variable (Y), what is being predicted or explained
a (Alpha) is the Constant or intercept
b1 is the Slope (Beta coefficient) for X1 â€¦
Multiple regression can establish that a set of independent variables (height, PC1) explains a proportion of the variance in a dependent variable (LMA) at a significant level (through a significance test of R2), and can establish the relative predictive importance of the independent variables (by comparing beta weights). Therefore, it is able to explain if either PC1 of height have a significant effect on LMA.
The first principal component (PCA1) captured 50.8 % of the variance in LMA. PCA1 was positively correlated with slope (.608) and sunlight (.807) and negatively correlated with moisture (-.970) and ph (-.314) Therefore higher PCA1 values describe plots which are steeper, lighter, drier and slightly more acidic than plots with low PCA value. PCA values decreases when moving from north to south (see figure 1).
Figure 1. Average LMA against average height for the eight surveyed species. A clear correlation between height and LMA is observed as higher plants also tend to have higher LMA.
Figure 2. Mean LMA (g/m2) against mean PC1 for each of the surveyed species. Note that LMA displays a positive correlation with PC1 for shrubs (closed symbols), whereas for trees (open symbols) LMA displays a negative correlation with PC1.
Figure 3. Mean height against mean PC1 for each of the surveyed species. Height tends to decrease with PC1, for both, trees and shrubs.
Table 1. Multiple regression for Average LMA of each species. LMA was used as a dependent factor and PC1 and height as independent factors and separate analyses were conducted for each species. B corresponds to increase in LMA for each unit of either PC1 or height. * = <0.05 and ** = <0.001
Horizontal patterns in plant diversity were observed. There is a positive correlation between average plant height and average LMA (figure 1). However, a different pattern was observed between average PC1 and average LMA (figure 2). For trees, a negative correlation was observed with PC1, as moving from South to North, LMA tends to decrease (figure 1); for shrubs, the opposite pattern was observed as LMA slightly increases with PC1. Height displays a similar pattern for both trees as shrubs, as it tends to decrease with PC1. In order to analyze the effects height and PC1 have on LMA, a multivariate regression analyses was ran on the data (see table 1). ,PC1 has a stronger effect on LMA than height for both D. spectabile and G. rupestre (Beta = .491, p<0.05 and Beta = .422 and p<0.05 respectively). For M. ramiflorus, C. robusta and E. dentatus, height appears to have a stronger effect on LMA than PC1 (Beta = .708 p<0.001; Beta = .787, p<0.05 and Beta = 638, p<0.05 respectively). No significant difference was observed between the effects of PC1 and height on LMA for M. excelsum, M. australis and B. repanda therefore it was not possible to differentiate between the effects of plant height and position along a horizontal gradient on leaf LMA for those species.
Horizontal and vertical patterns in leaf LMA were observed. However, patterns differed between species vertically and horizontally. Height related (vertical) trends were observed for 3 surveyed species (M. ramiflorus, C. robusta and E. dentatus) as for those species increase in LMA in significantly higher with vertically than horizontally. Horizontal patterns were observed for 2 species, (D. spectabile and G. rupestre), and for 3 species (M. excelsum, M. australis and B. repanda) it was not possible to distinguish between the effects of tree height (vertical) and position along the forest (horizontal).
Althought environmental conditions were not measured vertically, threre is a fair amount of evicence suggesting that environmental conditions such as light, temperature and humidity change vertically in forested environments (Oshima et al. 1997).
Overall the findings in this research suggests a relationship between LMA and plant height, as shrubs had lower LMA than trees. Previous research found similar patterns in leave traits, for example (Beaumont & Burns 2009) found that specific leaf area (the inverse of LMA) declined with plant height. There are some advantages for shorter trees to have low LMA as it provides a better photosintetic capacity in low light environment . Low LMA leaves tend to be broader, in order to increase the chance of being hit by sunlight, but thinner, which may be an indicator of a tradeoff between leaf size and thickeness. This may be an indication of divergence of traits (_____________), as different environemntal conditions associated with plant height are causing leaves to converge towards morphological similarity. Interspecific variarion in LMA shows a strong negative correlation with seedlling growth rates (Lambers & Poorter 1992), reflecting its value as an indicator of the cost of constructing leaf area (Villar & Merino 2001). Intraspecifically, LMA of a given species tends to markedly increase as seedlings grow bigger (Lusk & Warton 2007) when species are compared at a common size at a common environment.
Also, shrub species had lower LMA compared to canopy species, and it is consistent with previous research, which suggests that LMA increases with height (Ellsworth and Reich, 1993). Research also showed that whitin species, a large variation in leaf traits is observed within the same plant at different heights (vertical gradient) (Beaumont and Burns, 2009).
Plant height was similar for both, within trees and within shrubs (excep E. dentatus), therefore it may indicate that environment does not have a strongly affect plant height within the forest. However, there are patterns globally, as plants tend to get smaller when moving away from the Equator towards higher latitudes (see (Moles et al. 2009).
Horizontal patterns along a environmental gradient were also observed. In shrubs, LMA increases with PC1 (moving from S to N), conversely, for trees, LMA tends to decrease as PC1 increases. Plants growing in dry, sunnier environments tend to have higher LMA than those growing in areas with less light and more humid (Wright et al. 2002) .Therefore, one would expect that all surveyed species would show an increase in LMA when moving from South to North. Similarly to what (Ackerly et al. 2002) found while studying a chaparral in California were SLA was correlated with environment, such that species with low SLA were more abundant in areas with high light, whereas species with high SLA were more abundant in areas with low sunlight. That was the case for shrubs but not for trees. Perhaps, this could be due to the fact that for trees, access to sunlight is not an issue, and perhaps, amount of sunlight between North and South facing does not differ to a point that it will affect plant strategy (i.e. increasing LMA on North facing slopes). However, D. spectabile and G. rupestre leaf LMA is strongly affected by PC1 (horizontally). These species where also the two most abundant specie in the survey, and perhaps this could be due to the fact those plants can optimise their photossyntethic capacity by adapting their leaves to the environment.
Not only is LMA an adaptation to increase photossyntetic capacity. There are other advantages for the plant in matching LMA with environment. For example, in a cafeteria style study, it has been show that low LMA leaves are eaten preferably by herbivores (Cornelissen et al., 1999; Louault et al., 2005), and the same preference was also observed in the field (Perez-Harguindeguy et al., 2003). Furthermore, (Bach 1984) while studying betlle herbivory found that number of bettles are significantly reduced under shaded conditions, therefore, herbivory would be higher under light conditions, thus, it may be advantageous to the plant to have higher LMA in areas with more sunlight. (Damour et al., 2008) found that drought has a strong effect on LMA as plants growing under water strees have a higher LMA than those growing in the presence of water. Again, this may be the case investing more in mainteining a leaf instead of making a new one.