Now, most researchers use specialized software to analyze images and differentiate between vegetated and non-vegetated pixels.įigure 2. Photographs were originally analyzed by researchers themselves. Researchers would photograph the canopy from the ground using a fisheye lens. Hemisphere photography was one of the first methods used to indirectly estimate leaf area index. These indirect methods infer LAI from measurements of related variables, such as the amount of light that is transmitted through or reflected by a canopy. Several decades ago, canopy researchers began to look for new ways to measure LAI, both to save time and to avoid destroying the ecosystems they were trying to measure. Litter traps are another way to directly measure LAI, but they don’t work well in evergreen canopies and can only capture information from leaves that have senesced and abscised from the plant. It does, however, remain the most accurate method of calculating leaf area index because each individual leaf is physically measured. In tall forest canopies, it may not even be feasible. Modern equipment like flatbed scanners have made this process more efficient, but it is still labor intensive, time consuming, and destructive. Traditionally, researchers measured leaf area index by harvesting all the leaves from a plot and painstakingly measuring the area of each leaf. In this guide, we’ll discuss the theoretical basis of each of the major methods along with key advantages and limitations. For example, the grassland researcher may prefer a different method than the forestry researcher. The researcher who needs a single estimate of LAI might use a different method than the one who is monitoring changes in leaf area index over time. The method you choose will depend largely on your research objectives. Each method has advantages and disadvantages. Obviously, LAI is a useful metric for describing both spatial and temporal patterns of canopy growth and productivity. For example, from seeding to maturity, maize leaf area index can range from 0 to 6. Seasonally, annual and deciduous canopies and croplands can exhibit large variations in LAI.
Mid-latitude forests and shrublands typically have LAI values between 3 and 6. Some desert ecosystems have a leaf area index of less than 1, while the densest tropical forests can have an LAI as high as 9. A canopy with an leaf area index of 3 would have a 3:1 ratio of leaf area to ground area (Figure 1b). For example, a canopy with an LAI of 1 has a 1:1 ratio of leaf area to ground area (Figure 1a). LAI is unitless because it is a ratio of areas. By definition, it is the ratio of one-sided leaf area per unit ground area. Leaf area index (LAI) quantifies the amount of leaf material in a canopy. Several scenarios and special considerations are discussed, which will help individuals choose and apply the most appropriate method for their research needs.
#Leaf guide download#
Download this application guide for a brief introduction to the theory and instruments used to measure leaf area index. However, theory and technology developed in recent years have made measuring LAI much simpler and more feasible for a wide range of canopies. In the past, measuring leaf area index (LAI) was difficult and time consuming.
#Leaf guide how to#
In this article, learn how to measure leaf area index, what it is, and how to use it. Leaf area index is also commonly used as a measure of crop and forest growth and productivity at spatial scales ranging from the plot to the globe. For these reasons, LAI is often a key biophysical variable used in biogeochemical, hydrological, and ecological models. LAI is also useful for understanding canopy function because many of the biosphere-atmosphere exchanges of mass and energy occur at the leaf surface. Leaf area index (LAI) is one of the most widely used measurements for describing plant canopy structure. Visual BASIC macro for computing beam fractionĭR.How beam fraction calculation in the LP-80 simplifies LAI measurements.But that one number can lead to significant insight. Leaf area index is a single number–a statistical snapshot of a canopy taken at one particular time.
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