The Effects of Climate on the Growth of Lodgepole Pine
In order to model the growth and yield of trees over time, we need to determine how much wood a tree accumulates each year. Each year, a tree lays down an annual ring of wood in a layer under the bark. Pressler’s hypothesis states that area of wood laid down annually (measured by the cross-sectional area increment) increases linearly from the top of the tree to the base of the crown (the location of the lowest live branches) with the assumption that it is proportional to the amount of foliage above the point of interest. Below the crown, the area increment in any given year remains constant, except for the region of butt swell at the base of most trees. (For this case study, butt swell can be ignored.)
The growth of a tree in any given year is strongly influenced by growth in the previous years. One reason for this is that buds are formed the year before they start to grow and carbohydrates from good years can be stored to fuel growth in subsequent years. The effects of previous growing conditions can last from one to three years, depending on tree species and location.
Climate affects growth and influences both the size of the annual ring of wood and the proportions of early and late wood. Low density early wood is laid down during the spring when water is plentiful. Late wood, which is laid down from mid-summer until growth ceases in the fall, has a high density. Cessation of wood formation is sensitive to weather conditions such as temperature and drought. Basic knowledge of how climate affects wood properties will be useful in predicting changes in growth based on changes in climate.
Lodgepole pine (Pinus contorta Doug. ex Loud.) stands dominate much of western Canada and the United States, covering over 26 million hectares of forest land. It is an important commercial species in British Columbia; stands consisting of >50% lodgepole pine occupy 58% of the forests in the interior of the province. Lodgepole pine is primarily used for lumber, poles, railroad ties, posts, furniture, cabinetry, and construction timbers. It is commercially important to be able to predict how lodgepole pine will grow and accumulate wood over time. Using high resolution satellite images of lodgepole pine stands to predict wood attributes is under consideration, but first the relationship of crown properties such as the amount of foliage must be linked to wood properties and growth.
We have data on the annual growth and wood density of 60 lodgepole pine trees from four sites in two geographic areas in central British Columbia. Samples were removed at 10 to 13 locations along each tree and two radii (A and B) per sample disc were measured. Measurements of the last year of growth and wood density are often unreliable because of proximity to the bark and difficulties of sample preparation. However, it is for this ring only that we have measures of the amount of foliage.
The primary objective is to determine to what extent climate, position on the tree bole (trunk), and current foliar biomass explain cross-sectional area increment and proportion of early and late wood.
It is also of interest to learn the following:
How have temperature and precipitation affected the annual cross-sectional growth and the proportions of early and late wood in lodgepole pine?
- Is annual growth best explained by average annual temperature or do monthly maximum and/or minimum values provide a better explanation?
- Do early and late wood need to be considered separately?
- Does the use of climate variables to predict the growth and proportions of early and late wood provide more reliable estimates than the use of the growth and density measurements from previous years as measured from the interior rings?
To what extent do climate, position on the tree bole, and current foliar biomass explain cross-sectional area increment and proportion of early and late wood?
- Wood density data: Data files: Plain text, MS Excel There is a line in the dataset for each ring in each sample (disc) taken along the bole of each tree. The tree identifier consists of the letter for the site where the tree was located and a number that uniquely identifies the tree. Sites B and C are near Quesnel and sites J and T are near Kamloops. The trees from the Kamloops area were destructively sampled in 2003 and the trees from the Quesnel area were sampled in 2004. Variables that start with letter A refer to radius A; variables that start with letter B refer to radius B.
Variable Units Description Ayear year Calendar year corresponding to age of the tree Alatewoodw mm Width of late wood Aringwidth mm Width of annual ring Apclatewood % Percentage late wood Aearlywoodd kg/m3 Early wood density Alatewoodd kg/m3 Late wood density Aavedens kg/m3 Average ring density Aend mm Distance from bark along A radius to end of ring Astart mm Distance from bark along A radius to start of ring Bage year Age from pith Byear year Calendar year corresponding to age of the tree Blatewoodw mm Width of late wood Bringwidth mm Width of annual ring Bpclatewood % Percentage late wood Bearlywoodd kg/m3 Early wood density Blatewoodd kg/m3 Late wood density Bavedens kg/m3 Average ring density Bend mm Distance from bark along B radius to end of ring Bstart mm Distance from bark along B radius to start of ring tree Tree identifier height m Height along bole sample taken
- Climate data: Data are from the Environment Canada website, using the two nearest stations with long-term records, Kamloops (Latitude: 50° 42.133’ N Longitude: 120° 26.517’ W Elevation: 345.30 m) and Quesnel (Latitude: 53° 1.567’ N Longitude: 122° 30.600’ W Elevation: 545.00 m).
For each location (Quesnel and Kamloops) there are three files: (1) the minimum temperature in degrees Celsius, (2) the maximum temperature in degrees Celsius, and (3) the total precipitation in mm. Each line in the dataset gives the monthly, annual, and seasonal amount for one year starting in 1895. Data files:
- Foliar biomass data:The plain text data are in 2 files. The MS Excel file has 2 worksheets. For each tree, foliar biomass measurements were made for multiple branches so that there are estimates for each year of the tree’s life (so the number of lines of data per tree varies with the age of the tree). Each line of data in the first file has the following variables:
- Tree identifier (as for wood density data)
- Age of tree at branch initiation
- Average relative position of branch in the crown (1 is the base of the crown and 0 is the top)
- Foliar biomass (the mass in kg per square metre of needles subtended by the branches) at the position
- Tree identifier (as for wood density data)
- Total height of the tree in m
- The height to the base of the crown in m
- The length of the crown in m
- Pages Web de Henri D. Gissino-Mayer sur les anneaux
- Clark, D.A and Clark, D.B. (1994) Climate-induced annual variation in canopy tree growth in a Costa Rican tropical rain forest. Journal of Ecology, 82 (4): 865-872.
- Monserud, R.A. (1986) Time-series analyses of tree-ring chronologies. Forest Science, 32 (2): 349-372.
- Parish, R. and Antos, J.A. (2002) Dynamics of an old-growth, fire-initiated, subalpine forest in southern interior British Columbia: tree-ring reconstruction of two-year cycle spruce budworm outbreaks. Canadian Journal of Forest Research32: 1947-1960.